{"paper_id":"3e7df220-c37f-4c3d-b323-6c8a2d571ac6","body_text":"Identifying the association between Physical Activity and HCV infection status: An observational study and Mendelian randomization analysis | 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 Identifying the association between Physical Activity and HCV infection status: An observational study and Mendelian randomization analysis Liangchen Lei, Chen Ouyang, Pengpeng Liu, Quanyan Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5845762/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 Purpose To investigate the association and causality between physical activity and hepatitis C virus (HCV) infection. Methods In this cross-sectional study, we conducted a bidirectional two-sample Mendelian Randomization (MR) analysis using data from the GWAS database. The analytic population was divided into three categories based on hepatitis C virus infection outcomes, and statistical differences were analyzed with covariates. Additionally, Restricted Cubic Spline (RCS) analysis was applied to examine the nonlinear relationship between physical exercise and hepatitis C virus infection. Instrumental variables were selected with a threshold of P < 5*10⁻⁸, and the causal relationships were assessed using IVW, MR-Egger, Weighted Median, Weighted Mode, and Simple Mode methods. Cochran's Q test was used to assess and exclude data heterogeneity. Results In the population data analysis, the moderate-to-vigorous work (MVW) variable showed a significant association with HCV infection (p = 0.006). MVW demonstrated a positive association with HCV infection (OR = 2.46, 95% CI = 1.02–5.92). RCS analysis indicated that the risk of HCV infection significantly increased when MVW exceeded 810 minutes per week. MR analysis indicated that MVW had a unidirectional effect on HCV infection (IVW model: OR = 1.366, 95% CI: 1.121–1.663, p = 0.002), and heterogeneity was excluded from the analysis. Conclusions In the context of HCV infection, the primary factor influencing risk is not the duration of physical activity, but the type. High-intensity physical activity significantly elevates the risk of HCV infection. It may be prudent to manage work hours responsibly to minimize physical strain. GWAS Moderate-to-vigorous work NHANSE Types of Physical activity Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Hepatitis C is an infectious disease caused by the hepatitis C virus ( 1 )(HCV). Approximately 71 million people are infected with HCV, and hundreds of thousands die from HCV-related diseases annually( 2 ). Although over 95% of hepatitis C patients can be cured with antiviral therapies like direct-acting antiviral agents (DAAs), no effective HCV vaccine exists due to HCV's genetic diversity and viral variability( 3 ). Studies indicate that even after successful DAAs treatment, some patients may still experience long-term liver damage or other complications( 4 ). Therefore, infection prevention remains a top priority in managing hepatitis C. Contemporary medical guidelines recommend managing and adjusting health-related behaviors( 5 ), such as diet and physical activity, during viral infections to slow the progression of liver disease( 6 ). Importantly, this highlights the impact of lifestyle factors on disease progression. Physical activity plays a vital role in hepatitis C prevention( 7 ). Proper physical exercise can enhance liver function, slow liver disease progression, and improve patients' quality of life( 4 ). However, due to varying patient conditions, physical abilities, and living environments, further clinical studies are needed to determine the most effective exercise type, intensity, and frequency for hepatitis C patients( 8 ). Physical activity encompasses any bodily movement that elevates energy expenditure( 9 ). The World Health Organization (WHO) advises adults to engage in at least 150 minutes of moderate-intensity aerobic exercise per week( 10 ). Increasing evidence indicates that physical activity, across varying intensities, frequencies, and durations, can lower the risk of chronic diseases related to weight management( 11 ), metabolic health( 12 ), and mental health( 13 ). As research progresses, it has become increasingly evident that physical activity may play a crucial role in infectious diseases by regulating immune function( 14 ), modifying behavioral habits( 15 ), and increasing awareness of protective measures. However, there’s limited research on the impact of physical activity on HCV progression (i.e., how quickly the virus damages the liver). No consistent findings have emerged regarding the potential influence of exercise on disease severity or outcomes( 16 ). It’s challenging to conduct large-scale, controlled studies on these questions, especially when considering the long-term nature of HCV progression and the influence of other factors( 17 ). At present, the relationship between physical activity and HCV infection status is a complex one, and the current research paints a mixed picture. Genome-wide association studies (GWAS) have identified numerous genetic variants associated with complex phenotypes and are widely employed to provide optimal instrumental variables for Mendelian randomization (MR) analysis( 18 ). Mendelian randomization (MR) analysis utilizes genetic variants as instrumental variables to examine the causal relationship between clinical traits and disease phenotypes( 19 ). As genetic alleles are randomly assigned during meiosis and remain unaffected by environmental factors, MR surpasses observational studies in controlling for confounding factors and reverse causality( 20 ). In this study, we utilized data from the National Health and Nutrition Examination Survey (NHANES) to examine the association between physical activity and HCV infection status, adjusting for several potential confounders. Subsequently, we assessed the causal relationship between physical activity and HCV infection status and conducted bidirectional two-sample MR analyses to explore their causal effects. Methods 1. Study design in NHANES In this cross-sectional study, we combined data from the 2017–2020 continuous NHANES ( https://www.cdc.gov/nchs/nhanes/ ) to form our study population. As shown in Fig. 1 , We included adult participants aged 19 to 79 years (n = 9693) and excluded individuals without tests for HCV cRNA (n = 1424), HCV antibody (n = 1239), ALT (n = 109), and TB (n = 1). Among individuals who tested positive for HCV RNA, we further excluded those who lacked confirmed Hepatitis C antibody tests (n = 14), as it cannot distinguish between resolved and chronic HCV infections. Thus, the final analytic population comprised 6906 participants. 2. Definition of Physical Activity and HCV infection status in NHANES The Global Physical Activity Questionnaire was used to collect weekly physical activity data at the respondent level. Physical activity levels were classified into two categories: vigorous work or recreational activities, and moderate work or recreational activities( 21 ). Vigorous work or recreational activities were defined as those causing a significant increase in breathing or heart rate, sustained for at least 10 minutes( 22 ). Moderate work or leisure activities were defined as activities causing a slight increase in breathing or heart rate, sustained for at least 10 minutes. We categorized exercise into three types based on duration and intensity: moderate-vigorous work, moderate-vigorous activities, and sedentary activity( 23 ). HCV infection status was determined by HCV antibody screening, confirmation, and/or HCV-RNA tests. Participants testing positive for HCV-RNA and/or the anti-HCV antibody confirmation test were classified as having HCV infection( 24 ). 3. Covariates in NHANES We collected the following covariates: age, race, HIV infection status, alcohol use, smoking status, education level, alanine aminotransferase (ALT), total bilirubin (TBil), globulin, and albumin. Age was categorized into 18–39, 40–59, and 60–80 years. Race was classified into Hispanic, White, Black, Asian, and other races. Alcohol use was categorized as never, less than once a month, once a month or more, and other. Smoking status was categorized as every day, not at all, and some days. Education level was categorized as college graduate or above, high school graduate/GED or below, and some college or an associate degree. 4. MR study design As illustrated in Fig. 1 , a bidirectional two-sample Mendelian Randomization (MR) analysis was conducted to evaluate the causal relationship between physical activity and HCV infection status. Instrumental variables (IVs) for physical activity were extracted from a recent GWAS that included 91,105 individuals of European ancestry from the UK Biobank( www.ebi.ac.uk/gwas/ ). This GWAS identified 14 loci associated with device-measured physical activity and sleep duration. In the GWAS by Doherty et al.( 25 ), participants who consented to wear a wrist-worn accelerometer for 7 days also underwent genome-wide genotyping and imputation. They generated a continuous phenotype for overall activity time and applied a machine-learning model using balanced random forests with Markov confusion matrices to classify individuals into one of four activity states: sleep, sedentary, walking, or moderate intensity. Summary data for HCV infection from a GWAS were obtained from the UK Biobank, which included 219 cases and 456,129 controls of European ancestry( 26 ). All participants were of European ancestry, minimizing racial stratification bias. Details of the GWAS data used in these MR analyses are provided in Fig. 1 . 5. Selection of genetic instruments The selected instrumental variables (IVs) must satisfy three assumptions: (a) IVs are significantly associated with the exposure; (b) IVs influence the outcome only through the exposure; and (c) IVs are not related to any confounders between the exposure and outcome ( 27 ). To identify IVs for physical activity, we selected single-nucleotide polymorphisms (SNPs) significantly associated with physical activity (p < 5 × 10⁻⁸, linkage disequilibrium [LD] r² < 0.001). Finally, SNPs were identified as IVs significantly associated with physical activity and HCV infection, respectively. To perform reverse MR analysis between HCV infection status with physical activity, a more relaxed threshold was applied (p < 5 × 10⁻⁵). Weak genetic instruments were excluded if the F-statistic was less than 10. 6. Statistical analyses Data from NHANES were used for the observational analysis. Sample weights were applied throughout the analysis to account for the multistage probability sampling in NHANES. Baseline characteristics were compared between the HCV infection group and the normal group. Logistic regression analyses were conducted to examine the association between physical activity and HCV infection status. Three multivariate regression models were constructed: Model 1 (unadjusted); Model 2 (adjusted for age, race, HIV infection, alcohol use, smoking status, and education level); Model 3 (adjusted for age, race, HIV infection, alcohol use, smoking status, education level, ALT, TBil, globulin, and albumin). Statistical analyses were performed using R, with a significance threshold of P < 0.05. Restricted cubic spline curves were fitted to the logistic regression model with 3 knots. Mendelian Randomization (MR) analyses were primarily conducted using the random-effects inverse-variance weighted (IVW) method to estimate the causal relationship between physical activity and HCV infection status. The IVW method combines the Wald ratio for each SNP, assuming all instruments have causal effects ( 28 ). Supplementary methods for the IVW estimate included the weighted median, MR-Egger, simple mode, and weighted mode, which provide more robust estimates in broader contexts but are less efficient (with wider confidence intervals). The intercept of the MR-Egger regression was used to estimate directional pleiotropy( 29 ). The Cochran's Q test was performed, and a funnel plot( 30 ) was generated to assess heterogeneity. Additionally, the leave-one-out method was used to evaluate the robustness and consistency of the results. All statistical analyses were conducted using the TwoSampleMR package in R version 4.2.2 ( https://www.r-project.org/ ). P-value < 0.05 was considered significant in the MR-Egger regression and Cochran's Q test. Results 1. Baseline characteristics As shown in Table 1, among the 6906 participants, the prevalence of resolved and chronic HCV infection was 1.17% (81 individuals) and 1.08% (75 individuals), respectively. Compared to individuals without HCV infection (n = 6750), those with resolved or chronic HCV infection tended to be older and were more likely to have HIV infection, a history of stroke, lower education levels, and higher ALT, globulin, and albumin levels. No significant differences were observed in race, alcohol use, or TBil. For physical activity of all intensities, participants who engaged in more than 150 minutes of moderate-to-vigorous work per week were more likely to have HCV infection. Interestingly, no statistically significant difference in HCV infection was found among individuals who engaged in more than 150 minutes of physical activity per week. 2. Association between Physical Activity and HCV infection status Statistical results from various populations indicated that moderate-to-vigorous work (MVW) was closely associated with HCV infection. Multivariate logistic regression analyses were then used to investigate the association between moderate-to-vigorous work and HCV infection status. The results indicated that even after adjusting for multiple models, moderate-to-vigorous work remained significantly positively associated with HCV infection status (unadjusted model: OR = 2.69, 95% CI = 1.40-5.20; fully adjusted model: OR = 2.46, 95% CI = 1.02–5.92), as shown in Table 2. As shown in Figure 2, a restricted cubic spline (RCS) curve was generated to visually depict the relationship between moderate-to-vigorous work and HCV infection status, based on Model 3. The RCS analysis revealed no significant nonlinear association between moderate-to-vigorous work and HCV infection status (p for nonlinearity = 0.1799; reference = 810min). 3. Causal effect of Physical Activity on HCV infection status All instrumental variables (IVs) for Physical Activity were included in the Mendelian randomization (MR) analysis (Supplementary Table 1). None of the IVs were significantly associated with HCV infection status or any confounders. As shown in Table 3, the MR analysis indicated that physical activity had a significant causal effect on HCV infection status in the inverse-variance weighted (IVW) model (OR=1.366, 95% CI: 1.121–1.663, p = 0.002). A similar estimate was observed in the weighted median model (OR=1.499, 95% CI: 1.145–1.962, p = 0.003). The scatter plot is shown in Fig. 3A The intercept of the MR-Egger regression was 0.008 (p=0.507), indicating no evidence of pleiotropy. The Cochran's Q test indicated no heterogeneity (p=0.0556). The funnel plot showed symmetry, further indicating no heterogeneity (Fig. 3B). Additionally, leave-one-out analysis showed that no single IV significantly influenced the causal effect of depression on constipation (Fig. 3C). 4. Causal effect of HCV infection status on Physical Activity Since a p-value <5 × 10 -8 would yield too few IVs, we adjusted the threshold to p <5×10 -5 . A total of 634 HCV infection status-related IVs were included in the MR analysis (Supplementary Table 2). None of the IVs were significantly associated with physical activity or any confounders. As shown in Table 3, there was no significant causal effect of HCV infection status on physical activity (IVW: OR = 1.000, 95% CI: 0.997–1.002, p = 0.724). The Egger intercept was 0.0008 (p = 0.647), indicating no evidence of pleiotropy. The Cochran's Q test indicated no heterogeneity (p = 0.226). The funnel plot didn’t show symmetry, indicating no heterogeneity (Fig. 4A). No significant changes were observed by removing any single IV, as confirmed by the leave-one-out method (Fig. 4B). Discussion This observational study confirmed a positive association between physical activity and HCV infection status. Additionally, the type of physical activity was positively associated with the risk of HCV infection. A significant causal effect of physical activity on HCV infection status was identified through two-sample MR analyses. In contrast, no significant causal effect of HCV infection status on physical activity was found in the reverse MR analysis. The liver is a crucial organ responsible for regulating energy metabolism( 31 ). Hepatitis C is frequently associated with metabolic disorders, including insulin resistance( 32 ) and fatty liver disease( 33 ). Numerous studies indicate that physical activity plays a vital role in managing HCV infection by reducing liver fat accumulation( 34 ), improving liver metabolism, and enhancing immune system function( 35 ), thus increasing the body's ability to combat HCV infection( 36 ). Our observational studies found no association between sedentary behavior or weekly moderate-to-vigorous physical activities and HCV infection. However, moderate-to-vigorous work for more than 150 minutes per week significantly increased the risk of HCV infection. The risk of HCV infection significantly increased when moderate-to-vigorous work more than 810 minutes per week. This conclusion was further validated at the SNP level through a bidirectional Mendelian randomization (MR) experiment( 37 ). These findings suggest that while physical activity may have some benefits for HCV infection, its effects vary depending on the type of activity. Despite significant advances in HCV treatment, challenges in prevention persist( 38 ). It showed that sedentary or leisure-based high-intensity physical activity (over 150 minutes per week) had minimal impact on HCV infection risk, whereas work-based high-intensity physical activity significantly increased the risk. These findings suggest that high-intensity work negatively impacts health. In conclusion, high-intensity work, in addition to contributing to chronic fatigue( 39 ), cardiovascular disease( 40 ), and psychological disorders( 9 ), can reduce quality of life by increasing the risk of HCV infection. However, this study has several limitations. First, the NHANES database lacks genotypic data, preventing polygenic score analysis to explore potential genetic associations between physical activity and HCV infection status. Second, the MR analysis was based on GWAS data from a European population. High-quality GWAS data on physical activity are lacking. In our MR analysis, due to the absence of data on physical activity categories, we substituted overall physical activity for high-intensity work. However, observational studies suggest that only high-intensity work is associated with HCV infection, supporting the validity of this substitution. Finally, variability in work environments and tasks among high-intensity workers may affect the accuracy of the statistics. Further investigation is required to improve the credibility of these findings. All in all, our study suggests that moderate-to-vigorous work causally affects HCV infection status, rather than vice versa. Individuals should limit their moderate-to-vigorous work to less than 810 minutes per week. This finding underscores the need for further research on the relationship between work intensity and HCV infection. This is crucial not only for populations in high-risk occupations but also for improving global HCV infection prevention efforts. Declarations Acknowledgements We are very grateful for the data sharing of NHANES and GWAS. We want to acknowledge the participants and investigators of the NHGRI-EBI GWAS Catalog study. Conflict of Interest : The authors declare that they have no competing interests. The results of the study are presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation. The results of the present study do not constitute endorsement by the American College of Sports Medicine. Authors' contributions Liangchen Lei and Quanyan Liu conceived and designed the study. Liangchen Lei, Pengpeng Liu and Quanyan Liu were responsible for data analysis, collating, and writing the manuscript. Chen Ouyang contributed to data colletion. All authors read and approved the final manuscript. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Availability of data and materials The datasets generated and analyzed during the current study are available in the NHANES (https://www.cdc.gov/nchs/nhanes/). GWAS data for physical activity: www.ebi.ac.uk/gwas/studies/GCST006912.GWAS data for hepatitis C virus infection: www.ebi.ac.uk/gwas/studies/GCST90041714. Ethics approval and consent to participate Not applicable. The data analyzed in this study is de-identified data obtained from NHANES and GWAS summary data, and the ethics approval and consent to participate are not required. References Coppola N, Alessio L, Onorato L, et al. Epidemiology and management of hepatitis C virus infections in immigrant populations. Infect Dis Poverty. 2019;8(1):17. Ly KN, Hughes EM, Jiles RB, Holmberg SD. Rising Mortality Associated With Hepatitis C Virus in the United States, 2003–2013. Clin Infect Dis. 2016;62(10):1287–8. Mosa AI, Campo DS, Khudyakov Y et al. Polyvalent immunization elicits a synergistic broadly neutralizing immune response to hypervariable region 1 variants of hepatitis C virus. 2023;120(24). Kriss M, Burchill M. HCV and nonhepatic malignancy: Is pre-emptive direct‐acting antiviral therapy indicated prior to treatment? Hepatology. 2018;67(1):4–6. Bright EE, Finkelstein LB, Nealis MS, et al. 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Jeffery M. Diaphragmatic Fatigue and High-intensity Exercise in Patients with Chronic Obstructive Pulmonary Disease. AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE.2000;161. Reed JL, Terada T, Cotie LM, et al. The effects of high-intensity interval training, Nordic walking and moderate-to-vigorous intensity continuous training on functional capacity, depression and quality of life in patients with coronary artery disease enrolled in cardiac rehabilitation: A randomized controlled trial (CRX study). Prog Cardiovasc Dis. 2022;70:73–83. Tables Table 1 to 3 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table1.png Table 1. Baseline characteristics of participants in this study. Table2.png Table 2. Association of moderate-to-vigorous work (MVW) with HCV infection. Abbreviations: OR, odds ratio; CI, confidence interval. Non-adjusted model adjusted for: None. Adjust I model adjust for: age, race, HIV infection, alcohol use, smoking status, and education level. Adjust II model adjust for: age, race, HIV infection, alcohol use, smoking status, education level, ALT, TBil, globulin, and albumin. Table3.png Table 3. Mendelian randomization estimates of the association between physical activity and HCV infection. MR, Mendelian randomization; OR, odds ratio; CI, confidence interval. exposure.csv 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. 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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-5845762\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":403501126,\"identity\":\"9be2fe42-2552-4c6a-873e-fea49f26b4b9\",\"order_by\":0,\"name\":\"Liangchen Lei\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6ElEQVRIie3QPQrCMBiA4S8U2iXYNdLBKwSE4lDaq7QE4lLQAzhEBCfRteAlPEI1WK/QoYNF6OwkDiKmoI5tR8G8EMjwPeQHQKf7wXqA5mlY74haV+r5rcQEJL4EJVPOOhCAFN7EwNcDEq3EWoj0PCv8zXaRXTyaGmDJ466R4L26WFaxpMjGw5gWPcCc542ERIqYklESu05MKwMIdpvJoFTkWZPJzRlRiUQrIerHoqX01SmmA50IVheL1jIkOXf7K8qZ2fYW2zqV5f0mAzthFbk/PN+2ZNZIPkXie26X8bqg66BOp9P9YS/lkk0qOPvhHQAAAABJRU5ErkJggg==\",\"orcid\":\"\",\"institution\":\"Tianjin Medical University General Hospital\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Liangchen\",\"middleName\":\"\",\"lastName\":\"Lei\",\"suffix\":\"\"},{\"id\":403501127,\"identity\":\"70886c11-c1a8-4e02-a2a8-f617a46c38a6\",\"order_by\":1,\"name\":\"Chen Ouyang\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Tianjin Medical University General Hospital\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Chen\",\"middleName\":\"\",\"lastName\":\"Ouyang\",\"suffix\":\"\"},{\"id\":403501128,\"identity\":\"8a6f0df1-8b21-4221-90f1-45f6af46a745\",\"order_by\":2,\"name\":\"Pengpeng Liu\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Tianjin Medical University General Hospital\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Pengpeng\",\"middleName\":\"\",\"lastName\":\"Liu\",\"suffix\":\"\"},{\"id\":403501129,\"identity\":\"1a794be2-3ed2-4d4c-88c2-bca7be560db9\",\"order_by\":3,\"name\":\"Quanyan Liu\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Tianjin Medical University General Hospital\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Quanyan\",\"middleName\":\"\",\"lastName\":\"Liu\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2025-01-17 03:53:08\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-5845762/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-5845762/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":74241686,\"identity\":\"8cf41936-0597-4918-aaff-934f57cce51f\",\"added_by\":\"auto\",\"created_at\":\"2025-01-20 09:35:31\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":198811,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eFlowchart of participants selection in NHANES and Mendelian randomization study design. MR, Mendelian randomization.\\u003c/strong\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5845762/v1/e299941614155b4e57d86610.png\"},{\"id\":74240834,\"identity\":\"2ef25ddc-16c2-4dd5-beca-963cd8bf5ff8\",\"added_by\":\"auto\",\"created_at\":\"2025-01-20 09:27:31\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":97569,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eRestricted cubic spline (RCS) curve depicts the relationship between moderate-to-vigorous work and HCV infection status,\\u003c/strong\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5845762/v1/c75f98dcfddb47c9580f422f.png\"},{\"id\":74240843,\"identity\":\"a252f072-b4b8-48a1-9788-ce9fd0830b3c\",\"added_by\":\"auto\",\"created_at\":\"2025-01-20 09:27:32\",\"extension\":\"jpeg\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":139020,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eCausal effect of physical activity on HCV infection status.\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e(A) The scatter plots of MR analyses. (B) The funnel plot showing the results of each MR estimates. (C) The leave-one-out plot showing no single IV significantly influenced the causal effect of physical activity on HCV infection status\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image3.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5845762/v1/2a7845ef34011a574995b215.jpeg\"},{\"id\":74240844,\"identity\":\"2db44e3e-1c53-4e3d-925d-6d17340caec7\",\"added_by\":\"auto\",\"created_at\":\"2025-01-20 09:27:32\",\"extension\":\"jpeg\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":70020,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eCausal effect of HCV infection status on physical activity.\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e(A) The funnel plot showing the results of each MR estimates. (B) The leave-one-out plot showing no single IV significantly\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image4.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5845762/v1/36cb773b7dd0c1e6c6168536.jpeg\"},{\"id\":74244621,\"identity\":\"47543a4d-c61f-48aa-ad64-a897a238ed60\",\"added_by\":\"auto\",\"created_at\":\"2025-01-20 09:51:34\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":1172788,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5845762/v1/8d9b4153-3238-4712-b874-086b95dc7b54.pdf\"},{\"id\":74240836,\"identity\":\"1aa3d956-b09f-42cf-a0f5-c090778b3873\",\"added_by\":\"auto\",\"created_at\":\"2025-01-20 09:27:31\",\"extension\":\"png\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":301828,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eTable 1. Baseline characteristics of participants in this study.\\u003c/strong\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Table1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5845762/v1/c77279ccb2a15c2f4845822f.png\"},{\"id\":74241685,\"identity\":\"01965d4c-66f8-4f7a-b7bb-64244e855250\",\"added_by\":\"auto\",\"created_at\":\"2025-01-20 09:35:31\",\"extension\":\"png\",\"order_by\":2,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":37204,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eTable 2. Association of moderate-to-vigorous work (MVW) with HCV infection.\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAbbreviations: OR, odds ratio; CI, confidence interval.\\u003c/p\\u003e\\n\\u003cp\\u003eNon-adjusted model adjusted for: None. Adjust I model adjust for: age, race, HIV infection, alcohol use, smoking status, and education level. Adjust II model adjust for: age, race, HIV infection, alcohol use, smoking status, education level, ALT, TBil, globulin, and albumin.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Table2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5845762/v1/f05e63cb001a24fc2b3da3e9.png\"},{\"id\":74240838,\"identity\":\"5dad8adc-af2a-452f-8739-a563aa26375b\",\"added_by\":\"auto\",\"created_at\":\"2025-01-20 09:27:31\",\"extension\":\"png\",\"order_by\":3,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":151795,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eTable 3. Mendelian randomization estimates of the association between physical activity and HCV infection.\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eMR, Mendelian randomization; OR, odds ratio; CI, confidence interval.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Table3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5845762/v1/b618ea1f73c9880ae08f4fab.png\"},{\"id\":74240839,\"identity\":\"ea69d01d-b5c4-4d8e-b767-03a72abe873c\",\"added_by\":\"auto\",\"created_at\":\"2025-01-20 09:27:31\",\"extension\":\"csv\",\"order_by\":4,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":66994,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cbr\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"exposure.csv\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5845762/v1/6643a8f52807a938d0323e3b.csv\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Identifying the association between Physical Activity and HCV infection status: An observational study and Mendelian randomization analysis\",\"fulltext\":[{\"header\":\"Introduction\",\"content\":\"\\u003cp\\u003eHepatitis C is an infectious disease caused by the hepatitis C virus (\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e)(HCV). Approximately 71\\u0026nbsp;million people are infected with HCV, and hundreds of thousands die from HCV-related diseases annually(\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e). Although over 95% of hepatitis C patients can be cured with antiviral therapies like direct-acting antiviral agents (DAAs), no effective HCV vaccine exists due to HCV's genetic diversity and viral variability(\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e). Studies indicate that even after successful DAAs treatment, some patients may still experience long-term liver damage or other complications(\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e). Therefore, infection prevention remains a top priority in managing hepatitis C. Contemporary medical guidelines recommend managing and adjusting health-related behaviors(\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e), such as diet and physical activity, during viral infections to slow the progression of liver disease(\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e). Importantly, this highlights the impact of lifestyle factors on disease progression.\\u003c/p\\u003e \\u003cp\\u003ePhysical activity plays a vital role in hepatitis C prevention(\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e). Proper physical exercise can enhance liver function, slow liver disease progression, and improve patients' quality of life(\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e). However, due to varying patient conditions, physical abilities, and living environments, further clinical studies are needed to determine the most effective exercise type, intensity, and frequency for hepatitis C patients(\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e). Physical activity encompasses any bodily movement that elevates energy expenditure(\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e). The World Health Organization (WHO) advises adults to engage in at least 150 minutes of moderate-intensity aerobic exercise per week(\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e). Increasing evidence indicates that physical activity, across varying intensities, frequencies, and durations, can lower the risk of chronic diseases related to weight management(\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e), metabolic health(\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e), and mental health(\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e). As research progresses, it has become increasingly evident that physical activity may play a crucial role in infectious diseases by regulating immune function(\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e), modifying behavioral habits(\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e), and increasing awareness of protective measures. However, there’s limited research on the impact of physical activity on HCV progression (i.e., how quickly the virus damages the liver). No consistent findings have emerged regarding the potential influence of exercise on disease severity or outcomes(\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e). It’s challenging to conduct large-scale, controlled studies on these questions, especially when considering the long-term nature of HCV progression and the influence of other factors(\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e). At present, the relationship between physical activity and HCV infection status is a complex one, and the current research paints a mixed picture.\\u003c/p\\u003e \\u003cp\\u003eGenome-wide association studies (GWAS) have identified numerous genetic variants associated with complex phenotypes and are widely employed to provide optimal instrumental variables for Mendelian randomization (MR) analysis(\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e). Mendelian randomization (MR) analysis utilizes genetic variants as instrumental variables to examine the causal relationship between clinical traits and disease phenotypes(\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e). As genetic alleles are randomly assigned during meiosis and remain unaffected by environmental factors, MR surpasses observational studies in controlling for confounding factors and reverse causality(\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eIn this study, we utilized data from the National Health and Nutrition Examination Survey (NHANES) to examine the association between physical activity and HCV infection status, adjusting for several potential confounders. Subsequently, we assessed the causal relationship between physical activity and HCV infection status and conducted bidirectional two-sample MR analyses to explore their causal effects.\\u003c/p\\u003e \\n\\n\\n\\n\"},{\"header\":\"Methods\",\"content\":\"\\u003ch3\\u003e1. Study design in NHANES\\u003c/h3\\u003e\\u003cp\\u003eIn this cross-sectional study, we combined data from the 2017–2020 continuous NHANES (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://www.cdc.gov/nchs/nhanes/\\u003c/span\\u003e\\u003cspan address=\\\"https://www.cdc.gov/nchs/nhanes/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e) to form our study population. As shown in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e, We included adult participants aged 19 to 79 years (n = 9693) and excluded individuals without tests for HCV cRNA (n = 1424), HCV antibody (n = 1239), ALT (n = 109), and TB (n = 1). Among individuals who tested positive for HCV RNA, we further excluded those who lacked confirmed Hepatitis C antibody tests (n = 14), as it cannot distinguish between resolved and chronic HCV infections. Thus, the final analytic population comprised 6906 participants.\\u003c/p\\u003e\\u003cp\\u003e \\u003c/p\\u003e\\u003ch2\\u003e2. Definition of Physical Activity and HCV infection status in NHANES\\u003c/h2\\u003e\\u003cp\\u003eThe Global Physical Activity Questionnaire was used to collect weekly physical activity data at the respondent level. Physical activity levels were classified into two categories: vigorous work or recreational activities, and moderate work or recreational activities(\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e). Vigorous work or recreational activities were defined as those causing a significant increase in breathing or heart rate, sustained for at least 10 minutes(\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e). Moderate work or leisure activities were defined as activities causing a slight increase in breathing or heart rate, sustained for at least 10 minutes. We categorized exercise into three types based on duration and intensity: moderate-vigorous work, moderate-vigorous activities, and sedentary activity(\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e). HCV infection status was determined by HCV antibody screening, confirmation, and/or HCV-RNA tests. Participants testing positive for HCV-RNA and/or the anti-HCV antibody confirmation test were classified as having HCV infection(\\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e).\\u003c/p\\u003e\\u003ch3\\u003e3. Covariates in NHANES\\u003c/h3\\u003e\\u003cp\\u003eWe collected the following covariates: age, race, HIV infection status, alcohol use, smoking status, education level, alanine aminotransferase (ALT), total bilirubin (TBil), globulin, and albumin. Age was categorized into 18–39, 40–59, and 60–80 years. Race was classified into Hispanic, White, Black, Asian, and other races. Alcohol use was categorized as never, less than once a month, once a month or more, and other. Smoking status was categorized as every day, not at all, and some days. Education level was categorized as college graduate or above, high school graduate/GED or below, and some college or an associate degree.\\u003c/p\\u003e\\u003ch3\\u003e4. MR study design\\u003c/h3\\u003e\\u003cp\\u003eAs illustrated in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e, a bidirectional two-sample Mendelian Randomization (MR) analysis was conducted to evaluate the causal relationship between physical activity and HCV infection status. Instrumental variables (IVs) for physical activity were extracted from a recent GWAS that included 91,105 individuals of European ancestry from the UK Biobank(\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ewww.ebi.ac.uk/gwas/\\u003c/a\\u003e\\u003c/span\\u003e\\u003cspan address=\\\"http://www.ebi.ac.uk/gwas/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e). This GWAS identified 14 loci associated with device-measured physical activity and sleep duration. In the GWAS by Doherty et al.(\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e), participants who consented to wear a wrist-worn accelerometer for 7 days also underwent genome-wide genotyping and imputation. They generated a continuous phenotype for overall activity time and applied a machine-learning model using balanced random forests with Markov confusion matrices to classify individuals into one of four activity states: sleep, sedentary, walking, or moderate intensity. Summary data for HCV infection from a GWAS were obtained from the UK Biobank, which included 219 cases and 456,129 controls of European ancestry(\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e). All participants were of European ancestry, minimizing racial stratification bias. Details of the GWAS data used in these MR analyses are provided in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e.\\u003c/p\\u003e\\u003ch3\\u003e5. Selection of genetic instruments\\u003c/h3\\u003e\\u003cp\\u003eThe selected instrumental variables (IVs) must satisfy three assumptions: (a) IVs are significantly associated with the exposure; (b) IVs influence the outcome only through the exposure; and (c) IVs are not related to any confounders between the exposure and outcome (\\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e). To identify IVs for physical activity, we selected single-nucleotide polymorphisms (SNPs) significantly associated with physical activity (p \\u0026lt; 5 × 10⁻⁸, linkage disequilibrium [LD] r² \\u0026lt; 0.001). Finally, SNPs were identified as IVs significantly associated with physical activity and HCV infection, respectively. To perform reverse MR analysis between HCV infection status with physical activity, a more relaxed threshold was applied (p \\u0026lt; 5 × 10⁻⁵). Weak genetic instruments were excluded if the F-statistic was less than 10.\\u003c/p\\u003e\\u003ch3\\u003e6. Statistical analyses\\u003c/h3\\u003e\\u003cp\\u003eData from NHANES were used for the observational analysis. Sample weights were applied throughout the analysis to account for the multistage probability sampling in NHANES. Baseline characteristics were compared between the HCV infection group and the normal group. Logistic regression analyses were conducted to examine the association between physical activity and HCV infection status. Three multivariate regression models were constructed: Model 1 (unadjusted); Model 2 (adjusted for age, race, HIV infection, alcohol use, smoking status, and education level); Model 3 (adjusted for age, race, HIV infection, alcohol use, smoking status, education level, ALT, TBil, globulin, and albumin). Statistical analyses were performed using R, with a significance threshold of P \\u0026lt; 0.05. Restricted cubic spline curves were fitted to the logistic regression model with 3 knots. Mendelian Randomization (MR) analyses were primarily conducted using the random-effects inverse-variance weighted (IVW) method to estimate the causal relationship between physical activity and HCV infection status. The IVW method combines the Wald ratio for each SNP, assuming all instruments have causal effects (\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e). Supplementary methods for the IVW estimate included the weighted median, MR-Egger, simple mode, and weighted mode, which provide more robust estimates in broader contexts but are less efficient (with wider confidence intervals). The intercept of the MR-Egger regression was used to estimate directional pleiotropy(\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e). The Cochran's Q test was performed, and a funnel plot(\\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e) was generated to assess heterogeneity. Additionally, the leave-one-out method was used to evaluate the robustness and consistency of the results. All statistical analyses were conducted using the TwoSampleMR package in R version 4.2.2 (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://www.r-project.org/\\u003c/span\\u003e\\u003cspan address=\\\"https://www.r-project.org/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e). P-value \\u0026lt; 0.05 was considered significant in the MR-Egger regression and Cochran's Q test.\\u003c/p\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003e1. Baseline characteristics\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAs shown in Table 1, among the 6906 participants, the prevalence of resolved and chronic HCV infection was 1.17% (81 individuals) and 1.08% (75 individuals), respectively. Compared to individuals without HCV infection (n = 6750), those with resolved or chronic HCV infection tended to be older and were more likely to have HIV infection, a history of stroke, lower education levels, and higher ALT, globulin, and albumin levels. No significant differences were observed in race, alcohol use, or TBil. For physical activity of all intensities, participants who engaged in more than 150 minutes of moderate-to-vigorous work per week were more likely to have HCV infection. Interestingly, no statistically significant difference in HCV infection was found among individuals who engaged in more than 150 minutes of physical activity per week.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e2. Association between Physical Activity and HCV infection status\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eStatistical results from various populations indicated that moderate-to-vigorous work (MVW) was closely associated with HCV infection. Multivariate logistic regression analyses were then used to investigate the association between moderate-to-vigorous work and HCV infection status. The results indicated that even after adjusting for multiple models, moderate-to-vigorous work remained significantly positively associated with HCV infection status (unadjusted model: OR = 2.69, 95% CI = 1.40-5.20; fully adjusted model: OR = 2.46, 95% CI = 1.02\\u0026ndash;5.92), as shown in Table 2. As shown in Figure 2, a restricted cubic spline (RCS) curve was generated to visually depict the relationship between moderate-to-vigorous work and HCV infection status, based on Model 3. The RCS analysis revealed no significant nonlinear association between moderate-to-vigorous work and HCV infection status (p for nonlinearity = 0.1799; reference = 810min).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e3. Causal effect of Physical Activity on HCV infection status\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAll instrumental variables (IVs) for Physical Activity were included in the Mendelian randomization (MR) analysis (Supplementary Table 1). None of the IVs were significantly associated with HCV infection status or any confounders. As shown in Table 3, the MR analysis indicated that physical activity had a significant causal effect on HCV infection status in the inverse-variance weighted (IVW) model (OR=1.366, 95% CI: 1.121\\u0026ndash;1.663, p = 0.002). A similar estimate was observed in the weighted median model (OR=1.499, 95% CI: 1.145\\u0026ndash;1.962, p = 0.003). The scatter plot is shown in Fig. 3A The intercept of the MR-Egger regression was 0.008 (p=0.507), indicating no evidence of pleiotropy. The Cochran\\u0026apos;s Q test indicated no heterogeneity (p=0.0556). The funnel plot showed symmetry, further indicating no heterogeneity (Fig. 3B). Additionally, leave-one-out analysis showed that no single IV significantly influenced the causal effect of depression on constipation (Fig. 3C).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e4. Causal effect of HCV infection status on Physical Activity\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eSince a p-value \\u0026lt;5 \\u0026times; 10\\u003csup\\u003e-8\\u0026nbsp;\\u003c/sup\\u003ewould yield too few IVs, we adjusted the threshold to p \\u0026lt;5\\u0026times;10\\u003csup\\u003e-5\\u003c/sup\\u003e. A total of 634 HCV infection status-related IVs were included in the MR analysis (Supplementary Table 2). None of the IVs were significantly associated with physical activity or any confounders. As shown in Table 3, there was no significant causal effect of HCV infection status on physical activity (IVW: OR = 1.000, 95% CI: 0.997\\u0026ndash;1.002, p = 0.724). The Egger intercept was 0.0008 (p = 0.647), indicating no evidence of pleiotropy. The Cochran\\u0026apos;s Q test indicated no heterogeneity (p = 0.226). The funnel plot didn\\u0026rsquo;t show symmetry, indicating no heterogeneity (Fig. 4A). No significant changes were observed by removing any single IV, as confirmed by the leave-one-out method (Fig. 4B).\\u003c/p\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eThis observational study confirmed a positive association between physical activity and HCV infection status. Additionally, the type of physical activity was positively associated with the risk of HCV infection. A significant causal effect of physical activity on HCV infection status was identified through two-sample MR analyses. In contrast, no significant causal effect of HCV infection status on physical activity was found in the reverse MR analysis.\\u003c/p\\u003e \\u003cp\\u003eThe liver is a crucial organ responsible for regulating energy metabolism(\\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e). Hepatitis C is frequently associated with metabolic disorders, including insulin resistance(\\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e) and fatty liver disease(\\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e). Numerous studies indicate that physical activity plays a vital role in managing HCV infection by reducing liver fat accumulation(\\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e), improving liver metabolism, and enhancing immune system function(\\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e), thus increasing the body's ability to combat HCV infection(\\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e). Our observational studies found no association between sedentary behavior or weekly moderate-to-vigorous physical activities and HCV infection. However, moderate-to-vigorous work for more than 150 minutes per week significantly increased the risk of HCV infection. The risk of HCV infection significantly increased when moderate-to-vigorous work more than 810 minutes per week. This conclusion was further validated at the SNP level through a bidirectional Mendelian randomization (MR) experiment(\\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e). These findings suggest that while physical activity may have some benefits for HCV infection, its effects vary depending on the type of activity.\\u003c/p\\u003e \\u003cp\\u003eDespite significant advances in HCV treatment, challenges in prevention persist(\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e). It showed that sedentary or leisure-based high-intensity physical activity (over 150 minutes per week) had minimal impact on HCV infection risk, whereas work-based high-intensity physical activity significantly increased the risk. These findings suggest that high-intensity work negatively impacts health. In conclusion, high-intensity work, in addition to contributing to chronic fatigue(\\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e), cardiovascular disease(\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e), and psychological disorders(\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e), can reduce quality of life by increasing the risk of HCV infection.\\u003c/p\\u003e \\u003cp\\u003eHowever, this study has several limitations. First, the NHANES database lacks genotypic data, preventing polygenic score analysis to explore potential genetic associations between physical activity and HCV infection status. Second, the MR analysis was based on GWAS data from a European population. High-quality GWAS data on physical activity are lacking. In our MR analysis, due to the absence of data on physical activity categories, we substituted overall physical activity for high-intensity work. However, observational studies suggest that only high-intensity work is associated with HCV infection, supporting the validity of this substitution. Finally, variability in work environments and tasks among high-intensity workers may affect the accuracy of the statistics. Further investigation is required to improve the credibility of these findings.\\u003c/p\\u003e \\u003cp\\u003eAll in all, our study suggests that moderate-to-vigorous work causally affects HCV infection status, rather than vice versa. Individuals should limit their moderate-to-vigorous work to less than 810 minutes per week. This finding underscores the need for further research on the relationship between work intensity and HCV infection. This is crucial not only for populations in high-risk occupations but also for improving global HCV infection prevention efforts.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgements\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eWe are very grateful for the data sharing of NHANES and GWAS. We want to acknowledge the participants and investigators of the\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003eNHGRI-EBI GWAS Catalog study.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConflict of Interest\\u003c/strong\\u003e: The authors declare that they have no competing interests.\\u0026nbsp;The results of the study are presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation.\\u0026nbsp;The results of the present study do not constitute endorsement by the American College of Sports Medicine.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthors\\u0026apos; contributions\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eLiangchen Lei and Quanyan Liu conceived and designed the study.\\u0026nbsp;Liangchen Lei, Pengpeng Liu and Quanyan Liu were responsible for data analysis, collating, and writing the manuscript. Chen Ouyang contributed to data colletion.\\u0026nbsp;All authors read and approved the final manuscript.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAvailability of data and materials\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe datasets generated and analyzed during the current study are available in the NHANES (https://www.cdc.gov/nchs/nhanes/). GWAS data for physical activity: www.ebi.ac.uk/gwas/studies/GCST006912.GWAS data for hepatitis C virus infection: www.ebi.ac.uk/gwas/studies/GCST90041714.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eEthics approval and consent to participate\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable. The data analyzed in this study is de-identified data obtained from NHANES and GWAS summary data, and the ethics approval and consent to participate are not required.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eCoppola N, Alessio L, Onorato L, et al. Epidemiology and management of hepatitis C virus infections in immigrant populations. Infect Dis Poverty. 2019;8(1):17.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLy KN, Hughes EM, Jiles RB, Holmberg SD. Rising Mortality Associated With Hepatitis C Virus in the United States, 2003\\u0026ndash;2013. Clin Infect Dis. 2016;62(10):1287\\u0026ndash;8.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMosa AI, Campo DS, Khudyakov Y et al. 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Br J Anaesth. 2022;129(3):355\\u0026ndash;65.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHuang Y, Xu P, Fu X, et al. The effect of triglycerides in the associations between physical activity, sedentary behavior and depression: An interaction and mediation analysis. J Affect Disord. 2021;295:1377\\u0026ndash;85.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSilva JR, Rumpf MC, Hertzog M, et al. Acute and Residual Soccer Match-Related Fatigue: A Systematic Review and Meta-analysis. Sports Med. 2018;48(3):539\\u0026ndash;83.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHoare E. The associations between sedentary behaviour and mental health among adolescents: a systematic review. 2016.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eChen Y-C, Wang H-W, Huang Y-T, Jiang M-Y. Association of hepatitis C virus infection status and genotype with kidney disease risk: A population-based cross-sectional study. PLoS ONE. 2022;17(7):e0271197.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eDoherty A, Smith-Byrne K, Ferreira T, et al. GWAS identifies 14 loci for device-measured physical activity and sleep duration. Nat Commun. 2018;9(1):5257.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eJiang L, Zheng Z, Fang H, Yang J. A generalized linear mixed model association tool for biobank-scale data. Nat Genet. 2021;53(11):1616\\u0026ndash;21.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSmith GD, Ebrahim S. What can mendelian randomisation tell us about modifiable behavioural and environmental exposures?BMJ.2005;330.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBowden J, Davey Smith G, Burgess S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int J Epidemiol. 2015;44(2):512\\u0026ndash;25.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBurgess S, Thompson SG. Interpreting findings from Mendelian randomization using the MR-Egger method. Eur J Epidemiol. 2017;32(5):377\\u0026ndash;89.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHemani G, Zheng J, Elsworth B, et al. The MR-Base platform supports systematic causal inference across the human phenome. eLife. 2018;7:e34408.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHan H-S, Kang G, Kim JS, Choi BH, Koo S-H. Regulation of glucose metabolism from a liver-centric perspective. Exp Mol Med. 2016;48(3):e218\\u0026ndash;218.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSerfaty L, Capeau J, Hepatitis C. insulin resistance and diabetes: clinical and pathogenic data. Liver Int. 2009;29(s2):13\\u0026ndash;25.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLee J, Gil D, Park H et al. A multicellular liver organoid model for investigating hepatitis C virus infection and nonalcoholic fatty liver disease progression. Hepatology. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1097/HEP.0000000000000683\\u003c/span\\u003e\\u003cspan address=\\\"10.1097/HEP.0000000000000683\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGao Y, Zhang W, Zeng L-Q, et al. Exercise and dietary intervention ameliorate high-fat diet-induced NAFLD and liver aging by inducing lipophagy. Redox Biol. 2020;36:101635.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMascar\\u0026oacute; CM, Bouzas C, Montemayor S, et al. Effect of a Six-Month Lifestyle Intervention on the Physical Activity and Fitness Status of Adults with NAFLD and Metabolic Syndrome. Nutrients. 2022;14(9):1813.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eYou M. Role of Physical Activity in the Prevention and Treatment of Influenza: A Review. Sports Med - Open. 2023;9(1):115.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLega IC, Lipscombe LL, Review. Diabetes, Obesity, and Cancer\\u0026mdash;Pathophysiology and Clinical Implications. Endocr Rev. 2020;41(1):33\\u0026ndash;52.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCsete J, Kamarulzaman A, Kazatchkine M, et al. Public health and international drug policy. Lancet. 2016;387(10026):1427\\u0026ndash;80.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eJeffery M. Diaphragmatic Fatigue and High-intensity Exercise in Patients with Chronic Obstructive Pulmonary Disease. AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE.2000;161.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eReed JL, Terada T, Cotie LM, et al. The effects of high-intensity interval training, Nordic walking and moderate-to-vigorous intensity continuous training on functional capacity, depression and quality of life in patients with coronary artery disease enrolled in cardiac rehabilitation: A randomized controlled trial (CRX study). Prog Cardiovasc Dis. 2022;70:73\\u0026ndash;83.\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"},{\"header\":\"Tables\",\"content\":\"\\u003cp\\u003eTable 1 to 3 are available in the Supplementary Files section.\\u003c/p\\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\":\"GWAS, Moderate-to-vigorous work, NHANSE, Types of Physical activity\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-5845762/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-5845762/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003ch2\\u003ePurpose\\u003c/h2\\u003e \\u003cp\\u003eTo investigate the association and causality between physical activity and hepatitis C virus (HCV) infection.\\u003c/p\\u003e\\u003ch2\\u003eMethods\\u003c/h2\\u003e \\u003cp\\u003eIn this cross-sectional study, we conducted a bidirectional two-sample Mendelian Randomization (MR) analysis using data from the GWAS database. The analytic population was divided into three categories based on hepatitis C virus infection outcomes, and statistical differences were analyzed with covariates. Additionally, Restricted Cubic Spline (RCS) analysis was applied to examine the nonlinear relationship between physical exercise and hepatitis C virus infection. Instrumental variables were selected with a threshold of P\\u0026thinsp;\\u0026lt;\\u0026thinsp;5*10⁻⁸, and the causal relationships were assessed using IVW, MR-Egger, Weighted Median, Weighted Mode, and Simple Mode methods. Cochran's Q test was used to assess and exclude data heterogeneity.\\u003c/p\\u003e\\u003ch2\\u003eResults\\u003c/h2\\u003e \\u003cp\\u003eIn the population data analysis, the moderate-to-vigorous work (MVW) variable showed a significant association with HCV infection (p\\u0026thinsp;=\\u0026thinsp;0.006). MVW demonstrated a positive association with HCV infection (OR\\u0026thinsp;=\\u0026thinsp;2.46, 95% CI\\u0026thinsp;=\\u0026thinsp;1.02\\u0026ndash;5.92). RCS analysis indicated that the risk of HCV infection significantly increased when MVW exceeded 810 minutes per week. MR analysis indicated that MVW had a unidirectional effect on HCV infection (IVW model: OR\\u0026thinsp;=\\u0026thinsp;1.366, 95% CI: 1.121\\u0026ndash;1.663, p\\u0026thinsp;=\\u0026thinsp;0.002), and heterogeneity was excluded from the analysis.\\u003c/p\\u003e\\u003ch2\\u003eConclusions\\u003c/h2\\u003e \\u003cp\\u003eIn the context of HCV infection, the primary factor influencing risk is not the duration of physical activity, but the type. High-intensity physical activity significantly elevates the risk of HCV infection. It may be prudent to manage work hours responsibly to minimize physical strain.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Identifying the association between Physical Activity and HCV infection status: An observational study and Mendelian randomization analysis\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-01-20 09:27:26\",\"doi\":\"10.21203/rs.3.rs-5845762/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\":\"52f15019-9659-47af-b2b1-e0010b4b345d\",\"owner\":[],\"postedDate\":\"January 20th, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2025-01-21T06:23:14+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2025-01-20 09:27:26\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-5845762\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-5845762\",\"identity\":\"rs-5845762\",\"version\":[\"v1\"]},\"buildId\":\"8U1c8b4HqxoKbykW_rLl7\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}