精神分裂症中大脑形态的疾病进展模式:治疗耐药性的更先进阶段
Daichi Sone1,2, Alexandra Young3, Shunichiro Shinagawa1
1Department of Psychiatry, Jikei University School of Medicine, Tokyo, Japan.
Schizophrenia bulletin
|November 26, 2023
概括
精神分裂症的大脑变化显示有三种亚型. 治疗耐药性与晚期相关,这表明这种复杂的神经疾病的潜在新生物标志物.
科学领域:
- 神经成像是一种神经成像.
- 机器学习 机器学习
- 精神病学是一个精神病学.
背景情况:
- 精神分裂症表现出显著的异质性和疾病进展的潜力.
- 识别神经生物学亚型和进展模式可能会揭示新的生物标志物.
- 机器学习提供数据驱动的方法来分析复杂的大脑形态数据.
研究的目的:
- 使用机器学习识别精神分裂症中大脑形态变化的进展模式.
- 调查这些进展模式与精神分裂症治疗耐药性之间的关联.
- 探索精神分裂症亚型和进展的潜在新生物标志物.
主要方法:
- 使用了177名精神分裂症患者的横截面,多中心研究设计.
- 采用3D T1权重磁共振成像 (MRI) 来评估大脑形态.
- 应用了未经监督的机器学习算法子类型和阶段推理 (SuStaIn) 来识别进展模式.
主要成果:
- 确定了三种不同的大脑形态进展的亚型:下皮层体积减少 (SC),球体缩和皮层稀释 (GP-CX) 和纯皮层稀释 (纯CX).
- 与治疗反应的病例相比,治疗耐药的精神分裂症病例表现出明显更先进的进展阶段 (P=.001).
- GP-CX亚型呈现出比纯CX亚型更早的进展阶段 (P=.009).
结论:
- 精神分裂症中的大脑形态进展可以分为三个不同的亚型.
- 精神分裂症的治疗阻力与大脑形态进展的更先进阶段有关.
- 这些发现表明精神分裂症的潜在新生物标志物,特别是与治疗耐药性有关.
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