神经成像内类型揭示了潜在的机制和遗传因素,这些因素有助于四种大脑疾病的进展和发展
Junhao Wen1,2,3,4,5,6,7, Ioanna Skampardoni8, Ye Ella Tian9
1Laboratory of AI and Biomedical Science (LABS), Columbia University, New York, NY, USA. junhao.wen89@gmail.com.
Nature biomedical engineering
|June 6, 2025
概括
从人工智能分析中获得的新维神经成像内类型 (DNE) 可以识别与神经和精神疾病相关的大脑模式. 这些DNE提高了疾病预测,并将大脑结构与遗传学和健康结果联系起来.
科学领域:
- 神经科学是一个神经科学.
- 人工智能的人工智能
- 遗传学 是一个遗传学.
背景情况:
- 人工智能 (AI) 正在推进对疾病异质性的研究.
- 维度神经成像内因型 (DNEs) 是复杂的中间大脑表型.
- DNE为疾病研究提供了一个维度神经解剖学表示.
研究的目的:
- 在一般人口样本中调查九个DNE的存在和实用性.
- 探索DNE与遗传因素和疾病结果的关联.
- 评估DNE对各种系统性疾病和死亡率的预测能力.
主要方法:
- 利用了来自对阿尔茨海默病,自闭症谱系障碍,晚年抑郁症和精神分裂症的协调研究的9个DNE.
- 分析了来自英国生物银行研究的数据.
- 进行了全现象和全基因组的关联研究.
主要成果:
- 确定了与九个DNE相关的31个基因组位置.
- DNE及其多基因风险评分显著提高了对14种系统性疾病类别的预测准确度.
- 发现了对心理健康和中枢神经系统疾病以及死亡率特别强烈的关联.
结论:
- 这九个DNE有效地捕捉了一般人群中与疾病相关的大脑表型.
- DNE提供了大脑结构,遗传学,生活方式和慢性疾病之间的宝贵联系.
- 对于理解疾病异质性和改进预测模型,DNE具有显著的潜力.
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