Early pregnancy associations with Gestational Diabetes: methods and cohort results of the Hoosier Moms Cohort

Background Gestational Diabetes (GDM) raises the risk of adverse perinatal outcomes and long-term risk of type 2 diabetes. There is currently a lack of comprehensive GDM prediction models based on more than simple clinical features. Objective The objective of this study was to collect a comprehensive set of clinical, sociodemographic, biobehavioral, and genomic features in a prospective high-risk cohort for GDM, to discover novel predictive and therapeutic targets for GDM during early pregnancy. Study design The Hoosier Moms Cohort was a prospective observational study of pregnant individuals, with a singleton gestation <20 weeks. The study protocol included 2 visits during pregnancy and one at delivery. Psychosocial, dietary, social, and demographic characteristics were collected in addition to maternal and newborn samples. Developing GDM was the primary outcome. Univariate associations with GDM for continuous variables were analyzed using either two-sample t-test or Wilcoxon Rank Sum test, and categorical variables using either chi-square or Fishers exact test. Multiple logistic regression was performed for independent associations with GDM. Results A total of 411 participants were recruited, with complete data available for 391. Patients were on average 30 years of age, had a mean body mass index (BMI) of 28, and 17% were of Hispanic ethnicity. Additionally, 54% reported a family history of diabetes, with 4% reporting a personal prior history of GDM. A total of 39 participants (10.0%) developed GDM. Compared to those that did not, participants who developed GDM had a significantly higher baseline BMI (31.6 vs 27.2, p=0.003), HbA1c (5.24 vs 5.07, p<0.001), triglycerides (156.8 vs 134.2, p=0.022), and random blood glucose (85.90 vs 79.96, p=0.025) at the initial visit. Those with GDM were more likely to have a prior history of gestational diabetes (28.21% vs 1.96%, p<0.001), and current chronic hypertension (12.82% vs 1.9%, p=0.003). Additionally, they scored higher on a validated insomnia questionnaire (9.62 vs 7.80, p=0.028). A significant association was found between GDM and 3 previously reported genetic markers (p<0.01). Individuals with high polygenic risk scores for type 2 diabetes were not more likely to have a GDM diagnosis. Through stepwise logistic regression, prior history of GDM, current diagnosis of hypertension, insomnia, and BMI were independently associated with GDM (odds ratio, 95% confidence intervals: 14.98, 4.49-50.02; 10.94, 2.32-51.69; 1.11, 1.01-1.22; 1.09, 1.03-1.16, respectively). Conclusion The Hoosier Moms Cohort identified that participants with a previous GDM diagnosis, chronic hypertension, elevated BMI, and insomnia have significantly increased odds of developing GDM in a diverse cohort of participants. These factors will be integrated into a machine learning model with multi-omics data to develop a comprehensive predictor for GDM.