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Duarte KTN, Sidhu AS, Barros MC, Gobbi DG, McCreary CR, Saad F, Camicioli R, Smith EE, Bento MP, Frayne R. Multi-stage semi-supervised learning enhances white matter hyperintensity segmentation. Front Comput Neurosci 2024; 18:1487877. [PMID: 39502452 PMCID: PMC11534601 DOI: 10.3389/fncom.2024.1487877] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2024] [Accepted: 09/30/2024] [Indexed: 11/08/2024] Open
Abstract
Introduction White matter hyperintensities (WMHs) are frequently observed on magnetic resonance (MR) images in older adults, commonly appearing as areas of high signal intensity on fluid-attenuated inversion recovery (FLAIR) MR scans. Elevated WMH volumes are associated with a greater risk of dementia and stroke, even after accounting for vascular risk factors. Manual segmentation, while considered the ground truth, is both labor-intensive and time-consuming, limiting the generation of annotated WMH datasets. Un-annotated data are relatively available; however, the requirement of annotated data poses a challenge for developing supervised machine learning models. Methods To address this challenge, we implemented a multi-stage semi-supervised learning (M3SL) approach that first uses un-annotated data segmented by traditional processing methods ("bronze" and "silver" quality data) and then uses a smaller number of "gold"-standard annotations for model refinement. The M3SL approach enabled fine-tuning of the model weights with the gold-standard annotations. This approach was integrated into the training of a U-Net model for WMH segmentation. We used data from three scanner vendors (over more than five scanners) and from both cognitively normal (CN) adult and patients cohorts [with mild cognitive impairment and Alzheimer's disease (AD)]. Results An analysis of WMH segmentation performance across both scanner and clinical stage (CN, MCI, AD) factors was conducted. We compared our results to both conventional and transfer-learning deep learning methods and observed better generalization with M3SL across different datasets. We evaluated several metrics (F-measure, IoU, and Hausdorff distance) and found significant improvements with our method compared to conventional (p < 0.001) and transfer-learning (p < 0.001). Discussion These findings suggest that automated, non-machine learning, tools have a role in a multi-stage learning framework and can reduce the impact of limited annotated data and, thus, enhance model performance.
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Affiliation(s)
- Kauê T. N. Duarte
- Departments of Radiology and Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Calgary Image Processing and Analysis Centre, Foothills Medical Centre, Calgary, AB, Canada
| | - Abhijot S. Sidhu
- Department of Biomedical Engineering, Schulich School of Engineering, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Seaman Family MR Research Centre, Foothills Medical Centre, Calgary, AB, Canada
| | - Murilo C. Barros
- School of Technology, University of Campinas, Limeira, São Paulo, Brazil
| | - David G. Gobbi
- Departments of Radiology and Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Calgary Image Processing and Analysis Centre, Foothills Medical Centre, Calgary, AB, Canada
| | - Cheryl R. McCreary
- Departments of Radiology and Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Seaman Family MR Research Centre, Foothills Medical Centre, Calgary, AB, Canada
| | - Feryal Saad
- Departments of Radiology and Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Richard Camicioli
- Department of Medicine (Neurology), University of Alberta, Edmonton, AB, Canada
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada
| | - Eric E. Smith
- Departments of Radiology and Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Mariana P. Bento
- Department of Biomedical Engineering, Schulich School of Engineering, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Richard Frayne
- Departments of Radiology and Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Calgary Image Processing and Analysis Centre, Foothills Medical Centre, Calgary, AB, Canada
- Department of Biomedical Engineering, Schulich School of Engineering, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Seaman Family MR Research Centre, Foothills Medical Centre, Calgary, AB, Canada
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Page D, Buchanan CR, Moodie JE, Harris MA, Taylor A, Valdés Hernández M, Muñoz Maniega S, Corley J, Bastin ME, Wardlaw JM, Russ TC, Deary IJ, Cox SR. Examining the neurostructural architecture of intelligence: The Lothian Birth Cohort 1936 study. Cortex 2024; 178:269-286. [PMID: 39067180 DOI: 10.1016/j.cortex.2024.06.007] [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: 08/30/2023] [Revised: 05/10/2024] [Accepted: 06/05/2024] [Indexed: 07/30/2024]
Abstract
Examining underlying neurostructural correlates of specific cognitive abilities is practically and theoretically complicated by the existence of the positive manifold (all cognitive tests positively correlate): if a brain structure is associated with a cognitive task, how much of this is uniquely related to the cognitive domain, and how much is due to covariance with all other tests across domains (captured by general cognitive functioning, also known as general intelligence, or 'g')? We quantitatively address this question by examining associations between brain structural and diffusion MRI measures (global tissue volumes, white matter hyperintensities, global white matter diffusion fractional anisotropy and mean diffusivity, and FreeSurfer processed vertex-wise cortical volumes, smoothed at 20mm fwhm) with g and cognitive domains (processing speed, crystallised ability, memory, visuospatial ability). The cognitive domains were modelled using confirmatory factor analysis to derive both hierarchical and bifactor solutions using 13 cognitive tests in 697 participants from the Lothian Birth Cohort 1936 study (mean age 72.5 years; SD = .7). Associations between the extracted cognitive factor scores for each domain and g were computed for each brain measure covarying for age, sex and intracranial volume, and corrected for false discovery rate. There were a range of significant associations between cognitive domains and global MRI brain structural measures (r range .008 to .269, p < .05). Regions implicated by vertex-wise regional cortical volume included a widespread number of medial and lateral areas of the frontal, temporal and parietal lobes. However, at both global and regional level, much of the domain-MRI associations were shared (statistically accounted for by g). Removing g-related variance from cognitive domains attenuated association magnitudes with global brain MRI measures by 27.9-59.7% (M = 46.2%), with only processing speed retaining all significant associations. At the regional cortical level, g appeared to account for the majority (range 22.1-88.4%; M = 52.8% across cognitive domains) of regional domain-specific associations. Crystallised and memory domains had almost no unique cortical correlates, whereas processing speed and visuospatial ability retained limited cortical volumetric associations. The greatest spatial overlaps across cognitive domains (as denoted by g) were present in the medial and lateral temporal, lateral parietal and lateral frontal areas.
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Affiliation(s)
- Danielle Page
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, UK
| | - Colin R Buchanan
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, UK
| | - Joanna E Moodie
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, UK
| | - Mathew A Harris
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, UK
| | - Adele Taylor
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, UK
| | - Maria Valdés Hernández
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, UK; Division of Neuroimaging Sciences and Row Fogo Centre for Small Vessel Diseases Research, Centre for Clinical Brain Sciences, University of Edinburgh, UK; UK Dementia Research Institute Centre at the University of Edinburgh, UK
| | - Susana Muñoz Maniega
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, UK; Division of Neuroimaging Sciences and Row Fogo Centre for Small Vessel Diseases Research, Centre for Clinical Brain Sciences, University of Edinburgh, UK; UK Dementia Research Institute Centre at the University of Edinburgh, UK
| | - Janie Corley
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, UK
| | - Mark E Bastin
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, UK
| | - Joanna M Wardlaw
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, UK; Division of Neuroimaging Sciences and Row Fogo Centre for Small Vessel Diseases Research, Centre for Clinical Brain Sciences, University of Edinburgh, UK; UK Dementia Research Institute Centre at the University of Edinburgh, UK
| | - Tom C Russ
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, UK; Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, UK; Alzheimer Scotland Dementia Research Centre, University of Edinburgh, UK
| | - Ian J Deary
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, UK
| | - Simon R Cox
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, UK.
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Youssef H, Demirer M, Middlebrooks EH, Anisetti B, Meschia JF, Lin MP. Framingham Stroke Risk Profile Score and White Matter Disease Progression. Neurologist 2024; 29:259-264. [PMID: 38867496 DOI: 10.1097/nrl.0000000000000567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2024]
Abstract
OBJECTIVES To evaluate the relationship between Framingham Stroke Risk Profile (FSRP) score and rate of white matter hyperintensity (WMH) progression and cognition. METHODS Consecutive patients enrolled in the Mayo Clinic Florida Familial Cerebrovascular Diseases Registry (2011-2020) with 2 brain-MRI scans at least 1 year apart were included. The primary outcome was annual change in WMH volume (cm 3 /year) stratified as fast versus slow (above vs. below median). Cognition was assessed using a Mini-Mental State Exam (MMSE, 0-30). FSRP score (0 to 8) was calculated by summing the presence of age 65 years or older, smoking, systolic blood pressure greater than 130 mmHg, diabetes, coronary disease, atrial fibrillation, left ventricular hypertrophy, and antihypertensive medication use. Linear and logistic regression analyses were performed to examine the association between FSRP and WMH progression, and cognition. RESULTS In all, 207 patients were included, with a mean age of 60±16 y and 54.6% female. FSRP scores risk distribution was: 31.9% scored 0 to 1, 36.7% scored 2 to 3, and 31.4% scored ≥4. The baseline WMH volume was 9.6 cm 3 (IQR: 3.3-28.4 cm 3 ), and the annual rate of WMH progression was 0.9 cm3/year (IQR: 0.1 to 3.1 cm 3 /year). A higher FSRP score was associated with fast WMH progression (odds ratio, 1.45; 95% CI: 1.22-1.72; P<0.001) and a lower MMSE score (23.6 vs. 27.1; P<0.001). There was a dose-dependent relationship between higher FSRP score and fast WMH progression (odds ratios, 2.20, 4.64, 7.86, 8.03 for FSRP scores 1, 2, 3, and ≥4, respectively; trend P <0.001). CONCLUSIONS This study demonstrated an association between higher FSRP scores and accelerated WMH progression, as well as lower cognition.
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Affiliation(s)
| | - Mutlu Demirer
- Department of Radiology, Mayo Clinic, Jacksonville, FL
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Rivier CA, Singh S, Senff J, Tack RW, Marini S, Clocchiatti-Tuozzo S, Huo S, Renedo D, Papier K, Conroy M, Littlejohns TJ, Chemali Z, Kourkoulis C, Payabvash S, Newhouse A, Westover MB, Lazar RM, Pikula A, Ibrahim S, Howard VJ, Howard G, Brouwers HB, Van Duijn CM, Fricchione G, Tanzi RE, Yechoor N, Sheth KN, Anderson CD, Rosand J, Falcone GJ. Brain Care Score and Neuroimaging Markers of Brain Health in Asymptomatic Middle-Age Persons. Neurology 2024; 103:e209687. [PMID: 39052961 DOI: 10.1212/wnl.0000000000209687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/27/2024] Open
Abstract
OBJECTIVES To investigate associations between health-related behaviors as measured using the Brain Care Score (BCS) and neuroimaging markers of white matter injury. METHODS This prospective cohort study in the UK Biobank assessed the BCS, a novel tool designed to empower patients to address 12 dementia and stroke risk factors. The BCS ranges from 0 to 21, with higher scores suggesting better brain care. Outcomes included white matter hyperintensities (WMH) volume, fractional anisotropy (FA), and mean diffusivity (MD) obtained during 2 imaging assessments, as well as their progression between assessments, using multivariable linear regression adjusted for age and sex. RESULTS We included 34,509 participants (average age 55 years, 53% female) with no stroke or dementia history. At first and repeat imaging assessments, every 5-point increase in baseline BCS was linked to significantly lower WMH volumes (25% 95% CI [23%-27%] first, 33% [27%-39%] repeat) and higher FA (18% [16%-20%] first, 22% [15%-28%] repeat), with a decrease in MD (9% [7%-11%] first, 10% [4%-16%] repeat). In addition, a higher baseline BCS was associated with a 10% [3%-17%] reduction in WMH progression and FA decline over time. DISCUSSION This study extends the impact of the BCS to neuroimaging markers of clinically silent cerebrovascular disease. Our results suggest that improving one's BCS could be a valuable intervention to prevent early brain health decline.
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Affiliation(s)
- Cyprien A Rivier
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Sanjula Singh
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Jasper Senff
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Reinier W Tack
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Sandro Marini
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Santiago Clocchiatti-Tuozzo
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Shufan Huo
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Daniela Renedo
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Keren Papier
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Megan Conroy
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Thomas J Littlejohns
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Zeina Chemali
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Christina Kourkoulis
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Seyedmehdi Payabvash
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Amy Newhouse
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - M Brandon Westover
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Ronald M Lazar
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Aleksandra Pikula
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Sarah Ibrahim
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Virginia J Howard
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - George Howard
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - H Bart Brouwers
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Cornelia M Van Duijn
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Gregory Fricchione
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Rudolph E Tanzi
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Nirupama Yechoor
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Kevin N Sheth
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Christopher D Anderson
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Jonathan Rosand
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Guido J Falcone
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
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Yang HJ, Song JM, Lee S, Lee HK, Kim BS, Kim KW, Park JH. The Different Associations of White Matter Hyperintensities With Severity of Dementia and Cognitive Impairment According to the Distance From the Lateral Ventricular Surface in Patients With Alzheimer's Disease. Psychiatry Investig 2024; 21:850-859. [PMID: 39111744 PMCID: PMC11321875 DOI: 10.30773/pi.2024.0082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Revised: 05/18/2024] [Accepted: 05/24/2024] [Indexed: 08/15/2024] Open
Abstract
OBJECTIVE White matter hyperintensities (WMH) are common among the elderly. Although WMH play a key role in lowering the threshold for the clinical expression of dementia in Alzheimer's disease (AD)-related pathology, the clinical significance of their location is not fully understood. This study aimed to investigate the association between WMH and cognitive function according to the location of WMH in AD. METHODS Subjects underwent clinical evaluations including volumetric brain magnetic resonance imaging study and neuropsychological tests using the Korean version of the Consortium to Establish a Registry for Alzheimer's Disease Assessment Packet. WMH were calculated using automated quantification method. According to the distance from the lateral ventricular surface, WMH within 3 mm, WMH within 3-13 mm, and WMH over 13 mm were classified as juxtaventricular WMH (JVWMH), periventricular WMH (PVWMH), and deep WMH (DWMH), respectively. RESULTS Total WMH volume was associated with poor performance in categorical verbal fluency test (β=-0.197, p=0.035). JVWMH volume was associated with poor performances on categorical verbal fluency test (β=-0.201, p=0.032) and forward digit span test (β= -0.250, p=0.012). PVWMH volume was associated with poor performances on categorical verbal fluency test (β=-0.185, p=0.042) and word list memory test (β=-0.165, p=0.042), whereas DWMH volume showed no association with cognitive tests. PVWMH volume were also related to Clinical Dementia Rating Scale Sum of Boxes score (β=0.180, p=0.026). CONCLUSION WMH appear to exhibit different associations with the severity of dementia and cognitive impairment according to the distance from ventricle surface in AD.
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Affiliation(s)
- Hyun Ju Yang
- Department of Psychiatry, Jeju National University School of Medicine, Jeju National University Hospital, Jeju Special Self-Governing Province, Jeju, Republic of Korea
| | - Jae Min Song
- Department of Psychiatry, Jeju Medical Center, Jeju Special Self-Governing Province, Jeju, Republic of Korea
| | - Subin Lee
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea
| | - Ho Kyu Lee
- Department of Radiology, Jeju National University, Jeju Special Self-Governing Province, Jeju, Republic of Korea
| | - Bong Soo Kim
- Department of Radiology, Jeju National University, Jeju Special Self-Governing Province, Jeju, Republic of Korea
| | - Ki Woong Kim
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
- Department of Brain and Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul, Republic of Korea
| | - Joon Hyuk Park
- Department of Psychiatry, Jeju National University School of Medicine, Jeju National University Hospital, Jeju Special Self-Governing Province, Jeju, Republic of Korea
- Jeju Dementia Center, Jeju Special Self-Governing Province, Jeju, Republic of Korea
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Chen Q, Wu B, Shi Z, Wang Y, Yuan Y, Chen X, Wang Y, Hu J, Mao L, Gao Y, Wu G. LncRNA H19 knockdown promotes neuropathologic and functional recovery via the Nrf2/HO-1 axis after traumatic brain injury. CNS Neurosci Ther 2024; 30:e14870. [PMID: 39049714 PMCID: PMC11269889 DOI: 10.1111/cns.14870] [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: 05/12/2024] [Revised: 07/07/2024] [Accepted: 07/08/2024] [Indexed: 07/27/2024] Open
Abstract
AIMS Traumatic brain injury (TBI) stands as a significant concern in public health, frequently leading to enduring neurological deficits. Long non-coding RNA H19 (lncRNA H19) exerts a potential regulator role in the pathology of brain injury. This study investigates the effects of lncRNA H19 knockdown (H19-KD) on the pathophysiology of TBI and its potential neuroprotective mechanisms. METHODS Controlled cortical impact was employed to establish a stable TBI mouse model. The expression levels of various genes in perilesional cortex and striatum tissue after TBI was detected by RT-qPCR. AAV9-shRNA-H19 was injected into the lateral ventricle of mice to knockdown the expression of lncRNA H19. Various behavioral tests were performed to evaluate sensorimotor and cognitive functions after TBI. Immunofluorescence and Nissl staining were performed to assess brain tissue damage and neuroinflammation. The Nrf2 and HO-1 expression was performed by Western blot. RESULTS After TBI, the expression of lncRNA H19 was elevated in perilesional tissue and gradually reverted to baseline. Behavioral tests demonstrated that H19-KD significantly promoted the recovery of sensorimotor and cognitive functions after TBI. Besides, H19-KD reduced brain tissue loss, preserved neuronal integrity, and ameliorated white matter damage at the histological level. In addition, H19-KD restrained the pro-inflammatory and facilitated anti-inflammatory phenotypes of microglia/macrophages, attenuating the neuroinflammatory response after TBI. Furthermore, H19-KD promoted activation of the Nrf2/HO-1 axis after TBI, while suppression of Nrf2 partially abolished the neuroprotective effect. CONCLUSION H19-KD exerts neuroprotective effects after TBI in mice, partially mediated by the activation of the Nrf2/HO-1 axis.
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Affiliation(s)
- Qiankang Chen
- Department of Neurosurgery of Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceInstitutes of Brain Science, Fudan UniversityShanghaiChina
| | - Biwu Wu
- Department of Neurosurgery of Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceInstitutes of Brain Science, Fudan UniversityShanghaiChina
| | - Ziyu Shi
- Department of Neurosurgery of Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceInstitutes of Brain Science, Fudan UniversityShanghaiChina
| | - Yana Wang
- Department of Neurosurgery of Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceInstitutes of Brain Science, Fudan UniversityShanghaiChina
| | - Yiwen Yuan
- Department of Neurosurgery of Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceInstitutes of Brain Science, Fudan UniversityShanghaiChina
| | - Xingdong Chen
- Department of Neurosurgery of Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceInstitutes of Brain Science, Fudan UniversityShanghaiChina
| | - Yuqing Wang
- Department of Neurosurgery of Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceInstitutes of Brain Science, Fudan UniversityShanghaiChina
| | - Jin Hu
- Department of Neurosurgery of Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceInstitutes of Brain Science, Fudan UniversityShanghaiChina
| | - Leilei Mao
- Department of Neurosurgery of Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceInstitutes of Brain Science, Fudan UniversityShanghaiChina
| | - Yanqin Gao
- Department of Neurosurgery of Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceInstitutes of Brain Science, Fudan UniversityShanghaiChina
| | - Gang Wu
- Department of Neurosurgery of Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceInstitutes of Brain Science, Fudan UniversityShanghaiChina
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Malla S, Bryant AG, Jayakumar R, Woost B, Wolf N, Li A, Das S, van Veluw SJ, Bennett RE. Molecular profiling of frontal and occipital subcortical white matter hyperintensities in Alzheimer's disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.13.598845. [PMID: 38915516 PMCID: PMC11195168 DOI: 10.1101/2024.06.13.598845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
White matter hyperintensities (WMHs) are commonly detected on T2-weighted magnetic resonance imaging (MRI) scans, occurring in both typical aging and Alzheimer's disease. Despite their frequent appearance and their association with cognitive decline, the molecular factors contributing to WMHs remain unclear. In this study, we investigated the transcriptomic profiles of two commonly affected brain regions with coincident AD pathology-frontal subcortical white matter (frontal-WM) and occipital subcortical white matter (occipital-WM)-and compared with age-matched healthy controls. Through RNA-sequencing in frontal- and occipital-WM bulk tissues, we identified an upregulation of genes associated with brain vasculature function in AD white matter. To further elucidate vasculature-specific transcriptomic features, we performed RNA-seq analysis on blood vessels isolated from these white matter regions, which revealed an upregulation of genes related to protein folding pathways. Finally, comparing gene expression profiles between AD individuals with high- versus low-WMH burden showed an increased expression of pathways associated with immune function. Taken together, our study characterizes the diverse molecular profiles of white matter changes in AD compared to normal aging and provides new mechanistic insights processes underlying AD-related WMHs.
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Affiliation(s)
- Sulochan Malla
- Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Annie G Bryant
- Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
- School of Physics, The University of Sydney, Sydney, Australia
| | - Rojashree Jayakumar
- Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
| | - Benjamin Woost
- Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
| | - Nina Wolf
- Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
| | - Andrew Li
- Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
| | - Sudeshna Das
- Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Susanne J van Veluw
- Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Rachel E Bennett
- Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
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Zhou T, Zhao J, Ma Y, He L, Ren Z, Yang K, Tang J, Liu J, Luo J, Zhang H. Association of cognitive impairment with the interaction between chronic kidney disease and depression: findings from NHANES 2011-2014. BMC Psychiatry 2024; 24:312. [PMID: 38658863 PMCID: PMC11044494 DOI: 10.1186/s12888-024-05769-1] [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: 07/30/2023] [Accepted: 04/16/2024] [Indexed: 04/26/2024] Open
Abstract
BACKGROUND Cognitive impairment (CoI), chronic kidney disease (CKD), and depression are prevalent among older adults and are interrelated, imposing a significant disease burden. This study evaluates the association of CKD and depression with CoI and explores their potential interactions. METHOD Data for this study were sourced from the 2011-2014 National Health and Nutritional Examination Survey (NHANES). Multiple binary logistic regression models assessed the relationship between CKD, depression, and CoI while controlling for confounders. The interactions were measured using the relative excess risk of interaction (RERI), the attributable proportion of interaction (AP), and the synergy index (S). RESULTS A total of 2,666 participants (weighted n = 49,251,515) were included in the study, of which 700 (16.00%) had CoI. After adjusting for confounding factors, the risk of CoI was higher in patients with CKD compared to non-CKD participants (odds ratio [OR] = 1.49, 95% confidence interval [CI]:1.12-1.99). The risk of CoI was significantly increased in patients with depression compared to those without (OR = 2.29, 95% CI: 1.73-3.03). Furthermore, there was a significant additive interaction between CKD and depression in terms of the increased risk of CoI (adjusted RERI = 2.01, [95% CI: 0.31-3.71], adjusted AP = 0.50 [95% CI: 0.25-0.75], adjusted S = 2.97 [95% CI: 1.27-6.92]). CONCLUSION CKD and depression synergistically affect CoI, particularly when moderate-to-severe depression co-occurs with CKD. Clinicians should be mindful of the combined impact on patients with CoI. Further research is needed to elucidate the underlying mechanisms and assess the effects specific to different CKD stages.
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Affiliation(s)
- Tong Zhou
- Department of Nephrology, Affiliated Hospital of North Sichuan Medical College, 1 Maoyuan Road, Nanchong city, Sichuan Province, 637000, China
| | - Jiayu Zhao
- Department of physician, Nanchong Psychosomatic Hospital, Nanchong, China
| | - Yimei Ma
- Department of Nephrology, Affiliated Hospital of North Sichuan Medical College, 1 Maoyuan Road, Nanchong city, Sichuan Province, 637000, China
| | - Linqian He
- Department of Nephrology, Affiliated Hospital of North Sichuan Medical College, 1 Maoyuan Road, Nanchong city, Sichuan Province, 637000, China
| | - Zhouting Ren
- Department of Nephrology, Affiliated Hospital of North Sichuan Medical College, 1 Maoyuan Road, Nanchong city, Sichuan Province, 637000, China
| | - Kun Yang
- Department of Nephrology, Affiliated Hospital of North Sichuan Medical College, 1 Maoyuan Road, Nanchong city, Sichuan Province, 637000, China
| | - Jincheng Tang
- Department of Nephrology, Affiliated Hospital of North Sichuan Medical College, 1 Maoyuan Road, Nanchong city, Sichuan Province, 637000, China
| | - Jiali Liu
- Department of Clinical Medicine, North Sichuan Medical University, Nanchong, China
| | - Jiaming Luo
- Mental Health Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
- School of Psychiatry, North Sichuan Medical College, Nanchong, China
| | - Heping Zhang
- Department of Nephrology, Affiliated Hospital of North Sichuan Medical College, 1 Maoyuan Road, Nanchong city, Sichuan Province, 637000, China.
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Liampas I, Siokas V, Zoupa E, Kyriakoulopoulou P, Stamati P, Provatas A, Tsouris Z, Tsimourtou V, Lyketsos CG, Dardiotis E. Neuropsychiatric symptoms and white matter hyperintensities in older adults without dementia. Int Psychogeriatr 2024:1-13. [PMID: 38639110 PMCID: PMC11489321 DOI: 10.1017/s1041610224000607] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/20/2024]
Abstract
OBJECTIVE We aimed to examine associations between neuropsychiatric symptoms (NPS) and white matter hyperintensities (WMH) status in older adults without dementia under the hypothesis that WMH increased the odds of having NPS. DESIGN Longitudinal analysis of data acquired from the National Alzheimer's Coordinating Center Uniform Data Set. SETTINGS Data were derived from 46 National Institute on Aging - funded Alzheimer's Disease Research Centers. PARTICIPANTS NACC participants aged ≥50 years with available data on WMH severity with a diagnosis of mild cognitive impairment (MCI) or who were cognitively unimpaired (CU) were studied. Among 4617 CU participants, 376 had moderate and 54 extensive WMH. Among 3170 participants with MCI, 471 had moderate and 88 had extensive WMH. MEASUREMENTS Using Cardiovascular Health Study (CHS) scores, WMH were coded as no to mild (CHS score: 0-4), moderate (score: 5-6) or extensive (score: 7-8). NPS were quantified on the Neuropsychiatric Inventory Questionnaire. Binary logistic regression models estimated the odds of reporting each of 12 NPS by WMH status separately for individuals with MCI or who were CU. RESULTS Compared to CU individuals with no to mild WMH, the odds of having elation [9.87, (2.63-37.10)], disinhibition [4.42, (1.28-15.32)], agitation [3.51, (1.29-9.54)] or anxiety [2.74, (1.28-5.88)] were higher for the extensive WMH group, whereas the odds of having disinhibition were higher for the moderate WMH group [1.94, (1.05-3.61)]. In the MCI group, he odds of NPS did not vary by WMH status. CONCLUSIONS Extensive WMH were associated with higher odds of NPS in CU older adults but not in those with MCI.
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Affiliation(s)
- Ioannis Liampas
- Department of Neurology, University Hospital of Larissa, School of Medicine, University of Thessaly, Larissa 41100, Greece
| | - Vasileios Siokas
- Department of Neurology, University Hospital of Larissa, School of Medicine, University of Thessaly, Larissa 41100, Greece
| | - Elli Zoupa
- Larisa Day Care Center of People with Alzheimer’s Disease, Association for Regional Development and Mental Health (EPAPSY), 15124 Marousi, Greece
| | | | - Polyxeni Stamati
- Department of Neurology, University Hospital of Larissa, School of Medicine, University of Thessaly, Larissa 41100, Greece
| | - Antonios Provatas
- Department of Neurology, University Hospital of Larissa, School of Medicine, University of Thessaly, Larissa 41100, Greece
| | - Zisis Tsouris
- Department of Neurology, University Hospital of Larissa, School of Medicine, University of Thessaly, Larissa 41100, Greece
| | - Vana Tsimourtou
- Department of Neurology, University Hospital of Larissa, School of Medicine, University of Thessaly, Larissa 41100, Greece
| | - Constantine G. Lyketsos
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
| | - Efthimios Dardiotis
- Department of Neurology, University Hospital of Larissa, School of Medicine, University of Thessaly, Larissa 41100, Greece
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
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Kushwaha A, Basera DS, Kumari S, Sutar RF, Singh V, Das S, Agrawal A. Assessment of memory deficits in psychiatric disorders: A systematic literature review. J Neurosci Rural Pract 2024; 15:182-193. [PMID: 38746499 PMCID: PMC11090569 DOI: 10.25259/jnrp_456_2023] [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: 08/17/2023] [Accepted: 12/12/2023] [Indexed: 05/16/2024] Open
Abstract
Memory deficits are observed across psychiatric disorders ranging from the prodrome of psychosis to common mental disorders such as anxiety, depression, and dissociative disorders. Memory deficits among patients recovering from psychiatric disorders could be directly related to the primary illness or secondary to the adverse effect of a treatment such as Electroconvulsive Therapy (ECT). The trouble in the meaningful integration of working-memory and episodic memory is the most commonly affected domain that requires routine assessments. An update on the recent trends of methods of assessment of memory deficits is the first step towards understanding and correcting these deficits to target optimum recovery. A systematic literature search was conducted from October 2018 to October 2022 to review the recent methods of assessment of memory deficits in psychiatric disorders. The definition of 'Memory deficit' was operationalized as 'selective processes of memory, commonly required for activities of daily living, and affected among psychiatric disorders resulting in subjective distress and dysfunction'. We included 110 studies, most of them being conducted in western countries on patients with schizophrenia. Other disorders included dementia and mild cognitive impairment. Brief Assessment of Cognition in Schizophrenia, Cambridge Automated Neuropsychological Test Battery, California Verbal Learning Test, Trail Making Test Part A and B, Rey Auditory Verbal Learning Test, Wechsler Memory Scale, Wechsler Adults Intelligence Scale-IV were the most common neuropsychological assessments used. Mini-Mental State Examination and Montreal Cognitive Assessment were the most common bedside assessment tools used while Squire Subjective Memory Questionnaire was commonly used to measure ECT-related memory deficits. The review highlights the recent developments in the field of assessment of memory deficits in psychiatric disorders. Findings recommend and emphasize routine assessment of memory deficits among psychiatric disorders in developing countries especially severe mental illnesses. It remains interesting to see the role of standardized assessments in diagnostic systems given more than a decade of research on memory deficits in psychiatric disorders.
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Affiliation(s)
- Anuradha Kushwaha
- Department of Psychiatry, All India Institute of Medical Sciences, Bhopal, Madhya Pradesh, India
| | - Devendra Singh Basera
- Department of Psychiatry, All India Institute of Medical Sciences, Bhopal, Madhya Pradesh, India
| | - Sangita Kumari
- Department of Psychiatry, All India Institute of Medical Sciences, Bhopal, Madhya Pradesh, India
| | - Roshan Fakirchand Sutar
- Department of Psychiatry, All India Institute of Medical Sciences, Bhopal, Madhya Pradesh, India
| | - Vijender Singh
- Department of Psychiatry, All India Institute of Medical Sciences, Bhopal, Madhya Pradesh, India
| | - Saikat Das
- Department of Radiotherapy, All India Institute of Medical Sciences, Bhopal, Madhya Pradesh, India
| | - Amit Agrawal
- Department of Neurosurgery, All India Institute of Medical Sciences, Bhopal, Madhya Pradesh, India
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Levy SA, Misiura MB, Grant JG, Adrien TV, Taiwo Z, Armstrong R, Dotson VM. Depression, Vascular Burden, and Dementia Prevalence in Late Middle-Aged and Older Black Adults. J Gerontol B Psychol Sci Soc Sci 2024; 79:gbae009. [PMID: 38374692 PMCID: PMC10926943 DOI: 10.1093/geronb/gbae009] [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: 06/20/2023] [Indexed: 02/21/2024] Open
Abstract
OBJECTIVES Late-life depression and white matter hyperintensities (WMH) have been linked to increased dementia risk. However, there is a dearth of literature examining these relationships in Black adults. We investigated whether depression or WMH volume are associated with a higher likelihood of dementia diagnosis in a sample of late middle-aged to older Black adults, and whether dementia prevalence is highest in individuals with both depression and higher WMH volume. METHODS Secondary data analysis involved 443 Black participants aged 55+ with brain imaging within 1 year of baseline visit in the National Alzheimer's Coordinating Center Uniform Data Set. Chi-square analyses and logistic regression models controlling for demographic variables examined whether active depression in the past 2 years, WMH volume, or their combination were associated with higher odds of all-cause dementia. RESULTS Depression and higher WMH volume were associated with a higher prevalence of dementia. These associations remained after controlling for demographic factors, as well as vascular disease burden. Dementia risk was highest in the depression/high WMH volume group compared to the depression-only group, high WMH volume-only group, and the no depression/low WMH volume group. Post hoc analyses comparing the Black sample to a demographically matched non-Hispanic White sample showed associations of depression and the combination of depression and higher WMH burden with dementia were greater in Black compared to non-Hispanic White individuals. DISCUSSION Results suggest late-life depression and WMH have independent and joint relationships with dementia and that Black individuals may be particularly at risk due to these factors.
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Affiliation(s)
- Shellie-Anne Levy
- Department of Clinical and Health Psychology, The Center for Cognitive Aging and Memory, University of Florida, Gainesville, Florida, USA
- The Center for Cognitive Aging and Memory, University of Florida, Gainesville, Florida, USA
| | - Maria B Misiura
- Department of Psychology, Georgia State University, Atlanta, Georgia, USA
| | - Jeremy G Grant
- Department of Clinical and Health Psychology, The Center for Cognitive Aging and Memory, University of Florida, Gainesville, Florida, USA
| | - Tamare V Adrien
- Department of Clinical and Health Psychology, The Center for Cognitive Aging and Memory, University of Florida, Gainesville, Florida, USA
| | - Zinat Taiwo
- Department of Rehabilitation Psychology and Neuropsychology, TIRR Memorial Hermann, Houston, Texas, USA
- H. Ben Taub Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, Texas, USA
| | - Rebecca Armstrong
- Department of Clinical and Health Psychology, The Center for Cognitive Aging and Memory, University of Florida, Gainesville, Florida, USA
| | - Vonetta M Dotson
- Department of Psychology, Georgia State University, Atlanta, Georgia, USA
- Gerontology Institute, Georgia State University, Atlanta, Georgia, USA
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12
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Holmqvist SL, Jobson K, Desalme D, Simone SM, Tassoni M, McKniff M, Yamaguchi T, Olson I, Martin N, Giovannetti T. Preliminary validation of the Virtual Kitchen Challenge as an objective and sensitive measure of everyday function associated with cerebrovascular disease. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2024; 16:e12547. [PMID: 38318469 PMCID: PMC10840367 DOI: 10.1002/dad2.12547] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 12/27/2023] [Accepted: 01/12/2024] [Indexed: 02/07/2024]
Abstract
Preliminary validity of a computer-based test of everyday function (Virtual Kitchen Challenge [VKC]) was examined against brain-imaging markers of cerebrovascular disease and in contrast to conventional neuropsychological and self-report measures. Twenty community-dwelling older adults (n = 6 mild cognitive impairment) performed simulated breakfast and lunch tasks using a computer touchscreen (VKC). Automated measures (completion time, proportion time off screen, etc.) were computed during training and test conditions. White matter hyperintensity (WMH) volumes from brain magnetic resonance imaging and conventional measures of cognition and function also were obtained. VKC completion time and proportion time off screen improved significantly from training to test and were significantly associated with WMH volume (r > 0.573). VKC measures and WMH were not significantly correlated with conventional cognitive or self-report measures. The VKC holds promise as a valid measure of subtle functional difficulties in older adults that is sensitive to change and cerebrovascular pathology, highlighting its potential for clinical trials. Highlights Virtual Kitchen Challenge (VKC) scores showed significant improvement from training to test conditions.VKC scores (completion time and proportion of time off screen) were associated with a neuroimaging biomarker of brain health (white matter hyperintensities).
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Affiliation(s)
- Sophia L. Holmqvist
- Department of Psychology and NeuroscienceTemple UniversityPhiladelphiaPennsylvaniaUSA
| | - Katie Jobson
- Department of Psychology and NeuroscienceTemple UniversityPhiladelphiaPennsylvaniaUSA
| | - Dennis Desalme
- Department of Communication Sciences and DisordersEleanor M. Saffran Center for Cognitive NeuroscienceTemple UniversityPhiladelphiaPennsylvaniaUSA
| | - Stephanie M. Simone
- Department of Psychology and NeuroscienceTemple UniversityPhiladelphiaPennsylvaniaUSA
| | - Molly Tassoni
- Department of Psychology and NeuroscienceTemple UniversityPhiladelphiaPennsylvaniaUSA
| | - Moira McKniff
- Department of Psychology and NeuroscienceTemple UniversityPhiladelphiaPennsylvaniaUSA
| | - Takehiko Yamaguchi
- Department of Applied Information EngineeringSuwa University of ScienceNaganoJapan
| | - Ingrid Olson
- Department of Psychology and NeuroscienceTemple UniversityPhiladelphiaPennsylvaniaUSA
| | - Nadine Martin
- Department of Communication Sciences and DisordersEleanor M. Saffran Center for Cognitive NeuroscienceTemple UniversityPhiladelphiaPennsylvaniaUSA
| | - Tania Giovannetti
- Department of Psychology and NeuroscienceTemple UniversityPhiladelphiaPennsylvaniaUSA
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13
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Nakase T, Thyreau B, Tatewaki Y, Tomita N, Takano Y, Muranaka M, Taki Y. Association between Gray and White Matter Lesions and Its Involvement in Clinical Symptoms of Alzheimer's-Type Dementia. J Clin Med 2023; 12:7642. [PMID: 38137710 PMCID: PMC10744158 DOI: 10.3390/jcm12247642] [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: 10/26/2023] [Revised: 12/04/2023] [Accepted: 12/09/2023] [Indexed: 12/24/2023] Open
Abstract
BACKGROUND Not only gray matter lesions (GMLs) but also white matter lesions (WMLs) can play important roles in the pathology of Alzheimer's disease (AD). The progression of cognitive impairment (CI) and behavioral and psychological symptoms of dementia (BPSD) might be caused by a concerted effect of both GML and WML. OBJECTIVE This study aimed to investigate the association between GML and WML and how they are involved in the symptoms of CI and BPSD in dementia patients by means of imaging technology. METHODS Patients in our memory clinic, who were diagnosed with AD-type dementia or amnestic mild cognitive impairment (aMCI) and had undergone both single-photon emission computed tomography (SPECT) and brain MRI, were consecutively enrolled (n = 156; 61 males and 95 females; 79.8 ± 7.4 years old). Symptoms of CI and BPSD were obtained from patients' medical records. For the analysis of GMLs and WMLs, SPECT data and MRI T1-weighted images were used, respectively. This study followed the Declaration of Helsinki, and all procedures were approved by the institutional ethics committee. RESULTS According to a multivariate analysis, disorientation and disturbed attention demonstrated a relationship between the precuneus and WMLs in both hemispheres. Hyperactivity in BPSD showed multiple correlations between GMLs on both sides of the frontal cortex and WMLs. Patients with aMCI presented more multiple correlations between GMLs and WMLs compared with those with AD-type dementia regarding dementia symptoms including BPSD. CONCLUSION The interaction between GMLs and WMLs may vary depending on the symptoms of CI and BPSD. Hyperactivity in BPSD may be affected by the functional relationship between GMLs and WMLs in the left and right hemispheres. The correlation between GMLs and WMLs may be changing in AD-type dementia and aMCI.
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Affiliation(s)
- Taizen Nakase
- Department of Aging Research & Geriatric Medicine, Institute of Development, Aging and Cancer, Tohoku University, Sendai 980-8575, Japan; (Y.T.); (N.T.); (Y.T.)
| | - Benjamin Thyreau
- Smart Aging Research Center, Tohoku University, Sendai 980-8575, Japan;
| | - Yasuko Tatewaki
- Department of Aging Research & Geriatric Medicine, Institute of Development, Aging and Cancer, Tohoku University, Sendai 980-8575, Japan; (Y.T.); (N.T.); (Y.T.)
| | - Naoki Tomita
- Department of Aging Research & Geriatric Medicine, Institute of Development, Aging and Cancer, Tohoku University, Sendai 980-8575, Japan; (Y.T.); (N.T.); (Y.T.)
| | - Yumi Takano
- Department of Aging Research & Geriatric Medicine, Institute of Development, Aging and Cancer, Tohoku University, Sendai 980-8575, Japan; (Y.T.); (N.T.); (Y.T.)
| | - Michiho Muranaka
- Department of Aging Research & Geriatric Medicine, Institute of Development, Aging and Cancer, Tohoku University, Sendai 980-8575, Japan; (Y.T.); (N.T.); (Y.T.)
| | - Yasuyuki Taki
- Department of Aging Research & Geriatric Medicine, Institute of Development, Aging and Cancer, Tohoku University, Sendai 980-8575, Japan; (Y.T.); (N.T.); (Y.T.)
- Smart Aging Research Center, Tohoku University, Sendai 980-8575, Japan;
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14
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Li Y, Kalpouzos G, Bäckman L, Qiu C, Laukka EJ. Association of white matter hyperintensity accumulation with domain-specific cognitive decline: a population-based cohort study. Neurobiol Aging 2023; 132:100-108. [PMID: 37776581 DOI: 10.1016/j.neurobiolaging.2023.08.011] [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: 02/12/2023] [Revised: 08/28/2023] [Accepted: 08/29/2023] [Indexed: 10/02/2023]
Abstract
We investigated the association of load and accumulation of white matter hyperintensities (WMHs) with rate of cognitive decline. This population-based study included 510 dementia-free people (age ≥60 years) who had repeated measures of global and regional (lobar, deep, periventricular) WMHs up to 6 years (from 2001-2003 to 2007-2010) and repeated measures of cognitive function (episodic memory, semantic memory, category fluency, letter fluency, executive function, perceptual speed) up to 15 years (from 2001-2004 to 2016-2019). We found that greater baseline loads of global and regional WMHs were associated with faster decline in letter fluency, perceptual speed, and global cognition. Furthermore, faster accumulation of global, deep, and periventricular WMHs was related to accelerated cognitive decline, primarily in perceptual speed. These data show that WMHs are associated with decline in perceptual speed rather than episodic or semantic memory and that cognitive change is more vulnerable to WMH accumulations in deep and periventricular regions.
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Affiliation(s)
- Yuanjing Li
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Grégoria Kalpouzos
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Lars Bäckman
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Chengxuan Qiu
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden.
| | - Erika J Laukka
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden; Stockholm Gerontology Research Center, Stockholm, Sweden.
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15
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Augusto-Oliveira M, Arrifano GP, Leal-Nazaré CG, Santos-Sacramento L, Lopes-Araújo A, Royes LFF, Crespo-Lopez ME. Exercise Reshapes the Brain: Molecular, Cellular, and Structural Changes Associated with Cognitive Improvements. Mol Neurobiol 2023; 60:6950-6974. [PMID: 37518829 DOI: 10.1007/s12035-023-03492-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 07/07/2023] [Indexed: 08/01/2023]
Abstract
Physical exercise is well known as a non-pharmacological and holistic therapy believed to prevent and mitigate numerous neurological conditions and alleviate ageing-related cognitive decline. To do so, exercise affects the central nervous system (CNS) at different levels. It changes brain physiology and structure, promoting cognitive improvements, which ultimately improves quality of life. Most of these effects are mediated by neurotrophins release, enhanced adult hippocampal neurogenesis, attenuation of neuroinflammation, modulation of cerebral blood flow, and structural reorganisation, besides to promote social interaction with beneficial cognitive outcomes. In this review, we discuss, based on experimental and human research, how exercise impacts the brain structure and function and how these changes contribute to cognitive improvements. Understanding the mechanisms by which exercise affects the brain is essential to understand the brain plasticity following exercise, guiding therapeutic approaches to improve the quality of life, especially in obesity, ageing, neurodegenerative disorders, and following traumatic brain injury.
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Affiliation(s)
- Marcus Augusto-Oliveira
- Laboratório de Farmacologia Molecular, Instituto de Ciências Biológicas, Universidade Federal Do Pará, Belém, PA, Brazil.
| | - Gabriela P Arrifano
- Laboratório de Farmacologia Molecular, Instituto de Ciências Biológicas, Universidade Federal Do Pará, Belém, PA, Brazil
| | - Caio G Leal-Nazaré
- Laboratório de Farmacologia Molecular, Instituto de Ciências Biológicas, Universidade Federal Do Pará, Belém, PA, Brazil
| | - Letícia Santos-Sacramento
- Laboratório de Farmacologia Molecular, Instituto de Ciências Biológicas, Universidade Federal Do Pará, Belém, PA, Brazil
| | - Amanda Lopes-Araújo
- Laboratório de Farmacologia Molecular, Instituto de Ciências Biológicas, Universidade Federal Do Pará, Belém, PA, Brazil
| | - Luiz Fernando Freire Royes
- Laboratório de Bioquímica Do Exercício, Centro de Educacão Física E Desportos, Universidade Federal de Santa Maria, Santa Maria, RGS, Brazil
| | - Maria Elena Crespo-Lopez
- Laboratório de Farmacologia Molecular, Instituto de Ciências Biológicas, Universidade Federal Do Pará, Belém, PA, Brazil.
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16
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Alosco ML, Tripodis Y, Baucom ZH, Adler CH, Balcer LJ, Bernick C, Mariani ML, Au R, Banks SJ, Barr WB, Wethe JV, Cantu RC, Coleman MJ, Dodick DW, McClean MD, McKee AC, Mez J, Palmisano JN, Martin B, Hartlage K, Lin AP, Koerte IK, Cummings JL, Reiman EM, Stern RA, Shenton ME, Bouix S. White matter hyperintensities in former American football players. Alzheimers Dement 2023; 19:1260-1273. [PMID: 35996231 PMCID: PMC10351916 DOI: 10.1002/alz.12779] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Revised: 06/24/2022] [Accepted: 07/27/2022] [Indexed: 11/11/2022]
Abstract
INTRODUCTION The presentation, risk factors, and etiologies of white matter hyperintensities (WMH) in people exposed to repetitive head impacts are unknown. We examined the burden and distribution of WMH, and their association with years of play, age of first exposure, and clinical function in former American football players. METHODS A total of 149 former football players and 53 asymptomatic unexposed participants (all men, 45-74 years) completed fluid-attenuated inversion recovery magnetic resonance imaging, neuropsychological testing, and self-report neuropsychiatric measures. Lesion Segmentation Toolbox estimated WMH. Analyses were performed in the total sample and stratified by age 60. RESULTS In older but not younger participants, former football players had greater total, frontal, temporal, and parietal log-WMH compared to asymptomatic unexposed men. In older but not younger former football players, greater log-WMH was associated with younger age of first exposure to football and worse executive function. DISCUSSION In older former football players, WMH may have unique presentations, risk factors, and etiologies. HIGHLIGHTS Older but not younger former football players had greater total, frontal, temporal, and parietal lobe white matter hyperintensities (WMH) compared to same-age asymptomatic unexposed men. Younger age of first exposure to football was associated with greater WMH in older but not younger former American football players. In former football players, greater WMH was associated with worse executive function and verbal memory.
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Affiliation(s)
- Michael L. Alosco
- Boston University Alzheimer’s Disease Research Center, Boston University CTE Center, Department of Neurology, Boston University School of Medicine, Boston, MA
| | - Yorghos Tripodis
- Boston University Alzheimer’s Disease Research Center, Boston University CTE Center, Boston University School of Medicine, Boston, MA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Zachary H. Baucom
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Charles H. Adler
- Department of Neurology, Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale, AZ
| | - Laura J. Balcer
- Departments of Neurology, Population Health and Ophthalmology, NYU Grossman School of Medicine, New York, NY
| | - Charles Bernick
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV
- Department of Neurology, University of Washington, Seattle, WA
| | - Megan L. Mariani
- Boston University Alzheimer’s Disease Research Center, Boston University CTE Center, Boston University School of Medicine, Boston, MA
| | - Rhoda Au
- Boston University Alzheimer’s Disease Research Center, Boston University CTE Center, Department of Neurology, Boston University School of Medicine, Boston, MA
- Framingham Heart Study, Framingham, MA
- Slone Epidemiology Center, Boston University, Boston, MA
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA
| | - Sarah J. Banks
- Departments of Neuroscience and Psychiatry, University of California, San Diego, CA
| | - William B. Barr
- Department of Neurology, NYU Grossman School of Medicine, New York, NY
| | - Jennifer V. Wethe
- Department of Psychiatry and Psychology, Mayo Clinic School of Medicine, Mayo Clinic Arizona, Scottsdale, AZ
| | - Robert C. Cantu
- Boston University Alzheimer’s Disease Research Center, Boston University CTE Center, Department of Neurology, Boston University School of Medicine, Boston, MA
| | - Michael J. Coleman
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Boston, MA
| | - David W. Dodick
- Department of Neurology, Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale, AZ
| | - Michael D. McClean
- Department of Environmental Health, Boston University School of Public Health, Boston, MA
| | - Ann C. McKee
- Boston University Alzheimer’s Disease Research Center, Boston University CTE Center, Department of Neurology, Boston University School of Medicine, Boston, MA
- VA Boston Healthcare System, Boston, MA
| | - Jesse Mez
- Boston University Alzheimer’s Disease Research Center, Boston University CTE Center, Department of Neurology, Boston University School of Medicine, Boston, MA
- Framingham Heart Study, Framingham, MA
| | - Joseph N. Palmisano
- Biostatistics and Epidemiology Data Analytics Center (BEDAC), Boston University School of Public Health, Boston, MA
| | - Brett Martin
- Biostatistics and Epidemiology Data Analytics Center (BEDAC), Boston University School of Public Health, Boston, MA
| | - Kaitlin Hartlage
- Biostatistics and Epidemiology Data Analytics Center (BEDAC), Boston University School of Public Health, Boston, MA
| | - Alexander P. Lin
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Boston, MA
- Center for Clinical Spectroscopy, Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - Inga K. Koerte
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Boston, MA
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwigs-Maximilians-Universität, Munich, Germany
| | - Jeffrey L. Cummings
- Chambers-Grundy Center for Transformative Neuroscience, Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas, Las Vegas, NV
| | - Eric M. Reiman
- Banner Alzheimer’s Institute, University of Arizona, Arizona State University, Translational Genomics Research Institute, and Arizona Alzheimer’s Consortium, Phoenix, AZ
| | - Robert A. Stern
- Boston University Alzheimer’s Disease Research Center, Boston University CTE Center, Department of Neurology, Boston University School of Medicine, Boston, MA
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA
- Department of Neurosurgery, Boston University School of Medicine, Boston, MA
| | - Martha E. Shenton
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Boston, MA
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - Sylvain Bouix
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Boston, MA
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17
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Eisenmenger LB, Peret A, Famakin BM, Spahic A, Roberts GS, Bockholt JH, Johnson KM, Paulsen JS. Vascular contributions to Alzheimer's disease. Transl Res 2023; 254:41-53. [PMID: 36529160 PMCID: PMC10481451 DOI: 10.1016/j.trsl.2022.12.003] [Citation(s) in RCA: 29] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 12/05/2022] [Accepted: 12/12/2022] [Indexed: 12/23/2022]
Abstract
Alzheimer's disease (AD) is the most common cause of dementia and is characterized by progressive neurodegeneration and cognitive decline. Understanding the pathophysiology underlying AD is paramount for the management of individuals at risk of and suffering from AD. The vascular hypothesis stipulates a relationship between cardiovascular disease and AD-related changes although the nature of this relationship remains unknown. In this review, we discuss several potential pathological pathways of vascular involvement in AD that have been described including dysregulation of neurovascular coupling, disruption of the blood brain barrier, and reduced clearance of metabolite waste such as beta-amyloid, a toxic peptide considered the hallmark of AD. We will also discuss the two-hit hypothesis which proposes a 2-step positive feedback loop in which microvascular insults precede the accumulation of Aß and are thought to be at the origin of the disease development. At neuroimaging, signs of vascular dysfunction such as chronic cerebral hypoperfusion have been demonstrated, appearing early in AD, even before cognitive decline and alteration of traditional biomarkers. Cerebral small vessel disease such as cerebral amyloid angiopathy, characterized by the aggregation of Aß in the vessel wall, is highly prevalent in vascular dementia and AD patients. Current data is unclear whether cardiovascular disease causes, precipitates, amplifies, precedes, or simply coincides with AD. Targeted imaging tools to quantitatively evaluate the intracranial vasculature and longitudinal studies in individuals at risk for or in the early stages of the AD continuum could be critical in disentangling this complex relationship between vascular disease and AD.
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Affiliation(s)
- Laura B Eisenmenger
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin
| | - Anthony Peret
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin
| | - Bolanle M Famakin
- Department of Neurology, University of Wisconsin-Madison, Madison, Wisconsin
| | - Alma Spahic
- Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin
| | - Grant S Roberts
- Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin
| | - Jeremy H Bockholt
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, Georgia
| | - Kevin M Johnson
- Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin
| | - Jane S Paulsen
- Department of Neurology, University of Wisconsin-Madison, Madison, Wisconsin.
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18
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Beltran-Najera I, Mustafa A, Warren D, Salling Z, Misiura M, Woods SP, Dotson VM. Elevated frequency and everyday functioning implications of vascular depression in persons with HIV disease. J Psychiatr Res 2023; 160:78-85. [PMID: 36780803 PMCID: PMC10123762 DOI: 10.1016/j.jpsychires.2023.02.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/23/2022] [Revised: 01/24/2023] [Accepted: 02/04/2023] [Indexed: 02/09/2023]
Abstract
Depression and cardiovascular disease are common and associated with one another in HIV disease. This study aimed to determine the frequency and everyday functioning implications of the clinical syndrome of vascular depression among people living with HIV (PLWH). Participants in this cross-sectional study included 536 PLWH and 272 seronegative individuals who completed a biomedical and psychiatric research evaluation. Vascular depression was operationalized as the current presence of: 1) two or more vascular conditions; and 2) depression as determined by a normative elevation on the Depression/Dejection subscale of the Profile of Mood States or a diagnosis of Major Depressive Disorder per the Composite International Diagnostic Interview. Everyday functioning was measured by both self- and clinician-rated activities of daily living. A logistic regression model showed that HIV was associated with a three-fold increased risk of vascular depression, independent of potential confounding factors. A second logistic regression model within the PLWH sample showed that PLWH with vascular depression had significantly greater odds of dependence in everyday functioning as compared to PLWH with either vascular disease or depression alone. The elevated frequency of vascular depression in PLWH is consistent with the vascular depression hypothesis from the late-life depression literature. The high rate of functional dependence among PLWH with vascular depression highlights the clinical importance of prospective work on this syndrome in the context of HIV disease.
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Affiliation(s)
- Ilex Beltran-Najera
- Department of Psychology, University of Houston, 126 Heyne Bldg., Houston, TX, 77204, USA
| | - Andrea Mustafa
- Department of Psychology, University of Houston, 126 Heyne Bldg., Houston, TX, 77204, USA
| | - Desmond Warren
- Department of Psychology, Georgia State University, P.O. Box 5010, Atlanta, GA, 30302, USA
| | - Zach Salling
- Department of Psychology, Georgia State University, P.O. Box 5010, Atlanta, GA, 30302, USA
| | - Maria Misiura
- Department of Psychology, Georgia State University, P.O. Box 5010, Atlanta, GA, 30302, USA
| | - Steven Paul Woods
- Department of Psychology, University of Houston, 126 Heyne Bldg., Houston, TX, 77204, USA
| | - Vonetta M Dotson
- Department of Psychology, Georgia State University, P.O. Box 5010, Atlanta, GA, 30302, USA; Gerontology Institute, Georgia State University, P.O. Box 3984, Atlanta, GA, 30302, USA.
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19
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Fu Y, Sun Y, Wang ZB, Zhang DD, Tan L, Feng JF, Cheng W, Yu JT. Associations of Life's Simple 7 with cerebral white matter hyperintensities and microstructural integrity: UK Biobank cohort study. Eur J Neurol 2023; 30:1200-1208. [PMID: 36794682 DOI: 10.1111/ene.15750] [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: 12/21/2022] [Revised: 01/26/2023] [Accepted: 02/13/2023] [Indexed: 02/17/2023]
Abstract
BACKGROUND AND PURPOSE The American Heart Association Life's Simple 7 (LS7) metric was used to define optimal cardiovascular and brain health, but the associations with macrostructural hyperintensities and microstructural white matter damage are unclear. The objective was to determine the association of LS7 ideal cardiovascular health factors with macrostructural and microstructural integrity. METHOD A total of 37,140 participants with available LS7 and imaging data from UK Biobank were included in this study. Linear associations were implemented to examine the associations of LS7 score and subscores with white matter hyperintensity load (WMH) (WMH volume normalized by total white matter volume and logit-transformed) and diffusion imaging indices (fractional anisotropy [FA], mean diffusivity, orientation dispersion index [OD], intracellular volume fraction, isotropic volume fraction [ISOVF]). RESULTS In individuals (mean age 54.76 years; 19,697 females, 52.4%), higher LS7 score and subscores were strongly associated with lower WMH and microstructural white matter injury, including OD, ISOVF, FA. Both interaction analyses and stratified analyses of LS7 score and subscores with age and sex showed a strong association with microstructural damage markers, with remarkable age and sex differences. The association of OD was pronounced in females and populations younger than 50 years and FA, mean diffusivity and ISOVF were pronounced in males and populations older than 50 years. CONCLUSION These findings suggest that healthier LS7 profiles are associated with better profiles of both macrostructural and microstructural markers of brain health, and indicate that ideal cardiovascular health is associated with improved brain health.
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Affiliation(s)
- Yan Fu
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Yan Sun
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Zhi-Bo Wang
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Dan-Dan Zhang
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Jian-Feng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), China.,Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China.,MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.,Zhangjiang Fudan International Innovation Center, Shanghai, China
| | - Wei Cheng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), China.,Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China.,Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
| | - Jin-Tai Yu
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
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20
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Roseborough AD, Saad L, Goodman M, Cipriano LE, Hachinski VC, Whitehead SN. White matter hyperintensities and longitudinal cognitive decline in cognitively normal populations and across diagnostic categories: A meta-analysis, systematic review, and recommendations for future study harmonization. Alzheimers Dement 2023; 19:194-207. [PMID: 35319162 DOI: 10.1002/alz.12642] [Citation(s) in RCA: 21] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Revised: 02/03/2022] [Accepted: 02/04/2022] [Indexed: 01/18/2023]
Abstract
INTRODUCTION The primary aim of this paper is to improve the clinical interpretation of white matter hyperintensities (WMHs) and provide an overarching summary of methodological approaches, allowing researchers to design future studies targeting current knowledge gaps. METHODS A meta-analysis and systematic review was performed investigating associations between baseline WMHs and longitudinal cognitive outcomes in cognitively normal populations, and populations with mild cognitive impairment (MCI), Alzheimer's disease (AD), and stroke. RESULTS Baseline WMHs increase the risk of cognitive impairment and dementia across diagnostic categories and most consistently in MCI and post-stroke populations. Apolipoprotein E (APOE) genotype and domain-specific cognitive changes relating to strategic anatomical locations, such as frontal WMH and executive decline, represent important considerations. Meta-analysis reliability was assessed using multiple methods of estimation, and results suggest that heterogeneity in study design and reporting remains a significant barrier. DISCUSSION Recommendations and future directions for study of WMHs are provided to improve cross-study comparison and translation of research into consistent clinical interpretation.
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Affiliation(s)
- Austyn D Roseborough
- Vulnerable Brain Laboratory, Department of Anatomy and Cell Biology, The Schulich School of Medicine & Dentistry, The University of Western Ontario, London, Ontario, Canada
| | - Lorenzo Saad
- Vulnerable Brain Laboratory, Department of Anatomy and Cell Biology, The Schulich School of Medicine & Dentistry, The University of Western Ontario, London, Ontario, Canada
| | - Maren Goodman
- Western Libraries, The University of Western Ontario, London, Ontario, Canada
| | - Lauren E Cipriano
- Ivey Business School and Department of Epidemiology and Biostatistics, The University of Western Ontario, London, Ontario, Canada
| | - Vladimir C Hachinski
- Department of Clinical Neurological Sciences, The Schulich School of Medicine & Dentistry, The University of Western Ontario, London, Ontario, Canada
| | - Shawn N Whitehead
- Vulnerable Brain Laboratory, Department of Anatomy and Cell Biology, The Schulich School of Medicine & Dentistry, The University of Western Ontario, London, Ontario, Canada
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21
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Fellows RP, Bangen KJ, Graves LV, Delano-Wood L, Bondi MW. Pathological functional impairment: Neuropsychological correlates of the shared variance between everyday functioning and brain volumetrics. Front Aging Neurosci 2022; 14:952145. [PMID: 36620766 PMCID: PMC9816390 DOI: 10.3389/fnagi.2022.952145] [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: 05/24/2022] [Accepted: 12/09/2022] [Indexed: 12/24/2022] Open
Abstract
Objective Given that several non-cognitive factors can contribute to difficulties with everyday functioning, examining the extent to which cognition is associated with brain-related changes in everyday functioning is critical to accurate characterization of cognitive disorders. In this study, we examined neuropsychological correlates of the shared variance between everyday functioning and pathological indicators of cognitive aging using MRI brain volumetrics. Participants and methods Participants were 600 adults aged 55 and older without dementia [432 cognitively normal; 168 mild cognitive impairment (MCI)] from the National Alzheimer's Coordinating Center cohort who underwent neuropsychological testing, informant-rated everyday functioning, and brain MRI scanning at baseline. The shared variance between everyday functioning and brain volumetrics (i.e., hippocampal volume, white matter hyperintensity volume) was extracted using the predicted value from multiple regression. The shared variance was used as an indicator of pathological everyday functional impairment. The residual variance from the regression analysis was used to examine functional reserve. Results Larger white matter hyperintensity volumes (p = 0.002) and smaller hippocampal volumes (p < 0.001) were significantly correlated with worse informant-rated everyday functioning. Among individuals with MCI, worse performances on delayed recall (p = 0.013) and category fluency (p = 0.012) were significantly correlated with pathological functional impairment in multiple regression analysis. In the cognitively normal group, only worse auditory working memory (i.e., digit span backward; p = 0.025) significantly correlated with pathological functioning. Functional reserve was inversely related to anxiety (p < 0.001) in the MCI group and was associated with depressive symptoms (p = 0.003) and apathy (p < 0.001) in the cognitively normal group. Conclusion Subtle brain-related everyday functioning difficulties are evident in MCI and track with expected preclinical Alzheimer's disease cognitive phenotypes in this largely amnestic sample. Our findings indicate that functional changes occur early in the disease process and that interventions to target neuropsychiatric symptoms may help to bolster functional reserve in those at risk.
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Affiliation(s)
- Robert P. Fellows
- Psychology Service, VA San Diego Healthcare System, San Diego, CA, United States,Department of Psychiatry, University of California, San Diego, San Diego, CA, United States,*Correspondence: Robert P. Fellows, ✉
| | - Katherine J. Bangen
- Department of Psychiatry, University of California, San Diego, San Diego, CA, United States,Research Service, VA San Diego Healthcare System, San Diego, CA, United States
| | - Lisa V. Graves
- Department of Psychology, California State University, San Marcos, CA, United States
| | - Lisa Delano-Wood
- Psychology Service, VA San Diego Healthcare System, San Diego, CA, United States,Department of Psychiatry, University of California, San Diego, San Diego, CA, United States
| | - Mark W. Bondi
- Psychology Service, VA San Diego Healthcare System, San Diego, CA, United States,Department of Psychiatry, University of California, San Diego, San Diego, CA, United States
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22
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Hairu R, Close JCT, Lord SR, Delbaere K, Wen W, Jiang J, Taylor ME. The association between white matter hyperintensity volume and cognitive/physical decline in older people with dementia: A one-year longitudinal study. Aging Ment Health 2022; 26:2503-2510. [PMID: 34569854 DOI: 10.1080/13607863.2021.1980859] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
OBJECTIVES Understanding the relationship between white matter hyperintensities (WMHs) and cognitive and physical decline in people with dementia will assist in determining potential treatment strategies. Currently there is conflicting evidence describing the association between WMHs and cognitive decline and, WMHs association with declines in objective measures of physical function have not been examined. We examined the relationship between baseline WMH volume and physical/cognitive decline over one-year in older people with dementia. METHODS Twenty-six community-dwelling older people with dementia (mean age = 81 ± 8 years; 35% female) were assessed at baseline and follow-up (one-year) using the Addenbrooke's Cognitive Examination-Revised (including verbal fluency), Trail Making Test A, the Physiological Profile Assessment (PPA), timed-up-and-go (TUG) and gait speed. WMH volumes were quantified using a fully automated segmentation toolbox, UBO Detector. RESULTS In analyses adjusted for baseline performance, higher baseline WMH volume was associated with decline in executive function (verbal fluency), sensorimotor function (PPA) and mobility (TUG). Executive function (semantic/category fluency) was the only domain association that withstood adjustment for age, and additionally hippocampal volume. CONCLUSIONS In unadjusted analyses, WMH volume was associated with one-year declines in cognitive and physical function in older people with dementia. The association with executive function decline withstood adjustment for age. More research is needed to confirm these findings and explore whether vascular risk reduction strategies can reduce WMH volume and associated cognitive and physical impairments in this group.
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Affiliation(s)
- Rismah Hairu
- Falls, Balance and Injury Research Centre, Neuroscience Research Australia, UNSW, Sydney, NSW, Australia.,Prince of Wales Clinical School, Medicine, UNSW, Sydney, NSW, Australia
| | - Jacqueline C T Close
- Falls, Balance and Injury Research Centre, Neuroscience Research Australia, UNSW, Sydney, NSW, Australia.,Prince of Wales Clinical School, Medicine, UNSW, Sydney, NSW, Australia
| | - Stephen R Lord
- Falls, Balance and Injury Research Centre, Neuroscience Research Australia, UNSW, Sydney, NSW, Australia.,School of Public Health and Community Medicine, Medicine, UNSW, Sydney, NSW, Australia
| | - Kim Delbaere
- Falls, Balance and Injury Research Centre, Neuroscience Research Australia, UNSW, Sydney, NSW, Australia.,School of Public Health and Community Medicine, Medicine, UNSW, Sydney, NSW, Australia
| | - Wei Wen
- Neuropsychiatric Institute, Prince of Wales Hospital, Randwick, NSW, Australia.,Centre for Healthy Brain Ageing, School of Psychiatry, Medicine, UNSW, Sydney, NSW, Australia
| | - Jiyang Jiang
- Neuropsychiatric Institute, Prince of Wales Hospital, Randwick, NSW, Australia.,Centre for Healthy Brain Ageing, School of Psychiatry, Medicine, UNSW, Sydney, NSW, Australia
| | - Morag E Taylor
- Falls, Balance and Injury Research Centre, Neuroscience Research Australia, UNSW, Sydney, NSW, Australia.,Prince of Wales Clinical School, Medicine, UNSW, Sydney, NSW, Australia
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23
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Chen J, Ge A, Zhou Y, Ma Y, Zhong S, Chen C, Shi W, Ding J, Wang X. White matter integrity mediates the associations between white matter hyperintensities and cognitive function in patients with silent cerebrovascular diseases. CNS Neurosci Ther 2022; 29:412-428. [PMID: 36415139 PMCID: PMC9804066 DOI: 10.1111/cns.14015] [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: 03/21/2022] [Revised: 10/18/2022] [Accepted: 10/19/2022] [Indexed: 11/24/2022] Open
Abstract
OBJECTIVE To evaluate the relationships between cognitive function and white matter hyperintensity volume (WMHV) in patients with silent cerebrovascular disease and to investigate whether white matter integrity or brain atrophy play a role in this association. METHODS Automated Fiber Quantification and Voxel- based morphometry were used to track and identify the integrity of 20 well-defined white matter tracts and to measure the gray matter volume (GMV). A linear regression model was applied for examining the associations between cognitive function and WMHV and mediation analysis was used to identify the roles of white matter integrity or GMV in the influence of WMHV on cognitive function. RESULTS Two hundred and thirty-six individuals were included for analysis. Executive function was linearly associated with fractional anisotropy (FA) of the right interior frontal occipital fasciculus (IFOF) (β = 0.193; 95% CI, 0.126 to 1.218) and with WMHV (β = -0.188; 95% CI, -0.372 to -0.037). Information processing speed was linearly associated with WMHV (β = -0.357; 95% CI, -0.643 to -0.245), FA of the right anterior thalamic radiation (ATR) (β = 0.207; 95% CI, 0.116 to 0.920), and FA of the left superior longitudinal fasciculus (SLF) (β = 0.177; 95% CI, 0.103 to 1.315). The relationship between WMHV and executive function was mediated by FA of the right IFOF (effect size = -0.045, 95% CI, -0.015 to -0.092). Parallel mediation analysis showed that the association between WMHV and information processing speed was mediated by FA of the right ATR (effect size = -0.099, 95% CI, -0.198 to -0.038) and FA of the left SLF (effect size = -0.038, 95% CI, -0.080 to -0.003). CONCLUSION These findings suggest a mechanism by which WMH affects executive function and information processing speed by impairing white matter integrity. This may be helpful in providing a theoretical basis for rehabilitation strategies of cognitive function in patients with silent cerebrovascular diseases.
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Affiliation(s)
- Jing Chen
- Department of Neurology, Zhongshan HospitalFudan UniversityShanghaiChina
| | - Anyan Ge
- Department of Neurology, Zhongshan HospitalFudan UniversityShanghaiChina
| | - Ying Zhou
- Department of Neurology, XiaMen Branch, Zhongshan HospitalFudan UniversityShanghaiChina
| | - Yuanyuan Ma
- Department of Neurology, Zhongshan HospitalFudan UniversityShanghaiChina
| | - Shaoping Zhong
- Department of Neurology, Zhongshan HospitalFudan UniversityShanghaiChina
| | - Caizhong Chen
- Department of Radiology, Zhongshan HospitalFudan UniversityShanghaiChina
| | - Weibin Shi
- Health Examination Center, Zhongshan HospitalFudan UniversityShanghaiChina
| | - Jing Ding
- Department of Neurology, Zhongshan HospitalFudan UniversityShanghaiChina
| | - Xin Wang
- Department of Neurology, Zhongshan HospitalFudan UniversityShanghaiChina,Department of the State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science,Institutes of Brain ScienceFudan UniversityShanghaiChina
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24
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Traub J, Otto M, Sell R, Göpfert D, Homola G, Steinacker P, Oeckl P, Morbach C, Frantz S, Pham M, Störk S, Stoll G, Frey A. Serum phosphorylated tau protein 181 and neurofilament light chain in cognitively impaired heart failure patients. Alzheimers Res Ther 2022; 14:149. [PMID: 36217177 PMCID: PMC9549648 DOI: 10.1186/s13195-022-01087-4] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Accepted: 09/22/2022] [Indexed: 11/05/2022]
Abstract
BACKGROUND Chronic heart failure (HF) is known to increase the risk of developing Alzheimer's dementia significantly. Thus, detecting and preventing mild cognitive impairment, which is common in patients with HF, is of great importance. Serum biomarkers are increasingly used in neurological disorders for diagnostics, monitoring, and prognostication of disease course. It remains unclear if neuronal biomarkers may help detect cognitive impairment in this high-risk population. Also, the influence of chronic HF and concomitant renal dysfunction on these biomarkers is not well understood. METHODS Within the monocentric Cognition.Matters-HF study, we quantified the serum levels of phosphorylated tau protein 181 (pTau) and neurofilament light chain (NfL) of 146 extensively phenotyped chronic heart failure patients (aged 32 to 85 years; 15.1% women) using ultrasensitive bead-based single-molecule immunoassays. The clinical work-up included advanced cognitive testing and cerebral magnetic resonance imaging (MRI). RESULTS Serum concentrations of NfL ranged from 5.4 to 215.0 pg/ml (median 26.4 pg/ml) and of pTau from 0.51 to 9.22 pg/ml (median 1.57 pg/ml). We detected mild cognitive impairment (i.e., T-score < 40 in at least one cognitive domain) in 60% of heart failure patients. pTau (p = 0.014), but not NfL, was elevated in this group. Both NfL (ρ = - 0.21; p = 0.013) and pTau (ρ = - 0.25; p = 0.002) related to the cognitive domain visual/verbal memory, as well as white matter hyperintensity volume and cerebral and hippocampal atrophy. In multivariable analysis, both biomarkers were independently influenced by age (T = 4.6 for pTau; T = 5.9 for NfL) and glomerular filtration rate (T = - 2.4 for pTau; T = - 3.4 for NfL). Markers of chronic heart failure, left atrial volume index (T = 4.6) and NT-proBNP (T = 2.8), were further cardiological determinants of pTau and NfL, respectively. In addition, pTau was also strongly affected by serum creatine kinase levels (T = 6.5) and ferritin (T = - 3.1). CONCLUSIONS pTau and NfL serum levels are strongly influenced by age-dependent renal and cardiac dysfunction. These findings point towards the need for longitudinal examinations and consideration of frequent comorbidities when using neuronal serum biomarkers.
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Affiliation(s)
- Jan Traub
- grid.411760.50000 0001 1378 7891Department of Internal Medicine I, University Hospital Würzburg, Oberdürrbacherstraße 6, 97080 Würzburg, Germany ,grid.411760.50000 0001 1378 7891Comprehensive Heart Failure Center, University and University Hospital Würzburg, Am Schwarzenberg 15, Würzburg, 97078 Germany
| | - Markus Otto
- grid.410712.10000 0004 0473 882XDepartment of Neurology, University Hospital Ulm, Ulm, Germany ,grid.461820.90000 0004 0390 1701Department of Neurology, University Hospital Halle-Wittenberg, Halle, Germany
| | - Roxane Sell
- grid.411760.50000 0001 1378 7891Department of Psychiatry, Psychosomatics and Psychotherapy, University Hospital Würzburg, Würzburg, Germany
| | - Dennis Göpfert
- grid.411760.50000 0001 1378 7891Department of Internal Medicine I, University Hospital Würzburg, Oberdürrbacherstraße 6, 97080 Würzburg, Germany
| | - György Homola
- grid.411760.50000 0001 1378 7891Comprehensive Heart Failure Center, University and University Hospital Würzburg, Am Schwarzenberg 15, Würzburg, 97078 Germany ,grid.411760.50000 0001 1378 7891Department of Neuroradiology, University Hospital Würzburg, Würzburg, Germany
| | - Petra Steinacker
- grid.410712.10000 0004 0473 882XDepartment of Neurology, University Hospital Ulm, Ulm, Germany ,grid.461820.90000 0004 0390 1701Department of Neurology, University Hospital Halle-Wittenberg, Halle, Germany
| | - Patrick Oeckl
- grid.410712.10000 0004 0473 882XDepartment of Neurology, University Hospital Ulm, Ulm, Germany ,grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE e.V.), Ulm, Germany
| | - Caroline Morbach
- grid.411760.50000 0001 1378 7891Department of Internal Medicine I, University Hospital Würzburg, Oberdürrbacherstraße 6, 97080 Würzburg, Germany ,grid.411760.50000 0001 1378 7891Comprehensive Heart Failure Center, University and University Hospital Würzburg, Am Schwarzenberg 15, Würzburg, 97078 Germany
| | - Stefan Frantz
- grid.411760.50000 0001 1378 7891Department of Internal Medicine I, University Hospital Würzburg, Oberdürrbacherstraße 6, 97080 Würzburg, Germany ,grid.411760.50000 0001 1378 7891Comprehensive Heart Failure Center, University and University Hospital Würzburg, Am Schwarzenberg 15, Würzburg, 97078 Germany
| | - Mirko Pham
- grid.411760.50000 0001 1378 7891Comprehensive Heart Failure Center, University and University Hospital Würzburg, Am Schwarzenberg 15, Würzburg, 97078 Germany ,grid.411760.50000 0001 1378 7891Department of Neuroradiology, University Hospital Würzburg, Würzburg, Germany
| | - Stefan Störk
- grid.411760.50000 0001 1378 7891Department of Internal Medicine I, University Hospital Würzburg, Oberdürrbacherstraße 6, 97080 Würzburg, Germany ,grid.411760.50000 0001 1378 7891Comprehensive Heart Failure Center, University and University Hospital Würzburg, Am Schwarzenberg 15, Würzburg, 97078 Germany
| | - Guido Stoll
- grid.411760.50000 0001 1378 7891Comprehensive Heart Failure Center, University and University Hospital Würzburg, Am Schwarzenberg 15, Würzburg, 97078 Germany ,grid.411760.50000 0001 1378 7891Department of Neurology, University Hospital Würzburg, Würzburg, Germany
| | - Anna Frey
- grid.411760.50000 0001 1378 7891Department of Internal Medicine I, University Hospital Würzburg, Oberdürrbacherstraße 6, 97080 Würzburg, Germany ,grid.411760.50000 0001 1378 7891Comprehensive Heart Failure Center, University and University Hospital Würzburg, Am Schwarzenberg 15, Würzburg, 97078 Germany
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25
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Neuropsychiatric symptoms are associated with exacerbated cognitive impairment in covert cerebral small vessel disease. J Int Neuropsychol Soc 2022; 29:431-438. [PMID: 36039945 DOI: 10.1017/s1355617722000480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
OBJECTIVES Neuropsychiatric symptoms are related to disease progression and cognitive decline over time in cerebral small vessel disease (SVD) but their significance is poorly understood in covert SVD. We investigated neuropsychiatric symptoms and their relationships between cognitive and functional abilities in subjects with varying degrees of white matter hyperintensities (WMH), but without clinical diagnosis of stroke, dementia or significant disability. METHODS The Helsinki Small Vessel Disease Study consisted of 152 subjects, who underwent brain magnetic resonance imaging (MRI) and comprehensive neuropsychological evaluation of global cognition, processing speed, executive functions, and memory. Neuropsychiatric symptoms were evaluated with the Neuropsychiatric Inventory Questionnaire (NPI-Q, n = 134) and functional abilities with the Amsterdam Instrumental Activities of Daily Living questionnaire (A-IADL, n = 132), both filled in by a close informant. RESULTS NPI-Q total score correlated significantly with WMH volume (rs = 0.20, p = 0.019) and inversely with A-IADL score (rs = -0.41, p < 0.001). In total, 38% of the subjects had one or more informant-evaluated neuropsychiatric symptom. Linear regressions adjusted for age, sex, and education revealed no direct associations between neuropsychiatric symptoms and cognitive performance. However, there were significant synergistic interactions between neuropsychiatric symptoms and WMH volume on cognitive outcomes. Neuropsychiatric symptoms were also associated with A-IADL score irrespective of WMH volume. CONCLUSIONS Neuropsychiatric symptoms are associated with an accelerated relationship between WMH and cognitive impairment. Furthermore, the presence of neuropsychiatric symptoms is related to worse functional abilities. Neuropsychiatric symptoms should be routinely assessed in covert SVD as they are related to worse cognitive and functional outcomes.
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26
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Tippett LJ, Cawston EE, Morgan CA, Melzer TR, Brickell KL, Ilse C, Cheung G, Kirk IJ, Roberts RP, Govender J, Griner L, Le Heron C, Buchanan S, Port W, Dudley M, Anderson TJ, Williams JM, Cutfield NJ, Dalrymple-Alford JC, Wood P. Dementia Prevention Research Clinic: a longitudinal study investigating factors influencing the development of Alzheimer's disease in Aotearoa, New Zealand. J R Soc N Z 2022; 53:489-510. [PMID: 39439970 PMCID: PMC11459802 DOI: 10.1080/03036758.2022.2098780] [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: 12/02/2021] [Accepted: 07/04/2022] [Indexed: 10/15/2022]
Abstract
Aotearoa New Zealand's population is ageing. Increasing life expectancy is accompanied by increases in prevalence of Alzheimer's Disease (AD) and ageing-related disorders. The multicentre Dementia Prevention Research Clinic longitudinal study aims to improve understanding of AD and dementia in Aotearoa, in order to develop interventions that delay or prevent progression to dementia. Comprising research clinics in Auckland, Christchurch and Dunedin, this multi-disciplinary study involves community participants who undergo biennial investigations informed by international protocols and best practice: clinical, neuropsychological, neuroimaging, lifestyle evaluations, APOE genotyping, blood collection and processing. A key research objective is to identify a 'biomarker signature' that predicts progression from mild cognitive impairment to AD. Candidate biomarkers include: blood proteins and microRNAs, genetic, neuroimaging and neuropsychological markers, health, cultural, lifestyle, sensory and psychosocial factors. We are examining a range of mechanisms underlying the progression of AD pathology (e.g. faulty blood-brain barrier, excess parenchymal iron, vascular dysregulation). This paper will outline key aspects of the Dementia Prevention Research Clinic's research, provide an overview of data collection, and a summary of 266 participants recruited to date. The national outreach of the clinics is a strength; the heart of the Dementia Prevention Research Clinics are its people.
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Affiliation(s)
- Lynette J. Tippett
- NZ-Dementia Prevention Research Clinic, New Zealand
- School of Psychology, University of Auckland, Auckland, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Erin E. Cawston
- NZ-Dementia Prevention Research Clinic, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Department of Pharmacology, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Catherine A. Morgan
- NZ-Dementia Prevention Research Clinic, New Zealand
- School of Psychology, University of Auckland, Auckland, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Tracy R. Melzer
- NZ-Dementia Prevention Research Clinic, New Zealand
- New Zealand Brain Research Institute, Christchurch, New Zealand
- Department of Medicine, University of Otago, Christchurch, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Kiri L. Brickell
- NZ-Dementia Prevention Research Clinic, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- School of Medicine, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Christina Ilse
- NZ-Dementia Prevention Research Clinic, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Gary Cheung
- NZ-Dementia Prevention Research Clinic, New Zealand
- Department of Psychological Medicine, School of Medicine, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Ian J. Kirk
- NZ-Dementia Prevention Research Clinic, New Zealand
- School of Psychology, University of Auckland, Auckland, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Reece P. Roberts
- NZ-Dementia Prevention Research Clinic, New Zealand
- School of Psychology, University of Auckland, Auckland, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Jane Govender
- NZ-Dementia Prevention Research Clinic, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Leon Griner
- NZ-Dementia Prevention Research Clinic, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Department of Pharmacology, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Campbell Le Heron
- NZ-Dementia Prevention Research Clinic, New Zealand
- New Zealand Brain Research Institute, Christchurch, New Zealand
- Department of Medicine, University of Otago, Christchurch, New Zealand
- Dept of Neurology, Canterbury District Health Board, Christchurch, New Zealand
| | - Sarah Buchanan
- NZ-Dementia Prevention Research Clinic, New Zealand
- Department of Neurology, Southern District Health Board, Dunedin, New Zealand
- Department of Medicine, University of Otago, Dunedin, New Zealand
| | - Waiora Port
- NZ-Dementia Prevention Research Clinic, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Makarena Dudley
- NZ-Dementia Prevention Research Clinic, New Zealand
- School of Psychology, University of Auckland, Auckland, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Tim J. Anderson
- NZ-Dementia Prevention Research Clinic, New Zealand
- New Zealand Brain Research Institute, Christchurch, New Zealand
- Department of Medicine, University of Otago, Christchurch, New Zealand
- Dept of Neurology, Canterbury District Health Board, Christchurch, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Joanna M. Williams
- NZ-Dementia Prevention Research Clinic, New Zealand
- Brain Health Research Centre, University of Otago, Dunedin, New Zealand
- Department of Anatomy, University of Otago, Dunedin, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Nicholas J. Cutfield
- NZ-Dementia Prevention Research Clinic, New Zealand
- Department of Neurology, Southern District Health Board, Dunedin, New Zealand
- Department of Medicine, University of Otago, Dunedin, New Zealand
- Brain Health Research Centre, University of Otago, Dunedin, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - John C. Dalrymple-Alford
- NZ-Dementia Prevention Research Clinic, New Zealand
- New Zealand Brain Research Institute, Christchurch, New Zealand
- School of Psychology, Speech and Hearing, University of Canterbury, Christchurch, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Phil Wood
- NZ-Dementia Prevention Research Clinic, New Zealand
- School of Medicine, University of Auckland, Auckland, New Zealand
- Ministry of Health, Wellington, New Zealand
- Department of Older Adults and Home Health, Waitemata District Health Board, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - the NZ-DPRC
- NZ-Dementia Prevention Research Clinic, New Zealand
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de Siqueira Mendes FDCC, de Almeida MNF, Falsoni M, Andrade MLF, Felício APG, da Paixão LTVB, Júnior FLDA, Anthony DC, Brites D, Diniz CWP, Sosthenes MCK. The Sedentary Lifestyle and Masticatory Dysfunction: Time to Review the Contribution to Age-Associated Cognitive Decline and Astrocyte Morphotypes in the Dentate Gyrus. Int J Mol Sci 2022; 23:ijms23116342. [PMID: 35683023 PMCID: PMC9180988 DOI: 10.3390/ijms23116342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 05/15/2022] [Accepted: 05/16/2022] [Indexed: 02/01/2023] Open
Abstract
As aging and cognitive decline progresses, the impact of a sedentary lifestyle on the appearance of environment-dependent cellular morphologies in the brain becomes more apparent. Sedentary living is also associated with poor oral health, which is known to correlate with the rate of cognitive decline. Here, we will review the evidence for the interplay between mastication and environmental enrichment and assess the impact of each on the structure of the brain. In previous studies, we explored the relationship between behavior and the morphological features of dentate gyrus glial fibrillary acidic protein (GFAP)-positive astrocytes during aging in contrasting environments and in the context of induced masticatory dysfunction. Hierarchical cluster and discriminant analysis of GFAP-positive astrocytes from the dentate gyrus molecular layer revealed that the proportion of AST1 (astrocyte arbors with greater complexity phenotype) and AST2 (lower complexity) are differentially affected by environment, aging and masticatory dysfunction, but the relationship is not straightforward. Here we re-evaluated our previous reconstructions by comparing dorsal and ventral astrocyte morphologies in the dentate gyrus, and we found that morphological complexity was the variable that contributed most to cluster formation across the experimental groups. In general, reducing masticatory activity increases astrocyte morphological complexity, and the effect is most marked in the ventral dentate gyrus, whereas the effect of environment was more marked in the dorsal dentate gyrus. All morphotypes retained their basic structural organization in intact tissue, suggesting that they are subtypes with a non-proliferative astrocyte profile. In summary, the increased complexity of astrocytes in situations where neuronal loss and behavioral deficits are present is counterintuitive, but highlights the need to better understand the role of the astrocyte in these conditions.
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Affiliation(s)
- Fabíola de Carvalho Chaves de Siqueira Mendes
- Laboratório de Investigações em Neurodegeneração e Infecção, Instituto de Ciências Biológicas, Hospital Universitário João de Barros Barreto, Universidade Federal do Pará, Belém 66073-005, PA, Brazil; (F.d.C.C.d.S.M.); (M.N.F.d.A.); (M.F.); (M.L.F.A.); (A.P.G.F.); (L.T.V.B.d.P.); (F.L.d.A.J.); (C.W.P.D.)
- Curso de Medicina, Centro Universitário do Estado do Pará, Belém 66613-903, PA, Brazil
| | - Marina Negrão Frota de Almeida
- Laboratório de Investigações em Neurodegeneração e Infecção, Instituto de Ciências Biológicas, Hospital Universitário João de Barros Barreto, Universidade Federal do Pará, Belém 66073-005, PA, Brazil; (F.d.C.C.d.S.M.); (M.N.F.d.A.); (M.F.); (M.L.F.A.); (A.P.G.F.); (L.T.V.B.d.P.); (F.L.d.A.J.); (C.W.P.D.)
| | - Manoela Falsoni
- Laboratório de Investigações em Neurodegeneração e Infecção, Instituto de Ciências Biológicas, Hospital Universitário João de Barros Barreto, Universidade Federal do Pará, Belém 66073-005, PA, Brazil; (F.d.C.C.d.S.M.); (M.N.F.d.A.); (M.F.); (M.L.F.A.); (A.P.G.F.); (L.T.V.B.d.P.); (F.L.d.A.J.); (C.W.P.D.)
| | - Marcia Lorena Ferreira Andrade
- Laboratório de Investigações em Neurodegeneração e Infecção, Instituto de Ciências Biológicas, Hospital Universitário João de Barros Barreto, Universidade Federal do Pará, Belém 66073-005, PA, Brazil; (F.d.C.C.d.S.M.); (M.N.F.d.A.); (M.F.); (M.L.F.A.); (A.P.G.F.); (L.T.V.B.d.P.); (F.L.d.A.J.); (C.W.P.D.)
| | - André Pinheiro Gurgel Felício
- Laboratório de Investigações em Neurodegeneração e Infecção, Instituto de Ciências Biológicas, Hospital Universitário João de Barros Barreto, Universidade Federal do Pará, Belém 66073-005, PA, Brazil; (F.d.C.C.d.S.M.); (M.N.F.d.A.); (M.F.); (M.L.F.A.); (A.P.G.F.); (L.T.V.B.d.P.); (F.L.d.A.J.); (C.W.P.D.)
| | - Luisa Taynah Vasconcelos Barbosa da Paixão
- Laboratório de Investigações em Neurodegeneração e Infecção, Instituto de Ciências Biológicas, Hospital Universitário João de Barros Barreto, Universidade Federal do Pará, Belém 66073-005, PA, Brazil; (F.d.C.C.d.S.M.); (M.N.F.d.A.); (M.F.); (M.L.F.A.); (A.P.G.F.); (L.T.V.B.d.P.); (F.L.d.A.J.); (C.W.P.D.)
| | - Fábio Leite do Amaral Júnior
- Laboratório de Investigações em Neurodegeneração e Infecção, Instituto de Ciências Biológicas, Hospital Universitário João de Barros Barreto, Universidade Federal do Pará, Belém 66073-005, PA, Brazil; (F.d.C.C.d.S.M.); (M.N.F.d.A.); (M.F.); (M.L.F.A.); (A.P.G.F.); (L.T.V.B.d.P.); (F.L.d.A.J.); (C.W.P.D.)
| | - Daniel Clive Anthony
- Laboratory of Experimental Neuropathology, Department of Pharmacology, University of Oxford, Oxford OX1 3QT, UK;
| | - Dora Brites
- Research Institute for Medicines (iMed.ULisboa), Faculty of Pharmacy, Universidade de Lisboa, 1649-004 Lisbon, Portugal;
- Department of Pharmaceutical Sciences and Medicines, Faculty of Pharmacy, Universidade de Lisboa, 1649-004 Lisbon, Portugal
| | - Cristovam Wanderley Picanço Diniz
- Laboratório de Investigações em Neurodegeneração e Infecção, Instituto de Ciências Biológicas, Hospital Universitário João de Barros Barreto, Universidade Federal do Pará, Belém 66073-005, PA, Brazil; (F.d.C.C.d.S.M.); (M.N.F.d.A.); (M.F.); (M.L.F.A.); (A.P.G.F.); (L.T.V.B.d.P.); (F.L.d.A.J.); (C.W.P.D.)
| | - Marcia Consentino Kronka Sosthenes
- Laboratório de Investigações em Neurodegeneração e Infecção, Instituto de Ciências Biológicas, Hospital Universitário João de Barros Barreto, Universidade Federal do Pará, Belém 66073-005, PA, Brazil; (F.d.C.C.d.S.M.); (M.N.F.d.A.); (M.F.); (M.L.F.A.); (A.P.G.F.); (L.T.V.B.d.P.); (F.L.d.A.J.); (C.W.P.D.)
- Correspondence:
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Wang J, Zhou Y, He Y, Li Q, Zhang W, Luo Z, Xue R, Lou M. Impact of different white matter hyperintensities patterns on cognition: A cross-sectional and longitudinal study. Neuroimage Clin 2022; 34:102978. [PMID: 35255417 PMCID: PMC8897653 DOI: 10.1016/j.nicl.2022.102978] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 02/27/2022] [Accepted: 02/28/2022] [Indexed: 11/03/2022]
Abstract
OBJECTIVES White matter hyperintensities (WMH) are highly prevalent in older adults and considered to be a contributor to cognition impairment. However, the strategic WMH lesion distribution related to cognitive impairment is still debated. The aim of this study was to characterize the spatial patterns of WMH associated with cognitive impairment and explore its risk factors. METHODS We retrospectively analyzed patients who underwent T2 fluid attenuated inversion recovery (FLAIR) and mini-mental state examination (MMSE) in two centers. WHM was classified into four patterns based on T2 FLAIR as follows: (1) multiple subcortical spots (multi-spots); (2) peri-basal ganglia (peri-BG); (3) anterior subcortical patches (anterior SC patches); and (4) posterior subcortical patches (posterior SC patches). We cross-sectionally and longitudinally estimated associations between different WMH patterns and all-cause dementia and cognitive decline. Multivariable logistic regression analysis was followed to identify risk factors of WMH patterns related to cognitive impairment. RESULTS A total of 442 patients with WMH were enrolled, with average age of 71.6 ± 11.3 years, and MMSE score of 24.1 ± 5.4. Among them, 281 (63.6%), 66 (14.9%), 163 (36.9%) and 197 (44.6%) patients presented multi-spots, peri-BG, anterior SC patches and posterior SC patches, respectively. Patients with anterior SC patches were more likely to have all-cause dementia in cross-sectional study (OR 2.002; 95% CI 1.098-3.649; p = 0.024), and have cognitive decline in longitudinal analysis (OR 3.029; 95% CI 1.270-7.223; p = 0.012). Four patterns of WMH referred to different cognitive domains, and anterior SC patches had the most significant and extensive impact on cognition after Bonferroni multiple comparison correction (all p < 0.0125). In addition, older age (OR 1.054; 95% CI 1.027-1.082; p < 0.001), hypertension (OR 1.956; 95% CI 1.145-3.341; p = 0.014), higher percentage of neutrophils (OR 1.046; 95% CI 1.014-1.080; p = 0.005) and lower concentration of hemoglobin (OR 0.983; 95% CI 0.967-1.000; p = 0.044) were risk factors for the presence of anterior SC patches. CONCLUSIONS Different patterns of subcortical leukoaraiosis visually identified on MRI might have different impacts on cognitive impairment. Further studies should be undertaken to validate this simple visual classification of WMH in different population.
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Affiliation(s)
- Junjun Wang
- Department of Neurology, the Second Affiliated Hospital of Zhejiang University, School of Medicine. 88# Jiefang Road, Hangzhou, China; Department of Neurology, Zhejiang Hospital, #12 Lingyin Road, Hangzhou, China
| | - Ying Zhou
- Department of Neurology, the Second Affiliated Hospital of Zhejiang University, School of Medicine. 88# Jiefang Road, Hangzhou, China
| | - Yaode He
- Department of Neurology, the Second Affiliated Hospital of Zhejiang University, School of Medicine. 88# Jiefang Road, Hangzhou, China
| | - Qingqing Li
- Department of Neurology, the Second Affiliated Hospital of Zhejiang University, School of Medicine. 88# Jiefang Road, Hangzhou, China
| | - Wenhua Zhang
- Department of Neurology, the Second Affiliated Hospital of Zhejiang University, School of Medicine. 88# Jiefang Road, Hangzhou, China
| | - Zhongyu Luo
- Department of Neurology, the Second Affiliated Hospital of Zhejiang University, School of Medicine. 88# Jiefang Road, Hangzhou, China
| | - Rui Xue
- Department of Neurology, the Second Affiliated Hospital of Zhejiang University, School of Medicine. 88# Jiefang Road, Hangzhou, China
| | - Min Lou
- Department of Neurology, the Second Affiliated Hospital of Zhejiang University, School of Medicine. 88# Jiefang Road, Hangzhou, China.
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High-Density Lipoprotein Is Associated with Leukoaraiosis Severity in Patients with Acute Ischemic Stroke. Neurotox Res 2022; 40:900-908. [PMID: 35386025 DOI: 10.1007/s12640-022-00502-w] [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: 06/14/2021] [Revised: 03/28/2022] [Accepted: 03/29/2022] [Indexed: 10/18/2022]
Abstract
Many patients with acute ischemic stroke (AIS) are found to accompany with leukoaraiosis (LA) in brain imaging. The risk factors of LA in patients with AIS were examined in this study. Patients with AIS were recruited and underwent head magnetic resonance imaging. According to Fazekas scores, patients were divided into LA group and non-LA group. We compared demographic and laboratory characteristics in two groups. Multivariate logistic regression analysis demonstrated that high-density lipoprotein (HDL), age, stroke history, admission SBP, and homocysteine were independent risk factors for LA in patients with AIS (P < 0.05). Multinomial logistic regression analysis demonstrated that HDL was an independent risk factor for moderate LA (OR 4.151, 95% CI 1.898-9.078, P < 0.001) and severe LA (OR 3.151, 95% CI 1.350-7.358, P = 0.008). In order to further explore the correlation between HDL level and the severity of LA, HDL was categorized in quartiles and multinomial logistic regression analysis was presented. Regression analysis showed that HDL ≥ 1.34 mmol/L was correlated with moderate and severe LA after adjusting for corresponding confounding factors in different models. After 1-year follow-up, patients were divided into regular statin therapy group and irregular statin therapy group. There was no significant difference in HDL level between two groups; however, the proportion of patients with increased Fazekas scores in regular statin therapy group was significantly less than that in the irregular statin therapy group (P < 0.05). In conclusion, HDL was an independent risk factor for LA and associated with the severity of LA in patients with AIS; regular statin therapy may be negatively related with the progress of LA. These results provide more evidences for controlling risk factors and severity of LA in patient with AIS.
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30
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Clancy U, Ramirez J, Chappell FM, Doubal FN, Wardlaw JM, Black SE. Neuropsychiatric symptoms as a sign of small vessel disease progression in cognitive impairment. CEREBRAL CIRCULATION - COGNITION AND BEHAVIOR 2022; 3:100041. [PMID: 36324402 PMCID: PMC9616231 DOI: 10.1016/j.cccb.2022.100041] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 01/12/2022] [Accepted: 01/16/2022] [Indexed: 11/27/2022]
Abstract
Background Neuropsychiatric symptoms associate cross-sectionally with cerebral small vessel disease but it is not clear whether these symptoms could act as early clinical markers of small vessel disease progression. We investigated whether longitudinal change in Neuropsychiatric Inventory (NPI) scores associated with white matter hyperintensity (WMH) progression in a memory clinic population. Material and methods We included participants from the prospective Sunnybrook Dementia Study with Alzheimer's disease and vascular subtypes of mild cognitive impairment and dementia with two MRI and ≥ 1 NPI. We conducted linear mixed-effects analyses, adjusting for age, atrophy, vascular risk factors, cognition, function, and interscan interval. Results At baseline (n=124), greater atrophy, age, vascular risk factors and total NPI score were associated with higher baseline WMH volume, while longitudinally, all but vascular risk factors were associated. Change in total NPI score was associated with change in WMH volume, χ2 = 7.18, p = 0.007, whereby a one-point change in NPI score from baseline to follow-up was associated with a 0.0017 change in normalized WMH volume [expressed as cube root of (WMH volume cm³ as % intracranial volume)], after adjusting for age, atrophy, vascular risk factors and interscan interval. Conclusions In memory clinic patients, WMH progression over 1-2 years associated with worsening neuropsychiatric symptoms, while WMH volume remained unchanged in those with stable NPI scores in this population with low background WMH burden.
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Affiliation(s)
- Una Clancy
- Brain Research Imaging Centre, Division of Neuroimaging Sciences, Centre for Clinical Brain Sciences, UK Dementia Research Institute at the University of Edinburgh, Edinburgh, UK
| | - Joel Ramirez
- Dr. Sandra Black Centre for Brain Resilience & Recovery, LC Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, 2075 Bayview Avenue, Room A4 21, Toronto, ON M4N 3M5, Canada,Corresponding author.
| | - Francesca M. Chappell
- Brain Research Imaging Centre, Division of Neuroimaging Sciences, Centre for Clinical Brain Sciences, UK Dementia Research Institute at the University of Edinburgh, Edinburgh, UK
| | - Fergus N. Doubal
- Brain Research Imaging Centre, Division of Neuroimaging Sciences, Centre for Clinical Brain Sciences, UK Dementia Research Institute at the University of Edinburgh, Edinburgh, UK
| | - Joanna M. Wardlaw
- Brain Research Imaging Centre, Division of Neuroimaging Sciences, Centre for Clinical Brain Sciences, UK Dementia Research Institute at the University of Edinburgh, Edinburgh, UK
| | - Sandra E. Black
- Dr. Sandra Black Centre for Brain Resilience & Recovery, LC Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, 2075 Bayview Avenue, Room A4 21, Toronto, ON M4N 3M5, Canada,Department of Medicine (Neurology), Sunnybrook Health Sciences Centre and Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
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31
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Uretsky M, Bouix S, Killiany RJ, Tripodis Y, Martin B, Palmisano J, Mian AZ, Buch K, Farris C, Daneshvar DH, Dwyer B, Goldstein L, Katz D, Nowinski C, Cantu R, Kowall N, Huber BR, Stern RA, Alvarez VE, Stein TD, McKee A, Mez J, Alosco ML. Association Between Antemortem FLAIR White Matter Hyperintensities and Neuropathology in Brain Donors Exposed to Repetitive Head Impacts. Neurology 2022; 98:e27-e39. [PMID: 34819338 PMCID: PMC8726571 DOI: 10.1212/wnl.0000000000013012] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Accepted: 09/29/2021] [Indexed: 01/18/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Late neuropathologies of repetitive head impacts from contact sports can include chronic traumatic encephalopathy (CTE) and white matter degeneration. White matter hyperintensities (WMH) on fluid-attenuated inversion recovery (FLAIR) MRI scans are often viewed as microvascular disease from vascular risk, but might have unique underlying pathologies and risk factors in the setting of repetitive head impacts. We investigated the neuropathologic correlates of antemortem WMH in brain donors exposed to repetitive head impacts. The association between WMH and repetitive head impact exposure and informant-reported cognitive and daily function were tested. METHODS This imaging-pathologic correlation study included symptomatic male decedents exposed to repetitive head impacts. Donors had antemortem FLAIR scans from medical records and were without evidence of CNS neoplasm, large vessel infarcts, hemorrhage, or encephalomalacia. WMH were quantified using log-transformed values for total lesion volume (TLV), calculated using the lesion prediction algorithm from the Lesion Segmentation Toolbox. Neuropathologic assessments included semiquantitative ratings of white matter rarefaction, cerebrovascular disease, hyperphosphorylated tau (p-tau) severity (CTE stage, dorsolateral frontal cortex), and β-amyloid (Aβ). Among football players, years of play was a proxy for repetitive head impact exposure. Retrospective informant-reported cognitive and daily function were assessed using the Cognitive Difficulties Scale (CDS) and Functional Activities Questionnaire (FAQ). Regression models controlled for demographics, diabetes, hypertension, and MRI resolution. Statistical significance was defined as p ≤ 0.05. RESULTS The sample included 75 donors: 67 football players and 8 nonfootball contact sport athletes or military veterans. Dementia was the most common MRI indication (64%). Fifty-three (70.7%) had CTE at autopsy. Log TLV was associated with white matter rarefaction (odds ratio [OR] 2.32, 95% confidence interval [CI] 1.03, 5.24; p = 0.04), arteriolosclerosis (OR 2.38, 95% CI 1.02, 5.52; p = 0.04), CTE stage (OR 2.58, 95% CI 1.17, 5.71; p = 0.02), and dorsolateral frontal p-tau severity (OR 3.03, 95% CI 1.32, 6.97; p = 0.01). There was no association with Aβ. More years of football play was associated with log TLV (unstandardized β 0.04, 95% CI 0.01, 0.06; p = 0.01). Greater log TLV correlated with higher FAQ (unstandardized β 4.94, 95% CI 0.42, 8.57; p = 0.03) and CDS scores (unstandardized β 15.35, 95% CI -0.27, 30.97; p = 0.05). DISCUSSION WMH might capture long-term white matter pathologies from repetitive head impacts, including those from white matter rarefaction and p-tau, in addition to microvascular disease. Prospective imaging-pathologic correlation studies are needed. CLASSIFICATION OF EVIDENCE This study provides Class IV evidence of associations between FLAIR white matter hyperintensities and neuropathologic changes (white matter rarefaction, arteriolosclerosis, p-tau accumulation), years of American football play, and reported cognitive symptoms in symptomatic brain donors exposed to repetitive head impacts.
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Affiliation(s)
- Madeline Uretsky
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Sylvain Bouix
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Ronald J Killiany
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Yorghos Tripodis
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Brett Martin
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Joseph Palmisano
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Asim Z Mian
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Karen Buch
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Chad Farris
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Daniel H Daneshvar
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Brigid Dwyer
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Lee Goldstein
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Douglas Katz
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Christopher Nowinski
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Robert Cantu
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Neil Kowall
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Bertrand Russell Huber
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Robert A Stern
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Victor E Alvarez
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Thor D Stein
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Ann McKee
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Jesse Mez
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Michael L Alosco
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA.
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32
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Igwe KC, Lao PJ, Vorburger RS, Banerjee A, Rivera A, Chesebro A, Laing K, Manly JJ, Brickman AM. Automatic quantification of white matter hyperintensities on T2-weighted fluid attenuated inversion recovery magnetic resonance imaging. Magn Reson Imaging 2022; 85:71-79. [PMID: 34662699 PMCID: PMC8818099 DOI: 10.1016/j.mri.2021.10.007] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Revised: 08/20/2021] [Accepted: 10/12/2021] [Indexed: 01/03/2023]
Abstract
White matter hyperintensities (WMH) are areas of increased signal visualized on T2-weighted fluid attenuated inversion recovery (FLAIR) brain magnetic resonance imaging (MRI) sequences. They are typically attributed to small vessel cerebrovascular disease in the context of aging. Among older adults, WMH are associated with risk of cognitive decline and dementia, stroke, and various other health outcomes. There has been increasing interest in incorporating quantitative WMH measurement as outcomes in clinical trials, observational research, and clinical settings. Here, we present a novel, fully automated, unsupervised detection algorithm for WMH segmentation and quantification. The algorithm uses a robust preprocessing pipeline, including brain extraction and a sample-specific mask that incorporates spatial information for automatic false positive reduction, and a half Gaussian mixture model (HGMM). The method was evaluated in 24 participants with varying degrees of WMH (4.9-78.6 cm3) from a community-based study of aging and dementia with dice coefficient, sensitivity, specificity, correlation, and bias relative to the ground truth manual segmentation approach performed by two expert raters. Results were compared with those derived from commonly used available WMH segmentation packages, including SPM lesion probability algorithm (LPA), SPM lesion growing algorithm (LGA), and Brain Intensity AbNormality Classification Algorithm (BIANCA). The HGMM algorithm derived WMH values that had a dice score of 0.87, sensitivity of 0.89, and specificity of 0.99 compared to ground truth. White matter hyperintensity volumes derived with HGMM were strongly correlated with ground truth values (r = 0.97, p = 3.9e-16), with no observable bias (-1.1 [-2.6, 0.44], p-value = 0.16). Our novel algorithm uniquely uses a robust preprocessing pipeline and a half-Gaussian mixture model to segment WMH with high agreement with ground truth for large scale studies of brain aging.
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Affiliation(s)
- Kay C. Igwe
- Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA.,Gertrude H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA
| | - Patrick J. Lao
- Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA.,Gertrude H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA.,Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA
| | - Robert S. Vorburger
- Institute of Applied Simulation, School of Life Sciences and Facility Management, Zurich University of Applied Sciences, Wädenswil, 8820, Switzerland
| | - Arit Banerjee
- Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA.,Gertrude H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA
| | - Andres Rivera
- Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA.,Gertrude H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA
| | - Anthony Chesebro
- Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA.,Gertrude H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA
| | - Krystal Laing
- Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA.,Gertrude H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA
| | - Jennifer J. Manly
- Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA.,Gertrude H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA.,Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA
| | - Adam M. Brickman
- Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA.,Gertrude H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA.,Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA.,Corresponding author Adam M. Brickman, PhD, Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, PS Box 16, 630 West 168th Street, New York, NY 10032, Tel: 212 342 1348, Fax: 212 342 1838,
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Deary IJ, Cox SR, Hill WD. Genetic variation, brain, and intelligence differences. Mol Psychiatry 2022; 27:335-353. [PMID: 33531661 PMCID: PMC8960418 DOI: 10.1038/s41380-021-01027-y] [Citation(s) in RCA: 44] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 12/28/2020] [Accepted: 01/11/2021] [Indexed: 01/30/2023]
Abstract
Individual differences in human intelligence, as assessed using cognitive test scores, have a well-replicated, hierarchical phenotypic covariance structure. They are substantially stable across the life course, and are predictive of educational, social, and health outcomes. From this solid phenotypic foundation and importance for life, comes an interest in the environmental, social, and genetic aetiologies of intelligence, and in the foundations of intelligence differences in brain structure and functioning. Here, we summarise and critique the last 10 years or so of molecular genetic (DNA-based) research on intelligence, including the discovery of genetic loci associated with intelligence, DNA-based heritability, and intelligence's genetic correlations with other traits. We summarise new brain imaging-intelligence findings, including whole-brain associations and grey and white matter associations. We summarise regional brain imaging associations with intelligence and interpret these with respect to theoretical accounts. We address research that combines genetics and brain imaging in studying intelligence differences. There are new, though modest, associations in all these areas, and mechanistic accounts are lacking. We attempt to identify growing points that might contribute toward a more integrated 'systems biology' account of some of the between-individual differences in intelligence.
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Affiliation(s)
- Ian J. Deary
- grid.4305.20000 0004 1936 7988Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ UK
| | - Simon R. Cox
- grid.4305.20000 0004 1936 7988Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ UK
| | - W. David Hill
- grid.4305.20000 0004 1936 7988Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ UK
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Gerritsen L, Twait EL, Jonsson PV, Gudnason V, Launer LJ, Geerlings MI. Depression and Dementia: The Role of Cortisol and Vascular Brain Lesions. AGES-Reykjavik Study. J Alzheimers Dis 2022; 85:1677-1687. [PMID: 34958034 PMCID: PMC11044806 DOI: 10.3233/jad-215241] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
BACKGROUND Late-life depression (LLD) is related to an increased risk of developing dementia; however, the biological mechanisms explaining this relationship remain unclear. OBJECTIVE To determine whether the relationship between LLD and dementia can be best explained by the glucocorticoid cascade or vascular hypothesis. METHODS Data are from 4,354 persons (mean age 76±5 years) without dementia at baseline from the AGES-Reykjavik Study. LLD was assessed with the MINI diagnostic interview (current and remitted major depressive disorder [MDD]) and the Geriatric Depression Scale-15. Morning and evening salivary cortisol were collected (glucocorticoid cascade hypothesis). White matter hyperintensities (WMH; vascular hypothesis) volume was assessed using 1.5T brain MRI. Using Cox proportional hazard models, we estimated the associations of LLD, cortisol levels, and WMH volume with incident all-cause dementia, AD, and non-AD dementia. RESULTS During 8.8±3.2 years of follow-up, 843 persons developed dementia, including 397 with AD. Current MDD was associated with an increased risk of developing all-cause dementia (HR = 2.17; 95% CI 1.66-2.67), with risks similar for AD and non-AD, while remitted MDD was not (HR = 1.02; 95% CI 0.55-1.49). Depressive symptoms were also associated with increased risk of dementia, in particular non-AD dementias. Higher levels of evening cortisol increased risk of dementia, but this was independent of MDD. WMH partially explained the relation between current MDD and dementia risk but remained increased (HR = 1.71; 95% CI 1.34-2.08). CONCLUSION The current study highlights the importance of LLD in developing dementia. However, neither the glucocorticoid cascade nor the vascular hypotheses fully explained the relation between depression and dementia.
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Affiliation(s)
- Lotte Gerritsen
- Department of Psychology, Utrecht University, Utrecht, the Netherlands
| | - Emma L. Twait
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands
| | - Palmi V. Jonsson
- Department of Geriatrics, Landspitali University Hospital, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Vilmundur Gudnason
- Department of Psychology, Utrecht University, Utrecht, the Netherlands
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Lenore J. Launer
- National Institute on Aging, Laboratory for Epidemiology and Population Sciences, Baltimore, MD, USA
| | - Mirjam I. Geerlings
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands
- National Institute on Aging, Laboratory for Epidemiology and Population Sciences, Baltimore, MD, USA
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35
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Jiménez-Sánchez L, Hamilton OKL, Clancy U, Backhouse EV, Stewart CR, Stringer MS, Doubal FN, Wardlaw JM. Sex Differences in Cerebral Small Vessel Disease: A Systematic Review and Meta-Analysis. Front Neurol 2021; 12:756887. [PMID: 34777227 PMCID: PMC8581736 DOI: 10.3389/fneur.2021.756887] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Accepted: 10/04/2021] [Indexed: 01/12/2023] Open
Abstract
Background: Cerebral small vessel disease (SVD) is a common cause of stroke, mild cognitive impairment, dementia and physical impairments. Differences in SVD incidence or severity between males and females are unknown. We assessed sex differences in SVD by assessing the male-to-female ratio (M:F) of recruited participants and incidence of SVD, risk factor presence, distribution, and severity of SVD features. Methods: We assessed four recent systematic reviews on SVD and performed a supplementary search of MEDLINE to identify studies reporting M:F ratio in covert, stroke, or cognitive SVD presentations (registered protocol: CRD42020193995). We meta-analyzed differences in sex ratios across time, countries, SVD severity and presentations, age and risk factors for SVD. Results: Amongst 123 relevant studies (n = 36,910 participants) including 53 community-based, 67 hospital-based and three mixed studies published between 1989 and 2020, more males were recruited in hospital-based than in community-based studies [M:F = 1.16 (0.70) vs. M:F = 0.79 (0.35), respectively; p < 0.001]. More males had moderate to severe SVD [M:F = 1.08 (0.81) vs. M:F = 0.82 (0.47) in healthy to mild SVD; p < 0.001], and stroke presentations where M:F was 1.67 (0.53). M:F did not differ for recent (2015-2020) vs. pre-2015 publications, by geographical region, or age. There were insufficient sex-stratified data to explore M:F and risk factors for SVD. Conclusions: Our results highlight differences in male-to-female ratios in SVD severity and amongst those presenting with stroke that have important clinical and translational implications. Future SVD research should report participant demographics, risk factors and outcomes separately for males and females. Systematic Review Registration: [PROSPERO], identifier [CRD42020193995].
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Affiliation(s)
- Lorena Jiménez-Sánchez
- Translational Neuroscience PhD Programme, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Olivia K. L. Hamilton
- Translational Neuroscience PhD Programme, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Edinburgh Dementia Research Centre in the UK Dementia Research Institute, Edinburgh, United Kingdom
| | - Una Clancy
- Edinburgh Dementia Research Centre in the UK Dementia Research Institute, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Ellen V. Backhouse
- Edinburgh Dementia Research Centre in the UK Dementia Research Institute, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Catriona R. Stewart
- Edinburgh Dementia Research Centre in the UK Dementia Research Institute, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Michael S. Stringer
- Edinburgh Dementia Research Centre in the UK Dementia Research Institute, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Fergus N. Doubal
- Edinburgh Dementia Research Centre in the UK Dementia Research Institute, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Joanna M. Wardlaw
- Edinburgh Dementia Research Centre in the UK Dementia Research Institute, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Lothian Birth Cohorts, University of Edinburgh, Edinburgh, United Kingdom
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36
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Zacharias HU, Weihs A, Habes M, Wittfeld K, Frenzel S, Rashid T, Stubbe B, Obst A, Szentkirályi A, Bülow R, Berger K, Fietze I, Penzel T, Hosten N, Ewert R, Völzke H, Grabe HJ. Association Between Obstructive Sleep Apnea and Brain White Matter Hyperintensities in a Population-Based Cohort in Germany. JAMA Netw Open 2021; 4:e2128225. [PMID: 34609493 PMCID: PMC8493431 DOI: 10.1001/jamanetworkopen.2021.28225] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Accepted: 08/01/2021] [Indexed: 11/14/2022] Open
Abstract
Importance Underlying pathomechanisms of brain white matter hyperintensities (WMHs), commonly observed in older individuals and significantly associated with Alzheimer disease and brain aging, have not yet been fully elucidated. One potential contributing factor to WMH burden is chronic obstructive sleep apnea (OSA), a disorder highly prevalent in the general population with readily available treatment options. Objective To investigate potential associations between OSA and WMH burden. Design, Setting, and Participants Analyses were conducted in 529 study participants of the Study of Health in Pomerania-Trend baseline (SHIP-Trend-0) study with complete WMH, OSA, and important clinical data available. SHIP-Trend-0 is a general population-based, cross-sectional, observational study to facilitate the investigation of a large spectrum of common risk factors, subclinical disorders, and clinical diseases and their relationships among each other with patient recruitment from Western Pomerania, Germany, starting on September 1, 2008, with data collected until December 31, 2012. Data analysis was performed from February 1, 2019, to January 31, 2021. Exposures The apnea-hypopnea index (AHI) and oxygen desaturation index (ODI) were assessed during a single-night, laboratory-based polysomnography measurement. Main Outcomes and Measures The primary outcome was WMH data automatically segmented from 1.5-T magnetic resonance images. Results Of 529 study participants (mean [SD] age, 52.15 [13.58] years; 282 female [53%]), a total of 209 (40%) or 102 (19%) individuals were diagnosed with OSA according to AHI or ODI criteria (mean [SD] AHI, 7.98 [12.55] events per hour; mean [SD] ODI, 3.75 [8.43] events per hour). Both AHI (β = 0.024; 95% CI, 0.011-0.037; P <.001) and ODI (β = 0.033; 95% CI, 0.014-0.051; P <. 001) were significantly associated with brain WMH volumes. These associations remained even in the presence of additional vascular, metabolic, and lifestyle WMH risk factors. Region-specific WMH analyses found the strongest associations between periventricular frontal WMH volumes and both AHI (β = 0.0275; 95% CI, 0.013-0.042, P < .001) and ODI (β = 0.0381; 95% CI, 0.016-0.060, P < .001) as well as periventricular dorsal WMH volumes and AHI (β = 0.0165; 95% CI, 0.004-0.029, P = .008). Conclusions and Relevance This study found significant associations between OSA and brain WMHs, indicating a novel, potentially treatable WMH pathomechanism.
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Affiliation(s)
- Helena U. Zacharias
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- Department of Internal Medicine I, University Medical Center Schleswig-Holstein, Campus Kiel, Kiel, Germany
- Institute of Clinical Molecular Biology, Kiel University and University Medical Center Schleswig-Holstein, Campus Kiel, Kiel, Germany
| | - Antoine Weihs
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Mohamad Habes
- Neuroimage Analytics Laboratory and Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio, San Antonio
- Department of Radiology, University of Pennsylvania, Philadelphia
| | - Katharina Wittfeld
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Centre for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Germany
| | - Stefan Frenzel
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Tanweer Rashid
- Neuroimage Analytics Laboratory and Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio, San Antonio
| | - Beate Stubbe
- Department of Internal Medicine B–Cardiology, Pneumology, Infectious Diseases, Intensive Care Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Anne Obst
- Department of Internal Medicine B–Cardiology, Pneumology, Infectious Diseases, Intensive Care Medicine, University Medicine Greifswald, Greifswald, Germany
| | - András Szentkirályi
- Institute of Epidemiology and Social Medicine, University of Muenster, Muenster, Germany
| | - Robin Bülow
- Institute for Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Klaus Berger
- Institute of Epidemiology and Social Medicine, University of Muenster, Muenster, Germany
| | - Ingo Fietze
- Interdisciplinary Centre of Sleep Medicine, University Hospital Charité Berlin, Berlin, Germany
| | - Thomas Penzel
- Interdisciplinary Centre of Sleep Medicine, University Hospital Charité Berlin, Berlin, Germany
| | - Norbert Hosten
- Institute for Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Ralf Ewert
- Department of Internal Medicine B–Cardiology, Pneumology, Infectious Diseases, Intensive Care Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Henry Völzke
- Institute for Community Medicine, Department Study of Health in Pomerania/Clinical Epidemiological Research, University Medicine Greifswald, Greifswald, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Germany
| | - Hans J. Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Centre for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Germany
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Guo Y, Chen Z, Wang Q, Zhang M, Dong G, Zou W, Yao T, Xu Y. Influence of white matter lesions on the prognosis of acute cardioembolic stroke without reperfusion therapy. BMC Neurol 2021; 21:364. [PMID: 34536997 PMCID: PMC8449459 DOI: 10.1186/s12883-021-02372-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Accepted: 08/30/2021] [Indexed: 11/13/2022] Open
Abstract
Background Few studies have investigated the influence of white matter lesions (WMLs) on the prognosis of acute cardioembolic stroke (CES). We aimed to explore the role of WMLs in predicting 3-month prognosis of CES without reperfusion therapy. Methods A number of 251 acute CES patients without reperfusion therapy at a single center were retrospectively recruited. The severity of WMLs was evaluated by Fazekas scale and patients were divided into mild WMLs group (188 cases, Fazekas ≤ 2 points) and moderate to severe WMLs group (63 cases, Fazekas ≥ 3 points) accordingly. General data and clinical features of the two groups were compared. Functional outcomes of patients were followed up for 3 months using the modified Rankin scale (mRS) and patients were divided into poor outcome group (mRS ≥ 3) and favorable outcome group (mRS ≤ 2). The effect of WMLs on the prognosis was identified by binary logistic regression. Results Patients in moderate to severe WMLs group were older (P < 0.001). Also, they had higher baseline National Institutes of Health Stroke Scale (NIHSS) score (P < 0.001) and elevated incidence of asymptomatic cerebral hemorrhage (P = 0.040) and stroke associated pneumonia (P = 0.001) than those in mild WMLs group. At 3 months, there were 100 cases in the poor outcome group. Patients in poor outcome group had higher baseline NIHSS score, increased proportion of moderate to severe WMLs, and elevated incidence of stroke associated pneumonia than those in favorable outcome group (P < 0.001). Binary logistic regression analysis showed that moderate to severe WMLs (odds ratio [OR] = 4.105, 95 % confidence interval [CI] = 1.447–11.646), baseline NIHSS score (OR = 1.368, 95 % CI = 1.240–1.511), and stroke-associated pneumonia (OR = 4.840, 95 %CI = 1.889–12.400) were independent risk factors for poor outcome. Conclusions Moderate to severe WMLs is an independent risk factor for prognosis of CES patients without reperfusion therapy.
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Affiliation(s)
- Yikun Guo
- Department of Neurology, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, 321# Middle Zhongshan Road, Jiangsu Province, 210008, Nanjing, China.,Department of Neurology, The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, 213000, Changzhou, China
| | - Zhuoyou Chen
- Department of Neurology, The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, 213000, Changzhou, China
| | - Qian Wang
- Department of Neurology, The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, 213000, Changzhou, China
| | - Min Zhang
- Department of Neurology, The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, 213000, Changzhou, China
| | - Guanzhong Dong
- Department of Neurology, The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, 213000, Changzhou, China
| | - Wenying Zou
- Department of Neurology, The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, 213000, Changzhou, China
| | - Tian Yao
- Department of Neurology, The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, 213000, Changzhou, China
| | - Yun Xu
- Department of Neurology, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, 321# Middle Zhongshan Road, Jiangsu Province, 210008, Nanjing, China.
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Jokinen H, Laakso HM, Ahlström M, Arola A, Lempiäinen J, Pitkänen J, Paajanen T, Sikkes SAM, Koikkalainen J, Lötjönen J, Korvenoja A, Erkinjuntti T, Melkas S. Synergistic associations of cognitive and motor impairments with functional outcome in covert cerebral small vessel disease. Eur J Neurol 2021; 29:158-167. [PMID: 34528346 DOI: 10.1111/ene.15108] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Revised: 09/04/2021] [Accepted: 09/09/2021] [Indexed: 11/29/2022]
Abstract
BACKGROUND Cognitive and motor impairments are the key clinical manifestations of cerebral small vessel disease (SVD), but their combined effects on functional outcome have not been elucidated. This study investigated the interactions and mediating effects of cognitive and motor functions on instrumental activities of daily living (IADL) and quality of life in older individuals with various degrees of white matter hyperintensities (WMH). METHODS Participants of the Helsinki Small Vessel Disease Study (n = 152) were assessed according to an extensive clinical, physical, neuropsychological and MRI protocol. Volumes of WMH and gray matter (GM) were obtained with automated segmentation. RESULTS Cognitive (global cognition, executive functions, processing speed, memory) and motor functions (gait speed, single-leg stance, timed up-and-go) had strong interrelations with each other, and they were significantly associated with IADL, quality of life as well as WMH and GM volumes. A consistent pattern on significant interactions between cognitive and motor functions was found on informant-evaluated IADL, but not on self-evaluated quality of life. The association of WMH volume with IADL was mediated by global cognition, whereas the association of GM volume with IADL was mediated by global cognition and timed up-and-go performance. CONCLUSION The results highlight the complex interplay and synergism between motor and cognitive abilities on functional outcome in SVD. The combined effect of motor and cognitive disturbances on IADL is likely to be greater than their individual effects. Patients with both impairments are at disproportionate risk for poor outcome. WMH and brain atrophy contribute to disability through cognitive and motor impairment.
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Affiliation(s)
- Hanna Jokinen
- Division of Neuropsychology, HUS Neurocenter, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.,Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Hanna M Laakso
- Division of Neuropsychology, HUS Neurocenter, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.,Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Matti Ahlström
- Department of Neurology, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Anne Arola
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Juha Lempiäinen
- Department of Neurology, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Johanna Pitkänen
- Department of Neurology, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Teemu Paajanen
- Research and Service Centre, Finnish Institute of Occupational Health, Helsinki, Finland
| | - Sietske A M Sikkes
- Department of Clinical, Neuro and Developmental Psychology, VU University, Amsterdam, The Netherlands.,Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, The Netherlands
| | - Juha Koikkalainen
- Combinostics Ltd, Tampere, Finland.,Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Jyrki Lötjönen
- Combinostics Ltd, Tampere, Finland.,Department of Neuroscience and Biomedical Engineering, School of Science, Aalto University, Espoo, Finland
| | - Antti Korvenoja
- Department of Radiology, HUS Diagnostic Center, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Timo Erkinjuntti
- Department of Neurology, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Susanna Melkas
- Department of Neurology, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
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Gyanwali B, Lui B, Tan CS, Chong EJY, Vrooman H, Chen C, Hilal S. Cerebral Microbleeds and White Matter Hyperintensities are Associated with Cognitive Decline in an Asian Memory Clinic Study. Curr Alzheimer Res 2021; 18:399-413. [PMID: 34420506 DOI: 10.2174/1567205018666210820125543] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Revised: 05/21/2021] [Accepted: 05/29/2021] [Indexed: 11/22/2022]
Abstract
BACKGROUND Cerebral Small Vessel Disease (SVD); lacunes, Cerebral Microbleeds (CMBs), and White Matter Hyperintensities (WMH) have a vital role in cognitive impairment and dementia. SVD in lobar location is related to cerebral amyloid angiopathy, whereas SVD in a deep location with hypertensive arteriopathy. It remains unclear how different locations of SVD affect long-term cognitive decline. The present study aimed to analyse the association between different locations and severity of SVD with global and domain-specific cognitive decline over the follow-up interval of 3 years. METHODS We studied 428 participants who had performed MRI scans at baseline and at least 3 neuropsychological assessments. Locations of lacunes and CMBs were categorized into strictly lobar, strictly deep and mixed-location, WMH volume into anterior and posterior. The National Institute of Neurological Disorders and Stroke-Canadian Stroke Network Harmonization Neuropsychological Battery was used to assess cognitive function. To analyse the association between baseline location and severity of SVD with cognitive decline, linear regression models with generalized estimated equations were constructed to calculate the mean difference, 95% confidence interval and two-way interaction factor between time and SVD. RESULTS Increased numbers of baseline CMBs were associated with a decline in global cognition as well as a decline in executive function and memory domains. Location-specific analysis showed similar results with strictly lobar CMBs. There was no association with strictly deep and mixed-location CMBs with cognitive decline. Baseline WMH volume was associated with a decline in global cognition, executive function and memory. Similar results were obtained with anterior and posterior WMH volumes. Lacunes and their locations were not associated with cognitive decline. CONCLUSION Strictly lobar CMBs, as well as WMH volume in anterior and posterior regions, were associated with cognitive decline. Future research focuses are warranted to evaluate interventions that may prevent cognitive decline related to SVD.
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Affiliation(s)
- Bibek Gyanwali
- Memory Aging & Cognition Centre, National University Health System, 21 Lower Kent Ridge Rd, Singapore
| | - Benedict Lui
- Memory Aging & Cognition Centre, National University Health System, 21 Lower Kent Ridge Rd, Singapore
| | - Chuen S Tan
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, 21 Lower Kent Ridge Rd, Singapore
| | - Eddie J Y Chong
- Department of Psychological Medicine, National University Hospital, 21 Lower Kent Ridge Rd, Singapore
| | - Henri Vrooman
- Departments of Radiology & Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Christopher Chen
- Memory Aging & Cognition Centre, National University Health System, 21 Lower Kent Ridge Rd, Singapore
| | - Saima Hilal
- Memory Aging & Cognition Centre, National University Health System, 21 Lower Kent Ridge Rd, Singapore
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40
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McCollum LE, Das SR, Xie L, de Flores R, Wang J, Xie SX, Wisse LEM, Yushkevich PA, Wolk DA. Oh brother, where art tau? Amyloid, neurodegeneration, and cognitive decline without elevated tau. Neuroimage Clin 2021; 31:102717. [PMID: 34119903 PMCID: PMC8207301 DOI: 10.1016/j.nicl.2021.102717] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Revised: 05/21/2021] [Accepted: 06/02/2021] [Indexed: 12/24/2022]
Abstract
Mild cognitive impairment (MCI) can be an early manifestation of Alzheimer's disease (AD) pathology, other pathologic entities [e.g., cerebrovascular disease, Lewy body disease, LATE (limbic-predominant age-related TDP-43 encephalopathy)], or mixed pathologies, with concomitant AD- and non-AD pathology being particularly common, albeit difficult to identify, in living MCI patients. The National Institute on Aging and Alzheimer's Association (NIA-AA) A/T/(N) [β-Amyloid/Tau/(Neurodegeneration)] AD research framework, which classifies research participants according to three binary biomarkers [β-amyloid (A+/A-), tau (T+/T-), and neurodegeneration (N+/N-)], provides an indirect means of identifying such cases. Individuals with A+T-(N+) MCI are thought to have both AD pathologic change, given the presence of β-amyloid, and non-AD pathophysiology, given neurodegeneration without tau, because in typical AD it is tau accumulation that is most tightly linked to neuronal injury and cognitive decline. Thus, in A+T-(N+) MCI (hereafter referred to as "mismatch MCI" for the tau-neurodegeneration mismatch), non-AD pathology is hypothesized to drive neurodegeneration and symptoms, because β-amyloid, in the absence of tau, likely reflects a preclinical stage of AD. We compared a group of individuals with mismatch MCI to groups with A+T+(N+) MCI (or "prodromal AD") and A-T-(N+) MCI (or "neurodegeneration-only MCI") on cross-sectional and longitudinal cognition and neuroimaging characteristics. β-amyloid and tau status were determined by CSF assays, while neurodegeneration status was based on hippocampal volume on MRI. Overall, mismatch MCI was less "AD-like" than prodromal AD and generally, with some exceptions, more closely resembled the neurodegeneration-only group. At baseline, mismatch MCI had less episodic memory loss compared to prodromal AD. Longitudinally, mismatch MCI declined more slowly than prodromal AD across all included cognitive domains, while mismatch MCI and neurodegeneration-only MCI declined at comparable rates. Prodromal AD had smaller baseline posterior hippocampal volume than mismatch MCI, and whole brain analyses demonstrated cortical thinning that was widespread in prodromal AD but largely restricted to the medial temporal lobes (MTLs) for the mismatch and neurodegeneration-only MCI groups. Longitudinally, mismatch MCI had slower rates of volume loss than prodromal AD throughout the MTLs. Differences in cross-sectional and longitudinal cognitive and neuroimaging measures between mismatch MCI and prodromal AD may reflect disparate underlying pathologic processes, with the mismatch group potentially being driven by non-AD pathologies on a background of largely preclinical AD. These findings suggest that β-amyloid status alone in MCI may not reveal the underlying driver of symptoms with important implications for enrollment in clinical trials and prognosis.
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Affiliation(s)
- Lauren E McCollum
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA; Department of Medicine, University of Tennessee Graduate School of Medicine, Knoxville, TN, USA.
| | - Sandhitsu R Das
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA; Department of Radiology, Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, PA, USA
| | - Long Xie
- Department of Radiology, Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, PA, USA
| | - Robin de Flores
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA; Department of Radiology, Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, PA, USA; INSERM UMR-S U1237, Université de Caen Normandie, Caen, Normandy, USA
| | - Jieqiong Wang
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Sharon X Xie
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA
| | - Laura E M Wisse
- Department of Radiology, Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, PA, USA; Department of Diagnostic Radiology, Lund University, Lund, Sweden
| | - Paul A Yushkevich
- Department of Radiology, Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, PA, USA
| | - David A Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
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41
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Matuskova V, Ismail Z, Nikolai T, Markova H, Cechova K, Nedelska Z, Laczo J, Wang M, Hort J, Vyhnalek M. Mild Behavioral Impairment Is Associated With Atrophy of Entorhinal Cortex and Hippocampus in a Memory Clinic Cohort. Front Aging Neurosci 2021; 13:643271. [PMID: 34108874 PMCID: PMC8180573 DOI: 10.3389/fnagi.2021.643271] [Citation(s) in RCA: 62] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Accepted: 04/16/2021] [Indexed: 12/22/2022] Open
Abstract
Objectives Mild behavioral impairment (MBI) is a syndrome describing late-onset persistent neuropsychiatric symptoms (NPS) in non-demented older adults. Few studies to date have investigated the associations of MBI with structural brain changes. Our aim was to explore structural correlates of NPS in a non-demented memory clinic sample using the Mild Behavioral Impairment Checklist (MBI-C) that has been developed to measure MBI. Methods One hundred sixteen non-demented older adults from the Czech Brain Aging Study with subjective cognitive concerns were classified as subjective cognitive decline (n = 37) or mild cognitive impairment (n = 79). Participants underwent neurological and neuropsychological examinations and brain magnetic resonance imaging (MRI) (1.5 T). The Czech version of the MBI-C was administered to participants’ informants. Five a priori selected brain regions were measured, namely, thicknesses of the orbitofrontal cortex (OFC), anterior cingulate cortex (ACC), posterior cingulate cortex (PCC), and entorhinal cortex (ERC) and volume of the hippocampus (HV), and correlated with MBI-C total and domain scores. Results Entorhinal cortex was associated with MBI-C total score (rS = −0.368, p < 0.001) and with impulse dyscontrol score (rS = −0.284, p = 0.002). HV was associated with decreased motivation (rS = −0.248, p = 0.008) and impulse dyscontrol score (rS = −0.240, p = 0.011). Conclusion Neuropsychiatric symptoms, particularly in the MBI impulse dyscontrol and motivation domains, are associated with medial temporal lobe atrophy in a clinical cohort of non-demented older adults. This study supports earlier involvement of temporal rather than frontal regions in NPS manifestation. Since these regions are typically affected early in the course of Alzheimer’s disease (AD), the MBI-C may potentially help further identify individuals at-risk of developing AD dementia.
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Affiliation(s)
- Veronika Matuskova
- Memory Clinic, Department of Neurology, Second Faculty of Medicine, Charles University and Motol University Hospital, Prague, Czechia.,International Clinical Research Center, St. Anne's University Hospital Brno, Brno, Czechia
| | - Zahinoor Ismail
- Department of Psychiatry, Cumming School of Medicine, Calgary, AB, Canada.,Department of Clinical Neurosciences, Cumming School of Medicine, Calgary, AB, Canada.,Department of Community Health Sciences, Cumming School of Medicine, Calgary, AB, Canada.,Hotchkiss Brain Institute and O'Brien Institute for Public Health, University of Calgary, Calgary, AB, Canada
| | - Tomas Nikolai
- Memory Clinic, Department of Neurology, Second Faculty of Medicine, Charles University and Motol University Hospital, Prague, Czechia.,International Clinical Research Center, St. Anne's University Hospital Brno, Brno, Czechia
| | - Hana Markova
- Memory Clinic, Department of Neurology, Second Faculty of Medicine, Charles University and Motol University Hospital, Prague, Czechia.,International Clinical Research Center, St. Anne's University Hospital Brno, Brno, Czechia
| | - Katerina Cechova
- Memory Clinic, Department of Neurology, Second Faculty of Medicine, Charles University and Motol University Hospital, Prague, Czechia.,International Clinical Research Center, St. Anne's University Hospital Brno, Brno, Czechia
| | - Zuzana Nedelska
- Memory Clinic, Department of Neurology, Second Faculty of Medicine, Charles University and Motol University Hospital, Prague, Czechia.,International Clinical Research Center, St. Anne's University Hospital Brno, Brno, Czechia
| | - Jan Laczo
- Memory Clinic, Department of Neurology, Second Faculty of Medicine, Charles University and Motol University Hospital, Prague, Czechia.,International Clinical Research Center, St. Anne's University Hospital Brno, Brno, Czechia
| | - Meng Wang
- Department of Clinical Neurosciences, Cumming School of Medicine, Calgary, AB, Canada.,Department of Community Health Sciences, Cumming School of Medicine, Calgary, AB, Canada
| | - Jakub Hort
- Memory Clinic, Department of Neurology, Second Faculty of Medicine, Charles University and Motol University Hospital, Prague, Czechia.,International Clinical Research Center, St. Anne's University Hospital Brno, Brno, Czechia
| | - Martin Vyhnalek
- Memory Clinic, Department of Neurology, Second Faculty of Medicine, Charles University and Motol University Hospital, Prague, Czechia.,International Clinical Research Center, St. Anne's University Hospital Brno, Brno, Czechia
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42
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Lee H, Xu F, Liu X, Koundal S, Zhu X, Davis J, Yanez D, Schrader J, Stanisavljevic A, Rothman DL, Wardlaw J, Van Nostrand WE, Benveniste H. Diffuse white matter loss in a transgenic rat model of cerebral amyloid angiopathy. J Cereb Blood Flow Metab 2021; 41:1103-1118. [PMID: 32791876 PMCID: PMC8054716 DOI: 10.1177/0271678x20944226] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Diffuse white matter (WM) disease is highly prevalent in elderly with cerebral small vessel disease (cSVD). In humans, cSVD such as cerebral amyloid angiopathy (CAA) often coexists with Alzheimer's disease imposing a significant impediment for characterizing their distinct effects on WM. Here we studied the burden of age-related CAA pathology on WM disease in a novel transgenic rat model of CAA type 1 (rTg-DI). A cohort of rTg-DI and wild-type rats was scanned longitudinally using MRI for characterization of morphometry, cerebral microbleeds (CMB) and WM integrity. In rTg-DI rats, a distinct pattern of WM loss was observed at 9 M and 11 M. MRI also revealed manifestation of small CMB in thalamus at 6 M, which preceded WM loss and progressively enlarged until the moribund disease stage. Histology revealed myelin loss in the corpus callosum and thalamic CMB in all rTg-DI rats, the latter of which manifested in close proximity to occluded and calcified microvessels. The quantitation of CAA load in rTg-DI rats revealed that the most extensive microvascular Aβ deposition occurred in the thalamus. For the first time using in vivo MRI, we show that CAA type 1 pathology alone is associated with a distinct pattern of WM loss.
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Affiliation(s)
- Hedok Lee
- Department of Anesthesiology, Yale School of Medicine, New Haven, CT, USA
| | - Feng Xu
- George and Anne Ryan Institute for Neuroscience and the Department of Biomedical and Pharmaceutical Sciences, University of Rhode Island, RI, USA
| | - Xiaodan Liu
- Department of Anesthesiology, Yale School of Medicine, New Haven, CT, USA
| | - Sunil Koundal
- Department of Anesthesiology, Yale School of Medicine, New Haven, CT, USA
| | - Xiaoyue Zhu
- George and Anne Ryan Institute for Neuroscience and the Department of Biomedical and Pharmaceutical Sciences, University of Rhode Island, RI, USA
| | - Judianne Davis
- George and Anne Ryan Institute for Neuroscience and the Department of Biomedical and Pharmaceutical Sciences, University of Rhode Island, RI, USA
| | - David Yanez
- Department of Anesthesiology, Yale School of Medicine, New Haven, CT, USA
| | - Joseph Schrader
- George and Anne Ryan Institute for Neuroscience and the Department of Biomedical and Pharmaceutical Sciences, University of Rhode Island, RI, USA
| | - Aleksandra Stanisavljevic
- George and Anne Ryan Institute for Neuroscience and the Department of Biomedical and Pharmaceutical Sciences, University of Rhode Island, RI, USA
| | - Douglas L Rothman
- Departments of Radiology and Biomedical Imaging, Yale School of Medicine New Haven, CT, USA.,Department of Biomedical Engineering, Yale School of Medicine New Haven, CT, USA
| | - Joanna Wardlaw
- Brain Research Imaging Centre, Centre for Clinical Brain Sciences, Dementia Research Institute at the University of Edinburgh, Edinburgh, UK
| | - William E Van Nostrand
- George and Anne Ryan Institute for Neuroscience and the Department of Biomedical and Pharmaceutical Sciences, University of Rhode Island, RI, USA
| | - Helene Benveniste
- Department of Anesthesiology, Yale School of Medicine, New Haven, CT, USA.,Department of Biomedical Engineering, Yale School of Medicine New Haven, CT, USA
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Lam S, Lipton RB, Harvey DJ, Zammit AR, Ezzati A. White matter hyperintensities and cognition across different Alzheimer's biomarker profiles. J Am Geriatr Soc 2021; 69:1906-1915. [PMID: 33891712 DOI: 10.1111/jgs.17173] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Revised: 03/15/2021] [Indexed: 12/12/2022]
Abstract
BACKGROUND/OBJECTIVES To examine the association between white matter hyperintensities (WMH) and cognitive domains such as memory and executive function (EF) across different clinical and biomarker categories of Alzheimer's disease (AD). DESIGN Cross-sectional study. SETTING Alzheimer's Disease Neuroimaging Initiative. PARTICIPANTS A total of 216 cognitively normal (CN) participants and 407 participants with mild cognitive impairment (MCI) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) at baseline. MEASUREMENTS Based on the 2018 research framework, participants were classified using AT(N) (amyloid-β deposition [A], pathologic tau [T], and neurodegeneration [(N)]) biomarkers into one of three categories: biomarker negative [A - T- (N)-], amyloid negative but other biomarker positive [A - T ± (N)+ or A - T + (N)±] or amyloid positive [A + T ± (N)±]. Linear regression models were then used to examine the association between WMH and memory composite scores and EF composite scores. RESULTS Higher WMH burden was associated with worse EF in both CN and MCI subgroups while a significant association between WMH and memory was only found in the MCI subgroup. Furthermore, WMH was associated with EF in the group with A - T ± (N)+ or A - T + (N)± biomarker category, but not for A - T - (N)- (normal biomarker) and A + T ± (N) ± (AD pathology). The association between higher WMH and worse memory was independent of amyloid levels in individuals with MCI with evidence of AD pathology. CONCLUSION Vascular disease, as indexed by WMH, independent of AD pathology affects cognitive function in both CN and MCI subgroups. Future studies using the AT(N) research framework should consider white matter lesions as a key biomarker contributing to the clinical presentation of AD.
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Affiliation(s)
- Sharon Lam
- Department of Neurology, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Richard B Lipton
- Department of Neurology, Albert Einstein College of Medicine, Bronx, New York, USA.,Department of Neurology, Montefiore Medical Center, Bronx, New York, USA.,Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Danielle J Harvey
- Department of Public Health Sciences, University of California-Davis, Davis, California, USA
| | - Andrea R Zammit
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA.,Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago, Illinois, USA
| | - Ali Ezzati
- Department of Neurology, Albert Einstein College of Medicine, Bronx, New York, USA.,Department of Neurology, Montefiore Medical Center, Bronx, New York, USA
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Vipin A, Wong BYX, Kumar D, Low A, Ng KP, Kandiah N. Association between white matter hyperintensity load and grey matter atrophy in mild cognitive impairment is not unidirectional. Aging (Albany NY) 2021; 13:10973-10988. [PMID: 33861727 PMCID: PMC8109133 DOI: 10.18632/aging.202977] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 04/05/2021] [Indexed: 12/23/2022]
Abstract
Neuroimaging measures of Alzheimer's disease (AD) include grey matter volume (GMV) alterations in the Default Mode Network (DMN) and Executive Control Network (ECN). Small-vessel cerebrovascular disease, often visualised as white matter hyperintensities (WMH) on MRI, is often seen in AD. However, the relationship between WMH load and GMV needs further examination. We examined the load-dependent influence of WMH on GMV and cognition in 183 subjects. T1-MRI data from 93 Mild Cognitive Impairment (MCI) and 90 cognitively normal subjects were studied and WMH load was categorized into low, medium and high terciles. We examined how differing loads of WMH related to whole-brain voxel-wise and regional DMN and ECN GMV. We further investigated how regional GMV moderated the relationship between WMH and cognition. We found differential load-dependent effects of WMH burden on voxel-wise and regional atrophy in only MCI. At high load, as expected WMH negatively related to both ECN and DMN GMV, however at low load, WMH positively related to ECN GMV. Additionally, negative associations between WMH and memory and executive function were moderated by regional GMV. Our results demonstrate non-unidirectional relationships between WMH load, GMV and cognition in MCI.
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Affiliation(s)
- Ashwati Vipin
- National Neuroscience Institute, Singapore, Singapore
| | | | - Dilip Kumar
- National Neuroscience Institute, Singapore, Singapore
| | - Audrey Low
- National Neuroscience Institute, Singapore, Singapore
| | - Kok Pin Ng
- National Neuroscience Institute, Singapore, Singapore.,Duke-NUS Medical School, Singapore, Singapore.,Lee Kong Chian-Nanyang Technological University, Singapore, Singapore
| | - Nagaendran Kandiah
- National Neuroscience Institute, Singapore, Singapore.,Duke-NUS Medical School, Singapore, Singapore.,Lee Kong Chian-Nanyang Technological University, Singapore, Singapore
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45
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Drake JD, Chambers AB, Ott BR, Daiello LA. Peripheral Markers of Vascular Endothelial Dysfunction Show Independent but Additive Relationships with Brain-Based Biomarkers in Association with Functional Impairment in Alzheimer's Disease. J Alzheimers Dis 2021; 80:1553-1565. [PMID: 33720880 PMCID: PMC8150492 DOI: 10.3233/jad-200759] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
BACKGROUND Cerebrovascular dysfunction confers risk for functional decline in Alzheimer's disease (AD), yet the clinical interplay of these two pathogenic processes is not well understood. OBJECTIVE We utilized Alzheimer's Disease Neuroimaging Initiative (ADNI) data to examine associations between peripherally derived soluble cell adhesion molecules (CAMs) and clinical diagnostic indicators of AD. METHODS Using generalized linear regression models, we examined cross-sectional relationships of soluble plasma vascular cell adhesion molecule-1 (VCAM-1), intercellular adhesion molecule-1 (ICAM-1), and E-Selectin to baseline diagnosis and functional impairment (clinical dementia rating sum-of-boxes, CDR-SB) in the ADNI cohort (n = 112 AD, n = 396 mild cognitive impairment (MCI), n = 58 cognitively normal). We further analyzed associations of these biomarkers with brain-based AD biomarkers in a subset with available cerebrospinal fluid (CSF) data (n = 351). p-values derived from main effects and interaction terms from the linear regressions were used to assess the relationship between independent and dependent variables for significance (significance level was set at 0.05 a priori for all analysis). RESULTS Higher mean VCAM-1 (p = 0.0026) and ICAM-1 (p = 0.0189) levels were found in AD versus MCI groups; however, not in MCI versus cognitively normal groups. Only VCAM-1 was linked with CDR-SB scores (p = 0.0157), and APOE ɛ4 genotype modified this effect. We observed independent, additive associations when VCAM-1 and CSF amyloid-β (Aβ42), total tau, phosphorylated tau (P-tau), or P-tau/Aβ42 (all < p = 0.01) were combined in a CDR-SB model; ICAM-1 showed a similar pattern, but to a lesser extent. CONCLUSION Our findings indicate independent associations of plasma-based vascular biomarkers and CSF biomarkers with AD-related clinical impairment.
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Affiliation(s)
- Jonathan D Drake
- Alzheimer's Disease and Memory Disorders Center, Rhode Island Hospital, Providence, RI, USA.,Department of Neurology, Brown University Warren Alpert Medical School, Providence RI, USA
| | - Alison B Chambers
- Department of Medicine, Brown University Warren Alpert Medical School, Providence RI, USA
| | - Brian R Ott
- Alzheimer's Disease and Memory Disorders Center, Rhode Island Hospital, Providence, RI, USA.,Department of Neurology, Brown University Warren Alpert Medical School, Providence RI, USA
| | - Lori A Daiello
- Alzheimer's Disease and Memory Disorders Center, Rhode Island Hospital, Providence, RI, USA.,Department of Neurology, Brown University Warren Alpert Medical School, Providence RI, USA
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46
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Clancy U, Gilmartin D, Jochems ACC, Knox L, Doubal FN, Wardlaw JM. Neuropsychiatric symptoms associated with cerebral small vessel disease: a systematic review and meta-analysis. Lancet Psychiatry 2021; 8:225-236. [PMID: 33539776 DOI: 10.1016/s2215-0366(20)30431-4] [Citation(s) in RCA: 79] [Impact Index Per Article: 26.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Revised: 09/09/2020] [Accepted: 09/23/2020] [Indexed: 01/13/2023]
Abstract
BACKGROUND Cerebral small vessel disease, a common cause of vascular dementia, is often considered clinically silent before dementia or stroke become apparent. However, some individuals have subtle symptoms associated with acute MRI lesions. We aimed to determine whether neuropsychiatric and cognitive symptoms vary according to small vessel disease burden. METHODS In this systematic review and meta-analysis, we searched MEDLINE, EMBASE, and PsycINFO for articles published in any language from database inception to Jan 24, 2020. We searched for studies assessing anxiety, apathy, delirium, emotional lability, fatigue, personality change, psychosis, dementia-related behavioural symptoms or cognitive symptoms (including subjective memory complaints), and radiological features of cerebral small vessel disease. We extracted reported odds ratios (OR), standardised mean differences (SMD), and correlations, stratified outcomes by disease severity or symptom presence or absence, and pooled data using random-effects meta-analyses, reporting adjusted findings when possible. We assessed the bias on included studies using the Risk of Bias for Non-randomized Studies tool. This study is registered with PROSPERO, CRD42018096673. FINDINGS Of 7119 papers identified, 81 studies including 79 cohorts in total were eligible for inclusion (n=21 730 participants, mean age 69·2 years). Of these 81 studies, 45 (8120 participants) reported effect estimates. We found associations between worse white matter hyperintensity (WMH) severity and apathy (OR 1·41, 95% CI 1·05-1·89) and the adjusted SMD in apathy score between WMH severities was 0·38 (95% CI 0·15-0·61). Worse WMH severity was also associated with delirium (adjusted OR 2·9, 95% CI 1·12-7·55) and fatigue (unadjusted OR 1·63, 95% CI 1·20-2·22). WMHs were not consistently associated with subjective memory complaints (OR 1·34, 95% CI 0·61-2·94) and unadjusted SMD for WMH severity between these groups was 0·08 (95% CI -0·31 to 0·47). Anxiety, dementia-related behaviours, emotional lability, and psychosis were too varied or sparse for meta-analysis; these factors were reviewed narratively. Overall heterogeneity varied from 0% to 79%. Only five studies had a low risk of bias across all domains. INTERPRETATION Apathy, fatigue, and delirium associated independently with worse WMH, whereas subjective cognitive complaints did not. The association of anxiety, dementia-related behaviours, emotional lability, and psychosis with cerebral small vessel disease require further investigation. These symptoms should be assessed longitudinally to improve early clinical detection of small vessel disease and enable prevention trials to happen early in the disease course, long before cognition declines. FUNDING Chief Scientist Office of the Scottish Government, UK Dementia Research Institute, Fondation Leducq, Stroke Association Garfield-Weston Foundation, Alzheimer's Society, and National Health Service Research Scotland.
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Affiliation(s)
- Una Clancy
- Centre for Clinical Brain Sciences and UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Daniel Gilmartin
- Department of Geriatric Medicine, Royal Infirmary of Edinburgh, NHS Lothian, Edinburgh, UK
| | - Angela C C Jochems
- Centre for Clinical Brain Sciences and UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Lucy Knox
- Department of Medicine, Borders General Hospital, NHS Borders, Melrose, UK
| | - Fergus N Doubal
- Centre for Clinical Brain Sciences and UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences and UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK.
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47
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Brett BL, Koch KM, Muftuler LT, Budde M, McCrea MA, Meier TB. Association of Head Impact Exposure with White Matter Macrostructure and Microstructure Metrics. J Neurotrauma 2021; 38:474-484. [PMID: 33003979 PMCID: PMC7875606 DOI: 10.1089/neu.2020.7376] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Prior studies have reported white matter abnormalities associated with a history of cumulative concussion and/or repetitive head impacts (RHI) in contact sport athletes. Growing evidence suggests these abnormalities may begin as more subtle changes earlier in life in active younger athletes. We investigated the relationship between prior concussion and contact sport exposure with multi-modal white matter microstructure and macrostructure using magnetic resonance imaging. High school and collegiate athletes (n = 121) completed up to four evaluations involving neuroimaging. Linear mixed-effects models examined associations of years of contact sport exposure (i.e., RHI proxy) and prior concussion across multiple metrics of white matter, including total white matter volume, diffusion tensor imaging (DTI) metrics, diffusion kurtosis imaging (DKI) metrics, and quantitative susceptibility mapping (QSM). A significant inverse association between cumulative years of contact sport exposure and QSM was observed, F(1, 237.77) = 4.67, p = 0.032. Cumulative contact sport exposure was also associated with decreased radial diffusivity, F(1, 114.56) = 5.81, p = 0.018, as well as elevated fractional anisotropy, F(1, 115.32) = 5.40, p = 0.022, and radial kurtosis, F(1, 113.45) = 4.03, p = 0.047. In contrast, macroscopic white matter volume was not significantly associated with cumulative contact sport exposure (p > 0.05). Concussion history was not significantly associated with QSM, DTI, DKI, or white matter volume (all, p > 0.05). Cumulative contact sport exposure is associated with subtle differences in white matter microstructure, but not gross white matter macrostructure, in young active athletes. Longitudinal follow-up is required to assess the progression of these findings to determine their contribution to potential adverse effects later in life.
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Affiliation(s)
- Benjamin L. Brett
- Department of Neurosurgery, Neurobiology, and Anatomy, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
- Department of Neurology, Neurobiology, and Anatomy, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
- Center for Neurotrauma Research, Neurobiology, and Anatomy, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Kevin M. Koch
- Center for Neurotrauma Research, Neurobiology, and Anatomy, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
- Depertment of Radiology, Neurobiology, and Anatomy, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
- Center for Imaging Research, Neurobiology, and Anatomy, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - L. Tugan Muftuler
- Department of Neurosurgery, Neurobiology, and Anatomy, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
- Center for Neurotrauma Research, Neurobiology, and Anatomy, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
- Depertment of Radiology, Neurobiology, and Anatomy, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Matthew Budde
- Department of Neurosurgery, Neurobiology, and Anatomy, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
- Center for Neurotrauma Research, Neurobiology, and Anatomy, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Michael A. McCrea
- Department of Neurosurgery, Neurobiology, and Anatomy, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
- Department of Neurology, Neurobiology, and Anatomy, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
- Center for Neurotrauma Research, Neurobiology, and Anatomy, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Timothy B. Meier
- Department of Neurosurgery, Neurobiology, and Anatomy, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
- Center for Neurotrauma Research, Neurobiology, and Anatomy, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
- Department of Biomedical Engineering, Neurobiology, and Anatomy, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
- Department of Cell Biology, Neurobiology, and Anatomy, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
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Tsvetanov KA, Henson RNA, Rowe JB. Separating vascular and neuronal effects of age on fMRI BOLD signals. Philos Trans R Soc Lond B Biol Sci 2021; 376:20190631. [PMID: 33190597 PMCID: PMC7741031 DOI: 10.1098/rstb.2019.0631] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/19/2020] [Indexed: 12/14/2022] Open
Abstract
Accurate identification of brain function is necessary to understand the neurobiology of cognitive ageing, and thereby promote well-being across the lifespan. A common tool used to investigate neurocognitive ageing is functional magnetic resonance imaging (fMRI). However, although fMRI data are often interpreted in terms of neuronal activity, the blood oxygenation level-dependent (BOLD) signal measured by fMRI includes contributions of both vascular and neuronal factors, which change differentially with age. While some studies investigate vascular ageing factors, the results of these studies are not well known within the field of neurocognitive ageing and therefore vascular confounds in neurocognitive fMRI studies are common. Despite over 10 000 BOLD-fMRI papers on ageing, fewer than 20 have applied techniques to correct for vascular effects. However, neurovascular ageing is not only a confound in fMRI, but an important feature in its own right, to be assessed alongside measures of neuronal ageing. We review current approaches to dissociate neuronal and vascular components of BOLD-fMRI of regional activity and functional connectivity. We highlight emerging evidence that vascular mechanisms in the brain do not simply control blood flow to support the metabolic needs of neurons, but form complex neurovascular interactions that influence neuronal function in health and disease. This article is part of the theme issue 'Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity'.
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Affiliation(s)
- Kamen A. Tsvetanov
- Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0SZ, UK
- Department of Psychology, University of Cambridge, Cambridge CB2 3EB, UK
| | - Richard N. A. Henson
- Department of Psychiatry, University of Cambridge, Cambridge CB2 0SP, UK
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, UK
| | - James B. Rowe
- Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0SZ, UK
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, UK
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49
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Schaeffer MJ, Chan L, Barber PA. The neuroimaging of neurodegenerative and vascular disease in the secondary prevention of cognitive decline. Neural Regen Res 2021; 16:1490-1499. [PMID: 33433462 PMCID: PMC8323688 DOI: 10.4103/1673-5374.303011] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Structural brain changes indicative of dementia occur up to 20 years before the onset of clinical symptoms. Efforts to modify the disease process after the onset of cognitive symptoms have been unsuccessful in recent years. Thus, future trials must begin during the preclinical phases of the disease before symptom onset. Age related cognitive decline is often the result of two coexisting brain pathologies: Alzheimer’s disease (amyloid, tau, and neurodegeneration) and vascular disease. This review article highlights some of the common neuroimaging techniques used to visualize the accumulation of neurodegenerative and vascular pathologies during the preclinical stages of dementia such as structural magnetic resonance imaging, positron emission tomography, and white matter hyperintensities. We also describe some emerging neuroimaging techniques such as arterial spin labeling, diffusion tensor imaging, and quantitative susceptibility mapping. Recent literature suggests that structural imaging may be the most sensitive and cost-effective marker to detect cognitive decline, while molecular positron emission tomography is primarily useful for detecting disease specific pathology later in the disease process. Currently, the presence of vascular disease on magnetic resonance imaging provides a potential target for optimizing vascular risk reduction strategies, and the presence of vascular disease may be useful when combined with molecular and metabolic markers of neurodegeneration for identifying the risk of cognitive impairment.
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Affiliation(s)
- Morgan J Schaeffer
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
| | - Leona Chan
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
| | - Philip A Barber
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
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50
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Li X, Shen M, Jin Y, Jia S, Zhou Z, Han Z, Zhang X, Tong X, Jiao J. The Effect of Cerebral Small Vessel Disease on the Subtypes of Mild Cognitive Impairment. Front Psychiatry 2021; 12:685965. [PMID: 34335331 PMCID: PMC8322581 DOI: 10.3389/fpsyt.2021.685965] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 06/09/2021] [Indexed: 11/13/2022] Open
Abstract
Objectives: Cerebral small vessel disease (CSVD) is the most common vascular cause of dementia, and mild cognitive impairment (MCI) is an intermediate state between dementia and normal cognitive aging. The present study investigated the main imaging features of CSVD on different MCI subtypes in memory clinics. Methods: A total of 236 patients with MCI and 85 healthy controls were included. One hundred nine amnestic MCI-multiple domains (amMCI), 38 amnestic MCI-single domain (asMCI), 36 non-amnestic MCI-multiple domains (namMCI), and 53 non-amnestic MCI-single domain (nasMCI) patients were diagnosed. All participants were evaluated with the cognitive assessments and imaging features including white matter hyperintensity (WMH), enlarged perivascular spaces (EPVS), cerebral microbleeds (CMBs), and cerebral atrophy according to a standard procedure. Results: The patients with amMCI, namMCI, and nasMCI had more high-grade basal ganglia EPVS compared with healthy controls, while the percentages of high-grade basal ganglia EPVS in the patients with amMCI were also more than those in patients with asMCI, namMCI, and nasMCI. There were more high-grade centrum semiovale EPVS in patients with amMCI in comparison with all other groups. The patients with amMCI and namMCI had more percentages of severe deep and periventricular WMH and deep CMBs compared with healthy controls. All MCI groups had higher scores of the medial temporal lobe atrophy than healthy controls, whereas the scores of the amMCI group were also higher than those of the namMCI and nasMCI groups. Conclusions: There were varied neuroimaging features of CSVD including cerebral atrophy in different MCI groups, which meant that vascular mechanism contributed to the prodromal stage of dementia.
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Affiliation(s)
- Xudong Li
- Department of Cognitive Disorder, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Miaoxin Shen
- Medical School, Xizang Minzu University, Xianyang, China
| | - Yi Jin
- Department of Neurology, China-Japan Friendship Hospital, Beijing, China
| | - Shuhong Jia
- Department of Neurology, China-Japan Friendship Hospital, Beijing, China
| | - Zhi Zhou
- Department of Neurology, China-Japan Friendship Hospital, Beijing, China
| | - Ziling Han
- Department of Cognitive Disorder, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xiangfei Zhang
- Department of Neurology, China-Japan Friendship Hospital, Beijing, China
| | - Xiaopeng Tong
- Medical School, Xizang Minzu University, Xianyang, China
| | - Jinsong Jiao
- Department of Neurology, China-Japan Friendship Hospital, Beijing, China
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