Integrated genomic analysis and CRISPRi implicates EGFR in Alzheimer's disease risk
Yuk Yee LeungiD, Pavel P. KuksaiD, Luke CarteriD, Jeffrey CifelloiD, Emily Greenfest‐AlleniD, Otto ValladaresiD, Louisa Boateng, Shannon LaubiD, Natalia M. TulinaiD, Sofia MouraiD, Aura María RamíreziD, Katrina Celis, Fulai JiniD, Ru FengiD, Gao T. WangiD, Philip L. De JageriD, Jeffery M. VanceiD, Liyong WangiD, Struan F.A. GrantiD, Gerard D. SchellenbergiD, Alessandra ChesiiD, Li‐San WangiD
Abstract
Genome-wide association studies (GWAS) have identified numerous loci linked to late-onset Alzheimers disease (LOAD), but the pan-brain regional effects of these loci remain largely uncharacterized. To address this, we systematically analyzed all LOAD-associated regions reported by Bellenguez et al. using the FILER functional genomics catalog across 174 datasets, including enhancers, transcription factors, and quantitative trait loci. We identified 42 candidate causal variant-effector gene pairs and assessed their impact using enhancer-promoter interaction data, variant annotations, and brain cell-type-specific gene expression. Notably, the LOAD risk allele of rs74504435 at the SEC61G locus was computationally predicted to increase EGFR expression in LOAD related cell types: microglia, astrocytes, and neurons. Functional validation using promoter-focused Capture C, ATAC-seq, and CRISPR interference in the HMC3 human microglia cell line confirmed this regulatory relationship. Our findings reveal a microglial enhancer regulating EGFR in LOAD, suggesting EGFR inhibitors as a potential therapeutic avenue for the disease.
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