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Published on: December 15, 2011
1H NMR metabolomics study of age profiling in children
Haiwei Gu1, Zhengzheng Pan, Bowei Xi
1Department of Physics, Purdue University, West Lafayette, IN 47907, USA.
Insights
Urine metabolic profiling reveals age-related changes in children under 12. Key metabolites like creatinine, glycine, and citrate shift with age, offering insights into biological aging and metabolomics applications.
Area of Science:
- Metabolomics
- Biochemistry
- Pediatric Research
Background:
- Urinary metabolic profiling offers personalized endogenous metabolite markers.
- These markers correlate with factors including age, gender, disease, diet, and medication.
- Understanding individual factor contributions, like age, is crucial for accurate metabolomic interpretation.
Purpose of the Study:
- To analyze age-related metabolic changes in children aged 12 and below.
- To identify specific urinary metabolites that change with age in this demographic.
- To explore the potential of urinary metabolomics in assessing biological age in children.
Main Methods:
- (1)H NMR spectroscopy was used for urine metabolic profiling.
- Unsupervised principal component analysis (PCA) was employed to observe age-dependent clustering.
- Partial least squares with orthogonal signal correction (PLS-OSC) regression was used to identify age-related metabolic profiles.
Main Results:
- Distinct age-dependent clustering of urinary metabolite profiles was observed via PCA.
- PLS-OSC identified an age-related metabolic profile.
- Creatinine increased with age, while metabolites including creatine, glycine, betaine/TMAO, citrate, succinate, and acetone decreased.
Conclusions:
- Urinary metabolomics can reveal significant age-related shifts in children.
- Specific metabolites show a clear correlation with chronological age in young individuals.
- These findings may aid in assessing biological age and understanding confounding factors in pediatric metabolomics.
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 (1)H 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.
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