Literature DB >> 23375209

Branched chain amino acids are novel biomarkers for discrimination of metabolic wellness.

Bryan C Batch1, Svati H Shah, Christopher B Newgard, Christy B Turer, Carol Haynes, James R Bain, Michael Muehlbauer, Mahesh J Patel, Robert D Stevens, Lawrence J Appel, L Kristin Newby, Laura P Svetkey.   

Abstract

OBJECTIVE: To identify novel biomarkers through metabolomic profiles that distinguish metabolically well (MW) from metabolically unwell (MUW) individuals, independent of body mass index (BMI). MATERIALS/
METHODS: This study was conducted as part of the Measurement to Understand the Reclassification of Disease of Cabarrus/Kannapolis (MURDOCK) project. Individuals from 3 cohorts were classified as lean (BMI<25kg/m²), overweight (BMI≥25kg/m², BMI<30kg/m²) or obese (BMI≥30kg/m²). Cardiometabolic abnormalities were defined as: (1) impaired fasting glucose (≥100mg/dL and ≤126mg/dL); (2) hypertension; (3) triglycerides ≥150mg/dL; (4) HDL-C <40mg/dL in men, <50mg/dL in women; and (5) insulin resistance (calculated Homeostatic Model Assessment (HOMA-IR) index of >5.13). MW individuals were defined as having <2 cardiometabolic abnormalities and MUW individuals had≥two cardiometabolic abnormalities. Targeted profiling of 55 metabolites used mass-spectroscopy-based methods. Principal components analysis (PCA) was used to reduce the large number of correlated metabolites into clusters of fewer uncorrelated factors.
RESULTS: Of 1872 individuals, 410 were lean, 610 were overweight, and 852 were obese. Of lean individuals, 67% were categorized as MUW, whereas 80% of overweight and 87% of obese individuals were MUW. PCA-derived factors with levels that differed the most between MW and MUW groups were factors 4 (branched chain amino acids [BCAA]) [p<.0001], 8 (various metabolites) [p<.0001], 9 (C4/Ci4, C3, C5 acylcarnitines) [p<.0001] and 10 (amino acids) [p<.0002]. Further, Factor 4, distinguishes MW from MUW individuals independent of BMI.
CONCLUSION: BCAA and related metabolites are promising biomarkers that may aid in understanding cardiometabolic health independent of BMI category.
Copyright © 2013 Elsevier Inc. All rights reserved.

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Year:  2013        PMID: 23375209      PMCID: PMC3691289          DOI: 10.1016/j.metabol.2013.01.007

Source DB:  PubMed          Journal:  Metabolism        ISSN: 0026-0495            Impact factor:   8.694


  22 in total

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  88 in total

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