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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. and Dalca, Adrian V. , et al. (2017) In Neurology: Genetics 3(5).
Abstract

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 contributedMRIs 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 themanual and automated assessments of established MRI markers. A high-throughputMRI... (More)

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 contributedMRIs 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 themanual and automated assessments of established MRI markers. A high-throughputMRI 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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organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Neurology: Genetics
volume
3
issue
5
article number
e180
publisher
Lippincott Williams & Wilkins
external identifiers
  • scopus:85052666132
  • pmid:28852707
ISSN
2376-7839
DOI
10.1212/NXG.0000000000000180
language
English
LU publication?
yes
id
6c8b5eaf-dceb-48d6-b084-bebfddbf1220
date added to LUP
2018-10-19 11:07:34
date last changed
2024-11-26 14:21:13
@article{6c8b5eaf-dceb-48d6-b084-bebfddbf1220,
  abstract     = {{<p>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 contributedMRIs 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 themanual and automated assessments of established MRI markers. A high-throughputMRI 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.</p>}},
  author       = {{Giese, Anne Katrin and Schirmer, Markus D. and Donahue, Kathleen L. and Cloonan, Lisa and Irie, Robert and Winzeck, Stefan and Bouts, Mark J.R.J. and McIntosh, Elissa C. and Mocking, Steven J. and Dalca, Adrian V. and Sridharan, Ramesh and Xu, Huichun and Frid, Petrea and Giralt-Steinhauer, Eva and Holmegaard, Lukas and Roquer, Jaume and Wasselius, Johan and Cole, John W. and McArdle, Patrick F. and Broderick, Joseph P. and Jimenez-Conde, Jordi and Jern, Christina and Kissela, Brett M. and Kleindorfer, Dawn O. and Lemmens, Robin and Lindgren, Arne and Meschia, James F. and Rundek, Tatjana and Sacco, Ralph L. and Schmidt, Reinhold and Sharma, Pankaj and Slowik, Agnieszka and Thijs, Vincent and Woo, Daniel and Worrall, Bradford B. and Kittner, Steven J. and Mitchell, Braxton D. and Rosand, Jonathan and Golland, Polina and Wu, Ona and Rost, Natalia S.}},
  issn         = {{2376-7839}},
  language     = {{eng}},
  month        = {{10}},
  number       = {{5}},
  publisher    = {{Lippincott Williams & Wilkins}},
  series       = {{Neurology: Genetics}},
  title        = {{Design and rationale for examining neuroimaging genetics in ischemic stroke : The MRI-GENIE study}},
  url          = {{http://dx.doi.org/10.1212/NXG.0000000000000180}},
  doi          = {{10.1212/NXG.0000000000000180}},
  volume       = {{3}},
  year         = {{2017}},
}