Purpose: Sleep deprivation (SD), a common sleep disease in clinic, has certain risks, and its pathogenesis is still unclear. This study aimed to identify ferroptosis-cuproptosis-related genes (FCRGs) associated with SD through bioinformatics and machine learning, thus elucidating their biological significance and clinical value.
Methods: SD-DEGs were obtained from GEO. We intersected key WGCNA module genes of DE-FCRGs with SD-DEGs to obtain SD-DE-FCRGs. GO and KEGG analyses were performed. Machine learning was used to screen SD-DE-FCRGs, and filtered genes were intersected to obtain SD characteristic genes. ROC curves were used to evaluate the accuracy of SD characteristic genes. CIBERSORT was used to analyze the correlation between SD-DE-FCRGs and immune cells. We constructed a ceRNA network of SD-DE-FCRGs and used DGIbd to predict gene drug targets.
Results: The 156 DEGs were identified from GSE98566. Five SD-DE-FCRGs from DE- FCRGs and SD-DEGs were analyzed via WGCNA, and enrichment analysis involved mainly ribosome regulation, mitochondrial pathways, and neurodegenerative diseases. Machine learning was used to obtain Four SD-DE-FCRGs (IKZF1, JCHAIN, MGST3, and UQCR11), and these gene analyses accurately evaluated the distribution model (AUC=0.793). Immune infiltration revealed that SD hub genes were correlated with most immune cells. Unsupervised cluster analysis revealed significant differential expression of immune-related genes between two subtypes. GSVA and GSEA revealed that enriched biological functions included oxidative phosphorylation, ribonucleic acid, metabolic diseases, activation of oxidative phosphorylation, and other pathways. Four SD-DE-FCRGs associated with 29 miRNAs were identified via the construction of a ceRNA network. The important target lenalidomide of IKZF1 was predicted.
Conclusion: We first used bioinformatics and machine learning to screen four SD-DE-FCRGs. These genes may affect the involvement of infiltrating immune cells in pathogenesis of SD by regulating FCRGs. We predicted that lenalidomide may target IKZF1 from SD-DE-FCRGs.
{"title":"Using Bioinformatics and Machine Learning to Predict the Genetic Characteristics of Ferroptosis-Cuproptosis-Related Genes Associated with Sleep Deprivation.","authors":"Liang Wang, Shuo Wang, Chujiao Tian, Tao Zou, Yunshan Zhao, Shaodan Li, Minghui Yang, Ningli Chai","doi":"10.2147/NSS.S473022","DOIUrl":"https://doi.org/10.2147/NSS.S473022","url":null,"abstract":"<p><strong>Purpose: </strong>Sleep deprivation (SD), a common sleep disease in clinic, has certain risks, and its pathogenesis is still unclear. This study aimed to identify ferroptosis-cuproptosis-related genes (FCRGs) associated with SD through bioinformatics and machine learning, thus elucidating their biological significance and clinical value.</p><p><strong>Methods: </strong>SD-DEGs were obtained from GEO. We intersected key WGCNA module genes of DE-FCRGs with SD-DEGs to obtain SD-DE-FCRGs. GO and KEGG analyses were performed. Machine learning was used to screen SD-DE-FCRGs, and filtered genes were intersected to obtain SD characteristic genes. ROC curves were used to evaluate the accuracy of SD characteristic genes. CIBERSORT was used to analyze the correlation between SD-DE-FCRGs and immune cells. We constructed a ceRNA network of SD-DE-FCRGs and used DGIbd to predict gene drug targets.</p><p><strong>Results: </strong>The 156 DEGs were identified from GSE98566. Five SD-DE-FCRGs from DE- FCRGs and SD-DEGs were analyzed via WGCNA, and enrichment analysis involved mainly ribosome regulation, mitochondrial pathways, and neurodegenerative diseases. Machine learning was used to obtain Four SD-DE-FCRGs (IKZF1, JCHAIN, MGST3, and UQCR11), and these gene analyses accurately evaluated the distribution model (AUC=0.793). Immune infiltration revealed that SD hub genes were correlated with most immune cells. Unsupervised cluster analysis revealed significant differential expression of immune-related genes between two subtypes. GSVA and GSEA revealed that enriched biological functions included oxidative phosphorylation, ribonucleic acid, metabolic diseases, activation of oxidative phosphorylation, and other pathways. Four SD-DE-FCRGs associated with 29 miRNAs were identified via the construction of a ceRNA network. The important target lenalidomide of IKZF1 was predicted.</p><p><strong>Conclusion: </strong>We first used bioinformatics and machine learning to screen four SD-DE-FCRGs. These genes may affect the involvement of infiltrating immune cells in pathogenesis of SD by regulating FCRGs. We predicted that lenalidomide may target IKZF1 from SD-DE-FCRGs.</p>","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":"16 ","pages":"1497-1513"},"PeriodicalIF":3.0,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11438466/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142350440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background: Phase-amplitude coupling (PAC) between the phase of low-frequency signals and the amplitude of high-frequency activities plays many physiological roles and is involved in the pathological processed of various neurological disorders. However, how low-frequency and high-frequency neural oscillations or information synchronization activities change under chronic central hypoxia in OSA patients and whether these changes are closely associated with OSA remains largely unexplored. This study arm to elucidate the long-term consequences of OSA-related oxygen deprivation on central nervous system function.
Methods: : We screened 521 patients who were clinically suspected of having OSA at our neurology and sleep centers. Through polysomnography (PSG) and other clinical examinations, 103 patients were ultimately included in the study and classified into mild, moderate, and severe OSA groups based on the severity of hypoxia determined by PSG. We utilized the phase-amplitude coupling (PAC) method to analyze the modulation index (MI) trends between different frequency bands during NREM (N1/N2/N3), REM, and wakefulness stages in OSA patients with varying severity levels. We also examined the correlation between the MI index and OSA hypoxia indices.
Results: Apart from reduced N2 sleep duration and increased microarousal index, the sleep architecture remained largely unchanged among OSA patients with varying severity levels. Compared to the mild OSA group, patients with moderate and severe OSA exhibited higher MI values of PAC in the low-frequency theta phase and high-frequency beta amplitude in the frontal and occipital regions during N1 sleep and wakefulness. No significant differences in the MI of phase-amplitude coupling were observed during N2/3 and REM sleep. Moreover, the MI of phase-amplitude coupling in theta and beta bands positively correlated with hypoxia-related indices, including the apnea-hypopnea index (AHI) and oxygenation desaturation index (ODI), and the percentage of oxygen saturation below 90% (SaO2<90%).
Conclusion: OSA patients demonstrated increased MI values of theta phase and beta amplitude in the frontal and occipital regions during N1 sleep and wakefulness. This suggests that cortical coupling is prevalent and exhibits sleep-stage-specific patterns in OSA. Theta-beta PAC during N1 and wakefulness was positively correlated with hypoxia-related indices, suggesting a potential relationship between these neural oscillations and OSA severity. The present study provides new insights into the relationship between neural oscillations and respiratory hypoxia in OSA patients.
背景：低频信号的相位与高频活动的振幅之间的相位-振幅耦合（PAC）发挥着许多生理作用，并参与各种神经系统疾病的病理过程。然而，在OSA患者长期中枢缺氧的情况下，低频和高频神经振荡或信息同步活动是如何变化的，这些变化是否与OSA密切相关，这些问题在很大程度上仍未得到探讨。本研究旨在阐明 OSA 相关缺氧对中枢神经系统功能的长期影响：我们在神经科和睡眠中心筛查了 521 名临床疑似 OSA 患者。通过多导睡眠图（PSG）和其他临床检查，最终将 103 名患者纳入研究，并根据 PSG 确定的缺氧严重程度将其分为轻度、中度和重度 OSA 组。我们利用相位-振幅耦合（PAC）方法分析了不同严重程度的 OSA 患者在 NREM（N1/N2/N3）、REM 和清醒阶段不同频段之间的调制指数（MI）趋势。我们还研究了MI指数与OSA缺氧指数之间的相关性：结果：除了 N2 睡眠时间缩短和微唤醒指数增加外，不同严重程度的 OSA 患者的睡眠结构基本保持不变。与轻度OSA组相比，中度和重度OSA患者在N1睡眠和觉醒时，额叶和枕叶区低频θ相位的PAC和高频β振幅的MI值更高。在 N2/3 和快速动眼期睡眠中，相位-振幅耦合的 MI 值没有明显差异。此外，θ和β波段的相位-振幅耦合MI与缺氧相关指数呈正相关，包括呼吸暂停-低通气指数（AHI）和血氧饱和度指数（ODI），以及血氧饱和度低于90%的百分比（SaO2）：OSA患者在N1睡眠和清醒时，额叶和枕叶区域的θ相位和β振幅的MI值均有所增加。这表明皮质耦合在 OSA 中很普遍，并表现出睡眠阶段的特异性模式。N1 和清醒时的 Theta-beta PAC 与缺氧相关指数呈正相关，表明这些神经振荡与 OSA 严重程度之间存在潜在关系。本研究为了解 OSA 患者的神经振荡与呼吸缺氧之间的关系提供了新的视角。
{"title":"Phase-Amplitude Coupling in Theta and Beta Bands: A Potential Electrophysiological Marker for Obstructive Sleep Apnea.","authors":"Chan Zhang, Yanhui Wang, Mengjie Li, Pengpeng Niu, Shuo Li, Zhuopeng Hu, Changhe Shi, Yusheng Li","doi":"10.2147/NSS.S470617","DOIUrl":"https://doi.org/10.2147/NSS.S470617","url":null,"abstract":"<p><strong>Background: </strong>Phase-amplitude coupling (PAC) between the phase of low-frequency signals and the amplitude of high-frequency activities plays many physiological roles and is involved in the pathological processed of various neurological disorders. However, how low-frequency and high-frequency neural oscillations or information synchronization activities change under chronic central hypoxia in OSA patients and whether these changes are closely associated with OSA remains largely unexplored. This study arm to elucidate the long-term consequences of OSA-related oxygen deprivation on central nervous system function.</p><p><strong>Methods: </strong>: We screened 521 patients who were clinically suspected of having OSA at our neurology and sleep centers. Through polysomnography (PSG) and other clinical examinations, 103 patients were ultimately included in the study and classified into mild, moderate, and severe OSA groups based on the severity of hypoxia determined by PSG. We utilized the phase-amplitude coupling (PAC) method to analyze the modulation index (MI) trends between different frequency bands during NREM (N1/N2/N3), REM, and wakefulness stages in OSA patients with varying severity levels. We also examined the correlation between the MI index and OSA hypoxia indices.</p><p><strong>Results: </strong>Apart from reduced N2 sleep duration and increased microarousal index, the sleep architecture remained largely unchanged among OSA patients with varying severity levels. Compared to the mild OSA group, patients with moderate and severe OSA exhibited higher MI values of PAC in the low-frequency theta phase and high-frequency beta amplitude in the frontal and occipital regions during N1 sleep and wakefulness. No significant differences in the MI of phase-amplitude coupling were observed during N2/3 and REM sleep. Moreover, the MI of phase-amplitude coupling in theta and beta bands positively correlated with hypoxia-related indices, including the apnea-hypopnea index (AHI) and oxygenation desaturation index (ODI), and the percentage of oxygen saturation below 90% (SaO2<90%).</p><p><strong>Conclusion: </strong>OSA patients demonstrated increased MI values of theta phase and beta amplitude in the frontal and occipital regions during N1 sleep and wakefulness. This suggests that cortical coupling is prevalent and exhibits sleep-stage-specific patterns in OSA. Theta-beta PAC during N1 and wakefulness was positively correlated with hypoxia-related indices, suggesting a potential relationship between these neural oscillations and OSA severity. The present study provides new insights into the relationship between neural oscillations and respiratory hypoxia in OSA patients.</p>","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":"16 ","pages":"1469-1482"},"PeriodicalIF":3.0,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11423842/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142350439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Objective: Depression is a common psychiatric issue among patients with narcolepsy type 1 (NT1). Effective management requires accurate screening and prediction of depression in NT1 patients. This study aims to identify relevant factors for predicting depression in Chinese NT1 patients using machine learning (ML) approaches. Methods: A total of 203 drug-free NT1 patients (aged 5– 61), diagnosed based on the ICSD-3 criteria, were consecutively recruited from the Sleep Medicine Center at Peking University People’s Hospital between September 2019 and April 2023. Depression, daytime sleepiness, and impulsivity were assessed using the Center for Epidemiologic Studies Depression Scale for Children (CES-DC) or the Self-Rating Depression Scale (SDS), the Epworth Sleepiness Scale for adult or children and adolescents (ESS or ESS-CHAD), and the Barratt Impulse Scale (BIS-11). Demographic characteristics and objective sleep parameters were also analyzed. Three ML models-Logistic Regression (LR), Random Forest (RF), and Support Vector Machine (SVM)-were used to predict depression. Model performance was evaluated using receiver operating curve (AUC), accuracy, precision, recall, F1 score, and decision curve analysis (DCA). Results: The LR model identified hallucinations (OR 2.21, 95% CI 1.01– 4.90, p = 0.048) and motor impulsivity (OR 1.10, 95% CI 1.02– 1.18, p = 0.015) as predictors of depression. Among the ML models, SVM showed the best performance with an AUC of 0.653, accuracy of 0.659, sensitivity of 0.727, and F1 score of 0.696, reflecting its effectiveness in integrating sleep-related and psychosocial factors. Conclusion: This study highlights the potential of ML models for predicting depression in NT1 patients. The SVM model shows promise in identifying patients at high risk of depression, offering a foundation for developing a data-driven, personalized decision-making tool. Further research should validate these findings in diverse populations and include additional psychological variables to enhance model accuracy.
Keywords: narcolepsy type 1, depression, machine learning, support vector machine
目的：抑郁症是 1 型嗜睡症（NT1）患者中常见的精神问题。有效的治疗需要对 NT1 患者进行准确的抑郁筛查和预测。本研究旨在利用机器学习（ML）方法确定预测中国 NT1 患者抑郁的相关因素：在2019年9月至2023年4月期间，从北京大学人民医院睡眠医学中心连续招募了203名根据ICSD-3标准确诊的无药NT1患者（5-61岁）。采用流行病学研究中心儿童抑郁量表（CES-DC）或抑郁自评量表（SDS）、成人或儿童青少年埃普沃思嗜睡量表（ESS或ESS-CHAD）和巴拉特冲动量表（BIS-11）评估抑郁、白天嗜睡和冲动。此外，还分析了人口统计学特征和客观睡眠参数。三种 ML 模型--逻辑回归（LR）、随机森林（RF）和支持向量机（SVM）--用于预测抑郁症。使用接收器工作曲线（AUC）、准确度、精确度、召回率、F1得分和决策曲线分析（DCA）对模型性能进行了评估：LR模型发现幻觉（OR 2.21，95% CI 1.01-4.90，p = 0.048）和运动冲动（OR 1.10，95% CI 1.02-1.18，p = 0.015）是预测抑郁的因素。在ML模型中，SVM表现最佳，其AUC为0.653，准确度为0.659，灵敏度为0.727，F1得分为0.696，反映了其在整合睡眠相关因素和心理社会因素方面的有效性：本研究强调了 ML 模型在预测 NT1 患者抑郁方面的潜力。SVM 模型在识别抑郁症高风险患者方面显示出了前景，为开发数据驱动的个性化决策工具奠定了基础。进一步的研究应在不同人群中验证这些发现，并纳入更多心理变量以提高模型的准确性。 关键词：1型嗜睡症；抑郁症；机器学习；支持向量机
{"title":"Predicting Depression Among Chinese Patients with Narcolepsy Type 1: A Machine-Learning Approach","authors":"Mengmeng Wang, Huanhuan Wang, Zhaoyan Feng, Shuai Wu, Bei Li, Fang Han, Fulong Xiao","doi":"10.2147/nss.s468748","DOIUrl":"https://doi.org/10.2147/nss.s468748","url":null,"abstract":"<strong>Objective:</strong> Depression is a common psychiatric issue among patients with narcolepsy type 1 (NT1). Effective management requires accurate screening and prediction of depression in NT1 patients. This study aims to identify relevant factors for predicting depression in Chinese NT1 patients using machine learning (ML) approaches.<br/><strong>Methods:</strong> A total of 203 drug-free NT1 patients (aged 5– 61), diagnosed based on the ICSD-3 criteria, were consecutively recruited from the Sleep Medicine Center at Peking University People’s Hospital between September 2019 and April 2023. Depression, daytime sleepiness, and impulsivity were assessed using the Center for Epidemiologic Studies Depression Scale for Children (CES-DC) or the Self-Rating Depression Scale (SDS), the Epworth Sleepiness Scale for adult or children and adolescents (ESS or ESS-CHAD), and the Barratt Impulse Scale (BIS-11). Demographic characteristics and objective sleep parameters were also analyzed. Three ML models-Logistic Regression (LR), Random Forest (RF), and Support Vector Machine (SVM)-were used to predict depression. Model performance was evaluated using receiver operating curve (AUC), accuracy, precision, recall, F1 score, and decision curve analysis (DCA).<br/><strong>Results:</strong> The LR model identified hallucinations (OR 2.21, 95% CI 1.01– 4.90, <em>p</em> = 0.048) and motor impulsivity (OR 1.10, 95% CI 1.02– 1.18, <em>p</em> = 0.015) as predictors of depression. Among the ML models, SVM showed the best performance with an AUC of 0.653, accuracy of 0.659, sensitivity of 0.727, and F1 score of 0.696, reflecting its effectiveness in integrating sleep-related and psychosocial factors.<br/><strong>Conclusion:</strong> This study highlights the potential of ML models for predicting depression in NT1 patients. The SVM model shows promise in identifying patients at high risk of depression, offering a foundation for developing a data-driven, personalized decision-making tool. Further research should validate these findings in diverse populations and include additional psychological variables to enhance model accuracy.<br/><br/><strong>Keywords:</strong> narcolepsy type 1, depression, machine learning, support vector machine<br/>","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":"187 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142252543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xin Guo, Ying Xu, Yao Meng, Hao Lian, Jingwen He, Ruike Zhang, Jingzhou Xu, Hao Wang, Shuyu Xu, Wenpeng Cai, Lei Xiao, Tong Su, Yunxiang Tang
Background: Napping deprivation in habitual nappers leads to cognitive impairment. The ameliorative effect of acute aerobic exercise has been demonstrated for this post-cognitive impairment. However, it is still unclear which intensity of aerobic exercise is the most effective and how long this improvement can be sustained. Methods: Fifty-eight healthy adults with a chronic napping habit were randomly assigned to four intervention groups after undergoing nap deprivation: a sedentary control group, a low-intensity exercise group (50– 59% maximum heart rate, HRmax), a moderate-intensity exercise group (60– 69% HRmax), and a high-intensity exercise group (70– 79% HRmax). Working memory (N-back task), vigilance (Psychomotor Vigilance Task, PVT), and response inhibitory capacity (Go/NoGo task) were measured. Results: Regression analyses showed a quadratic trend between exercise intensity and working memory reaction time and accuracy (F =3.297– 5.769, p < 0.05, R2 =10.7– 18.9%). The effects of exercise were optimal at low-intensity. There was a significant quadratic trend between exercise intensity and PVT lapse (F =4.314, p =0.042, R² =7.2%). The effect of exercise increased with higher intensity. Prolonged observation found that the effect of low-intensity exercise on working memory was maintained for 2 hours. Conclusion: The effect of low-intensity exercise might be underestimated. Low-intensity exercise significantly improved working memory performance, and the effects could be maintained throughout the afternoon. In contrast, the effects of high-intensity exercise were unlikely to be maintained and might even have negative effects. Future researchers can broaden the categories of participants to enhance the external validity and collect diverse physiological indicators to explore related physiological mechanisms.
{"title":"Acute Aerobic Exercise Intensity on Working Memory and Vigilance After Nap Deprivation: Effects of Low-Intensity Deserve Attention","authors":"Xin Guo, Ying Xu, Yao Meng, Hao Lian, Jingwen He, Ruike Zhang, Jingzhou Xu, Hao Wang, Shuyu Xu, Wenpeng Cai, Lei Xiao, Tong Su, Yunxiang Tang","doi":"10.2147/nss.s471930","DOIUrl":"https://doi.org/10.2147/nss.s471930","url":null,"abstract":"<strong>Background:</strong> Napping deprivation in habitual nappers leads to cognitive impairment. The ameliorative effect of acute aerobic exercise has been demonstrated for this post-cognitive impairment. However, it is still unclear which intensity of aerobic exercise is the most effective and how long this improvement can be sustained.<br/><strong>Methods:</strong> Fifty-eight healthy adults with a chronic napping habit were randomly assigned to four intervention groups after undergoing nap deprivation: a sedentary control group, a low-intensity exercise group (50– 59% maximum heart rate, HR<sub>max</sub>), a moderate-intensity exercise group (60– 69% HR<sub>max</sub>), and a high-intensity exercise group (70– 79% HR<sub>max</sub>). Working memory (N-back task), vigilance (Psychomotor Vigilance Task, PVT), and response inhibitory capacity (Go/NoGo task) were measured.<br/><strong>Results:</strong> Regression analyses showed a quadratic trend between exercise intensity and working memory reaction time and accuracy (<em>F</em> =3.297– 5.769, <em>p</em> < 0.05, <em>R<sup>2</sup></em> =10.7– 18.9%). The effects of exercise were optimal at low-intensity. There was a significant quadratic trend between exercise intensity and PVT lapse (<em>F</em> =4.314, <em>p</em> =0.042, <em>R²</em> =7.2%). The effect of exercise increased with higher intensity. Prolonged observation found that the effect of low-intensity exercise on working memory was maintained for 2 hours.<br/><strong>Conclusion:</strong> The effect of low-intensity exercise might be underestimated. Low-intensity exercise significantly improved working memory performance, and the effects could be maintained throughout the afternoon. In contrast, the effects of high-intensity exercise were unlikely to be maintained and might even have negative effects. Future researchers can broaden the categories of participants to enhance the external validity and collect diverse physiological indicators to explore related physiological mechanisms.<br/><br/>","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":"75 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142252221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose: Converging evidence implicates the putamen in sleep-wake regulation. However, its role remains unclear. We hypothesized that metabolic abnormalities in the putamen are linked to insomnia disorder, which has not been previously addressed, and investigated putaminal N-acetylaspartate (NAA), choline (Cho), and creatine (Cr) in patients with insomnia disorder compared to healthy controls. Participants and Methods: In the present study, the concentrations of NAA, Cho, and Cr in the putamen of 23 patients with insomnia disorder and 18 healthy controls were determined using proton magnetic resonance spectroscopy. Sociodemographic, psychometric, and polysomnography data were obtained from all participants. Results: We found that the mean NAA/Cr ratio of the right putamen was significantly greater in the insomnia group compared to the control group and also greater than the left putamen within the insomnia group. The NAA/Cr ratio of the right putamen distinguished insomnia disorder from normal sleep with 78.3% sensitivity and 61.1% specificity. Furthermore, this ratio positively correlated with both objective and subjective insomnia severity and sleep quality. Conclusion: Our findings provide critical evidence for the dysfunctional putaminal metabolism of NAA/Cr in insomnia disorder, suggesting that the abnormal NAA/Cr ratio of the right putamen is linked to wakefulness in patients with insomnia disorder and may serve as a potential biomarker of insomnia disorder.
{"title":"The Abnormal N-Acetylaspartate to Creatine Ratio of the Right Putamen is Linked to Wakefulness in Patients with Insomnia Disorder","authors":"Qiaoting Huang, Changzheng Shi, Saurabh Sonkusare, Congrui Li, Valerie Voon, Jiyang Pan","doi":"10.2147/nss.s468269","DOIUrl":"https://doi.org/10.2147/nss.s468269","url":null,"abstract":"<strong>Purpose:</strong> Converging evidence implicates the putamen in sleep-wake regulation. However, its role remains unclear. We hypothesized that metabolic abnormalities in the putamen are linked to insomnia disorder, which has not been previously addressed, and investigated putaminal N-acetylaspartate (NAA), choline (Cho), and creatine (Cr) in patients with insomnia disorder compared to healthy controls.<br/><strong>Participants and Methods:</strong> In the present study, the concentrations of NAA, Cho, and Cr in the putamen of 23 patients with insomnia disorder and 18 healthy controls were determined using proton magnetic resonance spectroscopy. Sociodemographic, psychometric, and polysomnography data were obtained from all participants.<br/><strong>Results:</strong> We found that the mean NAA/Cr ratio of the right putamen was significantly greater in the insomnia group compared to the control group and also greater than the left putamen within the insomnia group. The NAA/Cr ratio of the right putamen distinguished insomnia disorder from normal sleep with 78.3% sensitivity and 61.1% specificity. Furthermore, this ratio positively correlated with both objective and subjective insomnia severity and sleep quality.<br/><strong>Conclusion:</strong> Our findings provide critical evidence for the dysfunctional putaminal metabolism of NAA/Cr in insomnia disorder, suggesting that the abnormal NAA/Cr ratio of the right putamen is linked to wakefulness in patients with insomnia disorder and may serve as a potential biomarker of insomnia disorder.<br/><br/><strong>Keywords:</strong> insomnia disorder, wakefulness, putamen, proton magnetic resonance spectroscopy, NAA/Cr ratio, polysomnography<br/>","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":"31 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142252222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ting Yang, Han-Rui Wang, Ya-Kui Mou, Wan-Chen Liu, Yao Wang, Xiao-Yu Song, Chao Ren, Xi-Cheng Song
Abstract: Patients with allergic rhinitis (AR) have a high incidence of sleep disorders, such as insomnia, which can easily exacerbate nasal symptoms. The aggravation of nasal symptoms further promotes the deterioration of sleep disorders, forming a vicious cycle. Severe cases may even trigger psychological and neurological issues, such as anxiety, depression, and cognitive impairment, causing significant distress to patients, making clinical diagnosis and treatment difficult, and increasing costs. Furthermore, satisfactory therapeutics remain lacking. As the pathogenesis of AR-associated sleep disorders is not clear and research is still insufficient, paying attention to and understanding AR-related sleep disorders is crucial in clinical practice. Multiple studies have shown that the most crucial issues in current research on AR and sleep are analyzing the relationship between AR and sleep disorders, searching for the influencing factors, and investigating potential targets for diagnosis and treatment. This review aimed to identify and summarize the results of relevant studies using “AR” and “sleep disorders” as search terms. In addition, we evaluated the correlation between AR and sleep disorders and examined their interaction and potential mechanisms, offering a foundation for additional screening of potential diagnostic biomarkers and therapeutic targets.
摘要：过敏性鼻炎（AR）患者失眠等睡眠障碍的发病率很高，而失眠很容易加重鼻部症状。鼻部症状的加重会进一步促进睡眠障碍的恶化，形成恶性循环。严重者甚至会引发焦虑、抑郁和认知障碍等心理和神经问题，给患者造成极大困扰，给临床诊断和治疗带来困难，并增加费用。此外，目前仍缺乏令人满意的治疗方法。由于AR相关睡眠障碍的发病机制尚不明确，研究仍显不足，因此关注和了解AR相关睡眠障碍在临床实践中至关重要。多项研究表明，目前 AR 与睡眠研究中最关键的问题是分析 AR 与睡眠障碍之间的关系、寻找影响因素以及研究潜在的诊断和治疗靶点。本综述旨在以 "AR "和 "睡眠障碍 "为检索词，识别并总结相关研究的结果。此外，我们还评估了AR与睡眠障碍之间的相关性，研究了它们之间的相互作用和潜在机制，为进一步筛选潜在的诊断生物标志物和治疗靶点奠定了基础。 关键词：过敏性鼻炎；生物节律；免疫炎症；神经调节；睡眠障碍
{"title":"Mutual Influence Between Allergic Rhinitis and Sleep: Factors, Mechanisms, and interventions—A Narrative Review","authors":"Ting Yang, Han-Rui Wang, Ya-Kui Mou, Wan-Chen Liu, Yao Wang, Xiao-Yu Song, Chao Ren, Xi-Cheng Song","doi":"10.2147/nss.s482258","DOIUrl":"https://doi.org/10.2147/nss.s482258","url":null,"abstract":"<strong>Abstract:</strong> Patients with allergic rhinitis (AR) have a high incidence of sleep disorders, such as insomnia, which can easily exacerbate nasal symptoms. The aggravation of nasal symptoms further promotes the deterioration of sleep disorders, forming a vicious cycle. Severe cases may even trigger psychological and neurological issues, such as anxiety, depression, and cognitive impairment, causing significant distress to patients, making clinical diagnosis and treatment difficult, and increasing costs. Furthermore, satisfactory therapeutics remain lacking. As the pathogenesis of AR-associated sleep disorders is not clear and research is still insufficient, paying attention to and understanding AR-related sleep disorders is crucial in clinical practice. Multiple studies have shown that the most crucial issues in current research on AR and sleep are analyzing the relationship between AR and sleep disorders, searching for the influencing factors, and investigating potential targets for diagnosis and treatment. This review aimed to identify and summarize the results of relevant studies using “AR” and “sleep disorders” as search terms. In addition, we evaluated the correlation between AR and sleep disorders and examined their interaction and potential mechanisms, offering a foundation for additional screening of potential diagnostic biomarkers and therapeutic targets.<br/><br/><strong>Keywords:</strong> allergic rhinitis, biological rhythm, immune inflammatory, neurological regulation, sleep disorders<br/>","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":"16 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142252542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract: Myopia is increasingly prevalent in children. Its association with insufficient sleep has been studied, yielding inconsistent findings. This review aims to assess the association of insufficient sleep with myopia and myopia-related refractive parameters in children. A total of 657 articles were identified, of which 40 were included in the systematic review and 33 were included in the meta-analysis. Results showed that insufficient sleep was significantly associated with an increased prevalence of myopia (odds ratio [OR] = 1.59; 95% confidence interval [CI] = 1.31, 1.95; I2 = 99%), and an increased prevalence of high myopia (OR = 3.36; 95% CI = 1.26, 9.00; I2 = 96%). Shorter sleep duration was significantly linked to faster changes in axial length (AL) (β = 0.05; 95% CI = 0.02, 0.08; I2 = 0%). However, correlation between insufficient sleep and the incidence of myopia, spherical equivalent refraction, corneal curvature radius (CR) and AL/CR were insignificant. Moreover, the effect of insufficient sleep on premyopia and astigmatism was not well-studied. The results of this study suggest that insufficient sleep may be an important risk factor for the development of myopia in school-aged children. Therefore, in addition to ensuring sufficient outdoor activities and reducing near work, it is necessary to inform children and parents about the importance of adequate sleep to mitigate the risk of myopia.
{"title":"Effects of Insufficient Sleep on Myopia in Children: A Systematic Review and Meta-Analysis","authors":"Xixuan Zhao, Yining He, Juzhao Zhang, Senlin Lin, Haidong Zou, Yingyan Ma","doi":"10.2147/nss.s472748","DOIUrl":"https://doi.org/10.2147/nss.s472748","url":null,"abstract":"<strong>Abstract:</strong> Myopia is increasingly prevalent in children. Its association with insufficient sleep has been studied, yielding inconsistent findings. This review aims to assess the association of insufficient sleep with myopia and myopia-related refractive parameters in children. A total of 657 articles were identified, of which 40 were included in the systematic review and 33 were included in the meta-analysis. Results showed that insufficient sleep was significantly associated with an increased prevalence of myopia (odds ratio [OR] = 1.59; 95% confidence interval [CI] = 1.31, 1.95; <em>I</em><sup>2</sup> = 99%), and an increased prevalence of high myopia (OR = 3.36; 95% CI = 1.26, 9.00; <em>I</em><sup>2</sup> = 96%). Shorter sleep duration was significantly linked to faster changes in axial length (AL) (β = 0.05; 95% CI = 0.02, 0.08; <em>I</em><sup>2</sup> = 0%). However, correlation between insufficient sleep and the incidence of myopia, spherical equivalent refraction, corneal curvature radius (CR) and AL/CR were insignificant. Moreover, the effect of insufficient sleep on premyopia and astigmatism was not well-studied. The results of this study suggest that insufficient sleep may be an important risk factor for the development of myopia in school-aged children. Therefore, in addition to ensuring sufficient outdoor activities and reducing near work, it is necessary to inform children and parents about the importance of adequate sleep to mitigate the risk of myopia.<br/><br/><strong>Keywords:</strong> insufficient sleep, myopia, children, axial length, refractive parameters<br/>","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":"6 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142252308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose: The Athens Insomnia Scale (AIS) is a widely used and authorized questionnaire for evaluating insomnia symptoms. However, its reliability and validity at high altitudes are uncertain. Therefore, this study aimed to confirm the validity and reliability of AIS during a 3658 m altitude exposure. Patients and Methods: A total of 387 young Chinese males were enlisted in the acute high-altitude exposure group. They flew for about two hours, climbing from 400 m to 3658 m. The high-altitude-acclimated group consisted of 86 young Chinese men who had lived at least six months at 3658 m altitude. The sleep quality of the acute high-altitude exposure group was evaluated using the AIS before the ascent and after exposure to 3658 m for 24 hours, and one week. The sleep quality of the high-altitude-acclimated group was also assessed. The AIS’s internal consistency, reliability, and validity were evaluated. Results: The respondents’ quality of sleep significantly decreased after being exposed to 3658 m as opposed to 400 m. Two factors comprised the AIS, according to an exploratory factor analysis: “sleep problem” (items 1– 5) and “daytime dysfunction” (items 6– 8). The Cronbach’s α internal consistency coefficients exceeded 0.8, and the corrected item-total correlations were all greater than 0.5 when the subjects were exposed to 3658 m. The model fit index was well within the criterion. The average variance extracted and composite reliability were all higher than 0.5 and 0.7, respectively. The interclass correlation coefficient was deemed “fair to good” at 0.482, which is greater than the 0.4 threshold. The AIS has satisfactory discriminant validity, as shown by the Fornell-Larcker criterion and cross-loading results. The daytime dysfunction R-square values (> 0.33) show that the frameworks have considerable predictive accuracy. Conclusion: The AIS exhibits strong consistency, reliability, and validity. The AIS’s features and simplicity make it an essential psychometric tool for high-altitude sleep research.
{"title":"Validation of the Athens Insomnia Scale Among Young Chinese Male Population in a High-Altitude Situation","authors":"Xugang Tang, Qiang Wang, Shuang Li, Xiuchuan Li, Qian Xin, Yongjian Yang","doi":"10.2147/nss.s475497","DOIUrl":"https://doi.org/10.2147/nss.s475497","url":null,"abstract":"<strong>Purpose:</strong> The Athens Insomnia Scale (AIS) is a widely used and authorized questionnaire for evaluating insomnia symptoms. However, its reliability and validity at high altitudes are uncertain. Therefore, this study aimed to confirm the validity and reliability of AIS during a 3658 m altitude exposure.<br/><strong>Patients and Methods:</strong> A total of 387 young Chinese males were enlisted in the acute high-altitude exposure group. They flew for about two hours, climbing from 400 m to 3658 m. The high-altitude-acclimated group consisted of 86 young Chinese men who had lived at least six months at 3658 m altitude. The sleep quality of the acute high-altitude exposure group was evaluated using the AIS before the ascent and after exposure to 3658 m for 24 hours, and one week. The sleep quality of the high-altitude-acclimated group was also assessed. The AIS’s internal consistency, reliability, and validity were evaluated.<br/><strong>Results:</strong> The respondents’ quality of sleep significantly decreased after being exposed to 3658 m as opposed to 400 m. Two factors comprised the AIS, according to an exploratory factor analysis: “sleep problem” (items 1– 5) and “daytime dysfunction” (items 6– 8). The Cronbach’s α internal consistency coefficients exceeded 0.8, and the corrected item-total correlations were all greater than 0.5 when the subjects were exposed to 3658 m. The model fit index was well within the criterion. The average variance extracted and composite reliability were all higher than 0.5 and 0.7, respectively. The interclass correlation coefficient was deemed “fair to good” at 0.482, which is greater than the 0.4 threshold. The AIS has satisfactory discriminant validity, as shown by the Fornell-Larcker criterion and cross-loading results. The daytime dysfunction R-square values (> 0.33) show that the frameworks have considerable predictive accuracy.<br/><strong>Conclusion:</strong> The AIS exhibits strong consistency, reliability, and validity. The AIS’s features and simplicity make it an essential psychometric tool for high-altitude sleep research.<br/><br/><strong>Keywords:</strong> athens insomnia scale, high altitude, internal consistency, reliability, sleep, validity<br/>","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":"10 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142268603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jia Wei, Mingfen Song, Hong Jing Mao, Ruobing Qi, Lili Yang, You Xu, Pan Yan, Linlin Hu
Background: The effectiveness of medication combined with smartphone-delivered cognitive behavioral therapy for insomnia (CBT-I) has been well verified, but there are few studies on the sequence of remission of insomnia symptoms. This study aims to understand the sequence of symptom improvement and the factors influencing the treatment effectiveness in patients with insomnia. Methods: Smartphone-delivered CBT, as a form of Online CBT, allows for training through mobile devices at any time and place. We utilized the Good Sleep 365 app to conduct a survey, involving 2820 patients who met the baseline inclusion criteria. These patients were assessed using a general demographic questionnaire and the Pittsburgh Sleep Quality Index (PSQI) to evaluate general demographic information and insomnia symptoms, and subsequently underwent CBT training using the Good Sleep 365 app. A total of 1179 patients completed follow-ups at 4 weeks, 8 weeks, 16 weeks, and 24 weeks. Results: At 4 weeks and 8 weeks, the descending order of the reduction rates of PSQI components (excluding component 6: use of sleeping medication) was: sleep latency, subjective sleep quality, sleep efficiency, sleep disturbance, sleep maintenance, and daytime dysfunction. At 16 weeks and 24 weeks, the descending order was subjective sleep quality, sleep latency, sleep efficiency, daytime dysfunction, sleep maintenance, and sleep disturbance. There were significant differences in the reduction rates of PSQI components (excluding component 6: use of sleeping medication) both at the same follow-up times and at different follow-up times (all P< 0.05). Multivariable logistic regression analysis showed that patients older than 30 years and those with a college degree or above had better treatment outcomes, whereas those with a disease duration of more than three years had worse outcomes. Conclusion: The sequence of symptom improvement in patients with insomnia changes over time, and age, educational level, and duration of disease are factors influencing treatment outcomes.
{"title":"Analysis of the Improvement Sequence in Insomnia Symptoms and Factors Influencing the Treatment Outcomes of Smartphone-Delivered CBT in Patients with Insomnia Disorder","authors":"Jia Wei, Mingfen Song, Hong Jing Mao, Ruobing Qi, Lili Yang, You Xu, Pan Yan, Linlin Hu","doi":"10.2147/nss.s486288","DOIUrl":"https://doi.org/10.2147/nss.s486288","url":null,"abstract":"<strong>Background:</strong> The effectiveness of medication combined with smartphone-delivered cognitive behavioral therapy for insomnia (CBT-I) has been well verified, but there are few studies on the sequence of remission of insomnia symptoms. This study aims to understand the sequence of symptom improvement and the factors influencing the treatment effectiveness in patients with insomnia.<br/><strong>Methods:</strong> Smartphone-delivered CBT, as a form of Online CBT, allows for training through mobile devices at any time and place. We utilized the Good Sleep 365 app to conduct a survey, involving 2820 patients who met the baseline inclusion criteria. These patients were assessed using a general demographic questionnaire and the Pittsburgh Sleep Quality Index (PSQI) to evaluate general demographic information and insomnia symptoms, and subsequently underwent CBT training using the Good Sleep 365 app. A total of 1179 patients completed follow-ups at 4 weeks, 8 weeks, 16 weeks, and 24 weeks.<br/><strong>Results:</strong> At 4 weeks and 8 weeks, the descending order of the reduction rates of PSQI components (excluding component 6: use of sleeping medication) was: sleep latency, subjective sleep quality, sleep efficiency, sleep disturbance, sleep maintenance, and daytime dysfunction. At 16 weeks and 24 weeks, the descending order was subjective sleep quality, sleep latency, sleep efficiency, daytime dysfunction, sleep maintenance, and sleep disturbance. There were significant differences in the reduction rates of PSQI components (excluding component 6: use of sleeping medication) both at the same follow-up times and at different follow-up times (all P< 0.05). Multivariable logistic regression analysis showed that patients older than 30 years and those with a college degree or above had better treatment outcomes, whereas those with a disease duration of more than three years had worse outcomes.<br/><strong>Conclusion:</strong> The sequence of symptom improvement in patients with insomnia changes over time, and age, educational level, and duration of disease are factors influencing treatment outcomes.<br/><br/>","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":"4 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142226040","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background: Sleep is critical in health problems including Parkinson’s disease (PD). This study examined the association between sleep characteristics and the likelihood of prodromal PD. Methods: At baseline examination of the Heart and Brain Investigation in Taicang (HABIT) study, potential PD biomarkers were obtained for 8777 participants aged over 50 years, and the probability of prodromal PD was assessed based on the Chinese expert consensus and Movement Disorder Society (MDS) criteria. General and component sleep characteristics were evaluated by the Pittsburgh Sleep Quality Index (PSQI). Median regression was applied to examine the association between sleep and the probability of prodromal PD, adjusting for age, sex, education level, physical activity, obesity, fast plasma glucose, lipids, and hypertension. Results: Based on China criteria, a higher level of PSQI score was significantly associated with a higher probability of prodromal PD (β = 0.02, 95% CI: 0.01– 0.03) and a higher risk of having an increased probability of prodromal PD (OR = 1.04, 95% CI: 1.02– 1.05). Compared to participants with good quality sleep, those with poor quality sleep had a 0.07% increased probability of prodromal PD (95% CI: 0.01– 0.13) and a 19% increased risk of having a high prodromal PD probability (95% CI: 1.04– 1.20). Similar associations between sleep quality and the probability of prodromal PD were also observed using the MDS criteria. Subjective sleep quality, sleep latency, habitual sleep efficiency, daytime dysfunction, and use of sleep medications were also associated with the probability of prodromal PD. Conclusion: Poor sleep quality was associated with a high probability of prodromal PD. Sleep may be helpful for understanding and intervention of prodromal PD.
{"title":"Association Between Sleep Characteristics and Likelihood of Prodromal Parkinson’s Disease: A Cross-Sectional Analysis in the HABIT Study","authors":"Cheng-Jie Mao, Hao Peng, Sheng Zhuang, Ying-Chun Zhang, Wei-Ye Xie, Jia-Hui Yan, Hui-Hui Liu, Jing Chen, Jun-Yi Liu, Jianan Zhang, Hai Jiang, Yonghong Zhang, Mingzhi Zhang, Chun-Feng Liu","doi":"10.2147/nss.s476348","DOIUrl":"https://doi.org/10.2147/nss.s476348","url":null,"abstract":"<strong>Background:</strong> Sleep is critical in health problems including Parkinson’s disease (PD). This study examined the association between sleep characteristics and the likelihood of prodromal PD.<br/><strong>Methods:</strong> At baseline examination of the Heart and Brain Investigation in Taicang (HABIT) study, potential PD biomarkers were obtained for 8777 participants aged over 50 years, and the probability of prodromal PD was assessed based on the Chinese expert consensus and Movement Disorder Society (MDS) criteria. General and component sleep characteristics were evaluated by the Pittsburgh Sleep Quality Index (PSQI). Median regression was applied to examine the association between sleep and the probability of prodromal PD, adjusting for age, sex, education level, physical activity, obesity, fast plasma glucose, lipids, and hypertension.<br/><strong>Results:</strong> Based on China criteria, a higher level of PSQI score was significantly associated with a higher probability of prodromal PD (β = 0.02, 95% CI: 0.01– 0.03) and a higher risk of having an increased probability of prodromal PD (OR = 1.04, 95% CI: 1.02– 1.05). Compared to participants with good quality sleep, those with poor quality sleep had a 0.07% increased probability of prodromal PD (95% CI: 0.01– 0.13) and a 19% increased risk of having a high prodromal PD probability (95% CI: 1.04– 1.20). Similar associations between sleep quality and the probability of prodromal PD were also observed using the MDS criteria. Subjective sleep quality, sleep latency, habitual sleep efficiency, daytime dysfunction, and use of sleep medications were also associated with the probability of prodromal PD.<br/><strong>Conclusion:</strong> Poor sleep quality was associated with a high probability of prodromal PD. Sleep may be helpful for understanding and intervention of prodromal PD.<br/><br/>","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":"15 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142201804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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