Genetic variants and the risk of gestational diabetes mellitus: a systematic review

Dietary Intake and Oral Glucose Tolerance Test Results in Women with Gestational Diabetes

Background/Objective: Diet is a risk factor for gestational diabetes mellitus (GDM). There are few studies on women's diet and glucose tolerance test (GTT) results during pregnancy. The objective of this study was to evaluate the relationship between one's previous diet and the number of abnormal values on the diagnostic GTT in women with GDM. We hypothesized that there would be an inverse relation between antioxidant micronutrient consumption and the number of abnormal GTT values. Methods: This cross-sectional study included 60 women diagnosed with GDM (2-h, 75 g-GTT), divided in two groups as follows: 1 abnormal glucose value and 2-3 abnormal values. Shortly after the diagnosis, participants answered a validated food frequency questionnaire to assess their food consumption in the last 6 months. The Mann-Whitney test was used to compare the dietary intake of the participants in the two groups. Results: The participant characteristics were similar. The median intake of total calories, carbohydrates, lipids, and proteins did not differ significantly between groups. Participants with 1 abnormal GTT value had significantly higher intakes of fiber (11.9 vs. 11.0 g/day p = 0.049), vitamin D (40.6 vs. 40.4 mcg/day p = 0.049), and vitamin C (180.0 vs. 151.0 mg/day p = 0.008) than those with 2-3 abnormal values. Conclusions: Our results suggest a possible association between the consumption of fiber and antioxidant micronutrients and the number of abnormal GTT values.

The associations of IGF2, IGF2R and IGF2BP2 gene polymorphisms with gestational diabetes mellitus: A case-control study

OBJECTIVE

To investigate the associations of Insulin-like growth factor-II (IGF2) gene, Insulin-like growth factor-II receptor (IGF2R) gene and Insulin-like growth factor-II binding protein 2 (IGF2BP2) gene polymorphisms with the susceptibility to gestational diabetes mellitus (GDM) in Chinese population.

METHODS

A total of 1703 pregnant women (835 GDM and 868 Non-GDM) were recruited in this case-control study. All participants underwent prenatal 75 g oral glucose tolerance test (OGTT) examinations during 24-28 gestational weeks at the Maternal and Child Health Hospital of Hubei Province from January 15, 2018 to March 31, 2019. Genotyping of candidate SNPs (IGF2 rs680, IGF2R rs416572, IGF2BP2 rs4402960, rs1470579, rs1374910, rs11705701, rs6777038, rs16860234, rs7651090) was performed on Sequenom MassARRAY platform. Logistic regression analysis was conducted to investigate the associations between candidate SNPs and risk of GDM. In addition, multifactor dimensionality reduction (MDR) method was applied to explore the effects of gene-gene interactions on GDM risk.

RESULTS

There were significant distribution differences between GDM group and non-GDM group in age, pre-pregnancy BMI, education level and family history of diabetes (P < 0.05). After adjusted for age, pre-pregnancy BMI, education level and family history of diabetes, there were no significant associations of the candidate SNPs polymorphisms and GDM risk (P > 0.05). Furthermore, there were no gene-gene interactions on the GDM risk among the candidate SNPs (P > 0.05). However, the fasting blood glucose (FBG) levels of rs6777038 CT carriers were significantly lower than TT carriers (4.69±0.69 vs. 5.03±1.57 mmol/L, P < 0.01), and the OGTT-2h levels of rs6777038 CC and CT genotype carriers were significantly lower than TT genotype carriers (8.10±1.91 and 8.08±1.87 vs. 8.99±2.90 mmol/L, P < 0.01).

CONCLUSIONS

IGF2 rs680, IGF2R rs416572, IGF2BP2 rs4402960, rs1470579, rs11705701, rs6777038, rs16860234, rs7651090 polymorphisms were not significantly associated with GDM risk in Wuhan, China. Further lager multicenter researches are needed to confirm these results.

Genetic and inflammatory factors underlying gestational diabetes mellitus: a review

Gestational diabetes mellitus (GDM) poses a significant global health concern, impacting both maternal and fetal well-being. Early detection and treatment are imperative to mitigate adverse outcomes during pregnancy. This review delves into the pivotal role of insulin function and the influence of genetic variants, including SLC30A8, CDKAL1, TCF7L2, IRS1, and GCK, in GDM development. These genetic variations affect beta-cell function and insulin activity in crucial tissues, such as muscle, disrupting glucose regulation during pregnancy. We propose a hypothesis that this variation may disrupt zinc transport, consequently impairing insulin production and secretion, thereby contributing to GDM onset. Furthermore, we discussed the involvement of inflammatory pathways, such as TNF-alpha and IL-6, in predisposing individuals to GDM. Genetic modulation of these pathways may exacerbate glucose metabolism dysregulation observed in GDM patients. We also discussed how GDM affects cardiovascular disease (CVD) through a direct correlation between pregnancy and cardiometabolic function, increasing atherosclerosis, decreased vascular function, dyslipidemia, and hypertension in women with GDM history. However, further research is imperative to unravel the intricate interplay between inflammatory pathways, genetics, and GDM. This understanding is pivotal for devising targeted gene therapies and pharmacological interventions to rectify genetic variations in SLC30A8, CDKAL1, TCF7L2, IRS1, GCK, and other pertinent genes. Ultimately, this review offers insights into the pathophysiological mechanisms of GDM, providing a foundation for developing strategies to mitigate its impact.

A Simplified Screening Model to Predict the Risk of Gestational Diabetes Mellitus in Caucasian and Latin American Pregnant Women

The pathophysiology of gestational diabetes mellitus (GDM) comprises clinical and genetic factors. In fact, GDM is associated with several single nucleotide polymorphisms (SNPs). This study aimed to build a prediction model of GDM combining clinical and genetic risk factors. A total of 1588 pregnant women from the San Carlos Cohort participated in the present study, including 1069 (67.3%) Caucasian (CAU) and 519 (32.7%) Latin American (LAT) individuals, and 255 (16.1%) had GDM. The incidence of GDM was similar in both groups (16.1% CAU and 16.0% LAT). Genotyping was performed via IPLEX Mass ARRAY PCR, selecting 110 SNPs based on literature references. SNPs showing the strongest likelihood of developing GDM were rs10830963, rs7651090, and rs1371614 in CAU and rs1387153 and rs9368222 in LAT. Clinical variables, including age, pre-pregnancy body mass index, and fasting plasma glucose (FPG) at 12 gestational weeks, predicted the risk of GDM (AUC 0.648, 95% CI 0.601-0.695 in CAU; AUC 0.688, 95% CI 0.628-9.748 in LAT), and adding SNPs modestly improved prediction (AUC 0.722, 95%CI 0.680-0.764 in CAU; AUC 0.769, 95% CI 0.711-0.826 in LAT). In conclusion, adding genetic variants enhanced the prediction model of GDM risk in CAU and LAT pregnant women.

Gestational Diabetes Mellitus and its Effects on the Developing Cerebellum: A Narrative Review on Experimental Studies

Diabetes mellitus during pregnancy is a common complication of gestation, but its effects on the offspring's development are poorly understood. Recently, some studies reported that gestational diabetes mellitus (GDM) impairs cerebellar development, and some genetic alterations have been described as consequences. Cerebellum, one of the hindbrain derived structures in the posterior cranial fossa, plays a crucial role in cognition and behavioral functions. In recent years, some surveys stated that gestational diabetes has adverse effects on the fetus's cerebellum. Disruption of cerebellar cortex morphogenesis, reduce the volume of the cerebellum, reduce the thickness of cerebellar cortex layers, and its neuronal cells and effects on the expression of synaptophysin, insulin, and insulin-like growth factor -1 receptors are some of the maternal diabetes effects on developing cerebellum. On other hand, GDM, as a neurotoxic agent, impaired cerebellar development and could be a cause for the behavioral, functional, and structural anomalies observed in pups of diabetic mothers. Based on the literature review, most studies have pointed out that administering insulin in patients with GDM decreased the cellular and molecular alterations that induced by GDM in the developing cerebellum. Undoubtedly, screening strategies for all pregnant women are necessary.

Association between insulin receptor substrate 1 gene polymorphism rs1801278 and gestational diabetes mellitus: an updated meta- analysis

OBJECTIVES

we performed this meta- analysis to investigate the impact of insulin receptor substrate 1 (IRS1) gene rs1801278 on susceptibility to gestational diabetes mellitus (GDM).

METHODS

The pooled odds ratio (OR) and 95% confidence interval (95% CI) were calculated, and p value is used to determine statistical significance. Sensitivity analysis was performed under three models (dominant, recessive and allele model), and the pooled ORs and 95%CI were calculated. Funnel plots and Begger's regression test were employed to test the publication bias.

RESULTS

The meta-analysis included 4777 participants (2116 cases and 2661 controls). The IRS1 rs1801278 (C/T) were not significant associated with GDM risk under the dominant and allele models, OR (95%CI) = 1.22 (0.88-1.70) and 1.24 (0.91-1.68), respectively (both p values were more than 0.05). But we also found the IRS1 rs1801278 (C/T) were significant associated with GDM risk under the recessive model, OR (95%CI) = 0.37 (0.16-0.86), p = 0.030. Our results showed that none of the studies affected the quality of the pooled OR. We also found no significant publication bias existed in this meta study for three genetic models, PTT + CT vs. CC = 0.445; PCC+CT vs. TT= 0.095; PC vs. T = 0.697.

CONCLUSION

this meta-analysis indicated that IRS1 rs1801278 (C/T) was associated with the GDM risk under the recessive model but was not associated with the GDM risk under dominant and allele models.

Association between pregnancy-related complications and development of type 2 diabetes and hypertension in women: an umbrella review

BACKGROUND

Despite many systematic reviews and meta-analyses examining the associations of pregnancy complications with risk of type 2 diabetes mellitus (T2DM) and hypertension, previous umbrella reviews have only examined a single pregnancy complication. Here we have synthesised evidence from systematic reviews and meta-analyses on the associations of a wide range of pregnancy-related complications with risk of developing T2DM and hypertension.

METHODS

Medline, Embase and Cochrane Database of Systematic Reviews were searched from inception until 26 September 2022 for systematic reviews and meta-analysis examining the association between pregnancy complications and risk of T2DM and hypertension. Screening of articles, data extraction and quality appraisal (AMSTAR2) were conducted independently by two reviewers using Covidence software. Data were extracted for studies that examined the risk of T2DM and hypertension in pregnant women with the pregnancy complication compared to pregnant women without the pregnancy complication. Summary estimates of each review were presented using tables, forest plots and narrative synthesis and reported following Preferred Reporting Items for Overviews of Reviews (PRIOR) guidelines.

RESULTS

Ten systematic reviews were included. Two pregnancy complications were identified. Gestational diabetes mellitus (GDM): One review showed GDM was associated with a 10-fold higher risk of T2DM at least 1 year after pregnancy (relative risk (RR) 9.51 (95% confidence interval (CI) 7.14 to 12.67) and although the association differed by ethnicity (white: RR 16.28 (95% CI 15.01 to 17.66), non-white: RR 10.38 (95% CI 4.61 to 23.39), mixed: RR 8.31 (95% CI 5.44 to 12.69)), the between subgroups difference were not statistically significant at 5% significance level. Another review showed GDM was associated with higher mean blood pressure at least 3 months postpartum (mean difference in systolic blood pressure: 2.57 (95% CI 1.74 to 3.40) mmHg and mean difference in diastolic blood pressure: 1.89 (95% CI 1.32 to 2.46) mmHg). Hypertensive disorders of pregnancy (HDP): Three reviews showed women with a history of HDP were 3 to 6 times more likely to develop hypertension at least 6 weeks after pregnancy compared to women without HDP (meta-analysis with largest number of studies: odds ratio (OR) 4.33 (3.51 to 5.33)) and one review reported a higher rate of T2DM after HDP (hazard ratio (HR) 2.24 (1.95 to 2.58)) at least a year after pregnancy. One of the three reviews and five other reviews reported women with a history of preeclampsia were 3 to 7 times more likely to develop hypertension at least 6 weeks postpartum (meta-analysis with the largest number of studies: OR 3.90 (3.16 to 4.82) with one of these reviews reporting the association was greatest in women from Asia (Asia: OR 7.54 (95% CI 2.49 to 22.81), Europe: OR 2.19 (95% CI 0.30 to 16.02), North and South America: OR 3.32 (95% CI 1.26 to 8.74)).

CONCLUSIONS

GDM and HDP are associated with a greater risk of developing T2DM and hypertension. Common confounders adjusted for across the included studies in the reviews were maternal age, body mass index (BMI), socioeconomic status, smoking status, pre-pregnancy and current BMI, parity, family history of T2DM or cardiovascular disease, ethnicity, and time of delivery. Further research is needed to evaluate the value of embedding these pregnancy complications as part of assessment for future risk of T2DM and chronic hypertension.

[－75 G/A Polymorphism of Apolipoprotein A1 Gene Promoter Region in Normal Pregnant Women and Patients With Gestational Diabetes Mellitus]

Objective

To investigate the －75 G/A single-nucleotide polymorphism in the promoter region of apolipoprotein A1 gene (apoA1) and its association with gestational diabetes mellitus (GDM) in pregnant women and to provide references for the exploration in the molecular genetic basis of GDM.

Methods

A total of 626 GDM patients and 1022 normal pregnant women, ie, the controls, were included in the study. The genotyping of apoA1 －75 G/A polymorphism was performed by polymerase chain reaction and restriction fragment length polymorphism (PCR-RFLP) analysis. Total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and glucose (Glu) were measured by enzymatic methods. Plasma insulin (INS) was measured by chemiluminescence immunoassay. The protein levels of apoA1 and apoB were measured by the turbidimetric immunoassay.

Results

Allele frequencies of G and A were 0.718 and 0.282 in the GDM group and 0.713 and 0.287 in the control group, respectively. Distribution of the genotype frequencies was found to be in Hardy-Weinberg equilibrium in both the GDM and control groups. There was no significant difference in the frequencies of alleles G and A and the genotypes of apoA1 －75 G/A polymorphism between the GDM and the control group (P>0.05). In the GDM group, the carriers with the genotype AA were associated with significantly higher levels of TC, HDL-C, and apoA1 than those with genotypes GG and GA did (all P<0.05). After the GDM patients were divided into obese and non-obese subgroups, the genotype-related apoA1 variation was observed only in obese patients, while the genotype-related TC and HDL-C variations were evident in non-obese patients (P<0.05). In the control group, carriers of genotypes AA and GA had higher systolic blood pressure (SBP) and HDL-C than the carriers of genotype GG did (all P<0.05). Carriers of genotypes AA had significantly lower Glu levels than carriers of genotypes GG and GA did (P<0.05). The control subjects were further divided into subgroups according to their body mass index (BMI). Analysis of the subgroups showed that AA carriers were associated with higher SBP levels in the obese control women only, while lower Glu levels were evident in both obese and non-obese control women.

Conclusion

These results suggest that －75 G/A polymorphism in the apoA1 gene is not associated with GDM. However, the genetic variation is closed associated with the plasma apoA1, HDL-C, and TC levels in GDM patients and plasma HDL-C, Glu, and SBP levels in the control subjects. The apoA1 variant-associated lipids and SBP variation is BMI dependent in both groups.

A Simplified Screening Model to Predict the Risk of Gestational Diabetes Mellitus in Pregnant Chinese Women

INTRODUCTION

This study aimed to develop a simplified screening model to identify pregnant Chinese women at risk of gestational diabetes mellitus (GDM) in the first trimester.

METHODS

This prospective study included 1289 pregnant women in their first trimester (6-12 weeks of gestation) with clinical parameters and laboratory data. Logistic regression was performed to extract coefficients and select predictors. The performance of the prediction model was assessed in terms of discrimination and calibration. Internal validation was performed through bootstrapping (1000 random samples).

RESULTS

The prevalence of GDM in our study cohort was 21.1%. Maternal age, prepregnancy body mass index (BMI), a family history of diabetes, fasting blood glucose levels, the alanine transaminase to aspartate aminotransferase ratio (ALT/AST), and the triglyceride to high-density lipoprotein cholesterol ratio (TG/HDL-C) were selected for inclusion in the prediction model. The Hosmer-Lemeshow goodness-of-fit test showed good consistency between prediction and actual observation, and bootstrapping indicated good internal performance. The area under the receiver operating characteristic curve (ROC-AUC) of the multivariate logistic regression model and the simplified clinical screening model was 0.825 (95% confidence interval [CI] 0.797-0.853, P < 0.001) and 0.784 (95% CI 0.750-0.818, P < 0.001), respectively. The performance of our prediction model was superior to that of three other published models.

CONCLUSION

We developed a simplified clinical screening model for predicting the risk of GDM in pregnant Chinese women. The model provides a feasible and convenient protocol to identify women at high risk of GDM in early pregnancy. Further validations are needed to evaluate the performance of the model in other populations.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT03246295.

Genetic and Epigenetic Factors in Gestational Diabetes Mellitus Pathology

Gestational diabetes (GDM) is the carbohydrate intolerance occurring during pregnancy. The risk factors of GDM include obesity, advanced maternal age, polycystic ovary syndrome, multigravidity, a sedentary lifestyle, and pre-existing hypertension. Additionally, complex genetic and epigenetic processes are also believed to play a crucial role in the development of GDM. In this narrative review, we discuss the role of genetic and epigenetic factors in gestational diabetes mellitus pathogenesis.

Integration of clinical demographics and routine laboratory analysis parameters for early prediction of gestational diabetes mellitus in the Chinese population

Gestational diabetes mellitus (GDM) is one of the most common complications in pregnancy, impairing both maternal and fetal health in short and long term. As early interventions are considered desirable to prevent GDM, this study aims to develop a simple-to-use nomogram based on multiple common risk factors from electronic medical health records (EMHRs). A total of 924 pregnant women whose EMHRs were available at Peking University International Hospital from January 2022 to October 2022 were included. Clinical demographics and routine laboratory analysis parameters at 8-12 weeks of gestation were collected. A novel nomogram was established based on the outcomes of multivariate logistic regression. The nomogram demonstrated powerful discrimination (the area under the receiver operating characteristic curve = 0.7542), acceptable agreement (Hosmer-Lemeshow test, P = 0.3214) and favorable clinical utility. The C-statistics of 10-Fold cross validation, Leave one out cross validation and Bootstrap were 0.7411, 0.7357 and 0.7318, respectively, indicating the stability of the nomogram. A novel nomogram based on easily-accessible parameters was developed to predict GDM in early pregnancy, which may provide a paradigm for repurposing clinical data and benefit the clinical management of GDM. There is a need for prospective multi-center studies to validate the nomogram before employing the nomogram in real-world clinical practice.

Comprehensive landscape of the T and B-cell repertoires of newly diagnosed gestational diabetes mellitus

This study conducted a high-throughput sequencing analysis of the T- and B- repertoires in the newly diagnosed GDM patients and evaluated the association between abnormal adaptive immunity and GDM. The unique TCR CDR3 clonotypes were mildly decreased in GDM patients, and the similarity of TCR V-J distributions was higher in the GDM group. Moreover, the usages of the V gene and V-J pair and the frequency distributions of some CDR3 amino acids (AAs) both in BCR and TCR were significantly different between groups. Moreover, the cytokines including IL-4, IL-6, IFN-γ and IL-17A were synchronously elevated in the GDM cases. Our findings provide a comprehensive view of BCR and TCR repertoires at newly diagnosed GDM patients, revealing the mild reduction in unique TCRB CDR3 sequences and slight alteration of the V gene, V-J combination and CDR3 (AA) usages of BCR and TCR. This work provides deep insight into the mechanism of maternal adaptive immunity in GDM and provides novel diagnostic biomarkers and potential immunotherapy targets for GDM.

[Association Between Apolipoprotein C-3 SstⅠ Polymorphism and Serum Lipids in Patients With Gestational Diabetes Mellitus]

Objective

To investigate the apolipoprotein C-3 (APOC3) gene Sst Ⅰ polymorphism and its relationship with changes in serum lipids in patients with gestational diabetes mellitus (GDM).

Methods

A total of 630 pregnant women with GDM and 1027 normal pregnant controls were covered in the study. The genotype and allele frequencies of APOC3 Sst Ⅰ polymorphism were analyzed by polymerase chain reaction and restriction fragment length polymorphism (PCR-RFLP). Total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and glucose (Glu) were measured by enzymatic methods. Plasma insulin (INS) was measured by chemiluminescence. Apolipoproteins A 1 (apoA1) and B (apoB) levels were measured by turbidimetric immunoassay.

Results

The allele frequencies of S1 and S2 of the APOC3 polymorphism at the SstⅠ locus were 0.704 and 0.296 in the GDM group and 0.721 and 0.279 in the control group, respectively. There was no significant difference in genotype frequency and allele frequency of APOC3 Sst Ⅰ polymorphism between the GDM and the control groups ( P>0.05). In the GDM group, those with S2S2 and S1S2 genotypes had higher plasma HDL-C levels and lower atherogenic index (AI) values than those with S1S1 genotype did, with the differences being statistically significant (all P<0.05). GDM patients were then divided into obesity and non-obesity subgroups. Further subgroup analysis showed that the association of APOC3 genotype with changes in HDL-C levels was observed only in obese GDM patients, while the association of APOC3 genotype with changes in AI values was observed in both obese and nonobese patients. In addition, in obese GDM patients, those with S2S2 genotype had significantly higher plasma TG levels than those with S1S1 and S1S2 genotypes did ( P<0.05 and P<0.01, respectively). In non-obese GDM patients, those with S2S2 genotype had significantly lower apoB/apoA1 ratio than S2S2 carriers did ( P<0.05). No genotype-related effect on lipid and apolipoprotein variations was evident in the normal controls.

Conclusion

APOC3 Sst Ⅰ polymorphism in GDM patients is associated with HDL-C and TG levels as well as AI value and apoB/apoA1 ratio. The changes in lipid levels and apolipoprotein ratio showed BMI-dependent features. However, association between polymorphism at the locus and the development of GDM was not observed.

Genetic variants in epoxyeicosatrienoic acid processing and degradation pathways are associated with gestational diabetes mellitus

AIM

To explore the genetic effects of CYP2C8, CYP2C9, CYP2J2, and EPHX2, the key genes involved in epoxyeicosatrienoic acid processing and degradation pathways in gestational diabetes mellitus (GDM) and metabolic traits in Chinese pregnant women.

METHODS

A total of 2548 unrelated pregnant women were included, of which 938 had GDM and 1610 were considered as controls. Common variants were genotyped using the Infinium Asian Screening Array. Association studies of single nucleotide polymorphisms (SNPs) with GDM and related traits were performed using logistic regression and multivariable linear regression analyses. A genetic risk score (GRS) model based on 12 independent target SNPs associated with GDM was constructed. Logistic regression was used to estimate odds ratios and 95% confidence intervals, adjusting for potential confounders including age, pre-pregnancy body mass index, history of polycystic ovarian syndrome, history of GDM, and family history of diabetes, with GRS entered both as a continuous variable and categorized groups. The relationship between GRS and quantitative traits was also evaluated.

RESULTS

The 12 SNPs in CYP2C8, CYP2C9, CYP2J2, and EPHX2 were significantly associated with GDM after adjusting for covariates (all P < 0.05). The GRS generated from these SNPs significantly correlated with GDM. Furthermore, a significant interaction between CYP2J2 and CYP2C8 in GDM (P_Interaction = 0.014, OR_Interaction= 0.61, 95%CI 0.41-0.90) was observed.

CONCLUSION

We found significant associations between GDM susceptibility and 12 SNPs of the four genes involved in epoxyeicosatrienoic acid processing and degradation pathways in a Chinese population. Subjects with a higher GRS showed higher GDM susceptibility with higher fasting plasma glucose and area under the curve of glucose and poorer β-cell function.

Risk prediction of gestational diabetes mellitus in women with polycystic ovary syndrome based on a nomogram model

Women with polycystic ovary syndrome are prone to develop gestational diabetes mellitus, a disease which may have significant impact on the postpartum health of both mother and infant. We performed a retrospective cohort study to develop and test a model that could predict gestational diabetes mellitus in the first trimester in women with polycystic ovary syndrome. Our study included 434 pregnant women who were referred to the obstetrics department between December 2017 and March 2020 with a diagnosis of polycystic ovary syndrome. Of these women, 104 were diagnosed with gestational diabetes mellitus in the second trimester. Univariate analysis revealed that in the first trimester, Hemoglobin A1c (HbA1C), age, total cholesterol(TC), low-density lipoprotein cholesterol (LDL-C), SBP (systolic blood pressure), family history, body mass index (BMI), and testosterone were predictive factors of gestational diabetes mellitus (P < 0.05). Logistic regression revealed that TC, age, HbA1C, BMI and family history were independent risk factors for gestational diabetes mellitus. The area under the ROC curve of the gestational diabetes mellitus risk prediction model was 0.937 in this retrospective analysis, demonstrating a great discriminatory ability. The sensitivity and specificity of the prediction model were 0.833 and 0.923, respectively. The Hosmer-Lemeshow test also showed that the model was well calibrated.

CYP2E1 C-1054T and 96-bp I/D genetic variations and risk of gestational diabetes mellitus in chinese women: a case-control study

BACKGROUND

Cytochrome P450 2E1 (CYP2E1) plays a key role in the metabolism of xenobiotic and endogenous low-molecular-weight compounds. This study aimed to determine if the genetic variations of 96-bp insertion/deletion (I/D) and C-1054T (rs2031920) in CYP2E1 were associated with the risk of gestational diabetes mellitus (GDM).

METHODS

CYP2E1 polymorphisms were genotyped in a case-control study of 1,134 women with uncomplicated pregnancies and 723 women with GDM. The effects of genotype on the clinical, metabolic, and oxidative stress indices were assessed.

RESULTS

The CYP2E1 C-1054T variant was associated with an increased risk of GDM based on the genotype, recessive, dominant, and allele genetic models (P < 0.05). The TT + CT genotype remained a significant predictive factor for GDM risk after correcting for maternal age and pre-pregnancy body mass index (OR = 1.277, 95% CI: 1.042-1.563, P = 0.018). Moreover, fasting insulin concentrations and homeostatic model assessment of insulin resistance were significantly higher in GDM patients carrying the T allele than in those with the CC genotype (P < 0.05). Furthermore, the combined genotype II + ID/TT + CT of the 96-bp I/D and C-1054T polymorphisms further increased the risk of GDM when the combined genotype DD/CC was set as the reference category (OR = 1.676, 95% CI: 1.182-2.376, P = 0.004).

CONCLUSIONS

The T allele of the C-1054T polymorphism and its combination with the I allele of the 96-bp I/D variation in CYP2E1 are associated with an increased risk of GDM in the Chinese population. The - 1054T allele may be associated with more serious insulin resistance in patients.

ATP-binding cassette transporter G1 (ABCG1) polymorphisms in pregnant women with gestational diabetes mellitus

CONTEXT AND OBJECTIVES

Gestational diabetes mellitus (GDM) is the most common metabolic disorder in pregnancy, and it often leads to adverse pregnancy outcomes and seriously harms the health of mothers and infants. ATP-binding cassette transporter G1 (ABCG1) plays critical roles in high-density lipoprotein (HDL) metabolism and reverse cholesterol transport. This study was designed to explore the relevance of the ABCG1 polymorphisms in the atherometabolic risk in GDM.

STUDY DESIGN

The case-control population consists of 1504 subjects. The rs2234715 and rs57137919 single nucleotide polymorphisms (SNPs) were genotyped using PCR and DNA sequencing, and clinical and metabolic parameters were determined.

RESULTS

The genotype distributions of the two SNPs showed no difference between the GDM patient and control groups. However, the rs57137919 polymorphism was associated with total cholesterol (TC), and diastolic blood pressure (DBP) levels in patients with GDM. Moreover, subgroup analysis showed that this polymorphism was associated with ApoA1 and DBP levels in overweight/obese patients with GDM, while it was associated with TC, and gestational weight gain (GWG) in non-obese patients with GDM. Meanwhile, the rs2234715 polymorphism was found to be associated with neonatal birth height in non-obese patients with GDM.

CONCLUSIONS

The two polymorphisms in the ABCG1 have an influence on atherometabolic traits, GWG, and fetal growth in GDM, depending on the BMI of the patients.

Integration of nutrigenomics, melatonin, serotonin and inflammatory cytokines in the pathophysiology of pregnancy-specific urinary incontinence in women with gestational diabetes mellitus

Gestational diabetes mellitus is an important public health problem and has been associated with the development of pregnancy-specific urinary incontinence. The interaction is related to hyperglycemia, and inflammatory and hormonal patterns, which favor functional alterations in different organs and systems. Several genes associated with human diseases have been identified and partially characterized. Most of these genes are known to cause monogenic diseases. However, about 3 % of diseases do not fit the monogenic theory due to the complex interactions between multiple genes and environmental factors, as in chronic metabolic diseases such as diabetes. The nutritional, immunological, and hormonal patterns associated with changes in maternal metabolism may influence and contribute to greater susceptibility to urinary tract disorders. However, early systematic reviews have not yielded consistent findings for these associations. This literature review summarizes important new findings from integrating nutrigenomics, hormones, and cytokines in women with Gestational diabetes mellitus and pregnancy-specific urinary incontinence. Changes in maternal metabolism due to hyperglycemia can generate an inflammatory environment with increased inflammatory cytokines. This environment modulated by inflammation can alter tryptophan uptake through food and thus influence the production of serotonin and melatonin. As these hormones seem to have protective effects against smooth muscle dysfunction and to restore the impaired contractility of the detrusor muscle, it is assumed that these changes may favor the onset of urinary incontinence specific to pregnancy.

Saudi Community-Based Screening Study on Genetic Variants in β-Cell Dysfunction and Its Role in Women with Gestational Diabetes Mellitus

BACKGROUND

Diabetes (hyperglycemia) is defined as a multifactorial metabolic disorder in which insulin resistance and defects in pancreatic β-cell dysfunction are two major pathophysiologic abnormalities that underpin towards gestational diabetes mellitus (GDM). TCF7L2, KCNQ1, and KCNJ11 genes are connected to the mechanism of β-cell dysfunction. The purpose of this study was to investigate the genes associated with β-cell dysfunction and their genetic roles in the rs7903146, rs2237892, and rs5219 variants in Saudi women diagnosed with type 2 diabetes mellitus and GDM.

MATERIALS AND METHODS

In this case-control study, 100 women with GDM and 100 healthy volunteers (non-GDM) were recruited. Genotyping was performed using polymerase chain reaction (PCR), followed by restriction fragment length analysis. Validation was performed using Sanger sequencing. Statistical analyses were performed using multiple software packages.

RESULTS

Clinical studies showed a β-cell dysfunction positive association in women with GDM when compared to non-GDM women (p < 0.05). Both rs7903146 (CT vs. CC: OR-2.12 [95%CI: 1.13-3.96]; p = 0.01 & T vs. C: (OR-2.03 [95%CI: 1.32-3.11]; p = 0.001) and rs5219 SNPs (AG vs. AA: OR-3.37 [95%CI: 1.63-6.95]; p = 0.0006 & G vs. A: OR-3.03 [95%CI: 1.66-5.52]; p = 0.0001) showed a positive association with genotype and allele frequencies in women with GDM. ANOVA analysis confirmed that weight (p = 0.02), BMI (p = 0.01), and PPBG (p = 0.003) were associated with rs7903146 and BMI (p = 0.03) was associated with rs2237892 SNPs.

CONCLUSIONS

This study confirms that the SNPs rs7903146 (TCF7L2) and rs5219 (KCNJ11) are strongly associated with GDM in the Saudi population. Future studies should address the limitations of this study.

Development and validation of a multivariable genotype-informed gestational diabetes prediction algorithm for clinical use in the Mexican population: insights into susceptibility mechanisms

INTRODUCTION

Gestational diabetes mellitus (GDM) is underdiagnosed in Mexico. Early GDM risk stratification through prediction modeling is expected to improve preventative care. We developed a GDM risk assessment model that integrates both genetic and clinical variables.

RESEARCH DESIGN AND METHODS

Data from pregnant Mexican women enrolled in the 'Cuido mi Embarazo' (CME) cohort were used for development (107 cases, 469 controls) and data from the 'Mónica Pretelini Sáenz' Maternal Perinatal Hospital (HMPMPS) cohort were used for external validation (32 cases, 199 controls). A 2-hour oral glucose tolerance test (OGTT) with 75 g glucose performed at 24-28 gestational weeks was used to diagnose GDM. A total of 114 single-nucleotide polymorphisms (SNPs) with reported predictive power were selected for evaluation. Blood samples collected during the OGTT were used for SNP analysis. The CME cohort was randomly divided into training (70% of the cohort) and testing datasets (30% of the cohort). The training dataset was divided into 10 groups, 9 to build the predictive model and 1 for validation. The model was further validated using the testing dataset and the HMPMPS cohort.

RESULTS

Nineteen attributes (14 SNPs and 5 clinical variables) were significantly associated with the outcome; 11 SNPs and 4 clinical variables were included in the GDM prediction regression model and applied to the training dataset. The algorithm was highly predictive, with an area under the curve (AUC) of 0.7507, 79% sensitivity, and 71% specificity and adequately powered to discriminate between cases and controls. On further validation, the training dataset and HMPMPS cohort had AUCs of 0.8256 and 0.8001, respectively.

CONCLUSIONS

We developed a predictive model using both genetic and clinical factors to identify Mexican women at risk of developing GDM. These findings may contribute to a greater understanding of metabolic functions that underlie elevated GDM risk and support personalized patient recommendations.

Mouse Models of Gestational Diabetes Mellitus and Its Subtypes: Recent Insights and Pitfalls

Gestational diabetes mellitus (GDM) is currently the most common complication of pregnancy and is defined as a glucose intolerance disorder with recognition during pregnancy. GDM is considered a uniform group of patients in conventional guidelines. In recent years, evidence of the disease's heterogeneity has led to a growing understanding of the value of dividing patients into different subpopulations. Furthermore, in view of the increasing incidence of hyperglycemia outside pregnancy, it is likely that many cases diagnosed as GDM are in fact patients with undiagnosed pre-pregnancy impaired glucose tolerance (IGT). Experimental models contribute significantly to the understanding of the pathogenesis of GDM and numerous animal models have been described in the literature. The aim of this review is to provide an overview of the existing mouse models of GDM, in particular those that have been obtained by genetic manipulation. However, these commonly used models have certain limitations in the study of the pathogenesis of GDM and cannot fully describe the heterogeneous spectrum of this polygenic disease. The polygenic New Zealand obese (NZO) mouse is introduced as a recently emerged model of a subpopulation of GDM. Although this strain lacks conventional GDM, it exhibits prediabetes and an IGT both preconceptionally and during gestation. In addition, it should be emphasized that the choice of an appropriate control strain is of great importance in metabolic studies. The commonly used control strain C57BL/6N, which exhibits IGT during gestation, is discussed in this review as a potential model of GDM.

Myeloperoxidase G-463A and CYBA C242T genetic variants in gestational diabetes mellitus

Oxidative stress plays an important role in the pathophysiology of gestational diabetes mellitus (GDM). We investigated the relationship between NADPH oxidase p22phox subunit (CYBA) C242T (rs4673) and myeloperoxidase (MPO) G-463A (rs2333227) genetic variants and GDM in 719 patients with GDM and 1205 control women. Clinical, metabolic, and oxidative stress parameters were analyzed. We found that frequencies of the A allele (15.6% vs 12.3%) and GA + AA genotype (28.5% vs 23.2%) of the MPO G-463A variation were significantly higher in patients with GDM than in the control women (OR = 1.318, 95% CI: 1.068-1.625, P = 0.010 for the dominant model; OR = 1.999, 95% CI: 1.040-3.843, P = 0.034 for the recessive model; OR = 1.320, 95% CI: 1.095-1.591, P = 0.004 for the allele model). Genotype GA + AA remained a significant predictor of GDM in a logistic regression model including age and BMI at delivery (OR = 1.282, 95% CI: 1.037‒1.583, P = 0.021). Furthermore, the ‒463A allele was associated with higher TG and the 242T allele was related to higher pre-pregnancy BMI and oxidative stress index in all subjects (P < 0.05). The 242T allele was also associated with higher homeostatic model assessment of insulin resistance but lower serum total antioxidant capacity in patients with GDM (P < 0.05). We conclude that the MPO G-463A, but not the CYBA C242T, genetic variation is associated with an increased risk of GDM in Chinese women. These two genetic polymorphisms may be linked to obesity, dyslipidemia, insulin resistance, and oxidative stress.

[Cholesterol 7α-Hydroxylase Gene-204A/C Polymorphism in Normal and Gestational Diabetic Pregnancies]

Objective

To investigate the cholesterol 7α-hydroxylase gene ( CYP7A1)-204A/C single nucleotide polymorphism and its relationship with the blood lipid levels of pregnant women with gestational diabetes mellitus (GDM) and normal pregnant women.

Methods

The genotype and allele frequencies of CYP7A1-204A/C gene polymorphism of 1037 normal pregnant women, the normal controls, and 627 pregnant women with GDM were examined by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) analysis. Total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C) and blood glucose (Glu) were measured by enzymatic assay. Chemiluminescence determination of plasma insulin (Ins) was conducted. Apolipoproteins A1 (apoA1) and B (apoB) were measured by the turbidimetric immunoassay.

Results

Allele frequencies of A and C at the CYP7A1-204A/C polymorphic locus were 0.586 and 0.414, respectively, in the GDM group and 0.557 and 0.443, respectively in the control group. The distribution of genotype frequencies in both groups showed conformity with the Hardy-Weinberg principle. There was no significant difference in allele and genotype frequencies between the GDM group and the control group. In the control group, carriers of the genotype AA were associated with significantly higher concentrations of apoA1 and lower levels of Ins and homeostatic model assessment of insulin resistance (HOMA-IR) compared with those with genotype CC (all P<0.05). In the non-obese subgroup of the control subjects, carriers of the genotype CC were associated with significantly higher plasma TG or apoA1 levels compared with those with genotype AA ( P<0.05). In the GDM group, carriers with genotype AA of CYP7A1-204A/C polymorphism had elevated levels of gestational weight gain (GWG) compared with those with genotype CC ( P<0.05).

Conclusion

These results suggest that 204A/C polymorphism in the CYP7A1 gene is not associated with GDM, but may be closely associated with gestational weight gain in pregnant women with GDM. Variants in this locus are strongly associated with plasma apoA1, Ins, and HOMA-IR levels in the controls and elevated plasma TG levels in non-obese controls.

Interactive effect of prepregnancy overweight/obesity and GDM history on prevalence of GDM in biparous women

BACKGROUND

Prepregnancy overweight/obesity (OWO) and gestational diabetes mellitus (GDM) history may increase the prevalence of GDM in parous women, but little is known about their potential combined effect on the prevalence of GDM in biparous women.

OBJECTIVE

This study aims to explore the interactive effect of prepregnancy overweight/obesity (OWO) and GDM history on the prevalence of GDM in biparous women.

METHODS

A retrospective study was conducted on 16,282 second-birth women who delivered a single neonate at ≧28 weeks of gestation twice. Logistic regression was used to assess the independent and multiplicative interactions of prepregnancy overweight/obesity (OWO) and GDM history on the risk of GDM in biparous women. Additive interactions were calculated using an Excel sheet that was made by Anderson to calculate relative excess risk.

RESULTS

A total of 14,998 participants were included in this study. Both prepregnancy OWO and GDM history were independently associated with an increased risk of GDM in biparous women (odds ratio (OR) = 19.225, 95% confidence interval (CI) = 17.106, 21.607 and OR = 6.826, 95% CI = 6.085, 7.656, respectively). The coexistence of prepregnancy OWO and GDM history was associated with GDM, with an adjusted OR of 1.754 (95% CI, 1.625, 1.909) compared to pregnant women without either condition. The additive interaction between prepregnancy OWO and GDM history was found to be not significant with regard to GDM in biparous women.

CONCLUSIONS

Prepregnancy OWO and GDM history both increase the risk of GDM in biparous women and have multiplicative interactions but not additive interactions.

Predictability of HOMA-IR for Gestational Diabetes Mellitus in Early Pregnancy Based on Different First Trimester BMI Values

Objective: To investigate the ability of homeostasis model assessment of insulin resistance (HOMA-IR) in early pregnancy for predicting gestational diabetes mellitus (GDM) in Chinese women with different first-trimester body mass index (FT-BMI) values. Methods: Baseline characteristics and laboratory tests were collected at the first prenatal visit (6−12 weeks of gestation). GDM was diagnosed by a 75 g oral glucose tolerance test (OGTT) at 24−28 weeks of gestation. Partial correlation analysis and binary logistic regression were applied to identify the association between HOMA-IR and GDM. The cutoff points for predicting GDM were estimated using receiver operating characteristic (ROC) curve analysis. Results: Of the total of 1343 women, 300 (22.34%) were diagnosed with GDM in the 24−28 weeks of gestation. Partial correlation analysis and binary logistic regression verified HOMA-IR as a significant risk factor for GDM in the normal weight subgroup (FT-BMI < 24 kg/m2) (adjusted OR 2.941 [95% CI 2.153, 4.016], P < 0.001), overweight subgroup (24.0 kg/m2 ≤ FT-BMI < 28.0 kg/m2) (adjusted OR 3.188 [95% CI 2.011, 5.055], P < 0.001), and obese subgroup (FT-BMI ≥ 28.0 kg/m2) (adjusted OR 9.415 [95% CI 1.712, 51.770], p = 0.01). The cutoff values of HOMA-IR were 1.52 (area under the curve (AUC) 0.733, 95% CI 0.701−0.765, p < 0.001) for all participants, 1.43 (AUC 0.691, 95% CI 0.651−0.730, p < 0.001) for normal weight women, 2.27 (AUC 0.760, 95% CI 0.703−0.818, p < 0.001) for overweight women, and 2.31 (AUC 0.801, 95% CI 0.696−0.907, p < 0.001) for obese women. Conclusions: Increased HOMA-IR in early pregnancy is a risk factor for GDM, and HOMA-IR can be affected by body weight. The cutoff value of HOMA-IR to predict GDM should be distinguished by different FT-BMI values.

Genetic Risk Factors and Gene-Lifestyle Interactions in Gestational Diabetes

Paralleling the increasing trends of maternal obesity, gestational diabetes (GDM) has become a global health challenge with significant public health repercussions. In addition to short-term adverse outcomes, such as hypertensive pregnancy disorders and fetal macrosomia, in the long term, GDM results in excess cardiometabolic morbidity in both the mother and child. Recent data suggest that women with GDM are characterized by notable phenotypic and genotypic heterogeneity and that frequencies of adverse obstetric and perinatal outcomes are different between physiologic GDM subtypes. However, as of yet, GDM treatment protocols do not differentiate between these subtypes. Mapping the genetic architecture of GDM, as well as accurate phenotypic and genotypic definitions of GDM, could potentially help in the individualization of GDM treatment and assessment of long-term prognoses. In this narrative review, we outline recent studies exploring genetic risk factors of GDM and later type 2 diabetes (T2D) in women with prior GDM. Further, we discuss the current evidence on gene-lifestyle interactions in the development of these diseases. In addition, we point out specific research gaps that still need to be addressed to better understand the complex genetic and metabolic crosstalk within the mother-placenta-fetus triad that contributes to hyperglycemia in pregnancy.

Multi-ancestry genome-wide association study of gestational diabetes mellitus highlights genetic links with type 2 diabetes

Gestational diabetes mellitus (GDM) is associated with increased risk of pregnancy complications and adverse perinatal outcomes. GDM often reoccurs and is associated with increased risk of subsequent diagnosis of type 2 diabetes (T2D). To improve our understanding of the aetiological factors and molecular processes driving the occurrence of GDM, including the extent to which these overlap with T2D pathophysiology, the GENetics of Diabetes In Pregnancy Consortium assembled genome-wide association studies of diverse ancestry in a total of 5485 women with GDM and 347 856 without GDM. Through multi-ancestry meta-analysis, we identified five loci with genome-wide significant association (P < 5 × 10-8) with GDM, mapping to/near MTNR1B (P = 4.3 × 10-54), TCF7L2 (P = 4.0 × 10-16), CDKAL1 (P = 1.6 × 10-14), CDKN2A-CDKN2B (P = 4.1 × 10-9) and HKDC1 (P = 2.9 × 10-8). Multiple lines of evidence pointed to the shared pathophysiology of GDM and T2D: (i) four of the five GDM loci (not HKDC1) have been previously reported at genome-wide significance for T2D; (ii) significant enrichment for associations with GDM at previously reported T2D loci; (iii) strong genetic correlation between GDM and T2D and (iv) enrichment of GDM associations mapping to genomic annotations in diabetes-relevant tissues and transcription factor binding sites. Mendelian randomization analyses demonstrated significant causal association (5% false discovery rate) of higher body mass index on increased GDM risk. Our results provide support for the hypothesis that GDM and T2D are part of the same underlying pathology but that, as exemplified by the HKDC1 locus, there are genetic determinants of GDM that are specific to glucose regulation in pregnancy.

Maternal diabetes negatively impacts fetal health

Diabetes is a chronic metabolic disease affecting an increasing number of people. Although diabetes has negative health outcomes for diagnosed individuals, a population at particular risk are pregnant women, as diabetes impacts not only a pregnant woman's health but that of her child. In this review, we cover the current knowledge and unanswered questions on diabetes affecting an expectant mother, focusing on maternal and fetal outcomes.

Polygenic Risk Score and Risk Factors for Gestational Diabetes

Gestational diabetes mellitus (GDM) is a common complication of pregnancy that adversely affects maternal and offspring health. A variety of risk factors, such as BMI and age, have been associated with increased risks of gestational diabetes. However, in many cases, gestational diabetes occurs in healthy nulliparous women with no obvious risk factors. Emerging data suggest that the tendency to develop gestational diabetes has genetic and environmental components. Here we develop a polygenic risk score for GDM and investigate relationships between its genetic architecture and genetically constructed risk factors and biomarkers. Our results demonstrate that the polygenic risk score can be used as an early screening tool that identifies women at higher risk of GDM before its onset allowing comprehensive monitoring and preventative programs to mitigate the risks.

Common single-nucleotide polymorphisms combined with a genetic risk score provide new insights regarding the etiology of gestational diabetes mellitus

AIMS

Few studies have constructed a genetic risk score (GRS) to predict the risk of gestaional diabetes mellitus (GDM). We tested the hypothesis that single-nucleotide polymorphisms (SNPs) confirmed for diabetes and obesity and the GRS are associated with GDM.

METHODS

We conducted a case-control study comprising 971 GDM cases and 1682 controls from the University of Hong Kong Shenzhen Hospital. A total of 1448 SNPs reported with type 2 diabetes (T2D), type 1 diabetes (T1D), and obesity were selected and the GRS based on SNPs associated with GDM was created.

RESULTS

We confirmed that rs10830963 (OR = 1.41,95% CI = 1.25, 1.59) in MTNR1B and rs2206734 (OR = 1.38, 95% CI = 1.22, 1.55) in CDKAL1 were strongly associated with the risk of GDM. Compared with participants with GRS based on T2D SNPs in the low tertile, the ORs of GDM across increasing GRS tertiles were 1.63 (95% CI 1.29, 2.06) and 2.72 (95% CI 2.18, 3.38) in the middle and high tertile, respectively. The positive associations between the GRS and the risk of GDM were also observed in GRS based on obesity/waist-to-hip ratio (WHR)/body mass index (BMI) SNPs. The resulting GRS for each allele increase was significantly associated with higher glycemic indices and lower HOMA-B values for GRS based on T2D SNPs, but not for GRS based on T1D SNPs and GRS based on obesity/WHR/BMI SNPs.

CONCLUSION

These findings indicate that GDM may share a common genetic background with T2D and obesity and that SNPs associated with insulin secretion defects have a vital role in the development of GDM.

Genetic risk of type 2 diabetes modifies the effects of a lifestyle intervention aimed at the prevention of gestational and postpartum diabetes

AIMS/HYPOTHESIS

The aim of this study was to assess the interaction between genetic risk and lifestyle intervention on the occurrence of gestational diabetes mellitus (GDM) and postpartum diabetes.

METHODS

The RADIEL study is an RCT aimed at prevention of GDM and postpartum diabetes through lifestyle intervention. Participants with a BMI ≥30 kg/m2 and/or prior GDM were allocated to intervention and control groups before pregnancy or in early pregnancy. The study visits took place every 3 months before pregnancy, once in each trimester, and at 6 weeks and 6 and 12 months postpartum. We calculated a polygenic risk score (PRS) based on 50 risk variants for type 2 diabetes.

RESULTS

Altogether, 516 participants provided genetic and GDM data. The PRS was associated with higher glycaemic levels (fasting glucose and/or HbA1c) and a lower insulin secretion index in the second and third trimesters and at 12 months postpartum, as well as with a higher occurrence of GDM and glycaemic abnormalities at 12 months postpartum (n = 356). There was an interaction between the PRS and lifestyle intervention (p=0.016 during pregnancy and p=0.024 postpartum) when analysing participants who did not have GDM at the first study visit during pregnancy (n = 386). When analysing women in tertiles according to the PRS, the intervention was effective in reducing the age-adjusted occurrence of GDM only among those with the highest genetic risk (OR 0.37; 95% CI 0.17, 0.82). The risk of glycaemic abnormalities at 12 months postpartum was reduced in the same group after adjusting additionally for BMI, parity, smoking and education (OR 0.35; 95% CI 0.13, 0.97).

CONCLUSIONS/INTERPRETATION

Genetic predisposition to diabetes modifies the response to a lifestyle intervention aimed at prevention of GDM and postpartum diabetes. This suggests that lifestyle intervention may benefit from being tailored according to genetic risk.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT01698385.

KCNJ11 and KCNQ1 Gene Polymorphisms and Placental Expression in Women with Gestational Diabetes Mellitus

Gestational diabetes mellitus (GDM) represents carbohydrate intolerance in pregnant women. The pathogenesis of GDM is very complex, but abnormalities in insulin production and secretion underlie the disease. Potassium channels play an important role in insulin production and secretion. The family of potassium channels includes (among others) the potassium inwardly rectifying channel, subfamily J, member 11 (KCNJ11) and voltage-gated K+ channel (KCNQ1). The aim of the study was to examine the distribution of the KCNJ11 rs5219 and KCNQ1 rs151290 and rs2237892 gene polymorphisms in women with GDM and pregnant women with normal carbohydrate tolerance, to verify whether these polymorphisms are risk factors for GDM. This study included 204 Caucasian pregnant women with GDM and 207 pregnant women with normal glucose tolerance (NGT) from the West Pomeranian region of Poland. The diagnosis of GDM was based on a 75 g oral glucose tolerance test (OGTT) at 24–28 weeks gestation. There were no statistically significant differences in distribution of the KCNJ11 rs5219 and KCNQ1 rs151290 and rs2237892 gene polymorphisms between women with GDM and pregnant women with normal carbohydrate tolerance. Moreover, there were no statistically significant associations between the studied genotypes and the selected clinical parameters in women with GDM. The results of our study suggest that the KCNJ11 rs5219 and KCNQ1 rs2237892 and rs151290 gene polymorphisms are not significant risk factors associated with the development of GDM in our population. There were also no differences in the expression of KCNJ11 and KCNQ1 genes in the placenta of women with GDM and normal carbohydrate tolerance. However, an association between KCNJ11 gene expression in placenta and APGAR score in newborns was found.

Altered Lipid Metabolism in Obese Women With Gestational Diabetes and Associations With Offspring Adiposity

CONTEXT

Gestational diabetes (GDM) affects 20 million women/year worldwide and is associated with childhood obesity. Infants of affected mothers have increased adiposity from birth, which leads to obesity in later life. However, it remains unknown whether the effect of GDM upon neonatal body composition is due to hyperglycemia alone or is mediated by other pathways.

OBJECTIVE

To investigate plasma lipid profiles in obese women according to GDM diagnosis, infant birthweight percentiles, and adiposity.

DESIGN

Prospective cohort from UPBEAT trial (ISRCTN 89971375).

SETTING

Hospital and community.

PATIENTS

867 obese pregnant women recruited in early pregnancy, assessed at 28 weeks for GDM. Offspring anthropometry was assessed at birth.

OUTCOME (PRESPECIFIED)

Neonatal birth percentile and abdominal circumference.

METHODS

Lipidomic profiling in the fasting plasma oral glucose tolerance test sample using direct infusion mass spectrometry. Analysis included logistic/linear regression, unadjusted and adjusted for maternal age, body mass index, parity, ethnicity, UPBEAT trial arm, and fetal sex. The limit of significance was P = 0.05 for offspring anthropometry and P = 0.002 for lipidomic data.

RESULTS

GDM in obese women was associated with elevated plasma concentrations of specific diglycerides [DG(32:0)] and triglycerides [TG(48:0), (50:1), (50:2)] containing fatty acids (16:0), (16:1), (18:0), and (18:1), consistent with increased de novo lipogenesis. In the whole cohort, these species were associated with birthweight percentile and neonatal abdominal circumference. Effects upon infant abdominal circumference remained significant after adjustment for maternal glycemia.

CONCLUSIONS

Increased de novo lipogenesis-related species in pregnant women with obesity and GDM are associated with measures of offspring adiposity and may be a target for improving lifelong health.

The role of insulin-like growth factor 2 mRNA binding proteins in female reproductive pathophysiology

Insulin-like growth factor 2 (IGF2) mRNA binding proteins (IMPs) family belongs to a highly conserved family of RNA-binding proteins (RBPs) and is responsible for regulating RNA processing including localization, translation and stability. Mammalian IMPs (IMP1-3) take part in development, metabolism and tumorigenesis, where they are believed to play a major role in cell growth, metabolism, migration and invasion. IMPs have been identified that are expressed in ovary, placenta and embryo. The up-to-date evidence suggest that IMPs are involved in folliculogenesis, oocyte maturation, embryogenesis, implantation, and placentation. The dysregulation of IMPs not only contributes to carcinogenesis but also disturbs the female reproduction, and may participate in the pathogenesis of reproductive diseases and obstetric syndromes, such as polycystic ovary syndrome (PCOS), pre-eclampsia (PE), gestational diabetes mellitus (GDM) and gynecological tumors. In this review, we summarize the role of IMPs in female reproductive pathophysiology, and hope to provide new insights into the identification of potential therapeutic targets.

Gestational Diabetes Mellitus Among Pregnant Women Attending Ante-natal Clinic at a Secondary Care Health Facility in Haryana, India

Introduction: Gestational diabetes has serious health effects during pregnancy and childbirth. We estimated the occurrence of gestational diabetes mellitus (GDM) among pregnant women in a secondary care hospital in Haryana.

Methods: It was a hospital-based cross-sectional study, done in an ante-natal clinic (ANC) at a sub-district hospital (SDH), Faridabad district of Haryana, India. Eligible pregnant women attending the ANC clinic were recruited. An oral glucose tolerance test (OGTT) with 75 g of glucose was done with a collection of blood for fasting blood sugar (FBS) and two-hour post-OGTT blood glucose. A pre-tested semi-structured interview schedule was administered. Both the modified International Association of the Diabetes and Pregnancy Study Groups criteria (IADPSGC) and the Diabetes in Pregnancy Study Group of India (DIPSI) criteria were used. Data were presented as percentages, means, standard deviation, and 95% confidence interval (CI). Bi-variable and multi-variable logistic regressions were done. The level of significance was set at 0.05.

Results: Of the 623 eligible participants, 66.1% were within the 20-25 age group. The GDM was found in 14.1% (95%CI: 11.5-17.1) participants as per modified IADPSG criteria and 6.7% (95%CI: 4.9-9.0) participants as per DIPSI criteria, respectively. Increasing age [adjusted odds ratio (AOR): 1.24 (95% CI: 1.05-1.47), p=0.008] and increasing years of schooling [AOR: 1.19 (1.01-1.41), p=0.032] were significantly associated with GDM by DIPSI criteria. Family history of DM was also found to have an increased odds with GDM using modified IADPSG criteria [AOR 2.87 (95% CI: 1.09-7.54), p=0.032]. 

Conclusion: Considerable proportion of pregnant women were found to have GDM in a Sub-district hospital at Ballabgarh in north India. The study highlighted the need and generated evidence about the feasibility of GDM screening utilizing routine staff in a secondary care facility.

Association of glucokinase gene and glucokinase regulatory protein gene polymorphisms with gestational diabetes mellitus: A case-control study

OBJECTIVES

The aim of this study was to investigate the association of glucokinase (GCK) gene, glucokinase regulatory protein (GCKR) gene polymorphisms with the susceptibility to GDM in Chinese population.

RESEARCH DESIGN AND METHODS

This case-control study included 835 GDM patients and 870 non-diabetic pregnant women who had their prenatal examinations at 24-28 gestational weeks at the Maternal and Child Health Hospital of Hubei Province from January 15, 2018 to March 31, 2019. The nurses were trained to collect clinical information and blood samples. The candidate single nucleotide polymorphism (SNPs, GCK rs1799884, rs4607517, rs10278336, rs2268574, rs730497 and GCKR rs780094, rs1260326) were genotyped on Sequenom Massarray platform. Statistical analysis including independent sample t test, chi-square test, logistic regression and one-way ANOVA were performed to evaluate the differences in allele and genotype distributions and their correlations with the odds of GDM.

RESULTS

There were statistically significant differences in age, pre-gestational BMI, education level and family history of diabetes between case and control group (P < 0.05). After adjusting for these confounders, GCK rs1799884 was still significantly associated with GDM (P < 0.05), but there were no significant associations between rs4607517, rs10278336 and rs2268574, rs780094 and rs1260326 polymorphisms and GDM odds (P > 0.05). In addition, the pregnant women with rs4607517 TT genotype had the significantly higher fasting blood glucose level than CC genotype (P < 0.05).

CONCLUSION

GCK rs1799884 mutation is associated with higher GDM odds in Chinese population. Further larger studies are needed to explore the association between GCK and GCKR polymorphisms and GDM susceptibility.

Pathophysiological Role of Genetic Factors Associated With Gestational Diabetes Mellitus

Gestational Diabetes Mellitus (GDM) is a highly prevalent maternal pathology characterized by maternal glucose intolerance during pregnancy that is, associated with severe complications for both mother and offspring. Several risk factors have been related to GDM; one of the most important among them is genetic predisposition. Numerous single nucleotide polymorphisms (SNPs) in genes that act at different levels on various tissues, could cause changes in the expression levels and activity of proteins, which result in glucose and insulin metabolism dysfunction. In this review, we describe various SNPs; which according to literature, increase the risk of developing GDM. These SNPs include: (1) those associated with transcription factors that regulate insulin production and excretion, such as rs7903146 (TCF7L2) and rs5015480 (HHEX); (2) others that cause a decrease in protective hormones against insulin resistance such as rs2241766 (ADIPOQ) and rs6257 (SHBG); (3) SNPs that cause modifications in membrane proteins, generating dysfunction in insulin signaling or cell transport in the case of rs5443 (GNB3) and rs2237892 (KCNQ1); (4) those associated with enzymes such as rs225014 (DIO2) and rs9939609 (FTO) which cause an impaired metabolism, resulting in an insulin resistance state; and (5) other polymorphisms, those are associated with growth factors such as rs2146323 (VEGFA) and rs755622 (MIF) which could cause changes in the expression levels of these proteins, producing endothelial dysfunction and an increase of pro-inflammatory cytokines, characteristic on GDM. While the pathophysiological mechanism is unclear, this review describes various potential effects of these polymorphisms on the predisposition to develop GDM.

CDKAL1 gene rs7756992 A/G and rs7754840 G/C polymorphisms are associated with gestational diabetes mellitus in a sample of Bangladeshi population: implication for future T2DM prophylaxis

BACKGROUND

Association of single nucleotide polymorphisms (SNP) rs7756992 A/G and rs7754840 G/C of cyclin-dependent kinase 5 regulatory subunit-associated protein 1-like 1 (CDKAL1) gene with the susceptibility of gestational diabetes mellitus (GDM) has been studied in a group of Bangladeshi women.

METHODS

In this case-control study, 212 GDM patients and 256 control subjects were genotyped for rs7756992 and rs7754840 by PCR-RFLP and TaqMan™ allelic discrimination assay method respectively. Genotyping results were confirmed by DNA sequencing and replicated TaqMan™ assay. The odds ratios and their 95% confidence interval were calculated by logistic regression to determine the associations between genotypes and GDM.

RESULTS

The genotype frequencies of rs7756992-AA/AG/GG in the GDM group and the control group were 37%/48%, 53%/45%, 10%/7% and those of rs7754840-CC/CG/GG were 51%/55%, 40.1%/39.8%, 9%/5% respectively. Under dominant and log additive models rs7756992 was revealed significantly associated with GDM after being adjusted for family history of diabetes (FHD) and gravidity. Conversely, rs7754840 was significantly associated (P = 0.047) with GDM only under the recessive model after the same adjustment. The risk allele frequency of both SNPs was higher in the GDM group but significantly (P = 0.029) increased prevalence was observed in the rs7756992 G allele. When positive FHD and risk alleles of these SNPs were synergistically present in any pregnant woman, the chance of developing GDM was augmented by many folds. The codominant model revealed 2.5 and 2.1 folds increase in odds by AG (rs7756992) and GC (rs7754840) genotypes and 3.7 and 4.5 folds by GG (rs7756992) and CC (rs7754840) genotypes respectively. A significant 2.7 folds (P = 0.038) increase in odds of GDM resulted from the interaction of rs7756992 and family history of diabetes under the dominant model. The cumulative effect of multigravidity and risk alleles of these SNPs increased the odds of GDM more than 1.5 folds in different genotypes.

CONCLUSION

This study not only revealed a significant association between rs7756992 and rs7754840 with GDM but also provided the possibility as potential markers for foretelling about GDM and type 2 diabetes mellitus in Bangladeshi women.

An early prediction model for gestational diabetes mellitus based on genetic variants and clinical characteristics in China

OBJECTIVES

To evaluate the influence of genetic variants and clinical characteristics on the risk of gestational diabetes mellitus (GDM) and to construct and verify a prediction model of GDM in early pregnancy.

METHODS

Four hundred seventy five women with GDM and 487 women without, as a control, were included to construct the prediction model of GDM in early pregnancy. Both groups had complete genotyping results and clinical data. They were randomly divided into a trial cohort (70%) and a test cohort (30%). Then, the model validation cohort, including 985 pregnant women, was used for the external validation of the GDM early pregnancy prediction model.

RESULTS

We found maternal age, gravidity, parity, BMI and family history of diabetes were significantly associated with GDM (OR > 1; P < 0.001), and assisted reproduction was a critical risk factor for GDM (OR = 1.553, P = 0.055). MTNR1B rs10830963, C2CD4A/B rs1436953 and rs7172432, CMIP rs16955379 were significantly correlated with the incidence of GDM (AOR > 1, P < 0.05). Therefore, these four genetic susceptible single nucleotide polymorphisms (SNPs) and six clinical characteristics were included in the construction of the GDM early pregnancy prediction model. In the trial cohort, a predictive model of GDM in early pregnancy was constructed, in which genetic risk score was independently associated with GDM (AOR = 2.061, P < 0.001) and was the most effective predictor with the exception of family history of diabetes. The ROC-AUC of the prediction model was 0.727 (95% CI 0.690-0.765), and the sensitivity and specificity were 69.9% and 64.0%, respectively. The predictive power was also verified in the test cohort and the validation cohort.

CONCLUSIONS

Based on the genetic variants and clinical characteristics, this study developed and verified the early pregnancy prediction model of GDM. This model can help screen out the population at high-risk for GDM in early pregnancy, and lifestyle interventions can be performed for them in a timely manner in early pregnancy.

Sleep Disturbances Before Pregnancy and Subsequent Risk of Gestational Diabetes Mellitus

PURPOSE

To investigate the relationship between sleep disturbances before pregnancy and the subsequent risk for gestational diabetes mellitus (GDM).

PATIENTS AND METHODS

Pregnant women who attended antenatal clinic before the 12th gestational week between September 2019 and June 2020 were enrolled. The sleep status at the month before the last menstrual period was collected by filling the Pittsburgh Sleep Quality Index (PSQI) and Berlin Questionnaire (BQ) to evaluate the sleep duration, quality and the risk of obstructive sleep apnea (OSA). With monthly antenatal care, the oral glucose tolerance test (OGTT) was performed during 24-28 gestational weeks. According to the results, GDM and non-GDM group were classified. The sleep status and baseline characters were compared between the two groups.

RESULTS

A total of 355 pregnant women were enrolled in this study, and 63 of them (17.7%) were diagnosed with GDM. Univariate analysis showed that maternal age, body mass index (BMI), family history of diabetes, PSQI score and positive BQ were associated with GDM (p < 0.05). Maternal age (aOR 1.10, 95% CI, 1.01-1.17), BMI before pregnancy (aOR 1.12, 95% CI, 1.02-1.23), family history of diabetes (aOR 2.35, 95% CI, 1.33-4.17), positive BQ (aOR 4.03, 95% CI, 1.04-15.63) were independent risk factors for GDM in multivariate analysis. The decision tree indicated that among the pregnant women with BMI >20.6 kg/m² and age >28.5, the risk for GDM with positive BQ increased from 27.5% to 66.7%.

CONCLUSION

The high risk of OSA before pregnancy may increase the risk for GDM during pregnancy.

Genetic risk score to improve prediction and treatment in gestational diabetes mellitus

Diabetes mellitus is a chronic disease caused by the interaction of genetics and the environment that can lead to chronic damage to many organ systems. Genome-wide association studies have identified accumulating single-nucleotide polymorphisms related to type 2 diabetes mellitus and gestational diabetes mellitus. Genetic risk score (GRS) has been utilized to evaluate the incidence risk to improve prediction and optimize treatments. This article reviews the research progress in the use of the GRS in diabetes mellitus in recent years and discusses future prospects.

Genetic variants for prediction of gestational diabetes mellitus and modulation of susceptibility by a nutritional intervention based on a Mediterranean diet

HYPOTHESIS

Gestational diabetes mellitus (GDM) entails a complex underlying pathogenesis, with a specific genetic background and the effect of environmental factors. This study examines the link between a set of single nucleotide polymorphisms (SNPs) associated with diabetes and the development of GDM in pregnant women with different ethnicities, and evaluates its potential modulation with a clinical intervention based on a Mediterranean diet.

METHODS

2418 women from our hospital-based cohort of pregnant women screened for GDM from January 2015 to November 2017 (the San Carlos Cohort, randomized controlled trial for the prevention of GDM ISRCTN84389045 and real-world study ISRCTN13389832) were assessed for evaluation. Diagnosis of GDM was made according to the International Association of Diabetes and Pregnancy Study Groups (IADPSG) criteria. Genotyping was performed by IPLEX MassARRAY PCR using the Agena platform (Agena Bioscience, SanDiego, CA). 110 SNPs were selected for analysis based on selected literature references. Statistical analyses regarding patients' characteristics were performed in SPSS (Chicago, IL, USA) version 24.0. Genetic association tests were performed using PLINK v.1.9 and 2.0 software. Bioinformatics analysis, with mapping of SNPs was performed using STRING, version 11.5.

RESULTS

Quality controls retrieved a total 98 SNPs and 1573 samples, 272 (17.3%) with GDM and 1301 (82.7%) without GDM. 1104 (70.2%) were Caucasian (CAU) and 469 (29.8%) Hispanic (HIS). 415 (26.4%) were from the control group (CG), 418 (26.6%) from the nutritional intervention group (IG) and 740 (47.0%) from the real-world group (RW). 40 SNPs (40.8%) presented some kind of significant association with GDM in at least one of the genetic tests considered. The nutritional intervention presented a significant association with GDM, regardless of the variant considered. In CAU, variants rs4402960, rs7651090, IGF2BP2; rs1387153, rs10830963, MTNR1B; rs17676067, GLP2R; rs1371614, DPYSL5; rs5215, KCNJ1; and rs2293941, PDX1 were significantly associated with an increased risk of GDM, whilst rs780094, GCKR; rs7607980, COBLL1; rs3746750, SLC17A9; rs6048205, FOXA2; rs7041847, rs7034200, rs10814916, GLIS3; rs3783347, WARS; and rs1805087, MTR, were significantly associated with a decreased risk of GDM, In HIS, variants significantly associated with increased risk of GDM were rs9368222, CDKAL1; rs2302593, GIPR; rs10885122, ADRA2A; rs1387153, MTNR1B; rs737288, BACE2; rs1371614, DPYSL5; and rs2293941, PDX1, whilst rs340874, PROX1; rs2943634, IRS1; rs7041847, GLIS3; rs780094, GCKR; rs563694, G6PC2; and rs11605924, CRY2 were significantly associated with decreased risk for GDM.

CONCLUSIONS

We identify a core set of SNPs in their association with diabetes and GDM in a large cohort of patients from two main ethnicities from a single center. Identification of these genetic variants, even in the setting of a nutritional intervention, deems useful to design preventive and therapeutic strategies.

Association of ACE2 gene functional variants with gestational diabetes mellitus risk in a southern Chinese population

OBJECTIVE

To explore the relationship between angiotensin-converting enzyme 2 (ACE2) genetic variants and gestational diabetes mellitus (GDM) in a southern Chinese population.

METHODS

Potential functional variants (rs2106809, rs6632677, and rs2074192) of ACE2 were selected and genotyped in 566 GDM patients and 710 normal pregnaõncies in Guilin, China. The odds ratio (OR) and its corresponding 95% confidence interval (CI) were used to evaluate the association between genetic variant and GDM risk, and then the false positive report probability, multifactor dimensional reduction (MDR), and bioinformatics tools were used to confirm the significant association in the study.

RESULTS

After adjusting for age and prepregnancy body mass index, logistic regression analysis showed that ACE2 rs6632677 was significantly associated with a decreased risk of GDM (CC vs. GG: adjusted OR = 0.09, 95% CI: 0.01 - 0.71, P = .023; GC/CC vs. GG: adjusted OR = 0.68, 95% CI = 0.46 - 0.99, P = .048; and CC vs. GG/GC: adjusted OR = 0.09, 95% CI = 0.01 - 0.72, P = .024), whereas rs2074192 was associated with increased GDM risk (TT vs. CC/CT: adjusted OR = 1.38, 95% CI = 1.08 - 1.75, P = .009). Furthermore, we found that rs6632677 interacted with SBP (P _interaction = .043) and FPG (P _interaction = .021) and rs2074192 interacted with HDL-c (P _interaction = .029) and LDL-c (P _interaction = .035) to influence the GDM risk of the individual. In the MDR analysis, the rs6632677 was the best one-locus model, and the three-loci model was the best interaction model to predict GDM risk. In addition, functional analysis confirmed that rs2074192 may regulate the splicing process of ACE2 gene.

CONCLUSION

ACE2 gene variants are significantly associated with the risk of GDM via gene-gene and gene-environment combinations. The rs2074192 C > T affects the splicing of the ACE2 gene, which may be a potential mechanism leading to the changed susceptibility of an individual female during pregnancy to GDM.

The relationship between hair metabolites, air pollution exposure and gestational diabetes mellitus: A longitudinal study from pre-conception to third trimester

BACKGROUND

Gestational diabetes mellitus (GDM) is a metabolic condition defined as glucose intolerance with first presentation during pregnancy. Many studies suggest that environmental exposures, including air pollution, contribute to the pathogenesis of GDM. Although hair metabolite profiles have been shown to reflect pollution exposure, few studies have examined the link between environmental exposures, the maternal hair metabolome and GDM. The aim of this study was to investigate the longitudinal relationship (from pre-conception through to the third trimester) between air pollution exposure, the hair metabolome and GDM in a Chinese cohort.

METHODS

A total of 1020 women enrolled in the Complex Lipids in Mothers and Babies (CLIMB) birth cohort were included in our study. Metabolites from maternal hair segments collected pre-conception, and in the first, second, and third trimesters were analysed using gas chromatography-mass spectrometry (GC-MS). Maternal exposure to air pollution was estimated by two methods, namely proximal and land use regression (LUR) models, using air quality data from the air quality monitoring station nearest to the participant's home. Logistic regression and mixed models were applied to investigate associations between the air pollution exposure data and the GDM associated metabolites.

RESULTS

Of the 276 hair metabolites identified, the concentrations of fourteen were significantly different between GDM cases and non-GDM controls, including some amino acids and their derivatives, fatty acids, organic acids, and exogenous compounds. Three of the metabolites found in significantly lower concentrations in the hair of women with GDM (2-hydroxybutyric acid, citramalic acid, and myristic acid) were also negatively associated with daily average concentrations of PM_2.5, PM₁₀, SO₂, NO₂, CO and the exposure estimates of PM_2.5 and NO_2, and positively associated with O₃.

CONCLUSIONS

This study demonstrated that the maternal hair metabolome reflects the longitudinal metabolic changes that occur in response to environmental exposures and the development of GDM.

Membrane Melatonin Receptors Activated Cell Signaling in Physiology and Disease

The pineal hormone melatonin has attracted great scientific interest since its discovery in 1958. Despite the enormous number of basic and clinical studies the exact role of melatonin in respect to human physiology remains elusive. In humans, two high-affinity receptors for melatonin, MT1 and MT2, belonging to the family of G protein-coupled receptors (GPCRs) have been cloned and identified. The two receptor types activate Gi proteins and MT2 couples additionally to Gq proteins to modulate intracellular events. The individual effects of MT1 and MT2 receptor activation in a variety of cells are complemented by their ability to form homo- and heterodimers, the functional relevance of which is yet to be confirmed. Recently, several melatonin receptor genetic polymorphisms were discovered and implicated in pathology-for instance in type 2 diabetes, autoimmune disease, and cancer. The circadian patterns of melatonin secretion, its pleiotropic effects depending on cell type and condition, and the already demonstrated cross-talks of melatonin receptors with other signal transduction pathways further contribute to the perplexity of research on the role of the pineal hormone in humans. In this review we try to summarize the current knowledge on the membrane melatonin receptor activated cell signaling in physiology and pathology and their relevance to certain disease conditions including cancer.

A low-carbohydrate dietary pattern characterised by high animal fat and protein during the first trimester is associated with an increased risk of gestational diabetes mellitus in Chinese women: a prospective cohort study

We aimed to examine the association between low-carbohydrate diet (LCD) scores during the first trimester and gestational diabetes mellitus (GDM) risk in a Chinese population. A total of 1455 women were included in 2017. Dietary information during the first trimester was collected by 24-h dietary recalls for 3 d. The overall, animal and plant LCD scores, which indicated adherence to different low-carbohydrate dietary patterns, were calculated. GDM was diagnosed based on the results of a 75-g, 2-h oral glucose tolerance test at 24-28 weeks gestation. Log-binomial models were used to estimate relative risks (RR) and 95 % CI. The results showed that the multivariable-adjusted RR of GDM from the lowest to the highest quartiles of the overall LCD score were 1·00 (reference), 1·15 (95 % CI 0·92, 1·42), 1·30 (95 % CI 1·06, 1·60) and 1·24 (95 % CI 1·01, 1·52) (P = 0·026 for trend). Multivariable-adjusted RR (95 % CI) of GDM from the lowest to the highest quartiles of the animal LCD score were 1·00 (reference), 1·20 (95 % CI 0·96, 1·50), 1·41 (95 % CI 1·14, 1·73) and 1·29 (95 % CI 1·04, 1·59) (P = 0·002 for trend). After additional adjustment for gestational weight gain before GDM diagnosis, the association of the overall LCD score with GDM risk was non-significant, while the association of animal LCD score with GDM risk remained significant. In conclusion, a low-carbohydrate dietary pattern characterised by high animal fat and protein during the first trimester is associated with an increased risk of GDM in Chinese women.

The role of vitamin D receptor gene polymorphisms in gestational diabetes mellitus susceptibility: a meta-analysis

BACKGROUND

Gestational diabetes mellitus (GDM) is a common disease during pregnancy. The association of vitamin D receptor (VDR) polymorphisms with GDM is still controversial. This study aimed to assess the associations between VDR polymorphisms and GDM risk.

METHODS

We searched Cochrane Library, PubMed, and Embase electronic database for all eligible studies published from Jan 1, 1980 to December 31, 2020 to conduct a Meta-analysis. We analyzed four VDR polymorphisms: BsmI (rs1544410), ApaI (rs7975232), TaqI (rs731236), and FokI (rs2228570).

INCLUSION CRITERIA

(1) The data can be evaluated; (2) case-control study; and (3) meeting the Hardy-Weinberg's law.

EXCLUSION CRITERIA

(1) Insufficient or extractable data; (2) Severe publication bias in the data; and (3) duplicate publications. We eventually included 15 studies in seven articles, including 2207 cases and 2706 controls.

RESULTS

We eventually included 15 studies in seven articles, including 2207 cases and 2706 controls. The data showed that ApaI (rs7975232) VDR gene polymorphism was related with the risk of GDM for the comparison of CC vs AA and recessive model in overall population and FokI (rs2228570) VDR gene polymorphism was associated with the risk of GDM for recessive model in overall population. BsmI (rs1544410) polymorphism was not related with the risk of GDM in overall population. However, in the analysis of subgroups grouped by race, BsmI (rs1544410) has certain correlations. And, the data suggested the TaqI (rs731236) polymorphism was not associated with GDM.

CONCLUSION

Based on the meta-analysis, VDR ApaI (rs7975232) and FokI (rs2228570) polymorphisms increase susceptibility to GDM. In the future, it can be used to diagnose and screen molecular biomarkers for GDM patients.