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Ji F, Wei JLK, Leng S, Zhong L, Tan RS, Gao F, Ng KK, Leong RLF, Pasternak O, Chee MWL, Koh WP, Zhou JH, Koh AS. Heart-brain mapping: Cardiac atrial function is associated with distinct cerebral regions with high free water in older adults. J Cereb Blood Flow Metab 2024; 44:1218-1230. [PMID: 38295860 PMCID: PMC11179607 DOI: 10.1177/0271678x241229581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 12/01/2023] [Accepted: 12/21/2023] [Indexed: 06/13/2024]
Abstract
Left atrial (LA) dysfunction has been linked to cognitive impairment and cerebrovascular dysfunction. Higher brain free-water (FW) derived from diffusion-MRI was associated with early and subtle cerebrovascular dysfunction and more severe cognitive impairment. We hypothesized that LA dysfunction would correlate with higher brain free-water (FW) among healthy older adults. 56 community older adults (73.13 ± 3.56 years; 24 female) with normal cognition and without known cardiovascular disease who had undergone cardiac-MRI, brain-MRI, and neuropsychological assessments were included. Whole-brain voxel-level general linear models were constructed to correlate brain FW measures with LA indices. We found lower scores in LA function measures were related to higher grey matter (GM) FW in regions including orbital frontal and right temporal regions (p < 0.01, family-wise error corrected). In parallel, LA dysfunction was associated with higher FW in white matter (WM) fibres including superior longitudinal fasciculus, internal capsule, and superior corona radiata. However, LA dysfunction was not related to WM tissue reduction and GM cortical thinning. Moreover, these cardiac-related higher brain FW were associated with lower executive function and higher serum B-type natriuretic peptide (p < 0.05, Holm-Bonferroni corrected). These findings may have implications for anti-ageing preventive strategies targeting cardiac and cerebral vascular functions to improve heart and brain outcomes.
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Affiliation(s)
- Fang Ji
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Joseph Lim Kai Wei
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Shuang Leng
- National Heart Centre Singapore, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Liang Zhong
- National Heart Centre Singapore, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Ru San Tan
- National Heart Centre Singapore, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Fei Gao
- National Heart Centre Singapore, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Kwun Kei Ng
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Ruth LF Leong
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Ofer Pasternak
- Departments of Psychiatry and Radiology, Brigham and Women’s Hospital, Harvard Medical School, USA
| | - Michael WL Chee
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Woon-Puay Koh
- Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Juan Helen Zhou
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
| | - Angela S Koh
- National Heart Centre Singapore, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
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Seitz-Holland J, Alemán-Gómez Y, Cho KIK, Pasternak O, Cleusix M, Jenni R, Baumann PS, Klauser P, Conus P, Hagmann P, Do KQ, Kubicki M, Dwir D. Matrix metalloproteinase 9 (MMP-9) activity, hippocampal extracellular free water, and cognitive deficits are associated with each other in early phase psychosis. Neuropsychopharmacology 2024; 49:1140-1150. [PMID: 38431757 PMCID: PMC11109110 DOI: 10.1038/s41386-024-01814-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 12/18/2023] [Accepted: 01/29/2024] [Indexed: 03/05/2024]
Abstract
Increasing evidence points toward the role of the extracellular matrix, specifically matrix metalloproteinase 9 (MMP-9), in the pathophysiology of psychosis. MMP-9 is a critical regulator of the crosstalk between peripheral and central inflammation, extracellular matrix remodeling, hippocampal development, synaptic pruning, and neuroplasticity. Here, we aim to characterize the relationship between plasma MMP-9 activity, hippocampal microstructure, and cognition in healthy individuals and individuals with early phase psychosis. We collected clinical, blood, and structural and diffusion-weighted magnetic resonance imaging data from 39 individuals with early phase psychosis and 44 age and sex-matched healthy individuals. We measured MMP-9 plasma activity, hippocampal extracellular free water (FW) levels, and hippocampal volumes. We used regression analyses to compare MMP-9 activity, hippocampal FW, and volumes between groups. We then examined associations between MMP-9 activity, FW levels, hippocampal volumes, and cognitive performance assessed with the MATRICS battery. All analyses were controlled for age, sex, body mass index, cigarette smoking, and years of education. Individuals with early phase psychosis demonstrated higher MMP-9 activity (p < 0.0002), higher left (p < 0.05) and right (p < 0.05) hippocampal FW levels, and lower left (p < 0.05) and right (p < 0.05) hippocampal volume than healthy individuals. MMP-9 activity correlated positively with hippocampal FW levels (all participants and individuals with early phase psychosis) and negatively with hippocampal volumes (all participants and healthy individuals). Higher MMP-9 activity and higher hippocampal FW levels were associated with slower processing speed and worse working memory performance in all participants. Our findings show an association between MMP-9 activity and hippocampal microstructural alterations in psychosis and an association between MMP-9 activity and cognitive performance. Further, more extensive longitudinal studies should examine the therapeutic potential of MMP-9 modulators in psychosis.
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Affiliation(s)
- Johanna Seitz-Holland
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
| | - Yasser Alemán-Gómez
- Connectomics Lab, Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Medical Image Analysis Laboratory, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Kang Ik K Cho
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ofer Pasternak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Martine Cleusix
- Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Service of General Psychiatry, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Raoul Jenni
- Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Service of General Psychiatry, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Philipp S Baumann
- Service of General Psychiatry, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Paul Klauser
- Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Service of Child and Adolescent Psychiatry, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Philippe Conus
- Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Service of General Psychiatry, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Patric Hagmann
- Connectomics Lab, Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Kim Q Do
- Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Marek Kubicki
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Daniella Dwir
- Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
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Martirosian RA, Wiedner CD, Sanchez J, Mun KT, Marla K, Teran C, Thirion M, Liebeskind DS, McGrath ER, Zucker JM, Bernal R, Beiser AS, DeCarli C, Himali JJ, Seshadri S, Hinman JD. Association of Incident Stroke Risk With an IL-18-Centered Inflammatory Network Biomarker Composite. Stroke 2024; 55:1601-1608. [PMID: 38690658 DOI: 10.1161/strokeaha.123.044719] [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: 08/28/2023] [Accepted: 03/20/2024] [Indexed: 05/02/2024]
Abstract
BACKGROUND A coordinated network of circulating inflammatory molecules centered on the pleotropic pro-atherogenic cytokine interleukin-18 (IL-18) is linked to cerebral small vessel disease. We sought to validate the association of this inflammatory biomarker network with incident stroke risk, cognitive impairment, and imaging metrics in a sample of the Framingham Offspring Cohort. METHODS Using available baseline measurements of serum levels of IL-18, GDF (growth and differentiation factor)-15, soluble form of receptor for advanced glycation end products, myeloperoxidase, and MCP-1 (monocyte chemoattractant protein-1) from Exam 7 of the Framingham Offspring Cohort (1998-2001), we constructed a population-normalized, equally weighted log-transformed mean Z-score value representing the average level of each serum analyte to create an inflammatory composite score (ICS5). Multivariable regression models were used to determine the association of ICS5 with incident stroke, brain magnetic resonance imaging features, and cognitive testing performance. RESULTS We found a significant association between ICS5 score and increased risk for incident all-cause stroke (hazard ratio, 1.48 [95% CI, 1.05-2.08]; P=0.024) and ischemic stroke (hazard ratio, 1.51 [95% CI, 1.03-2.21]; P=0.033) in the Exam 7 cohort of 2201 subjects (mean age 62±9 years; 54% female) aged 45+ years with an all-cause incident stroke rate of 6.1% (135/2201) and ischemic stroke rate of 4.9% (108/2201). ICS5 and its component serum markers are all associated with the Framingham Stroke Risk Profile score (β±SE, 0.19±0.02; P<0.0001). In addition, we found a significant inverse association of ICS5 with a global cognitive score, derived from a principal components analysis of the neuropsychological battery used in the Framingham cohort (-0.08±0.03; P=0.019). No association of ICS5 with magnetic resonance imaging metrics of cerebral small vessel disease was observed. CONCLUSIONS Circulating serum levels of inflammatory biomarkers centered on IL-18 are associated with an increased risk of stroke and cognitive impairment in the Framingham Offspring Cohort. Linking specific inflammatory pathways to cerebral small vessel disease may enhance individualized quantitative risk assessment for future stroke and vascular cognitive impairment.
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Affiliation(s)
- Richard A Martirosian
- David Geffen School of Medicine, University of California Los Angeles (R.A.M., J.S., K.T.M., K.M., C.T., M.T., D.S.L., J.D.H.)
| | - Crystal D Wiedner
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (C.D.W., R.B., J.J.H., S.S.), University of Texas Health Science Center at San Antonio
| | - Jasmin Sanchez
- David Geffen School of Medicine, University of California Los Angeles (R.A.M., J.S., K.T.M., K.M., C.T., M.T., D.S.L., J.D.H.)
| | - Katherine T Mun
- David Geffen School of Medicine, University of California Los Angeles (R.A.M., J.S., K.T.M., K.M., C.T., M.T., D.S.L., J.D.H.)
| | - Kiran Marla
- David Geffen School of Medicine, University of California Los Angeles (R.A.M., J.S., K.T.M., K.M., C.T., M.T., D.S.L., J.D.H.)
| | - Cristina Teran
- David Geffen School of Medicine, University of California Los Angeles (R.A.M., J.S., K.T.M., K.M., C.T., M.T., D.S.L., J.D.H.)
| | - Marissa Thirion
- David Geffen School of Medicine, University of California Los Angeles (R.A.M., J.S., K.T.M., K.M., C.T., M.T., D.S.L., J.D.H.)
| | - David S Liebeskind
- David Geffen School of Medicine, University of California Los Angeles (R.A.M., J.S., K.T.M., K.M., C.T., M.T., D.S.L., J.D.H.)
| | - Emer R McGrath
- Framingham Heart Study, MA (E.R.M.G., J.M.Z., A.S.B., C.D.C., J.J.H., S.S.)
- HRB Clinical Research Facility, School of Medicine, University of Galway, Ireland (E.R.M.G.)
| | - Jared M Zucker
- Framingham Heart Study, MA (E.R.M.G., J.M.Z., A.S.B., C.D.C., J.J.H., S.S.)
| | - Rebecca Bernal
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (C.D.W., R.B., J.J.H., S.S.), University of Texas Health Science Center at San Antonio
| | - Alexa S Beiser
- Framingham Heart Study, MA (E.R.M.G., J.M.Z., A.S.B., C.D.C., J.J.H., S.S.)
- Department of Neurology, Boston University School of Medicine, MA (A.S.B., J.J.H., S.S.)
- Department of Biostatistics, Boston University School of Public Health, MA (A.S.B., J.J.H.)
| | - Charles DeCarli
- Framingham Heart Study, MA (E.R.M.G., J.M.Z., A.S.B., C.D.C., J.J.H., S.S.)
- Department of Neurology, University of California Davis, Sacramento (C.D.C.)
| | - Jayandra J Himali
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (C.D.W., R.B., J.J.H., S.S.), University of Texas Health Science Center at San Antonio
- Department of Population Health Sciences (J.J.H.), University of Texas Health Science Center at San Antonio
- Framingham Heart Study, MA (E.R.M.G., J.M.Z., A.S.B., C.D.C., J.J.H., S.S.)
- Department of Neurology, Boston University School of Medicine, MA (A.S.B., J.J.H., S.S.)
- Department of Biostatistics, Boston University School of Public Health, MA (A.S.B., J.J.H.)
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (C.D.W., R.B., J.J.H., S.S.), University of Texas Health Science Center at San Antonio
- Framingham Heart Study, MA (E.R.M.G., J.M.Z., A.S.B., C.D.C., J.J.H., S.S.)
- Department of Neurology, Boston University School of Medicine, MA (A.S.B., J.J.H., S.S.)
| | - Jason D Hinman
- David Geffen School of Medicine, University of California Los Angeles (R.A.M., J.S., K.T.M., K.M., C.T., M.T., D.S.L., J.D.H.)
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Siow I, Narasimhalu K, Lee KS, Tan HK, Ting SKS, Hameed S, Chang HM, De Silva DA, Chen CLH, Tan EK. Predictors of post stroke cognitive impairment: VITATOPS cognition substudy. J Stroke Cerebrovasc Dis 2024; 33:107718. [PMID: 38604352 DOI: 10.1016/j.jstrokecerebrovasdis.2024.107718] [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: 10/21/2023] [Revised: 01/31/2024] [Accepted: 04/08/2024] [Indexed: 04/13/2024] Open
Abstract
INTRODUCTION Post stroke cognitive impairment (PSCI) is a common complication of ischemic stroke. PSCI can involve different depending on clinical and stroke related characteristics. The aim of this study is to determine the factors associated with impairments in specific cognitive domains. METHODS The Vitamins to Prevent Stroke (VITATOPS) trial is a large, multinational randomised controlled trial. In this substudy, consecutive patients admitted for ischaemic stroke or transient ischaemic attack (TIA) at a tertiary hospital in Singapore were included. PSCI was defined as impairment of any of the six cognitive subgroups - visuoconstruction, attention, verbal memory, language, visual memory and visuomotor function - that were assessed annually for up to five years. Univariate and multivariate Cox proportional hazard models were used to determine factors associated with impairments in each of these cognitive domains. RESULTS A total of 736 patients were included in this study, of which 173 (23.5 %) developed cognitive impairment. Out of the six cognitive domains, the greatest proportion of patients had an impairment in visuoconstruction (26.4 %) followed by attention (19.8 %), verbal memory (18.3 %), language (17.5 %), visual memory (17.3 %) and visuomotor function (14.8 %). Patients with posterior circulation cerebral infarction (POCI) as the index stroke subtype had higher rates of cognitive impairment. Further subgroup analyses show that Indian race and advanced age were predictive of language impairment, whilst fewer years of education and POCI were predictive of verbal memory impairment. POCI was predictive of visual memory impairment, and advanced age and POCI were predictive of visuomotor function impairment. CONCLUSION We identified visuoconstruction and attention domains to be the most affected in our Asian cohort of PSCI. Advanced age, lower levels of education, posterior circulation strokes and concomitant comorbidities such as peripheral artery disease are independent predictors of PSCI.
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Affiliation(s)
- Isabel Siow
- Ministry of Health Holdings Singapore, Singapore
| | - Kaavya Narasimhalu
- Department of Neurology, National Neuroscience Institute (Singapore General Hospital Campus), Singapore.
| | - Keng Siang Lee
- Department of Neurosurgery, King's College Hospital, London, UK; Department of Basic and Clinical Neurosciences, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London, UK
| | | | - Simon Kang Seng Ting
- Department of Neurology, National Neuroscience Institute (Singapore General Hospital Campus), Singapore
| | - Shahul Hameed
- Department of Neurology, National Neuroscience Institute (Singapore General Hospital Campus), Singapore
| | - Hui Meng Chang
- Department of Neurology, National Neuroscience Institute (Singapore General Hospital Campus), Singapore
| | - Deidre Anne De Silva
- Department of Neurology, National Neuroscience Institute (Singapore General Hospital Campus), Singapore
| | - Christopher Li Hsian Chen
- Memory Aging and Cognition Centre, Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Eng King Tan
- Department of Neurology, National Neuroscience Institute (Singapore General Hospital Campus), Singapore
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Won J, Maillard P, Shan K, Ashley J, Cardim D, Zhu DC, Zhang R. Association of Blood Pressure With Brain White Matter Microstructural Integrity Assessed With MRI Diffusion Tensor Imaging in Healthy Young Adults. Hypertension 2024; 81:1145-1155. [PMID: 38487873 PMCID: PMC11023804 DOI: 10.1161/hypertensionaha.123.22337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Accepted: 02/28/2024] [Indexed: 04/19/2024]
Abstract
BACKGROUND High blood pressure (BP) in middle-aged and older adults is associated with a brain white matter (WM) microstructural abnormality. However, little evidence is available in healthy young adults. We investigated the associations between high BP and WM microstructural integrity in young adults. METHODS This study included 1015 healthy young adults (542 women, 22-37 years) from the Human Connectome Project. Brachial systolic and diastolic BP were measured using a semiautomatic or manual sphygmomanometer. Diffusion-weighted magnetic resonance imaging was acquired to obtain diffusion tensor imaging metrics of free water (FW) content, FW-corrected WM fractional anisotropy, axial diffusivity, radial diffusivity, and mean diffusivity. Using whole-brain voxel-wise linear regression models and ANCOVA, we examined associations of BP and hypertension stage with diffusion tensor imaging metrics after adjusting for age, sex, education, body mass index, smoking status, alcohol consumption history, and differences in the b value used for diffusion magnetic resonance imaging. RESULTS Systolic and diastolic BP of the sample (mean±SD) were 122.8±13.0 and 76.0±9.9 mm Hg, respectively. Associations of BP with diffusion tensor imaging metrics revealed regional heterogeneity for FW-corrected fractional anisotropy. High BP and high hypertension stage were associated with higher FW and lower FW-corrected axial diffusivity, FW-corrected radial diffusivity, and FW-corrected mean diffusivity. Moreover, associations of high diastolic BP and hypertension stage with high FW were found only in men not in women. CONCLUSIONS High BP in young adults is associated with altered brain WM microstructural integrity, suggesting that high BP may have damaging effects on brain WM microstructural integrity in early adulthood, particularly in men.
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Affiliation(s)
- Junyeon Won
- Institute for Exercise and Environmental Medicine, Texas Health Presbyterian Hospital, Dallas, TX
- Department of Neurology, University of Texas Southwestern Medical Center, Dallas, TX
| | - Pauline Maillard
- Department of Neurology, University of California, Davis, CA, USA
| | - Kevin Shan
- Institute for Exercise and Environmental Medicine, Texas Health Presbyterian Hospital, Dallas, TX
- Department of Neurology, University of Texas Southwestern Medical Center, Dallas, TX
| | - John Ashley
- Institute for Exercise and Environmental Medicine, Texas Health Presbyterian Hospital, Dallas, TX
- Department of Neurology, University of Texas Southwestern Medical Center, Dallas, TX
| | - Danilo Cardim
- Institute for Exercise and Environmental Medicine, Texas Health Presbyterian Hospital, Dallas, TX
- Department of Neurology, University of Texas Southwestern Medical Center, Dallas, TX
| | - David C. Zhu
- Department of Radiology and Cognitive Imaging Research Center, Michigan State University, East Lansing, Michigan, USA
| | - Rong Zhang
- Institute for Exercise and Environmental Medicine, Texas Health Presbyterian Hospital, Dallas, TX
- Department of Neurology, University of Texas Southwestern Medical Center, Dallas, TX
- Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX
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Clancy U, Kancheva AK, Valdés Hernández MDC, Jochems ACC, Muñoz Maniega S, Quinn TJ, Wardlaw JM. Imaging Biomarkers of VCI: A Focused Update. Stroke 2024; 55:791-800. [PMID: 38445496 DOI: 10.1161/strokeaha.123.044171] [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] [Indexed: 03/07/2024]
Abstract
Vascular cognitive impairment is common after stroke, in memory clinics, medicine for the elderly services, and undiagnosed in the community. Vascular disease is said to be the second most common cause of dementia after Alzheimer disease, yet vascular dysfunction is now known to predate cognitive decline in Alzheimer disease, and most dementias at older ages are mixed. Neuroimaging has a major role in identifying the proportion of vascular versus other likely pathologies in patients with cognitive impairment. Here, we aim to provide a pragmatic but evidence-based summary of the current state of potential imaging biomarkers, focusing on magnetic resonance imaging and computed tomography, which are relevant to diagnosing, estimating prognosis, monitoring vascular cognitive impairment, and incorporating our own experiences. We focus on markers that are well-established, with a known profile of association with cognitive measures, but also consider more recently described, including quantitative tissue markers of vascular injury. We highlight the gaps in accessibility and translation to more routine clinical practice.
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Affiliation(s)
- Una Clancy
- Centre for Clinical Brain Sciences and UK Dementia Research Institute, The University of Edinburgh, United Kingdom (U.C., M.d.C.V.H. A.C.C.J., S.M.M., J.M.W.)
| | - Angelina K Kancheva
- School of Cardiovascular and Metabolic Health, University of Glasgow, United Kingdom (A.K.K., T.J.Q.)
| | - Maria Del C Valdés Hernández
- Centre for Clinical Brain Sciences and UK Dementia Research Institute, The University of Edinburgh, United Kingdom (U.C., M.d.C.V.H. A.C.C.J., S.M.M., J.M.W.)
| | - Angela C C Jochems
- Centre for Clinical Brain Sciences and UK Dementia Research Institute, The University of Edinburgh, United Kingdom (U.C., M.d.C.V.H. A.C.C.J., S.M.M., J.M.W.)
| | - Susana Muñoz Maniega
- Centre for Clinical Brain Sciences and UK Dementia Research Institute, The University of Edinburgh, United Kingdom (U.C., M.d.C.V.H. A.C.C.J., S.M.M., J.M.W.)
| | - Terence J Quinn
- School of Cardiovascular and Metabolic Health, University of Glasgow, United Kingdom (A.K.K., T.J.Q.)
| | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences and UK Dementia Research Institute, The University of Edinburgh, United Kingdom (U.C., M.d.C.V.H. A.C.C.J., S.M.M., J.M.W.)
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Abdolahi F, Yu V, Varma R, Zhou X, Wang RK, D'Orazio LM, Zhao C, Jann K, Wang DJ, Kashani AH, Jiang X. Retinal perfusion is linked to cognition and brain MRI biomarkers in Black Americans. Alzheimers Dement 2024; 20:858-868. [PMID: 37800578 PMCID: PMC10917050 DOI: 10.1002/alz.13469] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 08/14/2023] [Accepted: 08/17/2023] [Indexed: 10/07/2023]
Abstract
INTRODUCTION We investigated whether retinal capillary perfusion is a biomarker of cerebral small vessel disease and impaired cognition among Black Americans, an understudied group at higher risk for dementia. METHODS We enrolled 96 Black Americans without known cognitive impairment. Four retinal perfusion measures were derived using optical coherence tomography angiography. Neurocognitive assessment and brain magnetic resonance imaging (MRI) were performed. Multiple linear regression analyses were performed. RESULTS Lower retinal capillary perfusion was correlated with worse Oral Symbol Digit Test (P < = 0.005) and Fluid Cognition Composite scores (P < = 0.02), but not with the Crystallized Cognition Composite score (P > = 0.41). Lower retinal perfusion was also correlated with higher free water and peak width of skeletonized mean diffusivity, and lower fractional anisotropy (all P < 0.05) on MRI (N = 35). DISCUSSION Lower retinal capillary perfusion is associated with worse information processing, fluid cognition, and MRI biomarkers of cerebral small vessel disease, but is not related to crystallized cognition.
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Affiliation(s)
- Farzan Abdolahi
- Department of OphthalmologyUniversity of Southern California Keck School of MedicineLos AngelesCaliforniaUSA
| | - Victoria Yu
- Department of OphthalmologyUniversity of Southern California Keck School of MedicineLos AngelesCaliforniaUSA
| | - Rohit Varma
- Southern California Eye InstituteCHA Hollywood Presbyterian Medical CenterLos AngelesCaliforniaUSA
| | - Xiao Zhou
- Department of BioengineeringUniversity of WashingtonSeattleWashingtonUSA
| | - Ruikang K. Wang
- Department of BioengineeringUniversity of WashingtonSeattleWashingtonUSA
- Department of OphthalmologyUniversity of WashingtonSeattleWashingtonUSA
| | - Lina M. D'Orazio
- Department of NeurologyUniversity of Southern California Keck School of MedicineLos AngelesCaliforniaUSA
| | - Chenyang Zhao
- Laboratory of FMRI TechnologyStevens Neuroimaging and Informatics InstituteUniversity of Southern California Keck School of MedicineLos AngelesCaliforniaUSA
| | - Kay Jann
- Laboratory of FMRI TechnologyStevens Neuroimaging and Informatics InstituteUniversity of Southern California Keck School of MedicineLos AngelesCaliforniaUSA
| | - Danny J. Wang
- Department of NeurologyUniversity of Southern California Keck School of MedicineLos AngelesCaliforniaUSA
- Laboratory of FMRI TechnologyStevens Neuroimaging and Informatics InstituteUniversity of Southern California Keck School of MedicineLos AngelesCaliforniaUSA
| | - Amir H. Kashani
- Department of OphthalmologyWilmer Eye InstituteJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Xuejuan Jiang
- Department of OphthalmologyUniversity of Southern California Keck School of MedicineLos AngelesCaliforniaUSA
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Fernandez L, Corben LA, Bilal H, Delatycki MB, Egan GF, Harding IH. Free-Water Imaging in Friedreich Ataxia Using Multi-Compartment Models. Mov Disord 2024; 39:370-379. [PMID: 37927246 DOI: 10.1002/mds.29648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 09/14/2023] [Accepted: 10/11/2023] [Indexed: 11/07/2023] Open
Abstract
BACKGROUND The neurological phenotype of Friedreich ataxia (FRDA) is characterized by neurodegeneration and neuroinflammation in the cerebellum and brainstem. Novel neuroimaging approaches quantifying brain free-water using diffusion magnetic resonance imaging (dMRI) are potentially more sensitive to these processes than standard imaging markers. OBJECTIVES To quantify the extent of free-water and microstructural change in FRDA-relevant brain regions using neurite orientation dispersion and density imaging (NODDI), and bitensor diffusion tensor imaging (btDTI). METHOD Multi-shell dMRI was acquired from 14 individuals with FRDA and 14 controls. Free-water measures from NODDI (FISO) and btDTI (FW) were compared between groups in the cerebellar cortex, dentate nuclei, cerebellar peduncles, and brainstem. The relative sensitivity of the free-water measures to group differences was compared to microstructural measures of NODDI intracellular volume, free-water corrected fractional anisotropy, and conventional uncorrected fractional anisotropy. RESULTS In individuals with FRDA, FW was elevated in the cerebellar cortex, peduncles (excluding middle), dentate, and brainstem (P < 0.005). FISO was elevated primarily in the cerebellar lobules (P < 0.001). On average, FW effect sizes were larger than all other markers (mean ηρ 2 = 0.43), although microstructural measures also had very large effects in the superior and inferior cerebellar peduncles and brainstem (ηρ 2 > 0.37). Across all regions and metrics, effect sizes were largest in the superior cerebellar peduncles (ηρ 2 > 0.46). CONCLUSIONS Multi-compartment diffusion measures of free-water and neurite integrity distinguish FRDA from controls with large effects. Free-water magnitude in the brainstem and cerebellum provided the greatest distinction between groups. This study supports further applications of multi-compartment diffusion modeling, and investigations of free-water as a measure of disease expression and progression in FRDA. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Lara Fernandez
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Victoria, Australia
| | - Louise A Corben
- Bruce Lefroy Centre for Genetic Health Research, Murdoch Children's Research Institute, Parkville, Victoria, Australia
- Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia
- Turner Institute for Brain and Mental Health & School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
| | - Hiba Bilal
- Turner Institute for Brain and Mental Health & School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
| | - Martin B Delatycki
- Bruce Lefroy Centre for Genetic Health Research, Murdoch Children's Research Institute, Parkville, Victoria, Australia
- Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia
- Victorian Clinical Genetics Service, Melbourne, Victoria, Australia
| | - Gary F Egan
- Turner Institute for Brain and Mental Health & School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Melbourne, Victoria, Australia
| | - Ian H Harding
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Melbourne, Victoria, Australia
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Baril AA, Kojis DJ, Himali JJ, Decarli CS, Sanchez E, Johnson KA, El Fakhri G, Thibault E, Yiallourou SR, Himali D, Cavuoto MG, Pase MP, Beiser AS, Seshadri S. Association of Sleep Duration and Change Over Time With Imaging Biomarkers of Cerebrovascular, Amyloid, Tau, and Neurodegenerative Pathology. Neurology 2024; 102:e207807. [PMID: 38165370 PMCID: PMC10834132 DOI: 10.1212/wnl.0000000000207807] [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] [Received: 04/13/2023] [Accepted: 10/13/2023] [Indexed: 01/03/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Both short and long sleep duration were previously associated with incident dementia, but underlying mechanisms remain unclear. We evaluated how self-reported sleep duration and its change over time associate with (A)myloid, (T)au, (N)eurodegeneration, and (V)ascular neuroimaging markers of Alzheimer disease. METHODS Two Framingham Heart Study overlapping samples were studied: participants who underwent 11C-Pittsburg Compound B amyloid and 18F-flortaucipir tau PET imaging and participants who underwent an MRI. MRI metrics estimated neurodegeneration (total brain volume) and cerebrovascular injuries (white matter hyperintensities [WMHs] volume, covert brain infarcts, free-water [FW] fraction). Self-reported sleep duration was assessed and split into categories both at the time of neuroimaging testing and approximately 13 years before: short ≤6 hours. average 7-8 hours, and long ≥9 hours. Logistic and linear regression models were used to examine sleep duration and neuroimaging metrics. RESULTS The tested cohort was composed of 271 participants (age 53.6 ± 8.0 years; 51% male) in the PET imaging sample and 2,165 participants (age 61.3 ± 11.1 years; 45% male) in the MRI sample. No fully adjusted association was observed between cross-sectional sleep duration and neuroimaging metrics. In fully adjusted models compared with consistently sleeping 7-8 hours, groups transitioning to a longer sleep duration category over time had higher FW fraction (short to average β [SE] 0.0062 [0.0024], p = 0.009; short to long β [SE] 0.0164 [0.0076], p = 0.031; average to long β [SE] 0.0083 [0.0022], p = 0.002), and those specifically going from average to long sleep duration also had higher WMH burden (β [SE] 0.29 [0.11], p = 0.007). The opposite associations (lower WMH and FW) were observed in participants consistently sleeping ≥9 hours as compared with people consistently sleeping 7-8 hours in fully adjusted models (β [SE] -0.43 [0.20], p = 0.028; β [SE] -0.019 [0.004], p = 0.020). Each hour of increasing sleep (continuous, β [SE] 0.12 [0.04], p = 0.003; β [SE] 0.002 [0.001], p = 0.021) and extensive increase in sleep duration (≥2 hours vs 0 ± 1 hour change; β [SE] 0.24 [0.10], p = 0.019; β [SE] 0.0081 [0.0025], p = 0.001) over time was associated with higher WMH burden and FW fraction in fully adjusted models. Sleep duration change was not associated with PET amyloid or tau outcomes. DISCUSSION Longer self-reported sleep duration over time was associated with neuroimaging biomarkers of cerebrovascular pathology as evidenced by higher WMH burden and FW fraction. A longer sleep duration extending over time may be an early change in the neurodegenerative trajectory.
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Affiliation(s)
- Andrée-Ann Baril
- From the Douglas Mental Health University Institute (A.-A.B.), McGill University, Montreal, Quebec, Canada; The Framingham Heart Study (A.-A.B., D.J.K., J.J.H., D.H., M.P.P., A.S.B., S.S.); Boston University School of Public Health (D.J.K., J.J.H.), MA; Boston University School of Medicine (J.J.H., S.S.), MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (J.J.H., S.S.), UT Health San Antonio, TX; UC Davis Center for Neuroscience (C.S.D.), CA; Sunnybrook Research Institute (E.S.), University of Toronto, Ontario, Canada; Harvard Aging Brain Institute (K.A.J.), Harvard Medical School, Boston, MA; Gordon Center for Medical Imaging (G.E.F., E.T.), Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston; Turner Institute for Brain and Mental Health (S.R.Y., M.G.C., M.P.P.), Monash University, Clayton, Australia; and Harvard T.H. Chan School of Public Health (M.P.P.), Harvard University, Boston, MA
| | - Daniel J Kojis
- From the Douglas Mental Health University Institute (A.-A.B.), McGill University, Montreal, Quebec, Canada; The Framingham Heart Study (A.-A.B., D.J.K., J.J.H., D.H., M.P.P., A.S.B., S.S.); Boston University School of Public Health (D.J.K., J.J.H.), MA; Boston University School of Medicine (J.J.H., S.S.), MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (J.J.H., S.S.), UT Health San Antonio, TX; UC Davis Center for Neuroscience (C.S.D.), CA; Sunnybrook Research Institute (E.S.), University of Toronto, Ontario, Canada; Harvard Aging Brain Institute (K.A.J.), Harvard Medical School, Boston, MA; Gordon Center for Medical Imaging (G.E.F., E.T.), Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston; Turner Institute for Brain and Mental Health (S.R.Y., M.G.C., M.P.P.), Monash University, Clayton, Australia; and Harvard T.H. Chan School of Public Health (M.P.P.), Harvard University, Boston, MA
| | - Jayandra J Himali
- From the Douglas Mental Health University Institute (A.-A.B.), McGill University, Montreal, Quebec, Canada; The Framingham Heart Study (A.-A.B., D.J.K., J.J.H., D.H., M.P.P., A.S.B., S.S.); Boston University School of Public Health (D.J.K., J.J.H.), MA; Boston University School of Medicine (J.J.H., S.S.), MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (J.J.H., S.S.), UT Health San Antonio, TX; UC Davis Center for Neuroscience (C.S.D.), CA; Sunnybrook Research Institute (E.S.), University of Toronto, Ontario, Canada; Harvard Aging Brain Institute (K.A.J.), Harvard Medical School, Boston, MA; Gordon Center for Medical Imaging (G.E.F., E.T.), Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston; Turner Institute for Brain and Mental Health (S.R.Y., M.G.C., M.P.P.), Monash University, Clayton, Australia; and Harvard T.H. Chan School of Public Health (M.P.P.), Harvard University, Boston, MA
| | - Charles S Decarli
- From the Douglas Mental Health University Institute (A.-A.B.), McGill University, Montreal, Quebec, Canada; The Framingham Heart Study (A.-A.B., D.J.K., J.J.H., D.H., M.P.P., A.S.B., S.S.); Boston University School of Public Health (D.J.K., J.J.H.), MA; Boston University School of Medicine (J.J.H., S.S.), MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (J.J.H., S.S.), UT Health San Antonio, TX; UC Davis Center for Neuroscience (C.S.D.), CA; Sunnybrook Research Institute (E.S.), University of Toronto, Ontario, Canada; Harvard Aging Brain Institute (K.A.J.), Harvard Medical School, Boston, MA; Gordon Center for Medical Imaging (G.E.F., E.T.), Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston; Turner Institute for Brain and Mental Health (S.R.Y., M.G.C., M.P.P.), Monash University, Clayton, Australia; and Harvard T.H. Chan School of Public Health (M.P.P.), Harvard University, Boston, MA
| | - Erlan Sanchez
- From the Douglas Mental Health University Institute (A.-A.B.), McGill University, Montreal, Quebec, Canada; The Framingham Heart Study (A.-A.B., D.J.K., J.J.H., D.H., M.P.P., A.S.B., S.S.); Boston University School of Public Health (D.J.K., J.J.H.), MA; Boston University School of Medicine (J.J.H., S.S.), MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (J.J.H., S.S.), UT Health San Antonio, TX; UC Davis Center for Neuroscience (C.S.D.), CA; Sunnybrook Research Institute (E.S.), University of Toronto, Ontario, Canada; Harvard Aging Brain Institute (K.A.J.), Harvard Medical School, Boston, MA; Gordon Center for Medical Imaging (G.E.F., E.T.), Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston; Turner Institute for Brain and Mental Health (S.R.Y., M.G.C., M.P.P.), Monash University, Clayton, Australia; and Harvard T.H. Chan School of Public Health (M.P.P.), Harvard University, Boston, MA
| | - Keith A Johnson
- From the Douglas Mental Health University Institute (A.-A.B.), McGill University, Montreal, Quebec, Canada; The Framingham Heart Study (A.-A.B., D.J.K., J.J.H., D.H., M.P.P., A.S.B., S.S.); Boston University School of Public Health (D.J.K., J.J.H.), MA; Boston University School of Medicine (J.J.H., S.S.), MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (J.J.H., S.S.), UT Health San Antonio, TX; UC Davis Center for Neuroscience (C.S.D.), CA; Sunnybrook Research Institute (E.S.), University of Toronto, Ontario, Canada; Harvard Aging Brain Institute (K.A.J.), Harvard Medical School, Boston, MA; Gordon Center for Medical Imaging (G.E.F., E.T.), Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston; Turner Institute for Brain and Mental Health (S.R.Y., M.G.C., M.P.P.), Monash University, Clayton, Australia; and Harvard T.H. Chan School of Public Health (M.P.P.), Harvard University, Boston, MA
| | - Georges El Fakhri
- From the Douglas Mental Health University Institute (A.-A.B.), McGill University, Montreal, Quebec, Canada; The Framingham Heart Study (A.-A.B., D.J.K., J.J.H., D.H., M.P.P., A.S.B., S.S.); Boston University School of Public Health (D.J.K., J.J.H.), MA; Boston University School of Medicine (J.J.H., S.S.), MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (J.J.H., S.S.), UT Health San Antonio, TX; UC Davis Center for Neuroscience (C.S.D.), CA; Sunnybrook Research Institute (E.S.), University of Toronto, Ontario, Canada; Harvard Aging Brain Institute (K.A.J.), Harvard Medical School, Boston, MA; Gordon Center for Medical Imaging (G.E.F., E.T.), Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston; Turner Institute for Brain and Mental Health (S.R.Y., M.G.C., M.P.P.), Monash University, Clayton, Australia; and Harvard T.H. Chan School of Public Health (M.P.P.), Harvard University, Boston, MA
| | - Emma Thibault
- From the Douglas Mental Health University Institute (A.-A.B.), McGill University, Montreal, Quebec, Canada; The Framingham Heart Study (A.-A.B., D.J.K., J.J.H., D.H., M.P.P., A.S.B., S.S.); Boston University School of Public Health (D.J.K., J.J.H.), MA; Boston University School of Medicine (J.J.H., S.S.), MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (J.J.H., S.S.), UT Health San Antonio, TX; UC Davis Center for Neuroscience (C.S.D.), CA; Sunnybrook Research Institute (E.S.), University of Toronto, Ontario, Canada; Harvard Aging Brain Institute (K.A.J.), Harvard Medical School, Boston, MA; Gordon Center for Medical Imaging (G.E.F., E.T.), Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston; Turner Institute for Brain and Mental Health (S.R.Y., M.G.C., M.P.P.), Monash University, Clayton, Australia; and Harvard T.H. Chan School of Public Health (M.P.P.), Harvard University, Boston, MA
| | - Stephanie R Yiallourou
- From the Douglas Mental Health University Institute (A.-A.B.), McGill University, Montreal, Quebec, Canada; The Framingham Heart Study (A.-A.B., D.J.K., J.J.H., D.H., M.P.P., A.S.B., S.S.); Boston University School of Public Health (D.J.K., J.J.H.), MA; Boston University School of Medicine (J.J.H., S.S.), MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (J.J.H., S.S.), UT Health San Antonio, TX; UC Davis Center for Neuroscience (C.S.D.), CA; Sunnybrook Research Institute (E.S.), University of Toronto, Ontario, Canada; Harvard Aging Brain Institute (K.A.J.), Harvard Medical School, Boston, MA; Gordon Center for Medical Imaging (G.E.F., E.T.), Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston; Turner Institute for Brain and Mental Health (S.R.Y., M.G.C., M.P.P.), Monash University, Clayton, Australia; and Harvard T.H. Chan School of Public Health (M.P.P.), Harvard University, Boston, MA
| | - Dibya Himali
- From the Douglas Mental Health University Institute (A.-A.B.), McGill University, Montreal, Quebec, Canada; The Framingham Heart Study (A.-A.B., D.J.K., J.J.H., D.H., M.P.P., A.S.B., S.S.); Boston University School of Public Health (D.J.K., J.J.H.), MA; Boston University School of Medicine (J.J.H., S.S.), MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (J.J.H., S.S.), UT Health San Antonio, TX; UC Davis Center for Neuroscience (C.S.D.), CA; Sunnybrook Research Institute (E.S.), University of Toronto, Ontario, Canada; Harvard Aging Brain Institute (K.A.J.), Harvard Medical School, Boston, MA; Gordon Center for Medical Imaging (G.E.F., E.T.), Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston; Turner Institute for Brain and Mental Health (S.R.Y., M.G.C., M.P.P.), Monash University, Clayton, Australia; and Harvard T.H. Chan School of Public Health (M.P.P.), Harvard University, Boston, MA
| | - Marina G Cavuoto
- From the Douglas Mental Health University Institute (A.-A.B.), McGill University, Montreal, Quebec, Canada; The Framingham Heart Study (A.-A.B., D.J.K., J.J.H., D.H., M.P.P., A.S.B., S.S.); Boston University School of Public Health (D.J.K., J.J.H.), MA; Boston University School of Medicine (J.J.H., S.S.), MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (J.J.H., S.S.), UT Health San Antonio, TX; UC Davis Center for Neuroscience (C.S.D.), CA; Sunnybrook Research Institute (E.S.), University of Toronto, Ontario, Canada; Harvard Aging Brain Institute (K.A.J.), Harvard Medical School, Boston, MA; Gordon Center for Medical Imaging (G.E.F., E.T.), Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston; Turner Institute for Brain and Mental Health (S.R.Y., M.G.C., M.P.P.), Monash University, Clayton, Australia; and Harvard T.H. Chan School of Public Health (M.P.P.), Harvard University, Boston, MA
| | - Matthew P Pase
- From the Douglas Mental Health University Institute (A.-A.B.), McGill University, Montreal, Quebec, Canada; The Framingham Heart Study (A.-A.B., D.J.K., J.J.H., D.H., M.P.P., A.S.B., S.S.); Boston University School of Public Health (D.J.K., J.J.H.), MA; Boston University School of Medicine (J.J.H., S.S.), MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (J.J.H., S.S.), UT Health San Antonio, TX; UC Davis Center for Neuroscience (C.S.D.), CA; Sunnybrook Research Institute (E.S.), University of Toronto, Ontario, Canada; Harvard Aging Brain Institute (K.A.J.), Harvard Medical School, Boston, MA; Gordon Center for Medical Imaging (G.E.F., E.T.), Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston; Turner Institute for Brain and Mental Health (S.R.Y., M.G.C., M.P.P.), Monash University, Clayton, Australia; and Harvard T.H. Chan School of Public Health (M.P.P.), Harvard University, Boston, MA
| | - Alexa S Beiser
- From the Douglas Mental Health University Institute (A.-A.B.), McGill University, Montreal, Quebec, Canada; The Framingham Heart Study (A.-A.B., D.J.K., J.J.H., D.H., M.P.P., A.S.B., S.S.); Boston University School of Public Health (D.J.K., J.J.H.), MA; Boston University School of Medicine (J.J.H., S.S.), MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (J.J.H., S.S.), UT Health San Antonio, TX; UC Davis Center for Neuroscience (C.S.D.), CA; Sunnybrook Research Institute (E.S.), University of Toronto, Ontario, Canada; Harvard Aging Brain Institute (K.A.J.), Harvard Medical School, Boston, MA; Gordon Center for Medical Imaging (G.E.F., E.T.), Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston; Turner Institute for Brain and Mental Health (S.R.Y., M.G.C., M.P.P.), Monash University, Clayton, Australia; and Harvard T.H. Chan School of Public Health (M.P.P.), Harvard University, Boston, MA
| | - Sudha Seshadri
- From the Douglas Mental Health University Institute (A.-A.B.), McGill University, Montreal, Quebec, Canada; The Framingham Heart Study (A.-A.B., D.J.K., J.J.H., D.H., M.P.P., A.S.B., S.S.); Boston University School of Public Health (D.J.K., J.J.H.), MA; Boston University School of Medicine (J.J.H., S.S.), MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (J.J.H., S.S.), UT Health San Antonio, TX; UC Davis Center for Neuroscience (C.S.D.), CA; Sunnybrook Research Institute (E.S.), University of Toronto, Ontario, Canada; Harvard Aging Brain Institute (K.A.J.), Harvard Medical School, Boston, MA; Gordon Center for Medical Imaging (G.E.F., E.T.), Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston; Turner Institute for Brain and Mental Health (S.R.Y., M.G.C., M.P.P.), Monash University, Clayton, Australia; and Harvard T.H. Chan School of Public Health (M.P.P.), Harvard University, Boston, MA
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Nakaya M, Sato N, Matsuda H, Maikusa N, Ota M, Shigemoto Y, Sone D, Yamao T, Kimura Y, Tsukamoto T, Yokoi Y, Sakata M, Abe O. Assessment of Gray Matter Microstructural Alterations in Alzheimer's Disease by Free Water Imaging. J Alzheimers Dis 2024; 99:1441-1453. [PMID: 38759008 DOI: 10.3233/jad-231416] [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] [Indexed: 05/19/2024]
Abstract
Background Cortical neurodegenerative processes may precede the emergence of disease symptoms in patients with Alzheimer's disease (AD) by many years. No study has evaluated the free water of patients with AD using gray matter-based spatial statistics. Objective The aim of this study was to explore cortical microstructural changes within the gray matter in AD by using free water imaging with gray matter-based spatial statistics. Methods Seventy-one participants underwent multi-shell diffusion magnetic resonance imaging, 11C-Pittsburgh compound B positron emission tomography, and neuropsychological evaluations. The patients were divided into two groups: healthy controls (n = 40) and the AD spectrum group (n = 31). Differences between the groups were analyzed using voxel-based morphometry, diffusion tensor imaging, and free water imaging with gray matter-based spatial statistics. Results Voxel-based morphometry analysis revealed gray matter volume loss in the hippocampus of patients with AD spectrum compared to that in controls. Furthermore, patients with AD spectrum exhibited significantly greater free water, mean diffusivity, and radial diffusivity in the limbic areas, precuneus, frontal lobe, temporal lobe, right putamen, and cerebellum than did the healthy controls. Overall, the effect sizes of free water were greater than those of mean diffusivity and radial diffusivity, and the larger effect sizes of free water were thought to be strongly correlated with AD pathology. Conclusions This study demonstrates the utility of applying voxel-based morphometry, gray matter-based spatial statistics, free water imaging and diffusion tensor imaging to assess AD pathology and detect changes in gray matter.
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Affiliation(s)
- Moto Nakaya
- Department of Radiology, National Center Hospital of Neurology and Psychiatry, Tokyo, Japan
- Department of Radiology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Noriko Sato
- Department of Radiology, National Center Hospital of Neurology and Psychiatry, Tokyo, Japan
| | - Hiroshi Matsuda
- Department of Radiology, National Center Hospital of Neurology and Psychiatry, Tokyo, Japan
- Drug Discovery and Cyclotron Research Center, Southern TOHOKU Research Institute for Neuroscience, Koriyama, Japan
| | - Norihide Maikusa
- Department of Radiology, National Center Hospital of Neurology and Psychiatry, Tokyo, Japan
| | - Miho Ota
- Department of Radiology, National Center Hospital of Neurology and Psychiatry, Tokyo, Japan
- Department of Neuropsychiatry, University of Tsukuba, Tsukuba, Japan
| | - Yoko Shigemoto
- Department of Radiology, National Center Hospital of Neurology and Psychiatry, Tokyo, Japan
| | - Daichi Sone
- Department of Psychiatry, Jikei University School of Medicine, Tokyo, Japan
- Integrative Brain Imaging Center, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Tensho Yamao
- Department of Radiological Sciences, School of Health Sciences, Fukushima Medical University, Fukushima, Japan
| | - Yukio Kimura
- Department of Radiology, National Center Hospital of Neurology and Psychiatry, Tokyo, Japan
| | - Tadashi Tsukamoto
- Department of Neurology, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Yuma Yokoi
- Department of Educational Promotion, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Masuhiro Sakata
- Department of Psychiatry Saitama Prefectural Psychiatric Hospital, Saitama, Japan
| | - Osamu Abe
- Department of Radiology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
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Petrea RE, Pinheiro A, Demissie S, Ekenze O, Aparicio HJ, Satizabal C, Maillard P, DeCarli C, Beiser AS, Seshadri S, Lioutas VA, Romero JR. Hypertension Trends and White Matter Brain Injury in the Offspring Framingham Heart Study Cohort. Hypertension 2024; 81:87-95. [PMID: 37855140 PMCID: PMC10896002 DOI: 10.1161/hypertensionaha.123.21264] [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: 03/23/2023] [Accepted: 10/03/2023] [Indexed: 10/20/2023]
Abstract
BACKGROUND Hypertension is the most potent stroke risk factor and is also related to cerebral small vessel disease. We studied the relation between mid-to-late-life hypertension trends and cerebral white matter injury in community-dwelling individuals from the FHS (Framingham Heart Study). METHODS FHS Offspring cohort participants with available mid-life and late-life blood pressure measurements and brain magnetic resonance imaging were included. Multiple regression analyses were used to relate hypertension trends (normotension-normotension [reference], normotension-hypertension, and hypertension-hypertension) to white matter injury metrics on diffusion tensor imaging (free water, fractional anisotropy, and peak skeletonized mean diffusivity) and Fluid Attenuated Inversion Recovery (white matter hyperintensity volume) by different blood pressure cutoffs (130/80, 140/90, and 150/90 mm Hg). RESULTS We included 1018 participants (mean age 47.3±7.4 years at mid-life and 73.2±7.3 at late-life). At the 140/90 mm Hg cutoff, the hypertension-hypertension trend was associated with higher free water (β, 0.16 [95% CI, 0.03-0.30]; P=0.021) and peak skeletonized mean diffusivity (β, 0.15 [95% CI, 0.01-0.29]; P=0.033). At a 130/80 mm Hg cutoff, the hypertension-hypertension trend had significantly higher free water (β, 0.16 [95% CI, 0.01-0.30]; P=0.035); and the normotension-hypertension (β, 0.24 [95% CI, 0.03-0.44]; P=0.027) and hypertension-hypertension (β, 0.22 [95% CI, 0.04-0.41]; P=0.022) trends had significantly increased white matter hyperintensity volume. Exploratory stratified analysis showed effect modifications by APOE ɛ4 allele and age. CONCLUSIONS Mid-to-late-life hypertension exposure is significantly associated with microstructural and to a lesser extent, visible white matter injury; the effects are observed at both conventional and lower blood pressure cutoffs and are associated with longer duration of hypertension.
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Affiliation(s)
- Rodica Elena Petrea
- Department of Medicine, Section of Preventive Medicine and Epidemiology, Boston University School of Medicine, Boston, MA, USA
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
| | - Adlin Pinheiro
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Serkalem Demissie
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Oluchi Ekenze
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Graduate medical sciences, Boston University School of Medicine
| | - Hugo J. Aparicio
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Claudia Satizabal
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Pauline Maillard
- Alzheimer’s Disease Center and Imaging of Dementia and Aging (IDeA) Laboratory, Department of Neurology and Center for Neuroscience, University of California at Davis School of Medicine, Sacramento, CA, USA
| | - Charles DeCarli
- Alzheimer’s Disease Center and Imaging of Dementia and Aging (IDeA) Laboratory, Department of Neurology and Center for Neuroscience, University of California at Davis School of Medicine, Sacramento, CA, USA
| | - Alexa S Beiser
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Sudha Seshadri
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Vasileios-Arsenios Lioutas
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, MA, USA
| | - Jose Rafael Romero
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
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12
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Rowsthorn E, Pham W, Nazem-Zadeh MR, Law M, Pase MP, Harding IH. Imaging the neurovascular unit in health and neurodegeneration: a scoping review of interdependencies between MRI measures. Fluids Barriers CNS 2023; 20:97. [PMID: 38129925 PMCID: PMC10734164 DOI: 10.1186/s12987-023-00499-0] [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: 10/03/2023] [Accepted: 12/05/2023] [Indexed: 12/23/2023] Open
Abstract
The neurovascular unit (NVU) is a complex structure that facilitates nutrient delivery and metabolic waste clearance, forms the blood-brain barrier (BBB), and supports fluid homeostasis in the brain. The integrity of NVU subcomponents can be measured in vivo using magnetic resonance imaging (MRI), including quantification of enlarged perivascular spaces (ePVS), BBB permeability, cerebral perfusion and extracellular free water. The breakdown of NVU subparts is individually associated with aging, pathology, and cognition. However, how these subcomponents interact as a system, and how interdependencies are impacted by pathology remains unclear. This systematic scoping review identified 26 studies that investigated the inter-relationships between multiple subcomponents of the NVU in nonclinical and neurodegenerative populations using MRI. A further 112 studies investigated associations between the NVU and white matter hyperintensities (WMH). We identify two putative clusters of NVU interdependencies: a 'vascular' cluster comprising BBB permeability, perfusion and basal ganglia ePVS; and a 'fluid' cluster comprising ePVS, free water and WMH. Emerging evidence suggests that subcomponent coupling within these clusters may be differentially related to aging, neurovascular injury or neurodegenerative pathology.
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Affiliation(s)
- Ella Rowsthorn
- Department of Neuroscience, Central Clinical School, Monash University, 99 Commercial Road, Melbourne, VIC, 3004, Australia
- Turner Institute for Brain and Mental Health & School of Psychological Sciences, Monash University, 18 Innovation Walk, Clayton, VIC, 3168, Australia
| | - William Pham
- Department of Neuroscience, Central Clinical School, Monash University, 99 Commercial Road, Melbourne, VIC, 3004, Australia
| | - Mohammad-Reza Nazem-Zadeh
- Department of Neuroscience, Central Clinical School, Monash University, 99 Commercial Road, Melbourne, VIC, 3004, Australia
| | - Meng Law
- Department of Neuroscience, Central Clinical School, Monash University, 99 Commercial Road, Melbourne, VIC, 3004, Australia
- Department of Radiology, Alfred Health, 99 Commercial Road, Melbourne, VIC, 3004, Australia
- Department of Electrical and Computer Systems Engineering, Monash University, 14 Alliance Lane, Clayton, VIC, 3168, Australia
| | - Matthew P Pase
- Turner Institute for Brain and Mental Health & School of Psychological Sciences, Monash University, 18 Innovation Walk, Clayton, VIC, 3168, Australia
- Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA
| | - Ian H Harding
- Department of Neuroscience, Central Clinical School, Monash University, 99 Commercial Road, Melbourne, VIC, 3004, Australia.
- Monash Biomedical Imaging, Monash University, 762-772 Blackburn Road, Clayton, VIC, 3168, Australia.
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13
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Sun X, Zhao C, Chen SY, Chang Y, Han YL, Li K, Sun HM, Wang ZF, Liang Y, Jia JJ. Free Water MR Imaging of White Matter Microstructural Changes is a Sensitive Marker of Amyloid Positivity in Alzheimer's Disease. J Magn Reson Imaging 2023. [PMID: 38100518 DOI: 10.1002/jmri.29189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 12/01/2023] [Accepted: 12/02/2023] [Indexed: 12/17/2023] Open
Abstract
BACKGROUND Extracellular free water (FW) resulting from white matter degeneration limits the sensitivity of diffusion tensor imaging (DTI) in predicting Alzheimer's disease (AD). PURPOSE To evaluate the sensitivity of FW-DTI in detecting white matter microstructural changes in AD. To validate the effectiveness of FW-DTI indices to predict amyloid-beta (Aβ) positivity in mild cognitive impairment (MCI) subtypes. STUDY TYPE Retrospective. POPULATION Thirty-eight Aβ-negative cognitively healthy (CH) controls (68.74 ± 8.28 years old, 55% female), 15 Aβ-negative MCI patients (MCI-n) (68.87 ± 8.83 years old, 60% female), 29 Aβ-positive MCI patients (MCI-p) (73.03 ± 7.05 years old, 52% female), and 29 Aβ-positive AD patients (72.93 ± 9.11 years old, 55% female). FIELD STRENGTH/SEQUENCE 3.0T; DTI, T1 -weighted, T2 -weighted, T2 star-weighted angiography, and Aβ PET (18 F-florbetaben or 11 C-PIB). ASSESSMENT FW-corrected and standard diffusion indices were analyzed using trace-based spatial statistics. Area under the curve (AUC) in distinguishing MCI subtypes were compared using support vector machine (SVM). STATISTICAL TESTS Chi-squared test, one-way analysis of covariance, general linear regression analyses, nonparametric permutation tests, partial Pearson's correlation, receiver operating characteristic curve analysis, and linear SVM. A P value <0.05 was considered statistically significant. RESULTS Compared with CH/MCI-n/MCI-p, AD showed significant change in tissue compartment indices of FW-DTI. No difference was found in the FW index among pair-wise group comparisons (the minimum FWE-corrected P = 0.114). There was a significant association between FW-DTI indices and memory and visuospatial function. The SVM classifier with tissue radial diffusivity as an input feature had the best classification performance of MCI subtypes (AUC = 0.91), and the classifying accuracy of FW-DTI was all over 89.89%. DATA CONCLUSION FW-DTI indices prove to be potential biomarkers of AD. The classification of MCI subtypes based on SVM and FW-DTI indices has good accuracy and could help early diagnosis. EVIDENCE LEVEL 4 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Xuan Sun
- Medical School of Chinese PLA, Beijing, China
- Department of Geriatric Neurology, The Second Medical Centre, Chinese PLA General Hospital, Beijing, China
- National Clinical Research Center of Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Cui Zhao
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | - Si-Yu Chen
- Medical School of Chinese PLA, Beijing, China
- Department of Geriatric Neurology, The Second Medical Centre, Chinese PLA General Hospital, Beijing, China
- National Clinical Research Center of Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Yan Chang
- Department of Nuclear Medicine, The First Medical Centre, Chinese PLA General Hospital, Beijing, China
| | - Yu-Liang Han
- Department of Neurology, The 305 Hospital of PLA, Beijing, China
| | - Ke Li
- Department of Geriatric Neurology, The Second Medical Centre, Chinese PLA General Hospital, Beijing, China
- National Clinical Research Center of Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Hong-Mei Sun
- Medical School of Chinese PLA, Beijing, China
- Institute of Geriatrics, Chinese PLA General Hospital, Beijing, China
| | - Zhen-Fu Wang
- Department of Geriatric Neurology, The Second Medical Centre, Chinese PLA General Hospital, Beijing, China
- National Clinical Research Center of Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Ying Liang
- School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Jian-Jun Jia
- National Clinical Research Center of Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
- Institute of Geriatrics, Chinese PLA General Hospital, Beijing, China
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14
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Harding IH, Ryan J, Heritier S, Spark S, Flanagan Z, McIntyre R, Anderson CS, Naismith SL, Chong TTJ, O'Sullivan M, Egan G, Law M, Zoungas S. STAREE-Mind Imaging Study: a randomised placebo-controlled trial of atorvastatin for prevention of cerebrovascular decline and neurodegeneration in older individuals. BMJ Neurol Open 2023; 5:e000541. [PMID: 37920607 PMCID: PMC10619122 DOI: 10.1136/bmjno-2023-000541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Accepted: 10/08/2023] [Indexed: 11/04/2023] Open
Abstract
Introduction Cerebrovascular disease and neurodegeneration are causes of cognitive decline and dementia, for which primary prevention options are currently lacking. Statins are well-tolerated and widely available medications that potentially have neuroprotective effects. The STAREE-Mind Imaging Study is a randomised, double-blind, placebo-controlled clinical trial that will investigate the impact of atorvastatin on markers of neurovascular health and brain atrophy in a healthy, older population using MRI. This is a nested substudy of the 'Statins for Reducing Events in the Elderly' (STAREE) primary prevention trial. Methods Participants aged 70 years or older (n=340) will be randomised to atorvastatin or placebo. Comprehensive brain MRI assessment will be undertaken at baseline and up to 4 years follow-up, including structural, diffusion, perfusion and susceptibility imaging. The primary outcome measures will be change in brain free water fraction (a composite marker of vascular leakage, neuroinflammation and neurodegeneration) and white matter hyperintensity volume (small vessel disease). Secondary outcomes will include change in perivascular space volume (glymphatic drainage), cortical thickness, hippocampal volume, microbleeds and lacunae, prefrontal cerebral perfusion and white matter microstructure. Ethics and dissemination Academic publications from this work will address the current uncertainty regarding the impact of statins on brain structure and vascular integrity. This study will inform the utility of repurposing these well-tolerated, inexpensive and widely available drugs for primary prevention of neurological outcomes in older individuals. Ethics approval was given by Monash University Human Research Ethics Committee, Protocol 12206. Trial registration number ClinicalTrials.gov Identifier: NCT05586750.
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Affiliation(s)
- Ian H Harding
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Melbourne, Victoria, Australia
| | - Joanne Ryan
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Stephane Heritier
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Simone Spark
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Zachary Flanagan
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Richard McIntyre
- Monash Biomedical Imaging, Monash University, Melbourne, Victoria, Australia
| | - Craig S Anderson
- Global Brain Health Program, The George Institute for Global Health, University of New South Wales, Sydney, New South Wales, Australia
| | - Sharon L Naismith
- School of Psychology, University of Sydney, Sydney, New South Wales, Australia
| | - Trevor T-J Chong
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
| | - Michael O'Sullivan
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Gary Egan
- Monash Biomedical Imaging, Monash University, Melbourne, Victoria, Australia
| | - Meng Law
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Victoria, Australia
| | - Sophia Zoungas
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
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15
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Caprihan A, Hillmer L, Erhardt EB, Adair JC, Knoefel JE, Prestopnik J, Rosenberg GA. A trichotomy method for defining homogeneous subgroups in a dementia population. Ann Clin Transl Neurol 2023; 10:1802-1815. [PMID: 37602520 PMCID: PMC10578887 DOI: 10.1002/acn3.51869] [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] [Received: 04/04/2023] [Revised: 07/11/2023] [Accepted: 07/22/2023] [Indexed: 08/22/2023] Open
Abstract
INTRODUCTION Diagnosis of dementia in the aging brain is confounded by the presence of multiple pathologies. Mixed dementia (MX), a combination of Alzheimer's disease (AD) proteins with vascular disease (VD), is frequently found at autopsy, and has been difficult to diagnose during life. This report develops a method for separating the MX group and defining preclinical AD (presence of AD factors with normal cognition) and preclinical VD subgroups (presence of white matter damage with normal cognition). METHODS Clustering was based on three diagnostic axes: (1) AD factor (ADF) derived from cerebrospinal fluid proteins (Aβ42 and pTau), (2) VD factor (VDF) calculated from mean free water and peak width of skeletonized mean diffusivity in the white matter, and (3) Cognition (Cog) based on memory and executive function. The trichotomy method was applied to an Alzheimer's Disease Neuroimaging Initiative cohort (N = 538). RESULTS Eight biologically defined subgroups were identified which included the MX group with both high ADF and VDF (9.3%) and a preclinical VD group (3.9%), and a preclinical AD group (13.6%). Cog is significantly associated with both ADF and VDF, and the partial-correlation remains significant even when the effect of the other variable is removed (r(Cog, ADF/VDF removed) = 0.46, p < 10-28 and r(Cog, VDF/ADF removed) = 0.24, p < 10-7 ). DISCUSSION The trichotomy method creates eight biologically characterized patient groups, which includes MX, preclinical AD, and preclinical VD subgroups. Further longitudinal studies are needed to determine the utility of the 3-way clustering method with multimodal biological biomarkers.
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Affiliation(s)
| | - Laura Hillmer
- Center for Memory and AgingUniversity of New Mexico School of MedicineAlbuquerqueNew Mexico87106USA
| | - Erik Barry Erhardt
- Departments of Mathematics and StatisticsUniversity of New Mexico College of Arts and SciencesAlbuquerqueNew Mexico87106USA
| | - John C. Adair
- Center for Memory and AgingUniversity of New Mexico School of MedicineAlbuquerqueNew Mexico87106USA
- Department of NeurologyUniversity of New MexicoAlbuquerqueNew Mexico87106USA
| | - Janice E. Knoefel
- Center for Memory and AgingUniversity of New Mexico School of MedicineAlbuquerqueNew Mexico87106USA
- Department of NeurologyUniversity of New MexicoAlbuquerqueNew Mexico87106USA
| | - Jillian Prestopnik
- Center for Memory and AgingUniversity of New Mexico School of MedicineAlbuquerqueNew Mexico87106USA
| | - Gary A. Rosenberg
- Center for Memory and AgingUniversity of New Mexico School of MedicineAlbuquerqueNew Mexico87106USA
- Department of NeurologyUniversity of New MexicoAlbuquerqueNew Mexico87106USA
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16
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Pieciak T, París G, Beck D, Maximov II, Tristán-Vega A, de Luis-García R, Westlye LT, Aja-Fernández S. Spherical means-based free-water volume fraction from diffusion MRI increases non-linearly with age in the white matter of the healthy human brain. Neuroimage 2023; 279:120324. [PMID: 37574122 DOI: 10.1016/j.neuroimage.2023.120324] [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: 04/02/2023] [Revised: 08/08/2023] [Accepted: 08/10/2023] [Indexed: 08/15/2023] Open
Abstract
The term free-water volume fraction (FWVF) refers to the signal fraction that could be found as the cerebrospinal fluid of the brain, which has been demonstrated as a sensitive measure that correlates with cognitive performance and various neuropathological processes. It can be quantified by properly fitting the isotropic component of the magnetic resonance (MR) signal in diffusion-sensitized sequences. Using N=287 healthy subjects (178F/109M) aged 25-94, this study examines in detail the evolution of the FWVF obtained with the spherical means technique from multi-shell acquisitions in the human brain white matter across the adult lifespan, which has been previously reported to exhibit a positive trend when estimated from single-shell data using the bi-tensor signal representation. We found evidence of a noticeably non-linear gain after the sixth decade of life, with a region-specific variate and varying change rate of the spherical means-based multi-shell FWVF parameter with age, at the same time, a heteroskedastic pattern across the adult lifespan is suggested. On the other hand, the FW corrected diffusion tensor imaging (DTI) leads to a region-dependent flattened age-related evolution of the mean diffusivity (MD) and fractional anisotropy (FA), along with a considerable reduction in their variability, as compared to the studies conducted over the standard (single-component) DTI. This way, our study provides a new perspective on the trajectory-based assessment of the brain and explains the conceivable reason for the variations observed in FA and MD parameters across the lifespan with previous studies under the standard diffusion tensor imaging.
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Affiliation(s)
- Tomasz Pieciak
- Laboratorio de Procesado de Imagen (LPI), ETSI Telecomunicación, Universidad de Valladolid, Valladolid, Spain.
| | - Guillem París
- Laboratorio de Procesado de Imagen (LPI), ETSI Telecomunicación, Universidad de Valladolid, Valladolid, Spain
| | - Dani Beck
- Department of Psychology, University of Oslo, Oslo, Norway; NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway. https://twitter.com/_DaniBeck
| | - Ivan I Maximov
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen, Norway
| | - Antonio Tristán-Vega
- Laboratorio de Procesado de Imagen (LPI), ETSI Telecomunicación, Universidad de Valladolid, Valladolid, Spain
| | - Rodrigo de Luis-García
- Laboratorio de Procesado de Imagen (LPI), ETSI Telecomunicación, Universidad de Valladolid, Valladolid, Spain
| | - Lars T Westlye
- Department of Psychology, University of Oslo, Oslo, Norway; NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway. https://twitter.com/larswestlye
| | - Santiago Aja-Fernández
- Laboratorio de Procesado de Imagen (LPI), ETSI Telecomunicación, Universidad de Valladolid, Valladolid, Spain. https://twitter.com/SantiagoAjaFer1
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17
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Duering M, Biessels GJ, Brodtmann A, Chen C, Cordonnier C, de Leeuw FE, Debette S, Frayne R, Jouvent E, Rost NS, Ter Telgte A, Al-Shahi Salman R, Backes WH, Bae HJ, Brown R, Chabriat H, De Luca A, deCarli C, Dewenter A, Doubal FN, Ewers M, Field TS, Ganesh A, Greenberg S, Helmer KG, Hilal S, Jochems ACC, Jokinen H, Kuijf H, Lam BYK, Lebenberg J, MacIntosh BJ, Maillard P, Mok VCT, Pantoni L, Rudilosso S, Satizabal CL, Schirmer MD, Schmidt R, Smith C, Staals J, Thrippleton MJ, van Veluw SJ, Vemuri P, Wang Y, Werring D, Zedde M, Akinyemi RO, Del Brutto OH, Markus HS, Zhu YC, Smith EE, Dichgans M, Wardlaw JM. Neuroimaging standards for research into small vessel disease-advances since 2013. Lancet Neurol 2023; 22:602-618. [PMID: 37236211 DOI: 10.1016/s1474-4422(23)00131-x] [Citation(s) in RCA: 118] [Impact Index Per Article: 118.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 03/03/2023] [Accepted: 03/28/2023] [Indexed: 05/28/2023]
Abstract
Cerebral small vessel disease (SVD) is common during ageing and can present as stroke, cognitive decline, neurobehavioural symptoms, or functional impairment. SVD frequently coexists with neurodegenerative disease, and can exacerbate cognitive and other symptoms and affect activities of daily living. Standards for Reporting Vascular Changes on Neuroimaging 1 (STRIVE-1) categorised and standardised the diverse features of SVD that are visible on structural MRI. Since then, new information on these established SVD markers and novel MRI sequences and imaging features have emerged. As the effect of combined SVD imaging features becomes clearer, a key role for quantitative imaging biomarkers to determine sub-visible tissue damage, subtle abnormalities visible at high-field strength MRI, and lesion-symptom patterns, is also apparent. Together with rapidly emerging machine learning methods, these metrics can more comprehensively capture the effect of SVD on the brain than the structural MRI features alone and serve as intermediary outcomes in clinical trials and future routine practice. Using a similar approach to that adopted in STRIVE-1, we updated the guidance on neuroimaging of vascular changes in studies of ageing and neurodegeneration to create STRIVE-2.
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Affiliation(s)
- Marco Duering
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany; Medical Image Analysis Center, University of Basel, Basel, Switzerland; Department of Biomedical Engineering, University of Basel, Basel, Switzerland.
| | - Geert Jan Biessels
- Department of Neurology, University Medical Center Utrecht, Utrecht, Netherlands
| | - Amy Brodtmann
- Cognitive Health Initiative, Central Clinical School, Monash University, Melbourne, VIC, Australia; Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, VIC, Australia
| | - Christopher Chen
- Department of Pharmacology, Memory Aging and Cognition Centre, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Psychological Medicine, Memory Aging and Cognition Centre, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Charlotte Cordonnier
- Université de Lille, INSERM, CHU Lille, U1172-Lille Neuroscience and Cognition (LilNCog), Lille, France
| | - Frank-Erik de Leeuw
- Department of Neurology, Donders Center for Medical Neuroscience, Radboudumc, Nijmegen, Netherlands
| | - Stéphanie Debette
- Bordeaux Population Health Research Center, University of Bordeaux, INSERM, UMR 1219, Bordeaux, France; Department of Neurology, Institute for Neurodegenerative Diseases, CHU de Bordeaux, Bordeaux, France
| | - Richard Frayne
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada; Department of Radiology, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Seaman Family MR Research Centre, Foothills Medical Centre, University of Calgary, Calgary, AB, Canada
| | - Eric Jouvent
- AP-HP, Lariboisière Hospital, Translational Neurovascular Centre, FHU NeuroVasc, Université Paris Cité, Paris, France; Université Paris Cité, INSERM UMR 1141, NeuroDiderot, Paris, France
| | - Natalia S Rost
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | | | | | - Walter H Backes
- School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, Netherlands; School for Cardiovascular Diseases, Maastricht University Medical Center, Maastricht, Netherlands; Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, Netherlands
| | - Hee-Joon Bae
- Department of Neurology, Seoul National University College of Medicine, Seoul, South Korea; Cerebrovascular Disease Center, Seoul National University Bundang Hospital, Seongn-si, South Korea
| | - Rosalind Brown
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Hugues Chabriat
- Centre Neurovasculaire Translationnel, CERVCO, INSERM U1141, FHU NeuroVasc, Université Paris Cité, Paris, France
| | - Alberto De Luca
- Image Sciences Institute, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, Netherlands
| | - Charles deCarli
- Department of Neurology and Center for Neuroscience, University of California, Davis, CA, USA
| | - Anna Dewenter
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Fergus N Doubal
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Michael Ewers
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Thalia S Field
- Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada; Vancouver Stroke Program, Division of Neurology, University of British Columbia, Vancouver, BC, Canada
| | - Aravind Ganesh
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada; Department of Community Health Sciences, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Mathison Centre for Mental Health Research and Education, University of Calgary, Calgary, AB, Canada
| | - Steven Greenberg
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Karl G Helmer
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Athinoula A Martinos Center for Biomedical Imaging, Boston, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Saima Hilal
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
| | - Angela C C Jochems
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Hanna Jokinen
- Division of Neuropsychology, HUS Neurocenter, Helsinki University Hospital, University of Helsinki, Helsinki, Finland; Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Hugo Kuijf
- Image Sciences Institute, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, Netherlands
| | - Bonnie Y K Lam
- Division of Neurology, Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Gerald Choa Neuroscience Institute, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Margaret KL Cheung Research Centre for Management of Parkinsonism, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Therese Pei Fong Chow Research Centre for Prevention of Dementia, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Lui Che Woo Institute of Innovative Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Lau Tat-chuen Research Centre of Brain Degenerative Diseases in Chinese, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Jessica Lebenberg
- AP-HP, Lariboisière Hospital, Translational Neurovascular Centre, FHU NeuroVasc, Université Paris Cité, Paris, France; Université Paris Cité, INSERM UMR 1141, NeuroDiderot, Paris, France
| | - Bradley J MacIntosh
- Sandra E Black Centre for Brain Resilience and Repair, Hurvitz Brain Sciences, Physical Sciences Platform, Sunnybrook Research Institute, Toronto, ON, Canada; Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada; Computational Radiology and Artificial Intelligence Unit, Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Pauline Maillard
- Department of Neurology and Center for Neuroscience, University of California, Davis, CA, USA
| | - Vincent C T Mok
- Division of Neurology, Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Gerald Choa Neuroscience Institute, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Margaret KL Cheung Research Centre for Management of Parkinsonism, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Therese Pei Fong Chow Research Centre for Prevention of Dementia, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Lui Che Woo Institute of Innovative Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Lau Tat-chuen Research Centre of Brain Degenerative Diseases in Chinese, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Leonardo Pantoni
- Department of Biomedical and Clinical Science, University of Milan, Milan, Italy
| | - Salvatore Rudilosso
- Comprehensive Stroke Center, Department of Neuroscience, Hospital Clinic and August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain
| | - Claudia L Satizabal
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA; Department of Population Health Sciences, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA; Department of Neurology, Boston University Medical Center, Boston, MA, USA; Framingham Heart Study, Framingham, MA, USA
| | - Markus D Schirmer
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | | | - Colin Smith
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Julie Staals
- School for Cardiovascular Diseases, Maastricht University Medical Center, Maastricht, Netherlands; Department of Neurology, Maastricht University Medical Center, Maastricht, Netherlands
| | - Michael J Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; Edinburgh Imaging and Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | | | | | - Yilong Wang
- Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - David Werring
- Stroke Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Marialuisa Zedde
- Neurology Unit, Stroke Unit, Department of Neuromotor Physiology and Rehabilitation, Azienda Unità Sanitaria-IRCCS di Reggio Emilia, Reggio Emilia, Italy
| | - Rufus O Akinyemi
- Neuroscience and Ageing Research Unit, Institute for Advanced Medical Research and Training, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Oscar H Del Brutto
- School of Medicine and Research Center, Universidad de Especialidades Espiritu Santo, Ecuador
| | - Hugh S Markus
- Stroke Research Group, Department of Clinical Neuroscience, University of Cambridge, Cambridge, UK
| | - Yi-Cheng Zhu
- Department of Neurology, Peking Union Medical College Hospital, Beijing, China
| | - Eric E Smith
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada; Department of Community Health Sciences, University of Calgary, Calgary, AB, Canada; Department of Radiology, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Martin Dichgans
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany; German Center for Neurodegenerative Diseases (DZNE), Munich, Germany; German Centre for Cardiovascular Research (DZHK), Munich, Germany
| | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK.
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18
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Gugger JJ, Walter AE, Parker D, Sinha N, Morrison J, Ware J, Schneider AL, Petrov D, Sandsmark DK, Verma R, Diaz-Arrastia R. Longitudinal Abnormalities in White Matter Extracellular Free Water Volume Fraction and Neuropsychological Functioning in Patients with Traumatic Brain Injury. J Neurotrauma 2023; 40:683-692. [PMID: 36448583 PMCID: PMC10061336 DOI: 10.1089/neu.2022.0259] [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] [Indexed: 12/03/2022] Open
Abstract
Traumatic brain injury is a global public health problem associated with chronic neurological complications and long-term disability. Biomarkers that map onto the underlying brain pathology driving these complications are urgently needed to identify individuals at risk for poor recovery and to inform design of clinical trials of neuroprotective therapies. Neuroinflammation and neurodegeneration are two endophenotypes potentially associated with increases in brain extracellular water content, but the nature of extracellular free water abnormalities after neurotrauma and its relationship to measures typically thought to reflect traumatic axonal injury are not well characterized. The objective of this study was to describe the relationship between a neuroimaging biomarker of extracellular free water content and the clinical features of a cohort with primarily complicated mild traumatic brain injury. We analyzed a cohort of 59 adult patients requiring hospitalization for non-penetrating traumatic brain injury of all severities as well as 36 healthy controls. Patients underwent brain magnetic resonance imaging (MRI) at 2 weeks (n = 59) and 6 months (n = 29) post-injury, and controls underwent a single MRI. Of the participants with TBI, 50 underwent clinical neuropsychological assessment at 2 weeks and 28 at 6 months. For each subject, we derived a summary score representing deviations in whole brain white matter extracellular free water volume fraction (VF) and free water-corrected fractional anisotropy (fw-FA). The summary specific anomaly score (SAS) for VF was significantly higher in TBI patients at 2 weeks and 6 months post-injury relative to controls. SAS for VF exhibited moderate correlation with neuropsychological functioning, particularly on measures of executive function. These findings indicate abnormalities in whole brain white matter extracellular water fraction in patients with TBI and are an important step toward identifying and validating noninvasive biomarkers that map onto the pathology driving disability after TBI.
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Affiliation(s)
- James J. Gugger
- Department of Neurology, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Alexa E. Walter
- Department of Neurology, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Drew Parker
- Department of Radiology, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
- Department of Neurosurgery, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
- Diffusion and Connectomics in Precision Healthcare Research Lab, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Nishant Sinha
- Department of Neurology, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Justin Morrison
- Department of Neurology, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Jeffrey Ware
- Department of Radiology, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Andrea L.C. Schneider
- Department of Neurology, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Dmitriy Petrov
- Department of Neurosurgery, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Danielle K. Sandsmark
- Department of Neurology, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Ragini Verma
- Department of Radiology, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
- Department of Neurosurgery, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
- Diffusion and Connectomics in Precision Healthcare Research Lab, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Ramon Diaz-Arrastia
- Department of Neurology, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
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19
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Abstract
Cerebral small vessel disease (CSVD) has emerged as a common factor driving age-dependent diseases, including stroke and dementia. CSVD-related dementia will affect a growing fraction of the aging population, requiring improved recognition, understanding, and treatments. This review describes evolving criteria and imaging biomarkers for the diagnosis of CSVD-related dementia. We describe diagnostic challenges, particularly in the context of mixed pathologies and the absence of highly effective biomarkers for CSVD-related dementia. We review evidence regarding CSVD as a risk factor for developing neurodegenerative disease and potential mechanisms by which CSVD leads to progressive brain injury. Finally, we summarize recent studies on the effects of major classes of cardiovascular medicines relevant to CSVD-related cognitive impairment. Although many key questions remain, the increased attention to CSVD has resulted in a sharper vision for what will be needed to meet the upcoming challenges imposed by this disease.
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Affiliation(s)
- Fanny M. Elahi
- Departments of Neurology and Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY
- Neurology Service, VA Bronx Healthcare System, Bronx, NY
| | - Michael M. Wang
- Departments of Neurology and Molecular and Integrative Physiology, University of Michigan, Ann Arbor, MI
- Neurology Service, VA Ann Arbor Healthcare System, Ann Arbor, MI
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20
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Ottoy J, Ozzoude M, Zukotynski K, Kang MS, Adamo S, Scott C, Ramirez J, Swardfager W, Lam B, Bhan A, Mojiri P, Kiss A, Strother S, Bocti C, Borrie M, Chertkow H, Frayne R, Hsiung R, Laforce RJ, Noseworthy MD, Prato FS, Sahlas DJ, Smith EE, Kuo PH, Chad JA, Pasternak O, Sossi V, Thiel A, Soucy JP, Tardif JC, Black SE, Goubran M. Amyloid-PET of the white matter: Relationship to free water, fiber integrity, and cognition in patients with dementia and small vessel disease. J Cereb Blood Flow Metab 2023; 43:921-936. [PMID: 36695071 DOI: 10.1177/0271678x231152001] [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: 01/26/2023]
Abstract
White matter (WM) injury is frequently observed along with dementia. Positron emission tomography with amyloid-ligands (Aβ-PET) recently gained interest for detecting WM injury. Yet, little is understood about the origin of the altered Aβ-PET signal in WM regions. Here, we investigated the relative contributions of diffusion MRI-based microstructural alterations, including free water and tissue-specific properties, to Aβ-PET in WM and to cognition. We included a unique cohort of 115 participants covering the spectrum of low-to-severe white matter hyperintensity (WMH) burden and cognitively normal to dementia. We applied a bi-tensor diffusion-MRI model that differentiates between (i) the extracellular WM compartment (represented via free water), and (ii) the fiber-specific compartment (via free water-adjusted fractional anisotropy [FA]). We observed that, in regions of WMH, a decrease in Aβ-PET related most closely to higher free water and higher WMH volume. In contrast, in normal-appearing WM, an increase in Aβ-PET related more closely to higher cortical Aβ (together with lower free water-adjusted FA). In relation to cognitive impairment, we observed a closer relationship with higher free water than with either free water-adjusted FA or WM PET. Our findings support free water and Aβ-PET as markers of WM abnormalities in patients with mixed dementia, and contribute to a better understanding of processes giving rise to the WM PET signal.
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Affiliation(s)
- Julie Ottoy
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Miracle Ozzoude
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Katherine Zukotynski
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,Departments of Medicine and Radiology, McMaster University, Hamilton, ON, Canada.,Department of Medical Imaging, Schulich School of Medicine & Dentistry, Western University, London, ON, Canada.,Department of Radiology, University of British Columbia, Vancouver, BC, Canada
| | - Min Su Kang
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Sabrina Adamo
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Christopher Scott
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Joel Ramirez
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Walter Swardfager
- Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON, Canada
| | - Benjamin Lam
- Department of Medicine (Division of Neurology), Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Aparna Bhan
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Parisa Mojiri
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Alex Kiss
- Department of Research Design and Biostatistics, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Stephen Strother
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.,The Rotman Research Institute Baycrest, University of Toronto, Toronto, ON, Canada
| | - Christian Bocti
- Service de Neurologie, Département de Medicine, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Michael Borrie
- Lawson Health Research Institute, Western University, London, ON, Canada
| | - Howard Chertkow
- Jewish General Hospital and Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Richard Frayne
- Departments of Radiology and Clinical Neuroscience, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Robin Hsiung
- Physics and Astronomy Department and DM Center for Brain Health, University of British Columbia, Vancouver, BC, Canada
| | - Robert Jr Laforce
- Clinique Interdisciplinaire de Mémoire, Département des Sciences Neurologiques, Université Laval, Québec, QC, Canada
| | - Michael D Noseworthy
- Departments of Medicine and Radiology, McMaster University, Hamilton, ON, Canada.,Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON, Canada
| | - Frank S Prato
- Lawson Health Research Institute, Western University, London, ON, Canada
| | | | - Eric E Smith
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Phillip H Kuo
- Department of Medical Imaging, Medicine, and Biomedical Engineering, University of Arizona, Tucson, AZ, USA
| | - Jordan A Chad
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.,The Rotman Research Institute Baycrest, University of Toronto, Toronto, ON, Canada
| | - Ofer Pasternak
- Departments of Psychiatry and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Vesna Sossi
- Physics and Astronomy Department and DM Center for Brain Health, University of British Columbia, Vancouver, BC, Canada
| | - Alexander Thiel
- Jewish General Hospital and Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Jean-Paul Soucy
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | | | - Sandra E Black
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,Department of Medicine (Division of Neurology), Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Maged Goubran
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.,Physical Sciences Platform, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
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21
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Spartano NL, Wang R, Yang Q, Chernofsky A, Murabito JM, Levy D, Vasan RS, DeCarli C, Maillard P, Seshadri S, Beiser AS. Association of Physical Inactivity with MRI Markers of Brain Aging: Assessing Mediation by Cardiometabolic and Epigenetic Factors. J Alzheimers Dis 2023; 95:561-572. [PMID: 37574733 DOI: 10.3233/jad-230289] [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] [Indexed: 08/15/2023]
Abstract
INTRODUCTION Cardiometabolic risk factors and epigenetic patterns, increased in physically inactive individuals, are associated with an accelerated brain aging process. OBJECTIVE To determine whether cardiometabolic risk factors and epigenetic patterns mediate the association of physical inactivity with unfavorable brain morphology. METHODS We included dementia and stroke free participants from the Framingham Heart Study Third Generation and Offspring cohorts who had accelerometery and brain MRI data (n = 2,507, 53.9% women, mean age 53.9 years). We examined mediation by the 2017-revised Framingham Stroke Risk Profile (FSRP, using weights for age, cardiovascular disease, atrial fibrillation, diabetes and smoking status, antihypertension medications, and systolic blood pressure) and the homeostatic model of insulin resistance (HOMA-IR) in models of the association of physical inactivity with brain aging, adjusting for age, age-squared, sex, accelerometer wear time, cohort, time from exam-to-MRI, and season. We similarly assessed mediation by an epigenetic age-prediction algorithm, GrimAge, in a smaller sample of participants who had DNA methylation data (n = 1,418). RESULTS FSRP and HOMA-IR explained 8.3-20.5% of associations of higher moderate-to-vigorous physical activity (MVPA), higher steps, and lower sedentary time with higher brain volume. Additionally, FSRP and GrimAge explained 10.3-22.0% of associations of physical inactivity with lower white matter diffusivity and FSRP explained 19.7% of the association of MVPA with lower free water accumulation. CONCLUSION Our results suggest that cardiometabolic risk factors and epigenetic patterns partially mediate the associations of physical inactivity with lower brain volume, higher white matter diffusivity, and aggregation of free water in the extracellular compartments of the brain.
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Affiliation(s)
- Nicole L Spartano
- Section of Endocrinology, Diabetes, Nutrition, and Weight Management, Boston University Chobanian & Avedisian School of Medicine (BUCASM), Boston, MA, USA
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA, USA
| | - Ruiqi Wang
- Department of Biostatistics, Boston University School of Public Health (BUSPH), Boston, MA, USA
| | - Qiong Yang
- Department of Biostatistics, Boston University School of Public Health (BUSPH), Boston, MA, USA
| | - Ariel Chernofsky
- Department of Biostatistics, Boston University School of Public Health (BUSPH), Boston, MA, USA
| | - Joanne M Murabito
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA, USA
- Section of General Internal Medicine, Department of Medicine, BUCASM, Boston, MA, USA
| | - Daniel Levy
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Ramachandran S Vasan
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA, USA
- Section of Preventive Medicine and Epidemiology, Evans Department of Medicine, BUSM, Boston, MA, USA
- Department of Epidemiology, BUSPH, Boston, MA, USA
- UT School of Public Health in San Antonio, TX, and UT Health Sciences Center in San Antonio, TX, USA
| | - Charles DeCarli
- Department of Neurology University of California Davis, Davis, CA, USA
| | - Pauline Maillard
- Department of Neurology University of California Davis, Davis, CA, USA
| | - Sudha Seshadri
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, BUSM, Boston, MA, USA
- Department of Population Health Sciences, University of Texas Health Science Center, San Antonio, TX, USA
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Alexa S Beiser
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health (BUSPH), Boston, MA, USA
- Department of Neurology, BUSM, Boston, MA, USA
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22
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Maillard P, Hillmer LJ, Lu H, Arfanakis K, Gold BT, Bauer CE, Kramer JH, Staffaroni AM, Stables L, Wang DJ, Seshadri S, Satizabal CL, Beiser A, Habes M, Fornage M, Mosley TH, Rosenberg GA, Singh B, Singh H, Schwab K, Helmer KG, Greenberg SM, DeCarli C, Caprihan A. MRI free water as a biomarker for cognitive performance: Validation in the MarkVCID consortium. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2022; 14:e12362. [PMID: 36523847 PMCID: PMC9745638 DOI: 10.1002/dad2.12362] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 08/11/2022] [Accepted: 08/29/2022] [Indexed: 12/15/2022]
Abstract
Introduction To evaluate the clinical validity of free water (FW), a diffusion tensor imaging-based biomarker kit proposed by the MarkVCID consortium, by investigating the association between mean FW (mFW) and executive function. Methods Baseline mFW was related to a baseline composite measure of executive function (EFC), adjusting for relevant covariates, in three MarkVCID sub-cohorts, and replicated in five, large, independent legacy cohorts. In addition, we tested whether baseline mFW predicted accelerated EFC score decline (mean follow-up time: 1.29 years). Results Higher mFW was found to be associated with lower EFC scores in MarkVCID legacy and sub-cohorts (p-values < 0.05). In addition, higher baseline mFW was associated significantly with accelerated decline in EFC scores (p = 0.0026). Discussion mFW is a sensitive biomarker of cognitive decline, providing a strong clinical rational for its use as a marker of white matter (WM) injury in multi-site observational studies and clinical trials of vascular cognitive impairment and dementia (VCID).
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Affiliation(s)
- Pauline Maillard
- Department of NeurologyUniversity of CaliforniaDavisCaliforniaUSA
| | - Laura J. Hillmer
- Department of NeurologyUniversity of New MexicoAlbuquerqueNew MexicoUSA
| | - Hanzhang Lu
- Department of RadiologyJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Konstantinos Arfanakis
- Department of Biomedical EngineeringIllinois Institute of TechnologyChicagoIllinoisUSA
- Rush Alzheimer's Disease CenterDepartment of Diagnostic Radiology and Nuclear MedicineRush University Medical CenterChicagoIllinoisUSA
| | - Brian T. Gold
- Department of NeuroscienceUniversity of KentuckyLexingtonKentuckyUSA
| | | | - Joel H. Kramer
- Department of NeurologyMemory and Aging CenterWeill Institute for NeurosciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Adam M. Staffaroni
- Department of NeurologyMemory and Aging CenterWeill Institute for NeurosciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Lara Stables
- Department of NeurologyMemory and Aging CenterWeill Institute for NeurosciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Danny J.J. Wang
- Laboratory of FMRI Technology (LOFT)Stevens Neuroimaging and Informatics InstituteKeck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Sudha Seshadri
- Department of NeurologyBoston University School of MedicineBostonMassachusettsUSA
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health San AntonioSan AntonioTexasUSA
| | - Claudia L. Satizabal
- Department of NeurologyBoston University School of MedicineBostonMassachusettsUSA
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health San AntonioSan AntonioTexasUSA
- Department of Population Health SciencesUniversity of Texas Health San AntonioSan AntonioTexasUSA
| | - Alexa Beiser
- Department of NeurologyBoston University School of MedicineBostonMassachusettsUSA
- Department of BiostatisticsBoston University School of Public HealthBostonMassachusettsUSA
| | - Mohamad Habes
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health San AntonioSan AntonioTexasUSA
| | - Myriam Fornage
- Brown Foundation Institute of Molecular MedicineMcGovern Medical SchoolSchool of Public HealthThe University of Texas Health Science Center at HoustonHoustonTexasUSA
- Human Genetics CenterSchool of Public HealthThe University of Texas Health Science Center at HoustonHoustonTexasUSA
| | - Thomas H. Mosley
- MIND CenterUniversity of Mississippi Medical CenterJacksonMississippiUSA
| | - Gary A. Rosenberg
- Department of NeurologyUniversity of New MexicoAlbuquerqueNew MexicoUSA
| | - Baljeet Singh
- Department of NeurologyUniversity of CaliforniaDavisCaliforniaUSA
| | - Herpreet Singh
- Department of NeurologyMassachusetts General HospitalBostonMassachusettsUSA
| | - Kristin Schwab
- Department of NeurologyMassachusetts General HospitalBostonMassachusettsUSA
| | - Karl G. Helmer
- Department of RadiologyHarvard Medical SchoolBostonMassachusettsUSA
- Department of RadiologyMassachusetts General HospitalBostonMassachusettsUSA
| | | | - Charles DeCarli
- Department of NeurologyUniversity of CaliforniaDavisCaliforniaUSA
| | - Arvind Caprihan
- The Mind Research NetworkAlbuquerqueNew MexicoAlbuquerqueNew MexicoUSA
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23
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Kamagata K, Andica C, Takabayashi K, Saito Y, Taoka T, Nozaki H, Kikuta J, Fujita S, Hagiwara A, Kamiya K, Wada A, Akashi T, Sano K, Nishizawa M, Hori M, Naganawa S, Aoki S. Association of MRI Indices of Glymphatic System With Amyloid Deposition and Cognition in Mild Cognitive Impairment and Alzheimer Disease. Neurology 2022; 99:e2648-e2660. [PMID: 36123122 PMCID: PMC9757870 DOI: 10.1212/wnl.0000000000201300] [Citation(s) in RCA: 66] [Impact Index Per Article: 33.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 08/12/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES The glymphatic system is a whole-brain perivascular network, which promotes CSF/interstitial fluid exchange. Alterations to this system may play a pivotal role in amyloid β (Aβ) accumulation. However, its involvement in Alzheimer disease (AD) pathogenesis is not fully understood. Here, we investigated the changes in noninvasive MRI measurements related to the perivascular network in patients with mild cognitive impairment (MCI) and AD. Additionally, we explored the associations of MRI measures with neuropsychological score, PET standardized uptake value ratio (SUVR), and Aβ deposition. METHODS MRI measures, including perivascular space (PVS) volume fraction (PVSVF), fractional volume of free water in white matter (FW-WM), and index of diffusivity along the perivascular space (ALPS index) of patients with MCI, those with AD, and healthy controls from the Alzheimer's Disease Neuroimaging Initiative database were compared. MRI measures were also correlated with the levels of CSF biomarkers, PET SUVR, and cognitive score in the combined subcohort of patients with MCI and AD. Statistical analyses were performed with age, sex, years of education, and APOE status as confounding factors. RESULTS In total, 36 patients with AD, 44 patients with MCI, and 31 healthy controls were analyzed. Patients with AD had significantly higher total, WM, and basal ganglia PVSVF (Cohen d = 1.15-1.48; p < 0.001) and FW-WM (Cohen d = 0.73; p < 0.05) and a lower ALPS index (Cohen d = 0.63; p < 0.05) than healthy controls. Meanwhile, the MCI group only showed significantly higher total (Cohen d = 0.99; p < 0.05) and WM (Cohen d = 0.91; p < 0.05) PVSVF. Low ALPS index was associated with lower CSF Aβ42 (r s = 0.41, p fdr = 0.026), FDG-PET uptake (r s = 0.54, p fdr < 0.001), and worse multiple cognitive domain deficits. High FW-WM was also associated with lower CSF Aβ42 (r s = -0.47, p fdr = 0.021) and worse cognitive performances. DISCUSSION Our study indicates that changes in PVS-related MRI parameters occur in MCI and AD, possibly due to impairment of the glymphatic system. We also report the associations between MRI parameters and Aβ deposition, neuronal change, and cognitive impairment in AD.
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Affiliation(s)
- Koji Kamagata
- From the Department of Radiology (Koji Kamagata, C.A., K.T., Y.S., H.N., J.K., S.F., A.H., A.W., T.A., K.S., M.N., S.A.), Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo; Faculty of Health Data Science (C.A.), Juntendo University, Urayasu, Chiba, Department of Innovative Biomedical Visualization (iBMV) (T.T.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya; Department of Radiology (Kouhei Kamiya, M.H.), Toho University Omori Medical Center, Ota-ku, Tokyo; and Department of Radiology (S.N.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya, Japan.
| | - Christina Andica
- From the Department of Radiology (Koji Kamagata, C.A., K.T., Y.S., H.N., J.K., S.F., A.H., A.W., T.A., K.S., M.N., S.A.), Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo; Faculty of Health Data Science (C.A.), Juntendo University, Urayasu, Chiba, Department of Innovative Biomedical Visualization (iBMV) (T.T.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya; Department of Radiology (Kouhei Kamiya, M.H.), Toho University Omori Medical Center, Ota-ku, Tokyo; and Department of Radiology (S.N.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya, Japan
| | - Kaito Takabayashi
- From the Department of Radiology (Koji Kamagata, C.A., K.T., Y.S., H.N., J.K., S.F., A.H., A.W., T.A., K.S., M.N., S.A.), Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo; Faculty of Health Data Science (C.A.), Juntendo University, Urayasu, Chiba, Department of Innovative Biomedical Visualization (iBMV) (T.T.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya; Department of Radiology (Kouhei Kamiya, M.H.), Toho University Omori Medical Center, Ota-ku, Tokyo; and Department of Radiology (S.N.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya, Japan
| | - Yuya Saito
- From the Department of Radiology (Koji Kamagata, C.A., K.T., Y.S., H.N., J.K., S.F., A.H., A.W., T.A., K.S., M.N., S.A.), Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo; Faculty of Health Data Science (C.A.), Juntendo University, Urayasu, Chiba, Department of Innovative Biomedical Visualization (iBMV) (T.T.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya; Department of Radiology (Kouhei Kamiya, M.H.), Toho University Omori Medical Center, Ota-ku, Tokyo; and Department of Radiology (S.N.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya, Japan
| | - Toshiaki Taoka
- From the Department of Radiology (Koji Kamagata, C.A., K.T., Y.S., H.N., J.K., S.F., A.H., A.W., T.A., K.S., M.N., S.A.), Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo; Faculty of Health Data Science (C.A.), Juntendo University, Urayasu, Chiba, Department of Innovative Biomedical Visualization (iBMV) (T.T.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya; Department of Radiology (Kouhei Kamiya, M.H.), Toho University Omori Medical Center, Ota-ku, Tokyo; and Department of Radiology (S.N.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya, Japan
| | - Hayato Nozaki
- From the Department of Radiology (Koji Kamagata, C.A., K.T., Y.S., H.N., J.K., S.F., A.H., A.W., T.A., K.S., M.N., S.A.), Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo; Faculty of Health Data Science (C.A.), Juntendo University, Urayasu, Chiba, Department of Innovative Biomedical Visualization (iBMV) (T.T.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya; Department of Radiology (Kouhei Kamiya, M.H.), Toho University Omori Medical Center, Ota-ku, Tokyo; and Department of Radiology (S.N.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya, Japan
| | - Junko Kikuta
- From the Department of Radiology (Koji Kamagata, C.A., K.T., Y.S., H.N., J.K., S.F., A.H., A.W., T.A., K.S., M.N., S.A.), Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo; Faculty of Health Data Science (C.A.), Juntendo University, Urayasu, Chiba, Department of Innovative Biomedical Visualization (iBMV) (T.T.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya; Department of Radiology (Kouhei Kamiya, M.H.), Toho University Omori Medical Center, Ota-ku, Tokyo; and Department of Radiology (S.N.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya, Japan
| | - Shohei Fujita
- From the Department of Radiology (Koji Kamagata, C.A., K.T., Y.S., H.N., J.K., S.F., A.H., A.W., T.A., K.S., M.N., S.A.), Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo; Faculty of Health Data Science (C.A.), Juntendo University, Urayasu, Chiba, Department of Innovative Biomedical Visualization (iBMV) (T.T.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya; Department of Radiology (Kouhei Kamiya, M.H.), Toho University Omori Medical Center, Ota-ku, Tokyo; and Department of Radiology (S.N.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya, Japan
| | - Akifumi Hagiwara
- From the Department of Radiology (Koji Kamagata, C.A., K.T., Y.S., H.N., J.K., S.F., A.H., A.W., T.A., K.S., M.N., S.A.), Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo; Faculty of Health Data Science (C.A.), Juntendo University, Urayasu, Chiba, Department of Innovative Biomedical Visualization (iBMV) (T.T.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya; Department of Radiology (Kouhei Kamiya, M.H.), Toho University Omori Medical Center, Ota-ku, Tokyo; and Department of Radiology (S.N.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya, Japan
| | - Kouhei Kamiya
- From the Department of Radiology (Koji Kamagata, C.A., K.T., Y.S., H.N., J.K., S.F., A.H., A.W., T.A., K.S., M.N., S.A.), Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo; Faculty of Health Data Science (C.A.), Juntendo University, Urayasu, Chiba, Department of Innovative Biomedical Visualization (iBMV) (T.T.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya; Department of Radiology (Kouhei Kamiya, M.H.), Toho University Omori Medical Center, Ota-ku, Tokyo; and Department of Radiology (S.N.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya, Japan
| | - Akihiko Wada
- From the Department of Radiology (Koji Kamagata, C.A., K.T., Y.S., H.N., J.K., S.F., A.H., A.W., T.A., K.S., M.N., S.A.), Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo; Faculty of Health Data Science (C.A.), Juntendo University, Urayasu, Chiba, Department of Innovative Biomedical Visualization (iBMV) (T.T.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya; Department of Radiology (Kouhei Kamiya, M.H.), Toho University Omori Medical Center, Ota-ku, Tokyo; and Department of Radiology (S.N.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya, Japan
| | - Toshiaki Akashi
- From the Department of Radiology (Koji Kamagata, C.A., K.T., Y.S., H.N., J.K., S.F., A.H., A.W., T.A., K.S., M.N., S.A.), Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo; Faculty of Health Data Science (C.A.), Juntendo University, Urayasu, Chiba, Department of Innovative Biomedical Visualization (iBMV) (T.T.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya; Department of Radiology (Kouhei Kamiya, M.H.), Toho University Omori Medical Center, Ota-ku, Tokyo; and Department of Radiology (S.N.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya, Japan
| | - Katsuhiro Sano
- From the Department of Radiology (Koji Kamagata, C.A., K.T., Y.S., H.N., J.K., S.F., A.H., A.W., T.A., K.S., M.N., S.A.), Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo; Faculty of Health Data Science (C.A.), Juntendo University, Urayasu, Chiba, Department of Innovative Biomedical Visualization (iBMV) (T.T.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya; Department of Radiology (Kouhei Kamiya, M.H.), Toho University Omori Medical Center, Ota-ku, Tokyo; and Department of Radiology (S.N.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya, Japan
| | - Mitsuo Nishizawa
- From the Department of Radiology (Koji Kamagata, C.A., K.T., Y.S., H.N., J.K., S.F., A.H., A.W., T.A., K.S., M.N., S.A.), Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo; Faculty of Health Data Science (C.A.), Juntendo University, Urayasu, Chiba, Department of Innovative Biomedical Visualization (iBMV) (T.T.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya; Department of Radiology (Kouhei Kamiya, M.H.), Toho University Omori Medical Center, Ota-ku, Tokyo; and Department of Radiology (S.N.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya, Japan
| | - Masaaki Hori
- From the Department of Radiology (Koji Kamagata, C.A., K.T., Y.S., H.N., J.K., S.F., A.H., A.W., T.A., K.S., M.N., S.A.), Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo; Faculty of Health Data Science (C.A.), Juntendo University, Urayasu, Chiba, Department of Innovative Biomedical Visualization (iBMV) (T.T.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya; Department of Radiology (Kouhei Kamiya, M.H.), Toho University Omori Medical Center, Ota-ku, Tokyo; and Department of Radiology (S.N.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya, Japan
| | - Shinji Naganawa
- From the Department of Radiology (Koji Kamagata, C.A., K.T., Y.S., H.N., J.K., S.F., A.H., A.W., T.A., K.S., M.N., S.A.), Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo; Faculty of Health Data Science (C.A.), Juntendo University, Urayasu, Chiba, Department of Innovative Biomedical Visualization (iBMV) (T.T.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya; Department of Radiology (Kouhei Kamiya, M.H.), Toho University Omori Medical Center, Ota-ku, Tokyo; and Department of Radiology (S.N.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya, Japan
| | - Shigeki Aoki
- From the Department of Radiology (Koji Kamagata, C.A., K.T., Y.S., H.N., J.K., S.F., A.H., A.W., T.A., K.S., M.N., S.A.), Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo; Faculty of Health Data Science (C.A.), Juntendo University, Urayasu, Chiba, Department of Innovative Biomedical Visualization (iBMV) (T.T.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya; Department of Radiology (Kouhei Kamiya, M.H.), Toho University Omori Medical Center, Ota-ku, Tokyo; and Department of Radiology (S.N.), Nagoya University Graduate School of Medicine, Shouwa-ku, Nagoya, Japan
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24
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Gustavson DE, Archer DB, Elman JA, Puckett OK, Fennema-Notestine C, Panizzon MS, Shashikumar N, Hohman TJ, Jefferson AL, Eyler LT, McEvoy LK, Lyons MJ, Franz CE, Kremen WS. Associations among executive function Abilities, free Water, and white matter microstructure in early old age. Neuroimage Clin 2022; 37:103279. [PMID: 36493704 PMCID: PMC9731853 DOI: 10.1016/j.nicl.2022.103279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 10/26/2022] [Accepted: 11/30/2022] [Indexed: 12/04/2022]
Abstract
BACKGROUND Studies have investigated white matter microstructure in relation to late-life cognitive impairments, with fractional anisotropy (FA) and mean diffusivity (MD) measures thought to capture demyelination and axonal degradation. However, new post-processing methods allow isolation of free water (FW), which captures extracellular fluid contributions such as atrophy and neuroinflammation, from tissue components. FW also appears to be highly relevant to late-life cognitive impairment. Here, we evaluated whether executive functions are associated with FW, and FA and MD corrected for FW (FAFWcorr and MDFWcorr). METHOD We examined 489 non-demented men in the Vietnam Era Twin Study of Aging (VETSA) at mean age 68. Two latent factors capturing 'common executive function' and 'working-memory specific' processes were estimated based on 6 tasks. Analyses focused on 11 cortical white matter tracts across three metrics: FW, FAFWcorr, and MDFWcorr. RESULTS Better 'common executive function' was associated with lower FW across 9 of the 11 tracts. There were no significant associations with intracellular metrics after false discovery rate correction. Effects also appeared driven by individuals with MCI (13.7% of the sample). Working memory-specific tasks showed some associations with FAFWcorr, including the triangularis portion of the inferior frontal gyrus. There was no evidence that cognitive reserve (i.e., general cognitive ability assessed in early adulthood) moderated these associations between executive function and FW or FA. DISCUSSION Executive function abilities in early old age are associated primarily with extracellular fluid (FW) as opposed to white matter (FAFWcorr or MDFWcorr). Moderation analyses suggested cognitive reserve does not play a strong role in these associations, at least in this sample of non-demented men.
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Affiliation(s)
- Daniel E Gustavson
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA; Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA.
| | - Derek B Archer
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jeremy A Elman
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA
| | - Olivia K Puckett
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA
| | - Christine Fennema-Notestine
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA; Department of Radiology, University of California San Diego, La Jolla, CA, USA
| | - Matthew S Panizzon
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA
| | - Niranjana Shashikumar
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Timothy J Hohman
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Angela L Jefferson
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lisa T Eyler
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA
| | - Linda K McEvoy
- Department of Radiology, University of California San Diego, La Jolla, CA, USA; Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Carol E Franz
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA
| | - William S Kremen
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA
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25
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Rosenberg GA. Willis Lecture: Biomarkers for Inflammatory White Matter Injury in Binswanger Disease Provide Pathways to Precision Medicine. Stroke 2022; 53:3514-3523. [PMID: 36148658 PMCID: PMC9613611 DOI: 10.1161/strokeaha.122.039211] [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] [Indexed: 11/16/2022]
Abstract
Binswanger disease is the small vessel form of vascular cognitive impairment and dementia. Deposition of Alzheimer disease proteins can begin in midlife and progress slowly, whereas aging of the vasculature also can begin in midlife, continuing to progress into old age, making mixed dementia the most common type of dementia. Biomarkers facilitate the early diagnosis of dementias. It is possible to diagnose mixed dementia before autopsy with biomarkers for vascular disease derived from diffusor tensor images on magnetic resonance imaging and Alzheimer disease proteins, Aβ (amyloid β), and phosphorylated tau, in cerebrospinal fluid or in brain with positron emission tomography. The presence of vascular disease accelerates cognitive decline. Both misfolded proteins and vascular disease promote inflammation, which can be detected in cerebrospinal fluid by the presence of MMPs (matrix metalloproteinases), angiogenic growth factors, and cytokines. MMPs disrupt the blood-brain barrier and break down myelin, producing Binswanger disease's 2 main pathological features. Advances in detecting biomarkers in plasma will provide early detection of dementia and aided by machine learning and artificial intelligence, will enhance diagnosis and form the basis for early treatments.
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Affiliation(s)
- Gary A Rosenberg
- Center for Memory and Aging, Departments of Neurology, Neurosciences, Cell Biology and Physiology, University of New Mexico Health Sciences Center, Albuquerque
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26
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Bauer CE, Zachariou V, Maillard P, Caprihan A, Gold BT. Multi-compartment diffusion magnetic resonance imaging models link tract-related characteristics with working memory performance in healthy older adults. Front Aging Neurosci 2022; 14:995425. [PMID: 36275003 PMCID: PMC9581239 DOI: 10.3389/fnagi.2022.995425] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Accepted: 09/09/2022] [Indexed: 11/25/2022] Open
Abstract
Multi-compartment diffusion MRI metrics [such as metrics from free water elimination diffusion tensor imaging (FWE-DTI) and neurite orientation dispersion and density imaging (NODDI)] may reflect more specific underlying white-matter tract characteristics than traditional, single-compartment metrics [i.e., metrics from Diffusion Tensor Imaging (DTI)]. However, it remains unclear if multi-compartment metrics are more closely associated with age and/or cognitive performance than single-compartment metrics. Here we compared the associations of single-compartment [Fractional Anisotropy (FA)] and multi-compartment diffusion MRI metrics [FWE-DTI metrics: Free Water Eliminated Fractional Anisotropy (FWE-FA) and Free Water (FW); NODDI metrics: Intracellular Volume Fraction (ICVF), Orientation Dispersion Index (ODI), and CSF-Fraction] with both age and working memory performance. A functional magnetic resonance imaging (fMRI) guided, white matter tractography approach was employed to compute diffusion metrics within a network of tracts connecting functional regions involved in working memory. Ninety-nine healthy older adults (aged 60-85) performed an in-scanner working memory task while fMRI was performed and also underwent multi-shell diffusion acquisition. The network of white matter tracts connecting functionally-activated regions was identified using probabilistic tractography. Diffusion metrics were extracted from skeletonized white matter tracts connecting fMRI activation peaks. Diffusion metrics derived from both single and multi-compartment models were associated with age (p s ≤ 0.011 for FA, FWE-FA, ICVF and ODI). However, only multi-compartment metrics, specifically FWE-FA (p = 0.045) and ICVF (p = 0.020), were associated with working memory performance. Our results suggest that while most current diffusion metrics are sensitive to age, several multi-compartment metrics (i.e., FWE-FA and ICVF) appear more sensitive to cognitive performance in healthy older adults.
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Affiliation(s)
- Christopher E. Bauer
- Department of Neuroscience, University of Kentucky, Lexington, KY, United States
| | - Valentinos Zachariou
- Department of Neuroscience, University of Kentucky, Lexington, KY, United States
| | - Pauline Maillard
- Department of Neurology, University of California at Davis, Davis, CA, United States
- Center for Neuroscience, University of California at Davis, Davis, CA, United States
| | | | - Brian T. Gold
- Department of Neuroscience, University of Kentucky, Lexington, KY, United States
- Sanders-Brown Center on Aging, Lexington, KY, United States
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27
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Zachariou V, Bauer CE, Pappas C, Gold BT. High cortical iron is associated with the disruption of white matter tracts supporting cognitive function in healthy older adults. Cereb Cortex 2022; 33:4815-4828. [PMID: 36182267 PMCID: PMC10110441 DOI: 10.1093/cercor/bhac382] [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: 07/11/2022] [Revised: 08/29/2022] [Accepted: 08/30/2022] [Indexed: 01/25/2023] Open
Abstract
Aging is associated with brain iron accumulation, which has been linked to cognitive decline. However, how brain iron affects the structure and function of cognitive brain networks remains unclear. Here, we explored the possibility that iron load in gray matter is associated with disruption of white matter (WM) microstructure within a network supporting cognitive function, in a cohort of 95 cognitively normal older adults (age range: 60-86). Functional magnetic resonance imaging was used to localize a set of brain regions involved in working memory and diffusion tensor imaging based probabilistic tractography was used to identify a network of WM tracts connecting the functionally defined regions. Brain iron concentration within these regions was evaluated using quantitative susceptibility mapping and microstructural properties were assessed within the identified tracts using neurite orientation dispersion and density imaging. Results indicated that high brain iron concentration was associated with low neurite density (ND) within the task-relevant WM network. Further, regional associations were observed such that brain iron in cortical regions was linked with lower ND in neighboring but not distant WM tracts. Our results provide novel evidence suggesting that age-related increases in brain iron concentration are associated with the disruption of WM tracts supporting cognitive function in normal aging.
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Affiliation(s)
- Valentinos Zachariou
- Department of Neuroscience, University of Kentucky, Lexington, KY 40536-0298, United States.,College of Medicine, University of Kentucky, Lexington, KY 40536-0298, United States
| | - Christopher E Bauer
- Department of Neuroscience, University of Kentucky, Lexington, KY 40536-0298, United States.,College of Medicine, University of Kentucky, Lexington, KY 40536-0298, United States
| | - Colleen Pappas
- Department of Neuroscience, University of Kentucky, Lexington, KY 40536-0298, United States.,College of Medicine, University of Kentucky, Lexington, KY 40536-0298, United States
| | - Brian T Gold
- Department of Neuroscience, University of Kentucky, Lexington, KY 40536-0298, United States.,College of Medicine, University of Kentucky, Lexington, KY 40536-0298, United States.,Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY 40536-0298, United States.,Magnetic Resonance Imaging and Spectroscopy Center, University of Kentucky, Lexington, KY 40536-0298, United States
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28
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Kern KC, Wright CB, Leigh R. Global changes in diffusion tensor imaging during acute ischemic stroke and post-stroke cognitive performance. J Cereb Blood Flow Metab 2022; 42:1854-1866. [PMID: 35579236 PMCID: PMC9536124 DOI: 10.1177/0271678x221101644] [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: 11/16/2022]
Abstract
Post-stroke cognitive impairment is related to the effects of the acute stroke and pre-stroke brain health. We tested whether diffusion tensor imaging (DTI) can detect acute, global effects of stroke and predict post-stroke cognitive performance. Patients with stroke or TIA enrolled in a prospective cohort study were included if they had 1) at least one DTI acquisition at acute presentation, 24 hours, 5 days, or 30 days, and 2) follow-up testing with the telephone Montreal Cognitive Assessment (T-MoCA) at 30 and/or 90 days. A whole brain, white-matter skeleton excluding the infarct was used to derive mean global DTI measures for mean diffusivity (MD), fractional anisotropy (FA), free water (FW), FW-corrected MD (MDtissue), and FW-corrected FA (FAtissue). In 74 patients with ischemic stroke or TIA, there was a transient 4.2% increase in mean global FW between acute presentation and 24 hours (p = 0.024) that returned to initial values by 30 days (p = 0.03). Each acute global DTI measure was associated with 30-day T-MoCA score (n = 61, p = 0.0011-0.0076). Acute global FW, MD, FA and FAtissue were also associated with 90-day T-MoCA (n = 56, p = 0.0034-0.049). Transient global FW elevation likely reflects stroke-related interstitial edema, whereas other global DTI measures are more representative of pre-stroke brain health.
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Affiliation(s)
- Kyle C Kern
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Clinton B Wright
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Richard Leigh
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.,Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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29
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Mayer C, Nägele FL, Petersen M, Frey BM, Hanning U, Pasternak O, Petersen E, Gerloff C, Thomalla G, Cheng B. Free-water diffusion MRI detects structural alterations surrounding white matter hyperintensities in the early stage of cerebral small vessel disease. J Cereb Blood Flow Metab 2022; 42:1707-1718. [PMID: 35410517 PMCID: PMC9441727 DOI: 10.1177/0271678x221093579] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
In cerebral small vessel disease (CSVD), both white matter hyperintensities (WMH) of presumed vascular origin and the normal-appearing white matter (NAWM) contain microstructural brain alterations on diffusion-weighted MRI (DWI). Contamination of DWI-derived metrics by extracellular free-water can be corrected with free-water (FW) imaging. We investigated the alterations in FW and FW-corrected fractional anisotropy (FA-t) in WMH and surrounding tissue and their association with cerebrovascular risk factors. We analysed 1,000 MRI datasets from the Hamburg City Health Study. DWI was used to generate FW and FA-t maps. WMH masks were segmented on FLAIR and T1-weighted MRI and dilated repeatedly to create 8 NAWM masks representing increasing distance from WMH. Linear models were applied to compare FW and FA-t across WMH and NAWM masks and in association with cerebrovascular risk. Median age was 64 ± 14 years. FW and FA-t were altered 8 mm and 12 mm beyond WMH, respectively. Smoking was significantly associated with FW in NAWM (p = 0.008) and FA-t in WMH (p = 0.008) and in NAWM (p = 0.003) while diabetes and hypertension were not. Further research is necessary to examine whether FW and FA-t alterations in NAWM are predictors for developing WMH.
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Affiliation(s)
- Carola Mayer
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Felix L Nägele
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Marvin Petersen
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Benedikt M Frey
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Uta Hanning
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Ofer Pasternak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, USA.,Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, USA
| | - Elina Petersen
- Clinical for Cardiology, University Heart and Vascular Center, Germany.,Population Health Research Department, University Heart and Vascular Center, Hamburg, Germany
| | - Christian Gerloff
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Götz Thomalla
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Bastian Cheng
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
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30
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Ota Y, Shah G. Imaging of Normal Brain Aging. Neuroimaging Clin N Am 2022; 32:683-698. [PMID: 35843669 DOI: 10.1016/j.nic.2022.04.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Understanding normal brain aging physiology is essential to improving healthy human longevity, differentiation, and early detection of diseases, such as neurodegenerative diseases, which are an enormous social and economic burden. Functional decline, such as reduced physical activity and cognitive abilities, is typically associated with brain aging. The authors summarize the aging brain mechanism and effects of aging on the brain observed by brain structural MR imaging and advanced neuroimaging techniques, such as diffusion tensor imaging and functional MR imaging.
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Affiliation(s)
- Yoshiaki Ota
- Division of Neuroradiology, Department of Radiology, University of Michigan, 1500 East Medical Center Drive, UH B2, Ann Arbor, MI 48109, USA
| | - Gaurang Shah
- Division of Neuroradiology, Department of Radiology, University of Michigan, 1500 East Medical Center Drive, UH B2, Ann Arbor, MI 48109, USA.
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31
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Wang S, Zhang F, Huang P, Hong H, Jiaerken Y, Yu X, Zhang R, Zeng Q, Zhang Y, Kikinis R, Rathi Y, Makris N, Lou M, Pasternak O, Zhang M, O'Donnell LJ. Superficial white matter microstructure affects processing speed in cerebral small vessel disease. Hum Brain Mapp 2022; 43:5310-5325. [PMID: 35822593 PMCID: PMC9812245 DOI: 10.1002/hbm.26004] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Revised: 06/10/2022] [Accepted: 06/15/2022] [Indexed: 01/15/2023] Open
Abstract
White matter hyperintensities (WMH) are a typical feature of cerebral small vessel disease (CSVD), which contributes to about 50% of dementias worldwide. Microstructural alterations in deep white matter (DWM) have been widely examined in CSVD. However, little is known about abnormalities in superficial white matter (SWM) and their relevance for processing speed, the main cognitive deficit in CSVD. In 141 CSVD patients, processing speed was assessed using Trail Making Test Part A. White matter abnormalities were assessed by WMH burden (volume on T2-FLAIR) and diffusion MRI measures. SWM imaging measures had a large contribution to processing speed, despite a relatively low SWM WMH burden. Across all imaging measures, SWM free water (FW) had the strongest association with processing speed, followed by SWM mean diffusivity (MD). SWM FW was the only marker to significantly increase between two subgroups with the lowest WMH burdens. When comparing two subgroups with the highest WMH burdens, the involvement of WMH in the SWM was accompanied by significant differences in processing speed and white matter microstructure. Mediation analysis revealed that SWM FW fully mediated the association between WMH volume and processing speed, while no mediation effect of MD or DWM FW was observed. Overall, results suggest that the SWM has an important contribution to processing speed, while SWM FW is a sensitive imaging marker associated with cognition in CSVD. This study extends the current understanding of CSVD-related dysfunction and suggests that the SWM, as an understudied region, can be a potential target for monitoring pathophysiological processes.
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Affiliation(s)
- Shuyue Wang
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina,Brigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Fan Zhang
- Brigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Peiyu Huang
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
| | - Hui Hong
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
| | - Yeerfan Jiaerken
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
| | - Xinfeng Yu
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
| | - Ruiting Zhang
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
| | - Qingze Zeng
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
| | - Yao Zhang
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
| | - Ron Kikinis
- Brigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Yogesh Rathi
- Brigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Nikos Makris
- Brigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA,Center for Morphometric AnalysisMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Min Lou
- Department of Neurologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
| | - Ofer Pasternak
- Brigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Minming Zhang
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
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Berger M, Pirpamer L, Hofer E, Ropele S, Duering M, Gesierich B, Pasternak O, Enzinger C, Schmidt R, Koini M. Free water diffusion MRI and executive function with a speed component in healthy aging. Neuroimage 2022; 257:119303. [PMID: 35568345 PMCID: PMC9465649 DOI: 10.1016/j.neuroimage.2022.119303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 05/06/2022] [Accepted: 05/09/2022] [Indexed: 11/12/2022] Open
Abstract
Extracellular free water (FW) increases are suggested to better provide pathophysiological information in brain aging than conventional biomarkers such as fractional anisotropy. The aim of the present study was to determine the relationship between conventional biomarkers, FW in white matter hyperintensities (WMH), FW in normal appearing white matter (NAWM) and in white matter tracts and executive functions (EF) with a speed component in elderly persons. We examined 226 healthy elderly participants (median age 69.83 years, IQR: 56.99–74.42) who underwent brain MRI and neuropsychological examination. FW in WMH and in NAWM as well as FW corrected diffusion metrics and measures derived from conventional MRI (white matter hyperintensities, brain volume, lacunes) were used in partial correlation (adjusted for age) to assess their correlation with EF with a speed component. Random forest analysis was used to assess the relative importance of these variables as determinants. Lastly, linear regression analyses of FW in white matter tracts corrected for risk factors of cognitive and white matter deterioration, were used to examine the role of specific tracts on EF with a speed component, which were then ranked with random forest regression. Partial correlation analyses revealed that almost all imaging metrics showed a significant association with EF with a speed component (r = −0.213 – 0.266). Random forest regression highlighted FW in WMH and in NAWM as most important among all diffusion and structural MRI metrics. The fornix (R2=0.421, p = 0.018) and the corpus callosum (genu (R2 = 0.418, p = 0.021), prefrontal (R2 = 0.416, p = 0.026), premotor (R2 = 0.418, p = 0.021)) were associated with EF with a speed component in tract based regression analyses and had highest variables importance. In a normal aging population FW in WMH and NAWM is more closely related to EF with a speed component than standard DTI and brain structural measures. Higher amounts of FW in the fornix and the frontal part of the corpus callosum leads to deteriorating EF with a speed component.
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Affiliation(s)
- Martin Berger
- Department of Neurology, Division of Neurogeriatrics, Medical University of Graz, Auenbruggerplatz 22, Graz 8036, Austria
| | - Lukas Pirpamer
- Department of Neurology, Division of Neurogeriatrics, Medical University of Graz, Auenbruggerplatz 22, Graz 8036, Austria
| | - Edith Hofer
- Department of Neurology, Division of Neurogeriatrics, Medical University of Graz, Auenbruggerplatz 22, Graz 8036, Austria; Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria
| | - Stefan Ropele
- Department of Neurology, Division of Neurogeriatrics, Medical University of Graz, Auenbruggerplatz 22, Graz 8036, Austria
| | - Marco Duering
- Medical Image Analysis Center (MIAC AG) and Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Benno Gesierich
- Institute for Stroke and Dementia Research (ISD), University Hospital, Munich, Germany
| | - Ofer Pasternak
- Departments of Psychiatry and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Reinhold Schmidt
- Department of Neurology, Division of Neurogeriatrics, Medical University of Graz, Auenbruggerplatz 22, Graz 8036, Austria.
| | - Marisa Koini
- Department of Neurology, Division of Neurogeriatrics, Medical University of Graz, Auenbruggerplatz 22, Graz 8036, Austria
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Maillard P, Lu H, Arfanakis K, Gold BT, Bauer CE, Zachariou V, Stables L, Wang DJ, Jann K, Seshadri S, Duering M, Hillmer LJ, Rosenberg GA, Snoussi H, Sepehrband F, Habes M, Singh B, Kramer JH, Corriveau RA, Singh H, Schwab K, Helmer KG, Greenberg SM, Caprihan A, DeCarli C, Satizabal CL. Instrumental validation of free water, peak-width of skeletonized mean diffusivity, and white matter hyperintensities: MarkVCID neuroimaging kits. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2022; 14:e12261. [PMID: 35382232 PMCID: PMC8959640 DOI: 10.1002/dad2.12261] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Indexed: 11/11/2022]
Abstract
Introduction To describe the protocol and findings of the instrumental validation of three imaging-based biomarker kits selected by the MarkVCID consortium: free water (FW) and peak width of skeletonized mean diffusivity (PSMD), both derived from diffusion tensor imaging (DTI), and white matter hyperintensity (WMH) volume derived from fluid attenuation inversion recovery and T1-weighted imaging. Methods The instrumental validation of imaging-based biomarker kits included inter-rater reliability among participating sites, test-retest repeatability, and inter-scanner reproducibility across three types of magnetic resonance imaging (MRI) scanners using intra-class correlation coefficients (ICC). Results The three biomarkers demonstrated excellent inter-rater reliability (ICC >0.94, P-values < .001), very high agreement between test and retest sessions (ICC >0.98, P-values < .001), and were extremely consistent across the three scanners (ICC >0.98, P-values < .001). Discussion The three biomarker kits demonstrated very high inter-rater reliability, test-retest repeatability, and inter-scanner reproducibility, offering robust biomarkers suitable for future multi-site observational studies and clinical trials in the context of vascular cognitive impairment and dementia (VCID).
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Affiliation(s)
- Pauline Maillard
- Department of NeurologyUniversity of California, DavisDavisCaliforniaUSA
| | - Hanzhang Lu
- Department of RadiologyJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Konstantinos Arfanakis
- Department of Biomedical EngineeringIllinois Institute of TechnologyChicagoIllinoisUSA
- Department of Diagnostic Radiology and Nuclear Medicine, Rush Alzheimer's Disease CenterRush University Medical CenterChicagoIllinoisUSA
| | - Brian T. Gold
- Department of NeuroscienceUniversity of KentuckyLexingtonKentuckyUSA
| | | | | | - Lara Stables
- Department of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Danny J.J. Wang
- Laboratory of FMRI Technology (LOFT)Stevens Neuroimaging and Informatics InstituteKeck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Kay Jann
- Laboratory of FMRI Technology (LOFT)Stevens Neuroimaging and Informatics InstituteKeck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Sudha Seshadri
- Department of NeurologyBoston University School of MedicineBostonMassachusettsUSA
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health San AntonioSan AntonioTexasUSA
| | - Marco Duering
- Department of Biomedical EngineeringMedical Image Analysis Center (MIAC AG)University of BaselBaselSwitzerland
| | - Laura J. Hillmer
- Department of NeurologyUniversity of New MexicoAlbuquerqueNew MexicoUSA
| | - Gary A. Rosenberg
- Department of NeurologyUniversity of New MexicoAlbuquerqueNew MexicoUSA
| | - Haykel Snoussi
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health San AntonioSan AntonioTexasUSA
| | - Farshid Sepehrband
- Laboratory of FMRI Technology (LOFT)Stevens Neuroimaging and Informatics InstituteKeck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Mohamad Habes
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health San AntonioSan AntonioTexasUSA
| | - Baljeet Singh
- Department of NeurologyUniversity of California, DavisDavisCaliforniaUSA
| | - Joel H. Kramer
- Department of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | | | - Herpreet Singh
- Department of NeurologyMassachusetts General HospitalBostonMassachusettsUSA
| | - Kristin Schwab
- Department of NeurologyMassachusetts General HospitalBostonMassachusettsUSA
| | - Karl G. Helmer
- Department of RadiologyMassachusetts General HospitalBostonMassachusettsUSA
- Department of RadiologyHarvard Medical SchoolBostonMassachusettsUSA
| | | | | | - Charles DeCarli
- Department of NeurologyUniversity of California, DavisDavisCaliforniaUSA
| | - Claudia L. Satizabal
- Department of NeurologyBoston University School of MedicineBostonMassachusettsUSA
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health San AntonioSan AntonioTexasUSA
- Department of Population Health SciencesUniversity of Texas Health San AntonioSan AntonioTexasUSA
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Tseng WYI, Hsu YC, Kao TW. Brain Age Difference at Baseline Predicts Clinical Dementia Rating Change in Approximately Two Years. J Alzheimers Dis 2022; 86:613-627. [PMID: 35094993 DOI: 10.3233/jad-215380] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
BACKGROUND The Clinical Dementia Rating (CDR) has been widely used to assess dementia severity, but it is limited in predicting dementia progression, thus unable to advise preventive measures to those who are at high risk. OBJECTIVE Predicted age difference (PAD) was proposed to predict CDR change. METHODS All diffusion magnetic resonance imaging and CDR scores were obtained from the OASIS-3 databank. A brain age model was trained by a machine learning algorithm using the imaging data of 258 cognitively healthy adults. Two diffusion indices, i.e., mean diffusivity and fractional anisotropy, over the whole brain white matter were extracted to serve as the features for model training. The validated brain age model was applied to a longitudinal cohort of 217 participants who had CDR = 0 (CDR0), 0.5 (CDR0.5), and 1 (CDR1) at baseline. Participants were grouped according to different baseline CDR and their subsequent CDR in approximately 2 years of follow-up. PAD was compared between different groups with multiple comparison correction. RESULTS PADs were significantly different among participants with different baseline CDRs. PAD in participants with relatively stable CDR0.5 was significantly smaller than PAD in participants who had CDR0.5 at baseline but converted to CDR1 in the follow-up. Similarly, participants with relatively stable CDR0 had significantly smaller PAD than those who were CDR0 at baseline but converted to CDR0.5 in the follow-up. CONCLUSION Our results imply that PAD might be a potential imaging biomarker for predicting CDR outcomes in patients with CDR0 or CDR0.5.
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Affiliation(s)
- Wen-Yih Isaac Tseng
- AcroViz Inc. Taipei, Taiwan (R.O.C.).,Institute of Medical Device and Imaging, National Taiwan University College of Medicine, Taipei, Taiwan (R.O.C.).,Molecular Imaging Center, National Taiwan University, Taipei, Taiwan (R.O.C.)
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35
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Angoff R, Himali JJ, Maillard P, Aparicio HJ, Vasan RS, Seshadri S, Beiser AS, Tsao CW. Relations of Metabolic Health and Obesity to Brain Aging in Young to Middle-Aged Adults. J Am Heart Assoc 2022; 11:e022107. [PMID: 35229662 PMCID: PMC9075324 DOI: 10.1161/jaha.121.022107] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Accepted: 01/18/2022] [Indexed: 11/23/2022]
Abstract
Background We aimed to evaluate the association between metabolic health and obesity and brain health measured via magnetic resonance imaging and neurocognitive testing in community dwelling adults. Methods and Results Framingham Heart Study Third Generation Cohort members (n=2170, 46±9 years of age, 54% women) without prevalent diabetes, stroke, dementia, or other neurologic conditions were grouped by metabolic unhealthiness (≥2 criteria for metabolic syndrome) and obesity (body mass index ≥30 kg/m2): metabolically healthy (MH) nonobese, MH obese, metabolically unhealthy (MU) nonobese, and MU obese. We evaluated the relationships of these groups with brain structure (magnetic resonance imaging) and function (neurocognitive tests). In multivariable-adjusted analyses, metabolically unhealthy individuals (MU nonobese and MU obese) had lower total cerebral brain volume compared with the MH nonobese referent group (both P<0.05). Additionally, the MU obese group had greater white matter hyperintensity volume (P=0.004), whereas no association was noted between white matter hyperintensity volume and either groups of metabolic health or obesity alone. Obese individuals had less favorable cognitive scores: MH obese had lower scores on global cognition, Logical Memory-Delayed Recall and Similarities tests, and MU obese had lower scores on Similarities and Visual Reproductions-Delayed tests (all P≤0.04). MU and obese groups had higher free water content and lower fractional anisotropy in several brain regions, consistent with loss of white matter integrity. Conclusions In this cross-sectional cohort study of younger to middle-aged adults, poor metabolic health and obesity were associated with structural and functional evidence of brain aging. Improvement in metabolic health and obesity may present opportunities to improve long-term brain health.
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Affiliation(s)
- Rebecca Angoff
- Cardiovascular DivisionBeth Israel Deaconess Medical Center and Harvard Medical SchoolBostonMA
| | - Jayandra J. Himali
- Department of NeurologySchool of MedicineBoston UniversityBostonMA
- The Department of BiostatisticsBoston UniversityBostonMA
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative DiseasesUniversity of Texas Health Sciences CenterSan AntonioTX
- The Framingham Heart StudyFraminghamMA
| | - Pauline Maillard
- Department of Neurology and Center for NeuroscienceUniversity of California at DavisDavisCA
| | - Hugo J. Aparicio
- Department of NeurologySchool of MedicineBoston UniversityBostonMA
- The Framingham Heart StudyFraminghamMA
| | - Ramachandran S. Vasan
- Department of MedicineSchool of MedicineBoston UniversityBostonMA
- Department of EpidemiologyBoston UniversityBostonMA
- The Framingham Heart StudyFraminghamMA
| | - Sudha Seshadri
- Department of NeurologySchool of MedicineBoston UniversityBostonMA
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative DiseasesUniversity of Texas Health Sciences CenterSan AntonioTX
- Department of Population Health SciencesUniversity of Texas Health Science CenterSan AntonioTX
- The Framingham Heart StudyFraminghamMA
| | - Alexa S. Beiser
- Department of NeurologySchool of MedicineBoston UniversityBostonMA
- The Department of BiostatisticsBoston UniversityBostonMA
- The Framingham Heart StudyFraminghamMA
| | - Connie W. Tsao
- Cardiovascular DivisionBeth Israel Deaconess Medical Center and Harvard Medical SchoolBostonMA
- The Framingham Heart StudyFraminghamMA
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Hupfeld KE, Geraghty JM, McGregor HR, Hass CJ, Pasternak O, Seidler RD. Differential Relationships Between Brain Structure and Dual Task Walking in Young and Older Adults. Front Aging Neurosci 2022; 14:809281. [PMID: 35360214 PMCID: PMC8963788 DOI: 10.3389/fnagi.2022.809281] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 01/31/2022] [Indexed: 12/13/2022] Open
Abstract
Almost 25% of all older adults experience difficulty walking. Mobility difficulties for older adults are more pronounced when they perform a simultaneous cognitive task while walking (i.e., dual task walking). Although it is known that aging results in widespread brain atrophy, few studies have integrated across more than one neuroimaging modality to comprehensively examine the structural neural correlates that may underlie dual task walking in older age. We collected spatiotemporal gait data during single and dual task walking for 37 young (18–34 years) and 23 older adults (66–86 years). We also collected T1-weighted and diffusion-weighted MRI scans to determine how brain structure differs in older age and relates to dual task walking. We addressed two aims: (1) to characterize age differences in brain structure across a range of metrics including volumetric, surface, and white matter microstructure; and (2) to test for age group differences in the relationship between brain structure and the dual task cost (DTcost) of gait speed and variability. Key findings included widespread brain atrophy for the older adults, with the most pronounced age differences in brain regions related to sensorimotor processing. We also found multiple associations between regional brain atrophy and greater DTcost of gait speed and variability for the older adults. The older adults showed a relationship of both thinner temporal cortex and shallower sulcal depth in the frontal, sensorimotor, and parietal cortices with greater DTcost of gait. Additionally, the older adults showed a relationship of ventricular volume and superior longitudinal fasciculus free-water corrected axial and radial diffusivity with greater DTcost of gait. These relationships were not present for the young adults. Stepwise multiple regression found sulcal depth in the left precentral gyrus, axial diffusivity in the superior longitudinal fasciculus, and sex to best predict DTcost of gait speed, and cortical thickness in the superior temporal gyrus to best predict DTcost of gait variability for older adults. These results contribute to scientific understanding of how individual variations in brain structure are associated with mobility function in aging. This has implications for uncovering mechanisms of brain aging and for identifying target regions for mobility interventions for aging populations.
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Affiliation(s)
- Kathleen E. Hupfeld
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, United States
| | - Justin M. Geraghty
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, United States
| | - Heather R. McGregor
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, United States
| | - C. J. Hass
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, United States
| | - Ofer Pasternak
- Departments of Psychiatry and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States
| | - Rachael D. Seidler
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, United States
- University of Florida Norman Fixel Institute for Neurological Diseases, Gainesville, FL, United States
- *Correspondence: Rachael D. Seidler
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Rasgado-Toledo J, Shah A, Ingalhalikar M, Garza-Villarreal EA. Neurite orientation dispersion and density imaging in cocaine use disorder. Prog Neuropsychopharmacol Biol Psychiatry 2022; 113:110474. [PMID: 34758367 DOI: 10.1016/j.pnpbp.2021.110474] [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] [Received: 06/16/2021] [Revised: 10/29/2021] [Accepted: 11/01/2021] [Indexed: 01/01/2023]
Abstract
Cocaine use disorder (CUD) is characterized by a compulsive search for cocaine. Several studies have shown that cocaine users exhibit cognitive deficits, including lack of inhibition and decision-making as well as brain volume and diffusion-based white-matter alterations in a wide variety of brain regions. However, the non-specificity of standard volumetric and diffusion-tensor methods to detect structural micropathology may lead to wrong conclusions. To better understand microstructural pathology in CUD, we analyzed 60 CUD participants (3 female) and 43 non-CUD controls (HC; 2 female) retrospectively from our cross-sectional Mexican SUD neuroimaging dataset (SUDMEX-CONN), using multi-shell diffusion-weighted imaging and the neurite orientation dispersion and density imaging (NODDI) analysis, which aims to more accurately model microstructural pathology. We used Viso values of NODDI that employ a three-compartment model in white (WM) and gray-matter (GM). These values were also correlated with clinical measures, including psychiatric severity status, impulsive behavior and pattern of cocaine and tobacco use in the CUD group. We found higher whole-brain microstructural pathology in WM and GM in CUD patients than controls. ROI analysis revealed higher Viso-NODDI values in superior longitudinal fasciculus, cingulum, hippocampus cingulum, forceps minor and Uncinate fasciculus, as well as in frontal and parieto-temporal GM structures. We also found correlations between significant ROI and impulsivity, onset age of cocaine use and weekly dosage with Viso-NODDI. However, we did not find correlations with psychopathology measures. Overall, although their clinical relevance remains questionable, microstructural pathology seems to be present in CUD both in gray and white matter.
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Affiliation(s)
- Jalil Rasgado-Toledo
- Instituto de Neurobiología, Universidad Nacional Autónoma de México campus Juriquilla, Querétaro, Mexico
| | - Apurva Shah
- Symbiosis Center for Medical Image Analysis, Symbiosis Institute of Technology, Symbiosis International University, Pune, Maharashtra, India
| | - Madhura Ingalhalikar
- Symbiosis Center for Medical Image Analysis, Symbiosis Institute of Technology, Symbiosis International University, Pune, Maharashtra, India
| | - Eduardo A Garza-Villarreal
- Instituto de Neurobiología, Universidad Nacional Autónoma de México campus Juriquilla, Querétaro, Mexico.
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Zhu Z, Zeng Q, Zhang R, Luo X, Li K, Xu X, Zhang M, Yang Y, Huang P. White Matter Free Water Outperforms Cerebral Small Vessel Disease Total Score in Predicting Cognitive Decline in Persons with Mild Cognitive Impairment. J Alzheimers Dis 2022; 86:741-751. [PMID: 35124653 DOI: 10.3233/jad-215541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Vascular pathology is an important partner of Alzheimer's disease (AD). Both total cerebral small vessel disease (CSVD) score and white matter free water (FW) are useful markers that could reflect cerebral vascular injury. OBJECTIVE We aim to investigate the efficacy of these two metrics in predicting cognitive declines in patients with mild cognitive impairment (MCI). METHODS We enrolled 126 MCI subjects with 3D T1-weighted images, fluid-attenuated inversion recovery images, T2 * images, diffusion tensor imaging images, cerebrospinal fluid biomarkers and neuropsychological tests from the Alzheimer's Disease Neuroimaging Initiative database. The total CSVD score and FW values were calculated. Simple and multiple linear regression analyses were applied to explore the association between vascular and cognitive impairments. Linear mixed effect models were constructed to investigate the efficacy of total CSVD score and FW on predicting cognitive decline. RESULTS FW was associated with baseline cognition and could predict the decline of executive and language functions in MCI subjects, while no association was found between total CSVD score and cognitive declines. CONCLUSION FW is a promising imaging marker for investigating the effect of CSVD on AD progression.
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Affiliation(s)
- Zili Zhu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Shangcheng District, Hangzhou, China.,Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Ouhai District, Wenzhou, China
| | - Qingze Zeng
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Shangcheng District, Hangzhou, China
| | - Ruiting Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Shangcheng District, Hangzhou, China
| | - Xiao Luo
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Shangcheng District, Hangzhou, China
| | - Kaicheng Li
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Shangcheng District, Hangzhou, China
| | - Xiaopei Xu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Shangcheng District, Hangzhou, China
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Shangcheng District, Hangzhou, China
| | - Yunjun Yang
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Ouhai District, Wenzhou, China
| | - Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Shangcheng District, Hangzhou, China.,Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Ouhai District, Wenzhou, China
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Vemuri P, Decarli CS, Duering M. Imaging Markers of Vascular Brain Health: Quantification, Clinical Implications, and Future Directions. Stroke 2022; 53:416-426. [PMID: 35000423 PMCID: PMC8830603 DOI: 10.1161/strokeaha.120.032611] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Cerebrovascular disease (CVD) manifests through a broad spectrum of mechanisms that negatively impact brain and cognitive health. Oftentimes, CVD changes (excluding acute stroke) are insufficiently considered in aging and dementia studies which can lead to an incomplete picture of the etiologies contributing to the burden of cognitive impairment. Our goal with this focused review is 3-fold. First, we provide a research update on the current magnetic resonance imaging methods that can measure CVD lesions as well as early CVD-related brain injury specifically related to small vessel disease. Second, we discuss the clinical implications and relevance of these CVD imaging markers for cognitive decline, incident dementia, and disease progression in Alzheimer disease, and Alzheimer-related dementias. Finally, we present our perspective on the outlook and challenges that remain in the field. With the increased research interest in this area, we believe that reliable CVD imaging biomarkers for aging and dementia studies are on the horizon.
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Affiliation(s)
| | - Charles S. Decarli
- Departments of Neurology and Center for Neuroscience, University of California at Davis, Sacramento, California, USA
| | - Marco Duering
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Germany
- Medical Image Analysis Center (MIAC AG) and qbig, Department of Biomedical Engineering, University of Basel, Switzerland
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Bergamino M, Keeling EG, Baxter LC, Sisco NJ, Walsh RR, Stokes AM. Sex Differences in Alzheimer's Disease Revealed by Free-Water Diffusion Tensor Imaging and Voxel-Based Morphometry. J Alzheimers Dis 2022; 85:395-414. [PMID: 34842185 PMCID: PMC9015709 DOI: 10.3233/jad-210406] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
BACKGROUND Imaging biomarkers are increasingly used in Alzheimer's disease (AD), and the identification of sex differences using neuroimaging may provide insight into disease heterogeneity, progression, and therapeutic targets. OBJECTIVE The purpose of this study was to investigate differences in grey matter (GM) volume and white matter (WM) microstructural disorganization between males and females with AD using voxel-based morphometry (VBM) and free-water-corrected diffusion tensor imaging (FW-DTI). METHODS Data were downloaded from the OASIS-3 database, including 158 healthy control (HC; 86 females) and 46 mild AD subjects (24 females). VBM and FW-DTI metrics (fractional anisotropy (FA), axial and radial diffusivities (AxD and RD, respectively), and FW index) were compared using effect size for the main effects of group, sex, and their interaction. RESULTS Significant group and sex differences were observed, with no significant interaction. Post-hoc comparisons showed that AD is associated with reduced GM volume, reduced FW-FA, and higher FW-RD/FW-index, consistent with neurodegeneration. Females in both groups exhibited higher GM volume than males, while FW-DTI metrics showed sex differences only in the AD group. Lower FW, lower FW-FA and higher FW-RD were observed in females relative to males in the AD group. CONCLUSION The combination of VBM and DTI may reveal complementary sex-specific changes in GM and WM associated with AD and aging. Sex differences in GM volume were observed for both groups, while FW-DTI metrics only showed significant sex differences in the AD group, suggesting that WM tract disorganization may play a differential role in AD pathophysiology between females and males.
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Affiliation(s)
| | - Elizabeth G. Keeling
- Neuroimaging Research, Barrow Neurological Institute,School of Life Sciences, Arizona State University
| | | | | | - Ryan R. Walsh
- Muhammad Ali Parkinson Center at Barrow Neurological
Institute
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Blinkouskaya Y, Caçoilo A, Gollamudi T, Jalalian S, Weickenmeier J. Brain aging mechanisms with mechanical manifestations. Mech Ageing Dev 2021; 200:111575. [PMID: 34600936 PMCID: PMC8627478 DOI: 10.1016/j.mad.2021.111575] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2021] [Revised: 09/09/2021] [Accepted: 09/22/2021] [Indexed: 12/14/2022]
Abstract
Brain aging is a complex process that affects everything from the subcellular to the organ level, begins early in life, and accelerates with age. Morphologically, brain aging is primarily characterized by brain volume loss, cortical thinning, white matter degradation, loss of gyrification, and ventricular enlargement. Pathophysiologically, brain aging is associated with neuron cell shrinking, dendritic degeneration, demyelination, small vessel disease, metabolic slowing, microglial activation, and the formation of white matter lesions. In recent years, the mechanics community has demonstrated increasing interest in modeling the brain's (bio)mechanical behavior and uses constitutive modeling to predict shape changes of anatomically accurate finite element brain models in health and disease. Here, we pursue two objectives. First, we review existing imaging-based data on white and gray matter atrophy rates and organ-level aging patterns. This data is required to calibrate and validate constitutive brain models. Second, we review the most critical cell- and tissue-level aging mechanisms that drive white and gray matter changes. We focuse on aging mechanisms that ultimately manifest as organ-level shape changes based on the idea that the integration of imaging and mechanical modeling may help identify the tipping point when normal aging ends and pathological neurodegeneration begins.
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Affiliation(s)
- Yana Blinkouskaya
- Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States
| | - Andreia Caçoilo
- Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States
| | - Trisha Gollamudi
- Department of Biomedical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States
| | - Shima Jalalian
- Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States
| | - Johannes Weickenmeier
- Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States.
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Lim JS, Lee JJ, Woo CW. Post-Stroke Cognitive Impairment: Pathophysiological Insights into Brain Disconnectome from Advanced Neuroimaging Analysis Techniques. J Stroke 2021; 23:297-311. [PMID: 34649376 PMCID: PMC8521255 DOI: 10.5853/jos.2021.02376] [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: 07/04/2021] [Accepted: 09/17/2021] [Indexed: 12/24/2022] Open
Abstract
The neurological symptoms of stroke have traditionally provided the foundation for functional mapping of the brain. However, there are many unresolved aspects in our understanding of cerebral activity, especially regarding high-level cognitive functions. This review provides a comprehensive look at the pathophysiology of post-stroke cognitive impairment in light of recent findings from advanced imaging techniques. Combining network neuroscience and clinical neurology, our research focuses on how changes in brain networks correlate with post-stroke cognitive prognosis. More specifically, we first discuss the general consequences of stroke lesions due to damage of canonical resting-state large-scale networks or changes in the composition of the entire brain. We also review emerging methods, such as lesion-network mapping and gradient analysis, used to study the aforementioned events caused by stroke lesions. Lastly, we examine other patient vulnerabilities, such as superimposed amyloid pathology and blood-brain barrier leakage, which potentially lead to different outcomes for the brain network compositions even in the presence of similar stroke lesions. This knowledge will allow a better understanding of the pathophysiology of post-stroke cognitive impairment and provide a theoretical basis for the development of new treatments, such as neuromodulation.
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Affiliation(s)
- Jae-Sung Lim
- Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Jae-Joong Lee
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Korea.,Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Korea
| | - Choong-Wan Woo
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Korea.,Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Korea.,Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Korea
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43
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Suzuki H, Davis-Plourde K, Beiser A, Kunimura A, Miura K, DeCarli C, Maillard P, Mitchell GF, Vasan RS, Seshadri S, Fujiyoshi A. Coronary Artery Calcium Assessed Years Before Was Positively Associated With Subtle White Matter Injury of the Brain in Asymptomatic Middle-Aged Men: The Framingham Heart Study. Circ Cardiovasc Imaging 2021; 14:e011753. [PMID: 34256573 PMCID: PMC8323993 DOI: 10.1161/circimaging.120.011753] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
BACKGROUND Using magnetic resonance diffusion tensor imaging, we previously showed a cross-sectional association between carotid-femoral pulse wave velocity, a measure of aortic stiffness, and subtle white matter injury in clinically asymptomatic middle-age adults. While coronary artery calcium (CAC) is a robust measure of atherosclerosis, and a predictor of stroke and dementia, whether it predicts diffusion tensor imaging-based subtle white matter injury in the brain remains unknown. METHODS In FHS (Framingham Heart Study), an observational study, third-generation participants were assessed for CAC (2002-2005) and brain magnetic resonance imaging (2009-2014). Outcomes were diffusion tensor imaging-based measures; free water, fractional anisotropy, and peak width of mean diffusivity. After excluding the participants with neurological conditions and missing covariates, we categorized participants into 3 groups according to CAC score (0, 0 < to 100, and >100) and calculated a linear trend across the CAC groups. In secondary analyses treating CAC score as continuous, we computed slope of the outcomes per 20 to 80th percentiles higher log-transformed CAC score using linear regression. RESULTS In a total of 1052 individuals analyzed (mean age 45.4 years, 45.4% women), 71.6%, 22.4%, and 6.0% had CAC score of 0, 0 < to 100, and >100, respectively. We observed a significant linear trend of fractional anisotropy, but not other measures, across the CAC groups after multivariable adjustment. In the secondary analyses, CAC was associated with lower fractional anisotropy in men but not in women. CONCLUSIONS CAC may be a promising tool to predict prevalent subtle white matter injury of the brain in asymptomatic middle-aged men.
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Affiliation(s)
- Harumitsu Suzuki
- Department of Hygiene, Wakayama Medical University, Wakayama, Japan
| | - Kendra Davis-Plourde
- The Framingham Heart Study, Framingham, Massachusetts
- Department of Biostatistics, Boston University School of Public Health, Massachusetts
| | - Alexa Beiser
- The Framingham Heart Study, Framingham, Massachusetts
- Department of Biostatistics, Boston University School of Public Health, Massachusetts
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts
| | | | - Katsuyuki Miura
- Department of Public Health, Shiga University of Medical Science, Shiga, Japan
- NCD Epidemiology Research Center, Shiga, Japan
| | - Charles DeCarli
- Department of Neurology and Center for Neuroscience, University of California Davis, Davis, California
| | - Pauline Maillard
- Department of Neurology and Center for Neuroscience, University of California Davis, Davis, California
| | | | - Ramachandran S. Vasan
- The Framingham Heart Study, Framingham, Massachusetts
- Section of Cardiovascular Medicine, Boston University School of Medicine, Massachusetts
- Sections of Preventive Medicine and Epidemiology, Boston University School of Medicine, Massachusetts
- Department of Epidemiology, Boston University School of Public Health, Massachusetts
| | - Sudha Seshadri
- The Framingham Heart Study, Framingham, Massachusetts
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio
| | - Akira Fujiyoshi
- Department of Hygiene, Wakayama Medical University, Wakayama, Japan
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Raghavan S, Reid RI, Przybelski SA, Lesnick TG, Graff-Radford J, Schwarz CG, Knopman DS, Mielke MM, Machulda MM, Petersen RC, Jack CR, Vemuri P. Diffusion models reveal white matter microstructural changes with ageing, pathology and cognition. Brain Commun 2021; 3:fcab106. [PMID: 34136811 PMCID: PMC8202149 DOI: 10.1093/braincomms/fcab106] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 03/24/2021] [Accepted: 04/12/2021] [Indexed: 01/20/2023] Open
Abstract
White matter microstructure undergoes progressive changes during the lifespan, but the neurobiological underpinnings related to ageing and disease remains unclear. We used an advanced diffusion MRI, Neurite Orientation Dispersion and Density Imaging, to investigate the microstructural alterations due to demographics, common age-related pathological processes (amyloid, tau and white matter hyperintensities) and cognition. We also compared Neurite Orientation Dispersion and Density Imaging findings to the older Diffusion Tensor Imaging model-based findings. Three hundred and twenty-eight participants (264 cognitively unimpaired, 57 mild cognitive impairment and 7 dementia with a mean age of 68.3 ± 13.1 years) from the Mayo Clinic Study of Aging with multi-shell diffusion imaging, fluid attenuated inversion recovery MRI as well as amyloid and tau PET scans were included in this study. White matter tract level diffusion measures were calculated from Diffusion Tensor Imaging and Neurite Orientation Dispersion and Density Imaging. Pearson correlation and multiple linear regression analyses were performed with diffusion measures as the outcome and age, sex, education/occupation, white matter hyperintensities, amyloid and tau as predictors. Analyses were also performed with each diffusion MRI measure as a predictor of cognitive outcomes. Age and white matter hyperintensities were the strongest predictors of all white matter diffusion measures with low associations with amyloid and tau. However, neurite density decrease from Neurite Orientation Dispersion and Density Imaging was observed with amyloidosis specifically in the temporal lobes. White matter integrity (mean diffusivity and free water) in the corpus callosum showed the greatest associations with cognitive measures. All diffusion measures provided information about white matter ageing and white matter changes due to age-related pathological processes and were associated with cognition. Neurite orientation dispersion and density imaging and diffusion tensor imaging are two different diffusion models that provide distinct information about variation in white matter microstructural integrity. Neurite Orientation Dispersion and Density Imaging provides additional information about synaptic density, organization and free water content which may aid in providing mechanistic insights into disease progression.
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Affiliation(s)
| | - Robert I Reid
- Department of Information Technology, Mayo Clinic, Rochester, MN 55905, USA
| | - Scott A Przybelski
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | - Timothy G Lesnick
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | | | | | - David S Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Michelle M Mielke
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA.,Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Mary M Machulda
- Department of Psychology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
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45
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A longitudinal analysis of brain extracellular free water in HIV infected individuals. Sci Rep 2021; 11:8273. [PMID: 33859326 PMCID: PMC8050285 DOI: 10.1038/s41598-021-87801-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Accepted: 04/05/2021] [Indexed: 11/13/2022] Open
Abstract
Initiation of combination antiretroviral therapy (cART) reduces inflammation in HIV-infected (HIV+) individuals. Recent studies demonstrated that diffusion MRI based extracellular free water (FW) modeling can be sensitive to neuroinflammation. Here, we investigate the FW in HIV-infection, its temporal evolution, and its association with blood markers, and cognitive scores. Using 96 age-matched participants, we found that FW was significantly elevated in grey and white matter in cART-naïve HIV+ compared to HIV-uninfected (HIV−) individuals at baseline. These increased FW values positively correlated with neurofilament light chain (NfL) and negatively correlated with CD4 counts. FW in grey and white matter, as well as NfL decreased in the HIV+ after 12 weeks of cART treatment. No significant FW differences were noted between the HIV+ and HIV− cohorts at 1 and 2-year follow-up. Results suggest that FW elevation in cART-naïve HIV+ participants is likely due to neuroinflammation. The correlation between FW and NfL, and the improvement in both FW and NfL after 12 weeks of cART treatment further reinforces this conclusion. The longer follow-up at 1 and 2 years suggests that cART helped control neuroinflammation as inferred by FW. Therefore, FW could be used as a biomarker to monitor HIV-associated neuroinflammation.
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46
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Ueno Y, Saito A, Nakata J, Kamagata K, Taniguchi D, Motoi Y, Io H, Andica C, Shindo A, Shiina K, Miyamoto N, Yamashiro K, Urabe T, Suzuki Y, Aoki S, Hattori N. Possible Neuroprotective Effects of l-Carnitine on White-Matter Microstructural Damage and Cognitive Decline in Hemodialysis Patients. Nutrients 2021; 13:nu13041292. [PMID: 33919810 PMCID: PMC8070822 DOI: 10.3390/nu13041292] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 04/05/2021] [Accepted: 04/12/2021] [Indexed: 01/31/2023] Open
Abstract
Although l-carnitine alleviated white-matter lesions in an experimental study, the treatment effects of l-carnitine on white-matter microstructural damage and cognitive decline in hemodialysis patients are unknown. Using novel diffusion magnetic resonance imaging (dMRI) techniques, white-matter microstructural changes together with cognitive decline in hemodialysis patients and the effects of l-carnitine on such disorders were investigated. Fourteen hemodialysis patients underwent dMRI and laboratory and neuropsychological tests, which were compared across seven patients each in two groups according to duration of l-carnitine treatment: (1) no or short-term l-carnitine treatment (NSTLC), and (2) long-term l-carnitine treatment (LTLC). Ten age- and sex-matched controls were enrolled. Compared to controls, microstructural disorders of white matter were widely detected on dMRI of patients. An autopsy study of one patient in the NSTLC group showed rarefaction of myelinated fibers in white matter. With LTLC, microstructural damage on dMRI was alleviated along with lower levels of high-sensitivity C-reactive protein and substantial increases in carnitine levels. The LTLC group showed better achievement on trail making test A, which was correlated with amelioration of disorders in some white-matter tracts. Novel dMRI tractography detected abnormalities of white-matter tracts after hemodialysis. Long-term treatment with l-carnitine might alleviate white-matter microstructural damage and cognitive impairment in hemodialysis patients.
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Affiliation(s)
- Yuji Ueno
- Department of Neurology, Juntendo University Faculty of Medicine, Tokyo 113-8421, Japan; (D.T.); (Y.M.); (A.S.); (K.S.); (N.M.); (N.H.)
- Correspondence: ; Tel.: +81-3-3813-3111; Fax: +81-3-5800-0547
| | - Asami Saito
- Department of Radiology, Juntendo University Faculty of Medicine, Tokyo 113-8421, Japan; (A.S.); (K.K.); (C.A.); (S.A.)
- Department of Neurology and Stroke Medicine, Graduate School of Medicine, Yokohama City University, Yokohama 236-0004, Japan
| | - Junichiro Nakata
- Department of Nephrology, Juntendo University Faculty of Medicine, Tokyo 113-8421, Japan; (J.N.); (Y.S.)
| | - Koji Kamagata
- Department of Radiology, Juntendo University Faculty of Medicine, Tokyo 113-8421, Japan; (A.S.); (K.K.); (C.A.); (S.A.)
| | - Daisuke Taniguchi
- Department of Neurology, Juntendo University Faculty of Medicine, Tokyo 113-8421, Japan; (D.T.); (Y.M.); (A.S.); (K.S.); (N.M.); (N.H.)
| | - Yumiko Motoi
- Department of Neurology, Juntendo University Faculty of Medicine, Tokyo 113-8421, Japan; (D.T.); (Y.M.); (A.S.); (K.S.); (N.M.); (N.H.)
| | - Hiroaki Io
- Department of Nephrology, Juntendo University Nerima Hospital, Tokyo 177-8521, Japan;
| | - Christina Andica
- Department of Radiology, Juntendo University Faculty of Medicine, Tokyo 113-8421, Japan; (A.S.); (K.K.); (C.A.); (S.A.)
| | - Atsuhiko Shindo
- Department of Neurology, Juntendo University Faculty of Medicine, Tokyo 113-8421, Japan; (D.T.); (Y.M.); (A.S.); (K.S.); (N.M.); (N.H.)
| | - Kenta Shiina
- Department of Neurology, Juntendo University Faculty of Medicine, Tokyo 113-8421, Japan; (D.T.); (Y.M.); (A.S.); (K.S.); (N.M.); (N.H.)
| | - Nobukazu Miyamoto
- Department of Neurology, Juntendo University Faculty of Medicine, Tokyo 113-8421, Japan; (D.T.); (Y.M.); (A.S.); (K.S.); (N.M.); (N.H.)
| | - Kazuo Yamashiro
- Department of Neurology, Juntendo University Urayasu Hospital, Urayasu 279-0021, Japan; (K.Y.); (T.U.)
| | - Takao Urabe
- Department of Neurology, Juntendo University Urayasu Hospital, Urayasu 279-0021, Japan; (K.Y.); (T.U.)
| | - Yusuke Suzuki
- Department of Nephrology, Juntendo University Faculty of Medicine, Tokyo 113-8421, Japan; (J.N.); (Y.S.)
| | - Shigeki Aoki
- Department of Radiology, Juntendo University Faculty of Medicine, Tokyo 113-8421, Japan; (A.S.); (K.K.); (C.A.); (S.A.)
| | - Nobutaka Hattori
- Department of Neurology, Juntendo University Faculty of Medicine, Tokyo 113-8421, Japan; (D.T.); (Y.M.); (A.S.); (K.S.); (N.M.); (N.H.)
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47
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Zhang R, Yu W, Wu X, Jiaerken Y, Wang S, Hong H, Li K, Zeng Q, Luo X, Yu X, Xu X, Zhang M, Huang P. Disentangling the pathologies linking white matter hyperintensity and geriatric depressive symptoms in subjects with different degrees of vascular impairment. J Affect Disord 2021; 282:1005-1010. [PMID: 33601672 DOI: 10.1016/j.jad.2020.12.171] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2020] [Revised: 09/27/2020] [Accepted: 12/23/2020] [Indexed: 10/22/2022]
Abstract
BACKGROUND White matter hyperintensity (WMH) is closely associated with geriatric depressive symptoms, but its underlying neural mechanism is unclear. We aim to disentangle the contribution of vascular degeneration and fiber disruption to depressive symptoms in elderly subjects at different clinical status. METHODS One hundred and thirty-three normal elderly subjects, as well as 43 patients with cerebral small vessel disease (CSVD) were included. The Hamilton Depression Rating Scale (HAMD) was used to measure depressive symptoms. Based on the diffusion tensor imaging data, a free water elimination analytical model was adopted to reflect fiber tract disruption (measure: tissue fractional anisotropy, tFA) and increased white matter water content (measure: free water fraction, FW). RESULTS We found that WMH severity was significantly correlated with decreased tFA and increased FW in all subjects. In normal elderly subjects, the HAMD score was correlated with mean tFA, but not FW. Compared to the traditional fractional anisotropy measure, tFA showed stronger correlation with clinical symptoms. In CSVD subjects, the correlation was only significant for FW, and marginally significant for tFA. LIMITATIONS Most subjects had only mild to moderate depressive symptoms. Further validation in patients with major depressive disorder is needed to confirm these findings. CONCLUSIONS The neural mechanisms of depressive symptoms may be different in elderly people with or without severe vascular damage. The free water elimination model may disentangle the effects of fiber disruption and increased free water, providing sensitive imaging markers that could potentially be used on monitoring disease treatment.
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Affiliation(s)
- Ruiting Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, China
| | - Wenke Yu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, China
| | - Xiao Wu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, China
| | - Yeerfan Jiaerken
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, China
| | - Shuyue Wang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, China
| | - Hui Hong
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, China
| | - Kaicheng Li
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, China
| | - Qingze Zeng
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, China
| | - Xiao Luo
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, China
| | - Xinfeng Yu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, China
| | - Xiaopei Xu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, China
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, China.
| | - Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, China.
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48
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Huang P, Zhang R, Jiaerken Y, Wang S, Hong H, Yu W, Lian C, Li K, Zeng Q, Luo X, Yu X, Wu X, Xu X, Zhang M. White Matter Free Water is a Composite Marker of Cerebral Small Vessel Degeneration. Transl Stroke Res 2021; 13:56-64. [PMID: 33634379 DOI: 10.1007/s12975-021-00899-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2020] [Revised: 02/13/2021] [Accepted: 02/16/2021] [Indexed: 11/28/2022]
Abstract
To investigate the association between white matter free water (FW) and common imaging markers of cerebral small vessel diseases (CSVD) in two groups of subjects with different clinical status. One hundred and forty-four community subjects (mean age 60.5) and 84 CSVD subjects (mean age 61.2) were retrospectively included in the present study. All subjects received multi-modal magnetic resonance imaging and clinical assessments. The association between white matter FW and common CSVD imaging markers, including white matter hyperintensities (WMH), dilated perivascular space (PVS), lacunes, and microbleeds, were assessed using simple and multiple regression analysis. The association between FW and cognitive scores were also investigated. White matter FW was positively associated with WMH volume (β = 0.270, p = 0.001), PVS volume (β = 0.290, p < 0.001), number of microbleeds (β = 0.148, p = 0.043), and age (β = 0.170, p = 0.036) in the community cohort. In the CSVD cohort, FW was positively associated with WMH volume (β = 0.648, p < 0.001), PVS score (β = 0.224, p < 0.001), number of lacunes (β = 0.140, p = 0.046), and sex (β = 0.125, p = 0.036). The associations between FW and cognitive scores were stronger than conventional CSVD markers in both datasets. White matter FW is a potential composite marker that can sensitively detect cerebral small vessel degeneration and also reflect cognitive impairments.
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Affiliation(s)
- Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China.
| | - Ruiting Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China
| | - Yeerfan Jiaerken
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China
| | - Shuyue Wang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China
| | - Hui Hong
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China
| | - Wenke Yu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China
| | - Chunfeng Lian
- Department of Radiology and BRIC, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - Kaicheng Li
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China
| | - Qingze Zeng
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China
| | - Xiao Luo
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China
| | - Xinfeng Yu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China
| | - Xiao Wu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China
| | - Xiaopei Xu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China.
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Mitchell GF. Arterial Stiffness in Aging: Does It Have a Place in Clinical Practice?: Recent Advances in Hypertension. Hypertension 2021; 77:768-780. [PMID: 33517682 DOI: 10.1161/hypertensionaha.120.14515] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Aortic stiffness increases markedly with age and is associated with excess risk for various adverse clinical outcomes, including heart disease, dementia, and kidney disease. Although evidence for adverse effects of aortic stiffening is overwhelming, integration of direct and indirect measures of aortic stiffness into routine clinical assessment has lagged behind the science. This brief review will examine recent evidence supporting the value of stiffness as an important new risk factor for hypertension and cardiovascular disease and will offer suggestions for incorporating stiffness measures into routine clinical practice.
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Edde M, Theaud G, Rheault F, Dilharreguy B, Helmer C, Dartigues JF, Amieva H, Allard M, Descoteaux M, Catheline G. Free water: A marker of age-related modifications of the cingulum white matter and its association with cognitive decline. PLoS One 2020; 15:e0242696. [PMID: 33216815 PMCID: PMC7678997 DOI: 10.1371/journal.pone.0242696] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Accepted: 11/08/2020] [Indexed: 11/19/2022] Open
Abstract
Diffusion MRI is extensively used to investigate changes in white matter microstructure. However, diffusion measures within white matter tissue can be affected by partial volume effects due to cerebrospinal fluid and white matter hyperintensities, especially in the aging brain. In previous aging studies, the cingulum bundle that plays a central role in the architecture of the brain networks supporting cognitive functions has been associated with cognitive deficits. However, most of these studies did not consider the partial volume effects on diffusion measures. The aim of this study was to evaluate the effect of free water elimination on diffusion measures of the cingulum in a group of 68 healthy elderly individuals. We first determined the effect of free water elimination on conventional DTI measures and then examined the effect of free water elimination on verbal fluency performance over 12 years. The cingulum bundle was reconstructed with a tractography pipeline including a white matter hyperintensities mask to limit the negative impact of hyperintensities on fiber tracking algorithms. We observed that free water elimination increased the ability of conventional DTI measures to detect associations between tissue diffusion measures of the cingulum and changes in verbal fluency in older individuals. Moreover, free water content and mean diffusivity measured along the cingulum were independently associated with changes in verbal fluency. This suggests that both tissue modifications and an increase in interstitial isotropic water would contribute to cognitive decline. These observations reinforce the importance of using free water elimination when studying brain aging and indicate that free water itself could be a relevant marker for age-related cingulum white matter modifications and cognitive decline.
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Affiliation(s)
- Manon Edde
- EPHE, PSL, Bordeaux, France
- CNRS, INCIA, UMR 5287, Bordeaux, France
| | - Guillaume Theaud
- Sherbrooke Connectivity Imaging Lab, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - François Rheault
- Sherbrooke Connectivity Imaging Lab, Université de Sherbrooke, Sherbrooke, QC, Canada
| | | | - Catherine Helmer
- Université de Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR 1219, Bordeaux, France
| | - Jean-François Dartigues
- Université de Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR 1219, Bordeaux, France
- CHU de Bordeaux, Bordeaux, France
| | - Hélène Amieva
- Université de Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR 1219, Bordeaux, France
| | - Michèle Allard
- EPHE, PSL, Bordeaux, France
- CNRS, INCIA, UMR 5287, Bordeaux, France
- CHU de Bordeaux, Bordeaux, France
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Lab, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Gwénaëlle Catheline
- EPHE, PSL, Bordeaux, France
- CNRS, INCIA, UMR 5287, Bordeaux, France
- Université de Bordeaux, INCIA, UMR 5287, Bordeaux, France
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