Abstract

BackgroundObesity is correlated with many biomarkers, but the extent to which these correlate with underlying body composition is poorly understood. ObjectivesOur objectives were to 1) describe/compare distinct contributions of fat/lean mass with BMI–metabolite correlations and 2) identify novel metabolite biomarkers of fat/lean mass. MethodsThe Alberta Physical Activity and Breast Cancer Prevention Trial was a 2-center randomized trial of healthy, inactive, postmenopausal women (n = 304). BMI (in kg/m2) was calculated using weight and height, whereas DXA estimated fat/lean mass. Ultra-performance liquid chromatography and mass spectrometry measured relative concentrations of serum metabolite concentrations. We estimated partial Pearson correlations between 1052 metabolites and BMI, adjusting for age, smoking, and site. Fat mass index (FMI; kg/m2) and lean mass index (LMI; kg/m2) correlations were estimated similarly, with mutual adjustment to evaluate independent effects. ResultsUsing a Bonferroni-corrected α level <4.75 × 10–5, we observed 53 BMI-correlated metabolites (|r| = 0.24–0.42). Of those, 21 were robustly correlated with FMI (|r| > 0.20), 25 modestly (0.10 ≤ |r| ≤ 0.20), and 7 virtually null (|r| < 0.10). Ten of 53 were more strongly correlated with LMI than with FMI. Examining non–BMI-correlated metabolites, 6 robustly correlated with FMI (|r| = 0.24–0.31) and 2 with LMI (r = 0.25–0.26). For these, correlations for fat and lean mass were in opposing directions compared with BMI-correlated metabolites, in which correlations were mostly in the same direction. ConclusionsOur results demonstrate how a thorough evaluation of the components of fat and lean mass, along with BMI, provides a more accurate assessment of the associations between body composition and metabolites than BMI alone. Such an assessment makes evident that some metabolites correlated with BMI predominantly reflect lean mass rather than fat, and some metabolites related to body composition are not correlated with BMI. Correctly characterizing these relations is important for an accurate understanding of how and why obesity is associated with disease.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call