780 resultados para SNPs Associations


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Common diseases such as endometriosis (ED), Alzheimer's disease (AD) and multiple sclerosis (MS) account for a significant proportion of the health care burden in many countries. Genome-wide association studies (GWASs) for these diseases have identified a number of individual genetic variants contributing to the risk of those diseases. However, the effect size for most variants is small and collectively the known variants explain only a small proportion of the estimated heritability. We used a linear mixed model to fit all single nucleotide polymorphisms (SNPs) simultaneously, and estimated genetic variances on the liability scale using SNPs from GWASs in unrelated individuals for these three diseases. For each of the three diseases, case and control samples were not all genotyped in the same laboratory. We demonstrate that a careful analysis can obtain robust estimates, but also that insufficient quality control (QC) of SNPs can lead to spurious results and that too stringent QC is likely to remove real genetic signals. Our estimates show that common SNPs on commercially available genotyping chips capture significant variation contributing to liability for all three diseases. The estimated proportion of total variation tagged by all SNPs was 0.26 (SE 0.04) for ED, 0.24 (SE 0.03) for AD and 0.30 (SE 0.03) for MS. Further, we partitioned the genetic variance explained into five categories by a minor allele frequency (MAF), by chromosomes and gene annotation. We provide strong evidence that a substantial proportion of variation in liability is explained by common SNPs, and thereby give insights into the genetic architecture of the diseases.

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Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases and controls in schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). We apply univariate and bivariate methods for the estimation of genetic variation within and covariation between disorders. SNPs explained 17-29% of the variance in liability. The genetic correlation calculated using common SNPs was high between schizophrenia and bipolar disorder (0.68 +/- 0.04 s.e.), moderate between schizophrenia and major depressive disorder (0.43 +/- 0.06 s.e.), bipolar disorder and major depressive disorder (0.47 +/- 0.06 s.e.), and ADHD and major depressive disorder (0.32 +/- 0.07 s.e.), low between schizophrenia and ASD (0.16 +/- 0.06 s.e.) and non-significant for other pairs of disorders as well as between psychiatric disorders and the negative control of Crohn's disease. This empirical evidence of shared genetic etiology for psychiatric disorders can inform nosology and encourages the investigation of common pathophysiologies for related disorders.

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Several aspects of sleep behavior such as timing, duration and quality have been demonstrated to be heritable. To identify common variants that influence sleep traits in the population, we conducted a genome-wide association study of six sleep phenotypes assessed by questionnaire in a sample of 2,323 individuals from the Australian Twin Registry. Genotyping was performed on the Illumina 317, 370, and 610K arrays and the SNPs in common between platforms were used to impute non-genotyped SNPs. We tested for association with more than 2,000,000 common polymorphisms across the genome. While no SNPs reached the genome-wide significance threshold, we identified a number of associations in plausible candidate genes. Most notably, a group of SNPs in the third intron of the CACNA1C gene ranked as most significant in the analysis of sleep latency (P = 1.3 x 10(-)(6)). We attempted to replicate this association in an independent sample from the Chronogen Consortium (n = 2,034), but found no evidence of association (P = 0.73). We have identified several other suggestive associations that await replication in an independent sample. We did not replicate the results from previous genome-wide analyses of self-reported sleep phenotypes after correction for multiple testing.

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Serum gamma-glutamyl transferase (GGT) activity is a marker of liver disease which is also prospectively associated with the risk of all-cause mortality, cardiovascular disease, type 2 diabetes and cancers. We have discovered novel loci affecting GGT in a genome-wide association study (rs1497406 in an intergenic region of chromosome 1, P = 3.9 x 10(-8); rs944002 in C14orf73 on chromosome 14, P = 4.7 x 10(-13); rs340005 in RORA on chromosome 15, P = 2.4 x 10(-8)), and a highly significant heterogeneity between adult and adolescent results at the GGT1 locus on chromosome 22 (maximum P(HET) = 5.6 x 10(-12) at rs6519520). Pathway analysis of significant and suggestive single-nucleotide polymorphism associations showed significant overlap between genes affecting GGT and those affecting common metabolic and inflammatory diseases, and identified the hepatic nuclear factor (HNF) family as controllers of a network of genes affecting GGT. Our results reinforce the disease associations of GGT and demonstrate that control by the GGT1 locus varies with age.

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Migraine without aura is the most common form of migraine, characterized by recurrent disabling headache and associated autonomic symptoms. To identify common genetic variants associated with this migraine type, we analyzed genome-wide association data of 2,326 clinic-based German and Dutch individuals with migraine without aura and 4,580 population-matched controls. We selected SNPs from 12 loci with 2 or more SNPs associated with P values of <1 x 10(-5) for replication testing in 2,508 individuals with migraine without aura and 2,652 controls. SNPs at two of these loci showed convincing replication: at 1q22 (in MEF2D; replication P = 4.9 x 10(-4); combined P = 7.06 x 10(-11)) and at 3p24 (near TGFBR2; replication P = 1.0 x 10(-4); combined P = 1.17 x 10(-9)). In addition, SNPs at the PHACTR1 and ASTN2 loci showed suggestive evidence of replication (P = 0.01; combined P = 3.20 x 10(-8) and P = 0.02; combined P = 3.86 x 10(-8), respectively). We also replicated associations at two previously reported migraine loci in or near TRPM8 and LRP1. This study identifies the first susceptibility loci for migraine without aura, thereby expanding our knowledge of this debilitating neurological disorder.

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Adverse health behaviors as well as obesity are key risk factors for chronic diseases. Working conditions also contribute to health outcomes. It is possible that the effects of psychosocially strenuous working conditions and other work-related factors on health are, to some extent, explained by adverse behaviors. Previous studies about the associations between several working conditions and behavioral outcomes are, however, inconclusive. Moreover, the results are derived mostly from male populations, one national setting only, and with limited information about working conditions and behavioral risk factors. Thus, with an interest in employee health, this study was set to focus on behavioral risk factors among middle-aged employees. More specifically, the main aim was to shed light on the associations of various working conditions with health behaviors, weight gain, obesity, and symptoms of angina pectoris. In addition to national focus, international comparisons were included to test the associations across countries thereby aiming to produce a more comprehensive picture. Furthermore, a special emphasis was on gaining new evidence in these areas among women. The data derived from the Helsinki Health Study, and from collaborative partners at the Whitehall II Study, University College London, UK, and the Toyama University, Japan. In Helsinki, the postal questionnaires were mailed in 2000-2002 to employees of the City of Helsinki, aged 40 60 years (n=8960). The questionnaire data covered e.g., socio-economic indicators and working conditions such as Karasek s job demands and job control, work fatigue, working overtime, work-home interface, and social support. The outcome measures consisted of smoking, drinking, physical activity, food habits, weight gain, obesity, and symptoms of angina pectoris. The international cohorts included comparable data. Logistic regression analysis was used. The models were adjusted for potential confounders such as age, education, occupational class, and marital status subject to specific aims. The results showed that working conditions were mostly unassociated with health behaviors, albeit some associations were found. Low job strain was associated with healthy food habits and non-smoking among women in Helsinki. Work fatigue, in turn, was related to drinking among men and physical inactivity among women. Work fatigue and working overtime were associated with weight gain in Helsinki among both women and men. Finally, work fatigue, low job control, working overtime, and physically strenuous work were associated with symptoms of angina pectoris among women in Helsinki. Cross-country comparisons confirmed mostly non-existent associations. High job strain was associated with physical inactivity and smoking, and passive work with physical inactivity and less drinking. Working overtime, in turn, related to non-smoking and obesity. All these associations were, however, inconsistent between cohorts and genders. In conclusion, the associations of the studied working conditions with the behavioral risk factors lacked general patters, and were, overall, weak considering the prevalence of psychosocially strenuous work and overtime hours. Thus, based on this study, the health effects of working conditions are likely to be mediated by adverse behaviors only to a minor extent. The associations of work fatigue and working overtime with weight gain and symptoms of angina pectoris are, however, of potential importance to the subsequent health and work ability of employees.

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Socioeconomic health inequalities have been widely documented, with a lower social position being associated with poorer physical and general health and higher mortality. For mental health the results have been more varied. However, the mechanisms by which the various dimensions of socioeconomic circumstances are associated with different domains of health are not yet fully understood. This is related to a lack of studies tackling the interrelations and pathways between multiple dimensions of socioeconomic circumstances and domains of health. In particular, evidence from comparative studies of populations from different national contexts that consider the complexity of the causes of socioeconomic health inequalities is needed. The aim of this study was to examine the associations of multiple socioeconomic circumstances with physical and mental health, more specifically physical functioning and common mental disorders. This was done in a comparative setting of two cohorts of white-collar public sector employees, one from Finland and one from Britain. The study also sought to find explanations for the observed associations between economic difficulties and health by analysing the contribution of health behaviours, living arrangements and work-family conflicts. The survey data were derived from the Finnish Helsinki Health Study baseline surveys in 2000-2002 among the City of Helsinki employees aged 40-60 years, and from the fifth phase of the London-based Whitehall II study (1997-9) which is a prospective study of civil servants aged 35-55 years at the time of recruitment. The data collection in the two countries was harmonised to safeguard maximal comparability. Physical functioning was measured with the Short Form (SF-36) physical component summary and common mental disorders with the General Health Questionnaire (GHQ-12). Socioeconomic circumstances were parental education, childhood economic difficulties, own education, occupational class, household income, housing tenure, and current economic difficulties. Further explanatory factors were health behaviours, living arrangements and work-family conflicts. The main statistical method used was logistic regression analysis. Analyses were conducted separately for the two sexes and two cohorts. Childhood and current economic difficulties were associated with poorer physical functioning and common mental disorders generally in both cohorts and sexes. Conventional dimensions of socioeconomic circumstances i.e. education, occupational class and income were associated with physical functioning and mediated each other’s effects, but in different ways in the two cohorts: education was more important in Helsinki and occupational class in London. The associations of economic difficulties with health were partly explained by work-family conflicts and other socioeconomic circumstances in both cohorts and sexes. In conclusion, this study on two country-specific cohorts confirms that different dimensions of socioeconomic circumstances are related but not interchangeable. They are also somewhat differently associated with physical and mental domains of health. In addition to conventionally measured dimensions of past and present socioeconomic circumstances, economic difficulties should be taken into account in studies and attempts to reduce health inequalities. Further explanatory factors, particularly conflicts between work and family, should also be considered when aiming to reduce inequalities and maintain the health of employees.

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In genetic epidemiology, population-based disease registries are commonly used to collect genotype or other risk factor information concerning affected subjects and their relatives. This work presents two new approaches for the statistical inference of ascertained data: a conditional and full likelihood approaches for the disease with variable age at onset phenotype using familial data obtained from population-based registry of incident cases. The aim is to obtain statistically reliable estimates of the general population parameters. The statistical analysis of familial data with variable age at onset becomes more complicated when some of the study subjects are non-susceptible, that is to say these subjects never get the disease. A statistical model for a variable age at onset with long-term survivors is proposed for studies of familial aggregation, using latent variable approach, as well as for prospective studies of genetic association studies with candidate genes. In addition, we explore the possibility of a genetic explanation of the observed increase in the incidence of Type 1 diabetes (T1D) in Finland in recent decades and the hypothesis of non-Mendelian transmission of T1D associated genes. Both classical and Bayesian statistical inference were used in the modelling and estimation. Despite the fact that this work contains five studies with different statistical models, they all concern data obtained from nationwide registries of T1D and genetics of T1D. In the analyses of T1D data, non-Mendelian transmission of T1D susceptibility alleles was not observed. In addition, non-Mendelian transmission of T1D susceptibility genes did not make a plausible explanation for the increase in T1D incidence in Finland. Instead, the Human Leucocyte Antigen associations with T1D were confirmed in the population-based analysis, which combines T1D registry information, reference sample of healthy subjects and birth cohort information of the Finnish population. Finally, a substantial familial variation in the susceptibility of T1D nephropathy was observed. The presented studies show the benefits of sophisticated statistical modelling to explore risk factors for complex diseases.

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Previous microarray analyses identified 22 microRNAs (miRNAs) differentially expressed in paired ectopic and eutopic endometrium of women with and without endometriosis. To investigate further the role of these miRNAs in women with endometriosis, we conducted an association study aiming to explore the relationship between endometriosis risk and single-nucleotide polymorphisms (SNPs) in miRNA target sites for these differentially expressed miRNAs. A panel of 102 SNPs in the predicted miRNA binding sites were evaluated for an endometriosis association study and an ingenuity pathway analysis was performed. Fourteen rare variants were identified in this study. We found SNP rs14647 in the Wolf-Hirschhorn syndrome candidate gene1 (WHSC1) 3'UTR (untranslated region) was associated with endometriosis-related infertility presenting an odds ratio of 12.2 (95% confidence interval = 2.4-60.7, P = 9.03 x 10(-5)). SNP haplotype AGG in the solute carrier family 22, member 23 (SLC22A23) 3'UTR was associated with endometriosis-related infertility and more severe disease. With the individual genotyping data, ingenuity pathways analysis identified the tumour necrosis factor and cyclin-dependant kinase inhibitor as major factors in the molecular pathways. Significant associations between WHSC1 alleles and endometriosis-related infertility and SLC22A23 haplotypes and the disease severe stage were identified. These findings may help focus future research on subphenotypes of this disease. Replication studies in independent large sample sets to confirm and characterize the involvement of the gene variation in the pathogenesis of endometriosis are needed.

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SNPs discovered by genome-wide association studies (GWASs) account for only a small fraction of the genetic variation of complex traits in human populations. Where is the remaining heritability? We estimated the proportion of variance for human height explained by 294,831 SNPs genotyped on 3,925 unrelated individuals using a linear model analysis, and validated the estimation method with simulations based on the observed genotype data. We show that 45% of variance can be explained by considering all SNPs simultaneously. Thus, most of the heritability is not missing but has not previously been detected because the individual effects are too small to pass stringent significance tests. We provide evidence that the remaining heritability is due to incomplete linkage disequilibrium between causal variants and genotyped SNPs, exacerbated by causal variants having lower minor allele frequency than the SNPs explored to date.

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Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and approximately 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 x 10(-)(8)), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.

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Elevated serum uric acid levels cause gout and are a risk factor for cardiovascular disease and diabetes. To investigate the polygenetic basis of serum uric acid levels, we conducted a meta-analysis of genome-wide association scans from 14 studies totalling 28,141 participants of European descent, resulting in identification of 954 SNPs distributed across nine loci that exceeded the threshold of genome-wide significance, five of which are novel. Overall, the common variants associated with serum uric acid levels fall in the following nine regions: SLC2A9 (p = 5.2x10(-201)), ABCG2 (p = 3.1x10(-26)), SLC17A1 (p = 3.0x10(-14)), SLC22A11 (p = 6.7x10(-14)), SLC22A12 (p = 2.0x10(-9)), SLC16A9 (p = 1.1x10(-8)), GCKR (p = 1.4x10(-9)), LRRC16A (p = 8.5x10(-9)), and near PDZK1 (p = 2.7x10(-9)). Identified variants were analyzed for gender differences. We found that the minor allele for rs734553 in SLC2A9 has greater influence in lowering uric acid levels in women and the minor allele of rs2231142 in ABCG2 elevates uric acid levels more strongly in men compared to women. To further characterize the identified variants, we analyzed their association with a panel of metabolites. rs12356193 within SLC16A9 was associated with DL-carnitine (p = 4.0x10(-26)) and propionyl-L-carnitine (p = 5.0x10(-8)) concentrations, which in turn were associated with serum UA levels (p = 1.4x10(-57) and p = 8.1x10(-54), respectively), forming a triangle between SNP, metabolites, and UA levels. Taken together, these associations highlight additional pathways that are important in the regulation of serum uric acid levels and point toward novel potential targets for pharmacological intervention to prevent or treat hyperuricemia. In addition, these findings strongly support the hypothesis that transport proteins are key in regulating serum uric acid levels.