OBJECTIVES: Metabolomics aims for comprehensive characterization and measurement of small molecule metabolites (<1700 Da) in complex biological matrices. This study sought to assess the current understanding and usage of metabolomics in laboratory medicine globally and evaluate the perception of its promise and future implementation. METHODS: A survey was conducted by the IFCC metabolomics working group that queried 400 professionals from 79 countries. Participants provided insights into their experience levels, knowledge, and usage of metabolomics approaches, along with detailing the applications and methodologies employed. RESULTS: Findings revealed a varying level of experience among respondents, with varying degrees of familiarity and utilization of metabolomics techniques. Targeted approaches dominated the field, particularly liquid chromatography coupled to a triple quadrupole mass spectrometer, with untargeted methods also receiving significant usage. Applications spanned clinical research, epidemiological studies, clinical diagnostics, patient monitoring, and prognostics across various medical domains, including metabolic diseases, endocrinology, oncology, cardiometabolic risk, neurodegeneration and clinical toxicology. CONCLUSIONS: Despite optimism for the future of clinical metabolomics, challenges such as technical complexity, standardization issues, and financial constraints remain significant hurdles. The study underscores the promising yet intricate landscape of metabolomics in clinical practice, emphasizing the need for continued efforts to overcome barriers and realize its full potential in patient care and precision medicine.

Department of Clinical Biochemistry University Hospital Olomouc Olomouc Czechia

Department of Clinical Chemistry CIRM University of Liège CHU de Liège Liège Belgium

Department of Laboratory Medicine Ghent University Hospital Ghent Belgium

Faculty of Medicine and Dentistry Palacký University Olomouc Olomouc Czech Republic

Lipoprotein Metabolism Laboratory Translational Vascular Medicine Branch National Heart Lung and Blood Institute National Institutes of Health Bethesda MD USA

Metabolomics Unit Faculty of Biology and Medicine University of Lausanne Lausanne Switzerland

Roche Diagnostics GmbH Penzberg Germany

Singapore Lipidomics Incubator Life Sciences Institute National University of Singapore Singapore Singapore

ULR 4483 IMPECS IMPact de l'Environnement Chimique sur la Santé humaine Univ Lille Institut Pasteur de Lille et Unité Fonctionnelle de Toxicologie CHU Lille Lille France

See more in PubMed

Wishart, DS. Advances in metabolite identification. Bioanalysis 2011;3:1769–82. https://doi.org/10.4155/bio.11.155 . PubMed DOI

Wishart, DS. Emerging applications of metabolomics in drug discovery and precision medicine. Nat Rev Drug Discov 2016;15:473–84. https://doi.org/10.1038/nrd.2016.32 . PubMed DOI

Wishart, DS. Metabolomics for investigating physiological and pathophysiological processes. Physiol Rev 2019;99:1819–75. https://doi.org/10.1152/physrev.00035.2018 . PubMed DOI

Qiu, S, Cai, Y, Yao, H, Lin, C, Xie, Y, Tang, S, et al.. Small molecule metabolites: discovery of biomarkers and therapeutic targets. Signal Transduct Targeted Ther 2023;8:132. https://doi.org/10.1038/s41392-023-01399-3 . PubMed DOI PMC

Everett, JR. Pharmacometabonomics in humans: a new tool for personalized medicine. Pharmacogenomics 2015;16:737–54. https://doi.org/10.2217/pgs.15.20 . PubMed DOI

Dastmalchi, F, Deleyrolle, LP, Karachi, A, Mitchell, DA, Rahman, M. Metabolomics monitoring of treatment response to brain tumor immunotherapy. Front Oncol 2021;11:691246. https://doi.org/10.3389/fonc.2021.691246 . PubMed DOI PMC

Li, C, Chu, S, Tan, S, Yin, X, Jiang, Y, Dai, X, et al.. Towards higher sensitivity of mass spectrometry: a perspective from the mass analyzers. Front Chem 2021;9:813359. https://doi.org/10.3389/fchem.2021.813359 . PubMed DOI PMC

Wishart, DS. Quantitative metabolomics using NMR. Trends Anal Chem 2008;27:228–37. https://doi.org/10.1016/j.trac.2007.12.001 . DOI

Huynh, K, Barlow, CK, Jayawardana, KS, Weir, JM, Mellett, NA, Cinel, M, et al.. High-throughput plasma lipidomics: detailed mapping of the associations with cardiometabolic risk factors. Cell Chem Biol 2019;26:71–84.e4. https://doi.org/10.1016/j.chembiol.2018.10.008 . PubMed DOI

Mundra, PA, Barlow, CK, Nestel, PJ, Barnes, EH, Kirby, A, Thompson, P, et al.. Large-scale plasma lipidomic profiling identifies lipids that predict cardiovascular events in secondary prevention. JCI Insight 2018;3:1–15. https://doi.org/10.1172/jci.insight.121326 . PubMed DOI PMC

Rinschen, MM, Ivanisevic, J, Giera, M, Siuzdak, G. Identification of bioactive metabolites using activity metabolomics. Nat Rev Mol Cell Biol 2019;20:353–67. https://doi.org/10.1038/s41580-019-0108-4 . PubMed DOI PMC

Baker, SA, Rutter, J. Metabolites as signalling molecules. Nat Rev Mol Cell Biol 2023;24:355–74. https://doi.org/10.1038/s41580-022-00572-w . PubMed DOI

Tippetts, TS, Holland, WL, Summers, SA. Cholesterol – the devil you know; ceramide – the devil you don’t. Trends Pharmacol Sci 2021;42:1082–95. https://doi.org/10.1016/j.tips.2021.10.001 . PubMed DOI PMC

Hilvo, M, Meikle, PJ, Pedersen, ER, Tell, GS, Dhar, I, Brenner, H, et al.. Development and validation of a ceramide- and phospholipid-based cardiovascular risk estimation score for coronary artery disease patients. Eur Heart J 2020;41:371–80. https://doi.org/10.1093/eurheartj/ehz387 . PubMed DOI

Leiherer, A, Mündlein, A, Laaksonen, R, Lääperi, M, Jylhä, A, Fraunberger, P, et al.. Comparison of recent ceramide-based coronary risk prediction scores in cardiovascular disease patients. Eur J Prev Cardiol 2022;29:947–56. https://doi.org/10.1093/eurjpc/zwab112 . PubMed DOI

Summers, SA. Could ceramides become the new cholesterol? Cell Metabol 2018;27:276–80. https://doi.org/10.1016/j.cmet.2017.12.003 . PubMed DOI

Després, JP. Predicting longevity using metabolomics: a novel tool for precision lifestyle medicine? Nat Rev Cardiol 2020;11:67–8. https://doi.org/10.1038/s41569-019-0310-2 . PubMed DOI

Clish, CB. Metabolomics: an emerging but powerful tool for precision medicine. Cold Spring Harb Mol Case Stud 2015;1:a000588. https://doi.org/10.1101/mcs.a000588 . PubMed DOI PMC

Beger, RD, Dunn, W, Schmidt, MA, Gross, SS, Kirwan, JA, Cascante, M, et al.. Metabolomics enables precision medicine: “a white paper, community perspective”. Metabolomics 2016;12:149. https://doi.org/10.1007/s11306-016-1094-6 . PubMed DOI PMC

Du, X, Yang, L, Kong, L, Sun, Y, Shen, K, Cai, Y, et al.. Metabolomics of various samples advancing biomarker discovery and pathogenesis elucidation for diabetic retinopathy. Front Endocrinol 2022;13:1037164. https://doi.org/10.3389/fendo.2022.1037164 . PubMed DOI PMC

Karagiannidis, E, Moysidis, DV, Papazoglou, AS, Panteris, E, Deda, O, Stalikas, N, et al.. Prognostic significance of metabolomic biomarkers in patients with diabetes mellitus and coronary artery disease. Cardiovasc Diabetol 2022;21:70. https://doi.org/10.1186/s12933-022-01494-9 . PubMed DOI PMC

Filla, LA, Edwards, JL. Metabolomics in diabetic complications. Mol Biosyst 2016;12:1090–105. https://doi.org/10.1039/c6mb00014b . PubMed DOI PMC

Chowdhury, S, Faheem, SM, Nawaz, SS, Siddiqui, K. The role of metabolomics in personalized medicine for diabetes. Per Med 2021;18:501–8. https://doi.org/10.2217/pme-2021-0083 . PubMed DOI

Zhang, J, Fuhrer, T, Ye, H, Kwan, B, Montemayor, D, Tumova, J, et al.. High-throughput metabolomics and diabetic kidney disease progression: evidence from the chronic renal insufficiency (CRIC) study. Am J Nephrol 2022;53:215–25. https://doi.org/10.1159/000521940 . PubMed DOI PMC

Schiffer, L, Barnard, L, Baranowski, ES, Gilligan, LC, Taylor, AE, Arlt, W, et al.. Human steroid biosynthesis, metabolism and excretion are differentially reflected by serum and urine steroid metabolomes: a comprehensive review. J Steroid Biochem Mol Biol 2019;194:105439. https://doi.org/10.1016/j.jsbmb.2019.105439 . PubMed DOI PMC

Burt, LA, Kaufmann, M, Rose, MS, Jones, G, Billington, EO, Boyd, SK, et al.. Measurements of the vitamin D metabolome in the calgary vitamin D study: relationship of vitamin D metabolites to bone loss. J Bone Miner Res 2023;38:1312–21. https://doi.org/10.1002/jbmr.4876 . PubMed DOI

Jones, G, Kaufmann, M. Diagnostic aspects of vitamin D: clinical utility of vitamin D metabolite profiling. JBMR Plus 2021;5:e10581. https://doi.org/10.1002/jbm4.10581 . PubMed DOI PMC

Janečková, H, Hron, K, Wojtowicz, P, Hlídková, E, Barešová, A, Friedecký, D, et al.. Targeted metabolomic analysis of plasma samples for the diagnosis of inherited metabolic disorders. J Chromatogr A 2012;1226:11–7. https://doi.org/10.1016/j.chroma.2011.09.074 . PubMed DOI

Piskláková, B, Friedecká, J, Ivanovová, E, Hlídková, E, Bekárek, V, Prídavok, M, et al.. Rapid and efficient LC-MS/MS diagnosis of inherited metabolic disorders: a semi-automated workflow for analysis of organic acids, acylglycines, and acylcarnitines in urine. Clin Chem Lab Med 2023;61:2017–27. https://doi.org/10.1515/cclm-2023-0084 . PubMed DOI

Ismail, IT, Showalter, MR, Fiehn, O. Inborn errors of metabolism in the era of untargeted metabolomics and lipidomics. Metabolites 2019;9:1–26. https://doi.org/10.3390/metabo9100242 . PubMed DOI PMC

Armitage, EG, Southam, AD. Monitoring cancer prognosis, diagnosis and treatment efficacy using metabolomics and lipidomics. Metabolomics 2016;12:146. https://doi.org/10.1007/s11306-016-1093-7 . PubMed DOI PMC

Qi, SA, Wu, Q, Chen, Z, Zhang, W, Zhou, Y, Mao, K, et al.. High-resolution metabolomic biomarkers for lung cancer diagnosis and prognosis. Sci Rep 2021;11:11805. https://doi.org/10.1038/s41598-021-91276-2 . PubMed DOI PMC

Danzi, F, Pacchiana, R, Mafficini, A, Scupoli, MT, Scarpa, A, Donadelli, M, et al.. To metabolomics and beyond: a technological portfolio to investigate cancer metabolism. Signal Transduct Targeted Ther 2023;8:137. https://doi.org/10.1038/s41392-023-01380-0 . PubMed DOI PMC

Newgard, CB. Metabolomics and metabolic diseases: where do we stand? Cell Metabol 2017;25:43–56. https://doi.org/10.1016/j.cmet.2016.09.018 . PubMed DOI PMC

Cheng, S, Shah, SH, Corwin, EJ, Fiehn, O, Fitzgerald, RL, Gerszten, RE, et al.. Potential impact and study considerations of metabolomics in cardiovascular health and disease: a scientific statement from the American heart association. Circ Cardiovasc Genet 2017;10:e1-13. https://doi.org/10.1161/HCG.0000000000000032 . PubMed DOI PMC

Iida, M, Harada, S, Takebayashi, T. Application of metabolomics to epidemiological studies of atherosclerosis and cardiovascular disease. J Atherosclerosis Thromb 2019;26:747–57. https://doi.org/10.5551/jat.rv17036 . PubMed DOI PMC

Nayor, M, Brown, KJ, Vasan, RS. The molecular basis of predicting atherosclerotic cardiovascular disease risk. Circ Res 2021;128:287–303. https://doi.org/10.1161/circresaha.120.315890 . PubMed DOI PMC

Tzoulaki, I, Castagné, R, Boulangé, CL, Karaman, I, Chekmeneva, E, Evangelou, E, et al.. Serum metabolic signatures of coronary and carotid atherosclerosis and subsequent cardiovascular disease. Eur Heart J 2019;40:2883–96. https://doi.org/10.1093/eurheartj/ehz235 . PubMed DOI PMC

Laaksonen, R, Ekroos, K, Sysi-Aho, M, Hilvo, M, Vihervaara, T, Kauhanen, D, et al.. Plasma ceramides predict cardiovascular death in patients with stable coronary artery disease and acute coronary syndromes beyond LDL-cholesterol. Eur Heart J 2016;37:1967–76. https://doi.org/10.1093/eurheartj/ehw148 . PubMed DOI PMC

Ramos, P, Meeusen, JW. Ceramide risk scores can bring lipidomics to clinical medicine. Clin Chem 2022;68:1479–80. https://doi.org/10.1093/clinchem/hvac169 . PubMed DOI

Vogeser, M, Bendt, AK. From research cohorts to the patient – a role for “omics” in diagnostics and laboratory medicine? Clin Chem Lab Med 2023;61:974–80. https://doi.org/10.1515/cclm-2022-1147 . PubMed DOI

Szeremeta, M, Pietrowska, K, Niemcunowicz-Janica, A, Kretowski, A, Ciborowski, M. Applications of metabolomics in forensic toxicology and forensic medicine. Int J Mol Sci 2021;22:1–16. https://doi.org/10.3390/ijms22063010 . PubMed DOI PMC

Olesti, E, De Toma, I, Ramaekers, JG, Brunt, TM, Carbó, ML, Fernández-Avilés, C, et al.. Metabolomics predicts the pharmacological profile of new psychoactive substances. J Psychopharmacol 2019;33:347–54. https://doi.org/10.1177/0269881118812103 . PubMed DOI

Steuer, AE, Raeber, J, Simbuerger, F, Dornbierer, DA, Bosch, OG, Quednow, BB, et al.. Towards extending the detection window of gamma-hydroxybutyric acid-an untargeted metabolomics study in serum and urine following controlled administration in healthy men. Metabolites 2021;11:1–16. https://doi.org/10.3390/metabo11030166 . PubMed DOI PMC

Steuer, AE, Brockbals, L, Kraemer, T. Metabolomic strategies in biomarker research-new approach for indirect identification of drug consumption and sample manipulation in clinical and forensic toxicology? Front Chem 2019;7:319. https://doi.org/10.3389/fchem.2019.00319 . PubMed DOI PMC

Castillo-Peinado, LS, Luque de Castro, MD. Present and foreseeable future of metabolomics in forensic analysis. Anal Chim Acta 2016;925:1–15. https://doi.org/10.1016/j.aca.2016.04.040 . PubMed DOI

Locci, E, Bazzano, G, Chighine, A, Locco, F, Ferraro, E, Demontis, R, et al.. Forensic NMR metabolomics: one more arrow in the quiver. Metabolomics 2020;16:118. https://doi.org/10.1007/s11306-020-01743-6 . PubMed DOI PMC

Chighine, A, Porcu, M, Ferino, G, Lenigno, N, Trignano, C, d’Aloja, E, et al.. Infant urinary metabolomic profile in a fatal acute methadone intoxication. Int J Leg Med 2022;136:569–75. https://doi.org/10.1007/s00414-021-02772-z . PubMed DOI PMC

Mosley, JD, Schock, TB, Beecher, CW, Dunn, WB, Kuligowski, J, Lewis, MR, et al.. Establishing a framework for best practices for quality assurance and quality control in untargeted metabolomics. Metabolomics 2024;20:1–13. https://doi.org/10.1007/s11306-023-02080-0 . PubMed DOI PMC

Broeckling, CD, Beger, RD, Cheng, LL, Cumeras, R, Cuthbertson, DJ, Dasari, S, et al.. Current practices in LC-MS untargeted metabolomics: a scoping review on the use of pooled quality control samples. Anal Chem 2023;95:18645–54. https://doi.org/10.1021/acs.analchem.3c02924 . PubMed DOI PMC

Lippa, KA, Aristizabal-Henao, JJ, Beger, RD, Bowden, JA, Broeckling, C, Beecher, C, et al.. Reference materials for MS-based untargeted metabolomics and lipidomics: a review by the metabolomics quality assurance and quality control consortium (mQACC). Metabolomics 2022;18:1–29. https://doi.org/10.1007/s11306-021-01848-6 . PubMed DOI PMC