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

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 < 25 kg/m²), overweight (BMI ≥ 25 kg/m², BMI < 30 kg/m²) or obese (BMI ≥ 30 kg/m ²). Cardiometabolic abnormalities were defined as: (1) impaired fasting glucose (≥ 100 mg/dL and ≤ 126 mg/dL); (2) hypertension; (3) triglycerides ≥ 150 mg/dL; (4) HDL-C < 40 mg/dL in men, < 50 mg/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.