Causal relationship between multiple modifiable risk factors and gestational diabetes mellitus: a two-sample Mendelian randomization study.

Maternal hyperglycemia is linked to adverse neonatal outcomes. However, current evidence was insufficient for mechanistic pathways. We aim to use two-sample Mendelian randomization (MR) to obtain a comprehensive understanding of the causal association and mediation pathways. Genetic variants of fasting glucose (FG), insulin sensitivity index (ISI), glycated haemoglobin (HbA1c), gestational diabetes mellitus (GDM) and type 2 diabetes (T2D) were used as instruments (N = 50 404-898 130). The associations with offspring birthweight, gestational duration, spontaneous preterm and post-term birth were assessed by the inverse-variance weighted method, using summary statistics of European genome-wide association studies (N = 131 279-210 248). Sensitivity analyses, including multivariable MR removing pleiotropic effect from maternal body mass index (BMI), assessed the robustness. Mediation via placental weight and maternal hypertension were assessed via a two-step MR design. FG (0.46 SD per mmol/L, 95% confidence interval [95% CI]: 0.32, 0.61) and GDM liability (0.18 SD per log odds, 95% CI: 0.08, 0.18) were positively associated with birthweight, with consistent findings for HbA1c, T2D liability and ISI. These associations were mediated by placental weight (proportion mediated: 32.8% to 77.7%). Higher HbA1c, GDM and T2D liability were associated with preterm birth (odds ratios for GDM: 1.07, 95% CI: 1.01, 1.14) and shorter gestational duration, whilst the association for T2D attenuated after adjusted for maternal BMI and gestational hypertension. Maternal hyperglycemia is associated with higher birthweight (possibly indicating macrosomia), mediated via increased placental growth. GDM and T2D liability are related to preterm birth, whilst the association for T2D liability is driven by maternal adiposity.

BackgroundPrevious studies reported possible connections between dietary factors and pregnancy complications; however, confounders tend to confound the results. A two-sample Mendelian randomization (MR) study was carried out to explore the impact of dietary intakes on the risk of pregnancy complications.MethodsExposure data in this study were derived from the IEU Open GWAS project, and the outcome data were from the FinnGen study. The inverse variance-weighted (IVW) method is the main analytical method used in this study. In addition, we verified the accuracy of the findings by performing sensitivity analyses using other methods.ResultsAfter rigorous False Discovery Rate (FDR) correction, dried fruit intake can reduce the risk of ectopic pregnancy (OR [odds ratio]: 0.36, 95% CI [confidence interval]: 0.21–0.62). Fresh fruit intake was positively associated with pregnancy hypertension (OR: 2.26, 95% CI: 1.32–3.87), and cheese intake was negatively related to pregnancy hypertension (OR: 0.63, 95% CI: 0.47–0.85). In addition, cheese intake was negatively associated with pre-eclampsia (OR: 0.53, 95% CI: 0.38–0.72) and gestational diabetes (OR: 0.48, 95% CI: 0.36–0.64). There was no significant causality in this study for the analyses of other dietary intakes and pregnancy complications, and no heterogeneity or horizontal pleiotropy was found.ConclusionsOur two-sample MR study explores the causal association between dietary intakes and pregnancy complications, and our results contribute to the primary prevention of pregnancy complications. The mechanism by which dietary intakes affects pregnancy complications can be validated by further basic observational studies.

Dyslipidemia is linked to pregnancy complications, but its causal role remains uncertain. This two-sample Mendelian Randomization (MR) study investigated the causal relationship between lipid traits and pregnancy complications and evaluated the impact of lipid-modifying drug targets. Genetic instruments for lipid traits and targets for lipid-modifying drugs were obtained from the Global Lipids Genetics Consortium. Three pregnancy complications' summary statistics came from the FinnGen R9 database. Significant drug targets underwent further analysis using Expression Quantitative Trait Loci data, and mediation analysis identified potential mediators. Increased high-density lipoprotein cholesterol (HDL-C) reduced the incidence of preeclampsia (OR: 0.755, 95% CI: 0.639-0.891, p=0.001, FDR=0.012) and gestational diabetes mellitus (GDM) (OR: 0.835, 95% CI: 0.741-0.942, p=0.003, FDR=0.018). Genetic proxies for cholesteryl ester transfer protein (CETP) inhibition correlated with a decreased risk of preeclampsia (OR: 0.863, 95% CI: 0.786-0.947, p=0.002, FDR=0.027), while genetic inhibition of HMG-CoA reductase (HMGCR) increased preeclampsia risk (OR: 1.700, 95% CI: 1.189-2.431, p=0.004, FDR=0.036). Genetically mimicking the enhancement of lipoprotein lipase (LPL) related to a reduced risk of GDM (OR: 0.681, 95% CI: 0.560-0.829, p=1.29×10-4, FDR=0.004). Higher LPL expression in subcutaneous adipose tissue also reduced GDM risk (OR: 0.642, 95% CI: 0.454-0.909, p=0.013). Waist circumference (4.2%) and waist-to-hip ratio adjusted by BMI (5.7%) partially mediated LPL's effect on GDM risk. Elevated HDL-C levels help prevent preeclampsia and GDM. CETP and LPL could be therapeutic targets for preeclampsia and GDM, respectively. However, caution is advised with HMGCR-targeting drugs, as they may increase the preeclampsia risk.

Gestational diabetes mellitus (GDM) is one of the most prevalent pregnancy problems, and there is still debate over the relationship between vitamin D and GDM. Our objective is to investigate the correlation between vitamin D and GDM by employing Mendelian randomization (MR) with summary data obtained from genome-wide association studies (GWAS). Data on exposures and outcomes, namely vitamin D, vitamin D insufficiency, and GDM, were acquired from the IEU OpenGWAS Project. Bidirectional MR analysis was performed utilizing the inverse variance weighted (IVW) method as the principal analytical approach. The complementary approaches employed in this study encompassed weighted median, simple mode, weighted mode, and MR-Egger regression. A series of sensitivity analysis were conducted in order to assess the reliability of the obtained results. The data were acquired from the IEU OpenGWAS Project. Following the application of the three assumptions of MR, 13 single nucleotide polymorphisms (SNPs) were included in the MR analysis for vitamin D levels and vitamin D deficiency on GDM, and 10 and 26 SNPs were included for GDM on vitamin D levels and deficiency, respectively. The findings from the IVW analysis revealed a significant positive correlation between vitamin D levels and GDM (OR = 1.057, 95% CI: 1.011-1.104, p = 0.015). Conversely, a negative correlation was seen between vitamin D deficiency and GDM (OR = 0.979, 95% CI: 0.959-0.999, p = 0.039). The results of the reverse MR study revealed no evidence of reverse causation between GDM and vitamin D. The findings from multiple MR approaches were in line with the direction of IVW analysis. Sensitivity analysis revealed no evidence of heterogeneity, pleiotropy, or outliers, suggesting the robustness of the results. There exists a causal association between vitamin D and GDM, whereby vitamin D levels serve as a risk factor for GDM.

ObjectiveTo investigate the genetic underpinnings of the association between type 2 diabetes (T2D), glycemic indicators such as fasting glucose (FG), fasting insulin (FI), and glycated hemoglobin (GH), and venous thromboembolism (VTE), encompassing deep vein thrombosis (DVT) and pulmonary embolism (PE), thereby contributing novel insights to the scholarly discourse within this domain.MethodsGenome-wide association study (GWAS) summary data pertaining to exposures (T2D, FG, FI, GH) and outcomes (VTE, DVT, PE) were acquired from the IEU Open GWAS database, encompassing participants of European descent, including both male and female individuals. Two-sample Mendelian randomization (MR) analyses were conducted utilizing the TwoSampleMR and MRPRESSO packages within the R programming environment. The primary analytical approach employed was the random-effects inverse variance weighted (IVW) method. Heterogeneity was assessed via Cochran’s Q statistic for MR-IVW and Rucker’s Q statistic for MR-Egger. Horizontal pleiotropy was evaluated using the intercept test of MR Egger and MR pleiotropy residual sum and outlier (MR-PRESSO) analysis, with the latter also employed for outlier detection. Additionally, a “Leave one out” analysis was conducted to ascertain the influence of individual single nucleotide polymorphisms (SNPs) on MR results.ResultsThe random-effects IVW analysis revealed a negative genetic causal association between T2D) and VTE (P = 0.008, Odds Ratio [OR] 95% confidence interval [CI] = 0.896 [0.827–0.972]), as well as between FG and VTE (P = 0.002, OR 95% CI = 0.655 [0.503–0.853]), GH and VTE (P = 0.010, OR 95% CI = 0.604 [0.412–0.884]), and GH and DVT (P = 0.002, OR 95% CI = 0.413 [0.235–0.725]). Conversely, the random-effects IVW analysis did not detect a genetic causal relationship between FI and VTE (P > 0.05), nor between T2D, FG, or FI and DVT (P > 0.05), or between T2D, FG, FI, or GH and PE (P > 0.05). Both the Cochran’s Q statistic for MR-IVW and Rucker’s Q statistic for MR-Egger indicated no significant heterogeneity (P > 0.05). Moreover, the intercept tests of MR Egger and MR-PRESSO suggested the absence of horizontal pleiotropy (P > 0.05). MR-PRESSO analysis identified no outliers, while the “Leave one out” analysis underscored that the MR analysis was not influenced by any single SNP.ConclusionOur investigation revealed that T2D, FG, and GH exhibit negative genetic causal relationships with VTE at the genetic level, while GH demonstrates a negative genetic causal relationship with DVT at the genetic level. These findings furnish genetic-level evidence warranting further examination of VTE, DVT, and PE, thereby making a contribution to the advancement of related research domains.

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.

Background and Aims: As a common complication of pregnancy, gestational diabetes mellitus (GDM) may lead to a serious negative impact on pregnant women and their children. Autoimmune diseases are chronic pathologies triggered by abnormal responses of the human immune system that result in damage and disorders in the body. Recently, several studies have demonstrated that autoimmune diseases could be related to the risk of GDM. However, several other studies of this relationship have yielded conflicting results. We explored the causal relationship between autoimmune diseases and GDM risk through a two-sample Mendelian randomization (2SMR) study. Method: We obtained exposure data for rheumatoid arthritis (RA) from a genome-wide association study (GWAS) pooled dataset, which consisted of 361,194 participants. We selected single-nucleotide polymorphisms (SNPs) that had a relationship with RA and were at a significance level of not only p < 5 × 10[Formula: see text] but also at a low linkage disequilibrium (LD) level (r2 < 0.01). The results included 5,687 GDM cases and 117,892 controls. For detailed Methods, please see the Methods section in this article’s Online Repository at https://www.jacionline.org Results: The results of inverse variance weight (IVW) analysis suggested a positive correlation between RA and GDM risk. In addition, no validity was observed in the statistical models for heterogeneity and pleiotropy. However, for multiple sclerosis (MS), no causal relationship between it and GDM risk was found in our study. Conclusion: Our results suggest a strong casual association between RA and the risk of GDM. The results suggested the importance of enhanced antenatal care and early intervention among pregnant women with RA as well as clues for novel risk factors for GDM.

The escalating worldwide occurrence of diabetes mellitus, recognized as a chronic metabolic ailment contributing to an amplified global disease burden, has stimulated researchers to explore its etiology. Consequently, the study employed a two-sample Mendelian randomization (MR) methodology to examine the causal connection between bacterial pneumonia and diabetes, drawing upon the existing observational study that identified a potential association between bacterial pneumonia and diabetes. Furthermore, MR investigations suggest a reciprocal causal relationship between bacterial pneumonia and gestational diabetes mellitus(GDM), and a plausible causal link between bacterial pneumonia and T1DM. Background Previous observational studies have established the high prevalence of bacterial pneumonia in diabetic patients, which in turn leads to increased mortality. However, the presence of a causal connection between bacterial pneumonia and diabetes remains unobserved. Methods We chose genome-wide significant (Ρ < 1 × 10−5 and Ρ < 1 × 10−6) and independent (r2 < 0.001) single-nucleotide polymorphisms (SNPs) as instrumental variables (IVs) to proceed a bidirectional two-sample MR study. The extracted SNPs explored the relationship between bacterial pneumonia and diabetes by Inverse variance weighted (IVW), MR-Egger, and weighted median methods. In addition, we conducted the Heterogeneity test, the Pleiotropy test, MR-presso and the Leave-one-out (LOO) sensitivity test to validate the reliability of results. Results In an MR study with bacterial pneumonia as an exposure factor, four different types of diabetes as outcome. It was observed that bacterial pneumonia increases the incidence of GDM (OR = 1.150 (1.027–1.274, P = 0.011) and T1DM (OR = 1.277 (1.024–1.531), P = 0.016). In the reverse MR analysis, it was observed that GDM (OR = 1.112 (1.023–1.201, P = 0.009) is associated with an elevated risk of bacterial pneumonia. However, no significant association was observed bacterial pneumonia with T1DM and other types of diabetes (P > 0.05). Conclusion This study utilizing MR methodology yields robust evidence supporting a bidirectional causal association between bacterial pneumonia and GDM. Furthermore, our findings suggest a plausible causal link between bacterial pneumonia and T1DM.

Observational studies on the association between gestational diabetes mellitus (GDM) during pregnancy and pediatric neurological disorders (PNDs) such as cerebral palsy (CP), autism spectrum disorders (ASD), and epilepsy (EP) in offspring have yielded mixed findings, creating ambiguity in causal interpretations. The direct link between GDM and these PNDs remains unclear. Elucidating this connection is vital for developing effective early intervention strategies during pregnancy to mitigate the risk of PNDs in the offspring. This study utilizes a two-sample (2-sample) Mendelian randomization (MR) approach to investigate the causal relationship between GDM and its impact on CP, ASD, and EP in offspring. We employed 2-sample MR using 6 single nucleotide polymorphisms (SNPs) strongly associated with GDM. Summary-level data for CP, ASD, and EP were obtained from the Integrative Epidemiology Unit (IEU) Open Genome-Wide Association Study (GWAS) project, encompassing sample sizes of 217,278, 46,351, and 463,010, respectively. The robustness of our findings was assessed using the inverse variance-weighted (IVW) method along with additional sensitivity analyses. The results demonstrate that GDM is associated with a higher risk of offspring CP as determined by the IVW method [odds ratio (OR): 1.74; 95% confidence interval (CI): 1.27-2.37; P<0.001]. In contrast, no association was observed between GDM and ASD or EP. Additionally, alternative methods for sensitivity analyses showed consistent results, and there was no pleiotropy detected using MR-Egger regression (P=0.48). This study provides strong evidence supporting a positive causal relationship between genetically predicted GDM and the increased risk of offspring CP, with no observed correlation found with ASD or EP.

Observational studies have reported that Helicobacter pylori (H. pylori) infection is associated with a series of pregnancy and neonatal outcomes. However, the results have been inconsistent, and the causal effect is unknown. A two-sample Mendelian randomization (MR) study was performed using summary-level statistics for anti-H. pylori IgG levels from the Avon Longitudinal Study of Parents and Children Cohort. Outcome data for pregnancy (miscarriage, preeclampsia-eclampsia, gestational diabetes mellitus, placental abruption, premature rupture of membranes, postpartum hemorrhage) and neonates (birthweight, gestational age, and preterm birth) were sourced from genome-wide association meta-analysis as well as the FinnGen and Early Growth Genetics Consortium. Causal estimates were calculated by five methods including inverse variance weighted (IVW). The heterogeneity of instrumental variables was quantified by Cochran's Q test, while sensitivity analyses were performed via MR-Egger, MR-PRESSO, and leave-one-out tests. IVW estimates suggested that genetically predicted anti-H. pylori IgG levels were significantly associated with increased risks of preeclampsia-eclampsia (odds ratio [OR] = 1.12, 95% confidence interval [CI] 1.01-1.24, P = 0.026) and premature rupture of membranes (OR = 1.17, 95% CI 1.05-1.30, P = 0.004). Similar results were obtained for preeclampsia-eclampsia from the MR-Egger method (OR = 1.32, 95% CI 1.06-1.64, P = 0.027) and for premature rupture of membranes from the weighted median method (OR = 1.22, 95% CI 1.06-1.41, P = 0.006). No significant causal effects were found for other outcomes. There was no obvious heterogeneity and horizontal pleiotropy across the MR analysis. Our two-sample MR study demonstrated a causal relationship of H. pylori infection with preeclampsia-eclampsia and premature rupture of membranes. The findings confirm the epidemiological evidence on the adverse impact of H. pylori in pregnancy. Further studies are needed to elucidate the pathophysiological mechanisms and assess the effectiveness of pre-pregnancy screening and preventive eradication.

Observational studies have reported that autoimmune diseases are associated with gestational diabetes mellitus (GDM), but the causality is unknown. The study aimed to evaluate the potential causal effect of autoimmune diseases on GDM. A two-sample Mendelian randomization (MR) study was designed using the summary statistics of GDM (123,579 individuals) and three common autoimmune diseases, including inflammatory bowel disease (IBD, 59,957 individuals), rheumatoid arthritis (RA, 80,799 individuals) and systemic lupus erythematosus (SLE, 14,267 individuals), from the genome-wide association study (GWAS). The fixed-effects inverse variance weighted (IVW) was used to deduce the causal association between autoimmune diseases and GDM, and sensitivity analyses were further performed. The inverse variance weighting (IVW) method showed that RA and SLE increased the risk of GDM (RA: OR = 1.076, 95%CI = 1.033-1.122, P = 4.649E-04; SLE: OR = 1.025, 95%CI = 1.001-1.049, P = 0.044). But there were no any associations of IBD with GDM (P > 0.05). No significant horizontal pleiotropy was found by MR Egger regression (IBD: P for intercept = 0.905; RA: P for intercept = 0.103; SLE = P for intercept = 0.608). This two-sample MR study found that both SLE and RA are positively associated with the risk of GDM. Our findings provide help for the future prevention and treatment of GDM to reduce associated maternal and fetal complications. However, more research is needed to obviate the role of the GC and the HCQ to ensure this relationship is causal.

Overall and abdominal obesity were significantly associated with insulin resistance and type 2 diabetes mellitus (T2DM) risk in observational studies, though these associations cannot avoid the bias induced by confounding effects and reverse causation. This study aimed to test whether these associations are causal, and it compared the causal effects of overall and abdominal obesity on T2DM risk and glycemic traits by using a two-sample Mendelian randomization (MR) design. Based on summary-level statistics from genome-wide association studies, the instrumental variables for body mass index (BMI), waist-to-hip ratio (WHR), and WHR adjusted for BMI (WHRadjBMI) were extracted, and the horizontal pleiotropy was analyzed using MR–Egger regression and the MR–pleiotropy residual sum and outlier (PRESSO) method. Thereafter, by using the conventional MR method, the inverse-variance weighted method was applied to assess the causal effect of BMI, WHR, and WHRadjBMI on T2DM risk, Homeostatic model assessment of insulin resistance (HOMA-IR), fasting insulin, fasting glucose, and Hemoglobin A1c (HbA1c). A series of sensitivity analyses, including the multivariable MR (diastolic blood pressure, systolic blood pressure, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol as covariates), MR–Egger regression, weighted median, MR–PRESSO, and leave-one-out method, were conducted to test the robustness of the results from the conventional MR. Despite the existence of horizontal pleiotropy, consistent results were found in the conventional MR results and sensitivity analyses, except for the association between BMI and fasting glucose, and WHRadjBMI and fasting glucose. Each one standard deviation higher BMI was associated with an increased T2DM risk [odds ratio (OR): 2.741; 95% confidence interval (CI): 2.421–3.104], higher HbA1c [1.054; 1.04–1.068], fasting insulin [1.202; 1.173–1.231], and HOMA-IR [1.221; 1.187–1.255], similar to findings for causal effect of WHRadjBMI on T2DM risk [1.993; 1.704–2.33], HbA1c [1.061; 1.042–1.08], fasting insulin [1.102; 1.068–1.136], and HOMA-IR [1.127; 1.088–1.167]. Both BMI (P = 0.546) and WHRadjBMI (P = 0.443) were unassociated with fasting glucose in the multivariable MR analysis. In conclusion, overall and abdominal obesity have causal effects on T2DM risk and insulin resistance but no causal effect on fasting glucose. Individuals can substantially reduce their insulin resistance and T2DM risk through reduction of body fat mass and modification of body fat distribution.

Background Previous articles on the relationship between vitamin D and gestational diabetes mellitus (GDM) were inconsistent. Their relationship has been observed primarily through observational studies, and the causality of this association has not been established. Methods A two-sample Mendelian randomization (MR) research was conducted to test the causal association between vitamin D and GDM, utilizing publically available statistics from genome-wide association studies (GWAS). This study obtained genetic variants from GWAS including vitamin D (N = 373,045,10,783,672 Single Nucleotide Polymorphisms SNPs), and GDM (5687 cases and 117,892 controls). The major technique was the inverse variance weighted approach (IVW), although there were other approaches as well, such as MR-Egger regression, weighted median, weighted mode, and simple mode. Additionally, we conducted sensitivity analyses to detect any potential diversity and horizontal pleiotropy. Results The study suggested that there was no causal link between vitamin D and GDM (all methods p > 0.05). For heterogeneity, MR egger Q value was 113.7, p < 0.05; IVW Q value was 114.7, p < 0.05. Therefore, random- effects IVW approach was applied. Regarding pleiotropy, the MR Egger regression intercept was 0.0046, which was close to zero with a p value of 0.452, suggesting the absence of pleiotropy. Conclusions We observed no assosiation between genetically predicted vitamin D and the risk of GDM, implying that insufficient vitamin D may do not confer an increased susceptibility to GDM.

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.

BackgroundThe prevalence of gestational diabetes mellitus (GDM) has increased dramatically worldwide in the last decades, but unfortunately it was not studied in Egypt.ObjectiveThe objective of the study is to assess the prevalence and the risk factors of GDM in Assiut City, Egypt and to assess the better management and follow-up of GDM comparing the results of treatment options on maternal and fetal outcomes.Patients and methodsOur study was a prospective cohort study performed between June 2014 and June 2015. The study included 355 nondiabetic pregnant women at 24–28th weeks of gestation. A total of 242 cases had risk factors for GDM who underwent 75g 2h oral glucose tolerance test (OGTT). Diagnosis of GDM was carried out according to International Association of the Diabetes and Pregnancy Study Groups criteria. GDM cases were followed up and treatment was modified according to the targets for capillary blood glucose levels. Patients received an education program about the preferred food items and on the importance of physical activities, and if targets are not met within 1–2 weeks of initiation of lifestyle management, then those patients will be grouped into two groups: a group treated with metformin and another group treated with insulin. All participants were followed up till the end of pregnancy especially: maternal outcomes, for example preeclampsia and cesarean delivery. Also, fetal outcomes, for example macrosomia, hypoglycemia, hyperbilirubinemia, neonatal respiratory distress syndrome, and neonatal death. Follow-up of GDM cases was done at 6–12 weeks postpartum by OGTT 75g glucose to detect progression to type 2 DM.ResultsOur study has shown that the prevalence rate of GDM was 12.4% among the studied group. Family history of DM was the most prevalent risk factor with a highly significant positive relation that occurred in 73.3% of GDM cases (P<0.001) compared with 32.5% in non-GDM cases. BMI more than 30 was another important risk factor demonstrated in our study as a significant association was found between prevalence of GDM and obesity (BMI >30) was found in 50% of women with GDM (P<0.001) compared with 21.2% in non-GDM cases. Of the studied group, 31.8% had no risk factors for GDM, which shows the importance of usinguniversal screening measures. The prevalence of GDM was higher in those living in urban areas (76.7 vs. 23.3%%), P value 0.045. Our study showed that the most common complications of GDM were cesarean section, which occurred in 33.3% of cases and preeclampsia, which occurred in 23.3% of cases. Regarding fetal complications, the most frequent complications were macrosomia that occurred in 23.35% of cases and hypoglycemia in newborn babies, which occurred in 16.7% of cases. The use of metformin lessened the occurrence of macrosomia in 27.3% of babies compared with 28.6% with the insulin group. Neonatal hypoglycemia occurred less with the use of metformin in 9.1% compared with 28.6% with insulin use. Also, in our study 23.3% (7/30) of GDM cases progressed to type 2 diabetes when 2-h OGTT 75g glucose was done at 6–12 weeks postpartum. All of them had a family history of DM in first-degree relatives, obese with a BMI of above 30 and started insulin from the start of diagnosis.ConclusionThe prevalence of GDM in high-risk women attending Assiut University Women Health Hospital was 12.4% and family history of DM was the most frequent risk factors for GDM. High prevalence of BMI more than 30, past history of previous GDM, and the increasing age of the pregnant women were other important risk factors. Of the GDM women 31.8% had no definite risk factor and this enhances the need for universal screening of all pregnant women instead of selective screening for the high-risk group to pick up more and more cases with GDM. GDM women were more prevalent in urban than in rural areas. Our study showed that the most common maternal complications of GDM were cesarean section, preeclampsia, and postpartum progression to type 2 diabetes. Regarding fetal complications, the most frequent complications were macrosomia and hypoglycemia. Macrosomia occurred less with the usage of metformin compared with the insulin group. Neonatal hypoglycemia occurred less with the use of metformin compared with insulin use. Of the GDM cases 31.8% (7/30) progressed to type 2 DM when OGTT was done at 6–12 weeks postpartum and all of them had a family history of DM in first-degree relatives, obese with a BMI of above 30 and started insulin from the start of diagnosis.