Palmieri Rachel T, Wilson Melanie A, Iversen Edwin S, Clyde Merlise A, Calingaert Brian, Moorman Patricia G, Poole Charles, Anderson A Rebecca, Anderson Stephanie, Anton-Culver Hoda, Beesley Jonathan, Hogdall Estrid, Brewster Wendy, Carney Michael E, Chen Xiaoqing, Chenevix-Trench Georgia, Chang-Claude Jenny, Cunningham Julie M, Dicioccio Richard A, Doherty Jennifer A, Easton Douglas F, Edlund Christopher K, Gayther Simon A, Gentry-Maharaj Aleksandra, Goode Ellen L, Goodman Marc T, Kjaer Susanne Kruger, Hogdall Claus K, Hopkins Michael P, Jenison Eric L, Blaakaer Jan, Lurie Galina, McGuire Valerie, Menon Usha, Moysich Kirsten B, Ness Roberta B, Pearce Celeste Leigh, Pharoah Paul D P, Pike Malcolm C, Ramus Susan J, Rossing Mary Anne, Song Honglin, Terada Keith Y, Vandenberg David, Vierkant Robert A, Wang-Gohrke Shan, Webb Penelope M, Whittemore Alice S, Wu Anna H, Ziogas Argyrios, Berchuck Andrew, Schildkraut Joellen M
Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Cancer Epidemiol Biomarkers Prev. 2008 Dec;17(12):3567-72. doi: 10.1158/1055-9965.EPI-08-0548.
Over 22,000 cases of ovarian cancer were diagnosed in 2007 in the United States, but only a fraction of them can be attributed to mutations in highly penetrant genes such as BRCA1. To determine whether low-penetrance genetic variants contribute to ovarian cancer risk, we genotyped 1,536 single nucleotide polymorphisms (SNP) in several candidate gene pathways in 848 epithelial ovarian cancer cases and 798 controls in the North Carolina Ovarian Cancer Study (NCO) using a customized Illumina array. The inflammation gene interleukin-18 (IL18) showed the strongest evidence for association with epithelial ovarian cancer in a gene-by-gene analysis (P = 0.002) with a <25% chance of being a false-positive finding (q value = 0.240). Using a multivariate model search algorithm over 11 IL18 tagging SNPs, we found that the association was best modeled by rs1834481. Further, this SNP uniquely tagged a significantly associated IL18 haplotype and there was an increased risk of epithelial ovarian cancer per rs1834481 allele (odds ratio, 1.24; 95% confidence interval, 1.06-1.45). In a replication stage, 12 independent studies from the Ovarian Cancer Association Consortium (OCAC) genotyped rs1834481 in an additional 5,877 cases and 7,791 controls. The fixed effects estimate per rs1834481 allele was null (odds ratio, 0.99; 95% confidence interval, 0.94-1.05) when data from the 12 OCAC studies were combined. The effect estimate remained unchanged with the addition of the initial North Carolina Ovarian Cancer Study data. This analysis shows the importance of consortia, like the OCAC, in either confirming or refuting the validity of putative findings in studies with smaller sample sizes. (Cancer Epidemiol Biomarkers Prev 2008;17(12):3567-72).
2007年，美国有超过22000例卵巢癌病例被确诊，但其中只有一小部分可归因于BRCA1等高外显率基因的突变。为了确定低外显率基因变异是否会增加患卵巢癌的风险，在北卡罗来纳卵巢癌研究（NCO）中，我们使用定制的Illumina芯片，对848例上皮性卵巢癌病例和798例对照的几个候选基因途径中的1536个单核苷酸多态性（SNP）进行了基因分型。在逐个基因分析中，炎症基因白细胞介素-18（IL18）显示出与上皮性卵巢癌关联的最有力证据（P = 0.002），假阳性发现的可能性小于25%（q值 = 0.240）。通过对11个IL18标签SNP使用多变量模型搜索算法，我们发现rs1834481对这种关联的建模效果最佳。此外，该SNP独特地标记了一个显著相关的IL18单倍型，并且每一个rs1834481等位基因都会增加上皮性卵巢癌的风险（优势比，1.24；95%置信区间，1.06 - 1.45）。在复制阶段，来自卵巢癌协会联盟（OCAC）的12项独立研究对另外5877例病例和7791例对照的rs1834481进行了基因分型。当合并这12项OCAC研究的数据时，每个rs1834481等位基因的固定效应估计值为无效（优势比，0.99；95%置信区间，0.94 - 1.05）。加入最初的北卡罗来纳卵巢癌研究数据后，效应估计值保持不变。该分析表明了像OCAC这样的联盟在确认或反驳样本量较小的研究中假定发现的有效性方面的重要性。（《癌症流行病学、生物标志物与预防》2008年；17(12):3567 - 72）
