深度学习增强的ALPS揭示了大脑淋巴功能的遗传和环境因素
Cha Lin1, Hao Wu1, Wenbiao Xian2
1Shenzhen Key Laboratory of Systems Medicine in Inflammatory Diseases, School of Medicine, Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, 518107, China; Department of Medical Informatics and Neurobiology Research Center, School of Medicine, Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, 518107, China.
EBioMedicine
|January 31, 2026
概括
一种新的深度学习方法 (dALPS) 使用DTI-ALPS自动化大脑废物清除评估,揭示影响淋巴功能和中枢神经系统疾病的遗传和生活方式因素.
科学领域:
- 神经科学是一个神经科学.
- 医疗成像医学成像
- 遗传学 是一个遗传学.
背景情况:
- 淋巴系统对于大脑的废物清除和健康至关重要.
- 在周脉空间 (DTI-ALPS) 进行扩散张力成像,评估淋巴功能,但手动分析是主观和繁的.
- 开发了一种深度学习增强的DTI-ALPS (dALPS) 方法,用于自动化,大规模的淋巴功能评估.
研究的目的:
- 开发和验证用于测量DTI-ALPS的自动化深度学习方法 (dALPS).
- 确定淋巴功能的遗传和环境决定因素.
- 探索dALPS,生活方式,临床特征和中枢神经系统疾病之间的关联.
主要方法:
- 实现了一种结合CNN和YOLO的自动化工作流程,用于DTI-ALPS感兴趣地区检测.
- 对超过65,000名参与者计算了dALPS指数;进行了全基因组 (GWAS),全转录组 (TWAS) 和全蛋白质组 (PWAS) 关联研究.
- 评估了与人口统计学,生活方式和临床特征的关联,包括对药理疗法的调解分析.
主要成果:
- 自动化dALPS指数显示出高可靠性 (ICC=0.95) 和可重复性.
- GWAS确定了dALPS的五个重要的遗传位置;TWAS和PWAS突出了潜在的因果基因/蛋白质.
- 较高的健康生活方式指数与改善的dALPS相关;减少的dALPS与中枢神经系统疾病有关. 抗抑郁药与较低的淋巴功能有关.
结论:
- dALPS提供了一个可靠的,自动化生物标志物用于大脑淋巴功能评估.
- 这些发现揭示了淋巴活动的遗传和环境决定因素.
- dALPS显示出临床评估,疾病预测和向治疗的潜力.
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