Interpretable deep learning translation of GWAS and multi-omics findings to identify pathobiology and drug repurposing in Alzheimer's disease

Jielin Xu, Chengsheng Mao, Yuan Hou, Yuan Luo, Jessica L. Binder, Yadi Zhou, Lynn M. Bekris, Jiyoung Shin, Ming Hu, Fei Wang, Charis Eng, Tudor I. Oprea, Margaret E. Flanagan, Andrew A. Pieper, Jeffrey Cummings, James B. Leverenz, Feixiong Cheng*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Translating human genetic findings (genome-wide association studies [GWAS]) to pathobiology and therapeutic discovery remains a major challenge for Alzheimer's disease (AD). We present a network topology-based deep learning framework to identify disease-associated genes (NETTAG). We leverage non-coding GWAS loci effects on quantitative trait loci, enhancers and CpG islands, promoter regions, open chromatin, and promoter flanking regions under the protein-protein interactome. Via NETTAG, we identified 156 AD-risk genes enriched in druggable targets. Combining network-based prediction and retrospective case-control observations with 10 million individuals, we identified that usage of four drugs (ibuprofen, gemfibrozil, cholecalciferol, and ceftriaxone) is associated with reduced likelihood of AD incidence. Gemfibrozil (an approved lipid regulator) is significantly associated with 43% reduced risk of AD compared with simvastatin using an active-comparator design (95% confidence interval 0.51–0.63, p < 0.0001). In summary, NETTAG offers a deep learning methodology that utilizes GWAS and multi-genomic findings to identify pathobiology and drug repurposing in AD.

Original languageEnglish (US)
Article number111717
JournalCell reports
Volume41
Issue number9
DOIs
StatePublished - Nov 29 2022

Keywords

  • AD
  • Alzheimer's disease
  • CP: Neuroscience
  • EHR
  • GWAS
  • deep learning
  • drug repurposing
  • drug target
  • electronic health record
  • gemfibrozil
  • genome-wide association studies
  • multi-omics
  • pathobiology
  • protein-protein Interactome

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)

Fingerprint

Dive into the research topics of 'Interpretable deep learning translation of GWAS and multi-omics findings to identify pathobiology and drug repurposing in Alzheimer's disease'. Together they form a unique fingerprint.

Cite this