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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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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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 & 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. The work is made available under the Creative Commons CC0 public domain dedication: https://creativecommons.org/publicdomain/zero/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c700t-64cf22bfcce3696459cf6df75b586a8669bcb2c3cc034a23ac5a6a7046fcbd8e3</citedby><cites>FETCH-LOGICAL-c700t-64cf22bfcce3696459cf6df75b586a8669bcb2c3cc034a23ac5a6a7046fcbd8e3</cites><orcidid>0000-0001-9263-8930 ; 0000-0002-4142-0613 ; 0000-0001-8118-9607 ; 0000-0003-3948-3372</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8055008/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8055008/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,550,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79343,79344</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33872305$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://gup.ub.gu.se/publication/308418$$DView record from Swedish Publication Index$$Hfree_for_read</backlink><backlink>$$Uhttps://lup.lub.lu.se/record/e23962eb-2be7-43a7-abe9-0f1590d89fe8$$DView record from Swedish Publication Index$$Hfree_for_read</backlink></links><search><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><title>The copy number variation and stroke (CaNVAS) risk and outcome study</title><title>PloS one</title><addtitle>PLoS One</addtitle><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.</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 & 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 Protocol</subject><subject>Veterans</subject><subject>Visualization</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><sourceid>D8T</sourceid><sourceid>DOA</sourceid><recordid>eNp1kl1v0zAUhiMEYmPwDxBE4mZctDj-9g1SVb4mVXDB4NaynZMuXRpndjLUf4_TZtOKhiIr1vH7Pj5-dbLsdYHmBRHFh40fQmuaeedbmCNMpVDFk-y0UATPOEbk6YP9SfYixg1CjEjOn2cnhEiBCWKn2afLK8id73Z5O2wthPzWhNr0tW9z05Z57IO_hvx8ab7_Xvx8n4c6Xu8P_NA7v4UkGMrdy-xZZZoIr6b_Wfbry-fL5bfZ6sfXi-ViNXMCoX7GqaswtpVzQLjilClX8bISzDLJTepMWWexI84hQg0mxjHDjUCUV86WEshZ9vbA7Rof9RRA1JgVDBFFKU6Ki4Oi9Gaju1BvTdhpb2q9L_iw1ib0tWtAIypBQOoEI05LiYx1FFIRldRRYVxirQ6s-Ae6wR7RmqFLy6alI2jARHEMVmMLQlNihDYWlEZVwRQqpapAJtzsv7h1wqXSek8jSNJi1H-cHjvYLZQO2j6Y5sh2fNLWV3rtb7VEjCE0As4nQPA3A8Reb-vooGlMC344xMalIkQk6bt_pI-HO6nWJuVXt5VP97oRqhecSSUxEeO180dU6SthW7s0rFWd6kcGejC44GMMUN2_sUB6HPW7ZvQ46noa9WR78zCfe9PdbJO_P4f6_w</recordid><startdate>20210419</startdate><enddate>20210419</enddate><creator>Cole, 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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 & 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 & Allied Health Database</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological & 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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identifier | ISSN: 1932-6203 |
ispartof | PloS one, 2021-04, Vol.16 (4), p.e0248791-e0248791 |
issn | 1932-6203 1932-6203 |
language | eng |
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source | Public Library of Science (PLoS) Journals Open Access; MEDLINE; DOAJ Directory of Open Access Journals; EZB-FREE-00999 freely available EZB journals; PubMed Central; SWEPUB Freely available online; Free Full-Text Journals in Chemistry |
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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