Veterans Affairs Maryland Health Care System, University of Maryland School of Medicine, Baltimore, MD, United States of America.
University of Ibadan, Ibadan, Nigeria.
PLoS One. 2021 Apr 19;16(4):e0248791. doi: 10.1371/journal.pone.0248791. eCollection 2021.
The role of copy number variation (CNV) variation in stroke susceptibility and outcome has yet to be explored. The Copy Number Variation and Stroke (CaNVAS) Risk and Outcome study addresses this knowledge gap.
Over 24,500 well-phenotyped IS cases, including IS subtypes, and over 43,500 controls have been identified, all with readily available genotyping on GWAS and exome arrays, with case measures of stroke outcome. To evaluate CNV-associated stroke risk and stroke outcome it is planned to: 1) perform Risk Discovery using several analytic approaches to identify CNVs that are associated with the risk of IS and its subtypes, across the age-, sex- and ethnicity-spectrums; 2) perform Risk Replication and Extension to determine whether the identified stroke-associated CNVs replicate in other ethnically diverse datasets and use biomarker data (e.g. methylation, proteomic, RNA, miRNA, etc.) to evaluate how the identified CNVs exert their effects on stroke risk, and lastly; 3) perform outcome-based Replication and Extension analyses of recent findings demonstrating an inverse relationship between CNV burden and stroke outcome at 3 months (mRS), and then determine the key CNV drivers responsible for these associations using existing biomarker data.
The results of an initial CNV evaluation of 50 samples from each participating dataset are presented demonstrating that the existing GWAS and exome chip data are excellent for the planned CNV analyses. Further, some samples will require additional considerations for analysis, however such samples can readily be identified, as demonstrated by a sample demonstrating clonal mosaicism.
The CaNVAS study will cost-effectively leverage the numerous advantages of using existing case-control data sets, exploring the relationships between CNV and IS and its subtypes, and outcome at 3 months, in both men and women, in those of African and European-Caucasian descent, this, across the entire adult-age spectrum.
拷贝数变异(CNV)在中风易感性和结局中的作用尚未得到探索。拷贝数变异与中风(CaNVAS)风险与结局研究旨在解决这一知识空白。
已确定超过 24500 例经过良好表型分析的 IS 病例,包括 IS 亚型,以及超过 43500 例对照,所有病例均具有 GWAS 和外显子组芯片上易于获得的基因分型,以及中风结局的病例测量值。为了评估与 CNV 相关的中风风险和中风结局,计划:1)使用几种分析方法进行风险发现,以识别与 IS 及其亚型的风险相关的 CNV,跨越年龄、性别和种族范围;2)进行风险复制和扩展,以确定在其他种族多样化数据集中是否复制了确定的与中风相关的 CNV,并使用生物标志物数据(例如甲基化、蛋白质组学、RNA、miRNA 等)来评估确定的 CNV 如何对中风风险产生影响,最后;3)进行基于结局的复制和扩展分析,以验证最近发现的结果,即 CNV 负担与 3 个月(mRS)的中风结局之间呈反比关系,然后使用现有的生物标志物数据确定负责这些关联的关键 CNV 驱动因素。
展示了对来自每个参与数据集的 50 个样本的初始 CNV 评估结果,证明现有的 GWAS 和外显子芯片数据非常适合计划的 CNV 分析。此外,对于某些样本,分析需要额外考虑,但是可以通过显示克隆嵌合体的样本很容易地识别出此类样本。
CaNVAS 研究将以具有成本效益的方式利用利用现有病例对照数据集的诸多优势,探索 CNV 与 IS 及其亚型以及 3 个月结局之间的关系,包括男性和女性、非洲和欧洲-高加索血统、整个成年年龄段。