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

Understanding the potential contribution of polygenic risk scores to the prediction of gestational and type 2 diabetes in women from British Pakistani and Bangladeshi groups: a cohort study in Genes and Health

Background

British Pakistani and Bangladeshi (BPB) women have disproportionately high rates of gestational diabetes mellitus (GDM), with prevalence estimates up to three times higher than in the general population. They are also at increased risk of progressing to type 2 diabetes, leading to significant health complications. Despite this, predictive models tailored to this high-risk, yet understudied group are lacking.

Objective

To investigate whether combining genetic and traditional clinical data improves risk prediction of GDM and progression to type 2 diabetes among BPB women. We hypothesized that incorporating polygenic risk scores (PRS) would enhance the predictive accuracy of existing models.

Study Design

An observational cohort study utilizing the Genes & Health dataset, which includes comprehensive electronic health records. Women who gave birth between 2000 and 2023, both with and without a history of GDM, were included. Controls were defined as women without a GDM diagnosis during this period but who had a birth record. A total of 117 type 2 diabetes or GDM PRS were tested to determine the optimal PRS based on predictive performance metrics. The best-performing PRS was integrated with clinical variables for statistical analyses, including descriptive statistics, chi-square tests, logistic regression, and receiver operating characteristic curve analysis.

Results

Of 13,489 women with birth records, 10,931 were included in the analysis, with 29.3% developing GDM. Women with GDM were older (mean age 31.7 years, P<.001) and had a higher BMI (mean 28.4 kg/m2, P<.001) compared to controls. The optimal PRS demonstrated a strong association with GDM risk; women in the highest PRS decile had significantly increased odds of developing GDM (OR 5.66, 95% CI [4.59, 7.01], P=3.62×10-58). Furthermore, the risk of converting from GDM to type 2 diabetes was 30% in the highest PRS decile, compared to 19% among all GDM cases and 11% in the lowest decile. Incorporating genetic risk factors with clinical data improved the C-statistic for predicting type 2 diabetes following GDM from 0.62 to 0.67 (P=4.58×10-6), indicating better model discrimination.

Conclusion

The integration of genetic assessment with traditional clinical factors significantly enhances risk prediction for BPB women at high risk of developing type 2 diabetes after GDM. These findings support the implementation of targeted interventions and personalized monitoring strategies in this high-risk population. Future research should focus on validating these predictive models in external cohorts and exploring their integration into clinical practice to improve health outcomes.

Genetics and epigenetics in gestational diabetes contributing to type 2 diabetes

Gestational diabetes mellitus (GDM) is a common pregnancy complication and a risk factor for the subsequent development of type 2 diabetes (T2D) in mothers and of several metabolic diseases in offspring. However, the molecular underpinnings of these risks are not well understood. Genome-wide association studies (GWAS) and epigenetic studies may provide complementary insights into the causal relationships between GDM exposure and maternal/offspring metabolic outcomes. In this review we discuss the potential pathophysiological roles of specific genetic variants and commonly reported differentially methylated loci in GDM development, and their link to the progression to T2D in both the mother and the offspring in later life, pointing to the potential for tailored interventional strategies based on these genetic and epigenetic mechanisms.

Ultra-processed food, genetic risk, and the risk of cardiometabolic diseases and cardiometabolic multimorbidity: A prospective study

BACKGROUND AND AIMS

This study aims to evaluate the impact of ultra-processed food (UPF) on type 2 diabetes (T2D), cardiovascular disease (CVD), hypertension, and cardiometabolic multimorbidity (CMM), and to explore the role of genetic susceptibility in these associations.

METHODS AND RESULTS

90 631 participants from the UK Biobank were included (collected between 2006 and 2010). The outcomes assessed included T2D, CVD, hypertension and CMM. The Cox proportional hazards model was used to evaluate their associations and the potential modification by genetic risk, which was estimated using the polygenic risk score (PRS). Participants with high UPF consumption had a higher risk of T2D, CVD, and CMM, with the adjusted hazard ratio (HR) of 1.36 (95 % confidence interval [CI]: 1.15, 1.61), 1.13 (95%CI: 1.03, 1.23), and 1.14 (95%CI: 1.05, 1.24), respectively. Those with high UPF consumption and high PRS for T2D, CVD, and hypertension had the highest risk of T2D (HR: 4.01; 95%CI: 2.83, 5.69), CVD (HR: 2.18; 95%CI: 1.86, 2.56), and hypertension (HR: 1.79; 95%CI: 1.61, 1.99), respectively. In participants with one cardiometabolic disease (CMD), those with high UPF consumption and high PRST2D or PRSCVD had the highest risk of developing CMM. A significant additive interaction was observed between PRST2D and UPF consumption on the risk of T2D.

CONCLUSION

Our study underscored the importance of identifying individuals with high UPF consumption for targeted dietary interventions to mitigate the risk of CMDs and CMM, particularly among those with a high genetic risk of CMDs.

Periodic mobile application (eMOM) with self-tracking of glucose and lifestyle improves treatment of diet-controlled gestational diabetes without human guidance: a randomized controlled trial

BACKGROUND

Digitalization with minimal human resources could support self-management among women with gestational diabetes and improve maternal and neonatal outcomes.

OBJECTIVE

This study aimed to investigate if a periodic mobile application (eMOM) with wearable sensors improves maternal and neonatal outcomes among women with diet-controlled gestational diabetes without additional guidance from healthcare personnel.

STUDY DESIGN

Women with gestational diabetes were randomly assigned in a 1:1 ratio at 24 to 28 weeks' gestation to the intervention or the control arm. The intervention arm received standard care in combination with use of the periodic eMOM, whereas the control arm received only standard care. The intervention arm used eMOM with a continuous glucose monitor, an activity tracker, and a food diary 1 week/month until delivery. The primary outcome was the change in fasting plasma glucose from baseline to 35 to 37 weeks' gestation. Secondary outcomes included capillary glucose, weight gain, nutrition, physical activity, pregnancy complications, and neonatal outcomes, such as macrosomia.

RESULTS

In total, 148 women (76 in the intervention arm, 72 in the control arm; average age, 34.1±4.0 years; body mass index, 27.1±5.0 kg/m2) were randomized. The intervention arm showed a lower mean change in fasting plasma glucose than the control arm (difference, -0.15 mmol/L vs -2.7 mg/mL; P=.022) and lower capillary fasting glucose levels (difference, -0.04 mmol/L vs -0.7 mg/mL; P=.002). The intervention arm also increased their intake of vegetables (difference, 11.8 g/MJ; P=.043), decreased their sedentary behavior (difference, -27.3 min/d; P=.043), and increased light physical activity (difference, 22.8 min/d; P=.009) when compared with the control arm. In addition, gestational weight gain was lower (difference, -1.3 kg; P=.015), and there were less newborns with macrosomia in the intervention arm (difference, -13.1 %; P=.036). Adherence to eMOM was high (daily use >90%), and the usage correlated with lower maternal fasting (P=.0006) and postprandial glucose levels (P=.017), weight gain (P=.028), intake of energy (P=.021) and carbohydrates (P=.003), and longer duration of the daily physical activity (P=.0006). There were no significant between-arm differences in terms of pregnancy complications.

CONCLUSION

Self-tracking of lifestyle factors and glucose levels without additional guidance improves self-management and the treatment of gestational diabetes, which also benefits newborns. The results of this study support the use of digital self-management and education tools in maternity care.

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.

Call to action for a life course approach

Gestational diabetes remains the most common medical disorder in pregnancy, with short-term and long-term consequences for mothers and offspring. New insights into pathophysiology and management suggest that the current gestational diabetes treatment approach should expand from a focus on late gestational diabetes to a personalised, integrated life course approach from preconception to postpartum and beyond. Early pregnancy lifestyle intervention could prevent late gestational diabetes. Early gestational diabetes diagnosis and treatment has been shown to be beneficial, especially when identified before 14 weeks of gestation. Early gestational diabetes screening now requires strategies for integration into routine antenatal care, alongside efforts to reduce variation in gestational diabetes care, across settings that differ between, and within, countries. Following gestational diabetes, an oral glucose tolerance test should be performed 6-12 weeks postpartum to assess the glycaemic state. Subsequent regular screening for both dysglycaemia and cardiometabolic disease is recommended, which can be incorporated alongside other family health activities. Diabetes prevention programmes for women with previous gestational diabetes might be enhanced using shared decision making and precision medicine. At all stages in this life course approach, across both high-resource and low-resource settings, a more systematic process for identifying and overcoming barriers to preventative care and treatment is needed to reduce the current global burden of gestational diabetes.

A genetics-guided approach to the clinical management of schizophrenia

Schizophrenia is a highly heritable, severe mental illness characterized by hallucinations, delusions, social withdrawal, and cognitive dysfunction present in ∼1% of populations across cultures. There have been recent major advancements in our understanding of the genetic architecture of schizophrenia. Both rare, highly penetrant genetic variants as well as common, low-penetrant genetic variants can predispose individuals to schizophrenia and can impact the way people metabolize psychoactive medications used to treat schizophrenia. However, the impact of these findings on the clinical management of schizophrenia remains limited. This review highlights the few places where genetics currently informs schizophrenia management strategies, discusses major limitations, and reviews promising areas of genetics research that are most likely to impact future schizophrenia care. Specifically, I focuss on psychiatric genetic counseling, genetic testing strategies, pharmacogenetics, polygenic risk, and genetics-guided treatment. Lastly, I emphasize important ethical considerations in the clinical use of genetics for schizophrenia management, including the exacerbation of healthcare inequalities and unintended consequences of new genetic technologies.

Genetic risk of type 2 diabetes modifies the association between lifestyle and glycemic health at 5 years postpartum among high-risk women

INTRODUCTION

Lifestyle interventions are effective in preventing type 2 diabetes, but genetic background may influence the individual response. In the Finnish gestational diabetes prevention study, RADIEL, lifestyle intervention during pregnancy and first postpartum year was effective in preventing gestational diabetes (GDM) and postpartum glycemic abnormalities only among women at highest genetic risk of type 2 diabetes. This study aimed to assess whether still 5 years postpartum the genetic risk modifies the association between lifestyle and glycemic health.

RESEARCH DESIGN AND METHODS

The RADIEL study (randomized controlled trial) aimed to prevent GDM with a lifestyle intervention among high-risk women (body mass index ≥30 kg/m2 and/or prior GDM). The follow-up study 5 years postpartum included anthropometric measurements, laboratory assessments, device-measured physical activity (PA), and questionnaires. A Healthy Lifestyle Score (HLS) indicated adherence to lifestyle goals (PA, diet, smoking) and a polygenic risk score (PRS) based on 50 type 2 diabetes risk alleles depicted the genetic risk.

RESULTS

Altogether 314 women provided genetic and glycemic data 5 years postpartum. The PRS for type 2 diabetes was not associated with glycemic abnormalities, nor was HLS in the total study sample. There was, however, an interaction between HLS and type 2 diabetes PRS on glycemic abnormalities (p=0.03). When assessing the association between HLS and glycemic abnormalities in PRS tertiles, HLS was associated with reduced risk of glycemic abnormalities only among women at the highest genetic risk (p=0.008).

CONCLUSIONS

These results extend our previous findings from pregnancy and first postpartum year demonstrating that still at 5 years postpartum, healthy lifestyle is associated with a lower risk of prediabetes/diabetes only among women at the highest genetic risk of type 2 diabetes.

Relation between weight gain during pregnancy and postpartum reclassification in gestational diabetes

PURPOSE

Gestational diabetes mellitus (GDM) is the most common metabolic disease in pregnancy. It is known that GDM is a precursor to type 2 diabetes (T2D). There is evidence that excessive gestational weight variation (GWV) increases the risk of GDM. So, in this study, we aimed to evaluate the association between GWV and the persistence of diabetes in postpartum reclassification.

METHODS

A retrospective observational study including pregnant women based on data from the Portuguese National Registry of Gestational Diabetes. Six-to-eight weeks after delivery, all women included underwent a reclassification test. We performed unadjusted and adjusted logistic regression models to evaluate the associations between GWV and diabetes diagnosis at the reclassification test. A subgroup analysis according to the pre-gestational BMI was also performed.

RESULTS

We included 10,389 pregnant women, of which 19.6% had GDM in a previous pregnancy. The median of GWV was 10.0 [6.4, 14.0] kg and was found to be higher for those with a normal BMI. At the DM reclassification test, 1% of the women were diagnosed with T2D. We found a negative association between GWV and postpartum diabetes mellitus (DM). We also present a subgroup analysis, and these associations were only significant for the group with a normal pre-gestational BMI.

CONCLUSION

Our results showed that women with normal pre-gestational BMI and lower GWV were more likely to have a diagnosis of DM in the postpartum reclassification test. This study helps to fill the gap in the effect of GWG on the persistence of diabetes in postpartum reclassification.

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.

Progression to type 2 diabetes mellitus after gestational diabetes mellitus diagnosed by IADPSG criteria: Systematic review and meta-analysis

Background

To estimate the progression rates to type 2 diabetes mellitus (T2DM) in women with gestational diabetes mellitus (GDM) diagnosed by the International Association of Diabetes and Pregnancy Study Group (IADPSG) criteria.

Methods

Systematic review and meta-analysis were conducted by searching Medline, Embase, and Cochrane between January 1, 2010 and December 31, 2021 for observational studies investigating progression to T2DM after GDM. Inclusion criteria were IADPSG-diagnosed GDM, studies with both GDM and controls, postpartum follow-up duration at least one year. Data were pooled by random effects meta-analysis models. Heterogeneity was assessed by I2 statistic. The pooled relative risk for incidence of T2DM and pre-diabetes between GDM participants and controls were estimated. Reasons for heterogeneity among studies were investigated by prespecified subgroup and meta-regression analysis. Publication bias was assessed by the Begg's and Egger's tests.

Results

This meta-analysis of six studies assessed a total of 61932 individuals (21978 women with GDM and 39954 controls). Women with IADPSG-diagnosed GDM were 6.43 times (RR=6.43, 95% CI:3.45-11.96) more likely to develop T2DM in the future compared with controls. For GDM women, the cumulative incidence of T2DM was 12.1% (95% CI: 6.9%-17.3%), while the pooled cumulative incidence of T2DM was estimated to be 8% (95% CI: 5-11%) in studies with 1 to 5 years of follow-up and increased to 19% (95% CI: 3-34%) for studies with more than 5 years of follow-up. Women with IADPSG-diagnosed GDM had 3.69 times (RR=3.69, 95% CI:2.70-5.06) higher risk of developing pre-diabetes (including impaired fasting glucose and/or impaired glucose tolerance) than controls. Meta-regression analysis showed that the study effect size was not significantly associated with study design, race, length of follow-up, and maternal age (P>0.05). Overall, the studies had a relatively low risk of bias.

Conclusions

Women with IADPSG-diagnosed GDM have higher risk of developing T2DM and pre-diabetes. The risk of T2DM in GDM women are higher with longer follow-up duration. Our results highlight the importance of promoting postpartum screening and keeping health lifestyle as well as pharmacological interventions to delay/prevent the onset of T2DM/pre-diabetes in GDM women.

Systematic review registration

https://www.crd.york.ac.uk/prospero, identifier (CRD42022314776).