Abstract

Background Colorectal cancer (CRC) is the third most common cancer worldwide, with 1.9 million new cases in 2020 and a predicted rise to 3.2 million in 2040. Screening programmes are already in place to aid early detection and secondary prevention of CRC, but the rising prevalence means additional approaches are required in both primary and secondary prevention settings. Preventive therapy, whereby natural or synthetic agents are used to prevent, reverse or delay disease development, could be an effective strategy to further reduce cancer risk and potential agents have already been identified in conventional observational studies. However, as such studies are vulnerable to confounding and reverse causation, we aim to evaluate these observed relationships using Mendelian randomization (MR), an alternative causal inference approach which should be less susceptible to these biases. Methods and analysis We will use two-sample MR, which uses two independent samples for the exposure and outcome data, to investigate previously reported observational associations of multiple potential preventive agents with CRC risk. We define preventive agents as any synthetic (e.g. approved medication) or natural (e.g. micronutrient, endogenous hormone) molecule used to reduce the risk of cancer. We will first extract potential preventive agents that have been previously linked to CRC risk in observational studies from reviews of the literature. We will then evaluate whether we can develop a genetic instrument for each preventive agent from previously published genome-wide association studies (GWASs) of direct measures of molecular traits (e.g. circulating levels of protein drug targets, blood-based biomarkers of dietary vitamins). The summary statistics from these GWASs, and a large GWAS of CRC, will be used in two-sample MR analyses to investigate the causal effect of putative preventive therapy agents on CRC risk. Sensitivity analyses will be conducted to evaluate the robustness of findings to potential violations of MR assumptions.

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