Social and gene interactions to understand the risk of gestational diabetes mellitus

项目总结/文摘

PROJECT SUMMARY/ABSTRACT Gestational diabetes mellitus (GDM) is a risk factor for pregnancy complications and long-term morbidities affecting both women with the condition and their offspring. Asian women are disproportionately impacted by GDM but tend to have a lower prevalence of obesity, suggesting the possibility of a genetic or lifestyle predisposition in this group. We have the unique opportunity to use high-quality epidemiological, clinical and genetic data from a large Japanese cohort of ~22,000 pregnant women that could provide valuable insight regarding the etiology of GDM, including the interaction of lifestyle and genetic factors that play important roles in pregnancy-induced adaptation of glucose physiology. Independent of genetics, lifestyle factors (e.g., diet, physical activity) and social factors (e.g., social support, social capital) have been found to be predictors of GDM. Estimation of the effects of different levels of social, lifestyle, or behavioral factors in different genotypes could ultimately inform the personalization of lifestyle interventions to a person’s genetic makeup to prevent GDM. However, we could find only two studies on the association between genotypes and GDM and none on interactions between genetics and lifestyle or social determinants on the development of GDM, making this study highly innovative. To investigate such interactions, we will leverage already collected single nucleotide polymorphism (SNP) data from the Tohoku Medical Megabank Birth and Three-Generation Cohort Study: 1) to examine how genotypes of mothers and their fetuses modify the effects of lifestyle/behavioral factors (e.g., physical activity, sedentary behavior, dietary quality, sleep patterns, screen time) and anthropometry (e.g., BMI, waist circumference) on the risk of developing GDM in pregnant women (Aim 1), and 2) to examine how particular genotypes of mothers and fetuses modify the effects of social factors (e.g., social support/networks, social capital, socio-economic status) on the risk of developing GDM among pregnant women (Aim 2). We will first conduct a genome-wide association study (GWAS) using genome-wide SNP data to assess associations between each individual SNP and the risk of GDM, while accounting for relatedness between mother-infant dyads (and mothers and other relatives). We will also develop a novel genome-wide polygenic score for GDM, based on prior studies and maternal and fetal SNPs we identify (by assessing whether the existing score can be improved by adding or removing SNPs). Finally, while also taking into account relatedness, we will analyze associations between genotypes, lifestyle/behavioral and social factors, and GDM risk, specifically by conducting gene-environment interaction analyses to examine how particular genotypes modify the effects of specific lifestyle/behavioral and social factors on the risk of GDM. We expect to identify genetic and environmental risk factors that can inform “precision medicine” treatment approaches (i.e., personalized preventive interventions for GDM) to contribute to the prevention of GDM and its sequelae.