Confirmation of SNPs Associated with Aggressive PCa in a GWA Study
Confirmation of SNPs Associated with Aggressive PCa in a GWA Study
批准号:
8015277
负责人:
Jianfeng Xu
金额:
$56.53万
依托单位国家:
美国
项目类别:
财政年份:
2008
资助国家:
美国
项目状态:
已结题
起止时间:
2008-04-04 至 2014-01-31
关键词:
AffectCancer PatientCandidate Disease GeneCase-Control StudiesCharacteristicsDataDiagnosisDiseaseDisease AssociationDisease ProgressionDisease susceptibilityFrequenciesFundingGenesGeneticGenetic MarkersGenetic PolymorphismGenetic Predisposition to DiseaseGenomeGenomicsGenotypeGrantHospitalsInheritedJointsLeadLinkage DisequilibriumMalignant NeoplasmsMalignant neoplasm of prostateMapsMethodsNatureOncogenesPathway interactionsPhenotypePopulationPopulation StudyPreventionProbabilityRequest for ApplicationsResearch DesignResearch PersonnelRiskRoleSample SizeSingle Nucleotide PolymorphismStagingStratificationStructure of base of prostateStudy SubjectSwedenTestingTimeUniversitiesVariantWorkcancer genomecancer riskcase controldesigndisorder riskexperiencefollow-upforestgenetic associationgenome wide association studygenome-widegenotyping technologyimprovedmennovelnovel strategiespopulation basedsuccess
中文摘要
描述(申请人提供):标题:在一项GWA研究中证实与侵袭性前列腺癌相关的SNPs前列腺癌(PCA)的遗传易感性是公认的,也是所有常见癌症中最强的。许多基因中的遗传序列变异被认为共同构成了遗传易感性的基础,每个基因都具有中等风险。为了系统地识别这些风险变异,我们启动了一项雄心勃勃的全基因组关联(GWA)研究,其中包括瑞典和约翰霍普金斯医院的几个具有良好特征的大型研究人群,总计10,000例病例和对照。到目前为止,我们已经通过研究来自瑞典人群的500个攻击性病例和500个对照中的55万个SNPs,包括20K个非同义SNPs,完成了这个拟议的GWA的第一阶段。为了进一步提高识别中等风险SNPs的能力,我们建议进行一项研究,大幅增加GWA的样本量,并在独立研究人群中系统地跟踪大量SNPs。我们提出了四个具体的目标来检验这一假设,即基因组中的遗传序列变异可能会增加或修改PCA风险。目的1)作为第二阶段,我们将在另外800例侵袭性前列腺癌患者和800例瑞典对照中对500K SNPs和50K补充性SNPs子集进行基因分型。将在第一阶段和第二阶段进行受试者之间的联合关联分析,以选择SNPs进行进一步确认。目的2)作为第三阶段,我们将在来自约翰霍普金斯医院的另外2000例侵袭性PCa病例和1000例对照中检测~6500个SNP与PCa的相关性。将对所有可用的受试者中的这些SNPs进行联合分析,以确定达到全基因组显着水平的SNPs。目的3)对全基因组显著SNPs周围的基因组区域进行精细作图分析,以确定在3300例侵袭性PCa病例和2300例对照中与PCa风险最相关的变异。目的4)从瑞典全国范围内的局限性前列腺癌随访研究(FU研究)和来自约翰霍普金斯医院的500对进展者和非进展者配对的广泛随访信息中,评估5000例PCa风险变量与疾病进展的相关性。前列腺癌风险变量的识别可能会影响对这种疾病的理解、预防、诊断和治疗。
英文摘要
DESCRIPTION (provided by applicant): Title: Confirmation of SNPs Associated with Aggressive PCa in a GWA study A genetic predisposition to prostate cancer (PCa) is well established and is the strongest among all common cancers. Inherited sequence variants in a number of genes, each conferring a moderate risk, are believed to collectively underlie the genetic predisposition. To systematically identify these risk variants, we have initiated an ambitious genome-wide association (GWA) study that includes several large and well characterized study populations in Sweden and Johns Hopkins Hospital, totaling > 10,000 cases and controls. Thus far, we have completed the 1st stage of this proposed GWA by studying 550K SNPs, including 20K nonsynonymous SNPs, among 500 aggressive cases and 500 controls from a Swedish population (CAPS). To further improve the power of identifying moderate risk SNPs, we propose a study to considerably increase the sample size for a GWA and systematically follow-up a large number of SNPs among independent study populations. We propose four specific aims to test the hypothesis that inherited sequence variants in the genome may increase or modify PCa risk. Aim 1) As the 2nd stage, we will genotype 500K SNPs and a subset of 50K supplement SNPs among an additional 800 aggressive PCa cases and 800 controls from Sweden. A joint association analysis among subjects in stages 1 & 2 will be performed to select SNPs for further confirmation. Aim 2) As the 3rd stage, we will test for PCa associations for the ~6,500 SNPs among an additional 2,000 aggressive PCa cases and 1,000 controls from Johns Hopkins Hospital. A combined analysis will be performed for these SNPs among all available subjects to identify SNPs that reach genome-wide significance level. Aim 3) Perform a fine mapping analysis at genomic regions surrounding the genome-wide significant SNPs to identify variants that are most strongly associated with PCa risk among all 3,300 aggressive PCa cases and 2,300 controls. Aim 4) Assess association of the PCa risk variants with the disease progression among 5,000 cases with extensive follow-up information from a Swedish Nationwide Follow-Up study of Localized PCa (FU-study) and 500 matched-pairs of progressors and non-progressors from Johns Hopkins Hospital. The identification of PCa risk variants may impact the understanding, prevention, diagnosis, and treatment of this disease.
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Genome-wide association study in Chinese men identifies two new prostate cancer risk loci at 9q31.2 and 19q13.4.
中国男性全基因组关联研究确定了 9q31.2 和 19q13.4 两个新的前列腺癌风险位点
DOI:
10.1038/ng.2424
发表时间:
2012-11
期刊:
Nature genetics
影响因子:
30.8
作者:
[Xu J, Mo Z, Ye D, Wang M, Liu F, Jin G, Xu C, Wang X, Shao Q, Chen Z, Tao Z, Qi J, Zhou F, Wang Z, Fu Y, He D, Wei Q, Guo J, Wu D, Gao X, Yuan J, Wang G, Xu Y, Wang G, Yao H, Dong P, Jiao Y, Shen M, Yang J, Ou-Yang J, Jiang H, Zhu Y, Ren S, Zhang Z, Yin C, Gao X, Dai B, Hu Z, Yang Y, Wu Q, Chen H, Peng P, Zheng Y, Zheng X, Xiang Y, Long J, Gong J, Na R, Lin X, Yu H, Wang Z, Tao S, Feng J, Sun J, Liu W, Hsing A, Rao J, Ding Q, Wiklund F, Gronberg H, Shu XO, Zheng W, Shen H, Jin L, Shi R, Lu D, Zhang X, Sun J, Zheng SL, Sun Y]
通讯作者:
Sun Y
Predictive performance of prostate cancer risk in Chinese men using 33 reported prostate cancer risk-associated SNPs.
使用 33 个报告的前列腺癌风险相关 SNP 对中国男性的前列腺癌风险进行预测。
DOI:
10.1002/pros.21462
发表时间:
2012-04
期刊:
PROSTATE
影响因子:
2.8
作者:
[Zheng, Jie, Liu, Fang, Lin, Xiaoling, Wang, Xiang, Ding, Qiang, Jiang, Haowen, Chen, Hongyan, Lu, Daru, Jin, Guangfu, Hsing, Ann W., Shao, Qiang, Qi, Jun, Ye, Yu, Wang, Zhong, Gao, Xin, Wang, Guozeng, Chu, Lisa W., OuYang, Jun, Huang, Yichen, Chen, Yanbo, Gao, Yutang, Shi, Rong, Wu, Qijun, Wang, Meilin, Zhang, Zhengdong, Hu, Yanlin, Sun, Jielin, Zheng, S. Lilly, Gao, Xu, Xu, Chuanliang, Mo, Zengnan, Sun, Yinghao, Xu, Jianfeng]
通讯作者:
Xu, Jianfeng
DOI:
10.1007/s00439-012-1148-4
发表时间:
2012-07
期刊:
Human genetics
影响因子:
5.3
作者:
[Tao S, Feng J, Webster T, Jin G, Hsu FC, Chen SH, Kim ST, Wang Z, Zhang Z, Zheng SL, Isaacs WB, Xu J, Sun J]
通讯作者:
Sun J
DOI:
10.1002/pros.22661
发表时间:
2013-11
期刊:
PROSTATE
影响因子:
2.8
作者:
[Jiang, Haowen, Liu, Fang, Wang, Zhong, Na, Rong, Zhang, Limin, Wu, Yishuo, Zheng, Jie, Lin, Xiaoling, Jiang, Deke, Sun, Jielin, Zheng, S. Lilly, Ding, Qiang, Xu, Jianfeng]
通讯作者:
Xu, Jianfeng
Using graded response model for the prediction of prostate cancer risk.
使用分级反应模型预测前列腺癌风险。
DOI:
10.1007/s00439-012-1160-8
发表时间:
2012
期刊:
Human genetics
影响因子:
5.3
作者:
[Chen,Shyh-Huei, Ip,EdwardH, Xu,Jianfeng, Sun,Jielin, Hsu,Fang-Chi]
通讯作者:
Hsu,Fang-Chi
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