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从对378142例病例和485715例对照进行的全表型孟德尔随机化分析中揭示了八种常见癌症的风险因素。

Risk factors for eight common cancers revealed from a phenome-wide Mendelian randomisation analysis of 378,142 cases and 485,715 controls.

作者信息

Went Molly, Sud Amit, Mills Charlie, Hyde Abi, Culliford Richard, Law Philip, Vijayakrishnan Jayaram, Gockel Ines, Maj Carlo, Schumacher Johannes, Palles Claire, Kaiser Martin, Houlston Richard

机构信息

Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK.

Haemato-oncology Unit, The Royal Marsden Hospital NHS Foundation Trust, Sutton, UK.

出版信息

Res Sq. 2023 Mar 17:rs.3.rs-2587058. doi: 10.21203/rs.3.rs-2587058/v1.

DOI:10.21203/rs.3.rs-2587058/v1
PMID:36993383
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10055507/
Abstract

For many cancers there are few well-established risk factors. Summary data from genome-wide association studies (GWAS) can be used in a Mendelian randomisation (MR) phenome-wide association study (PheWAS) to identify causal relationships. We performed a MR-PheWAS of breast, prostate, colorectal, lung, endometrial, oesophageal, renal, and ovarian cancers, comprising 378,142 cases and 485,715 controls. To derive a more comprehensive insight into disease aetiology we systematically mined the literature space for supporting evidence. We evaluated causal relationships for over 3,000 potential risk factors. In addition to identifying well-established risk factors (smoking, alcohol, obesity, lack of physical activity), we provide evidence for specific factors, including dietary intake, sex steroid hormones, plasma lipids and telomere length as determinants of cancer risk. We also implicate molecular factors including plasma levels of IL-18, LAG-3, IGF-1, CT-1, and PRDX1 as risk factors. Our analyses highlight the importance of risk factors that are common to many cancer types but also reveal aetiological differences. A number of the molecular factors we identify have the potential to be biomarkers. Our findings should aid public health prevention strategies to reduce cancer burden. We provide a R/Shiny app (https://mrcancer.shinyapps.io/mrcan/) to visualise findings.

摘要

对于许多癌症而言,已明确的风险因素寥寥无几。全基因组关联研究(GWAS)的汇总数据可用于孟德尔随机化(MR)全表型关联研究(PheWAS),以确定因果关系。我们对乳腺癌、前列腺癌、结直肠癌、肺癌、子宫内膜癌、食管癌、肾癌和卵巢癌进行了MR-PheWAS,涵盖378,142例病例和485,715例对照。为了更全面地洞察疾病病因,我们系统地在文献空间中挖掘支持证据。我们评估了3000多个潜在风险因素的因果关系。除了确定已明确的风险因素(吸烟、饮酒、肥胖、缺乏体育活动)外,我们还为特定因素提供了证据,包括饮食摄入、性类固醇激素、血脂和端粒长度作为癌症风险的决定因素。我们还指出分子因素,包括血浆中IL-18、LAG-3、IGF-1、CT-1和PRDX1的水平作为风险因素。我们的分析突出了许多癌症类型共有的风险因素的重要性,但也揭示了病因学差异。我们确定的一些分子因素有可能成为生物标志物。我们的研究结果应有助于公共卫生预防策略减轻癌症负担。我们提供了一个R/Shiny应用程序(https://mrcancer.shinyapps.io/mrcan/)来可视化研究结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a09c/10055507/63a3d39783b1/nihpp-rs2587058v1-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a09c/10055507/b3304de05e2f/nihpp-rs2587058v1-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a09c/10055507/189e13948771/nihpp-rs2587058v1-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a09c/10055507/742ceabeeb03/nihpp-rs2587058v1-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a09c/10055507/4ac5fe538d25/nihpp-rs2587058v1-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a09c/10055507/63a3d39783b1/nihpp-rs2587058v1-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a09c/10055507/b3304de05e2f/nihpp-rs2587058v1-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a09c/10055507/189e13948771/nihpp-rs2587058v1-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a09c/10055507/742ceabeeb03/nihpp-rs2587058v1-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a09c/10055507/4ac5fe538d25/nihpp-rs2587058v1-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a09c/10055507/63a3d39783b1/nihpp-rs2587058v1-f0005.jpg

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