Your browser has javascript turned off or blocked. This will lead to some parts of our website to not work properly or at all. Turn on javascript for best performance.

The browser you are using is not supported by this website. All versions of Internet Explorer are no longer supported, either by us or Microsoft (read more here: https://www.microsoft.com/en-us/microsoft-365/windows/end-of-ie-support).

Please use a modern browser to fully experience our website, such as the newest versions of Edge, Chrome, Firefox or Safari etc.

Default user image.

Olle Melander

Principal investigator

Default user image.

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

Author

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

Summary, in English

Background and purpose 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. Methods 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. Results 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. Conclusion 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.

Department/s

  • Neurology, Lund
  • Clinical Stroke Research Group
  • EpiHealth: Epidemiology for Health
  • Cardiovascular Research - Epidemiology

Publishing year

2021

Language

English

Publication/Series

PLoS ONE

Volume

16

Issue

4 April

Document type

Journal article

Publisher

Public Library of Science

Topic

  • Neurology

Status

Published

Research group

  • Clinical Stroke Research Group
  • Cardiovascular Research - Epidemiology

ISBN/ISSN/Other

  • ISSN: 1932-6203