967 resultados para WIDE ASSOCIATION


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HIV-infected individuals may have accelerated atherogenesis and an increased risk for premature coronary artery disease. Dyslipidemia represents a key pro-atherogenic mechanism. In HIV-infected patients, dyslipidemia is typically attributed to the adverse effects of antiretroviral therapy. Nine recent genome-wide association studies have afforded a comprehensive, unbiased inventory of common SNPs at 36 genetic loci that are reproducibly associated with dyslipidemia in the general population. Genome-wide association study-validated SNPs have now been demonstrated to contribute to dyslipidemia in the setting of HIV infection and antiretroviral therapy. In a Swiss HIV-infected study population, a similar proportion of serum lipid variability was explained by antiretroviral therapy and by genetic background. In the individual patient, both antiretroviral therapy and the cumulative effect of SNPs contribute to the risk of high low-density lipoprotein cholesterol, low high-density lipoprotein cholesterol and hypertriglyceridemia. Genetic variants presumably contribute to additional major metabolic complications in HIV-infected individuals, including diabetes mellitus and coronary artery disease. In an effort to explain an increasing proportion of the heritability of complex metabolic traits, ongoing large-scale gene resequencing studies are focusing on the effects of rare SNPs and structural genetic variants.

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Genome-wide association studies (GWAS) have identified many risk loci for complex diseases, but effect sizes are typically small and information on the underlying biological processes is often lacking. Associations with metabolic traits as functional intermediates can overcome these problems and potentially inform individualized therapy. Here we report a comprehensive analysis of genotype-dependent metabolic phenotypes using a GWAS with non-targeted metabolomics. We identified 37 genetic loci associated with blood metabolite concentrations, of which 25 show effect sizes that are unusually high for GWAS and account for 10-60% differences in metabolite levels per allele copy. Our associations provide new functional insights for many disease-related associations that have been reported in previous studies, including those for cardiovascular and kidney disorders, type 2 diabetes, cancer, gout, venous thromboembolism and Crohn's disease. The study advances our knowledge of the genetic basis of metabolic individuality in humans and generates many new hypotheses for biomedical and pharmaceutical research.

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Genome-wide association studies have been instrumental in identifying genetic variants associated with complex traits such as human disease or gene expression phenotypes. It has been proposed that extending existing analysis methods by considering interactions between pairs of loci may uncover additional genetic effects. However, the large number of possible two-marker tests presents significant computational and statistical challenges. Although several strategies to detect epistasis effects have been proposed and tested for specific phenotypes, so far there has been no systematic attempt to compare their performance using real data. We made use of thousands of gene expression traits from linkage and eQTL studies, to compare the performance of different strategies. We found that using information from marginal associations between markers and phenotypes to detect epistatic effects yielded a lower false discovery rate (FDR) than a strategy solely using biological annotation in yeast, whereas results from human data were inconclusive. For future studies whose aim is to discover epistatic effects, we recommend incorporating information about marginal associations between SNPs and phenotypes instead of relying solely on biological annotation. Improved methods to discover epistatic effects will result in a more complete understanding of complex genetic effects.

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Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

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Recent genome-wide association studies (GWAS) have identified genetic variations near the IL28B gene which are strongly associated with spontaneous and treatment-induced clearance of hepatitis C virus (HCV) infection. Protective IL28B variations are strongly associated with on-treatment viral kinetics and approximately 2-fold increased sustained virologic response (SVR) rates in HCV genotype 1 and 4 patients. In HCV genotype 1 patients, IL28B variations were shown to be the strongest pre-treatment predictor of virologic response. In the treatment of HCV genotype 2 and 3 infected patients, IL28B variations play only a minor role. Preliminary data indicate that IL28B variations are also associated with treatment outcome of regimens, including directly acting antiviral (DAA) agents, though their impact seems to be attenuated compared to standard treatment. Here, we review these important findings and discuss possible implications for clinical decision making in the treatment of HCV infection.

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Adiponutrin (PNPLA3) is a predominantly liver-expressed transmembrane protein with phospholipase activity that is regulated by fasting and feeding. Recent genome-wide association studies identified PNPLA3 to be associated with hepatic fat content and liver function, thus pointing to a possible involvement in the hepatic lipoprotein metabolism. The aim of this study was to examine the association between two common variants in the adiponutrin gene and parameters of lipoprotein metabolism in 23,274 participants from eight independent West-Eurasian study populations including six population-based studies [Bruneck (n = 800), KORA S3/F3 (n = 1644), KORA S4/F4 (n = 1814), CoLaus (n = 5435), SHIP (n = 4012), Rotterdam (n = 5967)], the SAPHIR Study as a healthy working population (n = 1738) and the Utah Obesity Case-Control Study including a group of 1037 severely obese individuals (average BMI 46 kg/m2) and 827 controls from the same geographical region of Utah. We observed a strong additive association of a common non-synonymous variant within adiponutrin (rs738409) with age-, gender-, and alanine-aminotransferase-adjusted lipoprotein concentrations: each copy of the minor allele decreased levels of total cholesterol on average by 2.43 mg/dl (P = 8.87 x 10(-7)), non-HDL cholesterol levels by 2.35 mg/dl (P = 2.27 x 10(-6)) and LDL cholesterol levels by 1.48 mg/dl (P = 7.99 x 10(-4)). These associations remained significant after correction for multiple testing. We did not observe clear evidence for associations with HDL cholesterol or triglyceride concentrations. In conclusion, our study suggests that adiponutrin is involved in the metabolism of apoB-containing lipoproteins.

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We conducted a genome-wide association study for androgenic alopecia in 1,125 men and identified a newly associated locus at chromosome 20p11.22, confirmed in three independent cohorts (n = 1,650; OR = 1.60, P = 1.1 x 10(-14) for rs1160312). The one man in seven who harbors risk alleles at both 20p11.22 and AR (encoding the androgen receptor) has a sevenfold-increased odds of androgenic alopecia (OR = 7.12, P = 3.7 x 10(-15)).

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BACKGROUND: Genotypes obtained with commercial SNP arrays have been extensively used in many large case-control or population-based cohorts for SNP-based genome-wide association studies for a multitude of traits. Yet, these genotypes capture only a small fraction of the variance of the studied traits. Genomic structural variants (GSV) such as Copy Number Variation (CNV) may account for part of the missing heritability, but their comprehensive detection requires either next-generation arrays or sequencing. Sophisticated algorithms that infer CNVs by combining the intensities from SNP-probes for the two alleles can already be used to extract a partial view of such GSV from existing data sets. RESULTS: Here we present several advances to facilitate the latter approach. First, we introduce a novel CNV detection method based on a Gaussian Mixture Model. Second, we propose a new algorithm, PCA merge, for combining copy-number profiles from many individuals into consensus regions. We applied both our new methods as well as existing ones to data from 5612 individuals from the CoLaus study who were genotyped on Affymetrix 500K arrays. We developed a number of procedures in order to evaluate the performance of the different methods. This includes comparison with previously published CNVs as well as using a replication sample of 239 individuals, genotyped with Illumina 550K arrays. We also established a new evaluation procedure that employs the fact that related individuals are expected to share their CNVs more frequently than randomly selected individuals. The ability to detect both rare and common CNVs provides a valuable resource that will facilitate association studies exploring potential phenotypic associations with CNVs. CONCLUSION: Our new methodologies for CNV detection and their evaluation will help in extracting additional information from the large amount of SNP-genotyping data on various cohorts and use this to explore structural variants and their impact on complex traits.

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Recently, a locus centred on rs9273349 in the HLA-DQ region emerged from genome-wide association studies of adult-onset asthma. We aimed to further investigate the role of human leukocyte antigen (HLA) class II in adult-onset asthma and a possible interaction with occupational exposures. We imputed classical HLA-II alleles from 7579 single-nucleotide polymorphisms in 6025 subjects (1202 with adult-onset asthma) from European cohorts: ECRHS, SAPALDIA, EGEA and B58C, and from surveys of bakers and agricultural workers. Based on an asthma-specific job-exposure matrix, 2629 subjects had ever been exposed to high molecular weight (HMW) allergens. We explored associations between 23 common HLA-II alleles and adult-onset asthma, and tested for gene-environment interaction with occupational exposure to HMW allergens. Interaction was also tested for rs9273349. Marginal associations of classical HLA-II alleles and adult-onset asthma were not statistically significant. Interaction was detected between the DPB1*03:01 allele and exposure to HMW allergens (p = 0.009), in particular to latex (p = 0.01). In the unexposed group, the DPB1*03:01 allele was associated with adult-onset asthma (OR 0.67, 95%CI 0.53-0.86). HMW allergen exposures did not modify the association of rs9273349 with adult-onset asthma. Common classical HLA-II alleles were not marginally associated with adult-onset asthma. The association of latex exposure and adult-onset asthma may be modified by DPB1*03:01.

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Cervical artery dissection (CeAD), a mural hematoma in a carotid or vertebral artery, is a major cause of ischemic stroke in young adults although relatively uncommon in the general population (incidence of 2.6/100,000 per year). Minor cervical traumas, infection, migraine and hypertension are putative risk factors, and inverse associations with obesity and hypercholesterolemia are described. No confirmed genetic susceptibility factors have been identified using candidate gene approaches. We performed genome-wide association studies (GWAS) in 1,393 CeAD cases and 14,416 controls. The rs9349379[G] allele (PHACTR1) was associated with lower CeAD risk (odds ratio (OR) = 0.75, 95% confidence interval (CI) = 0.69-0.82; P = 4.46 × 10(-10)), with confirmation in independent follow-up samples (659 CeAD cases and 2,648 controls; P = 3.91 × 10(-3); combined P = 1.00 × 10(-11)). The rs9349379[G] allele was previously shown to be associated with lower risk of migraine and increased risk of myocardial infarction. Deciphering the mechanisms underlying this pleiotropy might provide important information on the biological underpinnings of these disabling conditions.

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The human genome encodes the blueprint of life, but the function of the vast majority of its nearly three billion bases is unknown. The Encyclopedia of DNA Elements (ENCODE) project has systematically mapped regions of transcription, transcription factor association, chromatin structure and histone modification. These data enabled us to assign biochemical functions for 80% of the genome, in particular outside of the well-studied protein-coding regions. Many discovered candidate regulatory elements are physically associated with one another and with expressed genes, providing new insights into the mechanisms of gene regulation. The newly identified elements also show a statistical correspondence to sequence variants linked to human disease, and can thereby guide interpretation of this variation. Overall, the project provides new insights into the organization and regulation of our genes and genome, and is an expansive resource of functional annotations for biomedical research.

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There is evidence across several species for genetic control of phenotypic variation of complex traits, such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human medicine, yet for complex traits, no individual genetic variants associated with variance, as opposed to the mean, have been identified. Here we perform a meta-analysis of genome-wide association studies of phenotypic variation using ∼170,000 samples on height and body mass index (BMI) in human populations. We report evidence that the single nucleotide polymorphism (SNP) rs7202116 at the FTO gene locus, which is known to be associated with obesity (as measured by mean BMI for each rs7202116 genotype), is also associated with phenotypic variability. We show that the results are not due to scale effects or other artefacts, and find no other experiment-wise significant evidence for effects on variability, either at loci other than FTO for BMI or at any locus for height. The difference in variance for BMI among individuals with opposite homozygous genotypes at the FTO locus is approximately 7%, corresponding to a difference of ∼0.5 kilograms in the standard deviation of weight. Our results indicate that genetic variants can be discovered that are associated with variability, and that between-person variability in obesity can partly be explained by the genotype at the FTO locus. The results are consistent with reported FTO by environment interactions for BMI, possibly mediated by DNA methylation. Our BMI results for other SNPs and our height results for all SNPs suggest that most genetic variants, including those that influence mean height or mean BMI, are not associated with phenotypic variance, or that their effects on variability are too small to detect even with samples sizes greater than 100,000.

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Hypertension and chronic kidney disease (CKD) are complex traits representing major global health problems. Multiple genome-wide association studies have identified common variants in the promoter of the UMOD gene, which encodes uromodulin, the major protein secreted in normal urine, that cause independent susceptibility to CKD and hypertension. Despite compelling genetic evidence for the association between UMOD risk variants and disease susceptibility in the general population, the underlying biological mechanism is not understood. Here, we demonstrate that UMOD risk variants increased UMOD expression in vitro and in vivo. Uromodulin overexpression in transgenic mice led to salt-sensitive hypertension and to the presence of age-dependent renal lesions similar to those observed in elderly individuals homozygous for UMOD promoter risk variants. The link between uromodulin and hypertension is due to activation of the renal sodium cotransporter NKCC2. We demonstrated the relevance of this mechanism in humans by showing that pharmacological inhibition of NKCC2 was more effective in lowering blood pressure in hypertensive patients who are homozygous for UMOD promoter risk variants than in other hypertensive patients. Our findings link genetic susceptibility to hypertension and CKD to the level of uromodulin expression and uromodulin's effect on salt reabsorption in the kidney. These findings point to uromodulin as a therapeutic target for lowering blood pressure and preserving renal function.

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BACKGROUND & AIMS: Steatosis is a prominent feature of hepatitis C, especially in patients infected with genotype 3. The analysis of genetic polymorphisms influencing steatosis in chronic hepatitis C has been limited by the studies' small sample size, and important single nucleotide polymorphisms (SNPs), such as those in the patatin-like phospholipase family 3 protein (PNPLA3), were never evaluated. METHODS: We analyzed the role of SNPs, from 19 systematically selected candidate genes, on steatosis in 626 Caucasian hepatitis C virus (HCV) infected patients. SNPs were extracted from a genome-wide association-generated dataset. Associations of alleles with the presence and/or different severity of steatosis were evaluated by univariate and multivariate logistic regression, accounting for all relevant covariates. RESULTS: The risk of steatosis was increased by carriage of I148M in PNPLA3, but only in patients with HCV genotypes non-3 (odds ratio [OR]=1.9, 95% confidence interval [CI]=1.6-2.3, p<0.001) and similar, albeit weaker associations were found for SNPs in peroxisome proliferator-activated receptor-γ (PPARG) and interleukin-28B (IL28B). Carriage of a SNP in the microsomal triglyceride transfer protein (MTTP) increased the risk of steatosis, but only in patients with HCV genotype 3 (rs1800803, OR=3.4, 95% CI=2.4-4.9, p=0.001). CONCLUSIONS: The rs738409 SNP in PNPLA3 is associated with an increased risk of steatosis in patients infected with HCV genotypes non-3. Host genes affect steatosis depending on the infecting HCV genotype, suggesting their interaction with viral factors.

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Recent years have seen a significant increase in understanding of the host genetic and genomic determinants of susceptibility to HIV-1 infection and disease progression, driven in large part by candidate gene studies, genome-wide association studies, genome-wide transcriptome analyses, and large-scale in vitro genome screens. These studies have identified common variants in some host loci that clearly influence disease progression, characterized the scale and dynamics of gene and protein expression changes in response to infection, and provided the first comprehensive catalogs of genes and pathways involved in viral replication. Experimental models of AIDS and studies in natural hosts of primate lentiviruses have complemented and in some cases extended these findings. As the relevant technology continues to progress, the expectation is that such studies will increase in depth (e.g., to include host whole exome and whole genome sequencing) and in breadth (in particular, by integrating multiple data types).