Functional Insights into Hypothyroidism Etiology through Complementary Genetic Association Methods

Abstract

Abstract Background Hypothyroidism is a common endocrine disorder that increases with age. The disease manifests itself when the thyroid gland fails to produce sufficient thyroid hormones. The disorder includes cases of congenital hypothyroidism (CH) due to thyroid development abnormalities. However, the majority of cases in the developed world derive from dysregulation of the hormonal feedback of the pituitary gland and the destruction of the thyroid gland by autoantibodies. In this study, we sought to identify hypothyroidism causal genes by applying a diverse collection of genome association studies to large populations. Methods The study used the UK-Biobank (UKB) database to report 13,687 cases of European ancestry and approximately 260,000 controls. To identify the associated variants, GWAS and coding-GWAS protocols were used. In addition, applying the complementary genetic association methods of PWAS (proteome-based) and TWAS (transcriptome-based) revealed hypothyroidism-associated genes. The prevalence among the affected population was 7.5% and 2.0% for the female and male groups, respectively. We further developed a risk prediction model through sex stratification. Results Comparing GWAS summary statistics revealed the CH developmental program. The gene-based PWAS method identified 77 statistically significant genes. Most of these genes are located within the Chr6 MHC locus and are enriched with autoimmunity-related genes. Comparing GWAS and TWAS revealed multiple facets of the etiology of hypothyroidism. Most notably, thyroid developmental programs and dysregulation of hormone secretion capacity in the thyroid. Despite a 3.6-fold higher prevalence in females relative to males for hypothyroidism, using a permutation approach, we found no sex-dependent genetic effect, with 98% of the associated genes being identical between the sexes. The prediction of the polygenic risk score (PRS) for hypothyroidism is mostly derived from the female affected group. Conclusions This study highlights the importance of synthesizing complementary genome-wide association methods for this complex disease. We conclude that the integration of established association methods can improve interpretability and clinical utility.