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基于出生队列的代谢组学分析新生儿出生体重与胎便代谢物之间的关系

陈遇洁 卢忠华 梁诗佳 张洁

色谱2024,Vol.42Issue(11):1024-1031,8.
色谱2024,Vol.42Issue(11):1024-1031,8.DOI:10.3724/SP.J.1123.2023.12012

基于出生队列的代谢组学分析新生儿出生体重与胎便代谢物之间的关系

Analysis of the relationship between neonatal birth weight and meconium metabolites based on birth cohort metabolomics

陈遇洁 1卢忠华 1梁诗佳 1张洁1

作者信息

  • 1. 厦门大学公共卫生学院,福建厦门 361102
  • 折叠

摘要

Abstract

Neonatal birth weight is a crucial indicator of intrauterine growth and development with important implications for child development and adult health.The birth weight of a new-born is closely linked to the nutrition and health of the mother during pregnancy as well as ge-netic factors.Therefore,assessing the metabolic status of the fetus in utero is greatly significant for understanding the mechanisms responsible for abnormal birth weight.While previous studies often analyzed the impact of maternal metabolism on fetal development using umbilical cord blood from pregnant women,such blood may not accurately reflect the actual intrauterine envi-ronment owing to the barrier function of the placenta;moreover,obtaining biological samples during the fetal period is challenging.Meconium,the first feces excreted by a newborn,pro-vides ideal biological material for studying maternal and infant health.Metabolomics can reveal metabolic changes in living organisms by analyzing small molecules in biological samples;hence studying meconium samples using metabolomics technology is expected to reveal fetal metabolic changes during pregnancy,thereby providing new insights into fetal nutritional in-take,growth,and development,as well as metabolic pathways related to birth weight.To gain a deeper understanding of the metabolic changes associated with birth weight,this study col-lected metabolomic data from the meconium of 484 newborns in the established Xiaogan birth cohort using an untargeted metabolomics technique based on liquid chromatography-high resolution mass spectrometry(LC-HRMS)and analyzed the association between meconium me-tabolites and birth weight.This cohort exhibited incidence rates of low birth weight(<2 500 g)and macrosomia(>4 000 g)of 3.3%and 7.2%,respectively,which were roughly equivalent to the national average.Orthogonal partial least squares discriminant analysis revealed significant differences between the meconium metabolomes of the low birth weight and macrosomic groups when compared to the normal weight group.We discovered significant distinctions be-tween the differential metabolites of newborns of low birth weight and those of normal weight,as well as between macrosomic and normal weight newborns that point to disparate biological pathways.Newborns with low birth weight exhibited significantly lower levels of critical amino acids,such as glutamate and proline,compared to the normal weight group,which may be as-sociated with placental dysfunction and maternal nutritional deficiencies.Conversely,the meco-nium of macrosomic newborns contained significantly elevated levels of hormone metabolites such as estrone that reflected the pathophysiological state associated with maternal metabolic diseases or excessive placental hormone levels.Our study suggests that the metabolomic profile of the meconium reflects the metabolic pathways and regulatory mechanisms at play during fe-tal growth and development,and offers potential metabolic biomarkers and directions for future in-depth research into diseases related to fetal development.However,this study was based solely on the Xiaogan birth cohort,which was limited to specific regions and populations.A multicenter,multiethnic,and multiregional study is expected to help validate the universality of our research findings.

关键词

代谢组学/出生队列/液相色谱-高分辨质谱/新生儿体重/胎便

Key words

metabolomics/birth cohort/liquid chromatography-high resolution mass spec-trometry(LC-HRMS)/neonatal birth weight/meconium

分类

化学化工

引用本文复制引用

陈遇洁,卢忠华,梁诗佳,张洁..基于出生队列的代谢组学分析新生儿出生体重与胎便代谢物之间的关系[J].色谱,2024,42(11):1024-1031,8.

基金项目

国家自然科学基金项目(22076157).National Natural Science Foundation of China(No.22076157). (22076157)

色谱

OA北大核心CSTPCDMEDLINE

1000-8713

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