Integrative Genetic, Proteogenomic, and Multi-omics Analyses Reveal Sex-Biased Causal Genes and Drug Targets in Alzheimer’s Disease

Abstract Sex differences are pervasive in Alzheimer’s disease, but the underlying drivers remain poorly understood. To address this, we performed sex-stratified genome-wide association studies of Alzheimer’s disease in ∼1,000,000 individuals, which we subsequently integrated with proteogenomics datasets from neurological tissues to identify candidate causal genes. We further prioritized genes through additional multi-omics approaches, including quantitative trait locus summary-based mendelian randomization and colocalization. Altogether, we prioritized 125 female-biased and 21 male-biased risk genes. Female-biased pathways included amyloid, neurite, stress, clearance, and immune processes, with genes enriched for microglia and astrocyte expression. Through computational drug repurposing analyses, a set of sex hormone related drugs, converging on Epidermal Growth Factor Receptor (EGFR), were uniquely prioritized in women. Finally, we identified Haptoglobin (HP) as a female-specific gene, leveraging long-read sequencing approaches to implicate a link to oxidative stress, APOE, and hemoglobin biology. Altogether, our findings provide a portal into sex-specific precision medicine for Alzheimer’s disease. Competing Interest Statement C.B.Y. has served as a consultant for Medidata Solutions. C.C. has received research support from GSK and EISAI. C.C. is a member of the scientific advisory board of Circular Genomics and owns stocks. C.C. is a member of the scientific advisory board of ADmit. T.S.W. is a co-founder of revXon. Funding Statement The funding organizations and sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Participants or their caregivers provided written informed consent in the original studies. The current study protocol was granted an exemption by the Washington University Institutional Review Board because the analyses were carried out on "de-identified, off-the-shelf" data; therefore, additional informed consent was not required. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Data availability Data used in the GWAS analyses are available upon application to: NIAGADS (https://www.niagads.org/) LONI (https://ida.loni.usc.edu/) AMP-AD knowledge portal / Synapse (https://www.synapse.org/) Rush (https://www.radc.rush.edu/) NACC (https://naccdata.org/) FinnGen (https://www.finngen.fi/en) The specific data repository and identifier for ADGC and ADSP data are indicated in Tables-S1-2 of the supplement. Full GWAS summary statistics will be available in NIAGADS and GWAS Catalogue upon publication. The protein weights used in the study are publicly available: Data used in the xQTL colocalization analyses are publicly available: eQTLgen (https://www.eqtlgen.org/cis-eqtls.html) UK Biobank PPP (https://metabolomips.org/ukbbpgwas/) Wingo et al. DLPFC pQTL and eQTL (https://www.synapse.org/Synapse:syn51150434/wiki/621280) Western et al. CSF pQTL (https://www.ebi.ac.uk/gwas/publications/39528825) MetaBrain (https://download.metabrain.nl/files.html) BrainMeta (https://yanglab.westlake.edu.cn/software/smr/#DataResource) Brain xQTL serve (http://mostafavilab.stat.ubc.ca/xqtl/) Fujita et al. brain single cell eQTL data (https://www.synapse.org/Synapse:syn52335807) Kosoy et al. microglia eQTL data (https://www.synapse.org/Synapse:syn30308484) Kosoy et al. microclia caQTL data (https://www.synapse.org/Synapse:syn30308248) eQTL Catalogue database (https://www.ebi.ac.uk/eqtl/Data_access/) A table overview of all QTL resources and their public identifiers are indicated in Table-S23 of the supplement. A public repository of all locus compare plots, with colocalization (PP4 ≥ 0.7) from the xQTL colocalization analyses, can be accessed at 10.5281/zenodo.16989952.