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author Giese, Anne-Katrin
Schirmer, Markus D.
Donahue, Kathleen L.
Cloonan, Lisa
Irie, Robert
Winzeck, Stefan
Bouts, Mark J.R.J.
McIntosh, Elissa C.
Mocking, Steven J.
Dalca, Adrian V.
Sridharan, Ramesh
Xu, Huichun
Frid, Petrea
Giralt-Steinhauer, Eva
Holmegaard, Lukas
Roquer, Jaume
Wasselius, Johan
Cole, John W.
McArdle, Patrick F.
Broderick, Joseph P.
Jimenez-Conde, Jordi
Jern, Christina
Kissela, Brett M.
Kleindorfer, Dawn O.
Lemmens, Robin
Lindgren, Arne
Meschia, James F.
Rundek, Tatjana
Sacco, Ralph L.
Schmidt, Reinhold
Sharma, Pankaj
Slowik, Agnieszka
Thijs, Vincent
Woo, Daniel
Worrall, Bradford B.
Kittner, Steven J.
Mitchell, Braxton D.
Rosand, Jonathan
Golland, Polina
Wu, Ona
Rost, Natalia S.
author_facet Giese, Anne-Katrin
Schirmer, Markus D.
Donahue, Kathleen L.
Cloonan, Lisa
Irie, Robert
Winzeck, Stefan
Bouts, Mark J.R.J.
McIntosh, Elissa C.
Mocking, Steven J.
Dalca, Adrian V.
Sridharan, Ramesh
Xu, Huichun
Frid, Petrea
Giralt-Steinhauer, Eva
Holmegaard, Lukas
Roquer, Jaume
Wasselius, Johan
Cole, John W.
McArdle, Patrick F.
Broderick, Joseph P.
Jimenez-Conde, Jordi
Jern, Christina
Kissela, Brett M.
Kleindorfer, Dawn O.
Lemmens, Robin
Lindgren, Arne
Meschia, James F.
Rundek, Tatjana
Sacco, Ralph L.
Schmidt, Reinhold
Sharma, Pankaj
Slowik, Agnieszka
Thijs, Vincent
Woo, Daniel
Worrall, Bradford B.
Kittner, Steven J.
Mitchell, Braxton D.
Rosand, Jonathan
Golland, Polina
Wu, Ona
Rost, Natalia S.
author_sort Giese, Anne-Katrin
collection PubMed
description OBJECTIVE: To describe the design and rationale for the genetic analysis of acute and chronic cerebrovascular neuroimaging phenotypes detected on clinical MRI in patients with acute ischemic stroke (AIS) within the scope of the MRI–GENetics Interface Exploration (MRI-GENIE) study. METHODS: MRI-GENIE capitalizes on the existing infrastructure of the Stroke Genetics Network (SiGN). In total, 12 international SiGN sites contributed MRIs of 3,301 patients with AIS. Detailed clinical phenotyping with the web-based Causative Classification of Stroke (CCS) system and genome-wide genotyping data were available for all participants. Neuroimaging analyses include the manual and automated assessments of established MRI markers. A high-throughput MRI analysis pipeline for the automated assessment of cerebrovascular lesions on clinical scans will be developed in a subset of scans for both acute and chronic lesions, validated against gold standard, and applied to all available scans. The extracted neuroimaging phenotypes will improve characterization of acute and chronic cerebrovascular lesions in ischemic stroke, including CCS subtypes, and their effect on functional outcomes after stroke. Moreover, genetic testing will uncover variants associated with acute and chronic MRI manifestations of cerebrovascular disease. CONCLUSIONS: The MRI-GENIE study aims to develop, validate, and distribute the MRI analysis platform for scans acquired as part of clinical care for patients with AIS, which will lead to (1) novel genetic discoveries in ischemic stroke, (2) strategies for personalized stroke risk assessment, and (3) personalized stroke outcome assessment.
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spelling pubmed-55706752017-08-29 Design and rationale for examining neuroimaging genetics in ischemic stroke: The MRI-GENIE study Giese, Anne-Katrin Schirmer, Markus D. Donahue, Kathleen L. Cloonan, Lisa Irie, Robert Winzeck, Stefan Bouts, Mark J.R.J. McIntosh, Elissa C. Mocking, Steven J. Dalca, Adrian V. Sridharan, Ramesh Xu, Huichun Frid, Petrea Giralt-Steinhauer, Eva Holmegaard, Lukas Roquer, Jaume Wasselius, Johan Cole, John W. McArdle, Patrick F. Broderick, Joseph P. Jimenez-Conde, Jordi Jern, Christina Kissela, Brett M. Kleindorfer, Dawn O. Lemmens, Robin Lindgren, Arne Meschia, James F. Rundek, Tatjana Sacco, Ralph L. Schmidt, Reinhold Sharma, Pankaj Slowik, Agnieszka Thijs, Vincent Woo, Daniel Worrall, Bradford B. Kittner, Steven J. Mitchell, Braxton D. Rosand, Jonathan Golland, Polina Wu, Ona Rost, Natalia S. Neurol Genet Article OBJECTIVE: To describe the design and rationale for the genetic analysis of acute and chronic cerebrovascular neuroimaging phenotypes detected on clinical MRI in patients with acute ischemic stroke (AIS) within the scope of the MRI–GENetics Interface Exploration (MRI-GENIE) study. METHODS: MRI-GENIE capitalizes on the existing infrastructure of the Stroke Genetics Network (SiGN). In total, 12 international SiGN sites contributed MRIs of 3,301 patients with AIS. Detailed clinical phenotyping with the web-based Causative Classification of Stroke (CCS) system and genome-wide genotyping data were available for all participants. Neuroimaging analyses include the manual and automated assessments of established MRI markers. A high-throughput MRI analysis pipeline for the automated assessment of cerebrovascular lesions on clinical scans will be developed in a subset of scans for both acute and chronic lesions, validated against gold standard, and applied to all available scans. The extracted neuroimaging phenotypes will improve characterization of acute and chronic cerebrovascular lesions in ischemic stroke, including CCS subtypes, and their effect on functional outcomes after stroke. Moreover, genetic testing will uncover variants associated with acute and chronic MRI manifestations of cerebrovascular disease. CONCLUSIONS: The MRI-GENIE study aims to develop, validate, and distribute the MRI analysis platform for scans acquired as part of clinical care for patients with AIS, which will lead to (1) novel genetic discoveries in ischemic stroke, (2) strategies for personalized stroke risk assessment, and (3) personalized stroke outcome assessment. Wolters Kluwer 2017-08-24 /pmc/articles/PMC5570675/ /pubmed/28852707 http://dx.doi.org/10.1212/NXG.0000000000000180 Text en Copyright © 2017 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (http://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits downloading and sharing the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.
spellingShingle Article
Giese, Anne-Katrin
Schirmer, Markus D.
Donahue, Kathleen L.
Cloonan, Lisa
Irie, Robert
Winzeck, Stefan
Bouts, Mark J.R.J.
McIntosh, Elissa C.
Mocking, Steven J.
Dalca, Adrian V.
Sridharan, Ramesh
Xu, Huichun
Frid, Petrea
Giralt-Steinhauer, Eva
Holmegaard, Lukas
Roquer, Jaume
Wasselius, Johan
Cole, John W.
McArdle, Patrick F.
Broderick, Joseph P.
Jimenez-Conde, Jordi
Jern, Christina
Kissela, Brett M.
Kleindorfer, Dawn O.
Lemmens, Robin
Lindgren, Arne
Meschia, James F.
Rundek, Tatjana
Sacco, Ralph L.
Schmidt, Reinhold
Sharma, Pankaj
Slowik, Agnieszka
Thijs, Vincent
Woo, Daniel
Worrall, Bradford B.
Kittner, Steven J.
Mitchell, Braxton D.
Rosand, Jonathan
Golland, Polina
Wu, Ona
Rost, Natalia S.
Design and rationale for examining neuroimaging genetics in ischemic stroke: The MRI-GENIE study
title Design and rationale for examining neuroimaging genetics in ischemic stroke: The MRI-GENIE study
title_full Design and rationale for examining neuroimaging genetics in ischemic stroke: The MRI-GENIE study
title_fullStr Design and rationale for examining neuroimaging genetics in ischemic stroke: The MRI-GENIE study
title_full_unstemmed Design and rationale for examining neuroimaging genetics in ischemic stroke: The MRI-GENIE study
title_short Design and rationale for examining neuroimaging genetics in ischemic stroke: The MRI-GENIE study
title_sort design and rationale for examining neuroimaging genetics in ischemic stroke: the mri-genie study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5570675/
https://www.ncbi.nlm.nih.gov/pubmed/28852707
http://dx.doi.org/10.1212/NXG.0000000000000180
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