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- Albrechtsen, A., et al.
(author)
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Exome sequencing-driven discovery of coding polymorphisms associated with common metabolic phenotypes
- 2013
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In: Diabetologia. - : Springer Science and Business Media LLC. - 0012-186X .- 1432-0428. ; 56:2, s. 298-310
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Journal article (peer-reviewed)abstract
- 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. The study comprised three stages. We performed medium-depth (8x) 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. 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 x 10(-14)), COBLL1 (type 2 diabetes: MAF 12.5%, OR 0.88, p = 1.2 x 10(-11)) and MACF1 (type 2 diabetes: MAF 23.4%, OR 1.10, p = 8.2 x 10(-10)). 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.
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- Gram, Inger T, et al.
(author)
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Cigarette smoking and risk of histological subtypes of epithelial ovarian cancer in the EPIC cohort study
- 2012
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In: International Journal of Cancer. - : Wiley. - 0020-7136 .- 1097-0215. ; 130:9, s. 2204-2210
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Journal article (peer-reviewed)abstract
- New data regarding a positive association between smoking and risk of epithelial ovarian cancer (EOC), especially the mucinous tumor type, has started to emerge. The purpose of this study was to examine the association between different measures of smoking exposures and subtypes of EOC in a large cohort of women from 10 European countries. The European Prospective Investigation into Cancer and Nutrition (EPIC) cohort is a multicenter prospective study initiated in 1992. The questionnaires included data about dietary, lifestyle, and health factors. Information about cigarette smoking was collected from individuals in all participating countries. We used Cox proportional hazard regression models to estimate hazard ratio (HR) of EOC overall and serous, mucinous, and endometroid histological subtypes, with 95% confidence intervals (CIs) associated with different measures of smoking exposures adjusting for confounding variables. Altogether 836 incident EOC cases were identified among 326,831 women. The tumors were classified as 400 serous, 83 mucinous, 80 endometroid, 35 clear cell, and 238 unspecified. Compared with never smokers, current smokers had a significantly increased risk for mucinous tumors [HR = 1.85 (95% CI 1.08-3.16)] and those smoking more than 10 cigarettes per day had a doubling in risk [HR = 2.25(95% CI 1.26-4.03)] as did those who had smoked less than 15 pack-years of cigarettes [HR = 2.18 (95% CI 1.07-4.43)]. The results from the EPIC study add further evidence that smoking increases risk of mucinous ovarian cancer and support the notion that the effect of smoking varies according to histological subtype.
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