five

The Siblings With Ischemic Stroke Study (SWISS) Protocol

收藏
PubMed Central2002-02-12 更新2026-05-16 收录
下载链接:
https://pmc.ncbi.nlm.nih.gov/articles/PMC79001/
下载链接
链接失效反馈
官方服务:
资源简介:
BACKGROUND: Family history and twins studies suggest an inherited component to ischemic stroke risk. Candidate gene association studies have been performed but have limited capacity to identify novel risk factor genes. The Siblings With Ischemic Stroke Study (SWISS) aims to conduct a genome-wide scan in sibling pairs concordant or discordant for ischemic stroke to identify novel genetic risk factors through linkage analysis. METHODS: Screening at multiple clinical centers identifies patients (probands) with radiographically confirmed ischemic stroke and a family history of at least 1 living full sibling with stroke. After giving informed consent, without violating privacy among other family members, the proband invites siblings concordant and discordant for stroke to participate. Siblings then contact the study coordinating center. The diagnosis of ischemic stroke in potentially concordant siblings is confirmed by systematic centralized review of medical records. The stroke-free status of potentially discordant siblings is confirmed by validated structured telephone interview. Blood samples for DNA analysis are taken from concordant sibling pairs and, if applicable, from 1 discordant sibling. Epstein-Barr virus-transformed lymphoblastoid cell lines are created, and a scan of the human genome is planned. DISCUSSION: Conducting adequately powered genomics studies of stroke in humans is challenging because of the heterogeneity of the stroke phenotype and the difficulty of obtaining DNA samples from clinically well-characterized members of a cohort of stroke pedigrees. The multicentered design of this study is intended to efficiently assemble a cohort of ischemic stroke pedigrees without invoking community consent or using cold-calling of pedigree members.
提供机构:
BMC
创建时间:
2002-02-12
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作