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Xinli Hu

Bio: Xinli Hu is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Genome-wide association study & Autoimmunity. The author has an hindex of 17, co-authored 22 publications receiving 5651 citations. Previous affiliations of Xinli Hu include Broad Institute & Brigham and Women's Hospital.

Papers
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Journal ArticleDOI
Luke Jostins1, Stephan Ripke2, Rinse K. Weersma3, Richard H. Duerr4, Dermot P.B. McGovern5, Ken Y. Hui6, James Lee7, L. Philip Schumm8, Yashoda Sharma6, Carl A. Anderson1, Jonah Essers9, Mitja Mitrovic3, Kaida Ning6, Isabelle Cleynen10, Emilie Theatre11, Sarah L. Spain12, Soumya Raychaudhuri9, Philippe Goyette13, Zhi Wei14, Clara Abraham6, Jean-Paul Achkar15, Tariq Ahmad16, Leila Amininejad17, Ashwin N. Ananthakrishnan9, Vibeke Andersen18, Jane M. Andrews19, Leonard Baidoo4, Tobias Balschun20, Peter A. Bampton21, Alain Bitton22, Gabrielle Boucher13, Stephan Brand23, Carsten Büning24, Ariella Cohain25, Sven Cichon26, Mauro D'Amato27, Dirk De Jong3, Kathy L Devaney9, Marla Dubinsky5, Cathryn Edwards28, David Ellinghaus20, Lynnette R. Ferguson29, Denis Franchimont17, Karin Fransen3, Richard B. Gearry30, Michel Georges11, Christian Gieger, Jürgen Glas22, Talin Haritunians5, Ailsa Hart31, Christopher J. Hawkey32, Matija Hedl6, Xinli Hu9, Tom H. Karlsen33, Limas Kupčinskas34, Subra Kugathasan35, Anna Latiano36, Debby Laukens37, Ian C. Lawrance38, Charlie W. Lees39, Edouard Louis11, Gillian Mahy40, John C. Mansfield41, Angharad R. Morgan29, Craig Mowat42, William G. Newman43, Orazio Palmieri36, Cyriel Y. Ponsioen44, Uroš Potočnik45, Natalie J. Prescott6, Miguel Regueiro4, Jerome I. Rotter5, Richard K Russell46, Jeremy D. Sanderson47, Miquel Sans, Jack Satsangi39, Stefan Schreiber20, Lisa A. Simms48, Jurgita Sventoraityte34, Stephan R. Targan, Kent D. Taylor5, Mark Tremelling49, Hein W. Verspaget50, Martine De Vos37, Cisca Wijmenga3, David C. Wilson39, Juliane Winkelmann51, Ramnik J. Xavier9, Sebastian Zeissig20, Bin Zhang25, Clarence K. Zhang6, Hongyu Zhao6, Mark S. Silverberg52, Vito Annese, Hakon Hakonarson53, Steven R. Brant54, Graham L. Radford-Smith55, Christopher G. Mathew12, John D. Rioux13, Eric E. Schadt25, Mark J. Daly2, Andre Franke20, Miles Parkes7, Severine Vermeire10, Jeffrey C. Barrett1, Judy H. Cho6 
Wellcome Trust Sanger Institute1, Broad Institute2, University of Groningen3, University of Pittsburgh4, Cedars-Sinai Medical Center5, Yale University6, University of Cambridge7, University of Chicago8, Harvard University9, Katholieke Universiteit Leuven10, University of Liège11, King's College London12, Université de Montréal13, New Jersey Institute of Technology14, Cleveland Clinic15, Peninsula College of Medicine and Dentistry16, Université libre de Bruxelles17, Aarhus University18, University of Adelaide19, University of Kiel20, Flinders University21, McGill University22, Ludwig Maximilian University of Munich23, Charité24, Icahn School of Medicine at Mount Sinai25, University of Bonn26, Karolinska Institutet27, Torbay Hospital28, University of Auckland29, Christchurch Hospital30, Imperial College London31, Queen's University32, University of Oslo33, Lithuanian University of Health Sciences34, Emory University35, Casa Sollievo della Sofferenza36, Ghent University37, University of Western Australia38, University of Edinburgh39, Queensland Health40, Newcastle University41, University of Dundee42, University of Manchester43, University of Amsterdam44, University of Maribor45, Royal Hospital for Sick Children46, Guy's and St Thomas' NHS Foundation Trust47, QIMR Berghofer Medical Research Institute48, Norfolk and Norwich University Hospital49, Leiden University50, Technische Universität München51, University of Toronto52, University of Pennsylvania53, Johns Hopkins University54, University of Queensland55
01 Nov 2012-Nature
TL;DR: A meta-analysis of Crohn’s disease and ulcerative colitis genome-wide association scans is undertaken, followed by extensive validation of significant findings, with a combined total of more than 75,000 cases and controls.
Abstract: Crohn's disease and ulcerative colitis, the two common forms of inflammatory bowel disease (IBD), affect over 2.5 million people of European ancestry, with rising prevalence in other populations. Genome-wide association studies and subsequent meta-analyses of these two diseases as separate phenotypes have implicated previously unsuspected mechanisms, such as autophagy, in their pathogenesis and showed that some IBD loci are shared with other inflammatory diseases. Here we expand on the knowledge of relevant pathways by undertaking a meta-analysis of Crohn's disease and ulcerative colitis genome-wide association scans, followed by extensive validation of significant findings, with a combined total of more than 75,000 cases and controls. We identify 71 new associations, for a total of 163 IBD loci, that meet genome-wide significance thresholds. Most loci contribute to both phenotypes, and both directional (consistently favouring one allele over the course of human history) and balancing (favouring the retention of both alleles within populations) selection effects are evident. Many IBD loci are also implicated in other immune-mediated disorders, most notably with ankylosing spondylitis and psoriasis. We also observe considerable overlap between susceptibility loci for IBD and mycobacterial infection. Gene co-expression network analysis emphasizes this relationship, with pathways shared between host responses to mycobacteria and those predisposing to IBD.

4,094 citations

Journal ArticleDOI
TL;DR: This study illustrates the advantages of dense SNP mapping analysis to inform subsequent functional investigations and refined the peak of association to a single gene for 19 loci, identified secondary independent effects at 6 loci and identified association to low-frequency variants at 4 loci.
Abstract: Using the Immunochip custom SNP array, which was designed for dense genotyping of 186 loci identified through genome-wide association studies (GWAS), we analyzed 11,475 individuals with rheumatoid arthritis (cases) of European ancestry and 15,870 controls for 129,464 markers. We combined these data in a meta-analysis with GWAS data from additional independent cases (n = 2,363) and controls (n = 17,872). We identified 14 new susceptibility loci, 9 of which were associated with rheumatoid arthritis overall and five of which were specifically associated with disease that was positive for anticitrullinated peptide antibodies, bringing the number of confirmed rheumatoid arthritis risk loci in individuals of European ancestry to 46. We refined the peak of association to a single gene for 19 loci, identified secondary independent effects at 6 loci and identified association to low-frequency variants at 4 loci. Bioinformatic analyses generated strong hypotheses for the causal SNP at seven loci. This study illustrates the advantages of dense SNP mapping analysis to inform subsequent functional investigations.

612 citations

Book ChapterDOI
25 Apr 2010
TL;DR: This work presents a direct multivariate finite mixture modeling approach, using skew and heavy-tailed distributions, to address the complexities of flow cytometric analysis and to deal with high-dimensional cytometric data without the need for projection or transformation.
Abstract: Flow cytometry is widely used for single cell interrogation of surface and intracellular protein expression by measuring fluorescence intensity of fluorophore-conjugated reagents We focus on the recently developed procedure of Pyne et al (2009, Proceedings of the National Academy of Sciences USA 106, 8519-8524) for automated high- dimensional flow cytometric analysis called FLAME (FLow analysis with Automated Multivariate Estimation) It introduced novel finite mixture models of heavy-tailed and asymmetric distributions to identify and model cell populations in a flow cytometric sample This approach robustly addresses the complexities of flow data without the need for transformation or projection to lower dimensions It also addresses the critical task of matching cell populations across samples that enables downstream analysis It thus facilitates application of flow cytometry to new biological and clinical problems To facilitate pipelining with standard bioinformatic applications such as high-dimensional visualization, subject classification or outcome prediction, FLAME has been incorporated with the GenePattern package of the Broad Institute Thereby analysis of flow data can be approached similarly as other genomic platforms We also consider some new work that proposes a rigorous and robust solution to the registration problem by a multi-level approach that allows us to model and register cell populations simultaneously across a cohort of high-dimensional flow samples This new approach is called JCM (Joint Clustering and Matching) It enables direct and rigorous comparisons across different time points or phenotypes in a complex biological study as well as for classification of new patient samples in a more clinical setting.

354 citations

Journal ArticleDOI
TL;DR: HLA-DRβ1 positions 13 and 71 implicate the P4 pocket in the antigen-binding groove, thus pointing to another critical protein structure for T1D risk, in addition to the HLA-DQ P9 pocket.
Abstract: Variation in the human leukocyte antigen (HLA) genes accounts for one-half of the genetic risk in type 1 diabetes (T1D). Amino acid changes in the HLA-DR and HLA-DQ molecules mediate most of the risk, but extensive linkage disequilibrium complicates the localization of independent effects. Using 18,832 case-control samples, we localized the signal to 3 amino acid positions in HLA-DQ and HLA-DR. HLA-DQβ1 position 57 (previously known; P = 1 × 10(-1,355)) by itself explained 15.2% of the total phenotypic variance. Independent effects at HLA-DRβ1 positions 13 (P = 1 × 10(-721)) and 71 (P = 1 × 10(-95)) increased the proportion of variance explained to 26.9%. The three positions together explained 90% of the phenotypic variance in the HLA-DRB1-HLA-DQA1-HLA-DQB1 locus. Additionally, we observed significant interactions for 11 of 21 pairs of common HLA-DRB1-HLA-DQA1-HLA-DQB1 haplotypes (P = 1.6 × 10(-64)). HLA-DRβ1 positions 13 and 71 implicate the P4 pocket in the antigen-binding groove, thus pointing to another critical protein structure for T1D risk, in addition to the HLA-DQ P9 pocket.

208 citations

Journal ArticleDOI
TL;DR: Functional investigations suggest a potential mechanism whereby increases in CD58 expression, mediated by the protective allele, up-regulate the expression of transcription factor FoxP3 through engagement of the CD58 receptor, CD2, leading to the enhanced function of CD4+CD25high regulatory T cells that are defective in subjects with MS.
Abstract: Multiple sclerosis (MS) is an inflammatory disease of the central nervous system associated with demyelination and axonal loss A whole genome association scan suggested that allelic variants in the CD58 gene region, encoding the costimulatory molecule LFA-3, are associated with risk of developing MS We now report additional genetic evidence, as well as resequencing and fine mapping of the CD58 locus in patients with MS and control subjects These efforts identify a CD58 variant that provides further evidence of association with MS (P = 11 × 10−6, OR 082) and the single protective effect within the CD58 locus is captured by the rs2300747G allele This protective rs2300747G allele is associated with a dose-dependent increase in CD58 mRNA expression in lymphoblastic cell lines (P = 11 × 10−10) and in peripheral blood mononuclear cells from MS subjects (P = 00037) This protective effect of enhanced CD58 expression on circulating mononuclear cells in patients with MS is supported by finding that CD58 mRNA expression is higher in MS subjects during clinical remission Functional investigations suggest a potential mechanism whereby increases in CD58 expression, mediated by the protective allele, up-regulate the expression of transcription factor FoxP3 through engagement of the CD58 receptor, CD2, leading to the enhanced function of CD4+CD25high regulatory T cells that are defective in subjects with MS

183 citations


Cited by
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Journal ArticleDOI
Stephan Ripke1, Stephan Ripke2, Benjamin M. Neale2, Benjamin M. Neale1  +351 moreInstitutions (102)
24 Jul 2014-Nature
TL;DR: Associations at DRD2 and several genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses.
Abstract: Schizophrenia is a highly heritable disorder. Genetic risk is conferred by a large number of alleles, including common alleles of small effect that might be detected by genome-wide association studies. Here we report a multi-stage schizophrenia genome-wide association study of up to 36,989 cases and 113,075 controls. We identify 128 independent associations spanning 108 conservatively defined loci that meet genome-wide significance, 83 of which have not been previously reported. Associations were enriched among genes expressed in brain, providing biological plausibility for the findings. Many findings have the potential to provide entirely new insights into aetiology, but associations at DRD2 and several genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses. Independent of genes expressed in brain, associations were enriched among genes expressed in tissues that have important roles in immunity, providing support for the speculated link between the immune system and schizophrenia.

6,809 citations

Journal ArticleDOI
Anshul Kundaje1, Wouter Meuleman1, Wouter Meuleman2, Jason Ernst3, Misha Bilenky4, Angela Yen2, Angela Yen1, Alireza Heravi-Moussavi4, Pouya Kheradpour1, Pouya Kheradpour2, Zhizhuo Zhang2, Zhizhuo Zhang1, Jianrong Wang1, Jianrong Wang2, 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 Wu2, Yi-Chieh Wu1, Andreas R. Pfenning2, Andreas R. Pfenning1, Xinchen Wang1, Xinchen Wang2, Melina Claussnitzer2, Melina Claussnitzer1, Yaping Liu2, Yaping Liu1, Cristian Coarfa5, R. Alan Harris5, Noam Shoresh2, Charles B. Epstein2, Elizabeta Gjoneska1, Elizabeta Gjoneska2, 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. Bansal1, Mukul S. Bansal2, Mukul S. Bansal10, Annaick Carles4, Jesse R. Dixon8, Kai How Farh2, Soheil Feizi2, Soheil Feizi1, 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 Polak2, Paz Polak15, Nisha Rajagopal8, Pradipta R. Ray12, Richard C Sallari1, Richard C Sallari2, Kyle Siebenthall7, Nicholas A Sinnott-Armstrong2, Nicholas A Sinnott-Armstrong1, 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. Jones19, Steven J.M. Jones4, Wei Li5, Marco A. Marra4, Michael T. McManus9, Shamil R. Sunyaev15, Shamil R. Sunyaev2, James A. Thomson20, Thea D. Tlsty9, Li-Huei Tsai1, Li-Huei Tsai2, Wei Wang, Robert A. Waterland5, Michael Q. Zhang21, Lisa Helbling Chadwick22, Bradley E. Bernstein2, Bradley E. Bernstein15, Bradley E. Bernstein6, 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
Kristin G. Ardlie, David S. DeLuca, Ayellet V. Segrè, Timothy J. Sullivan, Taylor Young, Ellen Gelfand, Casandra A. Trowbridge, Julian Maller, Taru Tukiainen, Monkol Lek, Lucas D. Ward, Pouya Kheradpour, Benjamin Iriarte, Yan Meng, Cameron D. Palmer, Tõnu Esko, Wendy Winckler, Joel N. Hirschhorn, Manolis Kellis, Daniel G. MacArthur, Gad Getz, Andrey A. Shabalin, Gen Li, Yi-Hui Zhou, Andrew B. Nobel, Ivan Rusyn, Fred A. Wright, Tuuli Lappalainen, Pedro G. Ferreira, Halit Ongen, Manuel A. Rivas, Alexis Battle, Sara Mostafavi, Jean Monlong, Michael Sammeth, Marta Melé, Ferran Reverter, Jakob M. Goldmann, Daphne Koller, Roderic Guigó, Mark I. McCarthy, Emmanouil T. Dermitzakis, Eric R. Gamazon, Hae Kyung Im, Anuar Konkashbaev, Dan L. Nicolae, Nancy J. Cox, Timothée Flutre, Xiaoquan Wen, Matthew Stephens, Jonathan K. Pritchard, Zhidong Tu, Bin Zhang, Tao Huang, Quan Long, Luan Lin, Jialiang Yang, Jun Zhu, Jun Liu, Amanda Brown, Bernadette Mestichelli, Denee Tidwell, Edmund Lo, Mike Salvatore, Saboor Shad, Jeffrey A. Thomas, John T. Lonsdale, Michael T. Moser, Bryan Gillard, Ellen Karasik, Kimberly Ramsey, Christopher Choi, Barbara A. Foster, John Syron, Johnell Fleming, Harold Magazine, Rick Hasz, Gary Walters, Jason Bridge, Mark Miklos, Susan L. Sullivan, Laura Barker, Heather M. Traino, Maghboeba Mosavel, Laura A. Siminoff, Dana R. Valley, Daniel C. Rohrer, Scott D. Jewell, Philip A. Branton, Leslie H. Sobin, Mary Barcus, Liqun Qi, Jeffrey McLean, Pushpa Hariharan, Ki Sung Um, Shenpei Wu, David Tabor, Charles Shive, Anna M. Smith, Stephen A. Buia, Anita H. Undale, Karna Robinson, Nancy Roche, Kimberly M. Valentino, Angela Britton, Robin Burges, Debra Bradbury, Kenneth W. Hambright, John Seleski, Greg E. Korzeniewski, Kenyon Erickson, Yvonne Marcus, Jorge Tejada, Mehran Taherian, Chunrong Lu, Margaret J. Basile, Deborah C. Mash, Simona Volpi, Jeffery P. Struewing, Gary F. Temple, Joy T. Boyer, Deborah Colantuoni, Roger Little, Susan E. Koester, Latarsha J. Carithers, Helen M. Moore, Ping Guan, Carolyn C. Compton, Sherilyn Sawyer, Joanne P. Demchok, Jimmie B. Vaught, Chana A. Rabiner, Nicole C. Lockhart 
08 May 2015-Science
TL;DR: The landscape of gene expression across tissues is described, thousands of tissue-specific and shared regulatory expression quantitative trait loci (eQTL) variants are cataloged, complex network relationships are described, and signals from genome-wide association studies explained by eQTLs are identified.
Abstract: Understanding the functional consequences of genetic variation, and how it affects complex human disease and quantitative traits, remains a critical challenge for biomedicine. We present an analysi...

4,418 citations

01 Feb 2015
TL;DR: In this article, the authors describe the integrative analysis of 111 reference human epigenomes generated as part of the NIH Roadmap Epigenomics Consortium, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression.
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.

4,409 citations

Journal ArticleDOI
Luke Jostins1, Stephan Ripke2, Rinse K. Weersma3, Richard H. Duerr4, Dermot P.B. McGovern5, Ken Y. Hui6, James Lee7, L. Philip Schumm8, Yashoda Sharma6, Carl A. Anderson1, Jonah Essers9, Mitja Mitrovic3, Kaida Ning6, Isabelle Cleynen10, Emilie Theatre11, Sarah L. Spain12, Soumya Raychaudhuri9, Philippe Goyette13, Zhi Wei14, Clara Abraham6, Jean-Paul Achkar15, Tariq Ahmad16, Leila Amininejad17, Ashwin N. Ananthakrishnan9, Vibeke Andersen18, Jane M. Andrews19, Leonard Baidoo4, Tobias Balschun20, Peter A. Bampton21, Alain Bitton22, Gabrielle Boucher13, Stephan Brand23, Carsten Büning24, Ariella Cohain25, Sven Cichon26, Mauro D'Amato27, Dirk De Jong3, Kathy L Devaney9, Marla Dubinsky5, Cathryn Edwards28, David Ellinghaus20, Lynnette R. Ferguson29, Denis Franchimont17, Karin Fransen3, Richard B. Gearry30, Michel Georges11, Christian Gieger, Jürgen Glas22, Talin Haritunians5, Ailsa Hart31, Christopher J. Hawkey32, Matija Hedl6, Xinli Hu9, Tom H. Karlsen33, Limas Kupčinskas34, Subra Kugathasan35, Anna Latiano36, Debby Laukens37, Ian C. Lawrance38, Charlie W. Lees39, Edouard Louis11, Gillian Mahy40, John C. Mansfield41, Angharad R. Morgan29, Craig Mowat42, William G. Newman43, Orazio Palmieri36, Cyriel Y. Ponsioen44, Uroš Potočnik45, Natalie J. Prescott6, Miguel Regueiro4, Jerome I. Rotter5, Richard K Russell46, Jeremy D. Sanderson47, Miquel Sans, Jack Satsangi39, Stefan Schreiber20, Lisa A. Simms48, Jurgita Sventoraityte34, Stephan R. Targan, Kent D. Taylor5, Mark Tremelling49, Hein W. Verspaget50, Martine De Vos37, Cisca Wijmenga3, David C. Wilson39, Juliane Winkelmann51, Ramnik J. Xavier9, Sebastian Zeissig20, Bin Zhang25, Clarence K. Zhang6, Hongyu Zhao6, Mark S. Silverberg52, Vito Annese, Hakon Hakonarson53, Steven R. Brant54, Graham L. Radford-Smith55, Christopher G. Mathew12, John D. Rioux13, Eric E. Schadt25, Mark J. Daly2, Andre Franke20, Miles Parkes7, Severine Vermeire10, Jeffrey C. Barrett1, Judy H. Cho6 
Wellcome Trust Sanger Institute1, Broad Institute2, University of Groningen3, University of Pittsburgh4, Cedars-Sinai Medical Center5, Yale University6, University of Cambridge7, University of Chicago8, Harvard University9, Katholieke Universiteit Leuven10, University of Liège11, King's College London12, Université de Montréal13, New Jersey Institute of Technology14, Cleveland Clinic15, Peninsula College of Medicine and Dentistry16, Université libre de Bruxelles17, Aarhus University18, University of Adelaide19, University of Kiel20, Flinders University21, McGill University22, Ludwig Maximilian University of Munich23, Charité24, Icahn School of Medicine at Mount Sinai25, University of Bonn26, Karolinska Institutet27, Torbay Hospital28, University of Auckland29, Christchurch Hospital30, Imperial College London31, Queen's University32, University of Oslo33, Lithuanian University of Health Sciences34, Emory University35, Casa Sollievo della Sofferenza36, Ghent University37, University of Western Australia38, University of Edinburgh39, Queensland Health40, Newcastle University41, University of Dundee42, University of Manchester43, University of Amsterdam44, University of Maribor45, Royal Hospital for Sick Children46, Guy's and St Thomas' NHS Foundation Trust47, QIMR Berghofer Medical Research Institute48, Norfolk and Norwich University Hospital49, Leiden University50, Technische Universität München51, University of Toronto52, University of Pennsylvania53, Johns Hopkins University54, University of Queensland55
01 Nov 2012-Nature
TL;DR: A meta-analysis of Crohn’s disease and ulcerative colitis genome-wide association scans is undertaken, followed by extensive validation of significant findings, with a combined total of more than 75,000 cases and controls.
Abstract: Crohn's disease and ulcerative colitis, the two common forms of inflammatory bowel disease (IBD), affect over 2.5 million people of European ancestry, with rising prevalence in other populations. Genome-wide association studies and subsequent meta-analyses of these two diseases as separate phenotypes have implicated previously unsuspected mechanisms, such as autophagy, in their pathogenesis and showed that some IBD loci are shared with other inflammatory diseases. Here we expand on the knowledge of relevant pathways by undertaking a meta-analysis of Crohn's disease and ulcerative colitis genome-wide association scans, followed by extensive validation of significant findings, with a combined total of more than 75,000 cases and controls. We identify 71 new associations, for a total of 163 IBD loci, that meet genome-wide significance thresholds. Most loci contribute to both phenotypes, and both directional (consistently favouring one allele over the course of human history) and balancing (favouring the retention of both alleles within populations) selection effects are evident. Many IBD loci are also implicated in other immune-mediated disorders, most notably with ankylosing spondylitis and psoriasis. We also observe considerable overlap between susceptibility loci for IBD and mycobacterial infection. Gene co-expression network analysis emphasizes this relationship, with pathways shared between host responses to mycobacteria and those predisposing to IBD.

4,094 citations