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Janssen E, de Leeuw FE. Progression in the Understanding of Cerebral Small Vessel Disease Regression. Neurology 2025; 104:e213391. [PMID: 39899784 DOI: 10.1212/wnl.0000000000213391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2024] [Accepted: 12/17/2024] [Indexed: 02/05/2025] Open
Affiliation(s)
- Esther Janssen
- From the Department of Neurology, Research Institute for Medical Innovation and Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, the Netherlands
| | - Frank-Erik de Leeuw
- From the Department of Neurology, Research Institute for Medical Innovation and Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, the Netherlands
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2
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Jochems ACC, Muñoz Maniega S, Clancy U, Arteaga-Reyes C, Jaime Garcia D, Chappell FM, Hamilton OKL, Backhouse EV, Barclay G, Jardine C, McIntyre D, Hamilton I, Sakka E, Valdés Hernández MDC, Wiseman S, Bastin ME, Stringer MS, Thrippleton M, Doubal F, Wardlaw JM. Longitudinal Cognitive Changes in Cerebral Small Vessel Disease: The Effect of White Matter Hyperintensity Regression and Progression. Neurology 2025; 104:e213323. [PMID: 39899790 PMCID: PMC11793922 DOI: 10.1212/wnl.0000000000213323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2024] [Accepted: 12/02/2024] [Indexed: 02/05/2025] Open
Abstract
BACKGROUND AND OBJECTIVES White matter hyperintensities (WMHs) are the commonest imaging marker of cerebral small vessel disease (SVD) and a major cause of cognitive decline and vascular dementia. WMHs typically accumulate over time, but recent studies show they can also regress, but potential clinical benefits have received little attention. We examined progressing, stable, and regressing WMH in people with stroke-related SVD and the effect on cognitive outcomes. METHODS We recruited patients with minor nondisabling ischemic stroke (modified Rankin score ≤2) from stroke services into our prospective longitudinal observational study. Participants underwent cognitive assessment and brain MRI within 3-month poststroke and 1 year later. We gathered information on vascular risk factors, stroke severity, global cognition (Montreal Cognitive Assessment [MoCA]), processing speed and executive functioning (Trail Making Test [TMT] A and B, and the B/A ratio with ratio ≥3 reflecting executive dysfunction), and the Letter Digit Substitution Test. We measured WMH volumes at baseline and 1 year and categorized net WMH volume change into quintiles: Q1 (most regression), Q3 (stable), and Q5 (most progression). We applied repeated-measures linear mixed models to analyze longitudinal WMH and cognitive changes, adjusting for age, sex, premorbid intelligence, stroke severity, disability, white matter structural integrity, and baseline WMH volume. RESULTS One hundred ninety-eight of 229 participants had WMH volumes available at both time-points. At baseline, the mean age was 67.5 years (SD = 10.9), with 33% female. Mean net WMH volume change per quintile was Q1 -1.79 mL (SD = 1.54), Q2 -0.27 mL (0.20), Q3 0.35 mL (0.18), Q4 1.43 mL (0.48), and Q5 5.31 mL (3.07). MoCA deteriorated the most in participants with most WMH progression (Q5) (estimated β -0.428 [95% CI -0.750 to -0.106]), compared with stable WMH (Q3), with no clear deterioration in those with most WMH regression (Q1). TMT B/A ratio improved in participants with most WMH regression (Q1; -0.385 [-0.758 to -0.012]). DISCUSSION WMH regression was associated with preserved global cognition and improved executive function, compared with stable WMH, while WMH progression was associated with global cognitive decline. Cognitive benefits of WMH regression suggest that WMH-affected tissue can recover, may explain variance in cognitive outcomes, offer an important intervention target, and should be assessed in other populations and longer follow-up times.
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Affiliation(s)
- Angela C C Jochems
- Centre for Clinical Brain Sciences, University of Edinburgh, United Kingdom
- UK Dementia Research Institute, University of Edinburgh, United Kingdom
| | - Susana Muñoz Maniega
- Centre for Clinical Brain Sciences, University of Edinburgh, United Kingdom
- UK Dementia Research Institute, University of Edinburgh, United Kingdom
| | - Una Clancy
- Centre for Clinical Brain Sciences, University of Edinburgh, United Kingdom
- UK Dementia Research Institute, University of Edinburgh, United Kingdom
| | - Carmen Arteaga-Reyes
- Centre for Clinical Brain Sciences, University of Edinburgh, United Kingdom
- UK Dementia Research Institute, University of Edinburgh, United Kingdom
| | - Daniela Jaime Garcia
- Centre for Clinical Brain Sciences, University of Edinburgh, United Kingdom
- UK Dementia Research Institute, University of Edinburgh, United Kingdom
| | - Francesca M Chappell
- Centre for Clinical Brain Sciences, University of Edinburgh, United Kingdom
- UK Dementia Research Institute, University of Edinburgh, United Kingdom
| | - Olivia K L Hamilton
- MRC/CSO Social and Public Health Sciences Unit, School of Health and Wellbeing, University of Glasgow, United Kingdom; and
| | - Ellen V Backhouse
- Centre for Clinical Brain Sciences, University of Edinburgh, United Kingdom
- UK Dementia Research Institute, University of Edinburgh, United Kingdom
| | - Gayle Barclay
- Edinburgh Imaging Facility, Royal Infirmary of Edinburgh, United Kingdom
| | - Charlotte Jardine
- Edinburgh Imaging Facility, Royal Infirmary of Edinburgh, United Kingdom
| | - Donna McIntyre
- Edinburgh Imaging Facility, Royal Infirmary of Edinburgh, United Kingdom
| | - Iona Hamilton
- Edinburgh Imaging Facility, Royal Infirmary of Edinburgh, United Kingdom
| | - Eleni Sakka
- Centre for Clinical Brain Sciences, University of Edinburgh, United Kingdom
| | - Maria Del C Valdés Hernández
- Centre for Clinical Brain Sciences, University of Edinburgh, United Kingdom
- UK Dementia Research Institute, University of Edinburgh, United Kingdom
| | - Stewart Wiseman
- Centre for Clinical Brain Sciences, University of Edinburgh, United Kingdom
- UK Dementia Research Institute, University of Edinburgh, United Kingdom
| | - Mark E Bastin
- Centre for Clinical Brain Sciences, University of Edinburgh, United Kingdom
| | - Michael S Stringer
- Centre for Clinical Brain Sciences, University of Edinburgh, United Kingdom
- UK Dementia Research Institute, University of Edinburgh, United Kingdom
| | - Michael Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, United Kingdom
- UK Dementia Research Institute, University of Edinburgh, United Kingdom
- Edinburgh Imaging Facility, Royal Infirmary of Edinburgh, United Kingdom
| | - Fergus Doubal
- Centre for Clinical Brain Sciences, University of Edinburgh, United Kingdom
- UK Dementia Research Institute, University of Edinburgh, United Kingdom
| | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences, University of Edinburgh, United Kingdom
- UK Dementia Research Institute, University of Edinburgh, United Kingdom
- Edinburgh Imaging Facility, Royal Infirmary of Edinburgh, United Kingdom
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Pappas C, Bauer CE, Zachariou V, Libecap TJ, Rodolpho B, Sudduth TL, Nelson PT, Jicha GA, Hartz AM, Shao X, Wang DJJ, Gold BT. Synergistic effects of plasma S100B and MRI measures of cerebrovascular disease on cognition in older adults. GeroScience 2025:10.1007/s11357-024-01498-1. [PMID: 39907937 DOI: 10.1007/s11357-024-01498-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2024] [Accepted: 12/19/2024] [Indexed: 02/06/2025] Open
Abstract
There is growing interest in studying vascular contributions to cognitive impairment and dementia (VCID) and developing biomarkers to identify at-risk individuals. A combination of biofluid and neuroimaging markers may better profile early stage VCID than individual measures. Here, we tested this possibility focusing on plasma levels of S100 calcium-binding protein B (S100B), which has been linked with blood-brain-barrier (BBB) integrity, and neuroimaging measures assessing BBB function (water exchange rate across the BBB (kw)) and cerebral small vessel disease (white matter hyperintensities (WMHs)). A total of 74 older adults without dementia had plasma samples collected and underwent cognitive assessment. A subsample had neuroimaging data including diffusion prepared pseudo-continuous arterial spin labeling (DP-pCASL) for assessment of BBB kw and T2-weighted fluid-attenuated inversion recovery (FLAIR) for quantification of WMHs. Results indicated that higher plasma S100B levels were associated with poorer episodic memory performance (β = - .031, SE = .008, p < .001). Moreover, significant interactions were observed between plasma S100B levels and parietal lobe BBB kw (interaction β = .095, SE = .042, p = .028) and between plasma S100B levels and deep WMH volume (interaction β = - .025, SE = .009, p = .007) for episodic memory. Individuals with the poorest memory performance showed both high plasma S100B and either low BBB kw in the parietal lobe or increased deep WMH burden. Taken together, our results provide support for the combined use of biofluid and neuroimaging markers in the study of VCID.
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Affiliation(s)
- Colleen Pappas
- Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY, 40536, USA
| | - Christopher E Bauer
- Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY, 40536, USA
| | - Valentinos Zachariou
- Department of Behavioral Science, College of Medicine, University of Kentucky, Lexington, KY, 40536, USA
| | - T J Libecap
- Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY, 40536, USA
| | - Beatriz Rodolpho
- Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY, 40536, USA
| | - Tiffany L Sudduth
- Sanders Brown Center On Aging, University of Kentucky, Lexington, KY, 40536, USA
| | - Peter T Nelson
- Sanders Brown Center On Aging, University of Kentucky, Lexington, KY, 40536, USA
- Department of Pathology and Laboratory Medicine, University of Kentucky, Lexington, KY, 40536, USA
| | - Gregory A Jicha
- Sanders Brown Center On Aging, University of Kentucky, Lexington, KY, 40536, USA
- Department of Neurology, University of Kentucky, Lexington, KY, 40536, USA
| | - Anika Ms Hartz
- Sanders Brown Center On Aging, University of Kentucky, Lexington, KY, 40536, USA
- Department of Pharmacology & Nutritional Sciences, University of Kentucky, Lexington, KY, 40536, USA
| | - Xingfeng Shao
- Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA
| | - Danny J J Wang
- Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA
| | - Brian T Gold
- Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY, 40536, USA.
- Sanders Brown Center On Aging, University of Kentucky, Lexington, KY, 40536, USA.
- Department of Radiology, College of Medicine, University of Kentucky, Lexington, KY, 40536, USA.
- Magnetic Resonance Imaging and Spectroscopy Center, University of Kentucky, Lexington, KY, 40536, USA.
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Xu Y, Huang D, Zhang H, Fang Q, Xia Y, Shi F, Gong X. White matter hyperintensities regress at a high rate at three months after minor ischemic stroke or transient ischemic attack. J Neuroradiol 2025; 52:101239. [PMID: 39798248 DOI: 10.1016/j.neurad.2024.101239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2024] [Revised: 12/06/2024] [Accepted: 12/16/2024] [Indexed: 01/15/2025]
Abstract
BACKGROUND The potential for early white matter hyperintensities(WMH) regression and associated contributory factors remains uncertain. The purpose of this study is to investigate whether WMH regress at early time of three months after minor ischemic stroke (MIS) or transient ischemic attack (TIA), while also identifying factors that may influence this outcome. METHODS A retrospective analysis of a prospective subcohort from the CHANCE trial comprising individuals with MIS and TIA was conducted. All patients underwent brain MRI at the onset and at three months. Deep learning algorithms were employed for the automatic segmentation of WMH volumes in four distinct regions. Scores for lacunes, cerebral microbleeds (CMB), perivascular spaces (PVS), WMH, and overall cerebral small vessel disease (CSVD) burden were quantified. Patients were divided into the stable, regression and progression groups according to change in WMH volume. The demographic, clinical, and imaging data of the participants in the three groups were collected and statistically analyzed. RESULTS A total of 98 patients with minor ischemic stroke or TIA were included. There were 22 patients in the stable group, 41 patients in the regression group and 35 patients in the progression group. Age and hypertension status were significantly different among the three groups. The lacunes, CMB,WMH, and total CSVD burden scores differed notably among groups, with all the CSVD markers being severely elevated in the progression group, moderately elevated in the regression group, and subtly elevated in the stable group. CONCLUSION The findings suggest that WMH could exhibit regression within three months following minor ischemic stroke or TIA. Patients under the age of 65, without a hypertension history, and with a low CSVD burden are more likely to experience WMH regression.
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Affiliation(s)
- Yuyun Xu
- Soochow Medical college of Soochow University, Suzhou, PR China; Center for Rehabilitation Medicine, Department of Radiology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang, PR China
| | - Danjiang Huang
- Taizhou First People's Hospital, Huangyan Hospital of Wenzhou Medical College, PR China
| | - He Zhang
- Taizhou First People's Hospital, Huangyan Hospital of Wenzhou Medical College, PR China
| | | | - Yuwei Xia
- Shanghai United Imaging Intelligence, Shanghai, PR China
| | - Feng Shi
- Shanghai United Imaging Intelligence, Shanghai, PR China
| | - Xiangyang Gong
- Soochow Medical college of Soochow University, Suzhou, PR China; Center for Rehabilitation Medicine, Department of Radiology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang, PR China.
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Bernal J, Menze I, Yakupov R, Peters O, Hellmann-Regen J, Freiesleben SD, Priller J, Spruth EJ, Altenstein S, Schneider A, Fliessbach K, Wiltfang J, Schott BH, Jessen F, Rostamzadeh A, Glanz W, Incesoy EI, Buerger K, Janowitz D, Ewers M, Perneczky R, Rauchmann BS, Teipel S, Kilimann I, Laske C, Sodenkamp S, Spottke A, Esser A, Lüsebrink F, Dechent P, Hetzer S, Scheffler K, Schreiber S, Düzel E, Ziegler G. Longitudinal evidence for a mutually reinforcing relationship between white matter hyperintensities and cortical thickness in cognitively unimpaired older adults. Alzheimers Res Ther 2024; 16:240. [PMID: 39465440 PMCID: PMC11520063 DOI: 10.1186/s13195-024-01606-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2024] [Accepted: 10/18/2024] [Indexed: 10/29/2024]
Abstract
BACKGROUND For over three decades, the concomitance of cortical neurodegeneration and white matter hyperintensities (WMH) has sparked discussions about their coupled temporal dynamics. Longitudinal studies supporting this hypothesis nonetheless remain scarce. METHODS We applied global and regional bivariate latent growth curve modelling to determine the extent to which WMH and cortical thickness were interrelated over a four-year period. For this purpose, we leveraged longitudinal MRI data from 451 cognitively unimpaired participants (DELCODE; median age 69.71 [IQR 65.51, 75.50] years; 52.32% female). Participants underwent MRI sessions annually over a four-year period (1815 sessions in total, with roughly four MRI sessions per participant). We adjusted all models for demographics and cardiovascular risk. RESULTS Our findings were three-fold. First, larger WMH volumes were linked to lower cortical thickness (σ = -0.165, SE = 0.047, Z = -3.515, P < 0.001). Second, individuals with higher WMH volumes experienced more rapid cortical thinning (σ = -0.226, SE = 0.093, Z = -2.443, P = 0.007), particularly in temporal, cingulate, and insular regions. Similarly, those with lower initial cortical thickness had faster WMH progression (σ = -0.141, SE = 0.060, Z = -2.336, P = 0.009), with this effect being most pronounced in temporal, cingulate, and insular cortices. Third, faster WMH progression was associated with accelerated cortical thinning (σ = -0.239, SE = 0.139, Z = -1.710, P = 0.044), particularly in frontal, occipital, and insular cortical regions. CONCLUSIONS Our study suggests that cortical thinning and WMH progression could be mutually reinforcing rather than parallel, unrelated processes, which become entangled before cognitive deficits are detectable. TRIAL REGISTRATION German Clinical Trials Register (DRKS00007966, 04/05/2015).
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Affiliation(s)
- Jose Bernal
- Institute of Cognitive Neurology and Dementia Research, Otto-Von-Guericke University Magdeburg, Magdeburg, Germany.
- German Centre for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.
- Centre for Clinical Brain Sciences, the University of Edinburgh, Edinburgh, UK.
- UK Dementia Research Institute Centre at the University of Edinburgh, Edinburgh, UK.
| | - Inga Menze
- Institute of Cognitive Neurology and Dementia Research, Otto-Von-Guericke University Magdeburg, Magdeburg, Germany
- German Centre for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Renat Yakupov
- Institute of Cognitive Neurology and Dementia Research, Otto-Von-Guericke University Magdeburg, Magdeburg, Germany
- German Centre for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Oliver Peters
- German Centre for Neurodegenerative Diseases (DZNE), Berlin, Germany
- Charité - Universitätsmedizin Berlin, Institute of Psychiatry and Psychotherapy, Berlin, Germany
| | - Julian Hellmann-Regen
- German Centre for Neurodegenerative Diseases (DZNE), Berlin, Germany
- Charité - Universitätsmedizin Berlin, Department of Psychiatry and Neurosciences, Campus Benjamin Franklin, Berlin, Germany
- German Centre for Mental Health (DZPG), Berlin, Germany
| | - Silka Dawn Freiesleben
- German Centre for Neurodegenerative Diseases (DZNE), Berlin, Germany
- Charité - Universitätsmedizin Berlin, Institute of Psychiatry and Psychotherapy, Berlin, Germany
| | - Josef Priller
- UK Dementia Research Institute Centre at the University of Edinburgh, Edinburgh, UK
- German Centre for Neurodegenerative Diseases (DZNE), Berlin, Germany
- Department of Psychiatry and Psychotherapy, Charité, Berlin, Germany
- School of Medicine, Department of Psychiatry and Psychotherapy, Technical University of Munich, Munich, Germany
| | - Eike Jakob Spruth
- German Centre for Neurodegenerative Diseases (DZNE), Berlin, Germany
- Department of Psychiatry and Psychotherapy, Charité, Berlin, Germany
| | - Slawek Altenstein
- German Centre for Neurodegenerative Diseases (DZNE), Berlin, Germany
- Department of Psychiatry and Psychotherapy, Charité, Berlin, Germany
| | - Anja Schneider
- German Centre for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Old Age Psychiatry and Cognitive Disorders, University Hospital Bonn and University of Bonn, Bonn, Germany
| | - Klaus Fliessbach
- German Centre for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Old Age Psychiatry and Cognitive Disorders, University Hospital Bonn and University of Bonn, Bonn, Germany
| | - Jens Wiltfang
- German Centre for Neurodegenerative Diseases (DZNE), Göttingen, Germany
- Department of Psychiatry and Psychotherapy, University Medical Centre Göttingen, University of Göttingen, Göttingen, Germany
- Neurosciences and Signalling Group, Institute of Biomedicine (iBiMED), Department of Medical Sciences, University of Aveiro, Aveiro, Portugal
| | - Björn H Schott
- German Centre for Neurodegenerative Diseases (DZNE), Göttingen, Germany
- Department of Psychiatry and Psychotherapy, University Medical Centre Göttingen, University of Göttingen, Göttingen, Germany
- Leibniz Institute for Neurobiology, Brenneckestr. 6, 39118, Magdeburg, Germany
| | - Frank Jessen
- German Centre for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Psychiatry, Medical Faculty, University of Cologne, Cologne, Germany
- Excellence Cluster On Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - Ayda Rostamzadeh
- Department of Psychiatry, Medical Faculty, University of Cologne, Cologne, Germany
| | - Wenzel Glanz
- German Centre for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Enise I Incesoy
- Institute of Cognitive Neurology and Dementia Research, Otto-Von-Guericke University Magdeburg, Magdeburg, Germany
- German Centre for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
- Department for Psychiatry and Psychotherapy, University Clinic Magdeburg, Magdeburg, Germany
| | - Katharina Buerger
- German Centre for Neurodegenerative Diseases (DZNE), Munich, Germany
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Daniel Janowitz
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Michael Ewers
- German Centre for Neurodegenerative Diseases (DZNE), Munich, Germany
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Robert Perneczky
- German Centre for Neurodegenerative Diseases (DZNE), Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy) Munich, Munich, Germany
- Ageing Epidemiology Research Unit (AGE), School of Public Health, Imperial College London, London, UK
| | - Boris-Stephan Rauchmann
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
- Department of Neuroradiology, University Hospital LMU, Munich, Germany
| | - Stefan Teipel
- German Centre for Neurodegenerative Diseases (DZNE), Rostock, Germany
- Department of Psychosomatic Medicine, Rostock University Medical Centre, Rostock, Germany
| | - Ingo Kilimann
- German Centre for Neurodegenerative Diseases (DZNE), Rostock, Germany
- Department of Psychosomatic Medicine, Rostock University Medical Centre, Rostock, Germany
| | - Christoph Laske
- German Centre for Neurodegenerative Diseases (DZNE), Tübingen, Germany
- Section for Dementia Research, Hertie Institute for Clinical Brain Research and Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Sebastian Sodenkamp
- German Centre for Neurodegenerative Diseases (DZNE), Tübingen, Germany
- Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Annika Spottke
- German Centre for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurology, University of Bonn, Bonn, Germany
| | - Anna Esser
- German Centre for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Falk Lüsebrink
- German Centre for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Peter Dechent
- Department of Cognitive Neurology, MR-Research in Neurosciences, Georg-August-University, Göttingen, Germany
| | - Stefan Hetzer
- Berlin Centre for Advanced Neuroimaging, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Klaus Scheffler
- Department for Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany
| | - Stefanie Schreiber
- German Centre for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
- Department of Neurology, University Hospital Magdeburg, Magdeburg, Germany
| | - Emrah Düzel
- Institute of Cognitive Neurology and Dementia Research, Otto-Von-Guericke University Magdeburg, Magdeburg, Germany
- German Centre for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Gabriel Ziegler
- Institute of Cognitive Neurology and Dementia Research, Otto-Von-Guericke University Magdeburg, Magdeburg, Germany
- German Centre for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
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Jochems ACC, Muñoz Maniega S, Clancy U, Arteaga Reyes C, Jaime Garcia D, Valdés Hernández MDC, Chappell FM, Barclay G, Jardine C, McIntyre D, Gerrish I, Wiseman S, Stringer MS, Thrippleton MJ, Doubal F, Wardlaw JM. Definitions of white matter hyperintensity change: impact on estimates of progression and regression. Stroke Vasc Neurol 2024:svn-2024-003300. [PMID: 39357898 DOI: 10.1136/svn-2024-003300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Accepted: 09/04/2024] [Indexed: 10/04/2024] Open
Abstract
BACKGROUND White matter hyperintensity (WMH) progression is well documented; WMH regression is more contentious, which might reflect differences in defining WMH change. We compared four existing WMH change definitions in one population to determine the effect of definition on WMH regression. METHODS We recruited patients with minor non-disabling ischaemic stroke who underwent MRI 1-3 months after stroke and 1 year later. We assessed WMH volume (in absolute mL and % intracranial volume) and applied four different definitions, including two thresholds (based on SD or mL), percentile and quintile approaches. RESULTS In 198 participants, mean age 65.5 (SD=11.13), baseline WMH volume was 15.46 mL (SD=19.2), the mean net WMH volume change was 0.98 mL (SD=2.84), range -7.98 to +12.84 mL. Proportion regressing/stable/progressing WMH were threshold 1 (SD), 29.8%/55.6%/14.6%; threshold 2(mL), 29.8%/16.7%/53.5%; percentile approach, 28.3%/21.2%/50.5%. The quintile approach includes five groups with quintile 3 reflecting no change (N=40), quintiles 1 and 2 any WMH decrease (N=80) and quintiles 4 and 5 any WMH increase (N=78). CONCLUSIONS Different WMH change definitions cause big differences in how participants are categorised; additionally, non-normal WMH distribution precludes use of some definitions. Consistent use of an appropriate definition would facilitate data comparisons, particularly in clinical trials of potential WMH treatments.
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Affiliation(s)
- Angela C C Jochems
- UK Dementia Research Institute at the University of Edinburgh, Edinburgh, UK
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Susana Muñoz Maniega
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
- The University of Edinburgh, Edinburgh Imaging Facility, Edinburgh, UK
| | - Una Clancy
- UK Dementia Research Institute at the University of Edinburgh, Edinburgh, UK
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Carmen Arteaga Reyes
- UK Dementia Research Institute at the University of Edinburgh, Edinburgh, UK
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Daniela Jaime Garcia
- UK Dementia Research Institute at the University of Edinburgh, Edinburgh, UK
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Maria Del C Valdés Hernández
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
- The University of Edinburgh, Edinburgh Imaging Facility, Edinburgh, UK
| | - Francesca M Chappell
- UK Dementia Research Institute at the University of Edinburgh, Edinburgh, UK
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Gayle Barclay
- The University of Edinburgh, Edinburgh Imaging Facility, Edinburgh, UK
| | - Charlotte Jardine
- The University of Edinburgh, Edinburgh Imaging Facility, Edinburgh, UK
| | - Donna McIntyre
- The University of Edinburgh, Edinburgh Imaging Facility, Edinburgh, UK
| | - Iona Gerrish
- The University of Edinburgh, Edinburgh Imaging Facility, Edinburgh, UK
| | - Stewart Wiseman
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
- The University of Edinburgh, Edinburgh Imaging Facility, Edinburgh, UK
| | - Michael S Stringer
- UK Dementia Research Institute at the University of Edinburgh, Edinburgh, UK
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Michael J Thrippleton
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
- The University of Edinburgh, Edinburgh Imaging Facility, Edinburgh, UK
| | - Fergus Doubal
- UK Dementia Research Institute at the University of Edinburgh, Edinburgh, UK
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Joanna M Wardlaw
- UK Dementia Research Institute at the University of Edinburgh, Edinburgh, UK
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
- The University of Edinburgh, Edinburgh Imaging Facility, Edinburgh, UK
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7
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Brito-Robinson T, Ayinuola YA, Ploplis VA, Castellino FJ. Plasminogen missense variants and their involvement in cardiovascular and inflammatory disease. Front Cardiovasc Med 2024; 11:1406953. [PMID: 38984351 PMCID: PMC11231438 DOI: 10.3389/fcvm.2024.1406953] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Accepted: 06/06/2024] [Indexed: 07/11/2024] Open
Abstract
Human plasminogen (PLG), the zymogen of the fibrinolytic protease, plasmin, is a polymorphic protein with two widely distributed codominant alleles, PLG/Asp453 and PLG/Asn453. About 15 other missense or non-synonymous single nucleotide polymorphisms (nsSNPs) of PLG show major, yet different, relative abundances in world populations. Although the existence of these relatively abundant allelic variants is generally acknowledged, they are often overlooked or assumed to be non-pathogenic. In fact, at least half of those major variants are classified as having conflicting pathogenicity, and it is unclear if they contribute to different molecular phenotypes. From those, PLG/K19E and PLG/A601T are examples of two relatively abundant PLG variants that have been associated with PLG deficiencies (PD), but their pathogenic mechanisms are unclear. On the other hand, approximately 50 rare and ultra-rare PLG missense variants have been reported to cause PD as homozygous or compound heterozygous variants, often leading to a debilitating disease known as ligneous conjunctivitis. The true abundance of PD-associated nsSNPs is unknown since they can remain undetected in heterozygous carriers. However, PD variants may also contribute to other diseases. Recently, the ultra-rare autosomal dominant PLG/K311E has been found to be causative of hereditary angioedema (HAE) with normal C1 inhibitor. Two other rare pathogenic PLG missense variants, PLG/R153G and PLG/V709E, appear to affect platelet function and lead to HAE, respectively. Herein, PLG missense variants that are abundant and/or clinically relevant due to association with disease are examined along with their world distribution. Proposed molecular mechanisms are discussed when known or can be reasonably assumed.
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Affiliation(s)
| | | | | | - Francis J. Castellino
- Department of Chemistry and Biochemistry and the W.M. Keck Center for Transgene Research, University of Notre Dame, Notre Dame, IN, United States
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Brown RB, Tozer DJ, Loubière L, Harshfield EL, Hong YT, Fryer TD, Williams GB, Graves MJ, Aigbirhio FI, O'Brien JT, Markus HS. MINocyclinE to Reduce inflammation and blood-brain barrier leakage in small Vessel diseAse (MINERVA): A phase II, randomized, double-blind, placebo-controlled experimental medicine trial. Alzheimers Dement 2024; 20:3852-3863. [PMID: 38629936 PMCID: PMC11180856 DOI: 10.1002/alz.13830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Revised: 02/13/2024] [Accepted: 03/16/2024] [Indexed: 06/18/2024]
Abstract
INTRODUCTION Cerebral small vessel disease (SVD) is a common cause of stroke/vascular dementia with few effective treatments. Neuroinflammation and increased blood-brain barrier (BBB) permeability may influence pathogenesis. In rodent models, minocycline reduced inflammation/BBB permeability. We determined whether minocycline had a similar effect in patients with SVD. METHODS MINERVA was a single-center, phase II, randomized, double-blind, placebo-controlled trial. Forty-four participants with moderate-to-severe SVD took minocycline or placebo for 3 months. Co-primary outcomes were microglial signal (determined using 11C-PK11195 positron emission tomography) and BBB permeability (using dynamic contrast-enhanced MRI). RESULTS Forty-four participants were recruited between September 2019 and June 2022. Minocycline had no effect on 11C-PK11195 binding (relative risk [RR] 1.01, 95% confidence interval [CI] 0.98-1.04), or BBB permeability (RR 0.97, 95% CI 0.91-1.03). Serum inflammatory markers were not affected. DISCUSSION 11C-PK11195 binding and increased BBB permeability are present in SVD; minocycline did not reduce either process. Whether these pathophysiological mechanisms are disease-causing remains unclear. INTERNATIONAL CLINICAL TRIALS REGISTRY PORTAL IDENTIFIER ISRCTN15483452 HIGHLIGHTS: We found focal areas of increased microglial signal and increased blood-brain barrier permeability in patients with small vessel disease. Minocycline treatment was not associated with a change in these processes measured using advanced neuroimaging. Blood-brain barrier permeability was dynamic but MRI-derived measurements correlated well with CSF/serum albumin ratio. Advanced neuroimaging is a feasible outcome measure for mechanistic clinical trials.
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Affiliation(s)
- Robin B. Brown
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
| | - Daniel J. Tozer
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
| | - Laurence Loubière
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
| | | | - Young T. Hong
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
- Wolfson Brain Imaging CentreUniversity of CambridgeCambridgeUK
| | - Tim D. Fryer
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
- Wolfson Brain Imaging CentreUniversity of CambridgeCambridgeUK
| | - Guy B. Williams
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
- Wolfson Brain Imaging CentreUniversity of CambridgeCambridgeUK
| | - Martin J. Graves
- Department of RadiologyUniversity of CambridgeCambridgeCambridgeUK
| | - Franklin I. Aigbirhio
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
- Wolfson Brain Imaging CentreUniversity of CambridgeCambridgeUK
| | | | - Hugh S. Markus
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
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Liu X, Wu N, Li J, Pang M, Wang Y, Wang Y, Jia S, Wang Y. Risk Factors and Clinical Characteristics of First-ever Ischemic Stroke Caused by ICAS with Leukoaraiosis. Int J Med Sci 2024; 21:1500-1510. [PMID: 38903919 PMCID: PMC11186426 DOI: 10.7150/ijms.95984] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Accepted: 05/16/2024] [Indexed: 06/22/2024] Open
Abstract
Background: Previous studies have mostly investigated the risk factors affecting the occurrence of leukoaraiosis and the risk factors affecting the severity of leukoaraiosis in patients with ischemic stroke, but there are relatively few studies on the risk factors and clinical characteristics affecting the severity of leukoaraiosis in the population with the most common type of first-episode ischemic stroke caused by intracranial atherosclerotic stenosis in China. Methods: We retrospectively studied patients with first-ever ischemic stroke due to intracranial atherosclerotic stenosis. All patients underwent diffusion weight magnetic resonance imaging and adjunctive examinations such as magnetic resonance angiography and/or computed tomography angiography and/or digital subtraction angiography. The characteristics and clinical data were also statistically analyzed. Results: Of the 504 patients enrolled, 176 (34.92%), 202 (40.08%), and 126 (25.00%) patients were in the mild, moderate, and severe groups, respectively, and the patients were older in the severe group compared with the moderate and mild groups (p < 0.05). Hypertension was more severe in the severe group compared with the severe and mild groups (p < 0.05). The time to hospital admission was shorter in the severe group compared with the moderate and mild groups (p < 0.05). The admission National Institutes of Health stroke scale was higher in the severe group than in the moderate and mild groups (p < 0.05). homocysteine, glucose, glycohemoglobin A1c, neutrophil-lymphocyte ratio, and ultrasensitive C-reactive protein to albumin ratio levels were significantly different between the three groups (p < 0.05). There was no significant correlation between the distribution of infarct foci in the anterior and posterior circulation in the three groups (p > 0.05). Conclusion: Age and homocysteine were independent risk factors for leukoaraiosis severity in patients with acute ischemic stroke, and all were positively associated with leukoaraiosis severity. Hypertension, glucose, glycohemoglobin A1c, neutrophil-lymphocyte ratio and ultrasensitive C-reactive protein to albumin ratio levels were highly significant in evaluating the prognosis of patients.
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Affiliation(s)
- Xiaopan Liu
- Department of Neurology II, Affiliated Hospital of Shandong Second Medical University, School of Clinical Medicine, Shandong Second Medical University, Weifang, China
| | - Ning Wu
- Ward 1, Department of Critical Care Medicine, Lin Yi Central Hospital, Lin Yi, Shandong, China
| | - Jian Li
- Department of Neurology II, Affiliated Hospital of Shandong Second Medical University, School of Clinical Medicine, Shandong Second Medical University, Weifang, China
| | - Meng Pang
- Department of Neurology II, Affiliated Hospital of Shandong Second Medical University, School of Clinical Medicine, Shandong Second Medical University, Weifang, China
| | - Yaozhen Wang
- Department of Neurology II, Affiliated Hospital of Shandong Second Medical University, School of Clinical Medicine, Shandong Second Medical University, Weifang, China
| | - Yuge Wang
- Department of Neurology, The Third Affiliated Hospital of SunYat-sen University, Guangzhou, China
| | - Shuai Jia
- Department of Neurology II, Affiliated Hospital of Shandong Second Medical University, School of Clinical Medicine, Shandong Second Medical University, Weifang, China
| | - Yanqiang Wang
- Department of Neurology II, Affiliated Hospital of Shandong Second Medical University, School of Clinical Medicine, Shandong Second Medical University, Weifang, China
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Jochems ACC, Muñoz Maniega S, Clancy U, Arteaga C, Jaime Garcia D, Chappell FM, Hewins W, Locherty R, Backhouse EV, Barclay G, Jardine C, McIntyre D, Gerrish I, Kampaite A, Sakka E, Valdés Hernández M, Wiseman S, Bastin ME, Stringer MS, Thrippleton MJ, Doubal FN, Wardlaw JM. Magnetic Resonance Imaging Tissue Signatures Associated With White Matter Changes Due to Sporadic Cerebral Small Vessel Disease Indicate That White Matter Hyperintensities Can Regress. J Am Heart Assoc 2024; 13:e032259. [PMID: 38293936 PMCID: PMC11056146 DOI: 10.1161/jaha.123.032259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 12/21/2023] [Indexed: 02/01/2024]
Abstract
BACKGROUND White matter hyperintensities (WMHs) might regress and progress contemporaneously, but we know little about underlying mechanisms. We examined WMH change and underlying quantitative magnetic resonance imaging tissue measures over 1 year in patients with minor ischemic stroke with sporadic cerebral small vessel disease. METHODS AND RESULTS We defined areas of stable normal-appearing white matter, stable WMHs, progressing and regressing WMHs based on baseline and 1-year brain magnetic resonance imaging. In these areas we assessed tissue characteristics with quantitative T1, fractional anisotropy (FA), mean diffusivity (MD), and neurite orientation dispersion and density imaging (baseline only). We compared tissue signatures cross-sectionally between areas, and longitudinally within each area. WMH change masks were available for N=197. Participants' mean age was 65.61 years (SD, 11.10), 59% had a lacunar infarct, and 68% were men. FA and MD were available for N=195, quantitative T1 for N=182, and neurite orientation dispersion and density imaging for N=174. Cross-sectionally, all 4 tissue classes differed for FA, MD, T1, and Neurite Density Index. Longitudinally, in regressing WMHs, FA increased with little change in MD and T1 (difference estimate, 0.011 [95% CI, 0.006-0.017]; -0.002 [95% CI, -0.008 to 0.003] and -0.003 [95% CI, -0.009 to 0.004]); in progressing and stable WMHs, FA decreased (-0.022 [95% CI, -0.027 to -0.017] and -0.009 [95% CI, -0.011 to -0.006]), whereas MD and T1 increased (progressing WMHs, 0.057 [95% CI, 0.050-0.063], 0.058 [95% CI, 0.050 -0.066]; stable WMHs, 0.054 [95% CI, 0.045-0.063], 0.049 [95% CI, 0.039-0.058]); and in stable normal-appearing white matter, MD increased (0.004 [95% CI, 0.003-0.005]), whereas FA and T1 slightly decreased and increased (-0.002 [95% CI, -0.004 to -0.000] and 0.005 [95% CI, 0.001-0.009]). CONCLUSIONS Quantitative magnetic resonance imaging shows that WMHs that regress have less abnormal microstructure at baseline than stable WMHs and follow trajectories indicating tissue improvement compared with stable and progressing WMHs.
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Affiliation(s)
- Angela C. C. Jochems
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Susana Muñoz Maniega
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Una Clancy
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Carmen Arteaga
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Daniela Jaime Garcia
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Francesca M. Chappell
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Will Hewins
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Rachel Locherty
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Ellen V. Backhouse
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Gayle Barclay
- Edinburgh Imaging Facility, Royal Infirmary of EdinburghEdinburghUnited Kingdom
| | - Charlotte Jardine
- Edinburgh Imaging Facility, Royal Infirmary of EdinburghEdinburghUnited Kingdom
| | - Donna McIntyre
- Edinburgh Imaging Facility, Royal Infirmary of EdinburghEdinburghUnited Kingdom
| | - Iona Gerrish
- Edinburgh Imaging Facility, Royal Infirmary of EdinburghEdinburghUnited Kingdom
| | - Agniete Kampaite
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
| | - Eleni Sakka
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
| | - Maria Valdés Hernández
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Stewart Wiseman
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Mark E. Bastin
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
| | - Michael S. Stringer
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Michael J. Thrippleton
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
- Edinburgh Imaging Facility, Royal Infirmary of EdinburghEdinburghUnited Kingdom
| | - Fergus N. Doubal
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Joanna M. Wardlaw
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
- Edinburgh Imaging Facility, Royal Infirmary of EdinburghEdinburghUnited Kingdom
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Markus HS. Cognition after stroke. Int J Stroke 2023; 18:884-887. [PMID: 37723654 DOI: 10.1177/17474930231196389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/20/2023]
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