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Meconium metabolomic profiling dysregulation and neonatal brain injury in selective fetal growth restriction. 胎粪代谢组学失调与选择性胎儿生长受限新生儿脑损伤。
IF 2.7 2区 医学 Q1 OBSTETRICS & GYNECOLOGY Pub Date : 2026-02-05 DOI: 10.1186/s12884-026-08727-9
Jingyu Liu, Nana Huang, Youzhen Zhang, Xiya Sun, Hai Jiang, Yixin Li, Yanrong Sun, Jing Yang, Yangyu Zhao

Background: Meconium serves as a valuable biological matrix for characterizing fetal metabolic signatures throughout gestation. Selective fetal growth restriction (sFGR) is associated with adverse neurological outcomes, potentially mediated by underlying metabolic perturbations. However, the specific relationship between dysregulated meconium metabolome and brain injury in sFGR remains poorly understood.

Methods: Untargeted metabolomics analysis was performed on meconium samples from sFGR (n = 20) and monochorionic diamniotic twins with birth weight concordance (MCDA-C, n = 13) to quantify metabolic alterations. Neonatal brain injury was assessed via cranial ultrasonography, and long-term neurodevelopmental outcomes were evaluated at 2-3 years of age using the Ages and Stages Questionnaire-third edition subscale. Univariate analysis, partial least-squares discrimination analysis (PLSDA) and pathway analysis were employed to compare the metabolic profiles across different brain injury categories. Machine learning algorithms and receiver operating characteristic (ROC) curve were utilized to identify potential biomarkers associated with neonatal brain injury. Spearman's-based correlation analysis was employed to correlate metabolites levels with physical development and long-term neurodevelopmental outcomes.

Results: In our study, PLSDA revealed distinct clustering of meconium metabolites profiles in neonates with severe brain injury compared to those with mild brain injury or normal findings. In all sFGR neonates, logistic regression identified two fatty acid metabolism products, 13, 16-docosadienoic acid and nonadecanoic acid, as notably associated with neonatal severe brain injury. Divergent meconium metabolic signatures associated with severe brain injury were observed between the smaller fetus (sFGR-S) and larger fetus (sFGR-L) in sFGR twins. In particular, nicotinamide, hippuric acid, citramalic acid and succinic acid were closely associated with severe brain injury in sFGR-S. Pathway analysis implicated significant dysregulation of the citrate cycle in this subgroup. For sFGR-L, histidine and trans-4-hydroxyproline emerged as best predictive markers for severe brain injury and showed significant correlations with long-term neurodevelopmental outcomes including gross motor and fine motor.

Conclusions: Dysregulated fatty acid metabolites in the meconium of sFGR neonates are associated with severe brain injury. Divergent metabolomic profiles between sFGR-S and sFGR-L revealed distinct pathological mechanisms underlying brain injury. These findings provide novel insights into metabolic mechanisms of brain injury in sFGR and offer potential predictive biomarkers for adverse neurological outcomes.

背景:胎粪作为一种有价值的生物学基质,用于表征整个妊娠期胎儿的代谢特征。选择性胎儿生长限制(sFGR)与不良神经预后相关,可能由潜在的代谢扰动介导。然而,sFGR中胎粪代谢组失调与脑损伤之间的具体关系尚不清楚。方法:对sFGR (n = 20)和出生体重一致的单绒毛膜双胎双胞胎(MCDA-C, n = 13)的胎粪样本进行非靶向代谢组学分析,量化代谢变化。通过颅脑超声检查评估新生儿脑损伤,并在2-3岁时使用年龄和分期问卷-第三版子量表评估长期神经发育结果。采用单因素分析、偏最小二乘判别分析(PLSDA)和途径分析比较不同脑损伤类别的代谢谱。利用机器学习算法和受试者工作特征(ROC)曲线来识别与新生儿脑损伤相关的潜在生物标志物。采用Spearman相关分析将代谢物水平与身体发育和长期神经发育结果联系起来。结果:在我们的研究中,PLSDA显示,与轻度脑损伤或正常的新生儿相比,重度脑损伤新生儿的胎粪代谢谱具有明显的聚类性。在所有sFGR新生儿中,logistic回归发现两种脂肪酸代谢产物,13,16 -二十二烯酸和壬烷酸,与新生儿严重脑损伤显著相关。在sFGR双胞胎中,小胎(sFGR- s)和大胎(sFGR- l)之间观察到与严重脑损伤相关的胎粪代谢特征的差异。其中,烟酰胺、马尿酸、柠檬酸和琥珀酸与sFGR-S重型脑损伤密切相关。通路分析暗示该亚组中存在显著的柠檬酸循环失调。对于sFGR-L,组氨酸和反式-4-羟脯氨酸成为严重脑损伤的最佳预测指标,并与大运动和精细运动等长期神经发育结果显示出显著相关性。结论:sFGR新生儿胎便中脂肪酸代谢物异常与严重脑损伤有关。sFGR-S和sFGR-L之间不同的代谢组学特征揭示了脑损伤的不同病理机制。这些发现为sFGR脑损伤的代谢机制提供了新的见解,并为不良神经预后提供了潜在的预测性生物标志物。
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{"title":"Angiomyofibroblastoma of the vulva in a 29-year-old woman: a case report of a rare entity with successful vaginal delivery.","authors":"Huiling Chen, Lu Wang, Dan Xie, Xiaojuan Lin, Daijuan Chen, Jitong Zhao","doi":"10.1186/s12884-026-08749-3","DOIUrl":"https://doi.org/10.1186/s12884-026-08749-3","url":null,"abstract":"","PeriodicalId":9033,"journal":{"name":"BMC Pregnancy and Childbirth","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2026-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146123708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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{"title":"Metagenomic next-generation sequencing for efficient detection of human parvovirus B19 in amniotic fluid: a case study of diagnosis and prenatal management of fetal infection.","authors":"Ruiyu Ma, Jinling Sun, Jing Zhu, Yi Wu, Yiru Shi, Yunfan Yang, Shan Wang, Xu Han, Shuyuan Li, Li Gao, Xinrong Zhao, Renyi Hua, Yanlin Wang","doi":"10.1186/s12884-026-08743-9","DOIUrl":"https://doi.org/10.1186/s12884-026-08743-9","url":null,"abstract":"","PeriodicalId":9033,"journal":{"name":"BMC Pregnancy and Childbirth","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2026-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146117899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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期刊
BMC Pregnancy and Childbirth
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