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The Two Sister Study

The Two Sister Study
两姐妹研究
批准号:
8149105
负责人:
Clarice Weinberg
金额:
$11.21万
依托单位国家:
美国
项目类别:
财政年份:
--
资助国家:
美国
项目状态:
未结题
起止时间:
关键词:

项目摘要

项目成果

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中文摘要
翻译
这项由科曼资助的研究正在确定并向患有年轻乳腺癌的女性发出邀请函,并帮助她们的父母。我们将有效地将他们的数据与目前从他们未受影响的姐妹(已加入姐妹研究)收集的DNA和环境数据以及从他们的父母那里收集的DNA结合起来。我们将使用这种以核心家庭为基础的方法来研究年轻乳腺癌涉及的遗传和环境因素。这项研究通过利用姐妹研究(Dale Sandler,PI)已经到位并顺利运行的基础设施,获得了巨大的运营效率优势。邮寄唾液试剂盒正在提供病例和父母的DNA。我们将收集临床数据,并尝试验证所有预期的1600例病例的诊断。对这些病例的跟踪(通过Sister研究)还将使我们能够确定影响治疗后健康的环境、临床和遗传因素。 对基因变异的病例-亲本分析受到保护,不会因遗传遗传造成的混淆而产生偏见,还允许检测母体介导的遗传效应和亲本(印记)效应。在这项拟议的研究中,参与研究的受影响姐妹每个人都在完成一次计算机辅助电话采访,就像她们的姐妹为姐妹研究完成的那样,提供有关个人暴露、生育史和过去职业暴露的信息。环境影响将通过对受影响和未受影响的姐妹进行配对比较来确定。基因与暴露之间的相互作用将用新的统计方法进行评估。总而言之,这项拟议的研究利用正在进行的Sister研究来建立一项成本效益高、功能强大和统计学上独立的年轻乳腺癌研究。与遗传变异和环境因素的综合影响相关的发现可以在稍后的Sister研究中重复。 我们现在总共招募了1517名乳腺癌幸存者,其中1000多人已经完成了所有基线活动。大约有900人仍在等待,但我们需要在9月底结束乳腺癌幸存者姐妹的新登记。我们还招募了1292名他们的父母,从他们那里收集了1260份唾液样本。这项工作是在EB支助服务合同的协助下完成的。 我们聘请了博士后费春元,他将根据最初的数据集撰写论文,使用基于第一批1107名参与者的病例对照同胞集,这些参与者提供的问卷数据已经通过了严格的Westat质量控制清洗。这将为与风险有关的环境因素的病例对照分析提供良好的力量。基于可用DNA的基因分型被推迟,以便为招募父母参与研究提供时间。
英文摘要
This Komen-funded study is identifying and sending a letter of invitation to women with young-onset breast cancer and with their help to their parents. We will effectively combine their data with the DNA and environmental data now being collected from their unaffected sisters (who have joined the Sister Study) and DNA being collected from their parents. We will use this nuclear-family-based approach to study genetic and environmental factors involved in young-onset breast cancer. The study gains enormous operational efficiency advantages, by taking advantage of the infrastructure that is already in place and functioning smoothly for the Sister Study (Dale Sandler, PI). Mail-back saliva kits are providing DNA from cases and parents. We will collect clinical data and attempt to validate the diagnoses for all the anticipated 1,600 cases. Follow-up of these cases (through the Sister Study) will also allow us to identify environmental, clinical, and genetic factors that influence health after treatment. Case-parent analyses of gene variants are protected against bias due to confounding by genetic heritage, and also permit detection of both maternally-mediated genetic effects and parent-of-origin (imprinting) effects. In the proposed study, the participating affected sisters are each completing a computer-assisted telephone interview like the one their sister completed for the Sister Study, providing information about personal exposures, reproductive history, and past occupational exposures. Environmental effects will be identifiable through a paired comparison of affected and unaffected sisters. Gene-by-exposure interactions will be assessed with novel statistical methods. In summary, the proposed study leverages off the ongoing Sister Study to build a cost-effective, powerful, and statistically independent study of young-onset breast cancer. Findings related to combined effects of genetic variants and environmental factors can be replicated later in the Sister Study. We have now recruited a total of 1,517 breast cancer survivors, more than 1,000 of whom have completed all baseline activities. Some 900 are still pending, but we will need to end new enrollments of breast cancer survivor sisters at the end of September. We have also enrolled 1,292 of their parents, collecting 1,260 saliva samples from them. This work was accomplished with assistance from the EB support services contract. We have hired a postdoc, Chunyuan Fei, who will be writing papers based on the initial data set, using the case-control sibling sets based on the first 1,107 enrollees, who have provided questionnaire data that has been through the rigorous Westat quality control cleaning. This should provide good power for case-control analyses of environmental factors related to risk. Genotyping based on the available DNA is being deferred to provide time for recruitment of the parents into the study.
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Statistical Methods For Genetic Epidemiology
Statistical Methods In Epidemiology--general
The Two Sister Study
Statistical Methods For Genetic Epidemiology
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