A Tutorial on Using Untargeted Metabolomics Data of Human Excreta to Investigate Drug Excretion and Wastewater Entry
Abstract
1. Introduction
2. Materials and Methods
2.1. Untargeted LC-MS Profiling Data
2.2. Drug Metabolite Identification
2.2.1. Defining the Exposure Status
2.2.2. Identification of Drug Use-Associated Features
2.2.3. Initial Feature Filtering
2.2.4. Manual Feature Filtering
2.2.5. Putative Metabolite Identification
3. Results
3.1. Feature Prioritization–Hydrochlorothiazide
3.2. Feature Prioritization–Furosemide
3.3. Metabolite Identification
3.3.1. Hydrochlorothiazide
3.3.2. Furosemide
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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| Kidney Transplant Recipients | Potential Living Kidney Donors | |||||||
|---|---|---|---|---|---|---|---|---|
| Drug | m/z | RT (min) | Rel. Mean a (%) | p Value | m/z | RT (min) | Rel. Mean a (%) | p Value |
| hydrochlorothiazide | 283.957 | 3.2 | 14 | 8.6 × 10−137 | 283.957 | 3.1 | 10 | 1.2 × 10−60 |
| 293.941 | 3.2 | 26 | 1.7 × 10−142 | 293.942 | 3.2 | 8 | 8.2 × 10−26 | |
| 295.957 b | 3.6 | 100 a | 1.1 × 10−200 | 295.957 b | 3.6 | 100 a | 2.9 × 10−84 | |
| furosemide | 329.000 c | 7.1 | 100 a | 1.4 × 10−165 | 329.001 c | 7.1 | 100 a | 9.3 × 10−146 |
| 505.032 | 6.7 | 45 | 7.3 × 10−121 | 505.032 | 6.8 | 20 | 5.3 × 10−117 | |
| Kidney Transplant Recipients (N = 106) | Potential Living Kidney Donors (N = 13) | |||||||
|---|---|---|---|---|---|---|---|---|
| Identity | Molecular Formula | m/z | Median (%) | IQR (%) | Range (%) | Median (%) | IQR (%) | Range (%) |
| salamide | C6H8ClN3O4S2 | 283.957 | 10.5 | 7.7–13.0 | 4.5–23.7 | 9.7 | 7.6–10.6 | 2.3–13.9 |
| chlorothiazide | C7H6ClN3O4S2 | 293.941 | 14.1 | 9.6–22.3 | 2.0–66.3 | 4.9 | 3.0–7.2 | 2.0–19.0 |
| hydrochlorothiazide | C7H8ClN3O4S2 | 295.957 | 74.0 | 66.3–81.3 | 28.2–91.8 | 85.5 | 82.6–88.2 | 71.3–92.8 |
| Kidney Transplant Recipients (N = 162) | Potential Living Kidney Donors (N = 32) | |||||||
|---|---|---|---|---|---|---|---|---|
| (Putative) Identity | Molecular Formula | m/z | Median (%) | IQR (%) | Range (%) | Median (%) | IQR (%) | Range (%) |
| furosemide | C12H11ClN2O5S | 329.000 | 77.2 | 70.6–83.7 | 43.4–99.7 | 88.0 | 85.0–90.2 | 79.8–96.4 |
| furosemide glucuronide | C18H19ClN2O11S | 505.032 | 22.8 | 16.3–29.4 | 0.3–56.6 | 12.0 | 9.8–15.0 | 3.6–20.2 |
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Han, S.; Hof, M.A.J.; Bakker, S.J.L.; Hopfgartner, G.; Hak, E.; Klont, F. A Tutorial on Using Untargeted Metabolomics Data of Human Excreta to Investigate Drug Excretion and Wastewater Entry. Environments 2026, 13, 179. https://doi.org/10.3390/environments13040179
Han S, Hof MAJ, Bakker SJL, Hopfgartner G, Hak E, Klont F. A Tutorial on Using Untargeted Metabolomics Data of Human Excreta to Investigate Drug Excretion and Wastewater Entry. Environments. 2026; 13(4):179. https://doi.org/10.3390/environments13040179
Chicago/Turabian StyleHan, Shihang, Marieke A. J. Hof, Stephan J. L. Bakker, Gérard Hopfgartner, Eelko Hak, and Frank Klont. 2026. "A Tutorial on Using Untargeted Metabolomics Data of Human Excreta to Investigate Drug Excretion and Wastewater Entry" Environments 13, no. 4: 179. https://doi.org/10.3390/environments13040179
APA StyleHan, S., Hof, M. A. J., Bakker, S. J. L., Hopfgartner, G., Hak, E., & Klont, F. (2026). A Tutorial on Using Untargeted Metabolomics Data of Human Excreta to Investigate Drug Excretion and Wastewater Entry. Environments, 13(4), 179. https://doi.org/10.3390/environments13040179

