The causal relationship between cathepsins and hepatocellular carcinoma risk: A Mendelian randomization study

The causal relationship between cathepsins and hepatocellular carcinoma risk: 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 The causal relationship between cathepsins and hepatocellular carcinoma risk: A Mendelian randomization study Lishi Yang, Fengyao Mao, Yuhan Li, Mingjia Lin, Fuhua Sun This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4206143/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Abnormal expression of cathepsins has been reported in patients with hepatocellular carcinoma (HCC). However, the evidence about the causal role of cathepsins in facilitating or preventing HCC is lacking. Systematically studying the causality between cathepsins and HCC would help provide novel targets for screening and prevention of HCC. Methods We conducted twosample Mendelian randomization (MR) analyses. The data of cathepsins and HCC for analysis were derived from publicly available genetic summary data. The causal effects were estimated with inverse variance weighted, MR-Egger and weighted median. Sensitivity analyses were implemented with Cochran's Q test, MR-Egger intercept test, MR-PRESSO and leave-one-out analysis. Results The results of univariate MR analysis show that elevated cathepsin S levels increase the risk of HCC. On the other hand, reverse MR analyses indicate that HCC may raise cathepsin Z levels. According to the results of multivariable analysis using nine cathepsin variables, an increased risk of HCC is associated with elevated levels of cathepsin S. Conclusion The evidence that cathepsin S is associated with HCC in a causal way provides a novel insight into the underlying mechanisms of HCC by integrating genomics with cathepsins, and has an implication for HCC screening and prevention. Cathepsin Hepatocellular carcinoma Mendelian randomization analysis Causality Figures Figure 1 Figure 2 1. Introduction Primary liver cancer has become the sixth most common malignancy and the third leading cause of cancer-related death worldwide [ 1 ]. As the most common histological type of primary liver cancer, hepatocellular carcinoma (HCC) accounts for the great majority of incidence and mortality of liver cancer cases [ 2 , 3 ]. At present, the clinical diagnosis of HCC is mainly determined by the imaging and evaluation of serum alpha-fetoprotein (AFP), but HCC is often found in an advanced stage and cannot be cured. It is estimated that HCC incidence and mortality will continue to rise over the next 20 years as the world population grows [ 4 ]. In this context, there is an urgent need for reliable and easily detectable biomarkers to identify and monitor the occurrence and progression of HCC as early as possible. Cathepsins are one of the lysosomal protease families and have a wide range of functions [ 5 ]. Considering that cathepsins may be involved in the complex physiological and pathological processes of human beings, studying their relationship with human diseases has aroused great interests among researchers [ 6 ]. There are also many studies on the potential relationship between cathepsins and tumors, which means that certain cathepsins are involved in the occurrence and development of tumors. Numbers of reports have found that cathepsin K promotes breast cancer [ 7 ], lung cancer, prostate cancer [ 8 , 9 ] and soft tissue sarcoma [ 10 , 11 ]. Cathepsin B is associated with many tumor progression, including breast cancer [ 12 ], lung cancer [ 13 ] and pancreatic cancer [ 14 ]. Cathepsin C has been linked to ovarian cancer progression and metastasis [ 15 ]. Cathepsin B, D, E and L contribute to the development of digestive cancers [ 16 ]. However, there is currently a lack of comprehensive and systematic research to evaluate the causal relationship between cathepsins and HCC. Therefore, due to the inherent limitations of traditional observational researches, it is not possible to determine cathepsins that promote the development of HCC based on existing evidence. Mendelian randomization (MR), which can infer the causal relationship between exposure and outcomes, is a widely used analytical approach [ 17 ]. MR analysis is an important alternative method in the absence of randomized controlled studies, as it can provide reliable evidence of the causal relationship between exposure and disease risk [ 18 ]. In this context, we explore the causal relationship between different types of cathepsins and HCC through univariate and multivariate MR methods. The findings of this work provide feasible strategies for establishing cancer screening and prevention in clinical practice. 2. Methods and materials 2.1. Instrumental variables Utilizing an instrumental variable from the INTERVAL study facilitated the assessment of cathepsin concentrations [ 19 ]. The reanalysis of data previously made public negated the necessity for further ethical consent. To identify genetic variants associated with cathepsins, a multi-step process was implemented. Initially, due to the scarcity of SNPs meeting the threshold for genome-wide significance, the criteria for association were adjusted to p < 5×10⁻⁶, with a pairwise linkage disequilibrium (LD) of r² < 0.001 within a 10000 kb distance. This approach facilitated the selection of top independent SNPs, aligning with the methodology described by Li et al [ 20 ]. 2.2. Genetic association of SNPs with HCC risk Statistics from GWAS related to HCC were derived from the TRICL, accessible through https://www.ebi.ac.uk/gwas , involving 1,866 cases of HCC and 195,745 control subjects. Comprehensive information regarding the diagnostic criteria, demographic details, and measures of quality control is documented in the foundational GWAS documentation. 2.3. Statistics and reproducibility A robust MR framework adheres to three core prerequisites: Initially, there must be a significant correlation between instrumental variables (IVs) and exposure. Next, IVs should remain unlinked to any confounders. Lastly, the IVs impact on the outcome is mediated solely through the exposure [ 21 ]. Violations of the latter two conditions may indicate the presence of horizontal pleiotropy, which is assessable through diverse statistical methodologies [ 21 ]. The inverse variance weighted (IVW) approach under a random-effects model synthesizes Wald ratios from individual SNPs to generate a consolidated estimate, serving as the primary technique in MR research [ 23 , 24 ]. Essentially, the IVW model presupposes the effectiveness of all genetic variants, making it as a highly efficacious strategy for MR analysis. To ensure the MR findings' solidity, the weighted median [ 25 ] and MR-Egger [ 26 ], have been applied as complementary methods. The "TwoSampleMR" software package (Version 0.5.8) within the R programming environment (Version 4.3.2) facilitated all related statistical computations. Following the identification of significant estimates (with IVW p-values less than 0.05), a series of sensitivity analyses were performed to affirm the validity of the MR assumptions. The Cochran’s Q test played a crucial role in unveiling heterogeneity among studies, with a p-value less than 0.05 indicating significant heterogeneity [ 27 ]. To pinpoint SNPs contributing to bias, the MR-PRESSO global test was employed, while the MR-Egger intercept facilitated the detection of horizontal pleiotropy [ 22 , 23 ]. Additionally, the MR-PRESSO outlier test served to examine and rectify horizontal pleiotropy [ 24 ]. The leave-one-out (LOO) strategy was integral in discerning influential data points affecting the collective IVW outcomes, further solidifying the conclusions' robustness. Potential cathepsins implicated in HCC progression satisfied several criteria: consistent directional and amplitude coherence across MR techniques; absence of detected heterogeneity or pleiotropy; and the lack of significant data points in LOO analyses. Multivariable MR is an advancement of univariate MR. In the study, multivariable MR was applied to analyze the causal effects of multiple cathepsins on HCC. The "Mendelian Randomization" software package facilitated the estimation of direct causal impacts from each exposure in a single analysis [ 23 ]. Reverse MR analyses, with HCC as the exposure and cathepsins as the outcome, were conducted to evaluate the reverse causal relationships, utilizing the aforementioned GWAS dataset. 3. Results 3.1. Causal effect from cathepsins to HCC To assess the influence of various cathepsins on HCC risk, an initial analysis using Two-Sample Mendelian Randomization (MR) focused on nine specific cathepsins (cathepsin B, E, F, G, H, L2, O, S, and Z) in relation to HCC was performed. The findings from the univariate MR approach indicated that elevated levels of cathepsin S increased the risk of HCC (IVW: p = 0.036, OR = 1.183, 95% confidence interval (CI) = 1.010–1.386). Similar risk assessments were obtained through the weighted median method (OR = 1.287, 95% CI = 1.030–1.610, p = 0.026) and MR-Egger regression analysis (OR = 1.936, 95% CI = 0.816–4.590, p = 0.161), although the correlation derived from MR-Egger regression did not reach statistical significance (Table 1 ). Heterogeneity assessments via Cochran’s Q test revealed no significant heterogeneity, with an IVW analysis yielding a p-value of 0.519 and MR-Egger analysis resulting in a p-value of 0.546 (Table 2 ). The absence of a significant intercept (intercept = -0.076; SE = 0.067, p = 0.279) suggested no horizontal pleiotropy was observed. This was corroborated by the MR-PRESSO global test (p-value = 0.530). The impact assessment of individual SNP is depicted in Fig. 1 a. Additionally, the leave-one-out sensitivity analysis demonstrated that no single SNP significantly deviated from the general influence of cathepsin S on HCC risk (Fig. 1 b). Table 1 Causality of cathepsins on HCC estimated by univariable Mendelian randomization analysis. Cathepsin nSNP Inverse variance weighted MR-Egger Weighted median OR(95%CI) p-value OR(95%CI) p-value OR(95%CI) p-value Cathepsin B 5 0.896(0.710–1.130) 0.355 1.001(0.550–1.822) 0.996 0.965(0.768–1.214) 0.767 Cathepsin E 7 0.868(0.745–1.011) 0.070 0.995(0.682–1.452) 0.983 0.879(0.708–1.092) 0.245 Cathepsin F 6 0.943(0.784–1.134) 0.535 0.807(0.489–1.332) 0.450 0.932(0.792–1.096) 0.396 Cathepsin G 3 1.139(0.883–1.468) 0.314 1.058(0.458–2.443) 0.916 1.124(0.830–1.522) 0.449 Cathepsin H 6 1.041(0.924–1.173) 0.502 1.093(0.930–1.284) 0.337 1.061(0.948–1.187) 0.298 Cathepsin L2 6 1.008(0.804–1.263) 0.943 2.260(0.984–5.190) 0.126 1.026(0.770–1.366) 0.858 Cathepsin O 6 1.063(0.874–1.293) 0.536 0.881(0.349–2.223) 0.802 1.168(0.905–1.507) 0.232 Cathepsin S 13 1.183(1.010–1.386) 0.036 1.936(0.816–4.590) 0.161 1.287(1.030–1.610) 0.026 Cathepsin Z 7 0.922(0.785–1.083) 0.326 0.726(0.522–1.011) 0.116 0.848(0.712–1.011) 0.066 Table 2 Pleiotropy and heterogeneity analyses of Two-Sample MR between cathepsin S and HCC. MR-Egger intercept MR-PRESSO global MR-IVW MR-Egger intercept p-value p-value Q Q-df Q-pval Q Q-df Q-pval -0.076 0.279 0.530 11.112 12 0.519 9.821 11 0.546 3.2. Causal effect from HCC to cathepsins In investigating the potential for a bidirectional causal relationship, reverse MR analyses were executed. These analyses revealed no evidence of a reverse causation from cathepsin S to HCC (Table 3 ). While, findings from the reverse MR study suggested that HCC might lead to increased levels of cathepsin Z, as indicated by IVW (p = 0.025, OR = 1.028, 95% CI = 1.003–1.054) and weighted median (p = 0.029, OR = 1.040, 95% CI = 1.003–1.078). Meanwhile, a similar effect was observed with MR-Egger regression (p = 0.103, OR = 1.030, 95% CI = 0.994–1.066), although the association did not reach statistical significance. Furthermore, the MR-Egger intercept (p = 0.921) and MR-PRESSO global test (p = 0.451) showed no indication of directional pleiotropy. With Cochran’s Q test results yielding p-values of 0.382 (IVW) and 0.341 (MR-Egger) (Table 4 ), heterogeneity was also not detected. Table 3 Reverse Mendelian randomization analysis to estimate causality between HCC and cathepsins. Inverse variance weighted MR-Egger Weighted median exposure outcome nSNP OR (95%CI) p-value OR (95%CI) p-value OR (95%CI) p-value HCC Cathepsin B 42 1.005(0.981–1.030) 0.655 1.001(0.967–1.036) 0.927 1.005(0.969–1.043) 0.755 Cathepsin E 42 1.020(0.993–1.047) 0.145 1.018(0.981–1.057) 0.342 1.020(0.983–1.058) 0.273 Cathepsin F 42 1.023(0.998–1.048) 0.061 1.024(0.991–1.059) 0.157 1.011(0.972–1.051) 0.580 Cathepsin G 42 1.009(0.983–1.035) 0.477 1.004(0.969–1.040) 0.810 1.018(0.982–1.055) 0.322 Cathepsin H 42 1.016(0.988–1.044) 0.245 0.992(0.956–1.028) 0.676 1.001(0.967–1.037) 0.930 Cathepsin L2 42 0.983(0.954–1.012) 0.258 0.972(0.933–1.012) 0.183 0.961(0.926–0.998) 0.041 Cathepsin O 42 1.009(0.983–1.036) 0.483 0.980(0.947–1.014) 0.266 0.992(0.957–1.029) 0.689 Cathepsin S 42 0.995(0.971–1.020) 0.745 1.007(0.974–1.042) 0.661 1.008(0.972–1.046) 0.646 Cathepsin Z 42 1.028(1.003–1.054) 0.025 1.030(0.994–1.066) 0.103 1.040(1.003–1.078) 0.029 Table 4 Pleiotropy and heterogeneity analyses of Two-Sample MR between HCC and cathepsin Z. MR-Egger intercept MR-PRESSO global MR-IVW MR-Egger intercept p-value p-value Q Q-df Q-pval Q Q-df Q-pval -0.000 0.921 0.451 43.084 41 41 43.073 40 0.546 3.3. Causal effect from multiple cathepsins to HCC To further investigate the genetic predisposition involving multiple cathepsins that influence the risk of HCC, a multivariable MR analysis was carried out. The analysis revealed that, even when adjustments were made for the levels of other cathepsins, a significant association persisted between elevated levels of cathepsin S and a higher risk of developing HCC, as demonstrated by both IVW (p = 0.031, OR = 1.208, 95% CI = 0.843–1.508) and MR-Egger analysis (p = 0.033, OR = 1.207, 95% CI = 1.034–1.379) (Fig. 2 ). This relationship was not observed with other cathepsins. Furthermore, heterogeneity analyses using Cochran’s Q test showed no significant heterogeneity (IVW p-value = 0.303, MR-Egger p-value = 0.302), and the MR-Egger intercept analysis indicated the absence of horizontal pleiotropy (p = 0.832). 4. Discussion The significant prevalence and mortality associated with HCC have placed a considerable strain on public health. AFP, though widely utilized as a biomarker for HCC, exhibits limitations, especially in the early diagnosis of the disease, underscoring the vital importance of effective screening and preventative strategies[ 25 ]. Proteolytic activities, pivotal in tumor development and progression, have garnered interest in oncological researchers, with the lysosomal protease family member, cathepsin, being of notable focus. Previous researches have highlighted several cathepsins in HCC. For example, findings by Wang et al. demonstrated a significant increase in cathepsin A in HCC tissues compared to normal liver samples [ 26 ], while Luo et al. associated high levels of cathepsin A with adverse clinical outcomes in HCC patients [ 27 ]. Additionally, HCC patients with lower levels of cathepsin D have been shown to exhibit markedly improved survival rates than those with elevated levels [ 28 ]. Despite the above literatures suggesting cathepsins' role in HCC, epidemiological studies have not conclusively demonstrated a link between cathepsins and HCC. In this pioneering study, we embarked on an exposure-wide MR investigation to meticulously assess the causative link between cathepsins and the risk of developing HCC, aiming to unveil new biomarkers for the detection and prevention of HCC. To the best of our knowledge, this is the inaugural MR analysis to comprehensively explore the causal influence of cathepsins on HCC. Our study explored the causative associations between nine distinct cathepsins and HCC risk. Drawing from a thorough study through both univariate and multivariate analyses, we identified cathepsin S as a significant risk factor for HCC. Furthermore, our findings revealed no evidence of a reverse causal relationship for cathepsin S with HCC. Cathepsin S, identified as a lysosomal cysteine protease found within spleen tissue and various antigen-presenting cells including B cells, macrophages, and dendritic cells [ 29 ], has been the subject of significant research interest due to its involvement in tumor-related processes. Studies have pinpointed cathepsin S as a crucial factor within the tumor's inflammatory milieu [ 30 ], contributing notably to the angiogenesis process [ 31 , 32 ] and facilitating tumor cell invasion and migration[ 29 , 32 , 33 ]. The dysregulation of cathepsin S expression has been observed in multiple tumor types, often correlating with adverse patient outcomes [ 34 – 36 ]. Research specifically focusing on the impact of cathepsin S on HCC risk has been sparse, highlighting the need for further detailed functional studies to elucidate its role in HCC progression. Additionally, insights from reverse MR analysis have illuminated an increase in cathepsin Z expression due to HCC, providing an explanation for the elevated cathepsin Z levels previously observed in HCC patients [ 37 , 38 ]. This study has several advantages. First, we can simulate randomized controlled trials (RCT) in an observational environment through MR study. RCT are universally acknowledged for their capacity to determine causality. While, due to its time-consuming, labor-consuming, need for more financial support, and relatively small sample size, may exist more ethical issues and other reasons, the possibility of its implementation is limited. By contrast, MR studies harness the random distribution of genetic variations at birth, effectively circumventing confounders and the issue of reverse causation. In this research, we applied MR study to investigate the causal impact of various cathepsins on HCC, using a combination of multivariate and reverse MR analyses to rigorously minimize bias, including confounding and reverse causation bias. Second, our findings may have the potential to guide early screening and prevention policies for HCC. Given the high prevalence and mortality of HCC, screening is particularly important. The role of serum biomarker detection, with its efficiency and simplicity, is indispensable in the early screening of cancers, and our findings pave the way for groundbreaking research into HCC-specific biomarkers. It's crucial to acknowledge, however, that the expansion of the P-value threshold, necessitated by the modest number of SNPs achieving genome-wide significance, represents a pragmatic adaptation frequently employed in genetic association studies. It's crucial to acknowledge, however, that we relaxed the p-value threshold due to the modest number of SNPs achieving genome-wide significance, which is a common way universally used. In conclusion, findings from this MR analysis indicate that elevated cathepsin S levels are linked to an increased risk of developing HCC. Moreover, the study presents evidence suggesting HCC may influence the expression levels of cathepsin Z. This research contributes to the identification of potential tumor markers, which could play crucial roles in the early detection, diagnosis, therapeutic intervention, and prognosis assessment of HCC. Declarations Funding This work was supported by the fund of Southwest Medical University (No. 2020ZRQNB059 and 2023ZD003) and the Luzhou City Science and Technology Bureau (No. 2020LZXNYDJ44), and Provincial Innovation and Entrepreneurship Training Program for College Students (S202310632154). Author contributions Conceptualization, Formal analysis, Writing-original draft: LS; Methodology: FY, YH and MJ; Data curation, Writing − review & editing: FH. Acknowledgement We are grateful to the consortium that provided all the public GWAS data. Data availability All datasets in this study are available for download in the online dataset and further contact the corresponding author if necessary. Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. 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Overexpression of cathepsin z contributes to tumor metastasis by inducing epithelial-mesenchymal transition in hepatocellular carcinoma. PLoS ONE. 2011;6. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4206143","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":288783761,"identity":"93394194-de85-454a-8e7d-646eac0c0ee9","order_by":0,"name":"Lishi Yang","email":"","orcid":"","institution":"The Affiliated Hospital of Southwest Medical University","correspondingAuthor":false,"prefix":"","firstName":"Lishi","middleName":"","lastName":"Yang","suffix":""},{"id":288783762,"identity":"6443a994-9760-4a06-8bec-501da6bdd4d7","order_by":1,"name":"Fengyao Mao","email":"","orcid":"","institution":"The Affiliated Hospital of Southwest Medical University","correspondingAuthor":false,"prefix":"","firstName":"Fengyao","middleName":"","lastName":"Mao","suffix":""},{"id":288783763,"identity":"846a7c85-f725-4889-9ba1-ba03af106e56","order_by":2,"name":"Yuhan Li","email":"","orcid":"","institution":"The Affiliated Hospital of Southwest Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yuhan","middleName":"","lastName":"Li","suffix":""},{"id":288783764,"identity":"e6315d6b-d7e7-4c9f-993c-4f6576bc144d","order_by":3,"name":"Mingjia Lin","email":"","orcid":"","institution":"The Affiliated Hospital of Southwest Medical University","correspondingAuthor":false,"prefix":"","firstName":"Mingjia","middleName":"","lastName":"Lin","suffix":""},{"id":288783765,"identity":"88c58a4a-694e-4b02-b09c-b6abfecb8da4","order_by":4,"name":"Fuhua Sun","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2UlEQVRIiWNgGAWjYJCCD4wNDAzy/I2NDxIqaojSwTgDpMVwxuHDBg/OHCNBC8OBtDTJhy3MhNXLz8g92My747A8Y8MZs4rEBjYG/vbuBLxaDG7kJTbznjls2M7cY3YjcYcMg8SZsxvwa5HIMX/M23aYsRFoy43EM2xAkVz8WuRn5Bg2A7XYNxzIMStIbGMmrIXhBkRLYgPQ+wxEaTE488awcW5bevJGYCBLJJw5xkPQL/LtOYYNb9usbecDo/Ljj4oaOf72XgIOQwc8pCkfBaNgFIyCUYAVAAAEG1APIYVlMAAAAABJRU5ErkJggg==","orcid":"","institution":"The Affiliated Hospital of Southwest Medical University","correspondingAuthor":true,"prefix":"","firstName":"Fuhua","middleName":"","lastName":"Sun","suffix":""}],"badges":[],"createdAt":"2024-04-02 10:59:59","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4206143/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4206143/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":54522151,"identity":"4659e8ef-f1d2-4858-80a2-585d462e8f50","added_by":"auto","created_at":"2024-04-11 18:26:29","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":58246,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Forest plot for the association between cathepsin S and HCC; (b) The leave-one-out study between cathepsin S and HCC.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4206143/v1/d7538c2ae163d1997245f5d5.jpeg"},{"id":54521745,"identity":"da9dc452-9ea8-4c10-94a3-3d4eab68a056","added_by":"auto","created_at":"2024-04-11 18:18:29","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":126589,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of multivariable Mendelian randomization analysis for various cathepsins and HCC risk.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4206143/v1/69d9b97ef46cbb13bf36146e.png"},{"id":62286306,"identity":"d0147a2c-6029-4156-9bb0-df5680f2ab52","added_by":"auto","created_at":"2024-08-12 13:36:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":712322,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4206143/v1/1df2311c-9974-4c99-a610-f157a8a79657.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The causal relationship between cathepsins and hepatocellular carcinoma risk: A Mendelian randomization study","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003ePrimary liver cancer has become the sixth most common malignancy and the third leading cause of cancer-related death worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. As the most common histological type of primary liver cancer, hepatocellular carcinoma (HCC) accounts for the great majority of incidence and mortality of liver cancer cases [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. At present, the clinical diagnosis of HCC is mainly determined by the imaging and evaluation of serum alpha-fetoprotein (AFP), but HCC is often found in an advanced stage and cannot be cured. It is estimated that HCC incidence and mortality will continue to rise over the next 20 years as the world population grows [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In this context, there is an urgent need for reliable and easily detectable biomarkers to identify and monitor the occurrence and progression of HCC as early as possible.\u003c/p\u003e \u003cp\u003eCathepsins are one of the lysosomal protease families and have a wide range of functions [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Considering that cathepsins may be involved in the complex physiological and pathological processes of human beings, studying their relationship with human diseases has aroused great interests among researchers [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. There are also many studies on the potential relationship between cathepsins and tumors, which means that certain cathepsins are involved in the occurrence and development of tumors. Numbers of reports have found that cathepsin K promotes breast cancer [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], lung cancer, prostate cancer [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] and soft tissue sarcoma [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Cathepsin B is associated with many tumor progression, including breast cancer [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], lung cancer [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] and pancreatic cancer [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Cathepsin C has been linked to ovarian cancer progression and metastasis [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Cathepsin B, D, E and L contribute to the development of digestive cancers [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. However, there is currently a lack of comprehensive and systematic research to evaluate the causal relationship between cathepsins and HCC. Therefore, due to the inherent limitations of traditional observational researches, it is not possible to determine cathepsins that promote the development of HCC based on existing evidence.\u003c/p\u003e \u003cp\u003eMendelian randomization (MR), which can infer the causal relationship between exposure and outcomes, is a widely used analytical approach [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. MR analysis is an important alternative method in the absence of randomized controlled studies, as it can provide reliable evidence of the causal relationship between exposure and disease risk [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In this context, we explore the causal relationship between different types of cathepsins and HCC through univariate and multivariate MR methods. The findings of this work provide feasible strategies for establishing cancer screening and prevention in clinical practice.\u003c/p\u003e"},{"header":"2. Methods and materials","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Instrumental variables\u003c/h2\u003e \u003cp\u003eUtilizing an instrumental variable from the INTERVAL study facilitated the assessment of cathepsin concentrations [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The reanalysis of data previously made public negated the necessity for further ethical consent. To identify genetic variants associated with cathepsins, a multi-step process was implemented. Initially, due to the scarcity of SNPs meeting the threshold for genome-wide significance, the criteria for association were adjusted to p\u0026thinsp;\u0026lt;\u0026thinsp;5\u0026times;10⁻⁶, with a pairwise linkage disequilibrium (LD) of r\u0026sup2; \u0026lt; 0.001 within a 10000 kb distance. This approach facilitated the selection of top independent SNPs, aligning with the methodology described by Li et al [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Genetic association of SNPs with HCC risk\u003c/h2\u003e \u003cp\u003eStatistics from GWAS related to HCC were derived from the TRICL, accessible through \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ebi.ac.uk/gwas\u003c/span\u003e\u003cspan address=\"https://www.ebi.ac.uk/gwas\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, involving 1,866 cases of HCC and 195,745 control subjects. Comprehensive information regarding the diagnostic criteria, demographic details, and measures of quality control is documented in the foundational GWAS documentation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Statistics and reproducibility\u003c/h2\u003e \u003cp\u003eA robust MR framework adheres to three core prerequisites: Initially, there must be a significant correlation between instrumental variables (IVs) and exposure. Next, IVs should remain unlinked to any confounders. Lastly, the IVs impact on the outcome is mediated solely through the exposure [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Violations of the latter two conditions may indicate the presence of horizontal pleiotropy, which is assessable through diverse statistical methodologies [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe inverse variance weighted (IVW) approach under a random-effects model synthesizes Wald ratios from individual SNPs to generate a consolidated estimate, serving as the primary technique in MR research [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Essentially, the IVW model presupposes the effectiveness of all genetic variants, making it as a highly efficacious strategy for MR analysis. To ensure the MR findings' solidity, the weighted median [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] and MR-Egger [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], have been applied as complementary methods. The \"TwoSampleMR\" software package (Version 0.5.8) within the R programming environment (Version 4.3.2) facilitated all related statistical computations.\u003c/p\u003e \u003cp\u003eFollowing the identification of significant estimates (with IVW p-values less than 0.05), a series of sensitivity analyses were performed to affirm the validity of the MR assumptions. The Cochran\u0026rsquo;s Q test played a crucial role in unveiling heterogeneity among studies, with a p-value less than 0.05 indicating significant heterogeneity [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. To pinpoint SNPs contributing to bias, the MR-PRESSO global test was employed, while the MR-Egger intercept facilitated the detection of horizontal pleiotropy [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Additionally, the MR-PRESSO outlier test served to examine and rectify horizontal pleiotropy [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The leave-one-out (LOO) strategy was integral in discerning influential data points affecting the collective IVW outcomes, further solidifying the conclusions' robustness. Potential cathepsins implicated in HCC progression satisfied several criteria: consistent directional and amplitude coherence across MR techniques; absence of detected heterogeneity or pleiotropy; and the lack of significant data points in LOO analyses. Multivariable MR is an advancement of univariate MR. In the study, multivariable MR was applied to analyze the causal effects of multiple cathepsins on HCC. The \"Mendelian Randomization\" software package facilitated the estimation of direct causal impacts from each exposure in a single analysis [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Reverse MR analyses, with HCC as the exposure and cathepsins as the outcome, were conducted to evaluate the reverse causal relationships, utilizing the aforementioned GWAS dataset.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Causal effect from cathepsins to HCC\u003c/h2\u003e \u003cp\u003eTo assess the influence of various cathepsins on HCC risk, an initial analysis using Two-Sample Mendelian Randomization (MR) focused on nine specific cathepsins (cathepsin B, E, F, G, H, L2, O, S, and Z) in relation to HCC was performed. The findings from the univariate MR approach indicated that elevated levels of cathepsin S increased the risk of HCC (IVW: p\u0026thinsp;=\u0026thinsp;0.036, OR\u0026thinsp;=\u0026thinsp;1.183, 95% confidence interval (CI)\u0026thinsp;=\u0026thinsp;1.010\u0026ndash;1.386). Similar risk assessments were obtained through the weighted median method (OR\u0026thinsp;=\u0026thinsp;1.287, 95% CI\u0026thinsp;=\u0026thinsp;1.030\u0026ndash;1.610, p\u0026thinsp;=\u0026thinsp;0.026) and MR-Egger regression analysis (OR\u0026thinsp;=\u0026thinsp;1.936, 95% CI\u0026thinsp;=\u0026thinsp;0.816\u0026ndash;4.590, p\u0026thinsp;=\u0026thinsp;0.161), although the correlation derived from MR-Egger regression did not reach statistical significance (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHeterogeneity assessments via Cochran\u0026rsquo;s Q test revealed no significant heterogeneity, with an IVW analysis yielding a p-value of 0.519 and MR-Egger analysis resulting in a p-value of 0.546 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The absence of a significant intercept (intercept = -0.076; SE\u0026thinsp;=\u0026thinsp;0.067, p\u0026thinsp;=\u0026thinsp;0.279) suggested no horizontal pleiotropy was observed. This was corroborated by the MR-PRESSO global test (p-value\u0026thinsp;=\u0026thinsp;0.530).\u003c/p\u003e \u003cp\u003eThe impact assessment of individual SNP is depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea. Additionally, the leave-one-out sensitivity analysis demonstrated that no single SNP significantly deviated from the general influence of cathepsin S on HCC risk (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCausality of cathepsins on HCC estimated by univariable Mendelian randomization analysis.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCathepsin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003enSNP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eInverse variance weighted\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eMR-Egger\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eWeighted median\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOR(95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR(95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eOR(95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCathepsin B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.896(0.710\u0026ndash;1.130)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.001(0.550\u0026ndash;1.822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.965(0.768\u0026ndash;1.214)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.767\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCathepsin E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.868(0.745\u0026ndash;1.011)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.995(0.682\u0026ndash;1.452)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.983\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.879(0.708\u0026ndash;1.092)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.245\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCathepsin F\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.943(0.784\u0026ndash;1.134)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.535\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.807(0.489\u0026ndash;1.332)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.450\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.932(0.792\u0026ndash;1.096)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.396\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCathepsin G\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.139(0.883\u0026ndash;1.468)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.314\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.058(0.458\u0026ndash;2.443)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.916\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.124(0.830\u0026ndash;1.522)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.449\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCathepsin H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.041(0.924\u0026ndash;1.173)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.502\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.093(0.930\u0026ndash;1.284)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.337\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.061(0.948\u0026ndash;1.187)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.298\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCathepsin L2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.008(0.804\u0026ndash;1.263)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.943\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.260(0.984\u0026ndash;5.190)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.026(0.770\u0026ndash;1.366)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.858\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCathepsin O\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.063(0.874\u0026ndash;1.293)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.536\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.881(0.349\u0026ndash;2.223)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.802\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.168(0.905\u0026ndash;1.507)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.232\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCathepsin S\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.183(1.010\u0026ndash;1.386)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.936(0.816\u0026ndash;4.590)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.287(1.030\u0026ndash;1.610)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCathepsin Z\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.922(0.785\u0026ndash;1.083)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.726(0.522\u0026ndash;1.011)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.848(0.712\u0026ndash;1.011)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.066\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePleiotropy and heterogeneity analyses of Two-Sample MR between cathepsin S and HCC.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMR-Egger intercept\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMR-PRESSO global\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eMR-IVW\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c12\" namest=\"c10\"\u003e \u003cp\u003eMR-Egger\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eintercept p-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eQ-df\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eQ-pval\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eQ-df\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eQ-pval\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e-0.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.530\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.519\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9.821\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.546\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Causal effect from HCC to cathepsins\u003c/h2\u003e \u003cp\u003eIn investigating the potential for a bidirectional causal relationship, reverse MR analyses were executed. These analyses revealed no evidence of a reverse causation from cathepsin S to HCC (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). While, findings from the reverse MR study suggested that HCC might lead to increased levels of cathepsin Z, as indicated by IVW (p\u0026thinsp;=\u0026thinsp;0.025, OR\u0026thinsp;=\u0026thinsp;1.028, 95% CI\u0026thinsp;=\u0026thinsp;1.003\u0026ndash;1.054) and weighted median (p\u0026thinsp;=\u0026thinsp;0.029, OR\u0026thinsp;=\u0026thinsp;1.040, 95% CI\u0026thinsp;=\u0026thinsp;1.003\u0026ndash;1.078). Meanwhile, a similar effect was observed with MR-Egger regression (p\u0026thinsp;=\u0026thinsp;0.103, OR\u0026thinsp;=\u0026thinsp;1.030, 95% CI\u0026thinsp;=\u0026thinsp;0.994\u0026ndash;1.066), although the association did not reach statistical significance. Furthermore, the MR-Egger intercept (p\u0026thinsp;=\u0026thinsp;0.921) and MR-PRESSO global test (p\u0026thinsp;=\u0026thinsp;0.451) showed no indication of directional pleiotropy. With Cochran\u0026rsquo;s Q test results yielding p-values of 0.382 (IVW) and 0.341 (MR-Egger) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), heterogeneity was also not detected.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eReverse Mendelian randomization analysis to estimate causality between HCC and cathepsins.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eInverse variance weighted\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eMR-Egger\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eWeighted median\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eexposure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eoutcome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003enSNP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"8\" rowspan=\"9\"\u003e \u003cp\u003eHCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCathepsin B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.005(0.981\u0026ndash;1.030)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.655\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.001(0.967\u0026ndash;1.036)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.927\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.005(0.969\u0026ndash;1.043)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.755\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCathepsin E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.020(0.993\u0026ndash;1.047)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.018(0.981\u0026ndash;1.057)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.342\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.020(0.983\u0026ndash;1.058)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.273\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCathepsin F\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.023(0.998\u0026ndash;1.048)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.024(0.991\u0026ndash;1.059)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.011(0.972\u0026ndash;1.051)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.580\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCathepsin G\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.009(0.983\u0026ndash;1.035)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.477\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.004(0.969\u0026ndash;1.040)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.810\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.018(0.982\u0026ndash;1.055)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.322\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCathepsin H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.016(0.988\u0026ndash;1.044)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.992(0.956\u0026ndash;1.028)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.676\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.001(0.967\u0026ndash;1.037)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.930\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCathepsin L2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.983(0.954\u0026ndash;1.012)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.258\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.972(0.933\u0026ndash;1.012)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.961(0.926\u0026ndash;0.998)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCathepsin O\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.009(0.983\u0026ndash;1.036)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.483\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.980(0.947\u0026ndash;1.014)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.992(0.957\u0026ndash;1.029)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.689\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCathepsin S\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.995(0.971\u0026ndash;1.020)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.745\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.007(0.974\u0026ndash;1.042)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.661\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.008(0.972\u0026ndash;1.046)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.646\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCathepsin Z\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.028(1.003\u0026ndash;1.054)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.030(0.994\u0026ndash;1.066)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.040(1.003\u0026ndash;1.078)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePleiotropy and heterogeneity analyses of Two-Sample MR between HCC and cathepsin Z.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMR-Egger intercept\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMR-PRESSO global\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eMR-IVW\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c12\" namest=\"c10\"\u003e \u003cp\u003eMR-Egger\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eintercept p-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eQ-df\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eQ-pval\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eQ-df\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eQ-pval\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e-0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.921\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e43.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e43.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.546\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Causal effect from multiple cathepsins to HCC\u003c/h2\u003e \u003cp\u003eTo further investigate the genetic predisposition involving multiple cathepsins that influence the risk of HCC, a multivariable MR analysis was carried out. The analysis revealed that, even when adjustments were made for the levels of other cathepsins, a significant association persisted between elevated levels of cathepsin S and a higher risk of developing HCC, as demonstrated by both IVW (p\u0026thinsp;=\u0026thinsp;0.031, OR\u0026thinsp;=\u0026thinsp;1.208, 95% CI\u0026thinsp;=\u0026thinsp;0.843\u0026ndash;1.508) and MR-Egger analysis (p\u0026thinsp;=\u0026thinsp;0.033, OR\u0026thinsp;=\u0026thinsp;1.207, 95% CI\u0026thinsp;=\u0026thinsp;1.034\u0026ndash;1.379) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This relationship was not observed with other cathepsins. Furthermore, heterogeneity analyses using Cochran\u0026rsquo;s Q test showed no significant heterogeneity (IVW p-value\u0026thinsp;=\u0026thinsp;0.303, MR-Egger p-value\u0026thinsp;=\u0026thinsp;0.302), and the MR-Egger intercept analysis indicated the absence of horizontal pleiotropy (p\u0026thinsp;=\u0026thinsp;0.832).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe significant prevalence and mortality associated with HCC have placed a considerable strain on public health. AFP, though widely utilized as a biomarker for HCC, exhibits limitations, especially in the early diagnosis of the disease, underscoring the vital importance of effective screening and preventative strategies[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Proteolytic activities, pivotal in tumor development and progression, have garnered interest in oncological researchers, with the lysosomal protease family member, cathepsin, being of notable focus. Previous researches have highlighted several cathepsins in HCC. For example, findings by Wang et al. demonstrated a significant increase in cathepsin A in HCC tissues compared to normal liver samples [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], while Luo et al. associated high levels of cathepsin A with adverse clinical outcomes in HCC patients [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Additionally, HCC patients with lower levels of cathepsin D have been shown to exhibit markedly improved survival rates than those with elevated levels [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Despite the above literatures suggesting cathepsins' role in HCC, epidemiological studies have not conclusively demonstrated a link between cathepsins and HCC.\u003c/p\u003e \u003cp\u003eIn this pioneering study, we embarked on an exposure-wide MR investigation to meticulously assess the causative link between cathepsins and the risk of developing HCC, aiming to unveil new biomarkers for the detection and prevention of HCC. To the best of our knowledge, this is the inaugural MR analysis to comprehensively explore the causal influence of cathepsins on HCC. Our study explored the causative associations between nine distinct cathepsins and HCC risk. Drawing from a thorough study through both univariate and multivariate analyses, we identified cathepsin S as a significant risk factor for HCC. Furthermore, our findings revealed no evidence of a reverse causal relationship for cathepsin S with HCC.\u003c/p\u003e \u003cp\u003eCathepsin S, identified as a lysosomal cysteine protease found within spleen tissue and various antigen-presenting cells including B cells, macrophages, and dendritic cells [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], has been the subject of significant research interest due to its involvement in tumor-related processes.\u003c/p\u003e \u003cp\u003eStudies have pinpointed cathepsin S as a crucial factor within the tumor's inflammatory milieu [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], contributing notably to the angiogenesis process [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] and facilitating tumor cell invasion and migration[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. The dysregulation of cathepsin S expression has been observed in multiple tumor types, often correlating with adverse patient outcomes [\u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eResearch specifically focusing on the impact of cathepsin S on HCC risk has been sparse, highlighting the need for further detailed functional studies to elucidate its role in HCC progression. Additionally, insights from reverse MR analysis have illuminated an increase in cathepsin Z expression due to HCC, providing an explanation for the elevated cathepsin Z levels previously observed in HCC patients [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study has several advantages. First, we can simulate randomized controlled trials (RCT) in an observational environment through MR study. RCT are universally acknowledged for their capacity to determine causality. While, due to its time-consuming, labor-consuming, need for more financial support, and relatively small sample size, may exist more ethical issues and other reasons, the possibility of its implementation is limited. By contrast, MR studies harness the random distribution of genetic variations at birth, effectively circumventing confounders and the issue of reverse causation.\u003c/p\u003e \u003cp\u003eIn this research, we applied MR study to investigate the causal impact of various cathepsins on HCC, using a combination of multivariate and reverse MR analyses to rigorously minimize bias, including confounding and reverse causation bias. Second, our findings may have the potential to guide early screening and prevention policies for HCC. Given the high prevalence and mortality of HCC, screening is particularly important. The role of serum biomarker detection, with its efficiency and simplicity, is indispensable in the early screening of cancers, and our findings pave the way for groundbreaking research into HCC-specific biomarkers.\u003c/p\u003e \u003cp\u003eIt's crucial to acknowledge, however, that the expansion of the P-value threshold, necessitated by the modest number of SNPs achieving genome-wide significance, represents a pragmatic adaptation frequently employed in genetic association studies. It's crucial to acknowledge, however, that we relaxed the p-value threshold due to the modest number of SNPs achieving genome-wide significance, which is a common way universally used.\u003c/p\u003e \u003cp\u003eIn conclusion, findings from this MR analysis indicate that elevated cathepsin S levels are linked to an increased risk of developing HCC. Moreover, the study presents evidence suggesting HCC may influence the expression levels of cathepsin Z. This research contributes to the identification of potential tumor markers, which could play crucial roles in the early detection, diagnosis, therapeutic intervention, and prognosis assessment of HCC.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003eThis work was supported by the fund of Southwest Medical University (No. 2020ZRQNB059 and 2023ZD003) and the Luzhou City Science and Technology Bureau (No. 2020LZXNYDJ44), and Provincial Innovation and Entrepreneurship Training Program for College Students (S202310632154).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u0026nbsp;\u003c/strong\u003eConceptualization, Formal analysis, Writing-original draft: LS; Methodology: FY, YH and MJ; Data curation, Writing \u0026minus; review \u0026amp; editing: FH.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u0026nbsp;\u003c/strong\u003eWe are grateful to the consortium that provided all the public GWAS data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003eAll datasets in this study are available for download in the online dataset and further contact the corresponding author if necessary.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e The authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. 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Nat Rev Cancer. 2015;15:712\u0026ndash;29.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSmyth P, Sasiwachirangkul J, Williams R, Scott CJ. Cathepsin s (ctss) activity in health and disease - a treasure trove of untapped clinical potential. Mol Aspects Med. 2022;88.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBatista AAS, Franco BM, Perez MM, Pereira EG, Rodrigues T, Wroclawski ML, Fonseca FLA, Suarez ER. Decreased levels of cathepsin z mrna expressed by immune blood cells: Diagnostic and prognostic implications in prostate cancer. Braz J Med Biol Res. 2021;54.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHotchin NA, Wang J, Chen L, Li Y, Guan X-Y. Overexpression of cathepsin z contributes to tumor metastasis by inducing epithelial-mesenchymal transition in hepatocellular carcinoma. PLoS ONE. 2011;6.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","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":"Cathepsin, Hepatocellular carcinoma, Mendelian randomization analysis, Causality","lastPublishedDoi":"10.21203/rs.3.rs-4206143/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4206143/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eAbnormal expression of cathepsins has been reported in patients with hepatocellular carcinoma (HCC). However, the evidence about the causal role of cathepsins in facilitating or preventing HCC is lacking. Systematically studying the causality between cathepsins and HCC would help provide novel targets for screening and prevention of HCC.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted twosample Mendelian randomization (MR) analyses. The data of cathepsins and HCC for analysis were derived from publicly available genetic summary data. The causal effects were estimated with inverse variance weighted, MR-Egger and weighted median. Sensitivity analyses were implemented with Cochran's Q test, MR-Egger intercept test, MR-PRESSO and leave-one-out analysis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe results of univariate MR analysis show that elevated cathepsin S levels increase the risk of HCC. On the other hand, reverse MR analyses indicate that HCC may raise cathepsin Z levels. According to the results of multivariable analysis using nine cathepsin variables, an increased risk of HCC is associated with elevated levels of cathepsin S.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe evidence that cathepsin S is associated with HCC in a causal way provides a novel insight into the underlying mechanisms of HCC by integrating genomics with cathepsins, and has an implication for HCC screening and prevention.\u003c/p\u003e","manuscriptTitle":"The causal relationship between cathepsins and hepatocellular carcinoma risk: A Mendelian randomization study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-11 18:18:25","doi":"10.21203/rs.3.rs-4206143/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","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":"96c84149-41cc-441b-8944-20c3cc5e01a5","owner":[],"postedDate":"April 11th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-08-12T13:36:12+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-11 18:18:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4206143","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4206143","identity":"rs-4206143","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}