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Genetic basis of autoimmunity
Alexander Marson, … , William J. Housley, David A. Hafler
Alexander Marson, … , William J. Housley, David A. Hafler
Published June 1, 2015
Citation Information: J Clin Invest. 2015;125(6):2234-2241. https://doi.org/10.1172/JCI78086.
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Genetic basis of autoimmunity

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Abstract

Autoimmune diseases affect up to approximately 10% of the population. While rare Mendelian autoimmunity syndromes can result from monogenic mutations disrupting essential mechanisms of central and peripheral tolerance, more common human autoimmune diseases are complex disorders that arise from the interaction between polygenic risk factors and environmental factors. Although the risk attributable to most individual nucleotide variants is modest, genome-wide association studies (GWAS) have the potential to provide an unbiased view of biological pathways that drive human autoimmune diseases. Interpretation of GWAS requires integration of multiple genomic datasets including dense genotyping, cis-regulatory maps of primary immune cells, and genotyped studies of gene expression in relevant cell types and cellular conditions. Improved understanding of the genetic basis of autoimmunity may lead to a more sophisticated understanding of underlying cellular phenotypes and, eventually, novel diagnostics and targeted therapies.

Authors

Alexander Marson, William J. Housley, David A. Hafler

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Figure 1

Moving from GWAS loci to cellular pathways.

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Moving from GWAS loci to cellular pathways.
The causal SNPs that contrib...
The causal SNPs that contribute to autoimmune disease risk are often inherited along with neighboring neutral SNPs as a result of linkage disequilibrium. The index SNPs that are genotyped and associated with disease risk in GWAS implicate genomic loci — linkage disequilibrium blocks — composed of multiple linked SNPs (gray boxes). GWAS loci associated with autoimmune disease are enriched in genes (rectangles) that are preferentially expressed in particular immune cell subsets (autoimmune disease cell signatures; bottom left) (38) and encode proteins (circles) that participate in a disproportionate number of direct and indirect physical interactions to form biological pathways (autoimmune disease pathways; bottom right) (41). Expression patterns and protein interaction network analysis have been used to triage candidate genes within linkage disequilibrium blocks. These analyses also suggest pathogenic cell types, protein complexes, and pathways that are affected by disease variants, which begins to elucidate the biology underlying complex autoimmune diseases and could direct drug discovery efforts. Adapted with permission from American Journal of Human Genetics (38) and PLoS Genetics (41).
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