Wang Qingyi, Zheng Shiyu, Ye Wujie, Zhu Lu, Huang Yan, Wang Zhaoqin, Liu Chengyong, Sun Fangyuan, Luo Zhihui, Li Guona, Wu Luyi, Wu Wenzhong, Wu Huangan
Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China; Shanghai Research Institute of Acupuncture and Meridian, Shanghai 200030, China.
Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing 210029, China.
J Affect Disord. 2025 Oct 15;387:119439. doi: 10.1016/j.jad.2025.119439. Epub 2025 May 18.
Sleep disorders are a widespread public health issue globally. Investigating the causal relationship between resting-state brain functional abnormalities and sleep disorders can provide scientific evidence for precision medicine interventions.
We screened single nucleotide polymorphisms (SNPs) associated with rs-fMRI phenotype as instrumental variables Using bidirectional two-sample Mendelian randomization (MR), mediation MR, and multivariate MR based on Bayesian methods, the study tested the causal relationship between genetically predicted rs-fMRI and nine common sleep disorders.
The main inverse variance weighted (IVW) analysis identified four resting state functional magnetic resonance imaging (rs-fMRI) phenotypes that are causally associated with the risk of sleep disorders. For example, increased amplitude in nodes of the parietal, precuneus, occipital, temporal, and cerebellum regions, as well as the default mode network (DMN), central executive network (CEN) and attention network (AN) was associated with an increased risk of sleep apnoea. Enhanced neural activity in the calcarine or lingual and cerebellum regions and increased functional connectivity with the visual and subcortical-cerebellum networks was associated with a reduced risk of snoring. The mediation MR analysis shows that, body mass index (BMI) plays a significant mediating role in the risk of sleep apnoea by modulating the amplitude of nodes in the parietal, temporal, and cerebellum regions, as well as the connectivity changes in the DMN, CEN, and AN.
This study identified three rs-fMRI phenotypes linked to increased sleep apnoea risk and one associated with decreased snoring risk, providing an important target for the treatment of sleep disorders at the level of brain functional networks.
睡眠障碍是全球普遍存在的公共卫生问题。研究静息态脑功能异常与睡眠障碍之间的因果关系可为精准医学干预提供科学依据。
我们筛选与静息态功能磁共振成像（rs-fMRI）表型相关的单核苷酸多态性（SNP）作为工具变量，采用双向双样本孟德尔随机化（MR）、中介MR和基于贝叶斯方法的多变量MR，该研究测试了基因预测的rs-fMRI与九种常见睡眠障碍之间的因果关系。
主要的逆方差加权（IVW）分析确定了四种与睡眠障碍风险有因果关系的静息态功能磁共振成像（rs-fMRI）表型。例如，顶叶、楔前叶、枕叶、颞叶和小脑区域以及默认模式网络（DMN）、中央执行网络（CEN）和注意力网络（AN）节点的振幅增加与睡眠呼吸暂停风险增加相关。距状裂或舌回及小脑区域的神经活动增强以及与视觉和皮层下-小脑网络的功能连接增加与打鼾风险降低相关。中介MR分析表明，体重指数（BMI）通过调节顶叶、颞叶和小脑区域节点的振幅以及DMN、CEN和AN的连接变化，在睡眠呼吸暂停风险中起显著中介作用。
本研究确定了三种与睡眠呼吸暂停风险增加相关的rs-fMRI表型和一种与打鼾风险降低相关的表型，为在脑功能网络水平治疗睡眠障碍提供了重要靶点。
