rs12390237 - PRKX

Magnitude 2.2 · 2 studies on file

Reported associations

  • Uncovering the shared genetic components of thyroid disorders and reproductive health. - European journal of endocrinology (2024) · Figuerêdo J, Krebs K, Pujol-Gualdo N, Haller T, Võsa U, Volke V, Laisk T, Mägi R · PubMed 39067062

    The aim of the study is to map the shared genetic component and relationships between thyroid and reproductive health traits to improve the understanding of the interplay between those domains. A large-scale genetic analysis of thyroid traits (hyper- and hypothyroidism, and thyroid-stimulating hormone levels) was conducted in up to 743 088 individuals of European ancestry from various cohorts. We evaluated genetic associations using genome-wide association study (GWAS) meta-analysis, GWAS Catalog lookup, gene prioritization, mouse phenotype lookup, and genetic correlation analysis. GWAS meta-analysis results for thyroid phenotypes showed that 50 lead variants out of 253 (including 5/52 of the novel hits) were linked to reproductive health in previous literature. Genetic correlation analyse

  • Genome-wide analyses identify a role for SLC17A4 and AADAT in thyroid hormone regulation - Unknown journal (n.d.) · Unknown authors · PubMed 30367059

    ABSTRACT: Thyroid dysfunction is an important public health problem, which affects 10% of the general population and increases the risk of cardiovascular morbidity and mortality. Many aspects of thyroid hormone regulation have only partly been elucidated, including its transport, metabolism, and genetic determinants. Here we report a large meta-analysis of genome-wide association studies for thyroid function and dysfunction, testing 8 million genetic variants in up to 72,167 individuals. One-hundred-and-nine independent genetic variants are associated with these traits. A genetic risk score, calculated to assess their combined effects on clinical end points, shows significant associations with increased risk of both overt (Graves' disease) and subclinical thyroid disease, as well as clin


Auto-generated from study metadata. AI-synthesised commentary is added when this entry is regenerated through content-service's LLM mode.