A protective causal relationship between morphine and colorectal cancer: a two-way Mendelian randomization study

A protective causal relationship between morphine and colorectal cancer: a two-way 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 A protective causal relationship between morphine and colorectal cancer: a two-way Mendelian randomization study Qing Deng, Yi fan Yu, Cheng yang Yu, Hui yan Luo, Chun Gong, Xiong Wen Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4007465/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: The relationship between morphine and colorectal cancer has been controversial. To address this controversial issue, we examined the relationship between morphine and colorectal cancer. Methods: The causal relationship between morphine and colorectal cancer was investigated through Mendelian randomization (MR). Analysis was conducted using the publicly available GWAS database. First, single nucleotide polymorphisms (SNPs) strongly associated with morphine exposure factors were screened. Then the causal relationship between morphine and colorectal cancer was analyzed using inverse variance weighted (IVW), weighted median, and MR Egger methods. Finally, tests for sensitivity, heterogeneity, and pleiotropy were performed to ensure the stability and reliability of the results. Result: The IVW analysis revealed a protective causal relationship between morphine use and colorectal cancer (odds ratio [OR] = 0.30, 95% confidence interval [CI]: 0.10-0.87, p = 0.03). Conclusion: We provide evidence of a possible protective causal relationship between morphine and colorectal cancer. Further validation through larger clinical randomized studies and more advanced methods is needed. Mendelian randomization morphine colorectal cancer causal relationship prospective analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Colorectal cancer (CRC) is the third most common tumor in the United States (Rim et al., 2009 ) and the fourth most deadly malignancy in the world, killing about 700,000 people each year. With the development of the economy, people's diet structure is gradually biased towards meat food, which leads to a global increase in the incidence of CRCs year by year. It is projected that there will be an additional 2.5 million cases of colon cancer in developing countries by 2035 (Dekker et al., 2019 ). Pain is a common symptom in CRC patients, with a prevalence of up to 70% (Zielinska et al., 2021 ). Cancer pain affects the physical and emotional well-being of patients. The World Health Organization(WHO) has adopted a three-step analgesic ladder for the treatment of cancer pain, with the first step using non-opioids, the second step using weak opioids, and the third step using strong opioids (Donnelly et al., 2002 ). Morphine is the most widely used strong opioid, with 85% of patients receiving good pain relief with morphine every 4 hours. It is still unclear whether morphine inhibits or promotes malignant cell proliferation and survival. Morphine has been reported to reduce cancer metastasis and recurrence, however, it also has been documented that morphine promotes the spread of cancer. Conflicting views on morphine immune suppression and inhibition of cancer progression exist in the real world. (Yuval et al., 2022 ). (Lu et al., 2021 ). The reason for the controversy does not exclude bias or confounding factors in the study design, which could lead to contradictory results. Mendelian randomization (MR) is a statistical method for analyzing the relationship between phenotype and disease using single nucleotide polymorphisms (SNPs) as instrumental variables (IVs) (Bowden and Holmes, 2019 ). MR has randomness and stability because it follows Mendel's law of inheritance, which includes the random assignment of parental genes during the formation of a fertilized egg. Therefore, MR can maximize the avoidance of all kinds of bias in the design and operation of a clinical trial, balance the confounding factors, and improve the precision of the statistical results. To better understand the causal relationship between morphine and colorectal cancer, we conducted a two-way MR. 2. Materials and methods 2.1 Research design Based on the Genome-Wide Association Study (GWAS) pooled data on morphine and CRC, we screened SNPs for MR analysis to investigate the causal relationship between morphine and colorectal cancer. This study strictly followed the three principles of MR analysis: (1) association is that instrumental variables (IVs) is closely linked to the exposure (2) independence is that the instrumental variable is independent of any confounding factors affecting the outcome; and (3) exclusivity is that the instrumental variable is independent of the outcome and can only affect the outcome through the exposure. Every dataset that was used in this research is openly accessible. Ethical clearance and written informed consent were provided in the original study. 2.2 Study cohort and GWAS Pooled GWAS data were used in Two-sample MR. Exposure and outcome GWAS data were obtained in the IEU Open GWAS program. All GWAS studies have been limited to individuals of European ancestry. In the analysis, morphine exposure data were obtained from Neale Lab and contained a sample size of 337,159 (194 cases, 336,965 control cases). Colorectal cancer outcome data came from UK Biobank and included 5,657 colorectal cancer cases (372,016 control subjects). UK Biobank is a population-based prospective study. To have a better knowledge of a person's illness process, the UK Biobank gathers biological and medical data from half a million people living in the UK who are between the ages of 40 and 69. Preliminary studies provided relevant enrollment procedures and diagnostic criteria. 2.3 Instrumental Variables Selection To choose IVs that would satisfy the three MR analysis assumptions and guarantee the stability and dependability of the MR analysis, a stringent set of quality controls was carried out. First, we used the R package TwoSampleMR (Hemani et al., 2018 )to select genetic instruments from GWAS and screen for SNPs (p < 5×10 − 8 ) that are closely associated with exposures. Second, linkage disequilibrium analysis was performed. We must eliminate linkage disequilibrium because it raises the likelihood that genetic variants in identical genomic sites may be inherited jointly. This would lead to alleles occurring simultaneously on the same chromosome more frequently than at random. Kb is the length of the region of chain imbalance. R 2 can respond to the degree of allelic correlation, ranging from 0 to 1. When r 2 = 0, it is in a state of complete interlocking equilibrium. When r 2 = 1, it is in a state of complete interlocking disequilibrium. Therefore, we need to extract SNPs with r 2 10,000. Third, we excluded SNPs associated with CRC (p < 5×10 − 08 ), because SNPs associated with CRC can confound the relationship between exposure and outcome, violating the exclusivity principle of Mendelian randomization study. Fourth, we applied the PhenoScanner database ( http://www.phenoscanner.medschl.cam.ac.uk/phenoscanner ) to exclude confounders (Hu et al., 2022 ). Fourth, to detect potential weak IVs bias, we also calculated the F-statistic for all SNPs. An average F statistic more than 10 indicates a strong association between the SNP and the phenotype.(Burgess et al., 2011 ). Fifth, the palindromic SNPs with intermediate allele frequencies were removed to ensure the accuracy of the results. 2.4 Research methodology The MR analysis of morphine and CRC were performed primarily using the Two Sample MR and MRPRESSO software packages in R (version 4.3.1). p-value < 0.05 was considered statistically significant. The main research methods included IVW, weighted median and MR Egger. IVW, which assumes that all SNPs are valid and assesses the combined effect by calculating the Wald value for each SNP, was used as the main method to assess causal effects. MR-Egger assumed that all SNPs were invalid, and weighted median method assumed that half of the SNPs were valid. MR-Egger and weighted median methods are able to provide reliable estimates over a wider range, but with reduced accuracy and relatively large standard errors, so they are complementary to IVW methods (Burgess and Thompson, 2017 ). Several sensitivity analysis methods, including MR-Egger intercept and MR polytropic residuals and leave-one-out sensitivity test, were also performed to assess the stability and confidence of the results (Bowden and Holmes, 2019 ). In the MR-Egger method, we used the relationship between intercepts and zeros to assess horizontal pleiotropy (Verbanck et al., 2018 ). Differences between studies are called heterogeneity. Instrumental variables from different analytical platforms, experiments, and populations may be heterogeneous which can affect the results of Mendelian randomization analyses, so the heterogeneity needs to be assessed. Heterogeneity was analyzed mainly using the Q statistic. If p > 0.05, the selected instrumental variables were considered not to be heterogeneous. Excessive heterogeneity means that the MR hypothesis may not be valid(Miao et al., 2022 ). At the same time, we performed Steiger filtering to determine if the direction of the exposure and the outcome were the same. Finally, we performed a bidirectional Mendelian analysis to assess the presence of reverse causality. 2.5 Mediation analysis In order to study deeply the effect of morphine on colorectal cancer, we performed a mediated Mendelian analysis. We used colorectal cancer and risk factors as keywords for a comprehensive search in PubMed. Then, we searched for publicly available GWAS statistical abstracts for colorectal cancer risk factors. Finally, eight risk factors that include alcohol consumption, type 2 diabetes, fast insulin, body mass index (BMI), cholesterol to total lipids ratio in IDL, polyunsaturated fatty acids (PFA), LDL cholesterol, and smoking were identified (Li et al., 2022 ; Zhou et al., 2018 ; Suzuki et al., 2021 ). We used a two-step Mendelian randomization analysis to study the mediating effects of morphine, colorectal cancer risk factors, and colorectal cancer, with the formula Beta = Beta (XZ)*Beta (ZY). In addition, standard errors (SE) and confidence intervals (CI) for the mediating effects were estimated using the delta method. The result of the MR analysis of exposure and outcome was the total effect. Direct effect = total effect - indirect effect (Beta (XY) – Beta) (Carter et al., 2021 ). 3. Results With the Two Sample MR package, SNPs with p < 5×10 − 08 were selected and then subjected to linkage disequilibrium analysis. Finally, three SNPs (rs117785145, rs35286491, rs639995) were selected to genetically represent the effects of morphine. Three SNPs were not associated with colorectal cancer risk factors as viewed through the PhenoScanner database. Through the mRnd ( https://shiny.cnsgenomics.com/mRnd ) calculation, we found that the F-values of instrumental variables greater than 10, indicating strong instrumental variables. After harmonizing the GWASs effector alleles for morphine and CRC, we performed MR primary methods to analyze the data. A protective causal relationship between morphine and colorectal cancer was found in the IVW analysis (OR 0.30, 95% CI 0.10–0.87, p = 0.027). The MR-Egger intercept suggested the absence of pleiotropy (MR-Egger intercept − 2 × 10 − 3 , SE 1 × 10 − 3 , p = 0.370). No single SNP strongly violated the overall effect of morphine on CRC in the leave-one-out sensitivity analysis. Cochran's Q test showed no significant heterogeneity in individual SNP estimates (p = 0.313). Steiger filtering provided assurance on the directionality of the causal relationships. In the reverse Mendelian randomization analysis, the p-values for IVW, MR-Egger, and weighted median were all greater than 0.05, suggesting that there is no reverse causality between morphine and colorectal cancer. The causal correlations estimated by MR-Egger were in contrast to those detected by the other two MR analyses, although it was nonsignificant. Therefore, these potential causal effects should be interpreted with caution. More investigations and studies are needed. However, the IVW method does not take into account pleiotropy and uses the inverse of the variance of the outcome as weights for the fit. The MR-Egger method takes into account the presence of intercept terms (multinomials) in the regression, leading to susceptibility to peripheral and influential instrumental variables and imprecision (Burgess and Thompson, 2017 ). Due to the lack of horizontal pleiotropy and heterogeneity (p > 0.05) in the Mendelian randomization analysis of morphine and CRC, the causality obtained by IVW was more accurate than the results of MR-Egger. Therefore, the value of IVW is reasonable. Although it was significant(p > 0.05), the weighted median methods were in the same direction as the IVW methods, which may reinforce the validity of a possible protective causal relationship between morphine and CRC. Table 1 The results of bidirectional Mendelian randomization. Exposure method OR (95%CI) P value Cochran Q (p value) MR-Egger intercept (P value) morphine IVW 0.30 (0.10–0.87) 0.03 2.32(p = 0.31) MR-Egger 2.56 (0.14–49.62) 0.64 0.01(p = 0.92) -2×10 − 3 (p = 0.37) Weighted median 0.38 (0.10–1.38) 0.14 Colorectal cancer IVW 1.01 (0.99–1.03) 0.45 6.01(p = 0.53) MR-Egger 1.00 (0.92–1.07) 0.91 5.88(p = 0.44) 3.14×10 − 5 (p = 0.73) Weighted median 1.02 (0.93–1.07) 0.31 Regrettably, we did not find a mediator between exposure and outcome among the eight risk factors. However, we found that the ORs between morphine and cholesterol to Total lipids ratio in IDL, and type 2 diabetes were less than 1. IVW, MR-Egger, and Weighted median were in the same direction. A causal relationship between cholesterol to total lipids ratio in IDL and CRC was determined by two-step Mendelian randomization. There was no causal relationship between morphine and cholesterol to total lipids ratio in IDL, but the results of the Mendelian randomization analysis of morphine and cholesterol to total lipids ratio in IDL suggested that they were directionally consistent (the supplementary material: Table S2). 4. Discussion The relationship between morphine and colorectal cancer is currently controversial. It has been suggested that morphine activates EGFR signaling in human colorectal cancer thereby promoting tumorigenesis (Lu et al., 2021 ). However, several more studies have reported the ability of morphine to inhibit the adhesion of colorectal cancer cells (Min et al., 2011). We aimed to better assess the relationship between morphine and colorectal cancer using bidirectional Mendelian randomization. The results of Mendelian randomization showed that morphine seems to reduce the risk of colorectal cancer. This study complements the clinical retrospective and randomized studies and provides some evidence that morphine reduces the risk of colorectal cancer. Morphine is a very effective analgesic. Morphine-3-glucuronide (M3G) and morphine-6-glucuronide (M6G) are the major metabolites of morphine. M6G is the main component of morphine that exerts pain relief. Morphine is a third-step analgesic that can quickly achieve pain relief and ease the pain of cancer patients. Morphine is a very safe and effective drug for tumor patients when used correctly. A retrospective cohort study shows older cancer survivors have lower long-term risk of opioid use than control noncancer patients (Jairam et al., 2020 ). Many studies have shown that physical and psychological pain stress promotes tumor development. Morphine improves the quality of life of tumor patients by effectively controlling pain and relieves stress to reduce tumor metastasis. The most common side effect of morphine is constipation. It is very interesting that one study showed that the most common type of cancer among constipated patients was non-colorectal gastrointestinal and colorectal gastrointestinal tumors were less common than other tumors (Roeland et al., 2019 ). Several potential mechanisms could explain the protective role of morphine in colorectal cancer. Morphine reduces adhesion of colorectal cancer cells to collagen and connective fibers of the extracellular matrix and decreases the invasiveness of cancer cells. It has also been shown that morphine inhibits the growth of blood vessels and reduces the ability of tumors to metastasize. The mechanism of morphine on CRC still requires further studies in pathology. Unfortunately, mediation analysis failed to find significant results. However, mediation analysis revealed that the cholesterol to total lipids ratio in IDL was a risk factor for CRC. At the same time, we cannot exclude the possibility that there is a relationship between morphine, cholesterol to total lipids ratio in IDL, and CRC. In the future, we need further experimental studies or more comprehensive data studies to verify this possibility. The study used Mendelian randomization analysis to find a possible protective effect of morphine in colorectal cancer patients. This evidence may provide some confidence in the rational use of morphine to control cancer pain in CRC patients. This study has several strengths. First, MR is a study that possesses a higher level of evidence, which can compensate for the limitations that exist in observational studies such as confounding and bias, and thus enhance causal inferences. Second, the GWAS dataset for this study was based primarily on European population pedigrees, reducing the impact of population differences on the study. Third, the results are very reliable. Because we used the PhenoScanner database to rigorously check for confounders related to morphine and CRC; no IVs with confounding factors were detected, preventing potential horizontal pleiotropy. Meanwhile, sensitivity analysis using MR-Egger and leave-one-out assessment methods ensured the reliability of the results. In addition, Cochran's Q test did not detect significant heterogeneity. Finally, to the best of our knowledge, this is the first article to discuss the causal relationship between morphine and colorectal cancer using Mendelian randomization study methods. There are limitations that need to be considered in interpreting our findings. First, only the primary analysis method, IVW, suggested a relationship between morphine and colorectal cancer. Results should be interpreted with caution. Larger samples and more sophisticated methods are needed to confirm the results. Second, the study only included a single population and needs further validation in a larger population. Third, Mendelian randomization could only find a protective causal relationship between morphine and colorectal, but it was not possible to understand the specific mechanisms and effects of morphine in the development of colorectal cancer, and further experimental studies are needed. 5. Conclusion In conclusion, we provide evidence of a possible protective causal relationship between morphine and colorectal cancer. Our study provides a new insight into the role of morphine in colorectal cancer risk. We increase new evidence that morphine can be used in the clinic to relieve pain in patients with colorectal cancer. Declarations Author Contributions: Q D and Y Y designed the study and written this article. C Y, H L and CG collected and analyzed the data. X W contributed to the revision of the manuscript. All authors were involved in the writing of the article and in the approval of the version for submission. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by the National Nature Science Foundation of China (No. 82274605). Institutional Review Board Statement: This study did not require ethical approval. Informed Consent Statement: The consent of the patients was not required because the informed consent had already been given in the original study. Data Availability Statement: All data involved in this study are available in the public database. For further information, please contact the corresponding authors. Acknowledgments: We would like to thank all of the GWASs for making their summary data available to the public, and all of the investigators and participants who contributed to these studies. In addition, we want to acknowledge the participants and investigators of the UK Biobank and Neale Lab. Conflicts of Interest: The authors declare to have carried out the study in the absence of any commercial or financial relationship that would constitute a potential conflict of interest. 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(2019). More opioids, more constipation? Evaluation of longitudinal total oral opioid consumption and self-reported constipation in patients with cancer. Supportive Care in Cancer 28 , 1793–1797.doi: 10.1007/s00520-019-04996-7 Supplementary Table Supplementary Table S2 is not available with this version 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. 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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-4007465","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":276175274,"identity":"83ba6f87-db1a-4295-a6f8-d70af92c12ba","order_by":0,"name":"Qing Deng","email":"","orcid":"","institution":"Guangzhou University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Qing","middleName":"","lastName":"Deng","suffix":""},{"id":276175275,"identity":"9e6d35a1-55bf-4553-b742-8fae6e37d45a","order_by":1,"name":"Yi fan Yu","email":"","orcid":"","institution":"Guangzhou University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yi","middleName":"fan","lastName":"Yu","suffix":""},{"id":276175276,"identity":"ea68fedb-61c2-4b81-b776-764d84fab728","order_by":2,"name":"Cheng yang Yu","email":"","orcid":"","institution":"Guangzhou University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Cheng","middleName":"yang","lastName":"Yu","suffix":""},{"id":276175277,"identity":"efa1b079-4da0-4f29-ad7d-b4a36e078589","order_by":3,"name":"Hui yan Luo","email":"","orcid":"","institution":"Guangzhou University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Hui","middleName":"yan","lastName":"Luo","suffix":""},{"id":276175278,"identity":"16483538-fd87-46c1-914e-f26d34b8a377","order_by":4,"name":"Chun Gong","email":"","orcid":"","institution":"The First Hospital of Hunan University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Chun","middleName":"","lastName":"Gong","suffix":""},{"id":276175279,"identity":"b50ce6c6-8801-4611-a2e9-0b11a59b5a65","order_by":5,"name":"Xiong Wen Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2UlEQVRIiWNgGAWjYLCCDxUSPPzszQcOfPhBpA7GGWcs5CR7jiUenNlDpBZmzrYKY4MbOcaHOdiIUM4/I/nYY4YzEokNN3I+HGbgYZDnFzuAX4vEjbR044IKicTGnrcbDhdYMBjOnJ1AwJrbOWbSM4C2NLPnbjg8g4chweA2AS3yt/O/SfO2SSS2MeQ8OMzDRoQWg9s5bCAtxjwcOQzEaTG8/8xMEugwOQmeYwbAQJYg7Be5M4efSXyoqOOxP978+MOHHzby/NIEtKADCdKUj4JRMApGwSjADgDULEnQwGvYBgAAAABJRU5ErkJggg==","orcid":"","institution":"First Affiliated Hospital of Guangzhou University of Chinese Medicine","correspondingAuthor":true,"prefix":"","firstName":"Xiong","middleName":"Wen","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2024-03-03 03:59:44","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4007465/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4007465/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":52085933,"identity":"2f07691b-787b-4d27-aa1a-79567ece1cf0","added_by":"auto","created_at":"2024-03-06 12:21:07","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":22485,"visible":true,"origin":"","legend":"\u003cp\u003eStudy design of Mendelian randomization between morphine and CRC. The blue solid lines represent the association between the IVs and exposure as well as the association between exposure and outcome. Dash lines with a cross means that the association doesn’t meet three basic assumptions of Mendelian randomization: (i) IVs is closely linked to the exposure, (ii) the genetic variants are independent of confounders between exposure and outcomes, (iii) the genetic variants only influence the outcome via exposure.\u003c/p\u003e","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4007465/v1/78c9fea088c8cf1fbe4e638a.png"},{"id":52085937,"identity":"bb2edca1-4fc4-47f0-adce-d85fbabbed2e","added_by":"auto","created_at":"2024-03-06 12:21:09","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":38568,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart for the analytical methods and how MR analysis was performed step-by-step.\u003c/p\u003e","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4007465/v1/e6f9ddb417cc9b609dc42b6c.png"},{"id":52085936,"identity":"617622f0-922e-4fc5-b271-bce2ad191f4f","added_by":"auto","created_at":"2024-03-06 12:21:07","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":25904,"visible":true,"origin":"","legend":"\u003cp\u003eThe relationships between morphine and colorectal cancer were examined using IVW, MR-Egger, and WM. IVW, inverse-variance weighted method; MR, Mendelian randomization; WM, weighted median method; OR, odds ratio; 95% CI, 95% confidence interval.\u003c/p\u003e","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-4007465/v1/a3f2516302a939c3f09ec967.png"},{"id":52085934,"identity":"fd72d94f-3ee4-4f23-b3d0-9aca1e1e5a57","added_by":"auto","created_at":"2024-03-06 12:21:07","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":37792,"visible":true,"origin":"","legend":"\u003cp\u003eScatter plots of the MR analyses of morphine and colorectal cancer.\u003c/p\u003e","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-4007465/v1/bb16daa8688250bc0ea43329.png"},{"id":52085935,"identity":"047e155f-7201-4c28-b024-c490fb6b8e37","added_by":"auto","created_at":"2024-03-06 12:21:07","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":19683,"visible":true,"origin":"","legend":"\u003cp\u003eLeave-one-out analysis shows no one SNP makes a huge effect on colorectal cancer.\u003c/p\u003e","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-4007465/v1/9963ecf7a55de09c4a0ab70f.png"},{"id":52086273,"identity":"0e50e812-451b-42ae-b9eb-defc7239241d","added_by":"auto","created_at":"2024-03-06 12:29:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":849414,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4007465/v1/883980ac-5a46-4515-8284-6ac7bf58a4ae.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A protective causal relationship between morphine and colorectal cancer: a two-way Mendelian randomization study","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eColorectal cancer (CRC) is the third most common tumor in the United States (Rim et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) and the fourth most deadly malignancy in the world, killing about 700,000 people each year. With the development of the economy, people's diet structure is gradually biased towards meat food, which leads to a global increase in the incidence of CRCs year by year. It is projected that there will be an additional 2.5\u0026nbsp;million cases of colon cancer in developing countries by 2035 (Dekker et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Pain is a common symptom in CRC patients, with a prevalence of up to 70% (Zielinska et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Cancer pain affects the physical and emotional well-being of patients. The World Health Organization(WHO) has adopted a three-step analgesic ladder for the treatment of cancer pain, with the first step using non-opioids, the second step using weak opioids, and the third step using strong opioids (Donnelly et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2002\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMorphine is the most widely used strong opioid, with 85% of patients receiving good pain relief with morphine every 4 hours. It is still unclear whether morphine inhibits or promotes malignant cell proliferation and survival. Morphine has been reported to reduce cancer metastasis and recurrence, however, it also has been documented that morphine promotes the spread of cancer. Conflicting views on morphine immune suppression and inhibition of cancer progression exist in the real world. (Yuval et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). (Lu et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The reason for the controversy does not exclude bias or confounding factors in the study design, which could lead to contradictory results.\u003c/p\u003e \u003cp\u003eMendelian randomization (MR) is a statistical method for analyzing the relationship between phenotype and disease using single nucleotide polymorphisms (SNPs) as instrumental variables (IVs) (Bowden and Holmes, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). MR has randomness and stability because it follows Mendel's law of inheritance, which includes the random assignment of parental genes during the formation of a fertilized egg. Therefore, MR can maximize the avoidance of all kinds of bias in the design and operation of a clinical trial, balance the confounding factors, and improve the precision of the statistical results. To better understand the causal relationship between morphine and colorectal cancer, we conducted a two-way MR.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Research design\u003c/h2\u003e \u003cp\u003eBased on the Genome-Wide Association Study (GWAS) pooled data on morphine and CRC, we screened SNPs for MR analysis to investigate the causal relationship between morphine and colorectal cancer. This study strictly followed the three principles of MR analysis: (1) association is that instrumental variables (IVs) is closely linked to the exposure (2) independence is that the instrumental variable is independent of any confounding factors affecting the outcome; and (3) exclusivity is that the instrumental variable is independent of the outcome and can only affect the outcome through the exposure.\u003c/p\u003e \u003cp\u003eEvery dataset that was used in this research is openly accessible. Ethical clearance and written informed consent were provided in the original study.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Study cohort and GWAS\u003c/h2\u003e \u003cp\u003ePooled GWAS data were used in Two-sample MR. Exposure and outcome GWAS data were obtained in the IEU Open GWAS program. All GWAS studies have been limited to individuals of European ancestry. In the analysis, morphine exposure data were obtained from Neale Lab and contained a sample size of 337,159 (194 cases, 336,965 control cases). Colorectal cancer outcome data came from UK Biobank and included 5,657 colorectal cancer cases (372,016 control subjects). UK Biobank is a population-based prospective study. To have a better knowledge of a person's illness process, the UK Biobank gathers biological and medical data from half a million people living in the UK who are between the ages of 40 and 69. Preliminary studies provided relevant enrollment procedures and diagnostic criteria.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Instrumental Variables Selection\u003c/h2\u003e \u003cp\u003eTo choose IVs that would satisfy the three MR analysis assumptions and guarantee the stability and dependability of the MR analysis, a stringent set of quality controls was carried out. First, we used the R package TwoSampleMR (Hemani et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)to select genetic instruments from GWAS and screen for SNPs (p\u0026thinsp;\u0026lt;\u0026thinsp;5\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e) that are closely associated with exposures. Second, linkage disequilibrium analysis was performed. We must eliminate linkage disequilibrium because it raises the likelihood that genetic variants in identical genomic sites may be inherited jointly. This would lead to alleles occurring simultaneously on the same chromosome more frequently than at random. Kb is the length of the region of chain imbalance. R\u003csup\u003e2\u003c/sup\u003e can respond to the degree of allelic correlation, ranging from 0 to 1. When r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0, it is in a state of complete interlocking equilibrium. When r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;1, it is in a state of complete interlocking disequilibrium. Therefore, we need to extract SNPs with r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and kb\u0026thinsp;\u0026gt;\u0026thinsp;10,000. Third, we excluded SNPs associated with CRC (p\u0026thinsp;\u0026lt;\u0026thinsp;5\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;08\u003c/sup\u003e), because SNPs associated with CRC can confound the relationship between exposure and outcome, violating the exclusivity principle of Mendelian randomization study. Fourth, we applied the PhenoScanner database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.phenoscanner.medschl.cam.ac.uk/phenoscanner\u003c/span\u003e\u003cspan address=\"http://www.phenoscanner.medschl.cam.ac.uk/phenoscanner\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to exclude confounders (Hu et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Fourth, to detect potential weak IVs bias, we also calculated the F-statistic for all SNPs. An average F statistic more than 10 indicates a strong association between the SNP and the phenotype.(Burgess et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Fifth, the palindromic SNPs with intermediate allele frequencies were removed to ensure the accuracy of the results.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Research methodology\u003c/h2\u003e \u003cp\u003eThe MR analysis of morphine and CRC were performed primarily using the Two Sample MR and MRPRESSO software packages in R (version 4.3.1). p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. The main research methods included IVW, weighted median and MR Egger. IVW, which assumes that all SNPs are valid and assesses the combined effect by calculating the Wald value for each SNP, was used as the main method to assess causal effects. MR-Egger assumed that all SNPs were invalid, and weighted median method assumed that half of the SNPs were valid. MR-Egger and weighted median methods are able to provide reliable estimates over a wider range, but with reduced accuracy and relatively large standard errors, so they are complementary to IVW methods (Burgess and Thompson, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Several sensitivity analysis methods, including MR-Egger intercept and MR polytropic residuals and leave-one-out sensitivity test, were also performed to assess the stability and confidence of the results (Bowden and Holmes, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In the MR-Egger method, we used the relationship between intercepts and zeros to assess horizontal pleiotropy (Verbanck et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Differences between studies are called heterogeneity. Instrumental variables from different analytical platforms, experiments, and populations may be heterogeneous which can affect the results of Mendelian randomization analyses, so the heterogeneity needs to be assessed. Heterogeneity was analyzed mainly using the Q statistic. If p\u0026thinsp;\u0026gt;\u0026thinsp;0.05, the selected instrumental variables were considered not to be heterogeneous. Excessive heterogeneity means that the MR hypothesis may not be valid(Miao et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). At the same time, we performed Steiger filtering to determine if the direction of the exposure and the outcome were the same. Finally, we performed a bidirectional Mendelian analysis to assess the presence of reverse causality.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Mediation analysis\u003c/h2\u003e \u003cp\u003eIn order to study deeply the effect of morphine on colorectal cancer, we performed a mediated Mendelian analysis. We used colorectal cancer and risk factors as keywords for a comprehensive search in PubMed. Then, we searched for publicly available GWAS statistical abstracts for colorectal cancer risk factors. Finally, eight risk factors that include alcohol consumption, type 2 diabetes, fast insulin, body mass index (BMI), cholesterol to total lipids ratio in IDL, polyunsaturated fatty acids (PFA), LDL cholesterol, and smoking were identified (Li et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zhou et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Suzuki et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). We used a two-step Mendelian randomization analysis to study the mediating effects of morphine, colorectal cancer risk factors, and colorectal cancer, with the formula Beta\u0026thinsp;=\u0026thinsp;Beta (XZ)*Beta (ZY). In addition, standard errors (SE) and confidence intervals (CI) for the mediating effects were estimated using the delta method. The result of the MR analysis of exposure and outcome was the total effect. Direct effect\u0026thinsp;=\u0026thinsp;total effect - indirect effect (Beta (XY) \u0026ndash; Beta) (Carter et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eWith the Two Sample MR package, SNPs with p\u0026thinsp;\u0026lt;\u0026thinsp;5\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;08\u003c/sup\u003e were selected and then subjected to linkage disequilibrium analysis. Finally, three SNPs (rs117785145, rs35286491, rs639995) were selected to genetically represent the effects of morphine. Three SNPs were not associated with colorectal cancer risk factors as viewed through the PhenoScanner database. Through the mRnd (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://shiny.cnsgenomics.com/mRnd\u003c/span\u003e\u003cspan address=\"https://shiny.cnsgenomics.com/mRnd\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) calculation, we found that the F-values of instrumental variables greater than 10, indicating strong instrumental variables. After harmonizing the GWASs effector alleles for morphine and CRC, we performed MR primary methods to analyze the data. A protective causal relationship between morphine and colorectal cancer was found in the IVW analysis (OR 0.30, 95% CI 0.10\u0026ndash;0.87, p\u0026thinsp;=\u0026thinsp;0.027). The MR-Egger intercept suggested the absence of pleiotropy (MR-Egger intercept \u0026minus;\u0026thinsp;2 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e, SE 1 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e, p\u0026thinsp;=\u0026thinsp;0.370). No single SNP strongly violated the overall effect of morphine on CRC in the leave-one-out sensitivity analysis. Cochran's Q test showed no significant heterogeneity in individual SNP estimates (p\u0026thinsp;=\u0026thinsp;0.313). Steiger filtering provided assurance on the directionality of the causal relationships. In the reverse Mendelian randomization analysis, the p-values for IVW, MR-Egger, and weighted median were all greater than 0.05, suggesting that there is no reverse causality between morphine and colorectal cancer.\u003c/p\u003e \u003cp\u003eThe causal correlations estimated by MR-Egger were in contrast to those detected by the other two MR analyses, although it was nonsignificant. Therefore, these potential causal effects should be interpreted with caution. More investigations and studies are needed. However, the IVW method does not take into account pleiotropy and uses the inverse of the variance of the outcome as weights for the fit. The MR-Egger method takes into account the presence of intercept terms (multinomials) in the regression, leading to susceptibility to peripheral and influential instrumental variables and imprecision (Burgess and Thompson, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Due to the lack of horizontal pleiotropy and heterogeneity (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) in the Mendelian randomization analysis of morphine and CRC, the causality obtained by IVW was more accurate than the results of MR-Egger. Therefore, the value of IVW is reasonable. Although it was significant(p\u0026thinsp;\u0026gt;\u0026thinsp;0.05), the weighted median methods were in the same direction as the IVW methods, which may reinforce the validity of a possible protective causal relationship between morphine and CRC.\u003c/p\u003e \u003cp\u003e \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\u003eThe results of bidirectional Mendelian randomization.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExposure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003emethod\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003cp\u003e(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\u003eCochran Q (p value)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMR-Egger intercept (P value)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003emorphine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIVW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003cp\u003e(0.10\u0026ndash;0.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.32(p\u0026thinsp;=\u0026thinsp;0.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMR-Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.56\u003c/p\u003e \u003cp\u003e(0.14\u0026ndash;49.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01(p\u0026thinsp;=\u0026thinsp;0.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e(p\u0026thinsp;=\u0026thinsp;0.37)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWeighted median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003cp\u003e(0.10\u0026ndash;1.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eColorectal cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIVW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003cp\u003e(0.99\u0026ndash;1.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.01(p\u0026thinsp;=\u0026thinsp;0.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMR-Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003cp\u003e(0.92\u0026ndash;1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.88(p\u0026thinsp;=\u0026thinsp;0.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.14\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e(p\u0026thinsp;=\u0026thinsp;0.73)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWeighted median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003cp\u003e(0.93\u0026ndash;1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eRegrettably, we did not find a mediator between exposure and outcome among the eight risk factors. However, we found that the ORs between morphine and cholesterol to Total lipids ratio in IDL, and type 2 diabetes were less than 1. IVW, MR-Egger, and Weighted median were in the same direction. A causal relationship between cholesterol to total lipids ratio in IDL and CRC was determined by two-step Mendelian randomization. There was no causal relationship between morphine and cholesterol to total lipids ratio in IDL, but the results of the Mendelian randomization analysis of morphine and cholesterol to total lipids ratio in IDL suggested that they were directionally consistent (the supplementary material: Table S2).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe relationship between morphine and colorectal cancer is currently controversial. It has been suggested that morphine activates EGFR signaling in human colorectal cancer thereby promoting tumorigenesis (Lu et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, several more studies have reported the ability of morphine to inhibit the adhesion of colorectal cancer cells (Min et al., 2011). We aimed to better assess the relationship between morphine and colorectal cancer using bidirectional Mendelian randomization. The results of Mendelian randomization showed that morphine seems to reduce the risk of colorectal cancer. This study complements the clinical retrospective and randomized studies and provides some evidence that morphine reduces the risk of colorectal cancer.\u003c/p\u003e \u003cp\u003eMorphine is a very effective analgesic. Morphine-3-glucuronide (M3G) and morphine-6-glucuronide (M6G) are the major metabolites of morphine. M6G is the main component of morphine that exerts pain relief. Morphine is a third-step analgesic that can quickly achieve pain relief and ease the pain of cancer patients. Morphine is a very safe and effective drug for tumor patients when used correctly. A retrospective cohort study shows older cancer survivors have lower long-term risk of opioid use than control noncancer patients (Jairam et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Many studies have shown that physical and psychological pain stress promotes tumor development. Morphine improves the quality of life of tumor patients by effectively controlling pain and relieves stress to reduce tumor metastasis. The most common side effect of morphine is constipation. It is very interesting that one study showed that the most common type of cancer among constipated patients was non-colorectal gastrointestinal and colorectal gastrointestinal tumors were less common than other tumors (Roeland et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Several potential mechanisms could explain the protective role of morphine in colorectal cancer. Morphine reduces adhesion of colorectal cancer cells to collagen and connective fibers of the extracellular matrix and decreases the invasiveness of cancer cells. It has also been shown that morphine inhibits the growth of blood vessels and reduces the ability of tumors to metastasize. The mechanism of morphine on CRC still requires further studies in pathology.\u003c/p\u003e \u003cp\u003eUnfortunately, mediation analysis failed to find significant results. However, mediation analysis revealed that the cholesterol to total lipids ratio in IDL was a risk factor for CRC. At the same time, we cannot exclude the possibility that there is a relationship between morphine, cholesterol to total lipids ratio in IDL, and CRC. In the future, we need further experimental studies or more comprehensive data studies to verify this possibility.\u003c/p\u003e \u003cp\u003eThe study used Mendelian randomization analysis to find a possible protective effect of morphine in colorectal cancer patients. This evidence may provide some confidence in the rational use of morphine to control cancer pain in CRC patients. This study has several strengths. First, MR is a study that possesses a higher level of evidence, which can compensate for the limitations that exist in observational studies such as confounding and bias, and thus enhance causal inferences. Second, the GWAS dataset for this study was based primarily on European population pedigrees, reducing the impact of population differences on the study. Third, the results are very reliable. Because we used the PhenoScanner database to rigorously check for confounders related to morphine and CRC; no IVs with confounding factors were detected, preventing potential horizontal pleiotropy. Meanwhile, sensitivity analysis using MR-Egger and leave-one-out assessment methods ensured the reliability of the results. In addition, Cochran's Q test did not detect significant heterogeneity. Finally, to the best of our knowledge, this is the first article to discuss the causal relationship between morphine and colorectal cancer using Mendelian randomization study methods. There are limitations that need to be considered in interpreting our findings. First, only the primary analysis method, IVW, suggested a relationship between morphine and colorectal cancer. Results should be interpreted with caution. Larger samples and more sophisticated methods are needed to confirm the results. Second, the study only included a single population and needs further validation in a larger population. Third, Mendelian randomization could only find a protective causal relationship between morphine and colorectal, but it was not possible to understand the specific mechanisms and effects of morphine in the development of colorectal cancer, and further experimental studies are needed.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn conclusion, we provide evidence of a possible protective causal relationship between morphine and colorectal cancer. Our study provides a new insight into the role of morphine in colorectal cancer risk. We increase new evidence that morphine can be used in the clinic to relieve pain in patients with colorectal cancer.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e Q D and Y Y designed the study and written this article. C Y, H L and CG collected and analyzed the data. X W contributed to the revision of the manuscript. All authors were involved in the writing of the article and in the approval of the version for submission. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This research was funded by the National Nature Science Foundation of China (No. 82274605).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstitutional Review Board Statement:\u003c/strong\u003e This study did not require ethical approval.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent Statement:\u003c/strong\u003e The consent of the patients was not required because the informed consent had already been given in the original study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e All data involved in this study are available in the public database. For further information, please contact the corresponding authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e We would like to thank all of the GWASs for making their summary data available to the public, and all of the investigators and participants who contributed to these studies. In addition, we want to acknowledge the participants and investigators of the UK Biobank and Neale Lab.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u003c/strong\u003e The authors declare to have carried out the study in the absence of any commercial or financial relationship that would constitute a potential conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRim, S. H., Seeff, L., Ahmed, F., King, J. B., and Coughlin, S. S. (2009). Colorectal cancer incidence in the United States, 1999-2004. 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Supportive Care in Cancer \u003cem\u003e28\u003c/em\u003e, 1793\u0026ndash;1797.doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00520-019-04996-7\u003c/span\u003e\u003cspan address=\"10.1007/s00520-019-04996-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Supplementary Table","content":"\u003cp\u003eSupplementary Table S2 is not available with this version\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":"[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":"Mendelian randomization, morphine, colorectal cancer, causal relationship, prospective analysis","lastPublishedDoi":"10.21203/rs.3.rs-4007465/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4007465/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePurpose: The relationship between morphine and colorectal cancer has been controversial. To address this controversial issue, we examined the relationship between morphine and colorectal cancer.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMethods: The causal relationship between morphine and colorectal cancer was investigated through Mendelian randomization (MR). Analysis was conducted using the publicly available GWAS database. First, single nucleotide polymorphisms (SNPs) strongly associated with morphine exposure factors were screened. Then the causal relationship between morphine and colorectal cancer was analyzed using inverse variance weighted (IVW), weighted median, and MR Egger methods. Finally, tests for sensitivity, heterogeneity, and pleiotropy were performed to ensure the stability and reliability of the results.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eResult: The IVW analysis revealed a protective causal relationship between morphine use and colorectal cancer (odds ratio [OR] = 0.30, 95% confidence interval [CI]: 0.10-0.87, p = 0.03).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConclusion: We provide evidence of a possible protective causal relationship between morphine and colorectal cancer. Further validation through larger clinical randomized studies and more advanced methods is needed.\u003c/p\u003e","manuscriptTitle":"A protective causal relationship between morphine and colorectal cancer: a two-way Mendelian randomization study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-06 12:21:02","doi":"10.21203/rs.3.rs-4007465/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":"c177a3c1-b9b0-4b4f-9ad2-d40befebd182","owner":[],"postedDate":"March 6th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-03-06T12:21:05+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-06 12:21:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4007465","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4007465","identity":"rs-4007465","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}