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Modification of TSH-related genetic effects by indicators of socioeconomic position

OBJECTIVE: Thyroid-stimulating hormone (TSH) is influenced by genetic and environmental factors such as socioeconomic position (SEP). However, interactions between TSH-related genetic factors and indicators of SEP have not been investigated to date. The aim of the study was to determine whether educ...

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Detalles Bibliográficos
Autores principales: Drogge, Sophie-Charlotte, Frank, Mirjam, Girschik, Carolin, Jöckel, Karl-Heinz, Führer-Sakel, Dagmar, Schmidt, Börge
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Bioscientifica Ltd 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9874972/
https://www.ncbi.nlm.nih.gov/pubmed/36547002
http://dx.doi.org/10.1530/EC-22-0127
Descripción
Sumario:OBJECTIVE: Thyroid-stimulating hormone (TSH) is influenced by genetic and environmental factors such as socioeconomic position (SEP). However, interactions between TSH-related genetic factors and indicators of SEP have not been investigated to date. The aim of the study was to determine whether education and income as SEP indicators may interact with TSH-related genetic effect allele sum scores (GES(TSH_2013) and GES(TSH_2020)) based on two different GWAS meta-analyses that affect TSH values in a population-based study. METHODS: In 4085 participants of the Heinz Nixdorf Recall Study associations between SEP indicators, GES(TSH) and TSH were quantified using sex- and age-adjusted linear regression models. Interactions between SEP indicators and GES(TSH) were assessed by GES(TSH) × SEP interaction terms, single reference joint effects and calculating genetic effects stratified by SEP group. RESULTS: Participants within the highest education group showed the strongest genetic effect with on average 1.109-fold (95% CI: 1.067–1.155) higher TSH values per GES(TSH_2013) SD, while in the lowest education group, the genetic effect was less strong (1.061-fold (95% CI: 1.022–1.103)). In linear regression models including interaction terms, some weak indication for a positive GES(TSH_2013) by education interaction was observed showing an interaction effect size estimate of 1.005 (95% CI: 1.000–1.010) per year of education and GES(TSH_2013) SD. No indication for interaction was observed for using income as SEP indicator. Using the GES(TSH_2020,) similar results were observed. CONCLUSION: Our results gave some indication that education may affect the expression of TSH-related genetic effects. Stronger genetic effects in high-education groups may be explained by environmental factors that have an impact on gene expression and are more prevalent in high SEP groups.