Biomarkers of insulin resistance and their performance as predictors of treatment response in adults with risk factors for type 2 diabetes

Insulin Resistance (IR) is a component of the pathogenesis of type 2 diabetes mellitus (T2DM), and risk factor for cardiovascular and neurodegenerative diseases. Amino acid and lipid metabolomic IR diagnostics associate with future T2DM risk in epidemiological cohorts. Whether these assays can accurately detect altered IR following treatment has not been established. In the present study we evaluated the ability of metabolomic diagnostics to predict altered IR following exercise treatment. We evaluated the performance of two distinct insulin assays and built combined clinical and metabolomic IR diagnostics. These were utilised to stratify IR status in the pre-intervention fasting samples in three independent cohorts (META-PREDICT (MP, n=179), STRRIDE-AT/RT (S-2, n=116) and STRRIDE-PD (S-PD, n=149)). Linear and Bayesian projective prediction strategies were used to evaluate biomarkers for fasting insulin and HOMA2- IR and change in fasting insulin with treatment. Both insulin assays accurately quantified international standard insulin (R ² >0.99), yet agreement for fasting insulin was less congruent (R ² =0.65). Only the high-sensitivity ELISA assay could identify the mean effect of treatment on fasting insulin. Clinical-metabolomic models were statistically related to fasting insulin (R ² 0.33 – 0.39) but had modest capacity to classify HOMA2-IR at a clinically relevant threshold. Furthermore, no model predicted treatment responses in any cohort. Thus, we demonstrate that the choice of insulin assay is critical when quantifying the influence of life-style on fasting insulin, while none of the clinical-metabolomic biomarkers, validated in cross-sectional data, are suitable for monitoring longitudinally changes in IR status.