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Review
. 2012 Jul;34(4):567-80.
doi: 10.1007/s00281-012-0312-1. Epub 2012 May 14.

From genome-wide association studies to disease mechanisms: celiac disease as a model for autoimmune diseases

Vinod Kumar  1 , Cisca Wijmenga, Sebo Withoff
Affiliations
Review

From genome-wide association studies to disease mechanisms: celiac disease as a model for autoimmune diseases

Vinod Kumar et al. Semin Immunopathol. 2012 Jul.

Abstract

Celiac disease is characterized by a chronic inflammatory reaction in the intestine and is triggered by gluten, a constituent derived from grains which is present in the common daily diet in the Western world. Despite decades of research, the mechanisms behind celiac disease etiology are still not fully understood, although it is clear that both genetic and environmental factors are involved. To improve the understanding of the disease, the genetic component has been extensively studied by genome-wide association studies. These have uncovered a wealth of information that still needs further investigation to clarify its importance. In this review, we summarize and discuss the results of the genetic studies in celiac disease, focusing on the "non-HLA" genes. We also present novel approaches to identifying the causal variants in complex susceptibility loci and disease mechanisms.

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Figures

Fig. 1
Fig. 1
Overview of the celiac disease loci. a Manhattan plot showing the CD susceptibility loci identified by Immunochip. The x-axis displays the − log10 P values and the y-axis displays the chromosomes. Candidate genes from 39 loci are shown in the first text column. At three loci (IRAK1, SH2B3, and MMEL1), the most significant SNPs at each locus are in absolute linkage with coding variants. Next, the odds ratios (OR) of all CD SNPs are displayed. In the last column 28 CD loci are also shown to be susceptibility regions for other autoimmune diseases (the shared disease associations are extracted from the GWAS catalogue (www.genome.gov/gwastudies)). AA alopecia areata, AID autoimmune disease, ASP ankylosing spondylitis, CrD Crohn’s disease, IBD inflammatory bowel disease, MS multiple sclerosis, PBC primary biliary cirrhosis, PSO psoriasis, RA rheumatoid arthritis, SLE systemic lupus erythematosus, T1D type I diabetes, UC ulcerative colitis, VL vitiligo. b Odds ratios (OR) and cumulative heritability associated with each locus. Along the x-axis all the CD risk loci are arranged according to decreasing OR. Multiple independent signals at one locus are depicted as “gene name”_2 or “gene name”_3 (e.g., SOCS1_1, SOCS1_2, and SOCS1_3 indicate three independent signals at the SOCS1 locus). We assumed a CD heritability of 89 % [75] and CD prevalence of 1.5 % to estimate the cumulative heritability explained. The OR of 12 for HLA [74] and the ORs of the non-HLA CD loci [24] were published previously
Fig. 2
Fig. 2
History of celiac disease genetics. The final Immunochip analysis increased the number of independent non-HLA CD susceptibility SNPs to 57 (see text for further details)
Fig. 3
Fig. 3
Location and effect of CD risk SNPs. a Genomic location of the SNPs. Proxy SNPs (R 2 > 0.8) for 57 CD top SNPs were extracted using the 1000 Genomes Project CEU population. Only three (5 %) of the 57 SNPs were in linkage with coding variants. About 5 and 9 % are located in the 5’-UTR and the 3’-UTR regions, respectively. This leaves 81 % of the variants to be located in non-coding regions of the genome (intergenic or intronic). The latter SNPs could be involved in the regulation of gene expression or they could affect non-coding RNA species. b Expression quantitative trait loci (eQTL) analysis at SNP rs917997. The figure shows the association of the risk genotype with a lower expression of IL18RAP (P = 1.1 × 10−133). The left panel displays the distribution of the normalized expression levels of IL18RAP mRNA according to the genotypes at rs917997. The blue and orange dots indicate samples from male and female volunteers, respectively. The right panel displays the foldchange in the levels of IL18RAP mRNA.
Fig. 4
Fig. 4
Co-expression analysis to predict the function of PTPRK gene. The left panel lists the genes showing co-expression with PTPRK in at least 15 different microarray datasets (extracted from the GEMMA co-expression database) and depicts the presence of interactions between those genes. The width of the lines represents the number of datasets (ranging from 15 to 25) containing evidence for the interaction. The right panel displays the results of an enrichment analysis performed on the PTPRK co-expressed genes, using the MetaCore GeneGo tool (see text). The x-axis displays significance for each of the biological processes plotted on the y-axis
Fig. 5
Fig. 5
Immune cell types implied to be involved in celiac disease by pathway analyses. Gluten molecules, the environmental trigger of CD, are degraded into gliadins which in turn are modified by tissue transglutaminase (tTG) into deamidated gliadin (da-Gliadin). The latter peptides are presented to the immune system, resulting in activation of various immune cell types (according to pathway analyses, see text). For a more detailed description of the genes involved in these processes, see the text and reviews by Trynka et al. [14] and Abadie et al. [67]. Abs, antibodies; FASLG, FAS ligand; ICOSLG, ICOS ligand; IEL, intra-epithelial lymphocytes
Fig. 6
Fig. 6
Summary of strategies to identify causal variants and disease mechanisms. GWAS association signals can be followed up by meta-analysis and/or fine-mapping to identify specific causal variants. Pathway and eQTL analyses can be applied to prioritize the causative genes and to generate hypotheses to explain the biological link between a causal gene and disease. Identified causal variants and genes can in turn be followed up by experiments by, for instance, ex vivo stimulation experiments using human or animal immune cells or by experiments with inflammation models in whole animals
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