Journal Article

The copy number variation and stroke (CaNVAS) risk and outcome study

Schlicht, Kristina, Lazcano Dobao, Uxue, Jern, Christina, McArdle, Patrick, Stenman, Martin, Mitchell, Braxton D., O’Connor, Timothy, Jimenez Conde, Jordi, Fornage, Myriam, Guizzardi, Beth, Fernandez, Israel, Xu, Huichun, Grond-Ginsbach, Caspar, Soriano Tárraga, Carolina, Tiwari, Hemant, Melander, Olle, Fecteau, Natalie, Cole, John W., Akinyemi, Rufus, Lindgren, Arne, Adigun, Taiwo, Bell, Steven, Corasaniti, Margaret, Chen, Bowang, Gaynor, Brady, Nguyen, Kevin, Söderholm, Martin, Kittner, Steven J., Krawczak, Michael, Srinivasasainagendra, Vinodh, Stine, O. Colin, Akpa, Onoja Matthew, Gallego-Fabrega, Cristina, Lopez, Haley, Owolabi, Mayowa, Markus, Hugh S.

2021

Overview

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.

• Publisher: Public Library of Science,Public Library of Science (PLoS)
• Subject: Age / Arteriosclerosis / Atherosclerosis / Biology and Life Sciences / Cardiovascular diseases / Case-Control Studies / Cerebral infarction / Clinical Medicine / Computer programs / Copy number / Copy number variations / Data analysis / Databases, Genetic / DNA Copy Number Variations - genetics / Drafting software / Editing / Estimates / Ethnicity - genetics / Exome - genetics / Female / Funding / Genetic aspects / Genetic Predisposition to Disease - genetics / Genome-Wide Association Study - methods / Genomes / Genotype / Health aspects / Health care / Health risks / Hospitals / Humans / Informatics / Ischemia / Klinisk medicin / Male / Medical and Health Sciences / Medical statistics / Medicin och hälsovetenskap / Medicine / Medicine and Health Sciences / Methodology / MicroRNAs - genetics / Myocardial infarction / Neurologi / Neurology / Outcome Assessment, Health Care - statistics & numerical data / Patient outcomes / Phenotype / Phenotypes / Pilot Projects / Polymorphism, Single Nucleotide - genetics / Population structure / Proteomics - methods / Public health / Research and Analysis Methods / Reviews / Risk Factors / Software / Statistical analysis / Stroke / Stroke (Disease) / Stroke - genetics / Stroke - physiopathology / Study Protocol / Veterans / Visualization