Application of Mendelian randomization to appraise causality in relationships between the gut microbiome and cancer

Application of Mendelian randomization to appraise causality in relationships between the gut microbiome and cancer | Research Square 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 Help Center Sign In Submit a Preprint Cite Share Download PDF Article Application of Mendelian randomization to appraise causality in relationships between the gut microbiome and cancer Amy Dawes, Charlie Hatcher, Alec McKinlay, Kaitlin Wade This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8444550/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Cancer is among the leading causes of death worldwide; however, with incidence rising, there is a requirement to identify novel risk factors and biomarkers to prevent and diagnose cancer earlier. Previous work has implicated a role of the gut microbiome in cancer aetiology; however, its causal relevance is not clear. Whilst Mendelian randomisation (MR) is increasingly being applied to assess the causal role of the gut microbiome on several health outcomes, the complexities and limitations of the method are not fully addressed in much of the current literature. Here, we aimed to appropriately apply MR to understand the role of the gut microbiome in cancer aetiology, whilst demonstrating the range of sensitivity analyses required to provide appropriate causal inference. Whilst findings initially suggested that there were several bacterial genera, families and phyla that may alter cancer risk, further sensitivity analyses indicated that these results were unlikely to reflect causality given violations of core MR assumptions. This study highlights the need for a rigorous MR analysis pipeline, incorporating sensitivity analyses evaluating the plausibility of MR-derived effect estimates, to avoid incorrect conclusions around causality, where estimates likely reflect more complex relationships. Health sciences/Medical research Health sciences/Risk factors Full Text Additional Declarations There is NO Competing Interest. Supplementary Files STROBEMRchecklistAD.pdf STROBE-MR checklist SupplementaryTablesST1ST20.xlsx Dataset 1 (Supplementary Tables 1-20) Supplementarymaterial.pdf Supplementary Methods and Supplementary Figures Cite Share Download PDF Status: Under Review 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 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

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