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Garrett Hellenthal

Bio: Garrett Hellenthal is an academic researcher from University College London. The author has contributed to research in topics: Population & Genome-wide association study. The author has an hindex of 34, co-authored 70 publications receiving 9592 citations. Previous affiliations of Garrett Hellenthal include University of Oxford & Wellcome Trust Centre for Human Genetics.


Papers
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Journal ArticleDOI
10 Aug 2011-Nature
TL;DR: In this article, a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, they have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci.
Abstract: Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis.

2,511 citations

Journal ArticleDOI
TL;DR: This study enhances the catalog of multiple sclerosis risk variants and illustrates the value of fine mapping in the resolution of GWAS signals.
Abstract: Using the ImmunoChip custom genotyping array, we analyzed 14,498 subjects with multiple sclerosis and 24,091 healthy controls for 161,311 autosomal variants and identified 135 potentially associated regions (P < 10 × 10(-4)) In a replication phase, we combined these data with previous genome-wide association study (GWAS) data from an independent 14,802 subjects with multiple sclerosis and 26,703 healthy controls In these 80,094 individuals of European ancestry, we identified 48 new susceptibility variants (P < 50 × 10(-8)), 3 of which we found after conditioning on previously identified variants Thus, there are now 110 established multiple sclerosis risk variants at 103 discrete loci outside of the major histocompatibility complex With high-resolution Bayesian fine mapping, we identified five regions where one variant accounted for more than 50% of the posterior probability of association This study enhances the catalog of multiple sclerosis risk variants and illustrates the value of fine mapping in the resolution of GWAS signals

1,197 citations

Journal ArticleDOI
TL;DR: A novel inference framework that aims to efficiently capture information on population structure provided by patterns of haplotype similarity and an efficient model-based approach to identify discrete populations using this matrix, which offers advantages over PCA and over existing clustering algorithms in terms of speed, number of separable populations, and sensitivity to subtle population structure.
Abstract: The advent of genome-wide dense variation data provides an opportunity to investigate ancestry in unprecedented detail, but presents new statistical challenges. We propose a novel inference framework that aims to efficiently capture information on population structure provided by patterns of haplotype similarity. Each individual in a sample is considered in turn as a recipient, whose chromosomes are reconstructed using chunks of DNA donated by the other individuals. Results of this “chromosome painting” can be summarized as a “coancestry matrix,” which directly reveals key information about ancestral relationships among individuals. If markers are viewed as independent, we show that this matrix almost completely captures the information used by both standard Principal Components Analysis (PCA) and model-based approaches such as STRUCTURE in a unified manner. Furthermore, when markers are in linkage disequilibrium, the matrix combines information across successive markers to increase the ability to discern fine-scale population structure using PCA. In parallel, we have developed an efficient model-based approach to identify discrete populations using this matrix, which offers advantages over PCA in terms of interpretability and over existing clustering algorithms in terms of speed, number of separable populations, and sensitivity to subtle population structure. We analyse Human Genome Diversity Panel data for 938 individuals and 641,000 markers, and we identify 226 populations reflecting differences on continental, regional, local, and family scales. We present multiple lines of evidence that, while many methods capture similar information among strongly differentiated groups, more subtle population structure in human populations is consistently present at a much finer level than currently available geographic labels and is only captured by the haplotype-based approach. The software used for this article, ChromoPainter and fineSTRUCTURE, is available from http://www.paintmychromosomes.com/.

1,000 citations

Journal ArticleDOI
Lam C. Tsoi1, Sarah L. Spain1, Sarah L. Spain2, Jo Knight1  +212 moreInstitutions (52)
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

Journal ArticleDOI
14 Feb 2014-Science
TL;DR: An atlas of worldwide human admixture history, constructed by using genetic data alone and encompassing over 100 events occurring over the past 4000 years, is revealed, revealing admixture to be an almost universal force shaping human populations.
Abstract: Modern genetic data combined with appropriate statistical methods have the potential to contribute substantially to our understanding of human history. We have developed an approach that exploits the genomic structure of admixed populations to date and characterize historical mixture events at fine scales. We used this to produce an atlas of worldwide human admixture history, constructed by using genetic data alone and encompassing over 100 events occurring over the past 4000 years. We identified events whose dates and participants suggest they describe genetic impacts of the Mongol empire, Arab slave trade, Bantu expansion, first millennium CE migrations in Eastern Europe, and European colonialism, as well as unrecorded events, revealing admixture to be an almost universal force shaping human populations.

688 citations


Cited by
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Journal Article
Fumio Tajima1
30 Oct 1989-Genomics
TL;DR: It is suggested that the natural selection against large insertion/deletion is so weak that a large amount of variation is maintained in a population.

11,521 citations

Journal ArticleDOI
01 Nov 2012-Nature
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

Journal ArticleDOI
John W. Belmont1, Andrew Boudreau, Suzanne M. Leal1, Paul Hardenbol  +229 moreInstitutions (40)
27 Oct 2005
TL;DR: A public database of common variation in the human genome: more than one million single nucleotide polymorphisms for which accurate and complete genotypes have been obtained in 269 DNA samples from four populations, including ten 500-kilobase regions in which essentially all information about common DNA variation has been extracted.
Abstract: Inherited genetic variation has a critical but as yet largely uncharacterized role in human disease. Here we report a public database of common variation in the human genome: more than one million single nucleotide polymorphisms (SNPs) for which accurate and complete genotypes have been obtained in 269 DNA samples from four populations, including ten 500-kilobase regions in which essentially all information about common DNA variation has been extracted. These data document the generality of recombination hotspots, a block-like structure of linkage disequilibrium and low haplotype diversity, leading to substantial correlations of SNPs with many of their neighbours. We show how the HapMap resource can guide the design and analysis of genetic association studies, shed light on structural variation and recombination, and identify loci that may have been subject to natural selection during human evolution.

5,479 citations

Journal ArticleDOI
Anshul Kundaje1, Wouter Meuleman1, Wouter Meuleman2, Jason Ernst3, Misha Bilenky4, Angela Yen1, Angela Yen2, Alireza Heravi-Moussavi4, Pouya Kheradpour2, Pouya Kheradpour1, Zhizhuo Zhang1, Zhizhuo Zhang2, Jianrong Wang2, Jianrong Wang1, Michael J. Ziller2, Viren Amin5, John W. Whitaker, Matthew D. Schultz6, Lucas D. Ward1, Lucas D. Ward2, Abhishek Sarkar2, Abhishek Sarkar1, Gerald Quon1, Gerald Quon2, Richard Sandstrom7, Matthew L. Eaton2, Matthew L. Eaton1, Yi-Chieh Wu1, Yi-Chieh Wu2, Andreas R. Pfenning1, Andreas R. Pfenning2, Xinchen Wang2, Xinchen Wang1, Melina Claussnitzer2, Melina Claussnitzer1, Yaping Liu1, Yaping Liu2, Cristian Coarfa5, R. Alan Harris5, Noam Shoresh2, Charles B. Epstein2, Elizabeta Gjoneska2, Elizabeta Gjoneska1, Danny Leung8, Wei Xie8, R. David Hawkins8, Ryan Lister6, Chibo Hong9, Philippe Gascard9, Andrew J. Mungall4, Richard A. Moore4, Eric Chuah4, Angela Tam4, Theresa K. Canfield7, R. Scott Hansen7, Rajinder Kaul7, Peter J. Sabo7, Mukul S. Bansal10, Mukul S. Bansal1, Mukul S. Bansal2, Annaick Carles4, Jesse R. Dixon8, Kai How Farh2, Soheil Feizi1, Soheil Feizi2, Rosa Karlic11, Ah Ram Kim1, Ah Ram Kim2, Ashwinikumar Kulkarni12, Daofeng Li13, Rebecca F. Lowdon13, Ginell Elliott13, Tim R. Mercer14, Shane Neph7, Vitor Onuchic5, Paz Polak15, Paz Polak2, Nisha Rajagopal8, Pradipta R. Ray12, Richard C Sallari1, Richard C Sallari2, Kyle Siebenthall7, Nicholas A Sinnott-Armstrong1, Nicholas A Sinnott-Armstrong2, Michael Stevens13, Robert E. Thurman7, Jie Wu16, Bo Zhang13, Xin Zhou13, Arthur E. Beaudet5, Laurie A. Boyer1, Philip L. De Jager15, Philip L. De Jager2, Peggy J. Farnham17, Susan J. Fisher9, David Haussler18, Steven J.M. Jones4, Steven J.M. Jones19, Wei Li5, Marco A. Marra4, Michael T. McManus9, Shamil R. Sunyaev2, Shamil R. Sunyaev15, James A. Thomson20, Thea D. Tlsty9, Li-Huei Tsai2, Li-Huei Tsai1, Wei Wang, Robert A. Waterland5, Michael Q. Zhang21, Lisa Helbling Chadwick22, Bradley E. Bernstein6, Bradley E. Bernstein2, Bradley E. Bernstein15, Joseph F. Costello9, Joseph R. Ecker11, Martin Hirst4, Alexander Meissner2, Aleksandar Milosavljevic5, Bing Ren8, John A. Stamatoyannopoulos7, Ting Wang13, Manolis Kellis1, Manolis Kellis2 
19 Feb 2015-Nature
TL;DR: It is shown that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease.
Abstract: The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.

5,037 citations

Journal ArticleDOI
TL;DR: The Ensembl Variant Effect Predictor can simplify and accelerate variant interpretation in a wide range of study designs.
Abstract: The Ensembl Variant Effect Predictor is a powerful toolset for the analysis, annotation, and prioritization of genomic variants in coding and non-coding regions. It provides access to an extensive collection of genomic annotation, with a variety of interfaces to suit different requirements, and simple options for configuring and extending analysis. It is open source, free to use, and supports full reproducibility of results. The Ensembl Variant Effect Predictor can simplify and accelerate variant interpretation in a wide range of study designs.

4,658 citations