A resource to empirically establish drug exposure records directly from untargeted metabolomics data
Jazyk angličtina Země Velká Británie, Anglie Médium electronic
Typ dokumentu časopisecké články
Grantová podpora
P50 HD106463
NICHD NIH HHS - United States
ZIC ES103363
Intramural NIH HHS - United States
K99 ES037746
NIEHS NIH HHS - United States
U19 AG063744
NIA NIH HHS - United States
R01 DK136117
NIDDK NIH HHS - United States
P30 MH062512
NIMH NIH HHS - United States
R37 AI126277
NIAID NIH HHS - United States
F32 AT011475
NCCIH NIH HHS - United States
U24 DK133658
NIDDK NIH HHS - United States
PubMed
41366203
PubMed Central
PMC12689629
DOI
10.1038/s41467-025-65993-5
PII: 10.1038/s41467-025-65993-5
Knihovny.cz E-zdroje
- MeSH
- HIV infekce farmakoterapie metabolismus MeSH
- lidé MeSH
- metabolomika * metody MeSH
- tandemová hmotnostní spektrometrie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
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.
Biological Sciences Division Pacific Northwest National Laboratory Richland WA USA
Catalan Institute for Water Research Girona Spain
Center for Microbiome Innovation University of California San Diego La Jolla CA USA
Chiba University UC San Diego Center for Mucosal Immunology Allergy and Vaccines La Jolla CA USA
Collaborative Mass Spectrometry Innovation Center University of California San Diego La Jolla CA USA
Department of Bioengineering University of California San Diego La Jolla California USA
Department of Biological Sciences University of Alberta Edmonton AB Canada
Department of Computer Science and Engineering University of California Riverside Riverside CA USA
Department of Computer Science and Engineering University of California San Diego La Jolla CA USA
Department of Computer Science University of Antwerp Antwerp Belgium
Department of Computing Science University of Alberta Edmonton AB Canada
Department of Medicinal Chemistry University of Washington Seattle WA USA
Department of Medicine Duke University Durham NC USA
Department of Medicine University of California San Diego La Jolla CA USA
Department of Neurosciences University of California San Diego La Jolla CA USA
Department of Pediatrics University of California San Diego La Jolla CA USA
Department of Pharmaceutical Sciences University of Vienna Vienna Austria
Department of Pharmacy University of Oslo Oslo Norway
Department of Plant Pathology University of Wisconsin Madison Madison WI USA
Department of Psychiatry and Behavioral Sciences Duke University Durham NC USA
Department of Psychiatry University of California San Diego La Jolla CA USA
Duke Institute of Brain Sciences Duke University Durham NC USA
Faculty of Chemistry Federal University of Pará Belém PA Brazil
Halıcıoğlu Data Science Institute University of California San Diego La Jolla CA USA
HIV Neurobehavioral Research Program University of California San Diego La Jolla CA USA
Institute of Microbiology Eidgenössische Technische Hochschule Zürich Zürich Switzerland
Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences Prague Czechia
Program in Materials Science and Engineering University of California San Diego La Jolla CA USA
Scripps Institution of Oceanography University of California San Diego La Jolla CA USA
Shu Chien Gene Lay Department of Bioengineering University of California San Diego La Jolla CA USA
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