967 resultados para WIDE ASSOCIATION
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Rapport de synthèse :Les individus HIV-positifs constituent une population à risque pour les maladies cardiovasculaires telles que |'infarctus cardiaque ou cérébrale. Celles-ci découlent d'une formation accélérée d'athéroscIérose. Ces pathologies s'expliquent en grande partie par une dyslipidémie observée au sein de cette population et qui sont dues à des facteurs externes tels que : l'immunosuppression avancée, la virémie non-contrôlée, et les effets de la thérapie antirétrovirale. Récemment, des polymorphismes nucléotidiques simples (SNP) associés à la dyslipidémie ont été mis en évidence d'une manière globale par des Genome-Wide Association Studies (GWAS). Le but principal de cette étude est d'éva|uer et de valider |'effet cumulatif des SNP identifiés dans ces GWAS pour la dyslipidémie chez des patients HIV-positifs. De plus, |'identification des facteurs non-génétiques qui contribuent à la dyslipidémie démontrent |'importance des facteurs externes, tels que mentionnés ci- dessus, et en particulier à ceux de la thérapie antirétrovirale.Les participants de l'étude proviennent de trois groupes: 426 personnes sélectionnées pour une étude précédente, 222 personnes sélectionnées de façon arbitraire dans la "Cohorte HIV Suisse" et 103 personnes sélectionnées avec un "New-Onset Diabetes mellitus" identifiées lors d'études précédentes. Ces individus ont contribué à plus de 34'000 mesures de lipides sur une durée moyenne supérieure à 7 ans. Pour l'étude, 33 SNP identifiés dans des GWAS et 9 SNP identifiés dans d'autres études publiées dans la littérature non-couverte par des GWAS ont été repris. Le génotypage a été complété pour 745 (99.2%) des 751 participants. Pour les analyses statistiques, les thérapies antirétrovirales ont été divisées en trois groupes (favorisant peu, moyennement et fortement la dyslipidémie), et trois scores génétiques ont été créés (profil favorable, moyennement favorable, non favorable/favorisant la dyslipidémie). Dans un premier temps, l'effet sur la valeur des lipides d'un ou deux allèles variants a été analysé au moyen d'un modèle de régression pour chaque SNP en ajustant le modèle pour les variables non- génétiques. Dans un deuxième temps, les SNP ayant une valeur p >= à 0.2 ont été repris dans un model Multi-SNP, ce modèle est également ajusté pour les variables non-génétiques. Puisque cette étude se base sur des SNP précédemment identifiés, celle-ci évalue uniquement l'association établie entre chaque SNP et les critères qui ont été établis au préalable, tels que : Cholestérol totale, HDL Cholestérol, non-HDL Cholestérol ou Triglycérides. Les résultats trouvés lors de |'étude confirment les résultats de la littérature. Cette étude montre que les SNP associés à la dyslipidémie doivent être analysés dans le contexte d'une thérapie antirétrovirale en tenant compte de la démographie et en considérant les valeurs du HIV (CD4+, virémie). Ces SNP montrent une tendance à prédire une dyslipidémie prolongée chez l'individu. En effet, un patient avec une thérapie antirétrovirale favorisant la dyslipidémie et un patrimoine génétique non-favorable a un risque qui est 3-f0is plus important d'avoir un Non-HDL- Cholestérol élevé, 5-fois plus important d'avoir un HDL-Cholestérol abaissé, et 4 à 5-fois plus important d'avoir une hypertriglycéridémie qu'un patient qui suit une thérapie antirétrovirale favorisant peu la dyslipidémie qui a un patrimoine génétique favorable. Vu la corrélation entre les SNP et la thérapie antirétrovirale, les cliniciens devraient intégrer les informations génétiques afin de choisir une thérapie antirétrovirale en fonction du patrimoine génétique.
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We previously used a single nucleotide polymorphism (SNP) in the CHRNA5-A3-B4 gene cluster associated with heaviness of smoking within smokers to confirm the causal effect of smoking in reducing body mass index (BMI) in a Mendelian randomisation analysis. While seeking to extend these findings in a larger sample we found that this SNP is associated with 0.74% lower body mass index (BMI) per minor allele in current smokers (95% CI -0.97 to -0.51, P = 2.00 × 10(-10)), but also unexpectedly found that it was associated with 0.35% higher BMI in never smokers (95% CI +0.18 to +0.52, P = 6.38 × 10(-5)). An interaction test confirmed that these estimates differed from each other (P = 4.95 × 10(-13)). This difference in effects suggests the variant influences BMI both via pathways unrelated to smoking, and via the weight-reducing effects of smoking. It would therefore be essentially undetectable in an unstratified genome-wide association study of BMI, given the opposite association with BMI in never and current smokers. This demonstrates that novel associations may be obscured by hidden population sub-structure. Stratification on well-characterized environmental factors known to impact on health outcomes may therefore reveal novel genetic associations.
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We performed association studies with 5,151 SNPs that were judged as likely candidate genetic variations conferring susceptibility to anorexia nervosa (AN) based on location under reported linkage peaks, previous results in the literature (182 candidate genes), brain expression, biological plausibility, and estrogen responsivity. We employed a case-control design that tested each SNP individually as well as haplotypes derived from these SNPs in 1,085 case individuals with AN diagnoses and 677 control individuals. We also performed separate association analyses using three increasingly restrictive case definitions for AN: all individuals with any subtype of AN (All AN: n = 1,085); individuals with AN with no binge eating behavior (AN with No Binge Eating: n = 687); and individuals with the restricting subtype of AN (Restricting AN: n = 421). After accounting for multiple comparisons, there were no statistically significant associations for any individual SNP or haplotype block with any definition of illness. These results underscore the importance of large samples to yield appropriate power to detect genotypic differences in individuals with AN and also motivate complementary approaches involving Genome-Wide Association (GWA) studies, Copy Number Variation (CNV) analyses, sequencing-based rare variant discovery assays, and pathway-based analysis in order to make up for deficiencies in traditional candidate gene approaches to AN.
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Recent genome-wide association studies have described many loci implicated in type 2 diabetes (T2D) pathophysiology and β-cell dysfunction but have contributed little to the understanding of the genetic basis of insulin resistance. We hypothesized that genes implicated in insulin resistance pathways might be uncovered by accounting for differences in body mass index (BMI) and potential interactions between BMI and genetic variants. We applied a joint meta-analysis approach to test associations with fasting insulin and glucose on a genome-wide scale. We present six previously unknown loci associated with fasting insulin at P < 5 × 10(-8) in combined discovery and follow-up analyses of 52 studies comprising up to 96,496 non-diabetic individuals. Risk variants were associated with higher triglyceride and lower high-density lipoprotein (HDL) cholesterol levels, suggesting a role for these loci in insulin resistance pathways. The discovery of these loci will aid further characterization of the role of insulin resistance in T2D pathophysiology.
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Nowadays, genome-wide association studies (GWAS) and genomic selection (GS) methods which use genome-wide marker data for phenotype prediction are of much potential interest in plant breeding. However, to our knowledge, no studies have been performed yet on the predictive ability of these methods for structured traits when using training populations with high levels of genetic diversity. Such an example of a highly heterozygous, perennial species is grapevine. The present study compares the accuracy of models based on GWAS or GS alone, or in combination, for predicting simple or complex traits, linked or not with population structure. In order to explore the relevance of these methods in this context, we performed simulations using approx 90,000 SNPs on a population of 3,000 individuals structured into three groups and corresponding to published diversity grapevine data. To estimate the parameters of the prediction models, we defined four training populations of 1,000 individuals, corresponding to these three groups and a core collection. Finally, to estimate the accuracy of the models, we also simulated four breeding populations of 200 individuals. Although prediction accuracy was low when breeding populations were too distant from the training populations, high accuracy levels were obtained using the sole core-collection as training population. The highest prediction accuracy was obtained (up to 0.9) using the combined GWAS-GS model. We thus recommend using the combined prediction model and a core-collection as training population for grapevine breeding or for other important economic crops with the same characteristics.
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With the trend in molecular epidemiology towards both genome-wide association studies and complex modelling, the need for large sample sizes to detect small effects and to allow for the estimation of many parameters within a model continues to increase. Unfortunately, most methods of association analysis have been restricted to either a family-based or a case-control design, resulting in the lack of synthesis of data from multiple studies. Transmission disequilibrium-type methods for detecting linkage disequilibrium from family data were developed as an effective way of preventing the detection of association due to population stratification. Because these methods condition on parental genotype, however, they have precluded the joint analysis of family and case-control data, although methods for case-control data may not protect against population stratification and do not allow for familial correlations. We present here an extension of a family-based association analysis method for continuous traits that will simultaneously test for, and if necessary control for, population stratification. We further extend this method to analyse binary traits (and therefore family and case-control data together) and accurately to estimate genetic effects in the population, even when using an ascertained family sample. Finally, we present the power of this binary extension for both family-only and joint family and case-control data, and demonstrate the accuracy of the association parameter and variance components in an ascertained family sample.
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Calcium has a pivotal role in biological functions, and serum calcium levels have been associated with numerous disorders of bone and mineral metabolism, as well as with cardiovascular mortality. Here we report results from a genome-wide association study of serum calcium, integrating data from four independent cohorts including a total of 12,865 individuals of European and Indian Asian descent. Our meta-analysis shows that serum calcium is associated with SNPs in or near the calcium-sensing receptor (CASR) gene on 3q13. The top hit with a p-value of 6.3 x 10(-37) is rs1801725, a missense variant, explaining 1.26% of the variance in serum calcium. This SNP had the strongest association in individuals of European descent, while for individuals of Indian Asian descent the top hit was rs17251221 (p = 1.1 x 10(-21)), a SNP in strong linkage disequilibrium with rs1801725. The strongest locus in CASR was shown to replicate in an independent Icelandic cohort of 4,126 individuals (p = 1.02 x 10(-4)). This genome-wide meta-analysis shows that common CASR variants modulate serum calcium levels in the adult general population, which confirms previous results in some candidate gene studies of the CASR locus. This study highlights the key role of CASR in calcium regulation.
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Many common genetic variants identified by genome-wide association studies for complex traits map to genes previously linked to rare inherited Mendelian disorders. A systematic analysis of common single-nucleotide polymorphisms (SNPs) in genes responsible for Mendelian diseases with kidney phenotypes has not been performed. We thus developed a comprehensive database of genes for Mendelian kidney conditions and evaluated the association between common genetic variants within these genes and kidney function in the general population. Using the Online Mendelian Inheritance in Man database, we identified 731 unique disease entries related to specific renal search terms and confirmed a kidney phenotype in 218 of these entries, corresponding to mutations in 258 genes. We interrogated common SNPs (minor allele frequency >5%) within these genes for association with the estimated GFR in 74,354 European-ancestry participants from the CKDGen Consortium. However, the top four candidate SNPs (rs6433115 at LRP2, rs1050700 at TSC1, rs249942 at PALB2, and rs9827843 at ROBO2) did not achieve significance in a stage 2 meta-analysis performed in 56,246 additional independent individuals, indicating that these common SNPs are not associated with estimated GFR. The effect of less common or rare variants in these genes on kidney function in the general population and disease-specific cohorts requires further research.
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The prevalence of hypertension in African Americans (AAs) is higher than in other US groups; yet, few have performed genome-wide association studies (GWASs) in AA. Among people of European descent, GWASs have identified genetic variants at 13 loci that are associated with blood pressure. It is unknown if these variants confer susceptibility in people of African ancestry. Here, we examined genome-wide and candidate gene associations with systolic blood pressure (SBP) and diastolic blood pressure (DBP) using the Candidate Gene Association Resource (CARe) consortium consisting of 8591 AAs. Genotypes included genome-wide single-nucleotide polymorphism (SNP) data utilizing the Affymetrix 6.0 array with imputation to 2.5 million HapMap SNPs and candidate gene SNP data utilizing a 50K cardiovascular gene-centric array (ITMAT-Broad-CARe [IBC] array). For Affymetrix data, the strongest signal for DBP was rs10474346 (P= 3.6 × 10(-8)) located near GPR98 and ARRDC3. For SBP, the strongest signal was rs2258119 in C21orf91 (P= 4.7 × 10(-8)). The top IBC association for SBP was rs2012318 (P= 6.4 × 10(-6)) near SLC25A42 and for DBP was rs2523586 (P= 1.3 × 10(-6)) near HLA-B. None of the top variants replicated in additional AA (n = 11 882) or European-American (n = 69 899) cohorts. We replicated previously reported European-American blood pressure SNPs in our AA samples (SH2B3, P= 0.009; TBX3-TBX5, P= 0.03; and CSK-ULK3, P= 0.0004). These genetic loci represent the best evidence of genetic influences on SBP and DBP in AAs to date. More broadly, this work supports that notion that blood pressure among AAs is a trait with genetic underpinnings but also with significant complexity.
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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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Hypertension is an important determinant of cardiovascular morbidity and mortality and has a substantial heritability, which is likely of polygenic origin. The aim of this study was to assess to what extent multiple common genetic variants contribute to blood pressure regulation in both adults and children and to assess overlap in variants between different age groups, using genome-wide profiling. Single nucleotide polymorphism sets were defined based on a meta-analysis of genome-wide association studies on systolic blood pressure and diastolic blood pressure performed by the Cohort for Heart and Aging Research in Genome Epidemiology (n=29 136), using different P value thresholds for selecting single nucleotide polymorphisms. Subsequently, genetic risk scores for systolic blood pressure and diastolic blood pressure were calculated in an independent adult population (n=2072) and a child population (n=1034). The explained variance of the genetic risk scores was evaluated using linear regression models, including sex, age, and body mass index. Genetic risk scores, including also many nongenome-wide significant single nucleotide polymorphisms, explained more of the variance than scores based only on very significant single nucleotide polymorphisms in adults and children. Genetic risk scores significantly explained ≤1.2% (P=9.6*10(-8)) of the variance in adult systolic blood pressure and 0.8% (P=0.004) in children. For diastolic blood pressure, the variance explained was similar in adults and children (1.7% [P=8.9*10(-10)] and 1.4% [P=3.3*10(-5)], respectively). These findings suggest the presence of many genetic loci with small effects on blood pressure regulation both in adults and children, indicating also a (partly) common polygenic regulation of blood pressure throughout different periods of life.
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Family studies suggest a genetic component to the etiology of chronic kidney disease (CKD) and end stage renal disease (ESRD). Previously, we identified 16 loci for eGFR in genome-wide association studies, but the associations of these single nucleotide polymorphisms (SNPs) for incident CKD or ESRD are unknown. We thus investigated the association of these loci with incident CKD in 26,308 individuals of European ancestry free of CKD at baseline drawn from eight population-based cohorts followed for a median of 7.2 years (including 2,122 incident CKD cases defined as eGFR <60ml/min/1.73m(2) at follow-up) and with ESRD in four case-control studies in subjects of European ancestry (3,775 cases, 4,577 controls). SNPs at 11 of the 16 loci (UMOD, PRKAG2, ANXA9, DAB2, SHROOM3, DACH1, STC1, SLC34A1, ALMS1/NAT8, UBE2Q2, and GCKR) were associated with incident CKD; p-values ranged from p = 4.1e-9 in UMOD to p = 0.03 in GCKR. After adjusting for baseline eGFR, six of these loci remained significantly associated with incident CKD (UMOD, PRKAG2, ANXA9, DAB2, DACH1, and STC1). SNPs in UMOD (OR = 0.92, p = 0.04) and GCKR (OR = 0.93, p = 0.03) were nominally associated with ESRD. In summary, the majority of eGFR-related loci are either associated or show a strong trend towards association with incident CKD, but have modest associations with ESRD in individuals of European descent. Additional work is required to characterize the association of genetic determinants of CKD and ESRD at different stages of disease progression.
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BACKGROUND: HIV-infected individuals have an increased risk of myocardial infarction. Antiretroviral therapy (ART) is regarded as a major determinant of dyslipidemia in HIV-infected individuals. Previous genetic studies have been limited by the validity of the single-nucleotide polymorphisms (SNPs) interrogated and by cross-sectional design. Recent genome-wide association studies have reliably associated common SNPs to dyslipidemia in the general population. METHODS AND RESULTS: We validated the contribution of 42 SNPs (33 identified in genome-wide association studies and 9 previously reported SNPs not included in genome-wide association study chips) and of longitudinally measured key nongenetic variables (ART, underlying conditions, sex, age, ethnicity, and HIV disease parameters) to dyslipidemia in 745 HIV-infected study participants (n=34 565 lipid measurements; median follow-up, 7.6 years). The relative impact of SNPs and ART to lipid variation in the study population and their cumulative influence on sustained dyslipidemia at the level of the individual were calculated. SNPs were associated with lipid changes consistent with genome-wide association study estimates. SNPs explained up to 7.6% (non-high-density lipoprotein cholesterol), 6.2% (high-density lipoprotein cholesterol), and 6.8% (triglycerides) of lipid variation; ART explained 3.9% (non-high-density lipoprotein cholesterol), 1.5% (high-density lipoprotein cholesterol), and 6.2% (triglycerides). An individual with the most dyslipidemic antiretroviral and genetic background had an approximately 3- to 5-fold increased risk of sustained dyslipidemia compared with an individual with the least dyslipidemic therapy and genetic background. CONCLUSIONS: In the HIV-infected population treated with ART, the weight of the contribution of common SNPs and ART to dyslipidemia was similar. When selecting an ART regimen, genetic information should be considered in addition to the dyslipidemic effects of ART agents.
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There are many known examples of multiple semi-independent associations at individual loci; such associations might arise either because of true allelic heterogeneity or because of imperfect tagging of an unobserved causal variant. This phenomenon is of great importance in monogenic traits but has not yet been systematically investigated and quantified in complex-trait genome-wide association studies (GWASs). Here, we describe a multi-SNP association method that estimates the effect of loci harboring multiple association signals by using GWAS summary statistics. Applying the method to a large anthropometric GWAS meta-analysis (from the Genetic Investigation of Anthropometric Traits consortium study), we show that for height, body mass index (BMI), and waist-to-hip ratio (WHR), 3%, 2%, and 1%, respectively, of additional phenotypic variance can be explained on top of the previously reported 10% (height), 1.5% (BMI), and 1% (WHR). The method also permitted a substantial increase (by up to 50%) in the number of loci that replicate in a discovery-validation design. Specifically, we identified 74 loci at which the multi-SNP, a linear combination of SNPs, explains significantly more variance than does the best individual SNP. A detailed analysis of multi-SNPs shows that most of the additional variability explained is derived from SNPs that are not in linkage disequilibrium with the lead SNP, suggesting a major contribution of allelic heterogeneity to the missing heritability.
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Extensive population-based genome-wide association studies have identified an association between the FTO gene and BMI; however, the mechanism of action is still unknown. To determine whether FTO may influence weight regulation through psychological and behavioral factors, seven single-nucleotide polymorphisms (SNPs) of the FTO gene were genotyped in 1,085 individuals with anorexia nervosa (AN) and 677 healthy weight controls from the international Price Foundation Genetic Studies of Eating Disorders. Each SNP was tested in association with eating disorder phenotypes and measures that have previously been associated with eating behavior pathology: trait anxiety, harm-avoidance, novelty seeking, impulsivity, obsessionality, compulsivity, and concern over mistakes. After appropriate correction for multiple comparisons, no significant associations between individual FTO gene SNPs and eating disorder phenotypes or related eating behavior pathology were identified in cases or controls. Thus, this study found no evidence that FTO gene variants associated with weight regulation in the general population are associated with eating disorder phenotypes in AN participants or matched controls. © 2011 Wiley-Liss, Inc.