Prioritization of therapeutic targets for dyslipidemia using integrative multi-omics and multi-trait analysis

Min Seo Kim, Minku Song, Beomsu Kim, Injeong Shim, Dan Say Kim, Pradeep Natarajan, Ron Do, Hong Hee Won

Research output: Contribution to journalArticlepeer-review


Drug targets with genetic support are several-fold more likely to succeed in clinical trials. We introduce a genetic-driven approach based on causal inferences that can inform drug target prioritization, repurposing, and adverse effects of using lipid-lowering agents. Given that a multi-trait approach increases the power to detect meaningful variants/genes, we conduct multi-omics and multi-trait analyses, followed by network connectivity investigations, and prioritize 30 potential therapeutic targets for dyslipidemia, including SORT1, PSRC1, CELSR2, PCSK9, HMGCR, APOB, GRN, HFE2, FJX1, C1QTNF1, and SLC5A8. 20% (6/30) of prioritized targets from our hypothesis-free drug target search are either approved or under investigation for dyslipidemia. The prioritized targets are 22-fold higher in likelihood of being approved or under investigation in clinical trials than genome-wide association study (GWAS)-curated targets. Our results demonstrate that the genetic-driven approach used in this study is a promising strategy for prioritizing targets while informing about the potential adverse effects and repurposing opportunities.

Original languageEnglish
Article number101112
JournalCell Reports Medicine
Issue number9
StatePublished - 19 Sep 2023


  • Mendelian randomization
  • PRS
  • PheWAS
  • dyslipidemia
  • eQTL
  • multi-omics
  • pQTL
  • plasma lipids
  • therapeutic targets


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