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Rheumatoid arthritis (RA) is an archetypal, common, complex autoimmune disease with both genetic and environmental contributions to disease aetiology. Two novel RA susceptibility loci have been reported from recent genome-wide and candidate gene association studies. We, therefore, investigated the evidence for association of the STAT4 and TRAF1/C5 loci with RA using imputed data from the Wellcome Trust Case Control Consortium (WTCCC). No evidence for association of variants mapping to the TRAF1/C5 gene was detected in the 1860 RA cases and 2930 control samples tested in that study. Variants mapping to the STAT4 gene did show evidence for association (rs7574865, P = 0.04). Given the association of the TRAF1/C5 locus in two previous large case-control series from populations of European descent and the evidence for association of the STAT4 locus in the WTCCC study, single nucleotide polymorphisms mapping to these loci were tested for association with RA in an independent UK series comprising DNA from >3000 cases with disease and >3000 controls and a combined analysis including the WTCCC data was undertaken. We confirm association of the STAT4 and the TRAF1/C5 loci with RA bringing to 5 the number of confirmed susceptibility loci. The effect sizes are less than those reported previously but are likely to be a more accurate reflection of the true effect size given the larger size of the cohort investigated in the current study.
\n \n\n \n \nFinnish samples have been extensively utilized in studying single-gene disorders, where the founder effect has clearly aided in discovery, and more recently in genome-wide association studies of complex traits, where the founder effect has had less obvious impacts. As the field starts to explore rare variants' contribution to polygenic traits, it is of great importance to characterize and confirm the Finnish founder effect in sequencing data and to assess its implications for rare-variant association studies. Here, we employ forward simulation, guided by empirical deep resequencing data, to model the genetic architecture of quantitative polygenic traits in both the general European and the Finnish populations simultaneously. We demonstrate that power of rare-variant association tests is higher in the Finnish population, especially when variants' phenotypic effects are tightly coupled with fitness effects and therefore reflect a greater contribution of rarer variants. SKAT-O, variable-threshold tests, and single-variant tests are more powerful than other rare-variant methods in the Finnish population across a range of genetic models. We also compare the relative power and efficiency of exome array genotyping to those of high-coverage exome sequencing. At a fixed cost, less expensive genotyping strategies have far greater power than sequencing; in a fixed number of samples, however, genotyping arrays miss a substantial portion of genetic signals detected in sequencing, even in the Finnish founder population. As genetic studies probe sequence variation at greater depth in more diverse populations, our simulation approach provides a framework for evaluating various study designs for gene discovery.
\n \n\n \n \nPhysical activity and sleep disorders are established risk factors for many diseases, but their etiology is poorly understood, partly due to a reliance on self-reported evidence. Here we report a genome-wide association study (GWAS) of wearable-defined and machine-learned physical activity and sleep phenotypes in 91,112 UK Biobank participants, and self-reported physical activity in 351,154 UK Biobank participants. While the self-reported activity analysis resulted in no significant (p<5x10-9) loci, the analysis of objectively-measured traits identified 10 loci, 6 of which are novel. These 10 loci account for 0.05% of activity and 0.33% of sleep phenotype variation, but genome-wide estimates suggest that common variation accounts for ~12% of phenotypic variation, indicating high polygenicity. Heritability was higher in women than in men for overall activity (\u0394h2 = 4%, p=6.3x10-5), moderate intensity activity (6%, p=6.7x10-8), and walking (5%, p=2.6x10-6). Heritability partitioning, enrichment and pathway analyses all indicate the central nervous system plays a role in activity behaviours. Mendelian randomization in publicly available GWAS data and in 278,367 UK Biobank participants, who were not included in our discovery analyses, suggest that overall activity might be causally related to lowering body fat percentage (beta per SD higher overall activity: -0.44, SE=0.047, p=2.70x10-21) and systolic blood pressure (beta per SD: -0.71, SE=0.125, p=1.38x10-8). Our current results advocate the value of physical activity for the reduction of adiposity and blood pressure.
\n \n\n \n \nMore than one in three adults worldwide is either overweight or obese. Epidemiological studies indicate that the location and distribution of excess fat, rather than general adiposity, are more informative for predicting risk of obesity sequelae, including cardiometabolic disease and cancer. We performed a genome-wide association study meta-analysis of body fat distribution, measured by waist-to-hip ratio (WHR) adjusted for body mass index (WHRadjBMI), and identified 463 signals in 346 loci. Heritability and variant effects were generally stronger in women than men, and we found approximately one-third of all signals to be sexually dimorphic. The 5% of individuals carrying the most WHRadjBMI-increasing alleles were 1.62 times more likely than the bottom 5% to have a WHR above the thresholds used for metabolic syndrome. These data, made publicly available, will inform the biology of body fat distribution and its relationship with disease.
\n \n\n \n \nFibroblast growth factor 21 (FGF21) is a hormone that has insulin-sensitizing properties. Some trials of FGF21 analogs show weight loss and lipid-lowering effects. Recent studies have shown that a common allele in the FGF21 gene alters the balance of macronutrients consumed, but there was little evidence of an effect on metabolic traits. We studied a common FGF21 allele (A:rs838133) in 451,099 people from the UK Biobank study, aiming to use the human allele to inform potential adverse and beneficial effects of targeting FGF21. We replicated the association between the A allele and higher percentage carbohydrate intake. We then showed that this allele is more strongly associated with higher blood pressure and waist-hip ratio, despite an association with lower total body-fat percentage, than it is with BMI or type 2 diabetes. These human phenotypes of variation in the FGF21 gene will inform research into FGF21's mechanisms and therapeutic potential.
\n \n\n \n \nAtrial fibrillation (AF) affects more than 33 million individuals worldwide1 and has a complex heritability2. We conducted the largest meta-analysis of genome-wide association studies (GWAS) for AF to date, consisting of more than half a million individuals, including 65,446 with AF. In total, we identified 97 loci significantly associated with AF, including 67 that were novel in a combined-ancestry analysis, and 3 that were novel in a European-specific analysis. We sought to identify AF-associated genes at the GWAS loci by performing RNA-sequencing and expression quantitative trait locus analyses in 101 left atrial samples, the most relevant tissue for AF. We also performed transcriptome-wide analyses that identified 57 AF-associated genes, 42 of which overlap with GWAS loci. The identified loci implicate genes enriched within cardiac developmental, electrophysiological, contractile and structural pathways. These results extend our understanding of the biological pathways underlying AF and may facilitate the development of therapeutics for AF.
\n \n\n \n \nMeta-analysis of genome-wide association studies (GWASs) has led to the discoveries of many common variants associated with complex human diseases. There is a growing recognition that identifying \"causal\" rare variants also requires large-scale meta-analysis. The fact that association tests with rare variants are performed at the gene level rather than at the variant level poses unprecedented challenges in the meta-analysis. First, different studies may adopt different gene-level tests, so the results are not compatible. Second, gene-level tests require multivariate statistics (i.e., components of the test statistic and their covariance matrix), which are difficult to obtain. To overcome these challenges, we propose to perform gene-level tests for rare variants by combining the results of single-variant analysis (i.e., p values of association tests and effect estimates) from participating studies. This simple strategy is possible because of an insight that multivariate statistics can be recovered from single-variant statistics, together with the correlation matrix of the single-variant test statistics, which can be estimated from one of the participating studies or from a publicly available database. We show both theoretically and numerically that the proposed meta-analysis approach provides accurate control of the type I error and is as powerful as joint analysis of individual participant data. This approach accommodates any disease phenotype and any study design and produces all commonly used gene-level tests. An application to the GWAS summary results of the Genetic Investigation of ANthropometric Traits (GIANT) consortium reveals rare and low-frequency variants associated with human height. The relevant software is freely available.
\n \n\n \n \nIn the version of this article originally published, the name of author Martin H. de Borst was coded incorrectly in the XML. The error has now been corrected in the HTML version of the paper.
\n \n\n \n \nBACKGROUND: Genetic determinants of stroke, the leading neurological cause of death and disability, are poorly understood and have seldom been explored in the general population. Our aim was to identify additional loci for stroke by doing a meta-analysis of genome-wide association studies. METHODS: For the discovery sample, we did a genome-wide analysis of common genetic variants associated with incident stroke risk in 18 population-based cohorts comprising 84\u2008961 participants, of whom 4348 had stroke. Stroke diagnosis was ascertained and validated by the study investigators. Mean age at stroke ranged from 45\u00b78 years to 76\u00b74 years, and data collection in the studies took place between 1948 and 2013. We did validation analyses for variants yielding a significant association (at p<5\u2008\u00d7\u200810(-6)) with all-stroke, ischaemic stroke, cardioembolic ischaemic stroke, or non-cardioembolic ischaemic stroke in the largest available cross-sectional studies (70\u2008804 participants, of whom 19\u2008816 had stroke). Summary-level results of discovery and follow-up stages were combined using inverse-variance weighted fixed-effects meta-analysis, and in-silico lookups were done in stroke subtypes. For genome-wide significant findings (at p<5\u2008\u00d7\u200810(-8)), we explored associations with additional cerebrovascular phenotypes and did functional experiments using conditional (inducible) deletion of the probable causal gene in mice. We also studied the expression of orthologs of this probable causal gene and its effects on cerebral vasculature in zebrafish mutants. FINDINGS: We replicated seven of eight known loci associated with risk for ischaemic stroke, and identified a novel locus at chromosome 6p25 (rs12204590, near FOXF2) associated with risk of all-stroke (odds ratio [OR] 1\u00b708, 95% CI 1\u00b705-1\u00b712, p=1\u00b748\u2008\u00d7\u200810(-8); minor allele frequency 21%). The rs12204590 stroke risk allele was also associated with increased MRI-defined burden of white matter hyperintensity-a marker of cerebral small vessel disease-in stroke-free adults (n=21\u2008079; p=0\u00b70025). Consistently, young patients (aged 2-32 years) with segmental deletions of FOXF2 showed an extensive burden of white matter hyperintensity. Deletion of Foxf2 in adult mice resulted in cerebral infarction, reactive gliosis, and microhaemorrhage. The orthologs of FOXF2 in zebrafish (foxf2b and foxf2a) are expressed in brain pericytes and mutant foxf2b(-/-) cerebral vessels show decreased smooth muscle cell and pericyte coverage. INTERPRETATION: We identified common variants near FOXF2 that are associated with increased stroke susceptibility. Epidemiological and experimental data suggest that FOXF2 mediates this association, potentially via differentiation defects of cerebral vascular mural cells. Further expression studies in appropriate human tissues, and further functional experiments with long follow-up periods are needed to fully understand the underlying mechanisms. FUNDING: NIH, NINDS, NHMRC, CIHR, European national research institutions, Fondation Leducq.
\n \n\n \n \nFatty acid desaturases (FADS) catalyze the formation of unsaturated fatty acids and have been related to insulin sensitivity (IS). FADS activities differ between tissues and are influenced by genetic factors that may impact the link to IS. Genome-wide association studies of \u03b4-5-desaturase (D5D), \u03b4-6-desaturase (D6D) and stearoyl-CoA desaturase-1 (SCD) activities (estimated by product-to-precursor ratios of fatty acids analyzed by gas chromatography) in serum cholesterol esters (n = 1453) and adipose tissue (n = 783, all men) were performed in two Swedish population-based cohorts. Genome-wide significant associated loci were evaluated for associations with IS measured with a hyperinsulinemic euglycemic clamp (n = 554). Variants at the FADS1 were strongly associated with D5D in both cholesterol esters (p = 1.9 \u00d7 10-70) and adipose tissue (p = 1.1 \u00d7 10-27). Variants in three further loci were associated with D6D in cholesterol esters (FADS2, p = 3.0 \u00d7 10-67; PDXDCI, p = 4.8 \u00d7 10-8; and near MC4R, p = 3.7 \u00d7 10-8) but no associations with D6D in adipose tissue attained genome-wide significance. One locus was associated with SCD in adipose tissue (PKDL1, p = 2.2 \u00d7 10-19). Genetic variants near MC4R were associated with IS (p = 3.8 \u00d7 10-3). The FADS cluster was the main genetic determinant of estimated FADS activity. However, fatty acid (FA) ratios in adipose tissue and cholesterol esters represent FADS activities in separate tissues and are thus influenced by different genetic factors with potential varying effects on IS.
\n \n\n \n \nLarge consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain >99% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analysed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways.
\n \n\n \n \nGenome-wide association studies (GWAS) have found few common variants that influence fasting measures of insulin sensitivity. We hypothesized that a GWAS of an integrated assessment of fasting and dynamic measures of insulin sensitivity would detect novel common variants. We performed a GWAS of the modified Stumvoll Insulin Sensitivity Index (ISI) within the Meta-Analyses of Glucose and Insulin-Related Traits Consortium. Discovery for genetic association was performed in 16,753 individuals, and replication was attempted for the 23 most significant novel loci in 13,354 independent individuals. Association with ISI was tested in models adjusted for age, sex, and BMI and in a model analyzing the combined influence of the genotype effect adjusted for BMI and the interaction effect between the genotype and BMI on ISI (model 3). In model 3, three variants reached genome-wide significance: rs13422522 (NYAP2; P = 8.87 \u00d7 10(-11)), rs12454712 (BCL2; P = 2.7 \u00d7 10(-8)), and rs10506418 (FAM19A2; P = 1.9 \u00d7 10(-8)). The association at NYAP2 was eliminated by conditioning on the known IRS1 insulin sensitivity locus; the BCL2 and FAM19A2 associations were independent of known cardiometabolic loci. In conclusion, we identified two novel loci and replicated known variants associated with insulin sensitivity. Further studies are needed to clarify the causal variant and function at the BCL2 and FAM19A2 loci.
\n \n\n \n \nCirculating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P\u200a=\u200a4.5\u00d710(-8)-1.2\u00d710(-43)). Using a novel method to combine data across ethnicities (N\u200a=\u200a4,232 African Americans, N\u200a=\u200a1,776 Asians, and N\u200a=\u200a29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p<3\u00d710(-4)). We next developed a multi-SNP genotypic risk score to test the association of adiponectin decreasing risk alleles on metabolic traits and diseases using consortia-level meta-analytic data. This risk score was associated with increased risk of T2D (p\u200a=\u200a4.3\u00d710(-3), n\u200a=\u200a22,044), increased triglycerides (p\u200a=\u200a2.6\u00d710(-14), n\u200a=\u200a93,440), increased waist-to-hip ratio (p\u200a=\u200a1.8\u00d710(-5), n\u200a=\u200a77,167), increased glucose two hours post oral glucose tolerance testing (p\u200a=\u200a4.4\u00d710(-3), n\u200a=\u200a15,234), increased fasting insulin (p\u200a=\u200a0.015, n\u200a=\u200a48,238), but with lower in HDL-cholesterol concentrations (p\u200a=\u200a4.5\u00d710(-13), n\u200a=\u200a96,748) and decreased BMI (p\u200a=\u200a1.4\u00d710(-4), n\u200a=\u200a121,335). These findings identify novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance.
\n \n\n \n \nDespite the success of genome-wide association studies, much of the genetic contribution to complex human traits is still unexplained. One potential source of genetic variation that may contribute to this \"missing heritability\" is that which differs in magnitude and/or direction between males and females, which could result from sexual dimorphism in gene expression. Such sex-differentiated effects are common in model organisms, and are becoming increasingly evident in human complex traits through large-scale male- and female-specific meta-analyses. In this article, we review the methodology for meta-analysis of sex-specific genome-wide association studies, and propose a sex-differentiated test of association with quantitative or dichotomous traits, which allows for heterogeneity of allelic effects between males and females. We perform detailed simulations to compare the power of the proposed sex-differentiated meta-analysis with the more traditional \"sex-combined\" approach, which is ambivalent to gender. The results of this study highlight only a small loss in power for the sex-differentiated meta-analysis when the allelic effects of the causal variant are the same in males and females. However, over a range of models of heterogeneity in allelic effects between genders, our sex-differentiated meta-analysis strategy offers substantial gains in power, and thus has the potential to discover novel loci contributing effects to complex human traits with existing genome-wide association data.
\n \n\n \n \nBACKGROUND AND AIMS: Increased proinsulin relative to insulin levels have been associated with subclinical atherosclerosis (measured by carotid intima-media thickness (cIMT)) and are predictive of future cardiovascular disease (CVD), independently of established risk factors. The mechanisms linking proinsulin to atherosclerosis and CVD are unclear. A genome-wide meta-analysis has identified nine loci associated with circulating proinsulin levels. Using proinsulin-associated SNPs, we set out to use a Mendelian randomisation approach to test the hypothesis that proinsulin plays a causal role in subclinical vascular remodelling. METHODS: We studied the high CVD-risk IMPROVE cohort (n\u00a0=\u00a03345), which has detailed biochemical phenotyping and repeated, state-of-the-art, high-resolution carotid ultrasound examinations. Genotyping was performed using Illumina Cardio-Metabo and Immuno arrays, which include reported proinsulin-associated loci. Participants with type 2 diabetes (n\u00a0=\u00a0904) were omitted from the analysis. Linear regression was used to identify proinsulin-associated genetic variants. RESULTS: We identified a proinsulin locus on chromosome 15 (rs8029765) and replicated it in data from 20,003 additional individuals. An 11-SNP score, including the previously identified and the chromosome 15 proinsulin-associated loci, was significantly and negatively associated with baseline IMTmean and IMTmax (the primary cIMT phenotypes) but not with progression measures. However, MR-Eggers refuted any significant effect of the proinsulin-associated 11-SNP score, and a non-pleiotropic SNP score of three variants (including rs8029765) demonstrated no effect on baseline or progression cIMT measures. CONCLUSIONS: We identified a novel proinsulin-associated locus and demonstrated that whilst proinsulin levels are associated with cIMT measures, proinsulin per se is unlikely to have a causative effect on cIMT.
\n \n\n \n \nUsing genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated \u223c2,000, \u223c3,700 and \u223c9,500 SNPs explained \u223c21%, \u223c24% and \u223c29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/\u03b2-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.
\n \n\n \n \nBACKGROUND: Growth differentiation factor 15 (GDF15), a stress-responsive cytokine produced in cardiovascular cells under conditions of inflammation and oxidative stress, is emerging as an important prognostic marker in individuals with and without existing cardiovascular disease (CVD). We therefore examined the clinical and genetic correlates of circulating GDF15 concentrations, which have not been investigated collectively. METHODS: Plasma GDF15 concentrations were measured in 2991 participants in the Framingham Offspring Study who were free of clinically overt CVD (mean age, 59 years; 56% women). Clinical correlates of GDF15 were examined in multivariable analyses. We then conducted a genomewide association study of the GDF15 concentration that included participants in the Framingham Offspring Study and participants in the PIVUS (Prospective Investigation of the Vasculature in Uppsala Seniors) study. RESULTS: GDF15 was positively associated with age, smoking, antihypertensive treatment, diabetes, worse kidney function, and use of nonsteroidal antiinflammatory drugs (NSAIDs), but it was negatively associated with total cholesterol and HDL cholesterol. Clinical correlates accounted for 38% of interindividual variation in the circulating GDF15 concentration, whereas genetic factors accounted for up to 38% of the residual variability (h(2) = 0.38; P = 2.5 \u00d7 10(-11)). We identified 1 locus of genomewide significance. This locus, which is on chromosome 19p13.11 and includes the GDF15 gene, is associated with GDF15 concentration (smallest P = 2.74 \u00d7 10(-32) for rs888663). Conditional analyses revealed 2 independent association signals at this locus (rs888663 and rs1054564), which were associated with altered cis gene expression in blood cell lines. CONCLUSIONS: In ambulatory individuals, both cardiometabolic risk factors and genetic factors play important roles in determining circulating GDF15 concentrations and contribute similarly to the overall variation.
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