In this project, we seek to identify novel blood-based epigenomic biomarkers to be used in early childhood as: biomarkers of natural history of prenatal exposure to gestational diabetes (GDM) and for profiling risks of obesity and cardiometabolic phenotypes among children born to GDM mothers (Aim 1);and intervention biomarkers that can help to predict the success of an early-childhood lifestyle intervention aiming at preventing GDM-related metabolic sequelae later in life (Aim 2). We will leverage extant resources from two investigations in Tianjin, China, i.e., the Tianjin GDM longitudinal observational study (TGDM-O) and the Tianjin GDM lifestyle-intervention randomized controlled trial (TGDM- T), both of which have been funded by the European Foundation for the Study of Diabetes (EFSD).
In Aim 1, we will identify blood methylomic patterns in TGDM-O correlated with prenatal GDM exposure and/or that predict adverse post-natal trajectories of body weight, adiposity and cardiometabolic phenotypes up to 10 years of age. We will also dissect genetic influences on the methylome by conducting joint analysis of genome- wide genetic (GWAS) and methylomic (EWAS) data. To ensure generalizability, we will confirm our findings in three large independent cohorts in the US and Europe (i.e., Project Viva, Avon Longitudinal Study of Parents and Children [ALSPAC], and Born in Bradford).
In Aim 2, we will leverage the resources of the ongoing TGDM- T to identify child's blood methylomic profiles that are induced by a 3-year lifestyle intervention. We will test our hypothesis that post-intervention methylomic profiles will allow for differentiating children who will maintain positive effects on body weight and metabolic profiles 2 years after the end of the intervention from those who will lose its benefits or rebound. In both aims, we will perform bisulfite-pyrosequencing for technical validation of DNA methylation findings and mRNA analysis to test whether methylomic differences correlate to gene expression. This will be the first study to prospectively examine the effects of GDM on the child's methylome and metabolic health, as well as to determine whether the lasting success of an early-life intervention can be predicted by monitoring changes in methylomic biomarkers. If successful, our project may provide novel tools to guide early childhood interventions through early biomarker monitoring. These biomarkers would be eventually used to implement personalized measures among children with GDM exposure and enhance long-lasting benefits to obesity prevention.
Gestational Diabetes Mellitus (GDM) is tightly linked to overweight and obesity and is now diagnosed in as many as 7% of pregnancies in the US. In this project, we will identify novel biomarkers that can reconstruct prenatal GDM exposure and profile future risks of childhood obesity and related cardiometabolic phenotypes. We will also measure the efficacy of a lifestyle intervention at both molecular and phenotype levels. Our results will generate new scientific knowledge that may pave the way for future efforts for the prevention of childhood obesity and cardiovascular diseases.
|Nisa, Hoirun; Qi, Kevin H T; Leng, Junhong et al. (2018) The Circadian Rhythm-Related MTNR1B Genotype, Gestational Weight Gain, and Postpartum Glycemic Changes. J Clin Endocrinol Metab 103:2284-2290|
|Liu, Huikun; Wang, Leishen; Zhang, Shuang et al. (2018) One-year weight losses in the Tianjin Gestational Diabetes Mellitus Prevention Programme: A randomized clinical trial. Diabetes Obes Metab 20:1246-1255|
|Li, Weiqin; Leng, Junhong; Liu, Huikun et al. (2018) Nomograms for incident risk of post-partum type 2 diabetes in Chinese women with prior gestational diabetes mellitus. Clin Endocrinol (Oxf) :|
|Shen, Yun; Wang, Peng; Wang, Leishen et al. (2018) Gestational diabetes with diabetes and prediabetes risks: a large observational study. Eur J Endocrinol 179:51-58|
|Wang, Jing; Liu, Enqing; Wang, Yue et al. (2018) Association of early pregnancy body mass index and children's birth weight with risk of being overweight in childhood. Am J Hum Biol 30:e23174|
|Han, Liyuan; Duan, Donghui; Zhang, Shuang et al. (2018) Effects of the interaction between glycated haemoglobin genetic risk score and postpartum weight reduction on glycaemic changes: A gene-weight interaction analysis. Diabetes Obes Metab 20:2733-2739|
|Zhang, S; Wang, L; Leng, J et al. (2017) Hypertensive disorders of pregnancy in women with gestational diabetes mellitus on overweight status of their children. J Hum Hypertens 31:731-736|
|Zhang, Tao; Wang, Peng; Liu, Huikun et al. (2017) Physical Activity, TV Watching Time, Sleeping, and Risk of Obesity and Hyperglycemia in the Offspring of Mothers with Gestational Diabetes Mellitus. Sci Rep 7:41115|
|Li, Weiqin; Wang, Leishen; Li, Nan et al. (2017) Maternal Prepregnancy BMI and Glucose Level at 24-28 Gestational Weeks on Offspring's Overweight Status within 3 Years of Age. Biomed Res Int 2017:7607210|
|Leng, Junhong; Wang, Leishen; Wang, Jing et al. (2017) Uric acid and diabetes risk among Chinese women with a history of gestational diabetes mellitus. Diabetes Res Clin Pract 134:72-79|
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