The antigenic link between thyroid autoimmunity and breast cancer.

BACKGROUND With several susceptibility single nucleotide polymorphisms identified by case-control association studies, Graves' disease is one of the most common forms of autoimmune thyroid disease. In this study, we aimed to determine whether any observed differences in genetic associations are influenced by sex in Chinese Han populations. METHODS A total of 8,835 patients with Graves' disease and 9,936 sex-matched healthy controls were enrolled in the study. Confirmed by a two-staged association analysis, sex-specific analyses among 20 Graves' disease susceptibility loci were conducted. RESULTS A significant sex-gene interaction was detected primarily at rs5912838 on Xq21.1 between the GPR174 and ITM2A genes, whereby male Graves' disease patients possessed a significantly higher frequency of risk alleles than their female counterparts. Interestingly, compared to women, male patients with Graves' disease had a higher cumulative genetic risk and higher persistent thyroid stimulating hormone receptor antibody-positive rate after receiving antithyroid drug therapy for at least 1 year. CONCLUSION The findings of this study suggest the existence of one potential sex-specific Graves' disease variant on Xq21.1. This could increase our understanding of the pivotal mechanism behind Graves' disease and ultimately aid in identifying possible therapeutic targets.

Candidate gene associations reveal sex-specific Graves' disease risk alleles among Chinese Han populations.

Autoimmune Addison's disease (AAD) is the most common cause of primary adrenal insufficiency (PAI). Despite its exceptionally high heritability, tools to estimate disease susceptibility in individual patients are lacking. We hypothesized that polygenic risk score (PRS) for AAD could help investigate PAI pathogenesis in pediatric patients.

https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/joim.13649

A polygenic risk score to help discriminate primary adrenal insufficiency of different etiologies

CONTEXT Graves disease (GD) is a common thyroid-specific autoimmune disease and one of the most heritable diseases in the population. We present a risk-prediction model, including confirmed, known genetic variants associated with GD. DESIGN To construct a stable-prediction model, we used known GD susceptibility single nucleotide polymorphisms (SNPs) as markers and trained and tested our model in a cohort of 4897 patients with GD and 5098 healthy controls. We weighted the contribution of each SNP to the disease to calculate the weighted genetic risk score (wGRS) for each individual. The efficiency of this model can be estimated by the area under the curve (AUC) receiver operator characteristic curve and the specificity and sensitivity of each wGRS. RESULTS With the 20 confirmed GD risk-related SNPs, our wGRS-prediction model could predict patients with GD from the general population (AUC 0.70 [95% CI: 0.69 to 0.71]) and did especially well in predicting patients with GD with persisting thyroid-stimulating hormone receptor antibody positive [pTRAb+; AUC 0.74 (95% CI: 0.72 to 0.76)]. We also evaluated how the four pTRAb+ specific risk SNPs predicted patients with GD with pTRAb+ among all patients with GD [AUC 0.62 (95% CI: 0.61 to 0.63)]. For clinical use, we partitioned subjects in each set into different risk categories to generate the wGRS cutoff of high risk for reference. CONCLUSIONS Our study provides an approach to predict GD risk in the general population by the calculation of the wGRS of 20 known GD susceptibility variants. The wGRS-prediction model was more stable and convenient, whereas the prediction performance was still modest.

/pdf/a-weighted-genetic-risk-score-using-known-susceptibility-2j702e8xzb.pdf

A Weighted Genetic Risk Score Using Known Susceptibility Variants to Predict Graves Disease Risk.

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A Weighted Genetic Risk Score Using Known Susceptibility Variants to Predict Graves Disease Risk.