{"title":"Free triiodothyronine and risk of gestational diabetes mellitus: an observational study and Mendelian randomization analysis.","authors":"Yanan Li, Shuai Yang, Zixuan Huang, Yong Zhang, Haixia Guan, Jianxia Fan","doi":"10.1186/s12986-025-00905-4","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Free triiodothyronine (FT3) exerts a significant influence on glucose metabolism. The relationship between gestational diabetes mellitus (GDM) and FT3 during pregnancy is complex and inconsistently reported. Our study aims to explore the bidirectional association between FT3 during pregnancy and GDM, and to assess whether this association is causal.</p><p><strong>Methods: </strong>The observational analysis included two clinical studies. Study 1 involved 6,221 pregnant women and applied multivariate logistic regression analysis to investigate the association between FT3 in early pregnancy and the subsequent risk of GDM. Study 2 comprised 387 pregnant women and employed linear regression analysis to examine the impact of GDM on FT3 in late pregnancy. Additionally, genome-wide association study (GWAS) summary statistics of FT3 and GDM were used to perform a bidirectional two-sample Mendelian randomization (MR) analysis to test for causal associations.</p><p><strong>Results: </strong>In Study 1, after adjusting for potential confounding factors, increased FT3 levels in early pregnancy were associated with the subsequent risk of GDM [odds ratio (OR) 1.122; 95% confidence interval (CI) 1.004, 1.255; P = 0.043], and the restricted cubic spline analysis indicated a linear association (P for nonlinearity = 0.72). In Study 2, we didn't find association between GDM and FT3 levels in late pregnancy. MR analysis found a positive causal relationship of genetically predicted FT3 on the risk of GDM (OR 1.26; 95% CI 1.01, 1.57; P = 0.041), while in the reverse MR, there was no significant relationship of GDM on FT3. In addition, the sensitivity analysis illustrated the robustness of our MR results.</p><p><strong>Conclusions: </strong>FT3 levels in early pregnancy were positively associated with the risk of GDM, and MR analysis provided evidence supporting a causal relationship. However, future studies are required to further investigate this association through larger-scale GWAS in diverse ethnic populations and to explore the underlying biological mechanisms.</p>","PeriodicalId":19196,"journal":{"name":"Nutrition & Metabolism","volume":"22 1","pages":"17"},"PeriodicalIF":3.9000,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11866897/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nutrition & Metabolism","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12986-025-00905-4","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"NUTRITION & DIETETICS","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Free triiodothyronine (FT3) exerts a significant influence on glucose metabolism. The relationship between gestational diabetes mellitus (GDM) and FT3 during pregnancy is complex and inconsistently reported. Our study aims to explore the bidirectional association between FT3 during pregnancy and GDM, and to assess whether this association is causal.
Methods: The observational analysis included two clinical studies. Study 1 involved 6,221 pregnant women and applied multivariate logistic regression analysis to investigate the association between FT3 in early pregnancy and the subsequent risk of GDM. Study 2 comprised 387 pregnant women and employed linear regression analysis to examine the impact of GDM on FT3 in late pregnancy. Additionally, genome-wide association study (GWAS) summary statistics of FT3 and GDM were used to perform a bidirectional two-sample Mendelian randomization (MR) analysis to test for causal associations.
Results: In Study 1, after adjusting for potential confounding factors, increased FT3 levels in early pregnancy were associated with the subsequent risk of GDM [odds ratio (OR) 1.122; 95% confidence interval (CI) 1.004, 1.255; P = 0.043], and the restricted cubic spline analysis indicated a linear association (P for nonlinearity = 0.72). In Study 2, we didn't find association between GDM and FT3 levels in late pregnancy. MR analysis found a positive causal relationship of genetically predicted FT3 on the risk of GDM (OR 1.26; 95% CI 1.01, 1.57; P = 0.041), while in the reverse MR, there was no significant relationship of GDM on FT3. In addition, the sensitivity analysis illustrated the robustness of our MR results.
Conclusions: FT3 levels in early pregnancy were positively associated with the risk of GDM, and MR analysis provided evidence supporting a causal relationship. However, future studies are required to further investigate this association through larger-scale GWAS in diverse ethnic populations and to explore the underlying biological mechanisms.
期刊介绍:
Nutrition & Metabolism publishes studies with a clear focus on nutrition and metabolism with applications ranging from nutrition needs, exercise physiology, clinical and population studies, as well as the underlying mechanisms in these aspects.
The areas of interest for Nutrition & Metabolism encompass studies in molecular nutrition in the context of obesity, diabetes, lipedemias, metabolic syndrome and exercise physiology. Manuscripts related to molecular, cellular and human metabolism, nutrient sensing and nutrient–gene interactions are also in interest, as are submissions that have employed new and innovative strategies like metabolomics/lipidomics or other omic-based biomarkers to predict nutritional status and metabolic diseases.
Key areas we wish to encourage submissions from include:
-how diet and specific nutrients interact with genes, proteins or metabolites to influence metabolic phenotypes and disease outcomes;
-the role of epigenetic factors and the microbiome in the pathogenesis of metabolic diseases and their influence on metabolic responses to diet and food components;
-how diet and other environmental factors affect epigenetics and microbiota; the extent to which genetic and nongenetic factors modify personal metabolic responses to diet and food compositions and the mechanisms involved;
-how specific biologic networks and nutrient sensing mechanisms attribute to metabolic variability.