Transcriptomics-based network medicine approach identifies metformin as a repurposable drug for atrial fibrillation

Jessica C. Lal, Chengsheng Mao, Yadi Zhou, Shamone R. Gore-Panter, Julie H. Rennison, Beth S. Lovano, Laurie Castel, Jiyoung Shin, A. Marc Gillinov, Jonathan D. Smith, John Barnard, David R. Van Wagoner, Yuan Luo*, Feixiong Cheng, Mina K. Chung*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

Effective drugs for atrial fibrillation (AF) are lacking, resulting in significant morbidity and mortality. This study demonstrates that network proximity analysis of differentially expressed genes from atrial tissue to drug targets can help prioritize repurposed drugs for AF. Using enrichment analysis of drug-gene signatures and functional testing in human inducible pluripotent stem cell (iPSC)-derived atrial-like cardiomyocytes, we identify metformin as a top repurposed drug candidate for AF. Using the active compactor, a new design analysis of large-scale longitudinal electronic health record (EHR) data, we determine that metformin use is significantly associated with a reduced risk of AF (odds ratio = 0.48, 95%, confidence interval [CI] 0.36–0.64, p < 0.001) compared with standard treatments for diabetes. This study utilizes network medicine methodologies to identify repurposed drugs for AF treatment and identifies metformin as a candidate drug.

Original languageEnglish (US)
Article number100749
JournalCell Reports Medicine
Volume3
Issue number10
DOIs
StatePublished - Oct 18 2022

Keywords

  • EHR
  • atrial fibrillation
  • drug repurposing
  • electronic health record
  • human inducible pluripotent stem cells
  • network medicine
  • pharmacoepidemiology
  • systems biology

ASJC Scopus subject areas

  • General Biochemistry, Genetics and Molecular Biology

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