Tayo Bamidele O, DiCioccio Richard A, Liang Yulan, Trevisan Maurizio, Cooper Richard S, Lele Shashikant, Sucheston Lara, Piver Steven M, Odunsi Kunle
Department of Preventive Medicine and Epidemiology, Loyola University Medical Center, Chicago, Illinois, United States of America.
PLoS One. 2009 Jun 17;4(6):e5939. doi: 10.1371/journal.pone.0005939.
Familial component is estimated to account for about 10% of ovarian cancer. However, the mode of inheritance of ovarian cancer remains poorly understood. The goal of this study was to investigate the inheritance model that best fits the observed transmission pattern of ovarian cancer among 7669 members of 1919 pedigrees ascertained through probands from the Gilda Radner Familial Ovarian Cancer Registry at Roswell Park Cancer Institute, Buffalo, New York.
METHODOLOGY/PRINCIPAL FINDINGS: Using the Statistical Analysis for Genetic Epidemiology program, we carried out complex segregation analyses of ovarian cancer affection status by fitting different genetic hypothesis-based regressive multivariate logistic models. We evaluated the likelihood of sporadic, major gene, environmental, general, and six types of Mendelian models. Under each hypothesized model, we also estimated the susceptibility allele frequency, transmission probabilities for the susceptibility allele, baseline susceptibility and estimates of familial association. Comparisons between models were carried out using either maximum likelihood ratio test in the case of hierarchical models, or Akaike information criterion for non-nested models. When assessed against sporadic model without familial association, the model with both parent-offspring and sib-sib residual association could not be rejected. Likewise, the Mendelian dominant model that included familial residual association provided the best-fitting for the inheritance of ovarian cancer. The estimated disease allele frequency in the dominant model was 0.21.
CONCLUSIONS/SIGNIFICANCE: This report provides support for a genetic role in susceptibility to ovarian cancer with a major autosomal dominant component. This model does not preclude the possibility of polygenic inheritance of combined effects of multiple low penetrance susceptibility alleles segregating dominantly.
据估计，家族因素约占卵巢癌病例的10%。然而，卵巢癌的遗传模式仍未得到充分了解。本研究的目的是调查最符合纽约州布法罗市罗斯韦尔帕克癌症研究所吉尔达·拉德纳家族性卵巢癌登记处通过先证者确定的1919个家系中7669名成员卵巢癌观察到的传递模式的遗传模型。
方法/主要发现：使用遗传流行病学统计分析程序，我们通过拟合不同的基于遗传假设的回归多变量逻辑模型，对卵巢癌患病状况进行了复杂的分离分析。我们评估了散发性、主基因、环境、一般以及六种孟德尔模型的可能性。在每个假设模型下，我们还估计了易感等位基因频率、易感等位基因的传递概率、基线易感性以及家族关联估计值。对于分层模型，使用最大似然比检验进行模型间比较；对于非嵌套模型，则使用赤池信息准则。与无家族关联的散发性模型相比，同时具有亲子和同胞残余关联的模型不能被拒绝。同样，包含家族残余关联的孟德尔显性模型最适合卵巢癌的遗传。显性模型中估计的疾病等位基因频率为0.21。
结论/意义：本报告支持遗传因素在卵巢癌易感性中起作用，且存在主要的常染色体显性成分。该模型并不排除多个低外显率易感等位基因显性分离产生联合效应的多基因遗传可能性。
