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使用脑MRI,肠道微生物组和血液数据来预测精神分裂症的生物年龄

Rui Han¹, Wei Wang¹, Jianhao Liao¹

¹School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou 511442, China.

Brain research bulletin

|April 29, 2025

概括

整合多种生物数据,包括脑MRI,微生物组和血液,可以提高生物年龄预测的准确性. 这种方法揭示了精神分裂症患者的显著生物年龄差距,与认知衰退和症状严重程度相关.

科学领域:

神经科学是一个神经科学.
遗传学是一个遗传学.
计算生物学计算生物学

背景情况:

生物年龄预测对于了解衰老和疾病至关重要.
单个数据源对复杂的病理过程提供了有限的洞察力.
整合多模生物数据可能会提高预测准确度.

研究的目的:

通过使用集成的多生物学数据,评估用于生物年龄预测的机器学习模型.
将多生物学数据模型与单个数据模型 (脑MRI) 的性能进行比较.
研究生物年龄差距 (BAG) 作为精神分裂症生物标志物的实用性.

主要方法:

利用机器学习模型进行生物年龄预测.
整合了来自大脑MRI,肠道微生物组和血液数据的功能.
分析了精神分裂症患者的特征解释性和与临床评分 (MCCB,PANSS) 相关联的BAG.

主要成果:

多生物数据模型的预测准确性高于仅使用脑MRI模型.
额叶,叶和叶是生物年龄的关键预测因素.
与对照组相比,精神分裂症患者的生物学年龄差距 (BAG) 显著增加.
在精神分裂症中,BAG与认知功能 (MCCB) 有负相关性,与症状严重程度 (PANSS) 有正相关性.

结论:

综合的多生物学数据增强了生物年龄的预测.
在精神分裂症等神经精神疾病中,BAG显示出作为认知衰退和症状严重性的生物标志物的潜力.

关键词:

生物年龄预测预测血液血液血液血液大脑MRI 脑部MRI 脑部我们的肠道微生物组.机器学习是机器学习.精神分裂症是一种精神分裂症.

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