The prevalence and predictive value of the SLC30A8 R325W polymorphism and zinc transporter 8 autoantibodies in the development of GDM and postpartum type 1 diabetes

Mechanisms and Physiological Roles of Polymorphisms in Gestational Diabetes Mellitus

Gestational diabetes mellitus (GDM) is a significant pregnancy complication linked to perinatal complications and an elevated risk of future metabolic disorders for both mothers and their children. GDM is diagnosed when women without prior diabetes develop chronic hyperglycemia due to β-cell dysfunction during gestation. Global research focuses on the association between GDM and single nucleotide polymorphisms (SNPs) and aims to enhance our understanding of GDM's pathogenesis, predict its risk, and guide patient management. This review offers a summary of various SNPs linked to a heightened risk of GDM and explores their biological mechanisms within the tissues implicated in the development of the condition.

Autoantibodies predict type 1 diabetes after gestational diabetes - a 23-year cohort study

Objective

To study the predictive value of autoantibodies for type 1 (T1DM) and type 2 (T2DM) diabetes morbidity after gestational diabetes (GDM) in a 23-year follow-up study.

Design

Prospective population-based cohort study.

Methods

We studied 391 women with GDM, and 391 age- and parity-matched controls, who delivered in 1984-1994. Four autoantibodies were analysed in first-trimester blood samples: islet cell autoantibodies (ICAs), glutamic acid decarboxylase autoantibodies (GADAs), insulin autoantibodies (IAAs) and insulinoma-associated antigen-2 autoantibodies (IA-2As). Two follow-up questionnaires (1995-1996, 2012-2013) were sent to assess development of T1DM and T2DM. Predictive value of autoantibodies and clinical factors were analysed by conditional linear regression and ROC analyses.

Results

Single autoantibody positivity was detected in 12% (41/342) of the GDM cohort and in 2.3% (8/353) of the control cohort. In the GDM cohort, 2.6% (9/342) tested positive for two autoantibodies and 2.3% (8/342) for three autoantibodies, whereas only one subject in the control cohort had two autoantibodies. ICA positivity was found in 12.5% of the cases, followed by GADA (6.0%), IA-2A (4.9%) and IAA (1.2%). In the control cohort, GADA positivity was found in 1.4%, IA-2A in 0.8%, IAA in 0.6%, and ICA in 0.3% of the subjects. Detection of ICA, GADA and/or IA-2A autoantibodies decreased T1DM-free survival time and time to diagnosis. All subjects with three positive autoantibodies developed T1DM within seven years from the GDM pregnancy. Development of T2DM after GDM occurred independent of autoantibody positivity.

Conclusion

Development of T1DM can be reliably predicted with GADA and ICA autoantibodies during early pregnancy.

Association of HHEX and SLC30A8 Gene Polymorphisms with Gestational Diabetes Mellitus Susceptibility: A Meta-analysis

Genetics plays a role in the development of gestational diabetes mellitus (GDM), which poses serious risks to pregnant women and their children. Several studies have demonstrated a link between GDM susceptibility and rs13266634 C/T polymorphism in SLC30A8 gene and rs1111875 C/T and rs5015480 C/T, which are located near the linkage disequilibrium block containing the IDE, HHEX, and KIF11 genes. However, the results are conflicting. Therefore, we aimed to investigate the association between susceptibility to GDM and HHEX and SLC30A8 gene polymorphisms. PubMed, Web of Science, EBSCO, CNKI, Wanfang Data, VIP, and SCOPUS were used to search for research articles. The quality of the selected literature was evaluated using the Newcastle-Ottawa scale. A meta-analysis was performed using Stata 15.1. Allelic, dominant, recessive, homozygote, and heterozygote models were used for the analysis. Nine articles with 15 studies were included. (1) Four studies about HHEX rs1111875 showed that the C allele was associated with the susceptibility to GDM; (2) three studies on HHEX rs5015480 indicated that the C allele in rs5015480 was significantly associated with GDM; (3) eight studies about SLC30A8 rs13266634 showed that the C allele was significantly associated with the susceptibility to GDM; and (4) a subgroup analysis showed that the rs5015480 polymorphism in HHEX and rs13266634 polymorphism in SLC30A8 gene were associated with GDM susceptibility in Asians. The meta-analysis provided evidence that the C allele in rs1111875 and rs5015480 in HHEX and rs13266634 in SLC30A8 can increase the risk of GDM.PROSPERO registration number CRD42022342280.

Association of solute carrier family 30 A8 zinc transporter gene variations with gestational diabetes mellitus risk in a Chinese population

Background

The solute carrier family 30 A8 zinc transporter (SLC30A8) plays a crucial role in insulin secretion. This study aimed to investigate the impact of SLC30A8 gene polymorphisms on gestational diabetes mellitus (GDM).

Methods

The research objective was to select 500 patients with GDM and 502 control subjects. Rs13266634 and rs2466293 were genotyped using the SNPscan™ genotyping assay. Statistical tests, such as the chi-square test, t-test, logistic regression, ANOVA, and meta-analysis, were conducted to determine the differences in genotypes, alleles, and their associations with GDM risk.

Results

Statistically significant differences were observed in age, pregestational BMI, SBP, DBP, and parity between individuals with GDM and healthy subjects (P < 0.05). After adjusting for these factors, rs2466293 remained significantly associated with an increased risk of GDM in overall subjects (GG+AG vs. AA: OR = 1.310; 95% CI: 1.005-1.707; P = 0.046, GG vs. AA: OR = 1.523; 95% CI: 1.010-2.298; P = 0.045 and G vs. A: OR = 1.249; 95% CI: 1.029-1.516; P = 0.024). Rs13266634 was still found to be significantly associated with a decreased risk of GDM in individuals aged ≥ 30 years (TT vs. CT+CC: OR = 0.615; 95% CI: 0.392-0.966; P = 0.035, TT vs. CC: OR = 0.503; 95% CI: 0.294-0.861; P = 0.012 and T vs. C: OR =0.723; 95% CI: 0.557-0.937; P = 0.014). Additionally, the haplotype CG was found to be associated with a higher risk of GDM (P < 0.05). Furthermore, pregnant women with the CC or CT genotype of rs13266634 exhibited significantly higher mean blood glucose levels than those with the TT genotype (P < 0.05). Our findings were further validated by the results of a meta-analysis.

Conclusion

The SLC30A8 rs2466293 polymorphism was found to be associated with an increased risk of GDM, while rs13266634 was associated with a decreased risk of GDM in individuals aged ≥ 30 years. These findings provide a theoretical basis for GDM testing.

Development and validation of risk prediction models for large for gestational age infants using logistic regression and two machine learning algorithms

BACKGROUND

Large for gestational age (LGA) is one of the adverse outcomes during pregnancy that endangers the life and health of mothers and offspring. We aimed to establish prediction models for LGA at late pregnancy.

METHODS

Data were obtained from an established Chinese pregnant women cohort of 1285 pregnant women. LGA was diagnosed as >90th percentile of birth weight distribution of Chinese corresponding to gestational age of the same-sex newborns. Women with gestational diabetes mellitus (GDM) were classified into three subtypes according to the indexes of insulin sensitivity and insulin secretion. Models were established by logistic regression and decision tree/random forest algorithms, and validated by the data.

RESULTS

A total of 139 newborns were diagnosed as LGA after birth. The area under the curve (AUC) for the training set is 0.760 (95% confidence interval [CI] 0.706-0.815), and 0.748 (95% CI 0.659-0.837) for the internal validation set of the logistic regression model, which consisted of eight commonly used clinical indicators (including lipid profile) and GDM subtypes. For the prediction models established by the two machine learning algorithms, which included all the variables, the training set and the internal validation set had AUCs of 0.813 (95% CI 0.786-0.839) and 0.779 (95% CI 0.735-0.824) for the decision tree model, and 0.854 (95% CI 0.831-0.877) and 0.808 (95% CI 0.766-0.850) for the random forest model.

CONCLUSION

We established and validated three LGA risk prediction models to screen out the pregnant women with high risk of LGA at the early stage of the third trimester, which showed good prediction power and could guide early prevention strategies.

Development and Validation of Risk Prediction Models for Gestational Diabetes Mellitus Using Four Different Methods

Gestational diabetes mellitus (GDM), a common perinatal disease, is related to increased risks of maternal and neonatal adverse perinatal outcomes. We aimed to establish GDM risk prediction models that can be widely used in the first trimester using four different methods, including a score-scaled model derived from a meta-analysis using 42 studies, a logistic regression model, and two machine learning models (decision tree and random forest algorithms). The score-scaled model (seven variables) was established via a meta-analysis and a stratified cohort of 1075 Chinese pregnant women from the Northwest Women's and Children's Hospital (NWCH) and showed an area under the curve (AUC) of 0.772. The logistic regression model (seven variables) was established and validated using the above cohort and showed AUCs of 0.799 and 0.834 for the training and validation sets, respectively. Another two models were established using the decision tree (DT) and random forest (RF) algorithms and showed corresponding AUCs of 0.825 and 0.823 for the training set, and 0.816 and 0.827 for the validation set. The validation of the developed models suggested good performance in a cohort derived from another period. The score-scaled GDM prediction model, the logistic regression GDM prediction model, and the two machine learning GDM prediction models could be employed to identify pregnant women with a high risk of GDM using common clinical indicators, and interventions can be sought promptly.

Type 1 diabetes-related autoimmune antibodies in women with gestational diabetes mellitus and the long-term risk for glucose intolerance

AIMS

To characterize women with gestational diabetes mellitus (GDM) positive for type 1 diabetes-related autoimmune antibodies (T1D-related autoantibodies) in pregnancy and to evaluate their risk for long-term glucose intolerance.

METHODS

In a multi-centric prospective cohort study with 1843 women receiving universal screening for GDM with a 75 g oral glucose tolerance test (OGTT), autoantibodies were measured in women with GDM: insulin autoantibodies (IAA), islet cell antibodies (ICA), insulinoma-associated protein-2 antibodies (IA-2A) and glutamic acid decarboxylase antibodies (GADA). Long-term follow-up ( ± 4.6 years after delivery) with a 75 g OGTT and re-measurement of autoantibodies was done in women with a history of GDM and autoantibody positivity in pregnancy.

RESULTS

Of all women with GDM (231), 80.5% (186) received autoantibody measurement at a mean of 26.2 weeks in pregnancy, of which 8.1% (15) had one positive antibody (seven with IAA, two with ICA, four with IA-2A and two with GADA). Characteristics in pregnancy were similar but compared to women without autoantibodies, women with autoantibodies had more often gestational hypertension [33.3% (5) vs. 1.7% (3), p<0.001] and more often neonatal hypoglycemia [40.0% (6) vs. 12.5% (19), p=0.012]. Among 14 of the 15 autoantibody positive women with an early postpartum OGTT, two had impaired fasting glucose (IFG). Of the 12 women with long-term follow-up data, four tested again positive for T1D-related autoantibodies (three positive for IA-2A and one positive for ICA and IAA). Five women were glucose intolerant at the long-term follow-up of which two had IA-2A (one had IFG and one had T1D) and three without autoantibodies. There were no significant differences in long-term characteristics between women with and without autoantibodies postpartum.

CONCLUSIONS

Systematic screening for T1D-related autoantibodies in GDM does not seem warranted since the low positivity rate for autoantibodies in pregnancy and postpartum. At 4.6 years postpartum, five out of 12 women were glucose intolerant but only two still had autoantibodies. In women with clinically significant increased autoantibody levels during pregnancy, postpartum autoantibody re-measurement seems useful since the high risk for further increase of autoantibody levels.

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.

N6-Methyladenosine-Related Gene Signature Associated With Monocyte Infiltration Is Clinically Significant in Gestational Diabetes Mellitus

OBJECTIVE

The objective of this study was to reveal the potential crosstalk between immune infiltration and N⁶- methyladenosine (m⁶A) modification in the placentas of patients with gestational diabetes mellitus (GDM), and to construct a model for the diagnosis of GDM.

METHODS

We analyzed imbalanced immune infiltration and differentially expressed m⁶A-related genes (DMRGs) in the placentas of patients with GDM, based on the GSE70493 dataset. An immune-related DMRG signature, with significant classifying power and diagnostic value, was identified using a least absolute shrinkage and selection operator (LASSO) regression. Based on the selected DMRGs, we developed and validated a nomogram model using GSE70493 and GSE92772 as the training and validation sets, respectively.

RESULTS

Infiltration of monocytes was higher in GDM placentas than in control samples, while the infiltration of macrophages (M1 and M2) in GDM placentas was lower than in controls. A total of 14 DMRGs were strongly associated with monocyte infiltration, seven of which were significant in distinguishing patients with GDM from normal controls. These genes were CD81, CFH, FABP5, GBP1, GNG11, IL1RL1, and SLAMF6. The calibration curve, decision curve, clinical impact curve, and receiver operating characteristic curve showed that the nomogram recognized GDM with high accuracy in both the training and validation sets.

CONCLUSIONS

Our results provide clues that crosstalk between m⁶A modification and immune infiltration may have implications in terms of novel biomarkers and therapeutic targets for GDM.

Is serum zinc status related to gestational diabetes mellitus? A meta-analysis

Gestational diabetes mellitus (GDM) is a common medical disorder that begins during pregnancy. The present work aimed to investigate the relationship of maternal or foetal circulatory zinc levels with GDM. Related studies were retrieved against the PubMed/Medline, Web of Science, Scopus databases till July 2020. The overall effects were expressed as standard mean difference (SMD). Furthermore, the random effects model was used to assess the summarised risk ratios (SRRs) to determine the relationship between zinc and the risk of GDM. A total of 15 articles involving were retrieved for meta‐analysis; in the meantime, 4955 subjects including 1549 GDM cases were enrolled for quantitative analysis. Compared with normal control, GDM cases had decreased circulating zinc level on the whole, but the difference was not statistically significant (SMD = −0.40, 95%CI: −0.80 to −0.00, P = 0.05). Interestingly, upon subgroup analysis stratified by serum zinc content but not plasma zinc concentration, there was significant difference in zinc content between GDM cases and normal controls (SMD = −0.56; 95%CI: −1.07 to −0.04, P = 0.03). Meanwhile, subgroup analysis also revealed similar tendency among the Asians and during the 2nd trimester, but not among the Caucasians or during the 1st or 3rd trimester. Data extracted from four studies that compared pregnant women with GDM in the high level of zinc and GDM in the low level of zinc yielded an SRR of 0.929 (95%CI: 0.905–0.954). According to existing evidence, the serum zinc content decreases among GDM cases compared with subjects with no abnormality in glucose tolerance, in particular among the Asians and during the second trimester. Nonetheless, more well designed prospective study should be carried out for understanding the dynamic relationship of zinc level with the incidence of GDM.

Risk Factors Screening for Gestational Diabetes Mellitus Heterogeneity in Chinese Pregnant Women: A Case-Control Study

PURPOSE

To study the risk factors of gestational diabetes mellitus (GDM) heterogeneity, and to evaluate the correlation between the risk factors and obesity.

METHODS

We performed a case-control study of 452 women with GDM and 516 women with normal glucose tolerance (NGT) at the first and second trimester. We defined GDM women as GDM-resistance subtype, GDM-dysfunction subtype, and GDM-mixed subtype, according to their simultaneous insulin-release test with predominant insulin-sensitivity defect, insulin-secretion defect, or both defects.

RESULTS

We found that higher maternal age, family history of diabetes, the elevated level of fasting blood glucose in the first trimester (≥5.1 mmol/L) were risk factors of all GDM subtypes. Pre-pregnancy overweight/obesity and the increased gestational weight gain (GWG) in the first-trimester are risk factors of the GDM-resistance subtype. Indicators including younger age at first menstruation, the elevated levels of alanine aminotransferase (ALT), total bile acid (TBA), triglyceride (TG), and the decreased level of high-density lipoprotein cholesterol (HDL-C) are risk factors of the GDM-resistance subtype. However, the associations between those risk factors and GDM-resistance subtype attenuated after adjusted by pre-pregnancy body mass index (pre-BMI) and gestational weight gain (GWG) in the first trimester. Nonalcoholic fatty liver disease (NAFLD) and the improved level of TG are independent risk factors for the GDM-resistance subtype and the GDM-mixed subtype, respectively.

CONCLUSION

Women with GDM exhibited heterogeneity based on glycemic physiology and their risk factors are not all the same. Some obesity-related risk factors are specific to the GDM-resistance subtype, which are mediated by pre-pregnancy overweight/obesity and the elevated GWG the first-trimester.

Testing for type 1 diabetes autoantibodies in gestational diabetes mellitus (GDM): is it clinically useful?

Gestational Diabetes Mellitus (GDM) is the most common metabolic disorder in pregnancy, and it is associated with increased risk of morbidity in maternal-fetal outcomes. GDM is also associated with a higher risk to develop diabetes in the future. Diabetes-related autoantibodies (AABs) have been detected in a small percentage (usually less than 10%) of women with gestational diabetes. The prevalence in gestational diabetes of these autoimmune markers of type 1 diabetes (T1D) has been assessed in many studies, together with the risk of progression of AABs-positive GDM towards impaired glucose regulation (IFG or IGT) and overt diabetes after pregancy. The question whether it is necessary to test for T1D autoantibodies in all pregnancies with GDM is still debated. Here we examine the epidemiology of T1D autoantibodies in GDM, their clinical relevance in term of future risk of diabetes or impaired glucose regulation and in term of maternal-fetal outcomes, and discuss when it may be the most appropriate time to search for T1D autoantibodies in women with gestational diabetes.

Heterogeneous impact of type 2 diabetes mellitus-related genetic variants on gestational glycemic traits: review and future research needs

Gestational glucose homeostasis influences mother's metabolic health, pregnancy outcomes, fetal development and offspring growth. To understand the genetic roles in pregnant glucose metabolism and genetic predisposition for gestational diabetes (GDM), we reviewed the recent literature up to Jan, 2018 and evaluated the influence of T2DM-related genetic variants on gestational glycemic traits and glucose tolerance. A total of 140 variants of 89 genes were integrated. Their associations with glycemic traits in and outside pregnancy were compared. The genetic circumstances underlying glucose metabolism exhibit a similarity between pregnant and non-pregnant populations. While, not all of the T2DM-associated genetic variants are related to pregnant glucose tolerance, such as genes involved in fasting insulin/C-peptide regulation. Some genetic variants may have distinct effects on gestational glucose homeostasis. And certain genes may be particularly involved in this process via specific mechanisms, such as HKDC1, MTNR1B, BACE2, genes encoding cell cycle regulators, adipocyte regulators, inflammatory factors and hepatic factors related to gestational glucose sensing and insulin signaling. However, it is currently difficult to evaluate these associations with quantitative synthesis due to inadequate data, different analytical methods, varied measurements for glycemic traits, controversies in diagnosis of GDM, and unknown ethnicity- and/or sex-related influences on pregnant maternal metabolism. In conclusion, different genetic associations with glycemic traits may exist between pregnant and non-pregnant conditions. Comprehensive research on specific genetic regulation in gestation is necessary.

Autoantibodies against ZnT8 are rare in Central-European LADA patients and absent in MODY patients, including those positive for other autoantibodies

BACKGROUND

Testing for autoantibodies against the zinc transporter ZnT8 (ZnTA) is becoming routine in pediatric diabetes. However, available data are inconclusive when focusing on adult-onset diabetes, including autoimmune diabetes, which does not require insulin at diagnosis (LADA).

BASIC PROCEDURES

We examined the ZnTA prevalence and titers and matched them with the clinical phenotype and PTPN22 genotypes of Czech LADA patients who were positive for GADA and/or IA2A and had a fasting C-peptide level >200 pmol/L at diagnosis as well as HNF4A-, GCK- or HNF1A-MODY patients and healthy controls.

MAIN FINDINGS

Most LADA patients were negative for ZnTA, and the sensitivity of the assay was only 18-20% for patients with LADA-like progression to insulinotherapy compared to healthy controls. In LADA patients, there was no association between the ZnTA and PTPN22 risk genotypes. LADA patients positive for ZnTA had a lower BMI than those positive for other autoantibodies alone. Importantly, MODY patients were completely negative for ZnTA, and the levels of ZnTA in MODY patients were similar to those in healthy controls.

CONCLUSIONS

ZnTA quantification did not improve LADA diagnosis. However, positivity for ZnTA can be used as a negative MODY pre-diagnostic criterion even in the region of Central and East Europe, where other islet cell autoantibodies are common in MODY patients.

Association of type 2 diabetes susceptible genes GCKR, SLC30A8, and FTO polymorphisms with gestational diabetes mellitus risk: a meta-analysis

PURPOSE

Current studies have detected the correlation of polymorphisms in type 2 diabetes susceptible genes GCKR, SLC30A8 and FTO with gestational diabetes mellitus (GDM) risk. However, findings of these studies were incongruous. Hence, we performed an integrated review and meta-analysis for the researches regarding the association of single nucleotide polymorphisms (SNPs) in GCKR, SLC30A8 and FTO genes and GDM risk.

METHODS

Eligible publications were selected on the basis of several inclusion and exclusion criteria. Correlation between each SNP and GDM risk was estimated by computing odds ratios (ORs) with 95% confidence intervals (95%CIs).

RESULTS

Consequently, 19 case-control studies (from 16 citations) including 3636 GDM cases and 7229 GDM-free controls were participated in a meta-analysis of seven prevalent SNPs (GCKR rs1260326 and rs780094; SLC30A8 rs13266634 and rs11558471; FTO rs8050136, rs1421085 and rs9939609). Our results demonstrated that the rs780094, rs13266634 and rs9939609 SNPs were significantly associated with GDM risk. In stratified analysis, correlations of rs780094 and rs13266634 SNPs could be observed in Asian and Caucasian subgroups. Moreover, association between rs9939609 SNP and GDM risk was detected in Caucasian subgroup.

CONCLUSIONS

The GCKR rs780094, SLC30A8 rs13266634 and FTO rs9939609 SNPs were demonstrated to be the potential biomarkers for GDM risk prediction.

Molecular Biomarkers for Gestational Diabetes Mellitus

Gestational diabetes mellitus (GDM) is a growing public health problem worldwide. The condition is associated with perinatal complications and an increased risk for future metabolic disease in both mothers and their offspring. In recent years, molecular biomarkers received considerable interest as screening tools for GDM. The purpose of this review is to provide an overview of the current status of single-nucleotide polymorphisms (SNPs), DNA methylation, and microRNAs as biomarkers for GDM. PubMed, Scopus, and Web of Science were searched for articles published between January 1990 and August 2018. The search terms included “gestational diabetes mellitus”, “blood”, “single-nucleotide polymorphism (SNP)”, “DNA methylation”, and “microRNAs”, including corresponding synonyms and associated terms for each word. This review updates current knowledge of the candidacy of these molecular biomarkers for GDM with recommendations for future research avenues.

Maternal obesity as a risk factor for early childhood type 1 diabetes: a nationwide, prospective, population-based case-control study

AIMS/HYPOTHESIS

Genetic and environmental factors are believed to cause type 1 diabetes. The aim of this study was to investigate the influence of maternal BMI and gestational weight gain on the subsequent risk of childhood type 1 diabetes.

METHODS

Children in the Swedish National Quality Register for Diabetes in Children were matched with control children from the Swedish Medical Birth Register. Children were included whose mothers had data available on BMI in early pregnancy and gestational weight gain, giving a total of 16,179 individuals: 3231 children with type 1 diabetes and 12,948 control children.

RESULTS

Mothers of children with type 1 diabetes were more likely to be obese (9% [n = 292/3231] vs 7.7% [n = 991/12,948]; p = 0.02) and/or have diabetes themselves (2.8% [n = 90/3231] vs 0.8% [n = 108/12,948]; p < 0.001) compared with mothers of control children. Gestational weight gain did not differ significantly between the two groups of mothers. In mothers without diabetes, maternal obesity was a significant risk factor for type 1 diabetes in the offspring (p = 0.04). A child had an increased risk of developing type 1 diabetes if the mother had been obese in early pregnancy (crude OR 1.20; 95% CI 1.05, 1.38; adjusted OR 1.18; 95% CI 1.02, 1.36). Among children with type 1 diabetes (n = 3231) there was a difference (p < 0.001) in age at onset in relation to the mother's BMI. Among children in the oldest age group (15-19 years), there were more mothers who had been underweight during pregnancy, while in the youngest age group (0-4 years) the pattern was reversed.

CONCLUSIONS/INTERPRETATION

Maternal obesity, in the absence of maternal diabetes, is a risk factor for type 1 diabetes in the offspring, and influences the age of onset of type 1 diabetes. This emphasises the importance of a normal maternal BMI to potentially decrease the incidence of type 1 diabetes.