180 resultados para Genetic-variants
Resumo:
The length of female reproductive lifespan is associated with multiple adverse outcomes, including breast cancer, cardiovascular disease and infertility. The biological processes that govern the timing of the beginning and end of reproductive life are not well understood. Genetic variants are known to contribute to ∼50% of the variation in both age at menarche and menopause, but to date the known genes explain <15% of the genetic component. We have used genome-wide association in a bivariate meta-analysis of both traits to identify genes involved in determining reproductive lifespan. We observed significant genetic correlation between the two traits using genome-wide complex trait analysis. However, we found no robust statistical evidence for individual variants with an effect on both traits. A novel association with age at menopause was detected for a variant rs1800932 in the mismatch repair gene MSH6 (P = 1.9 × 10(-9)), which was also associated with altered expression levels of MSH6 mRNA in multiple tissues. This study contributes to the growing evidence that DNA repair processes play a key role in ovarian ageing and could be an important therapeutic target for infertility.
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Both obesity and being underweight have been associated with increased mortality. Underweight, defined as a body mass index (BMI) ≤ 18.5 kg per m(2) in adults and ≤ -2 standard deviations from the mean in children, is the main sign of a series of heterogeneous clinical conditions including failure to thrive, feeding and eating disorder and/or anorexia nervosa. In contrast to obesity, few genetic variants underlying these clinical conditions have been reported. We previously showed that hemizygosity of a ∼600-kilobase (kb) region on the short arm of chromosome 16 causes a highly penetrant form of obesity that is often associated with hyperphagia and intellectual disabilities. Here we show that the corresponding reciprocal duplication is associated with being underweight. We identified 138 duplication carriers (including 132 novel cases and 108 unrelated carriers) from individuals clinically referred for developmental or intellectual disabilities (DD/ID) or psychiatric disorders, or recruited from population-based cohorts. These carriers show significantly reduced postnatal weight and BMI. Half of the boys younger than five years are underweight with a probable diagnosis of failure to thrive, whereas adult duplication carriers have an 8.3-fold increased risk of being clinically underweight. We observe a trend towards increased severity in males, as well as a depletion of male carriers among non-medically ascertained cases. These features are associated with an unusually high frequency of selective and restrictive eating behaviours and a significant reduction in head circumference. Each of the observed phenotypes is the converse of one reported in carriers of deletions at this locus. The phenotypes correlate with changes in transcript levels for genes mapping within the duplication but not in flanking regions. The reciprocal impact of these 16p11.2 copy-number variants indicates that severe obesity and being underweight could have mirror aetiologies, possibly through contrasting effects on energy balance.
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BACKGROUND:: The frequently prescribed antidementia drug galantamine is extensively metabolized by the enzymes cytochrome P450 (CYP) 2D6 and CYP3A and is a substrate of the P-glycoprotein. We aimed to study the relationship between genetic variants influencing the activity of these enzymes and transporters with galantamine steady state plasma concentrations. METHODS:: In this naturalistic cross-sectional study, 27 older patients treated with galantamine were included. The patients were genotyped for common polymorphisms in CYP2D6, CYP3A4/5, POR, and ABCB1, and galantamine steady state plasma concentrations were determined. RESULTS:: The CYP2D6 genotype seemed to be an important determinant of galantamine pharmacokinetics, with CYP2D6 poor metabolizers presenting 45% and 61% higher dose-adjusted galantamine plasma concentrations than heterozygous and homozygous CYP2D6 extensive metabolizers (median 2.9 versus 2.0 ng/mL·mg, P = 0.025, and 1.8 ng/mL·mg, P = 0.004), respectively. CONCLUSIONS:: The CYP2D6 genotype significantly influenced galantamine plasma concentrations. The influence of CYP2D6 polymorphisms on the treatment efficacy and tolerability should be further investigated.
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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 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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Elevated blood pressure is a common, heritable cause of cardiovascular disease worldwide. To date, identification of common genetic variants influencing blood pressure has proven challenging. We tested 2.5 million genotyped and imputed SNPs for association with systolic and diastolic blood pressure in 34,433 subjects of European ancestry from the Global BPgen consortium and followed up findings with direct genotyping (N ≤ 71,225 European ancestry, N ≤ 12,889 Indian Asian ancestry) and in silico comparison (CHARGE consortium, N = 29,136). We identified association between systolic or diastolic blood pressure and common variants in eight regions near the CYP17A1 (P = 7 × 10(-24)), CYP1A2 (P = 1 × 10(-23)), FGF5 (P = 1 × 10(-21)), SH2B3 (P = 3 × 10(-18)), MTHFR (P = 2 × 10(-13)), c10orf107 (P = 1 × 10(-9)), ZNF652 (P = 5 × 10(-9)) and PLCD3 (P = 1 × 10(-8)) genes. All variants associated with continuous blood pressure were associated with dichotomous hypertension. These associations between common variants and blood pressure and hypertension offer mechanistic insights into the regulation of blood pressure and may point to novel targets for interventions to prevent cardiovascular disease.
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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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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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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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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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OBJECTIVES: Etravirine (ETV) is metabolized by cytochrome P450 (CYP) 3A, 2C9, and 2C19. Metabolites are glucuronidated by uridine diphosphate glucuronosyltransferases (UGT). To identify the potential impact of genetic and non-genetic factors involved in ETV metabolism, we carried out a two-step pharmacogenetics-based population pharmacokinetic study in HIV-1 infected individuals. MATERIALS AND METHODS: The study population included 144 individuals contributing 289 ETV plasma concentrations and four individuals contributing 23 ETV plasma concentrations collected in a rich sampling design. Genetic variants [n=125 single-nucleotide polymorphisms (SNPs)] in 34 genes with a predicted role in ETV metabolism were selected. A first step population pharmacokinetic model included non-genetic and known genetic factors (seven SNPs in CYP2C, one SNP in CYP3A5) as covariates. Post-hoc individual ETV clearance (CL) was used in a second (discovery) step, in which the effect of the remaining 98 SNPs in CYP3A, P450 cytochrome oxidoreductase (POR), nuclear receptor genes, and UGTs was investigated. RESULTS: A one-compartment model with zero-order absorption best characterized ETV pharmacokinetics. The average ETV CL was 41 (l/h) (CV 51.1%), the volume of distribution was 1325 l, and the mean absorption time was 1.2 h. The administration of darunavir/ritonavir or tenofovir was the only non-genetic covariate influencing ETV CL significantly, resulting in a 40% [95% confidence interval (CI): 13-69%] and a 42% (95% CI: 17-68%) increase in ETV CL, respectively. Carriers of rs4244285 (CYP2C19*2) had 23% (8-38%) lower ETV CL. Co-administered antiretroviral agents and genetic factors explained 16% of the variance in ETV concentrations. None of the SNPs in the discovery step influenced ETV CL. CONCLUSION: ETV concentrations are highly variable, and co-administered antiretroviral agents and genetic factors explained only a modest part of the interindividual variability in ETV elimination. Opposing effects of interacting drugs effectively abrogate genetic influences on ETV CL, and vice-versa.
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Background: C-reactive protein (CRP) is associated with risk of coronary heart disease (CHD). Whether CRP is causally associated with CHD or merely a marker of underlying atherosclerosis is uncertain. Methods: We used a Mendelian randomisation design to investigate the causal relationship of CRP with CHD. We identified three genetic variants in the CRP locus (rs7553007, rs1130864 and rs1205) which influence CRP levels. We tested the three SNPs for association with CHD amongst 28,112 CHD cases and 100,823 controls. We then compared the observed relationship between the SNPs and CHD, with that predicted from the association of SNPs with CRP levels, and of CRP levels with CHD. Results: SNPs in the CRP locus were not associated with CHD: rs7553007, OR 0.98 (95% CI, 0.94-1.01); rs1130864, OR 1.00 (95% CI, 0.86-1.15); rs1205, OR 1.03 (95% CI, 0.99-1.07); combined OR for all three SNPs, 1.00 (95% CI, 0.97-1.02), per 20% lower CRP (figure). In contrast, the predicted OR for CHD from a 20% lower CRP level is 0.94 (95% CI, 0.94- 0.95), based on meta-analysis of observational studies. Conclusions: Though CRP variants are associated with CRP levels, and CRP levels with risk of CHD, we observed that CRP variants are not associated with CHD risk. Our Mendelian randomisation experiment strongly argues against a causal association of CRP with CHD.
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The role of serum uric acid (SUA) in cardio-metabolic conditions has long been contentious. It is still unclear if SUA is an independent risk factor or marker of cardio-metabolic conditions and most observed associations are not necessarily causal. This study aimed to further understand and explore the causal role of SUA in cardio-metabolic conditions using genetic and non-genetic epidemiological methods in population-based data. In the first part of this study, we found moderate to high heritability estimates for SUA and fractional excretion of urate (FEUA) suggesting the role of genetic factors in the etiology of hyperuricemia. With regards to the role of SUA on inflammatory markers (IMs), a strong positive association of SUA with C-reactive protein (CRP) and a weaker positive association with tumor necrosis factor alpha (TNF-α) and interleukin 6 (IL-6) was observed, which was in part mediated by body mass index (BMI). These findings suggest that SUA may have a role in sterile inflammation. In view of the inconsistency surrounding the causal nature and direction of the relation between SUA and adiposity, we applied a bidirectional Mendelian randomization approach using genetic variants to decipher the association. The finding that elevated SUA is a consequence rather than a cause of adiposity was not totally unexpected and is compatible with the hypothesis that hyperinsulinemia, accompanying obesity, enhances renal proximal tubular reabsorption of uric acid. The fourth part of this study examined the relationship between SUA and blood pressure (BP) in young adults. The association between SUA and BP, significant only in females, was strongly attenuated upon adjustment for BMI. The possibility that BMI lies in the causal pathway may explain the attenuation observed in the associations of SUA with BP and IMs. Finally, a significant hockey-stick shaped association of SUA with social phobia in our data suggests a protective effect of SUA only up to a certain concentration. Although our study findings have shed some light on the uncertainty underlying the pathophysiology of SUA, more compelling evidence using longitudinal designs, randomized controlled trials and the use of robust genetic tools is warranted to increase our understanding of the clinical significance of SUA.
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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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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.