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Exploring serum and tear micro-RNA as biomarkers for early diagnosis of Sjögren’s Syndrome

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Exploring serum and tear micro-RNA as biomarkers for early diagnosis of Sjögren’s Syndrome

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Exploring Serum and Tear Micro-RNA as Biomarkers for Early Diagnosis of
Sjögren’s Syndrome

By

Shruti Singh Kakan

A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(PHARMACEUTICAL AND TRANSLATIONAL SCIENCES)

December 2022

Copyright 2022 Shruti Singh Kakan

ii
Dedication

To Poorvi Giri, my eldest niece
(2001-2018)
And Mogi, my dæmon
(?-2021)
For the experience of unconditional love and pure joy

iii
Acknowledgements
Thank you to everyone.

iv
Table of Contents
Dedication ....................................................................................................................................... ii
Acknowledgements ........................................................................................................................ iii
Table of Contents ........................................................................................................................... iv
List of Tables ................................................................................................................................ viii
List of Figures ................................................................................................................................ ix
Abstract ......................................................................................................................................... xii
Chapter 1 Introduction .................................................................................................................... 1
1.1 SS: Pathophysiology and Disease Manifestations .................................................................... 1
1.2 SS: Demographics .................................................................................................................... 2
1.3 SS: Current Diagnostic Criteria ................................................................................................ 2
1.4 Biomolecules with Diagnostic Potential ................................. Error! Bookmark not defined.
1.5 Overview of miRNAs function ............................................... Error! Bookmark not defined.
1.6 Overview of exosome formation, secretion and function ......................................................... 5
1.6.1 Overview of Exosome Isolation Methods ...................................................................... 6
1.6.2 Tears are enriched in exosomes. .................................. Error! Bookmark not defined.
1.7 Animal Models ......................................................................................................................... 8
1.7.1 Male NOD mouse, a model of SS-associated autoimmune dacryoadenitis ................... 8
1.7.2 Rab3d knockout mouse – a model to study trafficking defects associated with SS ...... 9
1.8 Primary Aims .......................................................................................................................... 10
1.8.1 Aim 1 – Identifying dysregulated miRNAs in serum exosomes as potential
biomarkers for SS ......................................................................................................... 11
1.8.2 Aim 2 – Identifying dysregulated miRNAs in tears as putative biomarkers for SS. ... 12
1.9 Secondary Aims ...................................................................................................................... 12
1.9.1 Aim 3 ............................................................................ Error! Bookmark not defined.
Chapter 2 Small RNA deep sequencing identifies a unique miRNA signature released in serum
exosomes in a mouse model of Sjögren’s Syndrome^ .................................................................. 14
2.1 Abstract ................................................................................................................................... 14
2.2 Introduction ............................................................................................................................ 15
2.3 Materials and methods ............................................................................................................ 19
2.3.1 Mice .............................................................................................................................. 19
2.3.2 LG Histology and quantitative analysis of lymphocytic infiltration ............................ 19
2.3.3 Isolation of serum exosomes ........................................................................................ 19
Table of Contents

v
2.3.4 Total RNA Isolation ..................................................................................................... 20
2.3.5 Transmission Electron Microscopy .............................................................................. 21
2.3.6 Western Blotting .......................................................................................................... 21
2.3.7 Particle Size Analysis ................................................................................................... 22
2.3.8 Small RNA Deep Sequencing ...................................................................................... 23
2.3.9 Bioinformatics .............................................................................................................. 23
2.3.10 miRNA validation assays ............................................................................................. 24
2.3.11 Pathway and functional enrichment analysis ............................................................... 25
2.4 Results .................................................................................................................................... 26
2.4.1 Characterization of exosomes from mouse serum ....................................................... 26
2.4.2 Mouse serum exosomes contain several small RNA biotypes ..................................... 28
2.4.3 NOD serum exosomes contain a subset of dysregulated miRNA ................................ 32
2.4.4 Validation of miRNA differential expression .............................................................. 36
2.4.5 Pathway analysis identifies several pathways involved in lymphocyte activation ...... 37
2.5 Discussion ............................................................................................................................... 38
Chapter 3 Tear and LG miRNA from the RAB3DKO mouse model ........................................... 45
3.1 Introduction ............................................................................................................................ 45
3.2 Methods .................................................................................................................................. 46
3.2.1 Mice .............................................................................................................................. 47
3.2.2 Tear & LG collection ................................................................................................... 47
3.2.3 RNA Isolation .............................................................................................................. 47
3.2.4 sRNAseq and Bioinformatics ....................................................................................... 47
3.3 Results .................................................................................................................................... 48
3.3.1 Tears of RAB3DKO mice have differentially expressed miRNA ............................... 48
3.3.2 LG of RAB3DKO mice have differentially expressed miRNA ................................... 51
3.3.3 Tears of male RAB3DKO mice have differentially expressed ncRNA: ...................... 55
Chapter 4 Tear miRNAs identified in a murine model of Sjögren’s Syndrome as potential
diagnostic biomarkers and indicators of disease mechanism
^
....................................................... 59
4.1 Abstract ................................................................................................................................... 59
4.2 Introduction ............................................................................................................................ 60
4.3 Materials & Methods .............................................................................................................. 64
4.3.1 Animals ........................................................................................................................ 64
4.3.2 Human Subjects ........................................................................................................... 65
4.3.3 Tissue and Tear Collection ........................................................................................... 66
4.3.4 LG Histology & Quantification of Lymphocytic Infiltration ...................................... 67
4.3.5 RNA Isolation and Quality Control ............................................................................. 68
4.3.6 Library Preparation, NGS and Bioinformatics analysis ............................................... 68
4.3.7 RT-qPCR Validation .................................................................................................... 70
4.3.8 Ingenuity Pathway analysis of miRNA hits ................................................................. 71

vi
4.4 Results .................................................................................................................................... 71
4.4.1 Histological Analysis of LG lymphocytic infiltration ................................................. 71
4.4.2 Male NOD mice have differential tear production, but not total protein or RNA
yields ............................................................................................................................ 73
4.4.3 Male NOD mice tears from the discovery cohort exhibit differentially expressed
miRNA ......................................................................................................................... 74
4.4.4 qPCR confirms differential expression of multiple identified miRNAs in tears from
an additional, validation, mouse cohort ....................................................................... 79
4.4.5 qPCR confirms differential expression of some miRNAs in tears from patients
with SS relative to patients with MGD ........................................................................ 83
4.4.6 IPA identifies dysregulation of molecular functions and immunomodulation ............ 85
4.5 Discussion ............................................................................................................................... 89
Chapter 5 The miRNA landscape of lacrimal glands in a murine model of autoimmune
dacryoadenitis
^
.............................................................................................................................. 99
5.1 Abstract ................................................................................................................................... 99
5.2 Introduction .......................................................................................................................... 100
5.3 Methods ................................................................................................................................ 101
5.3.1 Mice ............................................................................................................................ 101
5.3.2 Tissue collection ......................................................................................................... 102
5.3.3 LG immune and epithelial cell enrichment ................................................................ 103
5.3.4 sRNAseq and Bioinformatics ..................................................................................... 104
5.3.5 RT-qPCR .................................................................................................................... 107
5.3.6 Pathway Analysis ....................................................................................................... 107
5.3.7 Statistics ..................................................................................................................... 108
5.4 Results .................................................................................................................................. 108
5.4.1 Differentially expressed miRNA in the male NOD LG ............................................. 108
5.4.2 Validating differentially expressed miRNA in male NOD LG .................................. 110
5.4.3 Influence of lymphocytic infiltration on differentially expressed miRNA ................ 114
5.4.4 IPA Analysis .............................................................................................................. 116
5.5 Discussion ............................................................................................................................. 117
Chapter 6 Serum and Tear Autoantibodies from NOR mice as Potential Diagnostic Indicators of
Local and Systemic Inflammation in Sjögren’s Syndrome
^
....................................................... 126
6.1 Introduction .......................................................................................................................... 126
6.2 Methods ................................................................................................................................ 127
6.3 Results .................................................................................................................................. 127
6.4 Conclusion ............................................................................................................................ 128
Chapter 7 Conclusions ................................................................................................................ 130
Table of Contents

vii
7.1 Summary of overall findings ................................................................................................ 130
7.2 Limitations ............................................................................................................................ 132
7.3 Future directions ................................................................................................................... 133

viii
List of Tables

Table 1.1 Estimates Of People Living With Autoimmune Diseases
3
. ..................................... 2
Table 2.1 Summary of the 7 most differentially expressed miRNAs detected in serum UC
exosomes from 14-week male BALB/c and NOD mice using three statistical
packages in RStudio ..................................................................................................... 34
Table 2.2. Reads aligned to various non-coding RNA ............................................................. 42
Table 3.1 Differentially expressed miRNA in RAB3DKO mice tears .................................... 49
Additional differentially expressed miRNA in RAB3DKO mice tears ................................... 49
Table 3.2 Differentially expressed miRNA in carbachol treated LG of RAB3DKO mice ...... 53
Table 3.3 Differentially expressed ncRNA in tears of RAB3DKO mice ................................ 58
Table 4.1 Differentially expressed miRNA in male NOD mice tears as compared to those
in tears of male BALB/c and female NOD mice ......................................................... 76
Table 4.2 qPCR validation of differentially expressed miRNA in male NOD mice tears ....... 83
Table 4.3 Literature summary for previous miRNA hits in studies on SS. .............................. 93
Table 5.1 Differentially expressed miRNA in LG of male (M) NOD mice ............................ 111
Table 5.2 Comparison of mRNAseq expression analysis of genes from the IL6-like
cytokine signaling pathway .......................................................................................... 122
Table 5.3 Catalog numbers of mouse qPCR primers ............................................................... 123
Table 5.4 mRNAseq, sRNAseq and IPA alignment parameters .............................................. 124

ix
List of Figures

Figure 1.1 Characteristics of rabbit lacrimal gland acinar cell (LGAC) exosomes isolated
by differential ultracentrifugation. ............................................................................... 6
Figure 1.2 Characteristics of rabbit LGAC exosomes isolated by size exclusion
chromatography (SEC). ................................................................................................ 7
Figure 1.3 Schematic showing protocols for exosome isolation from human
tears. ............................................................................................................................. Erro
r! Bookmark not defined.
Figure 1.4 Human tear exosomes isolated by size exclusion chromatography. ....................... 8
Figure 2.1 Schematic depicting the bioinformatics analysis pipelines. ................................... 25
Figure 2.2 Characterization of mouse serum-derived exosomes by differential ultra-
centrifugation (UC) and Size Exclusion Chromatography (SEC). .............................. 28
Figure 2.3 Infiltration of lymphocytes in lacrimal gland (LG) of male NOD but not
BALB/c mice reflects established autoimmune dacryoadenitis in the mice used as a
source of exosomes. ..................................................................................................... 27
Figure 2.4 Graphical presentations of the distribution of reads from NGS sequencing of
RNAs. ........................................................................................................................... 30
Figure 2.5 Profiling of UC exosome derived piRNA & differential expression analysis. ....... 31
Figure 2.6 Profiling of exosome derived miRNA. ................................................................... 33
Figure 2.7 Differential miRNA expression analysis. ............................................................... 35
Figure 2.8 Boxplots of differentially expressed miRNAs in exosomes isolated from 14-
week male BALB/c and NOD mouse serum. .............................................................. 36
Figure 2.9 Validation of miRNA ‘hits’ in Size Exclusion Chromatography (SEC)-purified
serum exosomes from 14-week male BALB/c and NOD mice. .................................. 37
Figure 2.10 Pathway analysis using miTALOS, miRPathDB and Ingenuity Pathway
Analysis (IPA). ............................................................................................................. 39
Figure 3.1 Quality assessment of RNA isolated from pooled tears of 12weeks old male
RAB3DKO ................................................................................................................... 48
Figure 3.2 sRNAseq identifies differentially expressed miRNA in RAB3DKO tears. ........... 50

x
Figure 3.3 qPCR validation of differentially expressed miRNA in tears of RAB3DKO
mice. ............................................................................................................................. 51
Figure 3.4 sRNAseq identifies differentially expressed miRNA in carbachol stimulated LG
of RAB3DKO mice. ..................................................................................................... 52
Figure 3.5 Bar plot of highest expressed miRNA in male RAB3DKO LG. ............................ 54
Figure 3.6 Venn diagram of miRNA expression in tears and carbachol treated LG of C57
and RAB3DKO mice. .................................................................................................. 55
Figure 3.7 Summary of sRNAseq analysis of small non-coding RNA in tears of male
RAB3DKO mice. ......................................................................................................... 57
Figure 4.1 Schematic overview of experiments and data analysis. .......................................... 69
Figure 4.2 Representative H & E-stained images of LG from 12 -14-week-old female
NOD, male BALB/c or male NOD mice. .................................................................... 72
Figure 4.3 Tear volumes and quality assessment of RNA isolated from pooled tears of 12-
14 weeks old female NOD, male BALB/c and male NOD mice using TapeStation. .. 74
Figure 4.4 Differential miRNA expression analysis of NOD mouse tears. ............................. 77
Figure 4.5 Multiple miRNAs are differentially expressed in tears of diseased male NOD
mice. ............................................................................................................................. 78
Figure 4.6 Comparison of expression of endogenous control miRNAs mmu-miR-25-3p and
mmu-miR-93-5p in RNA isolated from tears of male NOD, female NOD, male
BALB/c mice and human tears. ................................................................................... 80
Figure 4.7 qRT-PCR validation of miRNA hits in mice tears. ................................................ 81
Figure 4.8 Assessment of miRNA hits predicted from the bioinformatics analysis which
were not validated by qRT-PCR. ................................................................................. 82
Figure 4.9 Quality assessment of RNA isolated from tears of SS patients using Tapestation. 84
Figure 4.10 qRT-PCR validation of miRNA hits in human tears from patients with SS or
MGD. ............................................................................................................................ 85
Figure 4.11 Ingenuity Pathway (Enrichment )Analysis of tear miRNA hits. .......................... 86
Figure 4.12 IPA Network analysis of targeted miRNAs. ......................................................... 88
Figure 4.13 Relative expression of miRNA hits in RNA isolated from patients tears. ........... 97
Figure 5.1 Isolation and characterization of immune- and epithelial-enriched fractions from
13-week male NOD mice. ............................................................................................ 104
Figure 5.2 Overview of sRNAseq alignment to mouse genome and transcriptomes .............. 106

xi
Figure 5.3 miRNA expression from sRNAseq of stimulated LG from NOD and BALB/c
mice .............................................................................................................................. 109
Figure 5.4 Dysregulated miRNAs in LG from male NOD mice. ............................................ 112
Figure 5.5 RT-qPCR validation of miRNAs in topically-stimulated LG. ............................... 113
Figure 5.6 RT-qPCR validation of miRNA changes in unstimulated LG. .............................. 114
Figure 5.7 miRNA expression in immune-enriched (IEF) and epithelia-enriched (EEF) cell
fractions from male NOD mouse LG. .......................................................................... 115
Figure 5.8 Pathway Enrichment Analysis of predicted gene targets of IEF miRNAs. ............ 117
Figure 5.9 miRNAs targeting IL-6 signaling are dysregulated in male NOD LG IEF. ........... 118
Figure 5.10 Dysregulated miRNAs target IL-6-like cytokines and their downstream
effectors in EEF. ........................................................................................................... 120
Figure 6.1 Serum IgG autoantibodies in male NOR (above) and NOD (below) mice. ........... 128
Figure 6.2 Tear specific IgG autoantibodies in male NOR mice. ............................................ 129

xii
Abstract
Sjögren’s Syndrome (SS) is a common, debilitating, incurable autoimmune disease that
lacks an analytical diagnostic test, and relies on subjective methods that take an average of 3 years
for diagnosis. 90% of SS patients are women. To improve SS diagnostics, I have investigated
microRNAs (miRNA), a class of short regulatory non-coding RNA that can silence protein
translation and regulate cell signaling. Studying differences in their expression could identify
diagnostic biomarkers and shed light on disease progression and development. Using murine
models of SS, in Chapter 2 I have investigated serum exosomes of male Non-Obese Diabetic
(NOD), identified five differentially expressed miRNAs and validated two by qPCR. In Chapter
4, I have identified fourteen miRNAs that were dysregulated in tears of male NOD mice when
compared to healthy mice and validated eight candidate miRNAs by qPCR. Three of these
miRNAs – miR-203a-3p, miR-181a-5p, miR-181b-5p – successfully distinguished patients with
SS-associated autoimmune dry-eye from patients with non-autoimmune subtype of dry-eye by
qPCR. Several of these miRNAs have been previously reported in the context of SS, but miR-
181b-5p is a new find. In Chapter 5, I have reported that the miRNA transcriptome is greatly
altered in the male NOD mouse lacrimal gland (LG) after the onset of disease. miRNAs as a
percentage of both total RNA and small RNA are elevated in infiltrating immune cells in the LG
as compared to LG acini. Most upregulated miRNAs in male NOD LG are largely expressed in
infiltrating immune cells while most downregulated miRNAs are specific to the LG acini.
Dysregulated miRNAs in the male NOD LG are predicted to target genes involved in ‘Regulation
of Cytokine production’. Dysregulated miRNAs that are enriched in immune infiltrates are
predicted to upregulate the IL6 pathway.

1
Chapter 1 Introduction
1.1 SS: Pathophysiology and Disease Manifestations
Sjögren’s Syndrome (SS) is an incurable, chronic, systemic autoimmune disease in which
the body’s moisture producing secretory glands (such as the lacrimal and salivary glands) are
targets of immune mediated attack, leading to its hallmark symptoms of dry eye and dry mouth.
In its early stages, we see the glandular manifestation of the disease which can result in dryness of
not only eyes and mouth but also throat, nose, vagina and skin. Other common symptoms include
joint pain, fatigue, digestion issues and recurring infections. At this stage, patients are likely to
seek medical attention but a positive diagnosis for SS takes 3 years on average and requires
multiple visits and specialist referrals. Thus, SS patients have an unusually high burden of
healthcare than the general population and a significantly decreased quality of life.
While awaiting accurate diagnosis and disease modifying treatments, SS can get
progressively worse. The autoimmune attack spreads to internal organs and patients can present
with the extraglandular manifestation (resulting from increased inflammation of internal organs
including brain, lung and liver
1
) such as interstitial lung disease, vasculitis, nephritis and peripheral
neuropathies. These conditions can be life threatening and at any given time there are about 25%
of SS patients that present with these complications in the clinic. About 5% of SS patients go on
to develop B-cell lymphoma at later stages of the disease. Compared to healthy people, SS patients
have a 15-40-fold higher a risk of developing B-cell lymphoma
2
of the salivary gland (SG). The
incidence of lymphoma is higher in SS than in any other rheumatic diseases, being 6-fold higher
than Systemic Lupus Erythematosus (SLE) and 18-fold higher than Rheumatoid Arthritis (RA).
When left untreated, SS can result in corneal melt causing blindness.
Introduction

2
1.2 SS: Demographics
By some estimates, SS is now the second-most common rheumatic autoimmune disease,
affecting 0.19 – 1.39% of the population
3-5
(Table 1.1). SS disproportionately affects women more
than any other autoimmune disease with over 90% of SS patients being women
6
. The incidence of
SS is growing, particularly among younger women
7
. It was estimated that in 2018 there were
around 2.3 million people worldwide living with Sjögren’s syndrome. This number is predicted to
increase to 2.5 million by the year 2027.
Table 1.1 Estimates Of People Living With Autoimmune Diseases
3
.
Autoimmune Disease* Estimates
Rheumatoid Arthritis (RA) 1.293 million
3

Primary Sjogren’s Syndrome (SS) 1.3 million (95% CI 0.4 – 3.1 million)
3

Spondyloarthritis
†
0.639 – 2.41 million
3

Juvenile Rheumatoid Arthritis (JRA) 0.294 million (95% CI 0.188 – 0.400 million)
3

Systemic Lupus Erythematosus (SLE) 0.161million – 0.322 million
3

Systemic Sclerosis (SSc, Scleroderma) 0.049 million
3

†
Includes ankylosing spondylitis (AS), reactive arthritis, psoriatic arthritis, enteropathic
arthritis, juvenile spondylarthritis, and undifferentiated spondylarthritis.
1.3 SS: Current Diagnostic Criteria
Currently SS has no definitive diagnostic test for early detection. At present, diagnosis of
SS relies on a combination of subjective measures of ocular and salivary manifestations that
overlap with symptoms of other diseases
8
. The current ACR/EULAR criteria includes a) labial
salivary gland biopsy, which is painful, impractical and may be error-prone in early stages
9
; b)
blood tests to detect SS antigen A (SSA) autoantibody, which are present in only 40-60% SS
patients and 10-20% of patients with other autoimmune disease. Thus, this test has poor specificity
and low sensitivity; c) Schirmer’s test to assess dry eye by measuring volume of tears produced in
Chapter 1

3
5 minutes and ocular staining to assess integrity of corneal epithelium; d) Sialometry to assess dry
mouth by measuring saliva production. However, there can be many causes of dry-eye and dry
mouth. Differential diagnosis for dry-eye includes ocular infections, medications, etc. None of
these tests assess the health of the LG as it is dangerous to biopsy the LG. With a) and b) weighed
more heavily than c) or d) the current diagnostic criteria heavily favor SG assessment. As a result,
SS patients remain undiagnosed for several years by which time irreversible damage to exocrine
glands and other organs within the body has been established
10
. Patients with a more prominent
LG disease take a year more for definitive diagnosis than patients with a more prominent SG
disease. Lack of an evidence-based standardized screening tool to help Ophthalmologists decide
which dry eye patients to refer for SS workup results in a significant under-referral of likely SS
patients and therefore, continued underdiagnosis of the disease. Hence, there is a significant unmet
clinical need for an analytical early diagnostic test for SS.
Early diagnosis prior to inflammation-related damage of internal organs could allow these
patients to receive disease modifying treatments and better care. To address the need for timely
diagnosis, we are investigating minimally invasive (blood) or non-invasive (tear) biofluids for
identification of SS specific biomarkers with high sensitivity. I propose to investigate biofluids in
the developing stages of SS to identify candidate biomarkers for diagnostic purposes.
1.4 Overview of miRNAs function
The serum/plasma proteome has been investigated extensively for SS diagnostics.
Previously, the Hamm-Alvarez lab has investigated tear proteome for diagnostic biomarker
discovery and identified elevated cysteine protease Cathepsin S with tremendous diagnostic
potential. For this study, we wanted to investigate the tear transcriptome to identify RNA
biomarkers to further improve the sensitivity and specificity of the Cathepsin S tear test. For
Introduction

4
diagnostic purposes, we are studying a class of small regulatory non-coding RNA known as
microRNAs (miRNAs) which are 18-26 nucleotides in length and function in gene silencing and
post-transcriptional gene regulation
11
. As opposed to siRNA, miRNAs are partially
complementary to mRNA and bind primarily to the 3’ UTR of an mRNA. A single miRNA can
have multiple targets, and a target mRNA can be regulated by many different miRNAs (4 – 5 on
average). miRNAs are highly evolutionarily conserved and regulate nearly 60% of all mammalian
mRNA
12
. All nucleated eukaryotic cells produce hundreds of distinct miRNAs. Additionally,
prokaryotes, fungi & viruses are also known to produce miRNA. In higher organisms, miRNAs
circulate in a stable, cell-free form in all biofluids and are particularly enriched in tears and
serum
13
. They are transported between cells either bound to RNA binding proteins (such as
Argonauts) or inside exosomes, which are nanosized extracellular vesicles of MVB origin that
protect miRNA from RNAse mediated degradation
14
.
miRNAs are incredibly stable, and resistant to degradation by RNAses and this is an
important quality for a good biomarker and as such are the most studied class of small non-coding
RNA (sncRNA) as biomarkers. They have been previously implicated in inflammatory diseases
and shown to have diagnostic potential with >95% sensitivity and specificity in several studies.
Human tears are reported to consist of over 600 distinct proteins
15
and more than 300 miRNAs
13
.
They have a higher concentration of miRNA than urine, CSF or plasma
13
. Recently, tears have
been investigated for miRNA biomarkers in AD
16
and open angle glaucoma with very high
sensitivity and specificity (AUC = 0.92)
17
indicating that changes in the tear transcriptome can
reflect disease status. However, to the best of our knowledge, the tear transcriptome in SS has not
been investigated by RNA sequencing. In addition to identifying markers for timely diagnosis of
Chapter 1

5
SS, studying dysregulated miRNAs may also provide insights into molecular dysfunctions causing
inflammation in exocrine glands in SS and identify molecular targets for drug development.
1.5 Overview of exosome formation and function
Exosomes are nano sized extra-cellular vesicles that are generated as intraluminal vesicles
in multivesicular bodies (MVBs). When exosomes arrive at their target site, they can elicit
intracellular signaling by ligand-receptor interaction either through their membrane proteins or by
the release of their soluble contents. Alternatively, they can fuse with the membrane of their target
cells or be internalized
[1]
. Exosomes have been observed to undergo internalization by
macropinocytosis in pancreatic cancer-derived cell lines
[2]
, microglia
[3]
and bone marrow-derived
mesenchymal stromal cells
[4]
. Receptor and lipid raft-mediated endocytosis has also been observed
in exosomes derived from rat adrenal medulla and glioblastoma
[5]
. Exosomes internalized by these
pathways may be degraded in lysosomes or escape lysosomal degradation and deliver their cargo
in cytoplasm.
In one study, exosomes electroporated with shRNA for mutant KRAS successfully
inhibited its expression and improved survival in mice with KRAS positive pancreatic cancer
[2]
.
This suggests that internalized exosomes can protect their cargo from degradation in lysosomes
but how they prevent the lysosomal degradation of their cargo is not clear
[5]
. Exosomes express
markers on their surface and carry proteins and various forms of ncRNA including miRNA. In
particular, miRNAs transported from cell to cell via exosomes have been implicated in several
diseases
18
. Exosomal cargo is also protected from degradation by RNAse, and as such they confer
substantial stability to their encapsulated cargo and have emerged as a reliable source of miRNA
for biomarker discovery [18].
Introduction

6
1.5.1 Exosome Isolation Methods
We have isolated and characterized exosomes by differential ultracentrifugation (UC) and
size exclusion chromatography (SEC). Optimizations for exosome isolation protocols and
characterizations were done with primary cultures of rabbit lacrimal gland acinar cells (RbLGAC).
We confirmed using two particle size analysis methods – Nanoparticle Tracking Analysis (NTA)
and Dynamic Light Scattering (DLS) that the size range of isolated exosomes was 30-130 nm with
a median diameter of 100 nm. Using immunoblot, we detected known exosome markers CD63,
Alix, TSG101 and CD9. We also detected Cathepsin S in these exosomes. Normalized intensity
of CD9 relative to total protein was significantly higher in RbLGAC exosomes indicating that this
marker was significantly enriched in the exosome fraction (Figure 1.1).

Figure 1.1 Characteristics of rabbit lacrimal gland acinar cell (LGAC) exosomes isolated by
differential ultracentrifugation.
(A) Assessment of particle size distribution and concentration of exosomes by nanoparticle tracking
analysis (NTA). (B) Assessment of particle size distribution of exosomes by Dynamic Light Scattering
(DLS). (C) Western Blots of known exosomes markers in rabbit LGAC exosomes and LGAC lysates. (D)
Relative enrichment of exosome marker CD9 in LGAC secreted exosomes and lysates

Chapter 1

7
Tears can be collected using either capillaries or Schirmer’s Strips, followed by elution in
500 μL PBS. Exosomes are isolated by first removing microvesicles through centrifugation at
10,000x g and isolating the vesicular fraction by SEC. Ultrafiltration with 100 kDa filters helps
further remove low molecular proteins or lipids that may be present in the exosome fraction. We
have collected exosomes from human tears using this protocol and characterized their size
distribution by NTA and DLS (Figure 1.3A) and detected exosome markers TSG101 and CD9
using WB (Figure 1.3B).

Figure 1.2 Characteristics of rabbit LGAC exosomes isolated by size exclusion chromatography
(SEC). Assessment of exosome size distribution by (A) NTA and (B) DLS. (C) Comparison of exosome
concentration and mean size of rabbit LGAC exosomes from three subsequent runs of a single SEC
columns. (D) Western blot of known exosome markers in rabbit LGAC exosomes in three concurrent runs
of SEC columns vs LGAC lysates.
Introduction

8

Figure 1.3 Human tear exosomes isolated by size exclusion chromatography. A) NTA analysis of tear
exosomes shows median particle diameter of 135 nm. B) WB shows tear exosomes isolated from two
healthy individuals contained TSG101 and CD9.Animal Models
Due to the substantial delay in diagnosis of SS, it is not possible to study molecular
alterations in the developing disease in human subjects. Therefore, we have employed model
organisms to study developing disease. In-vitro models include human corneal epithelial (HCE)
cells and primary cultures from Rabbit Lacrimal Gland Acinar Cells (RbLGAC), and in-vivo
models include the male non-obese diabetic (NOD) mice and RAB3D knockout mice.
1.6.1 Male NOD mouse, a model of SS-associated autoimmune dacryoadenitis
NOD mice have been extremely valuable as a model for SS as they develop SS-like
lymphocytic infiltrates in exocrine glands, (also known as dacryoadenitis) leading to dry eyes,
remodeling of the LG extracellular matrix, damage to the corneal epithelium as well as systemic
symptoms
19, 20
. Previously the Hamm-Alvarez group has shown that Cathepsin S expression and
protease activity is elevated in male NOD LG acini and tears when compared to the healthy male
BALB/c
21
. These findings were validated in human subjects
22, 23
as tear cathepsin S was
Chapter 1

9
significantly increased in SS patients when compared to tears of healthy controls or patients with
other types of dry eye or autoimmune diseases. This demonstrates the utility of using male NOD
mice for investigating the genetic and proteomic changes leading to SS development. While male
NOD mice spontaneously develop dacryoadenitis at any age
24
, the female NOD mice present a
good model to study salivary dysfunctions of SS, as they develop significantly more severe
infiltration of lymphocytes in the SG (also known as sialadenitis), with a higher prevalence than
age-matched male NOD
25, 26
. Female NOD mice have normal tear production and no lymphocytic
infiltration in their LG by 12 weeks and can be utilized as additional controls for local assessment
of SS associated LG disease.
1.6.2 Rab3d knockout mouse – a model to study trafficking defects associated with SS
Rab3D, a GTPase of the RAB family of proteins is required for the maintenance and
secretion of normal sized exocytotic vesicles
27
. While most Rab proteins are ubiquitously
expressed, Rab3D is involved in trafficking of secretory vesicles (SV), necessary for effective
docking or tethering of SVs with the plasma membrane. Other studies have shown that Rab3D is
necessary for the formation of granules that store von Willebrand's factor and its subsequent
release upon histamine stimulation
28
, and that Rab3D is selectively involved in secretion of certain
thrombogenic factors but not others. Three hours after stimulation with carbachol, Rab3D was
localized to the trans-golgi network vesicles. Without Rab3D, it is possible that the initial large
vesicles would not be tailored to the right diameter during maturation. Or perhaps Rab3D controls
a pre-exocytosis step, preventing or controlling granule-granule fusion at the Golgi.
There is a significant decrease in Rab3D gene expression in NOD mice LG and altered
distribution of the remaining protein
29
. There is also a significant decrease in protein levels of
Rab3D in the labial salivary glands of SS patients and alteration in its cellular localization
30
.
Introduction

10
Interestingly, Rab3D knockout mice appear to mimic some of the trafficking defects observed in
exocrine glands of NOD mice. They have elevated Cathepsin S gene expression in LG and
increased secretion and protease activity of cathepsin S in tears
29
. It is likely that reduced
expression of Rab3D observed in the LG of NOD mice contributes to their elevated Cathepsin S
activity in NOD mice tears. Thus, the Rab3D knockout mouse model has utility to study the
consequences of abnormal secretory trafficking in lacrimal gland acini in SS.
1.6.3 Human Subjects: SS and MGD patients
The majority of evaporative dry eye is caused by meibomian gland dysfunction (MGD),
while autoimmune diseases, such as SS, are frequently responsible for aqueous-deficient dry eye,
although SS patients can have both MGD and SS. SS and MGD have different clinical signs, but
the presenting symptoms are often similar. In MGD patients, there is damage to the meibomian
gland. Thus, lipid secretion required to control evaporation and maintain a normal tear film is
abnormal, leading to evaporative dry eye. In contrasts, SS-related dry eye is largely an aqueous
deficient dry eye resulting from the lack of aqueous tear secretion by the LG due to inflammatory
changes to the gland. In Chapter 4, I have validated candidate miRNA biomarkers in tear samples
from a small cohort of human subjects, with 6 SS and 6 MGD patients. MGD-dominant dry eye
patients served as controls.
1.7 Primary Aims
miRNAs have not been looked at in SS in easy to collect biofluids using RNA sequencing,
and we hope that our study will not only generate candidate biomarkers for human trials but also
expand on our understanding of auto-immune diseases by elucidating altered signaling pathways.
Exosomes are increasingly being investigated for disease diagnostics and drug delivery. The
Chapter 1

11
diagnostic potential of exosomal miRNA has been explored for various cancers
31
,
neurodegenerative
32
, autoimmune
33
and metabolic diseases
34
with high fidelity but remains
understudied in the context of SS. I have investigated miRNAs in serum exosomes using RNA
sequencing, validated differentially expressed miRNA in-vivo as potential diagnostic biomarkers
for SS and preliminarily investigate the signaling pathways they affect.
1.7.1 Aim 1 – Identifying dysregulated miRNAs in serum exosomes as potential biomarkers
for SS
Blood tests are minimally invasive and are routinely employed for diagnostic purposes.
However, no definitive analytical test exists for SS. We chose serum over plasma to reduce the
risk of hemolysis.It is reported that the most abundant serum miRNAs are similar from patient to
patient and show little variation after two cycles of freeze-thaw
35
. Given that exosomal miRNA
are enriched in serum (more concentrated than urine or CSF)
20
, and are highly conserved in
mammals
11, 12
, studying dysregulation of serum miRNA in developing SS in murine models may
have tremendous utility for SS diagnostics.
In Chapter 2 of this manuscript, I have assessed the differences in exosomal miRNA in a
murine model of SS (male NOD mouse). I have isolated and characterized serum exosomes,
isolated their RNA and profiled the miRNA by RNA sequencing. I have analyzed the data with
existing informatics tools and developed novel tools for accurate alignment and counting of
miRNA. To understand how these miRNAs contribute to inflammation, I have identified the
mRNA targets of the upregulated miRNA using predictive models and used gene enrichment
pathway analysis algorithms to predict . The results from this aim have been published in Frontiers
in Immunology and form the Chapter 2 of this dissertation.
Introduction

12
1.7.2 Aim 2 – Identifying dysregulated miRNAs in tears as putative biomarkers for SS.
Tears are relatively clean, free of blood contamination, and relatively stable when stored
at – 80 °C. Tear composition has longitudinal stability
36
and tears can be collected non-invasively
using Schirmer’s strips
37
. Thus, tears are an idea biofluid for diagnostic biomarker discovery. To
the best of our knowledge, the tear transcriptome has not been investigated in the context of SS
using RNA sequencing. Differential expression of miRNA in tears may be reflective of lacrimal
disease resulting from inflammatory and secretory dysfunction. Our preliminary data shows that
stimulated tears from four strains of mice (NOD, its control BALB/C, RAB3D knockout mice and
its control C57/BL6) are sufficiently concentrated in RNA as confirmed by tapestation. We have
profiled the small non-coding RNA of pooled tears using next generation sequencing with Illumina
HiSeq with the 2 x 75bp configuration. I have identified 17 miRNAs in male and female NOD
tears that are dysregulated when compared to the healthy BALB/c and 6 miRNAs dysregulated
because of the RAB3D knockout. Focus on these miRNAs will help us identify potential diagnostic
miRNAs for SS and determine a) whether the dysregulated miRNAs come entirely from secretions
of the lacrimal gland or not b) whether the dysregulation in secretion is a result of inflammation
or defective secretion.
1.8 Secondary Aims
Exploring robust diagnostic biomarkers is critical for the early diagnosis of SS. As
molecular mechanisms leading to immune dysregulation in SS remain unclear and because
miRNA control the transcriptional regulation of nearly 60% of genes, investigating them in SS can
shed light on altered signaling pathways that contribute to inflammation. Serum exosomal
miRNAs can be reflective of systemic dysfunctions whereas studying the miRNA repertoire of
tears can be reflective of local dysfunction in LG. Identification of dysregulated miRNA with the
Chapter 1

13
understanding of their tissue of origin, their mRNA targets and pathology will improve our
understanding of dacryoadenitis in SS and may even help identify druggable targets. miRNAs may
also have utility as companion biomarkers to assess the clinical utility of a drug.

14
Chapter 2 Small RNA deep sequencing identifies a unique
miRNA signature released in serum exosomes in a mouse
model of Sjögren’s Syndrome^
Kakan SS, Janga SR, Cooperman B, et al. Small RNA Deep Sequencing Identifies a Unique miRNA
Signature Released in Serum Exosomes in a Mouse Model of Sjögren's Syndrome. Front Immunol.
2020;11:1475.
Keywords: Sjögren's Syndrome; diagnostic miRNA biomarkers; extracellular vesicles; small-RNA
sequencing; microRNA; piwi-RNA
^ Note: This chapter is taken verbatim from the above-mentioned publication.
2.1 Abstract
Sjögren’s Syndrome (SS) is an autoimmune disease characterized by lymphocytic
infiltration and loss of function of moisture-producing exocrine glands as well as systemic
inflammation. SS diagnosis is cumbersome, subjective and complicated by manifestation of
symptoms that overlap with those of other rheumatic and ocular diseases. Definitive diagnosis
averages 4-5 years and this delay may lead to irreversible tissue damage. Thus, there is an urgent
need for diagnostic biomarkers for earlier detection of SS. Extracellular vesicles called exosomes
carry functional small non-coding RNAs which play a critical role in maintaining cellular
homeostasis via transcriptional and translational regulation of mRNA. Alterations in levels of
specific exosomal miRNAs may be predictive of disease status. Here, we have assessed serum
exosomal RNA using next generation sequencing in a discovery cohort of the NOD mouse, a
model of early-intermediate SS, to identify dysregulated miRNAs that may be indicative of SS.
We found five miRNAs upregulated in serum exosomes of NOD mice with an adjusted p-value <
0.05 – miRNA-127-3p, miRNA-409-3p, miRNA-410-3p, miRNA-541-5p, and miRNA-540-5p.
Chapter 2
Kakan SS, et al. Frontiers in immunology. 2020 Jul 17; 11:1475.
15
miRNAs 127-3p and 541-5p were also statistically significantly upregulated in a validation cohort
of NOD mice. Pathway analysis and existing literature indicates that differential expression of
these miRNAs may dysregulate pathways involved in inflammation. Future studies will apply
these findings in a human cohort to understand how they are correlated with manifestations of SS
as well as understanding their functional role in systemic autoimmunity specific to SS.
2.2 Introduction
Sjögren’s Syndrome (SS) is a chronic and systemic autoimmune disease marked by
lymphocytic infiltration and loss of function of the body’s moisture producing exocrine glands
(e.g., lacrimal and salivary glands) as its defining manifestation. It is the second most common
rheumatic autoimmune disease, affecting about 0.5 – 1% of the general population
38, 39
. The
progressive inflammation of lacrimal and salivary exocrine glands is associated with their loss of
function, leading to debilitating dry eye and dry mouth, respectively
40
. SS is associated with
increased inflammation of internal organs including brain, lung and liver
1
as well as a 44-fold
increased risk of developing B-cell lymphoma
2, 41
. SS can occur in the absence of another
autoimmune disease (primary SS) or concurrently with another autoimmune disease such as
rheumatoid arthritis or systemic lupus erythematosus (secondary SS).
Diagnosis of SS relies on the weighted score obtained from a series of criteria established
in 2016 by the American College of Rheumatology (ACR) in collaboration with the European
League Against Rheumatism (EULAR)
42
. These criteria include: 1) labial salivary gland biopsy
showing focal lymphocytic sialadenitis with a focus score ≥1; 2) anti-SSA (Ro) positivity (serum
autoantibody); 3) ocular surface staining score ≥ 5 (or van Bijsterveld score ≥ 4) on at least one
eye; 4) a Schirmer’s value (tear flow) ≤ 5 mm/5 min on at least one eye; and 5) an unstimulated
whole saliva flow rate ≤ 0.1 ml/min. Although, commonly used for inclusion in clinical trials, these
Serum Exosomal miRNA in SS Model
Kakan SS, et al. Frontiers in immunology. 2020 Jul 17; 11:1475. 16
criteria are not always practically applicable for clinical diagnosis. In particular, the labial salivary
gland biopsy is painful, impractical and error-prone
9
. Furthermore, these criteria have been
developed primarily for patients with primary SS, and are not extensively validated in the far
greater numbers of patients suffering from secondary SS. Therefore, many patients experience a
substantial delay in diagnosis while some are never formally diagnosed. This delay in diagnosis
may also delay treatment with anti-inflammatory agents to the point when irreversible damage to
exocrine glands and other internal organs may already have occurred
10
. Hence, there is an urgent
need for an early, sensitive and non-invasive diagnostic test for SS.
In this study we utilized the Non-Obese Diabetic mouse model of SS. The NOD/Shi strain
originated from inbreeding of the Cataract Shionogi (CTS) strain, based on elevated fasting blood
glucose level in cataract-free mice for the development of a model for insulin dependent diabetes
mellitus. It was later also shown to develop features of exocrinopathy consistent with SS
43
. Despite
limitations to any animal model, this model exhibits several features of SS in humans including
reduced tear and salivary secretion
44, 45
, alterations in tear and salivary composition
21, 23, 46
,
lymphocytic infiltration of lacrimal and salivary glands (dacryoadenitis and sialadenitis,
respectively)
44, 45
, and the presence of many of the serum autoantibodies that are often present in
human patients, such as autoantibodies to Ro/SSA and La/SSB
19
, the M3 muscarinic acetylcholine
receptor
47, 48
, salivary gland protein 1
49
, carbonic anhydrase 6
49
and parotid secretory protein
(PSP)
49
. Finally, the lacrimal glands (LG) of these mice show characteristic changes in specific
proteins involved in the secretory process of exocrine glands typical of SS patients
29, 30
. We have
previously demonstrated that tear biomarkers identified in this murine model are also identified in
SS patients
21, 23, 46
.
Chapter 2
Kakan SS, et al. Frontiers in immunology. 2020 Jul 17; 11:1475.
17
Although, SS is more prevalent in women than in men at a 9:1 ratio
40
, only male NOD
mice were used in this study, because the male mice have been extensively characterized to exhibit
the features of autoimmune dacryoadenitis and systemic disease prior to the development of
diabetes. Females of this strain instead develop autoimmune sialadenitis concurrent with
diabetes
50
, complicating interpretation of any results. Thus, use of male NOD mice allows us to
avoid confounding effects associated with the concurrent development of diabetes. Our mice were
chosen at the age just after lymphocytic infiltration of the LG is typically established (14 weeks),
representing an early-intermediate stage disease model of autoimmune dacryoadenitis in SS. As
the disease development in this strain is polygenetic, and many of the diabetes resistant sub-strains
that have been developed as controls for studying diabetes still develop autoimmune
exocrinopathy
44, 51, 52
, there has been a lack of closely related healthy control strains for studies of
SS disease development and treatment. With this said, the BALB/c strain has been the most used
for studies of SS exocrinopathy by multiple groups beyond our own
53-56
. Therefore, we considered
it the most prudent choice for use as a control strain.
MicroRNAs (miRNA) are evolutionarily conserved short non-coding RNA that function
in gene silencing and post-transcriptional gene regulation
11
, regulating nearly 60% of messenger
RNA (mRNA)
12
. A single miRNA can target several mRNAs and any given mRNA may be
targeted by more than one miRNA. Cooperativity between a group of dysregulated miRNAs
targeting one or more mRNAs of a given signaling pathway or cellular process may substantially
upregulate or downregulate that pathway and lead to development and progression of disease.
Indeed, miRNA dysregulation is associated with cancer
57
, obesity
58
, heart disease
59
, kidney
disease
60
and diseases of the nervous system
61
. The diagnostic potential of miRNAs has been
explored with high fidelity in various cancers
31
, as well as neurodegenerative
32
, autoimmune
33
and
Serum Exosomal miRNA in SS Model
Kakan SS, et al. Frontiers in immunology. 2020 Jul 17; 11:1475. 18
metabolic diseases
34
. Thus, assessing the level of expression of a panel of functional mature
miRNAs can be diagnostic of a given disease. Compared to proteins, miRNAs have lower inter-
individual variation and less sequence heterogeneity, allowing for high specificity as biomarkers
62
.
Further, as miRNAs are highly evolutionarily conserved in mammals, results from an animal
model are typically readily applicable to human subjects
63
.
miRNAs circulate in a stable, cell-free form in all biofluids and are particularly enriched
in serum
13
. Relative to other biofluids such as saliva, urine, and cerebrospinal fluid (CSF), serum
has a higher concentration of miRNA
13, 64
. Most extracellular miRNAs as well as other non-coding
RNAs (ncRNA) can be found in exosomes which are nano-sized extracellular vesicles, generated
as intraluminal vesicles in multivesicular bodies (MVBs). Exosomes are actively shed from nearly
every cell type and engage in intercellular signaling. Literature suggests that aberrant exosome-
based intercellular communication plays a role in infectious, neurodegenerative and inflammatory
diseases and various cancers. Exosomes are an extremely reliable source of miRNA as their
contents are resistant to degradation by nucleases such as RNase
31, 65-68
. Moreover, exosomal
miRNAs are relatively stable following storage at -80 °C, have a very low inter-individual
variance, and also exhibit a low intra-individual variance over time
69
.
The goal of this study was to understand how changes in regulatory small RNAs in serum,
particularly miRNAs, might have utility as a source of diagnostic biomarkers for SS. Here we
identify a subset of dysregulated miRNAs that may be specific to SS. We identified 5 exosomal
miRNAs that showed significant changes in concert with establishment of SS-like symptoms in
NOD mice, representing putative biomarkers for early disease diagnosis. Additionally, we have
also assessed differential expression of other small non-coding RNA such as piRNA, that protect
the genome by silencing transposons.
Chapter 2
Kakan SS, et al. Frontiers in immunology. 2020 Jul 17; 11:1475.
19
2.3 Materials and methods
2.3.1 Mice
Age-matched male NOD/ShiltJ (Stock No. 001976) and BALB/cJ (Stock No. 000651)
mice were purchased from Jackson Laboratories (Bar Harbor, ME) and housed with a 12-hr light,
12-hr dark cycle with ad libitum access to food and water until 14 weeks of age, when SS-like
ocular symptoms are established in the NOD strain. All procedures performed on the mice were
in accordance with protocols approved by the University of Southern California’s Institutional
Animal Care and Use Committee (IACUC) and the Guide for Care and Use of Laboratory Animals
8
th
edition
70
.
2.3.2 LG Histology and quantitative analysis of lymphocytic infiltration
Lymphocytic infiltration in mouse lacrimal glands, indicative of autoimmune
dacryoadenitis, was confirmed and quantified with hematoxylin & eosin staining as described
71
.
Briefly, lacrimal glands from NOD and BALB/c mice were fixed in 10% NBF (Richard-Allan
Scientific, Kalamazoo, MI), fixed in paraffin, then cut into 5 µm horizontal sections and stained
with hematoxylin and eosin. Sections were imaged using an Aperio Digital ScanScope (Leica
Biosystems Inc, Buffalo Grove, IL) using the 40x objective lens. The percentage of lymphocytic
infiltration in the tissue was determined by calculating the area of infiltrates manually using ImageJ
(National Institutes of Health, http://imagej.nih.gov/ij). Data were analyzed by GraphPad Prism
using one-way non-parametric ANOVA (Kruskal-Wallis).
2.3.3 Isolation of serum exosomes
Mice were anesthetized by intraperitoneal injection with ketamine/xylazine (60–70 mg +
5–10 mg/kg, respectively), and blood was collected by cardiac puncture using a 1 mL syringe (BD
Serum Exosomal miRNA in SS Model
Kakan SS, et al. Frontiers in immunology. 2020 Jul 17; 11:1475. 20
Biosciences, San Jose, CA) into MiniCollect 0.8 mL gold cap Z Serum Separator tubes (Greiner
Bio-One, Kremsmünster, Austria). Thereafter the mice were euthanized by cervical dislocation.
Blood was allowed to clot for 20 min at room temperature followed by centrifugation at 4 ºC, 2000
x g for 15 min. Serum was collected and spun at 2000 x g for 20 min at 4 ºC to pellet cellular
debris. The supernatant was collected and spun at 12,000 x g for 45 min to remove microvesicles.
Approximately 2000 µL of pooled supernatant from 5 mice was concentrated using 10 kDa
Millipore Amicon Ultra concentrators (Burlington MA) to 500 µL and then loaded on an
equilibrated iZON qEV original size exclusion column (Christchurch, New Zealand). Fractions 7
– 9 containing 1.5 mL of exosomes were collected and concentrated by 10-fold using 100 kDa
concentrators (MilliporeSigma, Burlington, MA). Alternatively, exosomes were enriched from the
supernatant obtained by centrifugation of serum as above and resolved by differential
ultracentrifugation as previously described
72
with some modifications using a Beckman Coulter
Optima LE-80k with a Beckman Coulter Type 50.2 Fixed Angle Rotor. Briefly, after the 12,000x
g spin of the clarified serum, the supernatant was centrifuged at 110,000 x g for 120 min. The
pellet was resuspended in 2 mL of PBS containing 0.25 mM Trehalose (PBST) and centrifuged at
110,000 x g for 70 min. The exosome pellet was resuspended in 200 µL of PBST. Purified
exosomes from each protocol were used directly for RNA isolation, Western blotting or flash
frozen and stored at -80 °C for later analysis. A total of 5 groups per strain and 5 mice per group
were utilized as biological replicates for the discovery as well as validation cohort.
2.3.4 Total RNA Isolation
RNA was isolated using the miRNeasy Serum/Plasma Mini Kit (Qiagen, Hilden,
Germany). The manufacturer’s protocols were followed as written, except for the final collection
step which was performed sequentially in two steps. First, 25 μL of nuclease-free water was added
Chapter 2
Kakan SS, et al. Frontiers in immunology. 2020 Jul 17; 11:1475.
21
to the spin column for 10 min before elution of sample. Then, this step was repeated using 15 μL
of nuclease-free water to increase the recovery yield. Combination of both eluates yielded around
30 μL of total RNA collected per pooled exosome sample from 5 mice. The amount and quality of
RNA was analyzed using a Nanodrop to assess initial concentration, and TapeStation (Agilent) to
assess sample quality utilizing RNA integrity number (RIN).
2.3.5 Transmission Electron Microscopy
Exosomes stored at -80°C were thawed and fixed on 150 mesh copper carbon formvar grids
(Electron Microscopy Sciences, Hatfield, PA). With high precision negative forceps (Electron
Microscopy Sciences, Hatfield, PA), 10 µL of exosome samples were incubated with grids for 5
min. Excess liquid was absorbed using filter paper. The grid was incubated with 1% aqueous
uranyl acetate (Electron Microscopy Sciences, Hatfield, PA) for 5 min. After rinsing with 10 µL
ultrapure water, the grid was air dried for 30 min before storage or immediate viewing in a
JEM1400 transmission electron microscope operating at 100 keV.
2.3.6 Western Blotting
Equal volumes of exosome samples were heated for 5 min at 95 °C under reducing
conditions and resolved over 8 – 16 % Novex WedgeWell Tris-Glycine Polyacrylamide Gels
(ThermoFisher, Waltham, MA) for 90 min at 125 volts, under constant voltage. Proteins in gels
were transferred to nitrocellulose membrane using an iBLOT 2 device and Invitrogen iBLOT 2
NC stacks (ThermoFisher, Waltham, MA). Membranes were rinsed in Phosphate Buffered Saline
(PBS) and blocked in Rockland Blocking Buffer for Fluorescent Western Blotting (Pottstown, PA)
for 1 hr at room temperature. Membranes were incubated with rabbit primary polyclonal antibodies
to TSG101 (Abcam – EPR7130(B), 1:250 dilution), and primary monoclonal antibody to
Cathepsin L (Abcam – EPR8011, 1:500 dilution) overnight at 4
o
C. After six 5-min washes in 1x
Serum Exosomal miRNA in SS Model
Kakan SS, et al. Frontiers in immunology. 2020 Jul 17; 11:1475. 22
PBS, membranes were incubated in goat-anti rabbit IR800 secondary antibody for 1 hr at RT and
rinsed again with 1x PBS, 6 times for 5 min each before imaging on a LI-COR Odyssey
Fluorescent Imager. Images were analyzed using ImageStudio v5.2.5.
2.3.7 Particle Size Analysis
Size and concentration of exosomes was measured by Nanoparticle Tracking Analysis
(NTA) using a ZetaView (Particle Metrix, Meerbusch, Germany). Some samples were also
shipped to Alpha Nano Tech LLC (Chapel Hill, NC) for analysis by a ZetaView S/N 17-332
running the software ZetaView v8.04.02. After calibration with 100 nm standards (Applied
Microspheres, The Netherlands), samples were diluted in varying amounts of PBS to reach the
optimal concentration for analysis, then injected into the ZetaView cell for measurement. 11 cell
positions were sampled for two cycles each, with outliers automatically removed by the software.
Measurements were taken at 22 °C, using a sensitivity of 75, a frame rate of 30, and a shutter speed
of 100. These measurements were analyzed using a minimum brightness of 20, a maximum size
of 500 pixels, and a minimum size of 10 pixels. As it is the best determinant of particle size, the
mode was selected as the main sizing parameter
73
. Total particle count was calculated to account
for varying resuspension volumes.
Particle size was also analyzed by Dynamic Light Scattering (DLS) using a Wyatt Dyna-
Pro Plate reader II (Wyatt Technologies, Santa Barbara, CA). Briefly, 60 µL of exosome samples
were run in triplicates at 25 °C in a 384-well clear bottom plate (Greiner Bio One, Monroe, NC).
The hydrodynamic radius of isolated exosomes was measured and presented as a normalized
diameter. Data was analyzed using Dynamics V7 software (Wyatt, Santa Barbara, CA).
Chapter 2
Kakan SS, et al. Frontiers in immunology. 2020 Jul 17; 11:1475.
23
2.3.8 Small RNA Deep Sequencing
Library preparation and sequencing on exosome fractions were performed by GeneWiz
(South Plainfield, NJ). Total RNA containing the small RNA fraction was converted into cDNA
using the Illumina TruSeq Small RNA library prep kit according to the manufacturer’s
instructions. Briefly, 3’ adapter ‘RA3’ and 5’ adapter ‘RA5’, were ligated to total RNA which was
then reverse transcribed. Adapter ligated cDNA library was enriched by PCR using primers that
selectively anneal to the adapter sequence and then purified by gel electrophoresis. Quality of the
cDNA library was assessed using a DNA chip on bioanalyzer. Barcodes were added to each sample
and all 10 samples were sequenced on a single lane of an Illumina HiSeq system set to a 2x150 bp
configuration. The output generated a total of ~414 million reads which were then demultiplexed
with the added barcode separating the files according to the samples into FASTQ files.
2.3.9 Bioinformatics
The raw FASTQ files obtained from Genewiz were assessed for their quality using FastQC
v0.11.9. Adapter trimming was performed using Cutadapt v2.8 (https://github.com/
marcelm/cutadapt). High quality reads of minimum length 15 nucleotides (nt) were mapped to
whole genome (mm10 assembly GRCm38) using Bowtie v1.2.3
74
and annotated using
featureCounts v2.0.0
75
, using GENCODE (Release M24, GRCm38.p6) comprehensive gene
annotation GTF file (PRI) to obtain distribution of reads over genome and raw counts for various
non-coding RNA such as pre-miRNA, scRNA, scaRNA, snRNA, tRNA, rRNA, snoRNA and
lncRNA. Reads were then mapped to small RNA transcriptomes (miRbase v22, piRdbv2.0). The
output files in the SAM file format were sorted to mapped reads that had an alignment CIGAR
string of 18M or higher. Sam2counts, a python program was used to acquire counts of reads aligned
to transcriptomes (https://github.com/vsbuffalo/sam2counts)
76
.
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Kakan SS, et al. Frontiers in immunology. 2020 Jul 17; 11:1475. 24
Raw reads were also aligned to the piRNA and miRNA transcriptomes using an in-house
aligner ‘miRGrepp’ (https://github.com/singhkakan/miRGrep) that applies brute force to count the
number of reads containing a given miRNA or piRNA sequence. As miRNA are 19 – 26 bp long
and piRNA are 24 – 30 bp long, the entirety of their sequence is read during sequencing. As a
result, the reads (75 to 150 bp) are longer than the miRNA or piRNA of interest and contain their
complete sequence. miRGrepp yielded a final count table which was assembled in RStudio using
the dplyr package for further processing. After the miRNA or piRNA counts table was generated,
differential gene expression analysis was conducted using three statistical R packages DESEq2
77
,
EdgeR
78
and LimmaVoom
79
in RStudio. Statistical significance was determined by adjusted p
value of < 0.05 by DESEq2 or Limma or False Discovery Rate (FDR) < 0.1 by EdgeR. We have
included miRNAs considered significant by at least 1 statistical package for downstream analyses.
The experimental procedures and analysis pipeline are detailed in Figure 2.1.
2.3.10 miRNA validation assays
In a separate validation cohort of 5 groups with 5 mice per group, we isolated serum
exosomal RNA. The differential expression of miRNAs of interest was validated by qRT-PCR
using individual Taqman Advanced miRNA Assays (Applied Biosystems). Briefly, poly-A tailing
and adapter ligation was performed on 2 µL of total RNA isolated from serum exosomes of the
validation cohort using the Taqman Advanced cDNA synthesis kit. Following this cDNA
synthesis, miRNA amplification was conducted using the same kit. The amplified cDNA was
diluted 1:10 and set up in triplicate qRT-PCRs with 1 µL of specific Taqman Advanced miRNA
primer and run on a Quant-Studio Flex 6 (Applied Biosystems, Foster City, CA), using the assay’s
recommended cycling conditions. Results were analyzed by the DDCt method with BALB/c serum
exosomal small RNA as reference and miR-16-5p as housekeeping miRNA. 16-5p is identified in
Chapter 2
Kakan SS, et al. Frontiers in immunology. 2020 Jul 17; 11:1475.
25
the literature as a suitable housekeeping miRNA
80-83
and was unchanged between serum exosomes
in BALB/c and NOD mice in the sequencing data obtained in this study (p = 0.995, DESeq2).

Figure 2.1 Schematic depicting the bioinformatics analysis pipelines. Mouse serum was collected by
cardiac puncture and exosomes were isolated by differential ultracentrifugation (UC). Exosomal RNA was
isolated and assessed for quality. After library preparation, Illumina HiSeq was used for sequencing 150 bp
paired end reads. Data analysis was done using Bowtie and an in-house aligner miRGrep. (1) Quality of
reads was assessed using the program FastQC (v0.11.9). The QC found that the samples had adapter content
and required trimming. (2) Adapter content and reads with poor quality scores were removed using
Cutadapt (v2.8). (3) Trimmed reads were aligned to whole mouse genome (GRCm38.p6) to identify the
regions of the genome the reads map to (exons vs introns vs intergenic) using Bowtie (v1.2.3). (4) Counts
for various non-coding, RNA (including pre-miRNA snoRNA, scaRNA, scRNA, snRNA, rRNA, tRNA)
were obtained using featureCounts (v2.0.0). Reads were aligned to miRBase v22 using Bowtie and count
table was generated using a python program sam2counts. (5) Differential gene expression analysis was
conducted in RStudio using DESeq2, EdgeR and Limma.
Alternately, (1) alignment and quantification of reads to miRBase v22 and piRDb v2 was done using an in-
house aligner miRGrep that employs brute force as its alignment algorithm and generates a final count
table. (2) Differential Gene expression analysis was done similarly as before in RStudio using three
statistical packages.
2.3.11 Pathway and functional enrichment analysis
Pathway analyses were conducted using miTALOS v2.0
84
using StarBase2, a database of
experimentally validated miRNA targets. Pathway data were extracted from KEGG, Reactome,
and WikiPathways by miTALOS. Pathways with a corrected p-value < 0.05 and Enrichment score
> 1 are expected to contain over-represented miRNA targets. Functional enrichment analysis was
Serum Exosomal miRNA in SS Model
Kakan SS, et al. Frontiers in immunology. 2020 Jul 17; 11:1475. 26
done using the custom heatmap calculator of miRPathDB v2.0
85
using Gene Ontology (Biological
Enrichment) with at least two miRNA per pathway and two pathways per miRNA. The settings
were chosen such that signaling pathways in which at least 2 of our miRNAs of interest have an
mRNA target, would be identified. Additionally, the program was directed to identify at least two
pathways targeted by each miRNA. With these constraints we may identify pathways that have a
high probability of being dysregulated with the aberrant expression of the miRNA of interest.
Pathway analysis was also conducted using Ingenuity Pathway Analysis (IPA) to visualize the
interaction of miRNA “hits” with their targets in the signaling pathways relevant to autoimmunity,
which were also identified by miTALOS and miRPathDB.
2.4 Results
2.4.1 Characterization of exosomes from mouse serum
Establishment of autoimmune dacryoadenitis, the most notable characteristic of SS in these
mice, was confirmed in each NOD cohort relative to BALB/c by H & E staining of lacrimal gland
sections and quantitation of lymphocytic infiltrates (Figure 2.2A). While we did not observe any
lymphocytes infiltrating LG in the BALB/c, NOD mice had infiltration between 8 – 15% (p <
0.0001, one-way ANOVA) (Figure 2.2B). We chose exosomes as the principal source of serum
miRNAs based on findings that miRNAs are concentrated in these organelles in extracellular
biofluids. Exosomes were isolated by differential ultracentrifugation (UC) for discovery
experiments and by size exclusion chromatography (SEC) for validation experiments.
Transmission electron microscopy (TEM) images showed ~100 nm sized vesicles with the
characteristic cup shaped morphology typical of exosomes
86
for both UC
87
and SEC exosomes
(Figure 2.3A). UC exosomes had a median diameter of 136 nm from male NOD mouse serum and
131 nm for BALB/c mouse serum
87
, while SEC exosomes had a median diameter of 122 nm for
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Kakan SS, et al. Frontiers in immunology. 2020 Jul 17; 11:1475.
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NOD and BALB/c mouse serum (Figure 2.3B). There was no significant difference in the sizes
of the exosomes isolated by the two methods, although exosomes isolated by UC were slightly
larger in accord with previous reports
88
.
SEC has been reported to give a better yield than UC
89
, consistent with our findings. There
were no significant differences in the size or concentration of exosomes between the two strains
of mice. Western blotting also showed the presence of the universal exosome membrane protein
marker, TSG101, in exosomes isolated from both strains (Figure 2.3C). Various cathepsins (S, D,
K and L) have been found in exosomes derived from plasma
90
, macrophages
91
and microglia
92
.
Interestingly, we found enrichment of cathepsin L in exosomes isolated from both strains (Figure
2.3C). DLS found that SEC exosomes ranged from 60 – 130 nm with a mean diameter of 122 nm
(Figure 2.3D). There was no strain specific difference in size, concentration or marker expression
between exosomes isolated from the two strains. For study design, UC exosomes were used for
miRNA “hit” identification and SEC exosomes were used for “hit” validation.
A B

Figure 2.2 Infiltration of lymphocytes in lacrimal gland (LG) of male NOD but not BALB/c mice reflects
established autoimmune dacryoadenitis in the mice used as a source of exosomes.
(A) Representative hematoxylin and eosin (H&E) staining of LG sections shows that lymphocytic
infiltration is observed exclusively in the NOD mice (scalebar, ~250 μm). (B) Quantification of the area
of infiltration in three sections per mouse LG taken at 25%, 50% and 75% depth, shows that this
phenotype is statistically significant in the NOD mice (p < 0.0001, one-way ANOVA, n =5 groups, 5
age matched mice per group).
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Kakan SS, et al. Frontiers in immunology. 2020 Jul 17; 11:1475. 28

2.4.2 Mouse serum exosomes contain several small RNA biotypes
Since most extracellular ncRNA are associated with extracellular vesicles
93
, UC serum
exosomes were used as a source for small RNAs from NOD and BALB/c mice. Using next-
generation sequencing (NGS), we profiled small RNA in serum exosomes from each mouse strain
to identify both novel and differentially expressed miRNA. A total of 417 million raw reads were
generated which were mapped to the mouse genome and various small ncRNA transcriptomes.
A

B

C

D

Figure 2.3 Characterization of mouse serum-derived exosomes by differential ultra-
centrifugation (UC) and Size Exclusion Chromatography (SEC).
(A) Transmission Electron Microscopy (TEM) of SEC exosomes isolated from NOD (left) and
BALB/c (right) mouse serum. (B) NTA of SEC exosomes. (C) Western blotting of NOD and
BALB/c serum exosomes isolated by SEC shows enrichment of TSG101 and Cathepsin L. (D)
Exosome particle size of SEC exosomes analyzed by DLS showed a median diameter of 122 nm
from both strains. The graph is representative of three separate experiments.
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Of the reads that mapped to the mouse genome, roughly two-thirds of the reads mapped to
intergenic or intronic regions while a third of the reads mapped to exons. Less than 10% of the
reads mapped to transcription start or end sites. (
Figure 2.4A). Read distribution was fairly uniform across samples with no strain specific difference. More
than 50% of mapped reads were comprised of miRNA (both mature and precursor) and piRNA. Nearly
27% of reads mapped to lncRNA, and 20% to rRNA, whereas less than 1% mapped to small nucleolar RNA
(snoRNA) (
Figure 2.4B, C) in serum exosomes of both NODs and BALB/c mice. Reads that mapped to
miRNA, piRNA, lncRNA, snRNA, snoRNA, scaRNA and rRNA are provided in Table 2.2.
We did not observe any strain-specific differences in proportion of RNA sub-types within
the small ncRNA libraries of NOD and BALB/c serum exosomes (p = 0.925, ordinary two-way
ANOVA). piRNA are involved in gene silencing of transposons by forming complexes with
argonaute proteins
94
, and appear to provide RNA-mediated adaptive immunity against
transposons
95
. In our analysis we found that 208 piRNA were expressed in NOD mouse UC
exosome samples and 238 in BALB/c mouse samples. Of these, 171 were found in both but 37
were unique to NOD mouse samples, and 67 unique to BALB/c mouse samples (Figure 2.5B).
The ten most highly expressed piRNA did not appear to be dysregulated in the NOD strain (Figure
2.5A). There were no significant differences in the total number of distinct piRNA or the total
number of reads aligning to piRdb between the two strains (Figure 2.5C). We found 13 piRNA to
be upregulated in NOD mouse samples with a log2 fold change >3, while 15 were downregulated
with a log2 fold change < -3. Of these, only mmu-piR-58696 was significantly upregulated in the
NODs as determined by LimmaVoom (padj = 0.047) (Figure 2.5D).

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Kakan SS, et al. Frontiers in immunology. 2020 Jul 17; 11:1475. 30

Figure 2.4 Graphical presentations of the distribution of reads from NGS sequencing of RNAs. (A)
shows the regions of the mouse genome that reads of all samples were aligned to. The mapping percentage
is greater than 100 as multi-mapping reads were also counted. No significant sample to sample variation
was observed. (B) and (C) show the distribution of reads aligning to various ncRNAs in NOD & BALB/c
serum UC exosomes. Results were obtained from n=5 UC serum exosome samples per mouse strain, with
each sample comprising pooled serum exosomes from 5 mice.
TSS: Transcription Start Site; TES: Transcription End Site; kb: kilobases; pre miRNA: precursor
microRNA; rRNA: ribosomal RNA, lnc RNA – long non-coding RNA; snRNA – small nuclear RNA;
snoRNA – small nucleolar RNA, scaRNA – small cajal body specific RNA; mature miRNA – mature
microRNA; piRNA – piwi interacting RNA
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A

B

C

D

Figure 2.5 Profiling of UC exosome derived piRNA & differential expression analysis.
(A) Venn Diagram showing number of uniquely expressed piRNA per strain. (B) Barplot comparing
overall expression of piRNA in NODs and BALB/c (top) and the total number of distinct piRNA
expressed per strain (bottom). There was no strain specific difference in the overall expression of piRNA.
(C) Differential piRNA expression analysis found that piRNA58696 (piRdb) was significantly higher in
NODs when compared to BALB/c (LimmaVoom padj = 0.047, n =5 groups, 5 age matched mice per
group). (D) Barplot comparing the top 10 highly expressed piRNA in NOD and BALB/c serum UC
exosomes.

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Kakan SS, et al. Frontiers in immunology. 2020 Jul 17; 11:1475. 32
2.4.3 NOD serum exosomes contain a subset of dysregulated miRNA
FASTQ reads were preprocessed using FASTqc which identified the presence of adapter in ~ 90%
of the reads. Cutadapt was used to remove adapter sequences and exclude reads of quality < 20
and length < 15. from miRbase v22.0 using Bowtie v1.2.3, as well as our in-house aligner
miRGrepp, which utilizes brute force and was written specifically for the alignment of RNA < 30
nt in length such as miRNA and piRNA. With Bowtie, we identified 550 distinct miRNAs in NODs
and 255 in BALB/c. Using miRGrepp, we identified 251 miRNAs in the NODs and 242 miRNAs
in BALB/c. This was expected because miRGrepp uses brute-force to align reads to miRNA, with
no mismatch allowed in alignment and therefore, the miRNA identified by miRGrepp are a subset
of those identified by Bowtie
96
.
Of these, read counts for 38 miRNAs were found only in NOD serum exosomes while 29
miRNAs were found only in BALB/c serum exosomes (Figure 2.6A) in at least 3 out of 5 sample
groups per strain. The top 20 expressed miRNA in NOD serum exosomes were overrepresented to
the same extent in BALB/c (Figure 2.6B) with no discernible strain specific differences. Of these
miRNAs, miR-191-5p, miR-92a-3p, miR-22-3p, miR-16-5p, let-7f-5p, let-7i-5p, miR-26a-5p,
miR-30e-5p, miR-186-5p, miR-30d-5p, miR-451a, miR-181a-5p, miR-148a-3p, miR-423-5p, let-
7a-5p, and miR-25-3p have been previously reported to be abundant in serum exosomes
97
. miR-
486-5p (not shown) was the top over-represented miRNA as reported previously
97
. It is possible
that these miRNAs serve important regulatory functions that are evolutionarily conserved.
The volcano plot in Figure 2.7A shows the level of differential expression for all expressed
miRNA identified in NOD mouse serum. miRNA that had an adjusted p value > 0.05 and log2
fold change less than 3 or greater than -3 were not considered significant. DESeq2 and Limma
determine significance when an adjusted p value < 0.05 is reached whereas EdgeR considers a hit
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significant only when the FDR is < 0.1 in RStudio (Table 2.1). We have reported and assessed
miRNA that met our significance criteria by at least one of the statistical packages.

Figure 2.6 Profiling of exosome derived miRNA. (A) Venn diagram showing number of detectable
miRNAs per strain. (B) Barplot comparing the top 18 highly expressed miRNA in NOD and BALB/c UC
serum exosomes from 14-week NOD and BALB/c mice. Data are plotted as raw counts normalized to total
number of reads per strain that aligned to miRbase v22 (Data shown is mean ± SD, n =5 groups, 5 age
matched mice per group). There was no significant difference in the expression levels of the most abundant
miRNAs between the two strains. (C) Barplot showing miRNAs with fold change greater (or less than) 3.
However, only the upregulated miRNAs reached statistical significance (** p < 0.001; * p < 0.01, DESEq2,
n =5 groups, 5 age matched mice per group).

Unsupervised hierarchical clustering analysis of top hits using the Euclidean method
clustered NOD mouse miRNA samples in the same group, separate from BALB/c samples, as
shown by the top tree (Figure 2.7B), suggesting that the differential expression observed may be
attributed to dysregulation in the NOD strain. We performed an additional unsupervised technique
to visualize the variability between the two groups. Principal component analysis (PCA) of the 10
samples with ~ 500 expressed miRNAs revealed that 22% of the variance could be explained by
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Kakan SS, et al. Frontiers in immunology. 2020 Jul 17; 11:1475. 34
the differences in strain (Figure 2.7C). All three packages determined that miR-127-3p, miR-409-
3p and miR-540-3p were significantly overexpressed in NOD mouse (Figure 2.8A). Limma
identified miR-410-3p and miR-541-5p to be overexpressed in NOD serum exosomes (Figure
2.8B).
Furthermore, we found an additional 19 miRNAs that displayed an at least 3-fold higher
expression in NOD serum exosomes than in BALB/c and 11 miRNAs that were under-expressed
by at least 3-fold in NOD mice (Figure 2.6C). Despite a meaningful fold change these did not
reach statistical significance due to an outlier. Of these, miR-329-5p was found to be over 5-fold
overexpressed in NOD serum exosomes (DESeq2, EdgeR). As NOD mice, even when age
matched, show a variation in disease progression, it is possible that the outlier group may have
progressed further in disease than other groups and vice versa. Thus, we included miR-329-5p in
our downstream analyses as its differential expression may have biologically significance.
Table 2.1 Summary of the 7 most differentially expressed miRNAs detected in serum
UC exosomes from 14-week male BALB/c and NOD mice using three statistical
packages in RStudio
DESeq2 Limma EdgeR
miRNA Log 2 FC p adj Log 2 FC p adj Log 2 FC FDR
miR-127-3p 3.38 1.27 x 10
-7
3.77 6.08 x 10
-6
3.40 2.14 x 10
-4
miR-409-3p 6.22 2.25 x 10
-7
5.41 4.38 x 10
-6
6.16 5.06 x 10
-5
miR-540-3p 3.42 0.0485 3.67 5.0 x 10
-3
3.37 1.39 x 10
-3
miR-410-3p 3.08 0.101 3.49 8.29 x 10
-3
3.02 2.49 x 10
-3

miR-541-5p 3.32 0.406 5.34 2.3 x 10
-4
3.24 8.88 x 10
-3
miR-329-5p 5.13 0.229 - - 6.23 1.2 x 10
-2
miR-30d-3p -4.17 0.580 -2.67 0.196 -4.4 5.79 x 10
-3
Values reaching statistical significance at padj < 0.05 are bolded for DESeq2 and Limma;
Significance for EdgeR is determined by False Discovery Rate (FDR) < 0.10.

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Figure 2.7 Differential miRNA expression analysis. (A) The volcano plot highlights miRNAs that were
identified in exosomes isolated by differential ultracentrifugation as upregulated or downregulated by more
than 3-fold, shown in orange. Significantly upregulated Significantly upregulated miRNAs are shown in
red. (B) Unsupervised hierarchically clustered heatmaps of the most differentially expressed miRNA (with
highly expressed miRNAs in red and minimally expressed miRNAs in blue) in the ten samples. Samples
are labeled either N for NOD or B for BALB/c. Individual samples for the top differentially expressed
miRNA cluster by strain. (C) PCA plot of all miRNAs shows that 22% of the variance was accounted for
by strain.
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Kakan SS, et al. Frontiers in immunology. 2020 Jul 17; 11:1475. 36

Figure 2.8 Boxplots of differentially expressed miRNAs in exosomes isolated from 14-week male
BALB/c and NOD mouse serum. Reads were aligned with Bowtie and an in-house brute force-based
aligner, and differential gene expression analysis was conducted using DESEq2, EdgeR and Limma in
RStudio. (A) Both DESeq2 and Limma identified miR-127-3p, miR-409-3p and miR-540-3p as ‘hits’ with
p adj < 0.05. (B) Additionally, Limma identified miR-410-3p and miR-541-5p to be dysregulated with p adj <
0.05. miR-329-5p failed to reach statistical significance due to one outlier but exhibited the highest fold
change with Log 2FC > 5 in EdgeR and DESEq2. Results were obtained from data sets generated from small
RNA sequencing of 5 sets of RNA from exosomes from each mouse cohort, each isolated from purified
pooled serum exosomes from 5 groups of age-, gender-and strain-matched mice, with 5 mice per group.
2.4.4 Validation of miRNA differential expression
To validate our small RNA sequencing findings of known miRNAs that were differentially
expressed in NOD versus BALB/c mouse serum exosomes, we purified serum exosomes from
independent cohorts of mice, 5 samples per strain with each sample comprised of serum exosomes
from each of five mice. For this round of exosome isolation, we used the SEC method (Figure 2.3
A-D) which yielded exosomes of greater particle homogeneity. qRT-PCR was performed using
Advanced Taqman miRNA Assays. In agreement with the sequencing data, miRNA miR-127-3p,
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miR-409-3p, miR-540-3p, miR-410-3p, miR-541-5p and miR-329-5p were expressed at a higher
level in NOD mouse serum exosomes (Figure 2.9). Five out of the six miRNAs were more than
25-fold over-expressed in the NODs on average. Of these, over-expression of mmu-miR-127-3p
and mmu-miR-541-5p were found to be statistically significant (p < 0.01, Mann-Whitney U-test).
miR-410-3p & miR-329-5p were upregulated in 4/5 groups whereas miR-409-3p was upregulated
in 3/5 groups.

Figure 2.9 Validation of miRNA ‘hits’ in Size Exclusion Chromatography (SEC)-purified serum
exosomes from 14-week male BALB/c and NOD mice. Fold-change data represent mean ± SD
normalized to miR-16-5p using the DDCt method. Statistical significance was determined by the Mann-
Whitney U-test; ** p < 0.01. Results were obtained from data sets generated from qRT-PCR from RNA
isolated from SEC-purified pooled serum exosomes from 5 groups of mice per strain, with 5 mice per group.
All mice were age matched.

2.4.5 Pathway analysis identifies several pathways involved in lymphocyte activation
To understand the signaling pathways that “hit” miRNA may be involved in, we used three
methods (miTALOS, miRPathDB and IPA) which utilize a range of databases of predicted and
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Kakan SS, et al. Frontiers in immunology. 2020 Jul 17; 11:1475. 38
experimentally validated mRNA-miRNA interactions (such as Tarbase, TargetScan, miRanda,
Starbase2) and databases of known pathways (KEGG, Reactome, WikiPathways) in their pathway
analysis algorithm. These databases do not have information on all known miRNA for every
species, so we used multiple tools in our pathway analysis to be as comprehensive as possible.
Functional over-representation analysis using Gene Ontology (Biological Functions) in miTALOS
allows miRNA target prediction using the latest versions of TargetScan (6.2) and miRanda.
Additionally, a database of experimentally validated targets – StarBase2- was also implemented
in the pathway analysis and is available for both human and murine microRNAs. StarBase2
catalogs 3 miRNA hits identified in this study –mmu-miR-127-3p, mmu-miR-409-3p, mmu-miR-
410-3p. As these have identical sequences for human and mice, pathway analysis for both species
(Figure 2.10A,B) was conducted using these three hits. Databases in miRPathDB catalog mmu-
miR-541-5p in addition to the three miRNAs above.
Using miRPathDB, both KEGG (not shown) & WikiPathways identified B cell receptor
signaling (Figure 2.10C) while Gene ontology – Biological functions identified lymphocyte
activation (not shown). Other pathways identified are associated with cellular proliferation,
pluripotency, apoptosis, and p53 signaling, all pathways that may be relevant to cancer. IPA
identified several pathways involved in immune regulation (Figure 2.10D). Pathways common to
all three analyses include B-Cell Receptor (miR-targeted genes in lymphocyte in miTALOS),
TGF-beta and IL-6 Signaling.
2.5 Discussion
SS is a complicated autoimmune disease, with treatment hindered by a poorly understood
pathogenesis and a lack of reliable diagnostics. Here we report that an unbiased screen of exosomal
serum miRNA in a murine model of early-intermediate stage autoimmune dacryoadenitis and SS,
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identified the significant upregulation of multiple miRNAs. qPCR analysis of serum exosomes
from a separate set of disease-model versus healthy control mice validated two significant hits,
miR-127-3p and miR-541-3p, while confirming marked elevation of three additional miRNAs,
miR-409-3p, miR-410-3p and miR-329-5p with some variance across animal groups.
A B

D
C

Figure 2.10 Pathway analysis using miTALOS, miRPathDB and Ingenuity Pathway Analysis
(IPA).Pathway analysis conducted using miTALOS for (A) mouse and (B) human miRNAs 127-3p, 409-
3p and 410-3p. miRNA gene targets from experimentally validated databases. Pathways overrepresented
for differentially expressed miRNA in NOD mice include those involved in cellular differentiation &
proliferation (TGF-βsignaling pathway), immune regulation (IL-6, B Cell Receptor Signaling) and stem-
cell maintenance. (D) IPA figure summarizing the major pathways targeted by the miRNA hits that are
involved in immune regulation (including TGF-beta, IL-6 and B-cell receptor Signaling). Grey arrows
indicate relationship between signal transduction pathways and pink arrows show the interaction of each
specific miRNA with elements of the signal transduction pathways.

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Kakan SS, et al. Frontiers in immunology. 2020 Jul 17; 11:1475. 40
Given that miRNAs are master regulators of gene expression with their dysregulation implicated
in many diseases
98
, identification of this group of dysregulated miRNAs at the initial stages of
autoimmune dacryoadenitis and development of other indicators of established systemic disease
in the male NOD mice model of SS may be useful in establishment of future diagnostic biomarkers.
mmu-miR-127-3p, a significant and validated hit, has been shown to be necessary for the
self-renewal and differentiation of hematopoietic stem cells (HSC) in a mouse model of HSC self-
renewal defects
99
. It has also been proposed to be a regulator of senescence as a tumor suppressor
by directly targeting BCL6
100, 101
, a known protooncogene in human cell lines. As BCL6 is a
transcriptional repressor and inhibits the production of IL10, its downregulation by miR-127-3p
can lead to an increase in IL-10
102
. Increased levels of IL-10 are well-documented in SS patients
103,
104
and are also reported in the NOD mouse lacrimal gland in association with development of
autoimmune dacryoadenitis
21
. Our pathway analysis shows that mmu-miR-127-3p, is involved in
the regulation of TGF-beta and B-Cell receptor signaling (Figure 2.10C) through its targeting of
several MAP kinases and BCL6 (Figure 2.10D). Appropriate regulation of BCL6 is also necessary
for the development of germinal center B cell and follicular helper T cells
105
. Upregulated levels
of hsa-miR-127-3p are reported in testicular and nodal diffused large B-cell lymphomas, with an
inverse correlation to BCL6 levels
106
. Thus, regulated levels of miR-127-3p are necessary for
appropriate control of lymphoproliferation and B cell homeostasis and elevated levels may be
indicative of immune dysfunction/autoimmunity. This finding in the NOD mice is of particular
relevance because a subset of SS patients develop B cell lymphoma
2
. There is great interest in
biomarkers that may distinguish these patients from others with SS so that earlier interventions
may be applied to suppress development of B cell lymphoma. It will be of great interest to study
the potential dysregulation of miR-127-3p longitudinally in SS patients to explore its relationship
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Kakan SS, et al. Frontiers in immunology. 2020 Jul 17; 11:1475.
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to this debilitating and most destructive manifestation of SS.
mmu-miR-541-5p, a second significant and validated hit, may work in concert with mmu-
miR-127-3p. In a mouse model of multiple sclerosis, miR-541-5p and miR-127-3p were
upregulated in lymph nodes indicating that they may be involved in pathogenic neuro-
inflammation
107
. Interestingly, knockout of TNF-α in a mouse model led to downregulation of
both miR-541-5p and miR-127-3p in epidermal skin, hinting at a close involvement of these
miRNAs with pro-inflammatory cytokines
108
.
Another hit, miR-409-3p, is broadly implicated in animal models of autoimmune disease
and patients with chronic fatigue syndrome/myalgic encephalomyelitis
109
, multiple sclerosis
110
and
systemic lupus erythematosus
111
. Our pathway analysis using miRPathDB and IPA found miR-
409-3p is likely involved in the B Cell receptor, STAT3 and IL-6 signaling pathways (Figure
2.10C-D). Studies have found that in mice with experimental autoimmune encephalomyelitis
(EAE, a murine model of multiple sclerosis), mmu-miR-409-3p targets suppressor of cytokine
signaling protein 3 (SOCS3). Upregulation of mmu-miR-409-3p in astrocytes of EAE mice
silences SOCS3, leading to an increase in phosphorylation of STAT3 and increased production of
inflammatory cytokines such as IL-1β, CXCL10, IL-6, MC-P1
112
. Another study in NOD mouse
found that in co-culture of salivary gland acinar cells (SGAC) and B-lymphocyte (an in-vitro
model of salivary gland disease in SS) there was a significant increase in production of cytokines
IL-6 and IL-1 β by B-lymphocytes and increased phosphorylation of STAT3 in SGAC
113
. IL-1β is
upregulated in diseased NOD mouse LG, while its injection into murine LG further impairs tear
production
114
. Secretion of these cytokines by circulating lymphocytes is also increased in SS
patients
115
. Thus, mmu-miR-409-3p may be pro-inflammatory in nature and its upregulation may
increase cytokine production via the SOCS3/STAT3 signaling pathway.
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Kakan SS, et al. Frontiers in immunology. 2020 Jul 17; 11:1475. 42
According to TargetScan, mammals including mice and humans have an 8-mer conserved
site on the Stat3 gene for miR-410
12
. hsa-miR-410-3p appears to directly target STAT3, leading
to a reduction of IL-10 in T cells of patients with systemic lupus erythematosus
116
, and was also
shown to be elevated in the plasma of these patients
117
. Increased expression of miR-410-3p was
also observed in males with relapsing remitting multiple sclerosis, which is characterized by
cycling of autoimmune inflammatory status
118
. Expression of hsa-miR-410-3p was decreased in
the synovial fluid and synoviocytes of rheumatoid arthritis (RA) patients. On the other hand, in an
in-vitro model of RA, overexpression of hsa-miR-410-3p decreased the pro-inflammatory
cytokines TNF-α, IL-6, IL-1β and MMP-9
119
and was anti-proliferative and apoptotic in nature
through targeting of transcription factor YY1
120
. Based on these results, upregulated miR-410-3p
may have an immune-protective effect. If validated, use of this miRNA may have value as a
potential therapeutic.
Table 2.2. Reads aligned to various non-coding RNA
Sample
ID
pre
mirna
rRNA lncRNA snRNA
sno
RNA
sca
RNA
Mature
miRNA
piRNA
N1 318,327 676,237 776,674 24,507 6,066 470 217,302 376,931
N2 1,016,375 1,622,035 1,959,601 61,225 17,458 1,170 690,950 711,308
N3 284,848 191,858 295,180 1,926 8,102 305 207,677 145,113
N4 1,671,998 488,827 765,911 20,435 12,137 1,027 1,301,840 389,208
N5 137,166 246,737 355,721 2,610 4,328 258 89,614 164,174
B1 1,765,543 863,856 1,121,746 8,662 8,567 715 1,322,082 383,467
B2 270,562 580,068 705,545 12,206 7,734 275 182,109 384,545
B3 408,015 1,316,042 1,517,483 55,577 11,547 628 286,554 787,786
B4 562,897 393,866 576,291 5,063 16,827 899 435,244 288,629
B5 422,418 191,561 329,113 1,453 1,386 86 338,684 37,871
pre-mirna – precursor microRNA; rRNA – ribosomal RNA, lnc RNA – long non-coding RNA; snRNA –
small nuclear RNA; snoRNA – small nucleolar RNA, scaRNA – small cajal body specific RNA; mature
miRNA – mature microRNA; piRNA – piwi interacting RNA
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Of interest, five of the identified miRNAs (miR-127-3p, miR-329-5p, miR-409-3p, miR-
410-3p and miR-541-5p) are encoded on the highly evolutionarily conserved Dlk1-Gtl2 locus on
the maternally inherited allele of mouse chromosome 12, which is analogous to the locus Dlk1-
Dio3 on the maternally inherited allele of human chromosome 14
97
. The miRNAs from this locus
seem to regulate ground state pluripotency in embryonic stem cells
121
. Genes from this imprinted
locus play a critical role in embryonic and fetal development and appear to be dysregulated in
several diseases including blood cancers such as lymphoma, acute myeloid and acute
promyelocytic leukemia, as well as autoimmune diseases such as lupus nephritis
122
and multiple
sclerosis
118
. It is also interesting that the sequences of mature miRNA 127-3p, 409-3p and 410-3p
are identical in human and mouse. Sequences of miRNA-541-5p and miRNA-329-5p vary only by
3 nucleotides between human and mouse. This further highlights the applicability of miRNA-based
biomarkers arising from murine model in this study to humans.
Studies of extracellular vesicles rely on particle size analysis which cannot discriminate
between functional vesicles and lipid droplets of similar size, and the presence of these can be a
confounding factor in our studies. Future studies will aim to validate these results utilizing different
methods of exosome isolation. Although our choice of serum over plasma and the use of serum-
separator tubes was aimed at reducing hemolysis, it may also be a confounding factor in our study.
While miRNA stability studies in plasma have shown that levels of miR-127-3p are not altered by
hemolysis
109
, strengthening its potential as a biomarker candidate, similar investigations are
needed for the other miRNAs identified in this study.
While we have identified the potential role of some miRNA in inflammatory pathways and
SS, further study is required to better understand the relationships of these miRNAs as well as the
temporal changes that occur with disease progression. The panel of miRNAs identified in this
Serum Exosomal miRNA in SS Model
Kakan SS, et al. Frontiers in immunology. 2020 Jul 17; 11:1475. 44
study reflect early changes in SS progression, while different patterns of dysregulation may be
observed longitudinally as disease advances and/or as it impacts different organs. Secretions from
both lacrimal and salivary glands are also influenced by the autoimmune inflammation
characteristic of SS and have been used as sources of biomarkers to reflect both systemic and local
inflammation. Evaluating these biofluids as additional sources of potential biomarkers will be of
importance. Future studies will also focus on assessing the utility of this panel of miRNAs in
identifying SS patients as well as exploring their utility in longitudinal disease progression in
combination with existing blood-based biomarkers such as anti-La and anti-Ro antibodies and
others.

Data availability statement: The datasets generated for this study can be found in the Sequence Research
Archive under ID PRJNA622527 and are available for download here
https://www.ncbi.nlm.nih.gov/bioproject/622527
Ethics statement: The animal study was reviewed and approved by University of Southern California,
Institutional Animal Care and Use Committee (IACUC).
Author contributions: SK performed the bioinformatics, statistical analysis of next generation sequencing
data, isolated and characterized mouse serum exosomes from the validation mouse cohort, isolated
exosomal RNA, performed qPCR validation, and prepared the manuscript and supplementary files. SJ and
BC isolated and characterized mice serum exosomes and exosomal RNA from the test cohort. SJ assisted
with blood collection and performed qPCR validation of miRNA in the validation cohort. BC and SK
optimized serum exosome isolation protocols. ME contributed to writing the manuscript and
characterization of serum exosomes. DC contributed to data analysis and revised final manuscript. CO and
SH-A secured research funding and contributed to experimental design and writing the manuscript. SH-A
revised the final manuscript. All authors contributed to the article and approved the submitted version.
Funding: This work was supported by the National Institute of Health under Grant number NIH EY011386.
Research reported in this publication was also supported by the National Eye Institute of the National
Institutes of Health under Award Number P30EY029220 and Unrestricted Grant to the Department of
Ophthalmology from Research to Prevent Blindness, New York, NY.
Conflict of interest: The authors declare that the research was conducted in the absence of any commercial
or financial relationships that could be construed as a potential conflict of interest.
Acknowledgments: The authors thank Anthony Rodriguez for his assistance with TEM grid preparation
and imaging, Alexander Yao for his assistance with light microscopy and Hugo Avila in the preparation of
the supplemental figure draft.

45
Chapter 3 Tear and LG miRNA from the RAB3DKO mouse
model

3.1 Introduction
The Rab family of proteins, are small G proteins belonging to the superfamily of Ras
GTPases. GTP bound activated Rab can bind membrane proteins and interact with multiple
effectors, thus controlling different steps in membrane trafficking. Rab3 proteins are involved in
membrane tethering, the step immediately before vesicles fuse with other vesicles or plasma
membrane. Four isoforms of Rab3 (A-D) are found in mammals with Rab3A, B and C being
expressed predominantly in the nervous system. Rab3D is predominantly expressed outside of the
nervous system - in acinar cells of pancreas, parotid, lacrimal and salivary glands, several immune
cells (mast cells and granulocytes) and adipocytes - all of which have a high amount of exocytotic
activity
123
. Its highest expression is reported in acini of Lacrimal Gland (LG) and Salivary Gland
(SG)
124, 125
.
Studies elucidating function of Rab3 proteins found that while Rab3A was not essential for
survival in yeast or mice, and it’s knockout mice had significant alteration in synaptic vesicle
morphology and function in neurons. In mice, knocking out Rab3D resulted in increased diameter
of secretory granules in acini of pancreas and parotid gland with a doubling of SV volume, but no
change was observed in diameter of granules in mast cells
27
. The basal or stimulated enzyme
secretion by the pancreas or parotid gland was also not changed
27
. Others have reported that Rab3D
was essential for maturation of von-Willebrand's-factor-containing granules prior to their
secretion, and it may be selectively involved in secretion of certain pro-thrombogenic molecules
miRNA in the RAB3DKO mouse LG

46
but not others
28
. Rab3D may be an inhibitor of granule-granule fusion and granule maturation in
osteoclasts
126
. Pavlos et al., have reported that Rab3D knock out (RAB3DKO) mice exhibit
osteopetrosis in their bones, and that it is necessary for bone resorption
126
.
In the male Non-Obese Diabetic (NOD) mouse model of autoimmune Sjogren’s Syndrome
(SS), Rab3D is decreased in the LG at the mRNA
29
and protein level
127
and Rab3D-associated
secretory vesicles (SV) are redistributed throughout the cell as opposed to being concentrated at
the apical end in the healthy LG. They are also irregular and significantly larger in size as compared
to SVs in LG of BALB/c
127
. In LG acini of RAB3DKO, a redistribution of exocytotic vesicles was
observed in the LG, with vesicles at the basolateral end
29
, in a manner similar to the SVs in male
NOD LG. Additionally, in the RAB3DKO there is also an increase of Cathepsin S production,
secretion and proteolytic activity in the LG as well as tears
29
, similar to the male NODs. Finally,
the SVs in Rab3DKO mouse LG, are significantly larger in diameter when compared to SVs in
LG of the healthy C57
128
. Rab3D protein levels were significantly decreased in acinar cells
obtained from labial SG of SS patients
30
. Rab3D coated SVs were redistributed throughout the
acinar cells including the basolateral side
30
.
Thus, the RAB3DKO mouse model mimics some of the secretory dysfunctions observed
in SS. Given that dysregulated secretion is an important factor SS dry eyes, these results make
Rab3D’s function in trafficking extremely relevant to SS pathophysiology. In this chapter we take
a closer look at the microRNAs (miRNA) in RAB3DKO mice tears as well as carbachol stimulated
LG and try to assess the effect of Rab3D knockdown on miRNA (and other non-coding RNA)
expression and secretion into tears. We hope to understand how the secretory defects in SS affect
miRNA trafficking independent of or in addition to autoimmune infiltration in LG acini.
3.2 Methods
Chapter 3

47
3.2.1 Mice
Rab3D knockout (RAB3DKO) breeding pairs created by the Riedel lab at Max Planck
Institute for Biophysical Chemistry (Goettingen, Germany) were generously donated by Dr.
Dietmar Riedel
27
. 12-weeks old male RAB3DKO and sex- and age-matched healthy C57 were
used in this study. All protocols were in accordance with the Guide
129
(2008 Edition) and approved
by the Institutional Animal Care and Use and Committee (IACUC) at USC.
3.2.2 Tear & LG collection
Following topical carbachol stimulation, tears were collected using glass capillaries and
pooled from left and right eye as described previously
130
. For sufficient RNA isolation, each tear
sample for RNAseq comprised of tears from six age matched male mice. A total of 5 such samples
per mouse group were used in this study. One LG from the same mice was also collected and
pooled for RNA isolation and subsequent sRNA-Seq, while the contralateral LG was used for
histology.
3.2.3 RNA Isolation
Following addition of 10uL of RNAse inhibitor beta mercaptoethanol, tear RNA was
isolated using the miRNeasy Serum/Plasma RNA isolation kit (Qiagen), while LG RNA was
isolated using the RNEasy Universal RNA isolation kit. RNA quantity and quality was assessed
using Agilent Tapestation.
3.2.4 sRNAseq and Bioinformatics
sRNA sequencing was outsourced to Qiagen. FASTQ files were trimmed for presence of
adapter and library primer contamination and reads with length < 15 or average quality< 25 were
filtered. Bowtie index was generated using ncRNA fasta file obtained from RNACentral. This
miRNA in the RAB3DKO mouse LG

48
index consisted of 21 non-coding RNA subtypes including – antisense RNA, siRNA, piRNA,
miRNA, precursor-miRNA, tRNA, rRNA, snoRNA, snRNA, scaRNA, scRNA, telomerase RNA,
lncRNA, RNAse P RNA, RNAse MRP RNA, SRP RNA, guide RNA, vault RNA, ribozyme, Y
RNA and miscRNA. Reads were aligned using Bowtie and counts table was obtained using
sam2counts. Mature miRNA read counts were also obtained using the miRGrepp pipeline. Data
analysis and visualizations were done using RStudio.
A B C

Figure 3.1 Quality assessment of RNA isolated from pooled tears of 12weeks old male RAB3DKO
and male C57 using TapeStation. (A) There was no significant difference in the amount of RNA isolated
relative to the total tear volume isolated for each sample. (B) There was no significant difference in the
RNA Integrity Number (RIN) values between samples from the three groups. (C) Counts per million (CPM)
miRNA reads for each sample aligning to miRbase v22.0 did not differ significantly between the three
groups. Data are plotted as boxplots showing mean with 75% to 25% IQR and whiskers show the range.
N=5 samples for male RAB3DKP and C57; n=6 mice per sample. Samples analyzed by t-test with p<0.05
considered significantly different.
3.3 Results
3.3.1 Tears of RAB3DKO mice have differentially expressed miRNA
We detected the expression of over 500 miRNAs in tears of RAB3DKO mice and 525 miRNAs in
tears of C57 mice. There was no significant difference in the RNA quality (Figure 3.1A), RNA
amount per unit tear volume (Figure 3.1B), number of distinct miRNA species, or the total miRNA
reads detected (Figure 3.1C) in the tears of RAB3DKO mice as compared to tears of healthy sex
and age-matched C57 mice. The volcano plots in Figure 3.2A highlight the most differentially
Chapter 3

49
expressed miRNAs in red. Unsupervised hierarchical clustering (Figure 3.2B) of these miRNAs
‘hits’ clusters four out of five samples of RAB3DKO away from the C57 group. However, sample
R3 clustered with the C57 samples.

Table 3.1 Differentially expressed miRNA in RAB3DKO mice tears
miRNA Mean Expression
DESeq2
padj (FC)
EdgeR FDR
(FC)
Limma
padj (FC)
mmu-miR-375-3p*

763.41
6.96 x 10
-18

(9.64)
8.82 x 10
-7

(10.00)
7.33 x 10
-5
(8.71)
mmu-miR-486a-5p
†
50.12
9.14 x 10
-5
(10.77)
7.28 x 10
-3
(10.51)
0.46
(5.09)
mmu-miR-451a
†
6.14
1.44 x 10
-3

(47.17)
0.010
(39.94)
0.098
(10.14)
mmu-miR-6481
†
23.4
0.020
(4.55)
0.090
(4.47)
0.39
(4.00)
mmu-miR-29b-2-5p
†
17.60
0.020
(3.73)
0.114
(3.65)
0.48
(2.76)
* miRNA expression in LG of RAB3DKO is significantly decreased as compared to C57
† No significant difference in expression in LG of RAB3DKO as compared to C57
Additional differentially expressed miRNA in RAB3DKO mice tears
miRNA Mean Expression p value FC Notes
Upregulated
mmu-miR-3473a 2337.19 0.0022 1.84
mmu-miR-3473b 2730.95 0.0032 1.71
mmu-miR-152-3p 596.95 0.0032 1.65
mmu-miR-345-5p 120.37 0.040 1.59
mmu-miR-7a-5p 578.10 0.041 1.42
Downregulated
mmu-miR-340-5p 160.64 0.036 -1.73
mmu-miR-146a-5p* 24329.06 0.062 -1.61
decreased in tears of
13 weeks male NOD
mmu-miR-135b-5p 324.32 0.033 -1.59
mmu-miR-96-5p* 2918.61 0.015 -1.53
decreased in LG of
male RAB3DKO
mmu-miR-26b-5p 13249.28 0.058 -1.37
miRNAs are ordered by fold-change (FC); DESeq2 unadjusted p-values are shown
* miRNA expression in LG of RAB3DKO is significantly decreased as compared to C57 mice
miRNA in the RAB3DKO mouse LG

50
Figure 3.2 sRNAseq identifies differentially expressed miRNA in RAB3DKO tears. (A) Volcano plot
highlights the most differentially expressed miRNA in red. (B) Unsupervised hierarchical clustering
showing the level of expression of differentially expressed miRNA in each sample of the two mouse groups.
(C) Boxplots of individual miRNA upregulated tears of RAB3DKO mice. (D) Top 15 highly expressed
miRNA in tears of male RAB3DKO and C57 mice. None of these are significantly differentially expressed,
except for miR-146a-5p which is slightly decreased in tears of male RAB3DKO. Tears were pooled from
6 mice with 5 such pooled samples per group. (*padj < 0.05; ** padj < 0.01; *** padj < 0.005; **** padj
< 0.0005, DESeq2; ns – not significant).

A B

C

D

Chapter 3

51
Five miRNAs – miR-375-3p, miR-486a-5p, miR-29b-2-5p, miR-451a, miR-6481 – were
significantly increased in tears of male RAB3DKO mice relative to healthy controls (DESeq2,
Table 3.1). Few other miRNAs were dysregulated in tears of RAB3DKO mice but did not survive
the stringent p-value correction. (Table 3.1). However, these miRNAs merit further investigation
as they may have biological significance given their high transcript abundance. This includes miR-
146a-5p (FC=-1.6, p =0.06), one of the top 15 expressed tear miRNA which was also
downregulated in tears of male NOD experiments (Table 3.1). qRT-PCR of tear RNA from the
same mice found miR-375-3p (FC=8, p = 10
-4
, one-way Anova) and miR-29b-2-5p (FC=2, p =
0.04, one-way Anova) to be elevated in tears of RAB3DKO (Figure 3.3). qPCR in tears from
additional mice also found miR-375-3p to be significantly increased in tears of RAB3DKO (data
not shown). The remaining miRNA could not be validated, likely due to low transcript abundance.
Figure 3.3 qPCR validation of differentially expressed miRNA in tears of RAB3DKO mice. miRNA
‘hits’ were validated in the tears of same mice using LNA-conjugated primers. ΔCt values were normalized
to endogenous miR-23a-5p, and expression relative to miRNA expression in tears of is RAB3DKO are
plotted as box and whiskers. (n=5 samples, 6 mice/samples. (* p < 0.05, **** p < 10-4; One-way ANOVA
with Tukey’s HSD for multiple comparison corrections.)
3.3.2 LG of RAB3DKO mice have differentially expressed miRNA
PCA of all miRNAs shows that the principal components Pc1 and PC2 account for 36% of
the variation (Figure 3.4A). For the top 20 hits however, PC1 accounts for 81% of the variance in
the data (Figure 3.4B) and separates samples based on mouse groups. Heatmap showing the

miRNA in the RAB3DKO mouse LG

52
unsupervised hierarchical clustering of these ‘hits’, shows the five RAB3DKO samples clustering
together and away from the C57 samples (Figure 3.4C).
Figure 3.4 sRNAseq identifies differentially expressed miRNA in carbachol stimulated LG of
RAB3DKO mice.(A) PCA of all miRNAs detected in LG of 12-week-old male RAB3DKO and age-, sex-
matched C57 mice (B) PCA of differentially expressed miRNAs (C) Unsupervised hierarchical clustering
showing the level of expression of differentially expressed miRNA in each sample of the two mouse groups.
Red indicates high expression; blue indicates low expression. R1-R5: RAB3DKO samples 1-5; C1-C5: C57
samples 1-5
Several of these miRNAs were also observed to be differentially expressed in the carbachol
stimulated LG of male NOD mice in the same direction (Table 3.2).
A C

B

Chapter 3

53
Table 3.2 Differentially expressed miRNA in carbachol treated LG of RAB3DKO mice
miRNA
Mean
Expression
LG
p adj

(FC)
Tears
p adj (FC)
Upregulated
mmu-miR-146b-5p* 2067.83 1.53 x 10
-20
3.34 -
mmu-miR-142a-5p* 915.52 8.74 x 10
-6
2.07 -
mmu-miR-15b-5p* 7191.30 1.33 x 10
-7
1.69 -
mmu-miR-125a-5p 51242.00 1.28 x 10
-4
1.59 -
mmu-miR-99b-5p 10496.32 8.58 x 10
-7
1.58 -
mmu-miR-145a-5p 19617.93 1.42 x 10
-6
1.56 -
mmu-miR-342-3p* 15007.08 8.90 x 10
-4
1.53 -
mmu-miR-21a-5p 7770.46 2.02 x 10
-4
1.50 -
mmu-miR-223-3p 7303.99 7.11 x 10
-3
1.49 -
mmu-miR-142a-3p* 2006.74 2.79 x 10
-3
1.48
mmu-miR-146a-5p* 10875.02 6.38 x 10
-3
1.47 ns (-1.6)
mmu-miR-30b-5p 1115.04 4.02 x 10
-4
1.47 -
mmu-miR-126a-3p 27297.80 2.83 x 10
-3
1.45 -
mmu-miR-126a-5p 1589.69 1.64E-03 1.45
Downregulated
mmu-miR-375-3p*
†
105604.68 2.35 x 10
-13
-1.96 6.96 x 10
-18
(9.64)
mmu-miR-423-5p 4197.36 8.47 x 10
-5
-1.91 -
mmu-miR-672-5p* 1343.85 4.70 x 10
-9
-1.70 -
mmu-miR-181a-5p 7533.43 1.21 x 10
-6
-1.69 -
mmu-miR-423-3p 1272.92 1.42 x 10
-4
-1.68 -
mmu-miR-484 1313.79 1.38 x 10
-4
-1.67 -
mmu-miR-320-3p 1510.91 4.21 x 10
-3
-1.65 -
mmu-miR-365-3p* 12322.60 1.30 x 10
-4
-1.53 -
mmu-miR-96-5p 1277.07 6.94 x 10
-4
-1.42 ns (-1.53)
mmu-miR-200b-5p 3378.89 1.21 x 10
-6
-1.40 -
mmu-miR-200c-3p* 85292.29 5.16 x 10
-7
-1.39
Differentially expressed miRNA – p adj < 0.005, mean expression > 1000 in RAB3DKO (for
upregulated) or C57 (for downregulated) and abs(log fold change) > 0.5
miRNAs are ordered by their fold changes (FC)
* Have the same directional change in carbachol stimulated LG of male NOD mice (Table 5.1,
Chapter 5)
†
Differentially expressed in tears of RAB3DKO mouse
miRNA in the RAB3DKO mouse LG

54
Among these miR-146b-5p, miR-142a-5p, miR-342-3p and miR-146a-5p are significantly
upregulated while miR-148a-3p, miR-375-3p, miR-200c-3p and miR-365-3p are significantly
downregulated in LG of RAB3DKO. We also looked at the top 20 highest expressing miRNA in
stimulated LG and several of them overlap with the NOD LG dataset. Let-7c-5p was one of top 3
highest expressed miRNAs in mouse LG with average read counts > 10
5
. But unlike male NOD
LG, it is not downregulated in LG of male RAB3DKO (Figure 3.5), indicating that dysregulation
observed in the let-7c gene in the NODs may be immune related. miR-148a and miR-200c showed
a modest downregulation while miR-375 was decreased by 2-fold in stimulated LG of male
RAB3DKO. Whether this change is due to carbachol stimulation needs further investigation in
unstimulated LG by RT-qPCR.
Figure 3.5 Bar plot of highest expressed miRNA in male RAB3DKO LG. Several of the miRNAs with
base mean expression >104 are plotted as bars with error bars representing SEM. Of these, miRNA-375-
3p, which was significantly increased in tears of male RAB3DKO, is decreased in the LG of the same mice,
indicating that the differential expression observed in tears may be due to differential secretion. LG were
pooled from 6 mice with 5 such pooled samples per group (p-value * < 10
-2
; ** < 10
-3
; *** < 10
-4
; **** <
10
-5
; DESeq2)

Chapter 3

55

Figure 3.6 Venn diagram of miRNA expression in tears and carbachol treated LG of C57 and
RAB3DKO mice.
Arrows indicate regions of overlap with number of miRNAs exclusively observed in LG or tears. C LG
– C57 LG; R LG – RAB3DKO LG; C T – C57 Tears; R

We plotted Venn diagrams of distinct miRNAs in tears and LG of male RAB3DKO and
C57 mice. 435 miRNAs were detected in both sample types of both mouse groups. 116 miRNAs
were common to LG of RAB3DKO and C57 but were not detected in tears of either mice. These
may function intracellularly and are likely not secreted. On the other hand, 83 miRNAs observed
in tears of both RAB3DKO and C57 but not in LG of either. are possibly from sources of tears
other than the LG (such as the corneal epithelium, nerves or meibomian gland). 14 miRNAs
produced in LG, seem to be secreted in tears of male RAB3DKO but not in the tears of maleC57.
Another 22 seem to be secreted only in C57 (Figure 3.6).
3.3.3 Tears of male RAB3DKO mice have differentially expressed ncRNA:
We detected expression of 56,000 ncRNA species in tears of RAB3DKO mice and found
41 species to be differentially expressed. nucleolar (sno)RNA, transfer (t)RNA, telomerase
miRNA in the RAB3DKO mouse LG

56
(tel)RNA and miscellaneous (misc)RNA. Barplot in Figure 3.7A shows the diverse variety of
ncRNA species detected in tears of male RAB3DKO and C57 mice. On average, there are 37%
tRNA species, 28% piRNA species, 15% rRNA, 8% lncRNA, 6% of pre-miRNA, 1% miscRNA
(predicted genes), 1% snoRNA, 0.7% snRNA, and 0.3% Y RNA. Abundance for antisense, SRP,
vault, telomerase and scaRNA were <0.1%. The volcano plot (Figure 3.7B) highlights the ’hits’
with the ncRNA subtypes including – piwi-interacting (pi)RNA, long non-coding (lnc)RNA,
precursor-miRNA (pre-miR), small. These ‘hits’ accounts for 85% of the variation in the data with
PC1 axis separating the individual samples by strain (Figure 3.7C, D). After removing transcript
variants there were 14 lncRNA, 2 precursor miRNAs mir-96 and mir-375, 1 snoRNA Snord73b,
telomerase RNA, and 5 tRNA including one mitochondrial tRNA (mtRNA) differentially
expressed in tears of male RAB3DKO mice (Table 3.3).
Chapter 3

57
A

B

C

D

Figure 3.7 Summary of sRNAseq analysis of small non-coding RNA in tears of male RAB3DKO mice.
(A) The volcano plot highlights ncRNAs that were identified in tears of RAB4DKO as significantly
upregulated or downregulated by more than 2-fold, shown in colors representing different ncRNA subtypes.
(B) Distribution of reads aligning to various non-coding RNA subtypes. No significant difference was
observed in the % of reads aligning to a particular ncRNA subtype* (C) PCA plot of all ncRNAs shows
that 36% of the variance was accounted for by PC1. (D) PCA for top 40 differentially expressed ncRNA
shows that PC1 accounts for 77% of the variance likely attributable by strain
*The label ‘miRNA’ includes pre-miRNA and mature miRNA; ‘misc’ includes telRNA, Y RNA, scaRNA,
and scRNA.

miRNA in the RAB3DKO mouse LG

58
Table 3.3 Differentially expressed ncRNA in tears of RAB3DKO mice
ncRNA
Mean
Expression
Fold Change p adj
*
type
long non-coding RNA (lncRNA)
NONMMUT060660.2 34.70 12.42 3.1 x 10
-8
lncRNA
NONMMUT060655.2 (54.2)
†
41.48 10.85 4.2 x 10
-9
lncRNA
NONMMUT060651.2 (52.2, 50.2)
†
126.31 11.16 1.3 x 10
-8
lncRNA
NONMMUT029632.2 26.95 9.23 1.5 x 10
-8
lncRNA
NONMMUT060656.2 48.80 8.85 4.3 x 10
-13
lncRNA
NONMMUT060658.2 (57.2, 59.2)
†
104.68 4.55 1.7 x 10
-5
lncRNA
NONMMUT038757.2 57.71 5.11 3.0 x 10
-3
lncRNA
NONMMUT055773.2 58.59 4.44 2.5 x 10
-3
lncRNA
NONMMUT034512.2 12.70 4.07 4.6 x 10
-3
lncRNA
NONMMUT047323.2
(miscRNA 25687)
†+

39.72 3.83 1.0 x 10
-5
lncRNA
NONMMUT045918.2 18.18 -11.29 2.5 x 10
-3
lncRNA
NONMMUT036805.2 18.97 -4.76 1.8 x 10
-3
lncRNA
NONMMUT047458.2 36.50 -4.58 7.5 x 10
-5
lncRNA
NONMMUT064319.2 16.87 -4.21 3.9 x 10
-3
lncRNA
precursor micro-RNA
Mmu-Mir-375 stem-loop 165.42 5.95 4.7 x 10
-9
pre-miRNA
mmu-mir-96, precursor 690.22 -2.22 1.9 x 10
-3
pre-miRNA
piwi-interacting RNA (piRNA)
piR-mmu-70720 438.57 2.25 4.6 x 10
-3
piRNA
piR-mmu-72192 9553.00 -3.15 2.2 x 10
-8
piRNA
piR-mmu-100591 47927.29 -2.77 2.3 x 10
-3
piRNA
piR-mmu-49530704 99.82 -2.53 2.6 x 10
-3
piRNA
piR-mmu-49495736 31886.35 -2.79 3.4 x 10
-3
piRNA
piR-mmu-85958 33835.41 -2.79 3.9 x 10
-3
piRNA
Small nucleolar RNA (snoRNA)
U73B snoRNA (Snord73b) 534.67 -5.39 4.4 x 10
-3
snoRNA
Telomerase RNA (tel RNA)
telomerase RNA 159.70 -3.62 3.2 x 10
-3
tel RNA
Transfer RNA (tRNA)
anticodon CCC (tRNA-Gly-CCC-
2-1 tRNA-Gly-CCC-2-2)
3834.40 -8.11 4.9 x 10
-14
tRNA
tRNA-Arg 38.59 -8.04 1.4 x 10
-9
tRNA
mitochondrially encoded tRNA
arginine
50.81 -7.82 4.5 x 10
-8
tRNA
transfer RNA-Lys 38882.05 -2.80 2.9 x 10
-3
tRNA
transfer RNA-Arg 24.97 5.26 4.4 x 10
-3
tRNA
*
DESeq2 adjusted p-values; ncRNA are order by p adj;
†
Transcript variants that are similarly
differentially expressed. Data are average of all DE transcripts;
+
Alias: Signal recognition peptide

59
Chapter 4 Tear miRNAs identified in a murine model of
Sjögren’s Syndrome as potential diagnostic biomarkers and
indicators of disease mechanism
^

Kakan SS, Edman MC, Yao A, et al. Tear miRNAs Identified in a Murine Model of Sjögren's Syndrome
as Potential Diagnostic Biomarkers and Indicators of Disease Mechanism. Front Immunol
2022;13:833254.
Keywords: miRNA, NOD mouse, autoimmune disease, tears, Sjögren’s syndrome, Next-generation
sequencing
^ Note: This chapter is taken from the previously mentioned publication.
4.1 Abstract
The tear miRNAome of the male NOD mouse, a model of ocular symptoms of Sjögren’s syndrome
(SS), was analyzed to identify unique miRNAs. Male NOD mice, aged 12-14 weeks, were used to
identify tear miRNAs associated with development of autoimmune dacryoadenitis. Age- and sex-
matched male BALB/c mice served as healthy controls while age-matched female NOD mice that
do not develop the autoimmune dacryoadenitis characteristic of SS were used as additional
controls. Total RNA was isolated from stimulated tears pooled from 5 mice per sample and tear
miRNAs were sequenced and analyzed. Putative miRNA hits were validated in additional mouse
cohorts as well as in tears of SS patients versus patients with another form of dry eye disease,
meibomian gland disease (MGD) using qRT-PCR. The pathways influenced by the validated hits
were identified using Ingenuity Pathway Analysis. In comparison to tears from both healthy (male
BALB/c) and additional control (female NOD) mice, initial analysis identified 7 upregulated and
7 downregulated miRNAs in male NOD mouse tears. Of these, 8 were validated by RT-qPCR in
tears from additional mouse cohorts. miRNAs previously implicated in SS pathology included
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60
mmu-miR-146a/b-5p, which were significantly downregulated, as well as mmu-miR-150-5p and
mmu-miR-181a-5p, which were upregulated in male NOD mouse tears. All other validated hits
including the upregulated miR-181b-5p and mmu-miR-203-3p, as well as the downregulated
mmu-miR-322-5p and mmu-miR-503-5p, represent novel putative indicators of autoimmune
dacryoadenitis in SS. When compared to tears from patients with MGD, miRNAs hsa-miR-203a-
3p, hsa-miR-181a-5p and hsa-miR-181b-5p were also significantly increased in tears of SS
patients. A panel of differentially expressed miRNAs were identified in tears of male NOD mice,
with some preliminary validation in SS patients, including some never previously linked to SS.
These may have potential utility as indicators of ocular symptoms of SS; evaluation of the
pathways influenced by these dysregulated miRNAs may also provide further insights into SS
pathogenesis.
4.2 Introduction
Sjögren's Syndrome (SS) is a chronic, progressive autoimmune disease that affects ~1% of
the population
131
and causes inflammation of moisture-producing glands including lacrimal glands
(LG) and salivary glands (SG), leading to dry eye and dry mouth
132
. SS also causes systemic
disease including inflammation in skin, lung, kidneys, and the nervous system
42
resulting in
dryness of the skin, nose and vagina, debilitating muscle and joint pain, fatigue, and chronic
cough
133
. Among all autoimmune diseases, SS patients have the highest incidence of malignant
lymphoma
2, 41
. Diagnosis of SS is challenging because the current diagnostic criteria involve
multiple subjective and analytical tests including a blood draw and an invasive minor SG biopsy
134,
135
. Additionally, symptoms of SS overlap with those of other autoimmune diseases such as
rheumatoid arthritis (RA) and Systemic Lupus Erythematosus (SLE) and other dry eye diseases
such as Meibomian gland disease (MGD), leading to delays in diagnosis or misdiagnosis
10
. Thus,
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it can take several years before the disease is confirmed, during which time infiltrating immune
cells may further damage exocrine glands and sustain debilitating ocular and oral cavity symptoms.
SS can also lead to other ocular complications such as uveitis and optic neuritis
136, 137
. Although it
is the second most common autoimmune disorder in the United States
3
, SS receives far less
attention for research and therapeutic development than does RA or SLE. With growing
prevalence, there is a need for more specific diagnostic tests for SS to prevent irreversible tissue
and/or organ damage and to improve the health and vision-related quality of life for SS patients.
An ideal diagnostic tear biomarker for SS would be chemically stable and able to: 1) detect
SS with high sensitivity and specificity
138
; 2) distinguish SS from other autoimmune and dry eye
diseases; 3) be collected relatively non-invasively
138
; and 4) be processed inexpensively in a
straightforward manner
138, 139
. With these characteristics in mind, we investigated a type of short
non-coding RNAs called microRNA (miRNAs) that are 18-26 nucleotides long. miRNAs circulate
in the body either packaged inside secreted vesicles or bound to RNA-binding proteins and are
therefore highly stable and protected from RNAse degradation. miRNAs are responsible for
transcriptional regulation of nearly 60% of all mammalian messenger RNA (mRNAs)
63
, and
dysregulation of miRNA has been implicated in diseases such as cancer and neurodegenerative
disease
16, 32
. Moreover, miRNAs and their mRNA targets have co-evolved and are highly
evolutionarily conserved in mammals
12
, allowing for studies in model organisms to be directly
extrapolated to humans. This feature is critical for SS research, as mammalian model organisms
allow investigation of the earliest stages of glandular inflammation, which is difficult to do in
patients due to delays in SS diagnosis
While SS causes systemic symptoms, its hallmark manifestations are inflammation of LG
and SG. Although other biofluids and their components, i.e., plasma/serum, peripheral blood
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mononuclear cells (PBMC) and saliva, have been extensively investigated as sources of protein
and RNA based biomarkers, there are limited reports of the assessment of tears for the presence of
select miRNAs in SS
140
and none using comprehensive Next Generation Sequencing (NGS)
analysis. Tears are highly enriched in miRNA compared to other biofluids such as serum and
cerebrospinal fluid
13
. Moreover, tear miRNA candidates have been investigated for detection of
primary open-angle glaucoma
17
and Alzheimer’s disease
16
, with very high sensitivity and
specificity. Tear collection is quick, atraumatic, and non-invasive. Most importantly, changes in
tear composition are likely to be directly related to the health of the LG, the principal source of
most of the aqueous tear components and a primary target of autoimmune exocrinopathy
141
. Thus,
we propose that dysregulated tear microRNA may serve as indicators of LG disease in Sjögren's
syndrome and might also provide insights into disease pathogenesis.
This discovery study utilized male NOD mice, a well-established model of the ocular
symptoms of SS. These mice exhibit lymphocytic infiltration of the LG, beginning around six
weeks of age and by 12-14 weeks of age, they exhibit a notable lymphocytic infiltration of LG
associated with symptoms of dry eye disease
21, 44
. There are no ideal murine models of SS that
accurately recapitulate all of the elements of human disease, but the male NOD mouse has proven
an excellent choice for study of ocular symptoms. Importantly, by 12-14 weeks of age as used in
this study, male NOD mice displays multiple key characteristics of SS-like disease similar to
humans including a) lymphocytic infiltration in LG resulting in autoimmune dacryoadenitis
142
b)
loss of secretory function in LG
142, 143
c) development of anti-SSA/SSB and anti-muscarinic
receptor type III autoantibodies
56, 143, 144
; d) an increased degradation of ECM proteins and
deformation of ECM structures in LG
145
; and e) increased proteolytic enzymes in tears
21
.
Importantly, we first discovered elevated tear cathepsin S as a putative biomarker of SS-associated
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dry eye disease in the male NOD mice
21
, a finding that was later validated in tears of female SS
patients when compared to tears of healthy controls, and other dry eye and autoimmune disease
patients
46
. As well, male NOD mice manifest disease within a rapid time frame, unlike other
transgenic or knockout models which require extended aging
146, 147
.
Age- and sex-matched male BALB/C mice, which also lack LG disease and are frequently
used as a control for male NOD and their derivatives in studying disease development
21, 114
, served
as the primary healthy control. Additionally, female NOD mice do not manifest marked ocular
symptoms of SS, instead exhibiting SG inflammation at a later age starting at 16 weeks. They are
typically used to study autoimmune sialadenitis. At 12-14 weeks, female NODs do not exhibit
lymphocytic infiltration in their LG, and have intact ocular surfaces and tear production
comparable to healthy female BALB/c mice. The minimal local LG disease that they may express
occurs beyond 5 months of age
26, 148
. Female NOD mice share the genetic background of the male
NOD mice and so, age-matched female NOD mice were used as additional controls.
In this study, stimulated tears were collected from each mouse cohort and pooled for
isolation of total RNA, prior to conducting a comprehensive small RNA sequencing analysis
(Figure 4.1). Over 500 distinct miRNAs were identified in male NOD mouse tears of which 14
were differentially expressed compared to tears from both control groups. These findings were
validated in additional cohorts of mice using qRT-PCR, confirming differential expression of 8
miRNAs. In tears of 12-14 weeks old male NOD mice, miR-146a-5p, miR-146b-5p, miR-322-3p,
and miR-503-5p were down-regulated; whereas miR-181a-5p, miR-181b-5p, miR-150-5p, and
miR-203-3p were up-regulated. In a pilot study, we have also conducted a preliminary analysis of
the presence and abundance of these RNAs using qRT-PCR in tears of patients with SS-associated
dry eye disease versus patients with another form of dry eye due to meibomian gland disease
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(MGD). MGD is associated with changes in tear lipid secretion resulting in more rapid evaporation
and destabilization of the tear film
149
. MGD is the most common cause of non-autoimmune
evaporative dry eye
150
. In contrast, dry eye in SS is primarily aqueous-deficient, resulting from
autoimmune damage to the LG; however a component of evaporative dry eye may develop with
time due to consequent inflammation of meibomian glands
151
. Using MGD patients as a non-
autoimmune dry eye control group, we assessed whether miRNA hits identified from our NOD
studies could distinguish early SS disease resulting from autoimmune LG dysfunction. Three of
the 8 miRNAs identified from male NOD mice versus controls were significantly upregulated in
SS tears relative to MGD tears – hsa-miR-203a-3p, hsa-miR-181a-5p and hsa-miR-181b-5p. To
our knowledge, this is the first comprehensive tear miRNA NGS analysis in an animal model of
SS, the results of which may have important implications for improved understanding of
mechanisms involved in disease as well as impact diagnosis of ocular involvement in SS patients.
4.3 Materials & Methods
4.3.1 Animals
Male NOD/ShiLtJ (001976) mice aged 12-14 weeks were used as an early-intermediate
disease model of ocular manifestations of SS
19, 21
. Longitudinal studies confirm that in the age
range of 12-14 weeks in male NOD mice, there is no significant difference in tear production or
lymphocytic infiltration in the LG
26, 152, 153
. While age-matched male BALB/cJ (000665) mice
served as a healthy control, female NOD/ShiLtJ mice that do not develop lymphocytic infiltration
in the LG or other ocular manifestations of Sjögren's syndrome by 14 weeks were employed as an
additional, strain-specific control
26
. Mice older than 14 weeks were excluded to avoid potential
confounding effects of diabetes. All strains were purchased from Jackson Laboratories (Bar
Harbor, Maine). All animal procedures and experiments followed protocols approved by the
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Institutional Animal Care and Use Committee (IACUC) at the University of Southern California
(Protocol #10547) as well as the Guide for Care and Use of Laboratory animals, Eighth Edition
129
.
All sections of this report adhere to the ARRIVE Guidelines for reporting animal research and a
completed ARRIVE guidelines checklist is included in Checklist S1.
4.3.2 Human Subjects
Deidentified tear samples were obtained from the USC Dry Eye Center of Excellence tear
biorepository at the USC Roski Eye Institute. Use of samples from the tear biorepository is
approved under IRB protocol HS-19-01004 and meets the requirements for ‘non-human research
with biospecimens previously generated/collected to be analyzed for research purposes (Data and
Specimens) or Secondary Data Analysis ’. Samples obtained belonged to 6 SS and 6 age-matched
meibomian gland disease (MGD) patients undergoing treatment at the LAC+USC Medical Center
or Keck Medicine of USC Rheumatology clinics. The diagnosis of SS was based on the 2016
American College of Rheumatology/European League Against Rheumatism (ACR-EULAR)
consensus classification criteria for SS
154
or alternatively, by referral to the attending
ophthalmologist as SS patients by rheumatologists. Three of six SS patients were determined
positive in ophthalmology based on the 2016 ACR-EULAR criteria. The remaining 3 patients were
referred to the attending ophthalmologist as SS patients who met clinical criteria in ophthalmology
for keratoconjunctivitis sicca (ocular staining score ≥ 5 and/or Schirmer’s test ≤ 5 mm in 5 min in
at least 1 eye). MGD-dominant dry eye patients served as controls since lipid secretion required to
control evaporation and maintain a normal tear film is abnormal in these patients, leading to
evaporative dry eye. This contrasts to SS-related dry eye where aqueous deficient dry eye results
from the lack of aqueous tear secretion by the LG due to inflammatory changes, although,
evaporative and aqueous deficient dry eye are not mutually exclusive. The diagnosis of MGD was
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made clinically by the ophthalmologist based on presence of obstruction of meibomian glands due
to increased viscosity of meibum or hyper-keratinization of the glands and leading to decreased
secretion of meibum
149
. This decrease can affect tear film stability (measured by tear break-up
time, lipid layer thickness, and/or tear osmolarity)
149
. Written informed consent was obtained from
each patient and their samples were deidentified prior to depositing in the biorepository.
4.3.3 Tissue and Tear Collection
Tears were analyzed from two separate groups of mice, a discovery cohort used for library
preparation and NGS sequencing, and a validation cohort, used for RNA isolation and qRT-PCR
analysis to validate putative hits obtained by NGS. Stimulated tears were collected from mice as
described previously
21
. Briefly, mice were anesthetized with 20 mg/kg of Ketamine and 2 mg/kg
of Xylazine and placed on heating pads. An incision was made in the skin above the LG, and the
exposed gland was stimulated with 3 μL of 50 μM carbachol (Alfa Aesar, Haverhill, MA);
carbachol is a muscarinic and nicotinic agonist that efficiently evokes stimulated secretion of tear
proteins by the lacrimal gland through activation of M3 muscarinic receptors
155
. A minimum of
two mice producing a total of at least 6 μL of tears was required to isolate sufficient RNA
detectable by nanodrop or TapeStation (Agilent BioSciences). Tears were collected using 2 μL
sized Microcaps glass capillaries (Drummond Scientific, Broomall, PA) for 5 min after topical
stimulation. This process was repeated twice for a total of 15 min of stimulated collection, after
which the mice, still under anesthesia were euthanized by cervical dislocation. One LG (either left
or right) was selected at random for RNA isolation and the remaining LG was processed for
histology using Hematoxylin and Eosin (H & E) staining. Tears were pooled from 5 mice for a
single sample intended for Next Generation Sequencing (NGS) (to allow collection of sufficient
RNA for NGS library preparation), with 5 samples each for male NOD and BALB/c mice and 3
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samples for female NOD mice. As female mice represented an additional control beyond the age-
and sex-matched male BALB/c, we used a smaller number of total samples of pooled tears for this
group in the discovery cohort only; the numbers used for validation were equivalent for all strains.
For RT-qPCR validation experiments, tears were similarly collected; however, tears
comprising one sample were pooled from 3 mice from each mouse group. Four pooled samples
per group were analyzed. Cost constraints were the primary reason for the choice of the sample
size for discovery and validation cohorts. The number of mice used per sample to pool tear RNA
was determined by the need to exceed the minimum amount of RNA required for NGS library
preparation or RT-qPCR. We used 5 mice per group to target a goal of 50 ng per sample for NGS
library preparation. For the validation cohorts, all samples included pooled tears from three mice,
as qRT-PCR required less than 15 ng of total RNA.
Human tear samples were collected from filter paper used for Schirmer’s test. For the test,
filter paper strips were placed in the inferior fornix of each eye after topical application of 0.5%
proparacaine hydrochloride ophthalmic solution. The strips were removed after five min and
Schirmer’s Score (i.e., length of tear saturation in mm) was recorded
46
. Strips from each of left
and right eyes were placed in separate deidentified tubes and stored at -80
o
C.
4.3.4 LG Histology & Quantification of Lymphocytic Infiltration
LGs were placed in cassettes which were then fixed in 10% neutral buffered formalin
solution for at least 24 h and transferred to 70% ethanol. Tissues were embedded in paraffin, and
longitudinal cross-sections of 5-6 µm thickness were cut at various depths into the LG. Each tissue
section was stained with H&E dye and images were acquired with an AxioScope 5 with Axiocam
305 microscope (Carl Zeiss AG, Jena, Germany). Infiltrates were quantified using Image J
156
to
calculate the total area of the LG and the area occupied by infiltrating lymphocytes. The percentage
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infiltration was calculated by dividing the area occupied by foci divided by the total area of the
cross-section multiplied by 100. The percentage of infiltration at three depths within the LG in
each mouse was averaged to reflect the total amount of lymphocytic infiltration/gland.
4.3.5 RNA Isolation and Quality Control
5 µL of β-mercaptoethanol (BME) was added to each pooled mouse tear sample to prevent
degradation by RNAase. Addition of BME to tears improved RNA quality as indicated by
improvement of Agilent Tapestation traces and RNA integrity Number (RIN) (data not shown).
Total RNA was isolated using the miRNEasy total RNA isolation kit (Qiagen) following the
manufacturer’s guide, with a slight change in the final step. RNA was eluted from the dried column
by adding 14 µL of RNAse free water and eluting twice for a total elution volume of ~28 µL. RNA
was stored at -80°C prior to library preparation. RNA quality and concentration was assessed in
house using TapeStation with a High Sensitivity RNA ScreenTape (5067-5579, Agilent) to ensure
the RNA was of high integrity and of sufficient quantity for NGS library preparation. Samples
with RIN scores < 2 or RNA amount < 10 ng were excluded from sequencing.
Human tear samples were stored on Schirmer’s strips at -80
o
C. Tears were eluted from
Schirmer’s strips in 0.9 mL of Qiazol reagent (Qiagen), combined in a single tube and total RNA
was isolated using the miRNeasy Serum/plasma total RNA isolation kit (Qiagen). RNA
concentration, yield and quality were assessed using TapeStation. Samples with RNA Integrity
Numbers (RIN) 3 or higher were used for downstream cDNA synthesis and qPCR analysis.
4.3.6 Library Preparation, NGS and Bioinformatics analysis
Library preparation and NGS was outsourced to Qiagen where the RNA quality was again
assessed using Nanodrop and TapeStation prior to library preparation. The order of samples for
library preparation and NGS was not known to the authors. The small RNA library was prepared
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using the QIAseq miRNA library kit (331502, Qiagen), specifically optimized for very low input
small RNA, following the manufacturer’s guidelines.
Figure 4.1 Schematic overview of experiments and data analysis. Tears were collected by stimulating
both LG from each mouse with 50 μM Carbachol. Tears were pooled from n=5 mice for each sample, with
N=5 samples for male NOD and BALB/c mice and N=3 for female NOD mice In total, 13 samples were
sent for RNA sequencing, and raw data was analyzed as follows: (a1) Quality assessment by FASTqc
showed presence of 3’ adapters in the reads; (b) Using cutadapt
157
, 3’ adapters were trimmed and reads with
quality scores <20 or length <15 were removed; (c) Trimmed reads were aligned to mouse genome
GRCm38 using Bowtie
74
; and (d) Aligned reads were annotated using featureCounts
75
. Additionally, (a2)
raw FASTQ files were also run through our internal miRGrepp pipeline
96
and (e) miRNA counts were
normalized, and plotted to assess the quality of the data with statistics on these read counts performed using
R package, DESEq2
77
; (f) Shortlisted hits were validated by qPCR in a separate cohort of mice; and and
(g) Pathway analysis of the hits was done in Ingenuity Pathway Analysis (Qiagen). Graphic created with
Biorender.

Small RNA sequencing was conducted on an Illumina Nextseq 500/550 high output flow cell with
Sample collection from mouse groups

Bioinformatics Analysis

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75 cycles in single end configuration with an average sequencing depth of 17 to 18 million
reads/sample (expected to be sufficient to provide >1 million mapped miRNA reads per sample to
allow sufficient power to detect differentially expressed miRNA in accordance with exRNA
consortium guidelines). Read quality of the FASTQ files from all samples were assessed using
FASTQC; adapter and quality trimming was done with Cutadapt v2.0.Trimmed reads were aligned
to mouse whole genome GENCODE GRCm38 using Bowtie and quantified using featureCounts.
Raw reads were also aligned to miRbase v22.0 as described previously
96
using our in-house aligner
miRGrep
96
. miRNA read counts filtering, data normalization, and differential gene expression
analysis was done using DESEq2 in RStudio with no data points excluded in the analysis. (A full
list of software packages, R Code and program parameters can be found in Figure 4.1).
4.3.7 RT-qPCR Validation
Validation of miRNA hits utilized RT-qPCR analysis of tear miRNA isolated from separate
cohorts of mice and dry eye patients using Qiagen’s Custom PCR Panels. 13 miRNAs were tested.
Due to cost and other constraints in designing the custom PCR panel to validate hits, miR-322-3p
was not included. We reasoned that if the 5p counterpart evaluated in the panel was confirmed as
differentially expressed, it would be reasonable to expect that the 3p counterpart might also be
differentially expressed since they are the products of the same precursor miRNA, miR-322. cDNA
was prepared from 10 ng of total RNA using miRCury LNA-enhanced cDNA synthesis kit
(Qiagen) followed by PCR with 100 ng of cDNA using custom made PCR panels (Qiagen) which
were pre-coated with test and house-keeping miRNA primers. Real time PCR was done in
triplicates for 40 cycles on a QuantStudio 6000 flex instrument (Applied Biosystems, Foster City,
CA, USA). Raw Ct values were first normalized using the inter-plate calibrator UniSp3, followed
by normalization to internal controls, miR-25-3p and miR-16-5p. Statistics were performed on ΔCt
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values in GraphPad prism v7.0. Results were reported with respect to controls using the ΔΔCt
method.
4.3.8 Ingenuity Pathway analysis of miRNA hits
miRNA hits validated by qPCR were uploaded to Ingenuity Pathway Analysis (IPA) with
fold-change and p-values calculated from DESeq2. Using the ‘microRNA target filter’ module of
IPA, a list of mRNA targets sourced from TargetScan was obtained. IPA recognized seven
microRNA hits and reported a list of 3991 mRNA targets. This list was shortlisted by a) confidence
(experimentally validated, predicted high) to 1100 mRNA targets, and b)species (restricted to
mammals only– human, mouse, and rat), from which, a network map was generated. Using the
build and connect features of the main ‘pathways’ module, mRNA targets involved in
immunological and inflammatory diseases, inflammatory responses, and cancer were shortlisted.
Pathways, disease categories and functions over-represented by the miRNA and their mRNA
targets were obtained using the overlay feature of the ‘pathways’ module in decreasing order of
probability. From here, pathways most significantly over-represented were evaluated to gain
further insights into the potential role of the dysregulated miRNA hits in SS.
4.4 Results
4.4.1 Histological Analysis of LG lymphocytic infiltration
To determine the percentage of lymphocytic infiltration in mouse LG, H&E-stained images
of LG sections from the mice used for the initial tear collection were acquired and analyzed.
Neither the LG of female NOD mice (Figure 4.2A) or healthy male BALB/C mice (Figure 4.2B)
at 12-14 weeks of age showed any lymphocytic infiltration, as expected
26
. The male NOD LG had
notable lymphocytic infiltration from 12-14 weeks of age (Figure 4.2C), confirming establishment
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of LG disease associated with SS. The percentage infiltration of LG from the male NOD mice was
thus significantly higher than both the male BALB/c and female NOD mice in both discovery
(Figure 4.2D) and validation (Figure 4.2E) cohorts.
Figure 4.2 Representative H & E-stained images of LG from 12 -14-week-old female NOD, male
BALB/c or male NOD mice.No lymphocytic infiltration is observed in LG from (A) female NOD mice or
B) male BALB/c mice. Marked lymphocytic infiltration is observed in LG from (C) male NOD mice.
Scalebar, 25 μm. The percentage of total area of infiltrating lymphocytes in LG calculated in both the (D)
discovery cohort and (E) validation cohort of age-matched female NOD mice (blue), male BALB/c mice
(yellow) and male NOD mice (grey). Points represent the percentage lymphocytic infiltration for one LG
per mice. Data are plotted as a boxplot with whiskers showing range. (***p<10
-3
, ****p<10
-4
, One-Way
ANOVA). The correlation between percentage lymphocytic infiltration and tear production for male NOD
mice was calculated in both (F) discovery and (G) validation cohorts. Pearson’s correlation coefficient (r)
is shown. Points in D-G represent individual mouse LG (D, E) or mouse tears (F, G) with N=25 for male
NOD and BALB/c and N=15 for female NOD for discovery cohorts and N=12 for all mouse groups in the
validation cohort.

A B C

D E F G

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Tear production in male NOD mice was significantly lower than male BALB/c mice in both the
discovery (p < 10
-4
) and validation (p < 10
-4
) cohorts (Figure 4.3A). Tear production in male NOD
was not significantly different from female NOD mice in the discovery cohort but was significantly
lower in the validation (p < 10
-3
) cohort. This is likely due to the 1.25-fold lesser body weight and
1.75-fold smaller size of female mouse LG relative to their male counterparts
148
, as tear volumes
for female NOD and female BALB/c mice were comparable (Figure 4.3B) Tear production in
male NOD mice was weakly inversely correlated to the extent of lymphocytic infiltration in the
LG in mice from both the discovery cohort (Figure 4.2F) (r = -0.2567, Pearson’s correlation
coefficient) and the validation cohort (Figure 4.2G) (r = -0.2331, Pearson’s correlation
coefficient). It has been previously published that lymphocytic infiltration is only one of several
determinants of reduced tear flow
158, 159
.
4.4.2 Male NOD mice have differential tear production, but not total protein or RNA yields
As the LG is the predominant source of aqueous tear components, changes in miRNA
composition of tears may be indicative of LG disease. We have established previously that male
NOD mice have decreased tear production, similarly to SS patients
21, 46
. However, their tear protein
concentration when normalized to tear volume is not affected
21
. Similarly, we did not observe a
significant difference in the RNA tear concentration normalized to tear volume in the male NOD
mice as compared to male BALB/c and female NOD mice (Figure 4.3C). There were also no
significant differences in the RNA concentration or quality, as indicated by the RNA integrity
number (RIN) of samples in each group (Figure 4.3D). Assessing the total number of reads aligned
to miRbase v22, the counts per million miRNA or CPM miRNA normalized to RNA amount per
unit tear volume, showed no significant difference across the three groups (Figure 4.3E).
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Figure 4.3 Tear volumes and quality assessment of RNA isolated from pooled tears of 12-14 weeks
old female NOD, male BALB/c and male NOD mice using TapeStation. (A) Tear production in male
NOD mice was significantly lower as compared to male BALB/c mice in both discovery and validation
cohorts whereas it was significantly lower than the female mice in the validation cohort only. (* p < 0.05,
** p < 0.01, *** p < 10
-3
, **** p < 10
-4
, ns – not; significant, 2-way ANOVA, with Tukey’s test for
correction for multiple comparisons, at p < 0.05). (B) Comparison of tear volumes of 14-week old female
NOD and female BALB/c mice showing no significant change (mice were not part of discovery or
validation cohorts). (C) There was no significant difference in the amount of RNA isolated relative to the
total tear volume isolated for each sample. (D) There was no significant difference in the RNA Integrity
Number (RIN) values between samples from the three groups. (E) Counts per million (CPM) miRNA reads
for each sample aligning to miRbase v22.0 did not differ significantly between the three groups. Data are
plotted as boxplots showing mean with 75% to 25% IQR and whiskers show the range. N=5 samples for
male NOD and BALB/c, 3 samples for female NOD; n=5 mice per sample. Samples analyzed by Kruskal-
Wallis ANOVA with p<0.05 considered significantly different.
4.4.3 Male NOD mice tears from the discovery cohort exhibit differentially expressed
miRNA
We detected 563 distinct miRNAs in male NOD mouse tears, 511 miRNAs in the BALB/c
mouse tears, and 622 miRNAs in the female NOD mouse tears (Figure 4.4A). About 455 tear
miRNAs were common to all three strains while 28 and 21 miRNAs were unique to male NOD
A B

C D E

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and male BALB/c mouse strains, respectively. Female NOD mouse tears had the greatest number
of distinct miRNAs at 84, which is likely a sex effect. Female NODs also had more tear miRNA
in common with male NOD (64) than with male BALB/c (19), which may be attributed to a strain
effect. Both sex and strain were used as co-variates in the downstream statistical analysis. A
miRNA was considered as a ‘hit’ if it had 1) a normalized base mean expression of at least 10
reads, 2) was up or downregulated in male NOD tears in the same direction when compared to
both control samples from male BALB/c and female NOD tears, and 3) resulted in a significant
(p<0.05), unadjusted p-value in at least one of the two comparisons. The unadjusted p-values
(Table 4.1) were used for initial selection of differentially regulated miRNAs, which were further
validated by qPCR (Table 4.2). With these criteria, using DESEq2, 14 miRNAs were found to be
differentially expressed (Table 4.1). Seven miRNAs (miR-181a-5p, miR-181b-5p miR-203-3p,
miR-150-5p, miR-3076-3p, miR-3963, miR-3572-3p) were upregulated (Figure 4.5A), while
another 7 miRNAs (miR-146a/b-5p, miR-147-3p, miR-322-3p, miR-322-5p, miR-421-3p, miR-
503-5p) were downregulated in tears of male NOD mice (Figure 4.5B).
Unsupervised hierarchical clustering analysis (shown as heatmaps) of differentially
expressed miRNA clustered female NOD with BALB/c separately from male NODs (Figure
4.4B). Sample level variation is illustrated in the heatmaps. Principal component analysis (PCA)
of the data shows considerable overlap between male NOD and BALB/c when comparing all
miRNAs, while the female NOD samples cluster away from the males.PC1 accounts for 41% of
the variation in the data, likely attributable to sex (Figure 4.4C). When comparing the top miRNA
hits, however (Figure 4.4D), there do not appear to be any outliers and samples within a group
correlate well. PC1 accounts for 58% of the variation and appears to show a strain effect with
controls clustering close to each other and away from male NODs. PC2 accounts for 23% of the
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variation and shows a sex effect. Volcano plots comparing tear miRNA expression show greater
variability between male and female NOD mice (Figure 4.4F) and less in male NOD and BALB/c
mice tears (Figure 4.4E).

Table 4.1 Differentially expressed miRNA in male NOD mice tears as compared to those in
tears of male BALB/c and female NOD mice
miRNA
Mean
Expression
Log2 Fold Change pvalue
NOD M
vs. NOD F
NOD M vs.
BALB/c M
NOD M vs.
NOD F
NOD M vs.
BALB/c M
mmu-miR-203-3p 23892.76 0.656 0.477 0.1937 0.0389
mmu-miR-181b-5p 92.48 0.779 0.432 0.1569 2.411 x 10
-3

mmu-miR-181a-5p 1042.03 0.547 0.258 0.2634 4.470 x 10
-3

mmu-miR-3076-3p 10.00 1.269 4.143 3.810 x 10
-4
0.0919
mmu-miR-150-5p 425.41 0.639 0.510 0.1713 0.0473
mmu-miR-3572-3p 14.00 7.245 1.583 9.558 x 10
-3
1.270 x 10
-12

mmu-miR-3963 43.81 0.595 0.999 0.0182 0.0872
mmu-miR-146a-5p 40196.68 -1.045 -0.826 3.631 x 10
-4
1.141 x 10
-3

mmu-miR-146b-5p 461.41 -1.560 -0.578 2.406 x 10
-7
0.0277
mmu-miR-147-3p 27.53 -1.583 -1.258 7.051 x 10
-3
0.0134
mmu-miR-322-3p 72.25 -0.544 -1.136 0.0423 3.526 x 10
-7

mmu-miR-322-5p 1907.54 -1.376 -0.707 4.558 x 10
-4
0.0409
mmu-miR-421-3p 50.43 -1.028 -1.125 1.450 x 10
-3
4.195 x 10
-5

mmu-miR-503-5p 520.23 -1.485 -0.812 1.604 x 10
-4
0.0185
p-values and log2FoldChanges were calculated using DESeq2. Significant unadjusted p-values are in
bold.
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Figure 4.4 Differential miRNA expression analysis of NOD mouse tears. (A) Venn diagram showing
the overlap of miRNA in the three strains. (A) miRNA that had normalized read counts > 0 in at least 4 out
of 5 samples of NOD and BALB/c and 2 out of 3 samples for the female NOD were included for
calculations. (B) Heatmap of 14 miRNA that are differentially expressed in male NOD mouse tears as
compared to tears of male BALB/c and female NOD. Principal component analysis (PCA) plot of the (C)
complete miRNA data and (D) top miRNA hits, characterizes the trends exhibited by the expression profiles
of the 3 strains. Each dot represents a sample, and each color represents the type of the sample. Volcano
plot of differentially expressed miRNA in NOD mouse tears as compared to (E) that of male BALB/c and
(F) female NOD.
A

C

B

F
D
E

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A Upregulated miRNA

B Downregulated miRNA

Figure 4.5 Multiple miRNAs are differentially expressed in tears of diseased male NOD mice.
(A) 7 miRNAs were identified as upregulated in tears of 12-14 week male NOD mice while (B) 7 more
miRNAs were found to be downregulated in tears of 12-14 week male NOD mice as compared to both
age-matched female NOD and male BALB/c mice. Log10 Normalized miRNA counts as calculated by
DESeq2 are plotted for each strain. N=5 samples for male NOD and BALB/c, and N=3 samples for
female NOD mice; n=5 mice per sample for each strain. miRNA were considered differentially expressed
if the fold change trended in the same direction for NOD M vs BALB/c and NOD M vs NOD F; had a
mean expression value of 10 reads or higher and had a significant unadjusted p value in at least one of
the two comparisons. (* p < 0.05; ** p < 0.01, *** p < 0.001, **** p < 0.0001, DESeq2).
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4.4.4 qPCR confirms differential expression of multiple identified miRNAs in tears from
an additional, validation, mouse cohort
To validate the observed differential expression of these miRNAs in mouse tears, we
collected pooled stimulated tears from additional mouse cohorts for analysis of tear miRNA hits.
As with the original discovery cohort, the male NOD mice in this validation cohort had notable
autoimmune dacryoadenitis, while the female NOD and male BALB/c mice did not (Figure 4.2E).
From the NGS data analysis, we observed that five miRNAs (miR-25-3p, miR-93-5p, miR-16-5p,
miR-26a-3p and miR-23a-3p) were unchanged between the three strains (Figure 4.6A, B). These
miRNAs have been previously identified as endogenous controls in previous miRNA research
160
.
Additionally, qPCR validation on the same RNA samples showed that miR-93-3p and miR-
25-5p were unchanged between the three strains (Figure 4.6C, D). Therefore, for our validation
study, we used these two miRNAs as endogenous controls, in addition to the spike-in controls
UniSp6, and normalized the qPCR data to them in parallel. ‘Hits’ were considered validated if they
were significantly different with a fold change in the same direction in male NOD samples
compared to both female NOD and male BALB/c samples and when normalized to at least one of
the two endogenous miRNA controls. These assays showed that miRNAs miR-146a-5p, miR-
146b-5p, miR-322-5p and miR-503-3p were significantly downregulated, while miR-181a-5p,
miR-181b-5p, miR-203-3p and miR-150-5p were significantly upregulated in male NOD mice
tears as compared to tears of male BALB/c and female NOD (Figure 4.7). However, miR-146b-
5p and miR-322-5p were significantly downregulated in both comparisons when normalized to
only miR-93-3p, while miR-203-3p was upregulated in both comparisons when normalized to only
miR-25-3p (Table 4.2).
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Figure 4.6 Comparison of expression of endogenous control miRNAs mmu-miR-25-3p and mmu-
miR-93-5p in RNA isolated from tears of male NOD, female NOD, male BALB/c mice and human
tears.
miRNA sequencing data analysis of mouse tears showed that there were no significant differences in the
expression levels of (A) miR-25-3p and (B) miR-93-5p. Data for (A) and (B) are plotted as counts
normalized by DESeq2 box showing all points from minimum to maximum. Each sample from the three
strains had tears pooled from 5 mice, with 3 samples for the NOD female and 5 samples for male NOD
and BALB/c mice. On the same set of samples, qPCR showed that miRNAs (C) miR-25-3p and (D) miR-
93-5p had very similar expression levels between the three strains. Median Cq values are plotted as
boxplots showing mean with 75% to 25% IQR and whiskers show the range. N=5 samples for male NOD
and BALB/c, 3 samples for female NOD; n=5 mice per sample, Kruskal-Wallis ANOVA, p=0.05. With
human tear RNA samples from SS and MGD patients, qPCR showed that miRNAs (E) miR-25-3p and
(F) miR-93-5p had no difference in expression levels. N=6 samples for SS and MGD. Unpaired t-test with
equal variances assumed; p=0.05.
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Upregulated Downregulated
Normalized to miR-25-3p Normalized to miR-93-5p Normalized to miR-25-3p Normalized to miR-93-5p

Figure 4.7 qRT-PCR validation of miRNA hits in mice tears.
In a separate cohort of age-matched mice, 13 miRNA hits from the sequencing data set were tested by
qPCR to confirm the initial observation. Data was first normalized for plate to plate variation using a spike-
in RNA and then to two internal controls, miR-93-3p and miR-25-3p. Of the 13 original hits, 8 miRNA
were confirmed as differentially expressed. Statistics were performed on average ΔCt values; data are
plotted as ΔΔCt. qPCR was performed with N=4 biological replicate samples, n=3 mice per sample, with
3 technical replicates per sample. (* p < 0.05, ** p < 0.01, *** p < 10
-3
, **** p < 10
-4
, Kruskal-Wallis
ANOVA in Graph-Pad Prism).
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Of the hits we could not validate, the miR-147-3p primer exhibited multiple melt curves
across all samples for all three replicates and did not meet the quality control requirements for
qPCR. miR-3076-3p also did not meet quality control requirements due to failed amplification in
2 out of 4 samples of female NOD and male BALB/c mouse tears, and therefore lacked power for
statistical analysis. Differential expression of three other miRNAs, miR-3572-5p, miR-421-3p,
miR-3963 could not be validated by qPCR (Figure 4.8).

Normalized to miR-25-3p Normalized to miR-93-5p

Figure 4.8 Assessment of miRNA hits predicted from the bioinformatics analysis which were not
validated by qRT-PCR.
Differential expression of 4 miRNAs were not confirmed in the qRT-PCR validation. miRNA miR-3076-
3p expression was not significantly different from that of female NOD mice and was modestly
upregulated in male NOD tears as compared to male BALB/c. miR-3572-3p was found to be
downregulated in male NOD mice tears as compared to female NODs, but modestly upregulated when
compared to male BALB/c. miR-421-3p was modestly downregulated in male NOD tears with respect
to male BALB/c and female NOD, but this difference was not significantly different in either comparison.
Mean ΔΔCt values are plotted as boxplots showing mean with 75% to 25% IQR and whiskers show the
range. N=4 samples for male NOD and BALB/c, and female NOD; n=3 mice per sample. * p < 0.05, **
p < 0.01, *** p < 10
-3
, **** p < 10
-4
, ns – not; significant, Kruskal-Wallis ANOVA, p=0.05.
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4.4.5 qPCR confirms differential expression of some miRNAs in tears from patients with
SS relative to patients with MGD
To assess the differential expression of miRNAs in patient tears, we pooled tears acquired
from left and right eyes of individual patients with either SS-associated dry eye or MGD diagnosed
as described in Methods, prior to RNA isolation. The mean age of the two patient groups, SS and
Table 4.2 qPCR validation of differentially expressed miRNA in male NOD mice tears

Normalized to miR-25-3p Normalized to miR-93-5p

p value* Fold Change
+
p value* Fold Change
+

miRNA
NOD M v
NOD F
NOD M v
BALB/c M
NOD M v
NOD F
NOD M v
BALB/c M
NOD M v
NOD F
NOD M v
BALB/c M
NOD M v
NOD F
NOD M v
BALB/c M
mmu-miR-181a-5p < 0.0001 < 0.0001 2.253 2.058 0.0074 0.0074 2.384 1.711
mmu-miR-146a-5p 0.0014 < 0.0001 -1.451 -2.441 < 0.0001 < 0.0001 -2.632 -3.229
mmu-miR-203-3p < 0.0001 < 0.0001 2.747 1.846 0.0111 0.068 4.761 1.525
mmu-miR-146b-5p 0.4496 < 0.0001 1.212 -1.821 0.0063 < 0.0001 -1.667 -2.571
mmu-miR-150-5p < 0.0001 < 0.0001 3.845 2.317 0.0003 0.0042 3.886 3.877
mmu-miR-322-3p 0.1580 0.0137 1.065 -1.806 0.0062 0.0012 -3.043 -2.978
mmu-miR-181b-5p 0.0041 < 0.0001 1.939 2.238 0.0251 0.0097 3.671 3.423
mmu-miR-3963
††
< 0.0001 0.0163 -3.386 1.380 < 0.0001 0.477 -23.002 1.029
mmu-miR-3572-3p
†
0.0022 0.5291 -1.372 1.432 < 0.0001 0.8333 -9.319 -1.925
mmu-miR-503-5p 0.7268 0.1355 2.037 0.658 0.601 0.0102 2.863 1.976
mmu-miR-3076-3p - 0.4914 1.062 1.772 - 0.0677 - 1.835
mmu-miR-421-3p 0.6508 0.9841 1.184 1.026 0.9091 0.9727 -2.441 -1.252
* Between group p values calculated using ΔCt values normalized to miR-25-3p and miR-93-5p, using
Kruskal-Wallis ANOVA with Tukey’s multiple correction in Graph-Pad Prism. Significant p values are
shown in bold.
+
Fold changes reported are averaged ratio of ΔCt for male NOD to that of male BALB/c or female NOD
†
and
††
Not considered a validated hit due to reversal in direction of FC between the two comparisons;
††
Variation is largely driven by female NOD mice.
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MGD, were comparable with no significant differences (Figure 4.9A). We then compared tear
volumes as well as concentration and quality of RNA isolated from these tears. As expected, SS
patients had lower Schirmer’s test scores relative to patients with MGD (Figure 4.9B).
Normalized to mm of wetting of the Schirmer’s strip, the RNA amount (ng) in tears of SS
patients was significantly higher than that of MGD patients (Figure 4.9C). We obtained on
average 9.21 ng/μL (or 184.2 ng) of RNA from SS patient tears and 7.38 ng/μL (or 147.6 ng) of
RNA from MGD patient tears. Tear RNA quality of the two groups was comparable(Figure 4.9D).
8 out of the 13 miRNA hits assayed by qRT-PCR in mouse tears have completely identical
nucleotide sequences for human and mice. For validation in patient tears, we used the same custom
PCR panels as the mouse validation cohort. The 8 identical miRNA PCR amplified as expected,
but we also observed amplification of three murine primers for miRNAs miR-322-3p, miR-503-
5p and miR-3963. This is likely due to high sequence similarity of murine microRNAs miR-322-
3p and miR-503-5p with their respective human homologs. We observed that miRNA hsa-miR-
203a-3p was the most highly expressed of these miRNAs in patient tears, followed by hsa-miR-
146a-5p, hsa-miR-150-5p and mmu-miR-3963 (Figure 4.13).
A B C D

Figure 4.9 Quality assessment of RNA isolated from tears of SS patients using Tapestation.(A) There
was no significant difference in the age of patients from the two groups. (B) Schirmer’s test score was
higher for SS patients than MGD patients. (C) Normalized to tear volume, SS patient tears had significantly
higher amounts of total RNA than tears of MGD patients. (D) There was no significant difference in the
RIN values of RNA from SS and MGD patient tears. N=6 samples each for SS and MGD patients. Samples
were analyzed using a Mann-Whitney U test with p<0.05 considered significantly different.
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For qPCR validation, hsa-miR-93-5p and hsa-miR-25-3p were used as endogenous
controls for assay normalization and their levels did not vary between the two groups, similar to
the observation in male NOD mice tears (Figure 4.6 E, F). Of the 8 miRNA hits with identical
sequences, miRNAs hsa-miR-181a-5p, hsa-miR-181b-5p and hsa-miR-203a-3p were significantly
upregulated in tears of patients with SS-like dry eye when compared to tears of patients with MGD
when normalized to hsa-miR-25-3p (Figure 4.10).
4.4.6 IPA identifies dysregulation of molecular functions and immunomodulation
To understand the pathways and cellular processes involving the qPCR-validated
dysregulated miRNAs, we used Ingenuity Pathway Analysis (IPA). IPA identified mRNA targets
of hits that are a) experimentally validated or b) predicted targets with high probability scores
(from the TargetScan database). Biological processes with a relatively higher number of such
mRNA targets are more likely to be dysregulated by altered expression of miRNA hits and are,
therefore, termed ‘overrepresented’. Figure 4.11 shows the processes most likely to be affected,
in decreasing order of statistical probability. The most overrepresented cellular processes and

Figure 4.10 qRT-PCR validation of miRNA hits in human tears from patients with SS or MGD.
In a small cohort of patients, miRNAs hsa-miR-181a-5p, hsa-miR-181b-5p and hsa-miR-203a-3p were
significantly upregulated in tears of SS patients when compared to tears of patients with MGD. Data
were first normalized for variation arising from RT and PCR using spiked-in control. Statistics were
performed on ΔCt values normalized to hsa-miR-25-3p. Mean ΔΔCt values are plotted as boxplots
showing the mean with 75% to 25% IQR and whiskers depicting the range. (N=6 samples each for SS
and MGD patients; unpaired t-test with equal variances assumed; p=0.05).
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functions were differentiation and hematopoiesis of mononuclear leukocytes (p<10-55),
leukopoiesis (p<10-53) and lymphopoiesis (p<10-48), followed by connective tissue cells (p <10-
42), lymphatic system cells (p<10
-42
) proliferation of mononuclear leukocytes (p<10
-41
) and
lymphocytes (p <10
-41
).
Proliferation processes related to other cell types, such as those of liver (p<10
-16
), kidney
(p<10
-12
), and heart (p<10
-6
) were relatively underrepresented. Among cellular processes leading
to disease development, cancers such as nonhematologic malignant neoplasm and head and neck
tumor was the most over-represented (p<10
-43
). Figure 4.12A shows mRNAs targeted by more
than one miRNA hit, shown within the context of the subcellular location of the encoded protein.

Figure 4.11 Ingenuity Pathway (Enrichment )Analysis of tear miRNA hits.
The most statistically significant biological functions and processes generated by IPA for the genes
targeted by the differentially expressed tear miRNA hits, grouped by function categories (p values
calculated by IPA based on Table 4.1).
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The mRNA targets include those predicted to be targeted by miRNA hits with high
probability based on in-silico seed region matching, and targets that are experimentally validated.
Several mRNA targets appear to be transcription factors implicated in cell cycle progression such
as CDKN2AIP, CDC25A, CDCA4, CDC14 , CCDN1 and CCDN2. Also, of interest is PLSCR4
(Calcium dependent Phospholipid scramblase 4), an ATP-independent, transmembrane lipid
transporter responsible for inducing non-specific bidirectional movement of phospholipids in the
cell membrane during cell activation that has also been proposed as a potential mediator of
phosphatidylserine in the outer leaflet of the plasma membrane in apoptosis
161
. PLSCR4 is targeted
by three of the downregulated miRNA hits, miR-146a-5p, miR-322-5p and miR-503-5p. Genes
targeted by miRNA hits known to be involved in immunological processes include CD40,
TNFSF13B and HLA-DBQ2, with their expression predicted to increase due to the observed
downregulation of their regulating miRNAs. Interaction of CD40 with its ligand CD40L (or
CD154) plays an important role in immunity as it promotes plasma cell differentiation, antibody
production and is required for optimal immune response to most antigens. This is in line with
previous studies demonstrating that CD40 is overexpressed in SG ductal epithelial cells,
lymphocytes, and endothelial cells in SS patients
162
. Antibody blockade of CD40 has also shown
therapeutic potential for treatment of SS in clinical trials
163
.
Several key proinflammatory mediators are also targets of dysregulated miRNA. To
illustrate this, IPA results focused solely on IL-6 signaling pathways are shown in Figure 4.12B.
IL-8 and C-reactive protein (CRP) mRNAs are targets of the downregulated miRNA hits, miR-
322-3p and miR-146a-5p. TAK1 and TRAF6 of the NF-kB pathway and c-Raf of the MAPK/ERK
pathway are also targets of the downregulated hits, miR-322-5p, miR-146a-5p and miR-503-5p.

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A

B

Figure 4.12 IPA Network analysis of targeted miRNAs.
(A) IPA Network map of miRNA hits and their mRNA targets. Genes targeted by >1 miRNA hits are
shown according to their subcellular localization. Arrows represent post-transcriptional silencing of
genes by connected miRNA. Downregulated miRNA hits are shown in red, upregulated ones are in green,
whereas gene targets likely to be upregulated are shaded in green, and those likely to be downregulated
are shaded in orange. Gene icons shaded in white are targeted by both up and downregulated miRNA.
(B) Pathway analysis results suggest upregulation of IL-6 family cytokines and those transcribed through
the IL-6-response element (IL6RE). In the NF-κB signaling, TRAF6 and TAK1 are targets of hits miR-
146a-5p and miR-322-5p. Downregulation of these hits may lead to upregulation of TRAF6 and TAK1
and increase the transcription of the IL6RE, resulting in increased mRNA levels of cytokines. Of these,
IL-8 is directly targeted by miR-146a-5p and its levels could be particularly upregulated with depletion
of this miRNA. Also of key import is the targeting of SOCS3 by the upregulated miRNA miR-203-3p.
SOCS3 is a negative regulator of the JAK2/STAT3 pathway and is required to turn off the pathway to
prevent excessive production of cytokines.
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This downregulation may lead to upregulation of IL-6-Response elements (Figure 4.12B)
promoting upregulation of cytokines such as IL-6 and IL-8 which are highly relevant to SS
pathogenesis and upregulated in SG
164
, serum and tears
165
of SS patients. SOCS3, a negative
regulator of the JAK2/STAT3 pathway, is targeted by overexpressed miR-203-3p, which may
result in its downregulation leading to the constitutive transcription of CRP, VEGF and A2M
(Figure 4.12B). SOCS3 downregulation may lead to enhanced activity of pro-inflammatory IL6
family cytokines through its reduced ability to interaction with gp130
166
to modulate IL6 signaling,
also potentially contributing to SS pathogenesis.
4.5 Discussion
Dry eye disease is a multifactorial condition linked to chronic inflammatory diseases,
environmental challenges, hormonal status and even medication. However, SS-associated dry eye,
which occurs through a distinct mechanism involving development of autoimmune inflammation
and loss of secretory function of the LG, is arguably the most debilitating. In the absence of a
definitive diagnosis and without clinical intervention, SS patients with dry eye symptoms can
develop corneal lesions which can require corneal transplantation to restore vision
167, 168
.
Unchecked autoimmune inflammation in exocrine tissues including LG can lead to formation of
ectopic germinal centers which may also contribute to autoantibody production and other
mediators of extraglandular symptoms of SS
169, 170
. Clinical diagnosis of dry eye largely evaluates
functional measures such as tear flow, tear osmolarity, tear break up time and ocular surface
integrity; there are no diagnostic tests to directly assess inflammation of the LG. While the LG
cannot be biopsied owing to the substantial risk of damage, tear analysis is feasible. Soluble
constituents of tears are produced and secreted largely by the LG; thus, any damage, immune
infiltration, deposition, or fibrosis in the LG should be reflected by changes in the tear composition.
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Tear analysis thus provides critical insights into disease processes ongoing in the LG at different
stages.
Although symptoms of dry eye disease are a part of the ACR-EULAR criteria for SS
diagnosis, there are no specific tests which can easily detect autoimmune involvement of the LG
relative to the use of the minor SG biopsy which accompanies identification of oral dryness to aid
in diagnosis of SS with SG involvement. SS patients report uneven manifestation of ocular versus
oral symptoms
137
, suggesting that exocrinopathies of the LG and SG may not always develop in
parallel. Murine models of SS also manifest different patterns of LG and SG exocrinopathy
26, 171
.
The availability of a test that could enable eye care specialists and others to distinguish patients
with SS-associated dry eye disease versus those with dry eye due to other causes, could improve
diagnosis for the 15% of SS patients who present primarily with dry eye symptoms
172
. One study
has shown that the diagnosis of SS patients presenting with only dry eye symptoms is 2.7 times
more likely to be delayed
172
. More patients presenting with only dry mouth symptoms (53%) are
accurately diagnosed with SS within a year, relative to the accuracy of diagnosis of patients
presenting with dry eye symptoms within the same time frame (41%). About 42% of patients with
only dry eye symptoms take >1 year to be diagnosed accurately
172
putting patients with a more
prominent ocular symptoms at a disadvantage. As an additional benefit, tears can be collected non-
invasively using Schirmer’s strips
37
, obtained as part of a common clinical test for dry eye.
Dysregulated miRNAs can be measured at any time after tear collections are frozen and can be
multiplexed to detect multiple species, as they are chemically stable when stored at -80 °C
36
.
Tears are a viable source for identification of unique miRNAs denoting disease. Previous
studies comparing various biofluids have reported that human tears contain over 600 distinct
proteins
15
and over 300 miRNAs
13
. Tears also have a higher concentration of miRNA than does
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urine, CSF or plasma
13
. Tear miRNAs are thought to play important roles in maintaining the health
of the ocular surface and mediating immune response during infection. Recently, tears have been
investigated for miRNA biomarkers for Alzheimer’s diseases
16
and primary open-angle
glaucoma
17
with the identification of hits showing very high sensitivity and specificity (AUC =
0.93)
17
. These findings collectively suggest that changes in the tear miRNAome can reflect disease
status. To our knowledge, the tear miRNAome in SS has not been comprehensively sequenced.
Our study has identified >550 distinct miRNAs in NOD mouse tears, substantially more
than reports from a previous study investigating 43 tear miRNAs using qPCR
140
. Our approach
utilized NGS, which provides a broader, more comprehensive, and unbiased genome readout of
RNAs than do microarrays. Only 2 of our 8 validated miRNA hits, mmu-miR-146a/b-5p, have
previously been linked to ocular symptoms of SS while 4 of 8 of our validated miRNAs hits
including miR-181b-5p, miR-203-3p, miR-322-3p and miR-503-5p have never been previously
linked to SS. Two of these - miR-181b-5p, miR-203-3p, were validated in the small pilot study of
6 SS patients in Figure 4.10. Nearly 70% of human miRNA have mouse orthologs with conserved
seed-region sequences
63
. In our study, 6 of the 8 validated miRNA hits– mmu-miR-146a-5p, mmu-
miR-146b-5p, mmu-miR-150-5p, mmu-miR-181a-5p, mmu-miR-181b-5p, and mmu-miR-203-3p
– are completely identical between human and mouse
173
. This highlights the utility of miRNA
research in murine models to study development of SS as we have demonstrated in our pilot study.
Of the identified miRNAs that are not completely identical between human and mouse, miR-503-
5p differs from its human counterpart (hsa-miR-503-5p) by 1 nucleotide while identified orthologs
are known for miR-322-5p (hsa-miR-424-5p), so both miRNAs could likewise be evaluated in any
analyses of SS patient tears or tissue.
Tear miRNA Biomarkers for SS
Kakan SS et al. Frontiers in Immunology. 2022 Mar 4;13:833254.
92
miR-150-5p, miR-146a/b-5p, and miR-181a-5p, identified here as dysregulated in NOD
mouse tears, and for hsa-miR-181a-5p, in SS patients, have been previously linked to SS in other
studies. One study investigating peripheral blood mononuclear cells (PBMC) from SS, SLE and
healthy control subjects found miR-150-5p to be the only miRNA downregulated in SS patients
as compared to SLE and healthy controls
111
. However, other studies have found miR-150-5p to be
elevated in SS patients’ saliva, minor SG
174
, and serum
175
(4.3), consistent with the increased
expression in male NOD mice tears. miR-150-5p was previously found to be significantly
upregulated in a rabbit autoimmune dry eye model investigating differential expression of
miRNAs in LG
176
. This may be related to the observed upregulation of miR-150-5p in NOD mouse
tears, as the LG is the primary source of tears. We also analyzed preexisting raw datasets generated
by other groups
177
(SRA Accession: PRJNA542600, ENA Accession: PRJDB9749) in mouse
models of SS that were made publicly available at Sequence Read Archive (SRA) and European
Nucleotide Archive (ENA). In LG of Aire knockout mice, precursor miRNA miR-503 was 4-fold
downregulated as compared to LG of wild type mice. In LG of male NOD mice, gene expression
of precursor miR-181a was 3-fold upregulated as compared male BALB/c. This is similar to what
we observe for mature miRNAs miR-503-5p and miR-181a-5p in tears of the NOD model.
Altered expression of miR-146a-5p and miR-146b-5p has been reported in plasma/serum
and PBMCs of SS patients as well as in saliva, SG and LG from animal models of SS (Table 4.3).
A microarray of 43 miRNAs in SS patient tears showed that miR-146a-5p was downregulated in
tears of primary SS patients (i.e., SS patients who lack other autoimmune diseases
131
) relative to
healthy subjects but was significantly upregulated in tears of patients with secondary SS (i.e., SS
patients who also have other autoimmune diseases
131
) relative to patients with primary SS
140
. In
SS-prone B6DC mice, miR-146a levels were upregulated in LG and submandibular SG at 8 weeks
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Kakan SS et al. Frontiers in Immunology. 2022 Mar 4;13:833254.
93
but downregulated at 20 weeks, while its levels were increased significantly in PBMC of 20 weeks
old mice. Dysregulated expression of miR-146a/b-5p has also been found in animal studies and in
various biofluids in patients with SLE and RA and may serve as a more general indicator of
autoimmunity. A more comprehensive analysis of the changes in miR-146a/b-5p over time in tears,
in parallel with a more comprehensive analysis of LG disease status, may be necessary to
understand its utility in diagnosis of SS.
Dysregulation of miR-181a-5p has also been described in SS, with several studies reporting its
upregulation in PBMC of SS patients relative to healthy subjects (Table 4.3). We found it to be
upregulated in tear of patients with SS-like dry eye in our pilot study compared to those of patients
with MGD. In SG of SS patients, this miRNA was downregulated relative to healthy controls, but
within the SS patient cohort it was upregulated in the SG of those exhibiting more profound
decreases in salivary flow and high SG focus scores
174
. Intriguingly, this miRNA is also implicated
Table 4.3 Literature summary for previous miRNA hits in studies on SS.
microRNA Immune Cells Salivary Gland Serum Tears
miR-146a-5p
PBMC
111, 178-181

T & B¯ Lymphocytes
182

Mouse SG
180
Tears
140

miR-146b-5p PBMC
111, 178
SG
174
- Tears
140

miR-181a-5p PBMC
111, 181, 183

SG
184
¯
SG, SG Epithelial
Cells
183
||, *SG
174

- -
miR-150-5p
PBMC
111, 185
¯
Naïve B cell
175, 186

Activated B cell
186
¯
SG
174
Serum
175
-
miRNA in bold have identical sequence for human and mouse; *Upregulated in SS patient SG with
decreased salivary flow; upregulated; ¯ downregulated; || no change; PBMC: Peripheral
mononuclear blood cells.
Tear miRNA Biomarkers for SS
Kakan SS et al. Frontiers in Immunology. 2022 Mar 4;13:833254.
94
in regulation of the differentiation of germinal center B cells
187
, which may also be found in the
ectopic germinal centers that form at late stages of SS in exocrine glands.
All validated and dysregulated miRNAs identified here are expressed in blood cells and
function in immune cell development and differentiation. Unsurprisingly, pathway analysis of the
miRNA hits identifying likely gene targets and the biological processes involving these gene
products include differentiation, maturation and proliferation of T and B lymphocytes. Tears
produced by the LG and other ocular surface tissues drain through the canaliculus into
nasolacrimal ducts. Here, tear components including miRNAs can be reabsorbed into the blood
vessels surrounding the cavernous body of the nasolacrimal ducts
141
and shuttled back to the LG.
These tear constituents may have access to draining lymph nodes through the tear duct associated
lymphoid tissue (TALT). We hypothesize that a primary function of tear miRNAs is the regulation
and homeostasis of local immune responses in the LG and ocular surface; dysregulated miRNAs
may therefore contribute to induction and perpetuation of autoimmune processes by priming
immune cells in the TALT that migrate to the LG in SS.
Precursor miR-146a/b and miR-181a miRNAs participate in immune cell development and
differentiation of T and B cells from hematopoietic stem cells
188
. miR-150-5p is detected in human
serum
189
, while its increased expression is linked to autoimmune disease
190
. Its expression is
decreased in serum of patients with B cell malignancies, and in double negative thymocytes, but
its levels increase in differentiating T lymphocytes
191, 192
. miR-150-5p is highly expressed in naïve
T and B cells, with levels decreasing in mature B cells
191
. miR-150-5p is thought to maintain B
cells in the quiescent stage in lymphoid organs and to regulate their expansion by targeting the
transcription factor MYB
190
. It is also involved in natural killer cell maturation and
development
193
. These findings, along with our observation of its upregulation in male NOD tears,
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95
suggest it may participate in local T and B cell maturation with its levels possibly reflecting the
degree of immune cell infiltration of the LG.
Murine miR-322 promotes Th17 cell differentiation through its targeting of the
transcription factor NF-kB subunit p50
194
, interesting because of the prominent role of Th17 and
IL-17 as disease drivers in SS
195
. miR-322 may also act as an anti-inflammatory agent through its
ability to suppress cytokine secretion and signaling
196
. This function is consistent with our IPA
analysis which highlights the targeting of master regulators of IL-6 production (TAK1 and c-Raf)
by miR-322-5p (Figure 4.12B). Consistent with this, we have previously reported that IL-6 gene
expression increases significantly in LG of male NOD mice following the onset of autoimmune
dacryoadenitis, as compared to LG of age-matched male BALB/c and female NOD mice
21
. hsa-
miR-424, the human ortholog of murine miR-322, as well as miR-503-5p are also implicated in
monocyte differentiation
197, 198
. Suppressor of cytokine signaling 3 (SOCS3), a negative feedback
regulator of the JAK2/STAT3 pathway, is targeted by upregulated miR-203-3p which may lead to
its decreased expression. As a result, IL6-mediated signaling of the JAK2/STAT3 pathway may
be enhanced in cells with increased miR-203-3p.
One limitation of our study is our use of only a single model of SS. As well, SS patients
are predominantly female
25
, yet the male NOD mouse is one of the most common murine models
used to evaluate SS-associated dry eye disease. Use of the male NOD mouse in our hands has led
to discovery of the tear biomarker, cathepsin S, which has been validated as selectively and highly
upregulated in two separate cohorts of female SS patients
46, 199
. Exploration of the role of sex
hormones in development of autoimmune dacryoadenitis has shown that LG inflammation in this
model is induced by male sex hormones; orchiectomized mice exhibit a lesser immune infiltration
into LG
26
. Moreover, adoptive transfer experiments of splenocytes between male and female NOD
Tear miRNA Biomarkers for SS
Kakan SS et al. Frontiers in Immunology. 2022 Mar 4;13:833254.
96
and NOD SCID mice confirm that the lacrimal gland microenvironment in the male NOD mouse
contributes uniquely to lymphocytic infiltration
26, 200
. Male sex hormones do not have a
comparable effect in another autoimmune model of SS and other autoimmune diseases, the
MRL/lpr mouse
171
. Intriguingly, ductal epithelial cell from labial salivary gland biopsies in SS
patients were positive for testosterone, dihydrotestosterone and estradiol, whereas cells from
healthy control biopsies were positive only for estradiol
201
. Thus, much remains unknown
regarding the interaction between sex hormones and LG tissue in disease. The male and female
NOD mice are also predisposed to development of diabetes, although at an older age than the 12–
14-week aged mice used for tear collection. Thus, this predisposition represents a confounding
factor. Animal models may also not fully represent the complexity of SS disease progression. In
addition, the pooling strategy used to obtain RNA of sufficient quantity and quality may have
reduced our overall sensitivity, especially for miRNAs that are lowly expressed. However, these
conditions were still sufficient to detect several significantly altered miRNAs, half of which were
experimentally validated in separate samples. Moreover, 3 of these miRNAs were validated in a
small pilot study of SS patients. The size of our human cohort being extremely small is also a
limitation, and future studies will require investigations with much larger cohorts and additional
control groups.
In conclusion, we report here the identification and validation of 8 dysregulated miRNAs in tears
that have potential for use in diagnosis of ocular (LG) involvement in SS. Of these, 4 have been
previously identified in other biofluids or organs in SS patients or disease models and we have
validated 1 in a pilot study in SS patient tears; while 4 are newly implicated in SS of which we
have validated 2 in our pilot study with SS patients tears. This list of differentially expressed tear
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Kakan SS et al. Frontiers in Immunology. 2022 Mar 4;13:833254.
97
miRNAs is first of its kind, is of high priority for future investigation in SS patient tears and may
potentially distinguish ocular involvement in SS patients.

Data availability: The data used to support the findings of this study are included within the article and
Supplementary Materials. The raw datasets generated as part of this study can be found in the Sequence
Research Archive under BioProject Accession ID PRJNA769738 and are available for download here
https://www.ncbi.nlm.nih.gov/Traces/study/?acc=PRJNA769738&o=acc_s%3Aa. The code used for
analysis of the generated datasets can be found here https://github.com/singhkakan/miRGrep.
Ethics Statement: The animal study was reviewed and approved by The Institutional Animal Care and
Use Committee (IACUC). All procedures in the human-subjects study were approved by the USC
Institutional Review Board and were performed in accordance with the Declaration of Helsinki, and all
subjects provided written informed consent. Use of samples from the USC Dry Eye Center of Excellence
tear biorepository at the USC Roski Eye Institute tear biorepository is approved under IRB protocol HS-
19-01004 and meets the requirements for ‘nonhuman research with biospecimens previously
generated/collected to be analyzed for research purposes (Data and Specimens) or secondary data analyses.
Author contributions: All authors were involved in drafting the article or revising it critically for important
intellectual content. All authors approved the final version to be published. SK wrote the first draft. BH,
SHA, SK, and ME were involved in the study conception and design. SK, AY and AN acquired the data.
SK, BH, SHA, ME, CO, AY and AN were involved in the analysis and interpretation of data.

Figure 4.13 Relative expression of miRNA hits in RNA isolated from patients tears.
Primers for 8 miRNAs that have identical sequences for human and mouse (and can be used
interchangeably) amplified successfully during qPCR, with hsa-miR-203a-3p having the highest level of
expression followed by hsa-miR-146a-5p. 3 of the five mouse specific primers also appeared to amplify
successfully during qPCR, with mmu-miR-3963 being expressed at a much higher rate. Data are shown
as bar plots of qPCR normalized mean Ct values with error bars showing range (N=12).
Tear miRNA Biomarkers for SS
Kakan SS et al. Frontiers in Immunology. 2022 Mar 4;13:833254.
98
Funding: This work was supported by RO1 EY011386 to SHA. Further support for the project came from
P30EY029220, and an unrestricted departmental grant from Research to Prevent Blindness (RPB), New
York, NY 10022.
Conflict of Interest: The authors declare that the research was conducted in the absence of any commercial
or financial relationships that could be construed as a potential conflict of interest.
Acknowledgements: The authors acknowledge Dr. Yaping Ju for assistance with the Roski Eye Institute
Dry Eye Biorepository and identification of deidentified specimens and Srikanth Reddy Janga for assistance
with mouse tear collection.

99
Chapter 5 The miRNA landscape of lacrimal glands in a
murine model of autoimmune dacryoadenitis
^

Kakan SS, Edman MC, Okamoto CT, Hjelm BE, Hamm-Alvarez SF. The miRNA landscape of lacrimal
glands in a murine model of autoimmune dacryoadenitis. Invest Ophthalmol Vis Sci. 2022 (In review)
Keywords: Sjögren’s syndrome, microRNA, lacrimal gland, inflammation, autoimmunity,
interleukin-6 signaling
^ Note: This chapter is taken from the previously mentioned manuscript.
5.1 Abstract
To analyze the changes in lacrimal gland (LG) miRNAome from male non-obese diabetic (NOD)
mice, a model of autoimmune dacryoadenitis, relative to disease-free LG. LG from male NOD
mice with established dacryoadenitis as well as healthy control male BALB/c and dacryoadenitis-
free female NOD mice were collected for small RNA sequencing (sRNAseq) and data analysis to
identify dysregulated miRNAs. Validation in additional LG was by RT-qPCR. Immune-cell
enriched (IEF) and epithelial-enriched (EEF) cell fractions from additional male NOD mouse LG
were used to probe the relative cellular enrichment of dysregulated miRNAs. Ingenuity Pathway
Analysis (IPA) was used to identify putative miRNA-targets. Male NOD mouse LG exhibited 15
and 13 miRNAs that were significantly upregulated and downregulated, respectively, compared to
controls. Using defined criteria to focus our hits, we validated the dysregulated expression of 14
of these miRNAs (9 upregulated, 5 downregulated) in male NOD mouse LG relative to LG from
controls by RT-qPCR. Further analysis using RT-qPCR showed that 7 of the upregulated miRNAs
were primarily increased in IEF while 4 of the downregulated miRNAs showed higher expression
in EEF. Upregulated and validated LG miRNAs of particular interest due to their previous links to
SS pathophysiology in other tissues are miR-150-5p, miR-142a-3p, miR-142a-5p, and miR-
LG miRNAs in Murine Model of SS
Kakan SS, et al. [abstract] Arthritis & Rheumatology. 2022; 74 (suppl 9) 100
146a/b-5p. Downregulated miR-365-3p is implicated in autoimmune dacryoadenitis for the first
time. The predicted outcomes of dysregulation of miRNAs using IPA suggest upregulation of
interleukin (IL)-6 and IL-6-like pathways, confirmed by mRNA seq of published data. IL-6
signaling is implicated in SS pathogenesis.
5.2 Introduction
Sjögren’s syndrome (SS), the second most common autoimmune disease
3, 202
, is associated
with lymphocytic infiltration and secretory dysfunction of lacrimal glands (LG) and salivary
glands (SG). Systemic symptoms including interstitial lung disease
203, 204
, nephritis, peripheral
neuropathy, chronic fatigue and others
205, 206
are also associated with disease. The molecular events
involved in lacrimal gland inflammation in SS are not well understood. As a result, treatment
options specific for ocular symptoms of SS that can fundamentally modify disease processes in
the LG rather than provide symptomatic relief are lacking.
miRNAs are 16-26 nucleotide (nt), short non-coding functional RNAs (ncRNA) that
contain a 6-8 nt long ‘seed’ sequence partially complementary to over 60% of all mammalian
messenger RNAs (mRNAs)
12
. Through translational repression and other mechanisms
207
they are
master regulators of gene expression
208
and implicated in disease pathogenesis
209-213
. We have
previously isolated tear RNA from an SS disease model, the male non-obese diabetic (NOD)
mouse, to identify dysregulated tear miRNAs which could represent diagnostic biomarkers for
ocular manifestations of SS
130
. These tear miRNAs may also act on cells of the ocular surface and
in draining lymph nodes; thus they provide insights into the mechanisms of ocular surface disease
pathogenesis in SS. We hypothesized that comparable analysis of the changes in miRNA
expression in the diseased LG could identify other dysregulated miRNAs that might shed insights
into disease mechanisms and progression in the LG in SS. To date, few studies have reported on
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101
miRNA dysregulation in LG
180, 214
and fewer still have profiled LG miRNA in SS
176
.
The male NOD mouse is one of the most thoroughly investigated models of ocular
symptoms of SS
26, 29, 44, 145, 171, 215
. By 6-8 weeks of age, male NOD mice spontaneously develop
SS-like LG pathology including lymphocytic infiltration
44, 148
, decreased basal and stimulated tear
production
44
, increased cysteine protease expression in tissue
21, 152
and tears
21, 44, 199
, and
remodeling of extracellular matrix
145
. The male BALB/c mouse is commonly used as a sex-
matched control for healthy LG
114, 145, 215, 216
. Female NOD mice develop SS-like pathology in SG
but not LG even by 20 weeks of age
26, 148
. The females thus represent a strain-specific control
lacking ocular disease manifestations. We use both age-matched male BALB/c and female NOD
mouse LG as controls to compare to male NOD mouse LG for small RNA sequencing (sRNAseq)
evaluation of miRNA expression.
Here, we present the changes in the NOD mouse LG miRNA transcriptome associated with
autoimmune dacryoadenitis. Using Ingenuity Pathway Analysis (IPA), we relate findings on
miRNA dysregulation within immune and epithelial cell populations and their potential impact on
signaling changes associated with establishment and progression of disease, utilizing publicly-
available mRNA sequencing (mRNAseq) datasets to validate predictions. Our study provides a
snapshot of miRNA expression in the healthy LG and identifies dysregulation of particular
miRNAs associated with immune cell infiltration and loss/altered function of epithelia that may
provide new insights into mechanisms of disease.
5.3 Methods
5.3.1 Mice
Male NOD mice were used as a model for SS-associated autoimmune dacryoadenitis with
controls as described previously
130
. 8-week male and female NOD/ShiLtJ (001976), and male
LG miRNAs in Murine Model of SS
Kakan SS, et al. [abstract] Arthritis & Rheumatology. 2022; 74 (suppl 9) 102
BALB/c J (000665) mice were obtained from Jackson Laboratories (Bar Harbor, ME), housed up
to 5-mice per cage with ad libitum access to food and water, and aged to 13 weeks (± 3 days). All
procedures involving mice adhere to the ARVO Statement for the Use of Animals in Ophthalmic
and Vision Research, were performed in compliance with the Guide for the Care and Use of
Laboratory Animals
70
, and approved by the USC Institutional Animal Care and Use Committee
(IACUC).
5.3.2 Tissue collection
We have published sRNAseq data from tears of male NOD mice compared to tears from
female NOD and male BALB/c mice and identified dysregulated miRNAs
130
. From these same
13-week mice, following collection of stimulated tears through addition of topical carbachol as
described
130
, mice were euthanized. One LG from these mice was collected and processed
immediately for RNA isolation using the Universal mini kit (Qiagen, Germantown, MD) and
sRNAseq. The contralateral LG was used for histology to quantify autoimmune dacryoadenitis as
published
130
. Datasets generated from these LG RNA samples form the basis of the current
sRNAseq study.
For sRNAseq, one sample was comprised of RNA from 5 LG from each of 5 mice, with 5
samples for male NOD, 5 for male BALB/c and 3 for female NOD mice. Additional unstimulated
LG from male NOD and male BALB/c mice were collected for RNA isolation and validation of
dysregulated miRNAs identified by sRNAseq, with the left and right LG from each mouse pooled
prior to RNA isolation using the Universal mini kit (Qiagen). Additional LG from male NOD mice
were collected and pooled prior to isolation of cell populations as below, for RNA isolation and
analysis of miRNA expression by RT-qPCR.
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103
5.3.3 LG immune and epithelial cell enrichment
s-Ham's is Ham’s F-12 supplemented with: penicillin (100 U/mL), streptomycin (100
µg/mL), L-glutamine (2 mM), n-butyric acid (2 mM), linoleic acid (0.3 mM), soybean trypsin
inhibitor (50 mg/ml), BSA(5 mg/ml), and HEPES (10 mM), adjusted to pH 7.6) and washed 3x
with s-Hank’s (which is Hank’s Balanced Salt Solution supplemented with EDTA (0.76 mg/ml)
and HEPES (10 mM), adjusted to pH 7.6.
Immune cells from LG of male NOD mice were separated from epithelia using protocols
developed previously
217, 218
with modifications. The epithelial cell fraction is enriched in acinar
cells, which represent 85% of the mass of the LG. Briefly, LG were rinsed 3x in s-Ham’s
217

(Supplemental Methods), and digested using Collagenase I (300 U/mL) in s-Ham’s, by incubating
at 37°C for 10 min 3x with repeated trituration in fresh medium. The supernatant was collected
after each incubation and sequentially filtered through a 100 µm cell strainer stacked on a 10 µm
cell strainer over a 50 mL tube to collect enriched immune cells, allowing retention of epithelia in
the 10 µm cell strainer. The filtrate was spun down (300 x g, 5 min) and the cell pellet resuspended
2x in 5 mL s-Ham’s before sedimentation to concentrate the immune cell-enriched fraction (IEF).
The epithelial-enriched fraction (EEF) was collected by inverting the 10 µm strainer and eluting
with 30 mL of s-Ham’s (Figure 5.1A). Enriched epithelia were spun down (200x g, 5 min) and
resuspended 2x in 5 mL s-Ham’s before subsequent centrifugation. IEF and EEF cell pellets were
resuspended in 200 μL s-Ham’s and viability assessed with 0.4% Trypan Blue using a Tc-10 Cell
Counter (BioRad, Hercules, CA). Cells were lysed with Qiazol (Qiagen) and 10 μL of β-
mercaptoethanol was added to inhibit RNAse prior to isolation of total RNA using the miRNeasy
mini kit (Qiagen).
LG miRNAs in Murine Model of SS
Kakan SS, et al. [abstract] Arthritis & Rheumatology. 2022; 74 (suppl 9) 104
A

B

Figure 5.1 Isolation and characterization of immune- and epithelial-enriched fractions from 13-
week male NOD mice.(A) Schematic describes the isolation protocol for immune-enriched fractions
(IEF) and epithelial-enriched fractions (EEF) from LG of 13-week male NOD mice. (Scale bar 20 µm,
data are representative of five experiments) (B) Relative expression of epithelial-specific Aquaporin 5
(AQP5), LG acini-enriched RAB3D, and immune cell-enriched cytokines and cytokine receptor mRNAs
in IEF and EEF. n=5 mice per group, data are plotted as mean ± SEM; * q < 0.05, two-way ANOVA
with fdr controlled at q=0.05 for multiple comparisons correction
5.3.4 sRNAseq and Bioinformatics
For sRNAseq, total RNA was isolated from stimulated LG of the same mice used
previously for tear collection and tear sRNAseq
130
. Quality of LG RNA samples was assessed
using Agilent Tapestation, and RNA samples were outsourced to Qiagen for library preparation
and sequencing. sRNA libraries were prepared using the QIAseq miRNA Library Kit (Cat 331502)
and sequenced on NextSeq 550 (Illumina, San Diego, CA) platform (75 base-pairs (bp) single-end
Chapter 5

105
configuration, read depth ~25 million reads/sample. Raw mRNAseq datasets generated by Ohno
Y et. al
215
and in fastq formats were obtained from European Nucleotide Archive (ENA:
PRJDB9749, GEO GSE81621).
Fastp
219
was used for trimming adapter and library primer contaminants and reads with
average quality score < 25 and length < 15 nt were filtered. FASTQ reads were aligned to the
ncRNA transcriptome (EMBL), and to miRNAs (miRBase v22.01)
173
using Bowtie
74
as well as
miRGrepp
96
. After trimming adapters, the 150-bp paired end fastq reads were filtered based on
quality and min length using fastp, aligned to GRCm39 using Star
220
(v2.7.0a) and mapped to
Gencode PRI assembly using featureCounts
75
. Transcripts per million (TPM) were computed in
RStudio. For sRNAseq, reads were aligned to the non-coding (nc)RNA (Ensembl
221
) and miRNAs
transcriptomes (miRBase v22.01
173
) using Bowtie
74
as well as miRGrepp
96
. Alignment parameters
are in Table 5.4.
Preliminary sRNAseq analysis showed that the LG of male NOD mice exhibited a
significantly higher percentage of total reads aligning to ncRNA (p = 0.01) in general (Figure 5.2
A), and mature miRNA specifically, relative to sRNA from LG of male BALB/c or female NOD
mice (Figure 5.2 B, C). This increase was unique to LG, and not to tears of the same mice
130
.
Comparison of Tapestation and sRNA BioAnalyzer (Agilent) electropherogram peaks of RNA
from male NOD LG IEF also revealed a higher percentage of small ncRNA and miRNA relative
to total RNA (Figure 5.2 E, F). We accounted for this confounder, which appeared due to
additional sRNA expression from infiltrating immune cells, by normalizing the data to miRNA
aligned reads and sequencing depth prior to analyzing dysregulated miRNA expression.
LG miRNAs in Murine Model of SS
Kakan SS, et al. [abstract] Arthritis & Rheumatology. 2022; 74 (suppl 9) 106

A

B

C D

E F

Figure 5.2 Overview of sRNAseq alignment to mouse genome and transcriptomes
(A) Number of reads aligned to non-coding RNA (ncRNA) as a percentage of total reads. B) Distribution
of reads aligning to various ncRNA subtypes. (C) Number of reads aligned to miRbase as a percentage
of total reads aligned using miRGrepp† or (D) as a percentage of filtered reads aligned using Bowtie†.
(E) Barplots showing small RNA (0-150 nt) and miRNA (15-30 nt) as a percentage of total RNA. (F)
Barplots showing miRNA as a percentage of small RNA in immune-enriched (IEF) and epithelial-
enriched fractions (EEF) isolated from LG of male NOD††.
†Boxplots with range; n=5 samples/group for male NOD and BALB/c and n=3 samples/group for NOD
female mice, *p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001, adjusted p values. one-way
ANOVA with Tukey’s-HSD for multiple comparison correction.
††Data are plotted as mean ± SEM; n=5 mice/group, paired t-test
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107
5.3.5 RT-qPCR
For miRNA RT-qPCR, 200 ng of total RNA was used for cDNA synthesis using miRCury
LNA RT kit (Qiagen #339340), and 1.3 ng of cDNA/sample was used for RT-qPCR using the
miRCury LNA SYBR green qPCR kit (Qiagen #339345) and mature miRNA primers (Qiagen
#339306). Normalization was done using spike-in controls, UniSp6 (Qiagen) and housekeeping
sRNA Snord68. For validation of IEF and EEF, mouse mRNA primers were purchased from
ThermoFisher Scientific. cDNA was synthesized from 1 µg of total RNA. 60 – 80 ng of cDNA
was used for RT-qPCR using Taqman reagents (Applied Biosystems, ). For mRNA primers, gene
expression was normalized to gapdh. Relative expression was calculated using the ΔΔCt method.
Primer catalog numbers are in Supplemental Table 2.
5.3.6 Pathway Analysis
miRNAs expressed in IEF or EEF with their respective log fold-change and adjusted p-
values obtained using DESeq2 (Table 1) were uploaded in IPA (Qiagen) and potential gene targets
obtained. Using these, pathway enrichment analysis was run in Metascape to identify ‘biological
processes’ or ‘pathways’ most likely to be affected by miRNAs and assessed further in IPA to
obtain predictions specific to pathway genes. For validation of IPA results, publicly available
mRNAseq datasets were obtained from ENA (PRJDB9749). These were generated by Ohno et
al.
215
from LG RNA from an in-house colony of male NOD mice pre-onset of dacryoadenitis (4
weeks, Pre DO) and post-onset of dacryoadenitis (10 weeks, Post DO), along with age- and sex-
matched BALB/c mice
215
.
LG miRNAs in Murine Model of SS
Kakan SS, et al. [abstract] Arthritis & Rheumatology. 2022; 74 (suppl 9) 108
5.3.7 Statistics
sRNAseq/mRNAseq data were analyzed by DESeq2 or EdgeR. Data with > 2 groups or
factors, and > 5 comparisons were analyzed using two-way ANOVA, with repeated measures
along rows (i.e., genes) for unpaired data; or along rows (i.e., genes) and columns (such as cell
populations, disease state) for paired data. Correction for multiple comparisons and q-values
(analogous to adjusted p-values) were calculated using the Benjamini-Hochberg fdr procedure in
RStudio or GraphPad v7.0a. Data with < 5 comparisons were corrected for multiple comparisons
with Tukey’s honestly significant difference test in RStudio or GraphPad and adjusted p-values
are reported.
5.4 Results
5.4.1 Differentially expressed miRNA in the male NOD LG
sRNAseq analysis was initiated with LG topically-stimulated with the acetylcholine
agonist, carbachol
159, 222
, which stimulates exocytosis of secretory vesicles containing
encapsulated sRNAs
223, 224
. The changes in stimulated tear miRNA expression in male NOD mice
were described previously
130
and LG from the same mice were utilized for sRNAseq herein. This
choice enabled us to identify and focus on miRNA species that were expressed and retained in the
LG, as well as to maximize the use of these mice. By 13 weeks, LG lymphocytic infiltration in the
contralateral LG of the same male NOD mice was ~8% of the total area of the LG
130
. This value
was significantly higher than age-matched female NOD or male BALB/c mice, both of which
exhibited no discernable infiltration
130
. Evaluation of miRNA expression differences showed that
stimulated NOD male LG expressed about 700 unique miRNAs compared to 614 in male BALB/c
(p adj=1.50 x 10
-6
) and 630 in female NOD mouse LG (padj=3.44x10
-5
) (Figure 5.3A).
Chapter 5

109
A

C

B

Figure 5.3 miRNA expression from sRNAseq of stimulated LG from NOD and BALB/c mice (A)
Boxplot of the number of unique miRNAs per group†. Red dots indicate the mean, while other dots
indicate the individual data points. (Constraints: At least 1 read detected per each miRNA per sample).
(B) Venn Diagram of common and distinct miRNAs in LG from male (M) NOD, M BALB/c and female
(F) NOD mice. (Constraints: miRNAs are detected in at least 50% of the biological replicates of a group).
(C) Barplot of the most highly-expressed miRNAs
††
in each strain.
†
One-way ANOVA with Tukey’s-
HSD for multiple correction. *** p adj < 10
-4
, **** p adj < 10
-5
.
††
Average DESeq2 normalized counts >10
4
;
error bars = Standard Error of Mean (SEM).

We identified 56 miRNAs in male NOD that were not expressed in male BALB/c or female
NOD mouse LG (Figure 5.3B), although many were of low abundance with normalized mean
expression of < 50 reads. Differential gene expression analysis using DESeq2 identified 28
miRNAs that were statistically significantly altered (p-value <0.05) in stimulated LG of male NOD
LG miRNAs in Murine Model of SS
Kakan SS, et al. [abstract] Arthritis & Rheumatology. 2022; 74 (suppl 9) 110
mice but had comparable expression in stimulated LG of male BALB/ or female NOD (Table 5.1).
Of these, we shortlisted miRNA ‘hits’ based on i) mean expression in male NOD LG > 1000
normalized read counts; ii) fold change >|2|; iii) comparable expression in LG of the two control
groups; and iv) >95% sequence similarity with the human miRNA homolog.
9 miRNAs were significantly upregulated (Figure 5.4A), and 5 miRNAs were significantly
downregulated (Figure 5.4B) in LG from male NOD as compared to LG of control groups. Some
of the most differentially expressed miRNA were also the most highly expressed in the LG (let-
7c-5p, miR-200c-3p, miR-375-3p and miR-150-5p) (Figure 5.3C). The 9 upregulated miRNAs
accounted for an average 8.03% of all mature miRNA reads detected in NOD LG but made up <
0.5% of all miRNAs detected in either male BALB/c or female NOD LG. The 5 downregulated
miRNAs accounted for > 15.5% of total mature miRNA reads in the control groups but made up
only 9.5% of all reads in male NOD LG.
5.4.2 Validating differentially expressed miRNA in male NOD LG
RT-qPCR was used to validate the 14 dysregulated miRNAs that met the defined criteria
in both stimulated and unstimulated LG of male NOD mice (Figure 5.5). The expression of the
miRNA ‘hits’ was validated by RT-qPCR in the original cDNA isolated from topically-stimulated
pooled LG from male NOD mice relative to strain controls. miRNAs miR-150-5p, miR-155-5p,
miR-142a-3p, miR-142a-5p, miR-10a-5p were significantly increased (p < 0.0001) in LG of NOD
male mice as compared to LG from male BALB/c or female NOD mice (Figure 5.5A). miR-148a-
5p, miR-200c-3p, miR-375-3p and let-7c-5p were likewise significantly decreased in LG of NOD
male (p < 0.001) (Figure 5.5B). miR-34a-5p and miR-365-3p did not amplify.
Chapter 5

111

Table 5.1 Differentially expressed miRNA in LG of male (M) NOD mice
NOD M v NOD F NOD M v BALB/c M

Upregulated
Mean
expression
Log FC
*
p adj Log FC
*
p adj
mmu-miR-155-5p
‡
5223.45 7.32 2.01 x 10
-35
5.67 4.11 x 10
-29

mmu-miR-150-3p
†
70.27 6.73 5.05 x 10
-11
5.62 5.59 x 10
-16

mmu-miR-150-5p
†
96238.23 5.89 1.46 x 10
-12
5.42 2.45 x 10
-14

mmu-miR-142a-3p
†
20094.31 5.26 3.52 x 10
-25
5.06 4.75 x 10
-31

mmu-miR-20b-5p
†
121.97 4.08 4.52 x 10
-10
3.94 5.40 x 10
-13

mmu-miR-142a-5p
†
4399.73 3.91 3.67 x 10
-12
3.84 9.65 x 10
-16

mmu-miR-10a-5p
†
1031.51 4.41 9.70 x 10
-13
3.77 5.96 x 10
-13

mmu-miR-146a-5p
†
48476.01 3.59 2.21 x 10
-8
3.18 9.10 x 10
-9

mmu-miR-342-3p
†
7734.90 5.09 3.08 x 10
-19
2.57 9.81 x 10
-7

mmu-miR-15b-3p
†
480.58 2.78 1.13 x 10
-6
2.21 1.26 x 10
-5

mmu-miR-139-5p
‡
287.63 2.01 1.30 x 10
-3
2.19 3.67 x 10
-5

mmu-miR-503-5p
‡
69.91 1.92 4.50 x 10
-3
1.93 8.29 x 10
-4

mmu-miR-146b-5p
†
2999.26 1.78 4.50 x 10
-3
1.81 6.11 x 10
-4

mmu-miR-140-3p
||
12829.58 1.84 7.41 x 10
-3
1.76 2.88 x 10
-3

mmu-miR-34a-5p
†
7486.75 1.46 2.52 x 10
-2
1.59 4.33 x 10
-3

Downregulated
mmu-miR-148a-5p
†
1566.02 -1.64 9.85 x 10
-3
-1.78 8.70 x 10
-4

mmu-let-7b-3p
†
102.22 -2.60 5.91 x 10
-7
-1.66 7.08 x 10
-4

mmu-miR-365-3p
†
13953.80 -1.69 7.60 x 10
-3
-1.51 6.32 x 10
-3

mmu-miR-132-3p
†
314.05 -1.75 4.67 x 10
-3
-1.48 6.70 x 10
-3

mmu-miR-709
§
163.07 -1.18 1.11 x 10
-1
-1.46 1.65 x 10
-2

mmu-miR-200c-3p
†
132824.66 -1.48 2.38 x 10
-2
-1.44 1.06 x 10
-2

mmu-miR-182-5p
§
9259.79 -1.56 1.54 x 10
-2
-1.44 1.03 x 10
-2

mmu-miR-200b-5p
†
3981.54 -2.09 6.46 x 10
-4
-1.40 1.32 x 10
-2

mmu-miR-152-5p
‡
390.75 -1.68 1.13 x 10
-2
-1.37 1.95 x 10
-2

mmu-miR-30c-2-3p
†
870.93 -1.60 9.17 x 10
-3
-1.33 1.43 x 10
-2

mmu-miR-676-3p
||
4039.82 -1.77 4.67 x 10
-3
-1.33 1.86 x 10
-2

mmu-let-7c-5p
†
584719.04 -1.05 1.27 x 10
-1
-1.27 2.46 x 10
-2

mmu-miR-375-3p
†
136305.12 -2.23 2.64 x 10
-4
-0.93 1.28 x 10
-1

miRNA, in bold were validated by qRT-PCR; all mice were aged 13 weeks
* DESeq2 Log2 fold-changes and adjusted p values; miRNAs are ordered by their L2FC from the NOD
M v BALB/c M comparison.
†100%, ‡ > 95%, || 90-95% or § 85-90% sequence similarity between human and mouse miRNA
LG miRNAs in Murine Model of SS
Kakan SS, et al. [abstract] Arthritis & Rheumatology. 2022; 74 (suppl 9) 112

In additional samples from unstimulated male NOD mouse LG relative to unstimulated
male BALB/c mouse LG, we validated the upregulation of miR-150-5p, miR-155-5p, miR-142a-
3p, while miR-146b-5p was modestly but not significantly increased (Figure 5.6A). miR-148a-
5p, miR-365-3p, miR-200c-3p, miR-375-3p and let-7c-5p were significantly decreased in LG of
A Upregulated

B Downregulated

Figure 5.4 Dysregulated miRNAs in LG from male NOD mice.
miRNA that are (A) upregulated or (B) downregulated in LG from 13 week diseased male NOD mice
relative to disease-free LG of age-matched female NOD and male BALB/c mice. . Data are plotted as
Log10 normalized miRNA counts as calculated by DESeq2 for each group. N=5 samples for male NOD
and BALB/c and N=3 samples for female NOD mice; n=1 LG from each of 5 mice per sample. miRNA
were considered differentially expressed if they were up- or down-regulated in the male NOD vs male
BALB/c comparison as well as in the male NOD vs female NOD comparison; had a mean expression
value of 1000 or higher; had a significant unadjusted p value in at least one of the two comparisons; and
showed a >95% sequence similarity with human miRNA. (*p< 5 x 10
-2
, **p< 10
-3
, *** p < 10
-4
, **** p
< 10
-5
, Adjusted p values - DESeq2).
Chapter 5

113
male NOD mice (p<0.01) (Figure 5.6B). miR-34a-5p was significantly decreased in male NOD
LG (Figure 5.6B), as opposed to its apparent upregulation estimated by sRNAseq.

A Upregulated

B Downregulated

Figure 5.5 RT-qPCR validation of miRNAs in topically-stimulated LG.
Barplots show log2 fold-change in miRNA that are either (A) upregulated or (B) downregulated in 13-
week male NOD mouse LG relative to LG from age-matched male BALB/c or female NOD mice. LG
tissues were topically-stimulated with carbachol to discharge tear fluid prior to collection.
n=5 mice/group; data are plotted as mean ± SEM. one-way ANOVA with false discovery rate for multiple
comparisons correction. * q < 0.05, ** q < 0.01, *** q < 0.001, **** q < 0.0001
.
LG miRNAs in Murine Model of SS
Kakan SS, et al. [abstract] Arthritis & Rheumatology. 2022; 74 (suppl 9) 114
5.4.3 Influence of lymphocytic infiltration on differentially expressed miRNA
Given the large number of miRNAs detected in male NOD mouse LG compared to controls
(Figure 5.2B), we surmised that infiltrating lymphocytes might contribute to the miRNA milieu.
To test this, we separated cells from male NOD mouse LG into immune cell-enriched fractions
(IEF) and epithelial cell-enriched fractions (EEF). RT-qPCR was used to probe expression of
specific markers of immune and epithelial cells, finding the epithelial-specific aquaporin 5
20, 124,
125
and Rab3D
124, 125
to be significantly expressed in EEF and immune-enriched genes
124, 125
IL-4,
IL-12A, IL-17A and IL17R to be significantly expressed in IEF (Figure 5.1B). LG and SG
A Upregulated

B Downregulated

Figure 5.6 RT-qPCR validation of miRNA changes in unstimulated LG.
Barplots showing log2 fold change in miRNA that are either (A) upregulated or (B) downregulated in
unstimulated LG from 13-week male NOD mice relative to unstimulated LG from age-matched male
BALB/c mice. miRNA Ct values were normalized to the endogenous control, snord68; ΔCt values for a
given miRNA were then normalized to average ΔCt of that miRNA’s expression in the healthy control
group (male BALB/c). (Data are plotted as mean ± SEM. n=3 LG from 3 mice/strain, * q < 0.05, ** q <
0.01, *** q < 0.001, **** q < 0.0001, two-way ANOVA with fdr controlled at q=0.05 for multiple
comparisons correction.)
Chapter 5

115
epithelia can express cytokines and cytokine receptors in autoimmune dacryoadenitis and
sialadenitis, explaining the low expression of some immune-enriched genes in EEF. Using RT-
qPCR, we found that miR-150-5p, miR-155-5p, miR-142a-3p, miR-142a-5p, miR-10a-5p, miR-
146a-5p and miR-342-3p were highly expressed in IEF, suggesting their enrichment in infiltrating
immune cells (Figure 5.7A). miR-148a-5p, miR-365-3p, miR-200c-3p, and miR-375-3p were
more highly expressed in EEF (Figure 5.7B), suggesting that their depletion in male NOD mouse
A Upregulated in IEF

B Downregulated in IEF

Figure 5.7 miRNA expression in immune-enriched (IEF) and epithelia-enriched (EEF) cell
fractions from male NOD mouse LG.
Barplots comparing log2 relative expression of miRNAs that are either (A) upregulated or (B)
downregulated in IEF of 13-week male NOD mice relative to their expression in EEF. Ct values were
normalized to the endogenous control, snord68; ΔCt values for IEF were then normalized to average ΔCt
of the EEF. (n=5 mice/group, data are plotted as mean log2 fold change ± SEM. *q < 0.05, **q < 0.01,
***q < 0.001, ****q < 0.0001. ANOVA with repeated measures and fdr (q) controlled at 0.05 for
multiple comparisons correction).
LG miRNAs in Murine Model of SS
Kakan SS, et al. [abstract] Arthritis & Rheumatology. 2022; 74 (suppl 9) 116
LG could be due to loss or altered functioning of epithelia. miR-146b-5p showed only a modest
increase in IEF while let-7c-5p and miR-34a-5p showed no cell type specificity in expression.
5.4.4 IPA Analysis
IPA identified 584 experimentally validated gene targets of IEF miRNA ‘hits’ (i.e., dysregulated
miRNA in immune cells from male NOD mouse LG). Pathway enrichment analysis on these genes
using Metascape indicated that 85 genes belong to the biological processes (BP) ‘Regulation of
Cytokine Production’, predicting it to be the most likely BP affected by dysregulated miRNAs
(padj=10
-23
). Among the cytokines, ‘Regulation of IL-6 production’ was predicted to be the most
likely to be affected (padj=10
-10
) (Figure 5.8). IPA identified 32 genes in the IL-6 signaling
pathway targeted by IEF miRNA ‘hits’. In IEF, upregulated miR-155-5p can target SOCS1/3,
resulting in near-constitutive activation of JAK2/STAT3 & MAPK/ERK pathways (Figure 5.9A).
Downregulated miRNAs target expression of receptors including IL-6RA (miR-34a-5p),
gp130/IL-6ST (let-7c-5p, miR-34a-5p) and its effectors SOS and Ras (let-7c-5p). RT-qPCR of
total RNA from LG verified that gene expression of gp130/IL6ST is significantly increased in
male NOD mouse LG (Figure 5.9B). In EEF, downregulated miRNAs, miR-148a-3p, and miR-
200c-3p, were predicted to affect signaling of IL-6 and IL-6-like cytokines (IL-11, LIF, OSM,
CNTF, CLC and CT1) and to upregulate the JAK2/STAT1 pathway (Figure 5.10A).
Bioinformatics analysis of publicly deposited mRNA-Seq data from Ohno Y et. al.
215

(GEO GSE81621) in male NOD mouse LG before and after onset of autoimmune dacryoadenitis
verified that several genes from this pathway (e.g., IL6ST, STAT1 and JAK2) were significantly
upregulated after the onset of autoimmune dacryoadenitis symptoms (Figure 5.10B, Table 5.2)
supporting the predicted effects of dysregulated miRNAs by IPA.

Chapter 5

117
5.5 Discussion
While miRNA involvement in SS-associated SG disease
174, 183, 225-228
and systemic
autoimmunity
180, 183
has been investigated, their role in SS-associated LG disease is understudied.
Here we present the miRNAome from the LG of the male NOD mouse and identify species
dysregulated in parallel with development of autoimmune dacryoadenitis. For initial NGS
sequencing, we identified dysregulated species relative to healthy sex-matched and strain-specific
controls, while subsequent validation and expansion studies with RT-qPCR used sex-matched
healthy control male BALB/c mice.

Figure 5.8 Pathway Enrichment Analysis of predicted gene targets of IEF miRNAs.
Top 15 clusters with their representative enriched terms (one per cluster). For each cluster, n= the number
of genes (indicated in panel in white) targeted by miRNA ‘hits’ with me membership in the given
ontology term. "Log10(q)" is the multi-test adjusted p-value in log base 10. GO – Gene Ontology
LG miRNAs in Murine Model of SS
Kakan SS, et al. [abstract] Arthritis & Rheumatology. 2022; 74 (suppl 9) 118

A

B

Figure 5.9 miRNAs targeting IL-6 signaling are dysregulated in male NOD LG IEF.
(A) Arrows indicate direction of miRNA change. (Created in BioRender) (B) RT-qPCR confirmation of
gene expression changes in gp130, an IL-6 coreceptor, in male NOD relative to male BALB/c mouse LG.
(n=3 LG from 3 separate mice, data are plotted as mean fold change ± SEM, *p= 0.05, unpaired t-test)
Chapter 5

119
9 high-expression miRNAs were significantly upregulated in male NOD mouse LG, 7 of which
were validated by RT-qPCR; while 5 high-expression miRNAs were significantly downregulated
in male NOD mouse LG, all of which were validated by RT-qPCR.
Some of our identified miRNAs have been reported as dysregulated in tissues from SS
patients or SS animal models. sRNAseq of LG in an SS rabbit model found miRNAs miR-150-5p,
miR-142-3p, and miR-142-5p to be significantly upregulated
176
. A microarray comparing
expression of 534 human and viral miRNAs from minor SG of SS patients vs healthy controls also
found miR-150-5p, miR-155-5p, miR-142a-3p, miR-142a-5p, miR-10a-5p, miR-342-3p, and miR-
146b-5p to be significantly upregulated and miRNAs miR-148a-5p, miR-200c-3p, and miR-375-
3p significantly downregulated
174
. However, our finding of downregulated miR-365-3p in the LG
with disease is a novel finding in the context of SS.
To delineate the cellular origin of the dysregulated miRNAs, we isolated LG cells into IEF
and EEF. RT-qPCR analysis showed that all 7 validated upregulated miRNAs from Figure 5.6
showed high expression in IEFs; conversely, 4 of 5 validated downregulated miRNAs from Figure
5.6 were more highly expressed in EEF and minimally expressed in IEF. Thus, upregulation of
most miRNAs in male NOD mouse LG appears due to their expression by infiltrating immune
cells, whereas the epithelial cell specificity of most downregulated miRNAs suggests either a
decrease in epithelial cells or altered epithelial cell function with disease. Consistent with our
findings, miR-200b-5p is expressed in SS patient-derived SG epithelial cells but not in PBMC
183

and miR-375-3p expression is epithelial-specific and not detected in immune cells
229
. miR-146a
was previously reported as increased in both LG and SG from the NOD.Aec1Aec2 mouse model
of SS
180
and in PBMC of SS patients
178-180
.

LG miRNAs in Murine Model of SS
Kakan SS, et al. [abstract] Arthritis & Rheumatology. 2022; 74 (suppl 9) 120
A
IL6-Like Cytokine Signaling

Figure 5.10 Dysregulated miRNAs target IL-6-like cytokines and their downstream effectors in EEF.
(A) IL-6-like cytokine signaling pathway with gene expression as predicted by IPA due to the presence of
dysregulated miRNA in EEF. Color coded genes in orange are IPAs estimated predictions with color
saturation proportional to the intensity of predicted upregulation. (B) Heatmap showing levels of gene
expression in LG of NOD male mice before (Pre-dacryoadenitis onset, DO) and after onset of
dacryoadenitis (Post DO) as compared to LG of age and sex matched BALB/c. (Bulk-RNA Seq Data
generated by Ohno Y et. al. and raw data obtained from ENA Accession PRJDB9749
215
).
Chapter 5

121
Of the upregulated miRNAs in our study, miR-142a-5p, a lymphoid tissue specific
miRNA
230
, miR-200b and let-7b are predicted to target expression of SS autoantigens - Ro/SSA
(both TRIM21 and TROVE2 subunits) and La/SSB
183, 231
. Serum autoantibodies against these
antigens constitute diagnostic biomarkers for SS
154
. Additionally, gene transcripts for Rgs16 and
ccl22, part of the IL-17 pathway, are upregulated in Post DO male NOD LG from data deposited
by Ohno et. al.
215
Rgs16 is involved in autoantibody production and is targeted by let-7c. Thus,
downregulation of miR-200b-3p and let-7c could increase expression of Ro/SSA and La/SSB,
increasing their propensity to elicit an autoantibody response.
Several IEF-specific upregulated miRNAs were also significantly increased in tears of
male NOD mice relative to strain controls – miR-142-5p (FC=2.5, p=0.017, DESEq2) and miR-
155-5p (FC=1.4, p=0.012, DESEq2). As well, the EEF-specific downregulated miRNA – miR-
200c-3p – was also significantly decreased in tears of male NOD mice relative to strain controls
(FC=-1.3 p=0.04). Let-7c-5p was the most abundant miRNA in tears and LG overall; concurrent
with its decreased abundance in male NOD LG, it was also significantly decreased (FC=-1.45,
p=0.01) in tears of male NOD mice compared to tears of male BALB/c. These relationships
suggest these miRNAs may reach the tear film through acinar endocytic uptake and transcytotic
transport from the LG interstitium where they are secreted by the cells of origin. However, some
upregulated LG miRNAs from this study are significantly decreased in tears of male NOD mice -
miR-342-3p (FC=-3.06, p=10
-7
), miR-146a-5p (FC=-1.74, p=0.001), and miR-322-5p (FC=-1.6,
p=0.04)-compared to tears of male BALB/c mice, indicating an inverse relationship.
The major cytokine pathway predicted as targeted by dysregulated miRNAs is that
mediated by IL-6. IL-6 has pro- and anti-inflammatory effects, with the former elicited through
the trans-pathway via soluble IL-6Ra (sIL-6Ra), and the latter via membrane-bound
LG miRNAs in Murine Model of SS
Kakan SS, et al. [abstract] Arthritis & Rheumatology. 2022; 74 (suppl 9) 122

Table 5.2 Comparison of mRNAseq expression analysis of genes from the IL6-like
cytokine signaling pathway
Gene Symbol
Male NOD vs BALB/c
t statistic (p adj)
Pre –DO
†
Post –DO
†

il6st (gp130) 0.38 (0.55) 2.52 (0.050)
il6ra 0.19 (0.53) 2.24 (0.041)
clcf1 0.008 (0.54) 2.53 (0.013)
crlf1 2.33 (0.023) 2.72 (0.011)
il11ra2 2.83 (0.0031) 2.90 (0.0031)
lifr 0.48 (0.83) 1.24 (0.83)
adam10 0.65 (0.45) 2.73 (0.030)
jak2 0.0035 (0.54) 4.29 (< 0.0001)
stat1 0.518 (0.33) 8.538 (< 0.0001)
tgfb1 0.042 (0.53) 4.109 (0.0002)
il10 0.06 (0.99) 1.24 (0.54)
mcl1 0.49 (0.57) 2.78 (0.033)
timp1 1.11 (0.28) 3.86 (0.0034)
jun 1.57 (0.051) 4.38 (< 0.0001)
irf1 0.33 (0.49) 7.15 (< 0.0001)
fos 1.11 (0.25) 2.75 (0.014)
serpina1a
(alpha1 antitrypsin)
1.35 (0.14) 5.93 (< 0.0001)
serpina1b
(beta1 antitrypsin)
1.38 (0.13) 7.13 (< 0.0001)
†Dacryoadenitis onset, DO. Values from male NOD mice were normalized to those in age-
matched male BALB/c mice. Pre-DO mice were aged 4 weeks while post-DO mice were aged 10
weeks. Data were analyzed by two-way ANOVA, with fdr controlled at 0.05 for multiple
comparison correction (EdgeR). t-statistic is reflective of fold-change.
*Bulk-RNA Seq Data generated by Ohno Y et. al. and raw data obtained from ENA Accession
PRJDB974928
Chapter 5

123
gp130-IL-6Ra complex
232
. IL-6Ra is present largely on immune cells, whereas gp130 is more
ubiquitously expressed
124, 125, 233, 234
including in epithelia, and is also involved in IL-6-like
cytokine signaling
235
(Figure 5.10A). A different milieu of dysregulated miRNAs in immune
versus epithelia cells may differentially affect components of the IL-6 and IL-6-like pathways.
Downregulation of key miRNAs that target il6 and il6ra may make the pro-inflammatory IL-6
pathway more dominant in epithelial and immune cells. Previous use of tocilizumab (humanized
IL-6Ra recombinant antibody) was not successful in SS patients
236
. This could be due to its non-
specific and dual targeting of soluble and membrane-bound IL-6Ra. It is possible that selective
targeting of the trans-pathway to sequester sIL-6Ra and the sIL6Ra-il6 complex
233
, with a
recombinant soluble gp130-Fc protein (such as Olamkicept
237
) may have more utility in SS,
particularly if locally administered.
Table 5.3 Catalog numbers of mouse qPCR primers
Name Assay ID #
mRNA
Il-6st (gp130)
Thermo Fisher Scientific
Applied Biosystems
Catalog # 4331182
Mm00439665_m1
Il-17a Mm00439618_m1
Il-12a Mm00434165_m1
Il-4 Mm00445259_m1
Gapdh Mm99999915_g1
Aqp5 Mm00437578_m1
Il-17Ra Mm00434214_m1

LG miRNAs in Murine Model of SS
Kakan SS, et al. [abstract] Arthritis & Rheumatology. 2022; 74 (suppl 9) 124
Table 5.4 mRNAseq, sRNAseq and IPA alignment parameters
mRNAseq
Download https://www.ebi.ac.uk/ena/browser/view/PRJDB9749?show=reads
Fastp v 0.23.2

fastp -e 25 --detect_adapter_for_pe -c -i $data/DRR225264_1.fastq.gz -
I $data/DRR225264_2.fastq.gz -o $out/10WB1.R1.fastq.gz -O
$out/10WB1.R2.fastq.gz -3 -5
STAR v 2.7.10a STAR --runThreadN 16 --runMode genomeGenerate --genomeDir $dir
--genomeFastaFiles $genome --sjdbGTFfile $annot --sjdbOverhang 99
STAR
GRCm39
(GENCODE)
v 2.7.10a STAR --runThreadN 8 --genomeDir $dir --readFilesCommand gunzip -
c --readFilesIn ~/path/to/input.R1.fastq.gz ~/path/to/input.R2.fastq.gz --
-outFileNamePrefix ~/path/to/output/10WB1
featureCounts
(Subread)
v 2.0.0 featureCounts -J -C -s 0 -T 8 -M -p -d 15 -D 1000 -O -a $annot -g
gene_name -o $output/Counts.txt $input/*sam
sRNAseq
FastP adapter.fasta
file

v 0.23.2
>Illumina TruSeq Adapter Read 1
AGATCGGAAGAGCACACGTCTGAACTCCAGTCA
>Illumina Universal Adapter
AGATCGGAAGAG
>Qiaseq miRNA library kit 3 primer
AACTGTAGGCACCATCAAT
>Illumina Small RNA 3 Adapter
TGGAATTCTCGG
>Qiaseq miRNA library kit 5 primer
GTTCAGAGTTCTACAGTCCGACGATC
>polyA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
fastp -e 25 -i $data/file.fastq -o $out/file.fastq -l 15
--adapter_fasta=adapter.fasta -p
bowtie
GRCm39
Comprehensive
annotation
PRI
bowtie-build --threads 16 -f ~/path/to/dir/fasta.fa mm10
bowtie
(GENCODE)
bowtie --threads 16 -v 3 -y -k 1 --best --chunkmbs 128
~/path/to/index -q -S ~/path/to/file.fastq ~/path/to/output.sam
featureCounts subread-2.0.0 featureCounts -p -T 8 -a $annot -g gene_name -o $output/trial.txt
$input/*.sam
bowtie
(ncRNA)
bowtie-build ~/path/to/mouse_ncRNA.fasta ~/path/to/bowtie1_index
Chapter 5

125
bowtie --threads 16 -n 3 -l 18 -y --best --strata --chunkmbs 2048 -3 4 -5 4 -k 3 -e 280
$ref/ncRNA -q $data/001cut.fastq -S cut001.sam
sam2Counts v 0.91 python ~/path/to/dir/sam2counts.py ncRNA/aligned/*sam
miRGrepp ./miRGrep.py FASTA FASTQ n > output.txt
Pathway
Analysis
(IPA)
- IEF or EEF miRNA with their respective log fold-change and adjusted p-values obtained
using DESeq2 (Table 1) were uploaded in Ingenuity Pathway Analysis (IPA, Qiagen).
- Potential gene targets of miRNA were obtained using the ‘microRNA Target Filter’
module and shortlisted to ‘experimentally validated’ genes.
- Using these shortlisted gene targets, pathway enrichment analysis was run in Metascape to
identify enriched Gene Ontology (GO) ‘biological processes’ or KEGG ‘pathways’ most
likely to be affected by these miRNAs, using an established hypergeometric test coupled
with a Benjamini-Hochberg p-value correction algorithm.
- Biological Processes/Pathways identified here were further assessed in IPAs ‘My
Pathways’ module, by overlaying miRNA datasets using the ‘Overlay’ tool.
- Predictions specific to the pathway genes were obtained by the ‘Build -> grow’ tool with
‘Direct’ interactions of miRNA-miRNA and targeting confidence restricted to
‘Experimentally Validated’ and ‘Predicted’
- Figure 5.10A was plotted using ‘Path Designer’ tool of the ‘My Pathways’ module, with
edits to font only. Color coded predictions generated in previous for each gene were kept
intact in ‘Path Designer’

Acknowledgements: This research was supported by National Institutes of Health funding from
the National Eye Institute, grant EY011386 to SHA. The research reported in this publication was
also supported by P30EY029220 from the National Eye Institute and P30CA014089 from the
National Cancer Institute. The content is solely the responsibility of the authors and does not
necessarily represent the official views of the National Institutes of Health. An unrestricted Grant
to the Department of Ophthalmology from Research to Prevent Blindness, New York, NY, also
supported this research. Finally, the authors acknowledge the support of the Translational Research
Laboratory at the USC School of Pharmacy

126
Chapter 6 Serum and Tear Autoantibodies from NOR mice
as Potential Diagnostic Indicators of Local and Systemic
Inflammation in Sjögren’s Syndrome
^

Kakan SS, Ju Y, Edman MC, Hamm-Alvarez SH. Serum and Tear Autoantibodies from nor Mice as
Potential Diagnostic Indicators of Local and Systemic Inflammation in Sjögren’s Syndrome [abstract].
Arthritis Rheumatol. 2022; 74 (suppl 9).
Keywords: Animal Model, Autoantibody(ies), autoantigens, Biomarkers, Sjögren's Syndrome
^ Note: This chapter is taken from the previously mentioned abstract.
6.1 Introduction
Sjögren’s Syndrome (SS) is an autoimmune disease characterized by infiltration of
lymphocytes into lacrimal (LG) and salivary (SG) glands and their concurrent loss of tear and
saliva production, respectively, as well as the development of systemic symptoms. Diagnosis of
SS takes ~3 years, due in part to manifestation of symptoms that overlap with other autoimmune
diseases. Ro/SSA (and previously, ANA and La/SSB) serum autoantibodies, currently utilized for
diagnosis, are only present in 50-60% of SS patients and are also detected in patients with systemic
lupus erythematosus and rheumatoid arthritis. As the LG is specifically affected in SS, leading to
established changes in tear composition, we hypothesized that the presence of tear
autoantibodies may also aid in distinguishing SS from other autoimmune diseases. Here, we
have used two SS mouse models, the male NOD (non-obese diabetic) and the male NOR/Ltj (non-
obese diabetes resistant, alternative to NOD) to investigate the changes in IgG autoantibody
composition of tear fluid and serum for an array of autoantigens, relative to sex- and age-matched
healthy control BALB/c mice.
Chapter 6
Kakan SS, et al. [abstract] Arthritis Rheumatol. 2022; 74 (suppl 9)
127
The NOD mice develop autoimmune dacryoadenitis at about 6-8 weeks, whereas the NOR,
which is a NOD-related MHC-syngeneic strain, have a later onset of dacryoadenitis at about 14-
16 weeks. Though the NOD is the most established model for SS, the eventual development of
diabetes beyond 20 weeks is a confounder for studying SS, which the diabetes resistant NOR
model obviates.
6.2 Methods
Serum samples were collected from 16-week-old male NOR (n=6), and age and sex-
matched healthy BALB/c mice (n=3). Pooled tears were collected from the same mice following
in situ topical carbachol stimulation of LG. Additional serum samples were collected from 8-week
and 24-week male NOD mice (n=3) and age-matched healthy male BALB/c mice (n=3). Tears and
serum were screened for IgG/IgM reactivity against a panel of 128 autoantigens at the UT
Southwestern Microarray Core Facility, Dallas, TX. Instrument normalized data was analyzed in
RStudio and data points having a signal to noise ratio (SNR) < 3 were excluded from the
analysis
238
.
6.3 Results
Total IgG antibodies were 2.3 and 1.96-fold elevated in serum and tears, respectively, of
NOR mice (padj<0.05). IgG autoantibodies against Pm/Scl-100 (10.8-fold, p= 2.6 x10
-5
), La/SSB
(9.7-fold, p= 2.5 x10
-5
), PL-7 (6.8-fold, p= 0.01) and PCNA (4.4-fold, p= 0.04) were significantly
elevated in serum of NOR mice relative to healthy BALB/c. Interestingly, IgG autoantibodies
against the same autoantigens were also significantly increased in serum of male NOD mice. On
the other hand, IgG autoantibodies against Jo-1 (25.2-fold, p = 2.4x10
-3
), β-2 glycoprotein (28.5-
fold, p=8.6x10
-3
), complements C6 & C7, and EBNA1 were significantly increased tears of NOR
Tear Autoantibodies in SS model
Kakan SS, et al. [abstract] Arthritis & Rheumatology. 2022; 74 (suppl 9) 128
mice but remained unchanged in serum of the same mice relative to BALB/c. While no changes
were detected in IgM immunoreactivity for any of the antigens in serum of NOR mice, IgM
autoantibodies against Thyroid Peroxidase (TPO) (13.8-fold, p= 4.2x10
-4
) and Histone H4 (3.5-
fold, p =1.7x10
-6
) were significantly elevated in tears of NOR mice.
6.4 Conclusion
Tears of male NOR mouse, a model of SS, have autoantibody profiles distinct from serum
and may reflect local inflammation in the LG occurring independent of and/or prior to systemic
inflammation. Additionally, four serum autoantibodies found elevated in male NOR mice were
validated in the male NOD mice. Further investigation of these autoantibodies is necessary in tears
of SS patients.

Figure 6.1 Serum IgG autoantibodies in male NOR (above) and male NOD (below) mice.La/SSB,
Sjögren’s Syndrome Antigen B; PM/Scl-100, Polymyositis/Systemic Sclerosis Antigen 100; PL-7, anti-
threonyl-tRNAsynthetase-7; PCNA - Proliferating Cell Nuclear Antigen; (ns – not significant, * p < 0.010,
** p < 0.005, *** p < 10
-3
, **** p < 10
-4
, moderated t-tests and a priori contrasts computed using the R
Package limma, alpha value=0.01 as described previously
238
)

Chapter 6
Kakan SS, et al. [abstract] Arthritis Rheumatol. 2022; 74 (suppl 9)
129

Figure 6.2 Tear specific IgG autoantibodies in male NOR mice. (ns – not significant, * p < 0.010, ** p
< 10-3, moderated t-tests and a priori contrasts computed using linear model for series of array (limma) R
package, alpha value=0.010).

Acknowledgements: This work was funded by the NIH National Eye Institute grant RO1
EY011386 to SHA.

130
Chapter 7 Conclusions

Sjogren's syndrome (SS) disproportionately affects women as 90% of SS patients are
women. its prevalence is growing, especially among relatively younger people such as Serena
Williams. For a long time in the late 18
th
and early 19
th
century patients presenting with what we
now know to meet SS symptoms were dismissed as hysteria. This is also true for several other
autoimmune diseases. Due to this, SS research has suffered both in terms of diagnostics and disease
modifying treatments. Though significant progress has been made in the last 20 years, SS
diagnostics remain cumbersome, and heavily favors SG disease over LG disease. This body of
work is an effort in large part to improve SS diagnostics and, to a lesser extent, further our
understanding the disease pathophysiology of the LG disease in SS.
7.1 Summary of overall findings
I used mouse models of SS to identify several serum exosomal miRNAs, tear miRNAs as
well as serum and tear autoantibodies with diagnostic potential. Chapter 2 describes how we use
the male NOD mouse model to identify candidate miRNAs enclosed in serum Exosomes. In theory
dysregulated trafficking of secretory vesicles in the male NOD LG acini, particularly the increase
of vesicles on the basolateral side could increase the concentration of acinar Exosomes in NOD
mouse serum. The contents of these Exosomes could then provide diagnostic utility and would be
very specific to the diseased LG. Assessing serum Exosomes versus whole serum would have the
advantage of enriching the disease associated markers in the exosomal fraction, thus making them
easier to detect by conventional methods. I have identified 6 miRNAs that are over-expressed in
the male NOD and successfully validated 5 of these in serum exosomes – miR-127-3p, miR-409-
Chapter 7

131
5p, miR-410-5p, miR-540-5p - in a separate mouse cohort by RT-PCR. Chapter 3 reported on the
identification of miRNAs dysregulated in tears and LG of the male RAB3D knockout mice model
which exhibits some of the defective vesicular trafficking observed in SS. Interestingly in this
model, we see some of the elevated NOD serum exosomal miRNAs – miR-127-3p – being
differentially expressed in LG of RAB3DKO mice, hinting that dysregulated trafficking
alternatively in the disease model. MiRNA miR-486a-5p, which constituted 20% of the total
miRNA in serum exosomes was increased in tears of RAB3DKO mice.
In Chapter 4, I have discussed how the current EULAR/ACR diagnostic criteria lacks an
analytical test for the LG, as it is dangerous to biopsy the gland. Fortunately, tears provide an
excellent alternative as 80% of their constituents come from the LG. I have identified 14 miRNAs
in tears of male NODs that are dysregulated when compared to the tears of healthy BALB/c and
female NOD mice and validated eight of them in additional mice cohorts. Most excitingly, I found
that in a small cohort of human subjects, three out of the eight candidate miRNAs – miR-203-3p,
miR-181a-5p and miR-181b-5p – could distinguish SS-associated autoimmune dry-eye patients
from non-autoimmune aqueous deficient dry-eye from Meibomian gland disease (MGD) patients
relative to internal controls miR-93-5p and miR-25-3p.
Upon analysis of tears of SS patients, I observed that the total tear RNA amount (in ng)
was significantly increased when compared to tear RNA of patients with non-autoimmune dry-eye
(MGD). When normalized to tear volume (in mm), this increase was more profound in SS patients
and their average tear volume was lower that of MGD patients. I suspect this is due to
autoimmunity in LG, in which case it could also serve as a biomarker. It remains to be seen how
tear RNA amount per unit tear volume of SS patients compares with tears of healthy controls
or patients with lupus or rheumatoid arthritis. This finding will have to be reproduced with a larger
Conclusion
132
number of patients to determine whether this observation is unique to SS or not. It is also possible
that specific species of miRNA or other non-coding RNA are driving this increase in RNA amount.
This should be investigated by comparing Tapestation and small RNA BioAnalyzer traces side-by
side. In any case, tear RNA amount per unit tear volume (ng/uL) is a potential candidate biomarker
of LG disease that should be investigated further.
Chapter 5 described how the miRNA transcriptome is greatly altered in male NOD mouse
LG after the onset of autoimmune dacryoadenitis. Upregulated miRNAs in male NOD LG are
largely implicated in cytokine signaling and are expressed in infiltrating immune cells while
downregulated miRNAs are largely expressed in epithelial cells. It is important to note that miR-
181a-5p (↑ in NOD (M) tears) , miR-7a-5p, miR-148a-3p (↓ in (M) NOD LG) are the top 20 highly
abundant miRNA in NOD and BALB/c mouse serum exosomes. It is possible that the changes
observed in tears or LG of the male NOD are unique to the lacrimal apparatus.
7.2 Limitations
The study in chapter 2 employed an equal RNA amount comparison of individual miRNA.
In the future, studies should also look at an equal volume comparison or consider comparing
absolute values of tear RNA amount in ug. The study in chapter 4 utilized internal controls miR-
93-5p and miR-25-3p for the qPCR validation of miRNA ‘hits’ in tears of mice as well as human
subjects. While we did not observe any difference in the expression of these internal controls in
patient tears, a more stringent assessment of endogenous controls is necessary, particularly in
healthy control.
One short coming of our exosomes study from chapter 2 was the extremely low input RNA
used for our initial sRNAseq. This was partly due to the limit of blood volume obtained from mice,
and the relatively lower blood concentration of exosomes in mice and partly due to
Chapter 7

133
ultracentrifugation. Since doing the study, we have optimized our exosomes isolation protocols
and improved yield significantly. Another challenge, at least at the time of publication was
translating exosomes isolation based diagnostic strategies in the clinic. There would be a)
substantial batch to batch variation, b) the need for highly skilled laboratory technicians, c) issues
with sample storage and transportation due to the structural stability issues of exosomes and
difficulty in keeping costs low.
However, interest in the use of exosomes as therapeutics has propelled technological
advancements to control batch to batch variations arising from isolation methods. Simplified one-
pot methods for exosomes isolation are being developed. New instruments that combine isolation
with biochemical assessment of exosomes and could obviate the need for specialized technicians
and cut down costs are also in the pipeline. These developments can potentially address several of
the challenges and make exosome-based diagnostics feasible in the clinic.
7.3 Future directions
To validate the findings from Chapter 2 in the clinic, future efforts will focus on exosome
isolation from freshly drawn blood samples from SS patients and healthy control subjects,
followed by a blinded qRT-PCR assessment comparing equal volumes as well as equal RNA
amounts of exosomes. So far, we have tested several banked frozen serum samples of SS patients
for these miRNAs (unpublished data) and found that they were present at levels easily detectable
by qPCR. Interestingly, in the trafficking deficient Rab3D knockout mouse model we found miR-
127-3p to be up regulated in the LG but not in the tears. It is difficult to ascertain now if the miRNA
is being secreted at the basolateral side of the acini, and if the increased levels observed in the
serum exosomes are indeed coming from the LG acini. We will need In Situ Hybridization (ISH)
imaging to determine the sub cellular localization of this miRNA and evaluate its levels in the
Conclusion
134
serum before and after carbachol stimulation to determine if its secretion from the basolateral side
is upregulated. Of course, without an acinar cell specific exosome marker it would also be difficult
to be certain of the cell-of-origin of this miRNA in serum, as other tissues (such as the tree SG)
may also produce and secrete it.

135
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Abstract (if available)

Abstract Sjögren’s Syndrome (SS) is a common, debilitating, incurable autoimmune disease that lacks an analytical diagnostic test, and relies on subjective methods that take an average of 3 years for diagnosis. 90% of SS patients are women. To improve SS diagnostics, I have investigated microRNAs (miRNA), a class of short regulatory non-coding RNA that can silence protein translation and regulate cell signaling. Studying differences in their expression could identify diagnostic biomarkers and shed light on disease progression and development. Using murine models of SS, in Chapter 2 I have investigated serum exosomes of male Non-Obese Diabetic (NOD), identified five differentially expressed miRNAs and validated two by qPCR. In Chapter 4, I have identified fourteen miRNAs that were dysregulated in tears of male NOD mice when compared to healthy mice and validated eight candidate miRNAs by qPCR. Three of these miRNAs – miR-203a-3p, miR-181a-5p, miR-181b-5p – successfully distinguished patients with SS-associated autoimmune dry-eye from patients with non-autoimmune subtype of dry-eye by qPCR. Several of these miRNAs have been previously reported in the context of SS, but miR-181b-5p is a new find. In Chapter 5, I have reported that the miRNA transcriptome is greatly altered in the male NOD mouse lacrimal gland (LG) after the onset of disease. miRNAs as a percentage of both total RNA and small RNA are elevated in infiltrating immune cells in the LG as compared to LG acini. Most upregulated miRNAs in male NOD LG are largely expressed in infiltrating immune cells while most downregulated miRNAs are specific to the LG acini. Dysregulated miRNAs in the male NOD LG are predicted to target genes involved in ‘Regulation of Cytokine production’. Dysregulated miRNAs that are enriched in immune infiltrates are predicted to upregulate the IL6 pathway.

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Asset Metadata

Creator Singh Kakan, Shruti (author)

Core Title Exploring serum and tear micro-RNA as biomarkers for early diagnosis of Sjögren’s Syndrome

School School of Pharmacy

Degree Doctor of Philosophy

Degree Program Pharmaceutical and Translational Sciences

Degree Conferral Date 2022-12

Publication Date 07/11/2023

Defense Date 12/14/2022

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag autoimmunity,biomarkers,exosomes,lacrimal gland,lymphocytes,microRNA,non-coding RNA,OAI-PMH Harvest,RNA sequencing,serum,Sjögren’s syndrome,tears

Format theses (aat)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Hamm-Alvarez, Sarah F. (committee chair), Okamoto, Curtis T. (committee chair), Hjelm, Brooke E. (committee member), Mackay, Andrew (committee member)

Creator Email shruti.singh.222@gmail.com,singhkak@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-oUC112711067

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