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Träfflista för sökning "WFRF:(Key Timothy J.) ;pers:(Wareham Nicholas J);pers:(Navarro Carmen)"

Search: WFRF:(Key Timothy J.) > Wareham Nicholas J > Navarro Carmen

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1.
  • Wessel, Jennifer, et al. (author)
  • Low-frequency and rare exome chip variants associate with fasting glucose and type 2 diabetes susceptibility
  • 2015
  • In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 6
  • Journal article (peer-reviewed)abstract
    • Fasting glucose and insulin are intermediate traits for type 2 diabetes. Here we explore the role of coding variation on these traits by analysis of variants on the HumanExome BeadChip in 60,564 non-diabetic individuals and in 16,491 T2D cases and 81,877 controls. We identify a novel association of a low-frequency nonsynonymous SNV in GLP1R (A316T; rs10305492; MAF = 1.4%) with lower FG (beta = -0.09 +/- 0.01 mmol l(-1), P = 3.4 x 10(-12)), T2D risk (OR[95% CI] = 0.86[0.76-0.96], P = 0.010), early insulin secretion (beta = -0.07 +/- 0.035 pmol(insulin) mmol(glucose)(-1), P = 0.048), but higher 2-h glucose (beta = 0.16 +/- 0.05 mmol l(-1), P = 4.3 x 10(-4)). We identify a gene-based association with FG at G6PC2 (p(SKAT) = 6.8 x 10(-6)) driven by four rare protein-coding SNVs (H177Y, Y207S, R283X and S324P). We identify rs651007 (MAF = 20%) in the first intron of ABO at the putative promoter of an antisense lncRNA, associating with higher FG (beta = 0.02 +/- 0.004 mmol l(-1), P = 1.3 x 10(-8)). Our approach identifies novel coding variant associations and extends the allelic spectrum of variation underlying diabetes-related quantitative traits and T2D susceptibility.
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2.
  • Scott, Robert A., et al. (author)
  • A genomic approach to therapeutic target validation identifies a glucose-lowering GLP1R variant protective for coronary heart disease
  • 2016
  • In: Science Translational Medicine. - : American Association for the Advancement of Science (AAAS). - 1946-6234 .- 1946-6242. ; 8:341
  • Journal article (peer-reviewed)abstract
    • Regulatory authorities have indicated that new drugs to treat type 2 diabetes (T2D) should not be associated with an unacceptable increase in cardiovascular risk. Human genetics may be able to guide development of antidiabetic therapies by predicting cardiovascular and other health endpoints. We therefore investigated the association of variants in six genes that encode drug targets for obesity or T2D with a range of metabolic traits in up to 11,806 individuals by targeted exome sequencing and follow-up in 39,979 individuals by targeted genotyping, with additional in silico follow-up in consortia. We used these data to first compare associations of variants in genes encoding drug targets with the effects of pharmacological manipulation of those targets in clinical trials. We then tested the association of those variants with disease outcomes, including coronary heart disease, to predict cardiovascular safety of these agents. A low-frequency missense variant (Ala316Thr; rs10305492) in the gene encoding glucagon-like peptide-1 receptor (GLP1R), the target of GLP1R agonists, was associated with lower fasting glucose and T2D risk, consistent with GLP1R agonist therapies. The minor allele was also associated with protection against heart disease, thus providing evidence that GLP1R agonists are not likely to be associated with an unacceptable increase in cardiovascular risk. Our results provide an encouraging signal that these agents may be associated with benefit, a question currently being addressed in randomized controlled trials. Genetic variants associated with metabolic traits and multiple disease outcomes can be used to validate therapeutic targets at an early stage in the drug development process.
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3.
  • Lunetta, Kathryn L., et al. (author)
  • Rare coding variants and X-linked loci associated with age at menarche
  • 2015
  • In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 6
  • Journal article (peer-reviewed)abstract
    • More than 100 loci have been identified for age at menarche by genome-wide association studies; however, collectively these explain only similar to 3% of the trait variance. Here we test two overlooked sources of variation in 192,974 European ancestry women: low-frequency proteincoding variants and X-chromosome variants. Five missense/nonsense variants (in ALMS1/LAMB2/TNRC6A/TACR3/PRKAG1) are associated with age at menarche (minor allele frequencies 0.08-4.6%; effect sizes 0.08-1.25 years per allele; P<5 x 10(-8)). In addition, we identify common X-chromosome loci at IGSF1 (rs762080, P = 9.4 x 10(-13)) and FAAH2 (rs5914101, P = 4.9 x 10(-10)). Highlighted genes implicate cellular energy homeostasis, post-transcriptional gene silencing and fatty-acid amide signalling. A frequently reported mutation in TACR3 for idiopathic hypogonatrophic hypogonadism (p.W275X) is associated with 1.25-year-later menarche (P = 2.8 x 10(-11)), illustrating the utility of population studies to estimate the penetrance of reportedly pathogenic mutations. Collectively, these novel variants explain similar to 0.5% variance, indicating that these overlooked sources of variation do not substantially explain the 'missing heritability' of this complex trait.
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4.
  • Lotta, Luca A., et al. (author)
  • Integrative genomic analysis implicates limited peripheral adipose storage capacity in the pathogenesis of human insulin resistance
  • 2017
  • In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 49:1, s. 17-26
  • Journal article (peer-reviewed)abstract
    • Insulin resistance is a key mediator of obesity-related cardiometabolic disease, yet the mechanisms underlying this link remain obscure. Using an integrative genomic approach, we identify 53 genomic regions associated with insulin resistance phenotypes (higher fasting insulin levels adjusted for BMI, lower HDL cholesterol levels and higher triglyceride levels) and provide evidence that their link with higher cardiometabolic risk is underpinned by an association with lower adipose mass in peripheral compartments. Using these 53 loci, we show a polygenic contribution to familial partial lipodystrophy type 1, a severe form of insulin resistance, and highlight shared molecular mechanisms in common/mild and rare/severe insulin resistance. Population-level genetic analyses combined with experiments in cellular models implicate CCDC92, DNAH10 and L3MBTL3 as previously unrecognized molecules influencing adipocyte differentiation. Our findings support the notion that limited storage capacity of peripheral adipose tissue is an important etiological component in insulin-resistant cardiometabolic disease and highlight genes and mechanisms underpinning this link.
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5.
  • Kroeger, Janine, et al. (author)
  • Adherence to predefined dietary patterns and incident type 2 diabetes in European populations: EPIC-InterAct Study
  • 2014
  • In: Diabetologia. - : Springer Science and Business Media LLC. - 1432-0428 .- 0012-186X. ; 57:2, s. 321-333
  • Journal article (peer-reviewed)abstract
    • Few studies have investigated the relationship between predefined dietary patterns and type 2 diabetes incidence; little is known about the generalisability of these associations. We aimed to assess the association between predefined dietary patterns and type 2 diabetes risk in European populations. From among a case-cohort of 12,403 incident diabetes cases and 16,154 subcohort members nested within the prospective European Prospective Investigation into Cancer and Nutrition study, we used data on 9,682 cases and 12,595 subcohort participants from seven countries. Habitual dietary intake was assessed at baseline with country-specific dietary questionnaires. Two diet-quality scores (alternative Healthy Eating Index [aHEI], Dietary Approaches to Stop Hypertension [DASH] score) and three reduced rank regression (RRR)-derived dietary-pattern scores were constructed. Country-specific HRs were calculated and combined using a random-effects meta-analysis. After multivariable adjustment, including body size, the aHEI and DASH scores were not significantly associated with diabetes, although for the aHEI there was a tendency towards an inverse association in countries with higher mean age. We observed inverse associations of the three RRR-derived dietary-pattern scores with diabetes: HRs (95% CIs) for a 1-SD difference were 0.91 (0.86, 0.96), 0.92 (0.84, 1.01) and 0.87 (0.82, 0.92). Random-effects meta-analyses revealed heterogeneity between countries that was explainable by differences in the age of participants or the distribution of dietary intake. Adherence to specific RRR-derived dietary patterns, commonly characterised by high intake of fruits or vegetables and low intake of processed meat, sugar-sweetened beverages and refined grains, may lower type 2 diabetes risk.
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6.
  • Langenberg, Claudia, et al. (author)
  • Gene-Lifestyle Interaction and Type 2 Diabetes: The EPIC InterAct Case-Cohort Study.
  • 2014
  • In: PLoS Medicine. - : Public Library of Science (PLoS). - 1549-1676 .- 1549-1277. ; 11:5
  • Journal article (peer-reviewed)abstract
    • Understanding of the genetic basis of type 2 diabetes (T2D) has progressed rapidly, but the interactions between common genetic variants and lifestyle risk factors have not been systematically investigated in studies with adequate statistical power. Therefore, we aimed to quantify the combined effects of genetic and lifestyle factors on risk of T2D in order to inform strategies for prevention.
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7.
  • Li, Sherly X., et al. (author)
  • Interaction between genes and macronutrient intake on the risk of developing type 2 diabetes : systematic review and findings from European Prospective Investigation into Cancer (EPIC)-InterAct
  • 2017
  • In: American Journal of Clinical Nutrition. - : American society for nutrition. - 0002-9165 .- 1938-3207. ; 106:1, s. 263-275
  • Research review (peer-reviewed)abstract
    • Background: Gene-diet interactions have been reported to contribute to the development of type 2 diabetes (T2D). However, to our knowledge, few examples have been consistently replicated to date. Objective: We aimed to identify existing evidence for genemacronutrient interactions and T2D and to examine the reported interactions in a large-scale study. Design: We systematically reviewed studies reporting genemacronutrient interactions and T2D. We searched the MEDLINE, Human Genome Epidemiology Network, and WHO International Clinical Trials Registry Platform electronic databases to identify studies published up to October 2015. Eligibility criteria included assessment of macronutrient quantity (e.g., total carbohydrate) or indicators of quality (e. g., dietary fiber) by use of self-report or objective biomarkers of intake. Interactions identified in the review were subsequently examined in the EPIC (European Prospective Investigation into Cancer)-InterAct case-cohort study (n = 21,148, with 9403 T2D cases; 8 European countries). Prentice-weighted Cox regression was used to estimate countryspecific HRs, 95% CIs, and P-interaction values, which were then pooled by random-effects meta-analysis. A primary model was fitted by using the same covariates as reported in the published studies, and a second model adjusted for additional covariates and estimated the effects of isocaloric macronutrient substitution. Results: Thirteen observational studies met the eligibility criteria (n < 1700 cases). Eight unique interactions were reported to be significant between macronutrients [carbohydrate, fat, saturated fat, dietary fiber, and glycemic load derived from self-report of dietary intake and circulating n-3 (v-3) polyunsaturated fatty acids] and genetic variants in or near transcription factor 7-like 2 (TCF7L2), gastric inhibitory polypeptide receptor (GIPR), caveolin 2 (CAV2), and peptidase D (PEPD) (P-interaction, 0.05). We found no evidence of interaction when we tried to replicate previously reported interactions. In addition, no interactions were detected in models with additional covariates. Conclusions: Eight gene-macronutrient interactions were identified for the risk of T2D from the literature. These interactions were not replicated in the EPIC-InterAct study, which mirrored the analyses undertaken in the original reports. Our findings highlight the importance of independent replication of reported interactions.
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8.
  • Agudo, Antonio, et al. (author)
  • Impact of Cigarette Smoking on Cancer Risk in the European Prospective Investigation into Cancer and Nutrition Study
  • 2012
  • In: Journal of Clinical Oncology. - 0732-183X .- 1527-7755. ; 30:36, s. 4550-4557
  • Journal article (peer-reviewed)abstract
    • Purpose Our aim was to assess the impact of cigarette smoking on the risk of the tumors classified by the International Agency for Research on Cancer as causally associated with smoking, referred to as tobacco-related cancers (TRC). Methods The study population included 441,211 participants (133,018 men and 308,193 women) from the European Prospective Investigation Into Cancer and Nutrition. We investigated 14,563 participants who developed a TRC during an average follow-up of 11 years. The impact of smoking cigarettes on cancer risk was assessed by the population attributable fraction (AF(p)), calculated using the adjusted hazard ratios and 95% CI for current and former smokers, plus either the prevalence of smoking among cancer cases or estimates from surveys in representative samples of the population in each country. Results The proportion of all TRC attributable to cigarette smoking was 34.9% (95% CI, 32.5 to 37.4) using the smoking prevalence among cases and 36.2% (95% CI, 33.7 to 38.6) using the smoking prevalence from the population. The AF(p) were above 80% for cancers of the lung and larynx, between 20% and 50% for most respiratory and digestive cancers and tumors from the lower urinary tract, and below 20% for the remaining TRC. Conclusion Using data on cancer incidence for 2008 and our AF(p) estimates, about 270,000 new cancer diagnoses per year can be considered attributable to cigarette smoking in the eight European countries with available data for both men and women (Italy, Spain, United Kingdom, the Netherlands, Greece, Germany, Sweden, Denmark). 
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9.
  • Lotta, Luca A., et al. (author)
  • Association between low-density lipoprotein cholesterol-lowering genetic variants and risk of type 2 diabetes : A meta-analysis
  • 2016
  • In: JAMA: The Journal of the American Medical Association. - : American Medical Association (AMA). - 0098-7484 .- 1538-3598. ; 316:13, s. 1383-1391
  • Journal article (peer-reviewed)abstract
    • IMPORTANCE Low-density lipoprotein cholesterol (LDL-C)-lowering alleles in or near NPC1L1 or HMGCR, encoding the respective molecular targets of ezetimibe and statins, have previously been used as proxies to study the efficacy of these lipid-lowering drugs. Alleles near HMGCR are associated with a higher risk of type 2 diabetes, similar to the increased incidence of new-onset diabetes associated with statin treatment in randomized clinical trials. It is unknown whether alleles near NPC1L1 are associated with the risk of type 2 diabetes. OBJECTIVE To investigate whether LDL-C-lowering alleles in or near NPC1L1 and other genes encoding current or prospective molecular targets of lipid-lowering therapy (ie, HMGCR, PCSK9, ABCG5/G8, LDLR) are associated with the risk of type 2 diabetes. DESIGN, SETTING, AND PARTICIPANTS The associations with type 2 diabetes and coronary artery disease of LDL-C-lowering genetic variants were investigated in meta-analyses of genetic association studies. Meta-analyses included 50 775 individuals with type 2 diabetes and 270 269 controls and 60 801 individuals with coronary artery disease and 123 504 controls. Data collection took place in Europe and the United States between 1991 and 2016. EXPOSURES Low-density lipoprotein cholesterol-lowering alleles in or near NPC1L1, HMGCR, PCSK9, ABCG5/G8, and LDLR. MAIN OUTCOMES AND MEASURES Odds ratios (ORs) for type 2 diabetes and coronary artery disease. RESULTS Low-density lipoprotein cholesterol-lowering genetic variants at NPC1L1 were inversely associated with coronary artery disease (OR for a genetically predicted 1-mmol/L [38.7-mg/dL] reduction in LDL-C of 0.61 [95%CI, 0.42-0.88]; P = .008) and directly associated with type 2 diabetes (OR for a genetically predicted 1-mmol/L reduction in LDL-C of 2.42 [95%CI, 1.70-3.43]; P .001). For PCSK9 genetic variants, the OR for type 2 diabetes per 1-mmol/L genetically predicted reduction in LDL-C was 1.19 (95%CI, 1.02-1.38; P = .03). For a given reduction in LDL-C, genetic variants were associated with a similar reduction in coronary artery disease risk (I2 = 0%for heterogeneity in genetic associations; P = .93). However, associations with type 2 diabetes were heterogeneous (I2 = 77.2%; P = .002), indicating gene-specific associations with metabolic risk of LDL-C-lowering alleles. CONCLUSIONS AND RELEVANCE In thismeta-analysis, exposure to LDL-C-lowering genetic variants in or near NPC1L1 and other geneswas associated with a higher risk of type 2 diabetes. These data provide insights into potential adverse effects of LDL-C-lowering therapy.
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