Publications
368 results found
Zhang W, Jerneren F, Lehne BC, et al., 2016, Genome-wide association reveals that common genetic variation in the kallikrein-kinin system is associated with serum L-arginine levels, Thrombosis and Haemostasis, Vol: 116, Pages: 1041-1049, ISSN: 0340-6245
L-arginine is the essential precursor of nitric oxide, and is involved in multiple key physiological processes, including vascular and immune function. The genetic regulation of blood L-arginine levels is largely unknown. We performed a genome-wide association study (GWAS) to identify genetic factors determining serum L-arginine levels, amongst 901 Europeans and 1,394 Indian Asians. We show that common genetic variations at the KLKB1 and F12 loci are strongly associated with serum L-arginine levels. The G allele of single nucleotide polymorphism (SNP) rs71640036 (T/G) in KLKB1 is associated with lower serum L-arginine concentrations (10 µmol/l per allele copy, p=1×10–24), while allele T of rs2545801 (T/C) near the F12 gene is associated with lower serum L-arginine levels (7 µmol/l per allele copy, p=7×10–12). Together these two loci explain 7 % of the total variance in serum L-arginine concentrations. The associations at both loci were replicated in independent cohorts with plasma L-arginine measurements (p<0.004). The two sentinel SNPs are in nearly complete LD with the nonsynonymous SNP rs3733402 at KLKB1 and the 5’-UTR SNP rs1801020 at F12, respectively. SNPs at both loci are associated with blood pressure. Our findings provide new insight into the genetic regulation of L-arginine and its potential relationship with cardiovascular risk.
Surendran P, Drenos F, Young R, et al., 2016, Trans-ancestry meta-analyses identify rare and common variants associated with blood pressure and hypertension, Nature Genetics, Vol: 48, Pages: 1151-1161, ISSN: 1546-1718
High blood pressure is a major risk factor for cardiovascular disease and premature death. However, there is limited knowledge on specific causal genes and pathways. To better understand the genetics of blood pressure, we genotyped 242,296 rare, low-frequency and common genetic variants in up to ~192,000 individuals, and used ~155,063 samples for independent replication. We identified 31 novel blood pressure or hypertension associated genetic regions in the general population, including three rare missense variants in RBM47, COL21A1 and RRAS with larger effects (>1.5mmHg/allele) than common variants. Multiple rare, nonsense and missense variant associations were found in A2ML1 and a low-frequency nonsense variant in ENPEP was identified. Our data extend the spectrum of allelic variation underlying blood pressure traits and hypertension, provide new insights into the pathophysiology of hypertension and indicate new targets for clinical intervention.
Ehret GB, Ferreira T, Chasman DI, et al., 2016, The genetics of blood pressure regulation and its target organs from association studies in 342,415 individuals, Nature Genetics, Vol: 48, Pages: 1171-1184, ISSN: 1546-1718
To dissect the genetic architecture of blood pressure and assess effects on target organ damage, we analyzed 128,272 SNPs from targeted and genome-wide arrays in 201,529 individuals of European ancestry, and genotypes from an additional 140,886 individuals were used for validation. We identified 66 blood pressure-associated loci, of which 17 were new; 15 harbored multiple distinct association signals. The 66 index SNPs were enriched for cis-regulatory elements, particularly in vascular endothelial cells, consistent with a primary role in blood pressure control through modulation of vascular tone across multiple tissues. The 66 index SNPs combined in a risk score showed comparable effects in 64,421 individuals of non-European descent. The 66-SNP blood pressure risk score was significantly associated with target organ damage in multiple tissues but with minor effects in the kidney. Our findings expand current knowledge of blood pressure-related pathways and highlight tissues beyond the classical renal system in blood pressure regulation.
Lek M, Karczewski KJ, Minikel EV, et al., 2016, Analysis of protein-coding genetic variation in 60,706 humans, Nature, Vol: 536, Pages: 285-291, ISSN: 0028-0836
Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of predicted protein-truncating variants, with 72% of these genes having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human 'knockout' variants in protein-coding genes.
Kanoni S, Masca NG, Stirrups KE, et al., 2016, Analysis with the exome array identifies multiple new independent variants in lipid loci., Human Molecular Genetics, Vol: 25, Pages: 4094-4106, ISSN: 1460-2083
It has been hypothesized that low frequency (1-5% minor allele frequency (MAF)) and rare (<1% MAF) variants with large effect sizes may contribute to the missing heritability in complex traits. Here, we report an association analysis of lipid traits (total cholesterol, LDL-cholesterol, HDL-cholesterol triglycerides) in up to 27 312 individuals with a comprehensive set of low frequency coding variants (ExomeChip), combined with conditional analysis in the known lipid loci. No new locus reached genome-wide significance. However, we found a new lead variant in 26 known lipid association regions of which 16 were >1000-fold more significant than the previous sentinel variant and not in close LD (six had MAF <5%). Furthermore, conditional analysis revealed multiple independent signals (ranging from 1 to 5) in a third of the 98 lipid loci tested, including rare variants. Addition of our novel associations resulted in between 1.5- and 2.5-fold increase in the proportion of heritability explained for the different lipid traits. Our findings suggest that rare coding variants contribute to the genetic architecture of lipid traits.
Fuchsberger C, Flannick J, Teslovich TM, et al., 2016, The genetic architecture of type 2 diabetes., Nature, Vol: 536, Pages: 41-47, ISSN: 0028-0836
The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of the heritability of this disease. Here, to test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole-genome sequencing in 2,657 European individuals with and without diabetes, and exome sequencing in 12,940 individuals from five ancestry groups. To increase statistical power, we expanded the sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes.
Winkler TW, Justice AE, Graff M, et al., 2016, Correction: The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study, PLOS Genetics, Vol: 12, Pages: e1006166-e1006166, ISSN: 1553-7390
Alkaf B, Lehne B, Kooner JS, et al., 2016, Contribution of Adiposity to the Increased Risk of T2D in the UAE, 76th Scientific Sessions of the American-Diabetes-Association, Publisher: AMER DIABETES ASSOC, Pages: A404-A404, ISSN: 0012-1797
Scott WR, Zhang W, Loh M, et al., 2016, Investigation of Genetic Variation Underlying Central Obesity amongst South Asians, PLOS One, Vol: 11, ISSN: 1932-6203
ArticleAuthorsMetricsCommentsRelated ContentAbstractIntroductionMaterials and MethodsResultsDiscussion and ConclusionSupporting InformationAcknowledgmentsAuthor ContributionsReferencesReader Comments (0)Media Coverage (0)FiguresAbstractSouth Asians are 1/4 of the world’s population and have increased susceptibility to central obesity and related cardiometabolic disease. Knowledge of genetic variants affecting risk of central obesity is largely based on genome-wide association studies of common SNPs in Europeans. To evaluate the contribution of DNA sequence variation to the higher levels of central obesity (defined as waist hip ratio adjusted for body mass index, WHR) among South Asians compared to Europeans we carried out: i) a genome-wide association analysis of >6M genetic variants in 10,318 South Asians with focused analysis of population-specific SNPs; ii) an exome-wide association analysis of ~250K SNPs in protein-coding regions in 2,637 South Asians; iii) a comparison of risk allele frequencies and effect sizes of 48 known WHR SNPs in 12,240 South Asians compared to Europeans. In genome-wide analyses, we found no novel associations between common genetic variants and WHR in South Asians at P<5x10-8; variants showing equivocal association with WHR (P<1x10-5) did not replicate at P<0.05 in an independent cohort of South Asians (N = 1,922) or in published, predominantly European meta-analysis data. In the targeted analyses of 122,391 population-specific SNPs we also found no associations with WHR in South Asians at P<0.05 after multiple testing correction. Exome-wide analyses showed no new associations between genetic variants and WHR in South Asians, either individually at P<1.5x10-6 or grouped by gene locus at P<2.5x10−6. At known WHR loci, risk allele frequencies were not higher in South Asians compared to Europeans (P = 0.77), while effect sizes were unexpectedly smaller in South Asians than Europeans (P<5.0x10-8). Our find
Lehne B, Drong AW, Loh M, et al., 2016, Erratum to: A coherent approach for analysis of the Illumina HumanMethylation450 BeadChip improves data quality and performance in epigenome-wide association studies., Genome Biology, Vol: 17, ISSN: 1474-760X
van Leeuwen EM, Sabo A, Bis JC, et al., 2016, Meta-analysis of 49 549 individuals imputed with the 1000 Genomes Project reveals an exonic damaging variant in ANGPTL4 determining fasting TG levels, Journal of Medical Genetics, Vol: 53, Pages: 441-449, ISSN: 1468-6244
BACKGROUND: So far, more than 170 loci have been associated with circulating lipid levels through genome-wide association studies (GWAS). These associations are largely driven by common variants, their function is often not known, and many are likely to be markers for the causal variants. In this study we aimed to identify more new rare and low-frequency functional variants associated with circulating lipid levels. METHODS: We used the 1000 Genomes Project as a reference panel for the imputations of GWAS data from ∼60 000 individuals in the discovery stage and ∼90 000 samples in the replication stage. RESULTS: Our study resulted in the identification of five new associations with circulating lipid levels at four loci. All four loci are within genes that can be linked biologically to lipid metabolism. One of the variants, rs116843064, is a damaging missense variant within the ANGPTL4 gene. CONCLUSIONS: This study illustrates that GWAS with high-scale imputation may still help us unravel the biological mechanism behind circulating lipid levels.
Horikoshi M, Pasquali L, Wiltshire S, et al., 2016, Transancestral fine-mapping of four type 2 diabetes susceptibility loci highlights potential causal regulatory mechanisms, Human Molecular Genetics, Vol: 25, Pages: 2070-2081, ISSN: 1460-2083
To gain insight into potential regulatory mechanisms through which the effects of variants at four established type 2 diabetes (T2D) susceptibility loci (CDKAL1, CDKN2A-B, IGF2BP2 and KCNQ1) are mediated, we undertook transancestral fine-mapping in 22 086 cases and 42 539 controls of East Asian, European, South Asian, African American and Mexican American descent. Through high-density imputation and conditional analyses, we identified seven distinct association signals at these four loci, each with allelic effects on T2D susceptibility that were homogenous across ancestry groups. By leveraging differences in the structure of linkage disequilibrium between diverse populations, and increased sample size, we localised the variants most likely to drive each distinct association signal. We demonstrated that integration of these genetic fine-mapping data with genomic annotation can highlight potential causal regulatory elements in T2D-relevant tissues. These analyses provide insight into the mechanisms through which T2D association signals are mediated, and suggest future routes to understanding the biology of specific disease susceptibility loci.
Keenan T, Zhao W, Rasheed A, et al., 2016, Causal Assessment of Serum Urate Levels in Cardiometabolic Diseases Through a Mendelian Randomization Study, JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY, Vol: 67, Pages: 407-416, ISSN: 0735-1097
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- Citations: 121
Lu Y, Day FR, Gustafsson S, et al., 2016, New loci for body fat percentage reveal link between adiposity and cardiometabolic disease risk, NATURE COMMUNICATIONS, Vol: 7, ISSN: 2041-1723
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- Citations: 199
Pattaro C, Teumer A, Gorski M, et al., 2016, Genetic associations at 53 loci highlight cell types and biological pathways relevant for kidney function., Nat Commun, Vol: 7
Reduced glomerular filtration rate defines chronic kidney disease and is associated with cardiovascular and all-cause mortality. We conducted a meta-analysis of genome-wide association studies for estimated glomerular filtration rate (eGFR), combining data across 133,413 individuals with replication in up to 42,166 individuals. We identify 24 new and confirm 29 previously identified loci. Of these 53 loci, 19 associate with eGFR among individuals with diabetes. Using bioinformatics, we show that identified genes at eGFR loci are enriched for expression in kidney tissues and in pathways relevant for kidney development and transmembrane transporter activity, kidney structure, and regulation of glucose metabolism. Chromatin state mapping and DNase I hypersensitivity analyses across adult tissues demonstrate preferential mapping of associated variants to regulatory regions in kidney but not extra-renal tissues. These findings suggest that genetic determinants of eGFR are mediated largely through direct effects within the kidney and highlight important cell types and biological pathways.
Kim YJ, Lee J, Kim B-J, et al., 2015, A new strategy for enhancing imputation quality of rare variants from next-generation sequencing data via combining SNP and exome chip data, BMC Genomics, Vol: 16, ISSN: 1471-2164
BackgroundRare variants have gathered increasing attention as a possible alternative source of missing heritability. Since next generation sequencing technology is not yet cost-effective for large-scale genomic studies, a widely used alternative approach is imputation. However, the imputation approach may be limited by the low accuracy of the imputed rare variants. To improve imputation accuracy of rare variants, various approaches have been suggested, including increasing the sample size of the reference panel, using sequencing data from study-specific samples (i.e., specific populations), and using local reference panels by genotyping or sequencing a subset of study samples. While these approaches mainly utilize reference panels, imputation accuracy of rare variants can also be increased by using exome chips containing rare variants. The exome chip contains 250 K rare variants selected from the discovered variants of about 12,000 sequenced samples. If exome chip data are available for previously genotyped samples, the combined approach using a genotype panel of merged data, including exome chips and SNP chips, should increase the imputation accuracy of rare variants.ResultsIn this study, we describe a combined imputation which uses both exome chip and SNP chip data simultaneously as a genotype panel. The effectiveness and performance of the combined approach was demonstrated using a reference panel of 848 samples constructed using exome sequencing data from the T2D-GENES consortium and 5,349 sample genotype panels consisting of an exome chip and SNP chip. As a result, the combined approach increased imputation quality up to 11 %, and genomic coverage for rare variants up to 117.7 % (MAF < 1 %), compared to imputation using the SNP chip alone. Also, we investigated the systematic effect of reference panels on imputation quality using five reference panels and three genotype panels. The best performing approach was the combination of the study speci
Kato N, Loh M, Takeuchi F, et al., 2015, Trans-ancestry genome-wide association study identifies 12 genetic loci influencing blood pressure and implicates a role for DNA methylation, Nature Genetics, Vol: 47, Pages: 1282-1293, ISSN: 1546-1718
We carried out a trans-ancestry genome-wide association and replication study of blood pressure phenotypes among up to 320,251 individuals of East Asian, European and South Asian ancestry. We find genetic variants at 12 new loci to be associated with blood pressure (P = 3.9 × 10−11 to 5.0 × 10−21). The sentinel blood pressure SNPs are enriched for association with DNA methylation at multiple nearby CpG sites, suggesting that, at some of the loci identified, DNA methylation may lie on the regulatory pathway linking sequence variation to blood pressure. The sentinel SNPs at the 12 new loci point to genes involved in vascular smooth muscle (IGFBP3, KCNK3, PDE3A and PRDM6) and renal (ARHGAP24, OSR1, SLC22A7 and TBX2) function. The new and known genetic variants predict increased left ventricular mass, circulating levels of NT-proBNP, and cardiovascular and all-cause mortality (P = 0.04 to 8.6 × 10−6). Our results provide new evidence for the role of DNA methylation in blood pressure regulation.
He L, Tuomilehto J, Qiao Q, et al., 2015, Impact of classical risk factors of type 2 diabetes among Asian Indian, Chinese and Japanese populations., Diabetes Metab, Vol: 41, Pages: 401-409
AIMS: This review investigated the population impact of major modifiable type 2 diabetes (T2D) risk factors, with special focus on native Asian Indians, to estimate population attributable risks (PARs) and compare them with estimates from Chinese and Japanese populations. METHODS: Information was obtained on risk factors in 21,041 Asian Indian, 17,774 Chinese and 17,986 Japanese populations from multiple, large, cross-sectional studies (the DECODA project) of T2D. Crude and adjusted PARs were estimated for the major T2D risk factors. RESULTS: Age had the highest crude and adjusted PARs among Asian Indians and Chinese in contrast to waist-hip ratio among Japanese. After adjusting for age, the PAR for body mass index (BMI) in Asian Indians (41.4% [95% CI: 37.2%; 45.4%]) was second only to triglycerides (46.4% [95% CI: 39.5%; 52.8%]) compared with 35.8% [95% CI: 29.9%; 41.4%] in Japanese and 38.4% [95% CI: 33.5%; 43.2%] in Chinese people. The PAR for BMI adjusted for age, LDL and triglycerides (39.7% [95% CI: 31.6%; 47.2%]) was higher than for any other factor in Asian Indians, and was much higher than in the Chinese (16.8% [95% CI: 3.0%; 30.9%]) and Japanese (30.4% [95% CI: 17.5%; 42.2%]) populations. CONCLUSION: This review provides estimates of the association between major risk factors and prevalences of T2D among Asian populations by examining their PARs from large population-based samples. From a public-health point of view, the importance of BMI in Asian Indians is especially highlighted in comparison to the other Asian populations. Given these results and other recent findings on the causality link between BMI and T2D, it can be postulated that obesity may be involved in the aetiology of T2D through interaction with ethnic-specific genetic factors, although ethnicity itself is not a direct risk factor for T2D as people of all ethnic backgrounds develop diabetes.
Winkler TW, Justice AE, Graff M, et al., 2015, The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study, PLOS GENETICS, Vol: 11, ISSN: 1553-7404
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- Citations: 249
Wain LV, Shrine N, Miller S, et al., 2015, Novel insights into the genetics of smoking behaviour, lung function, and chronic obstructive pulmonary disease (UK BiLEVE): a genetic association study in UK Biobank, Lancet Respiratory Medicine, Vol: 3, Pages: 769-781, ISSN: 2213-2619
BackgroundUnderstanding the genetic basis of airflow obstruction and smoking behaviour is key to determining the pathophysiology of chronic obstructive pulmonary disease (COPD). We used UK Biobank data to study the genetic causes of smoking behaviour and lung health.MethodsWe sampled individuals of European ancestry from UK Biobank, from the middle and extremes of the forced expiratory volume in 1 s (FEV1) distribution among heavy smokers (mean 35 pack-years) and never smokers. We developed a custom array for UK Biobank to provide optimum genome-wide coverage of common and low-frequency variants, dense coverage of genomic regions already implicated in lung health and disease, and to assay rare coding variants relevant to the UK population. We investigated whether there were shared genetic causes between different phenotypes defined by extremes of FEV1. We also looked for novel variants associated with extremes of FEV1 and smoking behaviour and assessed regions of the genome that had already shown evidence for a role in lung health and disease. We set genome-wide significance at p<5 × 10−8.FindingsUK Biobank participants were recruited from March 15, 2006, to July 7, 2010. Sample selection for the UK BiLEVE study started on Nov 22, 2012, and was completed on Dec 20, 2012. We selected 50 008 unique samples: 10 002 individuals with low FEV1, 10 000 with average FEV1, and 5002 with high FEV1 from each of the heavy smoker and never smoker groups. We noted a substantial sharing of genetic causes of low FEV1 between heavy smokers and never smokers (p=2·29 × 10−16) and between individuals with and without doctor-diagnosed asthma (p=6·06 × 10−11). We discovered six novel genome-wide significant signals of association with extremes of FEV1, including signals at four novel loci (KANSL1, TSEN54, TET2, and RBM19/TBX5) and independent signals at two previously reported loci (NPNT and HLA-DQB1/HLA-DQA2). These variants also show
Huang J, Howie B, McCarthy S, et al., 2015, Improved imputation of low-frequency and rare variants using the UK10K haplotype reference panel., Nat Commun, Vol: 6
Imputing genotypes from reference panels created by whole-genome sequencing (WGS) provides a cost-effective strategy for augmenting the single-nucleotide polymorphism (SNP) content of genome-wide arrays. The UK10K Cohorts project has generated a data set of 3,781 whole genomes sequenced at low depth (average 7x), aiming to exhaustively characterize genetic variation down to 0.1% minor allele frequency in the British population. Here we demonstrate the value of this resource for improving imputation accuracy at rare and low-frequency variants in both a UK and an Italian population. We show that large increases in imputation accuracy can be achieved by re-phasing WGS reference panels after initial genotype calling. We also present a method for combining WGS panels to improve variant coverage and downstream imputation accuracy, which we illustrate by integrating 7,562 WGS haplotypes from the UK10K project with 2,184 haplotypes from the 1000 Genomes Project. Finally, we introduce a novel approximation that maintains speed without sacrificing imputation accuracy for rare variants.
Walter K, Min JL, Huang J, et al., 2015, The UK10K project identifies rare variants in health and disease, Nature, Vol: 526, Pages: 82-90, ISSN: 0028-0836
The contribution of rare and low-frequency variants to human traits is largely unexplored. Here we describe insights from sequencing whole genomes (low read depth, 7×) or exomes (high read depth, 80×) of nearly 10,000 individuals from population-based and disease collections. In extensively phenotyped cohorts we characterize over 24 million novel sequence variants, generate a highly accurate imputation reference panel and identify novel alleles associated with levels of triglycerides (APOB), adiponectin (ADIPOQ) and low-density lipoprotein cholesterol (LDLR and RGAG1) from single-marker and rare variant aggregation tests. We describe population structure and functional annotation of rare and low-frequency variants, use the data to estimate the benefits of sequencing for association studies, and summarize lessons from disease-specific collections. Finally, we make available an extensive resource, including individual-level genetic and phenotypic data and web-based tools to facilitate the exploration of association results.
Nikpay M, Goel A, Won H-H, et al., 2015, A comprehensive 1000 Genomes-based genome-wide association meta-analysis of coronary artery disease, Nature Genetics, Vol: 47, Pages: 1121-1130, ISSN: 1061-4036
Existing knowledge of genetic variants affecting risk of coronary artery disease (CAD) is largelybased on genome-wide association studies (GWAS) analysis of common SNPs. Leveragingphased haplotypes from the 1000 Genomes Project, we report a GWAS meta-analysis of 185thousand CAD cases and controls, interrogating 6.7 million common (MAF>0.05) as well as 2.7million low frequency (0.005<MAF<0.05) variants. In addition to confirmation of most knownCAD loci, we identified 10 novel loci, eight additive and two recessive, that contain candidategenes that newly implicate biological processes in vessel walls. We observed intra-locus allelicheterogeneity but little evidence of low frequency variants with larger effects and no evidence ofsynthetic association. Our analysis provides a comprehensive survey of the fine geneticarchitecture of CAD showing that genetic susceptibility to this common disease is largelydetermined by common SNPs of small effect size
Joshi PK, Esko T, Mattsson H, et al., 2015, Directional dominance on stature and cognition in diverse human populations, Nature, Vol: 523, Pages: 459-462, ISSN: 0028-0836
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 cognit
Chambers JC, Loh M, Lehne B, et al., 2015, Epigenome-wide association of DNA methylation markers in peripheral blood from Indian Asians and Europeans with incident type 2 diabetes: a nested case-control study, The Lancet Diabetes & Endocrinology, Vol: 3, Pages: 526-534, ISSN: 2213-8587
BackgroundIndian Asians, who make up a quarter of the world's population, are at high risk of developing type 2 diabetes. We investigated whether DNA methylation is associated with future type 2 diabetes incidence in Indian Asians and whether differences in methylation patterns between Indian Asians and Europeans are associated with, and could be used to predict, differences in the magnitude of risk of developing type 2 diabetes.MethodsWe did a nested case-control study of DNA methylation in Indian Asians and Europeans with incident type 2 diabetes who were identified from the 8-year follow-up of 25 372 participants in the London Life Sciences Prospective Population (LOLIPOP) study. Patients were recruited between May 1, 2002, and Sept 12, 2008. We did epigenome-wide association analysis using samples from Indian Asians with incident type 2 diabetes and age-matched and sex-matched Indian Asian controls, followed by replication testing of top-ranking signals in Europeans. For both discovery and replication, DNA methylation was measured in the baseline blood sample, which was collected before the onset of type 2 diabetes. Epigenome-wide significance was set at p<1 × 10−7. We compared methylation levels between Indian Asian and European controls without type 2 diabetes at baseline to estimate the potential contribution of DNA methylation to increased risk of future type 2 diabetes incidence among Indian Asians.Findings1608 (11·9%) of 13 535 Indian Asians and 306 (4·3%) of 7066 Europeans developed type 2 diabetes over a mean of 8·5 years (SD 1·8) of follow-up. The age-adjusted and sex-adjusted incidence of type 2 diabetes was 3·1 times (95% CI 2·8–3·6; p<0·0001) higher among Indian Asians than among Europeans, and remained 2·5 times (2·1–2·9; p<0·0001) higher after adjustment for adiposity, physical activity, family history of type 2 diabetes, and baselin
Echocardiographic Normal Ranges Meta-Analysis of the Left Heart Collaboration, 2015, Ethnic-Specific Normative Reference Values for Echocardiographic LA and LV Size, LV Mass, and Systolic Function: The EchoNoRMAL Study., JACC Cardiovasc Imaging, Vol: 8, Pages: 656-665
OBJECTIVES: This study sought to derive age-, sex-, and ethnic-appropriate adult reference values for left atrial (LA) and left ventricular (LV) dimensions and volumes, LV mass, fractional shortening, and ejection fraction (EF) derived from geographically diverse population studies. BACKGROUND: The current recommended reference values for measurements from echocardiography may not be suitable to the diverse world population to which they are now applied. METHODS: Population-based datasets of echocardiographic measurements from 22,404 adults without clinical cardiovascular or renal disease, hypertension, or diabetes were combined in an individual person data meta-analysis. Quantile regression was used to derive reference values at the 95th percentile (upper reference value [URV]) and fifth percentile (lower reference value [LRV]) of each measurement against age (treated as linear), separately within sex and ethnic groups. RESULTS: The URVs for left ventricular end-diastolic volume (LVEDV), LV end-systolic volume, and LV stroke volume (SV) were highest in Europeans and lowest in South Asians. Important sex and ethnic differences remained after indexation by body surface area or height for these measurements, as well as for the LRV for SV. LVEDV and SV decreased with increasing age for all groups. Importantly, the LRV for EF differed by ethnicity; there was a clear apparent difference between Europeans and Asians. The URVs for LV end-diastolic diameter and LV end-systolic diameter were higher for Europeans than those for East Asian, South Asian, and African people, particularly among men. Similarly, the URVs for LA diameter and volume were highest for Europeans. CONCLUSIONS: Sex- and/or ethnic-appropriate echocardiographic reference values are indicated for many measurements of LA and LV size, LV mass, and EF. Reference values for LV volumes and mass also differ across the age range.
Freitag DF, Butterworth AS, Willeit P, et al., 2015, Cardiometabolic effects of genetic upregulation of the interleukin 1 receptor antagonist: a Mendelian randomisation analysis, LANCET DIABETES & ENDOCRINOLOGY, Vol: 3, Pages: 243-253, ISSN: 2213-8587
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Huan T, Esko T, Peters MJ, et al., 2015, A meta-analysis of gene expression signatures of blood pressure and hypertension, PLoS Genetics, Vol: 11, ISSN: 1553-7390
Genome-wide association studies (GWAS) have uncovered numerous genetic variants (SNPs) that are associated with blood pressure (BP). Genetic variants may lead to BP changes by acting on intermediate molecular phenotypes such as coded protein sequence or gene expression, which in turn affect BP variability. Therefore, characterizing genes whose expression is associated with BP may reveal cellular processes involved in BP regulation and uncover how transcripts mediate genetic and environmental effects on BP variability. A meta-analysis of results from six studies of global gene expression profiles of BP and hypertension in whole blood was performed in 7017 individuals who were not receiving antihypertensive drug treatment. We identified 34 genes that were differentially expressed in relation to BP (Bonferroni-corrected p<0.05). Among these genes, FOS and PTGS2 have been previously reported to be involved in BP-related processes; the others are novel. The top BP signature genes in aggregate explain 5%–9% of inter-individual variance in BP. Of note, rs3184504 in SH2B3, which was also reported in GWAS to be associated with BP, was found to be a trans regulator of the expression of 6 of the transcripts we found to be associated with BP (FOS, MYADM, PP1R15A, TAGAP, S100A10, and FGBP2). Gene set enrichment analysis suggested that the BP-related global gene expression changes include genes involved in inflammatory response and apoptosis pathways. Our study provides new insights into molecular mechanisms underlying BP regulation, and suggests novel transcriptomic markers for the treatment and prevention of hypertension.
Lehne B, Drong AW, Loh M, et al., 2015, A coherent approach for analysis of the Illumina HumanMethylation450 BeadChip improves data quality and performance in epigenome-wide association studies, Genome Biology, Vol: 16, ISSN: 1474-760X
DNA methylation plays a fundamental role in the regulation of the genome, but the optimal strategy for analysis ofgenome-wide DNA methylation data remains to be determined. We developed a comprehensive analysis pipelinefor epigenome-wide association studies (EWAS) using the Illumina Infinium HumanMethylation450 BeadChip, basedon 2,687 individuals, with 36 samples measured in duplicate. We propose new approaches to quality control, datanormalisation and batch correction through control-probe adjustment and establish a null hypothesis for EWASusing permutation testing. Our analysis pipeline outperforms existing approaches, enabling accurate identificationof methylation quantitative trait loci for hypothesis driven follow-up experiments.
Shungin D, Winkler TW, Croteau-Chonka DC, et al., 2015, New genetic loci link adipose and insulin biology to body fat distribution, NATURE, Vol: 518, Pages: 187-U378, ISSN: 0028-0836
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