Joint IRB-BSC Program on Computational Biology, Barcelona Supercomputing Center, Barcelona, Catalonia, Spain.
PLoS Genet. 2012;8(12):e1003046. doi: 10.1371/journal.pgen.1003046. Epub 2012 Dec 6.
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.
2 型糖尿病(T2D)是一种高发的慢性代谢性疾病,与肥胖症和心血管疾病有着密切的共同发病机制。越来越多的证据表明,线粒体和胰岛素信号级联之间的串扰可能与 T2D 和胰岛素抵抗的发病机制有关。在这项研究中,我们使用系统生物学方法研究了这种串扰的分子基础。我们结合、过滤和分析了不同类型的功能相互作用数据,如直接蛋白质-蛋白质相互作用、共表达分析以及代谢和信号依赖性。结果,我们构建了线粒体-胰岛素(MITIN)网络,其中突出了 286 个基因作为这两个系统之间的候选功能连接子。三个独立的线粒体和胰岛素信号扰动实验模型的内部基因表达分析结果进一步支持了这些基因的连接作用。此外,我们还使用 DIAGRAM 联盟的全基因组关联研究荟萃分析,进一步评估了这些基因是否参与 T2D 的发病机制。该分析涉及 8130 例 T2D 病例和 38987 例对照。我们发现,我们的连接基因中与 T2D 相关的基因有适度的富集(p=0.0549),包括三个已验证的 T2D SNP 和 15 个额外的 SNP,当这些 SNP 组合在一起时,根据 MAGIC 全基因组荟萃分析,与空腹血糖水平升高相关(p=8.12×10(-5))。这项研究强调了结合系统生物学、实验和全基因组关联数据挖掘来识别增加复杂疾病易感性的新基因和相关变异的潜力。