Abstract Background and Aims Metabolomics is employed frequently in clinical research with the aim of identifying disease-related mechanisms, biomarkers, and druggable targets. This technique is also used increasingly to obtain molecular evidence of chemical exposures, including dietary (e.g. caffeine, ethanol), lifestyle (e.g. tobacco smoke, illicit drugs), and medical exposures (e.g. therapeutic drugs). The latter opportunity recently led to the development of the subfield of ‘pharmacometabolomics’ that aims to yield insights into real-world patterns of drug metabolism, which may not always be in agreement with published (consensus) metabolic patterns. These insights are particularly relevant for drugs having narrow therapeutic windows, such as immunosuppressive drugs, and could contribute to more personalized evaluations of drug efficacy and safety. In this work, we applied pharmacometabolomics to study the real-world metabolism of the immunosuppressive drugs azathioprine and mycophenolate mofetil in kidney transplant recipients (KTR). In addition, we used the same data to obtain molecular evidence for the use of various prescribed, contraindicated, and illicit drugs. Method Untargeted ‘SWATH’ pharmacometabolomics was applied to 24-hour urine samples of 1258 kidney transplant recipients included in the TransplantLines Food and Nutrition Biobank and Cohort Study (NCT02811835) and the TransplantLines Biobank and Cohort Study (NCT03272841). Corresponding data were evaluated in order to assess whether observed metabolite profiles of azathioprine and mycophenolate mofetil are in agreement with consensus metabolic patterns. In addition, data were evaluated to validate self-reported drug use and to detect illicit (e.g. cocaine) and contraindicated drugs (e.g. NSAIDs after kidney transplantation). Results We unveiled disagreements between the consensus and real-world metabolism of both azathioprine and mycophenolate mofetil by discovering previously unreported drug metabolites. Importantly, our data suggest that considerable portions of these two prodrugs are not converted to their active forms. Based on several therapeutic drug classes, we furthermore demonstrated the capability of pharmacometabolomics to validate self-reported drug use, with both data sources being in good agreement (Cohen's kappa ≥0.90). Pharmacometabolomics also proved to be useful in the study of underreported exposures, as we identified cocaine and varying cocaine adulterants in the urine of 5 (0.4%) KTR. Moreover, we found NSAIDs in the urine of 49 (4%) KTR, for which the latter drugs are contraindicated. Conclusion Our work provides new insights into the metabolic fate of azathioprine and mycophenolate mofetil. Notably, we found the parent prodrugs as well as multiple nonactivated drug metabolites which warrant further investigations to rule out potential underdosing, as is associated with an increased risk of graft failure and morbidity. In addition, we could use the same data to obtain molecular evidence of prescribed, contraindicated, and illicit drugs, as are frequently studied using data retrieved through anamnesis and questionnaires. This application thus allows for reducing information bias in subsequent pharmacoepidemiological studies. Furthermore, it may have a signaling function for certain risky lifestyle habits and for inappropriate drug use.
Read full abstract