Research Article

1H NMR metabolomics study of age profiling in children

  1. Haiwei Gu1,
  2. Zhengzheng Pan2,
  3. Bowei Xi3,
  4. Bryan E. Hainline4,
  5. Narasimhamurthy Shanaiah2,
  6. Vincent Asiago2,
  7. G. A. Nagana Gowda2,
  8. Daniel Raftery2,*

Article first published online: 13 MAY 2009

DOI: 10.1002/nbm.1395

Issue

NMR in Biomedicine

NMR in Biomedicine

Volume 22, Issue 8, pages 826–833, October 2009

Additional Information

How to Cite

Gu, H., Pan, Z., Xi, B., Hainline, B. E., Shanaiah, N., Asiago, V., Gowda, G. A. N. and Raftery, D. (2009), 1H NMR metabolomics study of age profiling in children. NMR Biomed., 22: 826–833. doi: 10.1002/nbm.1395

Author Information

  1. 1

    Department of Physics, Purdue University, West Lafayette, IN, USA

  2. 2

    Department of Chemistry, Purdue University, West Lafayette, IN, USA

  3. 3

    Department of Statistics, Purdue University, West Lafayette, IN, USA

  4. 4

    Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA

*Department of Chemistry, Purdue University, West Lafayette, IN 47907, USA.

Publication History

  1. Issue published online: 8 SEP 2009
  2. Article first published online: 13 MAY 2009
  3. Manuscript Accepted: 13 MAR 2009
  4. Manuscript Revised: 17 FEB 2009
  5. Manuscript Received: 21 AUG 2008

Funded by

  • NIH Roadmap Initiative on Metabolomics Technology. Grant Number: NIH/NIDDK 3 R21 DK070290-01
  • Purdue University/Discovery Park and the Indiana University School of Medicine collaborative grant

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Keywords:

  • age;
  • human urine;
  • metabolite profiling;
  • metabolomics;
  • metabonomics;
  • nuclear magnetic resonance;
  • orthogonal signal correction;
  • principal component analysis

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. Copyright © 2009 John Wiley & Sons, Ltd.

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