Inferring the molecular mechanisms of noncoding Alzheimer’s disease-associated genetic variants
Structured AbstractO_ST_ABSINTRODUCTIONC_ST_ABSWe set out to characterize the causal variants, regulatory mechanisms, tissue contexts, and target genes underlying noncoding late-onset Alzheimers Disease (LOAD)-associated genetic signals.\n\nMETHODSWe applied our INFERNO method to the IGAP genome-wide association study (GWAS) data, annotating all potentially causal variants with tissue-specific regulatory activity. Bayesian co-localization analysis of GWAS summary statistics and eQTL data was performed to identify tissue-specific target genes.\n\nRESULTSINFERNO identified enhancer dysregulation in all 19 tag regions analyzed, significant enrichments of enhancer overlaps in the immune-related blood category, and co-localized eQTL signals overlapping enhancers from the matching tissue class in ten regions (ABCA7, BIN1, CASS4, CD2AP, CD33, CELF1, CLU, EPHA1, FERMT2, ZCWPW1). We validated the allele-specific effects of several variants on enhancer function using luciferase expression assays.\n\nDISCUSSIONIntegrating functional genomics with GWAS signals yielded insights into the regulatory mechanisms, tissue contexts, and genes affected by noncoding genetic variation associated with LOAD risk.