A1 Refereed original research article in a scientific journal
A resource to empirically establish drug exposure records directly from untargeted metabolomics data
Authors: Zhao, Haoqi Nina; Kvitne, Kine Eide; Brungs, Corinna; Mohan, Siddharth; Charron-Lamoureux, Vincent; Bittremieux, Wout; Tang, Runbang; Schmid, Robin; Lamichhane, Santosh; Xing, Shipei; El Abiead, Yasin; Andalibi, Mohammadsobhan S.; Mannochio-Russo, Helena; Ambre, Madison; Avalon, Nicole E.; Bryant, MacKenzie; Burnett, Lindsey A.; Caraballo-Rodríguez, Andrés Mauricio; Maya, Martin Casas; Chin, Loryn; Corominas, Lluís; Ellis, Ronald J.; Franklin, Donald; Girod, Sagan; Gomes, Paulo Wender, P.; Hansen, Lauren; Heaton, Robert K.; Iudicello, Jennifer E.; Jarmusch, Alan K.; Khatib, Lora; Letendre, Scott; Magyari, Sarolt; McDonald, Daniel; Mohanty, Ipsita; Cumsille, Andrés; Moore, David J.; Rajkumar, Prajit; Ross, Dylan H.; Sapre, Harshada; Shahneh, Mohammad Reza Zare; Gil-Solsona, Ruben; Thomas, Sydney P.; Tribelhorn, Caitlin; Tubb, Helena M.; Walker, Corinn; Wang, Crystal X.; Zemlin, Jasmine; Zuffa, Simone; Wishart, David S.; Gago-Ferrero, Pablo; Kaddurah-Daouk, Rima; Wang, Mingxun; Raffatellu, Manuela; Zengler, Karsten; Pluskal, Tomáš; Xu, Libin; Knight, Rob; Tsunoda, Shirley M.; Dorrestein, Pieter C.
Publisher: Springer Nature
Publication year: 2025
Journal: Nature Communications
Article number: 10600
Volume: 16
eISSN: 2041-1723
DOI: https://doi.org/10.1038/s41467-025-65993-5
Publication's open availability at the time of reporting: Open Access
Publication channel's open availability : Open Access publication channel
Web address : https://doi.org/10.1038/s41467-025-65993-5
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/505914742
Despite extensive efforts, extracting medication exposure information from clinical records remains challenging. To complement this approach, here we show the Global Natural Product Social Molecular Networking (GNPS) Drug Library, a tandem mass spectrometry (MS/MS) based resource designed for drug screening with untargeted metabolomics. This resource integrates MS/MS references of drugs and their metabolites/analogs with standardized vocabularies on their exposure sources, pharmacologic classes, therapeutic indications, and mechanisms of action. It enables direct analysis of drug exposure and metabolism from untargeted metabolomics data, supporting flexible summarization at multiple ontology levels to align with different research goals. We demonstrate its application by stratifying participants in a human immunodeficiency virus (HIV) cohort based on detected drug exposures. We uncover drug-associated alterations in microbiota-derived N-acyl lipids that are not captured when stratifying by self-reported medication use. Overall, GNPS Drug Library provides a scalable resource for empirical drug screening in clinical, nutritional, environmental, and other research disciplines, facilitating insights into the ecological and health consequences of drug exposures. While not intended for immediate clinical decision-making, it supports data-driven exploration of drug exposures where traditional records are limited or unreliable.
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Funding information in the publication:
This research was supported in part by the Intramural Research Program of the NIH, National Institute of Environmental Health Sciences (ZIC ES103363). H.N.Z. was supported by the National Institute of Environmental Health Sciences of the National Institutes of Health under Award Number K99ES037746. C.B. was supported by the Czech Academy of Sciences PPLZ fellowship number L200552251. V.C.L. is supported by Fonds de recherche du Québec - Santé (FRQS) Postdoctoral fellowship (335368). N.E.A was supported in part by the National Center for Complementary and Integrative Health of the NIH under award number F32AT011475. A.M.C.-R. and P.C.D. were supported by the Gordon and Betty Moore Foundation grant GBMF12120. M.R. was supported by the NIH grant R37 AI126277. T.P. was supported by the Czech Science Foundation (GA CR) grant 21-11563 M and by the European Union’s Horizon 2020 research and innovation programme under Marie Skłodowska-Curie grant agreement No. 891397. L.C., R.G.-S., and P.G.-F. were supported by the Spanish Ministry of Science (PID2022-139446OB-C21 and PID2022-139446OB-C22). L.C. acknowledges the support from the Economy and Knowledge Department of the Catalan Government through Consolidated Research Group (ICRA-TECH 2021 SGR 01283), as well as from the CERCA programme. W.B. acknowledges support by the Research Foundation–Flanders (FWO G0AHY25N).
