Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.
PLoS Genet. 2010 Aug 12;6(8):e1001058. doi: 10.1371/journal.pgen.1001058.
Mitochondrial dysfunction has been observed in skeletal muscle of people with diabetes and insulin-resistant individuals. Furthermore, inherited mutations in mitochondrial DNA can cause a rare form of diabetes. However, it is unclear whether mitochondrial dysfunction is a primary cause of the common form of diabetes. To date, common genetic variants robustly associated with type 2 diabetes (T2D) are not known to affect mitochondrial function. One possibility is that multiple mitochondrial genes contain modest genetic effects that collectively influence T2D risk. To test this hypothesis we developed a method named Meta-Analysis Gene-set Enrichment of variaNT Associations (MAGENTA; http://www.broadinstitute.org/mpg/magenta). MAGENTA, in analogy to Gene Set Enrichment Analysis, tests whether sets of functionally related genes are enriched for associations with a polygenic disease or trait. MAGENTA was specifically designed to exploit the statistical power of large genome-wide association (GWA) study meta-analyses whose individual genotypes are not available. This is achieved by combining variant association p-values into gene scores and then correcting for confounders, such as gene size, variant number, and linkage disequilibrium properties. Using simulations, we determined the range of parameters for which MAGENTA can detect associations likely missed by single-marker analysis. We verified MAGENTA's performance on empirical data by identifying known relevant pathways in lipid and lipoprotein GWA meta-analyses. We then tested our mitochondrial hypothesis by applying MAGENTA to three gene sets: nuclear regulators of mitochondrial genes, oxidative phosphorylation genes, and approximately 1,000 nuclear-encoded mitochondrial genes. The analysis was performed using the most recent T2D GWA meta-analysis of 47,117 people and meta-analyses of seven diabetes-related glycemic traits (up to 46,186 non-diabetic individuals). This well-powered analysis found no significant enrichment of associations to T2D or any of the glycemic traits in any of the gene sets tested. These results suggest that common variants affecting nuclear-encoded mitochondrial genes have at most a small genetic contribution to T2D susceptibility.
线粒体功能障碍在糖尿病患者和胰岛素抵抗个体的骨骼肌中已被观察到。此外，线粒体 DNA 的遗传突变可导致一种罕见形式的糖尿病。然而，线粒体功能障碍是否是常见形式糖尿病的主要原因尚不清楚。迄今为止，与 2 型糖尿病（T2D）强烈相关的常见遗传变异尚未被证实影响线粒体功能。一种可能性是，多个线粒体基因包含可影响 T2D 风险的适度遗传效应。为了验证这一假设，我们开发了一种名为 Meta-Analysis Gene-set Enrichment of variaNT Associations（MAGENTA；http://www.broadinstitute.org/mpg/magenta）的方法。MAGENTA 类似于基因集富集分析，用于测试功能相关基因集是否与多基因疾病或特征相关联。MAGENTA 专门设计用于利用大型全基因组关联（GWA）研究荟萃分析的统计能力，这些荟萃分析的个体基因型不可用。这是通过将变体关联 p 值组合成基因分数来实现的，然后对基因大小、变体数量和连锁不平衡特性等混杂因素进行校正。通过模拟，我们确定了 MAGENTA 可以检测到可能被单标记分析遗漏的关联的参数范围。我们通过在脂质和脂蛋白 GWA 荟萃分析中识别已知相关途径，验证了 MAGENTA 的性能。然后，我们通过将 MAGENTA 应用于三个基因集来检验我们的线粒体假设：线粒体基因的核调节因子、氧化磷酸化基因和大约 1000 个核编码的线粒体基因。该分析使用了最近的 47117 人的 T2D GWA 荟萃分析和七个与糖尿病相关的血糖特征（多达 46186 名非糖尿病个体）的荟萃分析。这项功能强大的分析未发现任何基因集与 T2D 或任何血糖特征的关联有显著富集。这些结果表明，影响核编码线粒体基因的常见变体对 T2D 易感性的遗传贡献最多只有很小。
