Retrospective Urine Metabolomics of Clinical Toxicology Samples Reveals Features Associated With Cocaine Exposure

Background: /Objectives: Cocaine is a widely used illicit stimulant with significant toxic effects. Despite its clinical relevance, the broader metabolic alterations associated with co-caine use remain incompletely characterized. This study aims to identify novel bi-omarkers for cocaine exposure by applying untargeted metabolomics to retrospective urine drug screening data. Methods: We conducted a retrospective analysis of raw mass spectrometry (MS) dataset from urine comprehensive drug screening (UCDS) from 363 pa-tients at the University of Pittsburgh Medical Center Clinical Toxicology Laboratory. The liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-qToF-MS) data were preprocessed with MS-DIAL and subjected to multiple statistical analyses to identify features significantly associated with cocaine-enzyme immunoassay (EIA) results. Signif-icant features were further evaluated using MS-FINDER for feature annotation. Results: Out of 14,883 features, 262 were significantly associated with cocaine EIA results. A subset of 37 more significant features, including known cocaine metabolites and impurities, nic-otine metabolites, norfentanyl, and tryptophan-related metabolite (3-hydroxy-tryptophan) were annotated. Cluster analysis revealed co-varying features, including parent com-pounds, metabolites, and related ion species. Conclusions: Features associated with co-caine exposure, including previously underrecognized cocaine metabolites and impuri-ties, co-exposure markers and alterations in endogenous metabolic pathway, were identi-fied. Notably, norfentanyl was found to be significantly associated with cocaine-EIA, re-flecting current trends in illicit drug use. This study demonstrates the potential of repur-posing real-world clinical toxicology data for biomarker discovery, offering a valuable ap-proach to identifying exposure biomarkers and expanding our understanding of drug-induced metabolic disturbances in clinical toxicology. Further validation and ex-ploration using complementary analytical platforms are warranted.