Haplotype analysis of the PPARgamma Pro12Ala and C1431T variants reveals opposing associations with body weight.

BACKGROUND: Variation at the PPARG locus may influence susceptibility to type 2 diabetes and related traits. The Pro12Ala polymorphism may modulate receptor activity and is associated with protection from type 2 diabetes. However, there have been inconsistent reports of its association with obesity. The silent C1431T polymorphism has not been as extensively studied, but the rare T allele has also been inconsistently linked to increases in weight. Both rare alleles are in linkage disequilibrium and the independent associations of these two polymorphisms have not been addressed. RESULTS: We have genotyped a large population with type 2 diabetes (n = 1107), two populations of non-diabetics from Glasgow (n = 186) and Dundee (n = 254) and also a healthy group undergoing physical training (n = 148) and investigated the association of genotype with body mass index. This analysis has demonstrated that the Ala12 and T1431 alleles are present together in approximately 70% of the carriers. By considering the other 30% of individuals with haplotypes that only carry one of these polymorphisms, we have demonstrated that the Ala12 allele is consistently associated with a lower BMI, whilst the T1431 allele is consistently associated with higher BMI. CONCLUSION: This study has therefore revealed an opposing interaction of these polymorphisms, which may help to explain previous inconsistencies in the association of PPARG polymorphisms and body weight

Type 2 Diabetes, Metabolic traits and Risk of Heart Failure:a Mendelian Randomization study

OBJECTIVE: The aim of this study was to use Mendelian randomization (MR) techniques to estimate the causal relationships between genetic liability to type 2 diabetes (T2D), glycemic traits, and risk of heart failure (HF). RESEARCH DESIGN AND METHODS: Summary-level data were obtained from genome-wide association studies of T2D, insulin resistance (IR), glycated hemoglobin, fasting insulin and glucose, and HF. MR was conducted using the inverse-variance weighted method. Sensitivity analyses included the MR-Egger method, weighted median and mode methods, and multivariable MR conditioning on potential mediators. RESULTS: Genetic liability to T2D was causally related to higher risk of HF (odds ratio [OR] 1.13 per 1-log unit higher risk of T2D; 95% CI 1.11-1.14; P < 0.001); however, sensitivity analysis revealed evidence of directional pleiotropy. The relationship between T2D and HF was attenuated when adjusted for coronary disease, BMI, LDL cholesterol, and blood pressure in multivariable MR. Genetically instrumented higher IR was associated with higher risk of HF (OR 1.19 per 1-log unit higher risk of IR; 95% CI 1.00-1.41; P = 0.041). There were no notable associations identified between fasting insulin, glucose, or glycated hemoglobin and risk of HF. Genetic liability to HF was causally linked to higher risk of T2D (OR 1.49; 95% CI 1.01-2.19; P = 0.042), although again with evidence of pleiotropy. CONCLUSIONS: These findings suggest a possible causal role of T2D and IR in HF etiology, although the presence of both bidirectional effects and directional pleiotropy highlights potential sources of bias that must be considered

Type 2 Diabetes, Metabolic Traits, and Risk of Heart Failure: A Mendelian Randomization Study

OBJECTIVE: The aim of this study was to use Mendelian randomization (MR) techniques to estimate the causal relationships between genetic liability to type 2 diabetes (T2D), glycemic traits, and risk of heart failure (HF). RESEARCH DESIGN AND METHODS: Summary-level data were obtained from genome-wide association studies of T2D, insulin resistance (IR), glycated hemoglobin, fasting insulin and glucose, and HF. MR was conducted using the inverse-variance weighted method. Sensitivity analyses included the MR-Egger method, weighted median and mode methods, and multivariable MR conditioning on potential mediators. RESULTS: Genetic liability to T2D was causally related to higher risk of HF (odds ratio [OR] 1.13 per 1-log unit higher risk of T2D; 95% CI 1.11-1.14; P < 0.001); however, sensitivity analysis revealed evidence of directional pleiotropy. The relationship between T2D and HF was attenuated when adjusted for coronary disease, BMI, LDL cholesterol, and blood pressure in multivariable MR. Genetically instrumented higher IR was associated with higher risk of HF (OR 1.19 per 1-log unit higher risk of IR; 95% CI 1.00-1.41; P = 0.041). There were no notable associations identified between fasting insulin, glucose, or glycated hemoglobin and risk of HF. Genetic liability to HF was causally linked to higher risk of T2D (OR 1.49; 95% CI 1.01-2.19; P = 0.042), although again with evidence of pleiotropy. CONCLUSIONS: These findings suggest a possible causal role of T2D and IR in HF etiology, although the presence of both bidirectional effects and directional pleiotropy highlights potential sources of bias that must be considered

A gene risk score using missense variants in SLCO1B1 is associated with earlier onset statin intolerance

Background and aims The efficacy of statin therapy is hindered by intolerance to the therapy, leading to discontinuation. Variants in SLCO1B1, which encodes the hepatic transporter OATB1B1, influence statin pharmacokinetics, resulting in altered plasma concentrations of the drug and its metabolites. Current pharmacogenetic guidelines require sequencing of the SLCO1B1 gene, which is more expensive and less accessible than genotyping. In this study, we aimed to develop an easy, clinically implementable functional gene risk score (GRS) of common variants in SLCO1B1 to identify patients at risk of statin intolerance. Methods and results A GRS was developed from four common variants in SLCO1B1. In statin users from Tayside, Scotland, UK, those with a high-risk GRS had increased odds across three phenotypes of statin intolerance [general statin intolerance (GSI): ORGSI 2.42; 95% confidence interval (CI): 1.29–4.31, P = 0.003; statin-related myopathy: ORSRM 2.51; 95% CI: 1.28–4.53, P = 0.004; statin-related suspected rhabdomyolysis: ORSRSR 2.85; 95% CI: 1.03–6.65, P = 0.02]. In contrast, using the Val174Ala genotype alone or the recommended OATP1B1 functional phenotypes produced weaker and less reliable results. A meta-analysis with results from adjudicated cases of statin-induced myopathy in the PREDICTION-ADR Consortium confirmed these findings (ORVal174Ala 1.99; 95% CI: 1.01–3.95, P = 0.048; ORGRS 1.76; 95% CI: 1.16–2.69, P = 0.008). For those requiring high-dose statin therapy, the high-risk GRS was more consistently associated with the time to onset of statin intolerance amongst the three phenotypes compared with Val174Ala (GSI: HRVal174Ala 2.49; 95% CI: 1.09–5.68, P = 0.03; HRGRS 2.44; 95% CI: 1.46–4.08, P < 0.001). Finally, sequence kernel association testing confirmed that rare variants in SLCO1B1 are associated with the risk of intolerance (P = 0.02). Conclusion We provide evidence that a GRS based on four common SLCO1B1 variants provides an easily implemented genetic tool that is more reliable than the current recommended practice in estimating the risk and predicting early-onset statin intolerance

Gene variants influencing measures of inflammation or predisposing to autoimmune and inflammatory diseases are not associated with the risk of type 2 diabetes.

AIMS/HYPOTHESIS: There are strong associations between measures of inflammation and type 2 diabetes, but the causal directions of these associations are not known. We tested the hypothesis that common gene variants known to alter circulating levels of inflammatory proteins, or known to alter autoimmune-related disease risk, influence type 2 diabetes risk. METHODS: We selected 46 variants: (1) eight variants known to alter circulating levels of inflammatory proteins, including those in the IL18, IL1RN, IL6R, MIF, PAI1 (also known as SERPINE1) and CRP genes; and (2) 38 variants known to predispose to autoimmune diseases, including type 1 diabetes. We tested the associations of these variants with type 2 diabetes using a meta-analysis of 4,107 cases and 5,187 controls from the Wellcome Trust Case Control Consortium, the Diabetes Genetics Initiative, and the Finland-United States Investigation of NIDDM studies. We followed up associated variants (p < 0.01) in a further set of 3,125 cases and 3,596 controls from the UK. RESULTS: We found no evidence that inflammatory or autoimmune disease variants are associated with type 2 diabetes (at p <or= 0.01). The OR observed between the variant altering IL-18 levels, rs2250417, and type 2 diabetes (OR 1.00 [95% CI 0.99-1.03]), is much lower than that expected given (1) the effect of the variant on IL-18 levels (0.28 SDs per allele); and (2) estimates, based on other studies, of the correlation between IL-18 levels and type 2 diabetes risk (approximate OR 1.15 [95% CI 1.09-1.21] per 0.28 SD increase in IL-18 levels). CONCLUSIONS/INTERPRETATION: Our study provided no evidence that variants known to alter measures of inflammation, autoimmune or inflammatory disease risk, including type 1 diabetes, alter type 2 diabetes risk

Competing risks analysis for neutrophil to lymphocyte ratio as a predictor of diabetic retinopathy incidence in the Scottish population

Background Diabetic retinopathy (DR) is a major sight-threatening microvascular complication in individuals with diabetes. Systemic inflammation combined with oxidative stress is thought to capture most of the complexities involved in the pathology of diabetic retinopathy. A high level of neutrophil–lymphocyte ratio (NLR) is an indicator of abnormal immune system activity. Current estimates of the association of NLR with diabetes and its complications are almost entirely derived from cross-sectional studies, suggesting that the nature of the reported association may be more diagnostic than prognostic. Therefore, in the present study, we examined the utility of NLR as a biomarker to predict the incidence of DR in the Scottish population. Methods The incidence of DR was defined as the time to the first diagnosis of R1 or above grade in the Scottish retinopathy grading scheme from type 2 diabetes diagnosis. The effect of NLR and its interactions were explored using a competing risks survival model adjusting for other risk factors and accounting for deaths. The Fine and Gray subdistribution hazard model (FGR) was used to predict the effect of NLR on the incidence of DR. Results We analysed data from 23,531 individuals with complete covariate information. At 10 years, 8416 (35.8%) had developed DR and 2989 (12.7%) were lost to competing events (death) without developing DR and 12,126 individuals did not have DR. The median (interquartile range) level of NLR was 2.04 (1.5 to 2.7). The optimal NLR cut-off value to predict retinopathy incidence was 3.04. After accounting for competing risks at 10 years, the cumulative incidence of DR and deaths without DR were 50.7% and 21.9%, respectively. NLR was associated with incident DR in both Cause-specific hazard (CSH = 1.63; 95% CI: 1.28–2.07) and FGR models the subdistribution hazard (sHR = 2.24; 95% CI: 1.70–2.94). Both age and HbA1c were found to modulate the association between NLR and the risk of DR. Conclusions The current study suggests that NLR has a promising potential to predict DR incidence in the Scottish population, especially in individuals less than 65 years and in those with well-controlled glycaemic status

Meta-analysis of genome-wide association studies on the intolerance of angiotensin-converting enzyme inhibitors

Objectives—To identify SNPs associated with switching from an ACE-inhibitor to an angiotensin receptor blocker (ARB). Methods—Two cohorts of patients starting ACE-inhibitors were identified within the Rotterdam Study in the Netherlands and the GoDARTS study in Scotland. Cases were intolerant subjects who switched from an ACE-inhibitor to an ARB, controls were subjects who used ACE-inhibitors continuously for at least 2 years and did not switch. GWAS using an additive model was run in these sets and results were meta-analysed using GWAMA. Results—972 cases out of 5 161 ACE-inhibitor starters were identified. 8 SNPs within 4 genes reached the GWAS significance level (P<5×10-8) in the meta-analysis (RBFOX3, GABRG2, SH2B1 and MBOAT1). The strongest associated SNP was located in an intron of RBFOX3, which contains a RNA binding protein (rs2061538: MAF=0.16, OR=1.52[95%CI: 1.32-1.76], p=6.2x10-9). Conclusions—These results indicate that genetic variation in abovementioned genes may increase the risk of ACE-inhibitors induced adverse reactions

Genome-wide association study of angioedema induced by angiotensin-converting enzyme inhibitor and angiotensin receptor blocker treatment

Angioedema in the mouth or upper airways is a feared adverse reaction to angiotensin-converting enzyme inhibitor (ACEi) and angiotensin receptor blocker (ARB) treatment, which is used for hypertension, heart failure and diabetes complications. This candidate gene and genome-wide association study aimed to identify genetic variants predisposing to angioedema induced by these drugs. The discovery cohort consisted of 173 cases and 4890 controls recruited in Sweden. In the candidate gene analysis, ETV6, BDKRB2, MME, and PRKCQ were nominally associated with angioedema (p < 0.05), but did not pass Bonferroni correction for multiple testing (p < 2.89 × 10−5). In the genome-wide analysis, intronic variants in the calcium-activated potassium channel subunit alpha-1 (KCNMA1) gene on chromosome 10 were significantly associated with angioedema (p < 5 × 10−8). Whilst the top KCNMA1 hit was not significant in the replication cohort (413 cases and 599 ACEi-exposed controls from the US and Northern Europe), a meta-analysis of the replication and discovery cohorts (in total 586 cases and 1944 ACEi-exposed controls) revealed that each variant allele increased the odds of experiencing angioedema 1.62 times (95% confidence interval 1.05–2.50, p = 0.030). Associated KCNMA1 variants are not known to be functional, but are in linkage disequilibrium with variants in transcription factor binding sites active in relevant tissues. In summary, our data suggest that common variation in KCNMA1 is associated with risk of angioedema induced by ACEi or ARB treatment. Future whole exome or genome sequencing studies will show whether rare variants in KCNMA1 or other genes contribute to the risk of ACEi- and ARB-induced angioedema

Genetic risk factors for ischaemic stroke and its subtypes (the METASTROKE Collaboration): a meta-analysis of genome-wide association studies

&lt;p&gt;Background - Various genome-wide association studies (GWAS) have been done in ischaemic stroke, identifying a few loci associated with the disease, but sample sizes have been 3500 cases or less. We established the METASTROKE collaboration with the aim of validating associations from previous GWAS and identifying novel genetic associations through meta-analysis of GWAS datasets for ischaemic stroke and its subtypes.&lt;/p&gt; &lt;p&gt;Methods - We meta-analysed data from 15 ischaemic stroke cohorts with a total of 12 389 individuals with ischaemic stroke and 62 004 controls, all of European ancestry. For the associations reaching genome-wide significance in METASTROKE, we did a further analysis, conditioning on the lead single nucleotide polymorphism in every associated region. Replication of novel suggestive signals was done in 13 347 cases and 29 083 controls.&lt;/p&gt; &lt;p&gt;Findings - We verified previous associations for cardioembolic stroke near PITX2 (p=2·8×10−16) and ZFHX3 (p=2·28×10−8), and for large-vessel stroke at a 9p21 locus (p=3·32×10−5) and HDAC9 (p=2·03×10−12). Additionally, we verified that all associations were subtype specific. Conditional analysis in the three regions for which the associations reached genome-wide significance (PITX2, ZFHX3, and HDAC9) indicated that all the signal in each region could be attributed to one risk haplotype. We also identified 12 potentially novel loci at p&#60;5×10−6. However, we were unable to replicate any of these novel associations in the replication cohort.&lt;/p&gt; &lt;p&gt;Interpretation - Our results show that, although genetic variants can be detected in patients with ischaemic stroke when compared with controls, all associations we were able to confirm are specific to a stroke subtype. This finding has two implications. First, to maximise success of genetic studies in ischaemic stroke, detailed stroke subtyping is required. Second, different genetic pathophysiological mechanisms seem to be associated with different stroke subtypes.&lt;/p&gt