Continuous Glucose and Fetal State Monitoring: A Novel Approach to Understanding Neurodevelopmental Trajectories in Gestational Diabetes - ABSTRACT My research program focuses on leveraging novel technologies to study the influence of maternal metabolism on fetal behavior during pregnancy, with a focus on understanding early biomarkers of fetal-to-infant neurodevelopment. The proposed project will implement innovative wearable devices to study the impact of maternal glucose on fetal development pathways through which typical and atypical physiology and metabolic exposures shape fetal neurodevelopmental trajectories. My training to date has provided me with a strong foundation of skills in developmental psychology, infant neurobehavioral assessment, fetal to infant electrophysiology, and biomarkers related to early life experiences. To effectively establish and lead my research program I require additional training on glucose metabolism during pregnancy, advanced deep learning techniques to analyze complex continuous data, and additional mentoring on working with term and preterm neonates in a research setting. By engaging in this protected training time, I will enter my independent stage of research well prepared to lead a research team studying the impact of fluctuations in maternal glucose on fetal behavior and autonomic maturation and their long-term influence on neurodevelopmental trajectories. Research Project: Exposure to gestational diabetes in utero is associated with an increased risk for infant neurodevelopmental delays and psychiatric disorders. While neurodevelopment begins in utero, we lack critical knowledge about sensitive periods and mechanisms that contribute to increased vulnerability in affected offspring. This K99/R00 project aims to fill this gap by examining how maternal glucose fluctuations, assessed via continuous glucose monitoring (CGM), impact the development of fetal behavioral states and autonomic regulation in healthy and hyperglycemic pregnancies, and how these may predict neurodevelopmental risks in infancy. During the K99 phase, we will employ deep learning techniques to analyze how gestational diabetes affects sequential and temporal patterns of fetal heart rate, measured via fetal electrocardiogram (fECG), to evaluate fetal behavior and autonomic maturation (Aim 1). Additionally, we will examine how GDM affects the development of cyclicity and stability of fetal sleep-wake cycles in continuous overnight recordings (Aim 2). The R00 project will investigate how typical and atypical fluctuations in maternal glucose throughout pregnancy shape the development of fetal behavioral states and autonomic control, with neurobehavioral evaluation extending to 6 months after birth (Aim 3). By integrating wearable technologies such as CGM and fECG for continuous, naturalistic assessments, this project offers an unprecedented opportunity to capture the impact of glucose fluctuations on fetal behavior. This approach will lay a foundation for identifying sensitive periods, underlying mechanisms, and early indicators of neurobehavioral trajectories.
