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Background
Patients suffering from polycystic ovary syndrome (PCOS) are often insulin resistant and at elevated risk for developing gestational diabetes mellitus (GDM). The aim of this study was to explore afamin, which can be determined preconceptionally to indicate patients who will subsequently develop GDM. Serum concentrations of afamin are altered in conditions of oxidative stress like insulin resistance (IR) and correlate with the gold standard of IR determination, the HOMA index.
Methods
Afamin serum concentrations and the HOMA index were analyzed post hoc in 63 PCOS patients with live births. Patients were treated at Essen University Hospital, Germany, between 2009 and 2018. Mann–Whitney U test, T test, Spearman’s correlation, linear regression models and receiver-operating characteristic (ROC) analyses were performed for statistical analysis.
Results
Patients who developed GDM showed significantly higher HOMA and serum afamin values before their pregnancy (P < 0.001, respectively). ROCs for afamin concentrations showed an area under the curve of 0.78 (95% confidence interval (CI) 0.65–0.90) and of 0.77 (95% CI 0.64–0.89) for the HOMA index. An afamin threshold of 88.6 mg/L distinguished between women who will develop GDM and those who will not with a sensitivity of 79.3% and a specificity of 79.4%. A HOMA index of 2.5 showed a sensitivity of 65.5% and a specificity of 88.2%.
Conclusion
The HOMA index and its surrogate parameter afamin are able to identify pre-pregnant PCOS patients who are at risk to develop GDM. Serum afamin concentrations are independent of fasting status and therefore an easily determinable biomarker.
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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 (GESTSH_2013 and GESTSH_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, GESTSH and TSH were quantified using sex- and age-adjusted linear regression models. Interactions between SEP indicators and GESTSH were assessed by GESTSH × 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 GESTSH_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 GESTSH_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 GESTSH_2013 SD. No indication for interaction was observed for using income as SEP indicator. Using the GESTSH_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.
