An explained variance-based genetic risk score associated with gestational diabetes antecedent and with progression to pre-diabetes and type 2 diabetes: a cohort study

Genome-Wide Polygenic Risk Score Predicts Incident Type 2 Diabetes in Women With History of Gestational Diabetes

OBJECTIVE

Women with a history of gestational diabetes mellitus (GDM) are at increased risk of developing type 2 diabetes (T2D). It remains unclear whether genetic information improves prediction of incident T2D in these women.

RESEARCH DESIGN AND METHODS

Using five independent cohorts representing four different ancestries (n = 1,895), we investigated whether a genome-wide T2D polygenic risk score (PRS) is associated with increased risk of incident T2D. We also calculated the area under the receiver operating characteristics curve (AUROC) and continuous net reclassification improvement (NRI) following the incorporation of T2D PRS into clinical risk models to assess the diagnostic utility.

RESULTS

Among 1,895 women with previous history of GDM, 363 (19.2%) developed T2D in a range of 2 to 30 years. T2D PRS was higher in those who developed T2D (-0.08 vs. 0.31, P = 2.3 × 10-11) and was associated with an increased risk of incident T2D (odds ratio 1.52 per 1-SD increase, 95% CI 1.05-2.21, P = 0.03). In a model that includes age, family history of diabetes, systolic blood pressure, and BMI, the incorporation of PRS led to an increase in AUROC for T2D from 0.71 to 0.74 and an intermediate improvement of NRI (0.32, 95% CI 0.15-0.49, P = 3.0 × 10-4). Although there was variation, a similar trend was observed across study cohorts.

CONCLUSIONS

In cohorts of GDM women with diverse ancestry, T2D PRS was significantly associated with future development of T2D. A significant but small improvement was observed in AUROC when T2D PRS was integrated into clinical risk models to predict incident T2D.

Models Predicting Postpartum Glucose Intolerance Among Women with a History of Gestational Diabetes Mellitus: a Systematic Review

PURPOSE OF REVIEW

Despite the crucial role that prediction models play in guiding early risk stratification and timely intervention to prevent type 2 diabetes after gestational diabetes mellitus (GDM), their use is not widespread in clinical practice. The purpose of this review is to examine the methodological characteristics and quality of existing prognostic models predicting postpartum glucose intolerance following GDM.

RECENT FINDINGS

A systematic review was conducted on relevant risk prediction models, resulting in 15 eligible publications from research groups in various countries. Our review found that traditional statistical models were more common than machine learning models, and only two were assessed to have a low risk of bias. Seven were internally validated, but none were externally validated. Model discrimination and calibration were done in 13 and four studies, respectively. Various predictors were identified, including body mass index, fasting glucose concentration during pregnancy, maternal age, family history of diabetes, biochemical variables, oral glucose tolerance test, use of insulin in pregnancy, postnatal fasting glucose level, genetic risk factors, hemoglobin A1c, and weight. The existing prognostic models for glucose intolerance following GDM have various methodological shortcomings, with only a few models being assessed to have low risk of bias and validated internally. Future research should prioritize the development of robust, high-quality risk prediction models that follow appropriate guidelines, in order to advance this area and improve early risk stratification and intervention for glucose intolerance and type 2 diabetes among women who have had GDM.

Social Vulnerability and Initiation of Pharmacotherapy for Gestational Diabetes Mellitus in a Medicaid Population

OBJECTIVE

Our study examines the association between social vulnerability index (SVI) and pharmacotherapy initiation for gestational diabetes mellitus (GDM).

METHODS

We studied a retrospective cohort of pregnant patients with GDM, enrolled in Tennessee Medicaid, who gave birth between 2007 and 2019. Enrollment files were linked to birth and death certificates, state hospitalization registries, and pharmacy claims. SVI, measured at the community level and determined by residential census tract, ranged from 0 to 100 (low to high vulnerability). Multivariable logistic regression assessed the association between SVI and the odds of initiating the most common pharmacotherapies for GDM-insulin, glyburide, or metformin-and adjusted for relevant covariates. SVI was modeled with restricted cubic splines to account for nonlinear associations, using the median Tennessee SVI as a reference. Secondary analysis assessed associations with the SVI subthemes.

RESULTS

Among 33,291 patients with GDM, 21.7% (7,209) initiated pharmacotherapy during pregnancy. Patients from areas with higher SVI were more likely to be non-Hispanic Black with higher body mass index, whereas those with lower SVI were more likely to be nulliparous. Multivariable modeling demonstrated a complex nonlinear association between SVI and GDM pharmacotherapy initiation, relative to the reference. Higher SVI was associated with elevated odds of GDM pharmacotherapy initiation (e.g., odds ratio 1.11 [95% confidence interval 1.02-1.22] for SVI 80) and low to medium SVI had variable nonsignificant associations with GDM pharmacotherapy initiation, relative to the reference (lower odds of initiation for values 25-50, higher odds of initiation for values < 25). Secondary analysis demonstrated a nonlinear association between subtheme 3 and the odds of GDM pharmacotherapy initiation.

CONCLUSION

Social vulnerability is associated with initiation of pharmacotherapy for GDM, highlighting the possible role of social determinants of health in achieving glycemic control.

Genetics and Epigenetics: Implications for the Life Course of Gestational Diabetes

Gestational diabetes (GDM) is one of the most common complications of pregnancy, affecting as many as one in six pregnancies. It is associated with both short- and long-term adverse outcomes for the mother and fetus and has important implications for the life course of affected women. Advances in genetics and epigenetics have not only provided new insight into the pathophysiology of GDM but have also provided new approaches to identify women at high risk for progression to postpartum cardiometabolic disease. GDM and type 2 diabetes share similarities in their pathophysiology, suggesting that they also share similarities in their genetic architecture. Candidate gene and genome-wide association studies have identified susceptibility genes that are shared between GDM and type 2 diabetes. Despite these similarities, a much greater effect size for MTNR1B in GDM compared to type 2 diabetes and association of HKDC1, which encodes a hexokinase, with GDM but not type 2 diabetes suggest some differences in the genetic architecture of GDM. Genetic risk scores have shown some efficacy in identifying women with a history of GDM who will progress to type 2 diabetes. The association of epigenetic changes, including DNA methylation and circulating microRNAs, with GDM has also been examined. Targeted and epigenome-wide approaches have been used to identify DNA methylation in circulating blood cells collected during early, mid-, and late pregnancy that is associated with GDM. DNA methylation in early pregnancy had some ability to identify women who progressed to GDM, while DNA methylation in blood collected at 26-30 weeks gestation improved upon the ability of clinical factors alone to identify women at risk for progression to abnormal glucose tolerance post-partum. Finally, circulating microRNAs and long non-coding RNAs that are present in early or mid-pregnancy and associated with GDM have been identified. MicroRNAs have also proven efficacious in predicting both the development of GDM as well as its long-term cardiometabolic complications. Studies performed to date have demonstrated the potential for genetic and epigenetic technologies to impact clinical care, although much remains to be done.

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.

Molecular biomarkers for gestational diabetes mellitus and postpartum diabetes

ABSTRACT

Gestational diabetes mellitus (GDM) is a growing public health problem worldwide that threatens both maternal and fetal health. Identifying individuals at high risk for GDM and diabetes after GDM is particularly useful for early intervention and prevention of disease progression. In the last decades, a number of studies have used metabolomics, genomics, and proteomic approaches to investigate associations between biomolecules and GDM progression. These studies clearly demonstrate that various biomarkers reflect pathological changes in GDM. The established markers have potential use as screening and diagnostic tools in GDM and in postpartum diabetes research. In the present review, we summarize recent studies of metabolites, single-nucleotide polymorphisms, microRNAs, and proteins associated with GDM and its transition to postpartum diabetes, with a focus on their predictive value in screening and diagnosis.

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.

Risk of type 2 diabetes mellitus after gestational diabetes mellitus: A systematic review & meta-analysis

Background &objectives:

Women with gestational diabetes are at an increased risk of being diagnosed as type 2 diabetes, but the postpartum screening rate is low. To provide evidence-based data for health providers and promote postpartum screening, this systematic review and meta-analysis was conducted to access the risks of type 2 diabetes mellitus (T2DM) diagnosis after gestational diabetes mellitus (GDM) in different demographic and maternal subgroups.

Methods:

MEDLINE, Embase and Cochrane Library were searched systematically. Unadjusted relative risks (RRs) and 95 per cent confidence intervals (CIs) were calculated and pooled using a random-effects model. Heterogeneity was assessed with Cochrane’s Q text and by calculating I² values. Subgroup analyses were conducted to address the disparities of type 2 diabetes conversion after gestational diabetes in different demographic and maternal subgroups.

Results:

1809 publications were screened and 39 cohort studies including 2,847,596 women were selected. In these studies, 78,893 women were diagnosed as T2DM at six weeks or later after delivery. The unadjusted RRs of women diagnosed T2DM at six weeks or later after delivery ranged from 1.32 (95% CI, 0.46-3.37) to 47.25 (95% CI, 2.95-758.01) with a pooled unadjusted RR of 8.92 (95% CI, 7.84-10.14). Older women, women with a family history of diabetes, Black and non-Hispanic White women and women living in Europe and South-East Asia had a higher risk of developing T2DM after GDM.

Interpretation & conclusionsxs:

It is suggested that healthcare providers may focus on older women with GDM and women with GDM and a family history of diabetes. Black and non-Hispanic White women with GDM may receive more attention, and healthcare providers, especially those in Europe and South-East Asia, may pay more attention to preventive measures for postpartum T2DM.

Risk Factors for Progression From Gestational Diabetes to Postpartum Type 2 Diabetes: A Review

Gestational diabetes mellitus (GDM) complicates 6% to 8% of pregnancies and up to 50% of women with GDM progress to type 2 diabetes mellitus (DM) within 5 years postpartum. Clinicians have little guidance on which women are most at risk for DM progression or when evidence-based prevention strategies should be implemented in a woman's lifecycle. To help address this gap, the authors review identifiable determinants of progression from GDM to DM across the perinatal period, considering prepregnancy, pregnancy, and postpartum periods. The authors categorize evidence by pathways of risk including genetic, metabolic, and behavioral factors that influence progression to DM among women with GDM.

No deleterious effect of an additional pregnancy on glucose metabolism in women with previous gestational diabetes mellitus

OBJECTIVE

Women with gestational diabetes mellitus (GDM) often develop type 2 diabetes later in life. It remains unclear whether this results solely from a common underlying predisposition or, whether a pregnancy itself persistently impairs glucose metabolism in predisposed women. We therefore examined how an additional pregnancy affected different aspects of glucose metabolism in women with previous GDM.

RESEARCH DESIGN AND METHODS

Nested case-control study within the prospective cohort study PPSDiab, recruited in Munich, Germany from 2011-16. Cases (n = 41): women with previous GDM who completed an additional pregnancy; controls: no additional pregnancy, pairwise matching.

ENDPOINTS

change of the area under the glucose curve (AUGC) of an oral glucose tolerance, of plasma glucose at 60' of the test (PG 60'), of the insulin sensitivity index (ISI) and of the disposition index (DI), all between before and after the additional pregnancy in cases/the corresponding observation period in controls.

RESULTS

We observed no significant difference between cases and controls in the primary [ratio AUGC 1.05(0.92-1.15) vs. 0.97(0.85-1.14); p = 0.21] and in the secondary endpoints [difference PG 60', ratio ISI and ratio DI.

CONCLUSION

We did not find a deleterious effect of an additional pregnancy on glucose metabolism in women with previous GDM.

Genetic Studies of Gestational Diabetes and Glucose Metabolism in Pregnancy

PURPOSE OF REVIEW

In this review, we summarize studies investigating genetics of gestational diabetes mellitus (GDM) and glucose metabolism in pregnancy. We describe these studies in the context of the larger body of literature on type 2 diabetes (T2D) and glycemic trait genomics.

RECENT FINDINGS

We reviewed 23 genetic association studies for GDM and performed a meta-analysis, which revealed variants at eight T2D loci significantly associated with GDM after the Bonferroni correction. These studies suggest that GDM and T2D share a number of genetic risk loci. Only two unbiased genome-wide association studies (GWASs) have successfully revealed genetic associations for GDM and related glycemic traits in pregnancy. A GWAS for GDM in Korean women identified two loci (near CDKAL1 and MTNR1B) known to be associated with T2D, though the association of the MTNR1B locus with GDM appears to be stronger than that for T2D. A multi-ethnic GWAS for glycemic traits in pregnancy identified two novel loci (near HKDC1 and BACE2) which appear to be associated with post-load glucose and fasting c-peptide specifically in pregnant women. There are ongoing efforts to use this genetic information, in the form of polygenic scores, to predict risk of GDM and postpartum T2D. The body of literature examining genetic associations with GDM is limited, especially when compared to the available literature on T2D and glycemic trait genomics. Additional genetic discovery for glucose metabolism in pregnant women will require larger pregnancy cohorts and international collaborative efforts. Studies on the clinical implications of these findings are also warranted.

Genetic determinants of gestational diabetes mellitus: a case-control study in two independent populations

BACKGROUND

Genetic risk score (GRS) is more informative to identify the complicated associations between variants of genes and disease. Considering similar pathogenesis and shared genetic predispositions between gestational diabetes mellitus (GDM) and type 2 diabetes/obesity, we conducted this study to explore whether the GRS model integrating variants related to type 2 diabetes/obesity is also associated with GDM risk.

METHODS

A population-based case-control study that included 1429 subjects was conducted to investigate the association between the GRS model and GDM risk, which were analyzed employing stratified logistic regression analysis with the adjustment for age, BMI, parity and family history of diabetes.

RESULTS

We have screened 23 SNPs and further filtered six SNPs that were significantly associated with the risk of GDM: four risk SNPs (MTNR1B: rs10830963, rs1387153, rs2166706; MC4R: rs2229616) and two protective SNPs (MTNR1B: rs1447352 and rs4753426). The GRS model with a higher score indicated a higher genetic predisposition to develop GDM, especially in the highest quartile of GRS (all P < 0.001) and the strata of advanced maternal age (all P < 0.001) and obesity (all P = 0.005).

CONCLUSION

In this study, six SNPs were explored and further identified to be associated with GDM risk, which suggested GRSs including these polymorphisms might participate in facilitating GDM risk. These findings offer the potential to improve our understanding of the etiology of GDM.

Fine-tuning of Genome-Wide Polygenic Risk Scores and Prediction of Gestational Diabetes in South Asian Women

Gestational diabetes Mellitus (GDM) affects 1 in 7 births and is associated with numerous adverse health outcomes for both mother and child. GDM is suspected to share a large common genetic background with type 2 diabetes (T2D). The aim of our study was to characterize different GDM polygenic risk scores (PRSs) and test their association with GDM using data from the South Asian Birth Cohort (START). PRSs were derived for 832 South Asian women from START using the pruning and thresholding (P + T), LDpred, and GraBLD methods. Weights were derived from a multi-ethnic and a white Caucasian study of the DIAGRAM consortium. GDM status was defined using South Asian-specific glucose values in response to an oral glucose tolerance test. Association with GDM was tested using logistic regression. Results were replicated in South Asian women from the UK Biobank (UKB) study. The top ranking P + T, LDpred and GraBLD PRSs were all based on DIAGRAM's multi-ethnic study. The best PRS was highly associated with GDM in START (AUC = 0.62, OR = 1.60 [95% CI = 1.44-1.69]), and in South Asian women from UKB (AUC = 0.65, OR = 1.69 [95% CI = 1.28-2.24]). Our results highlight the importance of combining genome-wide genotypes and summary statistics from large multi-ethnic studies to optimize PRSs in South Asians.

Genetic factors and risk of type 2 diabetes among women with a history of gestational diabetes: findings from two independent populations

OBJECTIVE

Women with a history of gestational diabetes mellitus (GDM) have an exceptionally high risk for type 2 diabetes (T2D). Yet, little is known about genetic determinants for T2D in this population. We examined the association of a genetic risk score (GRS) with risk of T2D in two independent populations of women with a history of GDM and how this association might be modified by non-genetic determinants for T2D.

RESEARCH DESIGN AND METHODS

This cohort study included 2434 white women with a history of GDM from the Nurses' Health Study II (NHSII, n=1884) and the Danish National Birth Cohort (DNBC, n=550). A GRS for T2D was calculated using 59 candidate single nucleotide polymorphisms for T2D identified from genome-wide association studies in European populations. An alternate healthy eating index (AHEI) score was derived to reflect dietary quality after the pregnancy affected by GDM.

RESULTS

Women on average were followed for 21 years in NHSII and 13 years in DNBC, during which 446 (23.7%) and 155 (28.2%) developed T2D, respectively. The GRS was generally positively associated with T2D risk in both cohorts. In the pooled analysis, the relative risks (RRs) for increasing quartiles of GRS were 1.00, 0.97, 1.25 and 1.19 (p trend=0.02). In both cohorts, the association appeared to be stronger among women with poorer (AHEI <median) than better dietary quality (AHEI ≥median), although the interaction was not significant. For example, in NHSII, the RRs across increasing quartiles of GRS were 1.00, 0.99, 1.51 and 1.29 (p trend=0.06) among women with poorer dietary quality and 1.00, 0.83, 0.81 and 0.94 (p trend=0.79) among women with better dietary quality (p interaction=0.11).

CONCLUSIONS

Among white women with a history of GDM, higher GRS for T2D was associated with an increased risk of T2D.

The Risk for Glucose Intolerance after Gestational Diabetes Mellitus since the Introduction of the IADPSG Criteria: A Systematic Review and Meta-Analysis

The aim of the study was to assess the postpartum risk for glucose intolerance since the introduction of the ‘International Association of Diabetes and Pregnancy Study Groups’ (IADPSG) criteria for gestational diabetes mellitus (GDM). Studies published since 2010 were included, which evaluated the risk for type 2 diabetes mellitus (T2DM), impaired glucose tolerance (IGT), and cardiovascular (CV) events in women with previous GDM compared to normal glucose tolerant women. We included forty-three studies, evaluating 4,923,571 pregnant women of which 5.8% (284,312) had a history of GDM. Five studies used IADPSG criteria (n = 6174 women, 1314 with GDM). The overall pooled relative risk (RR) for postpartum T2DM was 7.42 (95% CI: 5.99–9.19) and the RR for postpartum T2DM with IADPSG criteria was 6.45 (95% CI: 4.74–8.77) compared to the RR of 9.08 (95% CI: 6.96–11.85; p = 0.17) for postpartum T2DM based on other diagnostic criteria. The RR for postpartum IGT was 2.45 (95% CI: 1.92–3.13), independent of the criteria used. None of the available studies with IADPSG criteria evaluated the risk for CV events. Women with a history of GDM based on the IADPSG criteria have a similarly increased risk for postpartum glucose intolerance compared to GDM based on other diagnostic criteria. More studies with GDM based on the IADPSG criteria are needed to increase the quality of evidence concerning the long-term metabolic risk.

Maternal genetic contribution to pre-pregnancy obesity, gestational weight gain, and gestational diabetes mellitus

INTRODUCTION

Pre-pregnancy obesity, gestational diabetes mellitus (GDM), and gestational weight gain (GWG) are associated with each other. This is the first study to investigate whether genetic variants were associated with having GDM, and whether genetic variants-related GDM were associated with adiposity including pre-pregnancy obesity and excessive GWG in Turkish women.

PATIENTS AND METHODS

Women with GDM (n = 160) and without GDM (n = 145) were included in case-controlled study. Genotyping of the HNF1A gene (p.I27L rs1169288, p.98V rs1800574, p.S487N rs2464196), the VDR gene (p.BsmI rs1544410, p.ApaI rs7975232, p.TaqI rs731236, p.FokI rs2228570), and FTO gene (rs9939609) SNPs were performed by using RT-PCR.

RESULTS

The FTO AA genotype was associated with an increased risk of having GDM (AA vs. AT + TT, 24.4% vs. 12.4%, OR = 2.27, 95% CI [1.23-4.19], p = 0.007). The HNF1A p.I27L GT/TT genotype was associated with increased GDM risk (GT + TT vs. GG-wild, 79.4% vs. 65.5%, OR = 2.02, 95% CI 1.21-3.38], p = 0.007). However, all VDR gene SNPs and the HNF1A p.A98V, p.S487N were not associated with having GDM (p > 0.05). The FTO AA genotype was associated with an increased risk for pre-pregnancy overweight/obesity (OR = 1.43, 95% CI [1.25-3.4], p = 0.035), but not associated with excessive GWG after adjusting for pre-pregnancy weight (p > 0.05). Pre-pregnancy weight, weight at delivery, and GWG did not differ in both VDR and HNF1A gene carriers (p > 0.05). HOMA-IR and HbA1c were increased in both p.I27L TT and FTO AA genotype carriers (p < 0.05).

CONCLUSION

The adiposity-related gene FTO is associated with GDM by the effect of FTO on pre-pregnancy obesity. The diabetes-related p.I27L gene is associated with GDM by increasing insulin resistance.

Prediction and Prevention of Type 2 Diabetes in Women with a History of GDM

PURPOSE OF THE REVIEW

Women with a history of gestational diabetes mellitus (GDM) have an alarmingly high risk of developing type 2 diabetes (T2D); yet, mechanisms underlying this progression are largely unknown.

RECENT FINDINGS

Clinical characteristics of a GDM pregnancy and postpartum metabolomics may contribute to risk prediction of T2D to identify those women at highest risk of progression and need for intervention. Evidence for effective postpartum lifestyle interventions from observational studies include adherence to a healthy dietary pattern, increasing physical activity, and maintaining a healthy body weight. Larger clinical trials with greater participant engagement are warranted to confirm the effectiveness of lifestyle interventions in women with recent GDM. Research is needed to refine prediction models of T2D after GDM, and to determine the most effective strategies to delay or prevent T2D onset. Incorporating novel biomarkers in the postpartum period, such as metabolomics, could offer a powerful approach.

Associations between fruit and vegetables intake and abnormal glucose tolerance among women with prior gestational diabetes mellitus

PURPOSE

Women with prior gestational diabetes mellitus (GDM) are at higher risk of type 2 diabetes (T2D). The aim of this study was to investigate the association between fruit and vegetables (FV) intake and abnormal glucose tolerance (AGT) among women with prior GDM.

METHODS

A total of 281 women with prior GDM have been recruited a mean of 6 years after their pregnancy in this cohort study. FV intake was obtained with a validated food frequency questionnaire (FFQ). Anthropometric and glycemic components were measured during their clinical visit and women were stratified according to normal glucose tolerance (NGT) or AGT.

RESULTS

A cross-sectional analysis showed that a total of 155 women had NGT and 126 AGT. Women with AGT had significantly lower FV (6.5 ± 0.2) and vegetables servings (3.9 ± 0.2) and tended to have lower fruit servings (2.6 ± 0.2) than women with NGT (7.4 ± 0.2, 4.5 ± 0.2 and 3.0 ± 0.1, respectively) (p = 0.001, p = 0.04 and p = 0.10, respectively, adjusted for age and BMI). FV intake, per one serving increase, was associated with a reduced likelihood of having AGT [OR = 0.88 (0.81-0.97) after adjustment for age and BMI]. Vegetables or fruit intake tended to be associated with a reduced likelihood of having AGT [OR = 0.88 (0.78-1.00) and OR = 0.88 (0.76-1.02), respectively, after adjustment for age and BMI].

CONCLUSIONS

Higher intake of FV may be associated with a lower likelihood of AGT among women with prior GDM. Further studies are needed to confirm these results in this high-risk population.

Risk Factors and Plasma Glucose Profile of Gestational Diabetes in Omani Women

OBJECTIVES

We sought to conduct a detailed study on the risk factors of gestational diabetes mellitus (GDM) in Omani women to determine the actual and applicable risk factors and glucose profile in this population.

METHODS

We conducted a cross-sectional case-control study using pregnant women diagnosed with GDM. Pregnant women without GDM were used as a control group. We collected information related to age, family history, prior history of pregnancy complications, age of marriage, age of first pregnancy, fasting glucose level, and oral glucose tolerance test (OGTT) results from three hospitals in Oman through face-to-face interviews and hospital records.

RESULTS

The median age of women with GDM was 33 years old (p < 0.050). A significant risk was noted in women with a history of diabetes (p < 0.001), and those with mothers' with a history of GDM. A significant (p < 0.010) relationship with a likelihood ratio of 43.9 was observed between the incidence of GDM in women with five or six pregnancies, a history of > 3 deliveries, height < 155 cm, and pregnancy or marriage at age < 18 years (p < 0.010). The mean difference in random plasma glucose, one-hour OGTT, and two-hour OGTT was significantly higher in GDM cases compared to control.

CONCLUSIONS

Glucose profile, family history, anthropometric profile, and age of first pregnancy and marriage should be considered while screening for GDM and determining the care needs of Omani women with GDM.

Joint effects of diabetic-related genomic loci on the therapeutic efficacy of oral anti-diabetic drugs in Chinese type 2 diabetes patients

Previous pharmacogenomic studies of oral anti-diabetic drugs have primarily focused on the effect of a single site. This study aimed to examine the joint effects of multiple loci on repaglinide or rosiglitazone efficacy in newly diagnosed type 2 diabetes mellitus (T2DM) patients. A total of 209 newly diagnosed T2DM patients were randomly assigned to treatment with repaglinide or rosiglitazone for 48 weeks. The reductions in fasting glucose (ΔFPG), 2h glucose (Δ2hPG) and glycated hemoglobin (ΔHbA1c) levels were significantly associated with genetic score that was constructed using the sum of the effect alleles both in the repaglinide (P = 0.0011, 0.0002 and 0.0067, respectively) and rosiglitazone cohorts (P = 0.0002, 0.0014 and 0.0164, respectively) after adjusting for age, gender, body mass index and dosage. Survival analyses showed a trend towards a greater attainment rate of target HbA1c level in individuals with a high genetic score in the repaglinide cohort and rosiglitazone cohort (P_log-rank = 0.0815 and 0.0867, respectively) when the attainment of treatment targets were defined as more than 20% decrease of FPG, 2hPG, and HbA1c levels after treatment. In conclusion, we identified the joint effects of several T2DM-related loci on the efficacy of oral anti-diabetic drugs; moreover, we built a model to predict the drug efficacy.

Model for individual prediction of diabetes up to 5 years after gestational diabetes mellitus

Aims

To identify predictors of diabetes development up to 5 years after gestational diabetes mellitus (GDM) and to develop a prediction model for individual use.

Methods

Five years after GDM, a 75-g oral glucose tolerance test (OGTT) was performed in 362 women, excluding women already diagnosed with diabetes at 1- to 2-year follow-up or later (n = 45). All but 21 women had results from follow-up at 1–2 years, while 84 women were lost from that point. Predictive variables were identified by logistic regression analysis.

Results

Five years after GDM, 28/362 women (8 %) were diagnosed with diabetes whereas 187/362 (52 %) had normal glucose tolerance (NGT). Of the latter, 139/187 (74 %) also had NGT at 1- to 2-year follow-up. In simple regression analysis, using NGT at 1–2 years and at 5 years as the reference, diabetes at 1- to 2-year follow-up or later was clearly associated with easily assessable clinical variables, such as BMI at 1- to 2-year follow-up, 2-h OGTT glucose concentration during pregnancy, and non-European origin (P < 0.0001). A prediction model based on these variables resulting in 86 % correct classifications, with an area under the receiver-operating characteristic curve of 0.91 (95 % CI 0.86–0.95), was applied in a function-sheet line diagram illustrating the individual effect of weight on diabetes risk.

Conclusions

The results highlight the importance of BMI as a potentially modifiable risk factor for diabetes after GDM. Our proposed prediction model performed well, and should encourage validation in other populations in future studies.

Prevalence of Gestational Diabetes and Risk of Progression to Type 2 Diabetes: a Global Perspective

Despite the increasing epidemic of diabetes mellitus affecting populations at different life stages, the global burden of gestational diabetes mellitus (GDM) is not well assessed. Systematically synthesized data on global prevalence estimates of GDM are lacking, particularly among developing countries. The hyperglycemic intrauterine environment as exemplified in pregnancies complicated by GDM might not only reflect but also fuel the epidemic of type 2 diabetes mellitus (T2DM). We comprehensively reviewed available data in the past decade in an attempt to estimate the contemporary global prevalence of GDM by country and region. We reviewed the risk of progression from GDM to T2DM as well. Synthesized data demonstrate wide variations in both prevalence estimates of GDM and the risk of progression from GDM to T2DM. Direct comparisons of GDM burden across countries or regions are challenging given the great heterogeneity in screening approaches, diagnostic criteria, and underlying population characteristics. In this regard, collaborative efforts to estimate global GDM prevalence would be a large but important leap forward. Such efforts may have substantial public health implications in terms of informing health policy makers and healthcare providers for disease burden and for developing more targeted and effective diabetes prevention and management strategies globally.