Author
Michael E. Weale
Other affiliations: Guy's Hospital, University of Southampton, Guy's and St Thomas' NHS Foundation Trust ...read more
Bio: Michael E. Weale is an academic researcher from King's College London. The author has contributed to research in topics: Genome-wide association study & Population. The author has an hindex of 64, co-authored 153 publications receiving 17824 citations. Previous affiliations of Michael E. Weale include Guy's Hospital & University of Southampton.
Papers published on a yearly basis
Papers
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Duke University1, University of Lausanne2, University of Zurich3, Vita-Salute San Raffaele University4, University of Modena and Reggio Emilia5, University College London6, Catholic University of the Sacred Heart7, King's College London8, Murdoch University9, University of Barcelona10, University of Copenhagen11, University of Geneva12, Harvard University13, John Radcliffe Hospital14
TL;DR: Using a whole-genome association strategy, polymorphisms that explain nearly 15% of the variation among individuals in viral load during the asymptomatic set-point period of infection are identified.
Abstract: Understanding why some people establish and maintain effective control of HIV-1 and others do not is a priority in the effort to develop new treatments for HIV/AIDS. Using a whole-genome association strategy, we identified polymorphisms that explain nearly 15% of the variation among individuals in viral load during the asymptomatic set-point period of infection. One of these is found within an endogenous retroviral element and is associated with major histocompatibility allele human leukocyte antigen (HLA)-B*5701, whereas a second is located near the HLA-C gene. An additional analysis of the time to HIV disease progression implicated two genes, one of which encodes an RNA polymerase I subunit. These findings emphasize the importance of studying human genetic variation as a guide to combating infectious agents.
1,230 citations
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University of Oxford1, King's College London2, University of Manchester3, Radboud University Nijmegen4, Wellcome Trust Sanger Institute5, University of London6, University of Sheffield7, Trinity College, Dublin8, Wellcome Trust9, Medical University of Graz10, University of Erlangen-Nuremberg11, Queen Mary University of London12, Western Infirmary13, Karolinska Institutet14, St George's, University of London15, University of Dundee16, University of Göttingen17, University of Gothenburg18, Sapienza University of Rome19, University of Cambridge20, University of Münster21, Moorfields Eye Hospital22, University College London23, University of Bristol24
TL;DR: These findings implicate pathways that integrate epidermal barrier dysfunction with innate and adaptive immune dysregulation in psoriasis pathogenesis and report compelling evidence for an interaction between the HLA-C and ERAP1 loci.
Abstract: To identify new susceptibility loci for psoriasis, we undertook a genome-wide association study of 594,224 SNPs in 2,622 individuals with psoriasis and 5,667 controls. We identified associations at eight previously unreported genomic loci. Seven loci harbored genes with recognized immune functions (IL28RA, REL, IFIH1, ERAP1, TRAF3IP2, NFKBIA and TYK2). These associations were replicated in 9,079 European samples (six loci with a combined P < 5 × 10⁻⁸ and two loci with a combined P < 5 × 10⁻⁷). We also report compelling evidence for an interaction between the HLA-C and ERAP1 loci (combined P = 6.95 × 10⁻⁶). ERAP1 plays an important role in MHC class I peptide processing. ERAP1 variants only influenced psoriasis susceptibility in individuals carrying the HLA-C risk allele. Our findings implicate pathways that integrate epidermal barrier dysfunction with innate and adaptive immune dysregulation in psoriasis pathogenesis.
919 citations
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TL;DR: A meta-analysis of genome-wide association studies and independent data sets genotyped on the Immunochip identified 15 new susceptibility loci, increasing to 36 the number associated with psoriasis in European individuals, and identified five independent signals within previously known loci.
Abstract: To gain further insight into the genetic architecture of psoriasis, we conducted a meta-analysis of 3 genome-wide association studies (GWAS) and 2 independent data sets genotyped on the Immunochip, including 10,588 cases and 22,806 controls. We identified 15 new susceptibility loci, increasing to 36 the number associated with psoriasis in European individuals. We also identified, using conditional analyses, five independent signals within previously known loci. The newly identified loci shared with other autoimmune diseases include candidate genes with roles in regulating T-cell function (such as RUNX3, TAGAP and STAT3). Notably, they included candidate genes whose products are involved in innate host defense, including interferon-mediated antiviral responses (DDX58), macrophage activation (ZC3H12C) and nuclear factor (NF)-κB signaling (CARD14 and CARM1). These results portend a better understanding of shared and distinctive genetic determinants of immune-mediated inflammatory disorders and emphasize the importance of the skin in innate and acquired host defense.
786 citations
17 Oct 2010
TL;DR: In this article, a genome-wide asociation study of 594,224 SNPs in 2,622 individuals with psoriasis and 5,667 controls was conducted.
Abstract: To identify new susceptibility loci for psoriasis, we undertOk a genome-wide asociation study of 594,224 SNPs in 2,622 individuals with psoriasis and 5,667 controls. We identified asociations at eight previously unreported genomic loci. Seven loci harbored genes with recognized iMune functions (IL28RA, REL, IFIH1, ERAP1, TRAF3IP2, NFKBIA and TYK2). These asociations were replicated in 9,079 European samples (six loci with a combined P < 5-10 -8 and two loci with a combined P < 5-10-7). We also report compeLing evidence for an interaction betwEn the HLA-C and ERAP1 loci (combined P = 6.95-10-6). ERAP1 plays an important role in MHC claS I peptide proceSing. ERAP1 variants only influenced psoriasis susceptibility in individuals carrying the HLA-C risk aLele. Our findings implicate pathways that integrate epidermal barrier dysfunction with iNate and adaptive iMune dysregulation in psoriasis pathogenesis.
773 citations
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TL;DR: In this paper, the authors conduct genome-wide association studies of the volumes of seven subcortical regions and the intracranial volume derived from magnetic resonance images of 30,717 individuals from 50 cohorts.
Abstract: The highly complex structure of the human brain is strongly shaped by genetic influences. Subcortical brain regions form circuits with cortical areas to coordinate movement, learning, memory and motivation, and altered circuits can lead to abnormal behaviour and disease. To investigate how common genetic variants affect the structure of these brain regions, here we conduct genome-wide association studies of the volumes of seven subcortical regions and the intracranial volume derived from magnetic resonance images of 30,717 individuals from 50 cohorts. We identify five novel genetic variants influencing the volumes of the putamen and caudate nucleus. We also find stronger evidence for three loci with previously established influences on hippocampal volume and intracranial volume. These variants show specific volumetric effects on brain structures rather than global effects across structures. The strongest effects were found for the putamen, where a novel intergenic locus with replicable influence on volume (rs945270; P = 1.08 × 10(-33); 0.52% variance explained) showed evidence of altering the expression of the KTN1 gene in both brain and blood tissue. Variants influencing putamen volume clustered near developmental genes that regulate apoptosis, axon guidance and vesicle transport. Identification of these genetic variants provides insight into the causes of variability in human brain development, and may help to determine mechanisms of neuropsychiatric dysfunction.
721 citations
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TL;DR: BEAST is a fast, flexible software architecture for Bayesian analysis of molecular sequences related by an evolutionary tree that provides models for DNA and protein sequence evolution, highly parametric coalescent analysis, relaxed clock phylogenetics, non-contemporaneous sequence data, statistical alignment and a wide range of options for prior distributions.
Abstract: The evolutionary analysis of molecular sequence variation is a statistical enterprise. This is reflected in the increased use of probabilistic models for phylogenetic inference, multiple sequence alignment, and molecular population genetics. Here we present BEAST: a fast, flexible software architecture for Bayesian analysis of molecular sequences related by an evolutionary tree. A large number of popular stochastic models of sequence evolution are provided and tree-based models suitable for both within- and between-species sequence data are implemented. BEAST version 1.4.6 consists of 81000 lines of Java source code, 779 classes and 81 packages. It provides models for DNA and protein sequence evolution, highly parametric coalescent analysis, relaxed clock phylogenetics, non-contemporaneous sequence data, statistical alignment and a wide range of options for prior distributions. BEAST source code is object-oriented, modular in design and freely available at http://beast-mcmc.googlecode.com/
under the GNU LGPL license. BEAST is a powerful and flexible evolutionary analysis package for molecular sequence variation. It also provides a resource for the further development of new models and statistical methods of evolutionary analysis.
11,916 citations
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TL;DR: For the next few weeks the course is going to be exploring a field that’s actually older than classical population genetics, although the approach it’ll be taking to it involves the use of population genetic machinery.
Abstract: So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to
9,847 citations
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TL;DR: It is shown that evolutionary conservation and coding consequence are key determinants of the strength of purifying selection, that rare-variant load varies substantially across biological pathways, and that each individual contains hundreds of rare non-coding variants at conserved sites, such as motif-disrupting changes in transcription-factor-binding sites.
Abstract: By characterizing the geographic and functional spectrum of human genetic variation, the 1000 Genomes Project aims to build a resource to help to understand the genetic contribution to disease. Here we describe the genomes of 1,092 individuals from 14 populations, constructed using a combination of low-coverage whole-genome and exome sequencing. By developing methods to integrate information across several algorithms and diverse data sources, we provide a validated haplotype map of 38 million single nucleotide polymorphisms, 1.4 million short insertions and deletions, and more than 14,000 larger deletions. We show that individuals from different populations carry different profiles of rare and common variants, and that low-frequency variants show substantial geographic differentiation, which is further increased by the action of purifying selection. We show that evolutionary conservation and coding consequence are key determinants of the strength of purifying selection, that rare-variant load varies substantially across biological pathways, and that each individual contains hundreds of rare non-coding variants at conserved sites, such as motif-disrupting changes in transcription-factor-binding sites. This resource, which captures up to 98% of accessible single nucleotide polymorphisms at a frequency of 1% in related populations, enables analysis of common and low-frequency variants in individuals from diverse, including admixed, populations.
7,710 citations
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Baylor College of Medicine1, Chinese Academy of Sciences2, Chinese National Human Genome Center3, University of Hong Kong4, The Chinese University of Hong Kong5, Hong Kong University of Science and Technology6, Illumina7, McGill University8, Washington University in St. Louis9, University of California, San Francisco10, Wellcome Trust Sanger Institute11, Beijing Normal University12, Health Sciences University of Hokkaido13, Shinshu University14, University of Tsukuba15, Howard University16, University of Ibadan17, Case Western Reserve University18, University of Utah19, Cold Spring Harbor Laboratory20, Johns Hopkins University21, University of Oxford22, North Carolina State University23, National Institutes of Health24, Massachusetts Institute of Technology25, Chinese Academy of Social Sciences26, Kyoto University27, Nagasaki University28, Wellcome Trust29, Genome Canada30, Foundation for the National Institutes of Health31, University of Maryland, Baltimore32, Vanderbilt University33, Stanford University34, University of California, Berkeley35, New York University36, University of Oklahoma37, University of New Mexico38, Université de Montréal39, University of California, Los Angeles40, University of Michigan41, University of Wisconsin-Madison42, London School of Economics and Political Science43, Genetic Alliance44, GlaxoSmithKline45, University of Washington46, Harvard University47, University of Chicago48, Fred Hutchinson Cancer Research Center49, University of Tokyo50
TL;DR: The HapMap will allow the discovery of sequence variants that affect common disease, will facilitate development of diagnostic tools, and will enhance the ability to choose targets for therapeutic intervention.
Abstract: The goal of the International HapMap Project is to determine the common patterns of DNA sequence variation in the human genome and to make this information freely available in the public domain. An international consortium is developing a map of these patterns across the genome by determining the genotypes of one million or more sequence variants, their frequencies and the degree of association between them, in DNA samples from populations with ancestry from parts of Africa, Asia and Europe. The HapMap will allow the discovery of sequence variants that affect common disease, will facilitate development of diagnostic tools, and will enhance our ability to choose targets for therapeutic intervention.
5,926 citations