Genetic susceptibility to autoimmune thyroid disease: past, present, and future

Abstract

Background: Autoimmune thyroid diseases (AITD), including Graves' disease and Hashimoto's thyroiditis, arise due to complex interactions between environmental and genetic factors. There are sound data coming from epidemiological, family, and twin studies demonstrating a strong genetic influence on the development of AITD. In this review we summarize the new findings on the genetic susceptibility to AITD focusing on emerging mechanisms of susceptibility.

Summary: Candidate gene analysis, whole-genome linkage screening, genome-wide association studies, and whole-genome sequencing are the major technologies that have advanced this field, leading to the identification of at least seven genes whose variants have been associated with AITD. One of the major ones is the HLA-DR gene locus. Recently, it was shown that substitution of the neutral amino acids Ala or Gln with arginine at position beta 74 in the HLA-DR peptide-binding pocket is key to the etiology of both Graves' disease and Hashimoto's thyroiditis. Several other genes have also been shown to confer susceptibility to AITD. These can be classified into two groups: (i) immune regulatory genes (cytotoxic T lymphocyte-associated protein 4, CD40, protein tyrosine phosphatase-22, and CD25) and (ii) thyroid-specific genes (thyroglobulin and thyrotropin receptor genes). The influence of individual genes on the development of AITD when assessed in a population appears to be weaker than would be expected from the data showing strong genetic susceptibility to AITD. Two possible mechanisms explaining this discrepancy are gene-gene interactions and subset effects.

Conclusions: Significant progress has been made in our understanding of the immunogenetic mechanisms leading to thyroid autoimmunity. For the first time we are beginning to unravel these mechanisms at the molecular level. It is hoped that these new data will be translated into novel therapies and prevention strategies in AITD, such as costimulatory blockade.

FIG. 1.

This figure illustrates the inherent paradox with the dogma that numerous genes with small effect can cause an additive strong genetic effect on susceptibility to disease. We simulated five genetic variants predisposing to autoimmune thyroid diseases, each giving an odds ratio (OR) of 1.2 individually. Therefore, the combined OR if an individual inherited all five variants, assuming an additive effect is 1.2 × 1.2 × 1.2 × 1.2 × 1.2 = 2.5. However, the calculated frequency in the population of the combined genotype including all five susceptible variants (assuming no linkage disequilibrium exists between them), assuming the frequency of each variant alone is 0.2 (20%) would be 0.2 × 0.2 × 0.2 × 0.2 × 0.2 = 0.00032 or 0.032%. Such a low frequency of the combined genotype is not consistent with the strong genetic influence on highly prevalent complex diseases, such as autoimmune thyroid diseases.

FIG. 2.

The model of subset effects or genetic heterogeneity. To simulate the effects of subsets we simulated a dataset of Graves' patients in which four genetic subsets exist: Subset 1 was assumed to comprise 15% of the total Graves' disease (GD) population; subset 2, 35%; subset 3, 30%; and subset 4, 20%. Each subset is simulated to be influenced by one gene. We simulated the relative risks of the subset-specific genes as follows: Gene 1 was assumed to have a relative risk (RR) of 2.0 for GD in subset 1; gene 2 was assumed to have an RR of 2.5 in subset 2; gene 3 was assumed to have an RR of 3.5 in subset 3; gene 4 was assumed to have an RR of 3.0 in subset 4. Using the assumed percent of the population belonging to each GD subset and the assumed relative risks contributed by each subset-specific gene, we calculated the relative risk contributed by the gene when testing the entire population of GD patients. The results showed that the relative risks decreased significantly when testing the gene in the entire dataset of GD patients; that is, the effect of the gene is diluted and the relative risk is reduced when the gene is tested in the entire GD population, most of which are not influenced by this gene.