Journal
JOURNAL OF MEDICINAL FOOD
Volume 22, Issue 5, Pages 499-507Publisher
MARY ANN LIEBERT, INC
DOI: 10.1089/jmf.2018.4310
Keywords
basal metabolic rate; genome-wide association study; metabolomics; obesity
Funding
- Korea Food Research Institute (KFRI) - Ministry of Science, ICT and Future Planning [E0150300-05]
- Korean Health Technology RAMP
- D project, Ministry of Health and Welfare [HI17C0863]
- National Research Council of Science & Technology (NST), Republic of Korea [E0150300-05, E0150300] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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A previous genome-wide association study (GWAS) on obese/overweight Korean women reported five new genetic loci associated with the basal metabolic rate (BMR) and body mass index (BMI), NRG3, OR8U8, BCL2L2-PABPN1, PABPN1, and SLC22A17. This metabolite GWAS (mGWAS) aimed to identify the key metabolites and metabolic pathways regulated by these genes. Potential metabolic pathways associated with leanness and obesity were identified by detecting metabolites in association with GWAS. Waist circumference, lean body mass, and body fat mass were strongly associated with BMI rather than BMR. However, plasma triglyceride and total cholesterol were significantly higher in obese individuals with low BMR than in lean individuals with high BMR. Upon analyzing NRG3, BCL2L2-PABPN1, and SLC22A17, uric acid, succinic acid, arginine, uridine, and aspartic acid were the metabolites positively associated with obesity. Uric acid and arginine were both identified through general metabolomics targeting of obesity genes classified on the basis of BMI or BMR. Metabolites associated with disruption in beta-oxidation, lipid metabolism, branched-chain amino acid and aromatic amino acid catabolism, the urea cycle, and purine/pyrimidine metabolism play important roles in obesity classified on the basis of either BMI or BMR in middle-aged Korean women. These results further the current understanding of obesity and the predictability of obesity-related risks using mGWAS.
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