Han Ying, Hazelett Dennis J, Wiklund Fredrik, Schumacher Fredrick R, Stram Daniel O, Berndt Sonja I, Wang Zhaoming, Rand Kristin A, Hoover Robert N, Machiela Mitchell J, Yeager Merideth, Burdette Laurie, Chung Charles C, Hutchinson Amy, Yu Kai, Xu Jianfeng, Travis Ruth C, Key Timothy J, Siddiq Afshan, Canzian Federico, Takahashi Atsushi, Kubo Michiaki, Stanford Janet L, Kolb Suzanne, Gapstur Susan M, Diver W Ryan, Stevens Victoria L, Strom Sara S, Pettaway Curtis A, Al Olama Ali Amin, Kote-Jarai Zsofia, Eeles Rosalind A, Yeboah Edward D, Tettey Yao, Biritwum Richard B, Adjei Andrew A, Tay Evelyn, Truelove Ann, Niwa Shelley, Chokkalingam Anand P, Isaacs William B, Chen Constance, Lindstrom Sara, Le Marchand Loic, Giovannucci Edward L, Pomerantz Mark, Long Henry, Li Fugen, Ma Jing, Stampfer Meir, John Esther M, Ingles Sue A, Kittles Rick A, Murphy Adam B, Blot William J, Signorello Lisa B, Zheng Wei, Albanes Demetrius, Virtamo Jarmo, Weinstein Stephanie, Nemesure Barbara, Carpten John, Leske M Cristina, Wu Suh-Yuh, Hennis Anselm J M, Rybicki Benjamin A, Neslund-Dudas Christine, Hsing Ann W, Chu Lisa, Goodman Phyllis J, Klein Eric A, Zheng S Lilly, Witte John S, Casey Graham, Riboli Elio, Li Qiyuan, Freedman Matthew L, Hunter David J, Gronberg Henrik, Cook Michael B, Nakagawa Hidewaki, Kraft Peter, Chanock Stephen J, Easton Douglas F, Henderson Brian E, Coetzee Gerhard A, Conti David V, Haiman Christopher A
Department of Preventive Medicine, Keck School of Medicine.
Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden.
Hum Mol Genet. 2015 Oct 1;24(19):5603-18. doi: 10.1093/hmg/ddv269. Epub 2015 Jul 10.
Interpretation of biological mechanisms underlying genetic risk associations for prostate cancer is complicated by the relatively large number of risk variants (n = 100) and the thousands of surrogate SNPs in linkage disequilibrium. Here, we combined three distinct approaches: multiethnic fine-mapping, putative functional annotation (based upon epigenetic data and genome-encoded features), and expression quantitative trait loci (eQTL) analyses, in an attempt to reduce this complexity. We examined 67 risk regions using genotyping and imputation-based fine-mapping in populations of European (cases/controls: 8600/6946), African (cases/controls: 5327/5136), Japanese (cases/controls: 2563/4391) and Latino (cases/controls: 1034/1046) ancestry. Markers at 55 regions passed a region-specific significance threshold (P-value cutoff range: 3.9 × 10(-4)-5.6 × 10(-3)) and in 30 regions we identified markers that were more significantly associated with risk than the previously reported variants in the multiethnic sample. Novel secondary signals (P < 5.0 × 10(-6)) were also detected in two regions (rs13062436/3q21 and rs17181170/3p12). Among 666 variants in the 55 regions with P-values within one order of magnitude of the most-associated marker, 193 variants (29%) in 48 regions overlapped with epigenetic or other putative functional marks. In 11 of the 55 regions, cis-eQTLs were detected with nearby genes. For 12 of the 55 regions (22%), the most significant region-specific, prostate-cancer associated variant represented the strongest candidate functional variant based on our annotations; the number of regions increased to 20 (36%) and 27 (49%) when examining the 2 and 3 most significantly associated variants in each region, respectively. These results have prioritized subsets of candidate variants for downstream functional evaluation.
前列腺癌遗传风险关联背后生物学机制的解读因相对大量的风险变异(n = 100)以及处于连锁不平衡状态的数千个替代单核苷酸多态性(SNP)而变得复杂。在此,我们结合了三种不同方法:多民族精细定位、基于表观遗传数据和基因组编码特征的假定功能注释以及表达定量性状位点(eQTL)分析,试图降低这种复杂性。我们在欧洲(病例/对照:8600/6946)、非洲(病例/对照:5327/5136)、日本(病例/对照:2563/4391)和拉丁裔(病例/对照:1034/1046)人群中,使用基因分型和基于推测的精细定位对67个风险区域进行了研究。55个区域的标记通过了区域特异性显著性阈值(P值截断范围:3.9×10⁻⁴ - 5.6×10⁻³),并且在30个区域中,我们鉴定出在多民族样本中比先前报道的变异与风险关联更显著的标记。在两个区域(rs13062436/3q21和rs17181170/3p12)还检测到了新的次要信号(P < 5.0×10⁻⁶)。在55个区域中P值与最相关标记相差一个数量级以内的666个变异中,48个区域的193个变异(29%)与表观遗传或其他假定功能标记重叠。在55个区域中的11个区域检测到了与附近基因的顺式eQTL。对于55个区域中的12个区域(22%),基于我们的注释,最显著的区域特异性前列腺癌相关变异代表最强的候选功能变异;当分别检查每个区域中2个和3个最显著相关的变异时,区域数量分别增加到20个(36%)和27个(49%)。这些结果为下游功能评估确定了候选变异的子集优先级。