Objective:To investigate the impact of reduced adipocyte fatty acid-binding protein 4 (FABP4) in control of body weight, glucose and lipid homeostasis in diet-induced obese (DIO) mice.Methods:We applied RNA interference (RNAi) technology to generate FABP4 germline knockdown mice to investigate their metabolic phenotype.Results:RNAi-mediated knockdown reduced FABP4 mRNA expression and protein levels by almost 90% in adipocytes of standard chow-fed mice. In adipocytes of DIO mice, RNAi reduced FABP4 expression and protein levels by 70 and 80%, respectively. There was no increase in adipocyte FABP5 expression in FABP4 knockdown mice. The knockdown of FABP4 significantly increased body weight and fat mass in DIO mice. However, FABP4 knockdown did not affect plasma glucose and lipid homeostasis in DIO mice; nor did it improve their insulin sensitivity.Conclusion:Our data indicate that robust knockdown of FABP4 increases body weight and fat mass without improving glucose and lipid homeostasis in DIO mice.

Precompetitive collaboration is a growing driver for innovation and increased productivity in biomedical science and drug development. The Biomarkers Consortium, a public-private platform for precompetitive collaboration specific to biomarkers, demonstrated that adiponectin has potential utility as a predictor of metabolic responses to peroxisome proliferator-activated receptor (PPAR) agonists in individuals with type 2 diabetes. Despite the challenges overcome by this project, the most important lesson learned is that cross-company precompetitive collaboration is a feasible robust approach to biomarker qualification.

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.