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Impact of common variation in bone-related genes on type 2 diabetes and related traits.

ABSTRACT: Exploring genetic pleiotropy can provide clues to a mechanism underlying the observed epidemiological association between type 2 diabetes and heightened fracture risk. We examined genetic variants associated with bone mineral density (BMD) for association with type 2 diabetes and glycemic traits in large well-phenotyped and -genotyped consortia. We undertook follow-up analysis in ∼19,000 individuals and assessed gene expression. We queried single nucleotide polymorphisms (SNPs) associated with BMD at levels of genome-wide significance, variants in linkage disequilibrium (r(2) > 0.5), and BMD candidate genes. SNP rs6867040, at the ITGA1 locus, was associated with a 0.0166 mmol/L (0.004) increase in fasting glucose per C allele in the combined analysis. Genetic variants in the ITGA1 locus were associated with its expression in the liver but not in adipose tissue. ITGA1 variants appeared among the top loci associated with type 2 diabetes, fasting insulin, β-cell function by homeostasis model assessment, and 2-h post-oral glucose tolerance test glucose and insulin levels. ITGA1 has demonstrated genetic pleiotropy in prior studies, and its suggested role in liver fibrosis, insulin secretion, and bone healing lends credence to its contribution to both osteoporosis and type 2 diabetes. These findings further underscore the link between skeletal and glucose metabolism and highlight a locus to direct future investigations.

SUBMITTER: Billings LK

PROVIDER: S-EPMC3402303 | biostudies-literature | 2012 Aug

REPOSITORIES: biostudies-literature

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Impact of common variation in bone-related genes on type 2 diabetes and related traits.

Billings Liana K LK Hsu Yi-Hsiang YH Ackerman Rachel J RJ Dupuis Josée J Voight Benjamin F BF Rasmussen-Torvik Laura J LJ Hercberg Serge S Lathrop Mark M Barnes Daniel D Langenberg Claudia C Hui Jennie J Fu Mao M Bouatia-Naji Nabila N Lecoeur Cecile C An Ping P Magnusson Patrik K PK Surakka Ida I Ripatti Samuli S Christiansen Lene L Dalgård Christine C Folkersen Lasse L Grundberg Elin E Eriksson Per P Kaprio Jaakko J Ohm Kyvik Kirsten K Pedersen Nancy L NL Borecki Ingrid B IB Province Michael A MA Balkau Beverley B Froguel Philippe P Shuldiner Alan R AR Palmer Lyle J LJ Wareham Nick N Meneton Pierre P Johnson Toby T Pankow James S JS Karasik David D Meigs James B JB Kiel Douglas P DP Florez Jose C JC

Diabetes 20120614 8

Exploring genetic pleiotropy can provide clues to a mechanism underlying the observed epidemiological association between type 2 diabetes and heightened fracture risk. We examined genetic variants associated with bone mineral density (BMD) for association with type 2 diabetes and glycemic traits in large well-phenotyped and -genotyped consortia. We undertook follow-up analysis in ∼19,000 individuals and assessed gene expression. We queried single nucleotide polymorphisms (SNPs) associated with B ...[more]

PMID: 22698912

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Project description: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.

Project description:IntroductionGenetic variants have been replicated for association with type 2 diabetes mellitus (T2D) and many of them with diabetes-related traits. Because T2D is highly prevalent in Mexico, this study aimed to test the association of CDKN2A/B, PPARGC1A, VEGFA, SIRT1 and UCP2 gene polymorphisms (rs10811661, rs8192678, rs2010963, rs7896005 and rs659366 respectively) with metabolic traits in 415 unrelated Mexican mestizos with T2D under three models of inheritance.Material and methodsA total of 415 unrelated Mexican mestizos were genotyped by TaqMan assays. Triglycerides, cholesterol, glucose, high-density lipoprotein cholesterol (HDL-C), insulin and anthropometric measurements were determined and the HOMA-IR was calculated. Association studies were tested by the Kruskal-Wallis test, linear regression, statistical power analysis, Bonferroni correction, paired SNP analysis, and physical interaction by GeneMANIA.ResultsAll polymorphisms were in Hardy-Weinberg equilibrium, and the association by genotype with T2D-related traits displayed nominal significance for rs8192678 with glucose (p = 0.023) and triglycerides (p = 0.013); rs2010963 with diastolic blood pressure (DBP) (p = 0.012) and cholesterol (p = 0.013); rs7896005 with DBP (p = 0.012) and insulin (p = 0.011); and rs659366 with cholesterol (p = 0.034), glucose (p = 0.031) and triglycerides (p = 0.028); and the association of rs2010963 with HDL-C (p = 0.0007) was significant. Linear regression performed with three models of inheritance, adjusted by age + sex + BMI and corrected with Bonferroni, showed a significant association of rs2010963 with HDL-C in an additive model (p = 0.007); and rs7896005 was significantly associated with DBP in the recessive model (p = 0.006).ConclusionsRigorous analysis evidenced the association of VEGFA rs2010963 and SIRT1 rs7896005 with HDL-C and DBP respectively; these traits are known predictors of cardiovascular complications, which increase the risk of cardiovascular diseases in this population.

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Impact of common variation in bone-related genes on type 2 diabetes and related traits.

Publications

Impact of common variation in bone-related genes on type 2 diabetes and related traits.

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