使用数据驱动方法对精神疾病的分类揭示了不同的皮质和细胞特征
bioRxiv : the preprint server for biology
|September 5, 2025
概括
精神病的亚型表现出明显的脑结构差异. 一种亚型的脑前部和脑顶部区域扩大,而另一种亚型的脑前部,脑前部和脑皮下区域缩小,影响临床症状.
科学领域:
- 神经成像和计算精神病学
- 精神疾病中的大脑结构和功能
- 神经解剖学的细胞相关物
背景情况:
- 大脑结构异常在精神病中很常见,
- 这种异质性使得理解潜在的病理生理学和开发治疗变得复杂.
- 识别不同的神经生物学亚型对于推进精神病研究至关重要.
研究的目的:
- 使用数据驱动的方法在广泛的精神病队伍中识别和描述解剖学衍生子类型.
- 研究这些亚型之间的神经结构差异及其与临床表现的关系.
- 探索精神病中观察到的结构变化的细胞基础.
主要方法:
- 应用相似性网络融合 (SNF) 对精神分裂谱系障碍 (SSD) 和双极性障碍 (BD) 患者的结构神经成像数据.
- 分析皮质表面积和皮质下体积以确定跨诊断亚型.
- 整合基因表达数据以将区域大脑结构与特定细胞类型的丰度联系起来.
主要成果:
- 发现了两种不同类型的精神病,
- 第1亚型表现出额头/胸部表面面积扩大和较大的条纹体积.
- 亚型2显示额/ 表面积减少,皮下体积较小,与更严重的负面症状和认知障碍相关.
- 表面积的减少与第5层谷氨酸性神经元相关,而皮质厚度的减少与第2亚型的质细胞和内部神经元相关.
结论:
- 精神病中的神经结构异质性可以分为不同的跨诊断亚型.
- 与特定的神经元类型相关的区域表面积变化可能作为精神病理生理学的生物标志物.
- 这些发现为精神病的多样化生物学基础提供了新的见解.
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