{"title":"Association Between Sleep Apnea Syndrome and Osteoarthritis: Insights from Bidirectional Mendelian Randomization and Bioinformatics Analysis","authors":"Lian Weng, Xiongjunjie Luo, Yuxi Luo, Qian Zhang, Kaitao Yao, Junjie Tan, Yiran Yin","doi":"10.2147/nss.s461010","DOIUrl":null,"url":null,"abstract":"<strong>Background:</strong> Sleep apnea syndrome(SAS) and osteoarthritis (OA) are two prevalent diseases that often coexist, but the causal relationship between them remains unclear. In light of this, our team utilizes Mendelian Randomization and bioinformatics analysis methods to investigate the potential association between the two diseases.<br/><strong>Methods:</strong> In this study, we utilized GWAS data pertaining to SAS and OA to assess the causal relationship between the two diseases through Mendelian randomization (MR) analysis. We then employed transcriptomic data to perform differential gene identification, WGCNA, shared gene determination, functional enrichment analysis, and colocalization analysis, all designed to further elucidate the mechanisms underlying the association between the two diseases. In the end, we utilized Mendelian randomization (MR) analysis again to delve deeper into the relationship between the two diseases and immune cells.<br/><strong>Results:</strong> Our research findings indicate that SAS is a risk factor for OA (p = 0.000004), knee OA (p = 0.0000001) and hip OA(p = 0.001). Furthermore, OA (p = 0.000195), knee OA (p = 0.001) are significant risk factors for SAS. However, there is no clear evidence that hip OA (p = 0.892) is a risk factor for SAS. Interestingly, the genes shared between OA and SAS are significantly enriched in leukocyte migration, leukocyte chemotaxis. Moreover, colocalization analysis suggests that the genes JUNB, COL8A1, FOSB, and IER2 may be key genes associated with both diseases. Furthermore, 57 immune cell phenotypes are associated with SAS, 95 with OA, and 6 shared between both diseases.<br/><strong>Conclusion:</strong> This research confirmed the bidirectional causal relationship between SAS and OA. Notably, the 4 genes (JUNB, COL8A1, FOSB, IER2) and 6 immune phenotypes are crucial for both diseases, these provide hopeful targets for future interventions against these two diseases.<br/><br/>","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":null,"pages":null},"PeriodicalIF":3.0000,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature and Science of Sleep","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2147/nss.s461010","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Sleep apnea syndrome(SAS) and osteoarthritis (OA) are two prevalent diseases that often coexist, but the causal relationship between them remains unclear. In light of this, our team utilizes Mendelian Randomization and bioinformatics analysis methods to investigate the potential association between the two diseases. Methods: In this study, we utilized GWAS data pertaining to SAS and OA to assess the causal relationship between the two diseases through Mendelian randomization (MR) analysis. We then employed transcriptomic data to perform differential gene identification, WGCNA, shared gene determination, functional enrichment analysis, and colocalization analysis, all designed to further elucidate the mechanisms underlying the association between the two diseases. In the end, we utilized Mendelian randomization (MR) analysis again to delve deeper into the relationship between the two diseases and immune cells. Results: Our research findings indicate that SAS is a risk factor for OA (p = 0.000004), knee OA (p = 0.0000001) and hip OA(p = 0.001). Furthermore, OA (p = 0.000195), knee OA (p = 0.001) are significant risk factors for SAS. However, there is no clear evidence that hip OA (p = 0.892) is a risk factor for SAS. Interestingly, the genes shared between OA and SAS are significantly enriched in leukocyte migration, leukocyte chemotaxis. Moreover, colocalization analysis suggests that the genes JUNB, COL8A1, FOSB, and IER2 may be key genes associated with both diseases. Furthermore, 57 immune cell phenotypes are associated with SAS, 95 with OA, and 6 shared between both diseases. Conclusion: This research confirmed the bidirectional causal relationship between SAS and OA. Notably, the 4 genes (JUNB, COL8A1, FOSB, IER2) and 6 immune phenotypes are crucial for both diseases, these provide hopeful targets for future interventions against these two diseases.
期刊介绍:
Nature and Science of Sleep is an international, peer-reviewed, open access journal covering all aspects of sleep science and sleep medicine, including the neurophysiology and functions of sleep, the genetics of sleep, sleep and society, biological rhythms, dreaming, sleep disorders and therapy, and strategies to optimize healthy sleep.
Specific topics covered in the journal include:
The functions of sleep in humans and other animals
Physiological and neurophysiological changes with sleep
The genetics of sleep and sleep differences
The neurotransmitters, receptors and pathways involved in controlling both sleep and wakefulness
Behavioral and pharmacological interventions aimed at improving sleep, and improving wakefulness
Sleep changes with development and with age
Sleep and reproduction (e.g., changes across the menstrual cycle, with pregnancy and menopause)
The science and nature of dreams
Sleep disorders
Impact of sleep and sleep disorders on health, daytime function and quality of life
Sleep problems secondary to clinical disorders
Interaction of society with sleep (e.g., consequences of shift work, occupational health, public health)
The microbiome and sleep
Chronotherapy
Impact of circadian rhythms on sleep, physiology, cognition and health
Mechanisms controlling circadian rhythms, centrally and peripherally
Impact of circadian rhythm disruptions (including night shift work, jet lag and social jet lag) on sleep, physiology, cognition and health
Behavioral and pharmacological interventions aimed at reducing adverse effects of circadian-related sleep disruption
Assessment of technologies and biomarkers for measuring sleep and/or circadian rhythms
Epigenetic markers of sleep or circadian disruption.