Baker Stuart G, Lichtenstein Paul, Kaprio Jaakko, Holm Niels
Biometry Research Group, Division of Cancer Prevention, National Cancer Institute, EPN 3131, 6130 Executive Boulevard, MSC 7354, Bethesda, Maryland 20892-7354, USA.
Biometrics. 2005 Mar;61(1):55-63. doi: 10.1111/j.0006-341X.2005.030924.x.
To investigate the role of genetics in the development of cancer, we developed a new approach to analyze data on prostate, breast, and colorectal cancer from the Swedish, Danish, and Finnish twin registries on monozygotic (MZ) and same-sex dizygotic (DZ) twins. In the spirit of a sensitivity analysis, we modeled genetic inheritance as either an autosomal recessive or dominant cancer susceptibility (CS) genotype that involves either a single gene, many genes with equal allele frequencies, or three genes with a ninefold range of allele frequencies. We also modeled the joint probability of cancer incidence among five age categories, conditional on the presence or absence of the CS genotype. The main assumptions are: (1) The joint distribution of unobserved environmental effects in a twin pair conditional on the presence or absence of the CS genotype is the same for MZ and DZ twins, (2) the probability of cancer conditional on the presence or absence of the CS genotype and the unobserved environmental effects (i.e., the gene-environment interaction) is the same for MZ and DZ twins, and (3) the probability of cancer is independent between twins with the CS genotype. Estimation was maximum likelihood via a search over allele frequency and two levels of EM algorithms. Models had acceptable or good fits. Variability was estimated using a bootstrap approach, but only 50 replications were feasible. The 94th percentile of bootstrap replications for the estimated fraction of cancers with the CS genotype ranged, over the various genetic models, from 0.16 to 0.45 for prostate cancer, 0.12 to 0.30 for breast cancer, and 0.08 to 0.27 for colorectal cancer. We conclude that genetic susceptibility makes only a small to moderate contribution to the incidence of prostate, breast, and colorectal cancer.
为了研究遗传学在癌症发展中的作用,我们开发了一种新方法,用于分析来自瑞典、丹麦和芬兰双胞胎登记处的单卵(MZ)和同性双卵(DZ)双胞胎的前列腺癌、乳腺癌和结直肠癌数据。本着敏感性分析的精神,我们将遗传遗传建模为常染色体隐性或显性癌症易感性(CS)基因型,该基因型涉及单个基因、许多具有相等等位基因频率的基因,或三个具有九倍等位基因频率范围的基因。我们还对五个年龄组中癌症发病率的联合概率进行了建模,条件是CS基因型的存在与否。主要假设是:(1)在CS基因型存在或不存在的条件下,双胞胎对中未观察到的环境效应的联合分布对于MZ和DZ双胞胎是相同的;(2)在CS基因型存在或不存在以及未观察到的环境效应(即基因 - 环境相互作用)的条件下,MZ和DZ双胞胎患癌症的概率是相同的;(3)具有CS基因型的双胞胎之间患癌症的概率是独立的。通过对等位基因频率和两级期望最大化(EM)算法进行搜索,采用最大似然估计。模型拟合度可接受或良好。使用自助法估计变异性,但仅50次重复是可行的。在各种遗传模型中,CS基因型癌症估计比例的自助重复的第94百分位数,前列腺癌为0.16至0.45,乳腺癌为0.12至0.30,结直肠癌为0.08至0.27。我们得出结论,遗传易感性对前列腺癌、乳腺癌和结直肠癌发病率的贡献仅为小到中等程度。