通过数据驱动的方法揭示精神分裂症的多个生物亚型
Yuran Wang1, Shixuan Feng2, Yuanyuan Huang2,3
1School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou, 511442, China.
Journal of translational medicine
|May 2, 2025
概括
用脑成像和肠道微生物群数据确定了精神分裂症 (SZ) 亚型. 这些独特的生物亚型与特定的临床症状和认知表现相关,为个性化治疗铺平了道路.
科学领域:
- 神经科学是一个神经科学.
- 微生物组研究 微生物组研究
- 精神病学是一个精神病学.
背景情况:
- 精神分裂症 (SZ) 研究一直专注于脑成像亚型.
- 在SZ中,多种生物数据类型之间的异质性在很大程度上仍未被探索.
研究的目的:
- 通过整合脑成像和肠道微生物群数据来调查精神分裂症的异质性.
- 通过数据驱动的方法来识别精神分裂症的不同生物亚型.
主要方法:
- 利用数据驱动模型对脑成像和肠道微生物群数据进行分类.
- 雇佣的点产品融合用于大脑肠道数据集成.
- 与临床症状和认知表现相关的已识别的亚型.
主要成果:
- 确定了与负面和积极症状相关的独立大脑亚型 (结构性和功能性改变).
- 发现了三种与症状相关的肠道微生物群亚型 (科林塞拉,普雷沃特拉,链球菌占主导地位).
- 揭示了与注意力缺陷和积极症状相关的脑肠互动亚型.
- 发现大脑和大脑-肠子类型与临床症状密切相关,而肠子类型提供了更多的认知生物标志物.
结论:
- 证明了在精神分裂症中识别多个不同的生物亚型的潜力.
- 突出了每个亚型不同的生物标志物的实用性.
- 建议个性化和精确的精神分裂症治疗策略的未来方向.
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