The genetics of human autoimmune disease: A perspective on progress in the field and future directions

Abstract

Progress in defining the genetics of autoimmune disease has been dramatically enhanced by large scale genetic studies. Genome-wide approaches, examining hundreds or for some diseases thousands of cases and controls, have been implemented using high throughput genotyping and appropriate algorithms to provide a wealth of data over the last decade. These studies have identified hundreds of non-HLA loci as well as further defining HLA variations that predispose to different autoimmune diseases. These studies to identify genetic risk loci are also complemented by progress in gene expression studies including definition of expression quantitative trait loci (eQTL), various alterations in chromatin structure including histone marks, DNase I sensitivity, repressed chromatin regions as well as transcript factor binding sites. Integration of this information can partially explain why particular variations can alter proclivity to autoimmune phenotypes. Despite our incomplete knowledge base with only partial definition of hereditary factors and possible functional connections, this progress has and will continue to facilitate a better understanding of critical pathways and critical changes in immunoregulation. Advances in defining and understanding functional variants potentially can lead to both novel therapeutics and personalized medicine in which therapeutic approaches are chosen based on particular molecular phenotypes and genomic alterations.

Keywords: Autoimmune diseases; Functional variants; Genetics; HLA; Immunoregulation; Susceptibility loci.

Figure 1

Diagram of general scheme for genetic studies of complex autoimmune diseases. GWAS studies can greatly benefit from imputation and replication studies for loci discovered in the discovery phase. For some studies replication studies are limited to those loci (genes) that are also part of pathways for genes identified as significantly associated with the disease in previous studies. This is also proposed for sequencing studies to identify less common variants in which power issues may be partially addressed by limiting replication analyses based on pathway information.

Figure 2

Comparison of effect size for gene associated SNPs in multiple different autoimmune diseases. Disease abbreviations that are not clear from the main text include: asthma (ASTH), Crohn’s disease (CRD), celiac disease (CEL) and psoriasis (PSOR). Asthma is included for comparison of autoimmune conditions with another immunologically mediated disease. The approximate odds ratios (ORs) are indicated by the color code legend and for each the OR is indicated in the positive direction (regardless of minor allele frequency). Horizontal or vertical lines are shown over the color coded ORs when the opposite SNP/haplotype is associated with different diseases (e.g. for the IKZF3 etc. in which the asthma association is clearly the opposite of those for PBC and SLE. The ORs are derived from studies of European ancestry subject sets and are preferentially chosen from larger studies or meta-analyses [26, 48, 54, 56, 57, 59-61, 94, 142, 148, 163-173]. For some of the genes for which the legend key indicates no association or not known (NA or NK) there may be limited data that suggests possible association that does not meet the standard criterion (p < 5 ×10⁻⁸). Where different SNPs show disparate ORs the association the highest OR is shown. The gene list was selected based on inclusion of most genes with at least moderate ORs (OR> 1.1) in at least one of the autoimmune diseases and is in part biased to emphasize the differences in effect sizes. IKZF3 etc represents a gene cluster that includes IKZF3, ORMDL3, ZPBP2, and GSDMB. CD58 etc. represents a gene cluster including CD58, CD2, and IGSF2.

Figure 3

Comparison of effect sizes for gene polymorphsims in three different population groups in three different autoimmune diseases. The approximate odds ratios (ORs) are indicated by the color code legend and for each the OR is indicated in the positive direction (regardless of minor allele frequency). The ORs were preferentially chosen from larger studies or meta-analyses ([57, 94, 96, 98, 99, 148, 170, 171, 174-179]. The genes selected were chosen on the bases of showing an OR of >1.3 in at least one of the populations chosen. For some of the genes for which the legend key indicates no association or not known (NA or NK) there may be limited data that suggests possible association that does not meet the standard genome-wide criteria for statistical significance.