Dissecting the role of a non-canonical interleukin-6 cytokine signaling in systemic chronic inflammation and multimorbidity induced by a high-fat diet

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Content Copyright 2024 Youngjoo Lee
DISSECTING THE ROLE OF A NON-CANONICAL INTERLEUKIN-6
CYTOKINE SIGNALING IN SYSTEMIC CHRONIC INFLAMMATION
AND MULTIMORBIDITY INDUCED BY A HIGH-FAT DIET
by

Youngjoo Lee
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
(DEVELOPMENT, STEM CELLS, AND REGENERATIVE MEDICINE)
August 2024

ii
ACKNOWLEDGMENTS
I express my gratitude to my PI, Dr. Denis Evseenko, for his guidance and support throughout my
doctoral journey. Your mentorship has been invaluable to my growth as a researcher. I am also
profoundly thankful to my committee members, Dr. Amy Merrill-Brugger, Dr. Michael Bonaguidi,
and Dr. Thomas Lozito for their insightful feedback and guidance. Your expertise and
encouragement have significantly shaped the direction and quality of my project.
My heartfelt appreciation goes to my outstanding colleagues: Joshua Lee, Dr. Arijita Sarkar, Dr.
Jenny Magallanes, Jade Tassey, Una Stevic, Dr. Ben Van Handel, Sean Limfat, Dr. Jinxiu Lu, and Dr.
Nancy Liu. Your camaraderie, support, and intellectual contributions have enriched my research
experience immensely. I miss all the jokes, food, and drinks we shared.
I am grateful for the assistance provided by Jon Levi and Dr. Seth Ruffins. Your help and
collaboration have been pivotal in my project.
Finally, I could not have reached this milestone without the boundless love and support from my
parents, Namyeong Lee and Insuk Kim, and my love, Andrew Carl Drake. Andrew, your belief in
me has been my greatest source of strength and motivation. We chose to do this not because it
was easy, but because it was hard. I am proud of us not only for achieving our goals but also for
supporting each other throughout the most challenging times.

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TABLE OF CONTENTS
Acknowledgments......................................................................................................................................... ii
List of Figures............................................................................................................................................... vi
Abbreviations............................................................................................................................................. viii
Abstract......................................................................................................................................................... x
CHAPTER 1. BACKGROUND...........................................................................................................................1
1.1 Inflammation and Aging......................................................................................................................1
1.2 Markers of Inflammaging....................................................................................................................4
1.3 Inflammaging and Multimorbidity......................................................................................................7
1.3.1 Inflammaging and Non-alcoholic fatty liver disease (NAFLD)......................................................8
1.3.2 Inflammaging and Osteoporosis..................................................................................................9
1.3.3 Inflammaging and Osteoarthritis...............................................................................................11
1.3.4 Inflammaging and Neurodegeneration .....................................................................................12
1.4 Obesity as an Accelerated Aging Model ...........................................................................................13
1.5 Interleukin-6 in Obesity and Aging ...................................................................................................16
1.5.1 Interleukin-6 (IL-6) Family of Cytokines and IL-6 Signaling Transducer, gp130.........................16
1.5.2 IL-6 in Obesity and Aging ...........................................................................................................17
1.6 SRC Family Kinase Activation by a Non-canonical IL-6/gp130 Signaling...........................................19
1.6.1 Src Family Kinases......................................................................................................................19
1.6.2 IL-6/gp130 Activation of SRC Family Kinases.............................................................................20
1.6.3 Inhibition of SFK Activation via IL-6/gp130................................................................................21
Chapter 2. GENETIC ABLATION OF GP130 Y814 SIGNALING REDUCES SYSTEMIC CHRONIC
INFLAMMATION INDUCED BY A HIGH-FAT DIET.........................................................................................23
2.1 Introduction ......................................................................................................................................23
2.2 Results...............................................................................................................................................24
2.2.1 High-fat diet induces pathologic remodeling in metabolic organs and elevates systemic
inflammation.......................................................................................................................................24
2.2.2 Genetic mutation of gp130Y814 ameliorates systemic inflammation induced by HFD............28
2.2.3 F814 mice exhibit attenuated inflammatory responses induced by HFD in adipose tissue
and liver. .............................................................................................................................................30
2.2.4 F814 mice demonstrate resistance to bone and cartilage loss induced by HFD. ......................35
2.2.5 F814 mice was protected from inflammation-induced disturbance in the neuro stem cell
niche....................................................................................................................................................39
2.3 Materials and Methods.....................................................................................................................41
2.3.1 Generation of Mutant Mouse and Treatments.........................................................................41

iv
2.3.2 Animal Sacrifice and Sample Collection.....................................................................................41
2.3.3 Dual-energy X-ray absorptiometry (DEXA) scanning .................................................................44
2.3.4 ELISA for serum cytokine/protein..............................................................................................44
2.3.5 White blood cell (WBC) differential...........................................................................................45
2.3.6 Quantitative real-time PCR ........................................................................................................45
2.3.7 RNA sequencing library preparation and sequencing ...............................................................45
2.3.8 RNA sequencing data analysis ...................................................................................................46
2.3.9 Picro Sirius Red staining .............................................................................................................46
2.3.10 Immunohistochemistry (IHC) for macrophages.......................................................................47
2.3.11 Micro-computed tomography (μCT) data collection and analysis...........................................48
2.3.12 Flow cytometry analysis for bone marrow and adipose immune cells...................................48
2.3.13 TRAP staining and quantification.............................................................................................49
2.3.14 OARSI scoring and synovitis scoring.........................................................................................49
2.3.15 Mesenchymal stem cell (MSC) culture and osteogenesis .......................................................50
2.3.16 Alizarin Red S staining and quantification ...............................................................................50
2.3.17 Osteoclastogenesis and quantification by TRAP staining ........................................................50
2.3.18 Cryosection and staining of hippocampus...............................................................................51
Chapter 3. PHARMACOLOGIC INHIBITION OF GP130/SFK SIGNALING REDUCES SYSTEMIC CHRONIC
INFLAMMATION INDUCED IN MICE BY A HIGH-FAT DIET...........................................................................53
3.1 Introduction ......................................................................................................................................53
3.2 Results...............................................................................................................................................55
3.2.1 Long-term treatment of R159 was safe and reduced weight gain induced by HFD..................55
3.2.2 R159 treatment reduced inflammatory responses in mice on HFD. .........................................56
3.2.3 R159 mitigates degenerative changes induced by HFD in musculoskeletal tissues..................61
3.2.4 R159 treatment protects from inflammation-induced decline in neurogenesis.......................63
3.2.5 R159 treatment did not affect hematopoietic and skin stem cell niches..................................65
3.2.6 R159 treatment increased physical activity levels in mice on HFD. ..........................................67
3.3 Materials and Methods.....................................................................................................................68
3.3.1 Animals and Treatments............................................................................................................68
3.3.2 Hematopoietic stem cell and progenitor isolation and quantification......................................69
3.3.3 Hair follicle stem cell isolation and quantification.....................................................................69
3.3.4 Cholesterol quantification .........................................................................................................70
3.3.5 Voluntary activity and motivation .............................................................................................71
Chapter 4. SEX DIFFERENCES IN RESPONSE TO HFD...................................................................................72

v
4.1 Introduction ......................................................................................................................................72
4.2 Results...............................................................................................................................................73
4.2.1 Female mice resisted weight gain in short-term HFD but not long-term..................................73
4.2.2 HFD elevated systemic inflammatory marker levels in female mice but to a lesser extent
than in males.......................................................................................................................................74
4.2.3 Female mice did not show significant bone density changes induced by HFD. ........................77
Chapter 5. DISCUSSIONS AND FUTURE DIRECTION....................................................................................78
Appendix: Pharmacologic Inhibition OF GP130/SFK SIGNALING ameliorates Bleomycino-induced
pulmonary fibrosis in mice..........................................................................................................................84
1. Introduction ........................................................................................................................................84
2. Results.................................................................................................................................................85
3. Materials and Methods.......................................................................................................................86
References ..................................................................................................................................................89

vi
LIST OF FIGURES
Figure 1. The seven pillars of aging...............................................................................................................3
Figure 2. Inflammaging and Multimorbidity.................................................................................................8
Figure 3. Obesity results in accelerated aging ............................................................................................14
Figure 4. IL-6 family cytokines and gp130 signaling complex.....................................................................17
Figure 5. SRC Activation ..............................................................................................................................20
Figure 6. SFK activation by gp130Y814 and inactivation by a point mutation. .............................................21
Figure 7. DEXA scan analysis in HFD induced changes in wildtype (WT) mice............................................25
Figure 8. HFD induced adipocyte hyperplasia and macrophage infiltration in adipose tissue...................25
Figure 9. HFD induced liver steatosis..........................................................................................................26
Figure 10. HFD induced liver fibrosis...........................................................................................................26
Figure 11. HFD increased macrophage infiltration in the liver...................................................................27
Figure 12. HFD increased serum levels of IL-6, MCP-1, CRP, and circulating monocyte.............................27
Figure 13. Experimental design to investigate the effect of HFD on F814 and WT ....................................28
Figure 14. DEXA scan analysis in high-fat diet (HFD) induced changes in WT and F814 mice. ..................28
Figure 15. HFD-induced changes in systemic inflammation markers in F814 and WT mice.......................29
Figure 16. HFD-induced changes in white blood cell differential in F814 and WT mice .............................30
Figure 17. HFD-induced gene expression changes in adipose tissue in F814 and WT mice........................31
Figure 18. HFD induced macrophage infiltration in adipose tissue in F814 and WT mice..........................31
Figure 19. Flow cytometry analysis of immune cells in adipose tissue from HFD-fed WT and F814 mice..32
Figure 20. HFD-induced fibrosis in the liver in F814 and WT mice..............................................................33
Figure 21. HFD-induced macrophage infiltration in the liver in F814 and WT mice...................................33
Figure 22. Differential gene expressions in the liver from F814 and WT mice on HFD...............................34
Figure 23. HFD-induced bone-density loss in F814 and WT mice. ..............................................................35
Figure 24. Bone matrix production by F814 or WT bone marrow-derived cells. ........................................37
Figure 25. RANKL expression and osteoclast activity in F814 and WT mice on HFD. .................................38
Figure 26. Osteoarthritis and synovitis evaluation of F814 and WT mice on HFD......................................39
Figure 27. Neuro stem cell and neurogenesis of F814 and WT mice on HFD..............................................40
Figure 28. Adsorbance, Distribution, Metabolism, Excretion (ADME) profile of drugs R805 and R159 .....54
Figure 29. R159 treatment inhibits SRC activation .....................................................................................54
Figure 30. Assessing R159's impact on aging mice on HFD ........................................................................55
Figure 31. HFD-induced systemic inflammation levels in R159 or Veh treated mice..................................56
Figure 32. HFD-induced gene expression changes in adipose tissue in mice on HFD treated with Veh
or R159........................................................................................................................................................57
Figure 33. HFD induced macrophage infiltration in adipose tissue in WT mice on HFD treated by Veh
or R159........................................................................................................................................................58
Figure 34. HFD-induced fibrosis in the liver in WT mice on HFD treated by Veh or R159...........................58
Figure 35. HFD-induced macrophage infiltration in the liver in WT mice on HFD treated by Veh or R159 59
Figure 36.Differential gene expressions in the liver from WT mice on HFD treated by Veh or R159..........60
Figure 37. HFD-induced lipid metabolism changes in WT mice on HFD treated by Veh or R159 ...............61
Figure 38. HFD-induced bone density loss in WT mice on HFD treated by Veh or R159.............................62
Figure 39. Osteoclast activity and RANKL expression in WT mice on HFD treated by Veh or R159............62
Figure 40. Osteoarthritis and synovitis evaluation of WT mice on HFD treated by Veh or R159 ...............63
Figure 41. Neuro stem cell and neurogenesis of WT mice at 12 months old and 16 months old...............64
Figure 42. Neuro stem cell and neurogenesis of WT mice on HFD treated with Veh or R159....................65

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Figure 43. Hematopoietic stem cell and progenitor cells of WT mice on HFD treated with Veh or R159 ..66
Figure 44. Hair follicle stem cells and progenitor cells of WT mice on HFD treated with Veh or R159 ......67
Figure 45. Evaluation of activity levels of WT mice on HFD treated with Veh or R159 ..............................68
Figure 46. Weight change during HFD administration for female mice .....................................................74
Figure 47. HFD-induced systemic inflammation levels in female mice.......................................................75
Figure 48. HFD-induced changes in white blood cell differential in female mice. ......................................76
Figure 49. HFD-induced bone density loss in WT mice on HFD treated by Veh or R159.............................77
Figure 50. R159 treatment resulted in improved outcomes in a mouse model of bleomycin-induced
pulmonary fibrosis ......................................................................................................................................86

viii
ABBREVIATIONS
BLM Bleomycin
BMI Body mass index
CCL2 Chemokine (C-C motif) ligand 2
CNS Central nervous system
CNTF ciliary neurotrophic factor
CRP C-reactive protein
DEXA Dual-energy X-ray absorptiometry
gp130 Glycoprotein 130
HCC Hepatocellular carcinoma
HFD High-fat diet
IHC Immunohistochemistry
IL-1b Interleukin-1b
IL-6 Interleukin-6
IL-6R IL-6 receptor
IPF Idiopathic pulmonary fibrosis
LIF leukemia inhibitory factor
MCP-1 Monocyte Chemoattractant Protein-1
MMP matrix metalloproteinases
MSC Mesenchymal stem cell
NAFLD Non-alcoholic fatty liver disease
NASH nonalcoholic steatohepatitis
ND Normal diet
NSC Neural stem cells
OA osteoarthritis
OARSI Osteoarthritis Research Society International
OB Osteoblast

ix
OC Osteoclast
OPG osteoprotegerin
OSM oncostatin M
RANK receptor activator of nuclear factor kappa beta
RANKL receptor activator of nuclear factor kappa beta ligand
SASP Senescence-associated secreted phenotype
SFK Src Family Kinase
TNFa Tumour Necrosis Factor alpha
uCT micro computed tomography
WBC White Blood Cell
WT wild type

x
ABSTRACT
Systemic chronic inflammation is a key factor in the onset and progression of degenerative
diseases linked to aging and obesity. Interleukin-6 (IL-6) family of cytokines are major regulators
of inflammation and immune response and part of the senescence-associated secretory
phenotype. IL-6 is a biomarker that demonstrates a robust correlation with age and body mass
index (BMI). However, these cytokines also play a crucial role in metabolic homeostasis and tissue
regeneration. Given the pleiotropic nature of IL-6 cytokines and multiple signaling pathways
activated by their receptors, selective modulation of this complex signaling may offer a unique
opportunity for therapeutic interventions for aging and obesity. Previously, we discovered that a
non-canonical signaling pathway downstream of tyrosine (Y) 814 within the intracellular domain
of gp130, the IL-6 co-receptor, is responsible for the recruitment and activation of SRC family of
kinases (SFK). Mice with constitutive genetic inactivation of gp130 Y814 (F814 mice) show
accelerated resolution of inflammatory response and superior regenerative outcomes in skin
wound healing and posttraumatic models of osteoarthritis. This thesis focused on the effects of
selective genetic or pharmacological inhibition of the non-canonical gp130-Y814/SFK signaling in
systemic chronic inflammation and multimorbidity in a high-fat diet (HFD) induced model of
accelerated aging. F814 mice showed significantly reduced inflammatory response to HFD in
adipose and liver tissue, with significantly reduced levels of systemic inflammation compared to
wild type (WT) mice. F814 mice were also protected from HFD-induced bone loss and cartilage
degeneration. Pharmacological inhibition of gp130-Y814/SFK in mice on HFD mirrored the effects
observed in F814 mice on HFD; furthermore, this pharmacological treatment also demonstrated
a marked increase in physical activity levels and protective effects against inflammation-

xi
associated suppression of neurogenesis in the brain tissue compared to the control group. These
findings suggest that selective inhibition of SFK signaling downstream of gp130 receptor
represents a promising strategy to alleviate systemic chronic inflammation. Degenerative
changes and tissue senescence are inevitable in obese and aged organisms, but this study
demonstrated that the systemic inflammatory responses and inflammation-associated multimorbidity can be therapeutically mitigated.

1
CHAPTER 1. BACKGROUND
1.1 Inflammation and Aging
Inflammation is an intricate defense mechanism that protects the body from various threats,
ranging from infections and injuries to autoimmune responses. Acute inflammation orchestrates
a cascade of immune mechanisms to eliminate invaders and repair damage and is followed by a
resolution, where lipid mediators and macrophages bring the inflammatory process to a close,
restoring tissue homeostasis through negative feedback (Hamidzadeh et al., 2017). However,
when inflammation persists in a low-grade, chronic form, devoid of adequate negative feedback,
a different scenario unfolds. Chronic inflammation lacks a resolution phase and this absence of
resolution results in the prolonged recruitment of monocytes and macrophages, leading to
further tissue damage and elevating systemic inflammatory levels (Franceschi & Campisi, 2014;
Oishi & Manabe, 2018). Chronic inflammation may stem from several sources, including
metabolic stress and cell senescence, and recent studies demonstrate strong correlations
between chronic inflammation and age-related diseases (Franceschi & Campisi, 2014; Hofseth &
Hébert, 2022; Kennedy et al., 2014).
Aging is broadly defined as a time-dependent functional decline in living organisms that
ultimately culminatesin death. At the cellular and molecular level, aging manifests as the gradual
accumulation of physiological integrity loss, resulting from combinations of environmental,
stochastic, and genetic events (López-Otín et al., 2013). To establish a framework for aging
research and intervention to improve human healthspan, López-Otín, et al. suggested the cellular
and molecular hallmarks of aging; Genomic instability, Telomere attrition, Epigenetic alterations,

2
Loss of proteostasis, Deregulated nutrient sensing, Mitochondrial dysfunction, Cellular
senescence, Stem cell exhaustion, Altered intercellular communication (López-Otín et al., 2013).
The hallmarks of aging are continuously evolving since the landmark paper, deepening the
understanding of each hallmark and the mechanistic links among them. “Inflammaging” is one of
the viewpoints derived from it, where it focuses on the chronic, sterile, and low-grade
inflammation in aging, which drives the pathogenesis of age-related diseases (Franceschi et al.,
2018).
Chronic inflammation is pivotal in the pathogenesis of various degenerative diseases and is
intimately linked with biological aging (Franceschi & Campisi, 2014; Kennedy et al., 2014). The
term “inflammaging,” coined by Franceschi et al., encapsulates the critical roles that chronic
inflammation plays in the aging process (Franceschi & Campisi, 2014). The underlying
mechanisms of aging and age-related diseases significantly overlap and seven core mechanisms
or 'pillars' of aging, which include systemic chronic inflammation, metabolic dysfunction,
adaptation to stress, epigenetic changes, macromolecular damage, loss of protein homeostasis,
impaired stem cell regeneration, are established (Kennedy et al., 2014). These pillars,
representing the complexity of aging, underscore the multifaceted nature of biological
deterioration over time. These pillars are not separate entities but interconnected, converging
on inflammation (Figure 1). Disruption in any single pillar leads to an increase in inflammation,
which in turn impacts the rest of the pillars. This persistent, low-level inflammation happens
without any infection but is fueled by internal signals, marking the chronic inflammation
associated with aging (Franceschi et al., 2018). Persistent systemic inflammation exacerbates

3
aging-related degenerative diseases such as osteoarthritis, osteoporosis, diabetes,
cardiovascular diseases, and neurodegenerative disorders (Franceschi et al., 2018).
Figure 1. The seven pillars of aging
The seven pillars are inflammation, stem cell regeneration, macromolecular damage, stress,
proteostasis, metabolism, and epigenetics. The relationships between the pillars are shown by the
interconnected network. The pillars are shared by aging and age-related diseases. (Franceschi et
al., 2018)

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This concept of inflammaging highlights how the chronic inflammation typical of aging is not just
a symptom but a fundamental driver of the biological aging process. This insight has led to a novel
approach in geroscience, advocating for a collective strategy against age-related diseases by
targeting the fundamental mechanisms of aging, rather than addressing these diseases
separately. In line with this innovative approach, our research focuses on identifying targets
within these fundamental mechanisms of inflammaging.
1.2Markers of Inflammaging
Inflammaging in older adults is usually marked in the clinic by stably elevated levels of IL-6, Creactive protein (CRP), and monocyte chemoattractant protein-1 (MCP-1) (Alberro et al., 2021;
Bettcher et al., 2019).
The circulating level of Interleukin 6 (IL-6) is the most extensively studied systemic cytokine for
inflammaging. In healthy adults, IL-6 concentrations are typically low or undetectable, but higher
levels have been observed in older adults, with further increases seen in the very elderly
(Minciullo et al., 2016; Puzianowska-Kuźnicka et al., 2016). Additionally, elevated IL-6 levels have
been linked to disability and mortality in older adults; A large population-based study showed
that older persons (71 years or older) with circulating IL-6 greater than 2.5 pg/mL are at higher
risk of functional decline over the subsequent 4 years (Ferrucci et al., 1999). Similarly, a 9-year
follow-up study for people over 60 years or older also showed that higher baseline IL-6 levels and
people with rapid increase in IL-6 were significantly linked to a faster rise in multimorbidity,
including hypertension, diabetes, joint disease, and cognitive impairment (Fabbri et al., 2015).
On the other hand, IL-6 is a pleiotropic cytokine that regulates immune responses, acute phase

5
reactions, hematopoiesis, and inflammation in both pro- and anti-inflammatory contexts (RoseJohn, 2020). Due to the complexity and multifaceted of IL-6 signaling and its pathways, we will
discuss IL-6 further in a later section.
C-Reactive Protein (CRP) was first identified as an acute phase reactant when it was found to be
elevated in patients with inflammatory conditions induced by xenobiotics (Abernethy & Avery,
1941; Tillett & Francis, 1930). However, decades of research revealed that an increased serum
level of CRP indicates not only acute infection but also an ongoing tissue-damaging process,
making CRP measurement a straightforward screening tool for organic diseases (Pepys, 1981).
CRP is a pentamer protein mainly secreted by hepatocytes, and this is principally regulated by IL6 and secondarily by Interleukin-1b (Zhang et al., 1996). The pentameric conformation of CRP,
which provides a binding site for apoptotic cells or bacterial cell walls and enables CRP to function
in the innate immune response, undergoes a conformational change upon binding to activated
immune cells or cells understress, leading to dissociation into monomeric CRP (Braig et al., 2017).
Both the pentameric and monomeric forms of CRP are highly pro-inflammatory molecules that
activate monocytes and these monocytes, in turn, secrete cytokines such as IL-6, which further
elevate CRP levels (Eisenhardt et al., 2009). CRP levels increase rapidly in response to
inflammation and infection and decrease just as quickly upon resolution of the condition, with a
plasma half-life of 19 hours (Vigushin et al., 1993). Therefore, a low-level prolonged elevation of
CRP is a sensitive marker for chronic inflammation (Harris et al., 1999). Consistent elevation of
CRP levels, especially above 3 mg/L, is associated with an increased risk of multi-organ failure—
including cardiovascular, pulmonary, and cognitive systems—and increased mortality,
independent of multimorbidities, in studies conducted across different ages, ethnicities, and

6
racial groups (Chen et al., 2019; Maluf et al., 2020; O’Doherty et al., 2014; Visser et al., 1999). A
10-year follow-up study of individuals over 50 years old revealed that a consistently low elevation
in CRP levels was associated with an increased risk of adverse aging outcomes, including
cardiovascular, respiratory, and cognitive disorders (Lassale et al., 2019).
Monocyte Chemoattractant Protein-1 (MCP-1), gene name C-C Motif Chemokine Ligand 2 (CCL2),
plays essential roles in monocyte recruitment with its receptor CCR2 during infections or
inflammatory conditions (Yadav et al., 2010). In non-acute conditions, MCP-1 promotes the
homeostatic migration of inflammatory monocytes from the bone marrow into the bloodstream
to maintain innate immunity (Deshmane et al., 2009). Under an inflammatory condition, elevated
circulating MCP-1 levels recruit monocytes from the bone marrow, increasing the number of
tissue monocytes, which then differentiate into tissue macrophages (Jakubzick et al., 2013). An
increase in MCP-1 with age was reported by a large-scale population study using multivariate
regression analysis, demonstrating its contribution to inflammaging (Inadera et al., 1999). Tissue
macrophages are highly specialized phagocytes crucial for tissue homeostasis, infection control,
and injury repair, however, prolonged recruitment of tissue macrophages due to inflammaging
plays critical roles in developing age-related diseases, including cardiovascular disease, diabetes
mellitus, and Alzheimer's disease (Davies et al., 2013; Yue et al., 2021). Increased levels of
circulating MCP-1 have been associated with decreases in memory and increased risk of
Alzheimer's disease, cardiovascular disease, and sarcopenia (Bettcher et al., 2019; Lee et al., 2018;
Yousefzadeh et al., 2018).
IL-6 has consistently demonstrated a correlation with age and age-related degenerative diseases
in multiple studies over the past three decades (Alberro et al., 2021; Brüünsgaard & Pedersen,

7
2003; Puzianowska-Kuźnicka et al., 2016). IL-6 is the primary inducer of CRP in the liver (Zhang et
al., 1996), and it is also one of the major inducers of MCP-1 (CCL2) production (Zhu et al., 2022).
Therefore, in this dissertation project, we focused on modulating IL-6 signaling to mitigate the
detrimental effects of inflammaging by reducing the pro-inflammatory responses of IL-6 and
reducing levels of CRP and MCP-1.
1.3 Inflammaging and Multimorbidity
This chronic low-grade inflammatory state causes long-term tissue damage, leading to
multimorbidity and adversely affecting longevity. Inflammaging is characterized by increased
levels of inflammatory markers in the bloodstream, even in the absence of acute infection or
disease (Franceschi et al., 2018). The sustained inflammatory response can damage various
tissues and organs over time, contributing to the development of multiple chronic conditions
such as cardiovascular disease, diabetes, arthritis, and neurodegenerative disorders (Franceschi
& Campisi, 2014, Figure 2). As these conditions often occur simultaneously in older adults, they
collectively contribute to the decline in functional status and quality of life, complicating medical
management and increasing healthcare costs. Furthermore, the presence of multimorbidity
accelerates the aging process, thereby shortening lifespan and highlighting the critical need for
interventions targeting the underlying mechanisms of inflammaging. As we delve deeper into the
consequences of inflammaging, it is crucial to examine how this pervasive inflammatory state
specifically impacts various age-related diseases.
Among the most prevalent conditions exacerbated by inflammaging are non-alcoholic fatty liver
disease (NAFLD), osteoarthritis, osteoporosis, and neurodegeneration. Understanding the

8
intricate connections between chronic inflammation and these diseases will provide valuable
insights for potential therapeutic targets to mitigate the adverse effects of inflammaging.
Figure 2. Inflammaging and Multimorbidity
Chronic inflammation in aging damages various tissues and organs over time, resulting in the development
of multiple chronic conditions such as cardiovascular disease, NAFLD, osteoporosis, osteoarthritis,
neurodegeneration, diabetes, metabolic syndrome, and so on. neurodegenerative disorders. These
conditions in turn, increase systemic chronic inflammation levels and accelerate the aging process.
1.3.1 Inflammaging and Non-alcoholic fatty liver disease (NAFLD)
NAFLD, encompassing a range of liver conditions from simple fatty liver (pure steatosis) to
nonalcoholic steatohepatitis (NASH), primarily affects middle-aged and elderly individuals, as the
prevalence of risk factors for its development tends to rise with age (Wang et al., 2013). Although
obesity is a primary risk factor for NAFLD and obesity prevalence increases with age, it may not
be the primary cause of NAFLD prevalence in the elderly (Wang et al., 2013). Additionally, NAFLD
is significantly more prevalent in men than in women under the age of 60; however, sex does not
play a role in NAFLD prevalence for people aged 60 and over (Wang et al., 2013). In older age (≥
60), adipocyte and preadipocyte senescence results in dysfunctional lipid storage, increasing
systemic free fatty acids, which exacerbate metabolic stress and increase systemic inflammation

9
(Cartwright et al., 2007). Moreover, increased free fatty acids trigger the redistribution of fat
from subcutaneous areas to intra-abdominal visceral depots and other ectopic sites, such as the
liver, resulting in NAFLD (DeNino et al., 2001). The global prevalence of NAFLD is on the rise with
the increasing aged or obese population, and it is the leading cause of chronic liver disease in
many regions around the world (Loomba & Sanyal, 2013). Left untreated, NAFLD could progress
to a more severe form of chronic liver disease such as cirrhosis and hepatocellular carcinoma
(HCC) that ultimately result in liver failure and death (Kim et al., 2021).
Inflammaging is closely linked to the development and progression of NAFLD, as preadipocyte
and adipocyte senescence are closely related to metabolic dysfunction, including insulin
resistance and dyslipidemia, both key factors in NAFLD (Cartwright et al., 2007). Senescent
adipocytes also secrete pro-inflammatory factors such as IL-6, MCP-1, and TNF-α that promote
liver inflammation and fibrosis, worsening NAFLD (Chung et al., 2006). Furthermore, increased
oxidative stress, which is exacerbated by inflammaging, poses a higher risk for NAFLD to progress
to more severe forms such as NASH and cirrhosis (Cartwright et al., 2007). Overall, the chronic
inflammation seen in inflammaging exacerbates the onset and progression of NAFLD, highlighting
the interplay between aging, inflammation, and liver disease.
1.3.2 Inflammaging and Osteoporosis
As age advances, the balance between bone resorption and formation during the remodeling
process becomes negative, leading to significant bone density loss and consequently raising the
risk of osteoporosis and fractures. (Burger et al., 1998). Previously, the decline in ovarian function
during menopause was believed to be the primary cause of skeletal involution, given the
prevalence of this condition in postmenopausal women (Lindsay, 1996). However, emerging

10
epidemiological, clinical, and biological studies increasingly support the hypothesis that chronic
inflammation significantly contributes to bone loss associated with aging (Kanis, 1996; Lencel &
Magne, 2011). Moreover, the decrease in estrogen after menopause has been shown to cause a
significant increase in IL-6 levels (Ershler & Keller, 2000; Masiukiewicz et al., 2002; Passeri et al.,
1993). Therefore, postmenopausal bone density loss may be the result of increased systemic
inflammation rather than hormonal imbalance. This shift in understanding highlights the role of
systemic inflammation in exacerbating osteoporosis, emphasizing the need to address
inflammaging as a critical factor in managing bone health in older adults.
Bone consists primarily of collagen, matrix proteins, and calcium hydroxyapatite crystals.
Osteoblasts (OBs) synthesize unmineralized bone matrix using type I collagen and noncollagenous proteins like osteocalcin and osteonectin. They also facilitate the active transport of
calcium, phosphate, and hydroxyl ions into the extracellular space, where they crystallize to form
calcium hydroxyapatite crystals. These crystals bind to matrix proteins, aligning parallel to
collagen fibers and enhancing bone strength. Osteoclasts (OCs), large multinucleated cells, resorb
bone by secreting hydrochloric acid and proteolytic enzymes such as cathepsin K and matrix
metalloproteinase 9. During the bone remodeling cycle, resorption is balanced by new bone
formation, orchestrated through interactions between OCs and OBs primarily regulated by the
receptor activator of nuclear factor-κB (RANK)/RANK ligand (RANKL)/osteoprotegerin (OPG)
system. RANKL promotes osteoclast formation and activity by binding to RANK on osteoclast
precursors, while OPG acts as a natural inhibitor by binding to RANKL and preventing its
interaction with RANK (Tanaka et al., 2005). This intricate balance is crucial for maintaining bone
density and structure throughout life. Cytokines such as IL-6, IL-1, and TNF-α and hormones like

11
estrogen modulate RANK/RANKL/OPG productions and interactions, influencing the
differentiation and activity of OCs and OBs (Lencel & Magne, 2011). Pro-inflammatory cytokines
promote bone resorption by increasing RANK production and monocyte recruitment, which are
precursors to osteoclasts, thereby promoting loss of bone density in patients with inflammatory
diseases (Abdelmagid et al., 2015). Additionally, estrogen deficiency in post-menopausal women
was shown to directly stimulate the production of IL-6, and among other cytokines, IL-6 is the
only one that is consistently demonstrated to be elevated with age (Ershler & Keller, 2000).
Therefore, modulating IL-6 signaling presents an attractive target for preventing bone density
loss in inflammaging.
1.3.3 Inflammaging and Osteoarthritis
Osteoarthritis (OA) is the predominant type of arthritis characterized by cartilage degeneration
and bony remodeling of joints, causing severe pain and often leading to significant disability
among the elderly (WHO Scientific Group on the Burden of Musculoskeletal Conditions at the
Start of the New Millennium, 2003). Aging is one of the most prominent risk factors for OA, with
systemic low-grade chronic inflammation playing a pivotal role in its onset and progression
(Greene & Loeser, 2015). Pro-inflammatory cytokines, chemokines, growth factors, and matrix
metalloproteinases (MMPs), collectively known as the SASP (senescence-associated secretory
phenotype) are found in synovial fluid of OA patients (Greene & Loeser, 2015). OA development
is a heterogeneous process of joint degeneration, and its etiology still remains elusive,
contributing to the absence of a cure for OA. IL-1β and TNF-α are reported to be particularly
relevant in OA development in older individuals, as both cytokines stimulate IL-6 production and
exert significant effects on body metabolism, composition, and acute-phase response, all of

12
which are influenced by aging (Beutler & Cerami, 1988; Dinarello Charles A. & Wolff Sheldon M.,
1993). A large-scale 15-year follow-up study determined that a higher level of circulating IL-6 was
the sole predictor for OA, whereas IL-1β and TNF-α did not achieve statistical significance (Livshits
et al., 2009). Systemic low levels of elevated CRP have also been reported as an early predictor
for OA, along with IL-6 (Spector et al., 1997). Human chondrocytes also express a range of C-C
chemokine receptors, including CCR2, which interacts with MCP-1 and release cartilage catabolic
enzymes (Borzì et al., 2000).
1.3.4 Inflammaging and Neurodegeneration
Neurodegeneration is a condition characterized by changes in the structure and function of
neurons, leading to decreased neuronal survival and increased neuronal death in the central
nervous system (CNS) (Ransohoff, 2016). Neural stem cells (NSCs), the resident stem cell
population of the CNS, undergo differentiation into neurons, astrocytes, and oligodendrocytes,
crucial for the development and maintenance of the CNS (Conover & Notti, 2008). Within the
dentate gyrus of the hippocampus, pivotal for learning and memory formation, continuous
neurogenesis by active NSCs persists throughout life (Moreno-Jimenez et al., 2019). The decline
in neurogenesis in the dentate gyrus over a lifetime is frequently linked to age-related
hippocampal cognitive decline, suggesting that impaired neurogenesis by impaired NSC niche
may contribute to the decline of hippocampal function (Fan et al., 2017). The NSC niche in this
region is highly sensitive to stressors, including inflammation and SASP, which directly impacts
NSC regeneration and central nervous system function, leading to changes in cognition and
behavior (Franceschi & Campisi, 2014; Peng & Bonaguidi, 2018). Traditionally the brain was
considered an immune-privileged region, however, recent studies have shown that cytokines

13
from systemic inflammation can breach the blood-brain barrier, inducing neuroinflammation
(Kempuraj et al., 2016; Walker, 2018). Inflammatory cytokines such as IL-6 and MCP-1 can induce
inflammation in the CNS by directly communicating with the CNS via afferent vagal nerve
signaling, and indirectly signaling through the cerebral endothelium (Walker, 2018).
Inflammaging can accelerate the progression of neurodegenerative diseases such as Alzheimer's
and Parkinson's, highlighting the critical need for therapeutic strategies targeting systemic
inflammation to preserve cognitive function and neuronal health.
1.4 Obesity as an Accelerated Aging Model
Obesity isincreasingly recognized as a critical driver ofsystemic chronic inflammation, a condition
closely mirroring the inflammatory processes observed in biological aging (Frasca et al., 2017). In
response to continuous excessive nutrition, mature adipocytes become hypertrophic, which
increases cellular stress and dysregulates normal adipogenesis and metabolic activity, turning
adipocytes senescent and necrotic (Weisberg et al., 2003). Hypertrophy and subsequent necrosis
cause a pathological adipose tissue remodeling and change of microenvironment, marked by
hypoxia, the encroachment of immune cells, and fibrosis, all of which compromise adipose tissue
function (Sun et al., 2011). Notably, hypertrophic adipocytes are characterized by a significant
upregulation in the production and release of pro-inflammatory cytokines, including IL-6, MCP-1,
and tumor necrosis factor α (TNFα) (Choe et al., 2016). This increase in pro-inflammatory
cytokines interferes with insulin signaling, notably through the serine phosphorylation of insulin
receptor substrate-1, mediated by the nuclear factor κB and Jun N-terminal kinase pathways,
ultimately leading to insulin resistance (H. Xu et al., 2003). Insulin resistance subsequently
amplifies adipose inflammation by upregulating MCP-1, which is a principal mediator in the

14
recruitment of pro-inflammatory monocytes (Shimobayashi et al., 2018). These cytokines
exacerbate the adipose inflammation by recruiting monocytes, which in turn give rise to proinflammatory macrophages in adipose tissue (Chawla et al., 2011). Macrophage infiltration into
adipose tissue turns adipose tissue into an active endocrine organ releasing pro-inflammatory
adipokines, including IL-6, TNFa, and MCP-1 (Duan et al., 2018; Fantuzzi, 2005; Kanda et al., 2006).
The inflammatory reactions initiated in adipose tissue extend beyond local effects, elevating the
levels of systemic chronic inflammation. This heightened state of inflammation sets the stage for
a cascade of adverse health outcomes, positioning obesity as a significant risk factor for a range
of conditions traditionally associated with the aging process. These include osteoarthritis,
sarcopenia, osteoporosis, and multiple organ dysfunctions including the liver, kidneys, and heart
(Duan et al., 2018). In this sense, obesity is perceived as a form of accelerated aging.
Figure 3. Obesity results in accelerated aging
Excessive nutrition leads to hypertrophy in mature adipocytes, increasing cellular stress and
disrupting normal adipogenesis and metabolic functions. This results in adipocytes becoming
senescent and necrotic, altering the microenvironment of adipose tissue with characteristics such
as hypoxia, immune cell accumulation, and fibrosis. Diseased adipose tissue produces various proinflammatory cytokines, including IL-6 and MCP-1, which worsen adipose inflammation by
attracting monocytes. These monocytes then develop into pro-inflammatory macrophages within
the adipose tissue. The infiltration of macrophages transforms adipose tissue into an active

15
endocrine organ that releases pro-inflammatory adipokines, such as IL-6, TNFa, and MCP-1,
elevating levels of systemic chronic inflammation. This increased inflammation contributes to a
series of negative health outcomes, making obesity a significant risk factor for various conditions
typically linked to aging. Consequently, obesity can be seen as a form of accelerated aging. (Figure
adapted from Longo et al., 2019)
Recognizing these parallels, high-fat diet (HFD) induced obesity emerges as a valuable
experimental model to explore the mechanisms of inflammaging as studying the mechanisms of
inflammaging in vivo presents several challenges. Aged animals are both expensive and delicate
to maintain, which can limit the scale and duration of research studies. Moreover, several
confounding factors may arise as age-related conditions can develop sporadically, making it
difficult to test a specific target to mitigate inflammaging. HFD leads to chronic, low-grade
systemic inflammation and progressive dysfunction of multiple organs and tissues that are typical
of inflammaging in human and mice (Duan et al., 2018; Schmid et al., 2004; Tan & Norhaizan,
2019). HFD induces a significant elevation of IL-6, MCP-1, and CRP levels in the systemic
circulation, indicative of the systemic inflammatory response that is similar to inflammaging
(Kanda et al., 2006; D. E. King et al., 2003). Furthermore, HFD induces degenerations commonly
associated with aging in mice including joint degeneration (Griffin et al., 2010; Kerr et al., 2021),
bone density loss (Cao et al., 2009; Gautam et al., 2014), and cognitive impairment (Pistell et al.,
2010). HFD administration is also a widely accepted method to induce NAFLD and NASH in
experimental animalsto study the impact of the condition and effective interventions (Nakamura
& Terauchi, 2013). Thus, utilizing the HFD-induced obesity in vivo model offers a pragmatic
approach to dissecting inflammaging, enabling the identification of therapeutic targets to
mitigate its effects. Therefore, we utilized the HFD-induced obesity model to test our hypothesis
on mitigating inflammaging, leveraging its relevance to accelerated aging processes.

16
1.5 Interleukin-6 in Obesity and Aging
Elevated levels of IL-6, CRP, and MCP-1 are characteristic of inflammaging and obesity (Alberro
et al., 2021; Bettcher et al., 2019; Choe et al., 2016). IL-6 is recognized as the key upstream
activator of CRP production by the liver cells (Ridker, 2009, 2016) and of MCP-1 production in
multiple tissues (Biswas et al., 1998; Hosaka et al., 2017). Therefore, we hypothesized that
modulating IL-6 signaling, which is a major pro-inflammatory cytokine that is highly associated
with increasing age (Ferrucci & Fabbri, 2018; Rodrigues et al., 2021; Sanada et al., 2018) and a
part of SASP (Coppé et al., 2010; Kumari & Jat, 2021; Yue et al., 2022), can alleviate systemic
chronic inflammation and mitigate the progression of age-related degenerative diseases
1.5.1 Interleukin-6 (IL-6) Family of Cytokines and IL-6 Signaling Transducer, gp130
The Interleukin-6 (IL-6) cytokine family, which includes IL-6, interleukin-11, leukemia inhibitory
factor (LIF), oncostatin M (OSM), ciliary neurotrophic factor (CNTF), among others, plays a crucial
role in a wide range of physiological and pathological processes. These include immune
regulation, inflammation, hematopoiesis, metabolic functions, and tissue regeneration (Wolf et
al., 2014). All IL-6 family cytokines signal through a common beta-receptor gp130, also known as
IL-6 signaling transducer, along with cytokine-specific alpha receptors ((Sims, 2020), Figure 4).
The formation of gp130 signaling complex triggers intracellular signaling through several tyrosine
and serine residues, leading to diverse biological outcomes. The complexity and breadth of IL-6
signaling arise from these combinations of family members and alpha receptors that merge to
activate the gp130 signaling complex, making IL-6/gp130 signaling multifaceted and contextspecific.

17
Figure 4. IL-6 family cytokines and gp130 signaling complex
IL-6 and IL-11 each bind to their specific β-receptor subunits (IL-6R and IL-11R, respectively) and
then associate with glycoprotein 130 (gp130) homodimers to form receptor complexes. The
leukemia inhibitory factor (LIF) receptor signals through a heterodimeric complex comprising the
LIF receptor (LIFR) and gp130. Similarly, Cardiotrophin 1 (CT-1) signals through LIFR and gp130,
and may involve an undefined CT-1-specific receptor subunit. OSM, notable for its versatility, can
signal not only through OSMR but also through a gp130:LIFR heterodimer. A distinct subgroup of
cytokines, including ciliary neurotrophic factor (CNTF) and neuropoietin (NP), utilizes complexes
that combine gp130:LIFR with the CNTF receptor (CNTFR). While CNTF and NP form relatively
simple complexes, Cardiotrophin-like cytokine factor 1 (CLCF1) signaling requires additional
components, including a soluble form of CNTFR or the cytokine receptor-like factor (CRLF), with
which CLCF1 forms a complex for secretion. (Sims, 2020)
1.5.2 IL-6 Family of Cytokines in Obesity and Aging
IL-6 family cytokines play a complex role in regulating immune responses, inflammation, and
metabolism, establishing it as a critical cytokine in the context of obesity and aging. Traditionally
recognized as a pro-inflammatory marker, IL-6 is integral to the chronic low-grade inflammation
commonly observed in both conditions, phenomena often referred to as 'metaflammation' and
'inflammaging' (Alberro et al., 2021; Ataseven et al., 2014; Franceschi et al., 2018; Khaodhiar et
al., 2004; Popko et al., 2010).

18
In obesity, adipocyte hyperplasia and pathological adipose tissue remodeling increases IL-6
secretion by adipose tissue (Ataseven et al., 2014; Khaodhiar et al., 2004). This increase is not
merely a reflection of increased fat mass but indicates a state of heightened immune system
activity and inflammation, which contribute to hallmarks of metabolic syndrome, including
increased blood pressure, insulin resistance, and abnormal cholesterol levels(Hotamisligil, 2017).
Elevated levels of IL-6 are also positively correlated with aging, where higher levels of IL-6 are
associated with poorer health state and outcomes relevant to age-related diseases (Alberro et
al., 2021). As a part of SASP secreted by senescent cells, IL-6 promotes inflammatory responses
and accelerates the declines in physiological functions seen in aging, affecting muscle strength,
bone density, and cognitive function (Mosteiro et al., 2018; Salech et al., 2022). Another IL-6
family cytokine that is a part of SASP is IL-11, and a recent publication showed that IL-11 inhibition
improved metabolic decline and frailty of old mice and extended the lifespan of mice by almost 25%
(Widjaja et al., 2024).
However, IL-6 family cytokine signaling is not solely detrimental to obesity and aging. IL-6 also
has important anti-inflammatory, metabolism, and regenerative roles. For example, IL-6-
deficient mice become obese upon maturity and they develop hepatic inflammation and systemic
insulin resistance (Matthews et al., 2010; Wallenius et al., 2002). An IL-6 receptor blocker,
tocilizumab, reduces chronic inflammatory responses but also puts patients at high risk of upper
respiratory diseases and neutropenia (Oldfield et al., 2009). There is no FDA-approved IL-11
signaling blocker yet, but complete blockade of IL-11 signaling could result in an increased risk of
inflammation and defect in hematopoiesis (Schwertschlag et al., 1999).

19
This paradoxical nature of IL-6 underscores the complexity of targeting this cytokine in
therapeutic strategies aimed at reducing chronic inflammation associated with obesity and aging.
A total blockade of IL-6 activity could disrupt beneficial aspects of its function, suggesting that
targeting specific pathways within the IL-6 signaling cascade may offer more promising
approaches.
1.6 SRC Family Kinase Activation by a Non-canonical IL-6/gp130 Signaling
1.6.1 Src Family Kinases
Src family kinases (SFK) play a key role in immune response and tumor progression, influencing
cell proliferation, differentiation, and migration. SFK includes Src, Lck, Hck, Fyn, Blk, Lyn, Fgr, Yes,
and Yrk, all sharing a conserved domain structure consisting of consecutive SH3, SH2, and
tyrosine kinase (SH1) domains(Boggon & Eck, 2004). SFK bears an autoinhibitory phosphorylation
site at Tyrosine 527 and to be activated, it requires phosphorylation at Tyrosine 416 (Cooper et
al., 1986; Smart et al., 1981; W. Xu et al., 1999, Figure 5). SFK can be activated by various
pathways and its pleiotropic function in different contexts is vast and still actively under
investigation. (Parsons & Parsons, 2004). For example, Src activated by PDGF stimulates
quiescent fibroblast, leading to fibrosis pathways (Ralston & Bishop, 1985); Src activated by EGF
induces mitogenesis associated with tumor growth (Ware et al., 1997) and actin cytoskeleton
remodeling that affects cell motility (Chang et al., 1995); Src activated by EGFR signaling enhances
cell survival and plays a critical role in cancer biology (Karni et al., 1999).

20
Figure 5. SRC Activation
(a) The compact structure of c-Src is maintained through internal interactions between the kinase
domain, SH2/SH3 domains, and the phosphorylated end of the C-terminal tail. In this
configuration, the activation loop adopts an inhibitory formation that compromises the active site
of the kinase by shifting the C helix. This arrangement is critical for forming the A loop helix, which
hinders substrate attachment and shields Tyr-416 from becoming phosphorylated, dependent on
the precise alignment of the kinase's two lobes. (b) The alteration of the SH2 and/or SH3 domains,
triggered by either the dephosphorylation of the C-terminal tail or the competitive attachment of
specific SH2/SH3 domain ligands, facilitates the opening of the kinase domain. This change
dismantles the A loop helix structure, making Tyr-416 accessible for phosphorylation. (c) The
phosphorylation of Tyr-416 leads to a comprehensive reconfiguration of the activation loop,
eliminating the obstruction to substrate attachment. This adjustment enables the C-terminal helix
to re-enter the active site, restoring the tyrosine kinase to its fully operational state. (W. Xu et al.,
1999)
1.6.2 IL-6/gp130 Activation of SRC Family Kinases
SFK activation is ubiquitous and can be mediated by numerous signaling pathways. Previously
published data identified the acidic domain 812 to 827 of gp130 as a region responsible for
activating SRC (Taniguchi et al., 2015). Based on this, our lab identified gp130 Tyrosine 814 as
the residue mainly responsible for SRC activation through serial residue mutations (Shkhyan et
al., 2023). A point mutation of Tyrosine 814 to Phenylalanine resulted in significantly reduced

21
Src activation and downstream pro-inflammatory and fibrotic gene expression in fibroblasts upon
a pro-inflammatory IL-6 family cytokine OSM stimulation (Figure 6, Shkhyan et al., 2023).
Figure 6. SFK activation by gp130Y814 and inactivation by a
point mutation.
Gp130 Tyrosine 814 is a residue mainly responsible for SRC
activation and a point mutation of Tyrosine 814 to
Phenylalanine inactivates the signaling pathways.
1.6.3 Inhibition of SFK Activation via IL-6/gp130
We generated CRISPR/Cas9 mice with a constitutively inactivated gp130Y814 (mutation of Y to
phenylalanine - F814) to further study this mechanism in vivo. F814 mice-derived cells showed
reduced Src activation upon stimulation of OSM, a pro-inflammatory IL-6 family cytokine, and
reduced inflammatory responses downstream of IL-6/gp130 (Shkhyan et al., 2023). F814 mice
showed decreased inflammatory and enhanced regenerative responses in joint and skin wound
models, potentially driven by differential macrophage responses and fibrotic responses; singlecell sequencing on macrophages on skin wound revealed the mutant had a lower number of proinflammatory macrophages and activated fibroblasts (Shkhyan et al., 2023).
Moreover, an SRC-targeting peptide, QQpYF, and a gp130-targeting small molecule, R805, both
showed similar inhibition of gp130 activation of SRC and resulted in better skin wound
regeneration and less bone matrix or cartilage degeneration upon osteoarthritis-inducing surgery
(Shkhyan et al., 2023). Both genetic and drug-mediated inactivation of SFK recruitment to gp130

22
receptor result in enhanced resolution of inflammation and accelerated regenerative outcomes
in several injury models in mouse, rat, and dog models (Shkhyan et al., 2023).

23
CHAPTER 2. GENETIC ABLATION OF GP130 Y814 SIGNALING REDUCES
SYSTEMIC CHRONIC INFLAMMATION INDUCED BY A HIGH-FAT DIET.
2.1 Introduction
In our recent study, we have identified a signaling tyrosine 814 (Y814) residue within the gp130
intracellular domain that acts as a “stress sensor” responsible for triggering degenerative, and
pathological changes in tissues via activation of SFK (Shkhyan et al., 2023). Mice with a
constitutively inactivated gp130Y814 (F814) showed enhanced regeneration upon skin or cartilage
injury and different macrophage responses in the injury site (Shkhyan et al., 2023).
However, the role of this novel regulatory mechanism in chronic systemic inflammation is not yet
defined. To investigate the effect of inactivation of gp130Y814 in chronic systemic inflammation,
we utilized a high-fat diet (HFD) mouse model. Multiple studies have shown that an experimental
HFD leads to chronic, low-grade systemic inflammation and progressive dysfunction of multiple
organs and tissues. HFD leads to a significant elevation of IL-6, MCP-1, and CRP levels in the
systemic circulation (Duan et al., 2018; Kanda et al., 2006; D. E. King et al., 2003). HFD causes
multiple organ dysfunction, including liver, kidney, and central nervous system, and increases
risks for cancer in liver, gastric system, and breast (reviewed in (Duan et al., 2018)). HFD also
negatively impacts musculoskeletal organs, causing osteoarthritis (OA), osteoporosis, and
sarcopenia (Duan et al., 2018; Griffin et al., 2010; Kerr et al., 2021).
We hypothesized that the non-canonical gp130-Y814/SFK signaling was a novel mechanism
implicated in the pathogenesis of chronic systemic inflammation and associated multimorbidity.
We evaluated the impact of HFD on C57BL/6J mice and the effects of gp130-Y815/SFK inhibition

24
by measuring levels of systemic inflammatory markers and examining multiple organs, including
metabolic organs, musculoskeletal organs, and the brain.
2.2 Results
2.2.1 High-fat diet induces pathologic remodeling in metabolic organs and elevates systemic
inflammation.
We utilized HFD-fed mice to study the mechanism of chronic systemic inflammation and
accelerated aging. After 10 months of HFD administration, C57BL/6J mice on HFD increased their
weight and fat content nearly 2-fold and significantly decreased bone mineral density compared
to the normal diet (ND) group (Figure 7A, B). Histological analysis revealed adipocyte hyperplasia
and a crown-like pattern of macrophages surrounding necrotic adipocytes in the adipose tissue
of HFD-fed mice, indicative of inflammatory changes (Figure 8A, B). The livers of HFD-fed mice
had an excess accumulation of lipid droplets (Figure 9A, B), increased fibrosis (Figure 10A, B), and
macrophage infiltration (Figure 11A, B), all of which are characteristics of non-alcoholic fatty liver
disease. Serum analysis demonstrated elevated levels of IL-6, CRP, and MCP-1, indicating
heightened systemic inflammation in HFD-fed mice (Figure 12A, B, C). Additionally, the white
blood cell differential of HFD-fed mice revealed an increase in circulating monocytes, further
supporting the presence of systemic chronic inflammation (Figure 12D). Taken together, these
results confirm that HFD-fed mice serve as a robust in vivo model for studying chronic
inflammation and its associated pathophysiological consequences.

25
Figure 7. DEXA scan analysis in HFD induced changes in wildtype (WT) mice
(A) Representative image and body composition analysis of WT mice on a normal diet (ND) or an
High-Fat Diet (HFD), generated by Dual Energy X-ray Absorptiometry (DEXA). Fat mass is shown
in red, lean mass in green, and bone mineral in grey. (B) Quantitative analysis for weight, fat
content, and bone mineral density of WT mice on ND or HFD. Two-tailed Student’s t-test was
used for statistical analysis and p-values less than 0.05 were considered significant. n= 4 for ND,
6 for HFD.
Figure 8. HFD induced adipocyte hyperplasia and macrophage infiltration in adipose tissue
(A) Representative image of visceral white adipose tissue of WT mice on ND. CD68 (brown,
arrow) marks macrophages. (B) Representative image of visceral white adipose tissue of WT
mice on HFD. Macrophages marked by CD68 (brown, arrow) formed crown-like patterns around
adipocytes.
ND HFD A
Fat mass Lean mass Bone Mineral
ND
HFD
0
20
40
60
80
Weight
gram
<0.0001
ND
HFD
0.00
0.02
0.04
0.06
0.08
0.10
Bone Mineral Density
Bone Mineral Content/Bone Area
(ratio)
0.0018
ND
HFD
0
10
20
30
40
Fat Content
Fat Mass/Total Mass (%)
<0.0001
B
A B

26
Figure 9. HFD induced liver steatosis
(A) Representative image of H&E staining of liver tissue from WT mice on ND. (B) Representative
image of H&E staining of liver tissue from WT mice on HFD. Excess lipid droplet deposits are
shown as white round voids.
Figure 10. HFD induced liver fibrosis
(A) Representative image of Picro Sirius Red staining of liver tissue from WT mice on ND. (B)
Representative image of Picro Sirius Red staining of liver tissue from WT mice on HFD. Red
staining shows excess fibrosis buildup in the liver tissue.
A B
A B

27
Figure 11. HFD increased macrophage infiltration in the liver
(A) Representative image of macrophages marked by CD68 staining (brown) in liver tissue from
WT mice on ND. (B) Representative image of macrophages marked by CD68 staining (brown) in
liver tissue from WT mice on HFD.
Figure 12. HFD increased serum levels of IL-6, MCP-1, CRP, and circulating monocyte.
(A) IL-6 in serum was measured by ELISA. (B) MCP-1 in serum was measured by ELISA. (C) CRP in
serum was measured by ELISA. (D) Circulating monocyte ratio was measured by white blood cell
differential. Two-tailed Student’s t-test, p-values less than 0.05 were considered significant.
A B
ND
HFD
0
5
10
15
20
25
IL-6
pg/mL
0.0202
ND
HFD
0
100
200
300
CCL2/MCP-1
pg/mL
0.0002
ND
HFD
0
5
10
15
20
25
C-Reactive Protein
ug/mL
0.0005
ND
HFD
0
2
4
6
8
10
Monocyte
% in WBC
0.0103
A B C D

28
2.2.2 Genetic mutation of gp130Y814 ameliorates systemic inflammation induced by HFD.
To investigate the role of gp130Y814 activation in a systemic chronic inflammatory condition, 2-
month-old F814 and wild type (WT) C57BL/6J mice were placed on HFD for 10 months (Figure
13A). Throughout the HFD administration period, F814 mutant mice exhibited weight gain similar
to that of WT mice (Figure 13B). DEXA scan analysis revealed no significant disparity between the
two groups (Figure 14A, B), suggesting that both WT and mutant mice experienced equivalent
metabolic stress and pro-inflammatory stimuli.
Figure 13. Experimental design to investigate the effect of HFD on F814 and WT
(A) At the age of 2 months, both F814 and WT mice were subjected to HFD feeding for 42 weeks,
after which changes were assessed at the 12-month-old time point. (B) Weight change of F814
and WT mice during HFD administration.
Figure 14. DEXA scan analysis in high-fat diet (HFD) induced changes in WT and F814 mice.
A B
Fat mass Lean mass Bone Mineral
HFD-WT HFD-F814
HFD-WT
HFD-F814
0.00
0.02
0.04
0.06
0.08
0.10
Bone Mineral Density
Bone Mineral Content/Bone Area
(ratio)
0.3514
HFD-WT
HFD-F814
0
10
20
30
40
Fat Content
Fat mass/Total mass (%)
0.2115
HFD-WT
HFD-F814
0
20
40
60
80
Weight
gram
0.3472
A B

29
(A) Representative image and body composition analysis of WT and F814 mice on HFD,
generated by DEXA. Fat mass is shown in red, lean mass in green, and bone mineral in grey. (B)
Quantitative analysis for weight, fat content, and bone mineral density of WT and F814 mice on
HFD. Two-tailed Student’s t-test was used for statistical analysis and p-values less than 0.05
were considered significant. n= 6 for each group.
Nevertheless, systemic inflammation levels differed between WT and F814 mice on HFD. While
serum IL-6 levels remained similar between WT and mutant mice, F814 mice displayed
significantly lower MCP-1 levels (Figure 15 A, B). MCP-1 is a classical monocyte recruiter that is
required for the migration of monocytes from bone marrow, which is especially critical for
chronic inflammatory conditions (Ingersoll et al., 2011; Serbina & Pamer, 2006). The mutant had
significantly lower levels of circulating monocytes, corroborating the lower MCP-1 level (Figure
16 A). Lymphocyte or neutrophil ratio was not significantly different among the groups (Figure
16B, C). Additionally, F814 mice on HFD displayed significantly lower CRP levels (Figure 15C), a
sensitive inflammation marker in clinical settings.
These results suggest that gp130Y814 residue may play a critical role in amplifying the proinflammatory signaling induced by HFD.
Figure 15. HFD-induced changes in systemic inflammation markers in F814 and WT mice.
(A) Serum IL-6 levels of F814 and WT mice on ND or HFD measured by ELISA. (B) Serum MCP-1
levels of F814 and WT mice on ND or HFD measured by ELISA. (C) Serum CRP levels of F814 and
ND HFD
0
5
10
15
IL-6
pg/mL
WT
F814
0.9967
0.0018
0.0823
0.3141
ND HFD
0
100
200
300
MCP-1
pg/mL
WT
F814
0.9957
<0.0001
0.0827
0.0007
ND HFD
0
10
20
30
CRP
ug/mL
WT
F814
0.9937
<0.0001
0.0354
0.0043
A B C

30
WT mice on ND or HFD measured by ELISA. 2-way ANOVA with multiple comparisons with Tukey
was used for statistical analysis, p-values less than 0.05 were considered significant.
Figure 16. HFD-induced changes in white blood cell differential in F814 and WT mice
(A) Monocyte ratio in peripheral blood analyzed from white blood cell (WBC) differential. (B)
Lymphocyte ratio in peripheral blood analyzed from WBC differential. (C) Neurophil ratio in
peripheral blood analyzed from white WBC differential. 2-way ANOVA with multiple
comparisons with Tukey was used for statistical analysis, p-values less than 0.05 were
considered significant.
2.2.3 F814 mice exhibit attenuated inflammatory responses induced by HFD in adipose tissue
and liver.
We expected HFD to induce inflammatory responses in major metabolic organs, so we evaluated
the adipose tissue and the liver of F814 and WT mice.
Transcription of genes representing adipose tissue-driven inflammation, including Ccl2 (MCP-1),
Tnf, and Il1b, was upregulated in both F814 and WT mice on HFD compared to their ND
counterparts (Figure 17A, B, C). However, the mutant mice exhibited a significantly lesser degree
of upregulation compared to the WT (Figure 17A, B, C). CD68 staining revealed adipose tissue
from F814 mice on HFD had reduced macrophage infiltration (Figure 18A, B). Flow cytometry
analysis of immune cells in adipose tissue from HFD mice also showed significantly fewer proND HFD
0
2
4
6
8
10
Monocytes
% in WBC
WT
F814 0.9282
0.0471
0.7037
0.0472
ND HFD
0
10
20
30
Neutrophils
% in WBC
WT
0.9351 F814
0.7848
0.7298
0.3997
ND HFD
0
20
40
60
80
100
Lymphocytes
% in WBC
WT
F814
0.8829
0.9996
0.7044
0.9670
A B C

31
inflammatory monocytes marked by CD11b+/Ly6Chi and macrophages marked by CD11b+/F4/80+
in F814 than in WT (Figure 19A, B). Taken together, these findings suggest that inflammatory
responses in adipose tissue induced by HFD are attenuated in F814 mice.
Figure 17. HFD-induced gene expression changes in adipose tissue in F814 and WT mice.
(A) Ccl2 (gene name for MCP-1) expression levels relative to a housekeeping gene Rpl7 in WT
and F814 mice on ND or HFD. (B) Tnf expression levels relative to a housekeeping gene Rpl7 in
WT and F814 mice on ND or HFD. (C) Il-1b expression levels relative to a housekeeping gene Rpl7
in WT and F814 mice on ND or HFD. 2-way ANOVA with multiple comparisons with Tukey was
used for statistical analysis, p-values less than 0.05 were considered significant.
HFD-WT
HFD-F814
0
5×104
1×105
1.5×105
2×105
CD68
Arbitrary Unit
0.0009
Figure 18. HFD induced macrophage infiltration in adipose tissue in F814 and WT mice
(A) Representative images of CD68 staining of adipose tissue of WT and F814 mice on HFD. (B)
Quantitative analysis of CD68 staining. Two-tailed Student’s t-test was used for statistical
analysis and p-values less than 0.05 were considered significant. n= 8 for each group.
ND HFD
0.000
0.001
0.002
0.003
0.004
0.005
Il-1b
Relative expression to Rpl7
WT
F814
0.7062
0.0007
0.0102
0.0376
ND HFD
0.00
0.01
0.02
0.03
0.04
0.05
Tnf
Relative expression to Rpl7
WT
F814
0.7338
<0.0001
0.0003
0.0274
ND HFD
0.0
0.1
0.2
0.3
Ccl2 (MCP-1)
Relative expression to Rpl7
WT
F814
0.9996
<0.0001
<0.0001
0.0022
A B C
A B

32
Figure 19. Flow cytometry analysis of immune cells in adipose tissue from HFD-fed WT and F814
mice.
(A) CD11b+
/Ly6Chi population marks pro-inflammatory monocytes recruited to adipose tissue.
(B) F4/80+ cells in CD11b+/Ly6G- population marks macrophages in adipose tissue. Two-tailed
Student’s t-test was used for statistical analysis and p-values less than 0.05 were considered
significant. n = 3-4 for each group. Cell staining and flow cytometry were performed by Jade
Tassey.
The livers of HFD-fed mice had an excessive accumulation of lipid droplets in both genotypes, but
F814 mice showed reduced fibrosis and macrophage infiltration (Figure 20A, B, Figure 21A, B).
Consistent with this, bulk RNA sequencing (RNA-seq) analysis of livers showed an increase in
inflammatory and fibrotic signaling in WT mice on HFD compared to F814 mice on HFD (Figure
22A). In particular, livers from WT on HFD had upregulated Ccr2, Ccr5, Osmr, Spp1, Src, Tlr2, and
Tlr5, suggesting more macrophage infiltration and activated immune responses than in F814

33
(Figure 22B). Upregulation of Col1a1, Ctsk, Itga4, Mmp2, and Pdgfb, indicating fibrotic activity,
was also attenuated in F814 on HFD than in WT (Figure 22B).
HFD-WT
HFD-F814
0
5×104
1×105
1.5×105
Picro Sirius Red
Arbitrary Unit
0.0079
Figure 20. HFD-induced fibrosis in the liver in F814 and WT mice
(A) Representative images of Picro Sirius Red staining marking fibrosis in the liver tissue of WT
and F814 mice on HFD. (B) Quantitative analysis of Picro Sirius Red staining. Two-tailed
Student’s t-test was used for statistical analysis and p-values less than 0.05 were considered
significant. n= 7 for each group.
HFD-WT
HFD-F814
0
2×104
4×104
6×104
8×104
1×105
CD68
Arbitrary Unit
0.0178
Figure 21. HFD-induced macrophage infiltration in the liver in F814 and WT mice
(A) Representative images of CD68 staining marking macrophages in the liver tissue of WT and
F814 mice on HFD. (B) Quantitative analysis of CD68 staining. Two-tailed Student’s t-test was
used for statistical analysis and p-values less than 0.05 were considered significant. n= 7 for
each group.
B
B

34
A
B
Figure 22. Differential gene expressions in the
liver from F814 and WT mice on HFD.
(A) Enriched terms for genes upregulated in the
liver of WT on HFD compared to F814
counterparts analyzed based on RNA-seq data.
(B) Heat map showing differentially regulated
genes (HFD-F814 vs HFD-WT) associated with
inflammation and fibrosis in the liver from bulk
RNA-seq. Library preparation and differential
gene expression analysis were performed by
Arijita Sarkar.
HFD-F814 HFD-WT Z-score

35
2.2.4 F814 mice demonstrate resistance to bone and cartilage loss induced by HFD.
Previous studies have shown that chronic inflammation is one of the major drivers of bone and
cartilage catabolism in various diseases (Abdelmagid et al., 2015; Bjarnason et al., 1997; Greene
& Loeser, 2015). The DEXA scans did not show significant differences in bone mineral density
between WT and F814 on HFD (Figure 14B), however, HFD-induced bone loss is reported to be in
trabecular bones rather than cortical bones, which cannot be evaluated by the resolution of DEXA
scans (Patsch et al., 2011). Micro-computed tomography (µCT) was utilized to analyze bone
mineral density of trabecular bone beneath the growth plate of proximal tibia (Figure 23A). While
both WT and F814 mice on HFD lost trabecular bone density compared to the ND counterparts,
F814 mice on HFD showed significant retention of trabecular bone compared to WT on HFD
(Figure 23B).
ND HFD
0.0
0.1
0.2
0.3
0.4
0.5
Trabecular
Bone Density
Bone Vol/Total Vol
WT
F814
0.5654
<0.0001
0.0079
0.0273
Figure 23. HFD-induced bone-density loss in F814 and WT mice.
(A) Area of interest for analyzing trabecular bone density. Micro-CT scans of the trabecular bone
beneath the growth plate of the proximal tibia were reconstructed in 3D. (B) Representative 3D
constructed images of trabecular bone of WT and F814 mice on HFD and quantitative analysis
F814
WT
A B
C

36
on bone density. 2-way ANOVA with multiple comparisons with Tukey correction, p-values less
than 0.05 were considered significant.
To determine whether the higher bone density resulted from enhanced osteogenesis or reduced
bone resorption under chronic inflammation, we evaluated the osteogenic and osteoclastogenic
potential of F814-derived cells in vitro. Mesenchymal stromal cells (MSCs) derived from bone
marrow were differentiated into osteocytes and bone matrix production was quantified by
Alizarin Red staining. F814 cells produced comparable amounts of bone matrix as WT
counterparts regardless of the inflammatory conditions induced by hyper-IL-6 or Oncostatin M
(OSM), a pro-inflammatory IL-6 family cytokine (Figure 24). F814 monocytes also differentiated
into osteoclasts at similar levels as WT cells when treated with the same concentration of
Receptor activator of nuclear factor-κB ligand (RANKL) (data not shown). RANKL is secreted by
osteoblasts, osteocytes, bone marrow stromal cells, and immune cells when stimulated by proinflammatory cytokines including IL-6 (Boyle et al., 2003; Takegahara et al., 2022). F814 MSCs
expressed reduced levels of RANKL (Tnfsf11) gene upon hyper-IL-6 stimulation compared to WT
counterparts (Figure 25A). In agreement with this, non-cultured total bone marrow cells from
F814 mice on HFD expressed significantly lower levels of RANKL (Tnfsf11) compared to WT on
HFD (Figure 25B). TRAP staining also showed a significantly reduced number of osteoclasts in
F814 on HFD compared to WT counterparts (Figure 25C). Collectively, the disruption of gp130-
Y814 signaling serves as a protective factor against bone density loss induced by a high-fat diet
through a reduction in RANKL production, ultimately ameliorating osteoclast activity and bone
resorption induced by systemic chronic inflammation.

37
Ctrl Hyper-IL6 OSM
0.00
0.02
0.04
0.06
0.08
0.10
Alizarin Red S
Arbitrary Unit
WT
F814
0.6539 0.9597 0.3278
Figure 24. Bone matrix production by F814 or WT bone marrow-derived cells.
Alizarin Red S staining shows bone matrix produced by osteocytes differentiated from F814 or WT
bone marrow-derived mesenchymal stem cells (MSC). 20ng/mL treatment of Hyper-IL6 or OSM
during osteocyte differentiation did not cause difference in bone matrix production between F814
and WT. Multiple unpaired t-test with FDR = 5% was used for statistical analysis and p-values less
than 0.05 were considered significant.
A B
C

A B
WT
F814
0
1
2
3
4
RANKL(Tnfsf11)
Fold Change to Ctrl
0.0074
ND HFD
0.0000
0.0002
0.0004
0.0006
0.0008
0.0010
RANKL(Tnfsf11)
Relative expression to Rpl7
WT
F814
0.9575
0.0411
0.9964
0.0037
WT F814 20µm 20µm HFD-WT
HFD-F814
0
5×103
1×104
1.5×104
2×104
2.5×104
TRAP
Arbitrary Unit
0.0310

38
Figure 25. RANKL expression and osteoclast activity in F814 and WT mice on HFD.
(A) Fold change of RANKL (Tnfsf11) expression levels of WT and F814 mesenchymal stromal cells
(MSCs) stimulated with hyper-IL-6 (10ng/mL) compared to non-stimulated WT and F814 MSC
controls. Two-tailed Student’s t-test, p-values less than 0.05 were considered significant. (B)
Expression of RANKL (Tnfsf11) relative to a housekeeping gene Rpl7 in bone marrow of HFD-fed
WT and F814 compared to ND counterparts. 2-way ANOVA with multiple comparisons with
Tukey correction, p-values less than 0.05 were considered significant. (C) Representative images
of TRAP staining (red) in trabecular bone (green) of WT and F814 mice on HFD and quantitative
analysis. Two-tailed Student’s t-test, p-values less than 0.05 were considered significant.
Long-term administration of HFD is reported to induce early onset or significantly worsened
progression of OA in mice (Sansone et al., 2019). Morphometric analysis of the joints showed
that F814 mice’ articular cartilage was largely protected from OA induced by HFD compared to
WT mice. The majority of mutant mice on HFD had mild or minimal symptoms of OA, while WT
counterparts developed mild to severe OA (Figure 26A, B, C). SFK activation is reported to be
critical for cartilage degeneration in OA, and our group has demonstrated that F814 cartilage
explants were resistant to OSM-induced degeneration (Novikov et al., 2021; Shkhyan et al., 2023).
Mild synovitis, a characteristic of OA induced by low-grade chronic inflammation, was present in
the majority of mice in both WT and F814 groups, although F814 mice exhibited a lower trend in
synovitis scores (Figure 26D).
A B
WT 50µm 10µm WT F814 50µm 10µm F814

39
C D
Figure 26. Osteoarthritis and synovitis evaluation of F814 and WT mice on HFD
(A) Representative images of Toluidine Blue staining on joint articular cartilage from WT mouse
knee joints. (B) Representative images of Toluidine Blue staining on joint articular cartilage from
F814 mouse knee joints. (C) Osteoarthritis evaluation. OARSI score 0-4: No OA; 5-9: Mild OA; 10-
14: Moderate OA; 15 and over: Severe OA. Synovitis evaluation. Synovitis score 1-4: low grade;
5-9: high grade. Multiple Mann-Whitney test with FDR = 10% was used for statistical analysis, qvalues less than 0.05 were considered significant. OARSI and synovitis scores were determined
by Nancy Liu.
2.2.5 F814 mice was protected from inflammation-induced disturbance in the neuro stem cell
niche.
Exhaustion of stem cells is known to be a major hallmark of aging leading to reduced regenerative
potential in various tissue (Franceschi et al., 2018). Neural stem and progenitor cells diminish
with age and obesity (Park et al., 2010), likely contributing to the cognitive decline observed in
aged, obese animals (Gontier et al., 2018). The hippocampus, a critical brain region for memory
formation and learning, harbors neural stem cells that continuously replenish neurons into
adulthood (Gonçalves et al., 2016). The dentate gyrus of the hippocampal region of brains from
12-month-old F814 and WT mice on ND or HFD were assessed for neurogenesis. Cells with radial
glial branch morphology that are positive for Nestin are counted as quiescent neural stem cells
ND HFD
0
5
10
15
20
OARSI Score
WT
F814
0.4086 0.0388
ND HFD
0
2
4
6
8
10
Synovitis Score
WT
F814
>0.9999 0.3915

40
(NSC). Among these cells, MCM2 positive cells mark cells under mitosis, indicating proliferating
NSCs. Doublecortin (DCX) marks a microtubule protein involved in cell migration of immature
neurons, indicating neurogenesis. We observed there was no significant difference in the NSC
number and neurogenesis even when the mice were put on HFD (Figure 27A, 27C). However, WT
mice on HFD showed a substantial decrease in proliferating NSCs, suggesting inflammationinduced niche disturbance (Figure 27B). F814 mice on HFD, on the other hand, maintained NSC
proliferation levels similar to ND controls (Figure 27B).
A B C
Figure 27. Neuro stem cell and neurogenesis of F814 and WT mice on HFD
(A) Nestin+ cells with radial glial branches are quiescent neural stem cells (NSCs). (B) Nestin+
cells with radial glial branches that are also Mcm2+ indicate proliferating NSCs. (C) DCX+ cells
mark newly born neurons. 2-way ANOVA with multiple comparisons with Tukey correction was
used for statistical analysis, q-values less than 0.05 were considered significant. Data generated
by Jonathan Levi.
ND HFD
0
5
10
15
20
Proliferating NSC
MCM2+ NSCs (%)
WT
F814
0.0859
0.0002
0.6553
0.0016
ND HFD
0
5×103
1×104
1.5×104
2×104
Neurogenesis
Dcx+/mm3
WT
F814
0.3322
0.8038
0.9216
0.9721
ND HFD
0
5×103
1×104
1.5×104
2×104
2.5×104
Neural Stem Cells
Nestin+/mm3
WT
F814
0.7570
0.3478
0.9968
0.7860

41
2.3 Materials and Methods
2.3.1 Generation of Mutant Mouse and Treatments
All experimental procedures were approved by the Institutional Animal Care and Use Committee
of the University of Southern California and met or exceeded the requirements of the Public
Health Service/National Institutes of Health and the Animal Welfare Act.
Selection and synthesis of Cas9 mRNA and sgRNA (5’ AAAATGTGAAATCTCTGGACAGG 3’) to
gp130 target region was provided by PNA Bio and targeting efficiency of the sgRNAs used for the
knock-in experiment was evaluated by surveyor nuclease assay to detect the sgRNA with highest
DNA cleavage efficiency. Microinjections by USC Transgenic Core were performed at one-cell
stage embryo using C57BL/6J (WT) mouse strain. Mice genotyping including PCR optimization,
amplicon production and purification, and Sanger sequencing for the CRISPR region was
performed by Azenta Life Sciences/GeneWiz (La Jolla, CA) as fee for fee-for-service to verify the
successful edit of the region of interest upon obtaining the genomic DNA from the F814 and WT
mouse. All animals used in this study were male.
F814 mutant and WT mice were fed a 60% high-fat diet (HFD) (Envigo, TD.06414) from 2 months
old for 10 months. Normal diet control mice were fed a standard rodent diet that contains 13%
fat (PicoLab, 5053). F814 and WT mice on a normal diet or HFD were sacrificed at 12 months old.
2.3.2 Animal Sacrifice and Sample Collection
2.3.2.1 Peripheral blood collection and cardiac perfusion

42
A mouse is put under anesthesia in an isoflurane chamber connected to an isoflurane vaporizer.
Peripheral blood is collected from the submandibular vein using a 25G needle or lancet. About
200 μL is collected in a MiniCollect EDTA tube (VWR, 76343-512) for WBC differential. The rest of
the peripheral blood is collected in a MiniCollect Serum tube (VWR, 95057-286). Put a nose cone
connected to the isoflurane vaporizer to maintain the animal under anesthesia. Wet the fur of
the ventral skin surface with 70% ethanol and wipe with gauze and make a 5-6 cm incision
through the skin and body wall just below the ribs. Using the Metzenbaum scissors (blunt scissors)
carefully incise along the length of the diaphragm, then continue through the ribs on each side
of the thorax until the sternum can be lifted away. Fold back the rib cage and fix it to expose
thoracic organs. Fill up 12 mL syringe with Perfusate (10 units/mL Heparin in PBS) and put on the
blue needle tip (BD, 309626). Cut the right atrium and push the needle into the left ventricle and
slowly push the liquid (1mL/min). After perfusing at least 10 mL of Perfusate, confirm the
euthanization by cervical dislocation.
2.3.2.2 Mouse tissue collection and process
Soft tissues for histology: Collect the entire brain except the cerebellum, small pieces (~1cm
diameter) of liver and visceral fat. Fix them in 4% PFA at 4°C overnight. Transfer the brain to 15%
sucrose solution and then transfer to 30% sucrose solution after two days. Keep the brain in 30%
sucrose at 4°C until cryosection. The liver and fat tissue are transferred to 70% EtOH and before
paraffin embedment.
Soft tissue for other assays: Collect cerebellum, liver, and visceral fat and snap-freeze them in
liquid nitrogen. Keep it in -80°C freezer until needed.

43
Joint: Collect an entire joint from a hind limb and put it in 4% PFA at 4°C overnight. Transfer the
joint to 70% EtOH. After μCT scanning, the joint must be decalcified in 14% EDTA for 10 to 15
days before paraffin embedment. (Acid decalcification is not compatible with TRAP staining.)
Bone marrow: Collect the bone from the other hind limb, sternum, humerus, and pelvis and grind
them using mortar and pestle. Rinse with ice cold 2% FBS PBS to collect the bone marrow.
Collected bone marrow in 2% FBS PBS is filtered through 70 μm cell strainer. Centrifugate at 300
xg for 10 minutes and resuspend the pellet with 3 mL 2% FBS PBS. Carefully lay the cell suspension
on top of 3 mL Ficoll-paque (Sigma, GE17-1440-02), and then rinse the tube with 1 mL 2% FBS
PBS and add on top of Ficoll-paque. Centrifugate at 300 xg with acceleration 2 and without brake
for 5 minutes for density grandient centrifugation. After the centrifugation, collect the PBMC
layer and wash with 10 mL 2% FBS PBS. Resuspend the cells in 1 mL PBS and mix with 9 mL NH4Cl
(Stemcell, 07850) and incubate on ice for 10 minutes to lyse red blood cells. Wash the cells twice
in 10 mL 2% FBS PBS and resuspend cells in 3 mL of freezing media (10% DMSO 20% FBS DMEM).
Aliquot 1 mL in each cryovile and put it in Mr.Frosty (Nalgene, NL51000001) to viably freeze the
cells in -80°C freezer.
Adipose tissue cells: Collect white adipose tissues (WAT) from visceral fat and inguinal fat pad.
Place the tissue in 10 cm petri dish, with cold 10 mL Digestion buffer (HBSS with 0.5% BSA, Type
I & II collagenase at 1mg/mL). Mince the tissue into small pieces and transfer to a 50 mL falcon
tube. Rinse the petri dish with Digestion buffer and add it to the 50 mL tube, raise the volume to
40 mL with Digestion buffer. Incubate the tube at 37°C for 40 – 60 minutes on a rocker/rotator,
pipette up and down to facilitate digestion every 20 minutes. When the mixture becomes
homogenous, add 800 ul of EDTA (0.5M solution) to 40 mL mixture (final concentration 10mM)

44
and incubate at 37°C for 5 min to dissociate cells from adipocytes. Filter the mixture through 100
μm cell stainer, pull from the bottom so the top layer of fat does not block the filter, and leave
the top layer. Add 20 mL 2% FBS PBS to the filtered mixture and centrifuge at 300 xg for 10 min.
Resuspend in 0.5 mL PBS and 4.5 mL Ammonium Chloride, and incubate on ice for 5 min. Wash
the cells twice in 10 mL 2% FBS PBS and resuspend cells in 2 mL of freezing media (10% DMSO
20% FBS DMEM). Aliquot 1 mL in each cryovile and put it in Mr.Frosty (Nalgene, NL51000001) to
viably freeze the cells in -80°C freezer.
2.3.3 Dual-energy X-ray absorptiometry (DEXA) scanning
Euthanized mice were scanned using iNSiGHT DEXA scanner (OsteoSys). Low energy at 60 kV and
high energy at 80 kV, 0.80 mA current, 5 seconds of scanning at each energy level. An embedded
software was used to compile the images and calculate the mass and area of fat and bone mineral
content.
2.3.4 ELISA for serum cytokine/protein
Peripheral blood was collected from the submandibular vein and left to clot for 2 hours at room
temperature before centrifuging for 20 minutes at 2000 x g. Collected serum was flash-frozen in
liquid nitrogen and kept in -80°C until the assay. ELISA kit was purchased from R&D system and
experiment was performed following the manufacturer’s instructions; Mouse CRP (MCRP00),
Mouse IL-6 (M6000B), Mouse CCL2/MCP-1 (MJE00B). CRP ELISA was done in 1:2500 dilution, IL6 in 1:2, and MCP-1 in 1:3.

45
2.3.5 White blood cell (WBC) differential
Mouse blood was collected from the submandibular vein in EDTA-coated vials and kept in ice
until the assay. WBC differential was performed by IDEXX BioAnalytics.
2.3.6 Quantitative real-time PCR
Total RNA was extracted using the RNeasy Mini Kit (Qiagen) following the manufacturer’s
protocol. For tissue RNA extraction, less than 30 mg of tissue was put in a microcentrifuge tube
with 700 µL of digestion buffer (10µL β-Mercaptoethanol in 1 mL RLP buffer), and ground with a
plastic pestle (DWK, 749521-1590) on ice. The lysate was centrifuged for 3 min at full speed and
the supernatant was used for RNA extraction. cDNA was generated using the Maxima First Strand
cDNA Synthesis Kit (Thermo Scientific). Power SYBR Green (Applied Biosystems) was used for RTPCR amplification and detection was performed using ViiA7 (Life Technologies) or Step One Plus
Real-Time PCR system(Applied Biolsystems). The comparative Ct method for relative
quantification (2−ΔΔCt) was used to quantitate gene expression, where results were normalized
to Rpl7 (ribosomal protein L7). Primer sequences used were: housekeeping gene Rpl7: forward
5’ ACCGCACTGAGATTCGGATG 3’; reverse 5’ GAACCTTACGAACCTTTGGGC 3’, Ccl2: forward 5’
TTAAAAACCTGGATCGGAACCAA 3’; reverse 5’ GCATTAGCTTCAGATTTACGGGT 3’, Tnf: forward 5’
GACGTGGAACTGGCAGAAGAG 3’; reverse 5’ TTGGTGGTT TGTGAGTGTGAG 3’, tnfsf11: forward 5’
CAGCATCGCTCTGTTCCTGTA 3’; reverse 5’ CTGCGTTTTCATGGAGTCTCA 3’.
2.3.7 RNA sequencing library preparation and sequencing
Total RNA was isolated using QIAGEN RNeasy Mini kit (Qiagen) and quantified using Qubit fluorometer
(ThermoFisher Scientific). Quality of the isolated RNA was checked using Agilent Bioanalyzer 2100.
Universal Plus mRNA-Seq Library with NuQuant (TECAN) was used to generate stranded RNA-seq libraries.

46
Briefly, poly(A) RNA was selected followed by RNA fragmentation. Double stranded cDNA was generated
thereafter using a mixture of random and oilgo(dT) priming. The library was then constructed by end
repairing the cDNA to generate blunt ends, ligation of Unique Dual Index (UDI) adaptors, strand selection
and PCR amplification. Different adapters were used for multiplexing samples in one lane. The quality of
the purified libraries was further assessed using Qubit fluorometer and Agilent Tapestation. Libraries were
pooled and sequencing was performed at UCLA Technology Center for Genomics & Bioinformatics (TCGB)
core on NovaSeq SP/ X Plus with paired end 50 base pair reads. Data quality check was done on Illumina
SAV. Demultiplexing was performed with Illumina CASAVA 1.8.2.
2.3.8 RNA sequencing data analysis
Quality of the raw fastq files were determined using FastQC (v0.11.9)
(https://www.bioinformatics.babraham.ac.uk/projects/fastqc/). Adapters were trimmed using
Cutadapt(Martin, 2011). Trimmed and filtered reads were aligned to mouse reference genome (mm39-
GENCODE Release M30) using STAR aligner (version 2.7.8a)(Dobin et al., 2013). Transcript levels were
quantified to the reference using a modified expectation-maximization (EM) algorithm. Normalization was
done using median ratio method. Differential expression analysis was performed using
DESeq2 (v3.5)(Love et al., 2014). Genes were considered to be differentially expressed based on fold
change>1.5 and p-value<0.05. Functional enrichment analysis for the differentially expressed genes was
performed using Ingenuity Pathway analysis (IPA, Qiagen). Heatmaps were generated in R (v4.2.3) using
pheatmap package (v1.0.12).
2.3.9 Picro Sirius Red staining
Mouse livers fixed in 4% PFA were embedded in paraffin and cut at a thickness of 5 µm. Sections were
deparaffinized and rehydrated by serial incubation in 100% Xyline, 100% EtOH, 95% EtOH, 80% EtOH,
70% EtOH, and DI water. Sections were stained with Picro-Sirius Red Stain Kit (Abcam, ab15068)

47
according to the manufacturer’s instructions. Stained sections were imaged using a Zeiss Axio
Imager.A2 Microscope Axiocam 105 color camera at three random locations. Positive staining
was quantified using ImageJ and an average of three images per sample was used for analysis. In
ImageJ, the image was loaded and the RGB color channels were split. Green channel image was
used for threshold adjustment and the quantified particle area was used as positive staining area.
2.3.10 Immunohistochemistry (IHC) for macrophages
Mouse livers and visceral adipose tissues fixed in 4% PFA were embedded in paraffin and cut at
a thickness of 5 µm. Sections were deparaffinized and rehydrated by serial incubation in 100%
Xyline, 100% EtOH, 95% EtOH, 80% EtOH, 70% EtOH, and DI water. Antigen was retrieved by
incubating in Tris HCL pH 10 (Sigma) at 95 °C for 20 minutes and then left on a bench at room
temperature for 20 minutes. Sections were blocked with 2.5% normal horse serum for 1 h at
room temperature. Sections were incubated with CD68 primary antibody (Invitrogen, PA5-
178996) in 1% BSA in 1:100 dilution at 4 °C overnight. Slides were washed and incubated at room
temperature for an hour in secondary antibody-HRP (Vector Laboratories, MP-7401). Antibodies
were then visualized by peroxidase substrate kit DAB (Vector Laboratories, SK-4100). Sections
were counterstained with Hematoxylin (Vector, H-3401) for 1 min. Slides were imaged using a
Zeiss Axio Imager.A2 Microscope Axiocam 105 color camera with Zen 2 program at three random
locations. Positive stain was quantified using ImageJ and an average of three images per sample
was used for analysis. In ImageJ, the image was loaded and the RGB color channels were split.
Blue channel image was used for threshold adjustment and the quantified particle area was used
as positive staining area.

48
2.3.11 Micro-computed tomography (μCT) data collection and analysis
Mouse legs were dissected and fixed in 4% PFA for 24 hour and scanned with XT H 225 ST (Nikon)
in 20 µm resolution, at 80 kV energy, 120 μA current, and 9.6 W power at USC Molecular Imaging
Center. Trabecular bone under the growth plate near the proximal tibia was reconstructed using
Amira (Thermo Fisher Scientific). Horizontal sections were used to set the area of interest and
total of 50 sections were used to quantify 1 mm length of tibia bone mineral density by bone
volume over total volume (BV/TV).
2.3.12 Flow cytometry analysis for bone marrow and adipose immune cells
Cells were incubated for 1 hour in fluorescent conjugated primary antibody cocktail made in 2%
FBS PBS. Cells were then washed once with 2% FBS PBS and resuspended in DAPI in 2%FBS PBS
(1:5000) and flow cytometry was performed on a BD FACS Aria II cell sorter.
For adipose tissue immune cells, populations of interest based on single cells that are negative
DAPI (Fisher Scientific, 5748) expression and surface marker expressions Ly6C, Ly6G, CD11b, and
F4/80 (BioLegend, 128005, 127639, 123131, 101216) were used.
For hematopoietic stem cells, bone marrow cells were stained using BD Stemflow™ Mouse
Hematopoietic Stem and Progenitor Cell Isolation Kit (BD, 560492) following the manufacturer’s
instructions.
For skin stem cells, populations of interest based on single cells that are negative DAPI (Fisher
Scientific, 5748) expression and surface marker expressions ITGA6 (Invitrogen, 12-0495-82),
ITGB1(BioLegend, 102215), CD34 (Invitrogen, 11-0341-82), Sca1 (BioLegend, 122513) were used
(Kostic et al., 2017).

49
All flow cytometry data was analyzed using FlowJo software.
2.3.13 TRAP staining and quantification
Mouse legs were dissected and fixed in 4% PFA for 24 h, then decalcified with 14% EDTA (pH 7.4)
for 21 days at 4 °C. Tissues were embedded in paraffin and cut at a thickness of 5 µm.
Deparaffinized and rehydrated sections were incubated in 50 mL TRAP staining medium (110 mM
Sodium Acetate (Sigma, S-2889), 50 mM Tartaric Acid (Sigma, T-6521), 4.5 mM Naphthol AS-BI
Phosphate (Sigma, N-2125) in distilled water) for 1 hr at 37°C. After incubation, 1 mL of
Pararosaniline Dye in Sodium Nitrite solution is mixed into the medium and incubated for 30 min
at 37°C. Sections are counter stained with 0.08% Fast Green for 90 sec. To quantify TRAP staining,
images were taken from three different locations per sample. Slides were imaged using a Zeiss
Axio Imager.A2 Microscope Axiocam 105 color camera with Zen 2 program at three random
locations. Positive stain was quantified using ImageJ and an average of three images per sample
was used for analysis.
2.3.14 OARSI scoring and synovitis scoring
Mouse legs were dissected and fixed in 4% PFA for 24 h, then decalcified with 14% EDTA (pH7.4)
for 21 days at 4 °C. Knee joint tissues were embedded in the sagittal plane in paraffin and cut at
a thickness of 5 µm. For osteoarthritis grade evaluation, deparaffinized and rehydrated sections
were stained in 0.4% Toluidine Blue solution for 10 min at room temperature and counterstained
in 0.02% Fast Green for 3 min. Research Society International (OARSI) scoring performed as
described previously (Glasson et al., 2010). For synovitis grade evaluation, deparaffinized and
rehydrated sections were stained in Mayers Hematoxylin for 1 minute and counterstained in
alcoholic-Eosin for 1 minute. H&E staining and synovitis scoring were performed as described

50
previously (Krenn et al., 2006). Observers performing the analysis were blinded from the sample
IDs.
2.3.15 Mesenchymal stem cell (MSC) culture and osteogenesis
F814 and WT bone marrow cells were cultured for 10 days in MesencultTM Expansion Kit for
Mouse (Stemcell tech, 05513) following the manufacturer’s instructions. After MSC expansion,
cells were plated at 10,000/well in a 24-wells plate. When cells reached 80% confluency, cells
were cultured in Complete Osteogenesis Differentiation Medium (StemPro, A1007201) for 14 to
20 days with or without 20 ng/mL hyper IL-6 (R&D, 8954-SR) or OSM (R&D, 495-MO) treatment.
2.3.16 Alizarin Red S staining and quantification
Cultured osteocytes in 24-well plate were fixed in 10% (v/v) formaldehyde at room temperature
for 15 minutes and incubated in 40mM Alizarin Red S at room temperature for 20 minutes with
gentle shaking. The wells were washed four times with water and imaged by REVOLVE
microscope (ECHO). After imaging, 10% (v/v) acetic acid was added (200 μL for 24-well plate) and
incubated at room temperature for 30 minutes with gentle shaking. All contents in the well
including the monolayer were transferred to a 1.5-mL microcentrifuge tube with a wide-mouth
pipette. The tube was incubated at 85 °C for 10 min to extract the dye. After centrifugation, the
supernatant was read in triplicate at 405 nm using Spectramax iD3 (Molecular Devices).
2.3.17 Osteoclastogenesis and quantification by TRAP staining
Mouse bone marrow was flushed from femur and tibia and plated in 10% FBS α-MEM media
supplemented with 30 ng/mL M-CSF (PeproTech, 315-02) for 3 days and then cultured in 10%
FBS α-MEM media supplemented with 100ng/mL RANKL (PeproTech, 315-11) and 30 ng/mL M-

51
CSF for 6 to 7 days. Differentiated cells were fixed in 10% (v/v) formaldehyde at room
temperature for 15 Acid Phosphatase and stained with Leukocyte (TRAP) Kit (Sigma-Aldrich,
387A).
2.3.18 Cryosection and staining of hippocampus
The brains were isolated and fixed overnight in 4% PFA, followed by incubation in 30% sucrose
solution for a subsequent 48 hours prior to sectioning. Frozen coronal sections in 45-µm thickness
through the entire dentate gyrus were performed using a sliding microtome (SM2010R, Leica,
Wetzlar, Germany). The sections were then transferred to a cryoprotectant solution (27.3%
sucrose, 45.5% glycerol, 27.3% ethylene glycol) and stored at −20°C until processing for
immunohistochemistry staining.
For Immunohistology, coronal sections of the hemisphere were stereologically sampled
throughout the entire hippocampus (5~6 sections per dentate gyrus). Secntions were mounted
on SuperFrost Plus slides (Thermo Scientific), dried overnight, rinsed in PBS, then incubated in
0.01 mol/L citric buffer (pH 6.5) for 40 min at 95~98°C for antigen retrieval. Sections were rinsed
again in PBS and incubated 2 overnights at 4°C with primary antibodies against the following
antigens: Goat anti-Nestin (R&D, AF2736), mouse anti-MCM2 (BD Laboratories, 610701), rabbit
anti-DCX (Cell Signaling Technology, 4604S). Sections were then washed with PBS and incubated
in appropriate secondary antibodies conjugated to fluorophores (Jackson Immunoresearch) with
DAPI counterstaining (Roche, 10236276001). Stained sections were washed, air dried, and
coverslipped with PVA/DABCO.
2.3.19 Quantification of NSCs and Neurogenesis

52
Images of the stained sections were acquired as a tiled z-stack across the area and the depth
containing the dentate gyrus region using a confocal microscope system (Axio.A1 Observer with
LSM700 Scanhead, Carl Zeiss, Germany) at 40X. Morphological and co-labeling analysis was done
using ZEN 2012 SP1 (black edition, Carl Zeiss, Germany). Nestin+ only cells with radial glial branch
are quiescent neural stem cells, same morphological cells that are Nestin+/Mcm2+ indicate active
neural stem cells, and DCX+ only cells repregent neurogenesis. The neural stem cell activation
rate percentages were calculated through dividing the number of active neural stem cells by the
number of total neural stem cells (both Nestin+/Mcm2- and Nestin+/Mcm2+ cells). The total
neural stem cell numbers and neurogenesis data were quantified by cells / mm3.

53
CHAPTER 3. PHARMACOLOGIC INHIBITION OF GP130/SFK SIGNALING
REDUCES SYSTEMIC CHRONIC INFLAMMATION INDUCED IN MICE BY A
HIGH-FAT DIET.
3.1 Introduction
Our previous studies showed that pharmacological inhibition of SFK signaling downstream of
gp130 leads to anti-inflammatory and anti-fibrotic effects in acute local injuries in small and large
animal models (Shkhyan et al., 2023). Previously reported SFK recruitment inhibitor R805,
developed by our group, had poor water solubility and was only suitable for local applications
(Shkhyan et al., 2023). R159, an analog of R805, was developed with an improved ADME profile
to enhance water solubility for better systemic administration (Figure 28). Similar to R805, R159
inhibited IL-6 cytokine-stimulated recruitment and activation of SFK by gp130Y814 (Figure 29A, B,
C).
To evaluate the effects of gp130Y814/SFK inactivation by R159 on systemic chronic inflammation,
1-year-old C57BL/6 mice were placed on HFD and administered R159 or vehicle (Veh) twice a
week via intraperitoneal injection for 12 weeks (Figure 30A). For this pharmacological
intervention study, older mice were used to closely model the progression of obesity-induced
multimorbidity in middle-aged humans. We also conducted additional experiments to evaluate
the effects of the drug therapy to enhance our understanding of its therapeutic potential in ageassociated chronic conditions.

54
Figure 28. Absorbance, Distribution, Metabolism, Excretion (ADME) profile of drugs R805 and
R159
TPSA (total polar surface area) range 60-140 Å² is considered good solubility and permeability.
cLogP and cLogD show predicted water solubility, cLogP less than 3 and cLogD less than 1 are
considered favorable for water solubility. pKa indicates the ionization state of the compound at
given pH. RLM/HLM show stability in rat/human liver microsomes, %LBF shows the clearance
attributed to liver blood flow. KS shows the solubility constant at a pH 7.4. MDCK WT and MDCK
MDR1 cells are used to test drug transport and permeability. A higher Papp value in the A-B
direction suggests better absorption potential and a higher Papp value in the B-A direction can
indicate strong efflux activity. EER shows an efflux ratio, an EER equal to or close to 1 suggests
balanced influx and efflux, indicating that efflux is not significantly hindering the compound's
permeability. Data generated by Charles River Laboratories.
A B
C
Figure 29. R159 treatment inhibits SRC activation
(A) Western blots for phosphorylated gp130 tyrosin814 in human
synovial fibroblast treated with or without OSM (10ng/mL) and
R159 (10 μM) for 4 hrs, n = 4. (B) Western blots for
phosphorylated SRC in human synovial fibroblast treated with or
without OSM (10ng/mL) and R159 (10 μM) for 4 hrs, n = 4. (C) IL6/gp130 activation of Src Family Kinase (SFK) via Y814 residue
was inhibited by a small molecule drug R159. 2-way ANOVA with
multiple comparisons with Tukey correction, p-values less than

55
0.05 were considered significant. Western blot and quantification was performed by
Ruzanna Shkhyan.
3.2 Results
3.2.1 Long-term treatment of R159 was safe and reduced weight gain induced by HFD.
Approximately 3-month treatment of R159 drug had no discernible adverse effects and organ
histology revealed no anomalies demonstrating its potential as a therapeutic intervention with
minimal side effects. (data not shown). Notably, mice treated with R159 gained less weight
compared to the Veh group (Figure 30B). There was no noticeable difference in white blood cell
composition between R159 and Veh groups (Figure 30C).
A B
C
Figure 30. Assessing R159's impact on aging mice on HFD
HFD-Veh
HFD-R159
0
5
10
15
Monocyte
% in WBC
0.7064
HFD-Veh
HFD-R159
0
20
40
60
80
100
Lymphocytes
% in WBC
0.4550
HFD-Veh
HFD-R159
0
5
10
15
20
25
Neutrophils
% in WBC
0.7947

56
(A) Experimental scheme to assess the effect of R159 on HFD-driven systemic chronic
inflammation. 12-month-old mice were administered HFD for 5 weeks to induce systemic
inflammation before the drug or vehicle (control) treatment began. Drug or vehicle was injected
twice a week intraperitoneally for 12 weeks while the mice were continued on HFD. Mice were 16
months old by the end of the experiment. (B) Weight change of R159 or vehicle-treated mice
during HFD administration, n= 9 per group. Multiple unpaired t-tests with FDR = 5% were used to
compare each time point, q-values less than 0.05 were considered significant. (C) White blood cell
differential of R159 or vehicle-treated mice on HFD. Two-tailed Student’s t-test, p-values less than
0.05 were considered significant.
3.2.2 R159 treatment reduced inflammatory responses in mice on HFD.
R159 treatment mirrored the F814 mutant group’s systemic inflammatory marker patterns,
significantly lowering systemic levels of MCP-1 and CRP without altering IL-6 levels compared to
the Veh-treated group (Figure 31).
A B C
Figure 31. HFD-induced systemic inflammation levels in R159 or Veh treated mice.
(A) Serum IL-6 levels of mice on HFD treated with Veh or R159 measured by ELISA. (B) Serum MCP1 levels of mice on HFD treated with Veh or R159 measured by ELISA. (C) Serum CRP levels of mice
on HFD treated with Veh or R159 measured by ELISA. Two-tailed Student’s t-test, p-values less
than 0.05 were considered significant. CRP ELISA was performed by Joshua Lee
Similar to the genetic inactivation of gp130Y814 signaling, R159 treatment attenuated the
expression of Ccl2 (MCP-1), Tnf, and Il1b in adipose tissue induced by HFD (Figure 32). Adipose
tissue from R159-treated mice on HFD showed reduced macrophage infiltration compared to
HFD-Veh
HFD-R159
0
5
10
15
CRP
ug/mL
0.0373
HFD-Veh
HFD-R159
0
5
10
15
20
25
IL-6
pg/mL
0.7271
HFD-Veh
HFD-R159
0
100
200
300
400
MCP-1
pg/mL
0.0044

57
Veh-treated mice (Figure 33). R159-treated mice liver tissue also exhibited reduced fibrosis and
macrophage infiltration compared to the Veh counterparts (Figure 34, 35). RNA-seq analysis of
the liver showed an increase in inflammatory and fibrotic pathways in mice treated with Veh on
HFD compared to the R159 group (Figure 36A). Similar to the liver RNA-seq results of F814 vs WT
on HFD, Veh-treated mice had upregulated Ccr2, Ccr5, Cx3cr1, Spp1, Src, Tlr2, and Tlr5, suggesting
increased macrophage presence and immune response, and upregulated Col1a1, Ctsk, Mmp2,
and Pdgfc, indicating more fibrosis activity compared to R159 counterparts (Figure 36B). The
RNA-seq results also suggested enrichment of atherosclerosis-associated genes in the Veh group
compared to the R159 group (Figure 36A). Serum lipid analysis revealed that R159 treatment
significantly reduced total cholesterol and LDL/VLDL, resulting in a higher HDL to LDL/VLDL ratio
(Figure 37).
Taken together, R159 treatment effectively mitigated systemic inflammatory responses of major
metabolic organs and weight gain in mice on HFD and provided substantial protection to liver
function.
A B C
Figure 32. HFD-induced gene expression changes in adipose tissue in mice on HFD treated with
Veh or R159
HFD-Veh
HFD-R159
0.00
0.05
0.10
0.15
0.20
Ccl2 (MCP-1)
Relative expression to Rpl7
0.0035
HFD-Veh
HFD-R159
0.000
0.005
0.010
0.015
Tnf
Relative expression to Rpl7
0.0212
HFD-Veh
HFD-R159
0.000
0.002
0.004
0.006
0.008
0.010
Il-1b
Relative expression to Rpl7
0.0408

58
(A) Ccl2 (gene name for MCP-1) expression levels relative to a housekeeping gene Rpl7 in WT
mice on HFD treated by Veh or R159. (B) Tnf expression levels relative to a housekeeping gene
Rpl7 in WT mice on HFD treated by Veh or R159. (C) Il-1b expression levels relative to a
housekeeping gene Rpl7 in WT mice on HFD treated by Veh or R159. Two-tailed Student’s t-test,
p-values less than 0.05 were considered significant.
A B
111
Figure 33. HFD induced macrophage infiltration in adipose tissue in WT mice on HFD treated by
Veh or R159
(A) Representative images of CD68 staining of adipose tissue of WT mice on HFD treated by Veh
or R159. (B) Quantitative analysis of CD68 staining. Two-tailed Student’s t-test was used for
statistical analysis and p-values less than 0.05 were considered significant.
A B
Figure 34. HFD-induced fibrosis in the liver in WT mice on HFD treated by Veh or R159
HFD-Veh
HFD-R159
0
5×104
1×105
1.5×105
CD68
Arbitrary Unit
0.0004
HFD-Veh 20µm HFD-R159 20µm
HFD-Veh
HFD-R159
0
2×104
4×104
6×104
8×104
1×105
Picro Sirius Red
Arbitrary Unit
0.0078
HFD-Veh 20µm HFD-R159 20µm

59
(A) Representative images of Picro Sirius Red staining marking fibrosis in the liver tissue of WT
mice treated by Veh or R159. (B) Quantitative analysis of Picro Sirius Red staining. Two-tailed
Student’s t-test was used for statistical analysis and p-values less than 0.05 were considered
significant.

A B

Figure 35. HFD-induced macrophage infiltration in the liver in WT mice on HFD treated by Veh
or R159
(A) Representative images of CD68 staining marking macrophages in the liver tissue of WT mice
treated by Veh or R159. (B) Quantitative analysis of CD68 staining. Two-tailed Student’s t-test
was used for statistical analysis and p-values less than 0.05 were considered significant.
HFD-Veh 20µm HFD-R159 20µm HFD-Veh
HFD-R159
0
5×104
1×105
1.5×105
CD68
Arbitrary Unit
0.0030

60
A
B

Figure 36.Differential gene expressions in the
liver from WT mice on HFD treated by Veh or
R159.
(A) Enriched terms for genes upregulated in
the liver of WT mice treated by Veh compared
to R159 counterparts analyzed based on RNAseq data. (B) Heat map showing differentially
regulated genes (HFD-R159 vs HFD-Veh)
associated with inflammation and fibrosis in
the liver from bulk RNA-seq. Library
preparation and differential gene expression
analysis were performed by Arijita Sarkar.
HFD-R159 HFD-Veh Z-score

61
A B C D
Figure 37. HFD-induced lipid metabolism changes in WT mice on HFD treated by Veh or R159
(A) Total cholesterol in the serum of WT mice on HFD treated by Veh or R159. (B) High Density
Lipoprotein (HDL) in the serum of WT mice on HFD treated by Veh or R159. (C) Low Density
Lipoprotein (LDL) and Very Low Density Lipoprotein (VLDL) in the serum of WT mice on HFD
treated by Veh or R159. (D) Ratio of HDL levels to LDL/VLDL levels. Two-tailed Student’s t-test, pvalues less than 0.05 were considered significant.
3.2.3 R159 mitigates degenerative changes induced by HFD in musculoskeletal tissues.
The attenuation of systemic chronic inflammation by R159 treatment in HFD-fed mice revealed
a multifaceted therapeutic potential, significantly reducing the adverse effects of HFD. Bone loss
induced by HFD was even more severe in older mice but was significantly mitigated by R159
treatment (Figure 38). The drug treatment group showed reduced osteoclasts marked by TRAP
staining in trabecular bone sections and lower expression of the RANKL (Tnfsf11) gene in the
bone marrow compared to the Veh counterparts (Figure 39). Additionally, while the vast majority
of vehicle-treated mice on HFD exhibited more advanced OA, R159-treated HFD mice showed
trends of milder osteoarthritis and lower synovitis score, although the effects were not
statistically significant (Figure 40).
HFD-Veh
HFD-R159
0
100
200
300
400
Total Cholesterol
mg/dL
0.0102
HFD-Veh
HFD-R159
0
100
200
300
400
HDL
mg/dL
0.0637
HFD-Veh
HFD-R159
0
20
40
60
80
100
LDL/VLDL
mg/dL
0.0040
HFD-Veh
HFD-R159
0
5
10
15
20
HDL to LDL/VLDL
Ratio
0.1218

62
A B
Figure 38. HFD-induced bone density loss in WT mice on HFD treated by Veh or R159
(A) Representative 3D constructed images of trabecular bone of vehicle or R159 treated mice on
HFD. (B) Quantitative analysis on bone density. Two-tailed Student’s t-test, p-values less than 0.05
were considered significant.
A B
A
Figure 39. Osteoclast activity and RANKL expression in WT mice on HFD treated by Veh or R159
(A) Representative images of TRAP staining (red) in trabecular bone (green) of vehicle or R159
treated mice on HFD and quantitative analysis of TRAP staining. (B) Expression of RANKL
(Tnfsf11) relative to a housekeeping gene Rpl7 in bone marrow of vehicle or R159 treated mice
on HFD. Two-tailed Student’s t-test, p-values less than 0.05 were considered significant.
HFD-Veh
HFD-R159
0.0
0.1
0.2
0.3
Trabecular
Bone density
Bone Vol/Total Vol
<0.0001
HFD-Veh HFD-R159
HFD-Veh
HFD-R159
0
5×103
1×104
1.5×104
2×104
TRAP
Arbitrary Unit
0.0118
HFD-Veh
HFD-R159
0.0000
0.0001
0.0002
0.0003
0.0004
RANKL(Tnfsf11)
Relative expression to Rpl7
0.0247
20µm HFD-Veh HFD-R159 20µm

63
A B
C D
Figure 40. Osteoarthritis and synovitis evaluation of WT mice on HFD treated by Veh or R159
(A) Representative images of Toluidine Blue staining on joint articular cartilage from WT mice
on HFD treated with Veh. (B) Representative images of Toluidine Blue staining on joint articular
cartilage from WT mice on HFD treated with R159. (C) Osteoarthritis evaluation. OARSI score 0-
4: No OA; 5-9: Mild OA; 10-14: Moderate OA; 15 and over: Severe OA. (D) Synovitis evaluation.
Synovitis score 1-4: low grade; 5-9: high grade. Multiple Mann-Whitney test with FDR = 10%
was used for statistical analysis, q-values less than 0.05 were considered significant. OARSI and
synovitis scores were determined by Nancy Liu.
3.2.4 R159 treatment protects from inflammation-induced decline in neurogenesis.
In 12-month-old mice, we did not observe a significant decrease in NSC number induced by HFD
(Figure 27A). In mice, the decrease in NSC number, neurogenesis, and NSC proliferation starts as
early as 6 months of age, with a substantial decline occurring around 12 to 18 months (Gontier
et al., 2018). Thus, the 12-month-old timepoint may have been too early to detect a significant
age-related decline in neurogenesis. When we compared WT mice on ND between 12-month-old
and 16-month-old, there were significant declines in the NSC pool, neurogenesis, and NSC
HFD-Veh HFD-R159 50µm 10µm 50µm 10µm
HFD-Veh
HFD-R159
0
2
4
6
8
10
Synovitis Score
0.3257
HFD-Veh
HFD-R159
0
5
10
15
20
25
OARSI Score
0.1058

64
proliferation (Figure 41). Remarkably, R159-treated mice on HFD at 16 months old showed
strikingly improved NSC maintenance and increased neurogenesis compared to their Veh-treated
counterparts (Figure 42).
A B C
Figure 41. Neuro stem cell and neurogenesis of WT mice at 12 months old and 16 months old
(A) Nestin+ cells with radial glial branches are quiescent neural stem cells (NSCs). (B) Nestin+
cells with radial glial branches that are also Mcm2+ indicate proliferating NSCs. (C) DCX+ cells
mark newly born neurons. Two-tailed Student’s t-test, p-values less than 0.05 were considered
significant. Data generated by Jonathan Levi.
A

B

12-mo WT
16-mo WT
0
5×103
1×104
1.5×104
2×104
2.5×104
Neural Stem Cells
Nestin+/mm3
0.0023
12-mo WT
16-mo WT
0
5
10
15
20
Proliferating NSC
MCM2+ NSCs (%)
0.0015
12-mo WT
16-mo WT
0
5×103
1×104
1.5×104
2×104
Neurogenesis
Dcx+/mm3
0.0166

65
C D E
Figure 42. Neuro stem cell and neurogenesis of WT mice on HFD treated with Veh or R159
(A) Representative images of Nestin (green) or MCM (red) cells in the dentate gyrus of WT mice
on HFD treated with Veh or R159. (B) Representative images of Doublecortin (red) cells cells in
the dentate gyrus of WT mice on HFD treated with Veh or R159. (C) Quantification of NSC based
on Nestin staining. (D) Quantification of proliferating NSC based on Nestin/MCM staining. (E)
Quantification of new neurons based on Dcx staining. Two-tailed Student’s t-test, p-values less
than 0.05 were considered significant. Data generated by Jonathan Levi.
3.2.5 R159 treatment did not affect hematopoietic and skin stem cell niches.
We next tested if R159 has a protective effect in stem cell niches other than brain in mice with
HFD-induced accelerated aging. Bone marrow is the primary site of immune cell production and
hematopoietic stem and progenitor cell (HSPC) populations are tightly regulated for self-renewal,
quiescence, differentiation, and mobilization (K. Y. King & Goodell, 2011). Exhaustion of HSPC
due to HFD-induced obesity is reported to decrease the number of short-term HPSCs and
proliferating HSPCs, shifting them to higher differentiation potential (van den Berg et al., 2016).
We did not observe changes in hematopoietic stem cell and progenitor cell population with R159
treatment (Figure 43).
Age-associated hair thinning and hair loss were reported to be due to the depletion of hair follicle
stem cells (HFSC) (Matsumura et al., 2016) and HFD was shown to accelerate HFSC depletion,
HFD-Veh
HFD-R159
0
5×103
1×104
1.5×104
2×104
2.5×104
Neural Stem Cells
Nestin+/mm3
0.0234
HFD-Veh
HFD-R159
0
5
10
15
20
Proliferating NSC
MCM2+ NSCs (%)
0.0455
HFD-Veh
HFD-R159
0
5×103
1×104
1.5×104
2×104
Neurogenesis
Dcx+/mm3
0.0008

66
leading to early follicle miniaturization and hair loss (Morinaga et al., 2021). In our previous study,
genetic and pharmacologic ablation of gp130Y814 signaling improved hair follicle regeneration
after acute skin injury in mice (Shkhyan et al., 2023). We evaluated if R159 treatment improved
HFSC maintenance by flow cytometry, however, we did not observe notable differences between
Veh or R159 groups (Figure 44).
A
B C D
Figure 43. Hematopoietic stem cell and progenitor cells of WT mice on HFD treated with Veh or
R159
(A) Representative flow cytometry plots of hematopoietic stem cells and progenitor cell isolation.
Lineage-/c-Kit+/Sca1+/CD34dim were considered hematopoietic stem cells and Lineage-/cKit+/Sca1+/CD34+ were considered hematopoietic progenitor cells. (B) Quantification of Lineagecell ratio in total bone marrow cells. (C) Quantification of hematopoietic stem cells in Lineagecells. (D) Quantification of progenitor cells in Lineage- cells. Two-tailed Student’s t-test, p-values
less than 0.05 were considered significant. Data generated by Jade Tassey.
HFD-Veh
HFD-R159
0
5
10
15
20
% of singlets
Lineage -
0.1892
HFD-Veh
HFD-R159
0
2
4
6
8
10
% of Lineage -
Hematopoietic
Stem Cells
0.4513
HFD-Veh
HFD-R159
0
2
4
6
% of Lineage -
Hematopoietic
Progenitor Cells
0.3936

67
A B C
Figure 44. Hair follicle stem cells and progenitor cells of WT mice on HFD treated with Veh or
R159
(A) Representative flow cytometry plots of hair follicle stem cell and progenitor cell isolation.
ITGA6+/ITGB1+/Sca1-/CD34+ were considered hair follicle stem cells and
ITGA6+/ITGB1+/Sca1+/CD34- were considered infundibulum/interfollicular progenitors. (B)
Quantification of hair follicle stem cells in ITGA6+/ITGB1+ cells. (C) Quantification of
infundibulum/interfollicular progenitors in ITGA6+/ITGB1+ cells. Two-tailed Student’s t-test, pvalues less than 0.05 were considered significant. Data generated by Jade Tassey.
3.2.6 R159 treatment increased physical activity levels in mice on HFD.
Observed structural and molecular changes with gp130Y814 inactivation demonstrated that the
effects of chronic systemic inflammation can be mitigated in multiple tissues in mice on HFD. We
investigated whether those changes resulted in a functional improvement. Reduction in activity
levels are highly associated with aging and obesity in both animals and humans (Hamrick et al.,
2006; Johannsen et al., 2008; Wärnberg et al., 2010). We measured the voluntary activity levels
of mice on HFD treated with either R159 or vehicle via a wheel running assay (Figure 45A). R159-
treated mice maintained their activity levels despite aging and weight gain, in contrast to Vehtreated mice, which exhibited a significant decline in activity levels (Figure 45B). Interestingly,
motivation levels were not different between the two groups, suggesting that R159-treated mice
could endure longer or faster runs, indicating less frailty (Figure 45C).
HFD-Veh
HFD-R159
0
1
2
3
4
5
% of ITGA6+/ITGB1+
Hair Follicle
Stem Cells
0.7312
HFD + Veh
HFD + 159
80
85
90
95
100
% of ITGA6+/ITGB1+ Infundibulum/Interfollicular
Progenitors
0.1856

68
A B C
Figure 45. Evaluation of activity levels of WT mice on HFD treated with Veh or R159
(A) A voluntary exercise behavior was assessed through a wheel running assay. (B) Voluntary
wheel running activity was measured before and during the drug treatment to assess activity
levels. Multiple unpaired t-tests with FDR = 5% were used for the statistical analysis, q-values less
than 0.05 were considered significant. (C) Motivation for voluntary exercise behavior was
evaluated by counting the number of attempts. Multiple Mann-Whitney tests with FDR = 5% were
used for the statistical analysis, q-values less than 0.05 were considered significant.
3.3 Materials and Methods
3.3.1 Animals and Treatments
All experimental procedures were approved by the Institutional Animal Care and Use Committee
of the University of Southern California (USC) and met or exceeded the requirements of the Public
Health Service/National Institutes of Health and the Animal Welfare Act.
11 months old C57BL/6J mice were purchased from Jackson Laboratory and acclimated for 3
weeks. The mice were put on a 60% high-fat diet (HFD) (Envigo, TD.06414) for 5 weeks to induce
obesity before drug or vehicle treatment began. Mice were 13 months old when drug or vehicle
treatment began and were continuously put on a high-fat diet during the 12-week drug/vehicle
treatment period. Drug or vehicle treated HFD mice were sacrificed at 16 months old. Drug R159
was dissolved in a 1% w/v Captisol solution in 0.9% saline at a concentration of 3 mg/mL and
administered via intraperitoneal injection at 10 µg per g body weight. The vehicle group was

69
injected with a 1% w/v Captisol solution in 0.9% saline by intraperitoneal injection. The injection
volume was kept at 200 µL at a time. All animals used in this study were male.
3.3.2 Hematopoietic stem cell and progenitor isolation and quantification
Bone marrow in the femur and tibia was flushed with 2% FBS PBS using a syringe. Cells were
centrifuged at 300xg for 10 minutes and resuspended in 1 mL PBS. 9mL of ammonium chloride
was added to 1 mL cell suspension and incubated on ice for 10 minutes to eliminate red blood
cells. 10 mL of 2% FBS PBS was added after the incubation and cells were centrifuged at 300xg
for 10 minutes. Cells were washed one more time in 10 mL 2% FBS PBS. Cells were resuspended
in freezing buffer (20% FBS 10% DMSO DMEM) and viably frozen and kept in -80°C until flow
cytometry.
For flow cytometry, cells from bone marrow were washed in 2% FBS PBS once and incubated in
an antibody cocktail of BD Stemflow Mouse Hematopoietic Stem and Progenitor Cell Isolation Kit
(BD, 560492) according to the manufacturer’s instruction. The kit contains a lineage cocktail that
includes antibodies for Lineage- consists of CD3, CD45R, Ly6C, Ly6G, CD11b, and TER-119, and
three specific antibodies to isolate hematopoietic stem cells (HSC) and progenitor cells (HPC);
CD34, Sca-1, and C-Kit (CD117). Among Lineage- cells, Sca-1 and c-Kit (CD117) are expressed by
both HPCs and HSCs. Then CD34 is expressed by HPCs and found to be dim to negative on HSC.
Flow cytometry was performed on a BD FACS Aria II cell sorter and data was analyzed using Flowjo.
3.3.3 Hair follicle stem cell isolation and quantification
Humanely euthanize a mouse and shave dorsal hair using an electric shaver. After shaving, use
70% ethanol to remove residual hair and disinfect skin. Carefully separate skin from fascia with

70
scissors. Place the skin on a dissection pad and scrape off fat from the skin using a blunt scalpel.
Place skin in a 100-mm culture dish with hair side facing up. Add 10 ml PBS without Ca2+ and
Mg2+ to wash the skin and aspirate PBS and add 10 ml 0.25% trypsin/EDTA. Incubate the
prepared sample at 4°C overnight. After incubation, use curved forceps and a blunt scalpel to
scrape the hair off the skin. Start at the tail and follow the direction of hair growth. In the culture
dish with scraped hair, vigorously pipette up and down hair suspension using a 10-ml pipet for a
few minutes to break up all hair clumps. Aspirate PBS from the dish with the hairless skin and use
it to rinse the cell culture dish that contained the hair suspension. Transfer it to the 50-ml tube.
Use a 10-ml pipet to mix the suspension in the tube and then filter it by passing through a 70-μm
cell strainer fitted onto a 50-ml tube. Wash the cells with 2% FBS PBS. Resuspend the cells in
freezing buffer (20% FBS 10% DMSO DMEM) and viably freeze the cells in -80°C.
For flow cytometry, skin cells were washed in 2% FBS PBS once and incubated in antibody cocktail
of ITGA6 (Invitrogen, 12-0495-82), ITGB1(BioLegend, 102215), CD34 (Invitrogen, 11-0341-82),
and Sca1 (BioLegend, 122513) for one hour and resuspended in 2% FBS PBS with DAPI (Fisher
Scientific, 5748). Populations that are negative DAPI expression and surface marker expressions
ITGA6+/ITGB1+/CD34+/Sca-1- are considered hair follicle stem cells HFSCs and
ITGA6+/ITGB1+/CD34-/Sca-1+ are considered interfollicular epidermis progenitors (Kostic et al.,
2017). Flow cytometry was performed on a BD FACS Aria II cell sorter and data was analyzed
using Flowjo.
3.3.4 Cholesterol quantification
Mice serum lipid levels were measured using Cholesterol Assay Kit (Abcam, ab65390) according
to the manufacturer’s instructions. Serum was diluted 1:75 for total cholesterol assay and

71
colorimetric assay was used to read the plate. For LDL/VLDL, 15 uL serum is diluted in 45 uL buffer
and 60 uL of 2x precipitation buffer was added. After spinning down the precipitation, the pellet
was reconstituted in 90 uL PBS and mixed with 180 uL buffer. 50uL was used for assay (1:18
dilution) and the fluorometric assay was used to read the plate. For HDL, 10 uL serum was mixed
with 140 uL buffer and 60 uL of the diluted buffer was mixed with 60 uL 2x precipitation buffer.
After spin down, 15 uL of supernatant was mixed in 135 uL buffer and 50 uL was used for assay
(1:300 dilution). The fluorometric assay was used to read the plate.
3.3.5 Voluntary activity and motivation
Mice were individually placed in a cage with access to a wheel (Panlab/Harvard Apparatus, LE904)
for 24 hours. Food and water were provided ad libitum. The wheel movement was tracked
continuously and recorded automatically in 30-minute increments by a multicounter
(Panlab/Harvard Apparatus, LE3806). The average number of wheel turns per hour was used to
assess activity levels, and the number of attempts was used to assess motivation levels.

72
CHAPTER 4. SEX DIFFERENCES IN RESPONSE TO HFD
4.1 Introduction
Female mice exhibit remarkable resistance to HFD-induced inflammation and metabolic disorder,
encompassing glucose sensitivity, bone density loss, and cognitive decline, despite experiencing
similar weight gain to their male counterparts (Gautam et al., 2014; Hwang et al., 2010;
Pettersson et al., 2012). In short-term HFD studies, young female mice demonstrate resistance
to weight gain, maintaining higher energy expenditure compared to males (Huang et al., 2020).
While the precise mechanisms underlying this reduced susceptibility to HFD in females remain
elusive, estrogen emerges as a prominent candidate due to its roles in mitigating inflammation
and metabolic stress (Litwak et al., 2014; Riant et al., 2009). Moreover, female mice are reported
to be shielded from HFD-induced metabolic alterations, attributed to the maintenance of an antiinflammatory environment in their intra-abdominal adipose tissue, notably through the
preservation of T-reg cell populations, contrasting with the inflammatory milieu observed in male
counterparts, characterized by adipose tissue inflammation, glucose intolerance,
hyperinsulinemia, and islet hypertrophy (Pettersson et al., 2012). Given these findings, we
exclusively utilized male mice in our investigation into the effects of IL-6/gp130-Y814 inhibition
on obesity-driven low-grade chronic inflammation. However, recognizing the importance of
gender diversity in research and to ensure a more robust dataset, we also conducted additional
experiments with female mice. Although the female data did not directly contribute to the main
claim of this thesis project, their inclusion provides supplementary insights and enhances the
comprehensiveness of our findings.

73
4.2 Results
4.2.1 Female mice resisted weight gain in short-term HFD but not long-term.
Consistent with previous reports, young female mice resisted weight gain during short-term HFD
administration regardless of their genotype (Figure 46A, Huang et al., 2020; Pettersson et al.,
2012). There was no significant difference in weight gain between F814 and WT female mice on
HFD (Figure 46A). However, after 16 weeks of HFD administration, female mice exhibited drastic
weight gains, reaching a similar weight to male mice by a 40-week time point (Figure 46A, B).
While aged male mice on HFD treated with R159 gained less weight than their Veh counterparts
(Figure 30B), aged female mice on HFD treated with R159 gained similar weight compared to
their Veh counterparts (Figure 46C).
A B
C D

74
Figure 46. Weight change during HFD administration for female mice
(A) Weight change of female WT or F814 mice on HFD from 2 months old to 12 months old, for a
total of 10 months. (B) Weight change of female WT and F814 mice compared to male WT and
F814 mice. WT or F814 mice were put on HFD from 2 months old to 12 months old, for a total of
10 months. (C) Weight change of aged female mice on HFD treated with R159 or Veh. 12-monthold WT female mice were put on HFD for 5 weeks before the drug or Veh treatment and kept on
HFD during the treatment. for a total of 4 months duration. HFD was administered for a total of
4 months. (D) Weight change of female WT mice with R159 or Veh treatment compared to male
counterparts. 12-month-old WT mice were put on HFD for 5 weeks before the drug or Veh
treatment and kept on HFD during the treatment. HFD was administered for a total of 4 months.
Multiple t-tests were used for the statistical analysis; q-values less than 0.05 were considered
significant.
On the other hand, the weight gain ratio of aged female mice (12 months old) was not different
from that of male mice counterparts during a 12-week short-term HFD administration (Figure
46D). Moreover, females gained weight faster after 4 weeks on HFD and caught up to the weight
of male mice after 12 week time point, despite their starting weights being significantly lower
than male mice (Figure 46D).
4.2.2 HFD elevated systemic inflammatory marker levels in female mice but to a lesser extent
than in males.
A 40-week long-term HFD administration elevated IL-6, MCP-1, and CRP levels in female WT and
F814 mice; however, these changes were not statistically significant, except for CRP (Figure 47A).
Interestingly, the elevation of MCP-1 and CRP levels induced by HFD was lesser in female mice
compared to males (Figure 47A, Figure 15). While F814 female mice on HFD had less increase of
MCP-1 and CRP levels than WT counterparts, the difference did not reach statistical significance
(Figure 47A).

75
12-month-old WT female mice on HFD treated with R159 or Veh and sacrificed at 16 monthstime
point exhibited a lesser extent of elevation in MCP-1 but similar elevation of IL-6 and CRP
compared to the male counterparts on HFD (Figure 47B, Figure 31). Mirroring the results in the
mutant, R159 treatment significantly reduced CRP levels in females on HFD compared to Vehtreated females, and although not statistically significant, IL-6 and MCP-1 levels were also lower
in R159-treated females (Figure 47B).
A
B
Figure 47. HFD-induced systemic inflammation levels in female mice.
(A) Serum IL-6, MCP-1, and CRP levels of WT and F814 mice on ND or HFD measured by ELISA. 2-
way ANOVA with multiple comparisons with Tukey correction was used for statistical analysis, qvalues less than 0.05 were considered significant. (B) Serum IL-6, MCP-1, and CRP levels of WT
mice on HFD treated with Veh or R159 measured by ELISA. Two-tailed Student’s t-test, p-values
less than 0.05 were considered significant.
ND HFD
0
50
100
150
200
MCP-1
pg/mL
WT
F814
0.8725
0.2191
0.6519
0.1901
ND HFD
0
5
10
15
CRP
ug/mL
WT
<0.0001
F814
0.2171
0.0092
0.5724
ND HFD
0
5
10
15
20
25
IL-6
pg/mL
WT
F814
0.9806
0.3088
0.0681
0.3747
HFD-Veh
HFD-R159
0
50
100
150
MCP-1
pg/mL
0.2728
HFD-Veh
HFD-R159
0
5
10
15
20
CRP
ug/mL
0.0029
HFD-Veh
HFD-R159
0
10
20
30
40
IL-6
pg/mL
0.1146

76
Correspondingly, the WBC differential analysis also revealed no notable differences in monocyte
percentage between HFD and ND groups of WT and F814, and no difference between HFD WT
and F814 (Figure 48A). Lymphocyte ratio in WT female mice on HFD was significantly increased
compared to their ND controls and neutrophil ratio was lower accordingly, but there was no
significant difference between the WT and F814 within the same diet group (Figure 48B, C).
Similarly, aged WT female mice on HFD treated with Veh or R159 did not show any significant
difference in WBC ratio (Figure 48D-F).
A B C
D E F
Figure 48. HFD-induced changes in white blood cell differential in female mice.
(A) Monocyte ratio in peripheral blood analyzed from white blood cell (WBC) differential of WT
and F814 on ND or HFD. (B) Lymphocyte ratio in peripheral blood analyzed from WBC
differential of WT and F814 on ND or HFD. (C) Neurophil ratio in peripheral blood analyzed from
white WBC differential of WT and F814 on ND or HFD. (D) Monocyte ratio in peripheral blood
analyzed from white blood cell (WBC) differential of WT on HFD treated with Veh or R159. (E)
Lymphocyte ratio in peripheral blood analyzed from WBC differential of WT on HFD treated with
Veh or R159. (F) Neurophil ratio in peripheral blood analyzed from white WBC differential of WT
on HFD treated with Veh or R159. Statistical analysis: (A)-(C) 2-way ANOVA with multiple
ND HFD
0
20
40
60
80
100
Lymphocytes
% in WBC
WT
F814
>0.9999
0.0376
0.4333
0.4462
ND HFD
0
10
20
30
Neutrophil
% in WBC
WT
F814
0.9964
0.0390
0.4252
0.6582
ND HFD
0
5
10
15
Monocyte
% in WBC
WT
F814
0.9998
0.9998
>0.9999
0.9996
Veh-HFD
159-HFD
0
5
10
15
Monocyte
% in WBC
0.1665
Veh-HFD
159-HFD
0
20
40
60
80
100
Lymphocytes
% in WBC
0.5636
Veh-HFD
159-HFD
0
10
20
30
Neutrophil
% in WBC
0.8400

77
comparisons with Tukey correction, p-values less than 0.05 were considered significant. (D)-(F):
Multiple t-test, q-values less than 0.05 were considered significant.
4.2.3 Female mice did not show significant bone density changes induced by HFD.
The trabecular bone density of females on ND was much lower than that of their male
counterparts (Figure 49A, Figure 23). Interestingly, female mice on HFD did not show significant
bone density loss compared to ND groups regardless of their genotypes (Figure 49A). Similarly,
aged females on HFD with R159 or Veh treatment showed similar trabecular bone density (Figure
49B).
A B C D
Figure 49. HFD-induced bone density loss in female mice on HFD.
(A) Representative 3D constructed images of trabecular bone of WT or F814 female mice on HFD.
(B) Quantitative analysis on bone density. 2-way ANOVA with multiple comparisons with Tukey
correction was used for statistical analysis, q-values less than 0.05 were considered significant.
(C) Representative 3D constructed images of trabecular bone of WT female mice on HFD treated
with Veh or R159. (D) Quantitative analysis on bone density. Two-tailed Student’s t-test, p-values
less than 0.05 were considered significant.

78
CHAPTER 5. DISCUSSIONS AND FUTURE DIRECTIONS
Recent literature highlights gp130 and similar major receptors as complex multimodal sensors,
not mere on/off switches, finely tuning diverse signaling pathways (Garbers et al., 2015;
Murakami et al., 2019; Nusse & Clevers, 2017). The findings suggest that selectively modulating
a non-canonical gp130 signaling presents a unique therapeutic potential by preserving beneficial
canonical signaling pathways while offering a broader impact than specific receptor blocking by
affecting all IL-6 family cytokine signaling. This approach could prove especially beneficial in
addressing systemic chronic inflammation associated with aging and obesity, where a delicate
balance between inflammation resolution and maintaining essential physiological functions is
crucial.
The gp130 receptor primarily activates the JAK/STAT3 signaling pathway which is crucial for
regulating immune responses, skeletal development, metabolic homeostasis, and regeneration
(Liu et al., 2022; Sano et al., 2008; Sims, 2020). In our recent study, we have identified a novel
non-canonical signaling pathway activated by tyrosine (Y) 814 residue within the gp130 receptor
that is responsible for the activation of inflammation and fibrosis by SRC kinases (Shkhyan et al.,
2023). We have demonstrated that this signaling can be genetically and pharmacologically
inactivated independently of the canonical arm of gp130-JAK/STAT3 pathway and resulted in
therapeutically beneficial outcomes in several injury models (Shkhyan et al., 2023). The receptor
modulation strategy, rather than a complete blockade, is fundamentally different from the
existing therapeutic approaches. For example, monoclonal antibodies for IL-6, such as
tocilizumab, not only block both canonical and non-canonical downstream signaling, but they
also have no effect on other IL-6 family members, including OSM, IL-11, and CNTF (Mihara et al.,

79
2005; Oldfield et al., 2009). Since all IL-6 members utilize gp130 as the signaling co-receptor,
gp130 modulation may not only overcome the negative consequences of complete gp130
blockade that are well-documented (Fasnacht & Müller, 2008), but also selectively change the
signaling induced by all members of this large family of cytokines. This conceptual innovation was
further advanced in the current study using a mouse model of HFD-induced model of chronic
inflammation and multimorbidity.
This dissertation study demonstrates that inactivation of a non-canonical gp130 Y814/SFK
signaling in both F814 mutant and R159 drug-treated mice exhibited a diminished inflammatory
response to HFD in adipose tissue and liver, the major metabolic organs. This led to significantly
lower systemic inflammation, as evidenced by reduced MCP-1 and CRP levels in F814 and R159-
treated mice compared to WT or Veh-treated counterparts. The upregulation of MCP-1 (Ccl2)
expression in adipose tissue induced by HFD contributes to monocyte recruitment and
macrophage infiltration in adipose tissue and the liver (Kamei et al., 2006; Kanda et al., 2006; Oh
et al., 2012). Our data show that the disruption of IL-6/gp130/SFK activation attenuates the
upregulation of Ccl2 along with other typical pro-inflammatory markers, such as Tnf and Il-1b, in
the adipose tissue. RNA-seq of the liver tissue revealed reduced expression of Ccr2 and Ccr5 in
both F814 mice and R159-treated mice compared to their respective control groups, indicating
decreased recruitment of macrophages. This was further validated by reduced CD68 staining in
the liver sections, and significantly lower systemic CRP levels reflect an attenuated liver
inflammatory response. CRP production is primarily induced in hepatocytes by IL-6; CRP is a
sensitive clinical marker for systemic inflammation and is known to have a positive association

80
with increasing age and BMI, reflecting the low-grade chronic inflammation characteristic of
aging and obesity (Puzianowska-Kuźnicka et al., 2016; Visser et al., 1999).
Histological examination and RNA-seq of the livers showed that WT and Veh-treated mice fed
HFD had not only more macrophages but also more severe liver fibrosis compared to F814 and
R159-treated mice. Non-alcoholic fatty liver disease (NAFLD), precipitated by obesity from HFD,
is characterized by excess fat accumulation, fibrosis, and increased immune cell presence
(Godoy-Matos et al., 2020). NAFLD may progress to more severe stages like steatohepatitis,
cirrhosis, and hepatocellular carcinoma if left untreated (Kim et al., 2021), underscoring the
clinical importance of effective interventions. Our findings align with existing literature that
demonstrates the inhibition of SFK can alleviate liver fibrosis caused by chemical injuries and
metabolic stress (Du et al., 2020; Seo et al., 2020), suggesting gp130 Y814 as a promising
therapeutic target for NAFLD. While exploring these implications for NAFLD falls beyond our
current scope, our results encourage further investigation.
Remarkably, F814 mutant and R159-treated mice were protected against the loss of trabecular
bone and the degeneration of cartilage typically prompted by chronic inflammation in aging and
obesity. Bone remodeling, a dynamic process involving osteoblasts constructing the bone matrix
and osteoclasts breaking it down, can be disrupted by chronic inflammation, often leading to
bone density loss (Abdelmagid et al., 2015; Mundy, 2007). IL-6 family cytokines influence this
process by regulating RANKL production, which is pivotal for osteoclast differentiation (Boyle et
al., 2003). The current study found that inhibition of gp130 Y814 signaling significantly reduced
RANKL transcription upon hyper-IL-6 stimulation in vitro, as well as in obesity-driven systemic
inflammatory conditions in vivo. Furthermore, the crucial role of SRC kinases in osteoclast

81
function is demonstrated by osteopetrosis in SRC-deficient mice (Soriano et al., 1991). Therefore,
inhibiting IL-6/gp130/SFK signaling provides a dual protective mechanism against bone density
loss in a chronic inflammatory condition by reducing RANKL transcription and SFK activity.
Additionally, SFK activity is reported to be critical to cartilage degeneration by promoting
cartilage matrix degradation and synovial inflammation (Goldring, 2023; Miao et al., 2023;
Novikov et al., 2021). Previous studies by our group demonstrated genetic or pharmacologic
inhibition of gp130 Y814 signaling enhances cartilage regeneration in post-traumatic
osteoarthritis models in mice and dogs (Shkhyan et al., 2023). While we observed attenuated
cartilage degeneration in both F814 and R159-treated mice compared to their respective control
groups, the effect was more substantial in the F814 groups than in the R159-treated group. This
discrepancy is likely attributed to the limitations of systemic administration affecting the drug’s
bioavailability within the synovial capsule, resulting in less effective cartilage protection
compared to direct intra-articular injection.
Systemic chronic inflammation suppresses neurogenesis in humans and mice (Kempuraj et al.,
2016), and HFD is reported to exacerbate neurodegeneration in the hippocampus by disrupting
the blood-brain barrier, especially in aged mice (Tucsek et al., 2014). Neurogenesis in the
hippocampus continues into adulthood and has functional association with learning, memory,
and mental health (Peng & Bonaguidi, 2018).
. We observed that 12-month-old WT mice on HFD
exhibited a significant reduction in neural stem cell (NSC) proliferation, whereas F814 mice
retained a comparable proliferation rate with ND controls. Notably, 16-month-old mice on HFD
treated with R159 showed substantially better NSC number, NSC proliferation, and neurogenesis
compared to the Veh group. While reduced levels of systemic inflammation may attribute to the

82
protective effect of R159 against neurodegeneration induced by HFD, the striking differences in
NSC niche preservation and neurogenesis suggest a potentially unknown role of IL-6/gp130-Y814
signaling in brain health, warranting further investigation.
IL-6 is a major cytokine of the senescence-associated secretory phenotype (SASP), a complex mix
of factors secreted by senescent cells that can influence inflammation and tissue remodeling by
affecting the surrounding cells and tissue environment (Freund et al., 2010). Cell senescence and
SASP not only increase with aging but also with an increasing BMI, which is why obesity is
considered a form of accelerated aging (Tchkonia et al., 2010). SASP-driven systemic chronic
inflammation is associated with dementia, depression, atherosclerosis, cancers, diabetes, and
mortality (Tchkonia et al., 2013). These morbidities often coexist in aging and obesity, making it
hard to treat the root cause and multimorbidity-driven systemic chronic inflammation
perpetuates a pathological feed-forward loop of inflammaging (Franceschi et al., 2018).
Eliminating senescent cells, senolytics, has shown promising results in animal models and human
tissues by reducing systemic chronic inflammation and diminishing signs of SASP-associated
conditions and are currently under active investigation in multiple clinical trials (Chaib et al.,
2022). However, it is a challenging task to specifically target senescent cells due to complex antiapoptotic pathway networks, and as of now, no senolytics have received FDA approval (54). Our
findings demonstrate that selective disruption of IL-6/gp130-Y814 signaling significantly reduced
the levels of systemic chronic inflammation, thereby alleviating the associated pathological
conditions. While this approach does not eliminate SASP components such as IL-6, it may help
mitigate the impact of SASP by reducing levels of subsequent systemic inflammation and

83
degenerative changes across multiple tissues. Consequently, this could lead to an improved
healthspan, exemplified by an enhancement in physical activity levels.
The current study has some limitations. although some initial ADME profile of R159 was
conducted, no detailed pharmacokinetic or pharmacodynamic studies of the drug were
performed in vivo. A detailed pharmacological assessment is required to explore the
bioavailability of the drug in the joints, central nervous system, and other locations notoriously
difficult for small molecule targeting. These studies will be essential for the optimization of the
treatment regimen in the late preclinical studies.
Collectively, this study highlights the potential of selectively targeting SFK signaling downstream
of IL-6/gp130 as an effective approach to reducing systemic chronic inflammation. While
degenerative changes and tissue senescence are unavoidable consequences of obesity and aging,
this study indicates that the related systemic immune responses and inflammation-driven
multimorbidity can be therapeutically addressed.

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APPENDIX: PHARMACOLOGIC INHIBITION OF GP130/SFK SIGNALING AMELIORATES
BLEOMYCINO-INDUCED PULMONARY FIBROSIS IN MICE
1. Introduction
Pulmonary fibrosis is a chronic and progressive lung disease characterized by the thickening and
scarring of lung tissue, with inflammation playing a large part in disease progression, leading to
severe impairment in respiratory function (Thannickal et al., 2004). Idiopathic pulmonary fibrosis
(IPF) is a particularly aggressive form of the disease that typically affects middle-aged and elderly
adults, with a median survival time of just 2-3 years after diagnosis (T. E. King et al., 2011). The
etiology of IPF remains largely unknown, and current treatments are limited to slowing disease
progression rather than reversing damage.
Bleomycin (BLM)-induced pulmonary fibrosis is the most well-established disease model for IPF
and is widely used to investigate the efficacy and mechanisms of therapeutic candidates (Della
Latta et al., 2015). In this study, alveolar injury and interstitial inflammation/fibrosis are induced
by intratracheal BLM administration. This model mimics several pathological features of human
IPF, making it a valuable tool for preclinical testing. The aim of this study is to examine the effect
of R159 on lung fibrosis in the BLM-induced pulmonary fibrosis model. Mice with BLM-induced
pulmonary fibrosis were intraperitoneally administered R159 from Day 0 to Day 20, then
sacrificed on Day 21. Samples were subsequently analyzed for fibrotic markers to evaluate the
potential efficacy of R159 for treating IPF.

85
2. Results
Mice administered BLM intratracheally (3.0 mg/kg) experienced major pulmonary inflammation
and fibrosis. Typically, 25-30% of untreated mice died within 21 days, with weight loss and an
increased lung weight to body weight ratio due to inflammatory cell infiltration and significant
collagen production (Figure 50A). Histologically, these changes were marked by significant
thickening of alveolar and bronchiolar walls, alterations in lung architecture, and eventual
extensive fibrotic extracellular matrix formation (Figure 50B). These changes are graded on the
Ashcroft scale from 0 (normal lung tissue without fibrosis) to 8 (extreme fibrosis with completely
obliterated lung architecture and extensive honeycombing throughout the section) (Ashcroft et
al., 1988) (Figure 50C). R159 treatment demonstrated clear anti-fibrotic effects in this model,
supporting weight retention, survival, and a highly significant reduction in lung fibrotic
transformation (Figure 50D,E).
A
B C
Veh R159

86
D E
Figure 51. R159 treatment resulted in improved outcomes in a mouse model of bleomycininduced pulmonary fibrosis
(A) BLM was administered intratracheally (3.0 mg/kg). Mice experienced major pulmonary
inflammation for 7 days and fibrosis occurred subsequently. 25-30% of Veh treated mice died
within 21 days. (B) Representative image of lung histology of Veh or R159 treated mice
administered BLM. (C) The Ashcroft score is a histological grading system for evaluating the extent
of pulmonary fibrosis in lung tissue samples, ranging from 0 (normal) to 8 (extreme fibrosis and
extensive honeycombing) (D) R159-treated mice maintained their body weight significantly better
than vehicle-treated mice 21 days after BLM injection. (E) R159 treatment enhanced the
probability of survival in mice with IPF. Data generated by CarthroniX, Inc.
3. Materials and Methods
1. Animals
6-week-old female C57BL/6 mice were purchased from Japan SLC, Inc. and housed and fed with
a normal diet (CE-2; CLEA Japan). All animals used in the study will be housed and cared for in
accordance with the Japanese Pharmacological Society Guidelines for Animal Use.
2. Induction of BLM-induced pulmonary fibrosis
Pulmonary fibrosis was induced in mice a single intratracheal administration of bleomycin
hydrochloride (BLM, Nippon Kayaku, Japan) in saline at a dose of 3.0 mg/kg, in a volume of 50 μL
per animal using Microsprayer® (Penn-Century, USA).

87
3. Route and doses of drug administration
R159 was administered intraperitoneally at a dose of 10 mg/kg in a volume of 5 mL/kg once daily.
4. Animal monitoring and sacrifice
The viability, clinical signs, body weight, and behavior were monitored daily. Mice were observed
for significant clinical signs of toxicity, moribundity, and mortality after each administration. The
animals were sacrificed on Day 21 by exsanguination through the abdominal vena cava under a
mixture of medetomidine (0.75 mg/kg), midazolam (4 mg/kg), and butorphanol (5 mg/kg)
anesthesia
If an animal shows >40% body weight loss compared to Day 0, and/or if it shows a moribundity
sign such as prone position, the animal was euthanized ahead of study termination. The samples
were not collected from euthanized animals.
5. Sample collection
Preparation of lung samples: Left and post-caval lobe bronchus were ligated to avoid leakage of
the fixative. The indwelling needle wasinserted into the trachea and connected to the instillation
route of the syringe. The syringe wasloaded 10% neutral buffered formalin and kept at the height
of 20 cm. Then, superior (A), middle (B) and inferior lobes (C)
were instilled 10% neutral buffered formalin and ligated after
inflation. Three fixed lobes (for shipping), unfixed left lung (E)
(for shipping) and unfixed post-caval lobe (D) (for shipping)
were harvested. Two unfixed lobes were washed with cold
saline and measured wet weight. Three fixed lobes were fixed in 10% neutral buffered formalin
A
B
C
E
D

88
for 24 hours. After fixation, these specimens were proceeded to paraffin embedding for shipping.
Post-caval lobe (D) was snap-frozen in liquid nitrogen and stored at -80°C for shipping. Left lung
(E) was snap-frozen in liquid nitrogen and stored at -80°C for shipping.
6. Analytical method of study results
Body weight: The primary data was calculated to the first decimal place. The average value and
standard deviation of each group was rounded off to the second decimal place and calculated to
the first decimal place.
Lung weight: The primary data was calculated as an integer. The average value and standard
deviation of each group was rounded off to the first decimal place and calculated as an integer.
Ashcroft Score was evaluated according to Ashcroft et al., (1988).

89
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Abstract (if available)

Abstract Systemic chronic inflammation is a key factor in the onset and progression of degenerative diseases linked to aging and obesity. Interleukin-6 (IL-6) family of cytokines are major regulators of inflammation and immune response and part of the senescence-associated secretory phenotype. IL-6 is a biomarker that demonstrates a robust correlation with age and body mass index (BMI). However, these cytokines also play a crucial role in metabolic homeostasis and tissue regeneration. Given the pleiotropic nature of IL-6 cytokines and multiple signaling pathways activated by their receptors, selective modulation of this complex signaling may offer a unique opportunity for therapeutic interventions for aging and obesity. Previously, we discovered that a non-canonical signaling pathway downstream of tyrosine (Y) 814 within the intracellular domain of gp130, the IL-6 co-receptor, is responsible for the recruitment and activation of SRC family of kinases (SFK). Mice with constitutive genetic inactivation of gp130 Y814 (F814 mice) show accelerated resolution of inflammatory response and superior regenerative outcomes in skin wound healing and posttraumatic models of osteoarthritis. This thesis focused on the effects of selective genetic or pharmacological inhibition of the non-canonical gp130-Y814/SFK signaling in systemic chronic inflammation and multimorbidity in a high-fat diet (HFD) induced model of accelerated aging. F814 mice showed significantly reduced inflammatory response to HFD in adipose and liver tissue, with significantly reduced levels of systemic inflammation compared to wild type (WT) mice. F814 mice were also protected from HFD-induced bone loss and cartilage degeneration. Pharmacological inhibition of gp130-Y814/SFK in mice on HFD mirrored the effects observed in F814 mice on HFD; furthermore, this pharmacological treatment also demonstrated a marked increase in physical activity levels and protective effects against inflammation-associated suppression of neurogenesis in the brain tissue compared to the control group. These findings suggest that selective inhibition of SFK signaling downstream of gp130 receptor represents a promising strategy to alleviate systemic chronic inflammation. Degenerative changes and tissue senescence are inevitable in obese and aged organisms, but this study demonstrated that the systemic inflammatory responses and inflammation-associated multi-morbidity can be therapeutically mitigated.

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Role of purinergic P2X7 receptors in inflammatory responses in the brain and liver: a study using a mouse model of chronic ethanol and high-fat diet exposure

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Creator Lee, Youngjoo (author)

Core Title Dissecting the role of a non-canonical interleukin-6 cytokine signaling in systemic chronic inflammation and multimorbidity induced by a high-fat diet

School Keck School of Medicine

Degree Doctor of Philosophy

Degree Program Development,Stem Cells and Regenerative Medicine

Degree Conferral Date 2024-08

Publication Date 08/23/2024

Defense Date 08/12/2024

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

Tag aging,chronic inflammation,CRP,gp-130,high-fat diet,IL-6,inflammaging,interleukin-6,MCP-1,multimorbidity,NAFLD,neuro degeneration,OAI-PMH Harvest,obesity,osteoarthritis,osteoporosis

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Language English

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Advisor Merrill-Brugger, Amy (committee chair), Bonaguidi, Michael (committee member), Evseenko, Denis (committee member), Lozito, Thomas (committee member)

Creator Email lee268@usc.edu,toyoungjoolee@gmail.com

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