¹H NMR metabolomics study of age profiling in children

Abstract

Metabolic profiling of urine provides a fingerprint of personalized endogenous metabolite markers that correlate to a number of factors such as gender, disease, diet, toxicity, medication, and age. It is important to study these factors individually, if possible to unravel their unique contributions. In this study, age-related metabolic changes in children of age 12 years and below were analyzed by 1H NMR spectroscopy of urine. The effect of age on the urinary metabolite profile was observed as a distinct age-dependent clustering even from the unsupervised principal component analysis. Further analysis, using partial least squares with orthogonal signal correction regression with respect to age, resulted in the identification of an age-related metabolic profile. Metabolites that correlated with age included creatinine, creatine, glycine, betaine/TMAO, citrate, succinate, and acetone. Although creatinine increased with age, all the other metabolites decreased. These results may be potentially useful in assessing the biological age (as opposed to chronological) of young humans as well as in providing a deeper understanding of the confounding factors in the application of metabolomics.

Detection of an Endogenous Urinary Biomarker Associated With Cyp2D6 Activity Using Global Metabolomics

“…Creatinine was used to normalize for urine concentrations in our study, and urinary creatinine concentrations were not significantly correlated with log M1 in any dataset except for the spot urine samples of the training set (p = 0.01). Urinary creatinine concentrations have been reported to change with age, [49] and a significant association between creatinine concentrations and age was observed in the training set (p = 0.036 and < 0.0001 in the spot and timed urine collections, respectively) but not in the validation set. Admittedly, creatinine concentrations may influence the interpretation of the data in the training set, but it does not appear to be an important confounder in the validation set.…”

Human samples for health assessments

“…The results suggested that the concentrations of amino acids, citric acid cycle intermediates, and urea cycle intermediates and purine metabolites increased with age, whereas the plasma levels of fatty acids, ketone bodies and cholesterol were reduced in younger individuals. Gu et al (2009) examined age-related metabolic changes in children. Urinary samples from children ranging from newborns to 12-year-olds were analysed by NMR spectroscopy and the data sets were subjected to multivariate statistical analysis.…”

Statistical Analysis and Modeling of Mass Spectrometry-Based Metabolomics Data

“…This is due to the underlying assumption of constant excretion of creatinine into urine, which generally holds except for some diseases that affect kidney function. Creatinine levels in urine also show a slight age dependence [3]. …”