Unravelling the Metabolic Underpinnings of Gestational Diabetes Mellitus: A Comprehensive Mendelian Randomisation Analysis Identifying Causal Metabolites and Biological Pathways.

Gestational diabetes mellitus (GDM) has a strong genetic predisposition. Integrating metabolomics with Mendelian randomisation (MR) analysis offers a potent method to uncover the metabolic factors causally linked to GDM pathogenesis. This study aims to identify specific metabolites and metabolic pathways causally associated with GDM susceptibility through a comprehensive MR analysis. Additionally, it seeks to explore the potential of these identified metabolites as circulating biomarkers for early GDM detection and risk assessment. Furthermore, it aims to evaluate the implicated metabolic pathways as potential therapeutic targets for preventive or interventional strategies against GDM. A two-sample MR study was conducted using summary statistics from a metabolite genome-wide association study (GWAS) of 8299 individuals and a GDM GWAS comprising 13,039 cases and 197,831 controls. Rigorous criteria were applied to select robust genetic instruments for 850 metabolites. MR analysis revealed 47 metabolites exhibiting putative causal associations with GDM risk. Among these, five metabolites demonstrated statistically significant associations after multiple-testing correction: Beta-citrylglutamate, Isobutyrylcarnitine (c4), 1,2-dilinoleoyl-GPC (18:2/18:2), Alliin and Cis-3,4-methyleneheptanoylcarnitine. Importantly, all these metabolites exhibited protective effects against GDM development. Additionally, metabolic pathway enrichment analysis implicated the methionine metabolism and spermidine and spermine biosynthesis pathways in the pathogenesis of GDM. This comprehensive MR study has robustly identified specific metabolites and metabolic pathways with causal links to GDM susceptibility. These findings provide novel insights into the metabolic underpinnings of GDM aetiology and offer promising translational implications. The identified metabolites could serve as potential circulating biomarkers for early detection and risk stratification, while the implicated metabolic pathways may represent therapeutic targets for preventive or interventional strategies against GDM.

Shen M ，Shi L ，Xing M ，Jiang H ，Ma Y ，Ma Y ，Zhang L ... -  《-》

Investigating causal associations among gut microbiota, gut microbiota-derived metabolites, and gestational diabetes mellitus: a bidirectional Mendelian randomization study.

Wu X ，Lin D ，Li Q ，Cai J ，Huang H ，Xiang T ，Tan H ... -  《Aging-US》

Mendelian randomization analysis reveals causal effects of blood lipidome on gestational diabetes mellitus.

Observational studies have revealed associations between maternal lipid metabolites and gestational diabetes mellitus (GDM). However, whether these associations are causal remain uncertain. To evaluate the causal relationship between lipid metabolites and GDM. A two-sample Mendelian randomization (MR) analysis was performed based on summary statistics. Sensitivity analyses, validation analyses and reverse MR analyses were conducted to assess the robustness of the MR results. Additionally, a phenome-wide MR (Phe-MR) analysis was performed to evaluate potential side effects of the targeted lipid metabolites. A total of 295 lipid metabolites were included in this study, 29 of them had three or more instrumental variables (IVs) suitable for sensitivity analyses. The ratio of triglycerides to phosphoglycerides (TG_by_PG) was identified as a potential causal biomarker for GDM (inverse variance weighted (IVW) estimate: odds ratio (OR) = 2.147, 95% confidential interval (95% CI) 1.415-3.257, P = 3.26e-4), which was confirmed by validation and reverse MR results. Two other lipid metabolites, palmitoyl sphingomyelin (d18:1/16:0) (PSM(d18:1/16:0)) (IVW estimate: OR = 0.747, 95% CI 0.583-0.956, P = 0.021) and triglycerides in very small very low-density lipoprotein (XS_VLDL_TG) (IVW estimate: OR = 2.948, 95% CI 1.197-5.215, P = 0.015), were identified as suggestive potential biomarkers for GDM using a conventional cut-off P-value of 0.05. Phe-MR results indicated that lowering TG_by_PG had detrimental effects on two diseases but advantageous effects on the other 13 diseases. Genetically predicted elevated TG_by_PG are causally associated with an increased risk of GDM. Side-effect profiles indicate that TG_by_PG might be a target for GDM prevention, though caution is advised due to potential adverse effects on other conditions.

Dong Y ，Hu AQ ，Han BX ，Cao MT ，Liu HY ，Li ZG ，Li Q ，Zheng YJ ... -  《Cardiovascular Diabetology》

[Exploring the Causal Relationship Between Coagulation Function and Gestational Diabetes Mellitus Through Mendelian Randomization].

To explore the causal association between coagulation function, including von Willebrand factor (vWF), a disintegrin and metalloproteinase with thrombospondin type 1 motif, member 13 (ADAMTS13), activated partial thromboplastin time (aPTT), coagulation factor Ⅷ (FⅧ), coagulation factor Ⅺ (FⅪ), coagulation factor Ⅶ (FⅦ), coagulation factor Ⅹ (FⅩ), endogenous thrombin potential (ETP), plasminogen activator inhibitor-1 (PAI-1), protein C, and plasmin, and gestational diabetes mellitus (GDM) using two-sample two-way Mendelian randomization (MR), and to provide genetic evidence for the association between coagulation function and the pathogenesis of GDM. The IEU OpenGWAS database was accessed using the R package TwoSampleMR (v 0.5.6) to obtain the statistical data of the genome-wide association study (GWAS) summary of GDM. MR analysis of the causal association between 11 coagulation function and GDM was performed by the inverse-variance weighted method (IVW), the MR-Egger method, and the weighted median method (WM). In this study, the GWAS summary statistics of GDM (covering 5 687 cases and 117 892 controls) were used for MR analysis. It was found that there was a causal relationship between the predicted plasma FⅧ level and the risk for GDM (IVW: [odds ratio, OR]=0.28, 95% confidence interval [CI]: 0.10-0.75, P<0.001; WM: OR=0.30, 95% CI: 0.09-0.98, P<0.001). There was no causal relationship between other coagulation function and the risk for GDM (P>0.05). There is a significant causal relationship between the plasma FⅧ level and the risk for GDM. This finding highlights the complex interaction between coagulation function and glucose metabolism during pregnancy, but further research on this finding is warranted.

Zeng F ，Shen P ，Guo W ，He G ... -  《-》

Investigating the causal impact of polycystic ovary syndrome on gestational diabetes mellitus: a two-sample Mendelian randomization study.

Determining the causal relationship between polycystic ovary syndrome (PCOS) and gestational diabetes mellitus (GDM) holds significant implications for GDM prevention and treatment. Despite numerous observational studies suggesting an association between PCOS and GDM, it remains unclear whether a definitive causal relationship exists between these two conditions and which specific features of PCOS contribute to increased incidence of GDM. The causal relationship between polycystic ovary syndrome (PCOS), its characteristic indices, and gestational diabetes mellitus (GDM) was investigated using a two-sample Mendelian randomization study based on publicly available statistics from genome-wide association studies (GWAS). The inverse-variance weighted method was employed as the primary analytical approach to examine the association between PCOS, its characteristic indices, and GDM. MR Egger intercept was used to assess pleiotropy, while Q values and their corresponding P values were utilized to evaluate heterogeneity. It is important to note that this study adopts a two-sample MR design where PCOS and its characteristic indices are considered as exposures, while GDM is treated as an outcome. The study results indicate that there is no causal relationship between PCOS and GDM (all methods P > 0.05, 95% CI of OR values passed 1). The IVW OR value was 1.007 with a 95% CI of 0.906 to 1.119 and a P value of 0.904. Moreover, the MR Egger Q value was 8.141 with a P value of 0.701, while the IVW Q value was also 8.141 with a P value of 0.774, indicating no significant heterogeneity. Additionally, the MR Egger intercept was 0.0004, which was close to zero with a P value of 0.988, suggesting no pleiotropy. However, the study did find a causal relationship between several other factors such as testosterone, high-density lipoprotein, sex hormone-binding globulin, body mass index, waist-hip ratio, apolipoprotein A-I, number of children, diabetes illnesses of mother, father and siblings, hemoglobin A1c, fasting insulin, fasting blood glucose, years of schooling, and GDM based on the IVW method. We observed no association between genetically predicted PCOS and the risk of GDM, implying that PCOS itself does not confer an increased susceptibility to GDM. The presence of other PCOS-related factors such as testosterone, high-density lipoprotein, and sex hormone-binding globulin may elucidate the link between PCOS and GDM. Based on these findings, efforts aimed at preventing GDM in individuals with PCOS should prioritize those exhibiting high-risk features rather than encompassing all women with PCOS.

Guixue G ，Yifu P ，Xiaofeng T ，Qian S ，Yuan G ，Wen Y ，Conghui H ，Zuobin Z ... -  《Frontiers in Endocrinology》