ALZHEIMER’S DISEASE PATHOLOGY IN AGED CHIMPANZEES
A dissertation submitted
to Kent State University in partial
fulfillment of the requirements for the
degree of Doctor of Philosophy
by
Melissa K. Edler
August 2016
© Copyright
All rights reserved
Except for previously published materials
Dissertation written by
Melissa K. Edler
B.A., Kent State University, 2000
B.A., Kent State University, 2000
M.A., Kent State University, 2007
Ph.D., Kent State University, 2016
Approved by
Mary Ann Raghanti, Ph.D.
, Chair, Doctoral Dissertation Committee
Heather K. Caldwell, Ph.D.
, Members, Doctoral Dissertation Committee
Ernest J. Freeman, Ph.D.
Stephen B. Fountain, Ph.D.
David C. Riccio, Ph.D.
Accepted by
Ernest J. Freeman, Ph.D.
, Director, School of Biomedical Sciences
James L. Blank, Ph.D.
, Dean, College of Arts and Sciences
TABLE OF CONTENTS ..................................................................................................................... iv
LIST OF ABBREVIATIONS................................................................................................................ vii
LIST OF FIGURES ............................................................................................................................. ix
LIST OF TABLES ............................................................................................................................... x
ACKNOWLEDGMENTS..................................................................................................................... xii
I.
OVERVIEW ........................................................................................................................... 1
REFERENCES ...................................................................................................................... 4
II.
ALZHEIMER’S DISEASE PATHOLOGY IN AGED CHIMPANZEES ................................... 10
INTRODUCTION................................................................................................................... 10
MATERIALS AND METHODS .............................................................................................. 12
Specimens ...................................................................................................................... 12
Sample Processing ......................................................................................................... 12
Identification of Sampling Regions ................................................................................. 13
Immunohistochemistry .................................................................................................... 13
Thioflavin S ..................................................................................................................... 14
Pathology Identification .................................................................................................. 14
Data Acquisition .............................................................................................................. 15
Pathology Scoring (Brain Age) ....................................................................................... 18
Statistical Analyses ......................................................................................................... 19
RESULTS .............................................................................................................................. 20
Chronological Age and Brain Age Correlations .............................................................. 20
APP/Aβ and Aβ42 Plaque Volume ................................................................................. 21
APP/Aβ and Aβ42 Vessel Volume and Diameter ........................................................... 22
Pretangle, NFT, and Tau Neuritic Plaque Densities ...................................................... 25
Correlations of Aβ and Tau Pathologies ........................................................................ 29
DISCUSSION ....................................................................................................................... 31
REFERENCES ...................................................................................................................... 37
III.
MICROGLIA CHANGES ASSOCIATED WITH ALZHEIMER’S
DISEASE PATHOLOGY IN AGED CHIMPANZEES ............................................................ 44
INTRODUCTION................................................................................................................... 44
iv
MATERIALS AND METHODS .............................................................................................. 45
Specimens ...................................................................................................................... 45
Sample Processing ......................................................................................................... 46
Identification of Sampling Regions ................................................................................. 46
Immunohistochemistry .................................................................................................... 47
Morphology Identification ................................................................................................ 47
Data Acquisition .............................................................................................................. 48
Statistical Analyses ......................................................................................................... 49
RESULTS .............................................................................................................................. 50
Activated and Morphological Microglia Densities ........................................................... 50
PHF1/Iba1-ir Microglia Density ....................................................................................... 54
Correlations with Chronological Age, Brain Age, and AD Pathology ............................. 55
DISCUSSION ....................................................................................................................... 59
REFERENCES ...................................................................................................................... 62
IV.
COLOCALIZATION OF CALBINDIN AND TAU INCREASES IN
CHIMPANZEES WITH ALZHEIMER’S DISEASE PATHOLOGY ......................................... 69
INTRODUCTION................................................................................................................... 69
MATERIALS AND METHODS .............................................................................................. 70
Specimens ...................................................................................................................... 70
Sample Processing ......................................................................................................... 71
Identification of Sampling Regions ................................................................................. 71
Immunohistochemistry .................................................................................................... 72
Data Acquisition .............................................................................................................. 72
Statistical Analyses ......................................................................................................... 73
RESULTS .............................................................................................................................. 73
CB-ir and AT8/CB-ir Neuron Densities by Region and Sex ........................................... 76
Correlations with Chronological Age and Brain Age ...................................................... 76
Associations of CB-ir and AT8/CB-ir Neuron Densities with AD Pathology ................... 76
DISCUSSION ....................................................................................................................... 79
REFERENCES ...................................................................................................................... 82
V.
BABOONS AND CHIMPANZEES EXPRESS HIGHER LEVELS OF
FOUR-REPEAT TAU THAN THREE-REPEAT TAU ISOFORMS ........................................ 89
INTRODUCTION................................................................................................................... 89
MATERIALS AND METHODS .............................................................................................. 91
Specimens and Sample Processing ............................................................................... 91
Preparation of Brain Homogenates ................................................................................ 91
Preparation of Tau HRP Conjugate ................................................................................ 91
Total Protein Assay ........................................................................................................ 92
Sandwich ELISA for 3R- and 4R-Tau Isoforms .............................................................. 92
v
Statistical Analyses ......................................................................................................... 93
RESULTS .............................................................................................................................. 94
DISCUSSION AND CONCLUSIONS .................................................................................... 97
REFERENCES ...................................................................................................................... 99
VI.
SUMMARY CHAPTER.......................................................................................................... 104
APPENDICES
A. SAMPLE DEMOGRAPHICS AND Aβ AND TAU PATHOLOGY BY INDIVIDUAL ............... 107
B. SUMMARY OF ANTIBODIES ............................................................................................... 108
C. REGIONAL AND TOTAL VOLUMES OCCUPIED BY APP/Aβ PLAQUES (%) ................... 109
D. REGIONAL AND TOTAL VOLUMES OCCUPIED BY Aβ42 PLAQUES (%) ....................... 110
E. REGIONAL AND TOTAL VOLUMES OCCUPIED BY APP/Aβ VESSELS (%) .................... 111
F. REGIONAL AND TOTAL VOLUMES OCCUPIED BY Aβ42 VESSELS (%) ........................ 112
G. REGIONAL AND AVERAGE PRETANGLE DENSITIES (mm3)........................................... 113
H. REGIONAL AND AVERAGE NEUROFIBRILLARY TANGLE DENSITIES (mm3) ............... 114
I.
REGIONAL AND AVERAGE TAU NEURITIC PLAQUE DENSITIES (mm3)........................ 115
J.
REGIONAL AND AVERAGE ACTIVATED MICROGLIA DENSITIES (mm3) ....................... 116
K. REGIONAL AND AVERAGE RAMIFIED MICROGLIA DENSITIES (mm3) .......................... 117
L. REGIONAL AND AVERAGE INTERMEDIATE MICROGLIA DENSITIES (mm3) ................ 118
M. REGIONAL AND AVERAGE AMOEBOID MICROGLIA DENSITIES (mm3) ........................ 119
N. REGIONAL AND AVERAGE PHF1/IBA1 MICROGLIA DENSITIES (mm3) ......................... 120
O. REGIONAL AND TOTAL MICROGLIA MORPHOLOGY RATIOS ....................................... 121
P. REGIONAL CALBINDIN-IMMUNOREACTIVE NEURON DENSITIES (mm3) ..................... 122
Q. REGIONAL AT8/CB-IMMUNOREACTIVE NEURON DENSITIES (mm3) ............................ 123
R. ABSORBANCE VALUES FOR 3R-TAU AND 4R-TAU ISOFORMS .................................... 124
S. NORMAL AND PATHOLOGIC AGING IN CHIMPANZEES ................................................. 125
vi
LIST OF ABBREVIATIONS
aa
Amino acid
Aβ
Amyloid-beta
AD
Alzheimer’s disease
AFF
Area fraction fractionator
ANOVA
Analysis of variance
APP
Amyloid precursor protein
BCA
Bicininchronic acid
Ca2+
Calcium ion
CA
Cornus Ammonis
CAA
Cerebral amyloid angiopathy
CB
Calbindin
CBD
Corticobasal degeneration
CD33
Sialic acid binding immunoglobulin-like lectin 3
CERAD
Consortium to Establish a Registry for AD
DAB
Diaminobenzidine
ELISA
Enzyme-linked immuosorbent assay
fAβ
Fibrillar amyloid-beta
4R
Four repeat
FC
Frontal cortex
H1
Haplotype 1
H2
Haplotype 2
HC
Hippocampus
HLA-DR
Human leukocyte antigen-D related
vii
HRP
Horseradish peroxidase
IL-1α
Interleukin-1 alpha
IL-6
Interleukin-6
ir
Immunoreactive
LL
Lightning-Link
MAPT
Microtubule associate protein tau
MTG
Midtemporal gyrus
MGv
Microglia density
NC
Neocortex
NFT
Neurofibrillary tangle
NP
Neuritic plaque
Nv
Neuron density
PBS
Phosphate buffered saline
PCA
Principal component analysis
PFC
Prefrontal cortex
PHF
Paired helical filaments
PSP
Progressive supranuclear palsy
RT
Room temperature
SD
Standard deviation
sp
Stratum pyramidale
so
Stratum orien
sr
Stratum radiatum
TBS
Tris buffered saline
TC
Temporal cortex
3R
Three repeat
TREM2
Triggering receptor expressed on myeloid cells 2
TNF-α
Tumor necrosis factor-alpha
viii
LIST OF FIGURES
Figure 1. Pathologic Mechanisms of Alzheimer’s Disease ................................................................ 4
Figure 2. Types of AD Pathology in Elderly Chimpanzees ................................................................ 15
Figure 3. Topographical Distribution of AD Pathology ....................................................................... 16
Figure 4. Tau Pathology by Stain ....................................................................................................... 17
Figure 5. APP/Aβ-ir and Aβ42-ir Plaques and Vessels ..................................................................... 23
Figure 6. Thioflavin S Staining in Elderly Chimpanzees .................................................................... 24
Figure 7. Aβ Pathology by Region and Stain Averaged for All Individuals ........................................ 25
Figure 8. Aβ Pathology by Sex and Region ....................................................................................... 25
Figure 9. Co-occurrence of Aβ, Tau, and Glial Activity ..................................................................... 27
Figure 10. Tau Lesions in Aged Chimpanzee Brains ........................................................................ 28
Figure 11. Tau Lesions by Regions ................................................................................................... 29
Figure 12. Tau Pathology by Sex ....................................................................................................... 29
Figure 13. Aβ Plaque Volume Versus Vessel Volume ...................................................................... 30
Figure 14. Significant Correlations of Tau Pathologies ...................................................................... 30
Figure 15. Significant Correlations of APP/Aβ and Tau Lesions ....................................................... 31
Figure 16. Aβ Plaque Volume and Tau Lesions by Severity of CAA ................................................ 34
Figure 17. Photomicrographs of Activated Microglia Morphologies in the Neocortex ....................... 48
Figure 18. Photomicrographs of Iba1-ir, PHF1/Iba1-ir, and AT8/Iba1-ir Staining .............................. 51
Figure 19. Iba1-ir Activated Microglia by Region and Sex ................................................................. 52
Figure 20. Photomicrographs of Iba1-ir Activated Microglia in the Hippocampus ............................ 52
Figure 21. Proportion of Iba1-ir Activated Microglia by Morphology and Region .............................. 53
Figure 22. Iba1-ir Microglia Density by Morphology, Region, and Sex .............................................. 54
Figure 23. PHF/Iba1-ir Microglia Density by Region and Sex ........................................................... 55
ix
Figure 24. Significant Correlations of PHF1/Iba1-ir Microglia Density
and Morphological Densities ............................................................................................. 55
Figure 25. Significant Correlations of Iba1-ir Activated and Intermediate Microglia Densities
with Aβ42-ir Plaque Volume.............................................................................................. 57
Figure 26. Significant Correlations of Iba1-ir Morphological Densities
with APP/Aβ-ir Vessel Volume .......................................................................................... 57
Figure 27. Significant Correlations of Iba1-ir Activated and Morphological Densities
with Aβ42-ir Vessel Volume .............................................................................................. 58
Figure 28. Significant Correlation of Neocortical Iba1-ir Activated Microglia Density
with Neocortical AT8-ir Pretangle Density ........................................................................ 58
Figure 29. Photomicrographs of CB-ir Interneurons and Pyramidal Neurons .................................. 74
Figure 30. Photomicrographs of AT8/CB-ir and CB-ir Neurons and Glia ......................................... 75
Figure 31. CB-ir Neuron Density by Region and Sex ........................................................................ 75
Figure 32. AT8/CB-ir Neuron Density by Region and Sex ................................................................. 77
Figure 33. Significant Correlations of AT8/CB-ir Neuron Density with Chronological Age
and Brain Age ................................................................................................................... 78
Figure 34. Significant Correlations of CB-ir and AT8/CB-ir Neuron Density
with Aβ Pathology ............................................................................................................. 78
Figure 35. Significant Correlations of CB-ir and AT8/CB-ir Neuron Density with Tau Densities ....... 79
Figure 36. Tau Isoforms in Humans and Chimpanzees Formed by Splicing Exons 2, 3, and 10 ..... 90
Figure 37. Standard Curves for 3R Tau and 4R Tau ........................................................................ 93
Figure 38. Total Protein Content in Frontal Cortex, Temporal Cortex, and Cerebellum
of Baboons and Chimpanzees .......................................................................................... 94
Figure 39. Comparisons of Three-repeat Versus Four-repeat Tau/Total Protein Content
by Species ......................................................................................................................... 96
Figure 40. Three-repeat and Four-repeat Tau/Total Protein Content by Tau Isoform....................... 97
x
LIST OF TABLES
Table 1. Proposed Scoring System for AD Pathology in Chimpanzees ............................................ 18
Table 2. Correlation Coefficients for Aβ and Tau Pathology Versus Chronological Age
and PCA-generated Brain Age ............................................................................................ 21
Table 3. Aβ and Tau Pathology in Normal and Pathologic Aging in Chimpanzees ........................... 36
Table 4. Correlation Coefficients for Activated, Morphological, and PHF/Iba1-ir Microglia
Densities Versus Chronological Age and PCA-generated Brain Age .................................. 56
Table 5. Correlation Coefficients for Total and Regional CB-ir Neuron Density and AT8/CB-ir
Neuron Density with Chronological Age and PCA-generated Brain Age ............................ 77
Table 6. Total Protein Content in Baboon and Chimpanzee Frontal Cortex, Temporal Cortex,
and Cerebellum .................................................................................................................... 94
Table 7. Three-repeat Tau/Total Protein Content in Frontal Cortex, Temporal Cortex, and
Cerebellum of Baboons and Chimpanzees ......................................................................... 95
Table 8. Four-repeat Tau/Total Protein Content in Frontal Cortex, Temporal Cortex, and
Cerebellum of Baboons and Chimpanzees ......................................................................... 95
xi
ACKNOWLEDGMENTS
This dissertation work and the journey to its completion would not have been possible without the help of
a village. To my advisor, Mary Ann Raghanti, for her support, training, and guidance during the past several
years, I am exceedingly grateful. You have afforded me an immense freedom of exploration and
independence during my research that has prepared me for a prosperous professional life beyond your
laboratory doors. Not only did you bring me into the fold of your amazing network of collaborators, you never
hesitated to take the time to answer my questions. Thank you, too, for understanding that sometimes my
family’s needs came first during this process. It was hugely comforting to have a mentor who was accepting
of such circumstances. You care about your students and their success as much as any professor I have
known during my academic career.
I also must thank Chet Sherwood for his constant encouragement and patronage, whether in the form of
a pep talk, rare ape tissue, funding, or requesting statistical analyses that few know of or have ever tried
personally. Similarly, I owe a huge debt to Patrick Hof for sharing his expertise in neuropathology and being
patient with my seemingly endless questions. The speed and clarity with which you answered my queries
was greatly appreciated. To the statistical wizard, Rich Meindl, thank you for creating clarity from data
chaos. To Joe Erwin, this project would not have been possible without your dedication and hard work for
many years with the Great Ape Aging Project. In addition, I would like to recognize Elliott Mufson, Bill
Hopkins, and John Ely for offering their considerable knowledge to this study as well as human and
chimpanzee tissue specimens.
I am grateful to Heather Caldwell, Stephen Fountain, and Ernest Freeman for their time and guidance as
members of my dissertation committee and to David Riccio for graciously agreeing to serve as my graduate
representative. Much appreciation also goes to Gina Wilson for training me on ELISAs, Sam Crish for
providing the laboratory space, and the entire Crish laboratory for making a visiting researcher feel
completely welcomed. To Chris Vinyard, thank you for the use of your dissection tools and access to the
xii
dissection lab at NEOMED. I also would like to express my gratitude to Peter Davies for supplying tau
antibodies, Juliette Hanson for providing sheep tissue, Michael Model for his confocal microscopy expertise,
and Cheryl Stimpson and Bridget Wicinski for their technical assistance. This research would not have been
possible without funding from the National Science Foundation (NSF BCS-1316829 to M.A.R.), National
Institutes of Health (NS-42867 and NS-73134 to W.D.H.; AG017802 to J.J.E.; AG014308 to J.M.E.;
AG014449 and AG43775 to E.J.M.), Sigma Xi, Kent State University Research Council, and Kent State
University Graduate Student Senate.
To the Raghanti laboratory members, thank you for ensuring there was never a dull moment. To Emily
Munger, I truly enjoyed training and collaborating with you, especially talking science, and I wish you the
best of luck with your own upcoming journey. To Aidan Ruth, I express my gratitude for your positive,
uplifting spirit, wonderful sense of humor, and immense skill at freeing a stubborn sheep brain from its
cranium. To my fellow comrades-in-arms, Sabina Bhatta, Krista DiSano, and Amanda Klein, it has been a
pleasure taking this ride through graduate school with you. I will fondly remember our times together,
whether it involved studying, bowling, hiking a snow-covered mountain, never-ending games, arguments of
where the true meniscus begins, or delicious food. It always included great company, stimulating
conversation, and amazing fun.
Finally, I must thank my wonderful family for their unwavering support, understanding, and love. To Tom,
Sue, Dave, and Don Reicosky, your interest in my work and sage advice has been greatly appreciated. To
Dottie and Jim Edler, your continuous encouragement and support have meant so much to me. To Sandy
and Paul Kuceyeski, thank you for always making me laugh and being two of my biggest supporters
throughout life. To Beverly Lomas, thank you for your kindness and being there whenever I need you. To
my brother, Richard Fry II, thank you for being a great little brother and always being proud of me. To my
parents, Susan and Richard Fry, I would not be who or where I am today without your patient guidance and
immense love. To my children, Emma and Owen Edler, thank you for being such great kids and for
understanding when Mama had to work and could not play. Finally, to my best friend and husband, Ryan
Edler, thank you for being with me every step of the way, for pushing me when I was tired or discouraged,
for all those extra nights on your own with the kids, and for your constant love, encouragement, and
understanding. This is as much your accomplishment as it is mine (well, almost).
xiii
CHAPTER I: OVERVIEW
Today, one of every three seniors in the United States dies with a form of dementia (1). The most
common cause of dementia is Alzheimer’s disease (AD), a progressive, irreversible brain disease that
results in decreased cognitive functioning and behavioral changes. Symptoms include memory loss,
changes in personality, agitation, restlessness, withdrawal, and loss of language abilities (2). Within 8-10
years after onset of symptoms, death typically occurs from an infection or organ failure (3).
AD can be categorized into three types: familial, early onset, and late onset. Less than 10% of cases
represent familial or early-onset AD, which have a strong genetic component, and symptoms that develop
prior to age 65. Sporadic late-onset AD accounts for approximately 90% of all cases with onset of symptoms
beginning after age 65 (4-6). Most cases of early-onset and familial AD result from genetic mutations of
APP, PSEN1, or PSEN2 genes (2, 7). The etiology of sporadic, late-onset AD remains unclear, but several
pathologic mechanisms have been proposed including neuroinflammation, calcium homeostasis
impairment, mitochondrial dysfunction, oxidative stress, and glucose dysregulation (7-11). Currently, the
predominant theory, known as the amyloid cascade hypothesis, suggests alterations in the production and
clearance of the amyloid-beta (Aβ) protein is the initiating factor of AD (12).
Amyloid is degraded and eliminated in a healthy brain, but in AD, Aβ protein fragments form extracellular,
insoluble plaques. According to the amyloid cascade hypothesis, amyloid precursor protein (APP) is
abnormally processed by β- and γ-secretases, resulting in overproduction and disrupted clearance of
amyloid-beta (12-15) (Figure 1). Consequently, Aβ peptides, particularly Aβ42, aggregate into soluble
oligomers, assemble as fibrils in an insoluble β-sheet conformation, and develop into plaques (12, 16-17).
Plaques then promote hyperphosphorylation of tau, a protein found mostly in neurons that stabilizes
microtubules. Microtubules maintain the structure of the cell and transport nutrients from one area of the cell
to another. In AD, hyperphosphorylated tau aggregates into insoluble paired helical filaments within neurons
resulting in the collapse of the microtubule structure and neurofibrillary tangle formation, apoptosis of
1
neurons, and dementia symptoms (18-21). However, the underlying factors that initiate aberrant
modifications of Aβ and tau remain unclear (22).
Another contributing factor to AD pathogenesis is neuroinflammation. During late stages of AD,
aggregated Aβ deposits are associated with microglial activation (23). Activation of these cells is
accompanied by increased expression of the complement pathway (C1q, C3b, C3a) and cytokines and
chemokines (interleukin-1β, interleukin-6, tumor necrosis factor α) (23-26). These cytokines stimulate
adjacent astrocytes to produce greater amounts of Aβ42 and release glutamate into the synapses (2728). Discharged glutamate activates the N-methyl-D-aspartate receptors in nearby neurons, triggering a
surge of calcium (28-29). In turn, increased calcium can stimulate APP metabolism (30-32).
According to the calcium hypothesis of AD, activation of the amyloidogenic signaling pathway remodels
the neuronal calcium signaling pathway (33). Dysregulation of calcium enhances the entry of external
calcium and sensitivity of the channels that release calcium from internal stores in the endoplasmic
reticulum. Increased calcium signaling correlates with progressive memory loss and greater neuronal
apoptosis in AD (10). Influx of calcium into neurons can induce oxidative stress, mitochondrial dysfunction,
tau hyperphosphorylation, and excessive nitric oxide, rendering neurons vulnerable to excitotoxicity and
apoptosis (29, 34).
Outside of pathogenic processes, a disturbance in the equimolar ratio of tau isoforms is found in
several neurodegenerative diseases including AD. Humans have six tau isoforms formed through
alternative splicing of the second, third, and tenth exons (35-36). The tau variants differ by the presence
of either three (3R) or four repeat (4R) regions in the C-terminus and the absence or presence of a 29amino acid or 58-amino acid insert in the N-terminus (35-37). Healthy adult human brains have an
approximate 1:1 ratio of 3R and 4R-tau isoforms, while studies have shown that multiple
neurodegenerative diseases are associated with an overproduction of 3R or 4R tau (38). Frontotemporal
dementia-17, progressive supranuclear palsy, and corticobasal degeneration are associated with an
overproduction of 4R tau, while 3R tau inclusions are more predominant in Pick’s disease, a tau-positive
variant of frontotemporal dementia (39-42). Evidence is contradictory in AD with reports of an increase in
3R:4R-tau ratio, an increase in 4R:3R-tau ratio, and normal ratios (43-47). In vitro work shows increased
ratios of 4R to 3R tau accelerates tau filament assembly and favors tau aggregation, while small amounts
2
of 3R tau can significantly inhibit 4R-tau assembly (48). Surprisingly, great apes seem relatively resistant
to developing tauopathy despite Aβ deposition and the formation of senile plaques (49-53). Prior research
suggests chimpanzees and gorillas may have fewer 4R-tau isoforms (54). If great apes have greater
levels of 3R-tau isoforms, this may confer resistance to developing tauopathy.
Currently, Alzheimer’s disease is considered exclusive to humans (55). Aβ pathology has been identified
in several species including dog, cat, bear, wolverine, lemur, marmoset, tamarin, squirrel monkey, rhesus
macaque, cynomolgus monkey, baboon, chimpanzee, orangutan, and gorilla (49-53, 56-58). Abnormally
phosphorylated tau protein or localized tau pathology has been found in rhesus and cynomolgus
macaques, squirrel monkeys, baboons, and a single female chimpanzee (56, 58-61). While Aβ and tau
pathology have been identified in species other than humans, these animals typically present with either Aβ
pathology or tauopathy, but not both. The human-specificity of AD suggests that changes in the structure
and function of our cerebral cortex during evolution may have made humans particularly vulnerable to
neurodegenerative diseases (16, 62-64). Thus, approaching AD from a comparative neuroanatomical
standpoint could elucidate the selective vulnerability of humans as well as improve our understanding of
this complex disease.
Few studies have investigated AD pathology in chimpanzees, the species closest in phylogeny and
most genetically related to humans. Prior investigations in great apes have lacked quantitative analyses
due to small, inconsistent sample sizes. The goals of the present research were to evaluate a large
sample of aged chimpanzees for the presence of AD-like pathology and to understand potential factors
that may contribute to human-specific susceptibility to AD. To this end, we examined four brain regions,
most noted for AD in humans, from 20 aged chimpanzees for AD pathogenic factors using
immunohistochemistry with antibodies directed against Aβ, tau, activated microglia, and calcium-binding
protein. We expected to observe occasional diffuse Aβ plaques, amyloid deposition in blood vessels, and
rising numbers of pretangles with age. We did not anticipate significant tangle pathology. Microglial
activation was expected to increase, while calbindin levels would not differ in association with age and Aβ
pathology. These analyses will inform the aforementioned hypotheses related to AD, including the
amyloid cascade and calcium hypotheses, and the role of neuroinflammation. Additionally, sandwich
ELISAs were performed to determine the levels of 3R- and 4R-tau isoforms in adult chimpanzees, which
3
currently is only known in humans and rodents. We hypothesized that normal adult chimpanzees and
baboons would have a 1:1 ratio of 3R- and 4R-tau isoforms.
Figure 1. Pathogenic mechanisms of Alzheimer’s disease. Adapted from Selkoe and Hardy, 2016.
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9
CHAPTER II: ALZHEIMER’S DISEASE PATHOLOGY IN AGED CHIMPANZEES
INTRODUCTION
Alzheimer’s disease (AD) is a progressive, irreversible brain disease that results in decreased
cognitive functioning and behavioral changes. Two diagnostic hallmarks of AD are amyloid-beta (Aβ)
plaques and neurofibrillary tangles (NFTs) (1-2). Amyloid plaques consist of extracellular deposits of
insoluble Aβ protein fragments and can be classified as diffuse or dense-core (3-5). Diffuse plaques have an
amorphous shape with ill-defined contours, lack a glial response, and are thioflavin-S negative. Dense-core
plaques contain fibrillar amyloid deposits with a compact, spherical core, and are associated with glial
reactivity and thioflavin-S positivity (6). Dense-core plaques are frequently surrounded by dystrophic
neurites, or axonal and dendritic segments containing paired helical filaments (PHFs), and are known as
neuritic plaques (NPs) (7-9). While diffuse plaques are relatively common in cognitively intact elderly people,
dense-core plaques are affiliated with cognitive impairment and used in the diagnosis of AD (10). In addition
to plaques, approximately 80% of AD patients have Aβ accumulation in the brain’s blood vessels, a
condition called cerebral amyloid angiopathy (CAA) (5). According to the amyloid cascade hypothesis,
alterations in the production and clearance of Aβ initiate the development of these plaques, which leads to
hyperphosphorylation, misfolding, and accumulation of a protein called tau (11-12). In early stages of tau
deposition, pretangle neurons look morphologically normal with minimal non-fibrillar tau and diffuse
cytoplasmic staining (13). Intracellular accumulations of hyperphosphorylated and misfolded tau protein
aggregate into insoluble PHFs, which extend into dendrites, forming NFTs that contribute to cellular death
(14-16).
Humans are considered uniquely susceptible to AD and other neurodegenerative disorders, potentially
due to genetic differences, changes in cerebral structure and function during evolution, and an increased
lifespan (17-20). While Aβ and tau pathology have been identified in species other than humans, these
animals typically present with one type of pathology and lack the cognitive deficits of AD (17-18, 21-23).
10
Previous studies in monkeys and great apes confirmed the presence of diffuse and neuritic plaques as
well as vascular amyloid (22-36). Those analyses reported that plaques in apes were negative or weakly
positive for thioflavin S, a dye that detects amyloid fibrils in plaques and PHF structure in NFTs, while
cerebrovascular amyloid stained with stronger intensity. Abnormally phosphorylated tau protein and taurelated changes in neurons and glia have been detected in rhesus macaques, squirrel monkeys, and
baboons (22, 37-40). Gorillas exhibited hyperphosphorylated tau-positive neurons in the neocortex in
close relationship with Aβ plaques, but neurons looked healthy and lacked histopathologic abnormalities
(36). Despite the presence of diffuse Aβ plaques and vascular amyloid, neuropathological findings in
chimpanzees and orangutans identified an absence of NFTs and neuropil threads (32-34). The only
evidence of tangle and Aβ pathology co-existing in a species other than humans was found recently in a
41 year-old female chimpanzee that had a history of high cholesterol and suffered a stroke prior to death
(35). This ape presented with scarce diffuse senile plaques and vascular amyloid, NFTs, neuropil threads,
and clusters of tau-positive neurites in the neocortex with little to no tau-related changes in the
hippocampus. Nevertheless, tauopathy in this instance may have been related to conditions that initiated
the ischemic event, a rare occurrence in nonhuman primates, since cerebrovascular diseases are
recognized as contributors to dementia and risk of dementia after stroke is increased twofold (41).
As the lone species besides humans to display both principal markers of AD, chimpanzees are in a
pivotal position to expand our knowledge of this complex disease. Tau protein in chimpanzees shares 100%
sequence homology with human tau, and all six tau isoforms in humans are present in chimpanzees (4244). Moreover, amyloid precursor protein 695 (APP695)―which can be cleaved into varying lengths of the
Aβ peptide in neurons―is more than 99% identical in chimpanzees and humans (23, 45). As our closest
living relative, chimpanzees demonstrate behavioral complexity and have much longer lifespans (53 years in
the wild and 62 years in captivity) compared to AD animal models (46-47). This makes chimpanzees an
ideal candidate to study age-related neurodegenerative diseases such as AD. The goal of the current study
was to evaluate a large group of aged chimpanzees for AD pathology and determine if existing pathology
was comparable to humans with AD.
11
MATERIALS AND METHODS
Specimens
Postmortem brain samples from 20 aged chimpanzees (Appendix A) were acquired from American Zoo
and Aquarium-accredited zoos or research institutions and maintained in accordance with each institution’s
animal care and use guidelines. The chimpanzees in this study did not participate in formal behavioral or
cognitive testing. Sex and age was balanced as equally as possible. Samples from four regions,
prefrontal cortex (PFC), midtemporal gyrus (MTG), and hippocampal subregions CA1 and CA3, were
taken from eight male (ages 39-62) and 12 female (ages 37-58) chimpanzees.
Sample Processing
Samples were taken from right or left hemispheres, depending on availability. Data examining interhemispheric distribution of AD and vascular pathology found NFT and Aβ deposition was symmetrical even
in early stages of neurodegeneration, and variability in the Clinical Dementia Rating scale was nearly
identical in the two hemispheres, indicating assessment of vascular and AD pathology in one hemisphere is
sufficient (48). Brains were collected postmortem (postmortem interval < 20 h) and immersion fixed in 10%
buffered formalin solution for at least 10-14 days. Specimens were transferred to a 0.1 M buffered saline
solution with 0.1% sodium azide, cryoprotected in a graded series of 10, 20, and 30% sucrose solutions,
and stored at 4°C. Brains were frozen in dry ice and cut into 40 µm-thick sections in the coronal plane using
a Leica SM2000R freezing sliding microtome (Buffalo Grove, IL). Sections were placed into individual
centrifuge tubes containing freezer storage solution (30% dH2O, 30% ethylene glycol, 30% glycerol, 10%
0.244 M phosphate buffered saline [PBS]), numbered sequentially, and stored at -20°C until histological or
immunohistochemical processing. Every tenth section was stained for Nissl substance with a 0.5% cresyl
violet solution to reveal cell somata. Nissl-stained sections were used to define cytoarchitectural boundaries
for regions of interests.
12
Identification of Sampling Regions
All regions in the study were readily identified using Nissl-stained sections. Brain areas were selected
based on Braak staging of NFTs and Thal phases of Aβ deposition in humans with AD as well as prior
studies in aged chimpanzees (32-33, 35, 49-51). Sampling regions included layer III (external pyramidal
layer) in Brodmann’s areas 9 and 10 of the dorsolateral PFC, layer III in Brodmann’s area 21 of the MTG,
and in stratum pyramidale layer in CA1 and CA3 subregions of the hippocampus. In AD, pyramidal neurons
in layers III and V of the neocortex and stratum pyramidale layer in the hippocampus suffer the greatest
neuron and synapse loss, and distribution of neuritic Aβ plaques and NFTs is most prevalent in these layers
(52-54).
Immunohistochemistry
Every twentieth section from each subject and sampling area was immunohistochemically processed for
tau epitopes, APP/Aβ, and Aβ42 (Appendix B) following established protocols utilizing the avidin-biotinperoxidase method (55-56). Further sections were double immunostained for AT8/Aβ42, AT8/GFAP,
AT8/Iba1, APP/Aβ/GFAP, and APP/Aβ/Iba1 to determine colocalization of pathologies and whether glial
reactivity was present near APP/Aβ-immunoreactive (ir) and Aβ42-ir plaques. Immunohistochemistry is the
preferred method of detection for Aβ plaques and NFTs (51), and specific antibodies for tau and Aβ were
chosen based on successful use in previous studies with chimpanzees and gorillas (35-36). Free-floating
sections were pretreated for antigen retrieval by incubation in 0.05% citraconic acid (pH 7.4) (APP/Aβ, AT8,
CP13, PHF1) at 86°C or in a 10 mM citrate buffer (pH 3.0-4.0) (MC1, Aβ42) at 37°C for 30 min.
Endogenous peroxidase was quenched (75% CH3OH, 2.5% H2O2 [30%], 22.5% dH2O) for 20 min at room
temperature (RT), and sections were preblocked for 1 h in a solution of 0.1 M PBS (pH 7.4), 0.6% Triton X,
4% normal serum, and 5% bovine serum albumin at RT. Sections then were placed in primary antibody
diluted in PBS for 48 h at 4°C. Next, sections were incubated in a biotinylated secondary antibody (1:200
dilution) in a solution of PBS and 2% normal serum (1 h, RT), followed by an avidin-peroxidase complex
(1 h, RT, PK6100, Vector Laboratories, Burlingame, CA) and either 3,3’-diaminobenzidine (DAB) with nickel
enhancement or Vector NovaRED (SK-4100/SK-4800, Vector Laboratories). Neocortical tissue from the
brain of a patient who died from AD was used as a positive control, and neocortical samples from young
13
chimpanzees (ages 16-20) as well as omission of the primary antibody were used as negative controls.
Thioflavin S
Adapted from previously published protocols, sections were rinsed in a 0.1 M PBS and mounted on
slides (57-59). Once dry, sections were placed in Citri-Solv for 10 min and hydrated in a series of ethanol
solutions (100/95/70/50%) followed by dH2O (2 x 1 min). Sections were incubated in a filtered 1% aqueous
thioflavin S solution (Sigma, T1892) for 15 min at RT followed by dehydration in 70/80/95/100/100% ethanol
solutions for 2 min each. Next, sections were placed in a filtered 1% sudan black B solution (Sigma, 19,9664, dissolved in 70% ethanol) for 15 min and then placed in Citri-Solv for 5 min. Cover glass was applied with
a hydrophilic mounting media, and slides were stored at 4°C for 48 h before images were taken at 20x (N.A.
0.7) on an Olympus FV1000 Laser Scanning Confocal Microscope using Olympus FV10-ASW 3.0 Viewer.
The excitation filter (DM 458/515) was selected based on available lasers and optimal excitation (~440-470
nm) and emission wavelengths for thioflavin S (~515-550 nm) (60).
Pathology Identification
The current study defined tau and Aβ pathology as previously outlined in Serrano-Pozo et al., 2011 (5).
Amyloid plaques were defined as extracellular deposits of insoluble Aβ. Plaques were not distinguished
between diffuse (Figure 2A) and dense-core (Figure 2B), though both types were present and confirmed by
thioflavin S staining. CAA was categorized by deposits of Aβ in the tunica media of leptomeningeal and
cortical arteries and in small arterioles (Figure 2C). Pretangles were defined as healthy-looking neurons with
the presence of diffuse punctate tau staining in the cytoplasm, well-preserved dendrites, and a centered
nucleus (Figure 2D). NFTs contained intraneuronal aggregates of hyperphosphorylated and misfolded tau,
and the nucleus was either displaced toward the periphery of the soma or absent (Figure 2E). Dendrites and
axons were distorted, shortened, or absent in tangles. Tau NPs contained clusters of dystrophic neurites,
consisting of AT8-ir swollen axons and dendrites, or diffuse, punctate staining (Figure 2F).
14
Data Acquisition
Quantitative analyses were performed using computer-assisted stereology with an Olympus BX-51
photomicroscope equipped with a digital camera and StereoInvestigator software version 11 (MBF
Bioscience, Williston, VT) by a single observer. Subsampling techniques were performed for each probe to
determine appropriate sampling parameters (61). Two-dimensional topographical mapping of APP/Aβ and
Aβ42 plaques and vessels (Figure 3A) and tau-ir profiles (AT8/CP13/MC1/PHF1) (Figure 3B) was
completed in individuals with the most pathology (n = 7). Maps were used to determine regional progression
of pathology for staging purposes (see Pathology Scoring). This spatial data indicated the highest number of
pretangles, NFTs, and tau NPs were detected by AT8, and thus, quantification for each tau pathology type
was performed with this stain (Figure 4).
Figure 2. Types of AD pathology in elderly chimpanzees. (A) diffuse APP/Aβ-ir plaque, (B) dense-core Aβ42-ir
plaque, (C) APP/Aβ-ir leptomeningeal arteries, (D) AT8-ir pretangle neuron, (E) AT8-ir NFT, and (F) AT8-ir tau
neuritic plaque. Scale bar = 25 µm (A-B, D-F), scale bar = 250 µm (C).
15
AT8-ir pretangle, NFT, and tau NP densities were obtained using the optical fractionator probe at 40x
(N.A. 0.75) under Köhler illumination. Grid size was 250 µm x 250 µm with a disector height of 8.00 µm and
a guard zone of 2%. Beginning at a random starting point, three equidistant sections (every tenth or 20th
section) per area of interest and individual were selected for analysis. Mounted section thickness was
measured every fifth sampling site. A different marker for each pathology type was placed when
encountered within the optical disector frame. Densities (mm3) for each region were calculated as the
population estimate of pretangle, NFT, and tau NP markers divided by planimetric volume of the disector
(62). For each individual, densities for PFC and MTG were averaged to calculate neocortical (NC)
density. The same process was executed for CA1 and CA3 to compute average hippocampal (HC)
density. Densities for all four regions were averaged for total pretangle, NFT, and tau NP densities.
Figure 2. Topographical distribution of AD pathology. (A) APP/Aβ-ir plaques and vessels (left) and corresponding
Nissl-stained section (right) and (B) AT8-ir pretangles, NFTs, and tau NPs (left) and corresponding Nissl-stained
section (right) in the midtemporal gyrus (MTG) and hippocampus (CA1/CA3) of a 57-year-old male chimpanzee.
16
Figure 4. Tau pathology (mm3) by stain. (A) pretangle density, (B) NFT density , and (C) tau NP density. Whiskers
represent 1 SD.
To correct for tissue shrinkage in the z axis, the height of the disector was multiplied by the ratio of section
thickness to the actual weighted mean thickness after mounting and dehydration. No correction was
necessary for the x and y dimensions because shrinkage in section surface area is minimal (63). The mean
number of sampling sites for each area per individual was 93 ± 30.99.
Percentages of volume occupied by APP/Aβ-ir and Aβ42-ir plaques and vessels were measured in all
regions of interest using the area fraction fractionator (AFF) probe, founded on a Cavalieri point counting
system. Using a 10x objective (N.A. 0.25), markers were placed on a grid of points (300 µm x 300 µm)
overlaying the sampling area. Every point on the grid received one of three potential markers: non-Aβ, Aβ
plaque, or Aβ vessel. Estimated area fractions were calculated by the AFF probe and reported as
percentages for each region per individual. Percentage of volume occupied by APP/Aβ-ir and Aβ42-ir
plaques for PFC and MTG were summed to calculate total neocortical (NC) percentage and the equivalent
was performed for CA1 and CA3 percentages to determine total hippocampal (HC) percentage.
Percentages from all four regions were summed for total volume occupied by APP/Aβ-ir and Aβ42-ir
plaques respectively. The same procedure was conducted for APP/Aβ-ir and Aβ42-ir vessel volumes. The
mean number of sampling sites for each area per individual was 70 ± 15.18. In addition, APP/Aβ-ir and
Aβ42-ir vessel diameters were measured using the quick circle tool in StereoInvestigator during AFF data
collection for every positive vessel within the grid. Diameters (µm) were averaged by region for every
subject.
17
Pathology Scoring (Brain Age)
To evaluate neuropathologic changes for each individual, a brain age value was computed utilizing a
pathology scoring system adapted from staging guidelines for Aβ and NFT deposition in AD and CAA
(Table 1) (8, 16, 49-51, 64-65). The Consortium to Establish a Registry for AD (CERAD) protocol was used
for scoring APP/Aβ-ir plaque and AT8-ir tau NP frequency (8). To measure regional progression of APP/Aβir plaque accumulation in the brain, a modified, four-point scale of Thal phases was incorporated (50-51).
Staging of CAA was based on prior studies examining topographical distribution and frequency of Aβ in
vasculature as well as intensity of staining (64-65). NFTs were evaluated using a revised Braak four-stage
classification described in the National Institute on Aging-Alzheimer’s Association guidelines for AD
assessment (49, 51).
For every animal, each of the four brain regions was given a score from 0 to 3 (e.g., PFC = 1, MTG = 0,
CA1 = 2, CA3 = 0). Regional scores then were summed for a total score per staging method ranging from 0
to 12. Scores for each of the five staging assessments were summed for a total pathology score (brain age)
with the maximum potential value of 60. Regional APP/Aβ-ir plaque and vessel volumes, AT8-ir pretangle,
NFT and tau NP densities, topographical distribution maps of all five pathologies (Figure 3), and staining
images were used for scoring purposes. Based on the CERAD protocol, APP/Aβ-ir plaque volume was
considered mild when less than 1% and moderate when more than 1%; no frequent cases were present in
this sample. Besides the number of regions affected, CAA staging was evaluated using total APP/Aβ-ir
vessel volume. Less than 1% was scored as minimal, 1-4% as mild, 5-15% as moderate, and more than
15% as severe. NFT stages were assigned based on location and severity of pathology. Tau NP densities
less than 100/mm3 were scored as sparse, 100-250/mm3 as moderate, and more than 250/mm3 as frequent.
Table 1. Proposed scoring system for AD pathology in chimpanzees
Pathology
Aβ plaques
Aβ vasculature
NFTs
Tau NPs
Staging
CERAD
Thal phases
CAA stages
Braak stages
CERAD
Scoring
0 Absent
1 Sparse
2 Moderate
3 Frequent
0 Absent
1 Stages 1/2
2 Stage 3
3 Stages 4/5
0 Absent/minimal
1 Mild CAA
2 Moderate CAA
3 Severe CAA
0 Absent
1 Stages I/II
2 Stages III/IV
3 Stages V/VI
0 Absent
1 Sparse
2 Moderate
3 Frequent
18
Statistical Analyses
All densities and volumes were checked for linearity and transformed using the formula: arcsin (sqrt
(volume or density/1,000)). Principal component analysis (PCA) was performed to reduce the number of
pathological variables to the most relevant factors for brain age in chimpanzees, and regression factors
(PCA-generated brain age factor) from this analysis were employed for further analyses. Data were
screened for inter-correlation of variables using a correlation matrix. To address potential errors due to
singularity and multicollinearity, variables that had extremely low or high correlations (0.1 > R > 0.9) were
excluded from factor analyses. Determinant of the R-matrix was 0.09. Though percentages of plaque and
vessel volume were quantified for APP/Aβ and Aβ42, only APP/Aβ-ir volumes were utilized in PCA
analyses as both stains measured the same underlying dimension. Pretangles are not used as a
diagnostic marker of AD pathology in humans; therefore, we excluded pretangle density from the PCAgenerated brain age factor. The Kaiser-Meyer-Olkin measure of sampling adequacy was 0.62, and
Bartlett’s test of sphericity was significant (χ2 = 39.98, p < 0.01). Communalities were above 0.45,
confirming each item shared some common variance with the other pathologies. As PCA-generated brain
age factor and calculated brain age score resulted in similar correlations with chronological age,
densities, and volumes, only correlations with PCA-generated brain age factor were reported. Spearman
rank correlation was used to evaluate relationships among PCA-generated brain age factor, brain age
score, and chronological age. To assess for sex differences in PCA-generated brain age factor, a MannWhitney U test was utilized. Regression analyses were performed to determine relationships between tau
densities and Aβ variables as well as with PCA-generated brain age factor and chronological age. Two-way
ANOVAs with Bonferroni post hoc tests were conducted to examine sex differences in tau and Aβ
pathologies. Variances among brain regions for each pathology variable were analyzed using one-way
ANOVA with Bonferroni post hoc. Statistical analyses were conducted using IBM SPSS Statistics, Version
22 (Armonk, NY), and level of significance (α) was set at 0.05.
19
RESULTS
Chronological Age and Brain Age Correlations
PCA was used to identify and compute a composite brain age value (PCA-generated brain age) for Aβ
and tau pathologies. Five variables (i.e., NC and HC tau NP densities, HC NFT density, and total
APP/Aβ-ir plaque and vessel volumes) explained 57.13% of the variance. All variables had primary
loadings between 0.67 and 0.87.
Chronological age and PCA-generated brain age were positively correlated (rs = 0.52, p = 0.01).
Neocortical, hippocampal, and total APP/Aβ-ir and Aβ42-ir plaque and vessel volumes significantly
increased with chronological age (p’s < 0.01) (Table 2). Total pretangle density also rose as animals aged
(p = 0.02), though NFT and tau NP densities did not exhibit a relationship with chronological age (p’s >
0.10). PCA-generated brain age was positively associated with percentage of volume occupied by
APP/Aβ-ir and Aβ42-ir plaques and vessels (p’s ≤ 0.01). Unlike chronological age, brain age was
correlated with all three tau pathology types. Total and hippocampal pretangle and NFT densities, in
addition to total, neocortical and hippocampal tau NP densities, were higher in individuals with greater
brain age (p’s ≤ 0.03), though the same relationship was not observed in neocortical pretangle and NFT
densities (p’s ≥ 0.68). Differences in PCA-generated brain age among the eight males and 12 females
were not found (Mann-Whitney U = 46.00, p = 0.91).
20
Table 2. Correlation coefficients for Aβ and tau pathology versus chronological age and PCA-generated brain age
Chronological Age
2
PCA-generated Brain Age
Adj R
T
p
Adj R2
t
p
NC APP/Aβ Plaque Volume
0.46
4.13
0.00
0.39
3.60
0.00
HC APP/Aβ Plaque Volume
0.46
4.11
0.00
0.53
4.69
0.00
Total APP/Aβ Plaque Volume
0.60
5.41
0.00
0.58
5.26
0.00
NC Aβ42 Plaque Volume
0.49
4.35
0.00
0.31
3.07
0.01
HC Aβ42 Plaque Volume
0.59
5.00
0.00
0.46
3.93
0.00
Total Aβ42 Plaque Volume
0.56
5.00
0.00
0.38
3.53
0.00
NC APP/Aβ Vessel Volume
0.75
7.69
0.00
0.76
7.73
0.00
HC APP/Aβ Vessel Volume
0.61
5.52
0.00
0.65
6.00
0.00
Total APP/Aβ Vessel Volume
0.73
7.23
0.00
0.74
7.40
0.00
NC Aβ42 Vessel Volume
0.59
5.34
0.00
0.55
4.88
0.00
HC Aβ42 Vessel Volume
0.50
4.21
0.00
0.44
3.78
0.00
Total Aβ42 Vessel Volume
0.58
5.26
0.00
0.52
4.65
0.00
NC Pretangle Density
0.10
1.75
0.10
-0.05
0.42
0.68
HC Pretangle Density
0.04
1.32
0.20
0.56
4.98
0.00
Total Pretangle Density
0.25
2.69
0.02
0.19
2.32
0.03
NC NFT Density
-0.03
-0.68
0.50
-0.06
-0.03
0.98
HC NFT Density
0.09
1.69
0.11
0.42
3.81
0.00
Total NFT Density
-0.03
0.68
0.51
0.23
2.58
0.02
NC Tau NP Density
0.06
1.45
0.16
0.49
4.42
0.00
HC Tau NP Density
0.06
1.46
0.16
0.50
4.51
0.00
Total Tau NP Density
0.09
1.69
0.11
0.61
5.53
0.00
APP/Aβ-ir and Aβ42-ir Plaque Volume
Thirteen chimpanzees had APP/Aβ-ir plaques while five presented with Aβ42-ir plaques (Figure 5A-F).
Of those with Aβ42-ir plaques, four were the oldest individuals in the study (57-62 years). Aβ42-ir plaques
were missing in the youngest subjects (39-44 years). Diffuse and dense-core plaques were identified in both
sexes and were thioflavin-S positive, though diffuse plaques displayed a weaker intensity than dense-core
plaques (Figure 6A-C). Plaques with an Aβ core surrounded by dystrophic neurites were not observed.
Plaques were distributed in all neocortical layers and were often near vessels with Aβ buildup (Figure 6MO). Reactive astrocytes were seldom noted in the vicinity of plaques. Phase 4 was the highest Thal phase
of Aβ deposition recorded in two of the eldest individuals.
21
Total percentage of area occupied by plaques was higher in the neocortex (APP/Aβ = 0.28%, Aβ42 =
0.24%) compared to the hippocampus (APP/Aβ = 0.12%, Aβ42 = 0.08%), though factorial ANOVA yielded
non-significant results for region (F1,73 = 2.22, p = 0.14) (Figure 7A). While all regions displayed a higher
percentage of area occupied by APP/Aβ-ir plaques, APP/Aβ-ir plaque volume did not differ significantly
from Aβ42-ir plaque volume (F1,73 = 0.96, p = 0.33), and the interaction between region and stain was not
significant (F1,73 = 0.33, p = 0.57) (Appendices C-D). APP/Aβ-ir plaque burden was similar in both sexes
(F1,72 = 0.35, p = 0.56) regardless of region (F3,72 = 1.21, p = 0.31) with no interaction between sex and
region (F3,72 = 0.99, p = 0.40) (Figure 8A). However, Aβ42-ir plaque volume showed a significantly higher
distribution in males than females (F1,66 = 5.13, p = 0.03) across all areas (F3,66 = 0.38, p = 0.77) with a
non-significant interaction (F3,66 = 0.01, p = 0.99; Figure 8D).
APP/Aβ-ir and Aβ42-ir Vessel Volume and Diameter
All 20 chimpanzees displayed both APP/Aβ-ir and Aβ42-ir blood vessels including leptomeningeal
arteries, cortical arteries, and smaller arterioles (Figure 5G-J). The three oldest individuals in the study
(ages 57-62) displayed severe CAA in both the neocortex and hippocampus. Total vessel volume ranged
from 21.6-23.3% for APP/Aβ and from 16.3-25.9% for Aβ42 (Appendices E-F). A single case of moderate
CAA was observed in a 58-year-old female chimpanzee with 5.2% total APP/Aβ-ir vessel volume and
3.8% total Aβ42-ir vessel volume. All other chimpanzees (ages 37-51 years) exhibited minimal to mild
CAA with total APP/Aβ-ir vessel volume between 0.1-2.7% and total Aβ42-ir vessel volume between 0.023.1%. These individuals also had decreased intensity in staining as well as fewer affected vessels and
regions than older chimpanzees, with those in the minimal category commonly lacking Aβ-positive blood
vessels in the hippocampus. Cerebrovascular amyloid was thioflavin-S positive (Figure 6I-L) and
frequently bordered by GFAP-ir astrocytes and tau pathology (Figure 9A,G-K).
Total vessel volume was greater in the neocortex (APP/Aβ = 3.0%, Aβ42 = 2.6%) compared to the
hippocampus (APP/Aβ = 1.2%, Aβ42 = 1.3%) based on a two-way ANOVA, which revealed a significant
main effect of region (F1,73 = 4.96, p = 0.03) but not stain (F1,73 = 0.00, p = 0.97), with a nonsignificant
interaction (F1,73 = 0.18, p = 0.67). However, Bonferroni post hoc analyses determined distribution of
APP/Aβ-ir and Aβ42-ir vessels was comparable respective of region (p’s > 0.10) (Figure 7B).
22
Figure 5. APP/Aβ-ir and Aβ42-ir plaques and vessels. (A-B,E) APP/Aβ-ir plaques, (C-D,F) Aβ42-ir plaques, (G)
APP/Aβ-ir cortical artery and arterioles, (H) APP/Aβ-ir leptomeningeal arteries, (I) Aβ42-ir cortical artery (J) Aβ42ir cortical arterioles, (K) APP/Aβ-ir cortical arterioles, (L) Aβ42-ir cortical arterioles, and (M-O) APP/Aβ-ir plaques
(red arrows) near immunoreactive vessels (white arrows). Scale bar = 280 µm.
23
Figure 6. Thioflavin S staining in elderly chimpanzees. (A) diffuse plaque, (B) dense-core plaque, (C) plaque near
immunoreactive vessel, (D) perivascular leakage from arteriole, (E-G) neurofibrillary tangles, (H) NFT near vessel,
(I-J) cortical arteries, and (K-L) cortical arterioles. Scale bar in each panel = 20 µm.
Percentage of area occupied by APP/Aβ-ir and Aβ42-ir vessels also did not vary between sexes (APP/Aβ:
F1,72 = 1.45, p = 0.23; Aβ42: F1,66 = 1.08, p = 0.30) (Figure 8B,E).
A two-way ANOVA for average blood vessel diameter found a significant main effect of region (F1,69 =
14.58, p < 0.01) and interaction of region and stain (F1,69 = 6.38, p = 0.01), but not for stain (F1,69 = 3.36, p =
0.07). Post hoc analyses revealed that average APP/Aβ-ir and Aβ42-ir vessel diameter in the neocortex
(APP/Aβ = 19.81 µm, Aβ42 = 18.00 µm) was greater than APP/Aβ-ir vessel diameter (p’s < 0.01), but not
Aβ42-ir vessel diameter (p = 1.00), in the hippocampus (APP/Aβ = 13.10 µm, Aβ42 = 14.66 µm). In
addition, average diameter of Aβ42-ir vessels was significantly larger than APP/Aβ-ir vessels in the
hippocampus (p = 0.02) (Figure 8C). Factorial ANOVA yielded nonsignificant main effects of sex (APP/Aβ:
F1,51 = 1.76, p = 0.20; Aβ42: F1,50 = 1.22, p = 0.28) and region (APP/Aβ: F3,51 = 1.41, p = 0.25; Aβ42: F3,50
= 1.36, p = 0.27), with no interaction (APP/Aβ: F3,51 = 0.47, p = 0.70; Aβ42: F3,50 = 0.07, p = 0.98) (Figure
8C,F).
24
Figure 7. Aβ pathology (%) by region and stain averaged for all individuals. (A) APP/Aβ-ir and Aβ42-ir plaque
volume, (B) APP/Aβ-ir and Aβ42-ir vessel volume, and (C) APP/Aβ-ir and Aβ42-ir vessel diameter (µm). Whiskers
represent 1 SD.
Figure 8. Aβ pathology (%) by sex and region. (A,D) APP/Aβ-ir and Aβ42-ir plaque volume, (B,E) APP/Aβ-ir and
Aβ42-ir vessel volume, and (C,F) APP/Aβ-ir and Aβ42-ir vessel diameter (µm). Whiskers represent 1 SD.
Pretangle, NFT, and Tau Neuritic Plaque Densities
AT8-ir pretangles, NFTs, tau NPs, and neuropil threads were present in the pyramidal layer of all CA
subfields (CA1-CA3). AT8-ir neurites extended from cell somas into the stratum radiatum and stratum
oriens. Pretangles and NFTs also were observed in the hilus of the dentate gyrus, subiculum, and entorhinal
cortex. All three types of tau-related pathology were identified in neocortical layers II-VI, though pretangles
and NFTs were more concentrated in layers III and V. Additionally, tau lesions were associated with reactive
25
astrocytes, activated microglia, and Aβ-positive vessels, and at times tau-ir appeared to be present in glial
cells (Figure 9B-L).
All 20 apes demonstrated AT8-ir pretangles in at least one brain region (Figure 10A-F; Appendix G).
Total average pretangle density was highest in NC (511.35/mm 3) compared to HC (102.51/mm 3) (F3,72 =
10.96, p < 0.01) (Figure 11A). The main effect of sex (F1,72 = 1.13, p = 0.29) (Figure 12A) and interaction
between region and sex (F3,72 = 0.71, p = 0.55) were nonsignificant. Pretangle densities were higher in
MTG (318.87/mm3) than PFC (192.48/mm 3) and in CA1 (84.78/mm3) compared to CA3 (17.73/mm 3),
though pretangle densities did not differ between the NC and HC (p’s > 0.80). CA3 was the least affected
area with only half of subjects having pretangles present.
Five individuals presented with AT8-ir NFTs (Figure 10G-L). Two chimpanzees displayed NFTs in the
PFC, though NFTs were absent in the MTG. Four apes exhibited NFTs in the CA1 but only one individual
had NFTs in the CA3. Braak stage V was recorded in a 57-year-old male, while three cases were
categorized as stage I or II. One animal with the greatest NFT density did not follow Braak staging.
Instead, this male exhibited intense, localized tau pathology exclusively in the PFC. Unlike pretangle
density, total average NFT density was higher in HC (7.36/mm3) than NC (6.31/mm3) (Appendix H),
although ANOVA yielded nonsignificant results for the main effects of region (F3,72 = 0.00, p = 1.00;
Figure 10B) and sex (F1,72 = 0.00, p = 1.00) (Figure 12B), with no interaction (F3,72 = 0.00, p = 1.00). PHF
structure of NFTs was verified with thioflavin S (Figure 6E-H).
Tau NPs were present in either a diffuse, punctate form or a cluster of well-defined dystrophic
neurites, and twelve apes exhibited tau NPs (Figure 10M-R). Tau NPs were found in both neocortical and
hippocampal regions for six cases, in NC only for three subjects, and in HC for another three individuals
(Appendix I). Though total average tau NP densities were higher in NC (81.15/mm3) than HC (8.40/mm3),
there was no significant effect of region (F3,72 = 2.35, p = 0.08) (Figure 11C), sex (F1,72 = 3.39, p = 0.07)
(Figure 12C), or interaction (F3,72 = 2.04, p = 0.12).
26
Figure 9. Co-occurrence of Aβ, tau, and glial activity. (A) APP/Aβ-ir blood vessel (DAB) with GFAP-ir astrocytes
(NovaRed, black arrows) in neocortex, (B-D) AT8-ir neuritic plaques and neurons (DAB) by reactive astrocytes
(NovaRed, black arrows) in neocortex (B-C) and hippocampus (D), (E-F) AT8-ir pretangle and neuritic plaque
(DAB) adjacent to activated microglia (NovaRed, red arrows) in neocortex, (G-L) AT8-ir pretangles, NFTs (blue
arrows), and NPs (white arrows) (DAB) associated with Aβ42-ir (NovaRed) vessels and plaques in neocortex (L)
and hippocampus (G-K). Scale bar = 280 µm.
27
Figure 10. Tau lesions (AT8-ir) in aged chimpanzee brains. (A-F) pretangles in the neocortex (C-D) and
hippocampus (A-B, E-F), (G-J) NFTs in the neocortex (H-J) and hippocampus (G, K), and (M-R) tau NPs in the
neocortex (M-N, P-R) and hippocampus (O). Scale bar = 280 µm.
28
Figure 11. Tau lesions (mm3) by regions. (A) pretangle density, (B) NFT density, and (C) tau NP density.
Whiskers represent 1 SD.
Figure 12. Tau pathology (mm3) by sex. (A) pretangle density, (B) NFT density, and (C) tau NP density. Whiskers
represent 1 SD.
Correlations of Aβ and Tau Pathologies
Average total volume occupied by Aβ vessels (APP/Aβ = 4.2%, Aβ42 = 3.9%) was significantly higher
than average total volume occupied by Aβ plaques (APP/Aβ = 0.4%, Aβ42 = 0.3%) in elderly
chimpanzees (rs = 0.70, p < 0.01) (Figure 13A). APP/Aβ-ir plaque volume correlated positively with Aβ42ir plaque volume (p < 0.01) (Figure 13B). Percentage of volume occupied by APP/Aβ-ir and Aβ42-ir
plaques also was associated positively with APP/Aβ-ir and Aβ42-ir vasculature volumes (p’s < 0.01)
(Figure 13C).
Neocortical and total average pretangle densities were not related with changes in NFT or tau NP
densities (p’s > 0.10). However, greater hippocampal pretangle density was accompanied by increases in
HC and total NFT density (p’s ≤ 0.01) (Figure 14A) as well as larger NC, HC, and overall tau NP loads
(p’s ≤ 0.03) (Figure 14B). Furthermore, hippocampal and total NFT densities were positively correlated
with NC and total tau NP densities (p’s ≤ 0.02) (Figure 14C).
29
Neocortical pretangle density and total NFT density were not associated with Aβ pathology (p’s ≥
0.25), but hippocampal and total pretangle densities were positively correlated with NC, HC, and total
APP/Aβ-ir vessel volume (p’s ≤ 0.05) (Figure 15A). Moreover, higher pretangle density was linked to
increased APP/Aβ-ir plaque volume in the hippocampus (p = 0.03) (Figure 15B). Greater NC and total
APP/Aβ-ir vessel volume was coupled with increased hippocampal NFT density (p’s = 0.02) (Figure 15C)
as well as HC and total tau NP loads (p’s ≤ 0.03) (Figure 15D). Hippocampal APP/Aβ-ir vessel volume
also was correlated with increased tau plaque loads (p’s ≤ 0.03) (Figure 15E). Unexpectedly, Aβ42-ir
plaque and vessel volumes were not affiliated with changes in tau pathology (p’s > 0.05).
Figure 13. Aβ-ir plaque volume versus vessel volume. (A) Total plaque vs vessel volume (%) by stain, (B) total
APP/Aβ-ir plaque volume vs total Aβ42-ir plaque volume (R2 = 0.54, p < 0.01), and (C) total plaque volume vs total
vessel volume by stain (APP/Aβ: R2 = 0.66, Aβ42: R2 = 0.87, p’s < 0.01). Whiskers represent 1 SD.
Figure 14. Significant correlations of tau pathologies (mm3) (p’s ≤ 0.05). (A) HC pretangle density vs HC NFT
density (R2 = 0.67), (B) HC pretangle density vs NC and HC tau NP densities (NC: R2 = 0.47, HC: R2 = 0.21), and
(C) HC NFT density vs NC tau NP density (R2 = 0.22).
30
Figure 15. Significant correlations of APP/Aβ-ir (%) and tau (mm3) lesions (p’s ≤ 0.05). (A) HC pretangle density
vs NC and HC APP/Aβ-ir vessel volume (NC: R2 = 0.22, HC: R2 = 0.18), (B) HC pretangle density vs HC APP/Aβir plaque volume (R2 = 0.19), (C) HC NFT density vs NC APP/Aβ-ir vessel volume (R2 = 0.23), (D) HC tau NP
density vs NC and HC APP/Aβ-ir vessel volume (NC: R2 = 0.20, HC: R2 = 0.20), and (E) NC tau NP density and
HC APP/Aβ-ir plaque volume (R2 = 0.27).
31
DISCUSSION
To date, less than 50 brains of elderly apes have been examined for AD pathology (66). Here, we
present the largest investigation of AD neuropathology in any great ape with 20 brains from chimpanzees
aged 37 to 62 years old. Our findings confirm that chimpanzees are the only species other than humans
to exhibit the two main histological markers of AD in humans.
APP/Aβ-ir and Aβ42-ir diffuse and dense-core plaques were most abundant in the temporal and frontal
neocortex compared to the hippocampus; this progression aligns with Thal phases of Aβ deposition in
humans (50). Volume occupied by Aβ42-ir plaques was slightly less than APP/Aβ-ir plaques in all regions.
This finding differs from prior histological results in rhesus macaques and orangutans where Aβ40 was the
major form of beta-amyloid in those species (32, 34). Similar to gorillas, amyloid plaques in chimpanzees
frequently were concomitant to amyloid-ir vessels and reactive astrocytes (36). Aβ42 plaque volume was
significantly greater in males than females, but this variance may not be an accurate reflection of sex
differences. Of chimpanzees with the most severe Aβ pathology, two were males and one was female.
Furthermore, sex was not found to be a significant factor for APP/Aβ-ir and Aβ42-ir vessel volume or any
tau pathological marker.
Elderly chimpanzees exhibited Aβ-positive vessels in the neocortex and hippocampus. Total volume
occupied by APP/Aβ-ir and Aβ42-ir vessels was 4.2% and 3.9% respectively, and vessels were strongly
positive for thioflavin S. These data imply that vessels accumulate fibrillar Aβ and that Aβ42 may be the
prevalent form of amyloid-beta in chimpanzees with CAA. This idea was supported by a recent study in
aging squirrel and rhesus monkeys that found immunoreactive parenchymal vasculature and plaques
contained mostly Aβ42 peptides (67). Previous research in chimpanzees also demonstrated higher soluble
and insoluble levels of Aβ42 than Aβ40 (35). Therefore, aged chimpanzees may differ from humans with
severe CAA in which Aβ-positive vessels express stronger Aβ40-ir than Aβ42-ir (68). However, regional
progression of Aβ deposition in CAA appears similar in humans and chimpanzees with greatest
accumulation in the occipital cortex followed by frontal, hippocampal, and frontobasal regions (65). While
occipital and frontobasal areas were not examined in this study, a higher percentage of vessels were
affected in the neocortex than hippocampus.
32
The presence of APP/Aβ and Aβ42-positive vasculature in all cases yet plaques in only two-thirds
suggests aggregation of Aβ in the vessels may be a precursor for plaque development in aged
chimpanzees. Production of Aβ by smooth muscle cells within vessel walls and derivation from brain
neuropil due to perivascular drainage have been implicated as sources of beta-amyloid in CAA (50, 69-72).
Leptomeningeal and cortical arteries as well as arterioles have smooth muscle cells in their tunica media,
while smaller capillaries lack a smooth muscle layer. Capillary diameter ranges from 5-10 µm, while
arterioles and arteries have a diameter larger than 10 µm (73). Approximately 86.4% of APP/Aβ-ir and
Aβ42-ir vessels in chimpanzees were greater than 10 µm in diameter, and most positive vessels under 10
µm were located in hippocampal subfields. Even in the hippocampus, average vessel diameter less than 10
µm accounted for merely 26.1% of immunoreactive vessels. Such evidence indicates that most vessels with
Aβ aggregation were arteries and arterioles rather than capillaries, supporting the hypothesis that smooth
muscle cells may produce Aβ in CAA in elderly chimpanzees. In addition, accumulation of Aβ in vessels has
been proposed to block the drainage pathway of extracellular interstitial fluid and soluble amyloid-beta,
resulting in leakage of these materials from the vessel. Extracellular soluble amyloid-beta then forms
plaques initiating development of tau pathology (71). Perivascular leakage was noted in this study, and in
some instances, near plaques, which may corroborate this notion in chimpanzees (Figure 6D).
Severity of CAA has been reported as significantly higher in demented patients, and new data have
shown that CAA is an independent risk factor for cognitive decline (5, 65, 74-79). Tangle density also is
dramatically higher in individuals with moderate or severe CAA compared to those with no or mild CAA,
despite similar plaque densities in both groups (80). The strong connection between CAA and neuritic
pathology is emphasized by AD cases in which neuritic plaques surround amyloid-laden cortical blood
vessels (81). Our data suggest aged chimpanzees may display an analogous pattern to humans (Figure
16). Total vessel volume occupied by APP/Aβ was significantly correlated with increased hippocampal
pretangle, NFT, and tau NP densities. Conversely, total APP/Aβ-ir plaque volume for all regions was not
associated with any tau lesion type. Rather only hippocampal APP/Aβ-ir plaque volume demonstrated a
significant relationship with tau-related markers, including hippocampal pretangle density and necortical and
total tau NP loads. Interestingly, Aβ42-ir plaque and vessel volumes were not correlated with tau pathology
in chimpanzees. These data indicate that CAA, not plaque development, may play a role in the precipitation
33
of NFT formation in chimpanzees and that the combination of Aβ40 and Aβ42 peptides (i.e., APP/Aβ) may
be more neurotoxic than Aβ42 alone.
Figure 16. Aβ plaque volume (%) and tau lesions (mm3) by severity of CAA. (A) total APP/Aβ-ir plaque volume vs
CAA stage, (B) total pretangle density vs CAA stage, (C) total NFT density vs CAA stage, and (D) total tau NP
density vs CAA stage.
Pretangle densities were highest in the neocortex, particularly MTG, compared to the hippocampus,
which is the same pattern found in a prior study of tauopathy in one chimpanzee (35). Distinct from that
case, though, NFT density was greater in the hippocampus in our group of elderly chimpanzees. Both
pretangle and NFT density patterns of deposition followed Braak staging of pretangle and tangle formation
in humans with AD. In humans, younger individuals have larger numbers of pretangles, which transition into
34
NFTs as they age (82). This evolution results in a pattern of decreasing pretangles and increasing NFTs in
older subjects. Chimpanzees displayed a different arrangement. As hippocampal pretangle densities grew,
hippocampal NFT density as well as neocortical and hippocampal tau NP load also increased. In
chimpanzees with extensive tau lesions, an intense foci of pretangles and NFTs were present in CA1,
particularly near the CA2 border. In AD, the hippocampus is one of the first and most severely affected
regions in humans (49, 51). While most individuals followed Braak staging patterns, a 39-year old male
chimpanzee presented with high concentrations of NFTs and tau NPs in the prefrontal cortex with little to
none present in the hippocampus. NFTs in this individual stained positive for thioflavin S. The location and
intensity of tau lesions in the anterior frontal lobe, in addition to an absence of Aβ plaques and only an
occasional, weakly-positive vessel, suggests tangle and tau NP plaque formation was not initiated by
amyloid-beta accumulation. Rather, this chimpanzee may offer the first pathological evidence of a tauopathy
in a species outside of humans. However, further analysis of additional brain regions and histopathological
lesions (i.e., astroglial inclusions) in this individual is required.
Contradictory to humans with AD, tau NPs in chimpanzees were not associated with an Aβ core and
were found in individuals with and without Aβ pathology. A prior study of tauopathy in a chimpanzee
demonstrated the same type of neuritic plaque (35). We also confirmed their findings that tau NPs in
chimpanzees are not astrocytic plaques by double staining for GFAP-ir astrocytes and AT8-ir (Figure 9B-C).
Tau NPs in chimpanzees appear in a diffuse, punctate form, similar to Aβ diffuse plaques, a cluster of
dystrophic neurites, or both. Neocortical layers II-V exhibited neuritic plaques. Tau-ir astrocytes and
microglia also were present near tau NPs.
Based on observations and data for Aβ and tau pathologies, we noted subtle differences between
normal aging and pathologic aging in chimpanzees (Table 3). Aβ-positive vessels and plaques increase
with both normal and pathologic aging, as evidenced by positive, significant correlations of APP/Aβ-ir and
Aβ42-ir plaque and vessel volumes with chronological age and PCA-generated brain age. In normal aging,
plaques are fewer and diffuse in nature. When pathologic aging occurs, plaque distribution is greater and a
combination of diffuse and dense-core plaques is present. Indeed, younger individuals had fewer Aβ
plaques and vessels than older individuals, while the four eldest chimpanzees had moderate or severe CAA
as well as higher plaque loads. Younger subjects also exhibited fewer Aβ-positive vessels with reduced
35
intensity of staining and shorter immunoreactive segments of vasculature. Individuals with the largest
distribution of Aβ pathology also displayed immunoreactive vessels in more brain regions, in deeper
neocortical layers and underlying white matter, and with perivascular leakage. Normal aging in chimpanzees
may be associated with an increase in hyperphosphorylation of tau, as indicated by the significant, positive
association between total pretangle density and chronological age. However, formation of NFTs and tau
NPs in chimpanzees was not correlated with chronological age, implying these pathologies are not part of
the normal aging process. Rather NFTs and tau NPs were related to PCA-generated brain age and are
likely an element of pathologic aging in chimpanzees. Apes with the most Aβ plaque and vessel pathology
also had the greatest tau pathology except the one chimpanzee previously mentioned with only tauopathy
present. The mechanisms that cause a transition from normal aging to pathologic aging remain unknown,
though as we see in humans, age is probably the greatest risk factor for pathologic aging in chimpanzees
since the oldest chimpanzees had moderate or severe CAA and tau lesions. A 57-year-old male
demonstrated extensive tau pathologies in each region, with the hippocampus being most severely affected
by NFTs, as well as occasional dense-core and diffuse Aβ plaques and severe CAA.
Table 3. Aβ and tau pathology in normal and pathologic aging in chimpanzees
Pathology
APP/Aβ plaque volume (%)
Normal Aging
Pathologic Aging
neocortical, hippocampal, and total volume
diffuse morphology
diffuse + dense-core morphology
mild glial response
neocortical, hippocampal, and total volume
few affected vessels in a single region
APP/Aβ vessel volume (%)
neocortical, hippocampal, and total volume
mild immunoreactivity in short segments of
vessels
neocortical, hippocampal, and total volume
several affected vessels in multiple regions
strong immunoreactivity in long segments of vessels
positive vessels present in deeper cortical layers
perivascular leakage
strong glial response
Pretangle density (mm3 )
total density
total and hippocampal density
regional density variances absent
NFT density (mm3 )
absent
Tau NP density (mm3 )
absent
total and hippocampal density
total, neocortical, and hippocampal density
highest density in neocortex
36
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CHAPTER III: MICROGLIA CHANGES ASSOCIATED WITH
ALZHEIMER’S DISEASE PATHOLOGY IN AGED CHIMPANZEES
INTRODUCTION
As the primary immune cell in the brain, microglia are widely dispersed with comparable distributions
across neocortical layers but higher concentrations in the hippocampus (1-4). In a healthy brain, microglia
use highly motile ramified processes to survey the cellular environment (5). When infection, trauma, or
neurodegeneration occurs, microglia go through rapid changes in cell shape, gene expression, and
functional behavior, a process known as microglial activation (6-11). Phenotypically, microglial activation
results in a graded response of decreased arborization, enlarged cell soma, and shorter or total loss of
cellular processes. When activated, microglia can travel to a lesion or infection site and increase in
density through mitotic proliferation to provide additional defense and restoration of tissue homeostasis
(12).
Microglia cells are macrophages that have been implicated in the inflammatory and degenerative
processes of Alzheimer’s disease (AD), which is characterized neuropathologically by amyloid-beta
plaques (Aβ) and neurofibrillary tangles (NFTs) (13-23). The neuroinflammation hypothesis of AD posits that
activated microglial cells stimulate neurons to overproduce Aβ peptides, leading to the formation of
extracellular plaques and hyperphosphorylation of the microtubule-stabilizing protein tau, which disrupts
normal axonal transport and leads to an accumulation of NFTs. Both of these effects in turn promote
increased microglial activation, creating a positive feedback loop that drives the development of AD. Recent
in vitro work in human neuronal cell lines demonstrated that inflammatory factors released from
stimulated human microglia upregulated mRNA and protein expression of all six tau isoforms and the
production of amyloid precursor protein (APP), which can be cleaved into Aβ peptides in AD (24).
Activated microglia cells also have been shown to migrate around Aβ plaques and NFTs, participate in the
clearance of Aβ, and proliferate at sites of Aβ deposition in the hippocampus (25-33). Colocalization of
44
NFTs, neuropil threads, and neuritic plaques with severely dystrophic (fragmented) microglial cells has
been reported, and microglial density increased in AD individuals with NFTs (34-35). Furthermore, the
relation of microglial activation to the clinical progression of AD pathology was explored by a recent study
in an AD mouse model (5xfAD) in which colony-stimulating factor 1 receptor, a necessary component for
microglial signaling and survival, was pharmacologically inhibited (36). Elimination of 80% of total
microglia due to this inhibition resulted in rescued dendritic loss, prevented neuronal loss, and improved
contextual memory despite unaltered Aβ plaque loads.
Nonhuman primates also display microglial activation in response to Aβ deposits. Microinjection of
insoluble Aβ fibrils (fAβ) in the cerebral cortex of aged rhesus monkeys resulted in profound neuron loss,
tau phosphorylation, and microglial proliferation (37). Moreover, inhibition of microglial activation with
macrophage/microglia inhibitory factor eliminated fAβ toxicity in elderly macaques (38). Yet until recently,
evidence of both Aβ and tau pathological markers of AD had not been found in species other than
humans (39). Our recent work in aged chimpanzees demonstrated the co-occurrence of Aβ and tau lesions,
suggesting AD pathology may not be limited to humans (40). This study builds upon that foundation by
evaluating activated microglia density and morphological changes of microglia in association with AD
pathology in aged chimpanzees.
MATERIALS AND METHODS
Specimens
Postmortem brain samples from 20 aged chimpanzees (Appendix A) were acquired from American Zoo
and Aquarium-accredited zoos or research institutions and maintained in accordance with each institution’s
animal care and use guidelines. Chimpanzees in this study did not participate in formal behavioral or
cognitive testing. Sex and age was balanced as equally as possible. Samples from four regions,
prefrontal cortex (PFC), midtemporal gyrus (MTG), and hippocampal subregions CA1 and CA3, were
taken from eight male (ages 39-62) and 12 female (ages 37-58) chimpanzees.
45
Sample Processing
Samples were taken from right or left hemispheres based on availability. Data examining interhemispheric distribution of AD and vascular pathology found NFT and Aβ deposition was symmetrical even
in early stages of neurodegeneration, and variability in the Clinical Dementia Rating scale was nearly
identical in the two hemispheres, indicating assessment of vascular and AD pathology in one hemisphere is
sufficient (41). Brains were collected postmortem (postmortem interval < 20 h) and immersion fixed in 10%
buffered formalin solution for at least 10-14 days. Specimens were transferred to a 0.1 M buffered saline
solution with 0.1% sodium azide, cryoprotected in a graded series of 10, 20, and 30% sucrose solutions,
and stored at 4°C. Brains were frozen in dry ice and cut into 40 µm-thick sections in the coronal plane using
a Leica SM2000R freezing sliding microtome (Buffalo Grove, IL). Sections were placed into individual
centrifuge tubes containing freezer storage solution (30% dH2O, 30% ethylene glycol, 30% glycerol, 10%
0.244 M phosphate buffered saline), numbered sequentially, and stored at -20°C until histological or
immunohistochemical processing. Every tenth section was stained for Nissl substance with a 0.5% cresyl
violet solution to reveal cell somata. Nissl-stained sections were used to define cytoarchitectural boundaries
for regions of interests.
Identification of Sampling Regions
All regions in the study were readily identified using Nissl-stained sections. Brain areas were selected
based on Braak staging of NFTs and Thal phases of Aβ deposition in humans with AD as well as prior
studies in aged chimpanzees (42-47). Sampling regions included layer III (external pyramidal layer) in
Brodmann’s areas 9 and 10 of the dorsolateral PFC, layer III in Brodmann’s area 21 of the MTG, and in
stratum pyramidale layer in CA1 and CA3 subregions of the hippocampus. In AD, pyramidal neurons in
layers III and V of the neocortex and stratum pyramidale layer in the hippocampus suffer the greatest
neuron and synapse loss, and distribution of neuritic Aβ plaques and NFTs is most prevalent in these layers
(48-50).
46
Immunohistochemistry
Every twentieth section from each subject and sampling area was immunohistochemically processed for
rabbit anti-ionized calcium-binding adapter molecule 1 (Iba1) corresponding to C-terminus (1:10,000
dilution, Wako, 019-19741) following established protocols utilizing the avidin-biotin-peroxidase method (5152). Iba1 is specifically expressed in macrophage/microglia and detects activated microglia. Additional
sections were double immunostained for PHF1 and Iba1 (1:10,000 dilution, gift from Dr. Peter Davies) or
AT8 and Iba1 (1:2,500, ThermoFisher, MN1020) to determine colocalization with NFTs (Appendix B). Freefloating sections were pretreated for antigen retrieval by incubation in 0.05% citraconic acid (pH 7.4) at 86°C
for 30 min. Endogenous peroxidase was quenched (75% CH3OH, 2.5% H2O2 [30%], 22.5% dH2O) for 20
min at room temperature (RT), and sections were preblocked for 1 h in a solution of 0.1 M phosphatebuffered saline (PBS, pH 7.4), 0.6% Triton X, 4% normal serum, and 5% bovine serum albumin at RT.
Sections then were placed in primary antibody diluted in PBS for 48 h at 4°C. Next, sections were incubated
in a biotinylated secondary antibody (1:200 dilution) in a solution of PBS and 2% normal serum (1 h, RT),
followed by an avidin-peroxidase complex (1 h, RT, PK6100, Vector Laboratories, Burlingame, CA) and
either 3,3’-diaminobenzidine with nickel enhancement (DAB) or Vector NovaRED (SK-4100/SK-4800,
Vector Laboratories).
Morphology Identification
To measure potential phagocytic activity in microglia, we quantified densities for three activated
morphological states―ramified, intermediate, and amoeboid―as previously defined (12). Briefly, ramified
morphology included long, highly arborized processes and a small cell soma (Figure 17A). The intermediate
stage of activation was noted by shorter, thicker prolongations, less arborization, and an enlarged cell body
(Figure 17B,D). The final phase was identified by an amoeboid shape with a round or enlarged cell soma
and loss of processes (Figure 17C).
47
Figure 17. Photomicrographs of activated microglia morphologies in the neocortex. (A) ramified morphology
with small cell soma and fine processes, (B) intermediate morphology with enlarged cell soma and thickened,
shorter processes, (C) amoeboid morphology with loss of nearly all processes, (D) PHF1/Iba1-immunoreactive
microglia with intermediate morphology (black arrows denote tau [PHF1] staining). Scale bar = 280 µm.
Data Acquisition
Quantitative analyses were performed using computer-assisted stereology with an Olympus BX-51
photomicroscope equipped with a digital camera and StereoInvestigator software version 11 (MBF
Bioscience, Williston, VT) by a single observer. Subsampling techniques were performed for each probe to
determine appropriate sampling parameters and to consistently provide coefficient of errors below 0.10 (53).
Densities for Iba1-immunoreactive (ir) activated microglia (MGv), activated microglia displaying ramified,
intermediate, and amoeboid morphologies, and microglia with PHF1/Iba1-ir were obtained using the optical
fractionator probe at 40x (N.A. 0.75) under Köhler illumination. Grid size was 250 µm x 250 µm with a
disector height of 8.00 µm and a guard zone of 2%. Beginning at a random starting point, three equidistant
sections (every tenth or 20th section) per area of interest and individual were selected for analysis. Mounted
section thickness was measured every fifth sampling site. Every Iba1-ir microglial cell received at least two
markers when encountered within the optical disector frame: one to quantify total activated MGv and a
second to denote morphology. Occasionally morphology could not be distinguished, and in these instances,
a morphology marker was not placed; undetermined morphology accounted for approximately 4% of
activated microglia. A third marker was placed when microglia were immunoreactive for both PHF1 and
Iba1. Microglia densities (mm3) for each region were calculated as the population estimate divided by
48
planimetric volume of the disector (54). For each individual, densities for PFC and MTG were averaged to
calculate neocortical (NC) density. The same process was executed for CA1 and CA3 to compute
average hippocampal (HC) density. Densities for all four regions were averaged for total activated,
ramified, intermediate, amoeboid, and PHF1/Iba1-ir microglia densities. The ratio of each morphology
type to total activated microglia density was calculated for NC and HC, by dividing the region’s ramified,
intermediate, and amoeboid density by the region’s activated microglia density (e.g., NC ramified
density/NC activated microglia density). To correct for tissue shrinkage in the z axis, the height of the
disector was multiplied by the ratio of section thickness to the actual weighted mean thickness after
mounting and dehydration. No correction was necessary for the x and y dimensions because shrinkage in
section surface area is minimal (55). The mean number of sampling sites for each area per individual was
48 ± 10.37 and mean number of markers for each area per individual was 246 ± 81.60.
Statistical Analyses
All densities were checked for linearity and transformed using the formula: arcsin (sqrt (volume or
density/1,000)). Previously, APP/Aβ-ir and Aβ42-ir plaque and vessel volume as well as AT8-ir pretangle,
NFT, and tau neuritic plaque densities were collected and calculated for each individual (40). As described
in the Chapter I, principal component analysis (PCA) was performed to reduce the number of Aβ and tau
pathological variables to the most relevant factors for a composite brain age value in chimpanzees.
Regression factors (PCA-generated brain age) from that analysis were employed for analyses in this study.
Five variables (i.e., NC and HC tau NP densities, HC NFT density, and total APP/Aβ-ir plaque and vessel
volumes) explained 57.13% of the variance. All variables had primary loadings between 0.67 and 0.87.
Regression analyses were utilized to determine relationships between NC, HC, and total activated microglia
density and morphological densities and ratios with chronological age, PCA-generated brain age, sex,
APP/Aβ-ir and Aβ42-ir plaque and vessel volumes (%), and pretangle, NFT, and tau neuritic plaque
densities (mm3). Two-way ANOVAs were conducted to evaluate sex differences in activated microglia and
morphology densities and variances among brain regions. Bonferroni post hoc tests were used to evaluate
significant findings. Statistical analyses were conducted using IBM SPSS Statistics, Version 22 (Armonk,
NY), and level of significance (α) was set at 0.05.
49
RESULTS
Activated and Morphological Microglia Densities
Activated microglia and representation of all three morphologies were present throughout the
neocortex and hippocampus (Figure 18A-D). Dystrophic microglia were observed mainly in layers I and II
of the neocortex (Figure 18E). Ramified microglia displayed staining in the cell soma and numerous fine
fibers, and cell bodies had a spherical, triangular, or elongated shape (Figure 18F-H). Intermediate and
amoeboid morphology often exhibited an increased intensity of staining and were observed in close
proximity to blood vessels and tau pathology (Figure 18I-L). Microglia were sometimes tau-positive (PHF1),
and territories of intermediate and amoeboid-shaped microglia were often overlapping compared to the
typical pattern of extracellular space seen between ramified microglia (Figure 18M-P).
Activated MGv was collected in all 20 chimpanzees, and the average density across all four regions
was 5,208.98/mm3 (Appendix J). Factorial ANOVA revealed a significant main effect of region (F 3,72 =
4.23, p < 0.01) but not sex (F1,72 = 0.18, p = 0.68) with no interaction (F3,72 = 0.29, p = 0.84) (Figure 19). A
Bonferroni post hoc test did not detect differences between the neocortex (5,187.29/mm3) and
hippocampus (5,230.67/mm3) or within the neocortex between PFC (5,702.25/mm 3) and MTG
(4,672.34/mm3) (p’s > 0.09). However, activated MGv was significantly greater in CA3 (6,383.81/mm 3)
than CA1 (4,077.53/mm3) in the hippocampus (p = 0.01) (Figure 20).
Microglia morphology densities were summed in 18 subjects, as morphology could not be consistently
identified in all regions for two individuals (Appendices K-M). Each morphology type was observed in
every region. Of total activated microglia, ramified morphology accounted for 9%, intermediate for 79%,
and amoeboid for 8%. Morphological composition was similar in the neocortex (ramified = 11%,
intermediate = 78%, and amoeboid = 9%) and hippocampus (ramified = 8%, intermediate = 75%, and
amoeboid = 6%) (Figure 21; Appendix O). Average ramified microglia density across brain areas was
428.31/mm3. Ramified MGv was comparable between neocortex (449.50/mm3) and hippocampus
(445.27/mm3), and analyses confirmed nonsignificant effects for region (F3,48 = 1.90, p = 0.14), sex (F1,48
= 0.92, p = 0.34), and interaction between region and sex (F 3,48 = 0.47, p = 0.71) (Figure 22A,D). Ramified
MGv was 551.45/mm3 in PFC, 367.99/mm3 in MTG,
50
Figure 18. Photomicrographs of Iba1-ir (A-D, F-H, O), PHF1/Iba1-ir (E,M,P), and AT8/Iba1-ir (I-L) staining. (A,B)
microglia in neocortex, (C,D) microglia in hippocampus, (E) dystrophic microglia in neocortex, (F,G,H) ramified
microglia with spherical (F), triangular (G), and elongated (H) cell somas in neocortex, (I,J) AT8-ir pretangles
surrounded by intermediate microglia in the neocortex (I, white arrows) and amoeboid microglia in the
hippocampus (J, red arrows), (K) AT8-ir NFT adjacent to amoeboid microglia in neocortex, (L) tau neuritic plaque
next to intermediate microglia, (M,N) PHF1-ir microglia (black arrows), and (O,P) overlapping territories of
intermediate microglia. Scale bar = 280 µm.
51
Figure 19. Iba1-ir activated microglia (mm3) by region (A) and sex (B). Whiskers represent 1 SD.
so
sp
sr
so
sp
sr
Figure 20. Photomicrographs of Iba1-ir activated microglia in the hippocampus. (A-C) hippocampal subfield CA1 has
significantly decreased microglial activation than subfield CA3 (D-F). Stratum orien (so), stratum pyramidale (sp),
stratum radiatum (sr). Scale bar = 280 µm.
52
653.10/mm3 in CA3, and 237.45/mm3 in CA1. Average intermediate microglia density was 4,195.42/mm 3
among all regions. In the neocortex, intermediate MGv was 4,109.8/mm3 and 4,688.54/mm 3 in the
hippocampus. PFC intermediate MGv (4,274.07/mm 3) was greater than MTG (3775.48/mm 3), and CA3
density (5,691.08/mm3) was higher than CA1 (3,685.99/mm3). However similar to the pattern observed in
ramified densities, ANOVA yielded nonsignificant effects for region (F 3,49 = 2.47, p = 0.07), sex (F1,49 =
0.60, p = 0.44), and interaction (F3,49 = 0.65, p = 0.59) (Figure 22B,E). For all four regions, average
amoeboid microglia density was 423.42/mm 3. Amoeboid MGv was consistent in the NC (460.25/mm 3) and
HC (365.39/mm3). Amoeboid density was 526.61/mm 3 in PFC, 376.84/mm 3 in MTG, and within the
hippocampus, CA3 amoeboid MGv was 495.16/mm3 and CA1 was 235.62/mm 3. Again, analyses for
amoeboid MGv determined nonsignificant effects for region (F 3,49 = 1.02, p = 0.39), sex (F1,49 = 0.00, p =
1.00), and interaction between region and sex (F3,49 = 0.66, p = 0.58) (Figure 22C,F).
Figure 21. Proportion of Iba1-ir activated microglia (mm3) by morphology and region.
53
Figure 22. Iba1-ir microglia (mm3) by morphology, region, and sex. (A,D) ramified density by (A) region and (D)
sex, (B,E) intermediate density by (B) region and (E) sex, and (C,F) amoeboid density by (C) region and (F) sex.
Whiskers represent 1 SD.
PHF1/Iba1-ir Microglia Density
Microglia that showed colocalization of PHF1-ir and Iba1-ir exhibited tau deposition most frequently in
the cell soma with occasional immunoreactivity in the processes, and PHF-ir was observed mainly in
intermediate and amoeboid morphologies (Figure 17D and Figure 18E,M-N,P). PHF1/Iba1-ir microglia were
identified in all subjects with an average PHF1/Iba1-ir MGv density across all brain areas of 959.77/mm3
(Appendix N). The ANOVA revealed a significant main effect of region (F 3,46 = 4.53, p < 0.01) and
nonsignificant effect of sex (F1,46 = 2.83, p = 0.10) with no interaction (F3,46 = 0.00, p = 1.00) (Figure 23).
Post hoc analyses detected higher PHF1/Iba1-ir MGv in PFC (1,728.21/mm 3) than CA1 (316.74/mm 3) and
CA3 (482.61/mm3) (p’s ≤ 0.04). PHF1/Iba1-ir MGv in MTG (1,135.89/mm 3) did not differ significantly from
other regions (p’s > 0.25), nor did CA1 vary from CA3 density (p = 1.00). Regression analyses confirmed
that increases in PHF1/Iba1-ir density was associated with an increase in intermediate microglia
morphology in the neocortex (p’s < 0.01) and amoeboid microglia morphology in the neocortex and
hippocampus (p’s < 0.01) (Figure 24).
54
Figure 23. PHF1/Iba1-ir microglia density (mm3) by (A) region and (B) sex. Whiskers represent 1 SD.
Figure 24. Significant correlations of PHF1/Iba1-ir microglia density and morphological densities (mm3)
(p’s ≤ 0.05). (A) NC PHF1/Iba1-ir microglia density vs NC intermediate microglia density (R2 = 0.32), (B) NC
PHF1/Iba1-ir microglia density vs NC amoeboid density (R2 = 0.32), and (C) NC PHF1/Iba1-ir microglia density vs
HC amoeboid microglia density (R2 = 0.18).
Correlations with Chronological Age, Brain Age, and AD Pathology
Linear regression showed that activated microglial density had no relationship with chronological age
(p’s > 0.45) (Table 4). Densities of each microglia morphology, ratios of morphologic microglia
densities/activated microglia densities, and PHF1/Iba1-ir microglia density also were not associated with
chronological age (p’s ≥ 0.25) (Table 4). PCA-generated brain age, an assessment for overall Aβ and tau
pathology in individuals, was not linked with activated microglia density, morphological microglia densities
and ratios, or PHF1/Iba1-ir density (p’s > 0.08) (Table 4).
Regression analyses determined APP/Aβ-ir plaque volume was not correlated with activated,
morphologic, or PHF1/Iba1-ir microglia densities (p’s ≥ 0.17, data not shown). Conversely, higher levels of
Aβ42-ir plaque volume was associated with increased microglial activation and intermediate morphology
in the hippocampus (Figure 25) (p’s ≤ 0.04). Hippocampal APP/Aβ-ir vessel volume was associated with
55
increased hippocampal intermediate and amoeboid densities (p ≤ 0.04) (Figure 26). Activated microglia
density in the hippocampus was linked to increased Aβ42-ir vessel volume (p = 0.05) (Figure 27A).
Neocortical Aβ42-ir vessel volume was positively correlated with hippocampal intermediate density (p’s ≤
0.03) (Figure 27B). In addition, neocortical and hippocampal Aβ42-ir vessel volume was related to greater
HC amoeboid density (p’s ≤ 0.02) (Figure 27C-D). Neocortical pretangle density was positively correlated
with higher neocortical activated microglia density (p’s ≤ 0.03) but was not linked with morphological or
PHF1/Iba1-ir MGv (p’s ≥ 0.17) (Figure 28). A significant relationship was not found between any MGv and
NFT density (p’s ≥ 0.11) or tau neuritic plaque density (p’s ≥ 0.09).
Table 4. Correlation coefficients for activated, morphological, and PHF1/Iba1-ir microglia densities versus
chronological age and PCA-generated brain age
Chronological Age
Adj R
2
PCA-generated Brain Age
t
p
Adj R2
t
p
NC Activated MGv
-0.04
0.50
0.62
-0.06
0.03
0.97
HC Activated MGv
-0.03
0.73
0.47
-0.05
0.17
0.87
Total Activated MGv
-0.02
0.75
0.46
-0.06
0.12
0.91
NC Ramified MGv
-0.05
-0.23
0.82
-0.02
-0.77
0.45
HC Ramified MGv
-0.05
0.17
0.87
-0.04
0.56
0.58
Total Ramified MGv
-0.03
-0.68
0.51
-0.03
-0.61
0.55
NC Intermediate MGv
-0.04
-0.44
0.67
-0.04
0.47
0.64
HC Intermediate MGv
-0.01
0.90
0.38
-0.01
0.89
0.38
Total Intermediate MGv
-0.05
-0.30
0.77
-0.05
0.31
0.76
NC Amoeboid MGv
-0.04
-0.44
0.67
-0.04
0.44
0.67
HC Amoeboid MGv
0.03
1.29
0.21
0.11
1.83
0.08
Total Amoeboid MGv
-0.06
0.09
0.93
0.00
0.97
0.35
NC PHF1/Iba1 MGv
-0.05
-0.43
0.67
-0.03
0.63
0.54
HC PHF1/Iba1 MGv
-0.03
-0.71
0.49
-0.05
-0.32
0.76
Total PHF1/Iba1 MGv
-0.03
-0.67
0.51
-0.05
0.26
0.80
56
Figure 25. Significant correlations of Iba1-ir activated and intermediate microglia densities (mm3) with Aβ42-ir
plaque volume (%) (p’s ≤ 0.05). (A) HC activated microglia density vs NC Aβ42-ir plaque volume (R2 = 0.15), (B)
HC activated microglia density vs HC Aβ42-ir plaque volume (R2 = 0.16), and (C) HC intermediate microglia
density vs NC Aβ42-ir plaque volume (R2 = 0.22).
Figure 26. Significant correlations of Iba1-ir morphological microglia densities (mm3) with APP/Aβ-ir vessel
volume (%) (p’s ≤ 0.05). (A) HC intermediate microglia density vs HC APP/Aβ-ir vessel volume (R2 = 0.17) and (B)
HC amoeboid microglia density vs HC APP/Aβ-ir vessel volume (R2 = 0.35).
57
Figure 27. Significant correlations of Iba1-ir activated and morphological microglia densities (mm3) with Aβ42
vessel volume (%) (p ≤ 0.05). (A) HC activated microglia density vs total Aβ42-ir vessel volume (R2 = 0.16), (B) HC
intermediate microglia density vs NC Aβ42-ir vessel volume (R2 = 0.22), (C) HC amoeboid microglia density vs
NC Aβ42-ir vessel volume (R2 = 0.27), and (D) HC amoeboid microglia density vs HC Aβ42-ir vessel volume (R2 =
0.24).
Figure 28. Significant correlation of neocortical Iba1-ir activated microglia density (mm3) with neocortical AT8-ir
pretangle density (mm3) (R2 = 0.21, p ≤ 0.05).
58
DISCUSSION
Research examining neuroinflammation in nonhuman primates is scarce. Here, we present the first
known quantification of activated microglia and morphological densities in a great ape and an examination
of these densities in correlation with AD pathology in aged chimpanzees.
Regional differences in activated microglia were noted in the hippocampus of aged chimpanzees with
higher density in CA3 than CA1 (Figure 20). The control group in a human AD study exhibited comparable,
though nonsignificant, results with greater Iba1-ir microglia density in CA3 (~160/mm2) than CA1 (~115120/mm2) (56). However in the same study, the AD group showed an increase in activated microglia density
in CA1 but not CA3 compared to controls. In AD, the CA1 subfield of the hippocampus is typically the first
area affected by NFTs and also associated with the greatest neuron loss, while CA3 remains relatively
unaffected by tau lesions and neurons are preserved (45, 57-58). Similar to humans, aged chimpanzees
with AD-like pathology displayed higher pretangle, NFT, and tau neuritic plaque loads in CA1, though
volume occupied by Aβ-positive plaques and blood vessels was greater in CA3 (40). Additionally, Aβ plaque
and vessel volume were correlated with higher activated microglia densities in the hippocampus of these
chimpanzees, indicating increased microglial activation in CA3 compared to CA1 may be related to Aβ
deposition and not tau pathology. This hypothesis is further supported by the lack of association in NFT and
tau neuritic plaque densities with microglial activation in chimpanzees. In addition, a recent study of APPoverexpressing mice (hAPP-J20) demonstrated a correlation of greater total Aβ and microglial activation
with neuronal loss in CA1, suggesting activation of microglia is closely associated with Aβ expression and
neuron loss (59). Taken together, these results demonstrate some variances between humans and
chimpanzees with AD pathology. Both tau and Aβ pathology are associated with increased microglial
activation in AD patients, while only Aβ lesions appear related to greater microglial activation in the
hippocampus of chimpanzees. Also, CA3 in chimpanzees may be more susceptible to Aβ pathological
changes rather than CA1, which contrasts with AD in humans in which CA1 is the first and most severely
affected area. Future work will investigate whether increased microglial activation and Aβ deposition in CA3
of aged chimpanzees is correlated with neuron loss.
The most predominant phenotype of activated microglia was intermediate (79%), while remaining
microglia were categorized as ramified (9%) or amoeboid (8%). Normal adult human brains demonstrated a
59
relatively analogous pattern in the dorsal anterior cingulate cortex with 66% of Iba1-ir microglia displaying an
intermediate morphology, 16% a ramified appearance, and 18% amoeboid shape (60). Morphological
microglia densities were consistent across the neocortex and hippocampus in male and female
chimpanzees, with no differences between the sexes. While microglial morphology did not vary by sex in
chimpanzees or humans, a study in 60-day old rats found that females had significantly more Iba1-ir
microglia with thicker and longer processes (i.e., intermediate) than males in the CA1, CA3, dentate gyrus,
and amygdala (56, 61). In addition, young, middle-aged, and old female B6 mice had 25-40% more
microglia in the dentate gyrus and CA1 than age-matched male C57Bl/6J mice (62). Whether these regional
or sex variances are species-specific requires further investigation of microglia distributions in rodents,
primates, and humans.
Among elderly chimpanzees, age was not associated with changes in activated microglia density or
morphology. These data coincide with previous findings in older nonhuman primates and rodents. Activated
microglia density in the visual cortex, substantia nigra, and ventral tegmental area of rhesus macaques did
not show a significant increase with age (63-64). Similarly, changes in activated microglia density in the
substantia nigra of young and middle-aged rats were not detected (65). In contrast, humans display
increased microglial activation, particularly in white matter tracts, with age (65-69). Activated interleukin-1
alpha (IL-1α) microglia density is greater with age in humans (70). IL-1α is a protein produced by activated
macrophages and responsible for the production of inflammation. Additionally, age-related morphological
changes in IL-1α microglia density were identified; intermediate and amoeboid morphologies, but not
ramified, were more prevalent with age in humans independent of postmortem interval and sex (70). Cases
of non-age related morphological modifications have also been reported in humans. For example, the
number of amoeboid microglia was significantly raised in the human substantia nigra despite activated
microglia densities not differing by age (71). As this study’s aim was to identify AD pathology, we
collected data in the oldest available individuals, and therefore, it is likely that the present sample did not
include individuals young enough to detect age-related differences in microglia densities. Future
examination of activated microglia density and morphology in younger chimpanzees should be performed to
further address age-related microglial activation in apes.
60
Similar to findings in humans, nonhuman primates, and rodent models of AD, aged chimpanzees
exhibited greater levels of microglial activation and an increase in intermediate and amoeboid-shaped
microglia morphologies associated with Aβ42-ir plaque volume and APP/Aβ-ir and Aβ42-ir vessel volume.
Several studies demonstrate the presence of a robust immune response in AD, including production of
inflammatory cytokines, genomic associations, and microglial activation (72-78). Cultures of microglia
cells isolated from aged mice displayed elevated production of proinflammatory molecules IL-6 and TNF𝛼, and microglia from these animals had a decreased ability to internalize amyloid-beta (72). New
molecular studies highlight the expression of polymorphisms in immune-related genes, such as TREM2
(triggering receptor expressed on myeloid cells 2), CD33 (sialic acid binding Ig-like lectin 3), and HLA-DR
(human leukocyte antigen-D related) in association with Alzheimer’s disease (73-75). HLA-DR-ir microglia
density was significantly higher in the midtemporal gyrus of AD patients than in controls, and CD33-ir
microglia density was positively correlated with insoluble Aβ42 levels and plaque loads in AD brains (7576). Aβ oligomers also trigger astrocyte and microglial activation in mice and cynomolgus macaques (7778). Additionally, evidence indicates cerebrovascular Aβ deposition promotes neuroinflammation in AD
and cerebral amyloid angiopathy (CAA) disorders. In sporadic and familial CAA, leptomeningeal and
cortical vessels were associated with an increased activation of monocyte/macrophage lineage cells (79).
A transgenic mouse model (Tg-SwDI) of CAA showed abundant reactive astrocytes and activated
microglia strongly associated with cortical microvascular fibrillar Aβ deposits (80).
In addition to Aβ plaques and vasculature, tau pathology correlates with neuroinflammation and
microglial activation and has been implicated in driving tau hyperphosphorylation, aggregation, and
neurodegeneration in human models of tauopathies (81-84). Activated microglia are adjacent to taupositive neurons in the brains of patients with progressive supranuclear palsy and corticobasal
degeneration (82-83). Microglial activation also has been demonstrated to precede tau pathology in the
P301S mouse model of tauopathy, and chemically or genetically enhanced microglial activation
significantly accelerated tau pathology in the hTau mice (85-86). Recent work also showed transfer of
purified microglia derived from hTau mice induced tau hyperphosphorylation within the non-transgenic
mouse brain, and inclusion of interleukin 1 receptor antagonist significantly reduced microglia-induced tau
pathology. Such results suggest that reactive microglia may drive tau pathology (87).
61
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CHAPTER IV: COLOCALIZATION OF CALBINDIN AND TAU INCREASES
IN CHIMPANZEES WITH ALZHEIMER’S DISEASE PATHOLOGY
INTRODUCTION
Calbindin D28k (CB) is a calcium-binding protein that belongs to the EF-hand protein family, noted for a
helix-loop-helix structure (1). Present throughout the brain, CB acts as a calcium buffer and sensor by
regulating the balance of intracellular calcium (Ca2+) and amplitude of calcium signaling (2-6). In the
hippocampus, CB is a neuromodulator of long-term potentiation, synaptic plasticity, and memory function
(7).
Dysregulation of Ca2+ homeostasis has been implicated as a pathogenic driver in Alzheimer’s disease
(AD), which is characterized by amyloid-beta plaques (Aβ) and neurofibrillary tangles (NFTs) (8-9).
According to the calcium hypothesis of AD, activation of the amyloidogenic signaling pathway remodels the
neuronal calcium signaling pathway responsible for learning and memory (10). Interaction of Aβ peptides
with the neuronal membrane increases intracellular Ca2+ (11). Upregulation of Ca2+ depletes internal
stores in the endoplasmic reticulum and enhances external entry of Ca2+. Perpetual elevation of Ca2+
leads to excitotoxicity in neurons and correlates with progressive memory loss by enhancing long-term
depression within neuronal cells in AD (12). In addition, disturbance of Ca2+ levels in neurons is linked with
AD risk factors such as presenilin and amyloid precursor protein (APP) mutations, and can induce oxidative
stress, mitochondrial dysfunction, tau hyperphosphorylation, and excessive nitric oxide, rendering neurons
vulnerable to apoptosis (13-15).
Evidence of calbindin’s role in AD pathogenesis was found in a novel transgenic mouse model of AD and
CB knockout (5xfAD/CBKOTg) (16). Depletion of CB in this model resulted in significant neuronal loss in the
subiculum compared to 5xfAD transgenic mice despite similar Aβ plaque loads. These experiments also
demonstrated that depletion of CB led to modifications of cellular death pathways, synaptic transmission,
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mitogen-activated protein kinase signaling, and cytoskeleton organization. Additionally, lower levels of CB in
the dentate gyrus of familial AD-mutant hAPP mice correlated with learning deficits (17).
In AD, calcium-binding proteins, such as CB, directly modulate Aβ generation and NFT formation. At the
same time, Aβ can trigger changes in intracellular Ca2+ homeostasis and reduce CB levels (17-18). The
ability of CB to block several pro-apoptotic pathways mediated by Aβ may be responsible for the
preservation of CB-positive neurons in humans with AD until late stages (17, 19-21). In the basal forebrain
of AD patients, loss of cholinergic neurons occurs primarily in cells that lack CB, and nearly all remaining
cholinergic neurons are CB-positive (18, 22). Moreover, most CB-deficient cholinergic neurons in the same
region contained NFTs and pretangles, while only a small percentage of CB-positive neurons in normal
elderly and AD brains showed tauopathy, suggesting the presence of CB may protect cholinergic neurons in
the basal forebrain from tangle formation (23). In the hippocampus of AD patients, CB-ir neurons lacked
tangles and were observed next to degenerating tau-positive pyramidal cells and in areas with low Aβ
plaque loads (24). However in AD cases with severe plaque and NFT distribution, CB-ir pyramidal cells
were lost in the hippocampus, presumably as a result of a persistent disruption in calcium homeostasis (24).
Recent work in aged chimpanzees demonstrated the co-occurrence of Aβ and tau pathology, suggesting
AD pathology may not be limited to humans (25). Using the same group of chimpanzees, we evaluated CBimmunoreactive (ir) neuron density and colocalization of calbindin and tau in neurons in the neocortex and
hippocampus to explore the relationship of calcium as a potential pathogenic mechanism of AD pathology in
chimpanzees.
MATERIALS AND METHODS
Specimens
Postmortem brain samples from 20 aged chimpanzees (Appendix A) were acquired from American Zoo
and Aquarium-accredited zoos or research institutions and maintained in accordance with each institution’s
animal care and use guidelines. Apes in this study did not participate in formal behavioral or cognitive
testing. Sex and age was balanced as equally as possible. Samples from three regions, prefrontal cortex
(PFC), midtemporal gyrus (MTG), and hippocampal subregion CA1, were taken from eight male (ages 39-
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62) and 12 female (ages 37-58) chimpanzees.
Sample Processing
Samples were taken from right and left hemispheres based on availability. Data examining interhemispheric distribution of AD and vascular pathology found NFT and Aβ deposition were symmetrical even
in early stages of neurodegeneration, and variability in the Clinical Dementia Rating scale was nearly
identical in the two hemispheres, indicating assessment of vascular and AD pathology in one hemisphere is
sufficient (26). Brains were collected postmortem (postmortem interval < 20 h) and immersion fixed in 10%
buffered formalin solution for at least 10-14 days. Specimens were transferred to a 0.1 M buffered saline
solution with 0.1% sodium azide, cryoprotected in a graded series of 10, 20, and 30% sucrose solutions,
and stored at 4°C. Brains were frozen in dry ice and cut into 40 µm-thick sections in the coronal plane using
a Leica SM2000R freezing sliding microtome (Buffalo Grove, IL). Sections were placed into individual
centrifuge tubes containing freezer storage solution (30% dH2O, 30% ethylene glycol, 30% glycerol, 10%
0.244 M phosphate buffered saline), numbered sequentially, and stored at -20°C until immunohistochemical
processing. Every tenth section was stained for Nissl substance with a 0.5% cresyl violet solution to reveal
cell somata. Nissl-stained sections were used to define cytoarchitectural boundaries for regions of interests.
Identification of Sampling Regions
All regions in the study were readily identified using Nissl-stained sections. Brain areas were selected
based on Braak staging of NFTs and Thal phases of Aβ deposition in humans with AD as well as prior
studies in aged chimpanzees (27-32). Sampling regions included layer III (external pyramidal layer) in
Brodmann’s areas 9 and 10 of the dorsolateral PFC, layer III in Brodmann’s area 21 of the MTG, and
stratum pyramidale layer in CA1 subfield of the hippocampus. Pyramidal neurons in layers III and V of the
neocortex and stratum pyramidale layer in the hippocampus suffer the greatest neuron and synapse loss in
AD, and distribution of neuritic Aβ plaques and NFTs is most prevalent in these layers (33-35). In layers IIVI of the neocortex, primarily CB-ir interneurons and only occasional CB-ir pyramidal neurons were present
(4, 36). In CA1 of the hippocampus, both CB-ir pyramidal cells and interneurons were found in the stratum
pyramidale layer (4, 37).
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Immunohistochemistry
Every twentieth section from each subject and sampling area was immunohistochemically processed for
rabbit anti-calbindin D-28k (1:20,000 dilution, Swant, CB-38a) following established protocols utilizing the
avidin-biotin-peroxidase method (38-39). Further sections were double immunostained for calbindin and
AT8 (1:2,500 dilution, Thermofisher, MN1020) and calbindin and APP/Aβ (1:7,500, Covance, SIG-39320)
(Appendix B) to determine colocalization. Free-floating sections were pretreated for antigen retrieval by
incubation in 0.05% citraconic acid (pH 7.4) at 86°C for 30 min. Endogenous peroxidase was quenched
(75% CH3OH, 2.5% H2O2 [30%], 22.5% dH2O) for 20 min at room temperature (RT), and sections were
preblocked for 1 h in a solution of 0.1 M phosphate-buffered saline (PBS, pH 7.4), 0.6% Triton X, 4% normal
serum, and 5% bovine serum albumin at RT. Sections then were placed in primary antibody diluted in PBS
for 48 h at 4°C. Next, sections were incubated in a biotinylated secondary antibody (1:200 dilution) in a
solution of PBS and 2% normal serum (1 h, RT), followed by an avidin-peroxidase complex (1 h, RT,
PK6100, Vector Laboratories, Burlingame, CA) and either 3,3’-diaminobenzidine with nickel enhancement
(DAB) or Vector NovaRED (SK-4100/SK-4800, Vector Laboratories).
Data Acquisition
Quantitative analyses were performed using computer-assisted stereology with an Olympus BX-51
photomicroscope equipped with a digital camera and StereoInvestigator software version 11 (MBF
Bioscience, Williston, VT) by a single observer. Subsampling techniques were performed for each probe to
determine appropriate sampling parameters and to consistently provide a coefficient of error below 0.10
(40). CB-ir and AT8/CB-ir neuron densities (Nv) were collected using the optical fractionator probe at 40x
(N.A. 0.75) under Köhler illumination. CB-ir neuron densities included primarily interneurons in PFC and
MTG and both pyramidal neurons and interneurons in CA1. Grid size was 250 µm x 250 µm with a disector
height of 8.00 µm and a guard zone of 2%. Beginning at a random starting point, three equidistant sections
(every tenth or 20th section) per area of interest and individual were selected for analysis. Mounted section
thickness was measured every fifth sampling site. A marker was placed for CB-ir neurons when
encountered within the optical disector frame. A second marker was placed if neurons were immunopositive
for AT8 and CB. Densities (mm3) for each region were calculated as the sum of each marker divided by
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planimetric volume of the disector (41). To correct for tissue shrinkage in the z axis, the height of the
disector was multiplied by the ratio of section thickness to the actual weighted mean thickness after
mounting and dehydration. No correction was necessary for the x and y dimensions because shrinkage in
section surface area is minimal (42). The mean number of sampling sites for each area per individual was
93 ± 30.99 and mean number of markers for each area per individual was 251 ± 104.5.
Statistical Analyses
Densities were checked for linearity and transformed using the formula: arcsin (sqrt (volume or
density/1,000)). Previously, APP/Aβ-ir and Aβ42-ir plaque and vessel volume as well as AT8-ir pretangle,
NFT, and tau neuritic plaque (NP) densities were collected and calculated for each individual (25).
Principal component analysis (PCA) (see Chapter II) was performed to reduce the number of Aβ and tau
pathological variables to the most relevant factors for a composite brain age value in chimpanzees.
Regression factors (PCA-generated brain age) from PCA were employed for analyses in this study. Five
variables (i.e., NC and HC tau NP densities, HC NFT density, and total APP/Aβ-ir plaque and vessel
volumes) explained 57.13% of the variance. All variables had primary loadings between 0.67 and 0.87.
Regression analyses were utilized to determine relationships of regional CB-ir and AT8/CB-ir Nv densities
(mm3) with chronological age, PCA-generated brain age, sex, APP/Aβ-ir and Aβ42-ir plaque and vessel
volumes (%), and pretangle, NFT, and tau NP densities (mm3). Two-way ANOVAs with Bonferroni post hoc
were conducted to examine region and sex differences in the neocortex, and Mann-Whitney U tests were
used to test for sex differences in CA1. Statistical analyses were conducted using IBM SPSS Statistics,
Version 22 (Armonk, NY), and level of significance (α) was set at 0.05.
RESULTS
Staining was consistent with previous descriptions of CB-ir distribution in the neocortex and
hippocampus (4, 36-37). CB-ir interneurons were present in layers II-V/VI, and occasional CB-ir pyramidal
neurons with incomplete labeling of axonal arborization and decreased staining intensity were found in
layers III and V of the neocortex (Figure 29A-C). In the hippocampus, CB-ir pyramidal neurons and
interneurons were present in the stratum pyramidale layer of CA1 and CA2 but not CA3 (Figure 29D-F). A
73
population of immunoreactive neurons also was observed in the inner molecular layer of the dentate
gyrus. AT8/CB-ir interneurons and sparse pyramidal neurons were present in layers II and III of the
neocortex and pyramidal layer of CA1 (Figure 30A-C). Occasional CB-ir microglia or astrocytes were
identified, and in one individual, a cluster of CB-positive microglia was found in the neocortex (Figure
29D).
Figure 29. Photomicrographs of CB-ir interneurons (white arrows) and pyramidal neurons (black arrow). (A-C)
neocortex and (D-F) CA1 subfield of hippocampus. Stratum orien (so), stratum pyramidale (sp), and stratum
radiatum (sr). Scale bar = 200 μm.
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Figure 30. Photomicrographs of AT8/CB-ir and CB-ir neurons and glia. (A-C) AT8/CB-ir neurons (black arrows)
and CB-ir neurons (white arrows) in CA1, (D) CB-ir microglia in neocortex, (E) AT8-ir tau neuritic plaque (red
arrow) and CB-ir interneurons in neocortex, (F) AT8-ir neuritic plaque (red arrow), AT8-ir pretangle (blue
arrow), and CB-ir interneurons in neocortex. Scale bar = 280 μm.
Figure 31. CB-ir neuron density (Nv) (mm3) by region (A) and sex (B). PFC and MTG include CB-ir interneuron
density and CA1 includes CB-ir pyramidal and interneuron density. Whisker bars represent 1 SD.
75
CB-ir and AT8/CB-ir Neuron Densities by Region and Sex
Average CB-ir neuron density was 2,848.35/mm3 in PFC and 2,135.85/mm 3 in MTG (Appendix P).
Factorial ANOVA analyzing the neocortical areas yielded nonsignificant main effects of region (F 1,36 =
3.60, p = 0.07) and sex (F1,36 = 0.00, p = 0.95), and no interaction between region and sex (F 1,36 = 1.27, p
= 0.72) (Figure 31). In CA1 of the hippocampus, average CB-ir neuron density was 1,515.80/mm 3, and a
Mann Whitney U test determined there were no differences between males and females (p = 0.91).
All 20 chimpanzees presented with AT8/CB-ir neurons in each region (Figure 30A-C for
photomicrographs and Figure 32 for densities per region). Average AT8/CB-ir neuron density was
168.91/mm3 in PFC and 301.44/mm 3 in MTG (Appendix Q). Repeated-measures ANOVA for neocortical
areas yielded a significant main effect of sex (F1,36 = 5.50, p = 0.03) with females (283.92/mm3) having a
significantly higher mean density than males (113.82/mm 3). The main effect of region (F1,36 = 2.27, p =
0.14) was nonsignificant and there was no interaction between region and sex (F 1,36 = 0.01, p = 0.92)
(Figure 32). Average hippocampal AT8/CB-ir neuron density was 32.59/mm 3, and differences between
the sexes were not found (p = 0.47).
Correlations with Chronological Age and PCA-Generated Brain Age
Linear regression demonstrated that AT8/CB-ir neuron density in CA1 significantly increased with
chronological age (R2 = 0.21, t = 2.43, p = 0.03) (Figure 33A) and PCA-generated brain age (R2 = 0.49, t
= 4.28, p < 0.01) (Figure 33B). Neocortical AT8/CB-ir neuron density did not correspond to chronological
age or PCA-generated brain age (p’s ≥ 0.16) (Table 5). No relationship was found between CB-ir neuron
densities in the neocortex or hippocampus and chronological age or PCA-generated brain age (p’s ≥
0.15).
Associations of CB-ir and AT8/CB-ir Neuron Densities with AD Pathology
Region-specific changes in CB-ir and AT8/CB-ir neuron densities were associated with Aβ plaque and
vessel volumes as well as tau-related pathologies. CB-ir neuron density in PFC was positively correlated
with neocortical Aβ42-ir plaque volume (p = 0.03) (Figure 34C), while increased CB-ir neuron density in
MTG was significantly associated with neocortical pretangle density (p < 0.01) (Figure 35A). Neocortical
76
pretangle density also was correlated with greater AT8/CB-ir neuron density in PFC and MTG (p’s <0.01)
(Figure 35B-C). AT8/CB-ir neuron density in CA1 was positively associated with hippocampal APP/Aβ-ir
and Aβ42-ir plaque volumes (p’s ≤ 0.04) (Figure 34A-B) as well as neocortical and hippocampal APP/Aβir and Aβ42-ir vessel volumes (p’s ≤ 0.03) (Figure 34D-G). In addition, AT8/CB-ir neuron density in CA1
was positively correlated with hippocampal NFT and neocortical tau neuritic plaque densities (p’s ≤ 0.04)
(Figure 35D-E).
Figure 32. AT8/CB-ir neuron density (Nv) (mm3) by (A) region and (B) sex. PFC and MTG include AT8/CB-ir
interneuron density and CA1 includes AT8/CB-ir pyramidal and interneuron density. Asterisk indicates significant
difference between females and males in neocortical regions (PFC and MTG). Whisker bars represent 1 SD.
Table 5. Correlation coefficients for total and regional CB-ir Nv and AT8/CB-ir Nv with chronological age and
PCA-generated brain age. PFC and MTG include CB-ir interneuron density and CA1 includes CB-ir pyramidal and
interneuron density. Asterisks indicate significant correlations.
Chronological Age
2
PCA-generated Brain Age
Adj R
t
p
Adj R2
t
p
PFC CB-ir Nv
0.00
0.98
0.34
-0.06
-0.01
0.99
MTG CB-ir Nv
0.06
1.49
0.15
0.03
1.28
0.22
CA1 CB-ir Nv
-0.01
-0.86
0.40
0.00
-0.99
0.34
PFC AT8/CB-ir Nv
0.06
1.48
0.16
-0.06
0.01
0.99
MTG AT8/CB-ir Nv
0.06
1.43
0.17
-0.05
0.48
0.64
CA1 AT8/CB-ir Nv
0.21
2.43
0.03*
0.49
4.28
0.00*
77
Figure 33. Significant correlations of AT8/CB-ir Nv (mm3) with chronological age and brain age (p ≤ 0.05). (A)
AT8/CB-ir Nv in CA1 with chronological age (R2 = 0.21) and (B) AT8/CB-ir Nv in CA1 with PCA-generated brain
age (R2 = 0.49). CA1 includes AT8/CB-ir pyramidal and interneuron density.
Figure 34. Significant correlations of CB-ir and AT8/CB-ir Nv (mm3) with Aβ pathology (%) (p ≤ 0.05). (A) CA1
AT8/CB-ir Nv with hippocampal (HC) APP/Aβ-ir plaque volume (R2 = 0.21), (B) CA1 AT8/CB-ir Nv with HC
Aβ42-ir plaque volume (R2 = 0.82), (C) PFC CB Nv with NC Aβ42-ir plaque volume (R2 = 0.22), (D) CA1
AT8/CB-ir Nv with NC APP/Aβ-ir vessel volume (R2 = 0.36), (E) CA1 AT8/CB-ir Nv with HC APP/Aβ-ir vessel
volume (R2 = 0.21), (F) CA1 AT8/CB-ir Nv with NC Aβ42-ir vessel volume (R2 = 0.20), and (G) CA1 AT8/CB-ir
Nv with NC Aβ42-ir vessel volume (R2 = 0.28). PFC includes CB-ir interneuron density and CA1 includes
AT8/CB-ir pyramidal and interneuron density.
78
Figure 35. Significant correlations of CB-ir and AT8/CB-ir Nv (mm3) with AT8-ir tau densities (mm3) (p ≤ 0.05).
(A) MTG CB-ir Nv with NC pretangle density (R2 = 0.40), (B) MTG AT8/CB-ir Nv with NC pretangle density (R2
= 0.89), (C) PFC AT8/CB-ir Nv with NC pretangle density (R2 = 0.68), (D) CA1 AT8/CB-ir Nv with HC NFT
density (R2 = 0.86), (E) CA1 AT8/CB-ir Nv with NC tau neuritic plaque density (R2 = 0.24). PFC and MTG include
CB-ir interneuron density or AT8/CB-ir interneuron density, and CA1 includes AT8/CB-ir pyramidal and
interneuron density.
DISCUSSION
Previous research demonstrated a selective vulnerability of CB-ir neurons to AD pathology in humans
and rodent models (43-46). The present analysis is the first to determine CB-ir neuron density and
colocalization of calbindin and tau in the neocortex and hippocampus of aged chimpanzees, including those
that express Aβ plaques and neurofibrillary tangles, the hallmarks of AD.
CB-ir neuron density in the neocortex and hippocampus showed no association with age in elderly
chimpanzees. This result varies from humans, in which age-related changes in CB-ir neuron densities
appear to be region-specific. A study examining 17 cortical areas found a loss of CB-positive neurons in four
regions, including the superior and midtemporal gyrus, parahippocampal gyrus, and primary visual cortex
(47). Conversely, mRNA levels of CB in the hippocampus remained stable during normal aging in humans
(43). While CB was not associated with age-related changes in this sample of chimpanzees, in which the
youngest ape was 37 years old, this subset of individuals was likely not young enough to capture whether a
79
true age-related difference exists. Additional analyses of CB-ir neuron density in younger individuals should
be performed to further examine the relationship of age and calbindin in apes.
CB-ir neuron densities did increase in association with AD pathology in the chimpanzee neocortex, in
which calbindin is expressed predominantly in a subpopulation of GABAergic inhibitory interneurons (4, 36).
Neocortical Aβ plaque volume was associated with greater CB-ir neuron density in the prefrontal cortex,
while neocortical pretangle density was correlated with higher CB-ir neuron density in the midtemporal
gyrus. In humans with AD, Aβ plaques initially form in the neocortex before moving into the allocortex,
hippocampus, and subcortical regions (31). Conversely, pretangles and NFTs develop in the entorhinal
cortex and hippocampal formation before expanding into the inferior, middle, and superior temporal gyri, and
eventually, into the frontal cortex (30, 48). Therefore, changes in CB-ir neuron density in chimpanzees
appear to be specific to the type of pathology present and follow the typical regional staging patterns of AD
pathology.
These results demonstrate a deviation in calbindin expression between chimpanzees and humans with
AD pathology. In the neocortex of humans with AD, CB-ir interneurons remain mostly unaffected, or in some
cases, may decrease in numbers (43-45, 49). Canines also exhibit depletion of cortical CB-ir neurons in
association with amyloid deposition (50). Additionally, calbindin mRNA and protein concentrations were
decreased in hippocampal CA1 and CA2 subregions of patients with Alzheimer’s, Huntington’s, and
Parkinson’s diseases, although loss of CB expression was not associated with reduced total neuron density
(43-45). However, chimpanzees with AD pathology exhibit an increase in CB-ir interneuron density in the
neocortex and no change in CB-ir neuron density in the hippocampus. These findings indicate interneurons
in the chimpanzee neocortex may upregulate intracellular calbindin protein expression in response to Aβ
and tau deposition, which in turn may protect these cells by blocking pro-apoptotic pathways despite being
in close proximity to such pathologic lesions (Figure 30E-F) (19-21). While chimpanzees differ from humans,
a recent investigation in mice found tau-containing neurons from control animals had increased cytoplasmic
calmodulin, a protein that acts as a calcium sensor and regulates the Calb1 gene, compared to neurons
lacking tau from tau knockout mice and the increase in calmodulin was correlated with a higher expression
of calbindin (51).
80
Increased CB-ir neuron density was exclusive to the neocortex and only associated with AD pathology.
In contrast, neuron density in the CA1 that colocalized tau (AT8) and CB was correlated with chronological
age, PCA-generated brain age, and AD pathology in chimpanzees. Neocortical AT8/CB-ir neuron density
also increased with AD pathology (i.e., pretangles) but not age. Because CB-ir neuron density was not
associated with age, it appears that an age-related increase in intracellular phosphorylated tau levels may
occur in the hippocampus of aged chimpanzees.
Changes in AT8/CB-ir neuron density in the neocortex were related to AD pathology, as neocortical
pretangle density was associated with greater colocalization of neuronal tau and calbindin in the PFC and
MTG. However in the hippocampus, Aβ plaque and vessel volume, NFT density, and tau neuritic plaque
density were correlated with increased AT8/CB-ir neuron density in chimpanzees. Interestingly, pretangle
density was not linked with changes in hippocampal neuronal colocalization of tau and calbindin. Such
findings are noteworthy as calbindin immunoreactivity is found primarily in interneurons in the neocortex but
in both pyramidal neurons and interneurons in the hippocampus (4, 36-37). In addition, CB-positive
pyramidal neurons in the CA1 of aged chimpanzees were intensely double stained for hyperphosphorylated
tau (AT8-ir) and exhibited degeneration in dendritic and axonal processes (Figure 30A-C). These data
indicate CB-ir pyramidal neurons in the aged chimpanzee hippocampus may be particularly vulnerable to
degeneration due to both normal and pathologic aging (i.e., Aβ and tau lesions) compared to the
neocortex. Comparable results have been identified in humans with AD in which CB-ir pyramidal neurons
in the neocortex were more prone to excitotoxicity attributed to persistent Ca2+ elevation (52-55). Moreover,
NFTs have been observed in only pyramidal cells, not interneurons, in the neocortex of human AD cases,
and neocortical NFT loads are correlated with increased CB mRNA levels, indicating an interaction between
tau and CB in the neurons of AD patients (45, 56). Older rats also display an age-related decrease in CB-ir
neurons that are not immunoreactive for GABA in the perirhinal cortex, suggesting cellular death occurs in
CB-ir pyramidal cells (46).
Unexpectedly, female chimpanzees demonstrated higher levels of tau and calbindin colocalization
specific to the neocortex compared to males, yet sex differences were not found in CB-ir neuron density for
any regions of interest (25). This suggests the variance between males and females may be related to
hyperphosphorylated tau and increasing age. Indeed, sex-specific changes in tau have been exhibited in
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mice models of tauopathy and AD (57-58). A transgenic mouse model of tauopathy (rTG4510) reported
significantly higher levels of hyperphosphorylated tau in females compared to males despite no evidence
of differential tau transgene expression between the sexes (57). Another model in mice for AD (TAPP)
also demonstrated that older female mice had increased NFTs in limbic areas and pretangles and NFTs
in the cortex (58). Such variance between sexes in tau-related modifications may be due to gonadal
hormones, such as estradiol, which has been reported to prevent hyperphosphorylation of tau in rat
cortical neurons and human neuroblastoma cells (59). Estradiol levels are known to decrease during
perimenopause and menopause in women, who are at greater risk for AD (60-61). Unfortunately, data on
estrogen levels in great apes are scarce and inconsistent. One study using observations of anogenital
swellings and menstruation in addition to urinary progestin levels found captive female chimpanzees are
menopausal around 50 years of age (62). However, evidence based on estrous cycle and hormonal
changes in estradiol, luteinizing hormone, and follicle stimulating hormone indicated that female
chimpanzees may be peri-menopausal between 30-35 years and menopausal between 35-40 years (63).
As all female apes in the current study sample were 37 years or older, it is possible progressively
declining estrogen levels may account for increasing hyperphosphorylated tau in these individuals
compared to males.
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CHAPTER V: BABOONS AND CHIMPANZEES EXPRESS HIGHER LEVELS
OF FOUR-REPEAT TAU THAN THREE-REPEAT TAU ISOFORMS
INTRODUCTION
Humans have six tau isoforms ranging from 352 to 441 amino acids long in the brain (1-2). Formed
through alternative splicing of the second, third and tenth exons of the MAPT (microtubule-associated
protein tau) gene, tau variants differ by the presence of either three or four repeat-regions in the Cterminus and absence or presence of a 29- or 58-amino acid insert in the N-terminus (Figure 36) (1-3).
Exclusion of exon 10 results in tau isoforms with three microtubule-binding repeats (3R), while inclusion
yields isoforms containing four microtubule-binding repeats (4R) (3).
Healthy adult human brains have an approximate 1:1 ratio of 3R and 4R tau (4). However during
neurodegenerative processes, small increases in one isoform relative to the other may trigger microtubule
instability, resulting in defective axonal transport and development of neurofibrillary tangles (NFTs) (5).
Support for this hypothesis is found in neurodegenerative diseases, in which a disturbance in the
equimolar ratio with either increased amounts of 3R or 4R tau was observed. Frontotemporal dementia17, progressive supranuclear palsy (PSP), and corticobasal degeneration (CBD) are associated with an
overproduction of 4R tau, while excess 3R tau inclusions are more predominant in Pick’s disease, a taupositive form of frontotemporal dementia (6-10). In Alzheimer’s disease (AD), data is contradictory with
reports of an increase in 3R:4R tau, an increase in 4R:3R tau, and normal ratios (11-15). Such
inconsistencies in AD may be explained by technical limitations of the experimental approaches or the
evolution of tau pathology (16). For example, pretangle formations predominantly consist of 4R tau, while
classic NFTs consist of both 3R and 4R tau, and ghost tangles primarily include 3R tau (17). Therefore if
tau isoforms were quantified from a patient who may have been in the early phases of AD with high loads
of pretangles, a higher ratio of 4R:3R tau could be present, while a patient who suffered from late stage
AD with greater levels of NFTs would have an increased 3R:4R tau ratio.
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Initial work in great apes demonstrated a lack of tauopathy despite Aβ deposition in plaque form and in
blood vessels (18-23). In addition, analyses in chimpanzees and gorillas suggested these species may
express a higher proportion of transcripts lacking exon 10 (i.e., 3R tau isoforms) than humans, despite
chimpanzees sharing 100% sequence homology with human tau as well as the presence of all six tau
isoforms (24-25). Thus, we hypothesized that resistance to developing NFTs in apes may be due to a
naturally-occurring increased ratio of 3R:4R tau. If the healthy nonhuman primate brain had greater levels
of 3R-tau isoforms, perhaps great apes lacked the ability to initiate tangle formation which may require an
overproduction of 4R tau. In vitro work demonstrated that 3R tau inhibited assembly of 4R-tau filaments,
which are known to accelerate tau filament assembly and favor tau aggregation (26). However contrary to
our original hypothesis, we found tangle and tau neuritic plaque pathology in a group of aged
chimpanzees (27). In light of this new data, the aim changed to examine the concentration of 3R and 4R
tau in two species known to exhibit NFTs, chimpanzees and baboons (27-29).
The ratio of 3R:4R tau has been established in humans and rodents (4, 30-32). As adults, mice and
rats produce solely 4R tau and do not exhibit tau pathology (30-32). Conversely, chimpanzees and
baboons are two species in which tauopathy naturally exists, but the ratio of 3R:4R tau is unknown (2729). This investigation utilized sandwich ELISA to measure the amount of 3R- and 4R-tau isoforms in
normal adult chimpanzee and baboon brains. We expect that adult chimpanzees and baboons will have
an equimolar ratio of 3R:4R tau similar to humans and that concentration of 3R and 4R tau will not differ
among brain regions.
Figure 36. Tau isoforms in humans and chimpanzees formed by splicing at exons 2, 3, and 10. (aa) amino, (N) N
terminus, (C) C terminus, (R) repeat.
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MATERIALS AND METHODS
Specimens and Sample Processing
Postmortem frozen brain samples from five chimpanzees (Pan troglodytes) were acquired from
American Zoo and Aquarium-accredited zoos or research institutions and maintained in accordance with
each institution’s animal care and use guidelines. Frozen brain tissue from two olive baboons (Papio
anubis) was acquired from Southwest National Primate Research Center. Samples were taken from right
and left hemispheres based on availability, and sex and age were balanced as equally as possible.
Samples from three regions, frontal cortex, temporal cortex, and cerebellum, were taken from three male
(22.5 to 28.9 years) and two female (22.5 to 30.8 years) chimpanzees as well as one male baboon (13
years) and one female baboon (8 years) for ELISA analysis. The cerebellum was chosen as a control
area, since tauopathy is rarely observed in that area in humans with AD. Brains were collected
postmortem (postmortem interval < 20 h), flash frozen, and maintained at -20°C until processing for
sandwich ELISA.
Preparation of Brain Homogenates
Frozen tissue samples (~0.5 g) were weighed and then homogenized via sonication (Branson Digital
Sonifier, 10% amplitude for four 2 sec pulses) in a tris buffered saline (TBS) homogenization buffer of 25
mM TBS, 10 mM sodium floride, 1 mM sodium metavanadate, 2 mM ethylene glycol tetraacetic acid, and
complete Mini protease inhibitor cocktail (Roche, Lewes, UK). Homogenate volume was approximately
100 ul buffer per 1 mg of tissue. A 2% (v/v) 5 M sodium chloride solution was added to homogenate
samples. Samples were heated for 10 min at 100⁰C, mixed well, and cooled on ice for 30 min.
Homogenates then were centrifuged at 14,000 xg for 20 min at 4⁰C, and supernatant was decanted into
fresh Eppendorf tubes, aliquoted, and stored at -20°C until processing for ELISA analysis.
Preparation of Tau HRP Conjugate
The Lightning-Link (LL) HRP kit (Innova Biosciences, 701-0000) was used according to manufacturer’s
guidelines to create the HRP-linked tau conjugate. Briefly, 10 μL of LL-modifier reagent was added to 100
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µg of detection antibody Tau 12 (BioLegend, SIG-39416), a purified monoclonal antibody against human
tau (epitope 6-18 aa), and incubated for 3 h at room temperature (RT). Next, 10 μL of LL-quencher was
added to the antibody sample and incubated for 30 min at RT to develop the HRP-tau conjugate. To
protect the performance of the HRP conjugate, LifeXtend HRP conjugate stabilizer (Innova Biosciences,
901-0005) was utilized. A sodium phosphate solution (880 μL, NaH3PO4, pH 8.0) was added to the HRPtau conjugate, and then 900 μL of the conjugate stabilizer was added to this solution. HRP-tau with
conjugate stabilizer was aliquoted and stored at -80⁰C until use in ELISA analysis.
Total Protein Assay
Total protein content was assessed in tissue samples using the Pierce Bicininchronic Acid (BCA)
assay kit (ThermoScientific Fisher, 23227). The standard curve was created using serial dilution of bovine
serum albumin beginning at 10 μL and diluted with PBS 1x (1:2 dilution). Sample extracts for each region
per individual were diluted with PBS 1x (1:10) and run in duplicate. The working solution provided in the
kit was added per manufacturer instructions and samples were incubated for 25 min at RT. The plate was
read at 562 nm on a SpectraMax 340PC plate reader (Molecular Devices, Sunnyvale, CA) using SoftMax
Pro 5.2 analytical software.
Sandwich ELISA for 3R- and 4R-Tau Isoforms
Enzyme-linked immunosorbent assays (ELISA) were used to quantify 3R-tau (RD3, Millipore, 05-803)
and 4R-tau (RD4, Millipore, 05-804) isoforms (Appendix B). Microtitre plates were coated with 6 μg/mL of
capture antibody (RD3 or RD4) diluted in coating buffer (100 μL, phosphate buffered saline [PBS] 1x, pH
7.4, 0.1 M EDTA) and incubated at 4⁰C for 48 h. The plate was washed in 300 μL of washing buffer (PBS
1x, pH 7.4, 0.1% Tween-20) 6 times x 1 min while gently shaking, and then incubated for 2 h at RT with
200 μL of blocking buffer (ThermoFisher Scientific, 37578). After washing, 50 μL of homogenate samples
(RD3: neat dilution, RD4: 1:2 dilution, diluted with PBS 1x) was added to each well previously coated with
RD3 or RD4 antibodies. One hundred microliters of the tau standards tau381 (1N3R, 1:500 dilution) and
tau412 (1N4R, 1:250 dilution) (rPeptide, Bogart, GA) in diluent buffer (PBS 1x) was used to construct
standardized curves for 3R- and 4R-tau isoforms with working standard starting at 10 ng mL-3 and serially
92
diluted. Samples and standards were run in duplicate. Diluted HRP-linked tau conjugate (50 μL, 1:10
dilution) was added to each well, and plates then were incubated for 24 h at 4⁰C. After washing, plates
were developed with 100 μL TMB substrate (ThermoFisher Scientific, 34028) for approximately 20 min at
RT on an orbital shaker. Fifty mL of stop solution (0.16M sulfuric acid, ThermoFisher Scientific, N600)
was added and the plate was read at 450 nm on the plate reader. Mean absorbance values were
recorded and calculated concentrations were based on the standard curve (RD3: log-logistic fit, RD4:
cubic spline fit) (Figure 37). Mean absorbance values (Appendix R) for each isoform were multiplied by
the appropriate dilution to calculate 3R- or 4R-tau protein concentrations (pg/µL), and then tau isoform
concentrations were divided by total protein content (µg/mL) to compute 3R or 4R tau/total protein content
for each region per individual (pg/µg).
Figure 37. Standard curves for (A) 3R tau (log-logistic) and (B) 4R tau (cubic spline). Read at 450 nm.
Statistical Analyses
Factorial ANOVAs were conducted to examine region and species variances in total protein content
(µg/mL) and to determine isoform, region, and species differences in tau isoform/total protein content
(pg/mg). Bonferroni post hoc or student t tests were used to evaluate significant findings. Statistical analyses
were conducted using IBM SPSS Statistics, Version 22 (Armonk, NY) and Statistica, Version 8 (StatSoft,
Inc., Tulsa, OK), and level of significance (α) was set at 0.05.
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RESULTS
Raw values for total protein content (µg/mL) in the frontal cortex, temporal cortex, and cerebellum of
baboons and chimpanzees are listed in Table 6. Average total protein content for baboons was 2,645.37
(SD = 266.95) in frontal cortex, 2,082.24 (SD = 341.52) in temporal cortex, and 3,152.61 (SD = 507.06) in
cerebellum. In chimpanzees, average total protein content was 2,953.09 (SD = 444.64) in frontal cortex,
3,962.50 (SD = 1,013.11) in temporal cortex, and 3,947.21 (SD = 642.92) in cerebellum. Factorial
ANOVA for total protein content showed a significant main effect of species (F1,13 = 9.46, p < 0.01). The
main effect of region (F2,13 = 1.90, p ≥ 0.19) and the interaction between region and species (F2,13 = 2.07,
p ≥ 0.16) were not significant (Figure 38). Post hoc student’s t-tests revealed that chimpanzees had
significantly higher total protein content than baboons in temporal cortex (p = 0.04) but not frontal cortex
or cerebellum (p’s > 0.10).
Table 6. Total protein content (µg/mL) in baboon and chimpanzee frontal cortex (FC), temporal cortex (TC), and
cerebellum (CB)
Individual
FC
TC
CB
Baboon 1
2834.13
1840.75
3511.15
Baboon 2
2456.61
2323.73
2794.06
Chimpanzee 1
3270.72
4709.12
4074.28
Chimpanzee 2
2865.77
-
-
Chimpanzee 3
2245.70
4736.54
3114.64
Chimpanzee 4
3007.08
2583.15
4675.37
Chimpanzee 5
3376.17
3821.19
3924.54
Figure 38. Total protein content (µg/mL) in frontal cortex (FC), temporal cortex (TC), and cerebellum (CB) of
baboons and chimpanzees
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Tau/total protein content (pg/mg) for 3R- and 4R-tau isoforms for each region and individual are listed
in Tables 7 and 8. For baboons, average 3R tau/total protein content was 1.4 x 10-2 (SD = 1.0 x 10-2) in
frontal cortex, 1.9 x 10-1 (SD = 2.2 x 10-1) in temporal cortex, and 2.9 x 10-2 (SD = 7.0 x 10-4) in
cerebellum. For chimpanzees, average 3R tau/total protein content was 1.7 x 10-3 (SD = 1.5 x 10-3) in
frontal cortex, 1.6 x 10-3 (SD = 3.1 x 10-3) in temporal cortex, and 3.3 x 10-2 (SD = 6.6 x 10-2) in
cerebellum. Average 4R tau/total protein content for baboons was 75.61 (SD = 1.79) in frontal cortex,
112.44 (SD = 60.74) in temporal cortex, and 71.53 (SD = 3.59) in cerebellum, and for chimpanzees, was
21.44 (SD = 17.69) in frontal cortex, 15.94 (SD = 7.76) in temporal cortex, and 12.77 (SD = 9.88) in
cerebellum.
Table 7. Three-repeat tau/total protein content (pg/mg) for in frontal cortex (FC), temporal cortex (TC), and
cerebellum (CB) of baboons and chimpanzees
Individual
Baboon 1
Age
13
Sex
M
FC
2.51E-002
TC
3.46E-001
CB
2.83E-002
Baboon 2
8
F
3.34E-003
4.15E-002
2.93E-002
Chimpanzee 1
29
M
1.36E-004
8.07E-006
9.08E-006
Chimpanzee 2
25
M
1.64E-003
1.46E-005
1.33E-001
Chimpanzee 3
22
M
3.92E-003
2.21E-005
9.84E-006
Chimpanzee 4
31
F
2.55E-003
6.40E-003
2.60E-004
Chimpanzee 5
22
F
3.64E-004
-
-
Table 8. Four-repeat tau/total protein content (pg/mg) for in frontal cortex (FC), temporal cortex (TC), and
cerebellum (CB) of baboons and chimpanzees
Individual
Baboon 1
Age
13
Sex
M
FC
74.34
TC
155.38
CB
68.98
Baboon 2
8
F
76.87
69.48
74.07
Chimpanzee 1
29
M
7.11
4.79
5.93
Chimpanzee 2
25
M
15.82
17.01
27.43
Chimpanzee 3
22
M
47.28
22.45
9.24
Chimpanzee 4
31
F
-
19.50
8.47
Chimpanzee 5
22
F
15.57
-
-
Factorial ANOVA results revealed significant main effects of species (F 1,25 = 48.24, p < 0.01), isoform
(F1,25 = 105.13, p < 0.01), and a significant interaction between species and isoform (F 1,25 = 48.06, p <
0.01). Bonferroni post hoc tests revealed baboons and chimpanzees both have greater amounts of 4R-
95
tau isoforms than 3R-tau isoforms in all areas (p’s ≤ 0.04) (Figure 39). Baboons also have higher levels of
4R tau than chimpanzees in all brain regions (p < 0.01) (Figure 40B). However, 3R tau did not differ
significantly between species regardless of region (Figure 40A). Nonsignificant results were found for the
main effect of region (F2,25 = 1.69, p = 0.21) and interactions between species and region (F 2,25 = 1.79, p =
0.19), region and isoform (F2,25 = 1.67, p = 0.21), and the three-way interaction of species, region and
isoform (F2,25 = 1.76, p = 0.19).
Figure 39. Comparisons of three-repeat (3R) (black, left) versus four-repeat (4R) (blue, right) tau/total protein
content (pg/mg) by species. (A) frontal cortex, (B) temporal cortex, and (C) cerebellum.
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Figure 40. Three-repeat (3R) and four-repeat (4R) tau/total protein content (pg/mg) by tau isoform. Note scale
difference.
DISCUSSION
Healthy adult chimpanzee and baboons exhibit a predominance of 4R- to 3R-tau isoforms in the cortex
and cerebellum. These unexpected results do not support prior research that indicated chimpanzees and
gorillas may have a higher proportion of transcripts lacking exon 10 (3R tau) in the temporal cortex than
humans; however, that study did not directly measure protein expression of tau isoforms (24).
Naturally-occurring increased expression of 4R-tau isoforms in chimpanzees and baboons may
account for the prevalence of pretangles and the ability of these animals to initiate neurofibrillary tangle
formation. During early stages of tau deposition, intracellular accumulations of hyperphosphorylated and
misfolded tau aggregate into pretangles before evolving into insoluble paired helical filaments and forming
NFTs (30-32). In humans with AD and limbic neurofibrillary tangle dementia, pretangles primarily consist
of 4R tau while NFTs are comprised of both 3R and 4R tau (17, 33). These data suggest that tau isoforms
may shift from a predominant pattern of higher 4R:3R-tau expression during the pretangle phase to
greater 3R:4R when NFTs are formed. Similar to humans, elderly chimpanzees and baboons exhibit
pretangles and NFTs, and in aged chimpanzees, pretangles were the most abundant type of tau-related
pathology (27-29).
Dysregulation of a species’ normal tau isoform ratio, which necessitates the presence of both 3R- and
4R-tau isoforms, also may contribute to the development of NFTs. An imbalance in the equimolar ratio of
97
tau isoforms in humans has been linked to the manifestation of neurodegenerative diseases, particularly
tauopathies (11-15). As aged chimpanzees also exhibit tau-related pathologies, it is possible tangle
formation may be related to a disruption of the animal’s typical tau isoform expression (i.e., an increase in
3R tau or decrease in 4R tau) due to neurodegenerative pathological processes (27, 29). Moreover,
correlational evidence from several species indicates tangle formation requires the presence of both 3Rand 4R-tau isoforms. Rodents, including mice, rats, and gerbils only express 4R-tau isoforms as adults
and do not form NFTs (34-37). Conversely, humans, nonhuman primates, and artiodactyls have both 3Rand 4R-tau isoforms and exhibit tau pathology. Besides humans, chimpanzees, and baboons who display
NFTs, evidence for abnormal tau phosphorylation has been found in rhesus macaques and gorillas (2122, 27-29, 38). Moreover, NFTs have been observed in cows and sheep, species that display the two
longest 3R- and 4R-tau isoforms, while pretangles have been identified in reindeer and American bison,
all animals that belong to the artiodactyl order (25, 37-39).
Greater levels of 4R-tau isoforms in presumably healthy chimpanzees and baboons differs from the
1:1 ratio of 3R- and 4R-tau isoforms discovered in normal human brains (4). The prevalence of
neurodegenerative diseases, such as AD, in humans also varies from nonhuman primates, though both
groups exhibit AD-related pathology (i.e., Aβ plaques and NFTs) (18, 27-29, 40). Such divergences may
be related to polymorphisms in the MAPT gene, which is characterized by two haplotypes (H1 and H2)
(41). H1 is the most frequent haplotype in human populations and associated with increased risk for
progressive supranuclear palsy, corticobasal degeneration, and Parkinson’s disease (42-45). H2
haplotype primarily exists in Europeans and was correlated with increased reproductive rates and
reduced risk for late-onset AD (46-48). In an analysis of single nucleotide polymorphisms that distinguish
H1 from H2 haplotypes, nonhuman primates, including chimpanzees, were homozygous for the H2
haplotype (24). This evidence also suggests the H1 haplotype may be unique to humans, and in addition
to longer lifespans, account for the increased occurrence of neurodegenerative processes in humans
compared to chimpanzees.
We also identified possible modifications in tau isoform expression and total protein between the Old
World monkey and ape. Baboons demonstrated significantly higher amounts of 4R tau than chimpanzees
despite both species having similar levels of 3R tau in the same regions. Conversely, chimpanzees had
98
significantly higher protein content in the temporal cortex. These variances may represent an independent
development in baboons or imply a subtle modification in the regulation of microtubule dynamics between
Old World monkeys and apes.
Findings in this study should be cautiously interpreted due to potential methodological concerns such
as specificity and binding strength of antibodies and variation in small sample sizes. Disparity in the
strength of binding and specificity has been reported for RD3 and RD4 in AD (49). RD4 was shown to
weakly stain 4R-tau isoforms due to deamidation at an asparagine residue in AD brains, but in the same
investigation, RD4 strongly stained 4R-tau isoforms in PSP and CBD brains. If binding specificity and
strength of RD4 was an issue in our study, we would expect higher levels of 3R tau than 4R tau in each
sample. Conversely, we found greater 4R-tau isoforms in each region for every case; therefore, such
concerns do not appear to be a major factor in this study. It also should be noted that our study was
performed in healthy brains, and to address this potential issue, we utilized a heat stable preparation for
homogenate samples, which is effective in unbinding tubulin and microtubules in brain lysates (50).
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103
CHAPTER VI: SUMMARY
In this study, aged chimpanzees exhibited Aβ plaques and NFTs, the two pathologic hallmarks of AD. In
humans, Aβ deposition is observed predominantly in the form of extracellular plaques in addition to buildup
in parenchymal vessels while NFTs are identified within the cell somata. In chimpanzees, amyloid-beta
deposition was most prevalent in blood vessels, suggesting amyloid deposition in the brain’s vasculature
may precede plaque formation in aged chimpanzees. Furthermore, amyloid deposition in the vasculature
appeared to be primarily Aβ42 in chimpanzees with cerebral amyloid angiopathy, while humans with severe
CAA demonstrate higher levels of Aβ40. Plaques with tau-positive dystrophic neurites in chimpanzees also
differed from humans in lacking an Aβ core. Moreover, greater tauopathy was correlated with Aβ-positive
vessels, rather than plaques, in these apes. Tau lesions were identified in multiple chimpanzees in the form
of pretangles, neurofibrillary tangles, and tau neuritic plaques, demonstrating tau pathology naturally exists
in apes. We also confirmed thioflavin-S positive NFTs for the first time in elderly chimpanzees. Comparable
regional staging patterns for Aβ deposition and NFT formation in human AD patients were observed in aged
chimpanzees. Most importantly, the coexistence of Aβ and tau lesions indicates Alzheimer’s disease may
not be unique to humans.
Nonetheless, AD is defined by changes in neuropathology, behavior, and cognition. Thus, studies of
nonhuman primates that include formal behavioral and cognitive testing as well as anatomical pathology are
the most useful in determining whether AD exists in species other than humans. Unfortunately cognitive
data that could directly inform our analyses were not collected for sample individuals, limiting our ability to
associate neuropathological changes with behavioral and cognitive alterations in great apes. Further
correlative analyses with cognitive and behavioral assessments are needed to shed light on whether
neurodegenerative diseases, such as AD, are truly human-specific.
In addition to development of Aβ and tau lesions in humans with AD, glial reactivity and disruption of
calcium homeostasis have been identified as factors contributing to the disease process. Elderly
104
chimpanzees demonstrate some of these AD-related modifications, though variances from humans also
were present. Chimpanzees displayed changes in activated microglia density and morphology related to
AD pathology. The chimpanzee hippocampus, particularly the CA3 subfield, seems most susceptible to
neuroinflammation with increased microglial activation as well as a greater number of microglia with
intermediate and amoeboid morphologies in relation to Aβ deposition but not NFT or tau neuritic plaque
density. This outcome diverges from humans with AD who display greater microglial activation and
morphological changes in response to both tau and Aβ pathology, especially in the CA1 subregion.
Additionally, unlike humans, chimpanzees did not display age-related changes in microglial activation or
morphology. Such evidence suggests the chimpanzee brain may not be protected from
neurodegeneration as previously assumed and supported by the correlation of Aβ pathology and
increased neuroinflammation.
Growing evidence suggests the detrimental cognitive effects of AD and other neurodegenerative
diseases may be the result of an increased lifespan, aging processes, and ratio of tau isoforms rather
than evolutionary modifications in cerebral structure and function between chimpanzees and humans. We
found evidence that normal aging could lead to naturally rising levels of phosphorylated tau in the
chimpanzee hippocampus. Modifications in tau may take place first in calbindin-ir pyramidal neurons, cells
known to be susceptible to neurodegenerative processes in human AD brains. Eventually, buildup of
intracellular tau along with age-related increases in Aβ plaque and vessel deposition may initiate pretangle
and NFT formation in chimpanzees (Appendix S). Another contributing factor to tangle development in
chimpanzees may be higher levels of 4R- relative to 3R-tau isoforms, as 4R-tau isoforms have the
capacity to assemble into paired helical filaments and form NFTs. Greater 4R-tau isoform expression, in
addition to disruption of a species’ normal tau isoform ratio perhaps due to age-associated increases in
hyperphosphorylated tau, may partially explain the occurrence of neurofibrillary tangle formation in these
species.
Unlike humans, chimpanzees exhibited increased calbindin-ir interneuron density in the neocortex,
possibly resulting from calcium dyshomeostasis related to AD pathology. In addition, neocortical
calbindin-ir interneurons appear relatively protected despite colocalization of tau and proximity to pretangles
105
and Aβ plaques. Female chimpanzees also demonstrated increased levels of hyperphosphorylated tau than
their male counterparts in calbindin-ir neocortical interneurons.
Future directions include examining the potential coexistence of neurodegenerative pathologies, such as
Lewy bodies and synaptopathy, and association of DNA sequence polymorphisms in the APP, tau, and
presenilin genes with observed neuropathy in elderly chimpanzees. Whether neuron or glia loss is
associated with normal aging or AD pathologies, and the effect of normal aging on microglia density and
morphology in aged chimpanzees also will be explored. Additionally, quantification of parvalbumin and
calretinin, two calcium-binding proteins known to regulate calcium homeostasis, will be performed to
determine if these neurons are spared in great apes similar to observations in humans with AD. Finally,
we would like to investigate levels of 3R and 4R tau in healthy humans and AD patients to compare with
apes and Old World monkeys.
106
APPENDICES
APPENDIX A. SAMPLE DEMOGRAPHICS AND Aβ AND TAU PATHOLOGY BY INDIVIDUAL
Subject
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Age
Sex
Pathology
Score
Aβ Plaq
(Thal)
Aβ Vas
(CAA)
Pretangle
NFT
(Braak)
Tau NP
(CERAD)
37
39
40
40
41
43
44
45
49
51
58
58
39
40
41
41
41
46
57
62
F
F
F
F
F
F
F
F
F
F
F
F
M
M
M
M
M
M
M
M
4
0
2
0
0
7
0
5
3
4
13
9
10
1
4
6
0
3
19
10
Phase 1
Phase 1
Phase 2
Phase 1
Phase 1
Phase 1
Phase 3
Phase 1
Phase 1
Phase 2
Phase 4
Phase 4
Minimal
Minimal
Minimal
Minimal
Minimal
Mild
Minimal
Mild
Minimal
Minimal
Moderate
Severe
Minimal
Minimal
Minimal
Mild
Minimal
Minimal
Severe
Severe
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
Stage II
Stage I
Stage I
+*
Stage V
-
Sparse
Sparse
Sparse
Sparse
Moderate
Sparse
Moderate
Sparse
Sparse
Sparse
Sparse
Moderate
-
Aβ (beta-amyloid), CAA (cerebral amyloid angiopathy), CERAD (Consortium to Establish a Registry for AD), F
(female), M (male), NFT (neurofibrillary tangle), NP (neuritic plaque), + positive for pathology, * does not follow
staging pattern.
107
APPENDIX B. SUMMARY OF ANTIBODIES
Antigen
APP/A (6E10)
A42
Tau (AT8)
Tau (CP13)
Tau (PHF1)
Tau (MC1)
Tau 12
RD3
RD4
Iba1
GFAP
Calbindin
Antibody
mouse monoclonal to A/APP
residues 1-16
rabbit monoclonal to Aβ[1-42]
mouse monoclonal to PHF-tau
pSer202/pThr205
mouse monoclonal to phosphotau pSer202
mouse monoclonal to
phospho-tau pSer396/404
mouse monoclonal to tau
residues 5-15, 312-322
(conformation-dependent)
purified mouse monoclonal
against 6-18 aa epitope of
human tau
mouse monoclonal against antitau, 3-repeat isoform, clone
8E6/C11
mouse monoclonal against antitau, 4-repeat isoform, clone
1E1/A6
rabbit anti-Iba1 corresponding
to C-terminus
rabbit anti-glial fibrillary acid
protein
rabbit anti-calbindin D-28k
Pathology/Protein
APP/A40/A42
plaques and vessels
A42 plaques and
vessels
early, middle, and
late tau
Dilution
Company/Catalog #
1:7,500
Covance, SIG-39320
1:2,500
Invitrogen, 700254
1:2.500
ThermoFisher, MN1020
early tau
1:10,000
Gift from Peter Davies
middle and late tau
1:10,000
Gift from Peter Davies
early tau
1:5,000
Gift from Peter Davies
all six isoforms of tau
100 μg/mL
BioLegend, SIG-39416
3R-tau isoforms
6 μg/mL
Millipore, 05-803
4R-tau isoforms
6 μg/mL
Millipore, 05-804
activated microglia
1:10,000
Wako, 019-19741
reactive astrocytes
1:12,500
Millipore, AB5804
calbindin neurons
1:20,000
Swant, CB-38a
108
APPENDIX C. REGIONAL AND TOTAL VOLUMES OCCUPIED BY APP/Aβ PLAQUES (%)
Subject
Age
Sex
PFC
MTG
CA1
CA3
NC
HC
Total
1
37
F
0.0000
0.0000
0.0004
0.0000
0.0000
0.0004
0.0004
2
39
F
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
3
40
F
0.0000
0.0003
0.0000
0.0000
0.0003
0.0000
0.0003
4
40
F
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
5
41
F
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
6
43
F
0.0105
0.0042
0.0002
0.0000
0.0147
0.0002
0.0149
7
44
F
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
8
45
F
0.0003
0.0000
0.0000
0.0000
0.0003
0.0000
0.0003
9
49
F
0.0005
0.0003
0.0000
0.0000
0.0008
0.0000
0.0008
10
51
F
0.0005
0.0064
0.0000
0.0000
0.0069
0.0000
0.0069
11
58
F
0.0009
0.0000
0.0011
0.0011
0.0009
0.0022
0.0031
12
58
F
0.0067
0.0074
0.0000
0.0000
0.0141
0.0000
0.0141
13
39
M
0.0000
0.0006
0.0000
0.0000
0.0006
0.0000
0.0006
14
40
M
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
15
41
M
0.0003
0.0000
0.0000
0.0000
0.0003
0.0000
0.0003
16
41
M
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
17
41
M
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
18
46
M
0.0000
0.0002
0.0001
0.0000
0.0002
0.0001
0.0003
19
57
M
0.0030
0.0032
0.0000
0.0106
0.0062
0.0106
0.0168
20
62
M
0.0013
0.0088
0.0027
0.0074
0.0101
0.0101
0.0202
F (female), M (male), PFC (prefrontal cortex), MTG (midtemporal gyrus), NC (neocortex), HC (hippocampus)
109
APPENDIX D. REGIONAL AND TOTAL VOLUMES OCCUPIED BY Aβ42 PLAQUES (%)
Subject
Age
Sex
PFC
MTG
CA1
CA3
NC
HC
Total
1
37
F
0.0000
0.0004
0.0000
0.0000
0.0004
0.0000
0.0004
2
39
F
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
3
40
F
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
4
40
F
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
5
41
F
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
6
43
F
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
7
44
F
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
8
45
F
0.0000
-
-
-
0.0000
0.0000
0.0000
9
49
F
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
10
51
F
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
11
58
F
0.0000
0.0000
0.0000
0.0005
0.0000
0.0005
0.0005
12
13
58
39
F
0.0031
0.0055
0.0000
0.0005
0.0086
0.0005
0.0091
M
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
14
40
M
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
15
41
M
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
16
41
M
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
17
41
M
0.0000
0.0000
-
-
0.0000
0.0000
0.0000
18
46
M
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
19
57
M
0.0047
0.0003
0.0010
0.0030
0.0050
0.0040
0.0090
20
62
M
0.007
0.0253
0.0046
0.0043
0.0323
0.0089
0.0412
F (female), M (male), PFC (prefrontal cortex), MTG (midtemporal gyrus), NC (neocortex), HC (hippocampus)
110
APPENDIX E. REGIONAL AND TOTAL VOLUMES OCCUPIED BY APP/Aβ VESSELS (%)
Subject
Age
Sex
PFC
MTG
CA1
CA3
NC
HC
Total
1
37
F
0.0005
0.0137
0.0018
0.0002
0.0142
0.0020
0.0162
2
39
F
0.0026
0.0002
0.0000
0.0000
0.0028
0.0000
0.0028
3
40
F
0.0000
0.0018
0.0000
0.0000
0.0018
0.0000
0.0018
4
40
F
0.0003
0.0044
0.0027
0.0011
0.0047
0.0038
0.0085
5
41
F
0.0006
0.0000
0.0000
0.0000
0.0006
0.0000
0.0006
6
43
F
0.0056
0.0015
0.0016
0.0011
0.0071
0.0027
0.0098
7
44
F
0.0007
0.0000
0.0000
0.0000
0.0007
0.0000
0.0007
8
45
F
0.0107
0.0149
0.0000
0.0009
0.0256
0.0009
0.0265
9
49
F
0.0112
0.0004
0.0002
0.0013
0.0116
0.0015
0.0131
10
51
F
0.0095
0.0015
0.0000
0.0001
0.0110
0.0001
0.0111
11
58
F
0.0237
0.0247
0.0017
0.0017
0.0484
0.0034
0.0518
12
58
F
0.0769
0.0620
0.0128
0.0644
0.1389
0.0772
0.2161
13
39
M
0.0003
0.0009
0.0000
0.0000
0.0012
0.0000
0.0012
14
40
M
0.0007
0.0008
0.0000
0.0000
0.0015
0.0000
0.0015
15
41
M
0.0019
0.0000
0.0012
0.0002
0.0019
0.0014
0.0033
16
41
M
0.0032
0.0068
0.0004
0.0000
0.0100
0.0004
0.0104
17
41
M
0.0009
0.0011
0.0000
0.0000
0.0020
0.0000
0.0020
18
46
M
0.0047
0.0011
0.0010
0.0011
0.0058
0.0021
0.0079
19
57
M
0.0939
0.0567
0.0248
0.0423
0.1506
0.0671
0.2177
20
62
M
0.0742
0.0838
0.0206
0.0545
0.1580
0.0751
0.2331
F (female), M (male), PFC (prefrontal cortex), MTG (midtemporal gyrus), NC (neocortex), HC (hippocampus)
111
APPENDIX F. REGIONAL AND TOTAL VOLUMES OCCUPIED BY Aβ42 VESSELS (%)
Subject
Age
Sex
PFC
MTG
CA1
CA3
NC
HC
Total
1
37
F
0.0000
0.0173
0.0128
0.0007
0.0173
0.0135
0.0308
2
39
F
0.0022
0.0002
0.0002
0.0000
0.0024
0.0002
0.0026
3
40
F
0.0077
0.0003
0.0000
0.0000
0.0080
0.0000
0.0080
4
40
F
0.0027
0.0035
0.0006
0.0000
0.0062
0.0006
0.0068
5
41
F
0.0016
0.0060
0.0086
0.0010
0.0076
0.0096
0.0172
6
43
F
0.0011
0.0025
0.0000
0.0000
0.0036
0.0000
0.0036
7
44
F
0.013
0.0077
0.0013
0.0000
0.0207
0.0013
0.0220
8
45
F
0.0050
-
-
-
0.0050
0.0000
0.0050
9
49
F
0.0014
0.0021
0.0000
0.0000
0.0035
0.0000
0.0035
10
51
F
0.0016
0.0004
0.0000
0.0000
0.0020
0.0000
0.0020
11
58
F
0.0123
0.0144
0.0076
0.0032
0.0267
0.0108
0.0375
12
58
F
0.0517
0.0400
0.0130
0.0578
0.0917
0.0708
0.1625
13
39
M
0.0000
0.0006
0.0001
0.0000
0.0006
0.0001
0.0007
14
40
M
0.0000
0.0020
0.0000
0.0007
0.0020
0.0007
0.0027
15
41
M
0.0037
0.0014
0.0013
0.0008
0.0051
0.0021
0.0072
16
41
M
0.0011
0.0000
0.0004
0.0000
0.0011
0.0004
0.0015
17
41
M
0.0002
0.0000
-
-
0.0002
0.0000
0.0002
18
46
M
0.0007
0.0000
0.0006
0.0011
0.0007
0.0017
0.0024
19
57
M
0.0751
0.0557
0.0191
0.0179
0.1308
0.0370
0.1678
20
62
M
0.0816
0.0901
0.0242
0.0631
0.1717
0.0873
0.2590
F (female), M (male), PFC (prefrontal cortex), MTG (midtemporal gyrus), NC (neocortex), HC (hippocampus)
112
APPENDIX G. REGIONAL AND AVERAGE PRETANGLE DENSITIES (mm3)
Subject
Age
Sex
1
37
F
2
39
F
3
40
F
4
40
5
6
PFC
MTG
CA1
CA3
NC
HC
8.45
8.12
12.57
443.66
505.80
-
390.31
628.66
F
121.21
41
F
43
F
7
44
8
Total
27.14
8.29
19.86
14.07
0.00
474.73
0.00
316.49
30.64
71.41
509.48
51.03
280.25
375.11
0.00
44.66
248.16
22.33
135.24
367.09
76.02
12.90
0.00
221.56
6.45
114.00
69.25
387.36
55.09
9.27
228.31
32.18
130.24
F
50.93
17.28
5.31
0.00
34.11
2.66
18.38
45
F
0.00
33.51
198.01
12.42
16.76
105.22
60.99
9
49
F
229.13
757.64
19.04
0.00
493.38
9.52
251.45
10
51
F
19.12
115.18
6.82
0.00
67.15
3.41
35.28
11
58
F
549.20
1405.12
32.66
0.00
977.16
16.33
496.74
12
58
F
578.43
448.49
68.04
20.05
513.46
44.05
278.75
13
39
M
76.53
97.89
12.68
0.00
87.21
6.34
46.77
14
40
M
0.00
31.04
6.90
0.00
15.52
3.45
9.48
15
41
M
69.98
424.76
4.29
10.24
247.37
7.26
127.32
16
41
M
79.33
536.23
34.07
12.00
307.78
23.03
165.41
17
41
M
87.26
0.00
-
-
43.63
0.00
43.63
18
46
M
229.52
161.09
13.58
0.00
195.30
6.79
101.05
19
57
M
39.75
109.44
1013.46
129.59
74.59
571.53
323.06
20
62
M
440.48
258.61
0.00
0.00
349.54
0.00
174.77
F (female), M (male), PFC (prefrontal cortex), MTG (midtemporal gyrus), NC (neocortex), HC (hippocampus)
113
APPENDIX H. REGIONAL AND AVERAGE NEUROFIBRILLARY TANGLE DENSITIES (mm3)
Subject
Age
Sex
PFC
MTG
CA1
CA3
NC
HC
Total
1
37
F
0.00
0.00
0.00
0.00
0.00
0.00
0.00
2
39
F
0.00
0.00
-
0.00
0.00
0.00
0.00
3
40
F
0.00
0.00
0.00
0.00
0.00
0.00
0.00
4
40
F
0.00
0.00
0.00
0.00
0.00
0.00
0.00
5
41
F
0.00
0.00
0.00
0.00
0.00
0.00
0.00
6
43
F
0.00
0.00
0.00
0.00
0.00
0.00
0.00
7
44
F
0.00
0.00
0.00
0.00
0.00
0.00
0.00
8
45
F
0.00
0.00
50.29
0.00
0.00
25.14
12.57
9
49
F
11.46
0.00
9.52
0.00
5.73
4.76
5.24
10
51
F
0.00
0.00
0.00
0.00
0.00
0.00
0.00
11
58
F
0.00
0.00
0.00
0.00
0.00
0.00
0.00
12
58
F
0.00
0.00
5.67
0.00
0.00
2.84
1.42
13
39
M
114.79
0.00
0.00
0.00
57.40
0.00
28.70
14
40
M
0.00
0.00
0.00
0.00
0.00
0.00
0.00
15
41
M
0.00
0.00
0.00
0.00
0.00
0.00
0.00
16
41
M
0.00
0.00
0.00
0.00
0.00
0.00
0.00
17
41
M
0.00
0.00
-
-
0.00
-
-
18
46
M
0.00
0.00
0.00
0.00
0.00
0.00
0.00
19
57
M
0.00
0.00
53.34
14.40
0.00
33.87
16.93
20
62
M
0.00
0.00
0.00
0.00
0.00
0.00
0.00
F (female), M (male), PFC (prefrontal cortex), MTG (midtemporal gyrus), NC (neocortex), HC (hippocampus)
114
APPENDIX I. REGIONAL AND AVERAGE TAU NEURITIC PLAQUE DENSITIES (mm3)
Subject
Age
Sex
1
37
2
39
3
F
PFC
16.90
MTG
0.00
CA1
25.14
CA3
0.00
NC
8.45
HC
12.57
Total
10.51
F
0.00
0.00
-
0.00
0.00
0.00
0.00
40
F
0.00
0.00
0.00
0.00
0.00
0.00
0.00
4
40
F
0.00
0.00
0.00
0.00
0.00
0.00
0.00
5
41
F
0.00
0.00
0.00
0.00
0.00
0.00
0.00
6
43
F
0.00
0.00
5.01
0.00
0.00
2.50
1.25
7
44
F
0.00
0.00
0.00
0.00
0.00
0.00
0.00
8
45
F
17.19
0.00
0.00
0.00
8.59
0.00
4.30
9
49
F
0.00
0.00
0.00
0.00
0.00
0.00
0.00
10
51
F
0.00
26.58
0.00
0.00
13.29
0.00
6.64
11
58
F
51.49
222.59
22.86
0.00
137.04
11.43
74.23
12
F
0.00
0.00
11.34
20.05
0.00
15.70
7.85
13
58
39
M
200.89
24.47
0.00
10.54
112.68
5.27
58.98
14
40
M
0.00
7.62
0.00
0.00
3.81
0.00
1.90
15
41
M
10.00
0.00
0.00
10.24
5.00
5.12
5.06
16
41
M
79.33
42.56
3.41
0.00
60.94
1.70
31.32
17
41
M
0.00
0.00
-
-
0.00
0.00
0.00
18
46
M
0.00
0.00
0.00
10.30
0.00
5.15
2.57
19
57
M
914.24
9.12
21.34
14.40
461.68
17.87
239.77
20
62
M
0.00
0.00
0.00
0.00
0.00
0.00
0.00
F (female), M (male), PFC (prefrontal cortex), MTG (midtemporal gyrus), NC (neocortex), HC (hippocampus)
115
APPENDIX J. REGIONAL AND AVERAGE ACTIVATED MICROGLIA DENSITIES (mm3)
Subject
Age
Sex
PFC
MTG
CA1
CA3
NC
HC
Total
1
37
2
39
F
2425.12
2025.55
2288.51
3948.18
2225.33
3118.35
2671.84
F
7150.69
5946.49
7043.56
8706.66
6548.59
7875.11
7211.85
3
40
F
6393.07
5297.51
4066.97
7276.80
5845.29
5671.88
5758.59
4
40
F
6624.70
6388.06
4065.95
6906.34
6506.38
5486.15
5996.26
5
41
F
5719.61
8620.16
6426.20
7406.87
7169.88
6916.53
7043.21
6
43
F
3552.43
4123.05
3959.86
4504.51
3837.74
4232.18
4034.96
7
44
F
4011.51
2832.19
5335.79
6835.05
3421.85
6085.42
4753.63
8
45
F
3186.69
4811.16
5302.64
9546.91
3998.92
7424.77
5711.85
9
49
F
10327.76
4788.36
3264.93
5745.79
7558.06
4505.36
6031.71
10
51
F
4292.40
3463.66
1176.57
1525.51
3878.03
1351.04
2614.54
11
58
F
4020.31
2568.96
2645.52
4008.64
3294.64
3327.08
3310.86
12
58
F
6982.66
5429.67
3990.32
9992.10
6206.16
6991.21
6598.69
13
39
M
5695.08
5196.29
1488.56
3030.83
5445.69
2259.69
3852.69
14
40
M
4769.52
3233.87
4869.07
7191.04
4001.70
6030.06
5015.88
15
41
M
6690.93
4156.56
4101.49
7464.61
5423.75
5783.05
5603.40
16
41
M
7828.81
6631.70
3788.23
6477.79
7230.25
5133.01
6181.63
17
41
M
3292.84
3754.91
2823.56
1830.54
3523.88
2327.05
2925.46
18
46
M
7461.30
3264.13
4279.78
5515.58
5362.72
4897.68
5130.20
19
57
M
6669.12
4547.92
3244.86
6904.99
5608.52
5074.92
5341.72
20
62
M
6950.41
6366.65
7388.17
12857.43
6658.53
10122.80
8390.66
F (female), M (male), PFC (prefrontal cortex), MTG (midtemporal gyrus), NC (neocortex), HC (hippocampus)
116
APPENDIX K. REGIONAL AND AVERAGE RAMIFIED MICROGLIA DENSITIES (mm3)
Subject
Age
Sex
PFC
MTG
CA1
CA3
NC
HC
Total
1
37
2
39
F
482.55
717.38
377.36
1198.33
599.96
787.84
693.90
F
0.00
190.95
445.28
713.66
95.47
579.47
337.47
3
40
F
1165.09
970.93
125.97
291.97
1068.01
208.97
638.49
4
40
F
52.37
76.96
91.37
66.62
64.67
78.99
71.83
5
41
F
367.53
305.44
-
-
336.48
-
336.48
6
43
F
373.94
799.18
-
-
586.56
-
586.56
7
44
F
3311.06
453.70
219.83
1651.98
1882.38
935.91
1409.14
8
45
F
350.54
428.22
106.58
767.76
389.38
437.17
413.27
9
49
F
-
-
-
-
-
-
-
10
51
F
-
-
-
-
-
-
-
11
58
F
172.75
121.75
-
-
147.25
-
147.25
12
58
F
293.39
370.81
141.67
262.95
332.10
202.31
267.20
13
39
M
20.78
62.61
-
-
41.70
-
41.70
14
40
M
489.65
216.80
-
-
353.22
-
353.22
15
41
M
753.59
274.49
-
-
514.04
-
514.04
16
41
M
-
-
123.34
542.08
-
332.71
332.71
17
41
M
483.36
196.59
-
-
339.97
-
339.97
18
46
M
391.41
252.30
543.46
593.45
321.86
568.46
445.16
19
57
M
76.95
21.86
131.55
523.11
49.41
327.33
188.37
20
62
M
1141.11
795.83
305.53
572.19
968.47
438.86
703.66
F (female), M (male), PFC (prefrontal cortex), MTG (midtemporal gyrus), NC (neocortex), HC (hippocampus)
117
APPENDIX L. REGIONAL AND AVERAGE INTERMEDIATE MICROGLIA DENSITIES (mm3)
Subject
Age
Sex
1
37
F
2
39
F
3
40
4
PFC
MTG
CA1
CA3
NC
HC
Total
1571.38
970.57
1752.90
2371.43
1270.98
2062.17
1666.57
4893.83
4882.67
6092.28
6779.77
4888.25
6436.02
5662.14
F
4286.94
3815.56
3419.13
6108.91
4051.25
4764.02
4407.64
40
F
5839.16
6054.55
3837.53
6284.55
5946.86
5061.04
5503.95
5
41
F
4708.92
7771.74
-
-
6240.33
-
6240.33
6
43
F
3014.89
2924.27
-
-
2969.58
-
2969.58
7
44
F
557.16
2034.77
4936.10
4955.93
1295.97
4946.01
3120.99
8
45
F
2613.08
4030.29
2478.12
5875.02
3321.69
4176.57
3749.13
9
49
F
-
-
-
-
-
-
-
10
51
F
-
-
-
-
-
-
-
11
58
F
2779.67
2081.95
-
-
2430.81
-
2430.81
12
58
F
5897.12
3840.50
3400.04
6310.80
4868.81
4855.42
4862.11
13
39
M
4344.06
4048.51
-
-
4196.29
-
4196.29
14
40
M
3953.44
2818.35
-
-
3385.90
-
3385.90
15
41
M
5571.97
3548.76
-
-
4560.37
-
4560.37
16
41
M
6836.43
-
2960.10
3550.59
6836.43
3255.35
4449.04
17
41
M
2507.39
3283.09
-
-
2895.24
-
2895.24
18
46
M
6238.13
2617.61
2615.42
3106.87
4427.87
2861.15
3644.51
19
57
M
5925.26
4154.35
2499.42
5544.91
5039.80
4022.16
4530.98
20
62
M
5394.34
5305.54
6554.91
11713.06
5349.94
9133.99
7241.96
F (female), M (male), PFC (prefrontal cortex), MTG (midtemporal gyrus), NC (neocortex), HC (hippocampus)
118
APPENDIX M. REGIONAL AND AVERAGE AMOEBOID MICROGLIA DENSITIES (mm3)
Subject
Age
Sex
PFC
MTG
CA1
CA3
NC
HC
Total
1
37
2
39
F
160.85
F
2185.59
232.09
97.38
627.38
323.84
189.21
196.47
143.30
169.88
142.73
1406.49
233.29
819.89
3
40
F
268.87
187.37
485.88
786.08
228.12
635.98
432.05
4
40
F
680.80
436.13
91.37
399.73
558.47
245.55
402.01
5
6
41
F
43
F
482.37
475.13
-
-
478.75
-
478.75
116.86
308.78
-
-
212.82
-
212.82
7
44
F
47.74
219.98
19.98
82.60
133.86
51.29
92.58
8
45
F
159.33
151.13
53.29
66.76
155.23
60.03
107.63
9
49
F
-
-
-
-
-
-
-
10
51
F
-
-
-
-
-
-
-
11
58
F
989.37
316.56
-
-
652.97
-
652.97
12
58
F
528.10
979.99
283.34
2892.45
754.05
1587.90
1170.97
13
39
M
1226.31
918.22
-
-
1072.27
-
1072.27
14
40
M
163.21
144.53
-
-
153.87
-
153.87
15
41
M
182.69
274.49
-
-
228.59
-
228.59
16
41
M
683.64
-
440.49
216.83
683.64
328.66
446.99
17
41
M
241.68
275.23
-
-
258.45
-
258.45
18
46
M
562.66
346.91
101.90
34.91
454.79
68.40
261.59
19
57
M
461.71
306.11
416.57
366.17
383.91
391.37
387.64
20
62
M
337.14
206.33
277.75
269.27
271.74
273.51
272.62
F (female), M (male), PFC (prefrontal cortex), MTG (midtemporal gyrus), NC (neocortex), HC (hippocampus)
119
APPENDIX N. REGIONAL AND AVERAGE PHF1/IBA1 MICROGLIA DENSITIES (mm3)
Subject
Age
Sex
PFC
1
37
F
61.86
2
39
F
5559.00
3
40
F
1792.45
4
40
F
5
41
6
43
7
MTG
CA1
CA3
NC
HC
295.39
48.69
1800.32
182.16
1601.17
5420.21
F
F
44
8
Total
25.23
178.63
36.96
107.79
0.00
3679.66
91.08
1885.37
233.94
786.08
1696.81
510.01
1103.41
5207.94
2307.09
3530.89
5314.08
2918.99
4116.53
1929.50
1662.95
-
-
1796.23
-
1796.23
70.11
998.98
-
-
534.54
-
534.54
F
159.17
0.00
0.00
0.00
79.59
0.00
39.79
45
F
1545.55
403.03
-
33.38
974.29
33.38
660.65
9
49
F
-
-
-
-
-
-
-
10
51
F
-
-
-
-
-
-
-
11
58
F
659.58
438.31
-
-
548.94
-
548.94
12
58
F
1965.71
2277.81
188.89
379.81
2121.76
284.35
1203.06
13
39
M
187.07
500.85
14.45
-
343.96
14.45
234.12
14
40
M
308.29
361.33
-
-
334.81
-
334.81
15
41
M
228.36
156.85
-
-
192.60
-
192.60
16
41
M
551.32
18.42
70.48
27.11
284.87
48.79
166.83
17
41
M
498.45
373.53
-
-
435.99
-
435.99
18
46
M
3620.57
567.68
33.97
17.46
2094.12
25.71
1059.92
19
57
M
4822.28
2645.66
87.70
26.16
3733.97
56.93
1895.45
20
62
M
-
-
-
-
-
-
-
F (female), M (male), PFC (prefrontal cortex), MTG (midtemporal gyrus), NC (neocortex), HC (hippocampus)
120
APPENDIX O. REGIONAL AND TOTAL MICROGLIA MORPHOLOGY RATIOS
Subject
Age
Sex
Total
Ram/Act
Total
Int/Act
Total
Amo/Act
NC
Ram/Act
NC
Int/Act
NC
Amo/Act
HC
Ram/Act
HC
Int/Act
HC
Amo/Act
1
37
F
0.26
0.62
0.06
0.27
0.57
0.09
0.25
0.66
0.05
2
39
F
0.05
0.79
0.11
0.01
0.75
0.21
0.07
0.82
0.03
3
40
F
0.11
0.77
0.08
0.18
0.69
0.04
0.04
0.84
0.11
4
40
F
0.01
0.92
0.07
0.01
0.91
0.09
0.01
0.92
0.04
5
41
F
0.05
0.89
0.07
0.05
0.87
0.07
-
-
-
6
43
F
0.15
0.74
0.05
0.15
0.77
0.06
-
-
-
7
44
F
0.30
0.66
0.02
0.55
0.38
0.04
0.15
0.81
0.01
8
45
F
0.07
0.66
0.02
0.10
0.83
0.04
0.06
0.56
0.01
9
49
F
-
-
-
-
-
-
-
-
-
10
51
F
-
-
-
-
-
-
-
-
-
11
58
F
0.04
0.73
0.20
0.04
0.74
0.20
-
-
-
12
58
F
0.04
0.74
0.18
0.05
0.78
0.12
0.03
0.69
0.23
13
39
M
0.01
1.09
0.28
0.01
0.77
0.20
-
-
-
14
40
M
0.07
0.68
0.03
0.09
0.85
0.04
-
-
-
15
41
M
0.09
0.81
0.04
0.09
0.84
0.04
-
-
-
16
41
M
0.04
0.72
0.07
0.00
0.95
0.09
0.06
0.63
0.06
17
41
M
0.12
0.99
0.09
0.10
0.82
0.07
-
-
-
18
46
M
0.09
0.71
0.05
0.06
0.83
0.08
0.12
0.58
0.01
19
57
M
0.04
0.85
0.07
0.01
0.90
0.07
0.06
0.79
0.08
20
62
M
0.08
0.86
0.03
0.15
0.80
0.04
0.04
0.90
0.03
F (female), M (male), Act (activated), Ram (ramified), Int (intermediate), Amo (amoeboid), NC (neocortex), HC
(hippocampus)
121
APPENDIX P. REGIONAL CALBINDIN-IMMUNOREACTIVE NEURON DENSITIES (mm3)
Subject
Age
Sex
PFC
MTG
CA1
1
2
37
39
F
F
53,753.00
47,333.80
37,377.50
51,452.80
34,009.70
30,171.90
3
40
F
54,243.00
52,266.60
37,407.10
4
40
F
45,495.30
55,364.40
51,287.00
5
41
F
66,370.60
29,851.40
45,071.70
6
43
F
69,725.70
59,044.70
32,737.40
7
44
F
52,732.10
29,002.90
39,047.80
8
45
F
47,085.00
32,742.90
22,355.10
9
49
F
50,090.00
46,671.30
62,546.80
10
51
F
45,016.90
32,470.60
34,642.90
11
58
F
51,075.40
61,401.70
24,711.70
12
58
F
57,875.20
44,468.20
28,870.70
13
39
M
40,812.60
43,690.00
27,925.00
14
40
M
63,570.70
35,012.40
63,711.20
15
41
M
39,993.40
45,435.10
28,984.50
16
41
M
57,169.70
56,420.90
23,652.40
17
41
M
42,528.80
25,086.70
43,668.00
18
46
M
44,493.30
48,521.40
40,873.30
19
57
M
43,223.10
46,491.50
47,444.30
20
62
M
76,390.20
63,853.50
21,639.20
F (female), M (male), PFC (prefrontal cortex), MTG (midtemporal gyrus). PFC and MTG include interneuron
density and CA1 includes pyramidal and interneuron density.
122
APPENDIX Q. REGIONAL AT8/CB-IMMUNOREACTIVE NEURON DENSITIES (mm3)
Subject
Age
Sex
PFC
MTG
CA1
1
2
37
39
F
F
2,906.60
20,798.30
2,850.00
22,490.10
2,507.10
0.00
3
40
F
18,981.10
22,679.40
5,535.70
4
40
F
11,009.40
19,367.90
0.00
5
41
F
18,326.00
8,718.90
2,539.40
6
43
F
8,321.90
19,381.10
7,076.80
7
44
F
7,136.60
4,157.40
2,304.80
8
45
F
0.00
-
14,071.70
9
49
F
13,955.80
26,293.40
4,363.10
10
51
F
4,372.40
10,311.10
2,611.40
11
58
F
22,879.20
31,428.60
4,781.10
12
58
F
24,328.70
21,177.50
7,530.10
13
39
M
3,945.50
9,254.90
2,517.90
14
40
M
0.00
5,571.00
2,627.30
15
41
M
7,744.70
20,609.80
2,070.30
16
41
M
8,906.70
21,038.10
5,220.50
17
41
M
9,341.50
8,801.00
0.00
18
46
M
15,150.00
12,194.10
2,606.00
19
57
M
5,460.10
10,461.40
12,859.00
20
62
M
-
-
-
F (female), M (male), PFC (prefrontal cortex), MTG (midtemporal gyrus). PFC and MTG include interneuron
density and CA1 includes pyramidal and interneuron density.
123
APPENDIX R. ABSORBANCE VALUES FOR 3R-TAU AND 4R-TAU ISOFORMS
Individual
Baboon 1
Baboon 2
Chimpanzee 1
Chimpanzee 2
Chimpanzee 3
Chimpanzee 4
Chimpanzee 5
3R-tau Isoforms
Age Sex
FC
13
M
0.1220
8
F
0.0985
29
M
0.0665
25
M
0.0765
22
M
0.0875
31
F
0.1025
22
F
0.0960
Individual
Baboon 1
Baboon 2
Chimpanzee 1
Chimpanzee 2
Chimpanzee 3
Chimpanzee 4
Chimpanzee 5
4R-tau Isoforms
Age Sex
FC
13
M
0.1880
8
F
0.1780
29
M
0.0580
25
M
0.0805
22
M
0.0710
31
F
0.1510
22
F
-
TC
0.1520
0.1280
0.0505
0.0550
0.0540
0.0930
TC
0.2245
0.1635
0.0570
0.1110
0.0900
0.1070
CB
0.1335
0.1285
0.0510
0.1405
0.0505
0.0760
CB
0.2035
0.1875
0.0585
0.1145
0.0795
0.0695
F (female), M (male), FC (frontal cortex), TC (temporal cortex), CB (cerebellum)
124
APPENDIX S. NORMAL AND PATHOLOGIC AGING IN CHIMPANZEES
Pathology
Normal Aging
APP/Aβ plaque volume (%)
Pathologic Aging
neocortical, hippocampal, and total volume
diffuse morphology
diffuse + dense-core morphology
mild glial response
neocortical, hippocampal, and total volume
few affected vessels in a single region
APP/Aβ vessel volume (%)
neocortical, hippocampal, and total volume
mild immunoreactivity in short segments of
vessels
neocortical, hippocampal, and total volume
several affected vessels in multiple regions
strong immunoreactivity in long segments of vessels
positive vessels present in deeper cortical layers
perivascular leakage
strong glial response
Pretangle density (mm3 )
total density
regional density variances absent
NFT density (mm3 )
absent
Tau NP density (mm3 )
absent
Activated microglia density and
morphologic densities (mm3 )
3
total and hippocampal density
total and hippocampal density
total, neocortical, and hippocampal density
highest density in neocortex
neocortical activation associated with pretangle density
no changes
hippocampal activation associated with Aβ pathology
intermediate and amoeboid morphology in hippocampus
Calbindin density (mm )
no changes
neocortical density
Tau/calbindin density (mm3 )
hippocampal density
neocortical and hippocampal density
125