Integration of epidemiologic, pharmacologic, genetic and gut microbiome data in a drug–metabolite atlas
Jun Liu (Erasmus MC, University of Oxford)
Lies Lahousse (Erasmus MC, Universiteit Gent)
Michel G. Nivard (Amsterdam Public Health, Universiteit van Amsterdam)
Mariska Bot (Amsterdam Public Health, Universiteit van Amsterdam)
Lianmin Chen (University Medical Center Groningen)
Jan Bert van Klinken (Leiden University Medical Center, Universiteit van Amsterdam)
Erik Ben van den Akker (TU Delft - Pattern Recognition and Bioinformatics, Leiden University Medical Center)
Dina Vojinovic (Erasmus MC)
Yuri Milaneschi (Universiteit van Amsterdam, TU Delft - Pattern Recognition and Bioinformatics)
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Abstract
Progress in high-throughput metabolic profiling provides unprecedented opportunities to obtain insights into the effects of drugs on human metabolism. The Biobanking BioMolecular Research Infrastructure of the Netherlands has constructed an atlas of drug–metabolite associations for 87 commonly prescribed drugs and 150 clinically relevant plasma-based metabolites assessed by proton nuclear magnetic resonance. The atlas includes a meta-analysis of ten cohorts (18,873 persons) and uncovers 1,071 drug–metabolite associations after evaluation of confounders including co-treatment. We show that the effect estimates of statins on metabolites from the cross-sectional study are comparable to those from intervention and genetic observational studies. Further data integration links proton pump inhibitors to circulating metabolites, liver function, hepatic steatosis and the gut microbiome. Our atlas provides a tool for targeted experimental pharmaceutical research and clinical trials to improve drug efficacy, safety and repurposing. We provide a web-based resource for visualization of the atlas (http://bbmri.researchlumc.nl/atlas/).
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