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

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...

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Veröffentlicht in:PloS one 2021-04, Vol.16 (4), p.e0248791-e0248791
Hauptverfasser: Cole, John W, Adigun, Taiwo, Akinyemi, Rufus, Akpa, Onoja Matthew, Bell, Steven, Chen, Bowang, Jimenez Conde, Jordi, Lazcano Dobao, Uxue, Fernandez, Israel, Fornage, Myriam, Gallego-Fabrega, Cristina, Jern, Christina, Krawczak, Michael, Lindgren, Arne, Markus, Hugh S, Melander, Olle, Owolabi, Mayowa, Schlicht, Kristina, Söderholm, Martin, Srinivasasainagendra, Vinodh, Soriano Tárraga, Carolina, Stenman, Martin, Tiwari, Hemant, Corasaniti, Margaret, Fecteau, Natalie, Guizzardi, Beth, Lopez, Haley, Nguyen, Kevin, Gaynor, Brady, O'Connor, Timothy, Stine, O Colin, Kittner, Steven J, McArdle, Patrick, Mitchell, Braxton D, Xu, Huichun, Grond-Ginsbach, Caspar
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container_end_page e0248791
container_issue 4
container_start_page e0248791
container_title PloS one
container_volume 16
creator Cole, John W
Adigun, Taiwo
Akinyemi, Rufus
Akpa, Onoja Matthew
Bell, Steven
Chen, Bowang
Jimenez Conde, Jordi
Lazcano Dobao, Uxue
Fernandez, Israel
Fornage, Myriam
Gallego-Fabrega, Cristina
Jern, Christina
Krawczak, Michael
Lindgren, Arne
Markus, Hugh S
Melander, Olle
Owolabi, Mayowa
Schlicht, Kristina
Söderholm, Martin
Srinivasasainagendra, Vinodh
Soriano Tárraga, Carolina
Stenman, Martin
Tiwari, Hemant
Corasaniti, Margaret
Fecteau, Natalie
Guizzardi, Beth
Lopez, Haley
Nguyen, Kevin
Gaynor, Brady
O'Connor, Timothy
Stine, O Colin
Kittner, Steven J
McArdle, Patrick
Mitchell, Braxton D
Xu, Huichun
Grond-Ginsbach, Caspar
description 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.
doi_str_mv 10.1371/journal.pone.0248791
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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.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0248791</identifier><identifier>PMID: 33872305</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><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 &amp; 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</subject><ispartof>PloS one, 2021-04, Vol.16 (4), p.e0248791-e0248791</ispartof><rights>COPYRIGHT 2021 Public Library of Science</rights><rights>This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. 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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.</description><subject>Age</subject><subject>Arteriosclerosis</subject><subject>Atherosclerosis</subject><subject>Biology and Life Sciences</subject><subject>Cardiovascular diseases</subject><subject>Case-Control Studies</subject><subject>Cerebral infarction</subject><subject>Clinical Medicine</subject><subject>Computer programs</subject><subject>Copy number</subject><subject>Copy number variations</subject><subject>Data analysis</subject><subject>Databases, Genetic</subject><subject>DNA Copy Number Variations - genetics</subject><subject>Drafting software</subject><subject>Editing</subject><subject>Estimates</subject><subject>Ethnicity - genetics</subject><subject>Exome - genetics</subject><subject>Female</subject><subject>Funding</subject><subject>Genetic aspects</subject><subject>Genetic Predisposition to Disease - genetics</subject><subject>Genome-Wide Association Study - methods</subject><subject>Genomes</subject><subject>Genotype</subject><subject>Health aspects</subject><subject>Health care</subject><subject>Health risks</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Informatics</subject><subject>Ischemia</subject><subject>Klinisk medicin</subject><subject>Male</subject><subject>Medical and Health Sciences</subject><subject>Medical statistics</subject><subject>Medicin och hälsovetenskap</subject><subject>Medicine</subject><subject>Medicine and Health Sciences</subject><subject>Methodology</subject><subject>MicroRNAs - genetics</subject><subject>Myocardial infarction</subject><subject>Neurologi</subject><subject>Neurology</subject><subject>Outcome Assessment, Health Care - statistics &amp; numerical data</subject><subject>Patient outcomes</subject><subject>Phenotype</subject><subject>Phenotypes</subject><subject>Pilot Projects</subject><subject>Polymorphism, Single Nucleotide - genetics</subject><subject>Population structure</subject><subject>Proteomics - methods</subject><subject>Public health</subject><subject>Research and Analysis Methods</subject><subject>Reviews</subject><subject>Risk Factors</subject><subject>Software</subject><subject>Statistical analysis</subject><subject>Stroke</subject><subject>Stroke (Disease)</subject><subject>Stroke - genetics</subject><subject>Stroke - physiopathology</subject><subject>Study 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copy number variation and stroke (CaNVAS) risk and outcome study</title><author>Cole, John W ; Adigun, Taiwo ; Akinyemi, Rufus ; Akpa, Onoja Matthew ; Bell, Steven ; Chen, Bowang ; Jimenez Conde, Jordi ; Lazcano Dobao, Uxue ; Fernandez, Israel ; Fornage, Myriam ; Gallego-Fabrega, Cristina ; Jern, Christina ; Krawczak, Michael ; Lindgren, Arne ; Markus, Hugh S ; Melander, Olle ; Owolabi, Mayowa ; Schlicht, Kristina ; Söderholm, Martin ; Srinivasasainagendra, Vinodh ; Soriano Tárraga, Carolina ; Stenman, Martin ; Tiwari, Hemant ; Corasaniti, Margaret ; Fecteau, Natalie ; Guizzardi, Beth ; Lopez, Haley ; Nguyen, Kevin ; Gaynor, Brady ; O'Connor, Timothy ; Stine, O Colin ; Kittner, Steven J ; McArdle, Patrick ; Mitchell, Braxton D ; Xu, Huichun ; Grond-Ginsbach, Caspar</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c700t-64cf22bfcce3696459cf6df75b586a8669bcb2c3cc034a23ac5a6a7046fcbd8e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Age</topic><topic>Arteriosclerosis</topic><topic>Atherosclerosis</topic><topic>Biology and Life Sciences</topic><topic>Cardiovascular diseases</topic><topic>Case-Control Studies</topic><topic>Cerebral infarction</topic><topic>Clinical Medicine</topic><topic>Computer programs</topic><topic>Copy number</topic><topic>Copy number variations</topic><topic>Data analysis</topic><topic>Databases, Genetic</topic><topic>DNA Copy Number Variations - genetics</topic><topic>Drafting software</topic><topic>Editing</topic><topic>Estimates</topic><topic>Ethnicity - genetics</topic><topic>Exome - genetics</topic><topic>Female</topic><topic>Funding</topic><topic>Genetic aspects</topic><topic>Genetic Predisposition to Disease - genetics</topic><topic>Genome-Wide Association Study - methods</topic><topic>Genomes</topic><topic>Genotype</topic><topic>Health aspects</topic><topic>Health care</topic><topic>Health risks</topic><topic>Hospitals</topic><topic>Humans</topic><topic>Informatics</topic><topic>Ischemia</topic><topic>Klinisk medicin</topic><topic>Male</topic><topic>Medical and Health Sciences</topic><topic>Medical statistics</topic><topic>Medicin och hälsovetenskap</topic><topic>Medicine</topic><topic>Medicine and Health Sciences</topic><topic>Methodology</topic><topic>MicroRNAs - genetics</topic><topic>Myocardial infarction</topic><topic>Neurologi</topic><topic>Neurology</topic><topic>Outcome Assessment, Health Care - statistics &amp; numerical data</topic><topic>Patient outcomes</topic><topic>Phenotype</topic><topic>Phenotypes</topic><topic>Pilot Projects</topic><topic>Polymorphism, Single Nucleotide - genetics</topic><topic>Population structure</topic><topic>Proteomics - methods</topic><topic>Public health</topic><topic>Research and Analysis Methods</topic><topic>Reviews</topic><topic>Risk Factors</topic><topic>Software</topic><topic>Statistical analysis</topic><topic>Stroke</topic><topic>Stroke (Disease)</topic><topic>Stroke - genetics</topic><topic>Stroke - physiopathology</topic><topic>Study Protocol</topic><topic>Veterans</topic><topic>Visualization</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Cole, John W</creatorcontrib><creatorcontrib>Adigun, Taiwo</creatorcontrib><creatorcontrib>Akinyemi, Rufus</creatorcontrib><creatorcontrib>Akpa, Onoja Matthew</creatorcontrib><creatorcontrib>Bell, Steven</creatorcontrib><creatorcontrib>Chen, Bowang</creatorcontrib><creatorcontrib>Jimenez Conde, Jordi</creatorcontrib><creatorcontrib>Lazcano Dobao, Uxue</creatorcontrib><creatorcontrib>Fernandez, Israel</creatorcontrib><creatorcontrib>Fornage, Myriam</creatorcontrib><creatorcontrib>Gallego-Fabrega, Cristina</creatorcontrib><creatorcontrib>Jern, Christina</creatorcontrib><creatorcontrib>Krawczak, Michael</creatorcontrib><creatorcontrib>Lindgren, Arne</creatorcontrib><creatorcontrib>Markus, Hugh S</creatorcontrib><creatorcontrib>Melander, Olle</creatorcontrib><creatorcontrib>Owolabi, Mayowa</creatorcontrib><creatorcontrib>Schlicht, Kristina</creatorcontrib><creatorcontrib>Söderholm, Martin</creatorcontrib><creatorcontrib>Srinivasasainagendra, Vinodh</creatorcontrib><creatorcontrib>Soriano Tárraga, Carolina</creatorcontrib><creatorcontrib>Stenman, Martin</creatorcontrib><creatorcontrib>Tiwari, Hemant</creatorcontrib><creatorcontrib>Corasaniti, Margaret</creatorcontrib><creatorcontrib>Fecteau, Natalie</creatorcontrib><creatorcontrib>Guizzardi, Beth</creatorcontrib><creatorcontrib>Lopez, Haley</creatorcontrib><creatorcontrib>Nguyen, Kevin</creatorcontrib><creatorcontrib>Gaynor, Brady</creatorcontrib><creatorcontrib>O'Connor, Timothy</creatorcontrib><creatorcontrib>Stine, O Colin</creatorcontrib><creatorcontrib>Kittner, Steven J</creatorcontrib><creatorcontrib>McArdle, Patrick</creatorcontrib><creatorcontrib>Mitchell, Braxton D</creatorcontrib><creatorcontrib>Xu, Huichun</creatorcontrib><creatorcontrib>Grond-Ginsbach, Caspar</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing &amp; Allied Health Database</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological &amp; Geoastrophysical 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text</collection><collection>SWEPUB Freely available online</collection><collection>SWEPUB Lunds universitet</collection><collection>SwePub Articles full text</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Cole, John W</au><au>Adigun, Taiwo</au><au>Akinyemi, Rufus</au><au>Akpa, Onoja Matthew</au><au>Bell, Steven</au><au>Chen, Bowang</au><au>Jimenez Conde, Jordi</au><au>Lazcano Dobao, Uxue</au><au>Fernandez, Israel</au><au>Fornage, Myriam</au><au>Gallego-Fabrega, Cristina</au><au>Jern, Christina</au><au>Krawczak, Michael</au><au>Lindgren, Arne</au><au>Markus, Hugh S</au><au>Melander, Olle</au><au>Owolabi, Mayowa</au><au>Schlicht, Kristina</au><au>Söderholm, Martin</au><au>Srinivasasainagendra, Vinodh</au><au>Soriano Tárraga, Carolina</au><au>Stenman, Martin</au><au>Tiwari, Hemant</au><au>Corasaniti, Margaret</au><au>Fecteau, Natalie</au><au>Guizzardi, Beth</au><au>Lopez, Haley</au><au>Nguyen, Kevin</au><au>Gaynor, Brady</au><au>O'Connor, Timothy</au><au>Stine, O Colin</au><au>Kittner, Steven J</au><au>McArdle, Patrick</au><au>Mitchell, Braxton D</au><au>Xu, Huichun</au><au>Grond-Ginsbach, Caspar</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The copy number variation and stroke (CaNVAS) risk and outcome study</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2021-04-19</date><risdate>2021</risdate><volume>16</volume><issue>4</issue><spage>e0248791</spage><epage>e0248791</epage><pages>e0248791-e0248791</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>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.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>33872305</pmid><doi>10.1371/journal.pone.0248791</doi><orcidid>https://orcid.org/0000-0001-9263-8930</orcidid><orcidid>https://orcid.org/0000-0002-4142-0613</orcidid><orcidid>https://orcid.org/0000-0001-8118-9607</orcidid><orcidid>https://orcid.org/0000-0003-3948-3372</orcidid><oa>free_for_read</oa></addata></record>
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subjects 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
title The copy number variation and stroke (CaNVAS) risk and outcome study
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