Exome sequencing-driven discovery of coding polymorphisms associated with common metabolic phenotypes

AIMS/HYPOTHESIS

Human complex metabolic traits are in part regulated by genetic determinants. Here we applied exome sequencing to identify novel associations of coding polymorphisms at minor allele frequencies (MAFs) >1% with common metabolic phenotypes.

METHODS

The study comprised three stages. We performed medium-depth (8×) whole exome sequencing in 1,000 cases with type 2 diabetes, BMI >27.5 kg/m(2) and hypertension and in 1,000 controls (stage 1). We selected 16,192 polymorphisms nominally associated (p < 0.05) with case-control status, from four selected annotation categories or from loci reported to associate with metabolic traits. These variants were genotyped in 15,989 Danes to search for association with 12 metabolic phenotypes (stage 2). In stage 3, polymorphisms showing potential associations were genotyped in a further 63,896 Europeans.

RESULTS

Exome sequencing identified 70,182 polymorphisms with MAF >1%. In stage 2 we identified 51 potential associations with one or more of eight metabolic phenotypes covered by 45 unique polymorphisms. In meta-analyses of stage 2 and stage 3 results, we demonstrated robust associations for coding polymorphisms in CD300LG (fasting HDL-cholesterol: MAF 3.5%, p = 8.5 × 10(-14)), COBLL1 (type 2 diabetes: MAF 12.5%, OR 0.88, p = 1.2 × 10(-11)) and MACF1 (type 2 diabetes: MAF 23.4%, OR 1.10, p = 8.2 × 10(-10)).

CONCLUSIONS/INTERPRETATION

We applied exome sequencing as a basis for finding genetic determinants of metabolic traits and show the existence of low-frequency and common coding polymorphisms with impact on common metabolic traits. Based on our study, coding polymorphisms with MAF above 1% do not seem to have particularly high effect sizes on the measured metabolic traits.

The publication of Diabetes UK position statements and care recommendations; a virtual issue

Diabetes UK is the charity that cares for, connects with and campaigns on behalf of all people affected by and at risk of diabetes. Founded in 1934 by the novelist H. G. Wells and Dr R. D. Lawrence, the charity has always combined the expertise of lay and professional members to achieve its mission to improve the lives of people with diabetes and to work towards a future without diabetes.

Sequencing PDX1 (insulin promoter factor 1) in 1788 UK individuals found 5% had a low frequency coding variant, but these variants are not associated with Type 2 diabetes

AIM

Genome-wide association studies have identified >30 common variants associated with Type 2 diabetes (>5% minor allele frequency). These variants have small effects on individual risk and do not account for a large proportion of the heritable component of the disease. Monogenic forms of diabetes are caused by mutations that occur in <1:2000 individuals and follow strict patterns of inheritance. In contrast, the role of low frequency genetic variants (minor allele frequency 0.1-5%) in Type 2 diabetes is not known. The aim of this study was to assess the role of low frequency PDX1 (also called IPF1) variants in Type 2 diabetes.

METHODS

We sequenced the coding and flanking intronic regions of PDX1 in 910 patients with Type 2 diabetes and 878 control subjects.

RESULTS

We identified a total of 26 variants that occurred in 5.3% of individuals, 14 of which occurred once. Only D76N occurred in >1%. We found no difference in carrier frequency between patients (5.7%) and control subjects (5.0%) (P=0.46). There were also no differences between patients and control subjects when analyses were limited to subsets of variants. The strongest subset were those variants in the DNA binding domain where all five variants identified were only found in patients (P=0.06).

CONCLUSION

Approximately 5% of UK individuals carry a PDX1 variant, but there is no evidence that these variants, either individually or cumulatively, predispose to Type 2 diabetes. Further studies will need to consider strategies to assess the role of multiple variants that occur in <1 in 1000 individuals.

Apolipoproteins, cardiovascular risk and statin response in type 2 diabetes: the Collaborative Atorvastatin Diabetes Study (CARDS)

AIMS/HYPOTHESIS

Controversy surrounds whether the ratio of apolipoprotein B (ApoB) to apolipoprotein A-I (ApoA-I) is the best lipoprotein discriminator of CHD risk in non-diabetic populations, but the issue has never been investigated in type 2 diabetes.

METHODS

In 2,627 participants without known vascular disease in the Collaborative Atorvastatin Diabetes Study, ApoB, ApoA-I, LDL-cholesterol (LDLC) and HDL-cholesterol (HDLC) were assayed at baseline.

RESULTS

There were 108 CHD and 59 stroke endpoints over 3.9 years. The ApoB:A-I ratio at baseline was the lipoprotein variable most closely predicting CHD risk both by comparison of the hazard ratio for a 1 SD change or tertiles of frequency distribution. The areas under the receiver-operator curve for the ApoB:ApoA-I and the LDLC to HDLC [corrected] ratios, although not significantly different from each other, were greater (p = 0.0005 and p = 0.0125 respectively) than that of non-HDLC:HDLC. The 27% decrease in the ApoB:ApoA-I ratio on atorvastatin predicted a 32% (95% CI 5.4-51.2%) risk reduction in CHD, close to the 36% decrease observed. Neither the ApoB:ApoA-I nor any other lipoprotein concentration or ratio predicted the stroke outcome.

CONCLUSIONS/INTERPRETATION

Overall, the ApoB:ApoA-I ratio improved on the non-HDLC:HDLC ratio in predicting CHD, but, depending on the assessment chosen, its superiority over LDLC:HDLC may be marginal. The statin-induced decrease in stroke risk may not be lipoprotein mediated.

TRIAL REGISTRATION

ClinicalTrials.gov NCT00327418.

FUNDING

The study was supported by unrestricted grants from Diabetes UK, the Department of Health and Pfizer to the University of Manchester and to University College, London.

Stroke prediction and stroke prevention with atorvastatin in the Collaborative Atorvastatin Diabetes Study (CARDS)

AIMS

Patients with Type 2 diabetes have an elevated risk of stroke. The role of lipid levels and diabetes-specific factors in risk prediction of stroke is unclear, and estimates of efficacy of lipid-lowering therapy vary between trials. We examined predictors of stroke and the effect of atorvastatin on specific stroke subtypes in Type 2 diabetes in the Collaborative Atorvastatin Diabetes Study (CARDS) [a trial of 2838 participants with mean low-density lipoprotein cholesterol < 4.14 mmol/l, no history of macrovascular disease and randomized to atorvastatin 10 mg daily or placebo].

METHODS

Median follow-up was 3.9 years. Cox regression models were used to estimate the effect of atorvastatin on stroke rate and risk of stroke associated with baseline risk factors. Risk factors that predicted stroke in univariate models were examined in a multivariable model.

RESULTS

Independent risk factors predicting stroke were age [10-year increments; hazard ratio (HR) 2.3, P < 0.001], microalbuminuria (albumin : creatinine ratio > 2.5 mg/mmol; HR 2.0, P = 0.007) and glycaemic control (HbA(1c) > 10%; HR 2.7, P = 0.007). Women were at lower risk of stroke (HR 0.3, P = 0.004). Lipids did not predict stroke. Of 60 first strokes, 47 were non-haemorrhagic, 13 were indeterminate and none was definitely haemorrhagic. Atorvastatin treatment was associated with 50% reduction in non-haemorrhagic stroke (95% confidence interval 9%-72%P = 0.024), similar to the 48% reduction (11%-69%) for all strokes combined.

CONCLUSIONS

Diabetes-specific risk factors are important predictors of stroke in Type 2 diabetes. Despite the lack of association between baseline lipids and first stroke, there was a reduction of 50% of non-haemorrhagic strokes associated with atorvastatin treatment in the CARDS population.

Parental influence on the spectrum of type 2 diabetes in the offspring among Indians

AIM

Familial aggregation of type 2 diabetes and its vascular complications is strong in Indians. In this study, we have analysed whether the age of the parent at birth of the offspring had any influence on the age at diagnosis of diabetes and age at onset of microvascular complications in the diabetic offspring.

METHODS

Families with either a type 2 diabetic father or mother and a type 2 diabetic offspring, all of whom had been tested at our centre were included in this study (n = 300, father--122, mother--178, offspring male --201, female--99). Anthropometric details, age at diagnosis of diabetes, age at onset of complications and duration of diabetes were recorded. All relevant clinical and investigatory tests were done and appropriate statistical analyses were done.

RESULTS

Age at onset of diabetes was lower in the offspring than in their parents at least by a decade. The age at diagnosis of diabetes in the offspring was determined inversely by the age of the parent at childbirth (p<0.001) and positively by the age of onset of diabetes and the presence of complications in the parents (both p<0.0001). Moreover, the age at diagnosis of complications in the offspring were determined inversely by the age of the parent at childbirth (p=0.0001) and positively by the age of onset of complications in the parents (p=0.0009).

DISCUSSION

A younger parental age at childbirth was protective to the offspring in that the offspring developed diabetes and the complications at an older age.