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中文摘要
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描述(申请人提供):“将叶酸的中间生物标记物与结直肠癌结合起来”这项建议的目标是测量中间生物标记物,并用旨在阐明结直肠癌潜在病因机制的统计方法对其进行评估。该提案利用了结肠癌家族登记处(Colon CFR)内进行的现有研究的基因数据。结肠癌家族登记处(Colon CFR)是一个由NCI支持的财团,成立于1997年,致力于建立一个全面的协作基础设施,用于结直肠癌遗传学和遗传流行病学的跨学科研究。受试者包括在FOCM途径基因候选基因研究(RO1CA112237)中分型的1,531个对照,以及在结肠CFR病例全基因组关联研究(U01CA122839)中分型的999个对照。在这些受试者中,我们将评估一个碳代谢中的血浆指标(血浆叶酸、维生素B2、B6、B12、蛋氨酸、甲基丙二酸、肌酐、血浆总同型半胱氨酸(THcy)和循环淋巴细胞DNA甲基化(PBL))。此外,我们在以前工作的基础上开发了统计方法,用于在假定的疾病途径中建立遗传关联的模型。这些模型整合了不同级别的数据,如基因类型、基因表达、生物标记物和外源暴露,以及先前的信息,以建立更全面的统计模型,以便更好地确定遗传效应的优先顺序、估计和表征。
英文摘要
DESCRIPTION (provided by applicant): "Incorporating intermediate biomarkers of folate with colorectal cancer" The goal of this proposal is to measure intermediate biomarkers and to evaluate these with statistical methods designed to elucidate the underlying etiologic mechanism of colorectal cancer. The proposal leverages existing genetic data from studies conducted within the Colon Cancer Family Registry (Colon CFR), an NCI-supported consortium initiated in 1997 and dedicated to the establishment of a comprehensive collaborative infrastructure for interdisciplinary studies in the genetics and genetic epidemiology of colorectal cancer. The subjects include 1,531 controls genotyped in a candidate gene study of FOCM pathway genes (RO1CA112237), and 999 controls genotyped in a genome wide association study of colon CFR cases (U01CA122839). In these subjects, we will evaluate plasma measures within one carbon metabolism (plasma folate, vitamins B2, B6, B12, methionine, methyl malonic acid, creatinine, plasma total Hcy (tHcy), and DNA methylation in circulating lymphocytes (PBL)). In addition, we build upon our previous work in developing statistical methods for modeling genetic associations in putative disease pathways. These models integrate various levels of data, e.g. genotypes, gene expression, biomarkers, and exogenous exposures, with prior information to build more comprehensive statistical models for better prioritization, estimation, and characterization of genetic effects.
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Multiethnic GWAS and TWAS to Inform Risk Prediction for Prostate Cancer
Leveraging Diversity in Cancer Epidemiology Cohorts and Novel Methods to Improve Polygenic Risk Scores
Multiethnic GWAS and TWAS to Inform Risk Prediction for Prostate Cancer
Leveraging Diversity in Cancer Epidemiology Cohorts and Novel Methods to Improve Polygenic Risk Scores
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