Publications by authors named "Anne-Katrin Giese"

53 Publications

Excessive White Matter Hyperintensity Increases Susceptibility to Poor Functional Outcomes After Acute Ischemic Stroke.

Front Neurol 2021 10;12:700616. Epub 2021 Sep 10.

Centogene AG, Rostock, Germany.

To personalize the prognostication of post-stroke outcome using MRI-detected cerebrovascular pathology, we sought to investigate the association between the excessive white matter hyperintensity (WMH) burden unaccounted for by the traditional stroke risk profile of individual patients and their long-term functional outcomes after a stroke. We included 890 patients who survived after an acute ischemic stroke from the MRI-Genetics Interface Exploration (MRI-GENIE) study, for whom data on vascular risk factors (VRFs), including age, sex, atrial fibrillation, diabetes mellitus, hypertension, coronary artery disease, smoking, prior stroke history, as well as acute stroke severity, 3- to-6-month modified Rankin Scale score (mRS), WMH, and brain volumes, were available. We defined the unaccounted WMH (uWMH) burden modeling of expected WMH burden based on the VRF profile of each individual patient. The association of uWMH and mRS score was analyzed by linear regression analysis. The odds ratios of patients who achieved full functional independence (mRS < 2) in between trichotomized uWMH burden groups were calculated by pair-wise comparisons. The expected WMH volume was estimated with respect to known VRFs. The uWMH burden was associated with a long-term functional outcome (β = 0.104, < 0.01). Excessive uWMH burden significantly reduced the odds of achieving full functional independence after a stroke compared to the low and average uWMH burden [OR = 0.4, 95% CI: (0.25, 0.63), < 0.01 and OR = 0.61, 95% CI: (0.42, 0.87), < 0.01, respectively]. The excessive amount of uWMH burden unaccounted for by the traditional VRF profile was associated with worse post-stroke functional outcomes. Further studies are needed to evaluate a lifetime brain injury reflected in WMH unrelated to the VRF profile of a patient as an important factor for stroke recovery and a plausible indicator of brain health.
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http://dx.doi.org/10.3389/fneur.2021.700616DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8461233PMC
September 2021

MRI Radiomic Signature of White Matter Hyperintensities Is Associated With Clinical Phenotypes.

Front Neurosci 2021 12;15:691244. Epub 2021 Jul 12.

Department of Neurology, Washington University School of Medicine and Barnes-Jewish Hospital, St. Louis, MO, United States.

Objective: Neuroimaging measurements of brain structural integrity are thought to be surrogates for brain health, but precise assessments require dedicated advanced image acquisitions. By means of quantitatively describing conventional images, radiomic analyses hold potential for evaluating brain health. We sought to: (1) evaluate radiomics to assess brain structural integrity by predicting white matter hyperintensities burdens (WMH) and (2) uncover associations between predictive radiomic features and clinical phenotypes.

Methods: We analyzed a multi-site cohort of 4,163 acute ischemic strokes (AIS) patients with T2-FLAIR MR images with total brain and WMH segmentations. Radiomic features were extracted from normal-appearing brain tissue (brain mask-WMH mask). Radiomics-based prediction of personalized WMH burden was done using ElasticNet linear regression. We built a radiomic signature of WMH with stable selected features predictive of WMH burden and then related this signature to clinical variables using canonical correlation analysis (CCA).

Results: Radiomic features were predictive of WMH burden ( = 0.855 ± 0.011). Seven pairs of canonical variates (CV) significantly correlated the radiomics signature of WMH and clinical traits with respective canonical correlations of 0.81, 0.65, 0.42, 0.24, 0.20, 0.15, and 0.15 (FDR-corrected -values < 0.001, -value = 0.012). The clinical CV1 was mainly influenced by age, CV2 by sex, CV3 by history of smoking and diabetes, CV4 by hypertension, CV5 by atrial fibrillation (AF) and diabetes, CV6 by coronary artery disease (CAD), and CV7 by CAD and diabetes.

Conclusion: Radiomics extracted from T2-FLAIR images of AIS patients capture microstructural damage of the cerebral parenchyma and correlate with clinical phenotypes, suggesting different radiographical textural abnormalities per cardiovascular risk profile. Further research could evaluate radiomics to predict the progression of WMH and for the follow-up of stroke patients' brain health.
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http://dx.doi.org/10.3389/fnins.2021.691244DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8312571PMC
July 2021

Outcome after acute ischemic stroke is linked to sex-specific lesion patterns.

Nat Commun 2021 06 2;12(1):3289. Epub 2021 Jun 2.

Department of Neurology, Washington University School of Medicine & Barnes-Jewish Hospital, St Louis, MO, USA.

Acute ischemic stroke affects men and women differently. In particular, women are often reported to experience higher acute stroke severity than men. We derived a low-dimensional representation of anatomical stroke lesions and designed a Bayesian hierarchical modeling framework tailored to estimate possible sex differences in lesion patterns linked to acute stroke severity (National Institute of Health Stroke Scale). This framework was developed in 555 patients (38% female). Findings were validated in an independent cohort (n = 503, 41% female). Here, we show brain lesions in regions subserving motor and language functions help explain stroke severity in both men and women, however more widespread lesion patterns are relevant in female patients. Higher stroke severity in women, but not men, is associated with left hemisphere lesions in the vicinity of the posterior circulation. Our results suggest there are sex-specific functional cerebral asymmetries that may be important for future investigations of sex-stratified approaches to management of acute ischemic stroke.
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http://dx.doi.org/10.1038/s41467-021-23492-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8172535PMC
June 2021

Abnormal dynamic functional connectivity is linked to recovery after acute ischemic stroke.

Hum Brain Mapp 2021 05 2;42(7):2278-2291. Epub 2021 Mar 2.

J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA.

The aim of the current study was to explore the whole-brain dynamic functional connectivity patterns in acute ischemic stroke (AIS) patients and their relation to short and long-term stroke severity. We investigated resting-state functional MRI-based dynamic functional connectivity of 41 AIS patients two to five days after symptom onset. Re-occurring dynamic connectivity configurations were obtained using a sliding window approach and k-means clustering. We evaluated differences in dynamic patterns between three NIHSS-stroke severity defined groups (mildly, moderately, and severely affected patients). Furthermore, we built Bayesian hierarchical models to evaluate the predictive capacity of dynamic connectivity and examine the interrelation with clinical measures, such as white matter hyperintensity lesions. Finally, we established correlation analyses between dynamic connectivity and AIS severity as well as 90-day neurological recovery (ΔNIHSS). We identified three distinct dynamic connectivity configurations acutely post-stroke. More severely affected patients spent significantly more time in a configuration that was characterized by particularly strong connectivity and isolated processing of functional brain domains (three-level ANOVA: p < .05, post hoc t tests: p < .05, FDR-corrected). Configuration-specific time estimates possessed predictive capacity of stroke severity in addition to the one of clinical measures. Recovery, as indexed by the realized change of the NIHSS over time, was significantly linked to the dynamic connectivity between bilateral intraparietal lobule and left angular gyrus (Pearson's r = -.68, p = .003, FDR-corrected). Our findings demonstrate transiently increased isolated information processing in multiple functional domains in case of severe AIS. Dynamic connectivity involving default mode network components significantly correlated with recovery in the first 3 months poststroke.
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http://dx.doi.org/10.1002/hbm.25366DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8046120PMC
May 2021

White Matter Hyperintensity Burden Is Associated With Hippocampal Subfield Volume in Stroke.

Front Neurol 2020 26;11:588883. Epub 2020 Oct 26.

Department of Neurology, J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States.

White matter hyperintensities of presumed vascular origin (WMH) are a prevalent form of cerebral small-vessel disease and an important risk factor for post-stroke cognitive dysfunction. Despite this prevalence, it is not well understood how WMH contributes to post-stroke cognitive dysfunction. Preliminary findings suggest that increasing WMH volume is associated with total hippocampal volume in chronic stroke patients. The hippocampus, however, is a complex structure with distinct subfields that have varying roles in the function of the hippocampal circuitry and unique anatomical projections to different brain regions. For these reasons, an investigation into the relationship between WMH and hippocampal subfield volume may further delineate how WMH predispose to post-stroke cognitive dysfunction. In a prospective study of acute ischemic stroke patients with moderate/severe WMH burden, we assessed the relationship between quantitative WMH burden and hippocampal subfield volumes. Patients underwent a 3T MRI brain within 2-5 days of stroke onset. Total WMH volume was calculated in a semi-automated manner. Mean cortical thickness and hippocampal volumes were measured in the contralesional hemisphere. Total and subfield hippocampal volumes were measured using an automated, high-resolution, computational atlas. Linear regression analyses were performed for predictors of total and subfield hippocampal volumes. Forty patients with acute ischemic stroke and moderate/severe white matter hyperintensity burden were included in this analysis. Median WMH volume was 9.0 cm. Adjusting for intracranial volume and stroke laterality, age (β = -3.7, < 0.001), hypertension (β = -44.7, = 0.04), WMH volume (β = -0.89, = 0.049), and mean cortical thickness (β = 286.2, = 0.006) were associated with total hippocampal volume. In multivariable analysis, age (β = -3.3, < 0.001) and cortical thickness (β = 205.2, = 0.028) remained independently associated with total hippocampal volume. In linear regression for predictors of hippocampal subfield volume, increasing WMH volume was associated with decreased hippocampal-amygdala transition area volume (β = -0.04, = 0.001). These finding suggest that in ischemic stroke patients, increased WMH burden is associated with selective hippocampal subfield degeneration in the hippocampal-amygdala transition area.
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http://dx.doi.org/10.3389/fneur.2020.588883DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7649326PMC
October 2020

Association of common genetic variants with brain microbleeds: A genome-wide association study.

Neurology 2020 12 10;95(24):e3331-e3343. Epub 2020 Sep 10.

From the Departments of Epidemiology (M.J.K., H.H.H.A., D.V., S.J.v.d.L., P.Y., M.W.V., N.A., C.M.v.D., M.A.I.), Radiology and Nuclear Medicine (H.H.H.A., P.Y., A.v.d.L., M.W.V.), and Clinical Genetics (H.H.H.A.), Erasmus MC University Medical Center, Rotterdam, the Netherlands; Stroke Research Group, Department of Clinical Neurosciences (D.L., M.T., J.L., D.J.T., H.S.M.), University of Cambridge, UK; Department of Neurology (J.R.J.R., C.L.S., J.J.H., A.S.B., C.D., S. Seshadri), Boston University School of Medicine; The Framingham Heart Study (J.R.J.R., C.L.S., J.J.H., A.S.B., S. Seshadri), MA; Department of Biostatistics (A.V.S.), University of Michigan, Ann Arbor; Icelandic Heart Association (A.V.S., S. Sigurdsson, V.G.), Kopavogur, Iceland; Brown Foundation Institute of Molecular Medicine, McGovern Medical School (M.F.), and Human Genetics Center, School of Public Health (M.F.), University of Texas Health Science Center at Houston; Clinical Division of Neurogeriatrics, Department of Neurology (E.H., L.P., R.S.), Institute for Medical Informatics, Statistics and Documentation (E.H.), and Gottfried Schatz Research Center, Department of Molecular Biology and Biochemistry (Y.S., H.S.), Medical University of Graz, Austria; Center of Cerebrovascular Diseases, Department of Neurology (J.L.), West China Hospital, Sichuan University, Chengdu; Stroke Research Centre, Queen Square Institute of Neurology (I.C.H., D.W., H.H., D.J.W.), University College London, UK; Department of Neurosurgery (I.C.H.), Klinikum rechts der Isar, University of Munich, Germany; Centre for Cognitive Ageing and Cognitive Epidemiology, Psychology (M.L., D.C.M.L., M.E.B., I.J.D., J.M.W.), and Centre for Clinical Brain Sciences, Edinburgh Imaging, UK Dementia Research Institute (M.E.B., J.M.W.), University of Edinburgh, UK; Department of Internal Medicine, Section of Gerontology and Geriatrics (S.T.), Department of Cardiology (S.T., J.v.d.G., J.W.J.), Section of Molecular Epidemiology, Biomedical Data Sciences (E.B.v.d.A., M.B., P.E.S.), Leiden Computational Biology Center, Biomedical Data Sciences (E.B.v.d.A.), Department of Radiology (J.v.d.G.), and Einthoven Laboratory for Experimental Vascular Medicine (J.W.J.), Leiden University Medical Center, the Netherlands; Department of Neurology (A.-K.G., N.S.R.), Massachusetts General Hospital, Harvard Medical School, Boston; Memory Aging and Cognition Center (S.H., C.C.), National University Health System, Singapore; Department of Pharmacology (S.H., C.C.) and Saw Swee Hock School of Public Health (S.H.), National University of Singapore and National University Health System, Singapore; Pattern Recognition & Bioinformatics (E.B.v.d.A.), Delft University of Technology, the Netherlands; Department of Biostatistics (S.L., J.J.H., Q.Y., A.S.B.), Boston University School of Public Health, MA; Department of Radiology (C.R.J., K.K.), Mayo Clinic, Rochester, MN; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (C.L.S., S. Seshadri), UT Health San Antonio, TX; Department of Medicine, Division of Geriatrics (B.G.W., T.H.M), and Memory Impairment and Neurodegenerative Dementia (MIND) Center (T.H.M.), University of Mississippi Medical Center, Jackson; Singapore Eye Research Institute (C.Y.C., J.Y.K., T.Y.W.); Department of Neuroradiology (Z.M., J.M.W.), NHS Lothian, Edinburgh; Institute of Cardiovascular and Medical Sciences (D.J.S.), College of Medical, Veterinary and Life Sciences, University of Glasgow, UK; Division of Cerebrovascular Neurology (R.F.G.), Johns Hopkins University, Baltimore, MD; Department of Neuroradiology (A.D.M.), Atkinson Morley Neurosciences Centre, St George's NHS Foundation Trust, London, UK; Department of Neurology (C.D.), University of California at Davis; Nuffield Department of Population Health (C.M.v.D.), University of Oxford, UK; Laboratory of Epidemiology and Population Sciences (L.J.L.), National Institute on Aging, Baltimore, MD; and Faculty of Medicine (V.G.), University of Iceland, Reykjavik, Iceland.

Objective: To identify common genetic variants associated with the presence of brain microbleeds (BMBs).

Methods: We performed genome-wide association studies in 11 population-based cohort studies and 3 case-control or case-only stroke cohorts. Genotypes were imputed to the Haplotype Reference Consortium or 1000 Genomes reference panel. BMBs were rated on susceptibility-weighted or T2*-weighted gradient echo MRI sequences, and further classified as lobar or mixed (including strictly deep and infratentorial, possibly with lobar BMB). In a subset, we assessed the effects of ε2 and ε4 alleles on BMB counts. We also related previously identified cerebral small vessel disease variants to BMBs.

Results: BMBs were detected in 3,556 of the 25,862 participants, of which 2,179 were strictly lobar and 1,293 mixed. One locus in the region reached genome-wide significance for its association with BMB (lead rs769449; odds ratio [OR] [95% confidence interval (CI)] 1.33 [1.21-1.45]; = 2.5 × 10). ε4 alleles were associated with strictly lobar (OR [95% CI] 1.34 [1.19-1.50]; = 1.0 × 10) but not with mixed BMB counts (OR [95% CI] 1.04 [0.86-1.25]; = 0.68). ε2 alleles did not show associations with BMB counts. Variants previously related to deep intracerebral hemorrhage and lacunar stroke, and a risk score of cerebral white matter hyperintensity variants, were associated with BMB.

Conclusions: Genetic variants in the region are associated with the presence of BMB, most likely due to the ε4 allele count related to a higher number of strictly lobar BMBs. Genetic predisposition to small vessel disease confers risk of BMB, indicating genetic overlap with other cerebral small vessel disease markers.
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http://dx.doi.org/10.1212/WNL.0000000000010852DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7836652PMC
December 2020

Diffusion-Weighted Imaging, MR Angiography, and Baseline Data in a Systematic Multicenter Analysis of 3,301 MRI Scans of Ischemic Stroke Patients-Neuroradiological Review Within the MRI-GENIE Study.

Front Neurol 2020 25;11:577. Epub 2020 Jun 25.

Department of Neurology and the Evelyn F. McKnight Brain Institute, Miller School of Medicine, University of Miami, Miami, FL, United States.

Magnetic resonance imaging (MRI) serves as a cornerstone in defining stroke phenotype and etiological subtype through examination of ischemic stroke lesion appearance and is therefore an essential tool in linking genetic traits and stroke. Building on baseline MRI examinations from the centralized and structured radiological assessments of ischemic stroke patients in the Stroke Genetics Network, the results of the MRI-Genetics Interface Exploration (MRI-GENIE) study are described in this work. The MRI-GENIE study included patients with symptoms caused by ischemic stroke ( = 3,301) from 12 international centers. We established and used a structured reporting protocol for all assessments. Two neuroradiologists, using a blinded evaluation protocol, independently reviewed the baseline diffusion-weighted images (DWIs) and magnetic resonance angiography images to determine acute lesion and vascular occlusion characteristics. In this systematic multicenter radiological analysis of clinical MRI from 3,301 acute ischemic stroke patients according to a structured prespecified protocol, we identified that anterior circulation infarcts were most prevalent (67.4%), that infarcts in the middle cerebral artery (MCA) territory were the most common, and that the majority of large artery occlusions 0 to 48 h from ictus were in the MCA territory. Multiple acute lesions in one or several vascular territories were common (11%). Of 2,238 patients with unilateral DWI lesions, 52.6% had left-sided infarct lateralization ( = 0.013 for χ test). This large-scale analysis of a multicenter MRI-based cohort of AIS patients presents a unique imaging framework facilitating the relationship between imaging and genetics for advancing the knowledge of genetic traits linked to ischemic stroke.
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http://dx.doi.org/10.3389/fneur.2020.00577DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7330135PMC
June 2020

White matter hyperintensity burden in acute stroke patients differs by ischemic stroke subtype.

Neurology 2020 07 3;95(1):e79-e88. Epub 2020 Jun 3.

From the Department of Neurology (A.-K.G., M.D.S., K.L.D., M.N., J.R., O.W., N.S.R.), Massachusetts General Hospital, Harvard Medical School, Boston; Program in Medical and Population Genetics (A.K.-G, J.R.), Broad Institute of MIT and Harvard; Computer Science and Artificial Intelligence Lab (M.D.S., A.V.D., R. Sridharan, P.G.), Massachusetts Institute of Technology, Cambridge; Department of Population Health Sciences (M.D.S.), German Centre for Neurodegenerative Diseases, Bonn, Germany; Athinoula A. Martinos Center for Biomedical Imaging (A.V.D., R.I., E.C.M., S.J.T.M., J.R., O.W.), Department of Radiology, Massachusetts General Hospital, Charlestown; Division of Endocrinology, Diabetes and Nutrition (H.X., P.F.M., B.D.M.), Department of Medicine, University of Maryland School of Medicine; Department of Neurology (J.W.C., S.J.K.), University of Maryland School of Medicine and Veterans Affairs Maryland Health Care System, Baltimore; Department of Neurology (E.G.-S., J.J.-C.), Neurovascular Research Group, IMIM-Hospital del Mar (Institut Hospital del Mar d'Investigacions Mèdiques), Universitat Autonoma de Barcelona, Spain; Institute of Biomedicine (C.J.), Sahlgrenska Academy at University of Gothenburg, Sweden; Department of Neurology and Rehabilitation Medicine (D.O.K., D.W.), University of Cincinnati College of Medicine, OH; KU Leuven-University of Leuven (R.L.), Department of Neurosciences, Experimental Neurology; VIB (R.L.), Vesalius Research Center, Laboratory of Neurobiology, University Hospitals Leuven, Department of Neurology, Belgium; Department of Clinical Sciences Lund (J.W., A.L.), Neurology, Lund University; Department of Neurology and Rehabilitation Medicine (A.L.), Neurology, Skåne University Hospital, Lund, Sweden; Department of Neurology (T.R., R.L.S.), Miller School of Medicine, University of Miami, The Evelyn F. McKnight Brain Institute, FL; Department of Neurology (R. Schmidt), Clinical Division of Neurogeriatrics, Medical University Graz, Austria; Institute of Cardiovascular Research (P.S.), Royal Holloway University of London, Egham, UK; Ashford and St Peter's Hospital (P.S.), UK; Department of Neurology (A.S.), Jagiellonian University Medical College, Krakow, Poland; Stroke Division (V.T.), Florey Institute of Neuroscience and Mental Health, University of Melbourne Heidelberg; Department of Neurology (V.T.), Austin Health, Heidelberg, Victoria, Australia; Departments of Neurology and Public Health Sciences (B.B.W.), University of Virginia, Charlottesville; Center for Genomic Medicine (J.R.), Massachusetts General Hospital; Henry and Allison McCance Center for Brain Health (J.R.), Boston, MA; and Department of Neurology (J.F.M.), Mayo Clinic, Jacksonville, FL.

Objective: To examine etiologic stroke subtypes and vascular risk factor profiles and their association with white matter hyperintensity (WMH) burden in patients hospitalized for acute ischemic stroke (AIS).

Methods: For the MRI Genetics Interface Exploration (MRI-GENIE) study, we systematically assembled brain imaging and phenotypic data for 3,301 patients with AIS. All cases underwent standardized web tool-based stroke subtyping with the Causative Classification of Ischemic Stroke (CCS). WMH volume (WMHv) was measured on T2 brain MRI scans of 2,529 patients with a fully automated deep-learning trained algorithm. Univariable and multivariable linear mixed-effects modeling was carried out to investigate the relationship of vascular risk factors with WMHv and CCS subtypes.

Results: Patients with AIS with large artery atherosclerosis, major cardioembolic stroke, small artery occlusion (SAO), other, and undetermined causes of AIS differed significantly in their vascular risk factor profile (all < 0.001). Median WMHv in all patients with AIS was 5.86 cm (interquartile range 2.18-14.61 cm) and differed significantly across CCS subtypes ( < 0.0001). In multivariable analysis, age, hypertension, prior stroke, smoking (all < 0.001), and diabetes mellitus ( = 0.041) were independent predictors of WMHv. When adjusted for confounders, patients with SAO had significantly higher WMHv compared to those with all other stroke subtypes ( < 0.001).

Conclusion: In this international multicenter, hospital-based cohort of patients with AIS, we demonstrate that vascular risk factor profiles and extent of WMH burden differ by CCS subtype, with the highest lesion burden detected in patients with SAO. These findings further support the small vessel hypothesis of WMH lesions detected on brain MRI of patients with ischemic stroke.
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http://dx.doi.org/10.1212/WNL.0000000000009728DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7371377PMC
July 2020

Brain Volume: An Important Determinant of Functional Outcome After Acute Ischemic Stroke.

Mayo Clin Proc 2020 05;95(5):955-965

Division of Neurocritical Care and Emergency Neurology, Department of Neurology, Helsinki University Central Hospital, Helsinki, Finland.

Objective: To determine whether brain volume is associated with functional outcome after acute ischemic stroke (AIS).

Patients And Methods: This study was conducted between July 1, 2014, and March 16, 2019. We analyzed cross-sectional data of the multisite, international hospital-based MRI-Genetics Interface Exploration study with clinical brain magnetic resonance imaging obtained on admission for index stroke and functional outcome assessment. Poststroke outcome was determined using the modified Rankin Scale score (0-6; 0 = asymptomatic; 6 = death) recorded between 60 and 190 days after stroke. Demographic characteristics and other clinical variables including acute stroke severity (measured as National Institutes of Health Stroke Scale score), vascular risk factors, and etiologic stroke subtypes (Causative Classification of Stroke system) were recorded during index admission.

Results: Utilizing the data from 912 patients with AIS (mean ± SD age, 65.3±14.5 years; male, 532 [58.3%]; history of smoking, 519 [56.9%]; hypertension, 595 [65.2%]) in a generalized linear model, brain volume (per 155.1 cm) was associated with age (β -0.3 [per 14.4 years]), male sex (β 1.0), and prior stroke (β -0.2). In the multivariable outcome model, brain volume was an independent predictor of modified Rankin Scale score (β -0.233), with reduced odds of worse long-term functional outcomes (odds ratio, 0.8; 95% CI, 0.7-0.9) in those with larger brain volumes.

Conclusion: Larger brain volume quantified on clinical magnetic resonance imaging of patients with AIS at the time of stroke purports a protective mechanism. The role of brain volume as a prognostic, protective biomarker has the potential to forge new areas of research and advance current knowledge of the mechanisms of poststroke recovery.
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http://dx.doi.org/10.1016/j.mayocp.2020.01.027DOI Listing
May 2020

Multi-atlas image registration of clinical data with automated quality assessment using ventricle segmentation.

Med Image Anal 2020 07 18;63:101698. Epub 2020 Apr 18.

J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, USA; Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, USA; Department of Population Health Sciences, German Centre for Neurodegenerative Diseases (DZNE), Germany. Electronic address:

Registration is a core component of many imaging pipelines. In case of clinical scans, with lower resolution and sometimes substantial motion artifacts, registration can produce poor results. Visual assessment of registration quality in large clinical datasets is inefficient. In this work, we propose to automatically assess the quality of registration to an atlas in clinical FLAIR MRI scans of the brain. The method consists of automatically segmenting the ventricles of a given scan using a neural network, and comparing the segmentation to the atlas ventricles propagated to image space. We used the proposed method to improve clinical image registration to a general atlas by computing multiple registrations - one directly to the general atlas and others via different age-specific atlases - and then selecting the registration that yielded the highest ventricle overlap. Finally, as an example application of the complete pipeline, a voxelwise map of white matter hyperintensity burden was computed using only the scans with registration quality above a predefined threshold. Methods were evaluated in a single-site dataset of more than 1000 scans, as well as a multi-center dataset comprising 142 clinical scans from 12 sites. The automated ventricle segmentation reached a Dice coefficient with manual annotations of 0.89 in the single-site dataset, and 0.83 in the multi-center dataset. Registration via age-specific atlases could improve ventricle overlap compared to a direct registration to the general atlas (Dice similarity coefficient increase up to 0.15). Experiments also showed that selecting scans with the registration quality assessment method could improve the quality of average maps of white matter hyperintensity burden, instead of using all scans for the computation of the white matter hyperintensity map. In this work, we demonstrated the utility of an automated tool for assessing image registration quality in clinical scans. This image quality assessment step could ultimately assist in the translation of automated neuroimaging pipelines to the clinic.
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http://dx.doi.org/10.1016/j.media.2020.101698DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7275913PMC
July 2020

Proteostasis regulators modulate proteasomal activity and gene expression to attenuate multiple phenotypes in Fabry disease.

Biochem J 2020 01;477(2):359-380

Translational Neurodegeneration Section "Albrecht-Kossel", Department of Neurology, University Medical Center Rostock, University of Rostock, 18147 Rostock, Germany.

The lysosomal storage disorder Fabry disease is characterized by a deficiency of the lysosomal enzyme α-Galactosidase A. The observation that missense variants in the encoding GLA gene often lead to structural destabilization, endoplasmic reticulum retention and proteasomal degradation of the misfolded, but otherwise catalytically functional enzyme has resulted in the exploration of alternative therapeutic approaches. In this context, we have investigated proteostasis regulators (PRs) for their potential to increase cellular enzyme activity, and to reduce the disease-specific accumulation of the biomarker globotriaosylsphingosine in patient-derived cell culture. The PRs also acted synergistically with the clinically approved 1-deoxygalactonojirimycine, demonstrating the potential of combination treatment in a therapeutic application. Extensive characterization of the effective PRs revealed inhibition of the proteasome and elevation of GLA gene expression as paramount effects. Further analysis of transcriptional patterns of the PRs exposed a variety of genes involved in proteostasis as potential modulators. We propose that addressing proteostasis is an effective approach to discover new therapeutic targets for diseases involving folding and trafficking-deficient protein mutants.
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http://dx.doi.org/10.1042/BCJ20190513DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6993862PMC
January 2020

Normal-appearing white matter microstructural injury is associated with white matter hyperintensity burden in acute ischemic stroke.

Int J Stroke 2021 02 17;16(2):184-191. Epub 2019 Dec 17.

Department of Neurology, J. Philip Kistler Stroke Research Center, 2348Massachusetts General Hospital and Harvard Medical School, Boston, USA.

Background: White matter hyperintensity of presumed vascular origin is a risk factor for poor stroke outcomes. In patients with acute ischemic stroke, however, the in vivo mechanisms of white matter microstructural injury are less clear.

Aims: To characterize the directional diffusivity components in normal-appearing white matter and white matter hyperintensity in acute ischemic stroke patients.

Methods: A retrospective analysis was performed on a cohort of patients with acute ischemic stroke and brain magnetic resonance imaging with diffusion tensor imaging sequences acquired within 48 h of admission. White matter hyperintensity volume was measured in a semi-automated manner. Median fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity values were calculated within normal-appearing white matter and white matter hyperintensity in the hemisphere contralateral to the acute infarct. Linear regression analysis was performed to evaluate predictors of white matter hyperintensity volume and normal-appearing white matter diffusivity metrics.

Results: In 319 patients, mean age was 64.9 ± 15.9 years. White matter hyperintensity volume was 6.33 cm (interquartile range 3.0-12.6 cm). Axial and radial diffusivity were significantly increased in white matter hyperintensity compared to normal-appearing white matter. In multivariable linear regression, age (β = 0.20,  = 0.003) and normal-appearing white matter axial diffusivity (β = 37.9,  < 0.001) were independently associated with white matter hyperintensity volume. Subsequent analysis demonstrated that increasing age (β = 0.004,  < 0.001) and admission diastolic blood pressure (β = 0.001,  = 0.02) were independent predictors of normal-appearing white matter axial diffusivity in multivariable linear regression.

Conclusions: Normal-appearing white matter axial diffusivity increases with age and is an independent predictor of white matter hyperintensity volume in acute ischemic stroke.
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http://dx.doi.org/10.1177/1747493019895707DOI Listing
February 2021

Rich-Club Organization: An Important Determinant of Functional Outcome After Acute Ischemic Stroke.

Front Neurol 2019 10;10:956. Epub 2019 Sep 10.

Department of Neurology, J. Philip Kistler Stroke Research Center, Harvard Medical School, Boston, MA, United States.

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). Consecutive AIS patients ( = 344) with acute brain magnetic resonance imaging (MRI) (<48 h) 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. 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 (OR 1.08, 95%CI 1.06-1.11; OR 1.05, 95%CI 1.03-1.07) and age (OR 1.03, 95%CI 1.01-1.05; OR 1.05, 95%CI 1.03-1.07). 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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http://dx.doi.org/10.3389/fneur.2019.00956DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6748157PMC
September 2019

Brain Connectivity Measures Improve Modeling of Functional Outcome After Acute Ischemic Stroke.

Stroke 2019 10 12;50(10):2761-2767. Epub 2019 Sep 12.

From the Stroke Division and Massachusetts General Hospital, J. Philip Kistler Stroke Research Center, Harvard Medical School, Boston (S.I.K., M.D.S., M.R.E., A.-K.G., C.T., B.B.M., N.S.R.).

Background and Purpose- The ability to model long-term functional outcomes after acute ischemic stroke represents a major clinical challenge. One approach to potentially improve prediction modeling involves the analysis of connectomics. The field of connectomics represents the brain's connectivity as a graph, whose topological properties have helped uncover underlying mechanisms of brain function in health and disease. Specifically, we assessed the impact of stroke lesions on rich club organization, a high capacity backbone system of brain function. Methods- In a hospital-based cohort of 41 acute ischemic stroke patients, we investigated the effect of acute infarcts on the brain's prestroke rich club backbone and poststroke functional connectomes with respect to poststroke outcome. Functional connectomes were created using 3 anatomic atlases, and characteristic path-length () was calculated for each connectome. The number of rich club regions affected were manually determined using each patient's diffusion weighted image. We investigated differences in with respect to outcome (modified Rankin Scale score; 90 days) and the National Institutes of Health Stroke Scale (NIHSS; early: 2-5 days; late: 90-day follow-up). Furthermore, we assessed the effect of including number of rich club regions and in outcome models, using linear regression and assessing the explained variance (R). Results- Of 41 patients (mean age [range]: 70 [45-89] years), 61% were male. Lower was generally associated with better outcome. Including number of rich club regions in the backward selection models of outcome, R increased between 1.3- and 2.6-fold beyond that of traditional markers (age and acute lesion volume) for NIHSS and modified Rankin Scale score. Conclusions- In this proof-of-concept study, we showed that information on network topology can be leveraged to improve modeling of poststroke functional outcome. Future studies are warranted to validate this approach in larger prospective studies of outcome prediction in stroke.
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http://dx.doi.org/10.1161/STROKEAHA.119.025738DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6756947PMC
October 2019

White matter hyperintensity quantification in large-scale clinical acute ischemic stroke cohorts - The MRI-GENIE study.

Neuroimage Clin 2019 29;23:101884. Epub 2019 May 29.

Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.

White matter hyperintensity (WMH) burden is a critically important cerebrovascular phenotype linked to prediction of diagnosis and prognosis of diseases, such as acute ischemic stroke (AIS). However, current approaches to its quantification on clinical MRI often rely on time intensive manual delineation of the disease on T2 fluid attenuated inverse recovery (FLAIR), which hinders high-throughput analyses such as genetic discovery. In this work, we present a fully automated pipeline for quantification of WMH in clinical large-scale studies of AIS. The pipeline incorporates automated brain extraction, intensity normalization and WMH segmentation using spatial priors. We first propose a brain extraction algorithm based on a fully convolutional deep learning architecture, specifically designed for clinical FLAIR images. We demonstrate that our method for brain extraction outperforms two commonly used and publicly available methods on clinical quality images in a set of 144 subject scans across 12 acquisition centers, based on dice coefficient (median 0.95; inter-quartile range 0.94-0.95; p < 0.01) and Pearson correlation of total brain volume (r = 0.90). Subsequently, we apply it to the large-scale clinical multi-site MRI-GENIE study (N = 2783) and identify a decrease in total brain volume of -2.4 cc/year. Additionally, we show that the resulting total brain volumes can successfully be used for quality control of image preprocessing. Finally, we obtain WMH volumes by building on an existing automatic WMH segmentation algorithm that delineates and distinguishes between different cerebrovascular pathologies. The learning method mimics expert knowledge of the spatial distribution of the WMH burden using a convolutional auto-encoder. This enables successful computation of WMH volumes of 2533 clinical AIS patients. We utilize these results to demonstrate the increase of WMH burden with age (0.950 cc/year) and show that single site estimates can be biased by the number of subjects recruited.
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http://dx.doi.org/10.1016/j.nicl.2019.101884DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6562316PMC
June 2020

Big Data Approaches to Phenotyping Acute Ischemic Stroke Using Automated Lesion Segmentation of Multi-Center Magnetic Resonance Imaging Data.

Stroke 2019 07 10;50(7):1734-1741. Epub 2019 Jun 10.

Department of Laboratory Medicine, Institute of Biomedicine, the Sahlgrenska Academy at University of Gothenburg, Sweden (E.L., T.M.S., C.J.).

Background and Purpose- We evaluated deep learning algorithms' segmentation of acute ischemic lesions on heterogeneous multi-center clinical diffusion-weighted magnetic resonance imaging (MRI) data sets and explored the potential role of this tool for phenotyping acute ischemic stroke. Methods- Ischemic stroke data sets from the MRI-GENIE (MRI-Genetics Interface Exploration) repository consisting of 12 international genetic research centers were retrospectively analyzed using an automated deep learning segmentation algorithm consisting of an ensemble of 3-dimensional convolutional neural networks. Three ensembles were trained using data from the following: (1) 267 patients from an independent single-center cohort, (2) 267 patients from MRI-GENIE, and (3) mixture of (1) and (2). The algorithms' performances were compared against manual outlines from a separate 383 patient subset from MRI-GENIE. Univariable and multivariable logistic regression with respect to demographics, stroke subtypes, and vascular risk factors were performed to identify phenotypes associated with large acute diffusion-weighted MRI volumes and greater stroke severity in 2770 MRI-GENIE patients. Stroke topography was investigated. Results- The ensemble consisting of a mixture of MRI-GENIE and single-center convolutional neural networks performed best. Subset analysis comparing automated and manual lesion volumes in 383 patients found excellent correlation (ρ=0.92; P<0.0001). Median (interquartile range) diffusion-weighted MRI lesion volumes from 2770 patients were 3.7 cm (0.9-16.6 cm). Patients with small artery occlusion stroke subtype had smaller lesion volumes ( P<0.0001) and different topography compared with other stroke subtypes. Conclusions- Automated accurate clinical diffusion-weighted MRI lesion segmentation using deep learning algorithms trained with multi-center and diverse data is feasible. Both lesion volume and topography can provide insight into stroke subtypes with sufficient sample size from big heterogeneous multi-center clinical imaging phenotype data sets.
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http://dx.doi.org/10.1161/STROKEAHA.119.025373DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6728139PMC
July 2019

FAHN/SPG35: a narrow phenotypic spectrum across disease classifications.

Brain 2019 06;142(6):1561-1572

Department of Neurodegenerative Diseases, Hertie-Institute for Clinical Brain Research, and Center for Neurology, University of Tübingen, Tübingen, Germany.

The endoplasmic reticulum enzyme fatty acid 2-hydroxylase (FA2H) plays a major role in the formation of 2-hydroxy glycosphingolipids, main components of myelin. FA2H deficiency in mice leads to severe central demyelination and axon loss. In humans it has been associated with phenotypes from the neurodegeneration with brain iron accumulation (fatty acid hydroxylase-associated neurodegeneration, FAHN), hereditary spastic paraplegia (HSP type SPG35) and leukodystrophy (leukodystrophy with spasticity and dystonia) spectrum. We performed an in-depth clinical and retrospective neurophysiological and imaging study in a cohort of 19 cases with biallelic FA2H mutations. FAHN/SPG35 manifests with early childhood onset predominantly lower limb spastic tetraparesis and truncal instability, dysarthria, dysphagia, cerebellar ataxia, and cognitive deficits, often accompanied by exotropia and movement disorders. The disease is rapidly progressive with loss of ambulation after a median of 7 years after disease onset and demonstrates little interindividual variability. The hair of FAHN/SPG35 patients shows a bristle-like appearance; scanning electron microscopy of patient hair shafts reveals deformities (longitudinal grooves) as well as plaque-like adhesions to the hair, likely caused by an abnormal sebum composition also described in a mouse model of FA2H deficiency. Characteristic imaging features of FAHN/SPG35 can be summarized by the 'WHAT' acronym: white matter changes, hypointensity of the globus pallidus, ponto-cerebellar atrophy, and thin corpus callosum. At least three of four imaging features are present in 85% of FA2H mutation carriers. Here, we report the first systematic, large cohort study in FAHN/SPG35 and determine the phenotypic spectrum, define the disease course and identify clinical and imaging biomarkers.
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http://dx.doi.org/10.1093/brain/awz102DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6536916PMC
June 2019

Silent but significant - A synonymous SNV alters prognosis in Pompe disease.

EBioMedicine 2019 May 12;43:20-21. Epub 2019 Apr 12.

Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.

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http://dx.doi.org/10.1016/j.ebiom.2019.04.015DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6562060PMC
May 2019

Spatial Signature of White Matter Hyperintensities in Stroke Patients.

Front Neurol 2019 19;10:208. Epub 2019 Mar 19.

Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States.

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). 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 Fluid Attenuated Inverse Recovery (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. 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, < 0.001) and small-vessel stroke subtype (0.212 ± 0.098, < 0.001) were associated with relative increase of WMH burden within the anterior (ACA and MCA) territories, whereas male sex (-0.275 ± 0.067, < 0.001) was associated with a relative decrease in WMHv. 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.
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http://dx.doi.org/10.3389/fneur.2019.00208DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6433778PMC
March 2019

White Matter Integrity and Early Outcomes After Acute Ischemic Stroke.

Transl Stroke Res 2019 12 28;10(6):630-638. Epub 2019 Jan 28.

J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, 175 Cambridge Street, Suite 300, Boston, MA, 02114, USA.

Chronic white matter structural injury is a risk factor for poor long-term outcomes after acute ischemic stroke (AIS). However, it is unclear how white matter structural injury predisposes to poor outcomes after AIS. To explore this question, in 42 AIS patients with moderate to severe white matter hyperintensity (WMH) burden, we characterized WMH and normal-appearing white matter (NAWM) diffusivity anisotropy metrics in the hemisphere contralateral to acute ischemia in relation to ischemic tissue and early functional outcomes. All patients underwent brain MRI with dynamic susceptibility contrast perfusion and diffusion tensor imaging within 12 h and at day 3-5 post stroke. Early neurological outcomes were measured as the change in NIH Stroke Scale score from admission to day 3-5 post stroke. Target mismatch profile, percent mismatch lost, infarct growth, and rates of good perfusion were measured to assess ischemic tissue outcomes. NAWM mean diffusivity was significantly lower in the group with early neurological improvement (ENI, 0.79 vs. 0.82 × 10, mm/s; P = 0.02). In multivariable logistic regression, NAWM mean diffusivity was an independent radiographic predictor of ENI (β = - 17.6, P = 0.037). Median infarct growth was 118% (IQR 26.8-221.9%) despite good reperfusion being observed in 65.6% of the cohort. NAWM and WMH diffusivity metrics were not associated with target mismatch profile, percent mismatch lost, or infarct growth. Our results suggest that, in AIS patients, white matter structural integrity is associated with poor early neurological outcomes independent of ischemic tissue outcomes.
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http://dx.doi.org/10.1007/s12975-019-0689-4DOI Listing
December 2019

A genome-wide association study identifies new loci for factor VII and implicates factor VII in ischemic stroke etiology.

Blood 2019 02 14;133(9):967-977. Epub 2019 Jan 14.

Department of Neurology, School of Medicine, University of Maryland, Baltimore, MD.

Factor VII (FVII) is an important component of the coagulation cascade. Few genetic loci regulating FVII activity and/or levels have been discovered to date. We conducted a meta-analysis of 9 genome-wide association studies of plasma FVII levels (7 FVII activity and 2 FVII antigen) among 27 495 participants of European and African ancestry. Each study performed ancestry-specific association analyses. Inverse variance weighted meta-analysis was performed within each ancestry group and then combined for a -ancestry meta-analysis. Our primary analysis included the 7 studies that measured FVII activity, and a secondary analysis included all 9 studies. We provided functional genomic validation for newly identified significant loci by silencing candidate genes in a human liver cell line (HuH7) using small-interfering RNA and then measuring messenger RNA and FVII protein expression. Lastly, we used meta-analysis results to perform Mendelian randomization analysis to estimate the causal effect of FVII activity on coronary artery disease, ischemic stroke (IS), and venous thromboembolism. We identified 2 novel ( and ) and 6 known loci associated with FVII activity, explaining 19.0% of the phenotypic variance. Adding FVII antigen data to the meta-analysis did not result in the discovery of further loci. Silencing in HuH7 cells upregulated FVII, whereas silencing downregulated FVII. Mendelian randomization analyses suggest that FVII activity has a positive causal effect on the risk of IS. Variants at and contribute to FVII activity by regulating expression levels. FVII activity appears to contribute to the etiology of IS in the general population.
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http://dx.doi.org/10.1182/blood-2018-05-849240DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6396174PMC
February 2019

Genetics of the thrombomodulin-endothelial cell protein C receptor system and the risk of early-onset ischemic stroke.

PLoS One 2018 1;13(11):e0206554. Epub 2018 Nov 1.

University of Adelaide, Adelaide, Australia.

Background And Purpose: Polymorphisms in coagulation genes have been associated with early-onset ischemic stroke. Here we pursue an a priori hypothesis that genetic variation in the endothelial-based receptors of the thrombomodulin-protein C system (THBD and PROCR) may similarly be associated with early-onset ischemic stroke. We explored this hypothesis utilizing a multi-stage design of discovery and replication.

Methods: Discovery was performed in the Genetics-of-Early-Onset Stroke (GEOS) Study, a biracial population-based case-control study of ischemic stroke among men and women aged 15-49 including 829 cases of first ischemic stroke (42.2% African-American) and 850 age-comparable stroke-free controls (38.1% African-American). Twenty-four single-nucleotide-polymorphisms (SNPs) in THBD and 22 SNPs in PROCR were evaluated. Following LD pruning (r2≥0.8), we advanced uncorrelated SNPs forward for association analyses. Associated SNPs were evaluated for replication in an early-onset ischemic stroke population (onset-age<60 years) consisting of 3676 cases and 21118 non-stroke controls from 6 case-control studies. Lastly, we determined if the replicated SNPs also associated with older-onset ischemic stroke in the METASTROKE data-base.

Results: Among GEOS Caucasians, PROCR rs9574, which was in strong LD with 8 other SNPs, and one additional independent SNP rs2069951, were significantly associated with ischemic stroke (rs9574, OR = 1.33, p = 0.003; rs2069951, OR = 1.80, p = 0.006) using an additive-model adjusting for age, gender and population-structure. Adjusting for risk factors did not change the associations; however, associations were strengthened among those without risk factors. PROCR rs9574 also associated with early-onset ischemic stroke in the replication sample (OR = 1.08, p = 0.015), but not older-onset stroke. There were no PROCR associations in African-Americans, nor were there any THBD associations in either ethnicity.

Conclusion: PROCR polymorphisms are associated with early-onset ischemic stroke in Caucasians.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0206554PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6211695PMC
April 2019

Cerebral Cortical Microinfarcts on Magnetic Resonance Imaging and Their Association With Cognition in Cerebral Amyloid Angiopathy.

Stroke 2018 10;49(10):2330-2336

From the Department of Neurology, Massachusetts General Hospital Stroke Research Center, Harvard Medical School, Boston (L.X., S.J.v.V., N.B., A.C., M.P., A.-K.G., P.F., G.R., K.S., E.M.G., A.B., S.M.G., A.V.).

Background and Purpose- We aimed to explore the association between presence of cerebral cortical microinfarcts (CMIs) on magnetic resonance imaging and other small-vessel disease neuroimaging biomarkers in cerebral amyloid angiopathy (CAA) and to analyze the role of CMIs on individual cognitive domains and dementia conversion. Methods- Participants were recruited from an ongoing longitudinal research cohort of eligible CAA patients between March 2006 and October 2016. A total of 102 cases were included in the analysis that assessed the relationship of cortical CMIs to CAA neuroimaging markers. Ninety-five subjects had neuropsychological tests conducted within 1 month of magnetic resonance imaging scanning. Seventy-five nondemented CAA patients had cognitive evaluation data available during follow-up. Results- Among 102 patients enrolled, 40 patients had CMIs (39%) on magnetic resonance imaging. CMIs were uniformly distributed throughout the cortex without regional predilection ( P=0.971). The presence of CMIs was associated with lower total brain volume (odds ratio, 0.85; 95% CI, 0.74-0.98; P=0.025) and presence of cortical superficial siderosis (odds ratio, 2.66; 95% CI, 1.10-6.39; P=0.029). In 95 subjects with neuropsychological tests, presence of CMIs was associated with impaired executive function (β, -0.23; 95% CI, -0.44 to -0.02; P=0.036) and processing speed (β, -0.24; 95% CI, -0.45 to -0.04; P=0.020). Patients with CMIs had a higher cumulative dementia incidence compared with patients without CMIs ( P=0.043), whereas only baseline total brain volume (hazard ratio, 0.76; 95% CI, 0.62-0.92; P=0.006) independently predicted dementia conversion. Conclusions- Magnetic resonance imaging-detected CMIs in CAA correlated with greater overall disease burden. The presence of CMIs was associated with worse cognitive performance, whereas only total brain atrophy independently predicted dementia conversion.
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http://dx.doi.org/10.1161/STROKEAHA.118.022280DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6209124PMC
October 2018

Journal Club: Florbetapir imaging in cerebral amyloid angiopathy-related hemorrhages.

Neurology 2018 09;91(12):574-577

From the Hemorrhagic Stroke Research Program, Department of Neurology, Massachusetts General Hospital Stroke Research Center, Harvard Medical School, Boston.

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http://dx.doi.org/10.1212/WNL.0000000000006195DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6161557PMC
September 2018

How to Organize a Journal Club for Fellows and Residents.

Stroke 2018 09;49(9):e283-e285

From the Department of Neurology, Massachusetts General Hospital Stroke Research Center, Harvard Medical School, Boston.

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http://dx.doi.org/10.1161/STROKEAHA.118.021728DOI Listing
September 2018

In search of a putative imaging biomarker for Fabry disease: Go with the flow?

Neurology 2018 04 21;90(16):721-722. Epub 2018 Mar 21.

From the J. Philip Kistler Stroke Research Center (A.-K.G., N.S.R.), Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston; and Program in Medical and Population Genetics (A.-K.G.), Broad Institute of MIT and Harvard, Cambridge, MA.

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http://dx.doi.org/10.1212/WNL.0000000000005320DOI Listing
April 2018

Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes.

Nat Genet 2018 04 12;50(4):524-537. Epub 2018 Mar 12.

Institute of Cardiovascular Research, Royal Holloway University of London, London, UK, and Ashford and St Peters Hospital, Surrey, UK.

Stroke has multiple etiologies, but the underlying genes and pathways are largely unknown. We conducted a multiancestry genome-wide-association meta-analysis in 521,612 individuals (67,162 cases and 454,450 controls) and discovered 22 new stroke risk loci, bringing the total to 32. We further found shared genetic variation with related vascular traits, including blood pressure, cardiac traits, and venous thromboembolism, at individual loci (n = 18), and using genetic risk scores and linkage-disequilibrium-score regression. Several loci exhibited distinct association and pleiotropy patterns for etiological stroke subtypes. Eleven new susceptibility loci indicate mechanisms not previously implicated in stroke pathophysiology, with prioritization of risk variants and genes accomplished through bioinformatics analyses using extensive functional datasets. Stroke risk loci were significantly enriched in drug targets for antithrombotic therapy.
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http://dx.doi.org/10.1038/s41588-018-0058-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5968830PMC
April 2018

Structural Integrity of Normal Appearing White Matter and Sex-Specific Outcomes After Acute Ischemic Stroke.

Stroke 2017 12 10;48(12):3387-3389. Epub 2017 Nov 10.

From the Department of Neurology, JPK Stroke Research Center, Massachusetts General Hospital and Harvard Medical School, Boston (M.R.E., O.W., P.C., A.-K.G., L.C., K.M.F., A.S.K., G.B., H.H.K., A.L., N.S.R.); Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology (O.W.) and Division of Neurocritical Care and Emergency Neurology, Department of Neurology and Center for Human Genetic Research (J.R.), Massachusetts General Hospital, Boston; and Department of Neurology, Rhode Island Hospital, Alpert Medical School of Brown University, Providence (K.L.F.).

Background And Purpose: Women have worse poststroke outcomes than men. We evaluated sex-specific clinical and neuroimaging characteristics of white matter in association with functional recovery after acute ischemic stroke.

Methods: We performed a retrospective analysis of acute ischemic stroke patients with admission brain MRI and 3- to 6-month modified Rankin Scale score. White matter hyperintensity and acute infarct volume were quantified on fluid-attenuated inversion recovery and diffusion tensor imaging MRI, respectively. Diffusivity anisotropy metrics were calculated in normal appearing white matter contralateral to the acute ischemia.

Results: Among 319 patients with acute ischemic stroke, women were older (68.0 versus 62.7 years; =0.004), had increased incidence of atrial fibrillation (21.4% versus 12.2%; =0.04), and lower rate of tobacco use (21.1% versus 35.9%; =0.03). There was no sex-specific difference in white matter hyperintensity volume, acute infarct volume, National Institutes of Health Stroke Scale, prestroke modified Rankin Scale score, or normal appearing white matter diffusivity anisotropy metrics. However, women were less likely to have an excellent outcome (modified Rankin Scale score <2: 49.6% versus 67.0%; =0.005). In logistic regression analysis, female sex and the interaction of sex with fractional anisotropy, radial diffusivity, and axial diffusivity were independent predictors of functional outcome.

Conclusions: Female sex is associated with decreased likelihood of excellent outcome after acute ischemic stroke. The correlation between markers of white matter integrity and functional outcomes in women, but not men, suggests a potential sex-specific mechanism.
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http://dx.doi.org/10.1161/STROKEAHA.117.019258DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5726524PMC
December 2017

White Matter Hyperintensity Volume and Outcome of Mechanical Thrombectomy With Stentriever in Acute Ischemic Stroke.

Stroke 2017 10 8;48(10):2892-2894. Epub 2017 Sep 8.

From the Department of Neurology, University of Miami Miller School of Medicine, FL (K.A.); and Department of Neurology, J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Harvard Medical School, Boston (T.L.M., K.D., A.-K.G., N.S.R.).

Background And Purpose: Finding of white matter hyperintensity (WMH) has been associated with an increased risk of parenchymal hematoma and poor clinical outcomes after mechanical thrombectomy using old-generation endovascular devices. Currently, no data exist with regard to the risk of mechanical thrombectomy using stentriever devices in patients with significant WMH. We hypothesized that WMH volume will not affect the hemorrhagic and clinical outcome in patients with acute ischemic stroke undergoing thrombectomy using new-generation devices.

Methods: A retrospective cohort of consecutive acute ischemic stroke patients >18-year-old receiving mechanical thrombectomy with stentriever devices at a single academic center was examined. WMH volume was assessed by a semiautomated volumetric analysis on T2 fluid attenuated inversion recovery-magnetic resonance imaging. Outcomes included the rate of any intracerebral hemorrhage, 90-day modified Rankin Score (mRS), the rate of good outcome (discharge mRS ≤2), and the rate of successful reperfusion (thrombolysis in cerebral ischemia score 2b or 3).

Results: Between June 2012 and December 2015, 56 patients with acute ischemic stroke met the study criteria. Median WMH volume was 6.76 cm (4.84-16.09 cm). Increasing WMH volume did not significantly affect the odds of good outcome (odds ratio [OR], 0.811; 95% confidence interval [CI], 0.456-1.442), intracerebral hemorrhage (OR, 1.055; 95% CI, 0.595-1.871), parenchymal hematoma (OR, 0.353; 95% CI, 0.061-2.057), successful recanalization (OR, 1.295; 95% CI, 0.704-2.383), or death (OR, 1.583; 95% CI, 0.84-2.98).

Conclusions: Mechanical thrombectomy using stentrievers seems to be safe in selected patients with acute ischemic stroke with large vessel occlusion, nonwithstanding the severity of WMH burden in this population. Larger prospective studies are warranted to validate these findings.
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http://dx.doi.org/10.1161/STROKEAHA.117.018653DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5659291PMC
October 2017
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