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Genetic Variation at the Sulfonylurea Receptor, Type 2 Diabetes, and Coronary Heart Disease.

ABSTRACT: Despite widespread clinical use in the treatment of type 2 diabetes, the impact of sulfonylurea therapy on cardiovascular outcomes remains uncertain. Studies of naturally occurring genetic variation can be used to anticipate the expected clinical consequences of a pharmacological therapy. A common missense variant in the gene encoding a component of the sulfonylurea receptor (ABCC8 p.A1369S) promotes closure of the target channel of sulfonylurea therapy and is associated with increased insulin secretion, thus mimicking the effects of sulfonylurea therapy. Using individual-level data from 120,286 participants in the UK Biobank and summary association results from four large-scale genome-wide association studies, we examined the impact of this variant on cardiometabolic traits, type 2 diabetes, and coronary heart disease. The p.A1369S variant was associated with a significantly lower risk of type 2 diabetes (odds ratio [OR] 0.93; 95% CI 0.91, 0.95; P = 1.2 × 10^-11). The variant was associated with increased BMI (+0.062 kg/m²; 95% CI 0.037, 0.086; P = 8.1 × 10^-7) but lower waist-to-hip ratio adjusted for BMI, a marker of abdominal fat distribution. Furthermore, p.A1369S was associated with a reduced risk of coronary heart disease (OR 0.98; 95% CI 0.96, 0.99; P = 5.9 × 10^-4). These results suggest that, despite a known association with increased weight, long-term sulfonylurea therapy may reduce the risk of coronary heart disease.

SUBMITTER: Emdin CA

PROVIDER: S-EPMC5521864 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundCoronary heart disease (CHD) and type 2 diabetes (T2D) are two complex diseases with complex interrelationships. However, the genetic architecture of the two diseases is often studied independently by the individual single-nucleotide polymorphism (SNP) approach. Here, we presented a genotypic-phenotypic framework for deciphering the genetic architecture underlying the disease patterns of CHD and T2D.MethodA data-driven SNP-set approach was performed in a genome-wide association study consisting of subpopulations with different disease patterns of CHD and T2D (comorbidity, CHD without T2D, T2D without CHD and all none). We applied nonsmooth nonnegative matrix factorization (nsNMF) clustering to generate SNP sets interacting the information of SNP and subject. Relationships between SNP sets and phenotype sets harboring different disease patterns were then assessed, and we further co-clustered the SNP sets into a genetic network to topologically elucidate the genetic architecture composed of SNP sets.ResultsWe identified 23 non-identical SNP sets with significant association with CHD or T2D (SNP-set based association test, P < 3.70 × [Formula: see text]). Among them, disease patterns involving CHD and T2D were related to distinct SNP sets (Hypergeometric test, P < 2.17 × [Formula: see text]). Accordingly, numerous genes (e.g., KLKs, GRM8, SHANK2) and pathways (e.g., fatty acid metabolism) were diversely implicated in different subtypes and related pathophysiological processes. Finally, we showed that the genetic architecture for disease patterns of CHD and T2D was composed of disjoint genetic networks (heterogeneity), with common genes contributing to it (pleiotropy).ConclusionThe SNP-set approach deciphered the complexity of both genotype and phenotype as well as their complex relationships. Different disease patterns of CHD and T2D share distinct genetic architectures, for which lipid metabolism related to fibrosis may be an atherogenic pathway that is specifically activated by diabetes. Our findings provide new insights for exploring new biological pathways.

Project description:ImportanceIn observational studies, abdominal adiposity has been associated with type 2 diabetes and coronary heart disease (CHD). Whether these associations represent causal relationships remains uncertain.ObjectiveTo test the association of a polygenic risk score for waist-to-hip ratio (WHR) adjusted for body mass index (BMI), a measure of abdominal adiposity, with type 2 diabetes and CHD through the potential intermediates of blood lipids, blood pressure, and glycemic phenotypes.Design, setting, and participantsA polygenic risk score for WHR adjusted for BMI, a measure of genetic predisposition to abdominal adiposity, was constructed with 48 single-nucleotide polymorphisms. The association of this score with cardiometabolic traits, type 2 diabetes, and CHD was tested in a mendelian randomization analysis that combined case-control and cross-sectional data sets. Estimates for cardiometabolic traits were based on a combined data set consisting of summary results from 4 genome-wide association studies conducted from 2007 to 2015, including up to 322 154 participants, as well as individual-level, cross-sectional data from the UK Biobank collected from 2007-2011, including 111 986 individuals. Estimates for type 2 diabetes and CHD were derived from summary statistics of 2 separate genome-wide association studies conducted from 2007 to 2015 and including 149 821 individuals and 184 305 individuals, respectively, combined with individual-level data from the UK Biobank.ExposuresGenetic predisposition to increased WHR adjusted for BMI.Main outcomes and measuresType 2 diabetes and CHD.ResultsAmong 111 986 individuals in the UK Biobank, the mean age was 57 (SD, 8) years, 58 845 participants (52.5%) were women, and mean WHR was 0.875. Analysis of summary-level genome-wide association study results and individual-level UK Biobank data demonstrated that a 1-SD increase in WHR adjusted for BMI mediated by the polygenic risk score was associated with 27-mg/dL higher triglyceride levels, 4.1-mg/dL higher 2-hour glucose levels, and 2.1-mm Hg higher systolic blood pressure (each P < .001). A 1-SD genetic increase in WHR adjusted for BMI was also associated with a higher risk of type 2 diabetes (odds ratio, 1.77 [95% CI, 1.57-2.00]; absolute risk increase per 1000 participant-years, 6.0 [95% CI, CI, 4.4-7.8]; number of participants with type 2 diabetes outcome, 40 530) and CHD (odds ratio, 1.46 [95% CI, 1.32-1.62]; absolute risk increase per 1000 participant-years, 1.8 [95% CI, 1.3-2.4]; number of participants with CHD outcome, 66 440).Conclusions and relevanceA genetic predisposition to higher waist-to-hip ratio adjusted for body mass index was associated with increased risk of type 2 diabetes and coronary heart disease. These results provide evidence supportive of a causal association between abdominal adiposity and these outcomes.

Project description:Inhibition of the endocannabinoid receptor CB1 improves insulin sensitivity, lowers glycemia, and slows atherosclerosis. We analyzed whether common variants in the gene encoding CB1, CNR1, are associated with insulin resistance, risk of type 2 diabetes (T2D) or coronary heart disease (CHD). We studied 2,411 participants of the Framingham Offspring Study (mean age 60 years, 52% women) for quantitative traits and CHD, and the Framingham SHARe database for T2D risk. We genotyped 19 single-nucleotide polymorphisms (SNPs) that tagged 85% (at r(2) = 0.8) of common (>5%) CNR1 SNPs. Fasting blood glucose and insulin at the 7th (1999-2001) exam were collected. We used age-, sex-, BMI-adjusted models to test additive associations of genotype with homeostasis model assessment of insulin resistance (HOMA(IR)) (linear mixed-effect models), T2D, or CHD. To account for multiple tests of SNPs, we generated empirical P values. The C allele at SNP rs806365 (frequency, 57.4%), ~4.1 kb 3' from CNR1, was associated with increased HOMA(IR) (n = 2,261, ? = 0.05 per C, empirical P = 0.01), risk of T2D (674 cases, odds ratio = 1.19 per C, nominal P = 0.01) and CHD (237 cases, hazard ratio = 1.23 per C, nominal P = 0.04). The association of rs806365 with HOMA(IR) was replicated in a meta-analysis of two independent cohorts (National Health and Nutrition Examination Survey III genetic cohort (NHANES-III) plus Partners Case-Control Diabetes Study; 2,540 white individuals, ? = 0.037, nominal P = 0.007), but not in the large Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) Consortium (n = 29,248, nominal P = 0.74). The association of rs806365 was not replicated either with T2D in Diabetes Genetics Replication and Meta-analysis (DIAGRAM) (n = 10,128, nominal P = 0.31), or with CHD in PROCARDIS (n = 13,614, nominal P = 0.37). Although supported by initial results, we found no reproducible statistical association of common variation at CNR1 with insulin resistance, T2D, or CHD.

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Genetic Variation at the Sulfonylurea Receptor, Type 2 Diabetes, and Coronary Heart Disease.

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