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31.
  • Scott, Robert A., et al. (författare)
  • Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways
  • 2012
  • Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 44:9, s. 991-1005
  • Tidskriftsartikel (refereegranskat)abstract
    • Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have increased the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q < 0.05). Loci influencing fasting insulin concentration showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional analysis of these newly discovered loci will further improve our understanding of glycemic control.
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32.
  • Scott, R. A., et al. (författare)
  • The link between family history and risk of type 2 diabetes is not explained by anthropometric, lifestyle or genetic risk factors : the EPIC-InterAct study
  • 2013
  • Ingår i: Diabetologia. - : Springer. - 0012-186X .- 1432-0428. ; 56:1, s. 60-69
  • Tidskriftsartikel (refereegranskat)abstract
    • Aims/hypothesis: Although a family history of type 2 diabetes is a strong risk factor for the disease, the factors mediating this excess risk are poorly understood. In the InterAct case-cohort study, we investigated the association between a family history of diabetes among different family members and the incidence of type 2 diabetes, as well as the extent to which genetic, anthropometric and lifestyle risk factors mediated this association.Methods: A total of 13,869 individuals (including 6,168 incident cases of type 2 diabetes) had family history data available, and 6,887 individuals had complete data on all mediators. Country-specific Prentice-weighted Cox models were fitted within country, and HRs were combined using random effects meta-analysis. Lifestyle and anthropometric measurements were performed at baseline, and a genetic risk score comprising 35 polymorphisms associated with type 2 diabetes was created.Results: A family history of type 2 diabetes was associated with a higher incidence of the condition (HR 2.72, 95% CI 2.48, 2.99). Adjustment for established risk factors including BMI and waist circumference only modestly attenuated this association (HR 2.44, 95% CI 2.03, 2.95); the genetic score alone explained only 2% of the family history-associated risk of type 2 diabetes. The greatest risk of type 2 diabetes was observed in those with a biparental history of type 2 diabetes (HR 5.14, 95% CI 3.74, 7.07) and those whose parents had been diagnosed with diabetes at a younger age (<50 years; HR 4.69, 95% CI 3.35, 6.58), an effect largely confined to a maternal family history.Conclusions/interpretation: Prominent lifestyle, anthropometric and genetic risk factors explained only a marginal proportion of the excess risk associated with family history, highlighting the fact that family history remains a strong, independent and easily assessed risk factor for type 2 diabetes. Discovering factors that will explain the association of family history with type 2 diabetes risk will provide important insight into the aetiology of type 2 diabetes.
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33.
  • Albrechtsen, A., et al. (författare)
  • Exome sequencing-driven discovery of coding polymorphisms associated with common metabolic phenotypes
  • 2013
  • Ingår i: Diabetologia. - : Springer Science and Business Media LLC. - 0012-186X .- 1432-0428. ; 56:2, s. 298-310
  • Tidskriftsartikel (refereegranskat)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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36.
  • Ekelund, U., et al. (författare)
  • Physical activity reduces the risk of incident type 2 diabetes in general and in abdominally lean and obese men and women : the EPIC-InterAct Study
  • 2012
  • Ingår i: Diabetologia. - : Springer Science and Business Media LLC. - 0012-186X .- 1432-0428. ; 55:7, s. 1944-1952
  • Tidskriftsartikel (refereegranskat)abstract
    • We examined the independent and combined associations of physical activity and obesity with incident type 2 diabetes in men and women. The InterAct case-cohort study consists of 12,403 incident type 2 diabetes cases and a randomly selected subcohort of 16,154 individuals, drawn from a total cohort of 340,234 participants with 3.99 million person-years of follow-up. Physical activity was assessed by a four-category index. Obesity was measured by BMI and waist circumference (WC). Associations between physical activity, obesity and case-ascertained incident type 2 diabetes were analysed by Cox regression after adjusting for educational level, smoking status, alcohol consumption and energy intake. In combined analyses, individuals were stratified according to physical activity level, BMI and WC. A one-category difference in physical activity (equivalent to approximately 460 and 365 kJ/day in men and women, respectively) was independently associated with a 13% (HR 0.87, 95% CI 0.80, 0.94) and 7% (HR 0.93, 95% CI 0.89, 0.98) relative reduction in the risk of type 2 diabetes in men and women, respectively. Lower levels of physical activity were associated with an increased risk of diabetes across all strata of BMI. Comparing inactive with active individuals, the HRs were 1.44 (95% CI 1.11, 1.87) and 1.38 (95% CI 1.17, 1.62) in abdominally lean and obese inactive men, respectively, and 1.57 (95% CI 1.19, 2.07) and 1.19 (95% CI 1.01, 1.39) in abdominally lean and obese inactive women, respectively. Physical activity is associated with a reduction in the risk of developing type 2 diabetes across BMI categories in men and women, as well as in abdominally lean and obese men and women.
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37.
  • Kilpeläinen, Tuomas O, et al. (författare)
  • Physical activity attenuates the influence of FTO variants on obesity risk: a meta-analysis of 218,166 adults and 19,268 children.
  • 2011
  • Ingår i: PLoS medicine. - : Public Library of Science (PLoS). - 1549-1676 .- 1549-1277. ; 8:11
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND: The FTO gene harbors the strongest known susceptibility locus for obesity. While many individual studies have suggested that physical activity (PA) may attenuate the effect of FTO on obesity risk, other studies have not been able to confirm this interaction. To confirm or refute unambiguously whether PA attenuates the association of FTO with obesity risk, we meta-analyzed data from 45 studies of adults (n=218,166) and nine studies of children and adolescents (n=19,268). METHODS AND FINDINGS: All studies identified to have data on the FTO rs9939609 variant (or any proxy [r(2)>0.8]) and PA were invited to participate, regardless of ethnicity or age of the participants. PA was standardized by categorizing it into a dichotomous variable (physically inactive versus active) in each study. Overall, 25% of adults and 13% of children were categorized as inactive. Interaction analyses were performed within each study by including the FTO×PA interaction term in an additive model, adjusting for age and sex. Subsequently, random effects meta-analysis was used to pool the interaction terms. In adults, the minor (A-) allele of rs9939609 increased the odds of obesity by 1.23-fold/allele (95% CI 1.20-1.26), but PA attenuated this effect (p(interaction) =0.001). More specifically, the minor allele of rs9939609 increased the odds of obesity less in the physically active group (odds ratio =1.22/allele, 95% CI 1.19-1.25) than in the inactive group (odds ratio =1.30/allele, 95% CI 1.24-1.36). No such interaction was found in children and adolescents. CONCLUSIONS: The association of the FTO risk allele with the odds of obesity is attenuated by 27% in physically active adults, highlighting the importance of PA in particular in those genetically predisposed to obesity.
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39.
  • Pennells, Lisa, et al. (författare)
  • Equalization of four cardiovascular risk algorithms after systematic recalibration : individual-participant meta-analysis of 86 prospective studies
  • 2019
  • Ingår i: European Heart Journal. - : Oxford University Press (OUP). - 0195-668X .- 1522-9645. ; 40:7, s. 621-
  • Tidskriftsartikel (refereegranskat)abstract
    • Aims: There is debate about the optimum algorithm for cardiovascular disease (CVD) risk estimation. We conducted head-to-head comparisons of four algorithms recommended by primary prevention guidelines, before and after ‘recalibration’, a method that adapts risk algorithms to take account of differences in the risk characteristics of the populations being studied.Methods and results: Using individual-participant data on 360 737 participants without CVD at baseline in 86 prospective studies from 22 countries, we compared the Framingham risk score (FRS), Systematic COronary Risk Evaluation (SCORE), pooled cohort equations (PCE), and Reynolds risk score (RRS). We calculated measures of risk discrimination and calibration, and modelled clinical implications of initiating statin therapy in people judged to be at ‘high’ 10 year CVD risk. Original risk algorithms were recalibrated using the risk factor profile and CVD incidence of target populations. The four algorithms had similar risk discrimination. Before recalibration, FRS, SCORE, and PCE over-predicted CVD risk on average by 10%, 52%, and 41%, respectively, whereas RRS under-predicted by 10%. Original versions of algorithms classified 29–39% of individuals aged ≥40 years as high risk. By contrast, recalibration reduced this proportion to 22–24% for every algorithm. We estimated that to prevent one CVD event, it would be necessary to initiate statin therapy in 44–51 such individuals using original algorithms, in contrast to 37–39 individuals with recalibrated algorithms.Conclusion: Before recalibration, the clinical performance of four widely used CVD risk algorithms varied substantially. By contrast, simple recalibration nearly equalized their performance and improved modelled targeting of preventive action to clinical need.
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40.
  • Perry, John R. B., et al. (författare)
  • Stratifying Type 2 Diabetes Cases by BMI Identifies Genetic Risk Variants in LAMA1 and Enrichment for Risk Variants in Lean Compared to Obese Cases
  • 2012
  • Ingår i: PLoS Genetics. - : Public Library of Science (PLoS). - 1553-7404. ; 8:5
  • Tidskriftsartikel (refereegranskat)abstract
    • Common diseases such as type 2 diabetes are phenotypically heterogeneous. Obesity is a major risk factor for type 2 diabetes, but patients vary appreciably in body mass index. We hypothesized that the genetic predisposition to the disease may be different in lean (BMI<25 Kg/m(2)) compared to obese cases (BMI >= 30 Kg/m(2)). We performed two case-control genome-wide studies using two accepted cut-offs for defining individuals as overweight or obese. We used 2,112 lean type 2 diabetes cases (BMI<25 kg/m(2)) or 4,123 obese cases (BMI >= 30 kg/m(2)), and 54,412 un-stratified controls. Replication was performed in 2,881 lean cases or 8,702 obese cases, and 18,957 un-stratified controls. To assess the effects of known signals, we tested the individual and combined effects of SNPs representing 36 type 2 diabetes loci. After combining data from discovery and replication datasets, we identified two signals not previously reported in Europeans. A variant (rs8090011) in the LAMA1 gene was associated with type 2 diabetes in lean cases (P = 8.4610 29, OR = 1.13 [95% CI 1.09-1.18]), and this association was stronger than that in obese cases (P = 0.04, OR = 1.03 [95% CI 1.00-1.06]). A variant in HMG20A-previously identified in South Asians but not Europeans-was associated with type 2 diabetes in obese cases (P = 1.3 x 10(-8), OR= 1.11 [95% CI 1.07-1.15]), although this association was not significantly stronger than that in lean cases (P = 0.02, OR = 1.09 [95% CI 1.02-1.17]). For 36 known type 2 diabetes loci, 29 had a larger odds ratio in the lean compared to obese (binomial P = 0.0002). In the lean analysis, we observed a weighted per-risk allele OR = 1.13 [95% CI 1.10-1.17], P = 3.2 x 10(-14). This was larger than the same model fitted in the obese analysis where the OR = 1.06 [95% CI 1.05-1.08], P = 2.2 x 10(-16). This study provides evidence that stratification of type 2 diabetes cases by BMI may help identify additional risk variants and that lean cases may have a stronger genetic predisposition to type 2 diabetes.
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