Brauer M, Roth GA, Aravkin AY, Zheng P, Abate KH, Abate YH, et al. Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet. 2024;403:2162–203. https://doi.org/10.1016/S0140-6736(24)00933-4.
Brown KF, Rumgay H, Dunlop C, Ryan M, Quartly F, Cox A, et al. The fraction of cancer attributable to modifiable risk factors in England, Wales, Scotland, Northern Ireland, and the United Kingdom in 2015. Br J Cancer. 2018;118:1130–41. https://doi.org/10.1038/s41416-018-0029-6.
Article PubMed PubMed Central Google Scholar
Rogers CJ, Prabhu KS, Vijay-Kumar M. The microbiome and obesity—an established risk for certain types of cancer. Cancer J. 2014;20:176 https://doi.org/10.1097/PPO.0000000000000049.
Article PubMed CAS Google Scholar
Singh S, Sharma P, Sarma DK, Kumawat M, Tiwari R, Verma V, et al. Implication of obesity and gut microbiome dysbiosis in the etiology of colorectal cancer. Cancers. 2023;15:1913 https://doi.org/10.3390/cancers15061913.
Article PubMed PubMed Central CAS Google Scholar
Liu B-N, Liu X-T, Liang Z-H, Wang J-H. Gut microbiota in obesity. World J Gastroenterol. 2021;27:3837–50. https://doi.org/10.3748/wjg.v27.i25.3837.
Article PubMed PubMed Central CAS Google Scholar
Burgess S, Butterworth A, Thompson SG. Mendelian randomization analysis with multiple genetic variants using summarized data. Genet Epidemiol. 2013;37:658–65. https://doi.org/10.1002/gepi.21758.
Article PubMed PubMed Central Google Scholar
Yoshiji S, Butler-Laporte G, Lu T, Willett JDS, Su C-Y, Nakanishi T, et al. Proteome-wide Mendelian randomization implicates nephronectin as an actionable mediator of the effect of obesity on COVID-19 severity. Nat Metab. 2023;5:248–64. https://doi.org/10.1038/s42255-023-00742-w.
Article PubMed PubMed Central CAS Google Scholar
Yengo L, Sidorenko J, Kemper KE, Zheng Z, Wood AR, Weedon MN, et al. Meta-analysis of genome-wide association studies for height and body mass index in ∼700000 individuals of European ancestry. Hum Mol Genet. 2018;27:3641–9. https://doi.org/10.1093/hmg/ddy271.
Article PubMed PubMed Central CAS Google Scholar
Pulit SL, Stoneman C, Morris AP, Wood AR, Glastonbury CA, Tyrrell J, et al. Meta-analysis of genome-wide association studies for body fat distribution in 694 649 individuals of European ancestry. Hum Mol Genet. 2019;28:166–74. https://doi.org/10.1093/hmg/ddy327.
Article PubMed PubMed Central CAS Google Scholar
Purcell S, Chang C. PLINK 1.9. Available: www.cog-genomics.org/plink/1.9/.
Chang CC, Chow CC, Tellier LC, Vattikuti S, Purcell SM, Lee JJ. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience. 2015;4:s13742–015.
Hemani G, Zheng J, Elsworth B, Wade KH, Haberland V, Baird D, et al. The MR-Base platform supports systematic causal inference across the human phenome. eLife. 7:e34408. https://doi.org/10.7554/eLife.34408.
Hemani G, Tilling K, Smith GD. Orienting the causal relationship between imprecisely measured traits using GWAS summary data. PLOS Genet. 2017;13:e1007081 https://doi.org/10.1371/journal.pgen.1007081.
Article PubMed PubMed Central CAS Google Scholar
Bowden J, Del Greco M F, Minelli C, Davey Smith G, Sheehan N, Thompson J. A framework for the investigation of pleiotropy in two-sample summary data Mendelian randomization. Stat Med. 2017;36:1783–802. https://doi.org/10.1002/sim.7221.
Article PubMed PubMed Central Google Scholar
Bowden J, Davey Smith G, Burgess S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int J Epidemiol. 2015;44:512–25. https://doi.org/10.1093/ije/dyv080.
Article PubMed PubMed Central Google Scholar
Corbin LJ, Richmond RC, Wade KH, Burgess S, Bowden J, Smith GD, et al. BMI as a modifiable risk factor for Type 2 diabetes: refining and understanding causal estimates using Mendelian randomization. Diabetes. 2016;65:3002–7. https://doi.org/10.2337/db16-0418.
Article PubMed PubMed Central CAS Google Scholar
Burgess S, Small DS, Thompson SG. A review of instrumental variable estimators for Mendelian randomization. Stat Methods Med Res. 2017;26:2333–55. https://doi.org/10.1177/0962280215597579.
Pierce BL, Ahsan H, VanderWeele TJ. Power and instrument strength requirements for Mendelian randomization studies using multiple genetic variants. Int J Epidemiol. 2011;40:740–52. https://doi.org/10.1093/ije/dyq151.
Brion M-JA, Shakhbazov K, Visscher PM. Calculating statistical power in Mendelian randomization studies. Int J Epidemiol. 2013;42:1497–501. https://doi.org/10.1093/ije/dyt179.
Article PubMed PubMed Central Google Scholar
Kurilshikov A, Medina-Gomez C, Bacigalupe R, Radjabzadeh D, Wang J, Demirkan A, et al. Large-scale association analyses identify host factors influencing human gut microbiome composition. Nat Genet. 2021;53:156–65. https://doi.org/10.1038/s41588-020-00763-1.
Article PubMed PubMed Central CAS Google Scholar
Kurki MI, Karjalainen J, Palta P, Sipilä TP, Kristiansson K, Donner KM, et al. FinnGen provides genetic insights from a well-phenotyped isolated population. Nature. 2023;613:508–18. https://doi.org/10.1038/s41586-022-05473-8.
Article PubMed PubMed Central CAS Google Scholar
Burgess S, Daniel RM, Butterworth AS, Thompson SG. Network Mendelian randomization: using genetic variants as instrumental variables to investigate mediation in causal pathways. Int J Epidemiol. 2015;44:484–95. https://doi.org/10.1093/ije/dyu176.
Carter AR, Sanderson E, Hammerton G, Richmond RC, Davey Smith G, Heron J, et al. Mendelian randomisation for mediation analysis: current methods and challenges for implementation. Eur J Epidemiol. 2021;36:465–78. https://doi.org/10.1007/s10654-021-00757-1.
Article PubMed PubMed Central Google Scholar
World Cancer Research Fund/American Institute for Cancer Research. Continuous Update Project Expert Report 2018. Diet, nutrition, physical activity and colorectal cancer. Available: dietandcancerreport.org.
Cerezo M, Sollis E, Ji Y, Lewis E, Abid A, Bircan KO, et al. The NHGRI-EBI GWAS Catalog: standards for reusability, sustainability and diversity. Nucleic Acids Res. 2025;53:D998–D1005. https://doi.org/10.1093/nar/gkae1070.
Article PubMed PubMed Central CAS Google Scholar
Staiger D, Stock JH. Instrumental Variables Regression with Weak Instruments. Rochester, NY; 1994. Available: https://papers.ssrn.com/abstract=225111.
Bowden J, Davey Smith G, Haycock PC, Burgess S. Consistent estimation in Mendelian randomization with some invalid instruments using a weighted median estimator. Genet Epidemiol. 2016;40:304–14. https://doi.org/10.1002/gepi.21965.
Article PubMed PubMed Central Google Scholar
Yates T, Went M, Mills C, Law P, Gockel I, Maj C, et al. Mendelian randomisation analysis to discover plasma metabolites mediating the effect of obesity on cancer risk. Br J Cancer. 2025:1–10. https://doi.org/10.1038/s41416-025-03170-7.
Chen L, Zhernakova DV, Kurilshikov A, Andreu-Sánchez S, Wang D, Augustijn HE, et al. Influence of the microbiome, diet and genetics on inter-individual variation in the human plasma metabolome. Nat Med. 2022;28:2333–43. https://doi.org/10.1038/s41591-022-02014-8.
Article PubMed PubMed Central CAS Google Scholar
Sanna S, Kurilshikov A, van der Graaf A, Fu J, Zhernakova A. Challenges and future directions for studying effects of host genetics on the gut microbiome. Nat Genet. 2022;54:100–6. https://doi.org/10.1038/s41588-021-00983-z.
Article PubMed CAS Google Scholar
Sun J, Zhao J, Zhou S, Li X, Li T, Wang L, et al. Systematic investigation of genetically determined plasma and urinary metabolites to discover potential interventional targets for colorectal cancer. JNCI J Natl Cancer Inst. 2024:djae089. https://doi.org/10.1093/jnci/djae089.
Fernandez-Rozadilla C, Timofeeva M, Chen Z, Law P, Thomas M, Schmit S, et al. Deciphering colorectal cancer genetics through multi-omic analysis of 100,204 cases and 154,587 controls of European and East Asian ancestries. Nat Genet. 2023;55:89–99. https://doi.org/10.1038/s41588-022-01222-9.
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