Fei Huang, Lianlin Zeng, Jianjiao Mou, Yangan Li, Kehui Hu
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Genetic instruments (single nucleotide polymorphisms) for these exposures were retrieved from the IEU Open Genome-Wide Association Study (GWAS) database, and two-sample MR analysis was conducted to infer causality. SD showed a strong positive association with stroke in the crude model [odds ratio (OR) = 2.62, 95% confidence interval (CI): 1.88-3.64, <i>P</i> < 0.001], which remained significant after adjusting for confounders (OR = 1.83, 95% CI: 1.28-2.63, <i>P</i> = 0.007). MR analysis identified nonorganic sleep disorder (OR = 1.025, <i>P</i> = 0.023) and sleep apnea (OR = 1.105, <i>P</i> = 0.002) as significant risk factors for stroke. Conversely, sleepwalking showed a negative association (OR = 0.986, <i>P</i> = 0.001). No evidence of horizontal pleiotropy or heterogeneity was detected, and reverse MR showed no causal effect of stroke on SD. Combining observational and genetic evidence, this study supports a causal relationship between certain SD subtypes and stroke risk. Nonorganic sleep disorders and sleep apnea may increase stroke risk, whereas sleepwalking may have a protective effect.<b>NEW & NOTEWORTHY</b> This study uniquely combines cross-sectional analysis and Mendelian randomization to reveal a causal link between specific sleep disorders and stroke risk. It identifies nonorganic sleep disorders and sleep apnea as independent risk factors while suggesting a protective effect of sleepwalking. These findings offer novel genetic and observational evidence supporting targeted prevention strategies and highlight the need for further investigation into underlying mechanisms and clinical implications.</p>","PeriodicalId":16563,"journal":{"name":"Journal of neurophysiology","volume":" ","pages":"1118-1132"},"PeriodicalIF":2.1000,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Association between sleep disorders and risk of stroke: insights from cross-sectional study and Mendelian randomization.\",\"authors\":\"Fei Huang, Lianlin Zeng, Jianjiao Mou, Yangan Li, Kehui Hu\",\"doi\":\"10.1152/jn.00246.2025\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>This study aimed to systematically evaluate the causal associations between various sleep disorders (SDs) and stroke risk by integrating cross-sectional observational analyses with Mendelian randomization (MR) approaches. 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引用次数: 0
摘要
目的:本研究旨在通过横断面观察分析与孟德尔随机化(MR)方法相结合,系统评估各种睡眠障碍(SD)与卒中风险之间的因果关系。方法:采用全国健康与营养调查(NHANES, 2015-2018)的数据进行横断面分析,包括7,264名参与者,其中270名有中风史。Logistic回归模型评估了SD与卒中风险之间的关系。研究人员检查了八种睡眠障碍:睡眠恐惧、睡眠-觉醒时间表障碍、梦游、睡眠呼吸暂停、非器质性睡眠障碍、失眠、入睡困难和白天打瞌睡。从IEU Open GWAS数据库中检索这些暴露的遗传工具(snp),并进行双样本MR分析以推断因果关系。结果:在粗模型中,SD显示与卒中有很强的正相关(OR = 2.62, 95% CI: 1.88-3.64, P < 0.001),在调整混杂因素后仍然显著(OR = 1.83, 95% CI: 1.28-2.63, P = 0.007)。MR分析发现非器质性睡眠障碍(OR = 1.025, P = 0.023)和睡眠呼吸暂停(OR = 1.105, P = 0.002)是卒中的重要危险因素。相反,梦游呈负相关(OR = 0.986, P = 0.001)。没有发现水平多效性或异质性的证据,反向MR显示卒中对SD没有因果影响。结论:结合观察和遗传证据,本研究支持某些SD亚型与卒中风险之间的因果关系。非器质性睡眠障碍和睡眠呼吸暂停可能会增加中风的风险,而梦游可能有保护作用。
Association between sleep disorders and risk of stroke: insights from cross-sectional study and Mendelian randomization.
This study aimed to systematically evaluate the causal associations between various sleep disorders (SDs) and stroke risk by integrating cross-sectional observational analyses with Mendelian randomization (MR) approaches. A cross-sectional analysis was performed using data from the National Health and Nutrition Examination Survey (2015-2018), including 7,264 participants, 270 of whom had a history of stroke. Logistic regression models assessed the association between SD and stroke risk. Eight sleep disorders were examined: sleep terrors, sleep-wake schedule disorders, sleepwalking, sleep apnea, nonorganic sleep disorder, insomnia, trouble falling asleep, and daytime dozing. Genetic instruments (single nucleotide polymorphisms) for these exposures were retrieved from the IEU Open Genome-Wide Association Study (GWAS) database, and two-sample MR analysis was conducted to infer causality. SD showed a strong positive association with stroke in the crude model [odds ratio (OR) = 2.62, 95% confidence interval (CI): 1.88-3.64, P < 0.001], which remained significant after adjusting for confounders (OR = 1.83, 95% CI: 1.28-2.63, P = 0.007). MR analysis identified nonorganic sleep disorder (OR = 1.025, P = 0.023) and sleep apnea (OR = 1.105, P = 0.002) as significant risk factors for stroke. Conversely, sleepwalking showed a negative association (OR = 0.986, P = 0.001). No evidence of horizontal pleiotropy or heterogeneity was detected, and reverse MR showed no causal effect of stroke on SD. Combining observational and genetic evidence, this study supports a causal relationship between certain SD subtypes and stroke risk. Nonorganic sleep disorders and sleep apnea may increase stroke risk, whereas sleepwalking may have a protective effect.NEW & NOTEWORTHY This study uniquely combines cross-sectional analysis and Mendelian randomization to reveal a causal link between specific sleep disorders and stroke risk. It identifies nonorganic sleep disorders and sleep apnea as independent risk factors while suggesting a protective effect of sleepwalking. These findings offer novel genetic and observational evidence supporting targeted prevention strategies and highlight the need for further investigation into underlying mechanisms and clinical implications.
期刊介绍:
The Journal of Neurophysiology publishes original articles on the function of the nervous system. All levels of function are included, from the membrane and cell to systems and behavior. Experimental approaches include molecular neurobiology, cell culture and slice preparations, membrane physiology, developmental neurobiology, functional neuroanatomy, neurochemistry, neuropharmacology, systems electrophysiology, imaging and mapping techniques, and behavioral analysis. Experimental preparations may be invertebrate or vertebrate species, including humans. Theoretical studies are acceptable if they are tied closely to the interpretation of experimental data and elucidate principles of broad interest.