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INTRODUCTION: Accurate epidemiologic estimates for dementia are lacking for American Indians, despite substantive social and health disparities. METHODS: The Strong Heart Study, a population‐based cohort of 11 American Indian tribes, conducted detailed cognitive testing and examinations over two visits approximately 7 years apart. An expert panel reviewed case materials for consensus adjudication of cognitive status (intact; mild cognitive impairment [MCI]; dementia; other impaired/not MCI) and probable etiology (Alzheimer's disease [AD], vascular bain injury [VBI], traumatic brain injury [TBI], other). RESULTS: American Indians aged 70–95 years had 54% cognitive impairment including 10% dementia. VBI and AD were primary etiology approximately equal proportions (>40%). Apolipoprotein (APO) Eε4 carriers were more common among those with dementia (p = 0.040). Plasma pTau, glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) were higher among those with cognitive impairment, but not amyloid beta (Aβ). Cognitive intact had mean 3MSE 92.2 (SD 6.4) and mean Montreal Cognitive Assessment (MoCA) score of 21.3 (SD 3.2). DISCUSSION: This is the first population‐based study to estimate the prevalence of vascular and Alzheimer's dementias in a population‐based study of American Indians. Highlights: The Strong Heart Study is a population‐based cohort of American Indian tribes, conducted over 30+ years and three US geographic regions (Northern Plains, Southern Plains, Southwest).Our teams conducted detailed cognitive testing, neurological examination, and brain imaging over two visits approximately 7 years apart. An expert panel reviewed collected materials for consensus‐based adjudication of cognitive status (intact; MCI; dementia; other impaired/not MCI) and probable underlying etiology (AD; VBI; TBI; other).In this cohort of American Indians aged 70–95, 54% were adjudicated with cognitive impairment, including approximately 35% MCI and 10% dementia. These data expand on prior reports from studies using electronic health records, which had suggested prevalence, and incidence of dementia in American Indians to be more comparable to the majority population or non‐Hispanic White individuals, perhaps due to latent case undercounts in clinical settings.Vascular and neurodegenerative injuries were approximately equally responsible for cognitive impairment, suggesting that reduction of cardiovascular disease is needed for primary prevention.Traumatic injury was more prevalent than in other populations, and common among those in the "other/not MCI" cognitive impairment category.Mean scores for common dementia screening instruments—even among those adjudicated as unimpaired—were relatively low compared to other populations (mean unimpaired 3MSE 92.2, SD 6.4; mean unimpaired MoCA 21.3, SD 3.2), suggesting the need for cultural and environmental adaptation of common screening and evaluation instruments. [ABSTRACT FROM AUTHOR]

Background: While traditional histologic neuropathological assessment of neurodegenerative disease has tremendous diagnostic value, insights into neurodegeneration's pathophysiological underpinnings can be significantly enhanced with large‐scale quantitative analyses. As part of the Seattle Alzheimer's Disease Brain Cell Atlas (SEA‐AD), we present a neuropathology dataset across 84 brains spanning the spectrum of AD neuropathologic change donated by UW Alzheimer's Disease Research Center and Adult Changes in Thought study participants. Method: Human brain tissue was collected at rapid autopsy (postmortem interval <12 hours). One hemisphere (randomly selected) was embedded in alginate for uniform coronal slicing (4mm), with alternating slabs fixed in 10% neutral buffered formalin or frozen in a dry ice isopentane slurry. Superior and Middle Temporal Gyrus (MTG) was sampled from fixed slabs and subjected to standard processing, embedding, sectioning (5µm), histochemical (H&E/Luxol fast blue), and immunohistochemical (duplex pTau and pTDP‐43, Aβ and Iba1, and monoplex GFAP, a‐synuclein, and NeuN) labeling. HALO image analysis software (Indica Labs, Albuquerque NM) was used to define and quantify relevant cellular and pathological features within each cortical layer (Figures 1‐3). Result: 84 individuals were included in these analyses (Table 1). While quantitative metrics of pTau and Aβ aligned with traditional neuropathological measures, they showed substantial variability within discrete diagnostic stages (Figure 4). These findings were robust to quantification (discrete count vs. total area stained) and normalization (total nuclei vs. total area analyzed) methods, and highlight the importance of deploying highly quantitative, continuous measures of pathology in the study of neurodegeneration. This unique resource provides spatially preserved measures of pathologic burden across the spectrum of AD with potential for correlative analysis across pathologies, clinical and biomarker parameters, and omics applications to better support the identification of vulnerable cell types in early stages of AD progression, the principal goal of SEA‐AD. Conclusion: Here we present a large‐scale quantitative neuropathology dataset, which enables analysis of pathological proteins and cell types at unprecedented scale and accuracy. Little is known about the interactions of AD‐relevant cell types with pathologic peptides across disease progression. The presented analyses exemplify the potential of this unique publicly‐accessible resource to identify and quantify novel disease‐relevant relationships. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) is best defined in vivo using quantifiable, objective markers reflecting amyloid deposition (A), pathologic tau (T), and neurodegeneration (N). However, gold standards for ATN (imaging or cerebrospinal proteins) are expensive, invasive, and/or impractical in low resource settings. Circulating proteins offer a practical alternative. Candidate plasma markers include amyloid‐β (Aβ40&42), phosphorylated tau‐181 (ptau), glial fibrillary protein (GFAP), and neurofilament light chain (NfL). However, no such markers have been evaluated in American Indians. Method: The Strong Heart Study recruited 401 American Indians over 3 states in 2017‐2019 for MRI, cognitive testing, and clinical examination. MRI included T1 sequences, which were processed using FreeSurfer to quantify structural volumes. Neuropsychological testing incuded California Verbal Learning Test, which was operationalized into categories of memory impairment using indices of learning and recall. Plasma samples were sent to University of Gothenburg for Simoa Quanterix assay. Statistics included descriptive summary; multivariate regression; and receiver operating characteristic analysis. Result: The study population was mean age 78 (SD 4.7, range 70‐95); majority female (71%); and 21% APOE ε4 allele carriers. An estimated 31% had any memory impairment (13.8% retrieval, 6.5% storage, 10.7% encoding). Median plasma marker values were: ptau 5.0pg/mL (range: 1.5‐442), Aβ40 128pg/mL (116‐175), Aβ42 8.2pg/mL (6.7‐9.7), GFAP 150pg/mL (0‐651), and NfL 31.6pg/mL (9.7‐343); median Aβ42:40 ratio 0.06. Comparing APOEε4 carriers to non‐carriers (Table1), ptau was +12%, Aβ40 ‐0.8%, Aβ42 ‐8.4%, Aβ4240 ‐16.7% (P = 0.006), GFAP +16.1%, NfL +3.2%, but only Aβ4240 was significant. Linear regressions with brain volumes identified significant associations for Aβ42, Aβ40, GFAP, and NfL (but not ptau) with ventricle, cortical, and overall volume; NfL was also associated with entorhinal and hippocampal volume. GFAP and ptau were significantly higher in those with memory encoding deficit; NfL higher with encoding or retrieval deficit (Table2). Although not significant, Aβ40 was lower with storage deficit, and Aβ42 with encoding or storage deficit. AUC range for plasma markers to discriminate memory impaired from intact: 0.4‐0.6. Conclusion: These data are a first look at ATN plasma markers in a population‐based cohort of American Indians, an underrepresented group in AD research. Future research should address generalizability and measurement validity. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) is the most common form of dementia. The progression of AD throughout the brain follows a stereotypical pattern that can be described by the quantification of histopathological changes in several brain regions. As part of The Seattle Alzheimer's Disease Cell Atlas (SEA‐AD, https://sea-ad.org), we previously quantified pathological proteins in the middle temporal gyrus (MTG) and used them to describe disease progression, vulnerable cell types, and the MTG molecular changes related to disease Method: In this work, we expanded our results and undertook a comparative approach. We measured a battery of neuropathological proteins (staining NeuN, AT8, IBA1, GFAP, 6e10, pTDP43, and a‐Syn immunoreactivity, and analyzing them with machine learning) in the middle temporal gyrus, the middle frontal gyrus, and medial entorhinal cortex in 84 donors. In addition, we undertook a multimodal single‐cell analysis of such regions, profiling cells using single‐cell RNA‐seq, ATAC‐seq, Multiome, and spatial transcriptomic. Borrowing from our hierarchically resolved cell types in MTG, based on the BRAIN initiative cell type reference, we used machine learning algorithms to create multimodal cell type maps across regions. We used Bayesian statistics to identify differentially accessible regulatory elements, link them to the affected genes and the regulatory transcriptional machinery binding in such elements. Result: We identified regional vulnerable neuronal populations and a core set of transcriptionally similar cell types susceptible to disease across the cortex. We created a cortex‐wide disease progression map combining neuropathological data from our three profiled regions with latent Bayesian statistical algorithms. In each area, we developed an AD pseudo‐progression timescale that describes the burden of disease in the area and, next, combined all areas to create a cortex‐wide holistic pseudo‐progression. We used the mapped cell types and our developed scale to synchronize changes occurring in each patient, describing abundances, gene expression, and chromatin accessibility modifications. Conclusion: The progression scale developed in this study serves as a reference to align changes across brain regions and, in the future, to reconcile differences across cohorts. [ABSTRACT FROM AUTHOR]

Background: The Seattle Alzheimer's Disease Cell Atlas (SEA‐AD, https://sea-ad.org) is a large‐scale effort to identify, at single cell resolution, the cellular and molecular mechanisms that cause AD and facilitate its progression. SEA‐AD brings together quantitative neuropathology (QNP) derived from classic histopathological and cell type stains with single nucleus transcriptomics, epigenetics, and spatial transcriptomics on a cohort of 84 aged donors that span the pathological and cognitive disease spectrum, including unaffected controls. Method: We ordered SEA‐AD donors based on QNP using a Bayesian latent space model to construct a model‐estimated "pseudo‐progression" (PS). We then used a general linear mixed effects model to test for gene expression changes along the PS in each of the BRAIN initiative's 139 cell types present in SEA‐AD's single nucleus RNA sequencing dataset (∼1.2 million nuclei) from the middle temporal gyrus. By separately fitting models to donors with lower and higher pathology, we obtained two beta coefficients for each gene that enabled distinction between early, late, and consistent up‐ and down‐regulation along PS. We then tested whether the betas for each gene were different across all cell types or in only certain ones to measure specificity. We curated gene modules from biological processes potentially relevant to AD, identified in gene‐set enrichment analyses and prior studies, and categorized each gene within them based on their dynamics and specificity. Result: Roughly one‐third of genes had differential expression across neuronal cell types (mean betas > 0.2), split evenly between up‐ and down‐regulation, while a smaller subset were changed in specific cell types. Modules enriched in broadly changed genes that had increased expression early in PS included those involved with the microtubule cytoskeleton, vesicle adaptors, and neurotransmitter receptors, while those with decreased expression included those involved with cholesterol synthesis, glycolysis, mitochondrial function, and neurofilaments. Among the genes changed only in specific cell types were NOTCH2 in Somatostatin and Parvalbumin interneurons selectively vulnerable to pathology, PTPRG in disease associated microglia, and COL21A1 in disease associated astrocytes. Conclusion: Broadly affected modules identified by SEA‐AD suggest most neurons are affected by disease pathology and cell type‐specific differences may provide clues to selective vulnerability. [ABSTRACT FROM AUTHOR]

Background: Abnormal cerebral blood flow (CBF) is observed in early Alzheimer's disease. Cerebrovascular reserve (CVR) represents the ability of the vasculature to maintain normal CBF. While CBF abnormalities can indicate a primary vascular dysfunction, it could also arise secondary to neurodegeneration and reduced metabolic demands. CVR, on the other hand, is a specific marker of vascular insufficiency. Our goal was to evaluate the associations between CVR, CBF, and cognition in older adults with and without MCI. Methods: 70 older adults (>65 years 77.3 ± 8.32 years old, 42F, 46 controls i.e., NC and 24 MCI) were scanned in compliance with Institutional Review Board guidelines. Besides a T1 scan, we performed pCASL to quantify baseline CBF and a breath‐hold BOLD fMRI experiment to quantify CVR. We use a mixed‐effects model in FSL to test CVR and CBF differences between groups as well as association with cognitive tests, i.e., Montreal Cognitive Assessment (MoCA), Immediate and Delayed recall (CRAFTi/d) and Trails‐B, using Gaussian random field theory for a cluster‐wise threshold of p = 0.05. All comparisons were adjusted for age and gender. Results: Only CVR was significantly (p<0.05) different between NC and MCI (Figure 1). While there was no group difference in CBF, the group difference between CVR was no longer significant when adjusted for baseline CBF. Investigating further, high CBF was significantly associated with lower CVR in the MCI group only. A high CBF was very weakly related to high CVR in NC (Figure 2). A high CVR was associated with a high MoCA score (Figure 3) and CRAFTi/d (Figure 4). Conclusion: We demonstrated the utility of a simple breath‐hold based CVR measurement in understanding the association between vascular mechanisms and cognition. It is likely that CBF is not different between groups because MCI participants utilize their vascular reserve to maintain baseline CBF. Consequently, an additional vascular challenge results in a lower CVR measurement. Furthermore, a higher CVR in MCI subjects such as that seen in association with cognitive tests could be a result steal phenomenon to redirect perfusion from degenerating tissue to viable tissue. However, these mechanisms need to be further investigated. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) is the most common form of dementia, which can be detected early as mild cognitive impairment but has no broadly effective treatments to halt patients' yearslong decline. Histopathology studies have long noted dramatic, progressive, and stereotyped changes across numerous brain regions, including protein aggregate formation and even selective loss of molecularly defined neuronal populations. But the underlying molecular and cellular mechanisms that cause AD and facilitate its progression remain unknown or are only coarsely understood, hampering efforts to treat or cure the disease. Method: To uncover these mechanisms, we characterized the transcriptomic and epigenetic landscapes of AD by applying single nucleus RNA and ATAC sequencing to ∼8 million nuclei isolated from 3 cortical regions (entorhinal cortex, middle temporal gyrus, and prefrontal cortex) in 84 aged donors that span the histopathological and cognitive disease spectrums (including unaffected controls) as part of a broader Seattle AD Brain Cell Atlas (SEA‐AD) effort. We identified ∼130 highly resolved transcriptional cell types from the BRAIN initiatives' neurotypical references and leveraged recently developed machine learning approaches to integrate and hierarchically classify nuclei across donors. This enabled characterization of cell type abundance, gene expression, and chromatin accessibility differences that correlate with AD neuropathology, cognition decline, and genetic background with unprecedented precision. Result: Our comprehensive molecular atlas identified specific intratelencephalic excitatory neurons, inhibitory neurons, and microglia subsets that have altered abundances, gene expression, and/or chromatin accessibility as a function of cognitive decline and quantitative neuropathology, suggesting these populations may be selectively vulnerable to AD or involved in disease etiology. Their differentially expressed genes and accessible chromatin regions include both those found by previous atlasing efforts and genome wide association studies as well as novel ones, providing new clues to the molecular pathways that underpin AD. By comparing the SEA‐AD atlas with the neurotypical references, we also identified how expression patterns of genes, chromatin accessibility, and cell‐cell interactions associated with AD are more broadly altered by the disease. Conclusion: The cell types and molecular pathways identified by our atlas provide new targets for the rational development of therapeutic interventions and as biomarkers for earlier detection of the disease. [ABSTRACT FROM AUTHOR]

Background: Little is known about cognitive impairment and dementia in American Indians, who are underrepresented in most studies of Alzheimer's disease and related dementias. Method: The Strong Heart Study recruited 4,549 American Indians aged 45‐75 from 3 major geographic regions in 1989‐1991. In 2010‐2013 and again in 2017‐2019, all eligible surviving participants were recruited for comprehensive cranial magnetic resonance imaging, cognitive, and clinical examinations. Neurological data collected included history of stroke and neurological symptoms. Cognitive data included Modified Mini Mental Status Examination, Weschler Adult Intelligence Scale, Controlled Word Association Test, California Verbal Learning Test, Wide Range Achievement Test, Montreal Cognitive Assessment, Craft Story Recall, Benson Figure Copy, Number Span test, Category Fluency, Trail Making test, Multilingual Naming Test, Functional Activities Questionnaire. Physical function tests included Short Physical Performance Battery, dynamometric grip strength, and Halstead finger tapping test. Mood and quality of life tests included Short Form 36 and Centers for Epidemiologic Studies Depression scale. Clinical examination included anthropometric measures, blood pressure, and basic blood and urine laboratory assays including serum glucose, lipids, creatinine, and albumin. Neuroradiologists blinded to clinical data examined MRI for vascular and structural findings, including presence and location of infarcts, hemorrhages, white matter hyperintensities, sulcal widening, ventricle enlargement, and volumetric estimates of hippocampus, parahippocampal gyrus, thalamus, and frontal lobe. Neuropsychologist panels adjudicated cognitive impairment and dementia by case review. Result: This report describes the structure and methods used to collect these longitudinal data, including the cognitive examinations, the neuropsychological data cleaning, and the panel‐based case reviews. We also include basic epidemiologic description of the data, including changes in cranial imaging findings and cognitive and functional examinations between the two neurological examinations (approximate follow‐up time: 7 years). Conclusion: This report adds to existing literature with the first longitudinal description of cranial imaging and cognitive testing data in American Indian elders, as well as the first cognitive measurements related to Alzheimer's disease, in this population. These data may be used to estimate incidence and prevalence of vascular brain injury, structural atrophy, imaging markers related to Alzheimer's disease, and cognitive function in this understudied population. [ABSTRACT FROM AUTHOR]