Causal associations between sarcopenia-related traits and obstructive sleep apnea: A Mendelian randomization study

Causal associations between sarcopenia-related traits and obstructive sleep apnea: A 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 Causal associations between sarcopenia-related traits and obstructive sleep apnea: A Mendelian randomization study Huixian Sun, Xin Zeng, Wei Gao, Xiang Lu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4768091/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 08 Mar, 2025 Read the published version in Aging Clinical and Experimental Research → Version 1 posted 9 You are reading this latest preprint version Abstract Background Evidence for a causal relationship between sarcopenia and obstructive sleep apnea (OSA) is scarce. This study aimed to investigate the causal association between sarcopenia-related traits and OSA utilizing Mendelian randomization (MR) analyses. Methods MR analyses were conducted using genetic instruments for sarcopenia-related traits, including hand grip strength, muscle mass, fat mass, water mass, and physical performance. Data from large-scale genome-wide association studies (GWAS) were utilized to identify genetic variants associated with these traits. Causal associations with OSA were assessed using various MR methods, including the inverse variance-weighted (IVW) method, MR-Egger, and weighted median approaches. Pleiotropy and heterogeneity were evaluated through MR-PRESSO and other sensitivity analyses. Results Low hand grip strength in individuals aged 60 years and older exhibited a positive correlation with the risk of OSA (IVW, OR = 1.190, 95% CI = 1.003–1.413, p = 0.047), while no significant causal effects were observed for grip strength in the left and right hands. Muscle mass, fat mass, and water mass were significantly associated with OSA, even after adjusting for multiple testing. Notably, higher levels of body fat percentage, trunk fat percentage, and limb fat percentage were strongly correlated with increased risk of OSA. Physical performance indicators such as walking pace demonstrated an inverse association with OSA, while a higher risk of OSA was observed with increased log odds of falling risk and greater frequency of falls in the last year. Additionally, a causal effect was found between long-standing illness, disability, or infirmity and OSA. Conclusions This comprehensive MR analysis provides evidence supporting a causal relationship between sarcopenia-related traits, including hand grip strength, muscle mass, fat mass, and physical performance, and the risk of OSA. These findings underscore the importance of addressing sarcopenia-related factors in the management and prevention of OSA. Sarcopenia-related traits Obstructive sleep apnea Mendelian randomization Genetic analyses Figures Figure 1 Figure 2 Figure 3 Introduction Sarcopenia is a skeletal muscle-related disorder. Studies have indicated that people with sarcopenia are at a higher risk of falls, cardiovascular disease, and type 2 diabetes [ 1 ]. Muscle strength, muscle mass, and physical performance are the three main indicators for the diagnosis of sarcopenia. At least two of these parameters are included in the diagnostic process, but different definitions of sarcopenia lead to varying cut-off points and standards. Hand grip strength is an efficient and valid measure of muscle strength. Low grip strength suggests further muscle mass assessment and predicts a series of adverse outcomes[ 2 ]. Appendicular lean mass (ALM) refers to the total skeletal muscle mass of the four limbs and approximately reflects overall body muscle content[ 3 ]. In clinical practice, physical performance is used to grade the severity of sarcopenia after a positive diagnosis, with walking pace, an objective measure, being the most widely applied indicator[ 4 ]. Sarcopenia is both an independent condition and a systemic disease[ 5 , 6 ]. Consequently, an increasing number of studies have investigated sarcopenia-related adverse outcomes, including falls, frailty, reduced quality of life, and mortality. Obstructive sleep apnea (OSA) is a prevalent and hazardous syndrome. Statistically, nearly 1 billion adults aged 30–69 years worldwide may suffer from OSA[ 7 ]. The main characteristic of OSA is chronic intermittent hypoxia, which increases the risk of systemic diseases such as diabetes[ 8 , 9 ]. However, most patients are unaware of their affected breathing and the importance of seeking medical attention, leading to low diagnosis rates and increased healthcare costs[ 10 ]. Observational studies have suggested a detrimental relationship between sarcopenia and OSA, but the causality remains unclear[ 11 , 12 ]. Mendelian randomization (MR) is a robust epidemiological technique that utilizes genetic variants as instrumental variables (IVs) to control for potential confounding factors. This method is highly valued for its ability to mitigate the risk of reverse causation bias and enhance the reliability of causal inferences between exposures and clinical outcomes[ 13 ]. In this study, we aimed to identify the causal relationship between sarcopenia and OSA by MR analysis. Design and methods Study design Our study employed a two-sample MR approach to investigate the causal association between sarcopenia-related traits and OSA. An overview of the design presented in Fig. 1 . The genetic variants serving as IVs, known as single nucleotide polymorphisms (SNPs), must meet three essential criteria[ 14 ]: (1) they should strongly predict the exposures, (2) they should be exclusively associated with the outcome through the exposures, and (3) they should not be associated with any confounders that could influence the exposure-outcome relationship. Data sources We identified 26 indices associated with sarcopenia as exposures, categorized into three domains: muscular strength, body composition, and physical performance, in alignment with established expert consensus. In terms of muscular strength, our study focused on hand grip strength, a crucial indicator that encompasses measurements for both the left and right hands as well as the criteria for low hand grip strength set forth by the European Working Group on Sarcopenia in Older People (EWGSOP), classifying individuals aged 60 and older with values below 30 kg for males and 20 kg for females. In terms of body composition, sarcopenia is characterized by the loss of appendicular lean mass (ALM). However, ALM is not the sole determinant; the whole-body fat mass and water mass also exert significant influence on this condition. In light of this, our study selected whole-body mass, trunk mass, and extremities mass as key parameters. Additionally, we considered similar indicators such as limb, trunk, and whole-body fat percentages. Physical performance is an essential measure that reflects the integrated functionality of the entire body, rather than the function of an isolated organ. The usual walking pace stands out as a frequently utilized metric in this context. Our analysis also encompassed other relevant aspects such as the duration and frequency of walking activities, including the number of days walked for 10 + minutes and the frequency of walking for leisure in the past four weeks. Furthermore, we examined fall-related factors, encompassing both the risk of falls and the actual number of falls within the preceding year. We also took into account indicators of malnutrition and frailty, including the frailty index and the presence of chronic illnesses, disabilities, or infirmities. The above exposure datasets were obtained from the UK Biobank through the IEU Open GWAS project ( https://gwas.mrcieu.ac.uk/ ). We also utilized GWAS data for OSA from the IEU Open GWAS Project, which contained 13,818 cases and 463,035 controls, for the outcome dataset. Data sources, participant demographics, ethnic backgrounds, and the studies included in our analysis are concisely outlined in Supplementary Table 1. Selection of instrumental variables In accordance with the three core assumptions of MR analysis, independent single-nucleotide polymorphisms (SNPs) that demonstrated a strong association with the exposures ( p < 5×10^−8) were selected as IVs for most indices. However, for indices related to falling risk, falls in the last year, and malnutrition, a less stringent threshold was applied ( p < 5×10^−6). To mitigate linkage disequilibrium (LD) among the IVs, SNPs were clumped with a threshold set to r 2 < 0.001 and a physical distance of kb = 10,000 [ 15 ]. Subsequently, palindromic SNPs were excluded during the harmonization process. MR-PRESSO (Pleiotropy Residual Sum and Outlier) was then utilized to identify and remove outlier SNPs, thereby preventing horizontal pleiotropy. The IVs that were eliminated due to being outliers are presented in Supplementary Table 2. The comprehensive steps of the screening process are outlined in Supplementary Table 3. All IVs with F value > 10 was considered of a sufficient strength of instrument[ 16 ]. Statistical analysis The causal relationship between sarcopenia-related indicators and OSA was investigated using a range of MR methods, primarily implemented through the 'TwoSampleMR' package (version 0.5.6). These methods included inverse variance weighting (IVW), MR Egger, simple mode, weighted median, and weighted mode[ 17 , 18 ]. Heterogeneity among the selected IVs was assessed using Cochran’s Q statistic and its corresponding P -values. If the null hypothesis of homogeneity was rejected, indicating significant heterogeneity, a random effects IVW model was employed instead of the fixed-effects IVW model[ 19 ]. To address the potential impact of horizontal pleiotropy, the MR-Egger method was applied. A significant intercept term in the MR-Egger regression suggests the presence of horizontal pleiotropy. To further mitigate this, the MR pleiotropy residual sum and outlier (MR-PRESSO) method was utilized to identify and exclude outliers that could skew the estimation results[ 20 ]. This method is particularly effective in controlling for horizontal pleiotropy. Scatter plots and funnel plots were also employed as visual tools. Scatter plots were used to confirm that the results were not influenced by outliers, while funnel plots were examined to ensure the robustness of the observed correlations and the absence of heterogeneity. Results The Causal Association between Sarcopenia-Related Traits and OSA The P -values from MR analyses and those adjusted by MR-PRESSO are presented in Fig. 2 . The detailed results of the MR analyses, including the values for heterogeneity and pleiotropy tests, are shown in Supplementary Table 4. Figure 3 provides detailed information on the MR analyses, illustrating the causal associations between sarcopenia-related features and OSA. Scatter plots depicting the causal relationships between sarcopenia-related traits and OSA are visualized in Supplementary Figures A1-26. Forest plots showing the causal associations between sarcopenia-related traits and OSA are presented in Supplementary Figures B1-26. The leave-one-out analysis results for the causality of sarcopenia-related traits with OSA are visualized in Supplementary Figures C1-26. Funnel plots illustrating the causal associations between sarcopenia-related traits and OSA are shown in Supplementary Figures D1-26. Hand Grip Strength and OSA Among the three grip strength targets, low hand grip strength in individuals aged 60 years and older was positively correlated with the risk of OSA. The odds ratio (OR) was 1.190 [95% confidence interval (95% CI), 1.003–1.413; p = 0.047] using the IVW method after excluding outliers identified by the MR-PRESSO test (Fig. 2 ). The P -value for the Egger-intercept test was 0.807, indicating no pleiotropic bias in assessing the effect of low grip strength in older adults with the IVW method. Leave-one-out analysis confirmed that the causal relationship was not driven by any single SNP. No significant causal effects were observed between hand grip strength (left and right) and OSA (Fig. 3 ). Muscle Mass, Fat Mass, Water Mass, and OSA Associations between appendicular lean mass (ALM), whole-body mass, trunk mass, extremities mass, and various fat percentages (limbs, trunk, and whole-body) with OSA were observed before adjusting the p -values. These associations remained significant after adjustment: OSA and ALM (IVW, OR = 1.133, 95% CI = 1.050–1.222, p = 0.001) Whole-body water mass (IVW, OR = 1.786, 95% CI = 1.586–2.011, p = 9.70E-22) Whole-body fat mass (IVW, OR = 1.981, 95% CI = 1.791–2.190, p = 1.48E-40) Trunk fat mass (IVW, OR = 1.828, 95% CI = 1.653–2.021, p = 5.47E-32) Left arm fat mass (IVW, OR = 2.225, 95% CI = 2.029–2.439, p = 3.53E-65) Right arm fat mass (IVW, OR = 2.274, 95% CI = 2.080–2.485, p = 3.67E-73) Left leg fat mass (IVW, OR = 2.808, 95% CI = 2.476–3.183, p = 2.08E-58) Right leg fat mass (IVW, OR = 2.659, 95% CI = 2.356–3.002, p = 1.92E-56) Body fat percentage (IVW, OR = 2.163, 95% CI = 1.888–2.478, p = 9.01E-29) Trunk fat percentage (IVW, OR = 1.767, 95% CI = 1.572–1.986, p = 1.19E-21) Left arm fat percentage (IVW, OR = 2.440, 95% CI = 2.129–2.797, p = 1.44E-37) Right arm fat percentage (IVW, OR = 2.484, 95% CI = 2.155–2.864, p = 5.48E-36) Left leg fat percentage (IVW, OR = 2.866, 95% CI = 2.433–3.377, p = 2.54E-36) Right leg fat percentage (IVW, OR = 2.729, 95% CI = 2.297–3.241, p = 2.80E-30) The results from MR Egger and the Weighted Median method were largely consistent. Additionally, no significant horizontal pleiotropy was detected by the MR-Egger intercept test (Supplementary Table 4). Physical Performance and OSA Usual walking pace was inversely associated with OSA using the IVW method, with an OR value of 0.153 (95% CI, 0.092–0.256; p = 8.24 × 10⁻¹³). The MR-Egger test indicated no significant pleiotropy in these results ( p = 0.825). No causal associations were found between the duration of walks, the frequency of walking for pleasure in the last four weeks, the number of days per week walked for 10 + minutes, and OSA. A one-unit increase in the log odds of falling risk was associated with a 47% higher risk of OSA (OR, 1.469, 95% CI: 1.199-1.800, p < 0.001). More falls in the past year were related to a higher risk of OSA (OR, 4.972, 95% CI: 2.408–10.265, p < 0.001). A similar result was found between the frailty index and OSA (OR, 1.965, 95% CI: 1.312–2.942, p = 0.001). We found strong evidence supporting the causality of long-standing illness, disability, or infirmity on OSA (OR, 4.387, 95% CI: 1.657–11.612, p = 0.003). Additionally, the IVW, MR Egger, and Weighted Median results all suggested no causal effect of malnutrition on OSA. The results of sensitivity analyses are shown in Supplementary Table 4. Discussion To our knowledge, this is the first mendelian randomization study to systematically evaluate the causal relationships between sarcopenia-related traits and OSA in European population. Existing clinical studies have indicated that early-onset sarcopenia is more likely to occur in younger patients with OSA[ 21 ]. The sarcopenia index was negatively correlated with the odds ratio of sleep disorders. Maintaining optimal muscle mass may have a beneficial effect on OSA[ 22 ]. Our findings reveal that genetically determined low hand grip strength, falls, frailty, and disability are significantly associated with increased risks of OSA. Genetically predicted usual walking pace was negatively correlated with OSA, indicating that a lower walking speed increases the probability of suffering from sleep apnea. Additionally, muscle mass, fat mass, and water mass were positively related to OSA. However, we did not find a direct causal relationship between (left & right) hand grip strength, malnutrition, the duration and frequency of walking and OSA. Overall, the current MR results provide valuable insights into the impact of sarcopenia on OSA, highlighting the importance of considering skeletal muscle health in preventive and therapeutic strategies. Observational investigations have demonstrated a transdiagnostic relationship between sleep duration and hand grip strength as well as the potential use of hand grip strength as a marker in OSA[ 23 ]. It also strongly endorses the effect of grip strength on OSA in MR analysis, revealing a causal association between sarcopenia and OSA. A cross-sectional study of Korean adults aged 40 to 80 years showed that low OSA risk was found to be associated with high grip strength after adjusting for other sleep parameters and confounders[ 24 ]. Another cross-sectional study involving Chinese individuals also reported that self-reported excessive daytime sleepiness accompanied by snoring or apnea was associated with the lowest grip strength[ 25 ]. Furthermore, a HypnoLaus cohort study based on a Swiss population found that severe OSA measured using polysomnography was associated with decreased muscle strength. In adults over 60 years of age, low muscle strength directly affected OSA[ 26 ]. This finding aligned with our MR results that the more severe the low grip strength condition in individuals over 60 years of age, the higher the risk of OSA. However, no association was found between left or right hand grip strength and OSA. Therefore, more extensive studies are still needed on the relationship between grip strength and OSA for different hand tests. Previous studies have found that sleep apnea is associated with an increased risk of falls in older men[ 27 , 28 ], independent of confounders. Sleep deprivation is a major cause of unintentional injuries from falls, but no studies have investigated whether the frequency of falls and the risk of falling increase the risk of OSA. Patients with sarcopenia experience decreased muscle strength, particularly in the lower limbs, leading to longer sitting or lying times[ 29 ]. Some studies have shown that a 20% reduction in muscle mass is associated with a reduced ability to perform activities of daily living and an increased risk of falls. The risk of death significantly increases when muscle mass loss reaches 40%. Our results suggest that falls is a risk factor for OSA, offering a new perspective for preventing OSA. Aging, inflammation, oxidative stress, and other factors may partially contribute to the development of sarcopenia and OSA[ 30 , 31 ]. Treatment of frailty is an important approach to treating OSA, and sarcopenia is a major component of frailty[ 32 ]. Karla et al. found that a gender-stratified association between OSA risk and frailty in women but not in men[ 33 ]. Nevertheless, cross-sectional analyses from a prospective cohort study focusing on older men in the United States suggested that OSA was independently associated with greater evidence of frailty[ 34 ]. In addition, Omachi et al. reported that patients with OSA are at increased risk of recent work disability relative to patients without OSA[ 35 ]. In our study, a strong causal relationship was found between frailty, disability and OSA. This findings also strongly validate the above studies and provide a broader range of therapeutic strategies for OSA. In contrast, genome-wide association studies have not found a causal relationship between malnutrition and OSA. A retrospective intra-laboratory review of PSG data similarly confirmed that sleep-disordered breathing is common among the patients with muscular dystrophy (MD). Not all types of MD had the same degree of OSA or the same clinical manifestations. After adjusting for age, gender, body mass index and type, MD was marginally associated with OSA[ 36 ]. Although some reports have claimed that deficient vitamin D leads to a statistically higher risk of OSA, especially in children and adolescents[ 37 ]. However, evidence supporting the role of vitamin D and other nutritional indicators in adult OSA remains limited. Further research is needed to determine whether interventions for malnutrition can prevent the development of OSA. Our MR study on the relationship of usual walking pace with OSA indicated that usual walking pace was a protective factor for OSA. A possible causal pathway for this finding involves the Rostral Fluid Shift hypothesis[ 38 ]. According to this hypothesis, during the day fluid accumulates in the intravascular and interstitial spaces of the legs due to gravity, and upon lying down at night redistributes rostrally, again owing to gravity. This fluid is displaced to the rostral side (towards the head), increasing the tendency to narrow the upper airway, thus predisposing to OSA[ 39 ]. Physical activity, such as walking, reduces fluid accumulation in the lower extremities, while increasing upper airway dilator muscle strength, reducing nasal resistance and improving sleep architecture[ 40 ]. A large population-based study also verified that a slower walking speed is associated with a greater prevalence of OSA[ 41 ]. Nevertheless, a large number of observational and cohort studies are needed to demonstrate the effect of walking duration and frequency on OSA. Different body fat distribution is a genetic factor for OSA. Excess fat mass in the neck (often increasing with central obesity), as indicated by high neck circumferences, pressures the upper airway, leading to airway collapse and reduced lung volume[ 42 , 43 ]. Moreover, in our study, excess fat content, whether in the limbs or trunk, also increases the risk of OSA. As visceral adipose tissue secretes abundant pro-inflammatory cytokines, Giovanna and her colleagues hypothesized interactions between obesity, pro-inflammatory cytokines (including IL-1, IL-6, and TNF-α), and OSA[ 44 ]. Fat mass continues to increase with age until about 70 years old, while muscle mass reduces from around 30. Rolland et al. reported that sarcopenic obesity increases the risk of decline in physical performance more than either sarcopenia or obesity alone[ 45 ]. ALM is a sarcopenia-related trait mainly affected by skeletal muscle and is more heritable than whole-body lean mass[ 46 , 47 ]. Contrary to the study by Liu et al.[ 48 ], we found a genetic causal relationship between ALM and OSA. Additionally, our results indicated that higher limb, trunk, and whole-body fat mass increases the risk of OSA, similar to a study showing a positive correlation between OSA severity and the muscle skeletal index reported by Takeshi et al.[ 11 ]. More observational studies are needed to investigate the relationship between skeletal muscle and OSA. Interestingly, we also found a strong link between whole-body water mass and OSA. This observation aligns with the findings of Hsu et al.[ 49 ], which suggested that increased truncal adiposity and body water mass are associated with a higher risk of low arousal threshold obstructive sleep apnea. While we adjusted for several potential confounding factors in our analyses, there may still be residual confounding or unmeasured variables that could influence the observed associations. Future studies incorporating additional covariates or using alternative analytical approaches may provide further insights into the causal pathways linking sarcopenia-related traits to OSA. Conclusion Despite these limitations, our study contributes to the growing body of evidence implicating sarcopenia-related traits as potential risk factors for OSA. Further research addressing these limitations and exploring the underlying mechanisms is warranted to inform preventive and therapeutic strategies for OSA. Declarations Supplementary Information The online version contains supplementary material available. Author contributions Conceptualization: Huixian Sun, Xin Zeng, Wei Gao, and Xiang Lu; Methodology: Huixian Sun, Wei Gao, and Xiang Lu; Formal analysis: Huixian Sun, Xin Zeng, and Wei Gao; Investigation: Huixian Sun, Xin Zeng; Visualization: Xin Zeng; Draft writing: Huixian Sun, Xin Zeng; Revision: Wei Gao, Xiang Lu. All authors have read and agreed to the published version of the manuscript. Funding This work was supported by grants from the National Natural Science Foundation of China (No. 8197020550 to Wei Gao). Data availability The GWAS summary data could be found at https://gwas.mrcieu.ac.uk/. The database ID of each GWAS and the data generated in our study could be found in Supplementary Material. The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. Declarations Conflict of interest All authors declare no conflict of interest. Ethical standard This study used publicly available summarized data from the GWAS database. All of the studies and consortia accessed in the present study were approved by their respective ethics committee. Informed consent Written informed consent was obtained from each participant. 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J Am Geriatr Soc 57(11):2085–2093. https://doi.org/10.1111/j.1532-5415.2009.02490.x Omachi TA, Claman DM, Blanc PD et al (2009) Obstructive sleep apnea: a risk factor for work disability. Sleep 32(6):791–798. https://doi.org/10.1093/sleep/32.6.791 Li L, Umbach DM, Li Y et al (2023) Sleep apnoea and hypoventilation in patients with five major types of muscular dystrophy. BMJ Open Respir Res 10(1):e001506. https://doi.org/10.1136/bmjresp-2022-001506 Prono F, Bernardi K, Ferri R et al (2022) The Role of Vitamin D in Sleep Disorders of Children and Adolescents: A Systematic Review. Int J Mol Sci 23(3):1430. https://doi.org/10.3390/ijms23031430 Redolfi S, Yumino D, Ruttanaumpawan P et al (2009) Relationship between overnight rostral fluid shift and Obstructive Sleep Apnea in nonobese men. Am J Respir Crit Care Med 179(3):241–246. https://doi.org/10.1164/rccm.200807-1076OC White LH, Bradley TD (2013) Role of nocturnal rostral fluid shift in the pathogenesis of obstructive and central sleep apnoea. J Physiol 591(5):1179–1193. https://doi.org/10.1113/jphysiol.2012.245159 Kline CE, Crowley EP, Ewing GB et al (2011) The effect of exercise training on obstructive sleep apnea and sleep quality: a randomized controlled trial. Sleep 34(12):1631–1640. https://doi.org/10.5665/sleep.1422 Suri SV, Batterham AM, Ells L et al (2015) Cross-sectional Association between Walking Pace and Sleep-disordered Breathing. Int J Sports Med 36(10):843–847. https://doi.org/10.1055/s-0035-1549856 Pillar G, Shehadeh N (2008) Abdominal fat and sleep apnea: the chicken or the egg? Diabetes care 31 Suppl 2(7S303–309. https://doi.org/10.2337/dc08-s272 Lévy P, Kohler M, McNicholas WT et al (2015) Obstructive sleep apnoea syndrome. Nat reviews Disease primers 1:15015. https://doi.org/10.1038/nrdp.2015.15 Muscogiuri G, Barrea L, Annunziata G et al (2019) Obesity and sleep disturbance: the chicken or the egg? Crit Rev Food Sci Nutr 59(13):2158–2165. https://doi.org/10.1080/10408398.2018.1506979 Batsis JA, Villareal DT (2018) Sarcopenic obesity in older adults: aetiology, epidemiology and treatment strategies. Nat Rev Endocrinol 14(9):513–537. https://doi.org/10.1038/s41574-018-0062-9 Pei YF, Liu YZ, Yang XL et al (2020) The genetic architecture of appendicular lean mass characterized by association analysis in the UK Biobank study. Commun biology 3(1):608. https://doi.org/10.1038/s42003-020-01334-0 Hsu FC, Lenchik L, Nicklas BJ et al (2005) Heritability of body composition measured by DXA in the diabetes heart study. Obes Res 13(2):312–319. https://doi.org/10.1038/oby.2005.42 Liu M, Yu D, Pan Y et al (2024) Causal Roles of Lifestyle, Psychosocial Characteristics, and Sleep Status in Sarcopenia: A Mendelian Randomization Study. The journals of gerontology. Series A, Biological sciences and medical sciences. 79(1):glad191. https://doi.org/10.1093/gerona/glad191 Hsu WH, Yang CC, Tsai CY et al (2023) Association of Low Arousal Threshold Obstructive Sleep Apnea Manifestations with Body Fat and Water Distribution. Life (Basel. Switzerland) 13(5):1218. https://doi.org/10.3390. Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterial.docx Cite Share Download PDF Status: Published Journal Publication published 08 Mar, 2025 Read the published version in Aging Clinical and Experimental Research → Version 1 posted Editorial decision: Revision requested 08 Oct, 2024 Reviews received at journal 08 Oct, 2024 Reviews received at journal 30 Sep, 2024 Reviewers agreed at journal 18 Sep, 2024 Reviewers agreed at journal 18 Sep, 2024 Reviewers invited by journal 02 Aug, 2024 Editor assigned by journal 30 Jul, 2024 Submission checks completed at journal 19 Jul, 2024 First submitted to journal 19 Jul, 2024 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. 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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-4768091","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":337093452,"identity":"c4682527-51ea-412f-9b50-3c19e1b816e2","order_by":0,"name":"Huixian Sun","email":"","orcid":"","institution":"Department of Geriatrics, Sir Run Run Hospital, Nanjing Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Huixian","middleName":"","lastName":"Sun","suffix":""},{"id":337093453,"identity":"f333a744-c730-48c9-b51c-0f96cf15bdbc","order_by":1,"name":"Xin Zeng","email":"","orcid":"","institution":"Department of Geriatrics, Sir Run Run Hospital, Nanjing Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xin","middleName":"","lastName":"Zeng","suffix":""},{"id":337093454,"identity":"5a10e46c-bb63-4446-89a9-be575f4a5f3f","order_by":2,"name":"Wei Gao","email":"","orcid":"","institution":"Department of Geriatrics, School of Medicine, Zhongda Hospital, Southeast University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Gao","suffix":""},{"id":337093455,"identity":"33c2bd86-de2a-4875-8117-b79c9ce5b53f","order_by":3,"name":"Xiang Lu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7UlEQVRIiWNgGAWjYBACPiA+AMRy/OwNDAZgoQMEtLBB1RhL9hwgQQsIJBrMSIAyCWqRyDE88HNHbYKB5NsDRTfbGOT4biQwfi7AqyUt4WDvmeN55tJ5Cca5bUAX3khglp6BV0vygQO8bceKLWfnGIC0JG64kcDGzINXS2LDwb9txxI33DwD1lJPhJbkA4d522qAhvOAtSQYENTC8yzhsGzbAWAgAx2Wc07CcOaZh83S+LTws+cYf3zbVgeMyjNmxjllNvJ8x5MPfsanBQoOg20ERqUEkGZsIKyBgaEORDA/IEbpKBgFo2AUjDwAAJS6TKhF6sGbAAAAAElFTkSuQmCC","orcid":"","institution":"Department of Geriatrics, Sir Run Run Hospital, Nanjing Medical University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Xiang","middleName":"","lastName":"Lu","suffix":""}],"badges":[],"createdAt":"2024-07-19 13:39:00","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4768091/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4768091/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s40520-025-02963-3","type":"published","date":"2025-03-08T15:58:41+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":63372813,"identity":"f2cac87b-1db5-4f15-8bb1-9ff7ff767689","added_by":"auto","created_at":"2024-08-27 12:13:17","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":356302,"visible":true,"origin":"","legend":"\u003cp\u003eOverview of the design.\u003c/p\u003e","description":"","filename":"Fig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-4768091/v1/f436b9a58deb253f652dfbc7.png"},{"id":63372814,"identity":"fd50da54-db0c-4883-a6af-b2c327176018","added_by":"auto","created_at":"2024-08-27 12:13:17","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":724191,"visible":true,"origin":"","legend":"\u003cp\u003eResults of main MR analyses with unadjusted \u003cem\u003ep\u003c/em\u003e-values and adjusted \u003cem\u003ep\u003c/em\u003e-values.\u003c/p\u003e","description":"","filename":"Fig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-4768091/v1/3bc56830450234206472703e.png"},{"id":63372815,"identity":"98f511d2-739d-4304-930e-803152203c8d","added_by":"auto","created_at":"2024-08-27 12:13:17","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":692059,"visible":true,"origin":"","legend":"\u003cp\u003eDetailed information about the causal relationships between sarcopenia-related traits and OSA. NSNP, number of instrumental SNPs used to process MR analyses; OR, odds ratio; Pval, \u003cem\u003eP\u003c/em\u003e-value; IVW, Inverse variance weighted.\u003c/p\u003e","description":"","filename":"Fig.3.png","url":"https://assets-eu.researchsquare.com/files/rs-4768091/v1/8e90e7d49e6e81bf8a79e58e.png"},{"id":78191469,"identity":"e84c95fe-2c99-4462-9ef0-4a78b8313264","added_by":"auto","created_at":"2025-03-10 20:03:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2069911,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4768091/v1/65f58d64-f8ab-4e3c-b65b-83d2ef167c64.pdf"},{"id":63372816,"identity":"a8cea704-1510-4c38-bbbb-17925ce10cd6","added_by":"auto","created_at":"2024-08-27 12:13:18","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":16213219,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-4768091/v1/b4fb4f8bd34268bdd63506b8.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Causal associations between sarcopenia-related traits and obstructive sleep apnea: A Mendelian randomization study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSarcopenia is a skeletal muscle-related disorder. Studies have indicated that people with sarcopenia are at a higher risk of falls, cardiovascular disease, and type 2 diabetes [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Muscle strength, muscle mass, and physical performance are the three main indicators for the diagnosis of sarcopenia. At least two of these parameters are included in the diagnostic process, but different definitions of sarcopenia lead to varying cut-off points and standards. Hand grip strength is an efficient and valid measure of muscle strength. Low grip strength suggests further muscle mass assessment and predicts a series of adverse outcomes[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Appendicular lean mass (ALM) refers to the total skeletal muscle mass of the four limbs and approximately reflects overall body muscle content[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In clinical practice, physical performance is used to grade the severity of sarcopenia after a positive diagnosis, with walking pace, an objective measure, being the most widely applied indicator[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Sarcopenia is both an independent condition and a systemic disease[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Consequently, an increasing number of studies have investigated sarcopenia-related adverse outcomes, including falls, frailty, reduced quality of life, and mortality.\u003c/p\u003e \u003cp\u003eObstructive sleep apnea (OSA) is a prevalent and hazardous syndrome. Statistically, nearly 1\u0026nbsp;billion adults aged 30\u0026ndash;69 years worldwide may suffer from OSA[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The main characteristic of OSA is chronic intermittent hypoxia, which increases the risk of systemic diseases such as diabetes[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. However, most patients are unaware of their affected breathing and the importance of seeking medical attention, leading to low diagnosis rates and increased healthcare costs[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Observational studies have suggested a detrimental relationship between sarcopenia and OSA, but the causality remains unclear[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMendelian randomization (MR) is a robust epidemiological technique that utilizes genetic variants as instrumental variables (IVs) to control for potential confounding factors. This method is highly valued for its ability to mitigate the risk of reverse causation bias and enhance the reliability of causal inferences between exposures and clinical outcomes[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In this study, we aimed to identify the causal relationship between sarcopenia and OSA by MR analysis.\u003c/p\u003e"},{"header":"Design and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eOur study employed a two-sample MR approach to investigate the causal association between sarcopenia-related traits and OSA. An overview of the design presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The genetic variants serving as IVs, known as single nucleotide polymorphisms (SNPs), must meet three essential criteria[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]: (1) they should strongly predict the exposures, (2) they should be exclusively associated with the outcome through the exposures, and (3) they should not be associated with any confounders that could influence the exposure-outcome relationship.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eData sources\u003c/h2\u003e \u003cp\u003eWe identified 26 indices associated with sarcopenia as exposures, categorized into three domains: muscular strength, body composition, and physical performance, in alignment with established expert consensus. In terms of muscular strength, our study focused on hand grip strength, a crucial indicator that encompasses measurements for both the left and right hands as well as the criteria for low hand grip strength set forth by the European Working Group on Sarcopenia in Older People (EWGSOP), classifying individuals aged 60 and older with values below 30 kg for males and 20 kg for females.\u003c/p\u003e \u003cp\u003eIn terms of body composition, sarcopenia is characterized by the loss of appendicular lean mass (ALM). However, ALM is not the sole determinant; the whole-body fat mass and water mass also exert significant influence on this condition. In light of this, our study selected whole-body mass, trunk mass, and extremities mass as key parameters. Additionally, we considered similar indicators such as limb, trunk, and whole-body fat percentages.\u003c/p\u003e \u003cp\u003ePhysical performance is an essential measure that reflects the integrated functionality of the entire body, rather than the function of an isolated organ. The usual walking pace stands out as a frequently utilized metric in this context. Our analysis also encompassed other relevant aspects such as the duration and frequency of walking activities, including the number of days walked for 10\u0026thinsp;+\u0026thinsp;minutes and the frequency of walking for leisure in the past four weeks. Furthermore, we examined fall-related factors, encompassing both the risk of falls and the actual number of falls within the preceding year. We also took into account indicators of malnutrition and frailty, including the frailty index and the presence of chronic illnesses, disabilities, or infirmities.\u003c/p\u003e \u003cp\u003eThe above exposure datasets were obtained from the UK Biobank through the IEU Open GWAS project (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gwas.mrcieu.ac.uk/\u003c/span\u003e\u003cspan address=\"https://gwas.mrcieu.ac.uk/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). We also utilized GWAS data for OSA from the IEU Open GWAS Project, which contained 13,818 cases and 463,035 controls, for the outcome dataset. Data sources, participant demographics, ethnic backgrounds, and the studies included in our analysis are concisely outlined in Supplementary Table\u0026nbsp;1.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eSelection of instrumental variables\u003c/h2\u003e \u003cp\u003eIn accordance with the three core assumptions of MR analysis, independent single-nucleotide polymorphisms (SNPs) that demonstrated a strong association with the exposures (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;5\u0026times;10^\u0026minus;8) were selected as IVs for most indices. However, for indices related to falling risk, falls in the last year, and malnutrition, a less stringent threshold was applied (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;5\u0026times;10^\u0026minus;6). To mitigate linkage disequilibrium (LD) among the IVs, SNPs were clumped with a threshold set to \u003cem\u003er\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and a physical distance of \u003cem\u003ekb\u003c/em\u003e\u0026thinsp;=\u0026thinsp;10,000 [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Subsequently, palindromic SNPs were excluded during the harmonization process. MR-PRESSO (Pleiotropy Residual Sum and Outlier) was then utilized to identify and remove outlier SNPs, thereby preventing horizontal pleiotropy. The IVs that were eliminated due to being outliers are presented in Supplementary Table\u0026nbsp;2. The comprehensive steps of the screening process are outlined in Supplementary Table\u0026nbsp;3. All IVs with \u003cem\u003eF\u003c/em\u003e value\u0026thinsp;\u0026gt;\u0026thinsp;10 was considered of a sufficient strength of instrument[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe causal relationship between sarcopenia-related indicators and OSA was investigated using a range of MR methods, primarily implemented through the 'TwoSampleMR' package (version 0.5.6). These methods included inverse variance weighting (IVW), MR Egger, simple mode, weighted median, and weighted mode[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Heterogeneity among the selected IVs was assessed using Cochran\u0026rsquo;s Q statistic and its corresponding \u003cem\u003eP\u003c/em\u003e-values. If the null hypothesis of homogeneity was rejected, indicating significant heterogeneity, a random effects IVW model was employed instead of the fixed-effects IVW model[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. To address the potential impact of horizontal pleiotropy, the MR-Egger method was applied. A significant intercept term in the MR-Egger regression suggests the presence of horizontal pleiotropy. To further mitigate this, the MR pleiotropy residual sum and outlier (MR-PRESSO) method was utilized to identify and exclude outliers that could skew the estimation results[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. This method is particularly effective in controlling for horizontal pleiotropy. Scatter plots and funnel plots were also employed as visual tools. Scatter plots were used to confirm that the results were not influenced by outliers, while funnel plots were examined to ensure the robustness of the observed correlations and the absence of heterogeneity.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eThe Causal Association between Sarcopenia-Related Traits and OSA\u003c/h2\u003e \u003cp\u003eThe \u003cem\u003eP\u003c/em\u003e-values from MR analyses and those adjusted by MR-PRESSO are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The detailed results of the MR analyses, including the values for heterogeneity and pleiotropy tests, are shown in Supplementary Table\u0026nbsp;4. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e provides detailed information on the MR analyses, illustrating the causal associations between sarcopenia-related features and OSA. Scatter plots depicting the causal relationships between sarcopenia-related traits and OSA are visualized in Supplementary Figures A1-26. Forest plots showing the causal associations between sarcopenia-related traits and OSA are presented in Supplementary Figures B1-26. The leave-one-out analysis results for the causality of sarcopenia-related traits with OSA are visualized in Supplementary Figures C1-26. Funnel plots illustrating the causal associations between sarcopenia-related traits and OSA are shown in Supplementary Figures D1-26.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eHand Grip Strength and OSA\u003c/h2\u003e \u003cp\u003eAmong the three grip strength targets, low hand grip strength in individuals aged 60 years and older was positively correlated with the risk of OSA. The odds ratio (OR) was 1.190 [95% confidence interval (95% CI), 1.003\u0026ndash;1.413; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.047] using the IVW method after excluding outliers identified by the MR-PRESSO test (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The \u003cem\u003eP\u003c/em\u003e-value for the Egger-intercept test was 0.807, indicating no pleiotropic bias in assessing the effect of low grip strength in older adults with the IVW method. Leave-one-out analysis confirmed that the causal relationship was not driven by any single SNP. No significant causal effects were observed between hand grip strength (left and right) and OSA (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eMuscle Mass, Fat Mass, Water Mass, and OSA\u003c/h2\u003e \u003cp\u003eAssociations between appendicular lean mass (ALM), whole-body mass, trunk mass, extremities mass, and various fat percentages (limbs, trunk, and whole-body) with OSA were observed before adjusting the \u003cem\u003ep\u003c/em\u003e-values. These associations remained significant after adjustment: OSA and ALM (IVW, OR\u0026thinsp;=\u0026thinsp;1.133, 95% CI\u0026thinsp;=\u0026thinsp;1.050\u0026ndash;1.222, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) Whole-body water mass (IVW, OR\u0026thinsp;=\u0026thinsp;1.786, 95% CI\u0026thinsp;=\u0026thinsp;1.586\u0026ndash;2.011, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;9.70E-22) Whole-body fat mass (IVW, OR\u0026thinsp;=\u0026thinsp;1.981, 95% CI\u0026thinsp;=\u0026thinsp;1.791\u0026ndash;2.190, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.48E-40) Trunk fat mass (IVW, OR\u0026thinsp;=\u0026thinsp;1.828, 95% CI\u0026thinsp;=\u0026thinsp;1.653\u0026ndash;2.021, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.47E-32) Left arm fat mass (IVW, OR\u0026thinsp;=\u0026thinsp;2.225, 95% CI\u0026thinsp;=\u0026thinsp;2.029\u0026ndash;2.439, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.53E-65) Right arm fat mass (IVW, OR\u0026thinsp;=\u0026thinsp;2.274, 95% CI\u0026thinsp;=\u0026thinsp;2.080\u0026ndash;2.485, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.67E-73) Left leg fat mass (IVW, OR\u0026thinsp;=\u0026thinsp;2.808, 95% CI\u0026thinsp;=\u0026thinsp;2.476\u0026ndash;3.183, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.08E-58) Right leg fat mass (IVW, OR\u0026thinsp;=\u0026thinsp;2.659, 95% CI\u0026thinsp;=\u0026thinsp;2.356\u0026ndash;3.002, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.92E-56) Body fat percentage (IVW, OR\u0026thinsp;=\u0026thinsp;2.163, 95% CI\u0026thinsp;=\u0026thinsp;1.888\u0026ndash;2.478, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;9.01E-29) Trunk fat percentage (IVW, OR\u0026thinsp;=\u0026thinsp;1.767, 95% CI\u0026thinsp;=\u0026thinsp;1.572\u0026ndash;1.986, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.19E-21) Left arm fat percentage (IVW, OR\u0026thinsp;=\u0026thinsp;2.440, 95% CI\u0026thinsp;=\u0026thinsp;2.129\u0026ndash;2.797, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.44E-37) Right arm fat percentage (IVW, OR\u0026thinsp;=\u0026thinsp;2.484, 95% CI\u0026thinsp;=\u0026thinsp;2.155\u0026ndash;2.864, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.48E-36) Left leg fat percentage (IVW, OR\u0026thinsp;=\u0026thinsp;2.866, 95% CI\u0026thinsp;=\u0026thinsp;2.433\u0026ndash;3.377, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.54E-36) Right leg fat percentage (IVW, OR\u0026thinsp;=\u0026thinsp;2.729, 95% CI\u0026thinsp;=\u0026thinsp;2.297\u0026ndash;3.241, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.80E-30) The results from MR Egger and the Weighted Median method were largely consistent. Additionally, no significant horizontal pleiotropy was detected by the MR-Egger intercept test (Supplementary Table\u0026nbsp;4).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePhysical Performance and OSA\u003c/h2\u003e \u003cp\u003eUsual walking pace was inversely associated with OSA using the IVW method, with an OR value of 0.153 (95% CI, 0.092\u0026ndash;0.256; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8.24 \u0026times; 10⁻\u0026sup1;\u0026sup3;). The MR-Egger test indicated no significant pleiotropy in these results (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.825). No causal associations were found between the duration of walks, the frequency of walking for pleasure in the last four weeks, the number of days per week walked for 10\u0026thinsp;+\u0026thinsp;minutes, and OSA. A one-unit increase in the log odds of falling risk was associated with a 47% higher risk of OSA (OR, 1.469, 95% CI: 1.199-1.800, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). More falls in the past year were related to a higher risk of OSA (OR, 4.972, 95% CI: 2.408\u0026ndash;10.265, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). A similar result was found between the frailty index and OSA (OR, 1.965, 95% CI: 1.312\u0026ndash;2.942, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001). We found strong evidence supporting the causality of long-standing illness, disability, or infirmity on OSA (OR, 4.387, 95% CI: 1.657\u0026ndash;11.612, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003). Additionally, the IVW, MR Egger, and Weighted Median results all suggested no causal effect of malnutrition on OSA. The results of sensitivity analyses are shown in Supplementary Table\u0026nbsp;4.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo our knowledge, this is the first mendelian randomization study to systematically evaluate the causal relationships between sarcopenia-related traits and OSA in European population. Existing clinical studies have indicated that early-onset sarcopenia is more likely to occur in younger patients with OSA[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The sarcopenia index was negatively correlated with the odds ratio of sleep disorders. Maintaining optimal muscle mass may have a beneficial effect on OSA[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Our findings reveal that genetically determined low hand grip strength, falls, frailty, and disability are significantly associated with increased risks of OSA. Genetically predicted usual walking pace was negatively correlated with OSA, indicating that a lower walking speed increases the probability of suffering from sleep apnea. Additionally, muscle mass, fat mass, and water mass were positively related to OSA. However, we did not find a direct causal relationship between (left \u0026amp; right) hand grip strength, malnutrition, the duration and frequency of walking and OSA. Overall, the current MR results provide valuable insights into the impact of sarcopenia on OSA, highlighting the importance of considering skeletal muscle health in preventive and therapeutic strategies.\u003c/p\u003e \u003cp\u003eObservational investigations have demonstrated a transdiagnostic relationship between sleep duration and hand grip strength as well as the potential use of hand grip strength as a marker in OSA[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. It also strongly endorses the effect of grip strength on OSA in MR analysis, revealing a causal association between sarcopenia and OSA. A cross-sectional study of Korean adults aged 40 to 80 years showed that low OSA risk was found to be associated with high grip strength after adjusting for other sleep parameters and confounders[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Another cross-sectional study involving Chinese individuals also reported that self-reported excessive daytime sleepiness accompanied by snoring or apnea was associated with the lowest grip strength[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Furthermore, a HypnoLaus cohort study based on a Swiss population found that severe OSA measured using polysomnography was associated with decreased muscle strength. In adults over 60 years of age, low muscle strength directly affected OSA[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. This finding aligned with our MR results that the more severe the low grip strength condition in individuals over 60 years of age, the higher the risk of OSA. However, no association was found between left or right hand grip strength and OSA. Therefore, more extensive studies are still needed on the relationship between grip strength and OSA for different hand tests.\u003c/p\u003e \u003cp\u003ePrevious studies have found that sleep apnea is associated with an increased risk of falls in older men[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], independent of confounders. Sleep deprivation is a major cause of unintentional injuries from falls, but no studies have investigated whether the frequency of falls and the risk of falling increase the risk of OSA. Patients with sarcopenia experience decreased muscle strength, particularly in the lower limbs, leading to longer sitting or lying times[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Some studies have shown that a 20% reduction in muscle mass is associated with a reduced ability to perform activities of daily living and an increased risk of falls. The risk of death significantly increases when muscle mass loss reaches 40%. Our results suggest that falls is a risk factor for OSA, offering a new perspective for preventing OSA. Aging, inflammation, oxidative stress, and other factors may partially contribute to the development of sarcopenia and OSA[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTreatment of frailty is an important approach to treating OSA, and sarcopenia is a major component of frailty[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Karla et al. found that a gender-stratified association between OSA risk and frailty in women but not in men[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Nevertheless, cross-sectional analyses from a prospective cohort study focusing on older men in the United States suggested that OSA was independently associated with greater evidence of frailty[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. In addition, Omachi et al. reported that patients with OSA are at increased risk of recent work disability relative to patients without OSA[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. In our study, a strong causal relationship was found between frailty, disability and OSA. This findings also strongly validate the above studies and provide a broader range of therapeutic strategies for OSA. In contrast, genome-wide association studies have not found a causal relationship between malnutrition and OSA. A retrospective intra-laboratory review of PSG data similarly confirmed that sleep-disordered breathing is common among the patients with muscular dystrophy (MD). Not all types of MD had the same degree of OSA or the same clinical manifestations. After adjusting for age, gender, body mass index and type, MD was marginally associated with OSA[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Although some reports have claimed that deficient vitamin D leads to a statistically higher risk of OSA, especially in children and adolescents[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. However, evidence supporting the role of vitamin D and other nutritional indicators in adult OSA remains limited. Further research is needed to determine whether interventions for malnutrition can prevent the development of OSA.\u003c/p\u003e \u003cp\u003eOur MR study on the relationship of usual walking pace with OSA indicated that usual walking pace was a protective factor for OSA. A possible causal pathway for this finding involves the Rostral Fluid Shift hypothesis[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. According to this hypothesis, during the day fluid accumulates in the intravascular and interstitial spaces of the legs due to gravity, and upon lying down at night redistributes rostrally, again owing to gravity. This fluid is displaced to the rostral side (towards the head), increasing the tendency to narrow the upper airway, thus predisposing to OSA[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Physical activity, such as walking, reduces fluid accumulation in the lower extremities, while increasing upper airway dilator muscle strength, reducing nasal resistance and improving sleep architecture[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. A large population-based study also verified that a slower walking speed is associated with a greater prevalence of OSA[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Nevertheless, a large number of observational and cohort studies are needed to demonstrate the effect of walking duration and frequency on OSA.\u003c/p\u003e \u003cp\u003eDifferent body fat distribution is a genetic factor for OSA. Excess fat mass in the neck (often increasing with central obesity), as indicated by high neck circumferences, pressures the upper airway, leading to airway collapse and reduced lung volume[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Moreover, in our study, excess fat content, whether in the limbs or trunk, also increases the risk of OSA. As visceral adipose tissue secretes abundant pro-inflammatory cytokines, Giovanna and her colleagues hypothesized interactions between obesity, pro-inflammatory cytokines (including IL-1, IL-6, and TNF-α), and OSA[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Fat mass continues to increase with age until about 70 years old, while muscle mass reduces from around 30. Rolland et al. reported that sarcopenic obesity increases the risk of decline in physical performance more than either sarcopenia or obesity alone[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eALM is a sarcopenia-related trait mainly affected by skeletal muscle and is more heritable than whole-body lean mass[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Contrary to the study by Liu et al.[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], we found a genetic causal relationship between ALM and OSA. Additionally, our results indicated that higher limb, trunk, and whole-body fat mass increases the risk of OSA, similar to a study showing a positive correlation between OSA severity and the muscle skeletal index reported by Takeshi et al.[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. More observational studies are needed to investigate the relationship between skeletal muscle and OSA. Interestingly, we also found a strong link between whole-body water mass and OSA. This observation aligns with the findings of Hsu et al.[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e], which suggested that increased truncal adiposity and body water mass are associated with a higher risk of low arousal threshold obstructive sleep apnea.\u003c/p\u003e \u003cp\u003eWhile we adjusted for several potential confounding factors in our analyses, there may still be residual confounding or unmeasured variables that could influence the observed associations. Future studies incorporating additional covariates or using alternative analytical approaches may provide further insights into the causal pathways linking sarcopenia-related traits to OSA.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eDespite these limitations, our study contributes to the growing body of evidence implicating sarcopenia-related traits as potential risk factors for OSA. Further research addressing these limitations and exploring the underlying mechanisms is warranted to inform preventive and therapeutic strategies for OSA.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eSupplementary Information\u0026nbsp;\u003c/strong\u003eThe online version contains supplementary material available.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003eConceptualization: Huixian Sun, Xin Zeng, Wei Gao, and Xiang Lu; Methodology: Huixian Sun, Wei Gao, and Xiang Lu; Formal analysis: Huixian Sun, Xin Zeng, and Wei Gao; Investigation: Huixian Sun, Xin Zeng; Visualization: Xin Zeng; Draft writing: Huixian Sun, Xin Zeng; Revision: Wei Gao, Xiang Lu. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003eThis work was supported by grants from the National Natural Science Foundation of China (No. 8197020550 to Wei Gao).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003eThe GWAS summary data could be found at https://gwas.mrcieu.ac.uk/. The database ID of each GWAS and the data generated in our study could be found in Supplementary Material. The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e All authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical standard\u003c/strong\u003e This study used publicly available summarized data from the GWAS database. All of the studies and consortia accessed in the present study were approved by their respective ethics committee.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed consent\u003c/strong\u003e Written informed consent was obtained from each participant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOpen Access\u003c/strong\u003e This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article\u0026apos;s Creative Commons licence, unless indicated\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eotherwise in a credit line to the material. 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Switzerland) 13(5):1218. https://doi.org/10.3390. \u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"aging-clinical-and-experimental-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"acer","sideBox":"Learn more about [Aging Clinical and Experimental Research](http://link.springer.com/journal/40520)","snPcode":"40520","submissionUrl":"https://submission.nature.com/new-submission/40520/3","title":"Aging Clinical and Experimental Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Sarcopenia-related traits, Obstructive sleep apnea, Mendelian randomization, Genetic analyses","lastPublishedDoi":"10.21203/rs.3.rs-4768091/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4768091/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eEvidence for a causal relationship between sarcopenia and obstructive sleep apnea (OSA) is scarce. This study aimed to investigate the causal association between sarcopenia-related traits and OSA utilizing Mendelian randomization (MR) analyses.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eMR analyses were conducted using genetic instruments for sarcopenia-related traits, including hand grip strength, muscle mass, fat mass, water mass, and physical performance. Data from large-scale genome-wide association studies (GWAS) were utilized to identify genetic variants associated with these traits. Causal associations with OSA were assessed using various MR methods, including the inverse variance-weighted (IVW) method, MR-Egger, and weighted median approaches. Pleiotropy and heterogeneity were evaluated through MR-PRESSO and other sensitivity analyses.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eLow hand grip strength in individuals aged 60 years and older exhibited a positive correlation with the risk of OSA (IVW, OR\u0026thinsp;=\u0026thinsp;1.190, 95% CI\u0026thinsp;=\u0026thinsp;1.003\u0026ndash;1.413, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.047), while no significant causal effects were observed for grip strength in the left and right hands. Muscle mass, fat mass, and water mass were significantly associated with OSA, even after adjusting for multiple testing. Notably, higher levels of body fat percentage, trunk fat percentage, and limb fat percentage were strongly correlated with increased risk of OSA. Physical performance indicators such as walking pace demonstrated an inverse association with OSA, while a higher risk of OSA was observed with increased log odds of falling risk and greater frequency of falls in the last year. Additionally, a causal effect was found between long-standing illness, disability, or infirmity and OSA.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThis comprehensive MR analysis provides evidence supporting a causal relationship between sarcopenia-related traits, including hand grip strength, muscle mass, fat mass, and physical performance, and the risk of OSA. These findings underscore the importance of addressing sarcopenia-related factors in the management and prevention of OSA.\u003c/p\u003e","manuscriptTitle":"Causal associations between sarcopenia-related traits and obstructive sleep apnea: A Mendelian randomization study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-27 12:13:12","doi":"10.21203/rs.3.rs-4768091/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-10-08T07:28:09+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-08T06:03:53+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-30T09:17:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"2361291280320164813083067839781869355","date":"2024-09-18T17:31:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"69908750446027096255960744802361631961","date":"2024-09-18T11:12:54+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-02T08:48:33+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-30T18:21:44+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-20T03:56:59+00:00","index":"","fulltext":""},{"type":"submitted","content":"Aging Clinical and Experimental Research","date":"2024-07-19T13:37:38+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"aging-clinical-and-experimental-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"acer","sideBox":"Learn more about [Aging Clinical and Experimental Research](http://link.springer.com/journal/40520)","snPcode":"40520","submissionUrl":"https://submission.nature.com/new-submission/40520/3","title":"Aging Clinical and Experimental Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"4e28b4b4-4f3e-465d-8440-a32435dd5a8f","owner":[],"postedDate":"August 27th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-03-10T20:03:03+00:00","versionOfRecord":{"articleIdentity":"rs-4768091","link":"https://doi.org/10.1007/s40520-025-02963-3","journal":{"identity":"aging-clinical-and-experimental-research","isVorOnly":false,"title":"Aging Clinical and Experimental Research"},"publishedOn":"2025-03-08 15:58:41","publishedOnDateReadable":"March 8th, 2025"},"versionCreatedAt":"2024-08-27 12:13:12","video":"","vorDoi":"10.1007/s40520-025-02963-3","vorDoiUrl":"https://doi.org/10.1007/s40520-025-02963-3","workflowStages":[]},"version":"v1","identity":"rs-4768091","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4768091","identity":"rs-4768091","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}