Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK.
Cancer Genetics and Evolution Laboratory, Institute of Cancer and Genomic Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK; Department of Histopathology, University Hospitals Birmingham, Birmingham, UK.
Mol Aspects Med. 2019 Oct;69:41-47. doi: 10.1016/j.mam.2019.01.002. Epub 2019 Feb 4.
Colorectal cancer (CRC) is the third most common cancer in economically developed countries and a major cause of cancer-related mortality. The importance of lifestyle and diet as major determinants of CRC risk is suggested by differences in CRC incidence between countries and in migration studies. Previous observational epidemiological studies have identified associations between modifiable environmental risk factors and CRC, but these studies can be susceptible to reverse causation and confounding, and their results can therefore conflict. Mendelian randomisation (MR) analysis represents an approach complementary to conventional observational studies examining associations between exposures and disease. The MR strategy employs allelic variants as instrumental variables (IVs), which act as proxies for non-genetic exposures. These allelic variants are randomly assigned during meiosis and can therefore inform on life-long exposure, whilst not being subject to reverse causation. In previous studies MR frameworks have associated several modifiable factors with CRC risk, including adiposity, hyperlipidaemia, fatty acid profile and alcohol consumption. In this review we detail the use of MR to investigate and discover CRC risk factors, and its future applications.
结直肠癌(CRC)是经济发达国家中第三常见的癌症,也是癌症相关死亡的主要原因。生活方式和饮食作为 CRC 风险的主要决定因素的重要性,体现在国家之间 CRC 发病率的差异和移民研究中。先前的观察性流行病学研究已经确定了可改变的环境风险因素与 CRC 之间的关联,但这些研究可能容易受到反向因果关系和混杂因素的影响,因此其结果可能存在冲突。孟德尔随机化(MR)分析代表了一种与传统观察性研究互补的方法,用于研究暴露与疾病之间的关联。MR 策略使用等位基因变异作为工具变量(IVs),这些 IVs 可以作为非遗传暴露的替代物。这些等位基因变异在减数分裂过程中随机分配,因此可以提供终生暴露的信息,而不会受到反向因果关系的影响。在以前的研究中,MR 框架已经将几种可改变的因素与 CRC 风险相关联,包括肥胖、高脂血症、脂肪酸谱和饮酒。在这篇综述中,我们详细介绍了使用 MR 来研究和发现 CRC 风险因素及其未来的应用。