Life (Jun 2021)

Identification of Metabolic Phenotypes in Young Adults with Obesity by <sup>1</sup>H NMR Metabolomics of Blood Serum

  • Khin Thandar Htun,
  • Jie Pan,
  • Duanghathai Pasanta,
  • Montree Tungjai,
  • Chatchanok Udomtanakunchai,
  • Sirirat Chancharunee,
  • Siriprapa Kaewjaeng,
  • Hong Joo Kim,
  • Jakrapong Kaewkhao,
  • Suchart Kothan

DOI
https://doi.org/10.3390/life11060574
Journal volume & issue
Vol. 11, no. 6
p. 574

Abstract

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(1) Since the obesity prevalence rate has been consistently increasing, it is necessary to find an effective way to prevent and treat it. Although progress is being made to reduce obesity in the young adult population, a better understanding of obesity-related metabolomics and related biochemical mechanisms is urgently needed for developing appropriate screening strategies. Therefore, the aim of this study is to identify the serum metabolic profile associated with young adult obesity and its metabolic phenotypes. (2) Methods: The serum metabolic profile of 30 obese and 30 normal-weight young adults was obtained using proton nuclear magnetic resonance spectroscopy (1H NMR). 1H NMR spectra were integrated into 24 integration regions, which reflect relative metabolites, and were used as statistical variables. (3) Results: The obese group showed increased levels of lipids, glucose, glutamate, N-acetyl glycoprotein, alanine, lactate, 3 hydroxybutyrate and branch chain amino acid (BCAA), and decreased levels of choline as compared with the normal-weight group. Non-hyperlipidemia obese adults showed lower levels of lipids and lactate, glutamate, acetoacetate, N-acetyl glycoprotein, isoleucine, and higher levels of choline and glutamine, as compared with hyperlipidemic obese adults. (4) Conclusions: This study reveals valuable findings in the field of metabolomics and young adult obesity. We propose several serum biomarkers that distinguish between normal weight and obese adults, i.e., glutamine (higher in the normal group, p p p < 0.05) in the obese with hyperlipidemia. Therefore, they can be used as biomarkers to identify these two types of obesity.

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