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Institution

Wellcome Trust Centre for Human Genetics

FacilityOxford, United Kingdom
About: Wellcome Trust Centre for Human Genetics is a facility organization based out in Oxford, United Kingdom. It is known for research contribution in the topics: Population & Genome-wide association study. The organization has 2122 authors who have published 4269 publications receiving 433899 citations.


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Journal ArticleDOI
TL;DR: It is shown that common genetic variation influences levels of clinically relevant proteins in human serum and plasma and the identification of protein quantitative trait loci (pQTLs) may be a powerful complementary method of improving the understanding of disease pathways.
Abstract: There is considerable evidence that human genetic variation influences gene expression. Genome-wide studies have revealed that mRNA levels are associated with genetic variation in or close to the gene coding for those mRNA transcripts – cis effects, and elsewhere in the genome – trans effects. The role of genetic variation in determining protein levels has not been systematically assessed. Using a genome-wide association approach we show that common genetic variation influences levels of clinically relevant proteins in human serum and plasma. We evaluated the role of 496,032 polymorphisms on levels of 42 proteins measured in 1200 fasting individuals from the population based InCHIANTI study. Proteins included insulin, several interleukins, adipokines, chemokines, and liver function markers that are implicated in many common diseases including metabolic, inflammatory, and infectious conditions. We identified eight Cis effects, including variants in or near the IL6R (p = 1.8×10−57), CCL4L1 (p = 3.9×10−21), IL18 (p = 6.8×10−13), LPA (p = 4.4×10−10), GGT1 (p = 1.5×10−7), SHBG (p = 3.1×10−7), CRP (p = 6.4×10−6) and IL1RN (p = 7.3×10−6) genes, all associated with their respective protein products with effect sizes ranging from 0.19 to 0.69 standard deviations per allele. Mechanisms implicated include altered rates of cleavage of bound to unbound soluble receptor (IL6R), altered secretion rates of different sized proteins (LPA), variation in gene copy number (CCL4L1) and altered transcription (GGT1). We identified one novel trans effect that was an association between ABO blood group and tumour necrosis factor alpha (TNF-alpha) levels (p = 6.8×10−40), but this finding was not present when TNF-alpha was measured using a different assay , or in a second study, suggesting an assay-specific association. Our results show that protein levels share some of the features of the genetics of gene expression. These include the presence of strong genetic effects in cis locations. The identification of protein quantitative trait loci (pQTLs) may be a powerful complementary method of improving our understanding of disease pathways.

446 citations

Journal ArticleDOI
TL;DR: Results of a nonsynonymous SNP scan for ulcerative colitis and a previously unknown susceptibility locus at ECM1 are reported, providing the first detailed illustration of the genetic relationship between these common inflammatory bowel diseases.
Abstract: We report results of a nonsynonymous SNP scan for ulcerative colitis and identify a previously unknown susceptibility locus at ECM1. We also show that several risk loci are common to ulcerative colitis and Crohn's disease (IL23R, IL12B, HLA, NKX2-3 and MST1), whereas autophagy genes ATG16L1 and IRGM, along with NOD2 (also known as CARD15), are specific for Crohn's disease. These data provide the first detailed illustration of the genetic relationship between these common inflammatory bowel diseases.

446 citations

Journal ArticleDOI
TL;DR: It is argued that the distribution of effect size of common variants is the same for all phenotypes regardless of species, and the importance of epistasis, pleiotropy, and gene by environment interactions is discussed.
Abstract: We compare and contrast the genetic architecture of quantitative phenotypes in two genetically well-characterized model organisms, the laboratory mouse, Mus musculus, and the fruit fly, Drosophila melanogaster, with that found in our own species from recent successes in genome-wide association studies. We show that the current model of large numbers of loci, each of small effect, is true for all species examined, and that discrepancies can be largely explained by differences in the experimental designs used. We argue that the distribution of effect size of common variants is the same for all phenotypes regardless of species, and we discuss the importance of epistasis, pleiotropy, and gene by environment interactions. Despite substantial advances in mapping quantitative trait loci, the identification of the quantitative trait genes and ultimately the sequence variants has proved more difficult, so that our information on the molecular basis of quantitative variation remains limited. Nevertheless, available data indicate that many variants lie outside genes, presumably in regulatory regions of the genome, where they act by altering gene expression. As yet there are very few instances where homologous quantitative trait loci, or quantitative trait genes, have been identified in multiple species, but the availability of high-resolution mapping data will soon make it possible to test the degree of overlap between species.

445 citations

Journal ArticleDOI
TL;DR: A genome-wide association analysis for commonly measured serum and urine biochemical traits found association between serum urate and SLC2A9, a glucose transporter, and provides a potential biological mechanism for the recent association of this same allele of the same SNP with increased risk of coronary disease.
Abstract: Many common diseases are accompanied by disturbances in biochemical traits. Identifying the genetic determinants could provide novel insights into disease mechanisms and reveal avenues for developing new therapies. Here, we report a genome-wide association analysis for commonly measured serum and urine biochemical traits. As part of the WTCCC, 500,000 SNPs genome wide were genotyped in 1955 hypertensive individuals characterized for 25 serum and urine biochemical traits. For each trait, we assessed association with individual SNPs, adjusting for age, sex, and BMI. Lipid measurements were further examined in a meta-analysis of genome-wide data from a type 2 diabetes scan. The most promising associations were examined in two epidemiological cohorts. We discovered association between serum urate and SLC2A9, a glucose transporter (p = 2 × 10−15) and confirmed this in two independent cohorts, GRAPHIC study (p = 9 × 10−15) and TwinsUK (p = 8 × 10−19). The odds ratio for hyperuricaemia (defined as urate >0.4 mMol/l) is 1.89 (95% CI = 1.36–2.61) per copy of common allele. We also replicated many genes previously associated with serum lipids and found previously recognized association between LDL levels and SNPs close to genes encoding PSRC1 and CELSR2 (p = 1 × 10−7). The common allele was associated with a 6% increase in nonfasting serum LDL. This region showed increased association in the meta-analysis (p = 4 × 10−14). This finding provides a potential biological mechanism for the recent association of this same allele of the same SNP with increased risk of coronary disease.

445 citations

Journal ArticleDOI
18 Jul 2013-Cell
TL;DR: A program, the Sanger Institute Mouse Genetics Project, that provides a step toward the aim of knocking out all genes and screening each line for a broad range of traits is described and it is found that hitherto unpublished genes were as likely to reveal phenotypes as known genes, suggesting that novel genes represent a rich resource for investigating the molecular basis of disease.

442 citations


Authors

Showing all 2127 results

NameH-indexPapersCitations
Mark I. McCarthy2001028187898
John P. A. Ioannidis1851311193612
Gonçalo R. Abecasis179595230323
Simon I. Hay165557153307
Robert Plomin151110488588
Ashok Kumar1515654164086
Julian Parkhill149759104736
James F. Wilson146677101883
Jeremy K. Nicholson14177380275
Hugh Watkins12852491317
Erik Ingelsson12453885407
Claudia Langenberg12445267326
Adrian V. S. Hill12258964613
John A. Todd12151567413
Elaine Holmes11956058975
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202221
202183
202074
2019134
2018182
2017323