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Integrated genomic analysis and CRISPRi implicates EGFR in Alzheimer's disease risk

Leung, Y. Y.; Kuksa, P. P.; Carter, L.; Cifello, J.; Greenfest-Allen, E.; Valladares, O.; Boateng, L.; Laub, S.; Tulina, N.; Moura, S.; Ramirez, A.; Celis, K.; Jin, F.; Feng, R.; Wang, G.; De Jager, P.; Vance, J. M.; Wang, L.; Grant, S. F.; Schellenberg, G. D.; Chesi, A.; Wang, L.-S.

2025-06-26 genetic and genomic medicine
10.1101/2025.06.25.25328705 medRxiv
Show 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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