Showing papers by "Erik Ingelsson published in 2015"
01 Jan 2015
TL;DR: This paper conducted a genome-wide association study and meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals.
Abstract: Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P 20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.
2,721 citations
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TL;DR: This article conducted a meta-analysis of coronary artery disease (CAD) cases and controls, interrogating 6.7 million common (minor allele frequency (MAF) > 0.05) and 2.7 millions low-frequency (0.005 < MAF < 0.5) variants.
Abstract: Existing knowledge of genetic variants affecting risk of coronary artery disease (CAD) is largely based on genome-wide association study (GWAS) analysis of common SNPs. Leveraging phased haplotypes from the 1000 Genomes Project, we report a GWAS meta-analysis of ∼185,000 CAD cases and controls, interrogating 6.7 million common (minor allele frequency (MAF) > 0.05) and 2.7 million low-frequency (0.005 < MAF < 0.05) variants. In addition to confirming most known CAD-associated loci, we identified ten new loci (eight additive and two recessive) that contain candidate causal genes newly implicating biological processes in vessel walls. We observed intralocus allelic heterogeneity but little evidence of low-frequency variants with larger effects and no evidence of synthetic association. Our analysis provides a comprehensive survey of the fine genetic architecture of CAD, showing that genetic susceptibility to this common disease is largely determined by common SNPs of small effect size.
1,839 citations
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TL;DR: A genome-wide association study in the Nordic region identifying a novel MM risk locus at ELL2 that encodes a stoichiometrically limiting component of the super-elongation complex that drives secretory-specific immunoglobulin mRNA production and transcriptional regulation in plasma cells is reported.
Abstract: Multiple myeloma (MM) is characterized by an uninhibited, clonal growth of plasma cells. While first-degree relatives of patients with MM show an increased risk of MM, the genetic basis of inherited MM susceptibility is incompletely understood. Here we report a genome-wide association study in the Nordic region identifying a novel MM risk locus at ELL2 (rs56219066T; odds ratio (OR)=1.25; P=9.6 × 10(-10)). This gene encodes a stoichiometrically limiting component of the super-elongation complex that drives secretory-specific immunoglobulin mRNA production and transcriptional regulation in plasma cells. We find that the MM risk allele harbours a Thr298Ala missense variant in an ELL2 domain required for transcription elongation. Consistent with a hypomorphic effect, we find that the MM risk allele also associates with reduced levels of immunoglobulin A (IgA) and G (IgG) in healthy subjects (P=8.6 × 10(-9) and P=6.4 × 10(-3), respectively) and, potentially, with an increased risk of bacterial meningitis (OR=1.30; P=0.0024).
1,342 citations
23 Oct 2015
TL;DR: A GWAS meta-analysis of CAD cases and controls provides a comprehensive survey of the fine genetic architecture of CAD, showing that genetic susceptibility to this common disease is largely determined by common SNPs of small effect size.
Abstract: Existing knowledge of genetic variants affecting risk of coronary artery disease (CAD) is largely based on genome-wide association study (GWAS) analysis of common SNPs. Leveraging phased haplotypes from the 1000 Genomes Project, we report a GWAS meta-analysis of ∼185,000 CAD cases and controls, interrogating 6.7 million common (minor allele frequency (MAF) > 0.05) and 2.7 million low-frequency (0.005 < MAF < 0.05) variants. In addition to confirming most known CAD-associated loci, we identified ten new loci (eight additive and two recessive) that contain candidate causal genes newly implicating biological processes in vessel walls. We observed intralocus allelic heterogeneity but little evidence of low-frequency variants with larger effects and no evidence of synthetic association. Our analysis provides a comprehensive survey of the fine genetic architecture of CAD, showing that genetic susceptibility to this common disease is largely determined by common SNPs of small effect size.
797 citations
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University of Queensland1, Medical Research Council2, University of New England (Australia)3, University of Cambridge4, University Medical Center Groningen5, University of Tartu6, Karolinska Institutet7, Stanford University8, Science for Life Laboratory9, Wellcome Trust Sanger Institute10, University of Colorado Boulder11, University of Melbourne12
TL;DR: It is demonstrated using simulations based on whole-genome sequencing data that ∼97% and ∼68% of variation at common and rare variants, respectively, can be captured by imputation, and evidence that height- and BMI-associated variants have been under natural selection is found.
Abstract: We propose a method (GREML-LDMS) to estimate heritability for human complex traits in unrelated individuals using whole-genome sequencing data. We demonstrate using simulations based on whole-genome sequencing data that ∼97% and ∼68% of variation at common and rare variants, respectively, can be captured by imputation. Using the GREML-LDMS method, we estimate from 44,126 unrelated individuals that all ∼17 million imputed variants explain 56% (standard error (s.e.) = 2.3%) of variance for height and 27% (s.e. = 2.5%) of variance for body mass index (BMI), and we find evidence that height- and BMI-associated variants have been under natural selection. Considering the imperfect tagging of imputation and potential overestimation of heritability from previous family-based studies, heritability is likely to be 60-70% for height and 30-40% for BMI. Therefore, the missing heritability is small for both traits. For further discovery of genes associated with complex traits, a study design with SNP arrays followed by imputation is more cost-effective than whole-genome sequencing at current prices.
748 citations
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Thomas W. Winkler1, Anne E. Justice2, Mariaelisa Graff2, Llilda Barata3 +435 more•Institutions (106)
TL;DR: In this paper, the authors performed meta-analyses of 114 studies with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium.
Abstract: Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age- and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent) with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium. Each study tested the association of up to ~2.8M SNPs with BMI and WHRadjBMI in four strata (men ≤50y, men >50y, women ≤50y, women >50y) and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE), sex-specific effects (G x SEX) or age-specific effects that differed between men and women (G x AGE x SEX). For BMI, we identified 15 loci (11 previously established for main effects, four novel) that showed significant (FDR<5%) age-specific effects, of which 11 had larger effects in younger (<50y) than in older adults (≥50y). No sex-dependent effects were identified for BMI. For WHRadjBMI, we identified 44 loci (27 previously established for main effects, 17 novel) with sex-specific effects, of which 28 showed larger effects in women than in men, five showed larger effects in men than in women, and 11 showed opposite effects between sexes. No age-dependent effects were identified for WHRadjBMI. This is the first genome-wide interaction meta-analysis to report convincing evidence of age-dependent genetic effects on BMI. In addition, we confirm the sex-specificity of genetic effects on WHRadjBMI. These results may provide further insights into the biology that underlies weight change with age or the sexually dimorphism of body shape.
584 citations
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TL;DR: This paper performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry, and identified 49 distinct association signals at these loci including five mapping in or near KCNQ1.
Abstract: We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine mapping implicated rs10830963 as driving T2D association. We confirmed that the T2D risk allele for this SNP increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease.
370 citations
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TL;DR: The prediction score developed accurately predicts 5 year all-cause mortality and can be used by individuals to improve health awareness, and by health professionals and organisations to identify high-risk individuals and guide public policy.
303 citations
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University of Helsinki1, National Institutes of Health2, Wellcome Trust Centre for Human Genetics3, University of Tartu4, University of Ferrara5, University Medical Center Groningen6, Amgen7, Karolinska Institutet8, Uppsala University9, VU University Amsterdam10, Erasmus University Rotterdam11, Lund University12, Leiden University Medical Center13, National Institute for Health Research14, University of Lübeck15, Medical Research Council16, Technische Universität München17, University of Tampere18, Steno Diabetes Center19, Ludwig Maximilian University of Munich20, Harvard University21, Massachusetts Institute of Technology22, European Bioinformatics Institute23, University of Leicester24, Turku University Hospital25, Uppsala University Hospital26, Erasmus University Medical Center27, University College London28, University of Turku29, University of Oxford30, University of Iceland31, Minerva Foundation Institute for Medical Research32, University of Liverpool33, Imperial College London34, Wellcome Trust Sanger Institute35
TL;DR: Using a genome-wide screen of 9.6 million genetic variants achieved through 1000 Genomes Project imputation in 62,166 samples, association to lipid traits in 93 loci is identified, including 79 previously identified loci with new lead SNPs and 10 new loci, including 15 locu with a low-frequency lead SNP and 10 loco with a missense lead SNP.
Abstract: Using a genome-wide screen of 9.6 million genetic variants achieved through 1000 Genomes Project imputation in 62,166 samples, we identify association to lipid traits in 93 loci, including 79 previously identified loci with new lead SNPs and 10 new loci, 15 loci with a low-frequency lead SNP and 10 loci with a missense lead SNP, and 2 loci with an accumulation of rare variants. In six loci, SNPs with established function in lipid genetics (CELSR2, GCKR, LIPC and APOE) or candidate missense mutations with predicted damaging function (CD300LG and TM6SF2) explained the locus associations. The low-frequency variants increased the proportion of variance explained, particularly for low-density lipoprotein cholesterol and total cholesterol. Altogether, our results highlight the impact of low-frequency variants in complex traits and show that imputation offers a cost-effective alternative to resequencing.
279 citations
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University of Queensland1, Erasmus University Medical Center2, Wellcome Trust Sanger Institute3, University of Tartu4, Broad Institute5, Harvard University6, National Institutes of Health7, Science for Life Laboratory8, University of North Carolina at Chapel Hill9, University of Michigan10, Technical University of Denmark11, University of Exeter12, Utrecht University13, University of Oslo14, University of Copenhagen15, Lundbeck16, VU University Amsterdam17, VU University Medical Center18, Wellcome Trust Centre for Human Genetics19, Icahn School of Medicine at Mount Sinai20, University of Cambridge21, Karolinska Institutet22, QIMR Berghofer Medical Research Institute23, St Thomas' Hospital24, Government of Victoria25, University of Melbourne26
TL;DR: It is found that many independent loci contribute to population genetic differences in height and body mass index in 9,416 individuals across 14 European countries.
Abstract: Across-nation differences in the mean values for complex traits are common, but the reasons for these differences are unknown. Here we find that many independent loci contribute to population genetic differences in height and body mass index (BMI) in 9,416 individuals across 14 European countries. Using discovery data on over 250,000 individuals and unbiased effect size estimates from 17,500 sibling pairs, we estimate that 24% (95% credible interval (CI) = 9%, 41%) and 8% (95% CI = 4%, 16%) of the captured additive genetic variance for height and BMI, respectively, reflect population genetic differences. Population genetic divergence differed significantly from that in a null model (height, P < 3.94 × 10(-8); BMI, P < 5.95 × 10(-4)), and we find an among-population genetic correlation for tall and slender individuals (r = -0.80, 95% CI = -0.95, -0.60), consistent with correlated selection for both phenotypes. Observed differences in height among populations reflected the predicted genetic means (r = 0.51; P < 0.001), but environmental differences across Europe masked genetic differentiation for BMI (P < 0.58).
249 citations
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TL;DR: In this article, the authors conducted a genome-wide meta-analysis of predominately regular-type coffee consumption (cups per day) among up to 91,462 coffee consumers of European ancestry with top single-nucleotide polymorphisms (SNPs) followed-up in ~30,062 and 7964 coffee consumers with European and African-American ancestry, respectively.
Abstract: Coffee, a major dietary source of caffeine, is among the most widely consumed beverages in the world and has received considerable attention regarding health risks and benefits. We conducted a genome-wide (GW) meta-analysis of predominately regular-type coffee consumption (cups per day) among up to 91,462 coffee consumers of European ancestry with top single-nucleotide polymorphisms (SNPs) followed-up in ~30 062 and 7964 coffee consumers of European and African-American ancestry, respectively. Studies from both stages were combined in a trans-ethnic meta-analysis. Confirmed loci were examined for putative functional and biological relevance. Eight loci, including six novel loci, met GW significance (log10Bayes factor (BF)>5.64) with per-allele effect sizes of 0.03-0.14 cups per day. Six are located in or near genes potentially involved in pharmacokinetics (ABCG2, AHR, POR and CYP1A2) and pharmacodynamics (BDNF and SLC6A4) of caffeine. Two map to GCKR and MLXIPL genes related to metabolic traits but lacking known roles in coffee consumption. Enhancer and promoter histone marks populate the regions of many confirmed loci and several potential regulatory SNPs are highly correlated with the lead SNP of each. SNP alleles near GCKR, MLXIPL, BDNF and CYP1A2 that were associated with higher coffee consumption have previously been associated with smoking initiation, higher adiposity and fasting insulin and glucose but lower blood pressure and favorable lipid, inflammatory and liver enzyme profiles (P<5 × 10(-8)).Our genetic findings among European and African-American adults reinforce the role of caffeine in mediating habitual coffee consumption and may point to molecular mechanisms underlying inter-individual variability in pharmacological and health effects of coffee.
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TL;DR: There is a primary association between a genetically determined shorterheight and an increased risk of CAD, a link that is partly explained by the association between shorter height and an adverse lipid profile.
Abstract: BACKGROUND The nature and underlying mechanisms of an inverse association between adult height and the risk of coronary artery disease (CAD) are unclear. METHODS We used a genetic approach to investigate the association between height and CAD, using 180 height-associated genetic variants. We tested the association between a change in genetically determined height of 1 SD (6.5 cm) with the risk of CAD in 65,066 cases and 128,383 controls. Using individual-level genotype data from 18,249 persons, we also examined the risk of CAD associated with the presence of various numbers of height-associated alleles. To identify putative mechanisms, we analyzed whether genetically determined height was associated with known cardiovascular risk factors and performed a pathway analysis of the height-associated genes. RESULTS We observed a relative increase of 13.5% (95% confidence interval [CI], 5.4 to 22.1; P<0.001) in the risk of CAD per 1-SD decrease in genetically determined height. There was a graded relationship between the presence of an increased number of height-raising variants and a reduced risk of CAD (odds ratio for height quar-tile 4 versus quartile 1, 0.74; 95% CI, 0.68 to 0.84; P<0.001). Of the 12 risk factors that we studied, we observed significant associations only with levels of low-density lipoprotein cholesterol and triglycerides (accounting for approximately 30% of the association). We identified several overlapping pathways involving genes associated with both development and atherosclerosis. CONCLUSIONS There is a primary association between a genetically determined shorter height and an increased risk of CAD, a link that is partly explained by the association between shorter height and an adverse lipid profile. Shared biologic processes that determine achieved height and the development of atherosclerosis may explain some of the association.
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TL;DR: In this article, the role of coding variation on intermediate traits for type 2 diabetes was explored by analysis of variants on the HumanExome BeadChip in 60,564 non-diabetic individuals and in 16,491 T2D cases and 81,877 controls.
Abstract: Fasting glucose and insulin are intermediate traits for type 2 diabetes. Here we explore the role of coding variation on these traits by analysis of variants on the HumanExome BeadChip in 60,564 non-diabetic individuals and in 16,491 T2D cases and 81,877 controls. We identify a novel association of a low-frequency nonsynonymous SNV in GLP1R (A316T; rs10305492; MAF=1.4%) with lower FG (β=-0.09±0.01 mmol l(-1), P=3.4 × 10(-12)), T2D risk (OR[95%CI]=0.86[0.76-0.96], P=0.010), early insulin secretion (β=-0.07±0.035 pmolinsulin mmolglucose(-1), P=0.048), but higher 2-h glucose (β=0.16±0.05 mmol l(-1), P=4.3 × 10(-4)). We identify a gene-based association with FG at G6PC2 (pSKAT=6.8 × 10(-6)) driven by four rare protein-coding SNVs (H177Y, Y207S, R283X and S324P). We identify rs651007 (MAF=20%) in the first intron of ABO at the putative promoter of an antisense lncRNA, associating with higher FG (β=0.02±0.004 mmol l(-1), P=1.3 × 10(-8)). Our approach identifies novel coding variant associations and extends the allelic spectrum of variation underlying diabetes-related quantitative traits and T2D susceptibility.
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TL;DR: It is demonstrated here that smoking is associated with LOY in blood cells in three independent cohorts, and the finding that smoking induces LOY thus links a preventable risk factor with the most common acquired human mutation.
Abstract: Tobacco smoking is a risk factor for numerous disorders, including cancers affecting organs outside the respiratory tract. Epidemiological data suggest that smoking is a greater risk factor for these cancers in males compared with females. This observation, together with the fact that males have a higher incidence of and mortality from most non–sex-specific cancers, remains unexplained. Loss of chromosome Y (LOY) in blood cells is associated with increased risk of nonhematological tumors. We demonstrate here that smoking is associated with LOY in blood cells in three independent cohorts [TwinGene: odds ratio (OR) = 4.3, 95% confidence interval (CI) = 2.8 to 6.7; Uppsala Longitudinal Study of Adult Men: OR = 2.4, 95% CI = 1.6 to 3.6; and Prospective Investigation of the Vasculature in Uppsala Seniors: OR = 3.5, 95% CI = 1.4 to 8.4] encompassing a total of 6014 men. The data also suggest that smoking has a transient and dose-dependent mutagenic effect on LOY status. The finding that smoking induces LOY thus links a preventable risk factor with the most common acquired human mutation.
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TL;DR: This study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been.
Abstract: Homozygosity has long been associated with rare, often devastating, Mendelian disorders, and Darwin was one of the first to recognize that inbreeding reduces evolutionary fitness. However, the effect of the more distant parental relatedness that is common in modern human populations is less well understood. Genomic data now allow us to investigate the effects of homozygosity on traits of public health importance by observing contiguous homozygous segments (runs of homozygosity), which are inferred to be homozygous along their complete length. Given the low levels of genome-wide homozygosity prevalent in most human populations, information is required on very large numbers of people to provide sufficient power. Here we use runs of homozygosity to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts, and find statistically significant associations between summed runs of homozygosity and four complex traits: height, forced expiratory lung volume in one second, general cognitive ability and educational attainment (P < 1 × 10(-300), 2.1 × 10(-6), 2.5 × 10(-10) and 1.8 × 10(-10), respectively). In each case, increased homozygosity was associated with decreased trait value, equivalent to the offspring of first cousins being 1.2 cm shorter and having 10 months' less education. Similar effect sizes were found across four continental groups and populations with different degrees of genome-wide homozygosity, providing evidence that homozygosity, rather than confounding, directly contributes to phenotypic variance. Contrary to earlier reports in substantially smaller samples, no evidence was seen of an influence of genome-wide homozygosity on blood pressure and low density lipoprotein cholesterol, or ten other cardio-metabolic traits. Since directional dominance is predicted for traits under directional evolutionary selection, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been.
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Science for Life Laboratory1, Uppsala University2, Karolinska Institutet3, University of Tartu4, VU University Amsterdam5, Erasmus University Medical Center6, National Institute for Health and Welfare7, University of Helsinki8, National Institutes of Health9, QIMR Berghofer Medical Research Institute10, Pennington Biomedical Research Center11, University of Leeds12, University of Oulu13, King's College London14, St George's, University of London15, University of Leicester16, Queen's University Belfast17, Centre national de la recherche scientifique18, French Institute of Health and Medical Research19, University of Milano-Bicocca20, Leiden University21, Imperial College London22, University of Oxford23
TL;DR: In this paper, the effect of body mass index (BMI) on risk of cardiovascular diseases was investigated using Mendelian randomization (MR) methods, and the results indicated a strong association between BMI and incident coronary heart disease (CHD), heart failure, and ischaemic stroke.
Abstract: Background: Adiposity, as indicated by body mass index (BMI), has been associated with risk of cardiovascular diseases in epidemiological studies. We aimed to investigate if these associations are causal, using Mendelian randomization (MR) methods. Methods: The associations of BMI with cardiovascular outcomes [coronary heart disease (CHD), heart failure and ischaemic stroke], and associations of a genetic score (32 BMI single nucleotide polymorphisms) with BMI and cardiovascular outcomes were examined in up to 22 193 individuals with 3062 incident cardiovascular events from nine prospective follow-up studies within the ENGAGE consortium. We used random-effects meta-analysis in an MR framework to provide causal estimates of the effect of adiposity on cardiovascular outcomes. Results: There was a strong association between BMI and incident CHD (HR = 1.20 per SD-increase of BMI, 95% CI, 1.12-1.28, P = 1.9·10-7), heart failure (HR = 1.47, 95% CI, 1.35-1.60, P = 9·10-19) and ischaemic stroke (HR = 1.15, 95% CI, 1.06-1.24, P = 0.0008) in observational analyses. The genetic score was robustly associated with BMI (β = 0.030 SD-increase of BMI per additional allele, 95% CI, 0.028-0.033, P = 3·10-107). Analyses indicated a causal effect of adiposity on development of heart failure (HR = 1.93 per SD-increase of BMI, 95% CI, 1.12-3.30, P = 0.017) and ischaemic stroke (HR = 1.83, 95% CI, 1.05-3.20, P = 0.034). Additional cross-sectional analyses using both ENGAGE and CARDIoGRAMplusC4D data showed a causal effect of adiposity on CHD. Conclusions: Using MR methods, we provide support for the hypothesis that adiposity causes CHD, heart failure and, previously not demonstrated, ischaemic stroke.
23 Jul 2015
TL;DR: In this article, the authors use runs of homozygosity to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts, and find statistically significant associations between summed runs of heterozygosity and four complex traits: height, forced expiratory lung volume in one second, general cognitive ability and educational attainment.
Abstract: Homozygosity has long been associated with rare, often devastating, Mendelian disorders1, and Darwin was one of the first to recognize that inbreeding reduces evolutionary fitness2. However, the effect of the more distant parental relatedness that is common in modern human populations is less well understood. Genomic data now allow us to investigate the effects of homozygosity on traits of public health importance by observing contiguous homozygous segments (runs of homozygosity), which are inferred to be homozygous along their complete length. Given the low levels of genome-wide homozygosity prevalent in most human populations, information is required on very large numbers of people to provide sufficient power3, 4. Here we use runs of homozygosity to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts, and find statistically significant associations between summed runs of homozygosity and four complex traits: height, forced expiratory lung volume in one second, general cognitive ability and educational attainment (P < 1 × 10−300, 2.1 × 10−6, 2.5 × 10−10 and 1.8 × 10−10, respectively). In each case, increased homozygosity was associated with decreased trait value, equivalent to the offspring of first cousins being 1.2 cm shorter and having 10 months’ less education. Similar effect sizes were found across four continental groups and populations with different degrees of genome-wide homozygosity, providing evidence that homozygosity, rather than confounding, directly contributes to phenotypic variance. Contrary to earlier reports in substantially smaller samples5, 6, no evidence was seen of an influence of genome-wide homozygosity on blood pressure and low density lipoprotein cholesterol, or ten other cardio-metabolic traits. Since directional dominance is predicted for traits under directional evolutionary selection7, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been.
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TL;DR: The hypothesis that exposure to dogs and farm animals during the first year of life reduces the risk of asthma in children at age 6 years is supported, and decision making for families and physicians on the appropriateness and timing of early animal exposure is helpful.
Abstract: Importance The association between early exposure to animals and childhood asthma is not clear, and previous studies have yielded contradictory results. Objective To determine whether exposure to dogs and farm animals confers a risk of asthma. Design, Setting and Participants In a nationwide cohort study, the association between early exposure to dogs and farm animals and the risk of asthma was evaluated and included all children born in Sweden from January 1, 2001, to December 31, 2010 (N = 1 011 051), using registry data on dog and farm registration, asthma medication, diagnosis, and confounders for parents and their children. The association was assessed as the odds ratio (OR) for a current diagnosis of asthma at age 6 years for school-aged children and as the hazard ratio (HR) for incident asthma at ages 1 to 5 years for preschool-aged children. Data were analyzed from January 1, 2007, to September 30, 2012. Exposures Living with a dog or farm animal. Main Outcomes and Measures Childhood asthma diagnosis and medication used. Results Of the 1 011 051 children born during the study period, 376 638 preschool-aged (53 460 [14.2%] exposed to dogs and 1729 [0.5%] exposed to farm animals) and 276 298 school-aged children (22 629 [8.2%] exposed to dogs and 958 [0.3%] exposed to farm animals) were included in the analyses. Of these, 18 799 children (5.0%) in the preschool-aged children’s cohort experienced an asthmatic event before baseline, and 28 511 cases of asthma and 906 071 years at risk were recorded during follow-up (incidence rate, 3.1 cases per 1000 years at risk). In the school-aged children’s cohort, 11 585 children (4.2%) experienced an asthmatic event during the seventh year of life. Dog exposure during the first year of life was associated with a decreased risk of asthma in school-aged children (OR, 0.87; 95% CI, 0.81-0.93) and in preschool-aged children 3 years or older (HR, 0.90; 95% CI, 0.83-0.99) but not in children younger than 3 years (HR, 1.03; 95% CI, 1.00-1.07). Results were comparable when analyzing only first-born children. Farm animal exposure was associated with a reduced risk of asthma in both school-aged children and preschool-aged children (OR, 0.48; 95% CI, 0.31-0.76, and HR, 0.69; 95% CI, 0.56-0.84), respectively. Conclusions and Relevance In this study, the data support the hypothesis that exposure to dogs and farm animals during the first year of life reduces the risk of asthma in children at age 6 years. This information might be helpful in decision making for families and physicians on the appropriateness and timing of early animal exposure.
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TL;DR: Evidence of links between genetic variants associated with lipids and T2D is found, but deeper knowledge of the underlying genetic mechanisms of specific lipid variants is needed before drawing definite conclusions about causality based on Mendelian randomization methodology.
Abstract: The effects of dyslipidemia on the risk of type 2 diabetes (T2D) and related traits are not clear. We used regression models and 140 lipid-associated genetic variants to estimate associations between circulating HDL cholesterol (HDL-C), LDL cholesterol (LDL-C), and triglycerides and T2D and related traits. Each genetic test was corrected for effects of variants on the other two lipid types and surrogates of adiposity. We used the largest data sets available: 34,840 T2D case and 114,981 control subjects from the DIAGRAM (DIAbetes Genetics Replication And Meta-analysis) consortium and up to 133,010 individuals without diabetes for insulin secretion and sensitivity from the MAGIC (Meta-Analyses of Glucose and Insulin-related traits Consortium) and GENESIS (GENEticS of Insulin Sensitivity) studies. Eight of 21 associations between groups of variants and diabetes traits were significant at the nominal level, including those between genetically determined lower HDL-C (β = -0.12, P = 0.03) and T2D and genetically determined lower LDL-C (β = -0.21, P = 5 × 10(-6)) and T2D. Although some of these may represent causal associations, we discuss why caution must be used when using Mendelian randomization in the context of circulating lipid levels and diabetes traits. In conclusion, we found evidence of links between genetic variants associated with lipids and T2D, but deeper knowledge of the underlying genetic mechanisms of specific lipid variants is needed before drawing definite conclusions about causality based on Mendelian randomization methodology.
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University of Leicester1, University of Nottingham2, University of Edinburgh3, University of British Columbia4, University of Bristol5, Imperial College London6, University of Cambridge7, Greifswald University Hospital8, Swiss Tropical and Public Health Institute9, Uppsala University10, University of Helsinki11, University of Split12, King's College London13, Wellcome Trust Centre for Human Genetics14, University of Western Australia15, Sir Charles Gairdner Hospital16, Laval University17, University Medical Center Groningen18, Pompeu Fabra University19, Oulu University Hospital20, National Institutes of Health21, University of Dundee22, University of Oxford23, Stanford University24, University of Queensland25, Boston Children's Hospital26, Merck & Co.27, University of Glasgow28, Turku University Hospital29, Wellcome Trust Sanger Institute30, University of Tampere31, Ludwig Maximilian University of Munich32, Technische Universität München33, University of Basel34, University of Liverpool35, University of Tartu36, St George's, University of London37, National Institute for Health Research38, Queen Mary University of London39
TL;DR: 14 novel loci are identified in or near ENSA, RNU5F-1, KCNS3, AK097794, ASTN2, LHX3, CCDC91, TBx3, TRIP11, RIN3, TEKT5, LTBP4, MN1 and AP1S2, providing a basis for new understanding of the genetic determinants of these traits and pulmonary diseases in which they are altered.
Abstract: Lung function measures are used in the diagnosis of chronic obstructive pulmonary disease. In 38,199 European ancestry individuals, we studied genome-wide association of forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC) and FEV1/FVC with 1000 Genomes Project (phase 1)-imputed genotypes and followed up top associations in 54,550 Europeans. We identify 14 novel loci (P<5 × 10(-8)) in or near ENSA, RNU5F-1, KCNS3, AK097794, ASTN2, LHX3, CCDC91, TBX3, TRIP11, RIN3, TEKT5, LTBP4, MN1 and AP1S2, and two novel signals at known loci NPNT and GPR126, providing a basis for new understanding of the genetic determinants of these traits and pulmonary diseases in which they are altered.
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TL;DR: A novel targeted proteomics approach using the proximity extension technique discovered several new associations of candidate proteins with carotid artery plaque prevalence in a large human sample.
13 Mar 2015
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TL;DR: Whole blood measurements of toxic metals are associated with genetic variants in metal transporter genes and others, relevant in inferring metabolic pathways of metals and identifying subsets of individuals who may be more susceptible to metal toxicity.
Abstract: The accumulation of toxic metals in the human body is influenced by exposure and mechanisms involved in metabolism, some of which may be under genetic control. This is the first genome-wide association study to investigate variants associated with whole blood levels of a range of toxic metals. Eleven toxic metals and trace elements (aluminium, cadmium, cobalt, copper, chromium, mercury, manganese, molybdenum, nickel, lead and zinc) were assayed in a cohort of 949 individuals using mass spectrometry. DNA samples were genotyped on the Infinium Omni Express bead microarray and imputed up to reference panels from the 1000 Genomes Project. Analyses revealed two regions associated with manganese level at genome-wide significance, mapping to 4q24 and 1q41. The lead single nucleotide polymorphism (SNP) in the 4q24 locus was rs13107325 (P-value = 5.1 × 10(-11), β = -0.77), located in an exon of SLC39A8, which encodes a protein involved in manganese and zinc transport. The lead SNP in the 1q41 locus is rs1776029 (P-value = 2.2 × 10(-14), β = -0.46). The SNP lies within the intronic region of SLC30A10, another transporter protein. Among other metals, the loci 6q14.1 and 3q26.32 were associated with cadmium and mercury levels (P = 1.4 × 10(-10), β = -1.2 and P = 1.8 × 10(-9), β = -1.8, respectively). Whole blood measurements of toxic metals are associated with genetic variants in metal transporter genes and others. This is relevant in inferring metabolic pathways of metals and identifying subsets of individuals who may be more susceptible to metal toxicity.
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Karolinska Institutet1, University of Milan2, University of Dundee3, University of Queensland4, University College London5, University of Verona6, Lund University7, Science for Life Laboratory8, Linköping University9, Semmelweis University10, University of Eastern Finland11, University Medical Center Groningen12, University of Perugia13, Uppsala University14, Umeå University15
TL;DR: Some evidence is provided for adiponectin protecting against atherosclerosis, with effects being confined to men; however, compared with established cardiovascular risk factors, the effect of plasma adiponECTin was modest.
Abstract: Background-—Plasma adiponectin levels have previously been inversely associated with carotid intima-media thickness (IMT), a marker of subclinical atherosclerosis. In this study, we used a sex-stratified Mendelian randomization approach to investigate whether adiponectin has a causal protective influence on IMT. Methods and Results-—BaselineplasmaadiponectinconcentrationwastestedforassociationwithbaselineIMT,IMTprogressionover 30 months, and occurrence of cardiovascular events within 3 years in 3430 participants (women, n=1777; men, n=1653) with high cardiovascular risk but no prevalent disease. Plasma adiponectin levels were inversely associated with baseline mean bifurcation IMT after adjustment for established risk factors (b=� 0.018, P<0.001) in men but not in women (b=� 0.006, P=0.185; P for interaction=0.061).Adiponectin levelswereinverselyassociatedwithprogression ofmeancommon carotid IMTinmen(b=� 0.0022, P=0.047), whereas no association was seen in women (0.0007, P=0.475; P for interaction=0.018). Moreover, we observed that adiponectin levels were inversely associated with coronary events in women (hazard ratio 0.57, 95% CI 0.37 to 0.87) but not in men (hazardratio0.82,95%CI0.54to1.25).Agenescoreofadiponectin-raisingallelesin6loci,reportedrecentlyinalargemulti-ethnicmetaanalysis, was inversely associated with baseline mean bifurcationIMT in men (b=� 0.0008,P=0.004)butnot in women(b=� 0.0003, P=0.522; P for interaction=0.007). Conclusions-—This report provides some evidence for adiponectin protecting against atherosclerosis, with effects being confined to men; however, compared with established cardiovascular risk factors, the effect of plasma adiponectin was modest. Further investigation involving mechanistic studies is warranted. (J Am Heart Assoc. 2015;4:e001853 doi: 10.1161/JAHA.115.001853)
29 Jan 2015
TL;DR: The approach identifies novel coding variant associations and extends the allelic spectrum of variation underlying diabetes-related quantitative traits and T2D susceptibility.
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University of Texas Health Science Center at Houston1, University of St. Thomas (Texas)2, Boston University3, Tufts University4, National Institutes of Health5, Washington University in St. Louis6, Erasmus University Rotterdam7, University of Washington8, University of Helsinki9, Albert Einstein College of Medicine10, Lund University11, University of Virginia12, Queen Mary University of London13, Karolinska Institutet14, University of Turku15, University of North Carolina at Chapel Hill16, New York Academy of Medicine17, Wake Forest University18, Harvard University19, Harokopio University20, Beth Israel Deaconess Medical Center21, University of Minnesota22, Wellcome Trust Sanger Institute23, University of Tampere24, Brigham and Women's Hospital25, Turku University Hospital26, Helsinki University Central Hospital27, Science for Life Laboratory28, Icahn School of Medicine at Mount Sinai29, Umeå University30
TL;DR: Ass associations between genetic predisposition and obesity traits were stronger with a healthier diet, and diet score modification of genetic associations with BMI and BMI-adjusted WHR was identified.
Abstract: Obesity is highly heritable. Genetic variants showing robust associationswith obesity traits have been identified through genome wide association studies. We investigated whether a composite score ...
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TL;DR: Proteomic blood profiling indicated cathepsin D as a new IR biomarker and suggested a causal effect of IR on t-PA, which was associated with incident T2D and predicted 5-year transition to hyperglycemia.
Abstract: Insulin resistance (IR) is a precursor of type 2 diabetes (T2D), and improved risk prediction and understanding of the pathogenesis are needed. We used a novel high-throughput 92-protein assay to identify circulating biomarkers for HOMA of IR in two cohorts of community residents without diabetes (n = 1,367) (mean age 73 ± 3.6 years). Adjusted linear regression identified cathepsin D and confirmed six proteins (leptin, renin, interleukin-1 receptor antagonist [IL-1ra], hepatocyte growth factor, fatty acid-binding protein 4, and tissue plasminogen activator [t-PA]) as IR biomarkers. Mendelian randomization analysis indicated a positive causal effect of IR on t-PA concentrations. Two biomarkers, IL-1ra (hazard ratio [HR] 1.28, 95% CI 1.03-1.59) and t-PA (HR 1.30, 1.02-1.65) were associated with incident T2D, and t-PA predicted 5-year transition to hyperglycemia (odds ratio 1.30, 95% CI 1.02-1.65). Additional adjustment for fasting glucose rendered both coefficients insignificant and revealed an association between renin and T2D (HR 0.79, 0.62-0.99). LASSO regression suggested a risk model including IL-1ra, t-PA, and the Framingham Offspring Study T2D score, but prediction improvement was nonsignificant (difference in C-index 0.02, 95% CI -0.08 to 0.12) over the T2D score only. In conclusion, proteomic blood profiling indicated cathepsin D as a new IR biomarker and suggested a causal effect of IR on t-PA.
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Wellcome Trust Centre for Human Genetics1, University of Michigan2, University of Oxford3, Broad Institute4, University of Texas Health Science Center at Houston5, University of Copenhagen6, University of Chicago7, McGill University8, Harvard University9, Lund University10, King's College London11, Science for Life Laboratory12, Texas Biomedical Research Institute13, University of California, San Francisco14, University of Mississippi Medical Center15, University of Southern Denmark16, Ninewells Hospital17, Uppsala University18, Helsinki University Central Hospital19, Steno Diabetes Center20, Aalborg University21, University of Eastern Finland22, National Institutes of Health23, University of North Carolina at Chapel Hill24, Cedars-Sinai Medical Center25, King Abdulaziz University26, University of Southern California27, Boston University28, Massachusetts Institute of Technology29
TL;DR: In this article, the authors analyzed exome-array data from up to 33,231 non-diabetic individuals of European ancestry and identified multiple coding variants in G6PC2 (p.Val219Leu, p.His177Tyr, and p.Tyr207Ser) influencing FG levels, conditionally independent of each other and the non-coding GWAS signal.
Abstract: Genome wide association studies (GWAS) for fasting glucose (FG) and insulin (FI) have identified common variant signals which explain 4.8% and 1.2% of trait variance, respectively. It is hypothesized that low-frequency and rare variants could contribute substantially to unexplained genetic variance. To test this, we analyzed exome-array data from up to 33,231 non-diabetic individuals of European ancestry. We found exome-wide significant (P<5×10-7) evidence for two loci not previously highlighted by common variant GWAS: GLP1R (p.Ala316Thr, minor allele frequency (MAF)=1.5%) influencing FG levels, and URB2 (p.Glu594Val, MAF = 0.1%) influencing FI levels. Coding variant associations can highlight potential effector genes at (non-coding) GWAS signals. At the G6PC2/ABCB11 locus, we identified multiple coding variants in G6PC2 (p.Val219Leu, p.His177Tyr, and p.Tyr207Ser) influencing FG levels, conditionally independent of each other and the non-coding GWAS signal. In vitro assays demonstrate that these associated coding alleles result in reduced protein abundance via proteasomal degradation, establishing G6PC2 as an effector gene at this locus. Reconciliation of single-variant associations and functional effects was only possible when haplotype phase was considered. In contrast to earlier reports suggesting that, paradoxically, glucose-raising alleles at this locus are protective against type 2 diabetes (T2D), the p.Val219Leu G6PC2 variant displayed a modest but directionally consistent association with T2D risk. Coding variant associations for glycemic traits in GWAS signals highlight PCSK1, RREB1, and ZHX3 as likely effector transcripts. These coding variant association signals do not have a major impact on the trait variance explained, but they do provide valuable biological insights.
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Stanford University1, University of Exeter2, Icahn School of Medicine at Mount Sinai3, University of Eastern Finland4, Lund University5, Cedars-Sinai Medical Center6, University of Oxford7, University of California, Los Angeles8, Uppsala University9, Merck & Co.10, National Health Research Institutes11, Newcastle University12
TL;DR: A genome-wide association study for direct measures of insulin sensitivity and the presence of a nonsynonymous variant of N-acetyltransferase 2 (NAT2) was strongly associated with decreased insulin sensitivity that was independent of BMI, supporting a role for NAT2 in insulin sensitivity.
Abstract: Decreased insulin sensitivity, also referred to as insulin resistance (IR), is a fundamental abnormality in patients with type 2 diabetes and a risk factor for cardiovascular disease. While IR predisposition is heritable, the genetic basis remains largely unknown. The GENEticS of Insulin Sensitivity consortium conducted a genome-wide association study (GWAS) for direct measures of insulin sensitivity, such as euglycemic clamp or insulin suppression test, in 2,764 European individuals, with replication in an additional 2,860 individuals. The presence of a nonsynonymous variant of N-acetyltransferase 2 (NAT2) [rs1208 (803A>G, K268R)] was strongly associated with decreased insulin sensitivity that was independent of BMI. The rs1208 “A” allele was nominally associated with IR-related traits, including increased fasting glucose, hemoglobin A1C, total and LDL cholesterol, triglycerides, and coronary artery disease. NAT2 acetylates arylamine and hydrazine drugs and carcinogens, but predicted acetylator NAT2 phenotypes were not associated with insulin sensitivity. In a murine adipocyte cell line, silencing of NAT2 ortholog Nat1 decreased insulin-mediated glucose uptake, increased basal and isoproterenol-stimulated lipolysis, and decreased adipocyte differentiation, while Nat1 overexpression produced opposite effects. Nat1-deficient mice had elevations in fasting blood glucose, insulin, and triglycerides and decreased insulin sensitivity, as measured by glucose and insulin tolerance tests, with intermediate effects in Nat1 heterozygote mice. Our results support a role for NAT2 in insulin sensitivity.
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University of Oxford1, Wellcome Trust Centre for Human Genetics2, University of Tartu3, University of Helsinki4, National Institutes of Health5, University of Ferrara6, Amgen7, Karolinska Institutet8, Science for Life Laboratory9, VU University Amsterdam10, Lund University11, University of Regensburg12, Erasmus University Medical Center13, Leiden University Medical Center14, University of Leicester15, National Institute for Health Research16, University of Lübeck17, VU University Medical Center18, University of Tampere19, Turku University Hospital20, European Bioinformatics Institute21, Steno Diabetes Center22, University of Düsseldorf23, Ludwig Maximilian University of Munich24, University College London25, University of South Australia26, Technische Universität München27, Uppsala University Hospital28, Broad Institute29, University of Turku30, University of Iceland31, Imperial College London32
TL;DR: This study demonstrates that 1000G imputation and genetic fine-mapping of common and low-frequency variant association signals at GWAS loci, integrated with genomic annotation in relevant tissues, can provide insight into the functional and regulatory mechanisms through which their effects on glycaemic and obesity-related traits are mediated.
Abstract: Reference panels from the 1000 Genomes (1000G) Project Consortium provide near complete coverage of common and low-frequency genetic variation with minor allele frequency ≥0.5% across European ancestry populations. Within the European Network for Genetic and Genomic Epidemiology (ENGAGE) Consortium, we have undertaken the first large-scale meta-analysis of genome-wide association studies (GWAS), supplemented by 1000G imputation, for four quantitative glycaemic and obesity-related traits, in up to 87,048 individuals of European ancestry. We identified two loci for body mass index (BMI) at genome-wide significance, and two for fasting glucose (FG), none of which has been previously reported in larger meta-analysis efforts to combine GWAS of European ancestry. Through conditional analysis, we also detected multiple distinct signals of association mapping to established loci for waist-hip ratio adjusted for BMI (RSPO3) and FG (GCK and G6PC2). The index variant for one association signal at the G6PC2 locus is a low-frequency coding allele, H177Y, which has recently been demonstrated to have a functional role in glucose regulation. Fine-mapping analyses revealed that the non-coding variants most likely to drive association signals at established and novel loci were enriched for overlap with enhancer elements, which for FG mapped to promoter and transcription factor binding sites in pancreatic islets, in particular. Our study demonstrates that 1000G imputation and genetic fine-mapping of common and low-frequency variant association signals at GWAS loci, integrated with genomic annotation in relevant tissues, can provide insight into the functional and regulatory mechanisms through which their effects on glycaemic and obesity-related traits are mediated.