Open AccessIndividual variability in human urinary metabolites identifies age‐related, body mass index‐related, and sex‐related biomarkers
Author(s) -
Wang Tianling,
Tang Lei,
Lin Ruili,
He Dian,
Wu Yanqing,
Zhang Yang,
Yang Pingrong,
He Junquan
Publication year - 2021
Publication title -
molecular genetics and genomic medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.765
H-Index - 29
ISSN - 2324-9269
DOI - 10.1002/mgg3.1738
Subject(s) - metabolomics , body mass index , urine , physiology , metabolome , dehydroepiandrosterone , metabolite , endocrinology , dehydroepiandrosterone sulfate , medicine , biology , bioinformatics , hormone , androgen
Abstract Background Metabolites present in human urine can be influenced by individual physiological parameters (e.g., body mass index [BMI], age, and sex). Observation of altered metabolites concentrations could provide insight into underlying disease pathology, disease prognosis and diagnosis, and facilitate discovery of novel biomarkers. Methods Quantitative metabolomics analysis in the urine of 183 healthy individuals was performed based on high‐resolution liquid chromatography–mass spectrometry (LC–MS). Coefficients of variation were obtained for 109 urine metabolites of all the 183 human healthy subjects. Results Three urine metabolites (such as dehydroepiandrosterone sulfate, acetaminophen glucuronide, and p ‐anisic acid) with CV 183 > 0.3, for which metabolomics studies have been scarce, are considered highly variable here. We identified 30 age‐related metabolites, 18 BMI‐related metabolites, and 42 sex‐related metabolites. Among the identified metabolites, three metabolites were found to be associated with all three physiological parameters (age, BMI, and sex), which included dehydroepiandrosterone sulfate, 3‐methylcrotonylglycine and N ‐acetyl‐aspartic acid. Pearson's coefficients demonstrated that some age‐, BMI‐, and sex‐related compounds are strongly correlated, suggesting that age, BMI, and sex could affect them concomitantly. Conclusion Metabolic differences between distinct physiological statuses were found to be related to several metabolic pathways (such as the caffeine metabolism, the amino acid metabolism, and the carbohydrate metabolism), and these findings may be key for the discovery of new diagnostics and treatments as well as new understandings on the mechanisms of some related diseases.