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Elucidating sex-specific risk for Alzheimer's disease through state-of-the-art genetics and multi-omics

PI
Belloy, Michael
DAR ID
11386
Initial Approval Date
January 6, 2025
Current DAR Status
Active
PI Institution
Washington University in St Louis
PI Institution Country
United States
PI Institution Type
Non-Profit
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NG00129NCRAD Families Whole Exome SequencingNG00126A fast and robust strategy to remove variant level artifacts in Alzheimer’s Disease Sequencing Project data (Belloy et al. 2022)NG00132Health and Retirement Study (HRS) APOE and Serotonin Transporter AllelesNG00118AMP-AD SV WGS and SV-xQTLNG00134National Health and Aging Trends Study (NHATS) GWASNG00130Large scale CSF proteogenomic atlasNG00144The Prediction of Alzheimer’s Disease through Multi-Trait Genetic ModelingNG00131Large scale genetics study on CSF and brain metabolite levelsNG00135UAB ADRC - University of Alabama at Birmingham Alzheimer’s Disease Research CenterNG00146Singapore Longitudinal study of Vascular Cognitive Impairment and DementiaNG00102Genomic atlas of the proteome from brain, CSF and plasma prioritizes proteins implicated in neurological disordersNG00154Dementia in Parkinson's Disease(PDD)NG00153Health and Retirement Study (HRS) DNA MethylationNG00160Sex-specific genetic architecture of late-life memory performanceNG00022ADC1 - Alzheimer's Disease Center Dataset 1NG00023ADC2 - Alzheimer's Disease Center Dataset 2NG00024ADC3 - Alzheimer's Disease Center Dataset 3NG00068ADC4 - Alzheimer's Disease Center Dataset 4NG00069ADC5 - Alzheimer's Disease Center Dataset 5NG00070ADC6 - Alzheimer's Disease Center Dataset 6NG00071ADC7 - Alzheimer's Disease Center Dataset 7NG00136ADC8 - Alzheimer's Disease Center Dataset 8NG00137ADC9 - Alzheimer's Disease Center Dataset 9NG00138ADC10 - Alzheimer's Disease Center Dataset 10NG00139ADC11 - Alzheimer's Disease Center Dataset 11NG00140ADC12 - Alzheimer's Disease Center Dataset 12NG00149ADC13 - Alzheimer's Disease Center Dataset 13NG00150ADC14 - Alzheimer's Disease Center Dataset 14NG00151ADC15 - Alzheimer's Disease Center Dataset 15NG00159Longitudinal Change in Memory Performance as a Strong Endophenotype for Alzheimer’s Disease – Archer, et al, 2023NG00116Resolving mutations in challenging genomic regions to test association with disease phenotypesNG00157Sex-specific genetic predictors of Alzheimer's disease biomarkers – Deming, et al. 2018NG00158Sex differences in the genetic predictors of Alzheimer’s pathology – Dumitrescu, et al. 2019NG00161Sex differences in the genetic architecture of cognitive resilience to Alzheimer's disease – Eissman, et al. 2022NG00145Colorado Adoption/Twin Study of Lifespan behavioral development & cognitive aging (CATSLife) APOENG00103Association Between Common Variants in RBFOX1, an RNA-Binding Protein, and Brain Amyloidosis in Early and Preclinical Alzheimer DiseaseNG00156Genetic variants and functional pathways associated with resilience to Alzheimer's diseaseNG00147Amyloid Neuroimaging and Genetics Initiative (ANGI) GWASNG00165CHARGE Association results from the ADSP R1 WGS data setNG00162Oligodendrocytes single-cell whole genome and RNA sequencingNG00166Association results from the ADSP R3 17k WGS data set - Lee et al., 2023NG00169Progressive Supranuclear Palsy (PSP) Summary Statistics- Farrell et al., 2024NG00141The Sacramento Area Latino Study on AgingNG00174Whole Genome Sequencing (WGS) and SNP Array data for the SEA-AD Consortium CohortNG00100Novel Alzheimer Disease Risk Loci and Pathways in African American Individuals Using the African Genome Resources Panel: A Meta-analysis. Kunkle et al. (2021)NG00035GWAS of CSF tau levels identifies risk variants for Alzheimer’s DiseaseNG00050GWAS of CLU, A potential endophenotype for Alzheimer's diseaseNG00171Population structure in LASI-DADNG00075IGAP Rare Variant Summary Statistics- Kunkle et al. (2019)NG00177ADGC Multi-Ancestry GWAS Meta-Analysis – Rajabli et al., 2025NG00179AD GWAS in participants of African ancestry – Ray et al., 2024NG00175Genome-wide association study of neuropathology endophenotypes
• Objectives: In this project, we seek to holistically investigate the genetic and molecular drivers of sex dimorphism in Alzheimer’s disease across ancestries.
• Study design: This study integrates large-scale population genetics with multi-omics and endophenotype analyses. We are integrating all data available from ADGC and ADSP, together with other data from AMP-AD and biobanks such as UKB, FinnGen, and MVP to conduct large-scale multi-ancestry GWAS, rare-variant gene aggregation analyses, QTL studies, PWAS, TWAS, etc. We also particularly focus on X chromosome association studies. The study design also interrogates interactions with ancestry, hormone exposures, and with APOE*4, as well as comparisons to non-stratified GWAS/XWAS of Alzheimer’s disease. Further, we will also employ genetic correlation analyses, mendelian randomization, colocalization, and pleiotropy analyses, to interrogate overlap with other complex traits to better understand the mechanisms underlying sex dimorphism in Alzheimer’s disease.
• Analysis plan, including the phenotypic characteristics that will be evaluated in association with genetic variants: Our phenotypes will include Alzheimer’s disease risk, conversion risk, various endophenotypes (including amyloid/tau biomarkers, brain imaging metrics, etc.) as well as molecular traits. As noted above, we will conduct large-scale multi-ancestry GWAS, XWAS, rare-variant gene aggregation analyses, QTL studies, PWAS, TWAS, etc. Specific aims include interrogating these question and analyses on (1) the autosomes, (2) the X chromosome, and (3) leveraging sex stratified QTL studies to drive discovery of risk genes.
Alzheimer’s disease (AD) manifests itself differently across men and women, but the genetic and molecular factors that drive this remain elusive. AD is the most common cause of dementia and till today remains largely untreatable. It is thus crucial to study the genetics of AD in a sex-specific manner, as this will help the field gain important insights into disease pathophysiology, identify novel sex-specific risk factors relevant to personalized genetic medicine, and uncover potential new AD drug targets that may benefit both sexes. This project uses large-scale genomics and multi-omics to elucidate novel sex agnostic and sex-specific AD risk genes. We will interrogate sex dimorphism for AD risk on the autosomes and the sex chromosomes. We similarly interrogate sex dimorphism in the genetic regulation of gene expression and protein levels, which we will integrate with genetic risk for Alzheimer’s disease to further discovery risk genes. Throughout, we will also interrogate how sex-specific risk for AD interactions with hormone exposures, ancestry, and the APOE*4 risk allele.

Reported Publications (4)

Publications shown are those reported by investigators through NIAGADS DAR reporting and renewal processes and may not represent a complete list of publications associated with the project.

  1. A quantitative trait locus for reduced microglial APOE expression associates with reduced cerebral amyloid angiopathy. Belloy ME, et al. Nature genetics. 2026. PMID: 41588232
  2. Sex-aware causal inference assessment of the immune system in complex neurodegenerative diseases. Lona-Durazo F, et al. Brain : a journal of neurology. 2026. PMID: 41437896
  3. APOE*4 Risk-Modifying Genes and Drug Targets in Alzheimer's Disease through Cell-Type Specific Genomic Analyses. Zeng Y, et al. medRxiv : the preprint server for health sciences. 2025. PMID: 41404291
  4. Integrative Genetic, Proteogenomic, and Multi-omics Analyses Reveal Sex-Biased Causal Genes and Drug Targets in Alzheimer's Disease. Cook N, et al. medRxiv : the preprint server for health sciences. 2025. PMID: 41282793