Celiac Disease Genetics: Current Concepts and Practical Applications
Celiac disease is a multifactorial disease with complex genetics. Both HLA and non-HLA genes contribute to the genetic component, but recent findings suggest that the importance of non-HLA genes might have been overestimated. No susceptibility genes other than HLA-DQ have yet been identified in celiac disease. In contrast to the meager knowledge regarding non-HLA genes, we have acquired a detailed understanding about which HLA genes are predisposing for disease, and how they are involved in the pathogenesis. This knowledge might pave the road for novel treatments for the disease. The role of HLA as a necessary, but not sufficient, genetic factor can moreover be used for diagnostic purposes to exclude a celiac disease diagnosis. The applicability of HLA genotyping is particularly useful for excluding celiac disease in family members or risk groups with fairly unbiased distribution of HLA alleles (ie, patients with Turner syndrome and patients with Down syndrome) and in patients with a clinical suspicion of celiac disease.
[Show abstract] [Hide abstract] ABSTRACT: The “four out of five rule” has not been officially endorsed by official guidelines. However, HLA-associated genes that predispose to CD are found in as much as 30–40% of healthy people. Thus, their presence seems too indecisive for the occurrence of CD.
- "Estimation of the degree of genetic risk for CD associated with specific HLA-DQ2/DQ8 genotypes is possible (Table 1). Absence of any CD-associated HLA alleles can exclude the diagnosis of CD . There is no difference in severity of CD among patients with HLA DQ2 genotype and those with HLA DQ8 genotype. "
[Show abstract] [Hide abstract] ABSTRACT: Although sarcoidosis and celiac disease are both chronic immunologic disorders involving multiple organ systems, reports about association of diseases in individual patients are sparse. While sarcoidosis is a chronic granulomatous disease presumably reflecting an exaggerated response to an unknown antigen, celiac disease is a T cell-driven disease triggered by ingestion of gluten, a protein composite found in wheat and related grains. We present three cases with a longstanding history of sarcoidosis that have been additionally diagnosed with celiac-like enteropathy. In two cases, celiac disease was established applying celiac-specific serology and duodenal histology, while one case was revealed as an AIE-75-positive autoimmune enteropathy. The HLA-DR3/DQ2 haplotype was confirmed in both celiac patients, hence confirming previous data of linkage disequilibrium as a cause for disease association. Remarkably, one celiac patient presented with granulomatous nodulae in the ileum, thus reflecting an intestinal sarcoid manifestation. In contrast the patient with an autoimmune enteropathy, was HLA-DQ9/DQ6-positive, also arguing against CD. Associations of sarcoidosis and celiac disease are rare but do occur. Determining the HLA status in patients with complex autoimmune associations might help classifying involved disease entities.
- "A large body of evidence links distinct HLA variants to either sarcoidosis or CD. In the latter, the HLA-DQ locus appears to have the biggest impact on disease development with the majority of patients carrying a variant of HLA-DQ2 (DQA1*05/DQB1*02) and only 5 % carrying HLA-DQ8  . On the other hand, the HLA- DR3, −DR11, −DR12, −DR14, and -DR15 alleles are established risk factors for sarcoidosis with the HLA- DR3 haplotype being typically associated with Löfgren's syndrome . "
[Show abstract] [Hide abstract] ABSTRACT: Genomic prediction aims to leverage genome-wide genetic data towards better disease diagnostics and risk scores. We have previously published a genomic risk score (GRS) for celiac disease (CD), a common and highly heritable autoimmune disease, which differentiates between CD cases and population-based controls at a clinically-relevant predictive level, improving upon other gene-based approaches. HLA risk haplotypes, particularly HLA-DQ2.5, are necessary but not sufficient for CD, with at least one HLA risk haplotype present in up to half of most Caucasian populations. Here, we assess a genomic prediction strategy that specifically targets this common genetic susceptibility subtype, utilizing a supervised learning procedure for CD that leverages known HLA-DQ2.5 risk. Using L1/L2-regularized support-vector machines trained on large European case-control datasets, we constructed novel CD GRSs specific to individuals with HLA-DQ2.5 risk haplotypes (GRS-DQ2.5) and compared them with the predictive power of the existing CD GRS (GRS14) as well as two haplotype-based approaches, externally validating the results in a North American case-control study. Consistent with previous observations, both the existing GRS14 and the GRS-DQ2.5 had better predictive performance than the HLA haplotype approaches. GRS-DQ2.5 models, based on directly genotyped or imputed markers, achieved similar levels of predictive performance (AUC = 0.718-0.73), which were substantially higher than those obtained from the DQ2.5 zygosity alone (AUC = 0.558), the HLA risk haplotype method (AUC = 0.634), or the generic GRS14 (AUC = 0.679). In a screening model of at-risk individuals, the GRS-DQ2.5 lowered the number of unnecessary follow-up tests for CD across most sensitivity levels. Relative to a baseline implicating all DQ2.5-positive individuals for follow-up, the GRS-DQ2.5 resulted in a net saving of 2.2 unnecessary follow-up tests for each justified test while still capturing 90 % of DQ2.5-positive CD cases. Genomic risk scores for CD that target genetically at-risk sub-groups improve predictive performance beyond traditional approaches and may represent a useful strategy for prioritizing individuals at increased risk of disease, thus potentially reducing unnecessary follow-up diagnostic tests.
- "Unlike the sensitivity and specificity, this ratio depends on the true prevalence of CD in the population being tested (here, all DQ2.5+ individuals). People at high risk of CD, for instance, due to a family history of the illness, have a 10 % prevalence of disease . Therefore for this modeling we likewise assumed a prevalence of 10 %, leading to a baseline ratio of 9:1 (equivalent to all DQ2.5-positive individuals being recommended for follow-up testing). "