Design and rationale for examining neuroimaging genetics in ischemic stroke: The MRI-GENIE study. (October 2017)

• Record Type: Journal Article
• Authors: 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.;
• Is Part Of: Neurology. Volume 3:Number 5(2017)
• Publication Date: 2017-10
• Subjects: Neurogenetics -- Periodicals; 616.80442
• DOI: 10.1212/NXG.0000000000000180
• Languages: English
• ISSNs: 2376-7839

Abstract

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 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.