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.

Vitamin B12 and Folate Markers Are Associated with Insulin Resistance During the Third Trimester of Pregnancy in South Asian Women, Living in the United Kingdom, with Gestational Diabetes and Normal Glucose Tolerance.

BACKGROUND: Gestational diabetes mellitus (GDM) can adversely affect the health of the developing fetus. Women of South Asian origin are particularly at risk of developing GDM. Insulin resistance (IR) contributes to the etiology of GDM, and although studies have shown associations of vitamin B12 (B12) and folate status with GDM and IR, only a limited number of B12 and folate markers have been used. OBJECTIVE: We used a comprehensive panel of B12 and folate markers to examine their association with IR in pregnant women with diet-controlled GDM and normal glucose tolerance (NGT). METHODS: In this cross-sectional study, 59 British-Bangladeshi women (24 GDM and 35 NGT) with a mean age of 29 y, BMI (in kg/m2) 26.7 and gestational age 33 wk were recruited. Serum total B12, holotranscobalamin, folate, methylmalonic acid, plasma homocysteine, 5-methyltetrahydrofolate, and red cell folate (RCF) were measured along with other parameters. The independent sample t-test and chi-squared test were used to assess differences in markers between GDM and NGT women. Spearman's test was used to look for correlations. A simple multiple regression analysis was used to investigate if markers of B12 and folate status predicted IR, using the HOMA-IR and adjusting for age, GDM status, and BMI. RESULTS: There were no differences in concentrations of B12 and folate markers between GDM and NGT women. In Spearman's analysis HOMA-IR correlated negatively with total serum B12 (P < 0.001) and holotranscobalamin (P < 0.05), and positively with BMI (P < 0.001), blood pressure (P < 0.05) and triglycerides (P < 0.05) in all women. MMA did not correlate with any of the B12 markers. In regression analysis, total B12 (ß = -0.622, P = 0.004), RCF (ß = 0.387, P = 0.018), and BMI (ß = 0.024, P < 0.001) were the significant predictors of HOMA-IR variance. CONCLUSIONS: Significant associations between markers of B12 and folate status with HOMA-IR were found during the third trimester in British-Bangladeshi women. B12 markers correlated poorly with each other.

mHealth apps for gestational diabetes mellitus that provide clinical decision support or artificial intelligence: A scoping review.

AIMS: Gestational diabetes (GDM) is the most common metabolic disorder of pregnancy, requiring complex management and empowerment of those affected. Mobile health (mHealth) applications (apps) are proposed for streamlining healthcare service delivery, extending care relationships into the community, and empowering those affected by prolonged medical disorders to be equal collaborators in their healthcare. This review investigates mHealth apps intended for use with GDM; specifically those powered by artificial intelligence (AI) or providing decision support. METHODS: A scoping review using the novel Survey Tool approach for collaborative literature Reviews (STaR) process was performed. RESULTS: From 18 papers, 11 discrete GDM-based mHealth apps were identified, but only 3 were reasonably mature with only one currently in use in a clinical setting. Two-thirds of the apps provided condition-relevant contextual user feedback that could aid in patient self care. However, although each app targeted one or more components of the GDM clinical pathway, no app addressed the entirety from diagnosis to postpartum. CONCLUSIONS: There are limited mHealth apps for GDM that incorporate AI or AI-based decision support. Many exist only to record patient information like blood glucose readings or diet, provide generic patient education or advice, or to reduce adverse events by providing medication or appointment alerts. Significant barriers remain that continue to limit the adoption of mHealth apps in clinical care settings. Further research and development are needed to deliver intelligent holistic mHealth apps using AI that can truly reduce healthcare resource use and improve outcomes by enabling patient self care in the community.

Areca catechu-(Betel-nut)-induced whole transcriptome changes in a human monocyte cell line that may have relevance to diabetes and obesity; a pilot study.

BACKGROUND: Betel-nut consumption is the fourth most common addictive habit globally and there is good evidence linking the habit to obesity, type 2 diabetes (T2D) and the metabolic syndrome. The aim of our pilot study was to identify gene expression relevant to obesity, T2D and the metabolic syndrome using a genome-wide transcriptomic approach in a human monocyte cell line incubated with arecoline and its nitrosated products. RESULTS: The THP1 monocyte cell line was incubated separately with arecoline and 3-methylnitrosaminopropionaldehyde (MNPA) in triplicate for 24 h and pooled cDNA indexed paired-end libraries were sequenced (Illumina NextSeq 500). After incubation with arecoline and MNPA, 15 and 39 genes respectively had significant changes in their expression (q < 0.05, log fold change 1.5). Eighteen of those genes have reported associations with T2D and obesity in humans; of these genes there was most marked evidence for CLEC10A, MAPK8IP1, NEGR1, NQ01 and INHBE genes. CONCLUSIONS: Our preliminary studies have identified a large number of genes relevant to obesity, T2D and metabolic syndrome whose expression was changed significantly in human TPH1 cells following incubation with betel-nut derived arecoline or with MNPA. These findings require validation by further cell-based work and investigation amongst betel-chewing communities.

Statin-induced LDL cholesterol response and type 2 diabetes: a bidirectional two-sample Mendelian randomization study.

It remains unclear whether the increased risk of new-onset type 2 diabetes (T2D) seen in statin users is due to low LDL-C concentrations, or due to the statin-induced proportional change in LDL-C. In addition, genetic instruments have not been proposed before to examine whether liability to T2D might cause greater proportional statin-induced LDL-C lowering. Using summary-level statistics from the Genomic Investigation of Statin Therapy (GIST, nmax = 40,914) and DIAGRAM (nmax = 159,208) consortia, we found a positive genetic correlation between LDL-C statin response and T2D using LD score regression (rgenetic = 0.36, s.e. = 0.13). However, mendelian randomization analyses did not provide support for statin response having a causal effect on T2D risk (OR 1.00 (95% CI: 0.97, 1.03) per 10% increase in statin response), nor that liability to T2D has a causal effect on statin-induced LDL-C response (0.20% increase in response (95% CI: -0.40, 0.80) per doubling of odds of liability to T2D). Although we found no evidence to suggest that proportional statin response influences T2D risk, a definitive assessment should be made in populations comprised exclusively of statin users, as the presence of nonstatin users in the DIAGRAM dataset may have substantially diluted our effect estimate.

Mediterranean-style diet in pregnant women with metabolic risk factors (ESTEEM): A pragmatic multicentre randomised trial.

BACKGROUND: Pregnant women with metabolic risk factors are at high risk of complications. We aimed to assess whether a Mediterranean-style diet reduces adverse pregnancy outcomes in high-risk women. METHODS AND FINDINGS: We conducted a multicentre randomised trial in 5 maternity units (4 in London and 1 in Birmingham) between 12 September 2014 and 29 February 2016. We randomised inner-city pregnant women with metabolic risk factors (obesity, chronic hypertension, or hypertriglyceridaemia) to a Mediterranean-style diet with high intake of nuts, extra virgin olive oil, fruits, vegetables, nonrefined grains, and legumes; moderate to high consumption of fish; low to moderate intake of poultry and dairy products; low intake of red and processed meat; and avoidance of sugary drinks, fast food, and food rich in animal fat versus usual care. Participants received individualised dietary advice at 18, 20, and 28 weeks' gestation. The primary endpoints were composite maternal (gestational diabetes or preeclampsia) and composite offspring (stillbirth, small for gestational age, or admission to neonatal care unit) outcomes prioritised by a Delphi survey. We used an intention-to-treat (ITT) analysis with multivariable models and identified the stratification variables and prognostic factors a priori. We screened 7,950 and randomised 1,252 women. Baseline data were available for 593 women in the intervention (93.3% follow-up, 553/593) and 612 in the control (95.6% follow-up, 585/612) groups. Over a quarter of randomised women were primigravida (330/1,205; 27%), 60% (729/1,205) were of Black or Asian ethnicity, and 69% (836/1,205) were obese. Women in the intervention arm consumed more nuts (70.1% versus 22.9%; adjusted odds ratio [aOR] 6.8, 95% confidence interval [CI] 4.3-10.6, p ≤ 0.001) and extra virgin olive oil (93.2% versus 49.0%; aOR 32.2, 95% CI 16.0-64.6, p ≤ 0.001) than controls; increased their intake of fish (p < 0.001), white meat (p < 0.001), and pulses (p = 0.05); and reduced their intake of red meat (p < 0.001), butter, margarine, and cream (p < 0.001). There was no significant reduction in the composite maternal (22.8% versus 28.6%; aOR 0.76, 95% CI 0.56-1.03, p = 0.08) or composite offspring (17.3% versus 20.9%; aOR 0.79, 95% CI 0.58-1.08, p = 0.14) outcomes. There was an apparent reduction in the odds of gestational diabetes by 35% (aOR 0.65, 95% CI 0.47-0.91, p = 0.01) but not in other individual components of the composite outcomes. Mothers gained less gestational weight (mean 6.8 versus 8.3 kg; adjusted difference -1.2 Kg, 95% CI -2.2 to -0.2, p = 0.03) with intervention versus control. There was no difference in any of the other maternal and offspring complications between both groups. When we pooled findings from the Effect of Simple, Targeted Diet in Pregnant Women With Metabolic Risk Factors on Pregnancy Outcomes (ESTEEM) trial with similar trials using random effects meta-analysis, we observed a significant reduction in gestational diabetes (odds ratio [OR] 0.67, 95% CI 0.53-0.84, I2 = 0%), with no heterogeneity (2 trials, 2,397 women). The study's limitations include the use of participant reported tools for adherence to the intervention instead of objective biomarkers. CONCLUSIONS: A simple, individualised, Mediterranean-style diet in pregnancy did not reduce the overall risk of adverse maternal and offspring complications but has the potential to reduce gestational weight gain and the risk of gestational diabetes. TRIAL REGISTRATION: ClinicalTrials.gov NCT02218931.

Maternal BMI and nutritional status in early pregnancy and its impact on neonatal outcomes at birth in Bangladesh.

BACKGROUND: To assess the maternal characteristics and nutritional status according to body mass index (BMI) at 6-14 weeks of gestation and to examine the relationship between maternal nutritional status in early pregnancy and its impact on neonatal birth weight. METHODS: The investigation was conducted from April 2011 to June 2012 in Dhaka, Bangladesh. A total of 498 primigravida pregnant women participated in the study; women with known diabetes or previous gestational diabetes (GDM) were excluded. Maternal demographic details, pregnancy history and anthropometric measurements were obtained from the mother at the recruitment (6-14 weeks), 2nd visit between 24 and 28 week of gestation and 3rd visit at delivery. Cord venous blood samples of newborns (n = 138) were collected immediately after delivery for blood glucose, insulin, lipid profile, leptin and micronutrients including serum folate, ferritin, homocysteine, vitamin D, and vitamin B12. RESULTS: The prevalence at 6-14 weeks of pregnancy of anemia (Hb, < 11 g/dl), vitamin D deficiency (< 30 nmol/l), vitamin B12 deficiency (< 200 pg/ml), high homocysteine level (> 15 µmol/l), folate deficiency (< 3 ng/ml) and iron deficiency (ferritin < 13 ng/ml) were 19.5, 46.4, 15.1, 1.2, 0.4, and 12.7% respectively. GDM was found in 18.4% women. The prevalence of GDM was higher in overweight women (28.1%) than underweight (16.7%) and normal weight women (16.0%: p <  0.05). The incidence of low birth weight (LBW) and preterm delivery were 11.6 and 5.8% respectively and was not related to maternal BMI at 6-14 weeks of pregnancy. Maternal height was positively (p = 0.02), and homocysteine was negatively associated with neonatal birth weight (p = 0.02). In addition, the newborn's cord serum folate was positively (p = 0.03) and cord triglyceride was negatively (p = 0.03) associated with neonatal birth weight. CONCLUSION: Multiple maternal micronutrient deficiencies were present in early pregnancy. Maternal BMI in early pregnancy was not related to preterm deliveries or LBW. LBW was associated with lower folate, elevated cord triglyceride concentrations of the neonates and mother's height and increase in maternal homocysteine levels. The data has important implications for pregnancy care in Bangladesh and other similar communities.

Maternal gestational diabetes is associated with genome-wide DNA methylation variation in placenta and cord blood of exposed offspring.

Exposure of a developing foetus to maternal gestational diabetes (GDM) has been shown to programme future risk of diabetes and obesity. Epigenetic variation in foetal tissue may have a mechanistic role in metabolic disease programming through interaction of the pregnancy environment with gene function. We aimed to identify genome-wide DNA methylation variation in cord blood and placenta from offspring born to mothers with and without GDM. Pregnant women of South Asian origin were studied and foetal tissues sampled at term delivery. The Illumina HumanMethylation450 BeadChip was used to assay genome-wide DNA methylation in placenta and cord blood from 27 GDM exposed and 21 unexposed offspring. We identified 1485 cord blood and 1708 placenta methylation variable positions (MVPs) achieving genome-wide significance (adjusted P-value <0.05) with methylation differences of >5%. MVPs were disproportionately located within first exons. A bioinformatic co-methylation algorithm was used to detect consistent directionality of methylation in 1000 bp window around each MVP was observed at 74% of placenta and 59% of cord blood MVPs. KEGG pathway analysis showed enrichment of pathways involved in endocytosis, MAPK signalling and extracellular triggers to intracellular metabolic processes. Replication studies should integrate genomics and transcriptomics with longitudinal sampling to elucidate stability, determine causality for translation into biomarker and prevention studies.

Quantification of the type 2 diabetes risk in women with gestational diabetes: a systematic review and meta-analysis of 95,750 women.

AIMS/HYPOTHESIS: Women with gestational diabetes mellitus (GDM) are at risk of developing type 2 diabetes, but individualised risk estimates are unknown. We conducted a meta-analysis to quantify the risk of progression to type 2 diabetes for women with GDM. METHODS: We systematically searched the major electronic databases with no language restrictions. Two reviewers independently extracted 2 × 2 tables for dichotomous data and the means plus SEs for continuous data. Risk ratios were calculated and pooled using a random effects model. RESULTS: There were 39 relevant studies (including 95,750 women) BMI (RR 1.95 [95% CI 1.60, 2.31]), family history of diabetes (RR 1.70 [95% CI 1.47, 1.97]), non-white ethnicity (RR 1.49 [95% CI 1.14, 1.94]) and advanced maternal age (RR 1.20 [95% CI 1.09, 1.34]) were associated with future risk of type 2 diabetes. There was an increase in risk with early diagnosis of GDM (RR 2.13 [95% CI 1.52, 3.56]), raised fasting glucose (RR 3.57 [95% CI 2.98, 4.04]), increased HbA1c (RR 2.56 [95% CI 2.00, 3.17]) and use of insulin (RR 3.66 [95% CI 2.78, 4.82]). Multiparity (RR 1.23 [95% CI 1.01, 1.50]), hypertensive disorders in pregnancy (RR 1.38 [95% CI 1.32, 1.45]) and preterm delivery (RR 1.81 [95% CI 1.35, 2.43]) were associated with future diabetes. Gestational weight gain, macrosomia in the offspring or breastfeeding did not increase the risk. CONCLUSIONS/INTERPRETATION: Personalised risk of progression to type 2 diabetes should be communicated to mothers with GDM. SYSTEMATIC REVIEW REGISTRATION: www.crd.york.ac.uk/PROSPERO CRD42014013597.

Effect of atorvastatin on glycaemia progression in patients with diabetes: an analysis from the Collaborative Atorvastatin in Diabetes Trial (CARDS).

AIMS/HYPOTHESIS: In an individual-level analysis we examined the effect of atorvastatin on glycaemia progression in type 2 diabetes and whether glycaemia effects reduce the prevention of cardiovascular disease (CVD) with atorvastatin. METHODS: The study population comprised 2,739 people taking part in the Collaborative Atorvastatin Diabetes Study (CARDS) who were randomised to receive atorvastatin 10 mg or placebo and who had post-randomisation HbA1c data. This secondary analysis used Cox regression to estimate the effect of atorvastatin on glycaemia progression, defined as an increase in HbA1c of ≥ 0.5% (5.5 mmol/mol) or intensification of diabetes therapy. Mixed models were used to estimate the effect of atorvastatin on HbA1c as a continuous endpoint. RESULTS: Glycaemia progression occurred in 73.6% of participants allocated placebo and 78.1% of those allocated atorvastatin (HR 1.18 [95% CI 1.08, 1.29], p < 0.001) by the end of follow-up. The HR was 1.22 (95% CI 1.19, 1.35) in men and 1.11 (95% CI 0.95, 1.29) in women (p = 0.098 for the sex interaction). A similar effect was seen in on-treatment analyses: HR 1.20 (95% CI 1.07, 1.35), p = 0.001. The net mean treatment effect on HbA1c was 0.14% (95% CI 0.08, 0.21) (1.5 mmol/mol). The effect did not increase through time. Diabetes treatment intensification alone did not differ with statin allocation. Neither baseline nor 1-year-attained HbA1c predicted subsequent CVD, and the atorvastatin effect on CVD did not vary by HbA1c change (interaction p value 0.229). CONCLUSIONS/INTERPRETATION: The effect of atorvastatin 10 mg on glycaemia progression among those with diabetes is statistically significant but very small, is not significantly different between sexes, does not increase with duration of statin and does not have an impact on the magnitude of CVD risk reduction with atorvastatin.