Mosaic chromosomal alterations (mCAs) in blood, a form of clonal hematopoiesis, have been linked to various diseases, but their role in Alzheimer’s disease (AD) remains unclear. We analyzed blood whole-genome sequencing (WGS) data from 24,049 individuals in the Alzheimer’s Disease Sequencing Project and found that autosomal mCAs were significantly associated with increased AD risk (odds ratio = 1.27; P = 1.3 × 10 -5 ). This association varied by ancestry, mCA subtype, APOE ε4 allele status, and chromosomal location. Using matched blood WGS and brain single-nucleus RNA-seq data, we identified microglia-annotated cells in the brain carrying the same mCAs found in blood. These findings suggest that blood mCAs may contribute to AD pathogenesis, potentially through infiltration into the brain and influencing local immune response.
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We previously identified sex-specific genetic loci associated with memory performance, a strong Alzheimer’s disease (AD) endophenotype. Here, we expand on this work by conducting sex-specific, cross-ancestral, genome-wide meta-analyses of three cognitive domains (memory, executive functioning, and language) in 33,918 older adults (57% female; 41% cognitively impaired; mean age=73 years) from 10 aging and AD cohorts. All three domains were comparably heritable across sexes. Genome-wide meta-analyses identified three novel loci: a female-specific language decline-associated locus, VRK2 (rs13387871), which is a published candidate for neuropsychiatric traits involving language ability; a male-specific memory decline-associated locus among cognitive impaired, DCHS2 (rs12501200), which is a published candidate gene for AD age-at-onset; and a sex-interaction with baseline executive functioning, AGA (rs1380012), among cognitive impaired. We additionally provide evidence for shared genetic architecture between lifetime estrogen exposure and AD-related cognitive decline. Overall, we identified sex-specific variants, genes, and pathways relating to three cognitive domains among older adults.
Due to methodological reasons, the X-chromosome has not been featured in the major genome-wide association studies on Alzheimer’s Disease (AD). To address this and better characterize the genetic landscape of AD, we performed an in-depth X-Chromosome-Wide Association Study (XWAS) in 115,841 AD cases or AD proxy cases, including 52,214 clinically-diagnosed AD cases, and 613,671 controls. We considered three approaches to account for the different X-chromosome inactivation (XCI) states in females, i.e. random XCI, skewed XCI, and escape XCI. We did not detect any genome-wide significant signals (P ≤ 5 × 10-8) but identified seven X-chromosome-wide significant loci (P ≤ 1.6 × 10-6). The index variants were common for the Xp22.32, FRMPD4, DMD and Xq25 loci, and rare for the WNK3, PJA1, and DACH2 loci. Overall, this well-powered XWAS found no genetic risk factors for AD on the non-pseudoautosomal region of the X-chromosome, but it identified suggestive signals warranting further investigations.
Organ-specific aging clocks have shown promise as predictors of disease risk and aging trajectories; however, the underlying biological mechanisms they reflect remain largely unexplored. Here, we use large-scale proteomic and imaging data to investigate the relationships among organ-specific and modality-specific aging clocks and to uncover the biological processes they represent. By estimating paired protein-based and imaging-based aging clocks across 8 major organs, we demonstrate that these omics and structural profiles exhibit distinct phenotypic and genetic signatures, each potentially quantifying different stages and playing complementary roles within a unified biological aging process. Furthermore, context-specific aging clocks from multiple organs often converge and jointly capture established biological and disease pathways. For example, 65.7% of the KEGG Alzheimer’s disease pathway is enriched by at least one of 11 protein- and imaging-based aging clocks, with each clock representing different components of the pathway. These results underscore the importance of a pan-organ multi-modal perspective for quantifying the mechanisms underlying age-related diseases. Additionally, we identify modality-specific links between aging clocks and complex diseases and lifestyle factors. In summary, we uncover intricate relationships among molecular and structural aging clocks across human organs, providing novel insights into their context-specific roles in capturing consequences of aging biology and their implications for disease risk.
BACKGROUND: The 17q21.31 region with various structural forms characterized by the H1/H2 haplotypes and three large copy number variations (CNVs) represents the strongest risk locus in progressive supranuclear palsy (PSP).
OBJECTIVE: To investigate the association between CNVs and structural forms on 17q.21.31 with the risk of PSP.
METHODS: Utilizing whole genome sequencing data from 1684 PSP cases and 2392 controls, the three large CNVs (α, β, and γ) and structural forms within 17q21.31 were identified and analyzed for their association with PSP.
RESULTS: We found that the copy number of γ was associated with increased PSP risk (odds ratio [OR] = 1.10, P = 0.0018). From H1β1γ1 (OR = 1.21) and H1β2γ1 (OR = 1.24) to H1β1γ4 (OR = 1.57), structural forms of H1 with additional copies of γ displayed a higher risk for PSP. The frequency of the risk sub-haplotype H1c rises from 1% in individuals with two γ copies to 88% in those with eight copies. Additionally, γ duplication up-regulates expression of ARL17B, LRRC37A/LRRC37A2, and NSFP1, while down-regulating KANSL1. Single-nucleus RNA-seq of the dorsolateral prefrontal cortex analysis reveals γ duplication primarily up-regulates LRRC37A/LRRC37A2 in neuronal cells.
CONCLUSIONS: The copy number of γ is associated with the risk of PSP after adjusting for H1/H2, indicating that the complex structure at 17q21.31 is an important consideration when evaluating the genetic risk of PSP. © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
INTRODUCTION: The Alzheimer’s Disease Sequencing Project (ADSP) is a national initiative to understand the genetic architecture of Alzheimer’s disease and related dementias (ADRD) by integrating whole genome sequencing (WGS) with other genetic, phenotypic, and harmonized datasets from diverse populations.
METHODS: The Genome Center for Alzheimer’s Disease (GCAD) uniformly processed WGS from 36,361 ADSP samples, including 35,014 genetically unique participants of which 45% are from non-European ancestry, across 17 cohorts in 14 countries in this fourth release (R4).
RESULTS: This sequencing effort identified 387 million bi-allelic variants, 42 million short insertions/deletions, and 6.8 million structural variants. Annotations and quality control data are available for all variants and samples. Additionally, detailed phenotypes from 15,927 participants across 10 domains are also provided. A linkage disequilibrium panel was created using unrelated AD cases and controls.
DISCUSSION: Researchers can access and analyze the genetic data via the National Institute on Aging Genetics of Alzheimer’s Disease Data Storage Site (NIAGADS) Data Sharing Service, the VariXam, or NIAGADS GenomicsDB.
HIGHLIGHTS: We detailed the genetic architecture and quality of the Alzheimer’s Disease Sequencing Project release 4 whole genome sequences. We identified 435 million single nucleotide polymorphisms, insertions and deletions, and structural variants from diverse genomes. We harmonized extensive phenotypes, linkage disequilibrium reference panel on subset of samples. Data is publicly available at NIAGADS Data Storage Site, variants and annotations are browsable on two different websites.
Up to 30% of older adults meet pathological criteria for a diagnosis of Alzheimer’s disease at autopsy yet never show signs of cognitive impairment. Recent work has highlighted genetic drivers of this resilience, or better-than-expected cognitive performance given a level of neuropathology, that allow the aged brain to protect itself from the downstream consequences of amyloid and tau deposition. However, models of resilience have been constrained by reliance on measures of neuropathology, substantially limiting the number of participants available for analysis. We sought to determine if novel approaches using APOE allele status, age, and other demographic variables as a proxy for neuropathology could still effectively quantify resilience and uncover novel genetic drivers associated with better-than-expected cognitive performance while vastly expanding sample size and statistical power. Leveraging 20,513 participants from eight well-characterized cohort studies of aging, we determined the effects of genetic variants on resilience metrics using mixed-effects regressions. The outcome of interest was residual cognitive resilience, quantified from residuals in three cognitive domains (memory, executive function, and language) and built within two frameworks: “silver” models, which obviate the requirement for neuropathological data (n=17,241), and “gold” models, which include post-mortem neuropathological assessments (n=3,272). We then performed cross-ancestry genome wide association studies (European ancestry n=18,269, African ancestry n=2,244), gene and pathway-based tests, and genetic correlation analyses. All analyses were conducted across all participants and repeated when restricted to those with unimpaired cognition at baseline. Despite different modeling approaches, the silver and gold phenotypes were highly correlated (R=0.77-0.88) and displayed comparable performance in quantifying better-than or worse-than-expected cognition, enabling silver-gold meta-analyses. Genetic correlation analyses highlighted associations of resilience with multiple neuropsychiatric and cardiovascular traits (PFDR values < 5.0×10-2). In pathway-level tests, we observed three significant associations with resilience: metabolism of amino acids and derivatives (PFDR=4.1×10-2), negative regulation of transforming growth factor beta production (PFDR=1.9×10-2), and severe acute respiratory syndrome (PFDR=3.9×10-4). Finally, in single-variant analyses, we identified a locus on chromosome 17 approaching genome-wide significance among cognitively unimpaired participants (index single nucleotide polymorphism: rs757022, minor allele frequency = 0.18, β=0.08, P=1.1×10-7). The top variant at this locus (rs757022) was significantly associated with expression of numerous ATP-binding cassette genes in brain. Overall, through validating a novel modeling approach, we demonstrate the utility of silver models of resilience to increase statistical power and participant diversity.
BACKGROUND: The 17q21.31 region with various structural forms characterized by the H1/H2 haplotypes and three large copy number variations (CNVs) represents the strongest risk locus in progressive supranuclear palsy (PSP).
OBJECTIVE: To investigate the association between CNVs and structural forms on 17q.21.31 with the risk of PSP.
METHODS: Utilizing whole genome sequencing data from 1684 PSP cases and 2392 controls, the three large CNVs (α, β, and γ) and structural forms within 17q21.31 were identified and analyzed for their association with PSP.
RESULTS: We found that the copy number of γ was associated with increased PSP risk (odds ratio [OR] = 1.10, P = 0.0018). From H1β1γ1 (OR = 1.21) and H1β2γ1 (OR = 1.24) to H1β1γ4 (OR = 1.57), structural forms of H1 with additional copies of γ displayed a higher risk for PSP. The frequency of the risk sub-haplotype H1c rises from 1% in individuals with two γ copies to 88% in those with eight copies. Additionally, γ duplication up-regulates expression of ARL17B, LRRC37A/LRRC37A2, and NSFP1, while down-regulating KANSL1. Single-nucleus RNA-seq of the dorsolateral prefrontal cortex analysis reveals γ duplication primarily up-regulates LRRC37A/LRRC37A2 in neuronal cells.
CONCLUSIONS: The copy number of γ is associated with the risk of PSP after adjusting for H1/H2, indicating that the complex structure at 17q21.31 is an important consideration when evaluating the genetic risk of PSP. © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
MOTIVATION: statistics from genome-wide association studies (GWAS) are widely used in fine-mapping and colocalization analyses to identify causal variants and their enrichment in functional contexts, such as affected cell types and genomic features. With the expansion of functional genomic (FG) datasets, which now include hundreds of thousands of tracks across various cell and tissue types, it is critical to establish scalable algorithms integrating thousands of diverse FG annotations with GWAS results.
RESULTS: We propose BTS (Bayesian Tissue Score), a novel, highly efficient algorithm uniquely designed for 1) identifying affected cell types and functional elements (context-mapping) and 2) fine-mapping potentially causal variants in a context-specific manner using large collections of cell type-specific FG annotation tracks. BTS leverages GWAS summary statistics and annotation-specific Bayesian models to analyze genome-wide annotation tracks, including enhancers, open chromatin, and histone marks. We evaluated BTS on GWAS summary statistics for immune and cardiovascular traits, such as Inflammatory Bowel Disease (IBD), Rheumatoid Arthritis (RA), Systemic Lupus Erythematosus (SLE), and Coronary Artery Disease (CAD). Our results demonstrate that BTS is over 100x more efficient in estimating functional annotation effects and context-specific variant fine-mapping compared to existing methods. Importantly, this large-scale Bayesian approach prioritizes both known and novel annotations, cell types, genomic regions, and variants and provides valuable biological insights into the functional contexts of these diseases.
AVAILABILITY AND IMPLEMENTATION: Docker image is available at https://hub.docker.com/r/wanglab/bts with pre-installed BTS R package (https://bitbucket.org/wanglab-upenn/BTS-R) and BTS GWAS summary statistics analysis pipeline (https://bitbucket.org/wanglab-upenn/bts-pipeline).
The Alzheimer’s Disease Sequencing Project (ADSP) is a national initiative to understand the genetic architecture of Alzheimer’s Disease and Related Dementias (AD/ADRD) by sequencing whole genomes of affected participants and age-matched cognitive controls from diverse populations. The Genome Center for Alzheimer’s Disease (GCAD) processed whole-genome sequencing data from 36,361 ADSP participants, including 35,014 genetically unique participants of which 45% are from non-European ancestry, across 17 cohorts in 14 countries in this fourth release (R4). This sequencing effort identified 387 million bi-allelic variants, 42 million short insertions/deletions, and 2.2 million structural variants. Annotations and quality control data are available for all variants and samples. Additionally, detailed phenotypes from 15,927 participants across 10 domains are also provided. A linkage disequilibrium panel was created using unrelated AD cases and controls. Researchers can access and analyze the genetic data via NIAGADS Data Sharing Service, the VariXam tool, or NIAGADS GenomicsDB.