Urine Untargeted Metabolomic Profiling Is Associated with the Dietary Pattern of Successful Aging among Malaysian Elderly

Nutrients. 2020 Sep 23;12(10):2900. doi: 10.3390/nu12102900.

Abstract

Food intake biomarkers (FIBs) can reflect the intake of specific foods or dietary patterns (DP). DP for successful aging (SA) has been widely studied. However, the relationship between SA and DP characterized by FIBs still needs further exploration as the candidate markers are scarce. Thus, 1H-nuclear magnetic resonance (1H-NMR)-based urine metabolomics profiling was conducted to identify potential metabolites which can act as specific markers representing DP for SA. Urine sample of nine subjects from each three aging groups, SA, usual aging (UA), and mild cognitive impairment (MCI), were analyzed using the 1H-NMR metabolomic approach. Principal components analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) were applied. The association between SA urinary metabolites and its DP was assessed using the Pearson's correlation analysis. The urine of SA subjects was characterized by the greater excretion of citrate, taurine, hypotaurine, serotonin, and melatonin as compared to UA and MCI. These urinary metabolites were associated with alteration in "taurine and hypotaurine metabolism" and "tryptophan metabolism" in SA elderly. Urinary serotonin (r = 0.48, p < 0.05) and melatonin (r = 0.47, p < 0.05) were associated with oat intake. These findings demonstrate that a metabolomic approach may be useful for correlating DP with SA urinary metabolites and for further understanding of SA development.

Keywords: 1H-NMR; biomarker; metabolomic profiling; older adult; partial least-squares discriminant analysis; principal component analysis; successful aging.

MeSH terms

  • Aged
  • Aging
  • Biomarkers / urine*
  • Diet*
  • Discriminant Analysis
  • Humans
  • Least-Squares Analysis
  • Magnetic Resonance Spectroscopy
  • Malaysia
  • Metabolomics / methods*
  • Principal Component Analysis / methods
  • Urine / chemistry*

Substances

  • Biomarkers