Abstract
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.
Highlights
Insulin resistance is a common trait present in complex disorders such as type 2 diabetes (T2D), obesity or metabolic syndrome (MetS)
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
Summary
Insulin resistance is a common trait present in complex disorders such as type 2 diabetes (T2D), obesity or metabolic syndrome (MetS). The application of systems biology approaches to analyze GWAS data may have the potential to increase the chances of unraveling susceptibility genes or biological processes for complex diseases. We applied systems biology approaches to screen and identify novel candidate T2D genes. The search has been guided by the hypothesis that the functional components of the crosstalk between the insulin signaling pathway and the biology of the mitochondria may play a role in the etiology or the evolution of the disease. We have generated and analyzed gene expression data on insulin resistance and mitochondria perturbed scenarios to support these candidate genes. We tested whether particular genetic variants in loci that contain the identified genes could be collectively associated with T2D
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