Sex-Stratified Mendelian Randomization Study on the Associations Between Dietary Habits and Colorectal Cancer Risk

Sex-Stratified Mendelian Randomization Study on the Associations Between Dietary Habits and Colorectal Cancer Risk | 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 Sex-Stratified Mendelian Randomization Study on the Associations Between Dietary Habits and Colorectal Cancer Risk Qilu Huang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5329671/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: Colorectal cancer (CRC) remains a major global health challenge, with dietary habits being a key modifiable risk factor. Understanding the relationship between specific dietary habits and CRC can offer valuable insights for prevention. This study aimed to investigate the associations between 72 dietary habits and CRC risk using a sex-stratified Mendelian randomization (MR) approach. Methods: We performed a sex-specific Mendelian randomization study in males and females to assess the causal associations between 72 dietary habits, including drinking water intake, low-calorie drink intake, fizzy drink intake, orange juice intake, and instant coffee intake, and CRC risk. Significant SNPs (P < 5e-6) associated with dietary habits were selected as instrumental variables after clumping. Five MR methods were applied, including Inverse Variance Weighted (IVW) with multiplicative random effects. Sensitivity analyses using IVW, MR-Egger, and leave-one-out tests were conducted to assess pleiotropy and heterogeneity. Dietary habits that remained significant after FDR correction (P < 0.05) were considered to have a significant association with CRC risk. Results: After FDR correction, significant associations were identified in males for average weekly fortified wine intake (OR (95% CI) = 0.985 (0.979–0.991), P = 3.30E-07), sweet pepper intake (OR (95% CI) = 0.996 (0.994–0.998), P = 6.56E-05), and bacon intake (OR (95% CI) = 1.002 (1.001–1.003), P = 0.000417887). In females, symptoms and signs concerning food and fluid intake were significantly associated with CRC (OR (95% CI) = 1.083 (1.046–1.121), P = 6.08E-06). No evidence of pleiotropy or heterogeneity was observed in the sensitivity analyses. Conclusion: This study provides robust evidence that several dietary habits are causally associated with CRC risk in a sex-specific manner. The findings emphasize the importance of personalized dietary recommendations for CRC prevention and highlight key dietary factors influencing CRC risk in both males and females. Mendelian randomization colorectal cancer dietary habits sex-stratified analysis FDR correction IVW MR-Egger sensitivity analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Colorectal cancer (CRC) is a major public health concern worldwide, ranking as one of the leading causes of cancer-related morbidity and mortality(Favoriti et al., 2016 ; Xi & Xu, 2021 ). Globally, CRC accounts for nearly 1.9 million new cases and over 900,000 deaths annually, making it the third most common cancer and the second leading cause of cancer deaths(Center, Jemal, Smith, & Ward, 2009 ; Douaiher et al., 2017 ). The burden of CRC is expected to increase significantly in the coming decades due to the aging population, lifestyle factors, and dietary habits, particularly in countries undergoing rapid urbanization and economic development(Salehiniya et al., 2017 ). Despite advances in early detection, screening, and treatment, the survival rates for CRC vary considerably across different regions, with developed countries generally showing better outcomes due to organized screening programs. CRC is a multifactorial disease with both genetic predispositions and environmental factors, including diet and lifestyle, playing critical roles in its development. Numerous studies have demonstrated that modifiable risk factors such as obesity, physical inactivity, smoking, and, most notably, diet, can significantly influence CRC risk(Al-Sohaily, Biankin, Leong, Kohonen‐Corish, & Warusavitarne, 2012 ; de la Chapelle, 2004 ). Thus, understanding the underlying risk factors and identifying potential preventive measures remain key areas of research in combating CRC. In particular, dietary habits have emerged as a crucial modifiable factor, with certain dietary patterns and specific food items either increasing or reducing CRC risk(Magalhães, Peleteiro, & Lunet, 2012 ; Pietrzyk, 2017 ). As such, dietary interventions hold promise as a public health strategy for reducing the incidence of CRC. Dietary factors have long been recognized as important contributors to the risk of developing colorectal cancer(Nishi, Yoshida, Hirata, & Miyake, 1997 ). The traditional Western diet, characterized by high intakes of red and processed meats, refined grains, sugary beverages, and low fiber intake, has been strongly linked to an increased risk of CRC(Fung & Brown, 2013 ). In contrast, diets rich in fruits, vegetables, whole grains, and fish, such as the Mediterranean diet, have been associated with a reduced risk of CRC(R. F. Tayyem et al., 2017 ). The consumption of fiber, antioxidants, vitamins, and other bioactive compounds in these foods is believed to exert protective effects against colorectal carcinogenesis by promoting gut health, reducing inflammation, and regulating cell proliferation and apoptosis(Reema F. Tayyem et al., 2017 ). Specific food items and beverages have been the subject of much epidemiological and experimental research. For instance, red and processed meat intake has been classified as a probable carcinogen for CRC by the International Agency for Research on Cancer (IARC), largely due to the presence of carcinogenic compounds such as N-nitroso compounds and heterocyclic amines(Cascella et al., 2018 ). Conversely, higher consumption of fiber-rich foods, particularly whole grains, has been consistently associated with a lower risk of CRC(X. He et al., 2019 ). Furthermore, the intake of specific beverages, such as alcohol and sugary drinks, has also been implicated in CRC risk, with alcohol consumption being a well-established risk factor(Fardet, Druesne-Pecollo, Touvier, & Latino-Martel, 2017 ). While observational studies have provided valuable insights into the relationship between diet and CRC risk, they are often subject to confounding factors, reverse causality, and measurement errors inherent in dietary assessments. Mendelian randomization (MR) has emerged as a powerful tool to overcome these limitations by using genetic variants as instrumental variables (IVs) to assess the causal relationships between exposures, such as dietary habits, and disease outcomes. This approach minimizes bias from confounding and reverse causality, making it a valuable method for studying the causal impact of diet on CRC risk. Several MR studies have successfully identified causal associations between diet and CRC, although the focus has primarily been on single dietary factors rather than comprehensive dietary patterns(Deng, Wang, Huang, Ding, & Wong, 2022 ; M. He, Huan, Wang, Fan, & Huang, 2024 ). In this study, we employed a Mendelian randomization (MR) approach to investigate the causal relationships between 72 dietary habits and CRC risk, using a sex-stratified analysis. This study represents one of the Mendelian randomization investigations of dietary habits and CRC risk. By employing a robust methodological framework and examining a wide range of dietary exposures, our research aims to enhance the understanding of how diet contributes to CRC risk in a sex-specific context. The findings from this study may have important implications for personalized dietary recommendations and public health strategies aimed at reducing the global burden of colorectal cancer. Methods Data source All GWAS summary data used in this study were derived from male and female participants separately to ensure the accuracy of the analysis. The GWAS data for 72 dietary habits, including drinking water intake, low calorie drink intake, fizzy drink intake, orange juice intake, instant coffee intake, filtered coffee intake, intake of sugar added to coffee, standard tea intake, milk intake, and red wine intake, were obtained from the results of GWAS round 2 from Neale Lab. Detailed information, such as recruitment criteria of population and quality control of genetic data, can be found in the http://www.nealelab.is/uk-biobank . The imputed genotypes were from the HRC plus UK10K & 1000 Genomes reference panels as released by UK Biobank in March 2018. The UK Biobank is a large-scale biomedical database and research resource containing in-depth genetic and health information from half a million UK participants, designed to improve the prevention, diagnosis, and treatment of a wide range of serious and life-threatening illnesses. The details of the dietary habits dataset can be found in Supplementary Table 1. The GWAS summary data for CRC were obtained from GWAS round 2 from Neale Lab (Cancer code, self-reported: large bowel cancer/colorectal cancer). The details of the CRC dataset can be found in Supplementary Table 2. These GWAS sample populations are predominantly of European descent. Although there is some overlap between the populations used in the exposure and outcome GWASs, specific Mendelian Randomization methods were applied to minimize the impact of this overlap on the results(Minelli et al., 2021 ). The list of covariates varies between original GWASs, but always included sex and age. Details can be found in the original studies. The data analyzed in this secondary study is publicly available from existing, published GWASs and therefore the ethical approval and informed consent have been obtained by all original studies. This is a secondary analysis based on summary statistics from existing, published studies. The ethical approval and informed consent have been obtained by all original studies. Genetic instrumental variables (IVs) selection The selection of instrumental variables (IVs) is crucial for ensuring the accuracy and robustness of causal inferences in Mendelian randomization analysis. IVs must satisfy three key assumptions: (1) the genetic variants must be associated with the exposures; (2) the genetic variants must not be related to confounders; and (3) the genetic variants should influence the outcomes only through the exposures, without affecting other pathways. This study adhered to specific criteria for selecting instrumental variables (IVs). Firstly, each SNP had to demonstrate a significant association with the 72 dietary habits, surpassing the genome-wide significance threshold of P < 5E-6. Secondly, linkage disequilibrium (LD) was assessed using European sample data from the 1000 Genomes Project reference panel, retaining only the most significant SNPs among those with an R2 < 0.001 within a clumping window of 10,000 kb. Thirdly, SNPs with a minor allele frequency (MAF) of ≤ 0.01 were excluded to mitigate potential bias from genetic pleiotropy. The final set of SNPs meeting these criteria was employed as instrumental variables in the TSMR analysis. Two-sample Mendelian randomization analysis Our study utilized MR to investigate the causal relationships between dietary habits and CRC. The analytical approach required comprehensive datasets for both exposures and outcomes, including SNP rsids, effect sizes (beta coefficients), alleles (effect and other), standard errors (SEs), effect allele frequencies (EAFs), and P-values. To avoid ambiguities caused by palindromic SNPs (SNPs with the same alleles on both DNA strands), we excluded such SNPs from the analysis. The MR analysis was conducted using five methods: Inverse Variance Weighted (multiplicative random effects), Weighted Median, Inverse Variance Weighted (IVW), Inverse Variance Weighted (fixed effects), and Weighted Mode. Among these, Inverse Variance Weighted (multiplicative random effects) served as the primary method for determining whether significant causal relationships exist between dietary habits and CRC. These methods were selected because, even in the presence of confounding factors, two-sample MR approaches—including fixed-effect and (multiplicative) random-effects meta-analysis, weighted median estimator, and weighted mode estimator—generally perform comparably to one-sample MR(Minelli et al., 2021 ). However, MR-Egger can introduce bias that reflects the direction and magnitude of confounding, and therefore was not the primary method used in this study. The list of covariates varies between original GWASs, but always included sex and age. Details can be found in the original studies. MR were performed using the “TwoSampleMR” (version 0.5.10) packages in R (version 4.3.3). Sensitivity analysis Heterogeneity in this study refers to the variability in causal estimates across the different genetic variants used as instrumental variables, which can indicate potential inconsistencies in causal effects. We assessed heterogeneity using the MR Egger and Inverse Variance Weighted methods, considering dietary habits with a Q_pval < 0.05 as indicative of heterogeneity. Pleiotropy, where a genetic variant influences multiple phenotypic traits and may confound causal estimates, was evaluated using the MR Egger method. Dietary habits with a p-value < 0.05 were considered to suggest pleiotropy. To evaluate the robustness and potential impact of individual variants, we employed the leave-one-out method, which involves iteratively removing one genetic variant at a time to assess its influence on the overall causal estimate. Visual representations of the MR analysis results were provided through scatter plots, forest plots, and leave-one-out plots. Results According to our IV selection strategy described previously, this study extracted a total of 1896 SNPs as instrumental variables for the 72 dietary habits, with the number of IVs per dietary habit ranging from 6 to 64 for male, and a total of 1909 SNPs as instrumental variables for the 72 dietary habits, with the number of IVs per dietary habit ranging from 9 to 116 for female. Subsequently, these SNPs and their proxies were extracted from datasets for the CRC. The details of all the IVs in the exposures and outcomes, including SNP rsids, effect sizes (beta coefficients), alleles (effect and other), standard errors (SEs), effect allele frequencies (EAFs), and P-values can be found in Supplementary Table 3. As shown in Fig. 1, The MR analysis results showed 3 positive associations in male and 2 positive associations in female before FDR correction. As shown in Fig. 2–4, after FDR correction, significant associations were identified in males for average weekly fortified wine intake (OR (95% CI) = 0.985 (0.979–0.991), P = 3.30E-07), sweet pepper intake (OR (95% CI) = 0.996 (0.994–0.998), P = 6.56E-05), and bacon intake (OR (95% CI) = 1.002 (1.001–1.003), P = 0.000417887). In females, symptoms and signs concerning food and fluid intake were significantly associated with CRC (OR (95% CI) = 1.083 (1.046–1.121), P = 6.08E-06). All the MR results, including those from the five MR methods, can be found in Supplementary Table 4. For sensitivity analysis, no evidence of heterogeneity or pleiotropy was detected for this result (Supplementary Tables 5 and 6). As shown in Figure S1 , the leave-one-out analysis indicated that the result was not significantly influenced by any single SNP. Discussion In this study, we performed a comprehensive sex-stratified Mendelian randomization analysis to investigate the causal relationships between 72 dietary habits and the risk of colorectal cancer in both males and females. Using genetic variants significantly associated with dietary habits as instrumental variables, we applied five robust MR methods, including Inverse Variance Weighted (IVW) with multiplicative random effects, to estimate causal effects. Additionally, sensitivity analyses such as MR-Egger, leave-one-out, and heterogeneity tests were conducted to ensure the robustness of the findings. After applying false discovery rate correction, several dietary habits were identified as significantly associated with CRC risk. Notably, in males, we found significant associations between CRC risk and average weekly fortified wine intake, sweet pepper intake, and bacon intake, while in females, symptoms and signs concerning food and fluid intake were significantly linked to CRC risk. Importantly, no evidence of pleiotropy or heterogeneity was observed in the sensitivity analyses, further strengthening the credibility of our results. Our findings provide novel insights into the sex-specific dietary factors contributing to CRC risk and underscore the potential for personalized dietary recommendations in cancer prevention. The significant associations identified in males for average weekly fortified wine intake, sweet pepper intake, and bacon intake provide intriguing insights into the potential dietary factors influencing colorectal cancer risk. Each of these dietary habits has a unique set of characteristics that may contribute to cancer development, highlighting the complexity of diet-disease interactions and the importance of examining these relationships in a sex-specific context. The inverse association observed between average weekly fortified wine intake and CRC risk (OR = 0.985, 95% CI = 0.979–0.991, P = 3.30E-07) suggests that moderate consumption of fortified wine may have a protective effect against CRC in males. While alcohol consumption is generally considered a risk factor for many cancers, including CRC, the specific components of fortified wine—such as polyphenols, antioxidants, and resveratrol—may play a protective role in certain contexts. These compounds have been shown to exhibit anti-inflammatory and anti-proliferative properties, potentially counteracting some of the harmful effects of alcohol. However, the complex nature of alcohol-related risks and benefits means that further studies are necessary to confirm whether this association is truly protective or reflects other underlying lifestyle factors. The significant association between sweet pepper intake and a reduced risk of CRC in males (OR = 0.996, 95% CI = 0.994–0.998, P = 6.56E-05) adds to the growing body of evidence supporting the role of vegetables in cancer prevention. Sweet peppers are rich in vitamins, particularly vitamin C, as well as carotenoids, flavonoids, and other bioactive compounds known for their antioxidant and anti-inflammatory properties(Azlan, Sultana, Huei, & Razman, 2022 ; de Sá Mendes & Branco de Andrade Gonçalves, 2020). These nutrients may help neutralize free radicals, reduce oxidative stress, and inhibit inflammation, all of which are processes implicated in colorectal carcinogenesis. The protective effect observed in this study suggests that regular consumption of sweet peppers may contribute to a lower risk of CRC, especially in males, who may have different dietary needs or metabolic responses compared to females. The positive association between bacon intake and CRC risk (OR = 1.002, 95% CI = 1.001–1.003, P = 0.000417887) is consistent with the well-established link between processed meat consumption and colorectal cancer. Bacon, like other processed meats, contains nitrates and nitrites, which can form carcinogenic N-nitroso compounds when metabolized(Crowe, Elliott, & Green, 2019 ; Deveci & Tek, 2024 ). Additionally, the cooking process, particularly at high temperatures, can produce heterocyclic amines (HCAs) and polycyclic aromatic hydrocarbons (PAHs), both of which are known carcinogens(Edna Hee, Liang, Zhang, & Fang, 2024 ). The slight increase in CRC risk associated with bacon intake in males reinforces existing dietary guidelines that recommend limiting the consumption of processed meats to reduce cancer risk. Interestingly, the magnitude of the effect in this study is relatively small (OR = 1.002), suggesting that while bacon consumption is a risk factor, the overall contribution to CRC risk may depend on other factors such as quantity, frequency, and interaction with other dietary components. The significant association between symptoms and signs concerning food and fluid intake and an increased risk of colorectal cancer (CRC) in females (OR = 1.083, 95% CI = 1.046–1.121, P = 6.08E-06) highlights an intriguing, yet complex relationship between gastrointestinal health and cancer risk. This result suggests that females who exhibit symptoms or signs related to food and fluid intake—such as digestive discomfort, irregular eating habits, or specific gastrointestinal issues—may have a heightened risk of developing CRC. There are several potential mechanisms through which gastrointestinal symptoms and CRC risk may be linked. Symptoms concerning food and fluid intake could be indicative of underlying digestive system dysfunctions that, over time, contribute to colorectal carcinogenesis(Ahmad Kendong, Raja Ali, Nawawi, Ahmad, & Mokhtar, 2021; Larsen et al., 2019 ). For example, chronic gastrointestinal issues such as irritable bowel syndrome (IBS), dyspepsia, or frequent episodes of bloating and indigestion may lead to prolonged inflammation or disturbances in the gut microbiome, both of which are increasingly recognized as factors that can promote the development of CRC. Inflammation in the gut creates an environment conducive to the development of cancer by increasing cell turnover and promoting genetic mutations. Additionally, an imbalance in the gut microbiota, known as dysbiosis, has been linked to several gastrointestinal diseases, and emerging evidence suggests it may play a role in CRC by altering the local immune response and promoting pro-carcinogenic pathways. Several limitations should be acknowledged. First, while MR is a powerful tool for assessing causal relationships and minimizing confounding and reverse causality, it relies on several key assumptions. One of the primary assumptions is that the instrumental variables (IVs) used—genetic variants associated with dietary habits—are only related to the outcome (CRC) through the exposure (dietary habits). However, the potential for horizontal pleiotropy, where genetic variants influence CRC through pathways other than dietary habits, cannot be entirely excluded. Although sensitivity analyses, including MR-Egger and leave-one-out tests, did not indicate substantial pleiotropy or heterogeneity, the presence of unmeasured pleiotropy may still bias the results. Second, the genetic instruments used for dietary habits were selected from genome-wide association studies (GWAS), which often rely on self-reported dietary data. Self-reported dietary intake is prone to measurement error and recall bias, which can affect the strength and accuracy of the associations between genetic variants and dietary habits. While the use of genetic instruments reduces the biases typically associated with observational studies, the precision of the MR estimates may still be limited by the quality of the dietary data used in the GWAS. Third, although we conducted sex-stratified analyses to explore potential differences in dietary associations with CRC between males and females, the power to detect significant associations might be constrained by sample size. Some dietary habits may have smaller or more nuanced effects on CRC risk that were not detected due to limited statistical power, particularly for habits with fewer available genetic instruments. Moreover, the generalizability of the findings may be limited to populations of European ancestry, as the majority of the GWAS data used to identify genetic instruments were derived from European cohorts. The associations observed in this study may differ in non-European populations due to differences in genetic background, dietary patterns, and CRC risk factors. Fourth, the dietary habits examined in this study were broad and included a wide range of food and beverage items. While this comprehensive approach is a strength, it also introduces complexity when interpreting the results. Some dietary habits, such as “symptoms and signs concerning food and fluid intake,” may encompass a variety of underlying behaviors or conditions that were not directly measured in this study. Therefore, the associations observed for these broader dietary categories may reflect a combination of factors, making it challenging to pinpoint the exact dietary components or behaviors driving the associations with CRC risk. Lastly, this study focused on CRC as a single outcome, without considering potential interactions between dietary habits and other lifestyle factors or comorbidities that may also influence cancer risk. For instance, smoking, physical activity, and alcohol consumption are known to interact with diet in shaping CRC risk, but these factors were not directly accounted for in the MR analysis. Future studies should consider examining these interactions and conducting stratified analyses based on other lifestyle factors to gain a more comprehensive understanding of the diet-CRC relationship. Conclusion This sex-stratified Mendelian randomization study offers robust evidence of the causal associations between specific dietary habits and colorectal cancer risk in both males and females. Our findings highlight significant associations between average weekly fortified wine intake, sweet pepper intake, and bacon intake with CRC risk in males, and symptoms and signs concerning food and fluid intake with CRC risk in females. These results emphasize the complexity of diet-disease interactions and suggest that dietary habits may have sex-specific effects on CRC development. This study underscores the importance of personalized dietary recommendations for CRC prevention and suggests that targeting specific dietary behaviors could play a crucial role in reducing CRC incidence. However, further research is needed to validate these findings in diverse populations and to explore the underlying biological mechanisms that link diet, sex, and CRC risk. Through such efforts, more effective, tailored public health strategies can be developed to mitigate the growing global burden of colorectal cancer. Declarations Ethics approval and consent to participate We employed publicly available GWAS summary statistics data obtained from he Drug-Gene Interaction Database (DGIdb, https://www.dgidb.org/ ), FinnGen Consortium ( https://www.finngen.fi/en ), https://www.finngen.fi/en ), IEU GWAS ( https://gwas.mrcieu.ac.uk/ ), which collects data from studies conducted with appropriate informed consent protocols approved by institutional review boards. As a result, our study does not require a separate ethics statement. Consent for publication The author approved the final manuscript and the submission to this journal. Competing interests The author declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Funding This study was not supported by grants from the institutional funds. Author Contribution Q.L.Huang contributed to the study topic selection, data collection, statistics and analysis, first draft and final manuscript. Acknowledgement We would like to extend our thanks to the Drug-Gene Interaction Database (DGIdb, https://www.dgidb.org/), FinnGen Consortium (https://www.finngen.fi/en), IEU GWAS (https://gwas.mrcieu.ac.uk/) for granting public access to their summary data. Furthermore, we are grateful to the principal investigators of the studies for their transparency in sharing their data for research purposes. Data Availability The datasets generated and/or analysed during the current study are available in the Drug-Gene Interaction Database (DGIdb, https://www.dgidb.org/), FinnGen Consortium (https://www.finngen.fi/en), https://www.finngen.fi/en), IEU GWAS (https://gwas.mrcieu.ac.uk/). References Ahmad Kendong SM, Ali R, Nawawi RA, Ahmad KNM, H. F., Mokhtar NM. 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Clin Nutr. 2017;36(3):848–52. 10.1016/j.clnu.2016.04.029 . Xi Y, Xu P. Global colorectal cancer burden in 2020 and projections to 2040. Translational Oncol. 2021;14(10). 10.1016/j.tranon.2021.101174 . Additional Declarations No competing interests reported. Supplementary Files Tables.xlsx FigureS1a.tif FigureS1b.tif FigureS1c.tif FigureS1d.tif FigureS1e.tif 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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Huang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyElEQVRIiWNgGAWjYBACAyjNw8fAfODAhx+kaGFjYEs8OLOHBC0MbAw8xoc52IjQYi6R/OzhFwZrGTaJnA+HGXgY5PnFDuDXYjkjzdxYhiGdh00id8PhAgsGw5mzEwg47EaCmbQEw2GIlhk8DAkGtwlqSf8G1ZLzAEgSpSXHTPIDRAsDkVrOvCmTZgD5heeZATCQJYjwy/H0bZI/GKzt+dmTH3/48MNGnl+agBYQYOb9xwxjSxBWDgKMPxiYCasaBaNgFIyCkQsAIVU9FQUEQJcAAAAASUVORK5CYII=","orcid":"","institution":"The People’s Hospital of Qiannan","correspondingAuthor":true,"prefix":"","firstName":"Qilu","middleName":"","lastName":"Huang","suffix":""}],"badges":[],"createdAt":"2024-10-25 05:23:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5329671/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5329671/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":68470312,"identity":"80869fa5-2e63-4d22-8ecb-2085ad6a194b","added_by":"auto","created_at":"2024-11-07 14:56:34","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":341505,"visible":true,"origin":"","legend":"\u003cp\u003eThe heat map for the MR result between dietary habits and colorectal cancer risk.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5329671/v1/90c89ee44101864b16a63a94.png"},{"id":68470311,"identity":"95605225-bbad-4d29-a7e6-29b9bb22eca4","added_by":"auto","created_at":"2024-11-07 14:56:34","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":100198,"visible":true,"origin":"","legend":"\u003cp\u003eThe forest plots for the MR result of potential associations.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5329671/v1/9ddb98cb74f65f6d10670826.png"},{"id":68470738,"identity":"c921b77e-a9e9-4986-b982-ce739e84739a","added_by":"auto","created_at":"2024-11-07 15:04:35","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":390787,"visible":true,"origin":"","legend":"\u003cp\u003eThe scatter plots for the MR result of potential associations.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5329671/v1/f276f5b2d71540b517fb7c1f.png"},{"id":68471880,"identity":"5489463c-967d-4f8c-98b9-024e2bcc9283","added_by":"auto","created_at":"2024-11-07 15:12:35","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":338006,"visible":true,"origin":"","legend":"\u003cp\u003eThe forest plots for the MR result of potential associations.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5329671/v1/34902c5b99e82228b5c285de.png"},{"id":69969698,"identity":"ccc92a5b-9222-46e2-8f1e-6204f0b86c55","added_by":"auto","created_at":"2024-11-27 06:02:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1396322,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5329671/v1/6385ee89-abd7-4239-abe0-9d557339f5ad.pdf"},{"id":68470737,"identity":"7c863fe5-c9b8-42d8-939a-ff8ea2541f39","added_by":"auto","created_at":"2024-11-07 15:04:34","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1009126,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-5329671/v1/73674499128be2cdf12934e9.xlsx"},{"id":68470314,"identity":"72da754d-2902-4aa2-b546-3ca213624217","added_by":"auto","created_at":"2024-11-07 14:56:35","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":7727590,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS1a.tif","url":"https://assets-eu.researchsquare.com/files/rs-5329671/v1/16003b16eb474d52ea155cc0.tif"},{"id":68470319,"identity":"2167aeaa-ef0a-4c15-98ec-9e4114e84a8a","added_by":"auto","created_at":"2024-11-07 14:56:35","extension":"tif","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":7727590,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS1b.tif","url":"https://assets-eu.researchsquare.com/files/rs-5329671/v1/f47ecd013ce82dd0f38232e0.tif"},{"id":68470318,"identity":"50398aa2-b9fd-44e3-8628-32c7ced9cb75","added_by":"auto","created_at":"2024-11-07 14:56:35","extension":"tif","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":6161298,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS1c.tif","url":"https://assets-eu.researchsquare.com/files/rs-5329671/v1/4fa195377919ed1a1abc6c3e.tif"},{"id":68470317,"identity":"85d69738-5729-4c59-ab2b-cdb56a23f119","added_by":"auto","created_at":"2024-11-07 14:56:35","extension":"tif","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":6161298,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS1d.tif","url":"https://assets-eu.researchsquare.com/files/rs-5329671/v1/3f26cea83ada601a0aa0b5f5.tif"},{"id":68470740,"identity":"4ab5577b-7f68-496e-bfb3-71a59d2a3b66","added_by":"auto","created_at":"2024-11-07 15:04:35","extension":"tif","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":6161298,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS1e.tif","url":"https://assets-eu.researchsquare.com/files/rs-5329671/v1/0e31ffc93d35313e479a1ddf.tif"}],"financialInterests":"No competing interests reported.","formattedTitle":"Sex-Stratified Mendelian Randomization Study on the Associations Between Dietary Habits and Colorectal Cancer Risk","fulltext":[{"header":"Introduction","content":"\u003cp\u003eColorectal cancer (CRC) is a major public health concern worldwide, ranking as one of the leading causes of cancer-related morbidity and mortality(Favoriti et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Xi \u0026amp; Xu, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Globally, CRC accounts for nearly 1.9\u0026nbsp;million new cases and over 900,000 deaths annually, making it the third most common cancer and the second leading cause of cancer deaths(Center, Jemal, Smith, \u0026amp; Ward, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Douaiher et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The burden of CRC is expected to increase significantly in the coming decades due to the aging population, lifestyle factors, and dietary habits, particularly in countries undergoing rapid urbanization and economic development(Salehiniya et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Despite advances in early detection, screening, and treatment, the survival rates for CRC vary considerably across different regions, with developed countries generally showing better outcomes due to organized screening programs. CRC is a multifactorial disease with both genetic predispositions and environmental factors, including diet and lifestyle, playing critical roles in its development. Numerous studies have demonstrated that modifiable risk factors such as obesity, physical inactivity, smoking, and, most notably, diet, can significantly influence CRC risk(Al-Sohaily, Biankin, Leong, Kohonen‐Corish, \u0026amp; Warusavitarne, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; de la Chapelle, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Thus, understanding the underlying risk factors and identifying potential preventive measures remain key areas of research in combating CRC. In particular, dietary habits have emerged as a crucial modifiable factor, with certain dietary patterns and specific food items either increasing or reducing CRC risk(Magalh\u0026atilde;es, Peleteiro, \u0026amp; Lunet, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Pietrzyk, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). As such, dietary interventions hold promise as a public health strategy for reducing the incidence of CRC.\u003c/p\u003e \u003cp\u003eDietary factors have long been recognized as important contributors to the risk of developing colorectal cancer(Nishi, Yoshida, Hirata, \u0026amp; Miyake, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). The traditional Western diet, characterized by high intakes of red and processed meats, refined grains, sugary beverages, and low fiber intake, has been strongly linked to an increased risk of CRC(Fung \u0026amp; Brown, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). In contrast, diets rich in fruits, vegetables, whole grains, and fish, such as the Mediterranean diet, have been associated with a reduced risk of CRC(R. F. Tayyem et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The consumption of fiber, antioxidants, vitamins, and other bioactive compounds in these foods is believed to exert protective effects against colorectal carcinogenesis by promoting gut health, reducing inflammation, and regulating cell proliferation and apoptosis(Reema F. Tayyem et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Specific food items and beverages have been the subject of much epidemiological and experimental research. For instance, red and processed meat intake has been classified as a probable carcinogen for CRC by the International Agency for Research on Cancer (IARC), largely due to the presence of carcinogenic compounds such as N-nitroso compounds and heterocyclic amines(Cascella et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Conversely, higher consumption of fiber-rich foods, particularly whole grains, has been consistently associated with a lower risk of CRC(X. He et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Furthermore, the intake of specific beverages, such as alcohol and sugary drinks, has also been implicated in CRC risk, with alcohol consumption being a well-established risk factor(Fardet, Druesne-Pecollo, Touvier, \u0026amp; Latino-Martel, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhile observational studies have provided valuable insights into the relationship between diet and CRC risk, they are often subject to confounding factors, reverse causality, and measurement errors inherent in dietary assessments. Mendelian randomization (MR) has emerged as a powerful tool to overcome these limitations by using genetic variants as instrumental variables (IVs) to assess the causal relationships between exposures, such as dietary habits, and disease outcomes. This approach minimizes bias from confounding and reverse causality, making it a valuable method for studying the causal impact of diet on CRC risk. Several MR studies have successfully identified causal associations between diet and CRC, although the focus has primarily been on single dietary factors rather than comprehensive dietary patterns(Deng, Wang, Huang, Ding, \u0026amp; Wong, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; M. He, Huan, Wang, Fan, \u0026amp; Huang, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this study, we employed a Mendelian randomization (MR) approach to investigate the causal relationships between 72 dietary habits and CRC risk, using a sex-stratified analysis. This study represents one of the Mendelian randomization investigations of dietary habits and CRC risk. By employing a robust methodological framework and examining a wide range of dietary exposures, our research aims to enhance the understanding of how diet contributes to CRC risk in a sex-specific context. The findings from this study may have important implications for personalized dietary recommendations and public health strategies aimed at reducing the global burden of colorectal cancer.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData source\u003c/h2\u003e \u003cp\u003eAll GWAS summary data used in this study were derived from male and female participants separately to ensure the accuracy of the analysis. The GWAS data for 72 dietary habits, including drinking water intake, low calorie drink intake, fizzy drink intake, orange juice intake, instant coffee intake, filtered coffee intake, intake of sugar added to coffee, standard tea intake, milk intake, and red wine intake, were obtained from the results of GWAS round 2 from Neale Lab. Detailed information, such as recruitment criteria of population and quality control of genetic data, can be found in the \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.nealelab.is/uk-biobank\u003c/span\u003e\u003cspan address=\"http://www.nealelab.is/uk-biobank\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. The imputed genotypes were from the HRC plus UK10K \u0026amp; 1000 Genomes reference panels as released by UK Biobank in March 2018. The UK Biobank is a large-scale biomedical database and research resource containing in-depth genetic and health information from half a million UK participants, designed to improve the prevention, diagnosis, and treatment of a wide range of serious and life-threatening illnesses. The details of the dietary habits dataset can be found in Supplementary Table\u0026nbsp;1.\u003c/p\u003e \u003cp\u003e The GWAS summary data for CRC were obtained from GWAS round 2 from Neale Lab (Cancer code, self-reported: large bowel cancer/colorectal cancer). The details of the CRC dataset can be found in Supplementary Table\u0026nbsp;2. These GWAS sample populations are predominantly of European descent. Although there is some overlap between the populations used in the exposure and outcome GWASs, specific Mendelian Randomization methods were applied to minimize the impact of this overlap on the results(Minelli et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The list of covariates varies between original GWASs, but always included sex and age. Details can be found in the original studies. The data analyzed in this secondary study is publicly available from existing, published GWASs and therefore the ethical approval and informed consent have been obtained by all original studies. This is a secondary analysis based on summary statistics from existing, published studies. The ethical approval and informed consent have been obtained by all original studies.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eGenetic instrumental variables (IVs) selection\u003c/h3\u003e\n\u003cp\u003eThe selection of instrumental variables (IVs) is crucial for ensuring the accuracy and robustness of causal inferences in Mendelian randomization analysis. IVs must satisfy three key assumptions: (1) the genetic variants must be associated with the exposures; (2) the genetic variants must not be related to confounders; and (3) the genetic variants should influence the outcomes only through the exposures, without affecting other pathways. This study adhered to specific criteria for selecting instrumental variables (IVs). Firstly, each SNP had to demonstrate a significant association with the 72 dietary habits, surpassing the genome-wide significance threshold of P\u0026thinsp;\u0026lt;\u0026thinsp;5E-6. Secondly, linkage disequilibrium (LD) was assessed using European sample data from the 1000 Genomes Project reference panel, retaining only the most significant SNPs among those with an R2\u0026thinsp;\u0026lt;\u0026thinsp;0.001 within a clumping window of 10,000 kb. Thirdly, SNPs with a minor allele frequency (MAF) of \u0026le;\u0026thinsp;0.01 were excluded to mitigate potential bias from genetic pleiotropy. The final set of SNPs meeting these criteria was employed as instrumental variables in the TSMR analysis.\u003c/p\u003e\n\u003ch3\u003eTwo-sample Mendelian randomization analysis\u003c/h3\u003e\n\u003cp\u003eOur study utilized MR to investigate the causal relationships between dietary habits and CRC. The analytical approach required comprehensive datasets for both exposures and outcomes, including SNP rsids, effect sizes (beta coefficients), alleles (effect and other), standard errors (SEs), effect allele frequencies (EAFs), and P-values. To avoid ambiguities caused by palindromic SNPs (SNPs with the same alleles on both DNA strands), we excluded such SNPs from the analysis. The MR analysis was conducted using five methods: Inverse Variance Weighted (multiplicative random effects), Weighted Median, Inverse Variance Weighted (IVW), Inverse Variance Weighted (fixed effects), and Weighted Mode. Among these, Inverse Variance Weighted (multiplicative random effects) served as the primary method for determining whether significant causal relationships exist between dietary habits and CRC. These methods were selected because, even in the presence of confounding factors, two-sample MR approaches\u0026mdash;including fixed-effect and (multiplicative) random-effects meta-analysis, weighted median estimator, and weighted mode estimator\u0026mdash;generally perform comparably to one-sample MR(Minelli et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, MR-Egger can introduce bias that reflects the direction and magnitude of confounding, and therefore was not the primary method used in this study. The list of covariates varies between original GWASs, but always included sex and age. Details can be found in the original studies. MR were performed using the \u0026ldquo;TwoSampleMR\u0026rdquo; (version 0.5.10) packages in R (version 4.3.3).\u003c/p\u003e\n\u003ch3\u003eSensitivity analysis\u003c/h3\u003e\n\u003cp\u003eHeterogeneity in this study refers to the variability in causal estimates across the different genetic variants used as instrumental variables, which can indicate potential inconsistencies in causal effects. We assessed heterogeneity using the MR Egger and Inverse Variance Weighted methods, considering dietary habits with a Q_pval\u0026thinsp;\u0026lt;\u0026thinsp;0.05 as indicative of heterogeneity. Pleiotropy, where a genetic variant influences multiple phenotypic traits and may confound causal estimates, was evaluated using the MR Egger method. Dietary habits with a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered to suggest pleiotropy. To evaluate the robustness and potential impact of individual variants, we employed the leave-one-out method, which involves iteratively removing one genetic variant at a time to assess its influence on the overall causal estimate. Visual representations of the MR analysis results were provided through scatter plots, forest plots, and leave-one-out plots.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eAccording to our IV selection strategy described previously, this study extracted a total of 1896 SNPs as instrumental variables for the 72 dietary habits, with the number of IVs per dietary habit ranging from 6 to 64 for male, and a total of 1909 SNPs as instrumental variables for the 72 dietary habits, with the number of IVs per dietary habit ranging from 9 to 116 for female. Subsequently, these SNPs and their proxies were extracted from datasets for the CRC. The details of all the IVs in the exposures and outcomes, including SNP rsids, effect sizes (beta coefficients), alleles (effect and other), standard errors (SEs), effect allele frequencies (EAFs), and P-values can be found in Supplementary Table\u0026nbsp;3.\u003c/p\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;1, The MR analysis results showed 3 positive associations in male and 2 positive associations in female before FDR correction. As shown in Fig.\u0026nbsp;2\u0026ndash;4, after FDR correction, significant associations were identified in males for average weekly fortified wine intake (OR (95% CI)\u0026thinsp;=\u0026thinsp;0.985 (0.979\u0026ndash;0.991), P\u0026thinsp;=\u0026thinsp;3.30E-07), sweet pepper intake (OR (95% CI)\u0026thinsp;=\u0026thinsp;0.996 (0.994\u0026ndash;0.998), P\u0026thinsp;=\u0026thinsp;6.56E-05), and bacon intake (OR (95% CI)\u0026thinsp;=\u0026thinsp;1.002 (1.001\u0026ndash;1.003), P\u0026thinsp;=\u0026thinsp;0.000417887). In females, symptoms and signs concerning food and fluid intake were significantly associated with CRC (OR (95% CI)\u0026thinsp;=\u0026thinsp;1.083 (1.046\u0026ndash;1.121), P\u0026thinsp;=\u0026thinsp;6.08E-06). All the MR results, including those from the five MR methods, can be found in Supplementary Table\u0026nbsp;4. For sensitivity analysis, no evidence of heterogeneity or pleiotropy was detected for this result (Supplementary Tables\u0026nbsp;5 and 6). As shown in Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e, the leave-one-out analysis indicated that the result was not significantly influenced by any single SNP.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we performed a comprehensive sex-stratified Mendelian randomization analysis to investigate the causal relationships between 72 dietary habits and the risk of colorectal cancer in both males and females. Using genetic variants significantly associated with dietary habits as instrumental variables, we applied five robust MR methods, including Inverse Variance Weighted (IVW) with multiplicative random effects, to estimate causal effects. Additionally, sensitivity analyses such as MR-Egger, leave-one-out, and heterogeneity tests were conducted to ensure the robustness of the findings. After applying false discovery rate correction, several dietary habits were identified as significantly associated with CRC risk. Notably, in males, we found significant associations between CRC risk and average weekly fortified wine intake, sweet pepper intake, and bacon intake, while in females, symptoms and signs concerning food and fluid intake were significantly linked to CRC risk. Importantly, no evidence of pleiotropy or heterogeneity was observed in the sensitivity analyses, further strengthening the credibility of our results. Our findings provide novel insights into the sex-specific dietary factors contributing to CRC risk and underscore the potential for personalized dietary recommendations in cancer prevention.\u003c/p\u003e \u003cp\u003eThe significant associations identified in males for average weekly fortified wine intake, sweet pepper intake, and bacon intake provide intriguing insights into the potential dietary factors influencing colorectal cancer risk. Each of these dietary habits has a unique set of characteristics that may contribute to cancer development, highlighting the complexity of diet-disease interactions and the importance of examining these relationships in a sex-specific context.\u003c/p\u003e \u003cp\u003eThe inverse association observed between average weekly fortified wine intake and CRC risk (OR\u0026thinsp;=\u0026thinsp;0.985, 95% CI\u0026thinsp;=\u0026thinsp;0.979\u0026ndash;0.991, P\u0026thinsp;=\u0026thinsp;3.30E-07) suggests that moderate consumption of fortified wine may have a protective effect against CRC in males. While alcohol consumption is generally considered a risk factor for many cancers, including CRC, the specific components of fortified wine\u0026mdash;such as polyphenols, antioxidants, and resveratrol\u0026mdash;may play a protective role in certain contexts. These compounds have been shown to exhibit anti-inflammatory and anti-proliferative properties, potentially counteracting some of the harmful effects of alcohol. However, the complex nature of alcohol-related risks and benefits means that further studies are necessary to confirm whether this association is truly protective or reflects other underlying lifestyle factors.\u003c/p\u003e \u003cp\u003eThe significant association between sweet pepper intake and a reduced risk of CRC in males (OR\u0026thinsp;=\u0026thinsp;0.996, 95% CI\u0026thinsp;=\u0026thinsp;0.994\u0026ndash;0.998, P\u0026thinsp;=\u0026thinsp;6.56E-05) adds to the growing body of evidence supporting the role of vegetables in cancer prevention. Sweet peppers are rich in vitamins, particularly vitamin C, as well as carotenoids, flavonoids, and other bioactive compounds known for their antioxidant and anti-inflammatory properties(Azlan, Sultana, Huei, \u0026amp; Razman, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; de S\u0026aacute; Mendes \u0026amp; Branco de Andrade Gon\u0026ccedil;alves, 2020). These nutrients may help neutralize free radicals, reduce oxidative stress, and inhibit inflammation, all of which are processes implicated in colorectal carcinogenesis. The protective effect observed in this study suggests that regular consumption of sweet peppers may contribute to a lower risk of CRC, especially in males, who may have different dietary needs or metabolic responses compared to females.\u003c/p\u003e \u003cp\u003eThe positive association between bacon intake and CRC risk (OR\u0026thinsp;=\u0026thinsp;1.002, 95% CI\u0026thinsp;=\u0026thinsp;1.001\u0026ndash;1.003, P\u0026thinsp;=\u0026thinsp;0.000417887) is consistent with the well-established link between processed meat consumption and colorectal cancer. Bacon, like other processed meats, contains nitrates and nitrites, which can form carcinogenic N-nitroso compounds when metabolized(Crowe, Elliott, \u0026amp; Green, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Deveci \u0026amp; Tek, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Additionally, the cooking process, particularly at high temperatures, can produce heterocyclic amines (HCAs) and polycyclic aromatic hydrocarbons (PAHs), both of which are known carcinogens(Edna Hee, Liang, Zhang, \u0026amp; Fang, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The slight increase in CRC risk associated with bacon intake in males reinforces existing dietary guidelines that recommend limiting the consumption of processed meats to reduce cancer risk. Interestingly, the magnitude of the effect in this study is relatively small (OR\u0026thinsp;=\u0026thinsp;1.002), suggesting that while bacon consumption is a risk factor, the overall contribution to CRC risk may depend on other factors such as quantity, frequency, and interaction with other dietary components.\u003c/p\u003e \u003cp\u003eThe significant association between symptoms and signs concerning food and fluid intake and an increased risk of colorectal cancer (CRC) in females (OR\u0026thinsp;=\u0026thinsp;1.083, 95% CI\u0026thinsp;=\u0026thinsp;1.046\u0026ndash;1.121, P\u0026thinsp;=\u0026thinsp;6.08E-06) highlights an intriguing, yet complex relationship between gastrointestinal health and cancer risk. This result suggests that females who exhibit symptoms or signs related to food and fluid intake\u0026mdash;such as digestive discomfort, irregular eating habits, or specific gastrointestinal issues\u0026mdash;may have a heightened risk of developing CRC. There are several potential mechanisms through which gastrointestinal symptoms and CRC risk may be linked. Symptoms concerning food and fluid intake could be indicative of underlying digestive system dysfunctions that, over time, contribute to colorectal carcinogenesis(Ahmad Kendong, Raja Ali, Nawawi, Ahmad, \u0026amp; Mokhtar, 2021; Larsen et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). For example, chronic gastrointestinal issues such as irritable bowel syndrome (IBS), dyspepsia, or frequent episodes of bloating and indigestion may lead to prolonged inflammation or disturbances in the gut microbiome, both of which are increasingly recognized as factors that can promote the development of CRC. Inflammation in the gut creates an environment conducive to the development of cancer by increasing cell turnover and promoting genetic mutations. Additionally, an imbalance in the gut microbiota, known as dysbiosis, has been linked to several gastrointestinal diseases, and emerging evidence suggests it may play a role in CRC by altering the local immune response and promoting pro-carcinogenic pathways.\u003c/p\u003e \u003cp\u003eSeveral limitations should be acknowledged. First, while MR is a powerful tool for assessing causal relationships and minimizing confounding and reverse causality, it relies on several key assumptions. One of the primary assumptions is that the instrumental variables (IVs) used\u0026mdash;genetic variants associated with dietary habits\u0026mdash;are only related to the outcome (CRC) through the exposure (dietary habits). However, the potential for horizontal pleiotropy, where genetic variants influence CRC through pathways other than dietary habits, cannot be entirely excluded. Although sensitivity analyses, including MR-Egger and leave-one-out tests, did not indicate substantial pleiotropy or heterogeneity, the presence of unmeasured pleiotropy may still bias the results. Second, the genetic instruments used for dietary habits were selected from genome-wide association studies (GWAS), which often rely on self-reported dietary data. Self-reported dietary intake is prone to measurement error and recall bias, which can affect the strength and accuracy of the associations between genetic variants and dietary habits. While the use of genetic instruments reduces the biases typically associated with observational studies, the precision of the MR estimates may still be limited by the quality of the dietary data used in the GWAS. Third, although we conducted sex-stratified analyses to explore potential differences in dietary associations with CRC between males and females, the power to detect significant associations might be constrained by sample size. Some dietary habits may have smaller or more nuanced effects on CRC risk that were not detected due to limited statistical power, particularly for habits with fewer available genetic instruments. Moreover, the generalizability of the findings may be limited to populations of European ancestry, as the majority of the GWAS data used to identify genetic instruments were derived from European cohorts. The associations observed in this study may differ in non-European populations due to differences in genetic background, dietary patterns, and CRC risk factors. Fourth, the dietary habits examined in this study were broad and included a wide range of food and beverage items. While this comprehensive approach is a strength, it also introduces complexity when interpreting the results. Some dietary habits, such as \u0026ldquo;symptoms and signs concerning food and fluid intake,\u0026rdquo; may encompass a variety of underlying behaviors or conditions that were not directly measured in this study. Therefore, the associations observed for these broader dietary categories may reflect a combination of factors, making it challenging to pinpoint the exact dietary components or behaviors driving the associations with CRC risk. Lastly, this study focused on CRC as a single outcome, without considering potential interactions between dietary habits and other lifestyle factors or comorbidities that may also influence cancer risk. For instance, smoking, physical activity, and alcohol consumption are known to interact with diet in shaping CRC risk, but these factors were not directly accounted for in the MR analysis. Future studies should consider examining these interactions and conducting stratified analyses based on other lifestyle factors to gain a more comprehensive understanding of the diet-CRC relationship.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis sex-stratified Mendelian randomization study offers robust evidence of the causal associations between specific dietary habits and colorectal cancer risk in both males and females. Our findings highlight significant associations between average weekly fortified wine intake, sweet pepper intake, and bacon intake with CRC risk in males, and symptoms and signs concerning food and fluid intake with CRC risk in females. These results emphasize the complexity of diet-disease interactions and suggest that dietary habits may have sex-specific effects on CRC development. This study underscores the importance of personalized dietary recommendations for CRC prevention and suggests that targeting specific dietary behaviors could play a crucial role in reducing CRC incidence. However, further research is needed to validate these findings in diverse populations and to explore the underlying biological mechanisms that link diet, sex, and CRC risk. Through such efforts, more effective, tailored public health strategies can be developed to mitigate the growing global burden of colorectal cancer.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eWe employed publicly available GWAS summary statistics data obtained from he Drug-Gene Interaction Database (DGIdb, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.dgidb.org/\u003c/span\u003e\u003c/span\u003e), FinnGen Consortium (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.finngen.fi/en\u003c/span\u003e\u003c/span\u003e), \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.finngen.fi/en\u003c/span\u003e\u003c/span\u003e), IEU GWAS (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gwas.mrcieu.ac.uk/\u003c/span\u003e\u003c/span\u003e), which collects data from studies conducted with appropriate informed consent protocols approved by institutional review boards. As a result, our study does not require a separate ethics statement.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eThe author approved the final manuscript and the submission to this journal.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe author declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis study was not supported by grants from the institutional funds.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eQ.L.Huang contributed to the study topic selection, data collection, statistics and analysis, first draft and final manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eWe would like to extend our thanks to the Drug-Gene Interaction Database (DGIdb, https://www.dgidb.org/), FinnGen Consortium (https://www.finngen.fi/en), IEU GWAS (https://gwas.mrcieu.ac.uk/) for granting public access to their summary data. Furthermore, we are grateful to the principal investigators of the studies for their transparency in sharing their data for research purposes.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe datasets generated and/or analysed during the current study are available in the Drug-Gene Interaction Database (DGIdb, https://www.dgidb.org/), FinnGen Consortium (https://www.finngen.fi/en), https://www.finngen.fi/en), IEU GWAS (https://gwas.mrcieu.ac.uk/).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAhmad Kendong SM, Ali R, Nawawi RA, Ahmad KNM, H. F., Mokhtar NM. Gut Dysbiosis and Intestinal Barrier Dysfunction: Potential Explanation for Early-Onset Colorectal Cancer. 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Translational Oncol. 2021;14(10). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.tranon.2021.101174\u003c/span\u003e\u003cspan address=\"10.1016/j.tranon.2021.101174\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\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":"Mendelian randomization, colorectal cancer, dietary habits, sex-stratified analysis, FDR correction, IVW, MR-Egger, sensitivity analysis","lastPublishedDoi":"10.21203/rs.3.rs-5329671/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5329671/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eColorectal cancer (CRC) remains a major global health challenge, with dietary habits being a key modifiable risk factor. Understanding the relationship between specific dietary habits and CRC can offer valuable insights for prevention. This study aimed to investigate the associations between 72 dietary habits and CRC risk using a sex-stratified Mendelian randomization (MR) approach.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe performed a sex-specific Mendelian randomization study in males and females to assess the causal associations between 72 dietary habits, including drinking water intake, low-calorie drink intake, fizzy drink intake, orange juice intake, and instant coffee intake, and CRC risk. Significant SNPs (P\u0026thinsp;\u0026lt;\u0026thinsp;5e-6) associated with dietary habits were selected as instrumental variables after clumping. Five MR methods were applied, including Inverse Variance Weighted (IVW) with multiplicative random effects. Sensitivity analyses using IVW, MR-Egger, and leave-one-out tests were conducted to assess pleiotropy and heterogeneity. Dietary habits that remained significant after FDR correction (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) were considered to have a significant association with CRC risk.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAfter FDR correction, significant associations were identified in males for average weekly fortified wine intake (OR (95% CI)\u0026thinsp;=\u0026thinsp;0.985 (0.979\u0026ndash;0.991), P\u0026thinsp;=\u0026thinsp;3.30E-07), sweet pepper intake (OR (95% CI)\u0026thinsp;=\u0026thinsp;0.996 (0.994\u0026ndash;0.998), P\u0026thinsp;=\u0026thinsp;6.56E-05), and bacon intake (OR (95% CI)\u0026thinsp;=\u0026thinsp;1.002 (1.001\u0026ndash;1.003), P\u0026thinsp;=\u0026thinsp;0.000417887). In females, symptoms and signs concerning food and fluid intake were significantly associated with CRC (OR (95% CI)\u0026thinsp;=\u0026thinsp;1.083 (1.046\u0026ndash;1.121), P\u0026thinsp;=\u0026thinsp;6.08E-06). No evidence of pleiotropy or heterogeneity was observed in the sensitivity analyses.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThis study provides robust evidence that several dietary habits are causally associated with CRC risk in a sex-specific manner. The findings emphasize the importance of personalized dietary recommendations for CRC prevention and highlight key dietary factors influencing CRC risk in both males and females.\u003c/p\u003e","manuscriptTitle":"Sex-Stratified Mendelian Randomization Study on the Associations Between Dietary Habits and Colorectal Cancer Risk","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-07 14:56:30","doi":"10.21203/rs.3.rs-5329671/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":"fbe1b629-5bfd-4d22-8386-d6cf9644b3d9","owner":[],"postedDate":"November 7th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-02-22T06:53:13+00:00","versionOfRecord":[],"versionCreatedAt":"2024-11-07 14:56:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5329671","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5329671","identity":"rs-5329671","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}