Diagnostic Value of Cell-free Circulating MicroRNAs for Obesity and Type 2 Diabetes: A Meta-analysis

Type 2 diabetes mellitus (T2DM) is the most common metabolic disorder worldwide. Because of population aging and increasing trends toward obesity and sedentary lifestyles, the number of affected individuals is increasing at worrisome rates. While both environmental and genetic factors are known to contribute to the development of T2DM, continuous research is needed to identify specific biomarkers that could aid both in prevention of the disease and development of newer therapeutic options. Circulating miRNAs are considered as potential biomarkers because they are stable and resistant to degradation by blood RNAses and are modified under different pathophysiological conditions. In this study we carried out a systematic electronic search on PubMed to retrieve all articles that have investigated circulating miRNAs for diagnosing obesity andT2DM in human. We also included lifestyle intervention studies known to be highly effective in delaying onset of diabetes, and studies analyzing the effect of bariatric surgery and anti-diabetic treatment. A total of 26 studies were enrolled in the global meta-analysis. Candidate miRNAs were defined as those reported in at least 2 studies with same direction of differential expression. Ten miRNAs altered in blood of patients suffering fromT2DM were identified (increased: miR-320a, miR-142-3p, miR-222, miR-29a, miR-27a, miR-375; decreased: miR-197, miR-20b, miR-17, miR-652) and 7 miRNAs in blood of obese subjects were identified (increased: miR-142-3p, miR-140-5p, miR-222; decreased:miR-21-5p, miR-221-3p, miR-125-5p, mir-103-5p). Both obese and T2DM patients had elevated concentrations of miR-142-3p and miR-222. MiRNAs target genes were predicted and their cellular functions are discussed in relation with the pathologies. Although a significant number of studies were taken into account in this review, we found a strong discrepancy between miRNA detection and quantification indicating that many of pre-analytical variables have yet to be normalized. Pre-analytical and analytical challenges are also discussed.