Common Inherited Variation in Mitochondrial Genes Is Not Enriched for Associations with Type 2 Diabetes or Related Glycemic Traits

被引:359
作者
Segre, Ayellet V. [1 ,2 ,3 ]
Groop, Leif [4 ]
Mootha, Vamsi K. [1 ,2 ,5 ,6 ]
Daly, Mark J. [1 ,2 ,6 ]
Altshuler, David [1 ,2 ,3 ,6 ,7 ]
机构
[1] Broad Inst Harvard & Massachusetts Inst Technol, Cambridge, MA USA
[2] Massachusetts Gen Hosp, Ctr Human Genet Res, Boston, MA 02114 USA
[3] Massachusetts Gen Hosp, Dept Mol Biol, Boston, MA 02114 USA
[4] Lund Univ, Malmo Univ Hosp, Dept Clin Sci, Diabet & Endocrinol Res Unit, S-21401 Malmo, Sweden
[5] Harvard Univ, Sch Med, Dept Syst Biol, Boston, MA USA
[6] Harvard Univ, Sch Med, Dept Med, Boston, MA USA
[7] Massachusetts Gen Hosp, Diabet Unit, Boston, MA 02114 USA
基金
瑞典研究理事会;
关键词
GENOME-WIDE ASSOCIATION; OXIDATIVE-PHOSPHORYLATION; INSULIN-RESISTANCE; PATHWAY ANALYSIS; CANDIDATE GENES; LOCI; GLUCOSE; SUSCEPTIBILITY; HOMEOSTASIS; DYSFUNCTION;
D O I
10.1371/journal.pgen.1001058
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
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,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.
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页数:19
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