Utility of adiponectin as a biomarker predictive of glycemic efficacy is demonstrated by collaborative pooling of data from clinical trials conducted by multiple sponsors.

This study, conducted under the Metabolic Disorders Steering Committee of the Biomarkers Consortium (a public-private partnership managed by the Foundation for the National Institutes of Health (FNIH)), analyzed blinded data on 2,688 type 2 diabetes (T2D) patients from randomized clinical trials conducted by four pharmaceutical companies. An increase in the levels of adiponectin was observed after peroxisome proliferator-activated receptor (PPAR)-agonist treatment (P < 0.0001), but not after treatment with non-PPAR drugs. This increase correlated with decreases in levels of glucose, hemoglobin A(1c) (Hb(A1c)), hematocrit, and triglycerides, and increases in levels of blood urea nitrogen, creatinine, and high-density lipoprotein cholesterol (HDL-C). Early (6-8 weeks) increases in levels of adiponectin after treatment with PPAR agonists showed a negative correlation (r = -0.21, P < 0.0001) with subsequent changes in levels of Hb(A1c). Changes in adiponectin level did not appear to be associated with baseline level of Hb(A1c). Logistic regression demonstrated that an increase in the level of adiponectin predicts a decrease in the level of Hb(A1c). These analyses confirm previously demonstrated relationships between adiponectin levels and metabolic parameters and support the robust predictive utility of adiponectin across the spectrum of glucose tolerance. Cross-company precompetitive collaboration is a feasible and powerful approach to biomarker qualification.