从呼吸到大脑:NICU呼吸干预和床边大脑信号预测了以后的自闭症风险
Madelyn G Nance1, Winnie R Chang1, Chad Aldridge1
1Department of Neurology, University of Virginia, Charlottesville, VA, United States.
Developmental cognitive neuroscience
|January 23, 2026
概括
这项研究通过使用非侵入性脑活动和呼吸支持措施来确定患有自闭症谱系障碍 (ASD) 高风险的早产婴儿. 通过大脑信号变化和PRISM得分的早期检测可以指导神经发育障碍的及时干预.
科学领域:
- 新生儿神经科学 新生儿神经科学
- 发育儿科 发育儿科
- 计算生物学是一种计算生物学.
背景情况:
- 过早出生的婴儿面临诸如缺氧和炎症等风险,增加对神经发育障碍 (如自闭症谱系障碍 (ASD)) 的敏感性.
- 早期发现患有自闭症风险的婴儿对于及时干预和改善结果至关重要.
- 现有的新生儿风险评估方法存在局限性.
研究的目的:
- 开发和验证用于早期识别患ASD风险的婴儿的非侵入性方法.
- 研究呼吸支负担,大脑信号变化和早产婴儿炎症之间的关系.
- 为了确定这些因素是否可以预测ASD风险.
主要方法:
- 脑电图 (EEG) 用于测量社会和非社会休息状态中的大脑信号变化.
- 收集唾液样本以评估炎症标记物 (细胞因子).
- 计算了一种新的预后呼吸强度评分指标 (PRISM),以量化呼吸支持需求.
主要成果:
- 较高的PRISM得分与非社会静止状态中大脑信号的增加相关.
- 在社会休息状态下,这种关联并不显著,特别是在男性婴儿中.
- 在女性婴儿中,大脑信号和PRISM得分之间的关系可能是由细胞因子介导的.
- 一个结合非社会静止状态大脑信号,性别和PRISM分数的模型预测了ASD风险,准确率为88%.
结论:
- 包括大脑信号和PRISM分数在内的非侵入性测量可以有效地识别患ASD高风险的早产婴儿.
- 这种预测模型,特别是考虑到性别,为医院出院前早期ASD风险评估提供了一个有希望的工具.
- 研究结果强调了炎症和性别特定的大脑活动模式在高风险婴儿中ASD发展中的潜在作用.
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