Pervasive Sharing of Genetic Effects in Autoimmune Disease

Center For Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
PLoS Genetics (Impact Factor: 7.53). 08/2011; 7(8):e1002254. DOI: 10.1371/journal.pgen.1002254
Source: PubMed


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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    • "Notably, the majority of these novel MS-associated genes played pivotal roles in the workings of the immune system and were also associated with other autoimmune diseases, supporting the hypothesis that the same processes occur in different autoimmune diseases (Baranzini, 2009; Cotsapas et al., 2011). "
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    • "The broader pursuit of examining multiple GWAS phenotypes has been explored in various ways, with some authors proposing combining traits before performing the GWAS as a way to increase power to detect pleiotropic genes [25]. Others have used multiple GWAS of the same disease to enhance biological pathway analysis [21], and statistics have been developed to identify pleiotropic SNPs from among several GWAS of related traits [7]. Our work builds on these ideas but explores a somewhat different question: that of using multiple GWAS of different phenotypes to enhance understanding of a single trait. "
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    • "Beyond transplantation, polymorphisms in the MHC region have been used as molecular markers for population genetics and studies of diseases and traits. In the past 30 years, no other region in the genome has provided more association signals with multifactorial traits, including autoimmune diseases [5]–[8], inflammatory and infectious diseases [9], cancer [10], adverse drug effects [11], [12], and behavioral traits such as mating [13], [14]. To assess HLA allelic diversity, these studies employed a broad range of methodologies from serology, restriction fragment length polymorphism, and microsatellites up to the latest generation of single nucleotide polymorphism (SNP) genotyping methods. "
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