Cited by 14Metabolomics and Mass Spectrometry StudiesHealth, Environment, Cognitive AgingForensic Toxicology and Drug Analysis

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Metabolomics data complemented drug use information in epidemiological databases: pilot study of potential kidney donors

Open access
Klont, Frank, Kremer, Daan, Gomes Neto, Antonio W., Berger, Stefan P., Touw, Daan J., Hak, Eelko, Bonner, Ron, Bakker, Stephan J.L., Hopfgartner, Gérard·2021·Journal of Clinical Epidemiology

Abstract

OBJECTIVE: The objective of this study was to investigate whether clinical metabolomics, which is increasingly applied in population-based and epidemiological studies, can be used to provide analytical evidence of exposures, and whether such information can be useful to strengthen and/or complement corresponding clinical database entries, taking drug use as an example. STUDY DESIGN AND SETTING: Liquid chromatography-mass spectrometry (LC-MS) metabolomics analyses were performed on urine from 100 randomly-selected control subjects (50% females) from the TransplantLines Food and Nutrition Biobank and Cohort Study (NCT identifier 'NCT02811835'), and drugs were identified through spectral library searching and targeted signal extraction. RESULTS: In 83 subjects for whom drug use information was available, 22 expected and 26 unexpected prescription-only drugs were identified, while 28 expected prescription-only drugs remained undetected. In addition, 7 prescription-only drugs were found in 17 subjects for whom drug use information was unavailable, and 58 over-the-counter drugs were identified in all 100 subjects. CONCLUSION: Molecular evidence for many drugs could be retrieved from LC-MS metabolomics data, which could be useful to complement and strengthen epidemiological databases given that considerable discrepancies were found between analytically-identified drugs and drugs listed in the available clinical database.

Overview

Integrity signals

Registry

Crossref · 10.1016/j.jclinepi.2021.02.008

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 29

  1. Williams, 1998, Epidemiological issues in health needs assessment, BMJ, 316, 1379, 10.1136/bmj.316.7141.1379 · DOI
  2. Pearce, 1996, Traditional epidemiology, modern epidemiology, and public health, Am J Public Health, 86, 678, 10.2105/AJPH.86.5.678 · DOI · Paper page
  3. Coughlin, 2014, Toward a road map for global -omics: a primer on -omic technologies, Am J Epidemiol, 180, 1188, 10.1093/aje/kwu262 · DOI
  4. Everson, 2018, Integrating -Omics Approaches into Human Population-Based Studies of Prenatal and Early-Life Exposures, Curr Environ Health Rep, 5, 328, 10.1007/s40572-018-0204-1 · DOI
  5. Dehghan, 2016, Mass spectrometry in epidemiological studies: What are the key considerations?, Eur J Epidemiol, 31, 715, 10.1007/s10654-016-0195-x · DOI
  6. Rattray, 2018, Beyond genomics: understanding exposotypes through metabolomics, Hum Genomics, 12, 4, 10.1186/s40246-018-0134-x · DOI
  7. Wishart, 2016, Emerging applications of metabolomics in drug discovery and precision medicine, Nat Rev Drug Discov, 15, 473, 10.1038/nrd.2016.32 · DOI
  8. Klont, 2020, SWATH data independent acquisition mass spectrometry for screening of xenobiotics in biological fluids: Opportunities and challenges for data processing, Talanta, 211, 10.1016/j.talanta.2020.120747 · DOI
  9. Prince, 2008, A comparison of direct versus self-report measures for assessing physical activity in adults: a systematic review, Int J Behav Nutr Phys Act, 5, 56, 10.1186/1479-5868-5-56 · DOI · Paper page
  10. Altmaier, 2011, Questionnaire-based self-reported nutrition habits associate with serum metabolism as revealed by quantitative targeted metabolomics, Eur J Epidemiol, 26, 145, 10.1007/s10654-010-9524-7 · DOI · Paper page
  11. van den Berg, 2014, Urinary sulfur metabolites associate with a favorable cardiovascular risk profile and survival benefit in renal transplant recipients, J Am Soc Nephrol, 25, 1303, 10.1681/ASN.2013050497 · DOI
  12. Broadhurst, 2018, Guidelines and considerations for the use of system suitability and quality control samples in mass spectrometry assays applied in untargeted clinical metabolomic studies, Metabolomics, 14, 72, 10.1007/s11306-018-1367-3 · DOI
  13. Sumner, 2007, Proposed minimum reporting standards for chemical analysis Chemical Analysis Working Group (CAWG) Metabolomics Standards Initiative (MSI), Metabolomics., 3, 211, 10.1007/s11306-007-0082-2 · DOI · Paper page
  14. Tsugawa, 2015, MS-DIAL: data-independent MS/MS deconvolution for comprehensive metabolome analysis, Nat Methods, 12, 523, 10.1038/nmeth.3393 · DOI
  15. Schachter, 2005, Chemical, pharmacokinetic and pharmacodynamic properties of statins: an update, Fundam Clin Pharmacol, 19, 117, 10.1111/j.1472-8206.2004.00299.x · DOI
  16. Park, 2017, Effects of CYP2C19 Genetic Polymorphisms on PK/PD Responses of Omeprazole in Korean Healthy Volunteers, J Korean Med Sci, 32, 729, 10.3346/jkms.2017.32.5.729 · DOI
  17. Nakai, 1994, Determination of a new H+—K+ ATPase inhibitor (E3810) and its four metabolites in human plasma by high-performance liquid chromatography, Journal of Chromatography B: Biomedical Sciences and Applications, 660, 211, 10.1016/0378-4347(94)00270-3 · DOI
  18. Renwick, 1988, The pharmacokinetics of oral nifedipine–a population study, Br J Clin Pharmacol, 25, 701, 10.1111/j.1365-2125.1988.tb05256.x · DOI
  19. Laporte, 2004, Upper gastrointestinal bleeding associated with the use of NSAIDs: newer versus older agents, Drug Saf, 27, 411, 10.2165/00002018-200427060-00005 · DOI
  20. Sediq, 2018, Concordance assessment of self-reported medication use in the Netherlands three-generation Lifelines Cohort study with the pharmacy database iaDB.nl: The PharmLines initiative, Clin Epidemiol, 10, 981, 10.2147/CLEP.S163037 · DOI
  21. Mathews, 2018, Prohibited Contaminants in Dietary Supplements, Sports Health, 10, 19, 10.1177/1941738117727736 · DOI
  22. Touw, 1997, Clinical implications of genetic polymorphisms and drug interactions mediated by Cytochrome P-450 enzymes, Drug Metabol Drug Interact, 14, 55
  23. Hare, 2003, Dietary salicylates, J Clin Pathol, 56, 649, 10.1136/jcp.56.9.649 · DOI
  24. Favaloro, 2011, Laboratory testing of anticoagulants: the present and the future, Pathology, 43, 682, 10.1097/PAT.0b013e32834bf5f4 · DOI
  25. Zhang, 2009, Mass defect filter technique and its applications to drug metabolite identification by high-resolution mass spectrometry, J Mass Spectrom, 44, 999, 10.1002/jms.1610 · DOI
  26. Scheubert, 2017, Significance estimation for large scale metabolomics annotations by spectral matching, Nat Commun, 8, 1494, 10.1038/s41467-017-01318-5 · DOI
  27. van Tilborgh-de Jong, 2015, Presence of medication taken by blood donors in plasma for transfusion, Vox Sang, 108, 323, 10.1111/vox.12230 · DOI
  28. Bi, 2020, The key points in the pre-analytical procedures of blood and urine samples in metabolomics studies, Metabolomics, 16, 68, 10.1007/s11306-020-01666-2 · DOI
  29. Li, 2018, Comprehensive evaluation of untargeted metabolomics data processing software in feature detection, quantification and discriminating marker selection, Anal Chim Acta, 1029, 50, 10.1016/j.aca.2018.05.001 · DOI

Cited by

Sorted by citations

Metadata

Authors
Klont, F., Kremer, D., Gomes Neto, A. W., Berger, S. P., Touw, D. J., Hak, E., Bonner, R., Bakker, S. J. L., & Hopfgartner, G.
Affiliations
  • University of Geneva (CH)
  • University Medical Center Groningen (NL)
  • University of Groningen (NL)
Venue
Journal of Clinical Epidemiology
Publisher
Elsevier BV
Published
2021-07
Volume
135
Pages
10-16
ISSN
0895-4356 (ISSN-L)
OpenAlex
W3128098604
Cited by
14
References
2
Citations by year
2026: 1 · 2025: 2 · 2024: 3 · 2022: 5 · 2021: 3
FWCI
0.86
Type
journal article
Language
en
Open access
Locations
  • Journal of Clinical Epidemiology (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Archive ouverte UNIGE (University of Geneva) (publishedVersion, other-oa)
  • University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, cc-by)
  • Archive ouverte UNIGE (University of Geneva) (submittedVersion, cc-by)
Funders
Horizon 2020 Marie Skłodowska-Curie Actions
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
  • Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Health, Environment, Cognitive Aging
  • Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Toxicology › Forensic Toxicology and Drug Analysis
Keywords
clinical metabolomics, drug use, prescription drugs, over-the-counter drugs, urinary metabolites, kidney donors, kidney transplantation, exposure assessment
MeSH terms
Data Management, Pharmaceutical Preparations, Female, Humans, Male, Middle Aged, Pilot Projects, Tissue Donors, Kidney Transplantation, Databases, Factual, Metabolomics

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review