Abstract 1262: Metabolomic Profiles Are Associated With Baseline Insulin Resistance and Improvement in Insulin Resistance With Weight Loss in the WLM Trial
Background. Insulin resistance (IR) improves with weight loss but this response is heterogeneous. As part of the MURDOCK WLM study, we hypothesized that metabolomic profiling would identify novel biomarkers that predict changes in IR with weight loss.
Methods. We randomly selected 500 participants who had lost ≥4 kg during Phase I of the Weight Loss Maintenance (WLM) trial. We performed mass spectrometry-based quantitative targeted profiling of 69 metabolites in baseline plasma samples. Insulin and glucose were measured using standard assays at baseline and 6 months. Homeostatic model assessment (HOMA) and change in HOMA with weight loss (ΔHOMA) were calculated. Principal components analysis (PCA) was used to reduce the large number of correlated metabolites into a smaller number of uncorrelated factors. Mixed models adjusted for race, sex, baseline weight and amount of weight loss were used to test for association of baseline metabolites with ΔHOMA.
Results. Thirteen metabolite factors were identified by PCA. Mean weight loss was 8.67 (SD 4.28) kg; mean ΔHOMA was −0.80 (SD 1.73), range −7.38 to 4.82. Factor 3 (branched chain amino acids and associated catabolites) was correlated with baseline HOMA (r=0.49, P<0.0001) and was independently associated with ΔHOMA in multivariable models (P<0.0001), with a linear relationship of HOMA measures across factor 3 quartiles (Table⇓).
Conclusions. A metabolite signature representing branched chain amino acid catabolism is correlated with IR and predicts improvement in IR with moderate weight loss independent of the amount of weight lost. These results may help identify individuals most likely to benefit from weight loss and elucidate novel mechanisms of IR.