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<p>Genome-wide association studies (GWAS) have identified numerous loci linked to late-onset Alzheimer’s 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 41 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 <i>SEC61G</i> locus was computationally predicted to increase <i>EGFR</i> 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 <i>EGFR</i> in LOAD, suggesting <i>EGFR</i> inhibitors as a potential therapeutic avenue for the disease.</p>

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

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月16日

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  • Yuk Yee Leung,
  • Pavel P. Kuksa,
  • Luke Carter,
  • Jeffrey Cifello,
  • Emily Greenfest-Allen,
  • Otto Valladares,
  • Louisa Boateng,
  • Shannon Laub,
  • Natalia Tulina,
  • Sofia Moura,
  • Aura Ramirez,
  • Katrina Celis,
  • Fulai Jin,
  • Ru Feng,
  • Gao Wang,
  • Phil De Jager,
  • Jeffery M. Vance,
  • Liyong Wang,
  • Struan F. A. Grant,
  • Gerard D. Schellenberg,
  • Alessandra Chesi,
  • Li-San Wang

摘要

Genome-wide association studies (GWAS) have identified numerous loci linked to late-onset Alzheimer’s 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 41 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.