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Blood-brain barrier breakdown and vessel integrity in Alzheimer’s disease

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Blood-brain barrier breakdown and vessel integrity in Alzheimer’s disease

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Content 1

Blood-brain barrier breakdown and
vessel integrity in Alzheimer’s disease

By
Ching-Ju Hsu
A Thesis Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the Requirements for the Degree
MASTER OF SCIENCE
(BIOCHEMISTRY AND MOLECULAR MEDICINE)
August 2019
2
Table of Contents
Abstract ........................................................................................................................................... 3
Introduction .................................................................................................................................... 4
Materials and Methods ................................................................................................................... 8
Human Postmortem Tissue Samples ...................................................................................................... 8
Immunohistochemistry .......................................................................................................................... 13
Imaging ................................................................................................................................................... 16
Analysis ................................................................................................................................................... 16
Statistics .................................................................................................................................................. 23
Results ........................................................................................................................................... 24
Microbleeds ............................................................................................................................................ 24
Extravascular Fibrinogen ..................................................................................................................... 26
Pericyte Coverage .................................................................................................................................. 28
Glucose Transporter 1 ........................................................................................................................... 30
Discussion ..................................................................................................................................... 32
Acknowledgment .......................................................................................................................... 35
References ..................................................................................................................................... 36

3
Abstract
Neurovascular dysfunction can initiate several pathways leading to neurodegeneration and
cognitive impairment. Many studies in live human patients and murine transgenic models have found
cerebrovascular changes and blood-brain barrier (BBB) dysfunction as early pathological hallmarks of
Alzheimer’s disease (AD) and other neurodegenerative disorders. In this study, we used
immunohistochemistry to examine a collection of AD-related neurovascular biomarkers in postmortem
tissues from 30 AD patients and 20 aged-matched controls with no cognitive impairment (NCI), covering
both hippocampal and cortical regions. The chosen biomarkers covered BBB breakdown (e.g., hemosiderin
deposits, extravascular fibrinogen, and pericyte coverage) and cerebrovascular changes (e.g., glucose
transporter 1 (GLUT1)). We found increased hemosiderin and extravascular fibrinogen deposition,
decreased pericyte coverage, decreased microvascular GLUT1 signal in AD compared to NCI cases. In
addition to presenting a comprehensive study of AD-related neurovascular biomarkers in a much larger
cohort than previous studies, this study provides standardized immunohistochemistry staining protocols
and objective quantification methods that can be followed by other researchers.

4
Introduction
Human brain consumes about 20% of the body’s total energy supply of oxygen and glucose, though it
only contributes to 2% of total body weight [31, 38]. This necessitates a proper regulation of cerebral blood
flow (CBF), as it delivers oxygen, energy metabolites and nutrients to and removes metabolic wastes from
the central nervous system (CNS) [38, 46, 84]. The neurovascular unit (NVU) plays an indispensable role
in CBF regulation [84]. It consists of vascular cells like endothelial cells, pericytes, and vascular smooth
muscle cells; glial cells like astrocytes and microglia; and neurons [84, 88]. As part of NVU, the blood-
brain barrier (BBB) is comprised of a thin layer of continuous, non-fenestrated CNS endothelial cells [53,
88]. The CNS endothelial cells have tissue specific circumferential tight junction complexes (e.g.,
OCCLUDIN, CLAUDIN 5, and ZO-1) and maintain minimal level of basal transcytosis, which render the
BBB the “sealing off” property that prevents entry of most of blood-derived metabolites to shield the brain
from potential toxins and pathogens [2, 73, 88], with the exception that small molecules like glucose can
cross the BBB through specialized receptors to meet the metabolic demand of the brain [71]. BBB integrity
is crucial for maintaining the homeostatic environment in the CNS, and its breakdown leads to increased
vascular permeability, entry of blood-derived toxins and pathogens to the brain, and is associated with
neuroinflammation, all of which will negatively affect proper neuronal functions [70, 71, 89].
Microvascular dysfunction and BBB breakdown are known to be associated with neurodegenerative
diseases such as mild cognitive impairment (MCI), Alzheimer’s disease (AD), Parkinson’s disease (PD),
and amyotrophic lateral sclerosis (ALS) [8, 20, 89, 22, 26, 39, 47, 58, 71, 76, 80]. AD is the most common
type of dementia affecting 5.7 million people nationally [1]. Clinically, it features short-term memory loss
and cognitive impairment, as well as behavior and psychological difficulties [1, 61, 86]. Pathologically, it
has primarily been characterized by extracellular aggregates of amyloid-β peptides (Aβ) and neurofibrillary
tau tangles [7, 19, 60]. Aβ is a peptide of 40-42 amino acid residues generated by the proteolytic cleavage
of amyloid precursor protein (APP) [40]. AD-causing mutations in genes APP, PS1 or PS2 usually affect
5
the production/accumulation and/or clearance of Aβ [40]. The so-called amyloid theory has prevailed in
the field and the deposition of Aβ has been considered as the cause of AD for over 20 years [36, 37].
However, the causal relationship between amyloid plaques and AD development has not been confirmed
yet and needed to be further studied [42]. Besides the accumulation of amyloid plaques and tau tangles,
vascular arteriosclerotic change was another pathological feature reported in Alois Alzheimer’s original
paper in 1907 that has not been more carefully explored until recently [69]. The two-hit vascular hypothesis
of AD proposed by Berislav Zlokovic in 2005 states that AD risk factors (genetic and/or environmental
factors) can independently and/or synergistically lead to cerebrovascular abnormalities, BBB dysfunction,
and blood flow reduction, which consequently cause neurodegeneration via Aβ-independent (hit 1) and/or
Aβ-dependent (hit 2) pathways of neurotoxicity [38, 53, 71, 84, 87]. In fact, many studies using human live
brain imaging and postmortem tissues have suggested that vascular dysfunction is the first detectable
biomarker of early AD pathogenesis [38, 52, 71, 73].
Vascular changes including CBF dysregulation, pericyte injury, BBB breakdown, and transporter
abnormalities have been observed in both AD patients and transgenic murine models of AD [53]. CBF
helps deliver nutrients to the brain and remove metabolic waste [38]. Dysregulation of CBF will lead to
chronic hypoperfusion and oligemia, which ultimately cause neuronal death [53, 84, 89]. Studies using
mouse models expressing AD-related mutations (e.g., APP, PSEN1 and APOE4) and AD patients have
shown CBF reduction and early BBB breakdown prior to Aβ plaques and tau tangles deposition [5, 50, 55].
Pericytes, part of the NVU, are crucial for maintaining BBB integrity and pericyte injury has been
reported in several studies of neurodegenerative diseases especially in AD [4, 6, 14, 64, 83]. sPDGFRβ,
one of the pericyte injury markers, has been found increased in cerebrospinal fluid from AD patients [48,
64], which has been confirmed by immunoprecipitation study using primary human mural cells from
individuals with cognitive dysfunction [52]. Reduced pericyte coverage reduction on brain capillaries has
been observed via immunohistochemistry in postmortem tissues from AD patients [35]. Moreover,
pericyte-deficient mice have been found to develop AD-like neurodegenerative phenotypes, such as neuron
6
loss and vascular damage [38, 49, 63, 85]. These evidences further supporting the role of pericyte injury
and BBB breakdown in AD pathogenesis.
Leakage of blood-derived components including fibrin(ogen), thrombin, immunoglobulin (IgG),
albumin, and hemosiderin is another phenotype of BBB breakdown [10, 13, 25, 28, 45, 62]. Accumulation
of blood-derived components has been found in both cortical and hippocampal tissues from AD patients
and murine models [35]. Consistent with this, neuroimaging studies with MRI and position emission
tomography (PET) also revealed microbleeds and iron-containing protein depositions in AD patients and
people at preclinical AD stage [5, 53]. Overall, these findings from mouse models, human live imaging,
and postmortem tissues have indicated the linkage of BBB breakdown to neurodegeneration.
Specialized transporters on the plasma membrane of CNS endothelial cells are involved in the
cross-membrane transportation of certain essential metabolic molecules [2, 70] The BBB localized glucose
transporter 1 (GLUT1) is responsible for glucose transportation into the brain [32]. GLUT1 deficiency was
found in patients with neurodegenerative diseases like AD, as well as individuals with AD associated
genetic variants [59]. Moreover, study using GLUT1-deficient Slc2a1
+/-
mice has found that decreased
GLUT1 level exacerbated AD development through accelerating cerebrovascular dysfunction, Aβ
accumulation, and eventually neuronal death [78]. Neuropathological studies of human postmortem brains
also found GLUT1 reduction in AD subjects [27]. Similar studies using immunohistochemistry also showed
reduction of LRP1 (related to Aβ clearance) and increase of RAGE (related to Aβ influx) in AD subjects
compared to age-match controls [15–17, 25, 44, 66].
As vascular changes get more and more attention for their contribution to AD and other
neurodegenerative diseases, the need for standardized protocols of immunohistochemistry and analysis has
increased. To date, most of the pathological studies assessing neurovascular dysfunction of AD have
caveats like small sample size, limited number of AD linked neurovascular biomarkers being assessed, and
lack of objective quantification methods. Therefore, a comprehensive characterization of BBB phenotypes
7
across a large cohort of AD patients is important. In this study, we investigated several AD-linked vascular
biomarkers like hemosiderin deposits, extravascular fibrinogen leakage, pericyte coverage reduction, and
GLUT1 downregulation in 50 subjects (20 controls and 30 AD), and identified BBB breakdown and
cerebrovascular abnormalities in AD patients, further confirmed previous studies [2, 25, 27, 35, 48, 62, 78].
Moreover, we described standardized methods for BBB phenotyping, which can be applied to the
characterization of additional MCI and AD cohorts and also to other neurological diseases such as ALS [20,
26, 39, 47, 80], PD [8, 22, 58, 76] and Huntington’s disease [18, 41] with neurovascular dysfunctions.

8
Materials and Methods
Human Postmortem Tissue Samples
Postmortem paraffin-embedded human prefrontal cortex (Brodmann area 9/10) and hippocampus
(level of Ammon’s horn) were obtained from the Center for Neurodegenerative Disease Research (CNDR)
of University of Pennsylvania [75]. Clinical diagnosis and neuropathological assessment were obtained as
previously described [81]. AD subjects met criteria for a clinical diagnosis of probable AD and underwent
neuropathological evaluation of AD including assignment of collapsed Braak stages (where I-II are referred
to as B1, III-IV as B2, and V-VI as B3) [21, 51] and the Consortium to Establish a Registry for Alzheimer’s
Disease (CERAD) neuritic plaque score (thioflavin stain) as described previously [30, 34]. Clinical
Dementia Rating (CDR) score, Mini-Mental State Examination (MMSE) score and disease duration were
available for most but not all individuals. NCI controls were age-matched subjects that did not carry a
diagnosis of dementia or AD. A total of 20 controls and 30 AD individuals were used for histopathological
analysis. The demographic information of all cases is provided in Table 1 and summarized in Table 2.

9
Table 1. Demographics of the NCI and AD patients participating in histological analysis.
ID
Clinical
Dx Sex Age
PMI
(hr) Atherosclerosis CERAD Braak* CAA
f

APOE
genotype
Disease
Duration
(years) MMSE CDR
100247
AD
Probable M 68 3 None/Normal 3 3 0 E3/E4 9 - -
100440
AD
Probable M 70 5 None/Normal 3 3 0 E3/E3 9 1 2
100706
AD
Probable F 74 12 Mild 3 3 1 E3/E4 6 9 2
100970
AD
Probable M 68 5 Mild 3 3 0 E3/E3 10 10 -
101229
AD
Probable M 81 10 Mild 3 3 0 E4/E4 13 18 -
101237
AD
Probable M 74 7.5 Moderate 3 3 0 E3/E4 11 - -
102690
AD
Probable M 79 13 None/Normal 3 3 1 E4/E4 5 18 1
102910
AD
Probable F 82 9 Mild 3 3 0 E3/E3 10 25 1
105055
AD
Probable F 72 12 Moderate 3 3 0 E3/E3 17 22 -
106011
AD
Probable F 70 6 Moderate 3 3 0 E3/E3 13 7 3
106203
AD
Probable M 79 6 None/Normal 3 3 0 E3/E3 3 21 -
107637
AD
Probable F 88 10.5 Mild 3 3 1 E3/E3 16 - -
108292
AD
Probable F 86 10 Mild 3 3 0 E3/E4 11 22 -
108373
AD
Probable M 76 13 Mild 3 3 1 E4/E4 14 18 -
108731
AD
Probable M 89 3 Moderate 3 3 0 E3/E4 12 1 3
108972
AD
Probable F 87 3 Moderate 3 3 0 E3/E4 11 16 0.5
10
ID
Clinical
Dx Sex Age
PMI
(hr) Atherosclerosis CERAD Braak* CAA
f

APOE
genotype
Disease
Duration
(years) MMSE
CDR

109437
AD
Probable F 90 5.5 Mild 3 3 0 E4/E4 22 0 3
109667
AD
Probable F 85 10 Mild 3 3 0 E3/E3 14 0 -
109677
AD
Probable M 91 4 Severe 3 3 0 E3/E4 7 22 2
110100
AD
Probable F 68 9 Mild 3 3 0 E3/E3 8 14 3
110252
AD
Probable M 96 7 None/Normal 3 3 0 E3/E3 4 23 1
110319
AD
Probable F 76 6.5 Mild 3 3 0 E4/E4 10 9 -
110620
AD
Probable F 84 11 Mild 3 3 1 E3/E3 6 7 3
110990
AD
Probable M 73 9 Moderate 3 3 0 E3/E3 9 - -
112137
AD
Probable M 86 12 Mild 3 3 0 E2/E3 12 10 2
112161
AD
Probable F 81 7.5 Mild 3 3 0 E3/E4 6 18 2
112829
AD
Probable F 89 4 Mild 3 3 0 E3/E3 5 2 3
112869
AD
Probable F 80 6 Mild 3 3 0 E3/E4 11 - -
114458
AD
Probable F 90 10 Moderate 3 3 0 E3/E3 7 0 2
115503
AD
Probable M 73 8.5 Mild 3 3 0 E4/E4 6 6 -
101060 Normal M 72 13.5 Moderate 1 1 0 E3/E4 - - -
103376 Normal F 68 15 None/Normal 0 1 0 E3/E3 - - -
106960 Normal M 80 10 Mild 2 2 0 E3/E4 - - -
108022 Normal M 76 4 Mild 0 1 0 E3/E3 - - -
11
ID
Clinical
Dx Sex Age
PMI
(hr) Atherosclerosis CERAD Braak* CAA
f

APOE
genotype
Disease
Duration
(years) MMSE
CDR

108484 CVD M 82 12 Moderate 3 1 1 - 10 - -
109028 Normal M 74 7.5 Mild 2 1 0 E2/E3 - - -
110362 Normal M 86 13 Mild 2 1 0 E3/E3 - 28 0
110780 Normal F 75 15 Mild 1 1 0 E3/E3 - - -
111122 Normal M 83 13 Mild 2 1 0 E3/E4 - - -
112090 Normal F 83 3 None/Normal 0 1 0 E2/E3 - 28 0
116003 Normal F 97 15 Mild 1 2 1 E3/E3 - 26 0.5
116619 Normal F 76 6 Severe 2 2 0 E3/E3 - - -
118467 Normal M 71 13 Mild 0 0 1 E3/E3 - - -
118624 Normal M 70 8 Mild 0 1 0 E3/E3 - - -
118709 Normal M 68 14 None/Normal 0 0 0 E2/E3 - - -
119767 Normal M 83 6 Moderate 0 1 0 E3/E3 - - -
120215 Normal M 74 6 Severe 1 1 0 E3/E3 - - -
120498 Normal Ma 70 9 Severe 1 1 0 E3/E3 - - -
121081 Normal F 82 12 None/Normal 0 1 1 E2/E4 - - -
121813 Normal F 81 10 None/Normal 1 1 0 E3/E3 - - -
Abbreviations: ClinicalDx, clinical diagnosis; PMI, post-mortem interval; CERAD, Consortium to
Establish a Registry for Alzheimer's disease; CAA, cerebral amyloid angiopathy; APOE, apolipoprotein-E;
MMSE, Mini-Mental State Examination; CDR, Clinical Dementia Rating; AD, Alzheimer’s disease; CVD,
cardiovascular disease.
- Data unknown.
*
Collapsed Braak stages (see Methods)
f
CAA scores refer to the presence of amyloid angiopathy on a semi-quantitative scale of 0-3.
12
Table 2. Summary of demographics.

Abbreviations: NCI, no cognitive impairment; AD, Alzheimer’s disease; PMI, post-mortem interval; CAA,
cerebral amyloid angiopathy; APOE, apolipoprotein-E; ns, non-significant; SD, standard deviation.

NCI (n=20) AD (n=30) p-value
Sex, female % 35 53 ns
Age (mean±SD) 77.55 (7.26) 80.17 (8.03) ns
Duration - 9.9 (4.21) ns
PMI (mean±SD) 10.25 (3.85) 7.93 (3.1) 0.02
Braak (mean±SD) 0.89 (0.6) 3 (0) <0.0001
CAA (mean±SD) 0.22 (0.44) 0.82 (0.39) <0.0001
APOE 𝜀4 frequency, % 20 50 0.04
Atherosclerosis frequency, % 25 83 ns
13
Immunohistochemistry
For all staining, paraformaldehyde-fixed, paraffin-embedded human brain tissue sections were used.
Embedded tissues were cut at a thickness of 6 µm. Sections were placed in a 60℃ oven for 1h,
deparaffinized with Naturalene (American MasterTech scientific laboratory supplies) 3 times for 5 min
each and then rehydrated with serial ethanol washes (100%, 95%, 70%, and 50%) for 2 times, 10 min per
concentration. After washing in distilled water for 5 min, sections were incubated in 1:100 diluted antigen
retrieval solution, pH 9 (H-3300, VECTOR) for 15 min at 92°C and then cooled down in PBS for 30 min.
The slides were then incubated with BLOXALL blocking solution (SP-6000, VECTOR) for 10 min to
quench endogenous peroxidase activity and then washed once for 5 min with PBS. The tissue sections were
next blocked in 2.5% horse serum blocking solution (S-2012, VECTOR) for 90 min before overnight
incubation with primary antibodies at 4°C. Commercially available antibodies used by previous studies [25,
28, 35, 78, 80] were tested on different AD and NCI sections with several conditions and the antibodies
with high specificity were chosen for the experiments (see Table 3 for antibody details). After incubation
with primary antibodies, the sections were then washed for 3 times, 10 min each with PBS, followed by 30
min incubation with appropriate ImmPRESS HRP-conjugated secondary IgG (see Table 3 for antibody
details). The slides were then washed 3 times for 10 min each with PBS. Next, VECTASTAIN® Elite®
ABC HRP reagent (PK-7100, VECTOR) was applied for 30 min, followed by 2 times washing with PBS
for 10 min each. To visualize the staining signal, tissues sections were incubated with ImmPACT SG (SK-
4705, VECTOR) for different times for each biomarker (please refer to Table 3 for chromogen details).
After incubation with chromogen, the tissues were washed at least 3 times for 10 min each time with
distilled water before imaging. For double staining, tissue sections after chromogen imaging were first
blocked with Avidin/Biotin Blocking Kit (SP-2001, VECTOR) according to manufacturer’s instructions, and
then incubated with the second primary antibody overnight at 4°C. After incubation, the slides were washed
3 times for 10 min each time using PBS and incubated with VECTASTAIN® Elite® ABC HRP reagent
(PK-7100, VECTOR) for 30 min followed by washing with PBS 2 times for 10 min each. To visualize the
14
staining signal, ImmPACT VIP (SK-4605, VECTOR) was applied for different times for each biomarker
(please refer to Table 3 for details). The sections were washed 3 times for 10 min each time with distilled
water, and then dehydrated with serial ethanol washes (50%, 70%, 95% and 100%) 2 times for 10 min each
per concentration. For mounting, slides were incubated in Naturalene for 5 min, 3 times and coverslipped
with Permount mounting solution (Fisher Scientific). For a detailed description of all primary antibodies,
secondary antibodies, chromogen incubation time, and iron stain kit (for analysis of Prussian blue-positive
hemosiderin deposits) see Table 3.

15
Table 3. Antibodies and chromogen used in specific applications.

No Biomarker 1
st
Primary
antibody
1
st
Secondary
antibody
1
st
Chromogen 2
nd
Primary
antibody

2
nd
Secondary
antibody
2
nd

Chromogen
1. Glucose
transporter
(GLUT1)
Rabbit anti-
GLUT1
(Abcam,
ab115730,
1:200)
ImmPRESS
HRP Reagent
Anti-Rabbit
IgG (Vector,
MP-7401)

ImmPACT® SG
Peroxidase (HRP)
Substrate (Vector,
MP-5401), 1 minute

N/A N/A N/A
2. Extravascular
fibrinogen
Biotinylated
Ulex
Europaeus
Agglutinin I
(UEA I)
(Vector, B-
1065, 1:250)
N/A ImmPACT® SG
Peroxidase (HRP)
Substrate (Vector,
MP-5401), 3 min
Rabbit anti-
human
Fibrinogen
(Dako,
A0080,
1:500)
ImmPRESS
HRP Reagent
Anti-Rabbit IgG
(Vector, MP-
7401)

ImmPACT®
VIP Peroxidase
(HRP)
Substrate
(Vector, Cat.
No: SK-4605),
30 seconds
3. Hemosiderin
deposits
Biotinylated
Ulex
Europaeus
Agglutinin I
(UEA I)
(Vector, B-
1065, 1:250)
N/A ImmPACT® SG
Peroxidase (HRP)
Substrate
(Vector, MP-5401),
5 min
Iron Stain Kit
(Sigma-
Aldrich,
HT20)
N/A N/A
4. Pericyte
coverage
Human PDGF
R beta
Biotinylated
Antibody
(R&D,
BAF385,
1:250)
N/A ImmPACT® SG
Peroxidase (HRP)
Substrate (Vector,
MP-5401), 15 min
Biotinylated
Ulex
Europaeus
Agglutinin I
(UEA I)
(Vector, B-
1065, 1:250)

N/A ImmPACT®
VIP Peroxidase
(HRP)
Substrate
(Vector, Cat.
No: SK-4605),
2 min
16
Imaging
All images were acquired using bright-field illumination microscope (BZ-9000, KEYENCE) using
20x magnification for hemosiderin deposits (20x objective lens, NA 0.45), 30x magnification for
extravascular fibrinogen and GLUT1 (1.5x digital magnification with 20x objective lens, NA 0.45) or 40x
magnification for pericyte coverage (40x objective lens, NA 0.60). At least 5 selected areas of interest (730
µm by 550 µm for hemosiderin deposits; 480 µm by 360 µm for extravascular fibrinogen and GLUT1; 365
µm by 275 µm for pericyte coverage) were taken randomly (~ 100 µm apart) across the hippocampal
formation and grey matter for cortical tissue in each tissue section to survey the entire region in a non-
biased systematic way. The operator was blinded and unaware of AD and NCI diagnosis throughout
imaging and analysis. The images were then analyzed using NIS-Element-Advanced Research program
(Nikon), as described below. The data were unblinded for statistical analysis.
Analysis
a. Hemosiderin deposits
Hemosiderin deposits were analyzed as previously described [79, 80]. In short, to quantify
hemosiderin deposits, 5 areas (730 x 550 µm each) were randomly taken per section (~ 100 µm
apart). Prussian-blue positive hemosiderin deposits were manually counted and expressed as the
total number of hemosiderin deposits summed up from five areas of interest per subject.

b. Extravascular fibrinogen
To quantify extravascular fibrinogen leakage, the abundance of extravascular fibrinogen was
measured as previously described [14, 25, 35, 40, 41, 48, 62]. In short, the NIS-Element-Advanced
Research program analysis explorer tool was used to measure the total area of fibrinogen-positive
signal (purple) per 5 areas (480 x 360 µm each) that were randomly taken (~ 100 µm apart) for
each subject. Any fibrinogen that colocalized with lectin-positive signal (grey) was subtracted from
17
the total area of leakage, yielding a value representing extravascular levels of fibrinogen per µm
2
.
All images were batch imported NIS-Element-Advanced Research program using the Analysis
explorer tool and programed to automatically quantify extravascular fibrinogen in the following
unbiased way. First, an RGB channel (‘purple’) was established to auto-select the fibrinogen signal
(with Threshold HIS: Hue, Saturation, Intensity, and Size; Binary Processing: Grow Dark Regions
to Intensity and Fill Holes). Second, another RGB channel (‘grey’) was established to auto-select
lectin-positive vessels (with Threshold HIS: Hue, Saturation, Intensity, and Size; Binary Processing:
Fill Holes). Then, a combined channel was established (with expression: purple minus grey) to
measure the extravascular fibrinogen (Figure 1).

18

Figure 1. Representative image demonstrating analysis method of extravascular fibrinogen using the
Analysis explorer tool (Nikon). Fibrinogen-positive area (purple) was automatically detected and outlined
with pink lines and lectin-positive area (grey) was auto-detected and outlined with yellow lines.
Extravascular levels of fibrinogen per µm
2
were quantified automatically by the software by subtracting the
lectin-positive area (grey) from the fibrinogen-positive area (purple).

19
c. Pericyte coverage
Pericyte coverage of brain capillaries was expressed as a percentage of PDGFRβ-positive area
occupying the lectin-positive capillaries profiles as previously described [25, 35], with a few
modifications as described below. Briefly, the NIS-Element-Advanced Research program analysis
explorer tool was used to measure the area of PDGFRβ-positive signal (grey) and lectin-positive
signal (purple). Pericyte coverage for each subject was quantified as a percentage of PDGFRβ-
positive pericyte surface area covering lectin-positive capillary surface area per 5 areas of interest
(365 x 275 µm each) that were randomly taken (~ 100 µm apart) for each subject. All images were
batch imported to NIS-Element-Advanced Research program using the Analysis explorer tool and
programed to automatically quantify pericyte coverage in the following unbiased way. First, an
RGB channel (‘grey’) was established to auto-select the PDGFRβ-positive pericyte (with
Threshold HIS: Hue, Saturation, Intensity, and Size; Binary Processing: Grow Dark Regions to
Intensity). Second, another RGB channel (‘purple’) was established to auto-select lectin-positive
vessels (with Threshold HIS: Hue, Saturation, Intensity, and Size; Binary Processing: Grow Dark
Regions to Intensity). Then, the area of the PDGFRβ-positive pericytes and lectin-positive vessels
were quantified by the software and expressed as a percentage (Figure 2).

20

Figure 2. Representative image demonstrating analysis method of pericyte coverage using the Analysis
explorer tool (Nikon). PDGFRβ-positive pericyte area (grey) was auto-detected and outlined with yellow
lines and lectin-positive vessel area (purple) was auto-detected and outlined with red lines. Pericyte
coverage was quantified by the software as the percentage of PDGFRβ-positive pericyte surface area
covering lectin-positive capillary surface area.

21
d. GLUT1
In earlier studies, GLUT1 expression was viewed and scored semi-quantitatively (grade 0-4 from
very weak to strong immunolabelling intensity of GLUT1) to assess changes in AD brain tissue
[27]. Therefore, we developed a quantitative method to better assess GLUT1 levels in brain
microvasculature using NIS-Element-Advanced Research program. First, we confirmed that lectin-
positive vessels were GLUT1-positive (Figure 3. a). For each subject, the density of GLUT1 per
GLUT1-positive vascular profile was measured using auto-select tool to select 6 to 10 capillaries
with a diameter between 4-8 µm per 5 areas of interest (480 x 360 µm each) that were randomly
taken ( ~ 100 µm apart) for each subject (Figure 3. b). However, this finding should be validated
by future studies using independent double immunofluorescent staining and western blotting.

22
a

b

Figure 3. Representative images of immunofluorescence staining of GLUT1 and Lectin, and analysis
method of GLUT1 using the Auto Detect ROI tool (Nikon). a. To confirm if GLUT1-positive vessels are
also Lectin positive, we performed immunofluorescence staining using anti-GLUT1 Alexa Fluor 647 (1:250,
Abcam, ab195020) and UEA I Dylight 594 (1:250, Vector, DL-1067) on human postmortem brain tissue.
b. Representative image demonstrating analysis method of GLUT1 using the Auto Detect ROI tool (Nikon).
The lectin-positive (grey) capillaries (with diameter 4-8µm) were detected and outlined with different
colors. The density of GLUT1 per GLUT1-positive vascular profile was measured automatically by the
software.

GLUT1 Lectin
Merged
50µm
23
Statistics
Sample sizes were calculated using nQuery assuming a two-sided α=0.05, 80% power, and
homogeneous variances for the two samples to be compared (NCI and AD). Using the means and standard
deviation for different parameters (i.e., extravascular fibrinogen, pericyte coverage, etc.) from prior studies
[25, 27, 35, 62], the minimum sample size needed to detect differences between NCI and AD was between
4 and 5 per group. Therefore, the present study using n=20 NCI and n=30 AD is sufficiently powered to
detect the expected differences in our studied parameters.
Analysis was performed with the statistical software package Prism 7 (GraphPad Software). F test
was first run to determine variance across groups. Then Mann-Whitney U test (non-parametric alternative
used when homogeneity of variance or normality assumptions were violated) was used to determine
significance. Grubbs’ Test was conducted to screen for significant outliers and outliers were further
excluded from the analysis. A P value less than 0.05 was considered statistically significant in all studies.
All numerical values were presented using the box and whisker plot, where the lines indicate the median
values, the boxes indicate the interquartile range, and the whiskers indicate the minimum and maximum
values.

24
Results
Microbleeds
To further characterize loss of cerebrovascular integrity, we performed immunohistochemistry of
lectin staining to visualize vessels followed by Prussian blue staining as previously described [80]. Our data
show a significant 9 fold increase of Prussian blue-positive hemosiderin deposits in hippocampal formation
(p < 0.0001) and 17 fold increase in grey matter of cortex (p < 0.0001) of AD subjects compared to NCI
controls (Figure 4), which is consistent with previous finding that microbleeds were present about 40% of
AD patients using 3 Tesla MRI [82] or up to 78% of AD patients using 7 Tesla MRI [9].

25

Figure 4. Hemosiderin deposits in the hippocampus and cortex of no cognitive impairment (NCI) and
Alzheimer’s disease (AD) subjects. a. Representative brightfield images of hemosiderin deposits (blue)
and lectin-positive capillaries (grey) in the hippocampus (left) and cortex (right) of NCI (top) and AD
(bottom). b. Magnified view of insets from panel a. c. Quantification of the number of hemosiderin deposits
in the hippocampus (left) and cortex (right) of NCI and AD. n=20 in NCI group, n=30 in AD group; p <
0.0001 in both hippocampus and in cortex by Mann-Whitney test for nonparametric data. All numerical

Figure 4. Hemosiderin deposits in the hippocampus and cortex of no cognitive impairment (NCI) and
Alzheimer’s disease (AD) subjects. a. Representative brightfield images of Prussian blue positive
hemosiderin deposits (blue) and lectin-positive capillaries (grey) in the hippocampal formation (left) and
grey matter of cortex (right) of NCI (Braak stage = 0) (top) and AD (Braak stage = V-VI) (bottom). b.
Magnified view of insets from AD cases in panel a. c. Quantification is expressed as the total number of
Prussian blue positive hemosiderin deposits from 5 areas of interest for each subject in the hippocampal
formation (left) and grey matter of cortex (right) of NCI and AD. n=20 in NCI group, n=30 in AD group;
p < 0.0001 in both hippocampal formation and in grey matter of cortex by Mann-Whitney U test for
nonparametric data. All numerical values were presented using the box and whisker plot, where the lines
indicate the median values, the boxes indicate the interquartile range, and the whiskers indicate the
minimum and maximum values.

a
NCI AD
B
30µm
Cortex
Hippocampus
Hippocampus
AD
AD
Cortex
b
Hemosiderin deposits
Lectin
Hippocampus Cortex c
NCI AD
0
20
40
60
80
100
120
140
160
Prussian blue
+

hemosiderin deposits
p < 0.0001
(n=19) (n=29)
NCI AD
0
20
40
60
80
100
120
140
160
Prussian blue
+

hemosiderin deposits
(n=20) (n=30)
p < 0.0001
900%
1700%
26
Extravascular Fibrinogen
One consequence of BBB breakdown is leakage of blood-derived components (fibrinogen, albumin,
and IgG) into the brain, which has been observed in studies using human postmortem tissues [11, 25, 62]
To investigate BBB disruption, we examined extravascular fibrinogen deposition by co-staining the UEA
lectin agglutinin and fibrinogen on the AD and NCI tissues. We observed more extravascular fibrinogen
leakage in both hippocampal and cortical tissues in AD compared to NCI using brightfield microscopy
(Figure 5. a,b). Quantitative analysis showed a 164% increase of extravascular fibrinogen in hippocampal
formation (p = 0.001) and a 460% increase of extravascular fibrinogen in grey matter of cortex (p < 0.0001)
in AD cases (Figure 5. c). Fibrinogen leakage was found in a small fraction of hippocampal formation from
NCI subjects (Figure 5. c), which is consistent with the finding using MRI study that BBB leakage also
occurred in normal aging, mild cognitive impairment [48] and AD patients [24] in the hippocampus.

27

Figure 5. Analysis of plasma-derived perivascular fibrinogen in the hippocampus and cortex of no
cognitive impairment (NCI) and Alzheimer’s disease (AD) subjects. a. Representative brightfield
microscopic images of extravascular fibrinogen (purple) and lectin-positive capillaries (grey) in the
hippocampal formation (left) and grey matter of cortex (right) of NCI (Braak stage = 0) (top) and AD (Braak
stage = V-VI) (bottom). b. Magnified view of the insets from panel a. of AD cases. c. Quantification of
extravascular fibrinogen deposition per µm
2
in the hippocampal formation (left) and cortex (right) of NCI
and AD. n=20 in NCI group, n=30 in AD group; p=0.0019 in hippocampal formation and p=0.0002 in grey
matter of cortex by Mann-Whitney U test for nonparametric data. All numerical values were presented
using the box and whisker plot, where the lines indicate the median values, the boxes indicate the
interquartile range, and the whiskers indicate the minimum and maximum values.

NCI AD
Hippocampus Cortex
50 µm
a
AD
Hippocampus
AD
Cortex
Hippocampus
NCI AD
0.0
0.5
1.0
1.5
Extravascular fibrinogen
deposition (µm
2
)
p = 0.01
(n=18) (n=29)
Cortex
b
c
Fibrinogen
Lectin
NCI AD
0.0
0.5
1.0
1.5
Extravascular fibrinogen
deposition (µm
2
)
p = 0.0002
(n=19) (n=29)
25µm
164%
460%
28
Pericyte Coverage
Pericytes are crucial for maintaining BBB integrity and loss of pericyte population has been shown
to lead to chronic BBB disruption in previous studies [25, 35, 64]. Here we performed double UEA lectin
agglutinin and PDGFRβ immunostaining in NCI and AD postmortem tissues. We found a significantly
reduced of pericyte coverage (expressed as percentage) in both hippocampal and cortical tissues in AD
subjects compared to NCI controls (Figure 6. a,b). The quantification revealed a 46% and 25% decrease
in PDGFRβ-positive pericyte coverage of capillary microvessels in AD compared to NCI controls in the
hippocampal formation (p < 0.0001) and grey matter region of cortex (p < 0.0001), respectively (Figure 6.
c).

29

Figure 6. Analysis of pericyte coverage in the hippocampus and cortex in subjects with no cognitive
impairment (NCI) and Alzheimer’s disease (AD). a. Representative brightfield microscopic images of
PDGFRβ-positive pericyte (grey) and lectin-positive capillaries (purple) in the hippocampal formation (left)
and grey matter of cortex (right) of NCI (Braak stage = 0) (top) and AD (Braak stage = V-VI) (bottom). b.
Magnified view of the insets from panel a. c. Quantification of the PDGFRβ-positive pericyte coverage of
lectin-positive vascular endothelial profiles in the hippocampal formation (left) and grey matter of cortex
(right) of NCI and AD. n=20 in NCI group, n=30 in AD group; p <0.0001 in both hippocampal formation
and grey matter of cortex by Mann-Whitney U test for nonparametric data. All numerical values were
presented using the box and whisker plot, where the lines indicate the median values, the boxes indicate the
interquartile range, and the whiskers indicate the minimum and maximum values.

30
Glucose Transporter 1
Downregulation of GLUT1 expression has been reported in both AD mouse lines with quantitative
method and human AD postmortem tissues with semi-quantitative method [3, 27, 32, 67, 78], to examine
whether GLUT1 expression was also affected in AD subjects, we performed GLUT1 immunostaining in
hippocampal and cortical sections of both NCI and AD brains. We observed a significant reduction of
GLUT1 signal in the AD group as compared to NCI (Figure 7. a,b). Quantitative analysis revealed a ~10%
reduction of GLUT1 per GLUT1-positive capillaries profiles in hippocampal formation (p = 0.0004) and
~20% reduction of GLUT1 per GLUT1-positive capillaries profiles in grey matter region of cortex (p <
0.0001) in AD cases compared to NCI controls using our method of averaging GLUT1 pixel density per
GLUT1-positive of vessel profiles (Figure 7. c). However, this finding should be confirmed by future
studies using independent double immunofluorescent staining for GLUT1 and an endothelial specific lectin
or CD31 and with quantitative immunoblotting of brain microvessels, given that previous studies using
brain capillaries and semi-quantitative analysis [27] indicated larger GLUT1 losses.

31

Figure 7. Glucose transporter 1 (GLUT1) immunostaining in the hippocampus and cortex of no
cognitive impairment (NCI) and Alzheimer’s disease (AD) subjects. a. Representative brightfield
images of GLUT1 (grey) in the hippocampal formation (left) and grey matter of cortex (right) of NCI (Braak
stage = 0) (top) and AD (Braak stage = V-VI) (bottom). b. Magnified view of the insets from panel a. c.
Quantification of GLUT1 pixel density per µm
2
GLUT1-positive area in the hippocampal formation (left)
and grey matter of cortex (right) of NCI and AD. n=20 in NCI group, n=30 in AD group; p=0.0004 in
hippocampal formation and p <0.0001 in grey matter of cortex by Mann-Whitney U test. All numerical
values were presented using the box and whisker plot, where the lines indicate the median values, the boxes
indicate the interquartile range, and the whiskers indicate the minimum and maximum values.

NCI AD
1.0
1.5
2.0
2.5
GLUT1 pixel density
per µm
2
GLUT1
+
area
(n=20) (n=30)
p = 0.0004
NCI AD
1.0
1.5
2.0
2.5
GLUT1 pixel density
per µm
2
GLUT1
+
area
p < 0.0001
(n=20) (n=30)
NCI AD
Hippocampus Cortex
GLUT-1
Hippocampus Cortex
NCI AD AD NCI
b
Hippocampus
Cortex
c
B
50 µm
25 µm
50 µm
32
Discussion
In this study, we demonstrated cerebrovascular abnormalities and blood-brain barrier dysfunction
in AD subjects using chromogen staining and quantitative analysis. In an effort to improve existing staining
protocols, we optimized multiple conditions to minimize the variation between subjects and reduce the
background signals. Furthermore, we designed a rigorously reproducible analysis protocol for each
experimental paradigm tested.
Previous studies using MRI and immunohistochemistry have identified AD-associated vascular
dysfunctions including reduced glucose utilization, presence of microbleeds, and accumulation of plasma-
derived components [31, 33, 68, 74, 89]. Here, we not only validated these phenotypes in a larger-than-ever
cohort but also established staining protocols and analysis methods that can be followed by other
researchers. To define criteria for diagnosis, we replaced the traditional grading methods with quantification
methods using NIS-elements AR software. After imaging and analyzing more than 500 pictures per
biomarker with the method we created, we reasoned that it is feasible and necessary to develop an automatic
quantification algorithm in the future for high throughput studies. In addition, our study is the first
comprehensive research testing various vascular biomarkers (microbleeds, fibrinogen, pericyte, GLUT1)
across the same cohort.
Increased microbleeds and iron accumulation were revealed by MRI studies in AD patients and
people at preclinical AD stage [23, 54, 65, 82]. The density of microbleed has been reported to be strongly
associated with ages, diabetes, vascular risk factors and Ab burden [54, 65, 82], which will be interesting
to study in our cohort in the future.
Fibrinogen is known for its hemostatic properties to plasma viscosity and blood cells aggregation
[62]. When the BBB breaks down, there is an influx of plasma-derived proteins from cerebrovascular
system to CNS across the leaky BBB [11]. Such leakage, in animal studies, then leads to microglia
activation and neuroinflammation, generation of reactive oxygen species, spine elimination, and cognitive
33
deficits [43, 84]. Moreover, a recent study using 3D molecule labeling and in vivo two-photon imaging in
cleared mouse and human AD brains showed fibrinogen deposits associated with loss of dendritic spines
independent of Aβ accumulation [43]. Furthermore, a study using oligodendrocyte and pericyte cultures
treated with fibrinogen and fibrin fibrils found autophagy-dependent cell death [49]. Also, pharmacological
and genetic manipulations of systemic fibrinogen levels in pericyte-deficient, but not control mice,
influenced the degree of white-matter fibrin(ogen) deposition, pericyte degeneration, vascular pathology
and white-matter changes [49].
As fibrinogen deposition will not be present in the healthy, intact BBB, it has high potential to be used as
an imaging biomarker for the diagnosis of AD and other neurological diseases in the future [12, 57].
Pathological phenotypes related to BBB leakage have been extensively studied previously in AD patients
and murine transgenic models using immunohistochemical approaches [11, 56, 62, 86]. In our study, we
double stained fibrinogen and lectin using dual-colored chromogens. Compared to the chromogen study
reported previously [62], we normalized the fibrinogen intensity with the surface area of the vessels to get
more accurate quantification of fibrinogen leakage. We also observed some fibrinogen leakage in a small
subset of NCI controls.
Pericytes play an important role in maintaining the BBB formation and maintenance [6, 72, 89].
Previous studies have also found loss of pericyte function and/or number in many CNS diseases [63, 77],
and such abnormalities can trigger either BBB breakdown or hypoperfusion, which further leads to neuronal
injury and neurodegeneration [25, 35, 53, 72, 84]. A most recent study has also shown that soluble PDGFRβ
(sPDGFRβ) shed by human brain pericytes is an early change of early cognitive impairment irrespective of
Aβ plaques and tau tangles [52]. Consistent with this, our data also show the same reduction of PDGFRβ-
positive pericyte coverage in UEA lectin-positive capillaries. Besides, people have reported that pericyte
degeneration correlates with BBB breakdown in AD subjects with Apolipoprotein E4 carriers [25]. It will
be interesting to see if such correlation is also in our cohort. Recently, a study found loss of pericyte function
not only lead to BBB breakdown but also white matter dysfunctions of neuronal connectivity (such as loss
34
of myelin, axons, and oligodendrocytes) in pericyte-deficient transgenic mice using MRI and
immunohistochemistry [49]. Although further investigation needs to be done to see whether the same
phenotypes happen in AD patients, this study implicates a potential therapy for pericyte-related CNS
diseases and neurogenerative disorders [49]. In addition to BBB breakdown and white matter dysfunction,
diminished CBF is another feature of pericyte degeneration reported by many studies in transgenic mice
[38]. In the future, it will be interesting to see if there is any correlation between CBF and pericyte loss in
AD patients.
We found that endothelial GLUT1 is significantly lower both in hippocampal and cortical tissues
of AD subjects. This result is consistent with the previous reported GLUT1 reduction in other AD subjects
[27]. These two human studies, together with study done in GLUT1 deficient mouse showing BBB
dysfunction and neuronal injure phenotypes [19], not only indicate the importance of GLUT1 in
maintaining vascular homeostasis and brain function, but more importantly, also reveal a potential
therapeutic target in AD [32]. Furthermore, we and other studies have also found reduced microvascular
density in AD subjects [53], which further exacerbated GLUT1 paucity overall in AD. This may cause an
even greater glucose deprivation in AD patients than what our GLUT quantification suggested here [29,
87]. Such transporter dysfunction may lead to neuronal injury and cognitive impairment [78].
Overall, the present study aimed to provide a “roadmap” for the characterization of vascular
phenotypes and BBB dysfunctions, in addition to reproducible standardized staining protocols of various
neurovascular biomarkers, and quantification methods. Although we have tried to improve the staining and
quantification methods to our best knowledge, the inherited variation among different human subjects
cannot be completely ruled out, partially due the semi-quantifiable nature of immunohistochemical
approaches. Therefore, further examination using western blot and enzyme-linked immunosorbent assay
(ELISA) to analyze these biomarkers will be an important validation of our findings. In addition to the
biomarkers covered in this study, the future direction might focus on establishing standardized
immunohistochemistry protocols for other potential biomarkers (e.g., PICALM, low density lipoprotein
35
receptor-related protein 1, receptor for advanced glycation end products, tight junction proteins, MMP-9,
and cyclophilin A) that are related to BBB breakdown and AD pathologies [38, 50, 53, 73].

Acknowledgment
I would like to thank Dr. Berislav Zlokovic for his great mentorship and guidance through my
master’s degree. I have learned so much during my time in his lab. In addition, thanks to our wonderful
collaborator, Dr. John Trojanowski from University of Pennsylvania for providing postmortem human brain
tissue sections for this project. Furthermore, I would like to thank my committee members, Dr. Justin Ichida,
Dr. Vijay Kalra, and Dr. Ansgar Siemer for their time and valuable scientific advice. I would also like to
thank Dr. Abhay Sagare, Dr. Amy Nelson, and Dr. Melanie Sweeney for their scientific discussion and
assistance with this project. Lastly, but most importantly, I would like to thank my boyfriend Shaoyu and
my family for their continued encouragement and support.
36
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Abstract (if available)

Abstract Neurovascular dysfunction can initiate several pathways leading to neurodegeneration and cognitive impairment. Many studies in live human patients and murine transgenic models have found cerebrovascular changes and blood-brain barrier (BBB) dysfunction as early pathological hallmarks of Alzheimer’s disease (AD) and other neurodegenerative disorders. In this study, we used immunohistochemistry to examine a collection of AD-related neurovascular biomarkers in postmortem tissues from 30 AD patients and 20 aged-matched controls with no cognitive impairment (NCI), covering both hippocampal and cortical regions. The chosen biomarkers covered BBB breakdown (e.g., hemosiderin deposits, extravascular fibrinogen, and pericyte coverage) and cerebrovascular changes (e.g., glucose transporter 1 (GLUT1)). We found increased hemosiderin and extravascular fibrinogen deposition, decreased pericyte coverage, decreased microvascular GLUT1 signal in AD compared to NCI cases. In addition to presenting a comprehensive study of AD-related neurovascular biomarkers in a much larger cohort than previous studies, this study provides standardized immunohistochemistry staining protocols and objective quantification methods that can be followed by other researchers.

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Creator Hsu, Ching-Ju (author)

Core Title Blood-brain barrier breakdown and vessel integrity in Alzheimer’s disease

School Keck School of Medicine

Degree Master of Science

Degree Program Biochemistry and Molecular Medicine

Publication Date 06/25/2020

Defense Date 04/30/2019

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

Tag aging,Alzheimer's disease,blood-brain barrier,cerebrovascular,dementia,neurodegenerative disease,OAI-PMH Harvest

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Language English

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Advisor Siemer, Ansgar (committee chair), Zlokovic, Berislav (committee chair), Ichida, Justin (committee member), Kalra, Vijay (committee member)

Creator Email hsuching@usc.edu,ruuhsu.886@gmail.com

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