Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
Wuhan Medical & Healthcare Center for Women and Children, Wuhan 430015, China.
Sci Bull (Beijing). 2024 Nov 15;69(21):3404-3414. doi: 10.1016/j.scib.2024.04.077. Epub 2024 Aug 24.
This study aimed to investigate whether fetal growth trajectories (FGTs) could predict early childhood development, indicate intrauterine metabolic changes, and explore potential optimal and suboptimal FGTs. FGTs were developed by using an unsupervised machine-learning approach. Children's neurodevelopment, anthropometry, and respiratory outcomes in the first 6 years of life were assessed at different ages. In a subgroup of participants, we conducted a metabolomics analysis of cord blood to reveal the metabolic features of FGTs. We identified 6 FGTs: early decelerating, early decelerating with late catch-up growth, early accelerating, early accelerating with late medium growth, late decelerating, and late accelerating. The early accelerating with late medium growth pattern might be the optimal FGT due to its associations with better psychomotor development, mental development, intelligence quotient, and lung function and a lower risk of behaviour and respiratory problems. Compared with the optimal FGT, early decelerating and late decelerating FGTs were associated with poor neurodevelopment and lung function, while early accelerating FGT was associated with more severe autistic symptoms, poor lung function, and increased risks of overweight/obesity. Metabolic alterations were enriched in amino acid metabolism for early decelerating and late decelerating FGTs, whereas altered metabolites were enriched in lipid metabolism for early accelerating FGT. These findings suggest that FGTs are predictors of early life development and may indicate intrauterine adaptive metabolism. The discovery of optimal and suboptimal FGTs provides potential clues for the early identification and intervention of fetal origin dysplasia or disease, but further research on related mechanisms is still needed.
本研究旨在探讨胎儿生长轨迹(FGT)是否能够预测儿童早期发育,提示宫内代谢变化,并探索潜在的最佳和次佳 FGT。使用无监督机器学习方法构建 FGT。在生命的头 6 年的不同年龄阶段评估儿童的神经发育、人体测量学和呼吸结局。在一部分参与者中,我们对脐血进行代谢组学分析,以揭示 FGT 的代谢特征。我们确定了 6 种 FGT:早期减速、早期减速伴后期追赶生长、早期加速、早期加速伴后期中等生长、晚期减速和晚期加速。由于与更好的精神运动发育、心理发育、智商和肺功能相关,且行为和呼吸问题的风险较低,早期加速伴后期中等生长模式可能是最佳的 FGT。与最佳 FGT 相比,早期减速和晚期减速 FGT 与神经发育和肺功能不良相关,而早期加速 FGT 与更严重的自闭症症状、肺功能不良和超重/肥胖风险增加相关。早期减速和晚期减速 FGT 中氨基酸代谢的代谢改变被富集,而早期加速 FGT 中脂质代谢的代谢改变被富集。这些发现表明 FGT 是生命早期发育的预测因子,可能提示宫内适应性代谢。最佳和次佳 FGT 的发现为胎儿起源发育不良或疾病的早期识别和干预提供了潜在线索,但仍需要进一步研究相关机制。