967 resultados para WIDE ASSOCIATION


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The impact of host genetic variation on determining the differential outcomes after HIV infection has been studied by two approaches: targeting of candidate genes and genome-wide association studies (GWASs). The overlap in genetic variants that has been identified by these two means has essentially been restricted to variants near to the human leukocyte antigen (HLA) class I genes, although variation in the CCR5 locus, which was first shown to have an effect on HIV outcomes using the candidate gene approach, does reach significance genome-wide when very large samples sizes (i.e. thousands) are used in GWAS. Overall, many of the variants identified by the candidate gene approach are likely to be spurious, as no additional variants apart from a novel variant near the HLA-C gene have been consistently identified by GWAS. Variants with low frequency and/or low impact on HIV outcomes are likely to exist in the genome and there could be many of them, but these are not identifiable, given current GWAS sample sizes. Several loci centrally involved in the immune response, including the immunoglobulin genes, T-cell receptor loci, or leukocyte receptor complex, are either poorly covered on the GWAS chips or difficult to interpret due to their repetitive nature and/or the presence of insertion/deletion polymorphisms in the region. These loci warrant further interrogation, but genetic characterization of these regions across a range of individuals will first be required. Finally, synergistic interactions between loci may affect outcome after infection, as suggested by associations of specific, functionally relevant HLA and killer cell immunoglobulin-like receptor variants with HIV disease outcomes, and these require further consideration as well.

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To identify common variants influencing body mass index (BMI), we analyzed genome-wide association data from 16,876 individuals of European descent. After previously reported variants in FTO, the strongest association signal (rs17782313, P = 2.9 x 10(-6)) mapped 188 kb downstream of MC4R (melanocortin-4 receptor), mutations of which are the leading cause of monogenic severe childhood-onset obesity. We confirmed the BMI association in 60,352 adults (per-allele effect = 0.05 Z-score units; P = 2.8 x 10(-15)) and 5,988 children aged 7-11 (0.13 Z-score units; P = 1.5 x 10(-8)). In case-control analyses (n = 10,583), the odds for severe childhood obesity reached 1.30 (P = 8.0 x 10(-11)). Furthermore, we observed overtransmission of the risk allele to obese offspring in 660 families (P (pedigree disequilibrium test average; PDT-avg) = 2.4 x 10(-4)). The SNP location and patterns of phenotypic associations are consistent with effects mediated through altered MC4R function. Our findings establish that common variants near MC4R influence fat mass, weight and obesity risk at the population level and reinforce the need for large-scale data integration to identify variants influencing continuous biomedical traits.

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Whole-grain foods are touted for multiple health benefits, including enhancing insulin sensitivity and reducing type 2 diabetes risk. Recent genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs) associated with fasting glucose and insulin concentrations in individuals free of diabetes. We tested the hypothesis that whole-grain food intake and genetic variation interact to influence concentrations of fasting glucose and insulin. Via meta-analysis of data from 14 cohorts comprising ∼ 48,000 participants of European descent, we studied interactions of whole-grain intake with loci previously associated in GWAS with fasting glucose (16 loci) and/or insulin (2 loci) concentrations. For tests of interaction, we considered a P value <0.0028 (0.05 of 18 tests) as statistically significant. Greater whole-grain food intake was associated with lower fasting glucose and insulin concentrations independent of demographics, other dietary and lifestyle factors, and BMI (β [95% CI] per 1-serving-greater whole-grain intake: -0.009 mmol/l glucose [-0.013 to -0.005], P < 0.0001 and -0.011 pmol/l [ln] insulin [-0.015 to -0.007], P = 0.0003). No interactions met our multiple testing-adjusted statistical significance threshold. The strongest SNP interaction with whole-grain intake was rs780094 (GCKR) for fasting insulin (P = 0.006), where greater whole-grain intake was associated with a smaller reduction in fasting insulin concentrations in those with the insulin-raising allele. Our results support the favorable association of whole-grain intake with fasting glucose and insulin and suggest a potential interaction between variation in GCKR and whole-grain intake in influencing fasting insulin concentrations.

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Motivation: Genome-wide association studies have become widely used tools to study effects of genetic variants on complex diseases. While it is of great interest to extend existing analysis methods by considering interaction effects between pairs of loci, the large number of possible tests presents a significant computational challenge. The number of computations is further multiplied in the study of gene expression quantitative trait mapping, in which tests are performed for thousands of gene phenotypes simultaneously. Results: We present FastEpistasis, an efficient parallel solution extending the PLINK epistasis module, designed to test for epistasis effects when analyzing continuous phenotypes. Our results show that the algorithm scales with the number of processors and offers a reduction in computation time when several phenotypes are analyzed simultaneously. FastEpistasis is capable of testing the association of a continuous trait with all single nucleotide polymorphism ( SNP) pairs from 500 000 SNPs, totaling 125 billion tests, in a population of 5000 individuals in 29, 4 or 0.5 days using 8, 64 or 512 processors.

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In vitro and in vivo analyses identified a significant component of heritability in cellular or host susceptibility to HIV-1. The bases for susceptibility can be traced to genetic differences (inter-species) resulting from evolutionary adaptation to exogenous (and endogenous) retroviral infections, and to intra-species and inter-individual (human) differences associated with genetic variation. We have completed large scale evolutionary analysis of genes involved in HIV life cycle and pathogenesis, as well as participating and conducting genome-wide association studies, linkage analysis, and transcriptome analysis. These studies allowed a better understanding of the influence of common human variants in HIV-1 susceptibility and define a number of experimental challenges in the filed: understanding of the role of rare and private mutations in susceptibility, and the development of better tools for the integration of data from large-scale studies.

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Introduction: Les études GVvA (Genome-wide association ,-studies) ont identifié et confirmé plus de 20 gènes de susceptibilité au DT2 et ont contribué à mieux comprendre sa physiopathologie. L'hyperglycémie à jeun (GJ), et 2 heures après une HGPO (G2h) sont les deux mesures cliniques du diagnostic du DT2. Nous avons identifié récemment la G6P du pancréas (G6PC2) comme déterminant de la variabilité physiologique de la GJ puis Ie récepteur à la mélatonine (MTNRIB) qui de plus lie la régulation du rythme circadien au DT2. Dans ce travail nous avons étudié la génétique de la G2h à l'aide de l'approche GWA. Résultats: Nous avons réalisé une méta-analyse GWA dans le cadre de MAGIC (Meta-Analysis of Glucose and Insulin related traits Consortium) qui a inclus 9 études GWA (N=15'234). La réplication de 29 loci (N=6958-30 121, P < 10-5 ) a confirmé 5 nouveaux loci; 2 étant connus comme associés avec Ie DT2 (TCF7L2, P = 1,6 X 10-10 ) et la GJ (GCKR, p = 5,6 X 10-10 ); alors que GIPR (p= 5,2 X 10-12), VSP13C (p= 3,9 X 10-8) et ADCY5 (p = 1,11 X 10-15 ) sont inédits. GIPR code Ie récepteur au GIP (gastric inhibitory polypeptide) qui est sécrété par les ceIlules intestinales pour stimuler la sécrétion de l'insuline en réponse au glucose (l'effet incrétine). Les porteurs du variant GIPR qui augmente la G2h ont également un indice insulinogénique plus bas, (p= 1,0 X 10-17) mais ils ne présentent aucune modification de leur glycémie suite à une hyperglycémie provoquée par voie veineuse (p= 0,21). Ces résultats soutiennent un effet incrétine du locus GIPR qui expliquerait ~9,6 % de la variance total de ce trait. La biologie de ADCY5 et VPS13C et son lien avec l'homéostasie du glucose restent à élucider. GIPR n'est pas associé avec le risque de DT2 indiquant qu'il influence la variabilité physiologique de la G2h alors que le locus ADCY5 est associé avec le DT2 (OR = 1,11, P = 1,5 X 10-15). Conclusion: Notre étude démontre que l'étude de la G2h est une approche efficace d'une part pour la compréhension de la base génétique de la physiologie de ce trait clinique important et d'autre part pour identifier de nouveaux gènes de susceptibilité au DT2.

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Chronic kidney disease (CKD), impairment of kidney function, is a serious public health problem, and the assessment of genetic factors influencing kidney function has substantial clinical relevance. Here, we report a meta-analysis of genome-wide association studies for kidney function-related traits, including 71,149 east Asian individuals from 18 studies in 11 population-, hospital- or family-based cohorts, conducted as part of the Asian Genetic Epidemiology Network (AGEN). Our meta-analysis identified 17 loci newly associated with kidney function-related traits, including the concentrations of blood urea nitrogen, uric acid and serum creatinine and estimated glomerular filtration rate based on serum creatinine levels (eGFRcrea) (P < 5.0 × 10(-8)). We further examined these loci with in silico replication in individuals of European ancestry from the KidneyGen, CKDGen and GUGC consortia, including a combined total of ∼110,347 individuals. We identify pleiotropic associations among these loci with kidney function-related traits and risk of CKD. These findings provide new insights into the genetics of kidney function.

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High systemic levels of IP-10 at onset of combination therapy for chronic hepatitis C mirror intrahepatic mRNA levels and predict a slower first phase decline in HCV RNA as well as poor outcome. Recently several genome wide association studies have revealed that single nucleotide polymorphisms (SNPs) on chromosome19 within proximity of IL28B predict spontaneous clearance of HCV infection and as therapeutic outcome among patients infected with HCV genotype 1, with three such SNPs being highly predictive: rs12979860, rs12980275, and rs8099917. In the present study, we correlated genetic variations in these SNPs from 253 Caucasian patients with pretreatment plasma levels of IP-10 and HCV RNA throughout therapy within a phase III treatment trial (HCV-DITTO). The favorable genetic variations in all three SNPs (CC, AA, and TT respectively) was significantly associated with lower baseline IP-10 (CC vs. CT/TT at rs12979860: median 189 vs. 258 pg/mL, P=0.02, AA vs. AG/GG at rs12980275: median 189 vs. 258 pg/mL, P=0.01, TT vs. TG/GG at rs8099917: median 224 vs. 288 pg/mL, P=0.04), were significantly less common among HCV genotype 1 infected patients than genotype 2/3 (P<0.0001, P<0.0001, and P=0.01 respectively) and had significantly higher baseline viral load than carriers of the SNP genotypes (6.3 vs. 5.9 log 10 IU/mL, P=0.0012, 6.3 vs. 6.0 log 10 IU/mL, P=0.026, and 6.3 vs. 5.8 log 10 IU/mL, P=0.0003 respectively). Among HCV genotype 1 infected homozygous or heterogeneous carriers of the favorable C, A, and T genotypes, lower baseline IP-10 was significantly associated with greater decline in HCV-RNA day 0-4, which translated into increased rates of achieving SVR among homozygous patients with baseline IP-10 below 150 pg/mL (85%, 75%, and 75% respectively). In a multivariate analysis among genotype 1 infected patients, both baseline IP-10 and the SNPs were significant independent predictors of SVR. Conclusion: Baseline plasma IP-10 is significantly associated with IL28B variations, and augments the predictiveness of the first phase decline in HCV RNA and final treatment outcome.

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Genome-wide studies in major depression have identified few replicated associations, potentially due to heterogeneity within the disorder. Several studies have suggested that age at onset (AAO) can distinguish sub-types of depression with specific heritable components. This paper investigates the role of AAO in the genetic susceptibility for depression using genome-wide association data on 2,746 cases and 1,594 screened controls from the RADIANT studies, with replication performed in 1,471 cases and 1,403 controls from two Munich studies. Three methods were used to analyze AAO: First a time-to-event analysis with controls censored, secondly comparing controls to case-subsets defined using AAO cut-offs, and lastly analyzing AAO as a quantitative trait. In the time-to-event analysis three SNPs reached suggestive significance (P < 5E-06), overlapping with the original case-control analysis of this study. In a case-control analysis using AAO thresholds, SNPs in 10 genomic regions showed suggestive association though again none reached genome-wide significance. Lastly, case-only analysis of AAO as a quantitative trait resulted in 5 SNPs reaching suggestive significance. Sex specific analysis was performed as a secondary analysis, yielding one SNP reaching genome-wide significance in early-onset males. No SNPs achieved significance in the replication study after correction for multiple testing. Analysis of AAO as a quantitative trait did suggest that, across all SNPs, common genetic variants explained a large proportion of the variance (51%, P = 0.04). This study provides the first focussed analysis of the genetic contribution to AAO in depression, and establishes a statistical framework that can be applied to a quantitative trait underlying any disorder. © 2012 Wiley Periodicals, Inc.

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Candidate gene and genome-wide association studies have not identified common variants, which are reliably associated with depression. The recent identification of obesity predisposing genes that are highly expressed in the brain raises the possibility of their genetic contribution to depression. As variation in the intron 1 of the fat mass- and obesity-associated (FTO) gene contributes to polygenic obesity, we assessed the possibility that FTO gene may contribute to depression in a cross-sectional multi-ethnic sample of 6561 depression cases and 21 932 controls selected from the EpiDREAM, INTERHEART, DeCC (depression case-control study) and Cohorte Lausannoise (CoLaus) studies. Major depression was defined according to DSM IV diagnostic criteria. Association analyses were performed under the additive genetic model. A meta-analysis of the four studies showed a significant inverse association between the obesity risk FTO rs9939609 A variant and depression (odds ratio=0.92 (0.89, 0.97), P=3 × 10(-4)) adjusted for age, sex, ethnicity/population structure and body-mass index (BMI) with no significant between-study heterogeneity (I(2)=0%, P=0.63). The FTO rs9939609 A variant was also associated with increased BMI in the four studies (β 0.30 (0.08, 0.51), P=0.0064) adjusted for age, sex and ethnicity/population structure. In conclusion, we provide the first evidence that the FTO rs9939609 A variant may be associated with a lower risk of depression independently of its effect on BMI. This study highlights the potential importance of obesity predisposing genes on depression.

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BACKGROUND: There is an ever-increasing volume of data on host genes that are modulated during HIV infection, influence disease susceptibility or carry genetic variants that impact HIV infection. We created GuavaH (Genomic Utility for Association and Viral Analyses in HIV, http://www.GuavaH.org), a public resource that supports multipurpose analysis of genome-wide genetic variation and gene expression profile across multiple phenotypes relevant to HIV biology. FINDINGS: We included original data from 8 genome and transcriptome studies addressing viral and host responses in and ex vivo. These studies cover phenotypes such as HIV acquisition, plasma viral load, disease progression, viral replication cycle, latency and viral-host genome interaction. This represents genome-wide association data from more than 4,000 individuals, exome sequencing data from 392 individuals, in vivo transcriptome microarray data from 127 patients/conditions, and 60 sets of RNA-seq data. Additionally, GuavaH allows visualization of protein variation in ~8,000 individuals from the general population. The publicly available GuavaH framework supports queries on (i) unique single nucleotide polymorphism across different HIV related phenotypes, (ii) gene structure and variation, (iii) in vivo gene expression in the setting of human infection (CD4+ T cells), and (iv) in vitro gene expression data in models of permissive infection, latency and reactivation. CONCLUSIONS: The complexity of the analysis of host genetic influences on HIV biology and pathogenesis calls for comprehensive motors of research on curated data. The tool developed here allows queries and supports validation of the rapidly growing body of host genomic information pertinent to HIV research.

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BACKGROUND/AIMS: Calcium homeostasis requires regulated cellular and interstitial systems interacting to modulate the activity and movement of this ion. Disruption of these systems in the kidney results in nephrocalcinosis and nephrolithiasis, important medical problems whose pathogenesis is incompletely understood. METHODS: We investigated 25 patients from 16 families with unexplained nephrocalcinosis and characteristic dental defects (amelogenesis imperfecta, gingival hyperplasia, impaired tooth eruption). To identify the causative gene, we performed genome-wide linkage analysis, exome capture, next-generation sequencing, and Sanger sequencing. RESULTS: All patients had bi-allelic FAM20A mutations segregating with the disease; 20 different mutations were identified. CONCLUSIONS: This autosomal recessive disorder, also known as enamel renal syndrome, of FAM20A causes nephrocalcinosis and amelogenesis imperfecta. We speculate that all individuals with biallelic FAM20A mutations will eventually show nephrocalcinosis.

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A genome-wide association study (GWAS) of educational attainment was conducted in a discovery sample of 101,069 individuals and a replication sample of 25,490. Three independent single-nucleotide polymorphisms (SNPs) are genome-wide significant (rs9320913, rs11584700, rs4851266), and all three replicate. Estimated effects sizes are small (coefficient of determination R(2) ≈ 0.02%), approximately 1 month of schooling per allele. A linear polygenic score from all measured SNPs accounts for ≈2% of the variance in both educational attainment and cognitive function. Genes in the region of the loci have previously been associated with health, cognitive, and central nervous system phenotypes, and bioinformatics analyses suggest the involvement of the anterior caudate nucleus. These findings provide promising candidate SNPs for follow-up work, and our effect size estimates can anchor power analyses in social-science genetics.

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It is common practice in genome-wide association studies (GWAS) to focus on the relationship between disease risk and genetic variants one marker at a time. When relevant genes are identified it is often possible to implicate biological intermediates and pathways likely to be involved in disease aetiology. However, single genetic variants typically explain small amounts of disease risk. Our idea is to construct allelic scores that explain greater proportions of the variance in biological intermediates, and subsequently use these scores to data mine GWAS. To investigate the approach's properties, we indexed three biological intermediates where the results of large GWAS meta-analyses were available: body mass index, C-reactive protein and low density lipoprotein levels. We generated allelic scores in the Avon Longitudinal Study of Parents and Children, and in publicly available data from the first Wellcome Trust Case Control Consortium. We compared the explanatory ability of allelic scores in terms of their capacity to proxy for the intermediate of interest, and the extent to which they associated with disease. We found that allelic scores derived from known variants and allelic scores derived from hundreds of thousands of genetic markers explained significant portions of the variance in biological intermediates of interest, and many of these scores showed expected correlations with disease. Genome-wide allelic scores however tended to lack specificity suggesting that they should be used with caution and perhaps only to proxy biological intermediates for which there are no known individual variants. Power calculations confirm the feasibility of extending our strategy to the analysis of tens of thousands of molecular phenotypes in large genome-wide meta-analyses. We conclude that our method represents a simple way in which potentially tens of thousands of molecular phenotypes could be screened for causal relationships with disease without having to expensively measure these variables in individual disease collections.

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Gene-lifestyle interactions have been suggested to contribute to the development of type 2 diabetes. Glucose levels 2 h after a standard 75-g glucose challenge are used to diagnose diabetes and are associated with both genetic and lifestyle factors. However, whether these factors interact to determine 2-h glucose levels is unknown. We meta-analyzed single nucleotide polymorphism (SNP) × BMI and SNP × physical activity (PA) interaction regression models for five SNPs previously associated with 2-h glucose levels from up to 22 studies comprising 54,884 individuals without diabetes. PA levels were dichotomized, with individuals below the first quintile classified as inactive (20%) and the remainder as active (80%). BMI was considered a continuous trait. Inactive individuals had higher 2-h glucose levels than active individuals (β = 0.22 mmol/L [95% CI 0.13-0.31], P = 1.63 × 10(-6)). All SNPs were associated with 2-h glucose (β = 0.06-0.12 mmol/allele, P ≤ 1.53 × 10(-7)), but no significant interactions were found with PA (P > 0.18) or BMI (P ≥ 0.04). In this large study of gene-lifestyle interaction, we observed no interactions between genetic and lifestyle factors, both of which were associated with 2-h glucose. It is perhaps unlikely that top loci from genome-wide association studies will exhibit strong subgroup-specific effects, and may not, therefore, make the best candidates for the study of interactions.