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口腔微生物组可以预测低出生体重婴儿的分娩吗?

Pei Liu¹, Weiye Wen², Ka Fung Yu³

¹Applied Oral Sciences & Community Dental Care, Faculty of Dentistry, The University of Hong Kong, Hong Kong SAR, China.

Journal of dentistry

|April 28, 2024

概括

使用口腔微生物群的机器学习模型成功预测了中国孕妇的低出生体重 (LBW). 唾液中的特定细菌物种可以作为LBW风险的生物标志物.

科学领域:

微生物学微生物学
基因组学就是基因组学.
机器学习机器学习

背景情况:

口腔微生物组在怀孕结果中起着重要作用.
识别与低出生体重 (LBW) 相关的特定口腔微生物群对于早期干预至关重要.

研究的目的:

为了确定与中国孕妇的LBW相关的口腔微生物群因素.
使用口腔微生物组数据开发基于机器学习的LBW预测模型.

主要方法:

一项嵌套病例对照研究涉及580名孕妇 (23例LBW,23例对照).
用16S rRNA基因测序分析唾液样本,以分析口腔微生物组.
机器学习算法被用来构建基于已识别的微生物生物标志物的预测模型.

主要成果:

在LBW组中观察到Streptococcus的过度代表性和Sacharibacteria_TM7的不足代表性.
十种口腔微生物物种,包括链球菌和机会性病原体,被确定为LBW生物标志物.
机器学习模型在预测LBW方面实现了82%的准确性,91%的灵敏性和73%的特异性 (AUC-ROC 0.89).

结论:

使用口腔微生物组数据的机器学习模型显示了预测LBW的巨大潜力.
特定的口腔细菌,即使没有明显的口腔疾病,也可以作为不利妊娠结果的指标.

关键词:

16s 核糖体RNA测序的16s 核糖体RNA测序负面的怀孕结果.低出生体重低出生体重机器学习是机器学习.微生物标记物的微生物标记物.口腔微生物组是口腔的微生物组.这是唾液的唾液.

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