Center for Genetic Epidemiology and Prevention, Van Andel Research Institute, Grand Rapids, MI, USA.
Hum Genet. 2012 Jul;131(7):1225-34. doi: 10.1007/s00439-012-1148-4. Epub 2012 Feb 26.
Approximately 40 single nucleotide polymorphisms (SNPs) that are associated with prostate cancer (PCa) risk have been identified through genome-wide association studies (GWAS). However, these GWAS-identified PCa risk-associated SNPs can explain only a small proportion of heritability (~13%) of PCa risk. Gene-gene interaction is speculated to be one of the major factors contributing to the so-called missing heritability. To evaluate the gene-gene interaction and PCa risk, we performed a two-stage genome-wide gene-gene interaction scan using a novel statistical approach named "Boolean Operation-based Screening and Testing". In the first stage, we exhaustively evaluated all pairs of SNP-SNP interactions for ~500,000 SNPs in 1,176 PCa cases and 1,101 control subjects from the National Cancer Institute Cancer Genetic Markers of Susceptibility (CGEMS) study. No SNP-SNP interaction reached a genome-wide significant level of 4.4E-13. The second stage of the study involved evaluation of the top 1,325 pairs of SNP-SNP interactions (P(interaction) <1.0E-08) implicated in CGEMS in another GWAS population of 1,964 PCa cases from the Johns Hopkins Hospital (JHH) and 3,172 control subjects from the Illumina iControl database. Sixteen pairs of SNP-SNP interactions were significant in the JHH population at a P(interaction) cutoff of 0.01. However, none of the 16 pairs of SNP-SNP interactions were significant after adjusting for multiple tests. The current study represents one of the first attempts to explore the high-dimensional etiology of PCa on a genome-wide scale. Our results suggested a list of SNP-SNP interactions that can be followed in other replication studies.
通过全基因组关联研究(GWAS)已经确定了大约 40 个与前列腺癌(PCa)风险相关的单核苷酸多态性(SNP)。然而,这些通过 GWAS 确定的与 PCa 风险相关的 SNP 只能解释 PCa 风险遗传率的一小部分(~13%)。基因-基因相互作用被认为是导致所谓的遗传缺失的主要因素之一。为了评估基因-基因相互作用和 PCa 风险,我们使用一种名为“基于布尔运算的筛选和测试”的新统计方法进行了两阶段全基因组基因-基因相互作用扫描。在第一阶段,我们详尽地评估了 1176 例 PCa 病例和 1101 例对照来自国家癌症研究所癌症遗传易感性标记物(CGEMS)研究中的 50 万个 SNP 之间的所有 SNP-SNP 相互作用。没有 SNP-SNP 相互作用达到全基因组显著水平 4.4E-13。研究的第二阶段涉及评估在 CGEMS 中具有相关性的前 1325 对 SNP-SNP 相互作用(P(interaction)<1.0E-08)在另一个 GWAS 人群中的评估,该人群包括来自约翰霍普金斯医院(JHH)的 1964 例 PCa 病例和来自 Illumina iControl 数据库的 3172 例对照。在 JHH 人群中,有 16 对 SNP-SNP 相互作用在 P(interaction)截值为 0.01 时具有统计学意义。然而,在进行多次检验调整后,没有一对 SNP-SNP 相互作用具有统计学意义。本研究代表了首次尝试在全基因组范围内探索 PCa 的高维病因学的研究之一。我们的研究结果提供了一个可以在其他复制研究中进行跟踪的 SNP-SNP 相互作用列表。