{"paper_id":"3cdabbe7-b50c-4dd7-a6fd-83d37d41ca0e","body_text":"Epigenetic Aging and Risk of Obstructive Sleep Apnea: a bidirectional Mendelian randomization study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Epigenetic Aging and Risk of Obstructive Sleep Apnea: a bidirectional Mendelian randomization study Chenyi Xu, Gang Yang, Yuehua Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5305378/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Obstructive Sleep apnea (OSA) is a prevalent sleep disorder characterized by repetitive interruptions of breathing during sleep, significantly impacting cardiovascular and metabolic health. Epigenetic aging, measured via DNA methylation-based clocks, has emerged as a robust predictor of biological aging and associated health outcomes. This study investigates the causal relationship between epigenetic aging and the risk of sleep apnea using a bidirectional Mendelian randomization (MR) approach. Methods We utilized genome-wide association study (GWAS) summary statistics for epigenetic aging markers (HannumAge, HorvathAge, PhenoAge, and GrimAge) and sleep apnea from FinnGen. Instrumental variables were selected based on stringent criteria to ensure validity. The causal association was assessed using inverse variance weighted (IVW), weighted median (WM), and MR-Egger methods. Sensitivity analyses, including heterogeneity and pleiotropy assessments, were conducted to validate the robustness of the findings. Results In this study, using Mendelian randomization analysis, we investigated the relationship between epigenetic age acceleration markers HannumAge, HorvathAge, PhenoAge, and GrimAge, and the risk of obstructive sleep apnea (OSA). The results showed that these markers of epigenetic age acceleration were not significantly associated with an increased risk of OSA. Quality control assessments confirmed the reliability of our findings. Although previous literature suggests an association between epigenetic age acceleration and sleep apnea, our study did not support a causal relationship between the two. This finding provides a new perspective on the relationship between epigenetic age acceleration and OSA, highlighting the need for further research. Conclusion The current Mendelian randomization analysis revealed no causal relationship between epigenetic clocks and obstructive sleep apnea (OSA). However, the potential for a shared genetic architecture should be considered. Conducting a comorbidity genetic analysis may provide further insights into this relationship. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Obstructive sleep apnea (OSA) is a major public health concern affecting millions globally[ 1 ]. Characterized by repeated episodes of partial or complete upper airway obstruction during sleep[ 2 ], OSA is associated with adverse cardiovascular outcomes and metabolic disturbances[ 3 , 4 ]. The condition leads to intermittent hypoxia, oxidative stress, and systemic inflammation[ 5 ], which are critical pathways contributing to cardiovascular and metabolic morbidities.[ 6 ] Additionally, chronic sleep fragmentation caused by OSA has been shown to induce endothelial dysfunction and vascular aging in both clinical and experimental settings[ 7 , 8 ]. Recent studies suggest a potential link between biological aging and sleep apnea[ 9 ], but the directionality and causality of this relationship remain unclear. Epigenetic clocks, which measure DNA methylation levels at specific loci, provide a quantifiable estimate of biological age[ 10 , 11 ]. These clocks, including HannumAge, HorvathAge, PhenoAge, and GrimAge[ 12 ], have demonstrated predictive power for various age-related diseases[ 13 ]. Epigenetic age acceleration (EAA) indicates that an individual's biological age is greater than their chronological age[ 14 ], which may predispose them to age-related conditions such as OSA. Previous research has highlighted that individuals with OSA exhibit accelerated epigenetic aging, as shown by increased DNA methylation age compared to their chronological age[ 15 , 16 ]. Moreover, effective treatment with continuous positive airway pressure (CPAP) has been found to partially reverse this acceleration, suggesting a dynamic interaction between sleep apnea and biological aging processes[ 9 , 17 ]. These findings underscore the need for a deeper understanding of the mechanistic links between OSA and epigenetic aging[ 18 ]. In this study, we aim to explore the direct causal relationship between OSA and epigenetic aging using Mendelian randomization[ 19 ]. By leveraging genetic variants associated with epigenetic aging and OSA, we seek to elucidate whether accelerated epigenetic aging contributes to the development of OSA or if OSA itself leads to changes in biological age[ 20 ]. This approach will help clarify the directionality and provide insights into potential therapeutic targets for mitigating the adverse effects of OSA on aging and overall health. Methods Study Design This bidirectional two-sample MR study leveraged genetic variants as instrumental variables (IVs) to examine the causal relationship between epigenetic aging and sleep apnea. The key assumptions of MR include relevance (IVs are associated with exposure), independence (IVs are not associated with confounders), and exclusion restriction (IVs influence the outcome solely through exposure). Data Sources We obtained summary-level GWAS data on epigenetic aging markers (GrimAge, HannumAge, HorvathAge and PhenoAge) from the Edinburgh DataShare and sleep apnea from the FinnGen biobank[ 21 ]. The epigenetic aging data encompassed 34,710 individuals, while the sleep apnea dataset included 16,761 cases and 201,194 controls of European descent. This study used in the raw data has been approved by the ethics committee, all participants have been formally provide consent. (Table 1) Selection of Genetic Instrumental Variables Criteria for Selecting Instrumental Variables:(1)SNPs that are significantly associated with epigenetic aging (HannumAge, HorvathAge, PhenoAge, and GrimAge) across the entire genome (P < 1×10^-5)[ 22 ].(2)SNPs are selected by setting the linkage disequilibrium parameter (r²) threshold at 0.001 and a genetic distance of 10,000 base pairs to eliminate the influence of linkage disequilibrium on the results[ 23 ].(3)Palindromic SNPs are removed. If SNPs associated with exposure are not present in the outcome data, appropriate proxy SNPs (r²>0.8) are sought and selected[ 19 , 24 ].(4)Remaining SNPs are verified for associated phenotypes in the Human Genotype-Phenotype Association Database to exclude SNPs associated with other phenotypes that correlate with the four types of benign biliary diseases[ 25 ]. The selected instrumental variables must meet the three main assumptions: relevance, exclusivity, and independence[ 26 ]. To meet MR assumptions, we applied strict criteria to ensure SNPs were not linked to confounders or other outcomes. SNPs exhibiting linkage disequilibrium were excluded[ 27 ]. Statistical Analysis Five commonly used Mendelian randomization methods were employed: inverse-variance weighting (IVW), MR-Egger regression, weighted median, simple mode, and weighted mode[ 28 ]. The IVW method, which uses the inverse of the outcome variance as the weight for fitting, is noted for its accurate estimation even in the presence of heterogeneity[ 29 ]. If the genetic variants selected as instrumental variables are effective, IVW can produce unbiased estimates. Therefore, IVW was chosen as the primary analysis method[ 28 ]. To enhance the reliability of the findings, additional analyses were conducted using MR-Egger regression, weighted median, simple mode, and weighted mode methods[ 30 ]. Heterogeneity, pleiotropy, and sensitivity assessment Horizontal pleiotropy was assessed using MR-Egger regression and MR-PRESSO tests. In MR-Egger regression, the intercept term represents the average pleiotropy of the instrumental variables, with a P-value greater than 0.05 indicating no significant horizontal pleiotropy[ 31 ]. When horizontal pleiotropy is detected, the MR-PRESSO outlier test is applied to further validate the results, correcting for pleiotropy and improving the accuracy of causal inferences[ 32 ]. Heterogeneity of the results was examined using Cochran's Q test, and a leave-one-out analysis was conducted to check the sensitivity of individual SNPs and identify any significant outliers[ 33 ]. Results Our analysis indicated that GrimAge HannumAge, HorvathAge and PhenoAge were not significantly associated with an increased risk of sleep apnea. Specifically, the odds ratios (ORs) for these four acceleration markers did not show a robust positive association with sleep apnea risk. (Obverse:GrimAge = 4, P = 0.146 ;HannumAge = 9, P = 0.725;HorvathAge = 24, P = 0.025; PhenoAge = 11, P = 0.888) (Reverse:GrimAge = 18, F = 0.421;HannumAge = 18, F = 0.426;HorvathAge = 19, P = 0.360; PhenoAge = 19, P = 0.144) These findings were consistent across various MR methods, indicating no causal relationship in either direction between epigenetic aging and obstructive sleep apnea. (Fig. 1–6) Quality Control Assessment The robustness of our results was confirmed through extensive quality control measures. Cochran's Q test and I² statistics indicated minimal heterogeneity. The MR-Egger intercept and MR-PRESSO Global test suggested no horizontal pleiotropy. Sensitivity analyses affirmed that the results were not driven by any single SNP. (Table 2) Discussion The observational study findings align with the growing body of literature identifying obstructive sleep apnea (OSA) as a significant contributor to systemic inflammation and oxidative stress, thereby accelerating the epigenetic clock measurement of biological aging processes[ 34 , 35 ]. OSA leads to repeated episodes of hypoxia and reoxygenation, creating a state of chronic intermittent hypoxia[ 36 ]. This condition triggers systemic inflammatory pathways and oxidative stress, both closely linked to aging and various age-related diseases[ 37 ]. Research shows that individuals with OSA exhibit elevated levels of inflammatory markers such as C-reactive protein (CRP), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α)[ 38 , 39 ]. Oxidative stress in OSA patients is marked by increased production of reactive oxygen species (ROS) and reduced activity of antioxidant enzymes, leading to cellular and molecular damage that contributes to aging[ 40 ]. The concept of epigenetic clocks, particularly DNA methylation clocks, has become a valuable tool for assessing biological age and age acceleration[ 41 ]. In individuals with OSA, these clocks often indicate accelerated aging[ 42 ]. Studies have shown that patients with OSA have higher epigenetic age acceleration compared to healthy controls, suggesting that the biological age of OSA patients is older than their chronological age[ 34 ]. This epigenetic aging is believed to result from the cumulative effects of oxidative stress and systemic inflammation[ 43 , 44 ]. Continuous positive airway pressure (CPAP) therapy is the standard treatment for OSA and has been shown to mitigate many of the negative effects associated with the condition[ 45 ]. CPAP therapy works by keeping the airway open during sleep, thereby preventing episodes of hypoxia and reducing the frequency of arousals[ 46 ]. This intervention not only improves sleep quality but also has significant impacts on systemic health[ 47 , 48 ]. The study highlights that adherent CPAP treatment can decelerate the epigenetic aging process, demonstrating a reversal of the accelerated epigenetic age observed in OSA patients[ 49 ]. This reversal underscores the potential therapeutic benefits of CPAP in reducing age-related health risks[ 50 ].The findings of the study suggest that early and consistent treatment of OSA with CPAP can have profound effects on biological aging, potentially reducing the risk of age-related diseases such as cardiovascular disease, neurodegenerative conditions, and metabolic disorders[ 17 , 51 ]. However, our MR analysis suggests a contrary view, indicating that there is no causal relationship between OSA and epigenetic age acceleration. This difference may have several reasons: observational studies, despite controlling for many confounding factors, may still be affected by residual confounding factors, such as lifestyle factors or other complications. Differences in population characteristics and sample sizes between observational and MR studies may have contributed to the different results. MR studies rely on genetic variants and thus require large sample sizes to detect small effects, which may not be possible with small observational cohorts. Nonetheless, this observational study provides real-world evidence of the relationship between OSA and epigenetic aging, including detailed phenotypic data and longitudinal follow-up. The use of CPAP treatment data provides insight into the potential reversibility of epigenetic changes. Despite these Mendelian randomization results, the biological plausibility that OSA affects epigenetic aging cannot be completely ruled out. OSA-induced hypoxia and sleep fragmentation are known to activate stress pathways and inflammatory processes, thereby affecting DNA methylation patterns. The accelerated reversal of epigenetic age observed with CPAP treatment supports the hypothesis that effective management of OSA can mitigate its biological impact on the aging process. Future research on epigenetic aging and its relationship with sleep apnea should focus on the molecular mechanisms, specifically on intermediate pathways and potential indirect effects. Our study has several unavoidable limitations. Firstly, the GWAS data we used are from individuals of European descent, which may limit the generalizability of our findings to other ethnic groups. Secondly, due to the lack of suitable public datasets, we were unable to perform a stratified analysis of the progression and severity of obstructive sleep apnea (OSA). Additionally, the summary-level statistics lack individual-level data, preventing us from stratifying the study population by important factors such as age or sex. Lastly, there may be sample overlap between the exposure and outcome datasets, which could affect the results. Declarations Ethics approval and consent to participate The study made use of the large publicly accessible GWAS database, which had received the necessary approvals from relevant ethical review boards and participants. Consent for publication All data used in this study were obtained from publicly available GWAS databases, with all participants having signed informed consent forms. Availability of data and materials This study did not generate any original data. The datasets utilized in this research are accessible to the public: the Edinburgh DataShare for GWAS of epigenetic clocks (https://datashare.ed.ac.uk/handle/10283/3645) and the FinnGen biobank for GWAS of OSA (phenocode: G6_SLEEPAPNO, https://www.finngen.fi/en/access_results). Competing interests The authors have stated that they have no commercial or financial conflicts of interest related to this work. Funding This research was supported by Clinical Research Plan of Shanghai Shenkang Hospital Development Centre: A prospective randomized controlled trial comparing orthodontic treatment with tonsillectomy and adenoidectomy in children with moderate OSAHS(No.SHDC2020CR2043B). Authors’ contributions All authors have read and approved the submission of the manuscript. YL presented research questions. CX and GY participated in the original draft of the manuscript and the literature search. CX contributed to the data retrieval, statistical analysis, and visualization of results. CX and GY were involved in the interpretation of the results. Acknowledgements This study leveraged data from the Edinburgh DataShare and the FinnGen Project Database. We express our heartfelt gratitude to all participants and researchers for their significant contributions in making these datasets accessible and publicly available. Clinical trial number: not applicable. References Benjafield AV, Ayas NT, Eastwood PR, Heinzer R, Ip MSM, Morrell MJ, Nunez CM, Patel SR, Penzel T, Pépin JLD, et al. Estimation of the global prevalence and burden of obstructive sleep apnoea: a literature-based analysis. Lancet Respiratory Med. 2019;7(8):687–98. Senaratna CV, Perret JL, Lodge CJ, Lowe AJ, Campbell BE, Matheson MC, Hamilton GS, Dharmage SC. Prevalence of obstructive sleep apnea in the general population: A systematic review. Sleep Med Rev. 2017;34:70–81. Mazzotti DR, Keenan BT, Lim DC, Gottlieb DJ, Kim J, Pack AI. Symptom Subtypes of Obstructive Sleep Apnea Predict Incidence of Cardiovascular Outcomes. Am J Respir Crit Care Med. 2019;200(4):493–506. Voulgaris A, Archontogeorgis K, Papanas N, Pilitsi E, Nena E, Xanthoudaki M, Mikhailidis DP, Froudarakis ME, Steiropoulos P. Increased risk for cardiovascular disease in patients with obstructive sleep apnoea syndrome-chronic obstructive pulmonary disease (overlap syndrome). Clin Respiratory J. 2019;13(11):708–15. Atkeson A, Jelic S. Mechanisms of endothelial dysfunction in obstructive sleep apnea. Vasc Health Risk Manag. 2008;4(6):1327–35. Gozal D, Kheirandish-Gozal L. Cardiovascular morbidity in obstructive sleep apnea - Oxidative stress, inflammation, and much more. Am J Respir Crit Care Med. 2008;177(4):369–75. Carreras A, Zhang SX, Peris E, Qiao ZH, Gileles-Hillel A, Li RC, Wang Y, Gozal D. Chronic Sleep Fragmentation Induces Endothelial Dysfunction and Structural Vascular Changes in Mice. Sleep. 2014;37(11):1817–24. Abd Elghany OSA, Elessawy AF, Elkhashab KA, Elebiary AM, Ebeid HM. Correlation between obstructive sleep apnea and ventricular function: a cross-sectional hospital-based study. Acta Cardiol. 2023;78(7):805–12. Gaspar LS, Alvaro AR, Moita J, Cavadas C. Obstructive Sleep Apnea and Hallmarks of Aging. Trends Mol Med. 2017;23(8):675–92. Hannum G, Guinney J, Zhao L, Zhang L, Hughes G, Sadda S, Klotzle B, Bibikova M, Fan JB, Gao Y, et al. Genome-wide Methylation Profiles Reveal Quantitative Views of Human Aging Rates. Mol Cell. 2013;49(2):359–67. Izadi M, Sadri N, Abdi A, Serajian S, Jalalei D, Tahmasebi S. Epigenetic biomarkers in aging and longevity: Current and future application. Life Sci 2024, 351. Lu AT, Quach A, Wilson JG, Reiner AP, Aviv A, Raj K, Hou LF, Baccarelli AA, Li Y, Stewart JD, et al. DNA methylation GrimAge strongly predicts lifespan and healthspan. Aging-Us. 2019;11(2):303–27. Bell CG, Lowe R, Adams PD, Baccarelli AA, Beck S, Bell JT, Christensen BC, Gladyshev VN, Heijmans BT, Horvath S et al. DNA methylation aging clocks: challenges and recommendations. Genome Biol 2019, 20(1). Dor Y, Cedar H. Principles of DNA methylation and their implications for biology and medicine. Lancet. 2018;392(10149):777–86. Cortese R. Epigenetic Alterations and Accelerated Biological Aging Associated With Impaired Ovarian Capacity in a Murine Model of OSA. Am J Respir Crit Care Med 2023, 207. Kheirandish-Gozal L, Khalyfa A, Gozal D, Bhattacharjee R, Wang Y. Endothelial Dysfunction in Children With Obstructive Sleep Apnea Is Associated With Epigenetic Changes in the < i > eNOS Gene. Chest. 2013;143(4):971–7. Cortese R, Sanz-Rubio D, Kheirandish-Gozal L, Marin JM, Gozal D. Epigenetic age acceleration in obstructive sleep apnoea is reversible with adherent treatment. Eur Respir J 2022, 59(4). Badran M, Puech C, Khalyfa A, Cortese R, Cataldo K, Qiao ZH, Gozal D. Senolytic-facilitated Reversal of End-Organ Dysfunction in a Murine Model of Obstructive Sleep Apnea. Am J Respir Crit Care Med. 2024;209(8):1001–12. Wang ZH, Liu Y, Zhang SX, Yuan YB, Chen SL, Li WH, Zuo MR, Xiang YF, Li TF, Yang WC et al. Effects of iron homeostasis on epigenetic age acceleration: a two-sample Mendelian randomization study. Clin Epigenetics 2023, 15(1). Smith GD, Ebrahim S. Mendelian randomization': can genetic epidemiology contribute to understanding environmental determinants of disease? Int J Epidemiol. 2003;32(1):1–22. McCartney DL, Min JEL, Richmond RC, Lu AT, Sobczyk MK, Davies G, Broer L, Guo XQ, Jeong A, Jung JS et al. Genome-wide association studies identify 137 genetic loci for DNA methylation biomarkers of aging. Genome Biol 2021, 22(1). Tian SY, Liao XY, Chen SQ, Wu Y, Chen M. Genetic association of the gut microbiota with epigenetic clocks mediated by inflammatory cytokines: a Mendelian randomization analysis. Front Immunol 2024, 15. Bahls M, Leitzmann MF, Karch A, Teumer A, Dörr M, Felix SB, Meisinger C, Baumeister SE, Baurecht H. Physical activity, sedentary behavior and risk of coronary artery disease, myocardial infarction and ischemic stroke: a two-sample Mendelian randomization study. Clin Res Cardiol. 2021;110(10):1564–73. Lin BY, Mu YZ, Ding ZX. Assessing the Causal Association between Biological Aging Biomarkers and the Development of Cerebral Small Vessel Disease: A Mendelian Randomization Study. Biology-Basel 2023, 12(5). Rosoff D, Yoo J, Bell A, Mavromatis L, Jung J, Wagner J, Lohoff F. A Multivariable Mendelian Randomization Study Disentangling the Relationships Between Neuropsychiatric Disorders, Substance Use Behaviors, and Longevity. Biol Psychiatry. 2022;91(9):S94–94. Li JX, Wang WR, Yang ZY, Qiu LJ, Ren Y, Wang DL, Li MJ, Li WJ, Gao F, Zhang J. Causal association of obesity with epigenetic aging and telomere length: a bidirectional mendelian randomization study. Lipids Health Dis 2024, 23(1). Xu WC, Zhang FJ, Shi YZ, Chen YZ, Shi B, Yu GC. Causal association of epigenetic aging and COVID-19 severity and susceptibility: A bidirectional Mendelian randomization study. Front Med 2022, 9. Burgess S, Dudbridge F, Thompson SG. Combining information on multiple instrumental variables in Mendelian randomization: comparison of allele score and summarized data methods. Stat Med. 2016;35(11):1880–906. Bowden J, Smith GD, Haycock PC, Burgess S. Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator. Genet Epidemiol. 2016;40(4):304–14. Burgess S, Thompson SG. Interpreting findings from Mendelian randomization using the MR-Egger methodvol 32, pg 377, (2017). European Journal of Epidemiology 2017, 32(5):391–392. Del Greco MF, Minelli C, Sheehanc NA, Thompsonc JR. Detecting pleiotropy in Mendelian randomisation studies with summary data and a continuous outcome. Stat Med. 2015;34(21):2926–40. Verbanck M, Chen CY, Neale B, Do R. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases (50, 693, 2018). Nat Genet. 2018;50(8):1196–1196. Verbanck M, Chen CY, Neale B, Do R. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases. Nat Genet. 2018;50(5):693–. Marin JM, Artal J, Martin T, Carrizo SJ, Andres M, Martin-Burriel I, Bolea R, Sanz A, Varona L, Godino J et al. Epigenetics modifications and Subclinical Atherosclerosis in Obstructive Sleep Apnea: The EPIOSA study. BMC Pulm Med 2014, 14. Wang AYM. Sleep-Disordered Breathing and Resistant Hypertension. Semin Nephrol. 2014;34(5):520–31. Quercioli A, Mach F, Montecucco F. Inflammation accelerates atherosclerotic processes in obstructive sleep apnea syndrome (OSAS). Sleep Breath. 2010;14(3):261–9. Fleming WE, Ferouz-Colborn A, Samoszuk MK, Azad A, Lu JJ, Riley JS, Cruz AB, Podolak S, Clark DJ, Bray KR, et al. Blood biomarkers of endocrine, immune, inflammatory, and metabolic systems in obstructive sleep apnea. Clin Biochem. 2016;49(12):854–61. Orrù G, Storari M, Scano A, Piras V, Taibi R, Viscuso D. Obstructive Sleep Apnea, oxidative stress, inflammation and endothelial dysfunction-An overview of predictive laboratory biomarkers. Eur Rev Med Pharmacol Sci. 2020;24(12):6939–48. Lavie L, Lavie P. Molecular mechanisms of cardiovascular disease in OSAHS: the oxidative stress link. Eur Respir J. 2009;33(6):1467–84. Horvath S, Raj K. DNA methylation-based biomarkers and the epigenetic clock theory of ageing. Nat Rev Genet. 2018;19(6):371–84. Quach A, Levine ME, Tanaka T, Lu AT, Chen BH, Ferrucci L, Ritz B, Bandinelli S, Neuhouser ML, Beasley JM, et al. Epigenetic clock analysis of diet, exercise, education, and lifestyle factors. Aging-Us. 2017;9(2):419–46. Noroozi R, Ghafouri-Fard S, Pisarek A, Rudnicka J, Spólnicka M, Branicki W, Taheri M, Pospiech E. DNA methylation-based age clocks: From age prediction to age reversion. Ageing Res Rev 2021, 68. Li XY, Joehanes R, Hoeschele I, Rich SS, Rotter JI, Levy D, Liu YM, Redline S, Sofer T. Association between sleep disordered breathing and epigenetic age acceleration: Evidence from the Multi-Ethnic Study of Atherosclerosis. Ebiomedicine. 2019;50:387–94. Reale A, Tagliatesta S, Zardo G, Zampieri M. Counteracting aged DNA methylation states to combat ageing and age-related diseases. Mech Ageing Dev 2022, 206. Chen WJ, Liaw SF, Lin CC, Chiu CH, Lin MW, Chang FT. Effect of Nasal CPAP on SIRT1 and Endothelial Function in Obstructive Sleep Apnea Syndrome. Lung. 2015;193(6):1037–45. Lin CC, Wang HY, Chiu CH, Liaw SF. Effect of oral appliance on endothelial function in sleep apnea. Clin Oral Invest. 2015;19(2):437–44. Fadaei R, Koushki M, Sharafkhaneh A, Moradi N, Ahmadi R, Rostampour M, Khazaie H. The impact of continuous positive airway pressure therapy on circulating levels of malondialdehyde: a systematic review and meta-analysis. Sleep Med. 2020;75:27–36. Chen Q, Chen LD, Chen MX, Wu YH, Zeng HX, Hu MF, Zhang WL, Zheng YF, Lin QC. The effect of continuous positive airway pressure on circulating malondialdehyde among obstructive sleep apnea patients: a meta-analysis. Sleep Breath. 2020;24(4):1407–15. Barros D, García-Río F. Obstructive sleep apnea and dyslipidemia: from animal models to clinical evidence. Sleep 2019, 42(3). Alonso-Fernández A, García-Río F, Arias MA, Hernanz A, de la Peña M, Piérola J, Barceló A, López-Collazo E, Agustí A. Effects of CPAP on oxidative stress and nitrate efficiency in sleep apnoea: a randomised trial. Thorax. 2009;64(7):581–6. Khalyfa A, Marin JM, Qiao ZH, Rubio DS, Kheirandish-Gozal L, Gozal D. Plasma exosomes in OSA patients promote endothelial senescence: effect of long-term adherent continuous positive airway pressure. Sleep 2020, 43(2). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-5305378\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":372511081,\"identity\":\"6f14c9af-df55-4d7a-b42a-fea119436a97\",\"order_by\":0,\"name\":\"Chenyi Xu\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Shanghai Stomatological Hospital\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Chenyi\",\"middleName\":\"\",\"lastName\":\"Xu\",\"suffix\":\"\"},{\"id\":372511083,\"identity\":\"469f8a70-088b-4a5e-972f-71d4304fbff2\",\"order_by\":1,\"name\":\"Gang Yang\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Shanghai Stomatological Hospital\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Gang\",\"middleName\":\"\",\"lastName\":\"Yang\",\"suffix\":\"\"},{\"id\":372511085,\"identity\":\"b4196cd7-d517-4fdd-874c-70536865e459\",\"order_by\":2,\"name\":\"Yuehua Liu\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6UlEQVRIiWNgGAWjYBACPmYwdYCBgb3xAQMPmJOAXwsbXAvPYQMitTDAtEgkE6uFncdMmqfiTmL/zMdsEm9q7jDws+cYMPzcgc9hIC1nniXOuJ3MJjnn2DMGyZ43Boy9Zwho4W07nNhwO/+YNA/bYQaDGzkGzIxthLT8O5w4/+ZhNmmef4cZ7InT0nA4ccMNZjaQdQwGEgS1sBVbzjl22HjjmWRmy7l9h3kkzjwrONiLRws//+GNN97UHJadd/ww44033w7L8bcnb3zwE48WIGCRQOaBo+YAXg0MDMwfCCgYBaNgFIyCkQ4AQUxMbal3QZkAAAAASUVORK5CYII=\",\"orcid\":\"\",\"institution\":\"Shanghai Stomatological Hospital\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Yuehua\",\"middleName\":\"\",\"lastName\":\"Liu\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2024-10-21 14:38:31\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-5305378/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-5305378/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":68755853,\"identity\":\"aa79ff75-9407-40b8-b785-5271f296956b\",\"added_by\":\"auto\",\"created_at\":\"2024-11-11 16:58:58\",\"extension\":\"jpg\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":188071,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eLegend not included with this version\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image3.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5305378/v1/fd128ea7f6170f3e970d12da.jpg\"},{\"id\":68755852,\"identity\":\"48c9235a-bbeb-41d3-b6b7-24051fd553de\",\"added_by\":\"auto\",\"created_at\":\"2024-11-11 16:58:58\",\"extension\":\"jpg\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":193763,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eLegend not included with this version\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image4.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5305378/v1/a84092e29e05d851061ee02a.jpg\"},{\"id\":68755854,\"identity\":\"347eb56a-3ba1-441d-a2f0-e82653ae9ad3\",\"added_by\":\"auto\",\"created_at\":\"2024-11-11 16:58:58\",\"extension\":\"jpg\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":194096,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eLegend not included with this version\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image5.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5305378/v1/8e28de64e0444daa73446a5b.jpg\"},{\"id\":68756270,\"identity\":\"b9fa19b0-aa09-40c3-9c06-2866745ffca0\",\"added_by\":\"auto\",\"created_at\":\"2024-11-11 17:06:58\",\"extension\":\"jpg\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":188889,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eLegend not included with this version\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image6.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5305378/v1/a36199618bcb980cd8077c5f.jpg\"},{\"id\":68755855,\"identity\":\"e743b1f4-93dd-4658-a3a2-f3372a5840f8\",\"added_by\":\"auto\",\"created_at\":\"2024-11-11 16:58:58\",\"extension\":\"jpg\",\"order_by\":5,\"title\":\"Figure 5\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":213477,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eLegend not included with this version\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image7.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5305378/v1/d6b5da51a78e3d5b49ad3d0b.jpg\"},{\"id\":68755857,\"identity\":\"6be0cfa4-aaf2-45b8-939f-a616b099c366\",\"added_by\":\"auto\",\"created_at\":\"2024-11-11 16:58:58\",\"extension\":\"jpg\",\"order_by\":6,\"title\":\"Figure 6\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":200079,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eLegend not included with this version\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image8.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5305378/v1/8f04f7ebcc851f6acbefb768.jpg\"},{\"id\":69602864,\"identity\":\"c0434b75-7d9b-4a74-92e7-eff674360af5\",\"added_by\":\"auto\",\"created_at\":\"2024-11-22 06:32:25\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":1615689,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5305378/v1/3e3403e1-82af-4ba9-887c-d922140fe13a.pdf\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Epigenetic Aging and Risk of Obstructive Sleep Apnea: a bidirectional Mendelian randomization study\",\"fulltext\":[{\"header\":\"Introduction\",\"content\":\"\\u003cp\\u003eObstructive sleep apnea (OSA) is a major public health concern affecting millions globally[\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e]. Characterized by repeated episodes of partial or complete upper airway obstruction during sleep[\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e], OSA is associated with adverse cardiovascular outcomes and metabolic disturbances[\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e]. The condition leads to intermittent hypoxia, oxidative stress, and systemic inflammation[\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e], which are critical pathways contributing to cardiovascular and metabolic morbidities.[\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e] Additionally, chronic sleep fragmentation caused by OSA has been shown to induce endothelial dysfunction and vascular aging in both clinical and experimental settings[\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eRecent studies suggest a potential link between biological aging and sleep apnea[\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e], but the directionality and causality of this relationship remain unclear. Epigenetic clocks, which measure DNA methylation levels at specific loci, provide a quantifiable estimate of biological age[\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e]. These clocks, including HannumAge, HorvathAge, PhenoAge, and GrimAge[\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e], have demonstrated predictive power for various age-related diseases[\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e]. Epigenetic age acceleration (EAA) indicates that an individual's biological age is greater than their chronological age[\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e], which may predispose them to age-related conditions such as OSA.\\u003c/p\\u003e \\u003cp\\u003ePrevious research has highlighted that individuals with OSA exhibit accelerated epigenetic aging, as shown by increased DNA methylation age compared to their chronological age[\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e]. Moreover, effective treatment with continuous positive airway pressure (CPAP) has been found to partially reverse this acceleration, suggesting a dynamic interaction between sleep apnea and biological aging processes[\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e]. These findings underscore the need for a deeper understanding of the mechanistic links between OSA and epigenetic aging[\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eIn this study, we aim to explore the direct causal relationship between OSA and epigenetic aging using Mendelian randomization[\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e]. By leveraging genetic variants associated with epigenetic aging and OSA, we seek to elucidate whether accelerated epigenetic aging contributes to the development of OSA or if OSA itself leads to changes in biological age[\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e]. This approach will help clarify the directionality and provide insights into potential therapeutic targets for mitigating the adverse effects of OSA on aging and overall health.\\u003c/p\\u003e \"},{\"header\":\"Methods\",\"content\":\"\\u003cp\\u003eStudy Design\\u003c/p\\u003e\\u003cp\\u003eThis bidirectional two-sample MR study leveraged genetic variants as instrumental variables (IVs) to examine the causal relationship between epigenetic aging and sleep apnea. The key assumptions of MR include relevance (IVs are associated with exposure), independence (IVs are not associated with confounders), and exclusion restriction (IVs influence the outcome solely through exposure).\\u003c/p\\u003e\\u003cp\\u003e\\u003cimg src=\\\"https://myfiles.space/user_files/127393_c7e80a1c9bb65875/127393_custom_files/img1731344004.png\\\"\\u003e\\u003cbr\\u003e\\u003c/p\\u003e\\u003cp\\u003eData Sources\\u003c/p\\u003e\\u003cp\\u003eWe obtained summary-level GWAS data on epigenetic aging markers (GrimAge, HannumAge, HorvathAge and PhenoAge) from the Edinburgh DataShare and sleep apnea from the FinnGen biobank[\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e]. The epigenetic aging data encompassed 34,710 individuals, while the sleep apnea dataset included 16,761 cases and 201,194 controls of European descent. This study used in the raw data has been approved by the ethics committee, all participants have been formally provide consent. (Table\\u0026nbsp;1)\\u003c/p\\u003e\\u003cp\\u003e\\u003cimg src=\\\"https://myfiles.space/user_files/127393_c7e80a1c9bb65875/127393_custom_files/img1731344135.png\\\"\\u003e\\u003cbr\\u003e\\u003c/p\\u003e\\u003cp\\u003eSelection of Genetic Instrumental Variables\\u003c/p\\u003e\\u003cp\\u003eCriteria for Selecting Instrumental Variables:(1)SNPs that are significantly associated with epigenetic aging (HannumAge, HorvathAge, PhenoAge, and GrimAge) across the entire genome (P \\u0026lt; 1×10^-5)[\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e].(2)SNPs are selected by setting the linkage disequilibrium parameter (r²) threshold at 0.001 and a genetic distance of 10,000 base pairs to eliminate the influence of linkage disequilibrium on the results[\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e].(3)Palindromic SNPs are removed. If SNPs associated with exposure are not present in the outcome data, appropriate proxy SNPs (r²\\u0026gt;0.8) are sought and selected[\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e].(4)Remaining SNPs are verified for associated phenotypes in the Human Genotype-Phenotype Association Database to exclude SNPs associated with other phenotypes that correlate with the four types of benign biliary diseases[\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e]. The selected instrumental variables must meet the three main assumptions: relevance, exclusivity, and independence[\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e]. To meet MR assumptions, we applied strict criteria to ensure SNPs were not linked to confounders or other outcomes. SNPs exhibiting linkage disequilibrium were excluded[\\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e].\\u003c/p\\u003e\\u003ch2\\u003eStatistical Analysis\\u003c/h2\\u003e\\u003cp\\u003eFive commonly used Mendelian randomization methods were employed: inverse-variance weighting (IVW), MR-Egger regression, weighted median, simple mode, and weighted mode[\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e]. The IVW method, which uses the inverse of the outcome variance as the weight for fitting, is noted for its accurate estimation even in the presence of heterogeneity[\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e]. If the genetic variants selected as instrumental variables are effective, IVW can produce unbiased estimates. Therefore, IVW was chosen as the primary analysis method[\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e]. To enhance the reliability of the findings, additional analyses were conducted using MR-Egger regression, weighted median, simple mode, and weighted mode methods[\\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e].\\u003c/p\\u003e\\u003cp\\u003eHeterogeneity, pleiotropy, and sensitivity assessment\\u003c/p\\u003e\\u003cp\\u003eHorizontal pleiotropy was assessed using MR-Egger regression and MR-PRESSO tests. In MR-Egger regression, the intercept term represents the average pleiotropy of the instrumental variables, with a P-value greater than 0.05 indicating no significant horizontal pleiotropy[\\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e]. When horizontal pleiotropy is detected, the MR-PRESSO outlier test is applied to further validate the results, correcting for pleiotropy and improving the accuracy of causal inferences[\\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e]. Heterogeneity of the results was examined using Cochran's Q test, and a leave-one-out analysis was conducted to check the sensitivity of individual SNPs and identify any significant outliers[\\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e].\\u003c/p\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cp\\u003eOur analysis indicated that GrimAge HannumAge, HorvathAge and PhenoAge were not significantly associated with an increased risk of sleep apnea. Specifically, the odds ratios (ORs) for these four acceleration markers did not show a robust positive association with sleep apnea risk. (Obverse:GrimAge\\u0026thinsp;=\\u0026thinsp;4, P\\u0026thinsp;=\\u0026thinsp;0.146 ;HannumAge\\u0026thinsp;=\\u0026thinsp;9, P\\u0026thinsp;=\\u0026thinsp;0.725;HorvathAge\\u0026thinsp;=\\u0026thinsp;24, P\\u0026thinsp;=\\u0026thinsp;0.025; PhenoAge\\u0026thinsp;=\\u0026thinsp;11, P\\u0026thinsp;=\\u0026thinsp;0.888) (Reverse:GrimAge\\u0026thinsp;=\\u0026thinsp;18, F\\u0026thinsp;=\\u0026thinsp;0.421;HannumAge\\u0026thinsp;=\\u0026thinsp;18, F\\u0026thinsp;=\\u0026thinsp;0.426;HorvathAge\\u0026thinsp;=\\u0026thinsp;19, P\\u0026thinsp;=\\u0026thinsp;0.360; PhenoAge\\u0026thinsp;=\\u0026thinsp;19, P\\u0026thinsp;=\\u0026thinsp;0.144)\\u003c/p\\u003e \\u003cp\\u003eThese findings were consistent across various MR methods, indicating no causal relationship in either direction between epigenetic aging and obstructive sleep apnea. (Fig.\\u0026nbsp;1\\u0026ndash;6)\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eQuality Control Assessment\\u003c/p\\u003e \\u003cp\\u003eThe robustness of our results was confirmed through extensive quality control measures. Cochran's Q test and I\\u0026sup2; statistics indicated minimal heterogeneity. The MR-Egger intercept and MR-PRESSO Global test suggested no horizontal pleiotropy. Sensitivity analyses affirmed that the results were not driven by any single SNP. (Table\\u0026nbsp;2) \\u003c/p\\u003e\\u003cp\\u003e\\u003cimg src=\\\"https://myfiles.space/user_files/127393_c7e80a1c9bb65875/127393_custom_files/img1731344196.png\\\"\\u003e\\u003cbr\\u003e\\u003c/p\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eThe observational study findings align with the growing body of literature identifying obstructive sleep apnea (OSA) as a significant contributor to systemic inflammation and oxidative stress, thereby accelerating the epigenetic clock measurement of biological aging processes[\\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e]. OSA leads to repeated episodes of hypoxia and reoxygenation, creating a state of chronic intermittent hypoxia[\\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e]. This condition triggers systemic inflammatory pathways and oxidative stress, both closely linked to aging and various age-related diseases[\\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e]. Research shows that individuals with OSA exhibit elevated levels of inflammatory markers such as C-reactive protein (CRP), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α)[\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e]. Oxidative stress in OSA patients is marked by increased production of reactive oxygen species (ROS) and reduced activity of antioxidant enzymes, leading to cellular and molecular damage that contributes to aging[\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eThe concept of epigenetic clocks, particularly DNA methylation clocks, has become a valuable tool for assessing biological age and age acceleration[\\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e41\\u003c/span\\u003e]. In individuals with OSA, these clocks often indicate accelerated aging[\\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e]. Studies have shown that patients with OSA have higher epigenetic age acceleration compared to healthy controls, suggesting that the biological age of OSA patients is older than their chronological age[\\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e]. This epigenetic aging is believed to result from the cumulative effects of oxidative stress and systemic inflammation[\\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e43\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eContinuous positive airway pressure (CPAP) therapy is the standard treatment for OSA and has been shown to mitigate many of the negative effects associated with the condition[\\u003cspan citationid=\\\"CR45\\\" class=\\\"CitationRef\\\"\\u003e45\\u003c/span\\u003e]. CPAP therapy works by keeping the airway open during sleep, thereby preventing episodes of hypoxia and reducing the frequency of arousals[\\u003cspan citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e46\\u003c/span\\u003e]. This intervention not only improves sleep quality but also has significant impacts on systemic health[\\u003cspan citationid=\\\"CR47\\\" class=\\\"CitationRef\\\"\\u003e47\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR48\\\" class=\\\"CitationRef\\\"\\u003e48\\u003c/span\\u003e]. The study highlights that adherent CPAP treatment can decelerate the epigenetic aging process, demonstrating a reversal of the accelerated epigenetic age observed in OSA patients[\\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e49\\u003c/span\\u003e]. This reversal underscores the potential therapeutic benefits of CPAP in reducing age-related health risks[\\u003cspan citationid=\\\"CR50\\\" class=\\\"CitationRef\\\"\\u003e50\\u003c/span\\u003e].The findings of the study suggest that early and consistent treatment of OSA with CPAP can have profound effects on biological aging, potentially reducing the risk of age-related diseases such as cardiovascular disease, neurodegenerative conditions, and metabolic disorders[\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR51\\\" class=\\\"CitationRef\\\"\\u003e51\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eHowever, our MR analysis suggests a contrary view, indicating that there is no causal relationship between OSA and epigenetic age acceleration. This difference may have several reasons: observational studies, despite controlling for many confounding factors, may still be affected by residual confounding factors, such as lifestyle factors or other complications. Differences in population characteristics and sample sizes between observational and MR studies may have contributed to the different results. MR studies rely on genetic variants and thus require large sample sizes to detect small effects, which may not be possible with small observational cohorts. Nonetheless, this observational study provides real-world evidence of the relationship between OSA and epigenetic aging, including detailed phenotypic data and longitudinal follow-up. The use of CPAP treatment data provides insight into the potential reversibility of epigenetic changes. Despite these Mendelian randomization results, the biological plausibility that OSA affects epigenetic aging cannot be completely ruled out. OSA-induced hypoxia and sleep fragmentation are known to activate stress pathways and inflammatory processes, thereby affecting DNA methylation patterns. The accelerated reversal of epigenetic age observed with CPAP treatment supports the hypothesis that effective management of OSA can mitigate its biological impact on the aging process. Future research on epigenetic aging and its relationship with sleep apnea should focus on the molecular mechanisms, specifically on intermediate pathways and potential indirect effects.\\u003c/p\\u003e \\u003cp\\u003eOur study has several unavoidable limitations. Firstly, the GWAS data we used are from individuals of European descent, which may limit the generalizability of our findings to other ethnic groups. Secondly, due to the lack of suitable public datasets, we were unable to perform a stratified analysis of the progression and severity of obstructive sleep apnea (OSA). Additionally, the summary-level statistics lack individual-level data, preventing us from stratifying the study population by important factors such as age or sex. Lastly, there may be sample overlap between the exposure and outcome datasets, which could affect the results.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003eEthics approval and consent to participate\\u003c/p\\u003e\\n\\u003cp\\u003eThe study made use of the large publicly accessible GWAS database, which had received the necessary approvals from relevant ethical review boards and participants.\\u003c/p\\u003e\\n\\u003cp\\u003eConsent for publication\\u003c/p\\u003e\\n\\u003cp\\u003eAll data used in this study were obtained from publicly available GWAS databases, with all participants having signed informed consent forms.\\u003c/p\\u003e\\n\\u003cp\\u003eAvailability of data and materials\\u003c/p\\u003e\\n\\u003cp\\u003eThis study did not generate any original data. The datasets utilized in this research are accessible to the public: the Edinburgh DataShare for GWAS of epigenetic clocks (https://datashare.ed.ac.uk/handle/10283/3645) and the FinnGen biobank for GWAS of OSA (phenocode: G6_SLEEPAPNO, https://www.finngen.fi/en/access_results).\\u003c/p\\u003e\\n\\u003cp\\u003eCompeting interests\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors have stated that they have no commercial or financial conflicts of interest related to this work.\\u003c/p\\u003e\\n\\u003cp\\u003eFunding\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;This research was supported by Clinical Research Plan of Shanghai Shenkang Hospital Development Centre: A prospective randomized controlled trial comparing orthodontic treatment with tonsillectomy and adenoidectomy in children with moderate OSAHS(No.SHDC2020CR2043B).\\u003c/p\\u003e\\n\\u003cp\\u003eAuthors\\u0026rsquo; contributions\\u003c/p\\u003e\\n\\u003cp\\u003eAll authors have read and approved the submission of the manuscript. YL presented research questions. CX and GY participated in the original draft of the manuscript and the literature search. CX contributed to the data retrieval, statistical analysis, and visualization of results. CX and GY were involved in the interpretation of the results.\\u003c/p\\u003e\\n\\u003cp\\u003eAcknowledgements\\u003c/p\\u003e\\n\\u003cp\\u003eThis study leveraged data from the Edinburgh DataShare and the FinnGen Project Database. We express our heartfelt gratitude to all participants and researchers for their significant contributions in making these datasets accessible and publicly available.\\u003c/p\\u003e\\n\\u003cp\\u003eClinical trial number: not applicable.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eBenjafield AV, Ayas NT, Eastwood PR, Heinzer R, Ip MSM, Morrell MJ, Nunez CM, Patel SR, Penzel T, P\\u0026eacute;pin JLD, et al. Estimation of the global prevalence and burden of obstructive sleep apnoea: a literature-based analysis. Lancet Respiratory Med. 2019;7(8):687\\u0026ndash;98.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSenaratna CV, Perret JL, Lodge CJ, Lowe AJ, Campbell BE, Matheson MC, Hamilton GS, Dharmage SC. Prevalence of obstructive sleep apnea in the general population: A systematic review. Sleep Med Rev. 2017;34:70\\u0026ndash;81.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMazzotti DR, Keenan BT, Lim DC, Gottlieb DJ, Kim J, Pack AI. Symptom Subtypes of Obstructive Sleep Apnea Predict Incidence of Cardiovascular Outcomes. Am J Respir Crit Care Med. 2019;200(4):493\\u0026ndash;506.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eVoulgaris A, Archontogeorgis K, Papanas N, Pilitsi E, Nena E, Xanthoudaki M, Mikhailidis DP, Froudarakis ME, Steiropoulos P. Increased risk for cardiovascular disease in patients with obstructive sleep apnoea syndrome-chronic obstructive pulmonary disease (overlap syndrome). Clin Respiratory J. 2019;13(11):708\\u0026ndash;15.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eAtkeson A, Jelic S. Mechanisms of endothelial dysfunction in obstructive sleep apnea. Vasc Health Risk Manag. 2008;4(6):1327\\u0026ndash;35.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGozal D, Kheirandish-Gozal L. Cardiovascular morbidity in obstructive sleep apnea - Oxidative stress, inflammation, and much more. Am J Respir Crit Care Med. 2008;177(4):369\\u0026ndash;75.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCarreras A, Zhang SX, Peris E, Qiao ZH, Gileles-Hillel A, Li RC, Wang Y, Gozal D. Chronic Sleep Fragmentation Induces Endothelial Dysfunction and Structural Vascular Changes in Mice. Sleep. 2014;37(11):1817\\u0026ndash;24.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eAbd Elghany OSA, Elessawy AF, Elkhashab KA, Elebiary AM, Ebeid HM. Correlation between obstructive sleep apnea and ventricular function: a cross-sectional hospital-based study. Acta Cardiol. 2023;78(7):805\\u0026ndash;12.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGaspar LS, Alvaro AR, Moita J, Cavadas C. Obstructive Sleep Apnea and Hallmarks of Aging. Trends Mol Med. 2017;23(8):675\\u0026ndash;92.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHannum G, Guinney J, Zhao L, Zhang L, Hughes G, Sadda S, Klotzle B, Bibikova M, Fan JB, Gao Y, et al. Genome-wide Methylation Profiles Reveal Quantitative Views of Human Aging Rates. Mol Cell. 2013;49(2):359\\u0026ndash;67.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eIzadi M, Sadri N, Abdi A, Serajian S, Jalalei D, Tahmasebi S. Epigenetic biomarkers in aging and longevity: Current and future application. Life Sci 2024, 351.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLu AT, Quach A, Wilson JG, Reiner AP, Aviv A, Raj K, Hou LF, Baccarelli AA, Li Y, Stewart JD, et al. DNA methylation GrimAge strongly predicts lifespan and healthspan. Aging-Us. 2019;11(2):303\\u0026ndash;27.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBell CG, Lowe R, Adams PD, Baccarelli AA, Beck S, Bell JT, Christensen BC, Gladyshev VN, Heijmans BT, Horvath S et al. DNA methylation aging clocks: challenges and recommendations. Genome Biol 2019, 20(1).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eDor Y, Cedar H. Principles of DNA methylation and their implications for biology and medicine. Lancet. 2018;392(10149):777\\u0026ndash;86.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCortese R. Epigenetic Alterations and Accelerated Biological Aging Associated With Impaired Ovarian Capacity in a Murine Model of OSA. Am J Respir Crit Care Med 2023, 207.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKheirandish-Gozal L, Khalyfa A, Gozal D, Bhattacharjee R, Wang Y. Endothelial Dysfunction in Children With Obstructive Sleep Apnea Is Associated With Epigenetic Changes in the \\u0026lt;\\u0026thinsp;i\\u0026thinsp;\\u0026gt;\\u0026thinsp;eNOS\\u0026thinsp;Gene. Chest. 2013;143(4):971\\u0026ndash;7.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCortese R, Sanz-Rubio D, Kheirandish-Gozal L, Marin JM, Gozal D. Epigenetic age acceleration in obstructive sleep apnoea is reversible with adherent treatment. Eur Respir J 2022, 59(4).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBadran M, Puech C, Khalyfa A, Cortese R, Cataldo K, Qiao ZH, Gozal D. Senolytic-facilitated Reversal of End-Organ Dysfunction in a Murine Model of Obstructive Sleep Apnea. Am J Respir Crit Care Med. 2024;209(8):1001\\u0026ndash;12.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWang ZH, Liu Y, Zhang SX, Yuan YB, Chen SL, Li WH, Zuo MR, Xiang YF, Li TF, Yang WC et al. Effects of iron homeostasis on epigenetic age acceleration: a two-sample Mendelian randomization study. Clin Epigenetics 2023, 15(1).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSmith GD, Ebrahim S. Mendelian randomization': can genetic epidemiology contribute to understanding environmental determinants of disease? Int J Epidemiol. 2003;32(1):1\\u0026ndash;22.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMcCartney DL, Min JEL, Richmond RC, Lu AT, Sobczyk MK, Davies G, Broer L, Guo XQ, Jeong A, Jung JS et al. Genome-wide association studies identify 137 genetic loci for DNA methylation biomarkers of aging. Genome Biol 2021, 22(1).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eTian SY, Liao XY, Chen SQ, Wu Y, Chen M. Genetic association of the gut microbiota with epigenetic clocks mediated by inflammatory cytokines: a Mendelian randomization analysis. Front Immunol 2024, 15.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBahls M, Leitzmann MF, Karch A, Teumer A, D\\u0026ouml;rr M, Felix SB, Meisinger C, Baumeister SE, Baurecht H. Physical activity, sedentary behavior and risk of coronary artery disease, myocardial infarction and ischemic stroke: a two-sample Mendelian randomization study. Clin Res Cardiol. 2021;110(10):1564\\u0026ndash;73.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLin BY, Mu YZ, Ding ZX. Assessing the Causal Association between Biological Aging Biomarkers and the Development of Cerebral Small Vessel Disease: A Mendelian Randomization Study. Biology-Basel 2023, 12(5).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eRosoff D, Yoo J, Bell A, Mavromatis L, Jung J, Wagner J, Lohoff F. A Multivariable Mendelian Randomization Study Disentangling the Relationships Between Neuropsychiatric Disorders, Substance Use Behaviors, and Longevity. Biol Psychiatry. 2022;91(9):S94\\u0026ndash;94.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLi JX, Wang WR, Yang ZY, Qiu LJ, Ren Y, Wang DL, Li MJ, Li WJ, Gao F, Zhang J. Causal association of obesity with epigenetic aging and telomere length: a bidirectional mendelian randomization study. Lipids Health Dis 2024, 23(1).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eXu WC, Zhang FJ, Shi YZ, Chen YZ, Shi B, Yu GC. Causal association of epigenetic aging and COVID-19 severity and susceptibility: A bidirectional Mendelian randomization study. Front Med 2022, 9.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBurgess S, Dudbridge F, Thompson SG. Combining information on multiple instrumental variables in Mendelian randomization: comparison of allele score and summarized data methods. Stat Med. 2016;35(11):1880\\u0026ndash;906.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBowden J, Smith GD, Haycock PC, Burgess S. Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator. Genet Epidemiol. 2016;40(4):304\\u0026ndash;14.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBurgess S, Thompson SG. Interpreting findings from Mendelian randomization using the MR-Egger methodvol 32, pg 377, (2017). \\u003cem\\u003eEuropean Journal of Epidemiology\\u003c/em\\u003e 2017, 32(5):391\\u0026ndash;392.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eDel Greco MF, Minelli C, Sheehanc NA, Thompsonc JR. Detecting pleiotropy in Mendelian randomisation studies with summary data and a continuous outcome. Stat Med. 2015;34(21):2926\\u0026ndash;40.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eVerbanck M, Chen CY, Neale B, Do R. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases (50, 693, 2018). Nat Genet. 2018;50(8):1196\\u0026ndash;1196.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eVerbanck M, Chen CY, Neale B, Do R. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases. Nat Genet. 2018;50(5):693\\u0026ndash;.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMarin JM, Artal J, Martin T, Carrizo SJ, Andres M, Martin-Burriel I, Bolea R, Sanz A, Varona L, Godino J et al. Epigenetics modifications and Subclinical Atherosclerosis in Obstructive Sleep Apnea: The EPIOSA study. BMC Pulm Med 2014, 14.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWang AYM. Sleep-Disordered Breathing and Resistant Hypertension. Semin Nephrol. 2014;34(5):520\\u0026ndash;31.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eQuercioli A, Mach F, Montecucco F. Inflammation accelerates atherosclerotic processes in obstructive sleep apnea syndrome (OSAS). Sleep Breath. 2010;14(3):261\\u0026ndash;9.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eFleming WE, Ferouz-Colborn A, Samoszuk MK, Azad A, Lu JJ, Riley JS, Cruz AB, Podolak S, Clark DJ, Bray KR, et al. Blood biomarkers of endocrine, immune, inflammatory, and metabolic systems in obstructive sleep apnea. Clin Biochem. 2016;49(12):854\\u0026ndash;61.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eOrr\\u0026ugrave; G, Storari M, Scano A, Piras V, Taibi R, Viscuso D. Obstructive Sleep Apnea, oxidative stress, inflammation and endothelial dysfunction-An overview of predictive laboratory biomarkers. Eur Rev Med Pharmacol Sci. 2020;24(12):6939\\u0026ndash;48.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLavie L, Lavie P. Molecular mechanisms of cardiovascular disease in OSAHS: the oxidative stress link. Eur Respir J. 2009;33(6):1467\\u0026ndash;84.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHorvath S, Raj K. DNA methylation-based biomarkers and the epigenetic clock theory of ageing. Nat Rev Genet. 2018;19(6):371\\u0026ndash;84.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eQuach A, Levine ME, Tanaka T, Lu AT, Chen BH, Ferrucci L, Ritz B, Bandinelli S, Neuhouser ML, Beasley JM, et al. Epigenetic clock analysis of diet, exercise, education, and lifestyle factors. Aging-Us. 2017;9(2):419\\u0026ndash;46.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eNoroozi R, Ghafouri-Fard S, Pisarek A, Rudnicka J, Sp\\u0026oacute;lnicka M, Branicki W, Taheri M, Pospiech E. DNA methylation-based age clocks: From age prediction to age reversion. Ageing Res Rev 2021, 68.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLi XY, Joehanes R, Hoeschele I, Rich SS, Rotter JI, Levy D, Liu YM, Redline S, Sofer T. Association between sleep disordered breathing and epigenetic age acceleration: Evidence from the Multi-Ethnic Study of Atherosclerosis. Ebiomedicine. 2019;50:387\\u0026ndash;94.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eReale A, Tagliatesta S, Zardo G, Zampieri M. Counteracting aged DNA methylation states to combat ageing and age-related diseases. Mech Ageing Dev 2022, 206.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eChen WJ, Liaw SF, Lin CC, Chiu CH, Lin MW, Chang FT. Effect of Nasal CPAP on SIRT1 and Endothelial Function in Obstructive Sleep Apnea Syndrome. Lung. 2015;193(6):1037\\u0026ndash;45.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLin CC, Wang HY, Chiu CH, Liaw SF. Effect of oral appliance on endothelial function in sleep apnea. Clin Oral Invest. 2015;19(2):437\\u0026ndash;44.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eFadaei R, Koushki M, Sharafkhaneh A, Moradi N, Ahmadi R, Rostampour M, Khazaie H. The impact of continuous positive airway pressure therapy on circulating levels of malondialdehyde: a systematic review and meta-analysis. Sleep Med. 2020;75:27\\u0026ndash;36.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eChen Q, Chen LD, Chen MX, Wu YH, Zeng HX, Hu MF, Zhang WL, Zheng YF, Lin QC. The effect of continuous positive airway pressure on circulating malondialdehyde among obstructive sleep apnea patients: a meta-analysis. Sleep Breath. 2020;24(4):1407\\u0026ndash;15.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBarros D, Garc\\u0026iacute;a-R\\u0026iacute;o F. Obstructive sleep apnea and dyslipidemia: from animal models to clinical evidence. Sleep 2019, 42(3).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eAlonso-Fern\\u0026aacute;ndez A, Garc\\u0026iacute;a-R\\u0026iacute;o F, Arias MA, Hernanz A, de la Pe\\u0026ntilde;a M, Pi\\u0026eacute;rola J, Barcel\\u0026oacute; A, L\\u0026oacute;pez-Collazo E, Agust\\u0026iacute; A. Effects of CPAP on oxidative stress and nitrate efficiency in sleep apnoea: a randomised trial. Thorax. 2009;64(7):581\\u0026ndash;6.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKhalyfa A, Marin JM, Qiao ZH, Rubio DS, Kheirandish-Gozal L, Gozal D. Plasma exosomes in OSA patients promote endothelial senescence: effect of long-term adherent continuous positive airway pressure. Sleep 2020, 43(2).\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":true,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true},\"keywords\":\"\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-5305378/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-5305378/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003ch2\\u003eBackground\\u003c/h2\\u003e \\u003cp\\u003eObstructive Sleep apnea (OSA) is a prevalent sleep disorder characterized by repetitive interruptions of breathing during sleep, significantly impacting cardiovascular and metabolic health. Epigenetic aging, measured via DNA methylation-based clocks, has emerged as a robust predictor of biological aging and associated health outcomes. This study investigates the causal relationship between epigenetic aging and the risk of sleep apnea using a bidirectional Mendelian randomization (MR) approach.\\u003c/p\\u003e\\u003ch2\\u003eMethods\\u003c/h2\\u003e \\u003cp\\u003eWe utilized genome-wide association study (GWAS) summary statistics for epigenetic aging markers (HannumAge, HorvathAge, PhenoAge, and GrimAge) and sleep apnea from FinnGen. Instrumental variables were selected based on stringent criteria to ensure validity. The causal association was assessed using inverse variance weighted (IVW), weighted median (WM), and MR-Egger methods. Sensitivity analyses, including heterogeneity and pleiotropy assessments, were conducted to validate the robustness of the findings.\\u003c/p\\u003e\\u003ch2\\u003eResults\\u003c/h2\\u003e \\u003cp\\u003eIn this study, using Mendelian randomization analysis, we investigated the relationship between epigenetic age acceleration markers HannumAge, HorvathAge, PhenoAge, and GrimAge, and the risk of obstructive sleep apnea (OSA). The results showed that these markers of epigenetic age acceleration were not significantly associated with an increased risk of OSA. Quality control assessments confirmed the reliability of our findings. Although previous literature suggests an association between epigenetic age acceleration and sleep apnea, our study did not support a causal relationship between the two. This finding provides a new perspective on the relationship between epigenetic age acceleration and OSA, highlighting the need for further research.\\u003c/p\\u003e\\u003ch2\\u003eConclusion\\u003c/h2\\u003e \\u003cp\\u003eThe current Mendelian randomization analysis revealed no causal relationship between epigenetic clocks and obstructive sleep apnea (OSA). However, the potential for a shared genetic architecture should be considered. Conducting a comorbidity genetic analysis may provide further insights into this relationship.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Epigenetic Aging and Risk of Obstructive Sleep Apnea: a bidirectional Mendelian randomization study\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2024-11-11 16:58:52\",\"doi\":\"10.21203/rs.3.rs-5305378/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"848059c2-835c-4632-882f-32e149e2f94f\",\"owner\":[],\"postedDate\":\"November 11th, 2024\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2024-11-22T06:24:15+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2024-11-11 16:58:52\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-5305378\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-5305378\",\"identity\":\"rs-5305378\",\"version\":[\"v1\"]},\"buildId\":\"qtupq5eGEP_6zYnWcrvyt\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}