Bennett, David A.

Abstract Physical activity (PA) is a modifiable lifestyle behaviour associated with lower dementia risk; however, molecular pathways bridging PA-related dementia prevention are poorly understood. We leveraged large-scale plasma proteomics to identify biological signatures of objectively monitored PA and cognitive ageing in functionally intact older adults, cross-validated these signatures in independent exercise cohorts and tested associations with both symptomatic and presymptomatic stages of neurodegeneration across multiple Alzheimer’s disease and related dementias (ADRD) cohorts. We analysed large-scale plasma proteomics data (SomaScan 7k) across three cohorts including naturalistic, objective PA monitoring (University of California, San Francisco Brain Aging Network for Cognitive Health cohort, n = 65), self-reported PA (Atherosclerosis Risk In Communities study, n = 10 644) and PA intervention (Health Risk Factors, Exercise Training and Genetics study, n = 654). Differential regression models examined individual protein correlates of PA, adjusting for age and sex. Weighted gene co-expression network analysis assembled proteins into unbiased modules of protein co-expression, which were annotated for gene ontology and cell-type enrichment. To test clinical relevance to ADRD, we examined PA-related protein levels across-cohorts of symptomatic Alzheimer’s disease and Parkinson’s disease (Stanford Alzheimer’s Disease Research Center), as well as frontotemporal dementia-spectrum disorders (ARTFL/LEFFTDS Longitudinal Frontotemporal Lobar Degeneration consortium). PA-related plasma proteins were also tested as predictors of antemortem cognitive change and post-mortem brain tissue mass spectrometry proteomic signatures in brain donors from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP) cohort. Differential regression and network analyses identified PA plasma proteomic signatures linked to cell adhesion/extracellular matrix (ECM), immune response and lipid metabolism. Protein co-expression module M12 ECM/neurodevelopment harboured growth factor, cell adhesion and vascular remodelling proteins that (i) were positively associated with PA across exercise cohorts, (ii) positively associated with cognitive function and (iii) negatively associated with Alzheimer’s disease, Parkinson’s disease and frontotemporal dementia. Furthermore, M12 was enriched for proteins from Alzheimer’s disease risk genes and antemortem plasma abundance of anthrax toxin receptor cell adhesion molecule 2 (ANTXR2), an M12 ‘hub’ protein and top PA hit across-cohorts, forecasted longitudinal global cognitive decline and post-mortem brain tissue signatures of synaptic function and proteolysis in ROSMAP. Collectively, our integrated systems biology analysis of six independent plasma proteomic datasets facilitated discovery and validation of blood-detectable molecular signatures of PA and neurodegenerative disease, including PA-related proteins with clinical and biological relevance to early stages of disease. Circulating levels of PA-related proteins reflecting ECM biology (e.g. ANTXR2) may represent key molecular targets for dementia prevention.

Abstract Histopathological assessment has served as the gold standard for diagnosing Alzheimer’s disease (AD). Emerging technological advancements, including the development of amyloid positron emission tomography (PET), have enabled early detection of amyloid pathology, one of the neuropathological hallmarks of AD. Genome-wide association study (GWAS) across cohorts of aging and AD, leveraging different measurements of amyloid burden, may facilitate the identification of novel genetic variants that drive the earliest neuropathological changes in AD. This study presents the largest GWAS of brain amyloidosis to date, leveraging amyloid β (Aβ) measured by in vivo amyloid PET and postmortem histopathology from 13,555 individuals of European ancestry. Amyloid positivity was defined as moderate or frequent neuritic plaques according to the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) staging scores for each postmortem cohort. A Gaussian mixture model (GMM) was applied to each amyloid PET cohort to identify the cohort and tracer-specific cut-offs that differentiate amyloid positive and negative populations. In silico and ex vivo analyses further characterized implicated loci, including interrogating the association between bulk and single-nucleus gene expression profiles and AD-related traits. Genetic covariance analysis assessed the extent amyloid PET and postmortem measures reflect the shared genetic architecture of brain amyloidosis. Our combined amyloidosis GWAS identified three established AD risk loci: BIN1 (rs6733839, OR = 1.20, 95% CI 1.14-1.26, P = 1.32 × 10−11), CR1 (rs4844610, OR = 1.24, 95% CI = 1.16-1.32, P = 4.21 × 10−10), APOE (rs429358, OR = 4.01, 95% CI = 3.66-4.38, P = 4.54 × 10−201), and a newly identified brain amyloidosis-associated variant on chromosome 17 (rs35635959, OR = 1.18, 95% CI = 1.12-1.25, P = 1.47 × 10−8). SuSiE fine-mapping identified a single credible set of 15 putative causal variants with rs35635959 as the lead variant. Subsequent eQTL and SuSiE-based colocalization analyses prioritized rs35635959 as a strong eQTL for TUBG2, encoding tubulin gamma 2, which is involved in microtubule organization and synaptic plasticity. Further cell-type-specific characterization of this gene in neurons from dorsolateral prefrontal cortex tissue indicated that decreased TUBG2 expression was associated with increased Aβ burden and AD case status (PFDR < 0.045). Furthermore, our study is the first to report a modest genetic covariance (covariance=0.17, P < 6.54 × 10−8) between the genetic architecture of amyloid burden captured by different modalities. While APOE showed a strong association with both amyloid endophenotypes, the observed genetic covariance was not substantially attenuated after excluding variants within the APOE region (covariance=0.16, P < 1.32 × 10−7). Our results highlight the benefits of leveraging compatible, harmonized AD endophenotypes to increase power to uncover new molecular insights into the etiology of AD neuropathology. Wang et al. present the largest GWAS of brain amyloidosis to date, analysing 13,555 individuals using amyloid PET and postmortem Aβ measures. They identify a novel amyloidosis-associated variant on chromosome 17, demonstrate genetic covariance between modalities, and highlight complex traits sharing genetic architecture with Aβ burden.

Abstract INTRODUCTION The vascular endothelial growth factor (VEGF) signaling family plays a role in neurodegenerative diseases, including Alzheimer's disease (AD). Previous work has shown widespread effects of the members FLT1 , FLT4 , and VEGFB on AD outcomes. However, these analyses have focused within the non‐Hispanic White (NHW) population. METHODS The goal of this study was to analyze the effects of the VEGF family in underrepresented populations, leveraging large and diverse bulk RNA sequencing and tandem mass tag–mass spectrometry (TMT‐MS) proteomic data. Outcomes included measures of AD pathology and diagnosis. RESULTS Within underrepresented populations, we replicated previously reported effects of FLT1 and FLT4 , whereby higher protein abundance was observed in the AD brain and was associated with higher neuropathology burden. In stratified analyses, these associations were largely consistent across race and ethnicity. DISCUSSION This multi‐omic study on the role of the VEGF family in AD emphasizes the need for more representative studies focused on therapeutic targets for AD. Highlights Vascular endothelial growth factor (VEGF) genes and proteins were quantified in four different brain regions. Samples included participants from four different populations. Previously observed effects were replicated in diverse populations. This study is the largest multi‐omic study of the vascular endothelial growth factor (VEGF) genes among Alzheimer's disease (AD) participants from diverse populations.

Abstract INTRODUCTION New methods estimate amyloid positivity onset age (EAOA) from amyloid positron emission tomography (PET). We explore the genetics of EAOA to identify molecular factors underlying the earliest Alzheimer's disease (AD) changes. METHODS Harmonized amyloid PET data from 4216 participants were used in genome‐wide survival, tissue‐specific gene expression, and genetic covariance analyses of EAOA. RESULTS Variants in apolipoprotein E ( APOE ), ABCA7 , and RASGEF1C associated with earlier EAOA. APOE ε4/ε4 and ε3/ε4 converted 6.3 and 5 years earlier than ε3/ε3, respectively. ε2 was protective against earlier EAOA. rs4147929, an expression quantitative trait locus for ABCA7 , associated with a 4 year earlier EAOA. This variant was associated with lower brain expression of ABCA7 , which was associated with increased amyloid pathology at autopsy. Multiple immune‐related diseases shared genetic covariance with EAOA. DISCUSSION APOE , ABCA7 , and RASGEF1C associated with earlier EAOA, with supporting evidence from tissue‐specific expression analyses, offering insights into intervenable targets at early stages of AD. Highlights Novel methods estimate how long ago a patient converted to amyloid positivity. Estimating this amyloid clock allows us to determine the onset of the earliest Alzheimer's disease changes. We evaluated what genes influence when someone converts to amyloid positivity. Apolipoprotein E ( APOE ) , ABCA7 , and RASGEF1C associated with earlier age of amyloid positivity. Genetic results were supported by tissue‐specific expression analyses.

AbstractBackgroundAlzheimer’s disease (AD) is a devastating neurodegenerative disorder with few therapies to treat, mitigate or prevent its onset. Understanding of this disease is predominantly based on research in non‐Hispanic Whites (NHW) although AD disproportionately affects African Americans (AA) and Latin Americans (LA), underrepresented in AD research. To address this knowledge gap, the Accelerating Medicine Partnership for Alzheimer’s Disease (AMP‐AD) Diversity Working Group was launched to generate multi‐omics data from post‐mortem brain tissue from donors of predominantly AA and LA descent. Here, we focus on genomic and transcriptomics measures, made available through the AD Knowledge Portal (ADKP).MethodBrain tissue from dorsolateral prefrontal cortex (DLPFC), caudate nucleus (CN), superior temporal gyrus (STG) and temporal pole (TP) regions of AA (N = 299), LA (N = 344) and NHW (N = 532) donors was obtained through Mayo Clinic, Mt. Sinai School of Medicine, Emory, Columbia, Rush Alzheimer’s Disease Center, Banner Sun Health, and 1Florida. DNA extracted from DLPFC tissue samples (n = 641) was utilized for whole genome sequencing (WGS) at New York Genome Center (NYGC). RNAseq of 2,224 samples was conducted either at Mayo, Rush or NYGC. Sequencing reads were processed through GenomeGPS and MAPRseq pipelines for WGS and RNAseq data, respectively. Following quality control (QC), RNAseq data was normalized and assessed for sources of variation (SOV). Integration of WGS and RNAseq data to perform comparative eQTL analysis across multi‐ethnic populations and brain regions is ongoing.ResultWGS data for 621 donors, and RNAseq data generated at Mayo (n = 1,136 samples), Rush (n = 627), and NYGC (n = 779) sequencing centers, were deposited to the ADKP. Consensus processing of RNAseq data revealed site, sex, race/ethnicity, RIN, AD diagnosis, age at death and/or library batch as SOV across various sites and brain regions. Principal component analysis of gene expression measures revealed no major stratification by disease or brain region. Accompanying clinical metadata of donors have been distributed through ADKP.ConclusionThese multi‐omics data made available to the research community is expected to be an initial step towards bridging our data and knowledge gap to elucidate conserved and distinct AD related pathways across these underrepresented at‐risk populations.

Abstract INTRODUCTION Alzheimer's disease (AD) is the most prevalent neurodegenerative disease, yet our comprehension predominantly relies on studies within non‐Hispanic White (NHW) populations. Here we provide an extensive survey of the proteomic landscape of AD across diverse racial/ethnic groups. METHODS Two cortical regions, from multiple centers, were harmonized by uniform neuropathological diagnosis. Among 998 unique donors, 273 donors self‐identified as African American, 229 as Latino American, and 434 as NHW. RESULTS While amyloid precursor protein and the microtubule‐associated protein tau demonstrated higher abundance in AD brains, no significant race‐related differences were observed. Further proteome‐wide and focused analyses (specific amyloid beta [Aβ] species and the tau domains) supported the absence of racial differences in these AD pathologies within the brain proteome. DISCUSSION Our findings indicate that the racial differences in AD risk and clinical presentation are not underpinned by dramatically divergent patterns in the brain proteome, suggesting that other determinants account for these clinical disparities. Highlights We present a large‐scale proteome (∼10,000 proteins) of DLPFC (998) and STG (244) across AD cases. About 50% of samples were from racially and ethnically diverse brain donors. Key AD proteins (amyloid and tau) correlated with CERAD and Braak stages. No significant race‐related differences in amyloid and tau protein levels were observed in AD brains. AD‐associated protein changes showed a strong correlation between the brain proteomes of African American and White individuals. This dataset advances understanding of ethnoracial‐specific AD pathways and potential therapies.

Abstract BACKGROUND Few rare variants have been identified in genetic loci from genome‐wide association studies (GWAS) of Alzheimer's disease (AD), limiting understanding of mechanisms, risk assessment, and genetic counseling. METHODS Using genome sequencing data from 197 families in the National Institute on Aging Alzheimer's Disease Family Based Study and 214 Caribbean Hispanic families, we searched for rare coding variants within known GWAS loci from the largest published study. RESULTS Eighty‐six rare missense or loss‐of‐function (LoF) variants completely segregated in 17.5% of families, but in 91 (22.1%) families Apolipoprotein E ( APOE)‐ 𝜀4 was the only variant segregating. However, in 60.3% of families, APOE 𝜀4, missense, and LoF variants were not found within the GWAS loci. DISCUSSION Although APOE 𝜀4and several rare variants were found to segregate in both family datasets, many families had no variant accounting for their disease. This suggests that familial AD may be the result of unidentified rare variants. Highlights Rare coding variants from GWAS loci segregate in familial Alzheimer's disease. Missense or loss of function variants were found segregating in nearly 7% of families. APOE‐𝜀4 was the only segregating variant in 29.7% in familial Alzheimer's disease. In Hispanic and non‐Hispanic families, different variants were found in segregating genes. No coding variants were found segregating in many Hispanic and non‐Hispanic families.

Abstract INTRODUCTION Multi‐omics studies in Alzheimer's disease (AD) revealed many potential disease pathways and therapeutic targets. Despite their promise of precision medicine, these studies lacked Black Americans (BA) and Latin Americans (LA), who are disproportionately affected by AD. METHODS To bridge this gap, Accelerating Medicines Partnership in Alzheimer's Disease (AMP‐AD) expanded brain multi‐omics profiling to multi‐ethnic donors. RESULTS We generated multi‐omics data and curated and harmonized phenotypic data from BA ( n = 306), LA ( n = 326), or BA and LA ( n = 4) brain donors plus non‐Hispanic White ( n = 252) and other ( n = 20) ethnic groups, to establish a foundational dataset enriched for BA and LA participants. This study describes the data available to the research community, including transcriptome from three brain regions, whole genome sequence, and proteome measures. DISCUSSION The inclusion of traditionally underrepresented groups in multi‐omics studies is essential to discovering the full spectrum of precision medicine targets that will be pertinent to all populations affected with AD. Highlights Accelerating Medicines Partnership in Alzheimer's Disease Diversity Initiative led brain tissue profiling in multi‐ethnic populations. Brain multi‐omics data is generated from Black American, Latin American, and non‐Hispanic White donors. RNA, whole genome sequencing and tandem mass tag proteomicsis completed and shared. Multiple brain regions including caudate, temporal and dorsolateral prefrontal cortex were profiled.

Abstract Resilience, which relates to one's ability to respond to stressors, typically declines with age and the development of comorbid conditions in older organisms. Although progress has been made to improve our understanding of resilience in older adults, disciplines have employed different frameworks and definitions to study various aspects of older adults' response to acute or chronic stressors. “Overview of the Resilience World: State of the Science,” a bench‐to‐bedside conference on October 12–13, 2022, was sponsored by the American Geriatrics Society and National Institute on Aging. This conference, summarized in this report, explored commonalities and differences among the frameworks of resilience most commonly used in aging research in the three domains of resilience: physical, cognitive, and psychosocial. These three main domains are intertwined, and stressors in one domain can lead to effects in other domains. The themes of the conference sessions included underlying contributors to resilience, the dynamic nature of resilience throughout the life span, and the role of resilience in health equity. Although participants did not agree on a single definition of “resilience(s),” they identified common core elements of a definition that can be applied to all domains and noted unique features that are domain specific. The presentations and discussions led to recommendations for new longitudinal studies of the impact of exposures to stressors on resilience in older adults, the use of new and existing cohort study data, natural experiments (including the COVID‐19 pandemic), and preclinical models for resilience research, as well as translational research to bring findings on resilience to patient care.