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Fetal weight growth trajectories and childhood development: A population-based cohort study.
Chen, Xinmei; Liu, Hongxiu; Zhou, Aifen; Jin, Feng; Jing, Chufeng; Li, Yuanyuan; Xia, Wei; Kahn, Linda G; Xie, Ya; Xiang, Xingliang; Cao, Shuting; Zhang, Wenxin; Mahai, Gaga; Cao, Zhongqiang; Xiao, Han; Xiong, Chao; Li, Wei; Li, Hanzeng; Xu, Shunqing.
Afiliação
  • Chen X; 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.
  • Liu H; 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.
  • Zhou A; Wuhan Medical & Healthcare Center for Women and Children, Wuhan 430015, China.
  • Jin F; Shunyi Women's and Children's Hospital of Beijing Children's Hospital, Beijing 101320, China.
  • Jing C; Wuxi Maternal and Child Health Hospital, Wuxi 214001, China.
  • Li Y; 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.
  • Xia W; 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.
  • Kahn LG; Department of Pediatrics, New York University Grossman School of Medicine, New York, 10016, USA.
  • Xie Y; 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.
  • Xiang X; School of Environmental Science and Engineering, Hainan University, Haikou 570208, China.
  • Cao S; 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.
  • Zhang W; 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.
  • Mahai G; School of Environmental Science and Engineering, Hainan University, Haikou 570208, China.
  • Cao Z; Wuhan Medical & Healthcare Center for Women and Children, Wuhan 430015, China.
  • Xiao H; Wuhan Medical & Healthcare Center for Women and Children, Wuhan 430015, China.
  • Xiong C; Wuhan Medical & Healthcare Center for Women and Children, Wuhan 430015, China.
  • Li W; Beijing Children's Hospital, Capital Medical University, Beijing 100045, China.
  • Li H; School of Environmental Science and Engineering, Hainan University, Haikou 570208, China.
  • Xu S; 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; School of Environmental S
Sci Bull (Beijing) ; 2024 Aug 24.
Article em En | MEDLINE | ID: mdl-39261129
ABSTRACT
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sci Bull (Beijing) Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China País de publicação: Holanda

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sci Bull (Beijing) Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China País de publicação: Holanda