A Multi-Context Regulome-Wide Association Atlas for Genetic Studies of Aging Brain Disorders

Genome-wide association studies have identified risk loci for aging brain disorders, but mechanistic interpretation depends on linking these loci to genes and to the tissues, cell types, and molecular modalities in which they act. Here, we introduce FunGen-xQTL Multi-Brain (FGMB), a multi-context atlas of cis-regulatory genetic prediction models for regulome-wide association studies (RWAS), built from molecular datasets assembled by the ADSP Functional Genomics Consortium (FunGen-AD). FGMB provides cis-genetic prediction models for 17,901 protein-coding genes across 36 molecular datasets, 18 contexts, and 3 regulatory modalities, comprising more than 293,000 imputable gene-level and splice-event models. These models are derived from eight sparse regression, Bayesian and multivariate prediction methods, including cross-context approaches that integrate information across tissues and cell types. We applied FGMB to Alzheimer's disease and identified 327 RWAS associations. Multi-context joint variant-gene fine-mapping then resolved 86 gene-molecular-trait pairs as regulatory signals rather than linkage disequilibrium (LD) hitchhiking.