Mendelian randomization in pharmacogenomics: The unforeseen potentials

Lubna Q. Khasawneh, Zeina N. Al-Mahayri, Bassam R. Ali

Research output: Contribution to journalReview articlepeer-review

11 Citations (Scopus)


Mendelian randomization (MR) is an epidemiological method that uses genetic variants to proxy an exposure predicting its causal association with an outcome. It occupies a valuable niche between observational studies and randomized trials. MR applications expanded lately, facilitated by the availability of big data, to include disease risk causation prediction, supporting evidence of prior observational data, identifying new drug targets, and drug repurposing. Concurrently, the last decade witnessed the growth of pharmacogenomics (PGx) research as a cornerstone in precision medicine. PGx research, conducted at discovery and implementation levels, resulted in validated PGx biomarkers and tests. Despite many clinically relevant PGx associations that could be translated into clinical applications, worldwide implementation is lagging far behind. The current review examines the intersection zones between MR and PGx research. MR can provide supporting evidence that allows generalizing PGx findings supporting its implementation. Interchangeability, PGx research can fuel MR studies with libraries of genetic variants of validated biological relevance. Furthermore, PGx and MR exhibit a synergistic relationship in drug discovery that can accelerate identifying new targets and repurposing old drugs. Interdisciplinary research applied by PGx researchers, epidemiologists with MR experience, and data scientists’ collaborations can unlock unforeseen opportunities in accelerating precision medicine acquisition.

Original languageEnglish
Article number112952
JournalBiomedicine and Pharmacotherapy
Publication statusPublished - Jun 2022


  • Electronic health records
  • Instrumental variables
  • Interdisciplinary research
  • Mendelian randomization
  • Pharmacogenomics

ASJC Scopus subject areas

  • Pharmacology


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