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Updated: Jun 29, 2025

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从母亲到孩子的垂直代谢转移:一种可解释的机器学习方法来检测代谢遗传性

Mario Lovrić^1,2,3, David Horner¹, Liang Chen¹

¹Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, 2820 Gentofte, Denmark.

|March 27, 2024

概括

母体代谢物转移到后代,影响生命早期的疾病. 机器学习模型准确地识别了母婴对,突出了异生菌作为关键的转移代谢物.

科学领域:

代谢学代谢学代谢学
围产期健康围产期健康
计算生物学计算生物学

背景情况:

母体代谢物的垂直传播会影响生命早期疾病的表型.
了解这些代谢相互作用对于围产期健康至关重要.
母亲的新陈代谢概况会影响后代的发育.

研究的目的:

使用代谢物配置文件,将真正的母婴二与非二区分开来.
量化垂直代谢物转移的倾向.
为了确定参与母婴代谢交换的关键代谢物.

主要方法:

使用的机器学习模型:随机森林 (RF),光梯度增强机 (LGBM) 和Elasticnet.
分析了母体血 (24周妊娠) 和婴儿血 (6个月).
为了模型的可解释性,采用了 permutation 的重要性和 SHapley 添加式解释 (SHAP).

主要成果:

随机森林模型在识别母婴二中表现出最高的准确性.
异生菌被确定为垂直转移中高度相关的代谢物.
确认了特定代谢物的传输,如 perfluorooctanoic 酸 (PFOA).

结论:

机器学习有效地识别了垂直代谢物转移模式.
母亲对后代的代谢影响是显著的和多方面的.
这种方法提供了新的见解,补充了传统的流行病学研究.

关键词:

在PFOAA中,PFOA是PFOA.这就是为什么PFOS是PFOS.童年的童年童年的童年怀孕怀孕怀孕怀孕怀孕倾向性的倾向性.

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