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Identification and prediction model of placenta-brain axis genes associated with neurodevelopmental delay in moderate and late preterm children

BACKGROUND: Moderate and late preterm (MLPT) birth accounts for the vast majority of preterm births, which is a global public health problem. The association between MLPT and neurobehavioral developmental delays in children and the underlying biological mechanisms need to be further revealed. The “p...

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Autores principales: Zhu, Yumin, Zhang, Yimin, Jin, Yunfan, Jin, Heyue, Huang, Kun, Tong, Juan, Gan, Hong, Rui, Chen, Lv, Jia, Wang, Xianyan, Wang, Qu’nan, Tao, Fangbiao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10464496/
https://www.ncbi.nlm.nih.gov/pubmed/37633927
http://dx.doi.org/10.1186/s12916-023-03023-1
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author Zhu, Yumin
Zhang, Yimin
Jin, Yunfan
Jin, Heyue
Huang, Kun
Tong, Juan
Gan, Hong
Rui, Chen
Lv, Jia
Wang, Xianyan
Wang, Qu’nan
Tao, Fangbiao
author_facet Zhu, Yumin
Zhang, Yimin
Jin, Yunfan
Jin, Heyue
Huang, Kun
Tong, Juan
Gan, Hong
Rui, Chen
Lv, Jia
Wang, Xianyan
Wang, Qu’nan
Tao, Fangbiao
author_sort Zhu, Yumin
collection PubMed
description BACKGROUND: Moderate and late preterm (MLPT) birth accounts for the vast majority of preterm births, which is a global public health problem. The association between MLPT and neurobehavioral developmental delays in children and the underlying biological mechanisms need to be further revealed. The “placenta-brain axis” (PBA) provides a new perspective for gene regulation and risk prediction of neurodevelopmental delays in MLPT children. METHODS: The authors performed multivariate logistic regression models between MLPT and children’s neurodevelopmental outcomes, using data from 129 MLPT infants and 3136 full-term controls from the Ma’anshan Birth Cohort (MABC). Furthermore, the authors identified the abnormally regulated PBA-related genes in MLPT placenta by bioinformatics analysis of RNA-seq data and RT-qPCR verification on independent samples. Finally, the authors established the prediction model of neurodevelopmental delay in children with MLPT using multiple machine learning models. RESULTS: The authors found an increased risk of neurodevelopmental delay in children with MLPT at 6 months, 18 months, and 48 months, especially in boys. Further verification showed that APOE and CST3 genes were significantly correlated with the developmental levels of gross-motor domain, fine-motor domain, and personal social domain in 6-month-old male MLPT children. CONCLUSIONS: These findings suggested that there was a sex-specific association between MLPT and neurodevelopmental delays. Moreover, APOE and CST3 were identified as placental biomarkers. The results provided guidance for the etiology investigation, risk prediction, and early intervention of neurodevelopmental delays in children with MLPT. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12916-023-03023-1.
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spelling pubmed-104644962023-08-30 Identification and prediction model of placenta-brain axis genes associated with neurodevelopmental delay in moderate and late preterm children Zhu, Yumin Zhang, Yimin Jin, Yunfan Jin, Heyue Huang, Kun Tong, Juan Gan, Hong Rui, Chen Lv, Jia Wang, Xianyan Wang, Qu’nan Tao, Fangbiao BMC Med Research Article BACKGROUND: Moderate and late preterm (MLPT) birth accounts for the vast majority of preterm births, which is a global public health problem. The association between MLPT and neurobehavioral developmental delays in children and the underlying biological mechanisms need to be further revealed. The “placenta-brain axis” (PBA) provides a new perspective for gene regulation and risk prediction of neurodevelopmental delays in MLPT children. METHODS: The authors performed multivariate logistic regression models between MLPT and children’s neurodevelopmental outcomes, using data from 129 MLPT infants and 3136 full-term controls from the Ma’anshan Birth Cohort (MABC). Furthermore, the authors identified the abnormally regulated PBA-related genes in MLPT placenta by bioinformatics analysis of RNA-seq data and RT-qPCR verification on independent samples. Finally, the authors established the prediction model of neurodevelopmental delay in children with MLPT using multiple machine learning models. RESULTS: The authors found an increased risk of neurodevelopmental delay in children with MLPT at 6 months, 18 months, and 48 months, especially in boys. Further verification showed that APOE and CST3 genes were significantly correlated with the developmental levels of gross-motor domain, fine-motor domain, and personal social domain in 6-month-old male MLPT children. CONCLUSIONS: These findings suggested that there was a sex-specific association between MLPT and neurodevelopmental delays. Moreover, APOE and CST3 were identified as placental biomarkers. The results provided guidance for the etiology investigation, risk prediction, and early intervention of neurodevelopmental delays in children with MLPT. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12916-023-03023-1. BioMed Central 2023-08-26 /pmc/articles/PMC10464496/ /pubmed/37633927 http://dx.doi.org/10.1186/s12916-023-03023-1 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Zhu, Yumin
Zhang, Yimin
Jin, Yunfan
Jin, Heyue
Huang, Kun
Tong, Juan
Gan, Hong
Rui, Chen
Lv, Jia
Wang, Xianyan
Wang, Qu’nan
Tao, Fangbiao
Identification and prediction model of placenta-brain axis genes associated with neurodevelopmental delay in moderate and late preterm children
title Identification and prediction model of placenta-brain axis genes associated with neurodevelopmental delay in moderate and late preterm children
title_full Identification and prediction model of placenta-brain axis genes associated with neurodevelopmental delay in moderate and late preterm children
title_fullStr Identification and prediction model of placenta-brain axis genes associated with neurodevelopmental delay in moderate and late preterm children
title_full_unstemmed Identification and prediction model of placenta-brain axis genes associated with neurodevelopmental delay in moderate and late preterm children
title_short Identification and prediction model of placenta-brain axis genes associated with neurodevelopmental delay in moderate and late preterm children
title_sort identification and prediction model of placenta-brain axis genes associated with neurodevelopmental delay in moderate and late preterm children
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10464496/
https://www.ncbi.nlm.nih.gov/pubmed/37633927
http://dx.doi.org/10.1186/s12916-023-03023-1
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