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Markus HS, Egle M, Croall ID, Sari H, Khan U, Hassan A, Harkness K, MacKinnon A, O'Brien JT, Morris RG, Barrick TR, Blamire AM, Tozer DJ, Ford GA. PRESERVE: Randomized Trial of Intensive Versus Standard Blood Pressure Control in Small Vessel Disease. Stroke 2021; 52:2484-2493. [PMID: 34044580 DOI: 10.1161/strokeaha.120.032054] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
[Figure: see text].
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Affiliation(s)
- Hugh S Markus
- Stroke Research Group, Department of Clinical Neuroscience, University of Cambridge (H.S.M., M.E., I.D.C., H.S., D.J.T.)
| | - Marco Egle
- Stroke Research Group, Department of Clinical Neuroscience, University of Cambridge (H.S.M., M.E., I.D.C., H.S., D.J.T.)
| | - Iain D Croall
- Stroke Research Group, Department of Clinical Neuroscience, University of Cambridge (H.S.M., M.E., I.D.C., H.S., D.J.T.)
| | - Hasan Sari
- Stroke Research Group, Department of Clinical Neuroscience, University of Cambridge (H.S.M., M.E., I.D.C., H.S., D.J.T.)
| | - Usman Khan
- Atkinson Morley Neuroscience Centre, St. Georges NHS Healthcare Trust (U.K., A.M.)
| | | | | | - Andrew MacKinnon
- Atkinson Morley Neuroscience Centre, St. Georges NHS Healthcare Trust (U.K., A.M.)
| | - John T O'Brien
- Department of Psychiatry, University of Cambridge (J.T.O.)
| | - Robin G Morris
- Kings College Institute of Psychiatry, Psychology and Neurosciences, London, United Kingdom (R.G.M.)
| | - Thomas R Barrick
- Neurosciences Research Centre, Molecular and Clinical Science Research Institute, St George's University of London, United Kingdom (T.R.B.)
| | - Andrew M Blamire
- Magnetic Resonance Centre, Institute of Cellular Medicine, Newcastle University, United Kingdom (A.M.B.)
| | - Daniel J Tozer
- Stroke Research Group, Department of Clinical Neuroscience, University of Cambridge (H.S.M., M.E., I.D.C., H.S., D.J.T.)
| | - Gary A Ford
- Oxford University Hospitals NHS Foundation Trust, University of Oxford (G.A.F.)
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52
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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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53
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Ulivi L, Cosottini M, Migaleddu G, Orlandi G, Giannini N, Siciliano G, Mancuso M. Brain MRI in Monogenic Cerebral Small Vessel Diseases: A Practical Handbook. Curr Mol Med 2021; 22:300-311. [DOI: 10.2174/1566524021666210510164003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Revised: 01/28/2021] [Accepted: 02/09/2021] [Indexed: 11/22/2022]
Abstract
:
Monogenic cerebral small vessel diseases are a topic of growing interest, as several genes responsible have been recently described and new sequencing techniques such as Next generation sequencing are available. Brain imaging is a key exam in these diseases. First, since it is often the first exam performed, an MRI is key in selecting patients for genetic testing and for interpreting Next generation sequencing reports. In addition, neuroimaging can be helpful in describing the underlying pathological mechanisms involved in cerebral small vessel disease. With this review, we aim to provide Neurologists and Stroke physicians with an up-to date overview of the current neuroimaging knowledge on monogenic small vessel diseases.
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Affiliation(s)
- Leonardo Ulivi
- Department of Experimental and Clinical Medicine, Neurological Clinic, Pisa University, Via Roma 67, Pisa, Italy
| | - Mirco Cosottini
- Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
| | - Gianmichele Migaleddu
- Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
| | - Giovanni Orlandi
- Department of Experimental and Clinical Medicine, Neurological Clinic, Pisa University, Via Roma 67, Pisa, Italy
| | - Nicola Giannini
- Department of Experimental and Clinical Medicine, Neurological Clinic, Pisa University, Via Roma 67, Pisa, Italy
| | - Gabriele Siciliano
- Department of Experimental and Clinical Medicine, Neurological Clinic, Pisa University, Via Roma 67, Pisa, Italy
| | - Michelangelo Mancuso
- Department of Experimental and Clinical Medicine, Neurological Clinic, Pisa University, Via Roma 67, Pisa, Italy
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54
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van den Brink H, Kopczak A, Arts T, Onkenhout L, Siero JC, Zwanenburg JJ, Duering M, Blair GW, Doubal FN, Stringer MS, Thrippleton MJ, Kuijf HJ, de Luca A, Hendrikse J, Wardlaw JM, Dichgans M, Biessels GJ. Zooming in on cerebral small vessel function in small vessel diseases with 7T MRI: Rationale and design of the "ZOOM@SVDs" study. CEREBRAL CIRCULATION - COGNITION AND BEHAVIOR 2021; 2:100013. [PMID: 36324717 PMCID: PMC9616370 DOI: 10.1016/j.cccb.2021.100013] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Revised: 04/14/2021] [Accepted: 04/15/2021] [Indexed: 06/01/2023]
Abstract
Background Cerebral small vessel diseases (SVDs) are a major cause of stroke and dementia. Yet, specific treatment strategies are lacking in part because of a limited understanding of the underlying disease processes. There is therefore an urgent need to study SVDs at their core, the small vessels themselves. Objective This paper presents the rationale and design of the ZOOM@SVDs study, which aims to establish measures of cerebral small vessel dysfunction on 7T MRI as novel disease markers of SVDs. Methods ZOOM@SVDs is a prospective observational cohort study with two years follow-up. ZOOM@SVDs recruits participants with Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL, N = 20), sporadic SVDs (N = 60), and healthy controls (N = 40). Participants undergo 7T brain MRI to assess different aspects of small vessel function including small vessel reactivity, cerebral perforating artery flow, and pulsatility. Extensive work-up at baseline and follow-up further includes clinical and neuropsychological assessment as well as 3T brain MRI to assess conventional SVD imaging markers. Measures of small vessel dysfunction are compared between patients and controls, and related to the severity of clinical and conventional MRI manifestations of SVDs. Discussion ZOOM@SVDs will deliver novel markers of cerebral small vessel function in patients with monogenic and sporadic forms of SVDs, and establish their relation with disease burden and progression. These small vessel markers can support etiological studies in SVDs and may serve as surrogate outcome measures in future clinical trials to show target engagement of drugs directed at the small vessels.
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Key Words
- ASL, Arterial Spin Labeling
- BOLD, Blood Oxygenation Level-Dependent
- CADASIL
- CADASIL, Cerebral Autosomal Dominant Arteriopathy with Leukoencephalopathy and Subcortical Infarcts
- CDR, Clinical Dementia Rating scale
- CERAD+, Consortium to Establish a Disease Registry for Alzheimer's Disease Plus battery
- CES-D, Center for Epidemiologic Studies Depression Scale
- CO2, Carbon Dioxide
- CSF, Cerebrospinal Fluid
- Cerebral small vessel disease
- DTI, Diffusion Tensor Imaging
- EPIC, European Prospective Investigation into Cancer and Nutrition
- EtCO2, End-tidal Carbon Dioxide
- FLAIR, Fluid Attenuated Inversion Recovery
- FOV, Field Of View
- FWHM, Full-Width-at-Half-Maximum
- GE, Gradient Echo
- GM, Grey Matter
- GPRS, General Packet Radio Service
- HRF, Hemodynamic Response Function
- High field strength MRI
- LMU, Ludwig-Maximilians-Universität
- MMSE, Mini-Mental State Examination
- NAWM, Normal Appearing White Matter
- NIHSS, National Institute for Health Stroke Scale
- PI, Pulsatility Index
- ROI, Region Of Interest
- SPPB, Short Physical Performance Battery
- SVDs, Small Vessel Diseases
- SWI, Susceptibility Weighted Imaging
- Small vessel function
- Sporadic SVD
- Stroke
- TE, Echo Time
- TI, Inversion Time
- TR, Repetition Time
- TSE, Turbo Spin Echo
- UMCU, University Medical Center Utrecht
- Vmax, Maximum velocity
- Vmean, Mean velocity
- Vmin, Minimum velocity
- WM, White Matter
- WMH, White Matter Hyperintensity
- fMRI, Functional Magnetic Resonance Imaging
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Affiliation(s)
- Hilde van den Brink
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3508 GA, the Netherlands
| | - Anna Kopczak
- Institute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilians-Universität, Munich, Germany
| | - Tine Arts
- Department of Radiology, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Laurien Onkenhout
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3508 GA, the Netherlands
| | - Jeroen C.W. Siero
- Department of Radiology, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
- Spinoza Centre for Neuroimaging Amsterdam, Amsterdam, the Netherlands
| | - Jaco J.M. Zwanenburg
- Department of Radiology, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Marco Duering
- Institute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilians-Universität, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
- German Center for Neurodegenerative Disease (DZNE), Munich, Germany
| | - Gordon W. Blair
- Brain Research Imaging Centre, Centre for Clinical Brain Sciences, UK Dementia Research Institute Centre at the University of Edinburgh, Edinburgh, United Kingdom
| | - Fergus N. Doubal
- Brain Research Imaging Centre, Centre for Clinical Brain Sciences, UK Dementia Research Institute Centre at the University of Edinburgh, Edinburgh, United Kingdom
| | - Michael S. Stringer
- Brain Research Imaging Centre, Centre for Clinical Brain Sciences, UK Dementia Research Institute Centre at the University of Edinburgh, Edinburgh, United Kingdom
| | - Michael J. Thrippleton
- Brain Research Imaging Centre, Centre for Clinical Brain Sciences, UK Dementia Research Institute Centre at the University of Edinburgh, Edinburgh, United Kingdom
| | - Hugo J. Kuijf
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Alberto de Luca
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3508 GA, the Netherlands
- Brain Research Imaging Centre, Centre for Clinical Brain Sciences, UK Dementia Research Institute Centre at the University of Edinburgh, Edinburgh, United Kingdom
| | - Jeroen Hendrikse
- Department of Radiology, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Joanna M. Wardlaw
- Brain Research Imaging Centre, Centre for Clinical Brain Sciences, UK Dementia Research Institute Centre at the University of Edinburgh, Edinburgh, United Kingdom
| | - Martin Dichgans
- Institute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilians-Universität, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
- German Center for Neurodegenerative Disease (DZNE), Munich, Germany
| | - Geert Jan Biessels
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3508 GA, the Netherlands
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55
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Redmond KJ, Milano MT, Kim MM, Trifiletti DM, Soltys SG, Hattangadi-Gluth JA. Reducing Radiation-Induced Cognitive Toxicity: Sparing the Hippocampus and Beyond. Int J Radiat Oncol Biol Phys 2021; 109:1131-1136. [PMID: 33714520 DOI: 10.1016/j.ijrobp.2021.01.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Accepted: 01/03/2021] [Indexed: 12/25/2022]
Affiliation(s)
- Kristin J Redmond
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland.
| | - Michael T Milano
- Department of Radiation Oncology, University of Rochester, Rochester, New York
| | - Michelle M Kim
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Daniel M Trifiletti
- Department of Radiation Oncology, Mayo Clinic Florida, Jacksonville, Florida
| | - Scott G Soltys
- Department of Radiation Oncology, Stanford University, Stanford, California
| | - Jona A Hattangadi-Gluth
- Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California
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56
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Feng M, Zhang Y, Liu Y, Wu Z, Song Z, Ma M, Wang Y, Dai H. White Matter Structural Network Analysis to Differentiate Alzheimer's Disease and Subcortical Ischemic Vascular Dementia. Front Aging Neurosci 2021; 13:650377. [PMID: 33867969 PMCID: PMC8044349 DOI: 10.3389/fnagi.2021.650377] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Accepted: 02/25/2021] [Indexed: 12/16/2022] Open
Abstract
To explore the evaluation of white matter structural network analysis in the differentiation of Alzheimer’s disease (AD) and subcortical ischemic vascular dementia (SIVD), 67 participants [31 AD patients, 19 SIVD patients, and 19 normal control (NC)] were enrolled in this study. Each participant underwent 3.0T MRI scanning. Diffusion tensor imaging (DTI) data were analyzed by graph theory (GRETNA toolbox). Statistical analyses of global parameters [gamma, sigma, lambda, global shortest path length (Lp), global efficiency (Eg), and local efficiency (Eloc)] and nodal parameters [betweenness centrality (BC)] were obtained. Network-based statistical analysis (NBS) was employed to analyze the group differences of structural connections. The diagnosis efficiency of nodal BC in identifying different types of dementia was assessed by receiver operating characteristic (ROC) analysis. There were no significant differences of gender and years of education among the groups. There were no significant differences of sigma and gamma in AD vs. NC and SIVD vs. NC, whereas the Eg values of AD and SIVD were statistically decreased, and the lambda values were increased. The BC of the frontal cortex, left superior parietal gyrus, and left precuneus in AD patients were obviously reduced, while the BC of the prefrontal and subcortical regions were decreased in SIVD patients, compared with NC. SIVD patients had decreased structural connections in the frontal, prefrontal, and subcortical regions, while AD patients had decreased structural connections in the temporal and occipital regions and increased structural connections in the frontal and prefrontal regions. The highest area under curve (AUC) of BC was 0.946 in the right putamen for AD vs. SIVD. White matter structural network analysis may be a potential and promising method, and the topological changes of the network, especially the BC change in the right putamen, were valuable in differentiating AD and SIVD patients.
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Affiliation(s)
- Mengmeng Feng
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou City, China
| | - Yue Zhang
- Department of Geratology, The First Affiliated Hospital of Soochow University, Suzhou City, China
| | - Yuanqing Liu
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou City, China
| | - Zhiwei Wu
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou City, China
| | - Ziyang Song
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou City, China
| | - Mengya Ma
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou City, China
| | - Yueju Wang
- Department of Geratology, The First Affiliated Hospital of Soochow University, Suzhou City, China
| | - Hui Dai
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou City, China.,Institute of Medical Imaging, Soochow University, Suzhou City, China
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57
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Ulivi L, Kanber B, Prados F, Davagnanam I, Merwick A, Chan E, Williams F, Hughes D, Murphy E, Lachmann RH, Wheeler-Kingshott CAMG, Cipolotti L, Werring DJ. White matter integrity correlates with cognition and disease severity in Fabry disease. Brain 2021; 143:3331-3342. [PMID: 33141169 DOI: 10.1093/brain/awaa282] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2019] [Revised: 06/21/2020] [Accepted: 07/12/2020] [Indexed: 01/13/2023] Open
Abstract
Cerebral white matter pathology is a common CNS manifestation of Fabry disease, visualized as white matter hyperintensities on MRI in 42-81% of patients. Diffusion tensor imaging (DTI) MRI is a sensitive technique to quantify microstructural damage within the white matter with potential value as a disease biomarker. We evaluated the pattern of DTI abnormalities in Fabry disease, and their correlations with cognitive impairment, mood, anxiety, disease severity and plasma lyso-Gb3 levels in 31 patients with genetically proven Fabry disease and 19 age-matched healthy control subjects. We obtained average values of fractional anisotropy and mean diffusivity within the white matter and performed voxelwise analysis with tract-based spatial statistics. Using a standardized neuropsychological test battery, we assessed processing speed, executive function, anxiety, depression and disease severity. The mean age (% male) was 44.1 (45%) for patients with Fabry disease and 37.4 (53%) for the healthy control group. In patients with Fabry disease, compared to healthy controls the mean average white matter fractional anisotropy was lower in [0.423 (standard deviation, SD 0.023) versus 0.446 (SD 0.016), P = 0.002] while mean average white matter mean diffusivity was higher (749 × 10-6 mm2/s (SD 32 × 10-6) versus 720 × 10-6 mm2/s (SD 21 × 10-6), P = 0.004]. Voxelwise statistics showed that the diffusion abnormalities for both fractional anisotropy and mean diffusivity were anatomically widespread. A lesion probability map showed that white matter hyperintensities also had a wide anatomical distribution with a predilection for the posterior centrum semiovale. However, diffusion abnormalities in Fabry disease were not restricted to lesional tissue; compared to healthy controls, the normal appearing white matter in patients with Fabry disease had reduced fractional anisotropy [0.422 (SD 0.022) versus 0.443 (SD 0.017) P = 0.003] and increased mean diffusivity [747 × 10-6 mm2/s (SD 26 × 10-6) versus 723 × 10-6 mm2/s (SD 22 × 10-6), P = 0.008]. Within patients, average white matter fractional anisotropy and white matter lesion volume showed statistically significant correlations with Digit Symbol Coding Test score (r = 0.558, P = 0.001; and r = -0.633, P ≤ 0.001, respectively). Average white matter fractional anisotropy correlated with the overall Mainz Severity Score Index (r = -0.661, P ≤ 0.001), while average white matter mean diffusivity showed a strong correlation with plasma lyso-Gb3 levels (r = 0.559, P = 0.001). Our findings using DTI confirm widespread areas of microstructural white matter disruption in Fabry disease, extending beyond white matter hyperintensities seen on conventional MRI. Moreover, diffusion measures show strong correlations with cognition (processing speed), clinical disease severity and a putative plasma biomarker of disease activity, making them promising quantitative biomarkers for monitoring Fabry disease severity and progression.
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Affiliation(s)
- Leonardo Ulivi
- Stroke Research Centre, Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London WC1B 5EH, UK.,Department of Experimental and Clinical Medicine, Neurological Clinic, Pisa University, Pisa, Italy
| | - Baris Kanber
- Department of Neuroinflammation, UCL Queen Square Institute of Neurology, London WC1B 5EH, UK.,Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, WC1V 6LJ, UK
| | - Ferran Prados
- Department of Neuroinflammation, UCL Queen Square Institute of Neurology, London WC1B 5EH, UK.,Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, WC1V 6LJ, UK.,e-Health Centre, Universitat Oberta de Catalunya, Barcelona, Spain
| | - Indran Davagnanam
- Stroke Research Centre, Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London WC1B 5EH, UK.,Academic Department of Neuroradiology, Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, Queen Square, London WC1N 3BG, UK
| | - Aine Merwick
- Stroke Research Centre, Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London WC1B 5EH, UK.,Cork University Hospital, University College Cork, Wilton, Cork, Ireland
| | - Edgar Chan
- Department of Neuropsychology, National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK
| | - Fay Williams
- Department of Neuropsychology, National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK.,Charles Dent Metabolic Unit, National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK
| | - Derralynn Hughes
- Lysosomal Storage Disorders Unit, Royal Free Hospital, London NW3 2PF, UK
| | - Elaine Murphy
- Charles Dent Metabolic Unit, National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK
| | - R H Lachmann
- Charles Dent Metabolic Unit, National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK
| | - Claudia A M Gandini Wheeler-Kingshott
- Department of Neuroinflammation, UCL Queen Square Institute of Neurology, London WC1B 5EH, UK.,Brain MRI 3T Research Centre, IRCCS Mondino Foundation, Pavia, Italy.,Department of Brain and Behavioural Sciences, University of Pavia, Italy
| | - Lisa Cipolotti
- Department of Neuropsychology, National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK
| | - David J Werring
- Stroke Research Centre, Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London WC1B 5EH, UK
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58
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Che Mohd Nassir CMN, Mohamad Ghazali M, Ahmad Safri A, Jaffer U, Abdullah WZ, Idris NS, Muzaimi M. Elevated Circulating Microparticle Subpopulations in Incidental Cerebral White Matter Hyperintensities: A Multimodal Study. Brain Sci 2021; 11:133. [PMID: 33498429 PMCID: PMC7909442 DOI: 10.3390/brainsci11020133] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Revised: 01/13/2021] [Accepted: 01/19/2021] [Indexed: 01/02/2023] Open
Abstract
Asymptomatic (or "silent") manifestations of cerebral small vessel disease (CSVD) are widely recognized through incidental findings of white matter hyperintensities (WMHs) as a result of magnetic resonance imaging (MRI). This study aims to examine the potential associations of surrogate markers for the evaluation of white matter integrity in CSVD among asymptomatic individuals through a battery of profiling involving QRISK2 cardiocerebrovascular risk prediction, neuroimaging, neurocognitive evaluation, and microparticles (MPs) titers. Sixty asymptomatic subjects (mean age: 39.83 ± 11.50 years) with low to moderate QRISK2 scores were recruited and underwent neurocognitive evaluation for memory and cognitive performance, peripheral venous blood collection for enumeration of selected MPs subpopulations, and 3T MRI brain scan with specific diffusion MRI (dMRI) sequences inclusive of diffusion tensor imaging (DTI). WMHs were detected in 20 subjects (33%). Older subjects (mean age: 46.00 ± 12.00 years) had higher WMHs prevalence, associated with higher QRISK2 score and reduced processing speed. They also had significantly higher mean percentage of platelet (CD62P)- and leukocyte (CD62L)-derived MPs. No association was found between reduced white matter integrity-especially at the left superior longitudinal fasciculus (LSLF)-with age and neurocognitive function; however, LSLF was associated with higher QRISK2 score, total MPs, and CD62L- and endothelial cell-derived MPs (CD146). Therefore, this study establishes these multimodal associations as potential surrogate markers for "silent" CSVD manifestations in the well-characterized cardiocerebrovascular demographic of relatively young, neurologically asymptomatic adults. Furthermore, to the best of our knowledge, this study is the first to exhibit elevated MP counts in asymptomatic CSVD (i.e., CD62P and CD62L), which warrants further delineation.
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Affiliation(s)
- Che Mohd Nasril Che Mohd Nassir
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian 16150, Kelantan, Malaysia; (C.M.N.C.M.N.); (M.M.G.); (A.A.S.); (U.J.)
| | - Mazira Mohamad Ghazali
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian 16150, Kelantan, Malaysia; (C.M.N.C.M.N.); (M.M.G.); (A.A.S.); (U.J.)
| | - Amanina Ahmad Safri
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian 16150, Kelantan, Malaysia; (C.M.N.C.M.N.); (M.M.G.); (A.A.S.); (U.J.)
| | - Usman Jaffer
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian 16150, Kelantan, Malaysia; (C.M.N.C.M.N.); (M.M.G.); (A.A.S.); (U.J.)
| | - Wan Zaidah Abdullah
- Department of Haematology, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian 16150, Kelantan, Malaysia;
- Hospital Universiti Sains Malaysia, Jalan Raja Perempuan Zainab II, Kubang Kerian 16150, Kelantan, Malaysia;
| | - Nur Suhaila Idris
- Hospital Universiti Sains Malaysia, Jalan Raja Perempuan Zainab II, Kubang Kerian 16150, Kelantan, Malaysia;
- Department of Family Medicine, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian 16150, Kelantan, Malaysia
| | - Mustapha Muzaimi
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian 16150, Kelantan, Malaysia; (C.M.N.C.M.N.); (M.M.G.); (A.A.S.); (U.J.)
- Hospital Universiti Sains Malaysia, Jalan Raja Perempuan Zainab II, Kubang Kerian 16150, Kelantan, Malaysia;
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59
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Huang L, Chen X, Sun W, Chen H, Ye Q, Yang D, Li M, Luo C, Ma J, Shao P, Xu H, Zhang B, Zhu X, Xu Y. Early Segmental White Matter Fascicle Microstructural Damage Predicts the Corresponding Cognitive Domain Impairment in Cerebral Small Vessel Disease Patients by Automated Fiber Quantification. Front Aging Neurosci 2021; 12:598242. [PMID: 33505302 PMCID: PMC7829360 DOI: 10.3389/fnagi.2020.598242] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Accepted: 12/07/2020] [Indexed: 11/13/2022] Open
Abstract
Objective: To characterize earlier damage pattern of white matter (WM) microstructure in cerebral small vessel disease (CSVD) and its relationship with cognitive domain dysfunction. Methods: A total of 144 CSVD patients and 100 healthy controls who underwent neuropsychological measurements and diffusion tensor imaging (DTI) examination were recruited. Cognitive function, emotion, and gait were assessed in each participant. The automated fiber quantification (AFQ) technique was used to extract different fiber properties between groups, and partial correlation and general linear regression analyses were performed to assess the relationship between position-specific WM microstructure and cognitive function. Results: Specific segments in the association fibers, commissural WM regions of interest (ROIs), and projection fibers were damaged in the CSVD group [P < 0.05, family-wise error (FWE) correction], and these damaged segments showed interhemispheric symmetry. In addition, the damage to specific tract profiles [including the posteromedial component of the right cingulum cingulate (CC), the occipital lobe portion of the callosum forceps major, the posterior portion of the left superior longitudinal fasciculus (SLF), and the bilateral anterior thalamic radiation (ATR)] was related to the dysfunction in specific cognitive domains. Among these tracts, we found the ATR to be the key set of tracts whose profiles were most associated with cognitive dysfunction. The left ATR was a specific fiber bundle associated with episode memory and language function, whereas the fractional anisotropy (FA) values of the intermediate component of the right ATR were negatively correlated with executive function and gait evaluation. It should be noted that the abovementioned relationships could not survive the Bonferroni correction (p < 0.05/27), so we chose more liberal uncorrected statistical thresholds. Conclusions: Damage to the WM fiber bundles showed extensive interhemispheric symmetry and was limited to particular segments in CSVD patients. Disruption of strategically located fibers was associated with different cognitive deficits, especially the bilateral ATR.
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Affiliation(s)
- Lili Huang
- Department of Neurology, Drum Tower Hospital, Medical School and the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neurological Medical Center, Nanjing, China
| | - Xin Chen
- Department of Neurology, Drum Tower Hospital, Medical School and the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neurological Medical Center, Nanjing, China
| | - Wenshan Sun
- Department of Neurology, Drum Tower Hospital, Medical School and the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neurological Medical Center, Nanjing, China
| | - Haifeng Chen
- Department of Neurology, Drum Tower Hospital, Medical School and the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neurological Medical Center, Nanjing, China
| | - Qing Ye
- Department of Neurology, Drum Tower Hospital, Medical School and the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neurological Medical Center, Nanjing, China
| | - Dan Yang
- Department of Neurology, Drum Tower Hospital, Medical School and the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neurological Medical Center, Nanjing, China
| | - Mengchun Li
- Department of Neurology, Drum Tower Hospital, Medical School and the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neurological Medical Center, Nanjing, China
| | - Caimei Luo
- Department of Neurology, Drum Tower Hospital, Medical School and the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neurological Medical Center, Nanjing, China
| | - Junyi Ma
- Department of Neurology, Drum Tower Hospital, Medical School and the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neurological Medical Center, Nanjing, China
| | - Pengfei Shao
- Department of Neurology, Drum Tower Hospital, Medical School and the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neurological Medical Center, Nanjing, China
| | - Hengheng Xu
- Department of Neurology, Drum Tower Hospital, Medical School and the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neurological Medical Center, Nanjing, China
| | - Bing Zhang
- Department of Radiology, Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
| | - Xiaolei Zhu
- Department of Neurology, Drum Tower Hospital, Medical School and the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neurological Medical Center, Nanjing, China
| | - Yun Xu
- Department of Neurology, Drum Tower Hospital, Medical School and the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neurological Medical Center, Nanjing, China
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60
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Valdés Hernández MDC, Smith K, Bastin ME, Nicole Amft E, Ralston SH, Wardlaw JM, Wiseman SJ. Brain network reorganisation and spatial lesion distribution in systemic lupus erythematosus. Lupus 2020; 30:285-298. [PMID: 33307988 PMCID: PMC7854491 DOI: 10.1177/0961203320979045] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Objective This work investigates network organisation of brain structural connectivity
in systemic lupus erythematosus (SLE) relative to healthy controls and its
putative association with lesion distribution and disease indicators. Methods White matter hyperintensity (WMH) segmentation and connectomics were
performed in 47 patients with SLE and 47 healthy age-matched controls from
structural and diffusion MRI data. Network nodes were divided into
hierarchical tiers based on numbers of connections. Results were compared
between patients and controls to assess for differences in brain network
organisation. Voxel-based analyses of the spatial distribution of WMH in
relation to network measures and SLE disease indicators were conducted. Results Despite inter-individual differences in brain network organization observed
across the study sample, the connectome networks of SLE patients had larger
proportion of connections in the peripheral nodes. SLE patients had
statistically larger numbers of links in their networks with generally
larger fractional anisotropy weights (i.e. a measure of white matter
integrity) and less tendency to aggregate than those of healthy controls.
The voxels exhibiting connectomic differences were coincident with WMH
clusters, particularly the left hemisphere’s intersection between the
anterior limb of the internal and external capsules. Moreover, these voxels
also associated more strongly with disease indicators. Conclusion Our results indicate network differences reflective of compensatory
reorganization of the neural circuits, reflecting adaptive or extended
neuroplasticity in SLE.
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Affiliation(s)
- Maria Del C Valdés Hernández
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.,UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Keith Smith
- Usher Institute for Population Health Science and Informatics, University of Edinburgh, Edinburgh, UK.,Health Data Research UK, London, UK
| | - Mark E Bastin
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - E Nicole Amft
- University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | - Stuart H Ralston
- Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, UK
| | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.,UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Stewart J Wiseman
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.,UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
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61
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Sargurupremraj M, Suzuki H, Jian X, Sarnowski C, Evans TE, Bis JC, Eiriksdottir G, Sakaue S, Terzikhan N, Habes M, Zhao W, Armstrong NJ, Hofer E, Yanek LR, Hagenaars SP, Kumar RB, van den Akker EB, McWhirter RE, Trompet S, Mishra A, Saba Y, Satizabal CL, Beaudet G, Petit L, Tsuchida A, Zago L, Schilling S, Sigurdsson S, Gottesman RF, Lewis CE, Aggarwal NT, Lopez OL, Smith JA, Valdés Hernández MC, van der Grond J, Wright MJ, Knol MJ, Dörr M, Thomson RJ, Bordes C, Le Grand Q, Duperron MG, Smith AV, Knopman DS, Schreiner PJ, Evans DA, Rotter JI, Beiser AS, Maniega SM, Beekman M, Trollor J, Stott DJ, Vernooij MW, Wittfeld K, Niessen WJ, Soumaré A, Boerwinkle E, Sidney S, Turner ST, Davies G, Thalamuthu A, Völker U, van Buchem MA, Bryan RN, Dupuis J, Bastin ME, Ames D, Teumer A, Amouyel P, Kwok JB, Bülow R, Deary IJ, Schofield PR, Brodaty H, Jiang J, Tabara Y, Setoh K, Miyamoto S, Yoshida K, Nagata M, Kamatani Y, Matsuda F, Psaty BM, Bennett DA, De Jager PL, Mosley TH, Sachdev PS, Schmidt R, Warren HR, Evangelou E, Trégouët DA, Ikram MA, Wen W, DeCarli C, Srikanth VK, Jukema JW, Slagboom EP, Kardia SLR, Okada Y, Mazoyer B, Wardlaw JM, Nyquist PA, Mather KA, Grabe HJ, Schmidt H, Van Duijn CM, Gudnason V, Longstreth WT, Launer LJ, Lathrop M, Seshadri S, Tzourio C, Adams HH, Matthews PM, Fornage M, Debette S. Cerebral small vessel disease genomics and its implications across the lifespan. Nat Commun 2020; 11:6285. [PMID: 33293549 PMCID: PMC7722866 DOI: 10.1038/s41467-020-19111-2] [Citation(s) in RCA: 83] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2020] [Accepted: 09/10/2020] [Indexed: 12/14/2022] Open
Abstract
White matter hyperintensities (WMH) are the most common brain-imaging feature of cerebral small vessel disease (SVD), hypertension being the main known risk factor. Here, we identify 27 genome-wide loci for WMH-volume in a cohort of 50,970 older individuals, accounting for modification/confounding by hypertension. Aggregated WMH risk variants were associated with altered white matter integrity (p = 2.5×10-7) in brain images from 1,738 young healthy adults, providing insight into the lifetime impact of SVD genetic risk. Mendelian randomization suggested causal association of increasing WMH-volume with stroke, Alzheimer-type dementia, and of increasing blood pressure (BP) with larger WMH-volume, notably also in persons without clinical hypertension. Transcriptome-wide colocalization analyses showed association of WMH-volume with expression of 39 genes, of which four encode known drug targets. Finally, we provide insight into BP-independent biological pathways underlying SVD and suggest potential for genetic stratification of high-risk individuals and for genetically-informed prioritization of drug targets for prevention trials.
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Affiliation(s)
- Muralidharan Sargurupremraj
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France
| | - Hideaki Suzuki
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo, Aoba, Sendai, 980-8573, Japan
- Department of Cardiovascular Medicine, Tohoku University Hospital, 1-1, Seiryo, Aoba, Sendai, 980-8574, Japan
- Department of Brain Sciences, Imperial College London, London, W12 0NN, UK
| | - Xueqiu Jian
- University of Texas Health Science Center at Houston McGovern Medical School, Houston, TX, 77030, USA
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, 78229, USA
| | - Chloé Sarnowski
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Tavia E Evans
- Department of Clinical Genetics, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
- Department of Radiology & Nuclear Medicine, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, 98101, USA
| | | | - Saori Sakaue
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, 565-0871, Japan
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Tsurumi-ku, Yokohama City, Kanagawa, 230-0045, Japan
- Department of Allergy and Rheumatology, Graduate School of Medicine, the University of Tokyo, Tokyo, 113-0033, Japan
| | - Natalie Terzikhan
- Department of Epidemiology, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
| | - Mohamad Habes
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, 78229, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Institute for Community Medicine, University Medicine Greifswald, 17475, Greifswald, Germany
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109-2029, USA
| | - Nicola J Armstrong
- Mathematics and Statistics, Murdoch University, Murdoch, WA, 6150, Australia
| | - Edith Hofer
- Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, 8036, Graz, Austria
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, 8036, Graz, Austria
| | - Lisa R Yanek
- GeneSTAR Research Program, Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Saskia P Hagenaars
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Social Genetic and Developmental Psychiatry Research Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
| | - Rajan B Kumar
- Department of Public Health Sciences, University of California at Davis, Davis, CA, 95616, USA
| | - Erik B van den Akker
- Section of Molecular Epidemiology, Biomedical Sciences, Leiden university Medical Center, 2333 ZA, Leiden, The Netherlands
- Pattern Recognition & Bioinformatics, Delft University of Technology, Delft, NL, 2629 HS, USA
- Leiden Computational Biology Centre, Leiden University Medical Centre, 2333 ZA, Leiden, The Netherlands
| | - Rebekah E McWhirter
- Centre for Law and Genetics, Faculty of Law, University of Tasmania, Hobart, TAS, 7005, Australia
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, 7000, Australia
| | - Stella Trompet
- Department of Internal Medicine, section of gerontology and geriatrics, Leiden University Medical Center, 2333 ZA, Leiden, The Netherlands
- Department of Cardiology, Leiden University Medical Center, 2333 ZA, Leiden, The Netherlands
| | - Aniket Mishra
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France
| | - Yasaman Saba
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France
- Gottfried Schatz Research Center, Department of Molecular Biology and Biochemistry, Medical University of Graz, 8010, Graz, Austria
| | - Claudia L Satizabal
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, 78229, USA
- Boston University and the NHLBI's Framingham Heart Study, Boston, MA, 02215, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, 02118, USA
| | - Gregory Beaudet
- University of Bordeaux, IMN, UMR 5293, 33000, Bordeaux, France
| | - Laurent Petit
- University of Bordeaux, IMN, UMR 5293, 33000, Bordeaux, France
| | - Ami Tsuchida
- University of Bordeaux, IMN, UMR 5293, 33000, Bordeaux, France
| | - Laure Zago
- University of Bordeaux, IMN, UMR 5293, 33000, Bordeaux, France
| | - Sabrina Schilling
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France
| | | | | | - Cora E Lewis
- University of Alabama at Birmingham School of Medicine, Birmingham, AL, 35233, USA
| | - Neelum T Aggarwal
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, 60612, USA
| | - Oscar L Lopez
- Departments of Neurology and Psychiatry, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109-2029, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, 48104, USA
| | - Maria C Valdés Hernández
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB, UK
- Row Fogo Centre for Ageing and The Brain, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Jeroen van der Grond
- Department of Radiology, Leiden University medical Center, 2333 ZA, Leiden, The Netherlands
| | - Margaret J Wright
- Queensland Brain Institute, The University of Queensland, St Lucia, QLD, 4072, Australia
- Centre for Advanced Imaging, The University of Queensland, St Lucia, QLD, 4072, Australia
| | - Maria J Knol
- Department of Epidemiology, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
| | - Marcus Dörr
- Department of Internal Medicine B, University Medicine Greifswald, 17475, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, 17475, Greifswald, Germany
| | - Russell J Thomson
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, 7000, Australia
- Centre for Research in Mathematics and Data Science, Western Sydney University, Penrith, NSW, 2751, Australia
| | - Constance Bordes
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France
| | - Quentin Le Grand
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France
| | - Marie-Gabrielle Duperron
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France
| | | | | | - Pamela J Schreiner
- University of Minnesota School of Public Health, Minneapolis, MN, 55455, USA
| | - Denis A Evans
- Department of Internal Medicine, Rush University Medical Center, Chicago, IL, 60612, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Pediatrics at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Alexa S Beiser
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
- Boston University and the NHLBI's Framingham Heart Study, Boston, MA, 02215, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, 02118, USA
| | - Susana Muñoz Maniega
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB, UK
| | - Marian Beekman
- Section of Molecular Epidemiology, Biomedical Sciences, Leiden university Medical Center, 2333 ZA, Leiden, The Netherlands
| | - Julian Trollor
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, 2052, Australia
- Department of Developmental Disability Neuropsychiatry, School of Psychiatry, University of New South Wales, Sydney, NSW, 2052, Australia
| | - David J Stott
- Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Meike W Vernooij
- Department of Radiology & Nuclear Medicine, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
| | - Katharina Wittfeld
- German Center for Neurodegenerative Diseases (DZNE), Rostock/Greifswald, 17489, Greifswald, Germany
| | - Wiro J Niessen
- Department of Radiology & Nuclear Medicine, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
- Faculty of Applied Sciences, Delft University of Technology, Delft, NL, 2629 HS, USA
| | - Aicha Soumaré
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France
| | - Eric Boerwinkle
- University of Texas Health Science Center at Houston School of Public Health, Houston, TX, 77030, USA
| | - Stephen Sidney
- Kaiser Permanente Division of Research, Oakland, CA, 94612, USA
| | - Stephen T Turner
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, 55905, USA
| | - Gail Davies
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, 8036, Graz, Austria
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Anbupalam Thalamuthu
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Pediatrics at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Uwe Völker
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, 17475, Greifswald, Germany
| | - Mark A van Buchem
- Row Fogo Centre for Ageing and The Brain, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - R Nick Bryan
- The University of Texas at Austin Dell Medical School, Austin, TX, 78712, USA
| | - Josée Dupuis
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, 78229, USA
- Department of Cardiology, Leiden University Medical Center, 2333 ZA, Leiden, The Netherlands
| | - Mark E Bastin
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, 8036, Graz, Austria
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, 48104, USA
| | - David Ames
- National Ageing Research Institute Royal Melbourne Hospital, Parkville, VIC, 3052, Australia
- Academic Unit for Psychiatry of Old Age, University of Melbourne, St George's Hospital, Kew, VIC, 3101, Australia
| | - Alexander Teumer
- Department of Epidemiology, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
- Department of Internal Medicine B, University Medicine Greifswald, 17475, Greifswald, Germany
| | - Philippe Amouyel
- Inserm U1167, 59000, Lille, France
- Department of Epidemiology and Public Health, Pasteur Institute of Lille, 59000, Lille, France
| | - John B Kwok
- Brain and Mind Centre - The University of Sydney, Camperdown, NSW, 2050, Australia
- School of Medical Sciences, University of New South Wales, Sydney, NSW, 2052, Australia
| | - Robin Bülow
- Department of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, 17489, Greifswald, Germany
| | - Ian J Deary
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, 8036, Graz, Austria
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Peter R Schofield
- School of Medical Sciences, University of New South Wales, Sydney, NSW, 2052, Australia
- Neuroscience Research Australia, Randwick, NSW, 2031, Australia
| | - Henry Brodaty
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Pediatrics at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
- Dementia Centre for Research Collaboration, University of New South Wales, Sydney, NSW, 2052, Australia
| | - Jiyang Jiang
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Pediatrics at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Yasuharu Tabara
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, 606-8501, Japan
| | - Kazuya Setoh
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto, 606-8501, Japan
| | - Susumu Miyamoto
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto, 606-8501, Japan
| | - Kazumichi Yoshida
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto, 606-8501, Japan
| | - Manabu Nagata
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto, 606-8501, Japan
| | - Yoichiro Kamatani
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Tsurumi-ku, Yokohama City, Kanagawa, 230-0045, Japan
| | - Fumihiko Matsuda
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, 606-8501, Japan
| | - Bruce M Psaty
- Departments of Epidemiology, Medicine and Health Services, University of Washington, Seattle, WA, 98195, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, 98101, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, 60612, USA
| | - Philip L De Jager
- Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, New York, NY, 10032, USA
- Program in Population and Medical Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Thomas H Mosley
- Memory Impairment and Neurodegenerative Dementia (MIND) Center, University of Mississippi Medical Center, Jackson, MS, 39216, USA
| | - Perminder S Sachdev
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Pediatrics at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
- Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, NSW, 2031, Australia
| | - Reinhold Schmidt
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109-2029, USA
| | - Helen R Warren
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, E1 4NS, UK
- National Institute for Health Research Barts Cardiovascular Biomedical Research Unit, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Evangelos Evangelou
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, SW7 2AZ, UK
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Mpizani, 455 00, Greece
| | - David-Alexandre Trégouët
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France
| | - Mohammad A Ikram
- Department of Epidemiology, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
| | - Wei Wen
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, 2052, Australia
| | - Charles DeCarli
- Department of Neurology and Center for Neuroscience, University of California at Davis, Sacramento, CA, 95817, USA
| | - Velandai K Srikanth
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, 7000, Australia
- Peninsula Clinical School, Central Clinical School, Monash University, Melbourne, VIC, 3004, Australia
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, 2333 ZA, Leiden, The Netherlands
| | - Eline P Slagboom
- Section of Molecular Epidemiology, Biomedical Sciences, Leiden university Medical Center, 2333 ZA, Leiden, The Netherlands
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109-2029, USA
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, 565-0871, Japan
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Tsurumi-ku, Yokohama City, Kanagawa, 230-0045, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, 565-0871, Osaka, Japan
| | - Bernard Mazoyer
- University of Bordeaux, IMN, UMR 5293, 33000, Bordeaux, France
| | - Joanna M Wardlaw
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB, UK
- Row Fogo Centre for Ageing and The Brain, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- MRC UK Dementia Research Institute at the University of Edinburgh, Edinburgh, EH8 9YL, UK
| | - Paul A Nyquist
- Department of Neurology, Johns Hopkins School of Medicine, Baltimone, MD, 21205, USA
- General Internal Medicine, Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA
| | - Karen A Mather
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, 2052, Australia
- Neuroscience Research Australia, Randwick, NSW, 2031, Australia
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, 17475, Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), Rostock/Greifswald, 17475, Greifswald, Germany
| | - Helena Schmidt
- Gottfried Schatz Research Center, Department of Molecular Biology and Biochemistry, Medical University of Graz, 8010, Graz, Austria
| | - Cornelia M Van Duijn
- Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - Vilmundur Gudnason
- Icelandic Heart Association, IS-201, Kópavogur, Iceland
- University of Iceland, Faculty of Medicine, 101, Reykjavík, Iceland
| | - William T Longstreth
- Departments of Neurology and Epidemiology, University of Washington, Seattle, WA, 98104-2420, USA
| | - Lenore J Launer
- Laboratory of Epidemiology, Demography, and Biometry, National Institute of Aging, The National Institutes of Health, Bethesda, MD, 20892, USA
- Intramural Research Program/National Institute on Aging/National Institutes of Health, Bethesda, MD, 20892, USA
| | - Mark Lathrop
- University of McGill Genome Center, Montreal, QC, H3A 0G1, Canada
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, 78229, USA
- Boston University and the NHLBI's Framingham Heart Study, Boston, MA, 02215, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, 02118, USA
| | - Christophe Tzourio
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France
- CHU de Bordeaux, Pole de santé publique, Service d'information médicale, 33000, Bordeaux, France
| | - Hieab H Adams
- Department of Clinical Genetics, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
- Department of Radiology & Nuclear Medicine, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
| | - Paul M Matthews
- Department of Brain Sciences, Imperial College London, London, W12 0NN, UK
- UK Dementia Research Institute, London, WC1E 6BT, UK
- Data Science Institute, Imperial College London, London, SW7 2AZ, UK
| | - Myriam Fornage
- University of Texas Health Science Center at Houston McGovern Medical School, Houston, TX, 77030, USA.
| | - Stéphanie Debette
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France.
- Department of Neurology, Boston University School of Medicine, Boston, MA, 02118, USA.
- Department of Neurology, CHU de Bordeaux, 33000, Bordeaux, France.
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Raghavan S, Przybelski SA, Reid RI, Graff-Radford J, Lesnick TG, Zuk SM, Knopman DS, Machulda MM, Mielke MM, Petersen RC, Jack CR, Vemuri P. Reduced fractional anisotropy of the genu of the corpus callosum as a cerebrovascular disease marker and predictor of longitudinal cognition in MCI. Neurobiol Aging 2020; 96:176-183. [PMID: 33022474 PMCID: PMC7722208 DOI: 10.1016/j.neurobiolaging.2020.09.005] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Revised: 08/25/2020] [Accepted: 09/01/2020] [Indexed: 12/29/2022]
Abstract
Our goal was to evaluate the utility of diffusion tensor imaging (DTI) for predicting future cognitive decline in mild cognitive impairment (MCI) in conjunction with Alzheimer's disease (AD) biomarkers (amyloid positron emission tomography and AD signature neurodegeneration) in 132 MCI individuals ≥60 year old with structural magnetic resonance imaging, DTI, amyloid positron emission tomography, and at least one clinical follow-up. We used mixed-effect models to evaluate the prognostic ability of fractional anisotropy of the genu of the corpus callosum (FA-Genu), as a cerebrovascular disease marker, for predicting cognitive decline along with AD biomarkers. We contrasted the value of white matter hyperintensities, a traditional cerebrovascular disease marker as well as FA in the hippocampal cingulum bundle with the FA-Genu models. FA-Genu significantly predicted cognitive decline even after accounting for AD biomarkers. WMH was not associated with cognitive decline in the model with both WMH and FA-Genu. DTI specifically FA-Genu provides unique complementary information to AD biomarkers and has significant utility for prediction of cognitive decline in MCI.
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Affiliation(s)
| | | | - Robert I Reid
- Information Technology, Mayo Clinic, Rochester, MN, USA
| | | | | | - Samantha M Zuk
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | | | | | - Michelle M Mielke
- Health Sciences Research, Mayo Clinic, Rochester, MN, USA; Department of Neurology, Mayo Clinic, Rochester, MN, USA
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63
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Tsentidou G, Moraitou D, Tsolaki M. Cognition in Vascular Aging and Mild Cognitive Impairment. J Alzheimers Dis 2020; 72:55-70. [PMID: 31561369 DOI: 10.3233/jad-190638] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Cardiovascular health declines with age, due to vascular risk factors, and this leads to an increasing risk of cognitive decline. Mild cognitive impairment (MCI) is defined as the negative cognitive changes beyond what is expected in normal aging. The purpose of the study was to compare older adults with vascular risk factors (VRF), MCI patients, and healthy controls (HC) in main dimensions of cognitive control. The sample comprised a total of 109 adults, aged 50 to 85 (M = 66.09, S.D. = 9.02). They were divided into three groups: 1) older adults with VRF, 2) MCI patients, and 3) healthy controls (HC). VRF and MCI did not differ significantly in age, educational level, or gender as was the case with HC. The tests used mainly examine inhibition, cognitive flexibility, and working memory processing. Results showed that the VRF group had more Set Loss Errors in drawing designs indicating deficits in establishing cognitive set and in cognitive shifting. MCI patients displayed lower performance in processing. Hence, different types of specific impairments emerge in vascular aging and MCI, and this may imply that discrete underlying pathologies may play a role in the development of somewhat different profiles of cognitive decline.
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Affiliation(s)
- Glykeria Tsentidou
- Laboratoty of Psychology, Department of Experimental and Cognitive Psychology, School of Psychology, Aristotle University of Thessaloniki, Thessaloniki, Greece.,Laboratory of Neurodegenerative Diseases, Center for Interdisciplinary Research and Innovation (CIRI), AUTh, Greece
| | - Despina Moraitou
- Laboratoty of Psychology, Department of Experimental and Cognitive Psychology, School of Psychology, Aristotle University of Thessaloniki, Thessaloniki, Greece.,Greek Association of Alzheimer's Disease and Related Disorders, Thessaloniki (GAADRD), Greece.,Laboratory of Neurodegenerative Diseases, Center for Interdisciplinary Research and Innovation (CIRI), AUTh, Greece
| | - Magda Tsolaki
- 1st Department of Neurology, Medical School, Aristotle University of Thessaloniki (AUTh), Greece.,Greek Association of Alzheimer's Disease and Related Disorders, Thessaloniki (GAADRD), Greece.,Laboratory of Neurodegenerative Diseases, Center for Interdisciplinary Research and Innovation (CIRI), AUTh, Greece
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64
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Disrupted white matter integrity and network connectivity are related to poor motor performance. Sci Rep 2020; 10:18369. [PMID: 33110225 PMCID: PMC7591496 DOI: 10.1038/s41598-020-75617-1] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Accepted: 10/15/2020] [Indexed: 11/24/2022] Open
Abstract
Motor impairment is common in the elderly population. Disrupted white matter tracts and the resultant loss of connectivity between cortical regions play an essential role in motor control. Using diffusion tensor imaging (DTI), we investigated the effect of white matter microstructure on upper-extremity and lower-extremity motor function in a community-based sample. A total of 766 participants (57.3 ± 9.2 years) completed the assessment of motor performance, including 3-m walking speed, 5-repeat chair-stand time, 10-repeat hand pronation-supination time, and 10-repeat finger-tapping time. Fractional anisotropy (FA), mean diffusivity (MD), and structural network connectivity parameters were calculated based on DTI. Lower FA and higher MD were associated with poor performance in walking, chair-stand, hand pronation-supination, and finger-tapping tests, independent of the presence of lacunes, white matter hyperintensities volume, and brain atrophy. Reduced network density, network strength, and global efficiency related to slower hand pronation-supination and finger-tapping, but not related to walking speed and chair-stand time. Disrupted white matter integrity and reduced cerebral network connectivity were associated with poor motor performance. Diffusion-based methods provide a more in-depth insight into the neural basis of motor dysfunction.
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65
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Zhang X, Liu X, Xia R, Li N, Liao X, Chen Z. Chinese herbal medicine for vascular cognitive impairment in cerebral small vessel disease: A protocol for systematic review and meta-analysis of randomized controlled trials. Medicine (Baltimore) 2020; 99:e22455. [PMID: 33019432 PMCID: PMC7535689 DOI: 10.1097/md.0000000000022455] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND Cerebral small vessel disease (CSVD) is the most common etiology of vascular cognitive impairment (VCI). VCI in CSVD (CSVD-VCI) shows a progressive course with multiple stages and is also associated with dysfunctions such as gait, emotional and behavioral, and urinary disturbances, which seriously affect the life quality of elderly people. In mainland China, Chinese herbal medicine (CHM) is clinically used for CSVD-VCI and presenting positive efficacy, but the evidence revealed in relevant clinical trials has not been systematically evaluated. The purpose of this study is to assess the current evidence available for the clinical efficacy and safety of CHM for CSVD-VCI. METHODS A literature search of published RCTs up to April 30, 2020, has been conducted in the following 7 electronic databases: PubMed, Embase, the Cochrane Library, Chinese National Knowledge Infrastructure Database (CNKI), Chinese Science and Technology Journals Database (VIP), Wanfang Database, and Chinese Biomedical Literature Service System (SinoMed). For unpublished studies, 2 clinical trial online registration websites will be searched: ClinicalTrials.gov and Chinese Clinical Trial Registry (ChiCTR). Only randomized controlled trials (RCTs) using CHM in the treatment of patients with CSVD-VCI, which compares CHM with no treatment, placebo, or other conventional treatments, will be included in this systematic review. Primary outcomes will be set as acknowledged scales measuring cognitive function. Secondary outcomes will involve activities of daily living, behavioral, and psychological symptoms, global performance of dementia, neurological function, biological markers of endothelial dysfunction, the clinical effective rate, and adverse events. After screening studies and extracting data, the Cochrane Collaborations tool for assessing risk of bias will be applied to assess the methodological quality of included RCTs. Review Manager Version 5.3 software will be used for data synthesis and statistical analysis. Subgroup analyses, sensitivity analyses, and meta-regression will be conducted to detect potential sources of heterogeneity. The funnel plot and Eggers test will be developed to evaluate publication bias, if available. We will perform the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system to appraise the quality of evidence. RESULTS Evidence exhibited in this systematic review will provide practical references in the field of CHM treating CSVD-VCI. Moreover, our detailed appraisals of methodological deficiencies of relevant RCTs will offer helpful advice for researchers who are designing trials of CHMs in the treatment of CSVD-VCI. CONCLUSION The conclusion about the clinical efficacy and safety of CHM for CSVD-VCI will be provided for clinical plans, decisions, and policy developments in the full version of this systematic review. SYSTEMATIC REVIEW REGISTRATION INPLASY202080120.
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Affiliation(s)
| | | | - Ruyu Xia
- Centre for Evidence-Based Chinese Medicine, Beijing University of Chinese Medicine
| | | | - Xing Liao
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China
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66
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Dobrynina LA, Gadzhieva ZS, Shamtieva KV, Kremneva EI, Akhmetzyanov BM, Kalashnikova LA, Krotenkova MV. Microstructural Predictors of Cognitive Impairment in Cerebral Small Vessel Disease and the Conditions of Their Formation. Diagnostics (Basel) 2020; 10:diagnostics10090720. [PMID: 32961692 PMCID: PMC7554972 DOI: 10.3390/diagnostics10090720] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Revised: 09/08/2020] [Accepted: 09/17/2020] [Indexed: 01/10/2023] Open
Abstract
Introduction: Cerebral small vessel disease (CSVD) is the leading cause of vascular and mixed degenerative cognitive impairment (CI). The variability in the rate of progression of CSVD justifies the search for sensitive predictors of CI. Materials: A total of 74 patients (48 women, average age 60.6 ± 6.9 years) with CSVD and CI of varying severity were examined using 3T MRI. The results of diffusion tensor imaging with a region of interest (ROI) analysis were used to construct a predictive model of CI using binary logistic regression, while phase-contrast magnetic resonance imaging and voxel-based morphometry were used to clarify the conditions for the formation of CI predictors. Results: According to the constructed model, the predictors of CI are axial diffusivity (AD) of the posterior frontal periventricular normal-appearing white matter (pvNAWM), right middle cingulum bundle (CB), and mid-posterior corpus callosum (CC). These predictors showed a significant correlation with the volume of white matter hyperintensity; arterial and venous blood flow, pulsatility index, and aqueduct cerebrospinal fluid (CSF) flow; and surface area of the aqueduct, volume of the lateral ventricles and CSF, and gray matter volume. Conclusion: Disturbances in the AD of pvNAWM, CB, and CC, associated with axonal damage, are a predominant factor in the development of CI in CSVD. The relationship between AD predictors and both blood flow and CSF flow indicates a disturbance in their relationship, while their location near the floor of the lateral ventricle and their link with indicators of internal atrophy, CSF volume, and aqueduct CSF flow suggest the importance of transependymal CSF transudation when these regions are damaged.
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67
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Varkanitsa M, Peñaloza C, Charidimou A, Caplan D, Kiran S. White Matter Hyperintensities Predict Response to Language Treatment in Poststroke Aphasia. Neurorehabil Neural Repair 2020; 34:945-953. [PMID: 32924765 DOI: 10.1177/1545968320952809] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND White matter hyperintensities (WMH) are a radiological marker of brain health that has been associated with language status in poststroke aphasia; however, its association with language treatment outcomes remains unknown. OBJECTIVE To determine whether WMH in the right hemisphere (RH) predict response to language therapy independently from demographics and stroke lesion-related factors in poststroke aphasia. METHODS We used the Fazekas scale to rate WMH in the RH in 30 patients with poststroke aphasia who received language treatment. We developed ordinal regression models to examine language treatment effects as a function of WMH severity after controlling for aphasia severity, stroke lesion volume, time post onset, age, and education level. We also evaluated associations between WMH severity and both pre-treatment naming ability and executive function. RESULTS The severity of WMH in the RH predicted treatment response independently from demographic and stroke-related factors such that patients with less severe WMH exhibited better treatment outcome. WMH scores were not significantly correlated with pretreatment language scores, but they were significantly correlated with pretreatment scores of executive function. CONCLUSION We suggest that the severity of WMH in the RH is a clinically relevant predictor of treatment response in this population.
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Affiliation(s)
- Maria Varkanitsa
- Boston University, Boston, MA, USA.,Massachusetts General Hospital, Boston, MA, USA
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68
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Gonzales MM, Wang CP, Quiben M, MacCarthy D, Seshadri S, Jacob M, Hazuda H. Joint trajectories of cognition and gait speed in Mexican American and European American older adults: The San Antonio longitudinal study of aging. Int J Geriatr Psychiatry 2020; 35:897-906. [PMID: 32281153 PMCID: PMC10869030 DOI: 10.1002/gps.5310] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2019] [Revised: 03/11/2020] [Accepted: 04/03/2020] [Indexed: 12/13/2022]
Abstract
OBJECTIVES Cognitive decline and gait speed slowing are independent predictors of disability and mortality. While both factors increase in prevalence with advancing age, little is known about their combined patterns of change. The study goal was to identify joint trajectories of cognition and gait speed within an aging bi-ethnic cohort of Mexican Americans and European Americans. METHODS/DESIGN Participants included 182 Mexican Americans and 188 European Americans, ages 65 to 74, who were followed over a mean of 9.5 years. Cognition was assessed with the mini-mental state examination and gait speed was examined with a timed 10-ft walk. Joint trajectory classes of cognition and gait speed were identified with latent growth mixture modeling. Odd-ratios assessed predictors for trajectory classes. RESULTS Three latent trajectory classes were identified: (a) relatively stable cognition and gait (termed stable cognition and gait class, 65.4%); (b) deteriorating cognition and gait (termed cognitive and physical vulnerability class, 22.2%); (c) stable cognition and deteriorating gait (termed physical vulnerability class, 12.4%). The odds of classification in the cognitive and physical vulnerability class vs stable cognition and gait class was associated with Mexican American ethnicity (OR = 3.771, P = .016), age (OR = 1.186, P = .017), income (OR = 0.828, P = .029), education (OR = 0.703, P < .001), and diabetes (OR = 4.547, P = .010). The odds of classification in the physical vulnerability class was associated with female sex (OR = 6.481, P = .004) and body mass index (OR = 1.118, P = .025). CONCLUSIONS The trajectories of cognition and gait speed were generally parallel, suggesting the two domains may act synergistically to shape important health outcomes. Socioeconomic disparities and Mexican American ethnicity independently conferred risk for accelerated decline.
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Affiliation(s)
- Mitzi M. Gonzales
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, Texas
- Department of Neurology, University of Texas Health Science Center, San Antonio, Texas
| | - Chen-Pin Wang
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, Texas
- Department of Population Health Sciences, University of Texas Health Science Center, San Antonio, Texas
- South Texas Veterans Health Care System, Geriatric Research, Education & Clinical Center, San Antonio, Texas
| | - Myla Quiben
- Department of Physical Therapy, University of North Texas Health Science Center, Fort Worth, Texas
| | - Daniel MacCarthy
- Department of Population Health Sciences, University of Texas Health Science Center, San Antonio, Texas
- South Texas Veterans Health Care System, Geriatric Research, Education & Clinical Center, San Antonio, Texas
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, Texas
- Department of Neurology, University of Texas Health Science Center, San Antonio, Texas
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts
| | - Mini Jacob
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, Texas
- Department of Family and Community Medicine, University of Texas Health Science Center, San Antonio, Texas
| | - Helen Hazuda
- Department of Medicine/Nephrology, University of Texas Health Science Center, San Antonio, Texas
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69
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Wang Y, Jiang C, Huang H, Liu N, Wang Y, Chen Z, Liang S, Wu M, Jiang Y, Wang X, Zhou T, Chen H, Zhang L, Li H. Correlation of Cerebral White Matter Lesions with Carotid Intraplaque Neovascularization assessed by Contrast-enhanced Ultrasound. J Stroke Cerebrovasc Dis 2020; 29:104928. [PMID: 32689582 DOI: 10.1016/j.jstrokecerebrovasdis.2020.104928] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Revised: 04/27/2020] [Accepted: 04/29/2020] [Indexed: 12/13/2022] Open
Abstract
PURPOSE Carotid atherosclerotic plaque is closely associated with cerebral white matter lesions (WMLs), while intraplaque neovascularization (IPN) contributes significantly to arterial remodeling and plaque vulnerability. In this study, we aim to evaluate the correlation of carotid IPN with cerebral WMLs. METHODS The presence of IPN and WMLs were assessed by contrast-enhanced ultrasound (CEUS) and MRI respectively. IPN was evaluated utilizing semi-quantification visual grading scale and WMLs was divided according to Fazekas grading scale. We investigated the baseline data, Fazekas grades, and IPN grades among 269 participants. We explored the influences of each variable on Fazekas grades using ordinal logistic regression and evaluated the relationship between IPN grades and WMLs Fazekas grades. RESULTS Increased age (OR: 1.06, P<0.001), hypertension (OR: 2.17, P=0.002), cerebral infarction (OR: 1.74, P=0.046), and elevated carotid IPN grading were significantly associated with aggravated Fazekas grades (grade 2 or 3). To be specific, people having grade 3, 2, and 1 carotid IPN were 25.84 (P<0.001), 10.64 (P<0.001), and 5.96 (P=0.010) times as likely to have elevated Fazekas grades compared with those who having grade 0 carotid IPN. CONCLUSION Increased carotid IPN is independently correlated with aggravated cerebral WMLs.
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Affiliation(s)
- Yuxuan Wang
- Department of Neurology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China; First Clinical Medical School, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China; Key Laboratory of Acupuncture and Medicine Research of Ministry of Education, Nanjing University of Chinese Medicine, Nanjing, China.
| | - Chao Jiang
- Department of Public Health, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China
| | - Hui Huang
- Department of Ultrasound, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China
| | - Niu Liu
- Department of Ultrasound, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China
| | - Yi Wang
- Department of Neurosurgery, Nanjing Drum Tower Hospital, Affiliated Hospital of Nanjing University Medical School, Nanjing, Jiangsu, China
| | - Zhaoyao Chen
- Department of Neurology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China
| | - Sen Liang
- Department of Neurology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China
| | - Minghua Wu
- Department of Neurology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China
| | - Yajun Jiang
- Department of Neurology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China
| | - Xiaoxiao Wang
- GCP Center, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China
| | - Tingting Zhou
- Department of Neurology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China; First Clinical Medical School, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China
| | - Hu Chen
- Department of Radiology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China
| | - Lin Zhang
- Department of Neurology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China; First Clinical Medical School, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China.
| | - Hui Li
- Department of Neurology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China; First Clinical Medical School, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China.
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70
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Yang D, Huang L, Luo C, Li M, Qin R, Ma J, Shao P, Xu H, Zhang B, Xu Y, Zhang M. Impaired Structural Network Properties Caused by White Matter Hyperintensity Related to Cognitive Decline. Front Neurol 2020; 11:250. [PMID: 32373044 PMCID: PMC7186334 DOI: 10.3389/fneur.2020.00250] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Accepted: 03/16/2020] [Indexed: 12/12/2022] Open
Abstract
Purpose: There is a high correlation between white matter hyperintensity (WMH) and cognitive impairment (CI) in elderly people. However, not all WMH will develop into CI, and the potential mechanism of WMH-related CI is still unclear. This study aimed to investigate the topological properties of white matter structural network in WMH-related CI. Methods: Forty-one WMH subjects with CI (WMH-CI), 42 WMH subjects without CI (WMH-no-CI), and 52 elderly healthy controls (HC) were recruited. Diffusion tensor imaging (DTI) fiber tractography and graph theoretical analysis were applied to construct the structural network. We compared network properties and clinical features among the three groups. Multiple linear regression analysis was performed to investigate the relationships among WMH volumes, impaired network properties, and cognitive functions in the WMH-CI group. Results: Compared with the controls, both WMH groups showed decreased network strength, global efficiency, and increased characteristic path length (Lp) at the level of the whole brain. The WMH-CI group displayed more profound impairments of nodal efficiency and nodal path length (NLp) within multiple regions including precentral, cingulate, and medial temporal gyrus. The disrupted network properties were associated with CI and WMH burdens in the WMH-CI group. Furthermore, a mediation effect of NLp in the left inferior frontal gyrus was observed for the association between periventricular WMH (PWMH) and memory deficit. Conclusions: Brain structural network in WMH-CI is significantly disturbed, and this disturbance is related to the severity of WMH and CI. Increased NLp in the left opercular part of inferior frontal gyrus (IFGoperc.L) was shown to be a mediation framework between PWMH and WMH-related memory, which shed light on investigating the underlying mechanisms of CI caused by WMH.
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Affiliation(s)
- Dan Yang
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Lili Huang
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Caimei Luo
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Mengchun Li
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Ruomeng Qin
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Junyi Ma
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Pengfei Shao
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Hengheng Xu
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Bing Zhang
- Department of Radiology, Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
| | - Yun Xu
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Meijuan Zhang
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
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71
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White matter hyperintensities are associated with falls in older people with dementia. Brain Imaging Behav 2020; 13:1265-1272. [PMID: 30145714 DOI: 10.1007/s11682-018-9943-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
Abstract
White Matter Hyperintensities (WMHs) are associated with impaired gait, balance and cognition and increased fall risk in cognitively healthy older people. However, few studies have examined such relationships in older people with dementia. Understanding the role of WMHs in falls may assist in developing effective fall prevention strategies. We investigated the relationship between baseline WMHs, cognitive and sensorimotor function and prospective falls in older people with dementia. Twenty-eight community-dwelling older people with mild-moderate dementia (MMSE 11-23; ACE-R < 83) underwent magnetic resonance imaging and assessment of sensorimotor and cognitive (global and processing speed) function at baseline. WMHs, were quantified using a fully automated segmentation toolbox, UBO Detector ( https://cheba.unsw.edu.au/group/neuroimaging-pipeline ). Falls were ascertained prospectively for 12-months using monthly calendars with the assistance of carers. The median age of the participants was 83 years (IQR 77-86); 36% were female; 21 (75%) fell during follow-up. Using Generalized Linear Models, larger volumes of total WMHs were found to be significantly associated with poorer global cognitive and sensorimotor function. Using modified Poisson regression, total, periventricular and deep WMHs were each associated with future falls while controlling for age, sex, intracranial volume and vascular risk. Each standard deviation increase in total and periventricular WMH volume resulted in a 33% (RR 1.33 95%CI 1.07-1.66) and 30% (RR 1.30 95%CI 1.06-1.60) increased risk of falling, respectively. When the deep WMH volume z-scores were dichotomized at the median, individuals with greater deep WMH volumes had an 81% (RR 1.81 95% CI 1.02-3.21) increased risk of falling. WMHs were associated with poorer sensorimotor and cognitive function in people with dementia and total, periventricular and deep WMHs were associated with falls. Further research is needed to confirm these preliminary findings and explore the impact of vascular risk reduction strategies on WMHs, functional performance and falls.
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72
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Liu D, Li K, Ma X, Li Y, Bu Q, Pan Z, Feng X, Shi Q, Zhou L, Hu W. Correlations Between the Microstructural Changes of the Medial Temporal Cortex and Mild Cognitive Impairment in Patients With Cerebral Small Vascular Disease (cSVD): A Diffusion Kurtosis Imaging Study. Front Neurol 2020; 10:1378. [PMID: 32010043 PMCID: PMC6974677 DOI: 10.3389/fneur.2019.01378] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2019] [Accepted: 12/13/2019] [Indexed: 12/18/2022] Open
Abstract
Object: The purpose of our study was to investigate the microstructural changes of the medial temporal cortex in mild cognitive impairment (MCI) patients with cerebral small vascular disease (cSVD) using diffusion kurtosis imaging (DKI) and to examine whether DKI parameters are correlated with MCI. Method: A total of 82 cSVD patients admitted to the Department of Neurology Beijing Chaoyang Hospital, Capital Medical University, were retrospectively enrolled in this study. The Montreal cognitive assessment scale (MoCA) score was used to assess overall cognitive function. According to the presence or absence of MCI, these patients were divided into an MCI group (n = 48) and a non-MCI group (n = 34). The general clinical data of the two groups were collected and analyzed. The regions of interest (ROIs) in the medial temporal cortex were selected for investigation. The averaged values of DKI parameters were measured in each ROI and compared between the two groups, and the correlations between DKI parameters and MoCA score and between diffusion and kurtosis parameters were examined. Results: Compared to the non-MCI group, MCI patients showed significantly increased mean diffusion (MD) and radial diffusion (RD) and significantly decreased mean kurtosis (MK) in the left hippocampus (P = 0.005, 0.006, 0.002, respectively). In the left hippocampus, fractional anisotropy (FA), MK, radial kurtosis (RK), and kurtosis fractional anisotropy (KFA) showed significantly positive correlations with MoCA score (r = 0.374, 0.37, 0.392, 0.242, respectively, all P < 0.05), while MK and RD were negatively correlated with MoCA score (r = -0.227, -0.255, respectively, both P < 0.05). In the left parahippocampal region, axial kurtosis (AK) and KFA were positively correlated with MoCA score (r = 0.228, 0.282, respectively, both P < 0.05), while RK was positively correlated with MoCA score in the right parahippocampal region (r = 0.231, P < 0.05). Significant correlations of MD with MK, RD with RK, and FA with KFA were observed in the medial temporal cortex (r = -0.254, -0.395, 0.807, respectively, all P < 0.05) but not of axial diffusion (AD) with AK. Conclusion: The DKI technique can be used to observe microstructural changes of the medial temporal cortex in MCI patients with cSVD. The DKI-derived parameters might be a feasible means of evaluating patients with MCI.
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Affiliation(s)
- Dongtao Liu
- Department of Neurology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Kun Li
- Department of Radiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Xiangke Ma
- Department of Neurosurgery, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Yue Li
- Department of Neurology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Qiao Bu
- Department of Radiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Zhenyu Pan
- Department of Radiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Xiang Feng
- MR Scientific Marketing, Diagnosis Imaging, Siemens Healthineers China, Beijing, China
| | - Qinglei Shi
- MR Scientific Marketing, Diagnosis Imaging, Siemens Healthineers China, Beijing, China
| | - Lichun Zhou
- Department of Neurology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Wenli Hu
- Department of Neurology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
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73
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Chen H, Huang L, Yang D, Ye Q, Guo M, Qin R, Luo C, Li M, Ye L, Zhang B, Xu Y. Nodal Global Efficiency in Front-Parietal Lobe Mediated Periventricular White Matter Hyperintensity (PWMH)-Related Cognitive Impairment. Front Aging Neurosci 2019; 11:347. [PMID: 31920627 PMCID: PMC6914700 DOI: 10.3389/fnagi.2019.00347] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2019] [Accepted: 11/28/2019] [Indexed: 12/24/2022] Open
Abstract
White matter hyperintensity (WMH) is widely observed in the elderly population and serves as a key indicator of cognitive impairment (CI). However, the underlying mechanism remains to be elucidated. Herein, we investigated the topological patterns of resting state functional networks in WMH subjects and the relationship between the topological measures and CI. A graph theory-based analysis was employed in the resting-state functional magnetic resonance scans of 112 subjects (38 WMH subjects with cognitive impairment without dementia (CIND), 36 WMH subjects with normal cognition and 38 healthy controls (HCs), and we found that WMH-CIND subjects displayed decreased global efficiency at the levels of the whole brain, specific subnetworks [fronto-parietal network (FPN) and cingulo-opercular network (CON)] and certain nodes located in the FPN and CON, as well as decreased local efficiency in subnetworks. Our results demonstrated that nodal global efficiency in frontal and parietal regions mediated the impairment of information processing speed related to periventricular WMH (PWMH). Additionally, we performed support vector machine (SVM) analysis and found that altered functional efficiency can identify WMH-CIND subjects with high accuracy, sensitivity and specificity. These findings suggest impaired functional networks in WMH-CIND individuals and that decreased functional efficiency may be a feature of CI in WMH subjects.
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Affiliation(s)
- Haifeng Chen
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Lili Huang
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Dan Yang
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Qing Ye
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Mengdi Guo
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Ruomeng Qin
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Caimei Luo
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Mengchun Li
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Lei Ye
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Bing Zhang
- Department of Radiology, Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
| | - Yun Xu
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
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74
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Wang S, Jiaerken Y, Yu X, Shen Z, Luo X, Hong H, Sun J, Xu X, Zhang R, Zhou Y, Lou M, Huang P, Zhang M. Understanding the association between psychomotor processing speed and white matter hyperintensity: A comprehensive multi-modality MR imaging study. Hum Brain Mapp 2019; 41:605-616. [PMID: 31675160 PMCID: PMC7267958 DOI: 10.1002/hbm.24826] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Revised: 09/22/2019] [Accepted: 10/02/2019] [Indexed: 01/01/2023] Open
Abstract
Cognitive processing speed is crucial for human cognition and declines with aging. White matter hyperintensity (WMH), a common sign of WM vascular damage in the elderly, is closely related to slower psychomotor processing speed. In this study, we investigated the association between WMH and psychomotor speed changes through a comprehensive assessment of brain structural and functional features. Multi-modal MRIs were acquired from 60 elderly adults. Psychomotor processing speeds were assessed using the Trail Making Test Part A (TMT-A). Linear regression analyses were performed to assess the associations between TMT-A and brain features, including WMH volumes in five cerebral regions, diffusivity parameters in the major WM tracts, regional gray matter volume, and brain activities across the whole brain. Hierarchical regression analysis was used to demonstrate the contribution of each index to slower psychomotor processing speed. Linear regression analysis demonstrated that WMH volume in the occipital lobe and fractional anisotropy of the forceps major, an occipital association tract, were associated with TMT-A. Besides, resting-state brain activities in the visual cortex connected to the forceps major were associated with TMT-A. Hierarchical regression showed fractional anisotropy of the forceps major and regional brain activities were significant predictors of TMT-A. The occurrence of WMH, combined with the disruption of passing-through fiber integrity and altered functional activities in areas connected by this fiber, are associated with a decline of psychomotor processing speed. While the causal relationship of this WMH-Tract-Function-Behavior link requires further investigation, this study enhances our understanding of these complex mechanisms.
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Affiliation(s)
- Shuyue Wang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Yeerfan Jiaerken
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xinfeng Yu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Zhujing Shen
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiao Luo
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Hui Hong
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Jianzhong Sun
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaojun Xu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Ruiting Zhang
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Ying Zhou
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Min Lou
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
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75
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Power MC, Su D, Wu A, Reid RI, Jack CR, Knopman DS, Coresh J, Huang J, Kantarci K, Sharrett AR, Gottesman RG, Griswold ME, Mosley TH. Association of white matter microstructural integrity with cognition and dementia. Neurobiol Aging 2019; 83:63-72. [PMID: 31585368 PMCID: PMC6914220 DOI: 10.1016/j.neurobiolaging.2019.08.021] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2019] [Revised: 08/07/2019] [Accepted: 08/21/2019] [Indexed: 10/26/2022]
Abstract
Late-life measures of white matter (WM) microstructural integrity may predict cognitive status, cognitive decline, and incident mild cognitive impairment (MCI) or dementia. We considered participants of the Atherosclerosis Risk in Communities study who underwent cognitive assessment and neuroimaging in 2011-2013 and were followed through 2016-2017 (n = 1775 for analyses of prevalent MCI and dementia, baseline cognitive performance, and longitudinal cognitive change and n = 889 for analyses of incident MCI, dementia, or death). Cross-sectionally, both overall WM fractional anisotropy and overall WM mean diffusivity were strongly associated with baseline cognitive performance and risk of prevalent MCI or dementia. Longitudinally, greater overall WM mean diffusivity was associated with accelerated cognitive decline, as well as incident MCI, incident dementia, and mortality, but WM fractional anisotropy was not robustly associated with cognitive change or incident cognitive impairment. Both cross-sectional and longitudinal associations were attenuated after additionally adjusting for likely downstream pathologic changes. Increased WM mean diffusivity may provide an early indication of dementia pathogenesis.
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Affiliation(s)
- Melinda C Power
- Department of Epidemiology and Biostatistics, Milken Institute School of Public Health, George Washington University, Washington, DC, USA.
| | - Dan Su
- Department of Data Science, JD Bower School of Population Health, University of Mississippi Medical Center, Jackson, MS, USA
| | - Aozhou Wu
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Robert I Reid
- Department of Information Technology, Mayo Clinic, Rochester, MN, USA
| | | | | | - Joe Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Juebin Huang
- Department of Neurology, University of Mississippi Medical Center, Jackson, MS, USA
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - A Richey Sharrett
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Rebecca G Gottesman
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Department of Neurology, Johns Hopkins University, Baltimore, MD, USA
| | - Mike E Griswold
- Department of Data Science, JD Bower School of Population Health, University of Mississippi Medical Center, Jackson, MS, USA
| | - Thomas H Mosley
- Department of Neurology, University of Mississippi Medical Center, Jackson, MS, USA; Department of Geriatrics, University of Mississippi Medical Center, Jackson, MS, USA
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76
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Finsterwalder S, Wuehr M, Gesierich B, Dietze A, Konieczny MJ, Schmidt R, Schniepp R, Duering M. Minor gait impairment despite white matter damage in pure small vessel disease. Ann Clin Transl Neurol 2019; 6:2026-2036. [PMID: 31524338 PMCID: PMC6801180 DOI: 10.1002/acn3.50891] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Revised: 07/29/2019] [Accepted: 08/12/2019] [Indexed: 01/17/2023] Open
Abstract
OBJECTIVE Gait impairment is common in patients with cerebral small vessel disease (SVD). However, gait studies in elderly SVD patients might be confounded by age-related comorbidities, such as polyneuropathy or sarcopenia. We therefore studied young patients with the genetically defined SVD CADASIL. Our aim was to examine the effects of pure SVD on single and dual task gait, and to investigate associations of gait performance with cognitive deficits and white matter alterations. METHODS We investigated single task walking and calculatory, semantic, or motoric dual task costs in 39 CADASIL patients (mean age 50 ± 8) using a computerized walkway. We obtained 3.0T MRI and neuropsychological data on processing speed, the main cognitive deficit in CADASIL. Spatiotemporal gait parameters were standardized based on data from 192 healthy controls. Associations between white matter integrity, assessed by diffusion tensor imaging, and gait were analyzed using both a global marker and voxel-wise analysis. RESULTS Compared to controls, CADASIL patients showed only mild single task gait impairment, and only in the rhythm domain. The semantic dual task additionally uncovered mild deficits in the pace domain. Processing speed was not associated with gait. White matter alterations were related to single task stride length but not to dual task performance. INTERPRETATION Despite severe disease burden, gait performance in patients with pure small vessel disease was relatively preserved in single and dual tasks. Results suggest that age-related pathologies other than small vessel disease might play a role for gait impairment in elderly SVD patients.
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Affiliation(s)
- Sofia Finsterwalder
- Institute for Stroke and Dementia ResearchUniversity HospitalLMU MunichMunichGermany
| | - Max Wuehr
- German Center for Vertigo and Balance Disorders DSGZDepartment of NeurologyUniversity HospitalLMU MunichMunichGermany
| | - Benno Gesierich
- Institute for Stroke and Dementia ResearchUniversity HospitalLMU MunichMunichGermany
| | - Anna Dietze
- German Center for Vertigo and Balance Disorders DSGZDepartment of NeurologyUniversity HospitalLMU MunichMunichGermany
| | - Marek J. Konieczny
- Institute for Stroke and Dementia ResearchUniversity HospitalLMU MunichMunichGermany
| | | | - Roman Schniepp
- German Center for Vertigo and Balance Disorders DSGZDepartment of NeurologyUniversity HospitalLMU MunichMunichGermany
| | - Marco Duering
- Institute for Stroke and Dementia ResearchUniversity HospitalLMU MunichMunichGermany
- Munich Cluster for Systems Neurology (SyNergy)MunichGermany
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77
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Williams OA, Zeestraten EA, Benjamin P, Lambert C, Lawrence AJ, Mackinnon AD, Morris RG, Markus HS, Barrick TR, Charlton RA. Predicting Dementia in Cerebral Small Vessel Disease Using an Automatic Diffusion Tensor Image Segmentation Technique. Stroke 2019; 50:2775-2782. [PMID: 31510902 PMCID: PMC6756294 DOI: 10.1161/strokeaha.119.025843] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Supplemental Digital Content is available in the text. Cerebral small vessel disease (SVD) is the most common cause of vascular cognitive impairment, with a significant proportion of cases going on to develop dementia. We explore the extent to which diffusion tensor image segmentation technique (DSEG; which characterizes microstructural damage across the cerebrum) predicts both degree of cognitive decline and conversion to dementia, and hence may provide a useful prognostic procedure.
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Affiliation(s)
- Owen A Williams
- From the Neurosciences Research Centre, Molecular and Clinical Sciences Research Institute, St George's University of London, United Kingdom (O.A.W., E.A.Z., C.L., T.R.B.)
| | - Eva A Zeestraten
- From the Neurosciences Research Centre, Molecular and Clinical Sciences Research Institute, St George's University of London, United Kingdom (O.A.W., E.A.Z., C.L., T.R.B.)
| | - Philip Benjamin
- Department of Radiology, Charing Cross Hospital campus, Imperial College NHS Trust, United Kingdom (P.B.)
| | - Christian Lambert
- From the Neurosciences Research Centre, Molecular and Clinical Sciences Research Institute, St George's University of London, United Kingdom (O.A.W., E.A.Z., C.L., T.R.B.).,Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, United Kingdom (C.L.)
| | - Andrew J Lawrence
- Stroke Research Group, Clinical Neurosciences, University of Cambridge, United Kingdom (A.J.L., H.S.M.)
| | - Andrew D Mackinnon
- Atkinson Morley Regional Neuroscience Centre, St George's NHS Healthcare Trust, London, United Kingdom (A.G.M.)
| | - Robin G Morris
- Department of Psychology, King's College Institute of Psychiatry, Psychology, and Neuroscience, London, United Kingdom (R.G.M.)
| | - Hugh S Markus
- Stroke Research Group, Clinical Neurosciences, University of Cambridge, United Kingdom (A.J.L., H.S.M.)
| | - Thomas R Barrick
- From the Neurosciences Research Centre, Molecular and Clinical Sciences Research Institute, St George's University of London, United Kingdom (O.A.W., E.A.Z., C.L., T.R.B.)
| | - Rebecca A Charlton
- Department of Psychology, Goldsmiths University of London, United Kingdom (R.A.C.)
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78
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Ter Telgte A, van Leijsen EMC, Wiegertjes K, Klijn CJM, Tuladhar AM, de Leeuw FE. Cerebral small vessel disease: from a focal to a global perspective. Nat Rev Neurol 2019; 14:387-398. [PMID: 29802354 DOI: 10.1038/s41582-018-0014-y] [Citation(s) in RCA: 290] [Impact Index Per Article: 58.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Cerebral small vessel disease (SVD) is commonly observed on neuroimaging among elderly individuals and is recognized as a major vascular contributor to dementia, cognitive decline, gait impairment, mood disturbance and stroke. However, clinical symptoms are often highly inconsistent in nature and severity among patients with similar degrees of SVD on brain imaging. Here, we provide a new framework based on new advances in structural and functional neuroimaging that aims to explain the remarkable clinical variation in SVD. First, we discuss the heterogeneous pathology present in SVD lesions despite an identical appearance on imaging and the perilesional and remote effects of these lesions. We review effects of SVD on structural and functional connectivity in the brain, and we discuss how network disruption by SVD can lead to clinical deficits. We address reserve and compensatory mechanisms in SVD and discuss the part played by other age-related pathologies. Finally, we conclude that SVD should be considered a global rather than a focal disease, as the classically recognized focal lesions affect remote brain structures and structural and functional network connections. The large variability in clinical symptoms among patients with SVD can probably be understood by taking into account the heterogeneity of SVD lesions, the effects of SVD beyond the focal lesions, the contribution of neurodegenerative pathologies other than SVD, and the interaction with reserve mechanisms and compensatory mechanisms.
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Affiliation(s)
- Annemieke Ter Telgte
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Medical Neuroscience, Radboud University Medical Center, Nijmegen, Netherlands
| | - Esther M C van Leijsen
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Medical Neuroscience, Radboud University Medical Center, Nijmegen, Netherlands
| | - Kim Wiegertjes
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Medical Neuroscience, Radboud University Medical Center, Nijmegen, Netherlands
| | - Catharina J M Klijn
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Medical Neuroscience, Radboud University Medical Center, Nijmegen, Netherlands
| | - Anil M Tuladhar
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Medical Neuroscience, Radboud University Medical Center, Nijmegen, Netherlands
| | - Frank-Erik de Leeuw
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Medical Neuroscience, Radboud University Medical Center, Nijmegen, Netherlands.
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79
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Remote ischemic conditioning improves cognition in patients with subcortical ischemic vascular dementia. BMC Neurol 2019; 19:206. [PMID: 31443692 PMCID: PMC6706912 DOI: 10.1186/s12883-019-1435-y] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Accepted: 08/18/2019] [Indexed: 01/27/2023] Open
Abstract
BACKGROUND Subcortical ischemic vascular dementia (SIVD) is very common among the older people, but has no approved treatment. Preclinical trials show that remote ischemic conditioning (RIC) reduces recurrence of ischemic stroke. We hypothesize that RIC may also be an effective therapy for patients with SIVD. METHODS Thirty-seven consecutive SIVD cases were enrolled in this randomized control study. Eighteen RIC patients underwent five brief cycles of conditioning (bilateral upper limb compression at 200 mmHg) followed by reperfusion twice daily over 6 consecutive months. Nineteen control patients underwent the same process, but at a pressure of 60 mmHg which caused no restriction on the blood flow of the upper limb. The primary outcome measures were changes in neuropsychological assessments. The secondary outcomes included the changes in high-sensitive C-reactive protein (hs-CRP) concentration, white matter lesion volume (WMLV), diffusion tension imaging (DTI) metrics of white matter. All data were collected at baseline and follow-up. RESULTS A significant treatment difference favoring RIC at 6 months was observed on performance of Hopkins Verbal Learning Test-Revised (HVLT-R), Controlled Oral Word Association Test (COWAT), Trail Making Test A and B (TMT-A & TMT-B), and Judgment of Line Orientation (JLO) (p < 0.05). The control group did not show much improvement after the treatment, and only with a slight change in HVLT-R and TMT-R (p < 0.05). Covariance analysis of efficacy between the two groups suggested that RIC patients performed better on JLO than control patients at the 6-month follow-up (RIC 23.10 vs. control 18.56; p = 0.013). Although DTI metrics were comparable, Hs-CRP levels and WMLV in RIC patients showed a declining trend. CONCLUSIONS Over the 6-month treatment period, we found that RIC was safe and effective for improving cognitive function in SIVD patients. TRIAL REGISTRATION Clinical Trial Registration ( http://www.clinicaltrials.gov ), Unique identifier: NCT03022149; Retrospectively registered; Date of registration: January 16, 2017.
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80
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Liao Z, Dang C, Li M, Bu Y, Han R, Jiang W. Microstructural damage of normal-appearing white matter in subcortical ischemic vascular dementia is associated with Montreal Cognitive Assessment scores. J Int Med Res 2019; 47:5723-5731. [PMID: 31342825 PMCID: PMC6862888 DOI: 10.1177/0300060519863520] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
Objectives This study was performed to determine whether multimodal biomarkers are more strongly associated with the Montreal Cognitive Assessment (MoCA) scores compared with the Mini-Mental State Examination (MMSE) scores, and whether they are correlated with the Clinical Dementia Rating (CDR) in patients with subcortical ischemic vascular dementia (SIVD). Methods Patients diagnosed with SIVD were enrolled. Peripheral blood hypersensitive C-reactive protein, white matter lesion volume (WMLV), fractional anisotropy (FA)/mean diffusivity (MD) of whole brain white matter (WBWM), and normal-appearing white matter (NAWM) were measured and correlated with MMSE, MoCA, and CDR scores. Results Bivariate analyses of data from 48 included patients revealed that both MoCA and MMSE were significantly associated with age, education, and FA of NAWM. Only MD of NAWM was correlated with MoCA scores. In partial correlation analysis adjusted for demographic and neuroimaging variables, MD/FA of NAWM and the MoCA scores were significantly correlated. FA/MD of NAWM had a modest trend toward a correlation with the CDR, but it was not significant. Conclusions In the patients with SIVD, FA/MD of NAWM were more strongly related to MoCA scores compared with MMSE scores.
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Affiliation(s)
- Zhangyuan Liao
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China.,Tianjin Neurological Institute, Key Laboratory of Post-neurotrauma Neuro-repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
| | - Chun Dang
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China.,Tianjin Neurological Institute, Key Laboratory of Post-neurotrauma Neuro-repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
| | - Meijie Li
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China.,Tianjin Neurological Institute, Key Laboratory of Post-neurotrauma Neuro-repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
| | - Yali Bu
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China.,Tianjin Neurological Institute, Key Laboratory of Post-neurotrauma Neuro-repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
| | - Ranran Han
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China.,Tianjin Neurological Institute, Key Laboratory of Post-neurotrauma Neuro-repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
| | - Wei Jiang
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China.,Tianjin Neurological Institute, Key Laboratory of Post-neurotrauma Neuro-repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
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81
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Caunca MR, De Leon-Benedetti A, Latour L, Leigh R, Wright CB. Neuroimaging of Cerebral Small Vessel Disease and Age-Related Cognitive Changes. Front Aging Neurosci 2019; 11:145. [PMID: 31316367 PMCID: PMC6610261 DOI: 10.3389/fnagi.2019.00145] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2019] [Accepted: 05/31/2019] [Indexed: 01/04/2023] Open
Abstract
Subclinical cerebrovascular disease is frequently identified in neuroimaging studies and is thought to play a role in the pathogenesis of cognitive disorders. Identifying the etiologies of different types of lesions may help investigators differentiate between age-related and pathological cerebrovascular damage in cognitive aging. In this review article, we aim to describe the epidemiology and etiology of various brain magnetic resonance imaging (MRI) measures of vascular damage in cognitively normal, older adult populations. We focus here on population-based prospective cohort studies of cognitively unimpaired older adults, as well as discuss the heterogeneity of MRI findings and their relationships with cognition. This review article emphasizes the need for a better understanding of subclinical cerebrovascular disease in cognitively normal populations, in order to more effectively identify and prevent cognitive decline in our rapidly aging population.
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Affiliation(s)
- Michelle R Caunca
- Division of Epidemiology and Population Health Sciences, Department of Public Health Sciences, Leonard M. Miller School of Medicine, Evelyn F. McKnight Brain Institute, University of Miami, Miami, FL, United States.,Department of Neurology, Leonard M. Miller School of Medicine, University of Miami, Miami, FL, United States
| | - Andres De Leon-Benedetti
- Department of Neurology, Leonard M. Miller School of Medicine, University of Miami, Miami, FL, United States
| | - Lawrence Latour
- National Institute of Neurological Diseases and Stroke (NINDS), National Institutes of Health, Bethesda, MD, United States
| | - Richard Leigh
- National Institute of Neurological Diseases and Stroke (NINDS), National Institutes of Health, Bethesda, MD, United States
| | - Clinton B Wright
- National Institute of Neurological Diseases and Stroke (NINDS), National Institutes of Health, Bethesda, MD, United States
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82
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Luo DH, Tseng WYI, Chang YL. White matter microstructure disruptions mediate the adverse relationships between hypertension and multiple cognitive functions in cognitively intact older adults. Neuroimage 2019; 197:109-119. [PMID: 31029871 DOI: 10.1016/j.neuroimage.2019.04.063] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2019] [Revised: 04/23/2019] [Accepted: 04/23/2019] [Indexed: 01/01/2023] Open
Abstract
Although hypertension is a prominent vascular risk factor for late-life cognitive decline, the underlying pathophysiological mechanism remains unclear. Accordingly, the aim of this study was to examine the role of white matter microstructural integrity in hypertension-related cognitive detriments. We recruited 66 cognitively normal older adults, comprising 41 hypertensive patients and 25 normotensive controls. All participants underwent a comprehensive neuropsychological battery. White matter microstructural integrity was assessed using a tract-based automatic analysis approach derived from diffusion spectrum imaging. Mediating effects of white matter integrity were evaluated using structural equation modeling analyses. The results revealed that hypertensive older adults displayed poorer processing speed, executive function, and memory encoding. Lower white matter microstructural integrity was observed in the hypertensive elderly patients, primarily in long-range association fiber bundles. In particular, low microstructural integrity in specific tract bundles connecting frontal and posterior cerebral regions was found to underlie the adverse relationships between hypertension and multiple cognitive domains, including processing speed, executive function, memory encoding, and memory retention. Our findings suggest that hypertension may impair multiple cognitive functions by undermining white matter microstructures, even in cognitively intact older adults, thus further highlighting the necessity of monitoring vascular health to prevent cognitive decline.
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Affiliation(s)
- Di-Hua Luo
- Department of Psychology, College of Science, National Taiwan University, Taipei, 10617, Taiwan
| | - Wen-Yih Isaac Tseng
- Neurobiology and Cognitive Science Center, National Taiwan University, Taipei, 10617, Taiwan; Graduate Institute of Medical Device and Imaging, College of Medicine, National Taiwan University, Taipei, 10051, Taiwan; Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei, 10051, Taiwan; Department of Medical Imaging, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, 10048, Taiwan
| | - Yu-Ling Chang
- Department of Psychology, College of Science, National Taiwan University, Taipei, 10617, Taiwan; Neurobiology and Cognitive Science Center, National Taiwan University, Taipei, 10617, Taiwan; Center for Artificial Intelligence and Advanced Robotics, National Taiwan University, Taipei, 10617, Taiwan; Department of Neurology, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, 10048, Taiwan.
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83
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Du J, Xu Q. Neuroimaging studies on cognitive impairment due to cerebral small vessel disease. Stroke Vasc Neurol 2019; 4:99-101. [PMID: 31338220 PMCID: PMC6613873 DOI: 10.1136/svn-2018-000209] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2018] [Revised: 02/23/2019] [Accepted: 03/18/2019] [Indexed: 01/17/2023] Open
Abstract
Vascular cognitive impairment (VCI) is a major contributor to age-related dementing illnesses which imposes a tremendous burden on families and society. It is a heterogeneous group of brain disorders. However, cerebral small vessel disease (CSVD) accounts for about 50%-70% of VCI, which represented a more homogeneous subtype of VCI. Advanced multimodal neuroimaging techniques like brain network connectome analyses are currently applied to explore the underlying mechanism of VCI. Some progress in the field of structural and functional brain network researches on a poststroke longitudinal CSVD cohort (Renji CSVD Cohort Study) was reported. Global and regional brain network characters were compared between patients with CSVD and healthy control. It suggested that distributed brain structural network disruption may play a pivot role in the cognitive decline. The results showed that brain structural network characters have distinctive differentiating capacity on the cognition of patients with CSVD.
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Affiliation(s)
- Jing Du
- Neurology, Shanghai Jiao Tong University School of Medicine Affiliated Renji Hospital, Shanghai, China
| | - Qun Xu
- Health Manage Center, Shanghai Jiao Tong University School of Medicine Affiliated Renji Hospital, Shanghai, China
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84
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Raja R, Rosenberg G, Caprihan A. Review of diffusion MRI studies in chronic white matter diseases. Neurosci Lett 2019; 694:198-207. [PMID: 30528980 PMCID: PMC6380179 DOI: 10.1016/j.neulet.2018.12.007] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2018] [Revised: 12/03/2018] [Accepted: 12/04/2018] [Indexed: 02/07/2023]
Abstract
Diffusion MRI studies characterizing the changes in white matter (WM) due to vascular cognitive impairment, which includes all forms of small vessel disease are reviewed. We reviewed the usefulness of diffusion methods in discriminating the affected WM regions and its relation to cognitive impairment. These studies were categorized based on the diffusion MRI techniques used. The most common method was the diffusion tensor imaging, whereas other methods included diffusion weighted imaging, diffusion kurtosis imaging, intravoxel incoherent motion, and studies based on diffusion tractography. The diffusion measures showed correlation with cognitive scores and disease progression, with mean diffusivity being the most robust parameter. Future studies should focus on incorporating multi-compartment and higher order diffusion models, which can handle the presence of multiple and crossing fibers inside a voxel.
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Affiliation(s)
- Rajikha Raja
- The MIND Research Network, Albuquerque, NM, United States.
| | - Gary Rosenberg
- Department of Neurology, University of New Mexico Health Sciences Center, Albuquerque, NM, United States
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85
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Wei N, Deng Y, Yao L, Jia W, Wang J, Shi Q, Chen H, Pan Y, Yan H, Zhang Y, Wang Y. A Neuroimaging Marker Based on Diffusion Tensor Imaging and Cognitive Impairment Due to Cerebral White Matter Lesions. Front Neurol 2019; 10:81. [PMID: 30814973 PMCID: PMC6381840 DOI: 10.3389/fneur.2019.00081] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2018] [Accepted: 01/21/2019] [Indexed: 11/13/2022] Open
Abstract
Background: The peak width of skeletonized mean diffusivity (PSMD) is a new, fully automated, robust imaging marker for cerebral small vessel disease (SVD), strongly associated with processing speed. However, it has never been applied to cerebral white matter lesions (WMLs). Our study aimed to investigate the correlation between PSMD and cognition, particularly in the executive function of patients with WMLs. Methods: A total of 111 WML patients and 50 healthy controls (HCs) were enrolled, and their demographic information and cardiovascular disease risk factors were recorded. Subjects were divided into three groups: WMLs with normal cognition (WMLs-NC), WMLs with vascular cognitive impairment (WMLs-VCI), and HCs. They underwent conventional head magnetic resonance imaging and diffusion tensor imaging (DTI), followed by neuropsychological and psychological examinations, including the Montreal Cognitive Assessment (MoCA), and the executive function tests. We compared executive function and PSMD among the three groups and analyzed the correlation between PSMD and cognitive function in all subjects. Results: There were no significant differences in demographic characteristics (age, sex, education level, and cardiovascular disease risk factors) among the three groups (P > 0.05), but there were significant differences in global cognition (P < 0.0001), executive function (P < 0.0001), and PSMD (P < 0.0001). The average PSMD value (×10-4 mm2/s) was 2.40 ± 0.23, 2.68 ± 0.30, and 4.51 ± 0.39 in the HC, WMLs-NC, and WMLs-VCI groups, respectively. There was no correlation between PSMD and cognition in the HC group, but PSMD was significantly correlated with MoCA scores (r = -0.3785, P < 0.0001) and executive function (r = -0.4744, P < 0.0001) in the WMLs-NC group and in the WMLs-VCI group (r = -0.4448, P < 0.0001 and r = -0.6279, P < 0.0001, respectively). Conclusions: WML patients have higher PSMD and worse cognitive performance than HCs, and PSMD is strongly associated with global cognition and executive functions in WML patients. This result provides new insights into the pathophysiology of cognitive impairment in WML patients. PSMD could be a surrogate marker for disease progression and could thus be used in therapeutic trials involving WML patients.
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Affiliation(s)
- Na Wei
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, China
| | - Yiming Deng
- China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China.,Department of Interventional Neuroradiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Li Yao
- College of Information Science and Technology, Beijing Normal University, Beijing, China
| | - Weili Jia
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jinfang Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Department of Neurology, General Hospital of The Yang Tze River Shipping, Wuhan Brain Hospital, Wuhan, China
| | - Qingli Shi
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Hongyan Chen
- Department of Neuroimaging, Beijing Neurosurgery Institute, Capital Medical University, Beijing, China
| | - Yuesong Pan
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Hongyi Yan
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yumei Zhang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, China
| | - Yongjun Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, China
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86
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Zacharzewska-Gondek A, Pokryszko-Dragan A, Gondek TM, Kołtowska A, Gruszka E, Budrewicz S, Sąsiadek M, Bladowska J. Apparent diffusion coefficient measurements in normal appearing white matter may support the differential diagnosis between multiple sclerosis lesions and other white matter hyperintensities. J Neurol Sci 2019; 397:24-30. [DOI: 10.1016/j.jns.2018.12.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2018] [Revised: 11/30/2018] [Accepted: 12/13/2018] [Indexed: 10/27/2022]
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87
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Liu X, Cheng R, Chen L, Luo T, Lv F, Gong J, Jiang P. Alterations of White Matter Integrity in Subcortical Ischemic Vascular Disease with and Without Cognitive Impairment: a TBSS Study. J Mol Neurosci 2019; 67:595-603. [PMID: 30685818 DOI: 10.1007/s12031-019-01266-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2018] [Accepted: 01/17/2019] [Indexed: 10/27/2022]
Abstract
Patients with subcortical ischemic vascular disease (SIVD) may exhibit a high risk of cognitive impairment (CI) by disruption of white matter (WM) integrity. Diffusion tensor imaging (DTI) is recommended as a sensitive method to explore whole brain WM alterations at an asymptomatic stage of the disease, which might be correlated with underlying cognitive disorders. We aim to investigate alterations in WM microstructures and evaluate the relationships between the mean values of diffusion metrics (FA, MD, AD, and RD) and cognitive assessments in SIVD patients. Fifty SIVD patients with (SVCI, N = 25) and without (pre-SVCI, N = 25) cognitive impairments and normal controls (NC, N = 23) underwent DTI and neuropsychological examinations. DTI data were analyzed via TBSS to detect significant changes in WM tracts. Spearman correlation analysis was performed to evaluate relationships between the mean values of diffusion indices and the cognitive assessments. In general, extensive symmetrically altered areas that involved approximately the entire cerebral WM were noted in the pre-SVCI group but were less distinct than that noted in the SVCI group compared with NCs. The genu of corpus callosum exhibited the most damaged WM fiber. Throughout WM, FA was decreased, whereas MD, AD, and RD were increased. Some specific WM tracts in patient groups were significantly correlated with the severity of white matter hyperintensity (WMH), cognitive assessments about executive functions and processing speed. WM integrity has already been damaged at the pre-SVCI stage, which would be associate with future cognitive dysfunction. DTI could potentially establish early biomarkers to detect underlying mechanisms of SIVD.
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Affiliation(s)
- Xiaoshuang Liu
- The Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Runtian Cheng
- The Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Li Chen
- The Department of Radiology, The Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Tianyou Luo
- The Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
| | - FaJin Lv
- The Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Junwei Gong
- The Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Peiling Jiang
- The Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
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88
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Abstract
In a somewhat narrow diagnostic lens, Alzheimer disease (AD) has been considered a brain-specific disease characterized by the presence of Aβ (β-amyloid) plaques and tau neural fibrillary tangles and neural inflammation; these pathologies lead to neuronal death and consequently clinical symptoms, such as memory loss, confusion, and impaired cognitive function. However, for decades, researchers have noticed a link between various cardiovascular abnormalities and AD-such as heart failure, coronary artery disease, atrial fibrillation, and vasculopathy. A considerable volume of work has pointed at this head to heart connection, focusing mainly on associations between cerebral hypoperfusion and neuronal degradation. However, new evidence of a possible systemic or metastatic profile to AD calls for further analysis of this connection. Aβ aggregations-biochemically and structurally akin to those found in the typical AD pathology-are now known to be present in the hearts of individuals with idiopathic dilated cardiomyopathy, as well as the hearts of patients with AD. These findings suggest a potential systemic profile of proteinopathies and a new hypothesis for the link between peripheral and central symptoms of heart failure and AD. Herein, we provide an overview of the cardiovascular links to Alzheimer disease.
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Affiliation(s)
- Joshua M Tublin
- From the College of Nursing (J.M.T., J.M.A., L.E.W.), The Ohio State University, Columbus
| | - Jeremy M Adelstein
- From the College of Nursing (J.M.T., J.M.A., L.E.W.), The Ohio State University, Columbus
| | | | - Colin K Combs
- Department of Biomedical Sciences, University of North Dakota, Grand Forks (C.K.C.)
| | - Loren E Wold
- From the College of Nursing (J.M.T., J.M.A., L.E.W.), The Ohio State University, Columbus
- Department of Physiology and Cell Biology, College of Medicine (L.E.W.), The Ohio State University, Columbus
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89
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Characteristic changes in the default mode network in hypertensive patients with cognitive impairment. Hypertens Res 2018; 42:530-540. [PMID: 30573810 DOI: 10.1038/s41440-018-0176-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2018] [Revised: 08/24/2018] [Accepted: 09/17/2018] [Indexed: 02/04/2023]
Abstract
Hypertension has a close affinity to brain degeneration and cognitive decline during the aging process. The default mode network (DMN) is usually affected in various diseases related to cognitive impairment (CI). The present research aimed to explore the alterations in the DMN and its subcomponents in hypertensive patients with and without CI and to investigate the associations between cognitive performance and network abnormalities. Resting-state functional magnetic resonance imaging and neuropsychological tests were performed in 74 subjects, namely, 30 hypertensive patients with normal cognition (HTN-NC), 25 hypertensive patients with CI (HTN-CI), and 19 healthy controls. Seed-based functional connectivity (FC) analysis was performed to identify the DMN patterns. The group differences in the DMN were mainly shown in brain regions related to the core subsystem and the dorsal medial subsystem of the DMN. Post hoc analysis revealed a trend of dissociation among the DMN subsystems in the HTN-NC group. In contrast, the HTN-CI group displayed extensively increased FC in both subsystems. Importantly, increased FC of the dorsal medial subsystem in the HTN-CI patients was associated with poor cognitive performance, such as scores on Mini-Mental State Examination (ρ = -0.438, P = 0.029) and Montreal Cognitive Assessment (ρ = -0.449, P = 0.025). The findings suggest that extensively increased connectivities in the core subsystem and the dorsal media subsystem of the DMN may distinguish hypertension with CI from hypertension with normal cognition. The characteristic change in the dorsal medial subsystem may become an early imaging biomarker for the diagnosis and treatment of cognitive impairment associated with hypertension.
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90
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Redmond KJ, Hildreth M, Sair HI, Terezakis S, McNutt T, Kleinberg L, Cohen KJ, Wharam M, Horska A, Mahone EM. Association of Neuronal Injury in the Genu and Body of Corpus Callosum After Cranial Irradiation in Children With Impaired Cognitive Control: A Prospective Study. Int J Radiat Oncol Biol Phys 2018; 101:1234-1242. [PMID: 29908790 PMCID: PMC6050077 DOI: 10.1016/j.ijrobp.2018.04.037] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2017] [Revised: 03/01/2018] [Accepted: 04/15/2018] [Indexed: 11/16/2022]
Abstract
PURPOSE Brain radiation is associated with functional deficits in children. The purpose of this study was to examine white matter integrity as measured by diffusion tensor imaging and associations with region-specific radiation dose and neuropsychological functioning in children treated with cranial irradiation. METHODS AND MATERIALS A total of 20 patients and 55 age- and sex-matched controls were included in the present study. Diffusion tensor imaging and neuropsychological assessments were conducted at baseline and 6, 15, and 27 months after treatment. The neuropsychological assessment included motor dexterity, working memory, and processing speed. White matter regions were contoured, and the apparent diffusion coefficient (ADC) and fractional anisotropy (FA) were recorded for each participant. Linear mixed effects regression models were used to prospectively compare the associations among ADC, FA, radiation dose to contoured structures, and performance on the neuropsychological assessments over time. RESULTS The mean prescription dose was 44 Gy (range 12-54). Across visits, compared with the controls, the patients showed a significantly increased ADC across all selected regions and alterations in FA in the dorsal midbrain and corpus callosum (genu, splenium, body). An increased radiation dose to the genu and body of the corpus callosum was associated with alterations in ADC and FA and reduced neuropsychological performance, most notably motor speed and processing. CONCLUSIONS These prospective data suggest that subcortical white matter, especially the genu and body of the corpus callosum, could be regions with increased susceptibility to radiation-induced injury, with implications for cognitive function.
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Affiliation(s)
- Kristin J. Redmond
- Department of Radiation Oncology and Molecular Radiation Sciences, The Johns Hopkins University,Corresponding author: Kristin J. Redmond, 401 North Broadway, Suite 1440, Baltimore, MD 21231, , Phone: 410-614-1642, Fax: 410-502-1419
| | - Meghan Hildreth
- Department of Radiation Oncology and Molecular Radiation Sciences, The Johns Hopkins University
| | - Haris I. Sair
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University
| | - Stephanie Terezakis
- Department of Radiation Oncology and Molecular Radiation Sciences, The Johns Hopkins University
| | - Todd McNutt
- Department of Radiation Oncology and Molecular Radiation Sciences, The Johns Hopkins University
| | - Lawrence Kleinberg
- Department of Radiation Oncology and Molecular Radiation Sciences, The Johns Hopkins University
| | - Kenneth J. Cohen
- Division of Pediatric Oncology, The Sidney Kimmel Comprehensive Cancer Center
| | - Moody Wharam
- Department of Radiation Oncology and Molecular Radiation Sciences, The Johns Hopkins University
| | - Alena Horska
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University
| | - E. Mark Mahone
- Department of Neuropsychology, Kennedy Krieger Institute
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Chen HJ, Gao YQ, Che CH, Lin H, Ruan XL. Diffusion Tensor Imaging With Tract-Based Spatial Statistics Reveals White Matter Abnormalities in Patients With Vascular Cognitive Impairment. Front Neuroanat 2018; 12:53. [PMID: 29997482 PMCID: PMC6028522 DOI: 10.3389/fnana.2018.00053] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2018] [Accepted: 06/04/2018] [Indexed: 11/26/2022] Open
Abstract
Purpose: The aim of this study was to evaluate microstructural changes of major white matter (WM) tracts in patients with vascular cognitive impairment (VCI). Method: Diffusion tensor imaging (DTI) data were obtained from 24 subjects with subcortical ischemic vascular disease (SIVD), including 13 subjects with VCI-no dementia (VCIND) and 11 subjects with normal cognition (as a control group). A tract-based spatial statistics approach was performed to investigate WM microstructure in VCIND by integrating multiple indices including fractional anisotropy (FA) and mean diffusivity (MD), which are intra-voxel metrics, and local diffusion homogeneity (LDH), which is an inter-voxel metric. Results: The VCIND group had decreased FA and increased MD values throughout widespread WM areas predominately in the corpus callosum, bilateral internal capsule/corona radiata/posterior thalamic radiation/inferior fronto-occipital fasciculus and right inferior/superior longitudinal fasciculus. There was a slight discrepancy between the distribution of areas with decreased FA and LDH. The FA, MD and LDH values were significantly correlated with cognitive test results. According to a WM tract atlas, 10 major tracts were identified as tracts of interest in which three diffusion metrics simultaneously differed between groups, including bilateral anterior thalamic radiation, forceps minor, right corticospinal tract, bilateral inferior fronto-occipital fasciculus, left inferior and superior longitudinal fasciculus, and bilateral uncinate fasciculus. Receiver operating characteristic (ROC) analysis demonstrated the feasibility of using diffusion metrics along the forceps minor and left anterior thalamic radiation for separating two groups. Conclusion: The results suggest WM microstructural abnormalities contribute to cognitive impairments in SIVD patients. DTI parameters may be potential biomarkers for detecting VCIND from SIVD.
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Affiliation(s)
- Hua-Jun Chen
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Yong-Qing Gao
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China.,Department of Radiology, Fuqing City Hospital, Fuqing, China
| | - Chun-Hui Che
- Department of Neurology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Hailong Lin
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Xin-Lin Ruan
- Department of Geriatrics, Fujian Medical University Union Hospital, Fuzhou, China
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92
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Heinen R, Vlegels N, de Bresser J, Leemans A, Biessels GJ, Reijmer YD. The cumulative effect of small vessel disease lesions is reflected in structural brain networks of memory clinic patients. NEUROIMAGE-CLINICAL 2018; 19:963-969. [PMID: 30003033 PMCID: PMC6039838 DOI: 10.1016/j.nicl.2018.06.025] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/14/2018] [Revised: 05/23/2018] [Accepted: 06/17/2018] [Indexed: 01/16/2023]
Abstract
Background and purpose Mechanisms underlying cognitive impairment in patients with small vessel disease (SVD) are still unknown. We hypothesized that cognition is affected by the cumulative effect of multiple SVD-related lesions on brain connectivity. We therefore assessed the relationship between the total SVD burden on MRI, global brain network efficiency, and cognition in memory clinic patients with vascular brain injury. Methods 173 patients from the memory clinic of the University Medical Center Utrecht underwent a 3 T brain MRI scan (including diffusion MRI sequences) and neuropsychological testing. MRI markers for SVD were rated and compiled in a previously developed total SVD score. Structural brain networks were reconstructed using fiber tractography followed by graph theoretical analysis. The relationship between total SVD burden score, global network efficiency and cognition was assessed using multiple linear regression analyses. Results Each point increase on the SVD burden score was associated with 0.260 [−0.404 - -0.117] SD units decrease of global brain network efficiency (p < .001). Global network efficiency was associated with information processing speed (standardized B = −0.210, p = .004) and attention and executive functioning (B = 0.164, p = .042), and mediated the relationship between SVD burden and information processing speed (p = .027) but not with executive functioning (p = .12). Conclusion Global network efficiency is sensitive to the cumulative effect of multiple manifestations of SVD on brain connectivity. Global network efficiency may therefore serve as a useful marker for functionally relevant SVD-related brain injury in clinical trials. Increasing small vessel disease burden (SVD) related to decreasing network efficiency. Network efficiency mediates association between SVD burden and processing speed. Cumulative effect of SVD might partly affect cognition through disrupted connectivity.
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Affiliation(s)
- Rutger Heinen
- Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Naomi Vlegels
- Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
| | - Jeroen de Bresser
- Department of Radiology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands; Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Alexander Leemans
- Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Geert Jan Biessels
- Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Yael D Reijmer
- Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
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93
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Duering M, Finsterwalder S, Baykara E, Tuladhar AM, Gesierich B, Konieczny MJ, Malik R, Franzmeier N, Ewers M, Jouvent E, Biessels GJ, Schmidt R, de Leeuw FE, Pasternak O, Dichgans M. Free water determines diffusion alterations and clinical status in cerebral small vessel disease. Alzheimers Dement 2018; 14:764-774. [PMID: 29406155 PMCID: PMC5994358 DOI: 10.1016/j.jalz.2017.12.007] [Citation(s) in RCA: 84] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2017] [Revised: 12/16/2017] [Accepted: 12/19/2017] [Indexed: 10/18/2022]
Abstract
INTRODUCTION Diffusion tensor imaging detects early tissue alterations in Alzheimer's disease and cerebral small vessel disease (SVD). However, the origin of diffusion alterations in SVD is largely unknown. METHODS To gain further insight, we applied free water (FW) imaging to patients with genetically defined SVD (Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy [CADASIL], n = 57), sporadic SVD (n = 444), and healthy controls (n = 28). We modeled freely diffusing water in the extracellular space (FW) and measures reflecting fiber structure (tissue compartment). We tested associations between these measures and clinical status (processing speed and disability). RESULTS Diffusion alterations in SVD were mostly driven by increased FW and less by tissue compartment alterations. Among imaging markers, FW showed the strongest association with clinical status (R2 up to 34%, P < .0001). Findings were consistent across patients with CADASIL and sporadic SVD. DISCUSSION Diffusion alterations and clinical status in SVD are largely determined by extracellular fluid increase rather than alterations of white matter fiber organization.
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Affiliation(s)
- Marco Duering
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany.
| | - Sofia Finsterwalder
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany
| | - Ebru Baykara
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany
| | - Anil Man Tuladhar
- Department of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
| | - Benno Gesierich
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany
| | - Marek J Konieczny
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany
| | - Rainer Malik
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany
| | - Nicolai Franzmeier
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany
| | - Michael Ewers
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany
| | - Eric Jouvent
- Univ Paris Diderot, DHU NeuroVasc Sorbonne Paris Cité, UMR-S 1161 INSERM, Paris, France; Department of Neurology, Assistance publique - hôpitaux de Paris (AP-HP), Lariboisière Hospital, Paris, France
| | - Geert Jan Biessels
- Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Reinhold Schmidt
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Frank-Erik de Leeuw
- Department of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
| | - Ofer Pasternak
- Departments of Psychiatry and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Martin Dichgans
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany; German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
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94
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Rutten-Jacobs LC, Tozer DJ, Duering M, Malik R, Dichgans M, Markus HS, Traylor M. Genetic Study of White Matter Integrity in UK Biobank (N=8448) and the Overlap With Stroke, Depression, and Dementia. Stroke 2018; 49:1340-1347. [PMID: 29752348 PMCID: PMC5976227 DOI: 10.1161/strokeaha.118.020811] [Citation(s) in RCA: 54] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2018] [Revised: 04/12/2018] [Accepted: 04/19/2018] [Indexed: 12/29/2022]
Abstract
BACKGROUND AND PURPOSE Structural integrity of the white matter is a marker of cerebral small vessel disease, which is the major cause of vascular dementia and a quarter of all strokes. Genetic studies provide a way to obtain novel insights in the disease mechanism underlying cerebral small vessel disease. The aim was to identify common variants associated with microstructural integrity of the white matter and to elucidate the relationships of white matter structural integrity with stroke, major depressive disorder, and Alzheimer disease. METHODS This genome-wide association analysis included 8448 individuals from UK Biobank-a population-based cohort study that recruited individuals from across the United Kingdom between 2006 and 2010, aged 40 to 69 years. Microstructural integrity was measured as fractional anisotropy- (FA) and mean diffusivity (MD)-derived parameters on diffusion tensor images. White matter hyperintensity volumes (WMHV) were assessed on T2-weighted fluid-attenuated inversion recovery images. RESULTS We identified 1 novel locus at genome-wide significance (VCAN [versican]: rs13164785; P=3.7×10-18 for MD and rs67827860; P=1.3×10-14 for FA). LD score regression showed a significant genome-wide correlation between FA, MD, and WMHV (FA-WMHV rG 0.39 [SE, 0.15]; MD-WMHV rG 0.56 [SE, 0.19]). In polygenic risk score analysis, FA, MD, and WMHV were significantly associated with lacunar stroke, MD with major depressive disorder, and WMHV with Alzheimer disease. CONCLUSIONS Genetic variants within the VCAN gene may play a role in the mechanisms underlying microstructural integrity of the white matter in the brain measured as FA and MD. Mechanisms underlying white matter alterations are shared with cerebrovascular disease, and inherited differences in white matter microstructure impact on Alzheimer disease and major depressive disorder.
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Affiliation(s)
- Loes C.A. Rutten-Jacobs
- From the Department of Clinical Neurosciences, Stroke Research Group, University of Cambridge, United Kingdom (L.C.A.R.-J., D.J.T., H.S.M., M.T.),German Center for Neurodegenerative Diseases, Population Health Sciences, Bonn, Germany (L.C.A.R.-J.)
| | - Daniel J. Tozer
- From the Department of Clinical Neurosciences, Stroke Research Group, University of Cambridge, United Kingdom (L.C.A.R.-J., D.J.T., H.S.M., M.T.)
| | - Marco Duering
- Institute for Stroke and Dementia Research, Klinikum der Universität München, Germany (M. Duering, R.M., M. Dichgans)
| | - Rainer Malik
- Institute for Stroke and Dementia Research, Klinikum der Universität München, Germany (M. Duering, R.M., M. Dichgans)
| | - Martin Dichgans
- Institute for Stroke and Dementia Research, Klinikum der Universität München, Germany (M. Duering, R.M., M. Dichgans)
| | - Hugh S. Markus
- From the Department of Clinical Neurosciences, Stroke Research Group, University of Cambridge, United Kingdom (L.C.A.R.-J., D.J.T., H.S.M., M.T.)
| | - Matthew Traylor
- From the Department of Clinical Neurosciences, Stroke Research Group, University of Cambridge, United Kingdom (L.C.A.R.-J., D.J.T., H.S.M., M.T.)
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95
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Banerjee G, Jang H, Kim HJ, Kim ST, Kim JS, Lee JH, Im K, Kwon H, Lee JM, Na DL, Seo SW, Werring DJ. Total MRI Small Vessel Disease Burden Correlates with Cognitive Performance, Cortical Atrophy, and Network Measures in a Memory Clinic Population. J Alzheimers Dis 2018; 63:1485-1497. [DOI: 10.3233/jad-170943] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Gargi Banerjee
- Stroke Research Centre, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology and the National Hospital for Neurology and Neurosurgery, London, UK
| | - Hyemin Jang
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Republic of Korea
| | - Hee Jin Kim
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, Republic of Korea
| | - Sung Tae Kim
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Jae Seung Kim
- Department of Nuclear Medicine, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Jae Hong Lee
- Department of Neurology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Kiho Im
- Division of Newborn Medicine, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Hunki Kwon
- Department of Biomedical Engineering, Hanyang University, Seoul, Republic of Korea
| | - Jong Min Lee
- Department of Biomedical Engineering, Hanyang University, Seoul, Republic of Korea
| | - Duk L. Na
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, Republic of Korea
| | - Sang Won Seo
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, Republic of Korea
| | - David John Werring
- Stroke Research Centre, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology and the National Hospital for Neurology and Neurosurgery, London, UK
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96
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Mascalchi M, Salvadori E, Toschi N, Giannelli M, Orsolini S, Ciulli S, Ginestroni A, Poggesi A, Giorgio A, Lorenzini F, Pasi M, De Stefano N, Pantoni L, Inzitari D, Diciotti S. DTI-derived indexes of brain WM correlate with cognitive performance in vascular MCI and small-vessel disease. A TBSS study. Brain Imaging Behav 2018; 13:594-602. [DOI: 10.1007/s11682-018-9873-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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97
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Zhu H, Li Z, Lv J, Zhao R. Effects of cerebral small vessel disease on the outcome of patients with ischemic stroke caused by large artery atherosclerosis. Neurol Res 2018. [PMID: 29543130 DOI: 10.1080/01616412.2018.1446283] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Affiliation(s)
- Hui Zhu
- Medical College, Qingdao University, Qingdao, China
| | - Zhixing Li
- Medical College, Qingdao University, Qingdao, China
| | - Jinglei Lv
- Department of Neurology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Renliang Zhao
- Department of Neurology, The Affiliated Hospital of Qingdao University, Qingdao, China
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98
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Ye Q, Bai F. Contribution of diffusion, perfusion and functional MRI to the disconnection hypothesis in subcortical vascular cognitive impairment. Stroke Vasc Neurol 2018; 3:131-139. [PMID: 30294468 PMCID: PMC6169607 DOI: 10.1136/svn-2017-000080] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2017] [Revised: 01/26/2018] [Accepted: 02/14/2018] [Indexed: 11/29/2022] Open
Abstract
Vascular cognitive impairment (VCI) describes all forms of cognitive impairment caused by any type of cerebrovascular disease. Early identification of VCI is quite difficult due to the lack of both sensitive and specific biomarkers. Extensive damage to the white matter tracts, which connect the cortical and subcortical regions, has been shown in subcortical VCI (SVCI), the most common subtype of VCI that is caused by small vessel disease. Two specific MRI sequences, including diffusion tensor imaging (DTI) and functional MRI (fMRI), have emerged as useful tools for identifying subtle white matter changes and the intrinsic connectivity between distinct cortical regions. This review describes the advantages of these two modalities in SVCI research and the current DTI and fMRI findings on SVCI. Using DTI technique, a variety of studies found that white matter microstructural damages in the anterior and superior areas are more specific to SVCI. Similarly, functional brain abnormalities detected by fMRI have also been mainly shown in anterior brain areas in SVCI. The characteristic distribution of brain abnormalities in SVCI interrupts the prefrontal-subcortical loop that results in cognitive impairments in particular domains, which further confirms the ‘disconnection syndrome’ hypothesis. In addition, another MRI technique, arterial spin labelling (ASL), has been used to describe the disconnection patterns in a variety of conditions by measuring cerebral blood flow. The role of the ASL technique in SVCI research is also assessed. Finally, the review proposes the application of multimodality fusion in the investigation of SVCI pathogenesis.
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Affiliation(s)
- Qing Ye
- Department of Neurology, Affiliated Drum Tower Hospital, Nanjing University Medical School, Nanjing, Jiangsu, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Nanjing University Medical School, Nanjing, China
| | - Feng Bai
- Department of Neurology, Affiliated Drum Tower Hospital, Nanjing University Medical School, Nanjing, Jiangsu, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Nanjing University Medical School, Nanjing, China
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99
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Hirsiger S, Koppelmans V, Mérillat S, Erdin C, Narkhede A, Brickman AM, Jäncke L. Executive Functions in Healthy Older Adults Are Differentially Related to Macro- and Microstructural White Matter Characteristics of the Cerebral Lobes. Front Aging Neurosci 2017; 9:373. [PMID: 29249957 PMCID: PMC5715235 DOI: 10.3389/fnagi.2017.00373] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2017] [Accepted: 10/31/2017] [Indexed: 01/13/2023] Open
Abstract
Aging is associated with microstructural white matter (WM) changes. WM microstructural characteristics, measured with diffusion tensor imaging (DTI), are different in normal appearing white matter (NAWM) and WM hyperintensities (WMH). It is largely unknown how the microstructural properties of WMH are associated with cognition and if there are regional effects for specific cognitive domains. We therefore examined within 200 healthy older participants (a) differences in microstructural characteristics of NAWM and WMH per cerebral lobe; and (b) the association of macrostructural (WMH volume) and microstructural characteristics (within NAWM and WMH separately) of each lobe with measures of executive function and processing speed. Multi-modal imaging (i.e., T1, DTI, and FLAIR) was used to assess WM properties. The Stroop and the Trail Making Test were used to measure inhibition, task-switching (both components of executive function), and processing speed. We observed that age was associated with deterioration of white matter microstructure of the NAWM, most notably in the frontal lobe. Older participants had larger WMH volumes and lowest fractional anisotropy values within WMH were found in the frontal lobe. Task-switching was associated with cerebral NAWM volume and NAWM volume of all lobes. Processing speed was associated with total NAWM volume, and microstructural properties of parietal NAWM, the parietal WMH, and the temporal NAWM. Task-switching was related to microstructural properties of WMH of the frontal lobe and WMH volume of the parietal lobe. Our results confirm that executive functioning and processing speed are uniquely associated with macro- and microstructural properties of NAWM and WMH. We further demonstrate for the first time that these relationships differ by lobar region. This warrants the consideration of these distinct WM indices when investigating cognitive function.
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Affiliation(s)
- Sarah Hirsiger
- International Normal Aging and Plasticity Imaging Center, University of Zurich, Zurich, Switzerland.,University Research Priority Program Dynamics of Healthy Aging, University of Zurich, Zurich, Switzerland
| | - Vincent Koppelmans
- Department of Psychiatry, University of Utah, Salt Lake City, UT, United States.,School of Kinesiology, University of Michigan, Ann Arbor, MI, United States
| | - Susan Mérillat
- International Normal Aging and Plasticity Imaging Center, University of Zurich, Zurich, Switzerland.,University Research Priority Program Dynamics of Healthy Aging, University of Zurich, Zurich, Switzerland
| | - Cornelia Erdin
- International Normal Aging and Plasticity Imaging Center, University of Zurich, Zurich, Switzerland.,University Research Priority Program Dynamics of Healthy Aging, University of Zurich, Zurich, Switzerland
| | - Atul Narkhede
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, NY, United States
| | - Adam M Brickman
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, NY, United States
| | - Lutz Jäncke
- International Normal Aging and Plasticity Imaging Center, University of Zurich, Zurich, Switzerland.,University Research Priority Program Dynamics of Healthy Aging, University of Zurich, Zurich, Switzerland.,Division of Neuropsychology, University of Zurich, Zurich, Switzerland.,Department of Special Education, King Abdulaziz University, Jeddah, Saudi Arabia
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100
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D'Souza MM, Gorthi SP, Vadwala K, Trivedi R, Vijayakumar C, Kaur P, Khushu S. Diffusion tensor tractography in cerebral small vessel disease: correlation with cognitive function. Neuroradiol J 2017; 31:83-89. [PMID: 29027841 DOI: 10.1177/1971400916682753] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
Background Patients with cerebral small vessel disease may suffer from varying levels of cognitive deficit and may progress on to vascular dementia. The extent of involvement, as seen on conventional magnetic resonance (MR) measures, correlates poorly with the level of cognitive decline. The purpose of this study was to investigate the utility of diffusion tensor imaging (DTI) as a marker for white matter damage in small vessel disease and to assess its correlation with cognitive function. Methods Thirty consecutive patients with cerebral small vessel disease underwent conventional MR imaging, DTI, and neuropsychological assessment. Results On tractographic analysis, fractional anisotropy was significantly reduced while mean diffusivity significantly increased in several white matter tracts. The alteration in DTI indices correlated well with cognitive function. No significant correlation was identified between T2 lesion load and cognitive performance. Conclusions Tractographic analysis of white matter integrity is a useful measure of disease severity and correlates well with cognitive function. It may have a significant potential in monitoring disease progression and may serve as a surrogate marker for treatment trials.
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Affiliation(s)
- Maria M D'Souza
- 1 Institute of Nuclear Medicine & Allied Sciences, Delhi, India
| | - S P Gorthi
- 2 Department of Neurology, Kasturba Medical College, Manipal Karnataka, India
| | - Kunal Vadwala
- 1 Institute of Nuclear Medicine & Allied Sciences, Delhi, India
| | - Richa Trivedi
- 1 Institute of Nuclear Medicine & Allied Sciences, Delhi, India
| | - C Vijayakumar
- 1 Institute of Nuclear Medicine & Allied Sciences, Delhi, India
| | - Prabhjot Kaur
- 1 Institute of Nuclear Medicine & Allied Sciences, Delhi, India
| | - Subash Khushu
- 1 Institute of Nuclear Medicine & Allied Sciences, Delhi, India
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