Cited by 606Genetic Associations and EpidemiologyMultiple Sclerosis Research StudiesGenetic Mapping and Diversity in Plants and Animals

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Pervasive Sharing of Genetic Effects in Autoimmune Disease

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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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Crossref · 10.1371/journal.pgen.1002254

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Figure 1 Patterns of association across diseases correlate with protein-protein interactions. A: 47 SNPs with evidence of association to multiple diseases (Pcpma<0.01) fall into groups clustered by the pattern of association across diseases. Clusters are numbered arbitrarily. B: Clusters show different patterns of association across diseases. We summarize the differential disease effects of each cluster with a cumulative association statistic (Fisher's method for combining p values). These patterns are different for each cluster, suggesting each represents a different co-morbid mechanism. Note that these figures are based on the same underlying association statistics the clustering in the first panel is derived from. C: proteins encoded within the linkage disequilibrium scope around SNPs in the same cluster interact either directly or via common intermediates. Three of our four clusters have significant protein inter-connectivity (permuted P<0.05; see Materials and Methods and [19] for details).
Figure 1 Patterns of association across diseases correlate with protein-protein interactions. A: 47 SNPs with evidence of association to multiple diseases (Pcpma<0.01) fall into groups clustered by the pattern of association across diseases. Clusters are numbered arbitrarily. B: Clusters show different patterns of association across diseases. We summarize the differential disease effects of each cluster with a cumulative association statistic (Fisher's method for combining p values). These patterns are different for each cluster, suggesting each represents a different co-morbid mechanism. Note that these figures are based on the same underlying association statistics the clustering in the first panel is derived from. C: proteins encoded within the linkage disequilibrium scope around SNPs in the same cluster interact either directly or via common intermediates. Three of our four clusters have significant protein inter-connectivity (permuted P<0.05; see Materials and Methods and [19] for details).CC BY · PubMed Central

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Metadata

Authors
Cotsapas, C., Voight, B. F., Rossin, E., Lage, K., Neale, B. M., Wallace, C., Abecasis, G. R., Barrett, J. C., Behrens, T., Cho, J., De Jager, P. L., Elder, J. T., Graham, R. R., Gregersen, P., Klareskog, L., Siminovitch, K. A., van Heel, D. A., Wijmenga, C., Worthington, J., Todd, J. A., Hafler, D. A., Rich, S. S., Daly, M. J., & on behalf of the FOCiS Network of Consortia
Affiliations
  • Massachusetts General Hospital (US)
  • Broad Institute (US)
  • University of Cambridge (GB)
  • University of Michigan (US)
  • Wellcome Sanger Institute (GB)
  • Genentech (US)
  • Yale University (US)
  • Northwell Health (US)
  • Karolinska Institutet (SE)
  • Mount Sinai Hospital (CA)
  • University Medical Center Groningen (NL)
  • Manchester Academic Health Science Centre (GB)
  • University of Virginia (US)
Corresponding author
Daly, Mark J.
Venue
PLoS Genetics
Published
2011-08-10
Volume
7
Issue
8
Pages
e1002254
ISSN
  • 1553-7390 (ISSN-L)
  • 1553-7404
OpenAlex
W1859891932
Cited by
606
References
30
Citations by year
2026: 18 · 2025: 18 · 2024: 21 · 2023: 26 · 2022: 26 · 2021: 27 · 2020: 40 · 2019: 37 · 2018: 40 · 2017: 77 · 2016: 40 · 2015: 54 · 2014: 57 · 2013: 63 · 2012: 52
FWCI
6.01
Type
journal article
Language
en
Open access
Locations
  • PLoS Genetics (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Research Explorer (The University of Manchester) (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
  • Figshare (submittedVersion, cc-by)
  • Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU) (submittedVersion, other-oa)
  • University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, cc-by)
  • Queen Mary Research Online (Queen Mary University of London) (submittedVersion, cc-by)
  • PLoS eBooks
Funders
  • Wellcome Trust (091157, 089989)
  • National Institute for Health and Care Research (NF-SI-0508-10275)
  • Versus Arthritis (/17552)
  • National Institute of General Medical Sciences (T32GM007753)
  • National Institute of Diabetes and Digestive and Kidney Diseases (P30DK043351)
  • National Institute of Arthritis and Musculoskeletal and Skin Diseases (R01AR050511, R01AR042742, R01AR054966)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Health Sciences › Medicine › Clinical Neurology › Multiple Sclerosis Research Studies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
Keywords
autoimmune disease, shared genetic risk, immune-mediated diseases, single nucleotide polymorphisms, celiac disease, Crohn's disease, multiple sclerosis, psoriasis, rheumatoid arthritis, systemic lupus erythematosus, type 1 diabetes, protein-protein interaction network, pathogenesis, MHC locus
MeSH terms
Autoimmune Diseases, Humans, Phenotype, Comorbidity, Cluster Analysis, Polymorphism, Single Nucleotide, Genome-Wide Association Study, Genetic Loci, Protein Interaction Maps

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