Type 2 Diabetes (T2D) is a highly prevalent chronic metabolic disease with strong co-morbidity with obesity and cardiovascular diseases. There is growing evidence supporting the notion that a crosstalk between mitochondria and the insulin signaling cascade could be involved in the etiology of T2D and insulin resistance. In this study we investigated the molecular basis of this crosstalk by using systems biology approaches. We combined, filtered, and interrogated different types of functional interaction data, such as direct protein–protein interactions, co-expression analyses, and metabolic and signaling dependencies. As a result, we constructed the mitochondria-insulin (MITIN) network, which highlights 286 genes as candidate functional linkers between these two systems. The results of internal gene expression analysis of three independent experimental models of mitochondria and insulin signaling perturbations further support the connecting roles of these genes. In addition, we further assessed whether these genes are involved in the etiology of T2D using the genome-wide association study meta-analysis from the DIAGRAM consortium, involving 8,130 T2D cases and 38,987 controls. We found modest enrichment of genes associated with T2D amongst our linker genes (p = 0.0549), including three already validated T2D SNPs and 15 additional SNPs, which, when combined, were collectively associated to increased fasting glucose levels according to MAGIC genome wide meta-analysis (p = 8.12×10−5). This study highlights the potential of combining systems biology, experimental, and genome-wide association data mining for identifying novel genes and related variants that increase vulnerability to complex diseases.
It has been shown that the crosstalk between insulin signaling and the mitochondria may be involved in the etiology of type 2 diabetes. In order to characterize the molecular basis of this crosstalk, we mined and filtered several interaction databases of different natures, including protein–protein interactions, gene co-expression, signaling, and metabolic pathway interactions, to identify reliable direct and indirect interactions between insulin signaling cascade and mitochondria genes. This allowed us to identify 286 genes that are associated simultaneously with insulin signaling and mitochondrial genes and therefore could act as a molecular bridge between both systems. We performed in vitro and in vivo experiments where the insulin signaling or the mitochondrial function were disrupted, and we found deregulation of these connecting genes. Finally, we found that common variants in genomic regions where these genes lie are enriched for genetic associations with type 2 diabetes and glycemic traits according to large genome-wide association meta-analyses. In summary, we reconstructed the network implicated in the crosstalk between the mitochondria and the insulin signaling and provide a list of genes connecting both systems. We also propose new potential type 2 diabetes candidate genes.