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GWAS Meta-Analysis Supports Existence of Autoimmune Disease Clusters

NEW YORK (GenomeWeb News) – A new paper in PLoS Genetics today suggests the same genetic variants that increase an individual's risk for one set of autoimmune diseases may actually make them less susceptible to others.

Researchers from Stanford University and collaborators at a California hospital and clinical center did a meta-analysis of genome-wide association studies on half a dozen autoimmune conditions, including type 1 diabetes and rheumatoid arthritis. They found a pattern in which specific diseases grouped together based on SNP data, with variants that increased the risk of some conditions protecting against others.

Based on these findings, the team suggests it may be useful to classify autoimmune diseases according to their shared genetic factors rather than considering them a single group.

"Maybe we should stop considering all autoimmune diseases in one lumped category," senior author Atul Butte, a pediatric and bioinformatics researcher at Stanford University and director of the Lucile Packard Children's Hospital's Center for Pediatric Bioinformatics, said in a statement. "It looks as if there may be at least two different kinds."

Although autoimmune diseases share some common disease mechanisms, Butte and his team noted, certain autoimmune diseases have more in common than others. For example, past research suggests that individuals with type 1 diabetes are at increased risk for autoimmune diseases such as autoimmune thyroid disease, multiple sclerosis, and celiac disease.

And, they added, at least one SNP has already been shown to have opposing effects in different autoimmune conditions: the G allele of that SNP, called rs2076530, is more common in individuals with type 1 diabetes or rheumatoid arthritis whereas the A allele is more common in those with systematic lupus erythematosus.

That led Butte and his colleagues to speculate about how genetic factors relate to autoimmune disease clusters. In the current paper, the team did a meta-analysis involving 573 SNPs assessed in several GWAS of six autoimmune diseases — type 1 diabetes, rheumatoid arthritis, Crohn's disease, multiple sclerosis, autoimmune thyroid disease, and ankylosing spondylitis — and five non-autoimmune diseases.

By assessing alleles associated with each disease and the strength of these associations, the team came up with a so-called "genetic variation score" to evaluate ties between specific alleles and diseases across different genotyping platforms.

Of the nearly 600 SNPs evaluated, the team found nine SNPs for which one allele appears to increase an individual's risk of multiple sclerosis and autoimmune thyroid disease but decrease his or her risk of rheumatoid arthritis and ankylosing spondylitis. The alternative alleles for these SNPs, meanwhile, have the opposite effect.

"What was surprising was our finding that at nine locations generally associated with autoimmunity risk, where a particular chemical unit conferred a heightened risk of certain autoimmune diseases, but reduced risk of getting certain others," lead author Marina Sirota, a graduate student in Butte's Stanford University lab, said in a statement.

Based on their analyses, the researchers suggest autoimmune diseases fall into at least two different groups: one containing rheumatoid arthritis and ankylosing spondylitis and another containing multiple sclerosis and autoimmune thyroid disease.

Meanwhile, they reported, type 1 diabetes resembled both of the groups to a certain extent, sharing characteristics with autoimmune thyroid disease but not multiple sclerosis. Crohn's disease, on the other hand, did not cluster with either group.

In the future, the team hopes that the findings contribute not only to a better understanding of the biological pathways involved in these autoimmune diseases, but also give researchers a better sense of how to apply existing therapies — and come up with new ones.

"Several of these nine interesting SNPs we've found are located in or near genes that code for molecules found on cell surfaces," Butte said, "which makes them potentially easier targets for the drugs pharmaceutical researchers are best at producing."

And, Butte and his co-workers explained, the repertoire of SNPs involved will likely increase as additional autoimmune disease GWAS turn up new genetic variants involved in these — and other — diseases.

"As more genomic information becomes available on increasingly advanced platforms, this sort of analysis can be done on more diseases, possibly hundreds of them," Sirota said.

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