Design and rationale for examining neuroimaging genetics in ischemic stroke

Giese, Anne-Katrin; Schirmer, Markus D.; Donahue, Kathleen; Cloonan, Lisa; Irie, Robert; Winzeck, Stefan; Bouts, Mark J. R. J.; McIntosh, Elissa C.; Mocking, Steven J. T.; Dalca, Adrian V.; Sridharan, Ramesh; Xu, Huichun; Frid, Petrea; Giralt-Steinhauer, Eva; Holmegaard, Lukas; Roquer, Jaume; Wassélius, Johan; Cole, John W.; McArdle, Patrick F.; Broderick, Joseph P.; Jiménez‐Conde, Jordi; Jern, Christina; Kissela, Brett M; Kleindorfer, Dawn; Lemmens, Robin; Lindgren, Arne; Meschia, James F.; Rundek, Tatjana; Sacco, Ralph L.; Schmidt, Reinhold; Sharma, Pankaj; Słowik, Agnieszka; Thijs, Vincent; Woo, Daniel; Worrall, Bradford B.; Kittner, Steven J.; Mitchell, Braxton D.; Rosand, Jonathan; Golland, Polina; Wu, Ona; Rost, Natalia S.

doi:10.1212/nxg.0000000000000180

Cited by 38 publications

(47 citation statements)

References 34 publications

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“…We reviewed all ischemic stroke cases in the neuroimaging repository of the MRI-GENetics Interface Exploration (MRI-GENIE) collaboration [10]. Data were contributed by 12 of the original National Institute of Neurological Disorders and Stroke Genetics Network (NINDS-SiGN) study sites [11].…”

Section: Settingmentioning

confidence: 99%

“…Data were contributed by 12 of the original National Institute of Neurological Disorders and Stroke Genetics Network (NINDS-SiGN) study sites [11]. Previous publications provide detailed descriptions of the NINDS-SiGN and MRI-GENIE studies, as well as collection periods and inclusion criteria for each site [10,12].…”

Section: Settingmentioning

confidence: 99%

“…MRI scans were transferred to the MRI-GENIE neuroimaging repository in DICOM format and were available for review through a secure XNAT viewer [10]. Two senior neuroradiologists (J.W., M.D.…”

Section: Mri Evaluationmentioning

confidence: 99%

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Detailed phenotyping of posterior vs. anterior circulation ischemic stroke: a multi-center MRI study

et al. 2019

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Objective Posterior circulation ischemic stroke (PCiS) constitutes 20-30% of ischemic stroke cases. Detailed information about differences between PCiS and anterior circulation ischemic stroke (ACiS) remains scarce. Such information might guide clinical decision making and prevention strategies. We studied risk factors and ischemic stroke subtypes in PCiS vs. ACiS and lesion location on magnetic resonance imaging (MRI) in PCiS. Methods Out of 3,301 MRIs from 12 sites in the National Institute of Neurological Disorders and Stroke (NINDS) Stroke Genetics Network (SiGN), we included 2,381 cases with acute DWI lesions. The definition of ACiS or PCiS was based on lesion location. We compared the groups using Chi-squared and logistic regression. Results PCiS occurred in 718 (30%) patients and ACiS in 1663 (70%). Diabetes and male sex were more common in PCiS vs. ACiS (diabetes 27% vs. 23%, p < 0.05; male sex 68% vs. 58%, p < 0.001). Both were independently associated with PCiS (diabetes, OR = 1.29; 95% CI 1.04-1.61; male sex, OR = 1.46; 95% CI 1.21-1.78). ACiS more commonly had large artery atherosclerosis (25% vs. 20%, p < 0.01) and cardioembolic mechanisms (17% vs. 11%, p < 0.001) compared to PCiS. Small artery occlusion was more common in PCiS vs. ACiS (20% vs. 14%, p < 0.001). Small artery occlusion accounted for 47% of solitary brainstem infarctions. Conclusion Ischemic stroke subtypes differ between the two phenotypes. Diabetes and male sex have a stronger association with PCiS than ACiS. Definitive MRI-based PCiS diagnosis aids etiological investigation and contributes additional insights into specific risk factors and mechanisms of injury in PCiS.

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Section: Settingmentioning

confidence: 99%

Section: Settingmentioning

confidence: 99%

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Detailed phenotyping of posterior vs. anterior circulation ischemic stroke: a multi-center MRI study

et al. 2019

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“…3 However, determinants of stroke outcome are poorly understood. 4,5 Recent studies indicate that structural aspects, such as white matter microstructural integrity, are related to functional outcome post-stroke. 6 This reflects the role that structural connectivity, defined by brain regions connected through white matter tracts, has in maintaining brain function and suggests that a disrupted brain network (connectome 7 ) may contribute to the observed symptoms of stroke.…”

Section: Introductionmentioning

confidence: 99%

Rich-Club organization: an important determinant of functional outcome after acute ischemic stroke

Schirmer

Ktena

Nardin

et al. 2019

Preprint

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Objective:To determine whether the rich-club organization, essential for information transport in the human connectome, is an important biomarker of functional outcome after acute ischemic stroke (AIS). Methods: Consecutive AIS patients (N=344) with acute brain magnetic resonance imaging (MRI) (<48 hours) were eligible for this study. Each patient underwent a clinical MRI protocol, which included diffusion weighted imaging (DWI). All DWIs were registered to a template on which rich-club regions have been defined. Using manual outlines of stroke lesions, we automatically counted the number of affected rich-club regions and assessed its effect on the National Institute of Health Stroke Scale (NIHSS) and modified Rankin Scale (mRS; obtained at 90 days post-stroke) scores through ordinal regression. Results: Of 344 patients (median age 65, inter-quartile range 54-76 years) with a median DWI lesion volume (DWIv) of 3cc, 64% were male. We established that an increase in number of rich-club regions affected by a stroke increases the odds of poor stroke outcome, measured by NIHSS (OR: 1.77, 95%CI 1.41-2.21) and mRS (OR: 1.38, 95%CI 1.11-1.73). Additionally, we demonstrated that the OR exceeds traditional markers, such as DWIv (ORNIHSS 1.08, 95%CI 1.06-1.11; ORmRS 1.05, 95%CI 1.03-1.07) and age (ORNIHSS 1.03, 95%CI 1.01-1.05; ORmRS 1.05, 95%CI 1.03-1.07). Conclusion: In this proof-of-concept study, the number of rich-club nodes affected by a stroke lesion presents a translational biomarker of stroke outcome, which can be readily assessed using standard clinical AIS imaging protocols and considered in functional outcome prediction models beyond traditional factors.

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“…Even though WMH burden has been linked to both incidence and outcomes of stroke (Kuller et al, 2004), spatial specificity of WMH has not been fully explored. WMH is commonly assessed on axial T2 Fluid Attenuated Inverse Recovery (FLAIR) magnetic resonance (MR) images and total WMH burden can be summarized as WMH volume (WMHv) (Debette and Markus, 2010;Giese et al, 2017;Kuller et al, 2004). Importantly, it has been shown, that WMHv presents an accurate and uniform way of quantifying this phenotype in clinical populations, such as acute ischemic stroke (AIS) patients (Zhang et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Spatial signature of white matter hyperintensities in stroke patients

Schirmer

Fotiadis

Etherton

et al. 2018

Preprint

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Keywords: acute ischemic stroke, white matter hyperintensity, spatial, vascular territory, template Abstract Purpose: White matter hyperintensity (WMH) is a common phenotype across a variety of neurological diseases, particularly prevalent in stroke patients; however, vascular territory dependent variation in WMH burden has not yet been identified. Here, we sought to investigate the spatial specificity of WMH burden in patients with acute ischemic stroke (AIS). Materials and Methods:We created a novel age-appropriate high-resolution brain template and anatomically delineated the cerebral vascular territories. We used WMH masks derived from the clinical T2 FLAIR MRI scans and spatial normalization of the template to discriminate between WMH volume within each subject's anterior cerebral artery (ACA), middle cerebral artery (MCA), and posterior cerebral artery (PCA) territories. Linear regression modeling including age, sex, common vascular risk factors, and TOAST stroke subtypes was used to assess for spatial specificity of WMH volume (WMHv) in a cohort of 882 AIS patients.Results: Mean age of this cohort was 65.23±14.79 years, 61.7% were male, 63.6% were hypertensive, 35.8% never smoked. Mean WMHv was 11.58c +/-13.49 cc. There were significant differences in territory-specific, relative to global, WMH burden. In contrast to PCA territory, age (0.018±0.002, p<0.001) and small-vessel stroke subtype (0.212±0.098, p<0.001) were associated with relative increase of WMH burden within the anterior (ACA and MCA) territories, whereas male sex (-0.275±0.067, p<0.001) was associated with a relative decrease in WMHv. Conclusions:Our data establish the spatial specificity of WMH distribution in relation to vascular territory and risk factor exposure in AIS patients and offer new insights into the underlying pathology. Sex = Male (%; n missing) 542 (61.7; 4) Smoking (%; n missing) 559 (64.2; 11) HTN (%; n missing) 558 (63.6; 5) DM2 (%; n missing) 173 (19.7; 5) HLD (%; n missing) 362 (41.3; 5) SV (%; n missing) 85 (11.8; 162) CE (%; n missing) 263 (36.5; 162) LA (%; n missing) 164 (22.8; 162) Other (%; n missing) 167 (23.2; 162) TIA (%; n missing) 68 (7.8; 6) Prior stroke (%; n missing) 138 (15.7; 4) WMHv (mean (sd); n missing) 11.58 (13.49) DWIv (mean (sd); n missing) 13.52 (28.61; 238)

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Design and rationale for examining neuroimaging genetics in ischemic stroke

Cited by 38 publications

References 34 publications

Detailed phenotyping of posterior vs. anterior circulation ischemic stroke: a multi-center MRI study

Detailed phenotyping of posterior vs. anterior circulation ischemic stroke: a multi-center MRI study

Rich-Club organization: an important determinant of functional outcome after acute ischemic stroke

Spatial signature of white matter hyperintensities in stroke patients

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