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Autoimmune diseases develop through the exposure of genetically susceptible hosts to environmental triggers. Advances in high-throughput genotyping and sequencing technologies coupled with comprehensive databases of human genetic variation and the assembly of large cohorts of case and control subjects have led to substantial progress in defining the genetic risk factors that underlie autoimmune diseases (1). The workhorse statistical methodology has been the genome-wide association study (GWAS). Studies using the GWAS approach have convincingly and reproducibly identified ∼700 genomic regions in 183 published studies of autoimmune diseases at the level of genome-wide statistical significance (P < 10−8) (www.genome.gov/gwastudies). The majority of these genetic associations are near genes that map to critical immunoregulatory pathways, illuminating genetic effects that are shared across multiple autoimmune diseases and other genetic effects that are restricted to only a few (1).  GWAS studies detect most causal variants indirectly, by leveraging linkage disequilibrium (LD) throughout the human genome. Classically defined, LD is the nonrandom association of two or more loci, resulting in segments of the genome being inherited as haplotype “blocks.” Knowledge of the allele at one variant predicts with high likelihood the alleles at the other variants on the same haplotype block (2). Though LD makes locus discovery by GWAS very efficient, because only one or two variants per haplotype block need to be genotyped in order to detect association, the high correlation of variants on associated haplotypes confounds the ability of genetic association methods to distinguish causal from noncausal variants. The UBE2L3 locus associated with multiple autoimmune diseases, including systemic lupus erythematosus (SLE) (3), illustrates the problem vividly, where 34 SLE-associated variants are located within a 67-kb haplotype, but we assume that only a few are likely to be causal (3). With a situation such as this, which variants are we to choose for functional screening? No specific guidelines exist on how to answer this question.  In general, the approach to overcoming the LD problem is to first comprehensively understand the genetic architecture at a given locus. Doing this in multiple ethnic populations when possible, adds significant power to our ability to discern causal variants by allowing the comparison of haplotypes across populations. Comprehensive characterization of a locus may include the following activities: 1) locus enrichment—capture for analysis all available genetic variation present on the risk haplotype, 2) locus refinement—winnow down the associated variants within a locus to a prioritized list for functional testing, and 3) functional testing—identify allele-specific differences in biologic function that support the variant’s role(s) in causality. In this review, we discuss each of these steps and describe in more detail the available molecular methods that can provide the functional evidence required to assign causality to variants associated with autoimmune diseases.

Disease Mechanisms in Rheumatology—Tools and Pathways: Defining Functional Genetic Variants in Autoimmune Diseases