Pervasive Sharing of Genetic Effects in Autoimmune Disease
Genome-wide association (GWA) studies have identified numerous, replicable, genetic associations between common single nucleotide polymorphisms (SNPs) and risk of common autoimmune and inflammatory (immune-mediated) diseases, some of which are shared between two diseases. Along with epidemiological...
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| Published in | PLoS genetics Vol. 7; no. 8; p. e1002254 |
|---|---|
| Main Authors | , , , , , , , , , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Public Library of Science
01.08.2011
Public Library of Science (PLoS) |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1553-7404 1553-7390 1553-7404 |
| DOI | 10.1371/journal.pgen.1002254 |
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| Abstract | Genome-wide association (GWA) studies have identified numerous, replicable, genetic associations between common single nucleotide polymorphisms (SNPs) and risk of common autoimmune and inflammatory (immune-mediated) diseases, some of which are shared between two diseases. Along with epidemiological and clinical evidence, this suggests that some genetic risk factors may be shared across diseases-as is the case with alleles in the Major Histocompatibility Locus. In this work we evaluate the extent of this sharing for 107 immune disease-risk SNPs in seven diseases: celiac disease, Crohn's disease, multiple sclerosis, psoriasis, rheumatoid arthritis, systemic lupus erythematosus, and type 1 diabetes. We have developed a novel statistic for Cross Phenotype Meta-Analysis (CPMA) which detects association of a SNP to multiple, but not necessarily all, phenotypes. With it, we find evidence that 47/107 (44%) immune-mediated disease risk SNPs are associated to multiple-but not all-immune-mediated diseases (SNP-wise P(CPMA)<0.01). We also show that distinct groups of interacting proteins are encoded near SNPs which predispose to the same subsets of diseases; we propose these as the mechanistic basis of shared disease risk. We are thus able to leverage genetic data across diseases to construct biological hypotheses about the underlying mechanism of pathogenesis. |
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| AbstractList |
Genome-wide association (GWA) studies have identified numerous, replicable, genetic associations between common single nucleotide polymorphisms (SNPs) and risk of common autoimmune and inflammatory (immune-mediated) diseases, some of which are shared between two diseases. Along with epidemiological and clinical evidence, this suggests that some genetic risk factors may be shared across diseases--as is the case with alleles in the Major Histocompatibility Locus. In this work we evaluate the extent of this sharing for 107 immune disease-risk SNPs in seven diseases: celiac disease, Crohn's disease, multiple sclerosis, psoriasis, rheumatoid arthritis, systemic lupus erythematosus, and type 1 diabetes. We have developed a novel statistic for Cross Phenotype Meta-Analysis (CPMA) which detects association of a SNP to multiple, but not necessarily all, phenotypes. With it, we find evidence that 47/107 (44%) immune-mediated disease risk SNPs are associated to multiple--but not all--immune-mediated diseases (SNP-wise PCPMA<0.01). We also show that distinct groups of interacting proteins are encoded near SNPs which predispose to the same subsets of diseases; we propose these as the mechanistic basis of shared disease risk. We are thus able to leverage genetic data across diseases to construct biological hypotheses about the underlying mechanism of pathogenesis. Genome-wide association (GWA) studies have identified numerous, replicable, genetic associations between common single nucleotide polymorphisms (SNPs) and risk of common autoimmune and inflammatory (immune-mediated) diseases, some of which are shared between two diseases. Along with epidemiological and clinical evidence, this suggests that some genetic risk factors may be shared across diseases--as is the case with alleles in the Major Histocompatibility Locus. In this work we evaluate the extent of this sharing for 107 immune disease-risk SNPs in seven diseases: celiac disease, Crohn's disease, multiple sclerosis, psoriasis, rheumatoid arthritis, systemic lupus erythematosus, and type 1 diabetes. We have developed a novel statistic for Cross Phenotype Meta-Analysis (CPMA) which detects association of a SNP to multiple, but not necessarily all, phenotypes. With it, we find evidence that 47/107 (44%) immune-mediated disease risk SNPs are associated to multiple--but not all--immune-mediated diseases (SNP-wise PCPMA<0.01). We also show that distinct groups of interacting proteins are encoded near SNPs which predispose to the same subsets of diseases;we propose these as the mechanistic basis of shared disease risk. We are thus able to leverage genetic data across diseases to construct biological hypotheses about the underlying mechanism of pathogenesis. Genome-wide association (GWA) studies have identified numerous, replicable, genetic associations between common single nucleotide polymorphisms (SNPs) and risk of common autoimmune and inflammatory (immune-mediated) diseases, some of which are shared between two diseases. Along with epidemiological and clinical evidence, this suggests that some genetic risk factors may be shared across diseases—as is the case with alleles in the Major Histocompatibility Locus. In this work we evaluate the extent of this sharing for 107 immune disease-risk SNPs in seven diseases: celiac disease, Crohn's disease, multiple sclerosis, psoriasis, rheumatoid arthritis, systemic lupus erythematosus, and type 1 diabetes. We have developed a novel statistic for Cross Phenotype Meta-Analysis (CPMA) which detects association of a SNP to multiple, but not necessarily all, phenotypes. With it, we find evidence that 47/107 (44%) immune-mediated disease risk SNPs are associated to multiple—but not all—immune-mediated diseases (SNP-wise P CPMA <0.01). We also show that distinct groups of interacting proteins are encoded near SNPs which predispose to the same subsets of diseases; we propose these as the mechanistic basis of shared disease risk. We are thus able to leverage genetic data across diseases to construct biological hypotheses about the underlying mechanism of pathogenesis. Over the last five years we have found over 100 genetic variants predisposing to common diseases affecting the immune system. In this study we analyze 107 such variants across seven diseases and find that almost half are shared across diseases. We also find that the patterns of sharing across diseases cluster these variants into groups; proteins encoded near variants in the same group tend to interact. This suggests that genetic variation may influence entire pathways to create risk to multiple diseases. Genome-wide association (GWA) studies have identified numerous, replicable, genetic associations between common single nucleotide polymorphisms (SNPs) and risk of common autoimmune and inflammatory (immune-mediated) diseases, some of which are shared between two diseases. Along with epidemiological and clinical evidence, this suggests that some genetic risk factors may be shared across diseases-as is the case with alleles in the Major Histocompatibility Locus. In this work we evaluate the extent of this sharing for 107 immune disease-risk SNPs in seven diseases: celiac disease, Crohn's disease, multiple sclerosis, psoriasis, rheumatoid arthritis, systemic lupus erythematosus, and type 1 diabetes. We have developed a novel statistic for Cross Phenotype Meta-Analysis (CPMA) which detects association of a SNP to multiple, but not necessarily all, phenotypes. With it, we find evidence that 47/107 (44%) immune-mediated disease risk SNPs are associated to multiple-but not all-immune-mediated diseases (SNP-wise P(CPMA)<0.01). We also show that distinct groups of interacting proteins are encoded near SNPs which predispose to the same subsets of diseases; we propose these as the mechanistic basis of shared disease risk. We are thus able to leverage genetic data across diseases to construct biological hypotheses about the underlying mechanism of pathogenesis. Genome-wide association (GWA) studies have identified numerous, replicable, genetic associations between common single nucleotide polymorphisms (SNPs) and risk of common autoimmune and inflammatory (immune-mediated) diseases, some of which are shared between two diseases. Along with epidemiological and clinical evidence, this suggests that some genetic risk factors may be shared across diseases-as is the case with alleles in the Major Histocompatibility Locus. In this work we evaluate the extent of this sharing for 107 immune disease-risk SNPs in seven diseases: celiac disease, Crohn's disease, multiple sclerosis, psoriasis, rheumatoid arthritis, systemic lupus erythematosus, and type 1 diabetes. We have developed a novel statistic for Cross Phenotype Meta-Analysis (CPMA) which detects association of a SNP to multiple, but not necessarily all, phenotypes. With it, we find evidence that 47/107 (44%) immune-mediated disease risk SNPs are associated to multiple-but not all-immune-mediated diseases (SNP-wise P(CPMA)<0.01). We also show that distinct groups of interacting proteins are encoded near SNPs which predispose to the same subsets of diseases; we propose these as the mechanistic basis of shared disease risk. We are thus able to leverage genetic data across diseases to construct biological hypotheses about the underlying mechanism of pathogenesis.Genome-wide association (GWA) studies have identified numerous, replicable, genetic associations between common single nucleotide polymorphisms (SNPs) and risk of common autoimmune and inflammatory (immune-mediated) diseases, some of which are shared between two diseases. Along with epidemiological and clinical evidence, this suggests that some genetic risk factors may be shared across diseases-as is the case with alleles in the Major Histocompatibility Locus. In this work we evaluate the extent of this sharing for 107 immune disease-risk SNPs in seven diseases: celiac disease, Crohn's disease, multiple sclerosis, psoriasis, rheumatoid arthritis, systemic lupus erythematosus, and type 1 diabetes. We have developed a novel statistic for Cross Phenotype Meta-Analysis (CPMA) which detects association of a SNP to multiple, but not necessarily all, phenotypes. With it, we find evidence that 47/107 (44%) immune-mediated disease risk SNPs are associated to multiple-but not all-immune-mediated diseases (SNP-wise P(CPMA)<0.01). We also show that distinct groups of interacting proteins are encoded near SNPs which predispose to the same subsets of diseases; we propose these as the mechanistic basis of shared disease risk. We are thus able to leverage genetic data across diseases to construct biological hypotheses about the underlying mechanism of pathogenesis. |
| Audience | Academic |
| Author | Voight, Benjamin F. Klareskog, Lars Wijmenga, Cisca Barrett, Jeffrey C. Elder, James T. Gregersen, Peter Worthington, Jane Todd, John A. Abecasis, Gonçalo R. Cotsapas, Chris Neale, Benjamin M. Wallace, Chris van Heel, David A. Cho, Judy Daly, Mark J. Behrens, Timothy Siminovitch, Katherine A. Graham, Robert R. Lage, Kasper Rich, Stephen S. Rossin, Elizabeth Hafler, David A. De Jager, Philip L. |
| AuthorAffiliation | 2 Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America 20 Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Canada 4 Department of Neurology, Yale University School of Medicine, New Haven, Connecticut, United States of America 9 Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby, Denmark 16 Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts, United States of America 3 Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America 8 Pediatric Surgical Research Laboratories, Massachusetts General Hospital, Boston, Massachusetts, United States of America 14 Genentech, South San Francisco, California, United States of America 13 Human Genetics, Wellcome Trust Sanger Institute, Cambridge, United Kingdom 17 Department of Dermatology, University of Michigan, Ann Arbor, Michigan, United States of Amer |
| AuthorAffiliation_xml | – name: 7 Harvard Biological and Biomedical Sciences Program, Harvard University, Boston, Massachusetts, United States of America – name: 1 Center For Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America – name: University of Geneva Medical School, Switzerland – name: 23 Arthritis Research UK Epidemiology Unit, School of Translational Medicine, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, United Kingdom – name: 6 Health Science and Technology MD Program, Harvard University and Massachusetts Institute of Technology, Boston, Massachusetts, United States of America – name: 2 Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America – name: 13 Human Genetics, Wellcome Trust Sanger Institute, Cambridge, United Kingdom – name: 14 Genentech, South San Francisco, California, United States of America – name: 22 Department of Genetics, University Medical Center Groningen and Groningen University, Groningen, The Netherlands – name: 19 Rheumatology Unit, Department of Medicine, Karolinska Institutet, Stockholm, Sweden – name: 3 Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America – name: 5 Department of Genetics, Yale University School of Medicine, New Haven, Connecticut, United States of America – name: 11 Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, United Kingdom – name: 16 Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts, United States of America – name: 21 Blizard Institute, The London School of Medicine and Dentistry, London, United Kingdom – name: 10 Analytical and Translational Genetics Unity, Massachusetts General Hospital, Boston, Massachusetts, United States of America – name: 15 Departments of Medicine and Genetics, Yale University School of Medicine, New Haven, Connecticut, United States of America – name: 18 Feinstein Institute for Medical Research, North Shore-Long Island Jewish Health System, Manhasset, New York, United States of America – name: 24 Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America – name: 9 Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby, Denmark – name: 20 Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Canada – name: 4 Department of Neurology, Yale University School of Medicine, New Haven, Connecticut, United States of America – name: 8 Pediatric Surgical Research Laboratories, Massachusetts General Hospital, Boston, Massachusetts, United States of America – name: 12 Center for Statistical Genetics, University of Michigan, Ann Arbor, Massachusetts, United States of America – name: 17 Department of Dermatology, University of Michigan, Ann Arbor, Michigan, United States of America |
| Author_xml | – sequence: 1 givenname: Chris surname: Cotsapas fullname: Cotsapas, Chris – sequence: 2 givenname: Benjamin F. surname: Voight fullname: Voight, Benjamin F. – sequence: 3 givenname: Elizabeth surname: Rossin fullname: Rossin, Elizabeth – sequence: 4 givenname: Kasper surname: Lage fullname: Lage, Kasper – sequence: 5 givenname: Benjamin M. surname: Neale fullname: Neale, Benjamin M. – sequence: 6 givenname: Chris surname: Wallace fullname: Wallace, Chris – sequence: 7 givenname: Gonçalo R. surname: Abecasis fullname: Abecasis, Gonçalo R. – sequence: 8 givenname: Jeffrey C. surname: Barrett fullname: Barrett, Jeffrey C. – sequence: 9 givenname: Timothy surname: Behrens fullname: Behrens, Timothy – sequence: 10 givenname: Judy surname: Cho fullname: Cho, Judy – sequence: 11 givenname: Philip L. surname: De Jager fullname: De Jager, Philip L. – sequence: 12 givenname: James T. surname: Elder fullname: Elder, James T. – sequence: 13 givenname: Robert R. surname: Graham fullname: Graham, Robert R. – sequence: 14 givenname: Peter surname: Gregersen fullname: Gregersen, Peter – sequence: 15 givenname: Lars surname: Klareskog fullname: Klareskog, Lars – sequence: 16 givenname: Katherine A. surname: Siminovitch fullname: Siminovitch, Katherine A. – sequence: 17 givenname: David A. surname: van Heel fullname: van Heel, David A. – sequence: 18 givenname: Cisca surname: Wijmenga fullname: Wijmenga, Cisca – sequence: 19 givenname: Jane surname: Worthington fullname: Worthington, Jane – sequence: 20 givenname: John A. surname: Todd fullname: Todd, John A. – sequence: 21 givenname: David A. surname: Hafler fullname: Hafler, David A. – sequence: 22 givenname: Stephen S. surname: Rich fullname: Rich, Stephen S. – sequence: 23 givenname: Mark J. surname: Daly fullname: Daly, Mark J. |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/21852963$$D View this record in MEDLINE/PubMed http://kipublications.ki.se/Default.aspx?queryparsed=id:123215553$$DView record from Swedish Publication Index |
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| Copyright | COPYRIGHT 2011 Public Library of Science Cotsapas et al. 2011 2011 Cotsapas et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Cotsapas C, Voight BF, Rossin E, Lage K, Neale BM, et al. (2011) Pervasive Sharing of Genetic Effects in Autoimmune Disease. PLoS Genet 7(8): e1002254. doi:10.1371/journal.pgen.1002254 |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Conceived and designed the experiments: C Cotsapas, BF Voight, DA Hafler, SS Rich, MJ Daly. Performed the experiments: C Cotsapas, BF Voight, E Rossin, BM Neale, MJ Daly. Analyzed the data: C Cotsapas, BF Voight, E Rossin, K Lage, MJ Daly. Contributed reagents/materials/analysis tools: BF Voight, K Lage, BM Neale, C Wallace, GR Abecasis, JC Barrett, T Behrens, J Cho, PL De Jager, JT Elder, RR Graham, P Gregersen, L Klareskog, KA Siminovitch, DA van Heel, C Wijmenga, J Worthington, JA Todd, DA Hafler, SS Rich, MJ Daly. Wrote the paper: C Cotsapas, BF Voight, JA Todd, DA Hafler, SS Rich, MJ Daly. |
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| Snippet | Genome-wide association (GWA) studies have identified numerous, replicable, genetic associations between common single nucleotide polymorphisms (SNPs) and risk... Genome-wide association (GWA) studies have identified numerous, replicable, genetic associations between common single nucleotide polymorphisms (SNPs) and... |
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| SubjectTerms | Autoimmune diseases Autoimmune Diseases - genetics Biology Cluster Analysis Comorbidity Disease Genetic aspects Genetic Loci Genetics Genome-Wide Association Study Humans Immune system Lupus Phenotype Polymorphism, Single Nucleotide Protein Interaction Maps Protein-protein interactions Risk factors Single nucleotide polymorphisms |
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| Title | Pervasive Sharing of Genetic Effects in Autoimmune Disease |
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