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Stanzione R, Pietrangelo D, Cotugno M, Forte M, Rubattu S. Role of autophagy in ischemic stroke: insights from animal models and preliminary evidence in the human disease. Front Cell Dev Biol 2024; 12:1360014. [PMID: 38590779 PMCID: PMC10999556 DOI: 10.3389/fcell.2024.1360014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Accepted: 03/13/2024] [Indexed: 04/10/2024] Open
Abstract
Stroke represents a main cause of death and permanent disability worldwide. The molecular mechanisms underlying cerebral injury in response to the ischemic insults are not completely understood. In this article, we summarize recent evidence regarding the role of autophagy in the pathogenesis of ischemic stroke by reviewing data obtained in murine models of either transient or permanent middle cerebral artery occlusion, and in the stroke-prone spontaneously hypertensive rat. Few preliminary observational studies investigating the role of autophagy in subjects at high cerebrovascular risk and in cohorts of stroke patients were also reviewed. Autophagy plays a dual role in neuronal and vascular cells by exerting both protective and detrimental effects depending on its level, duration of stress and type of cells involved. Protective autophagy exerts adaptive mechanisms which reduce neuronal loss and promote survival. On the other hand, excessive activation of autophagy leads to neuronal cell death and increases brain injury. In conclusion, the evidence reviewed suggests that a proper manipulation of autophagy may represent an interesting strategy to either prevent or reduce brain ischemic injury.
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Affiliation(s)
| | - Donatella Pietrangelo
- Clinical and Molecular Medicine Department, School of Medicine and Psychology, Sapienza University of Rome, Rome, Italy
| | | | | | - Speranza Rubattu
- IRCCS Neuromed, Pozzilli, Italy
- Clinical and Molecular Medicine Department, School of Medicine and Psychology, Sapienza University of Rome, Rome, Italy
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Marzi C, Scheda R, Salvadori E, Giorgio A, De Stefano N, Poggesi A, Inzitari D, Pantoni L, Mascalchi M, Diciotti S. Fractal dimension of the cortical gray matter outweighs other brain MRI features as a predictor of transition to dementia in patients with mild cognitive impairment and leukoaraiosis. Front Hum Neurosci 2023; 17:1231513. [PMID: 37822707 PMCID: PMC10562576 DOI: 10.3389/fnhum.2023.1231513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 08/31/2023] [Indexed: 10/13/2023] Open
Abstract
Background The relative contribution of changes in the cerebral white matter (WM) and cortical gray matter (GM) to the transition to dementia in patients with mild cognitive impairment (MCI) is not yet established. In this longitudinal study, we aimed to analyze MRI features that may predict the transition to dementia in patients with MCI and T2 hyperintensities in the cerebral WM, also known as leukoaraiosis. Methods Sixty-four participants with MCI and moderate to severe leukoaraiosis underwent baseline MRI examinations and annual neuropsychological testing over a 2 year period. The diagnosis of dementia was based on established criteria. We evaluated demographic, neuropsychological, and several MRI features at baseline as predictors of the clinical transition. The MRI features included visually assessed MRI features, such as the number of lacunes, microbleeds, and dilated perivascular spaces, and quantitative MRI features, such as volumes of the cortical GM, hippocampus, T2 hyperintensities, and diffusion indices of the cerebral WM. Additionally, we examined advanced quantitative features such as the fractal dimension (FD) of cortical GM and WM, which represents an index of tissue structural complexity derived from 3D-T1 weighted images. To assess the prediction of transition to dementia, we employed an XGBoost-based machine learning system using SHapley Additive exPlanations (SHAP) values to provide explainability to the machine learning model. Results After 2 years, 18 (28.1%) participants had transitioned from MCI to dementia. The area under the receiving operator characteristic curve was 0.69 (0.53, 0.85) [mean (90% confidence interval)]. The cortical GM-FD emerged as the top-ranking predictive feature of transition. Furthermore, aggregated quantitative neuroimaging features outperformed visually assessed MRI features in predicting conversion to dementia. Discussion Our findings confirm the complementary roles of cortical GM and WM changes as underlying factors in the development of dementia in subjects with MCI and leukoaraiosis. FD appears to be a biomarker potentially more sensitive than other brain features.
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Affiliation(s)
- Chiara Marzi
- Department of Statistics, Computer Science, Applications "Giuseppe Parenti, " University of Florence, Florence, Italy
| | - Riccardo Scheda
- Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi, " University of Bologna, Cesena, Italy
| | - Emilia Salvadori
- NEUROFARBA Department, Neuroscience Section, University of Florence, Florence, Italy
| | - Antonio Giorgio
- Department of Medicine, Surgery, and Neuroscience, University of Siena, Siena, Italy
| | - Nicola De Stefano
- Department of Medicine, Surgery, and Neuroscience, University of Siena, Siena, Italy
| | - Anna Poggesi
- NEUROFARBA Department, Neuroscience Section, University of Florence, Florence, Italy
| | - Domenico Inzitari
- NEUROFARBA Department, Neuroscience Section, University of Florence, Florence, Italy
| | - Leonardo Pantoni
- Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
| | - Mario Mascalchi
- Department of Experimental and Clinical Biomedical Sciences "Mario Serio, " University of Florence, Florence, Italy
- Division of Epidemiology and Clinical Governance, Institute for Study, Prevention and Network in Oncology (ISPRO), Florence, Italy
| | - Stefano Diciotti
- Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi, " University of Bologna, Cesena, Italy
- Alma Mater Research Institute for Human-Centered Artificial Intelligence, University of Bologna, Bologna, Italy
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Miller KB, Mi KL, Nelson GA, Norman RB, Patel ZS, Huff JL. Ionizing radiation, cerebrovascular disease, and consequent dementia: A review and proposed framework relevant to space radiation exposure. Front Physiol 2022; 13:1008640. [PMID: 36388106 PMCID: PMC9640983 DOI: 10.3389/fphys.2022.1008640] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 09/29/2022] [Indexed: 09/05/2023] Open
Abstract
Space exploration requires the characterization and management or mitigation of a variety of human health risks. Exposure to space radiation is one of the main health concerns because it has the potential to increase the risk of cancer, cardiovascular disease, and both acute and late neurodegeneration. Space radiation-induced decrements to the vascular system may impact the risk for cerebrovascular disease and consequent dementia. These risks may be independent or synergistic with direct damage to central nervous system tissues. The purpose of this work is to review epidemiological and experimental data regarding the impact of low-to-moderate dose ionizing radiation on the central nervous system and the cerebrovascular system. A proposed framework outlines how space radiation-induced effects on the vasculature may increase risk for both cerebrovascular dysfunction and neural and cognitive adverse outcomes. The results of this work suggest that there are multiple processes by which ionizing radiation exposure may impact cerebrovascular function including increases in oxidative stress, neuroinflammation, endothelial cell dysfunction, arterial stiffening, atherosclerosis, and cerebral amyloid angiopathy. Cerebrovascular adverse outcomes may also promote neural and cognitive adverse outcomes. However, there are many gaps in both the human and preclinical evidence base regarding the long-term impact of ionizing radiation exposure on brain health due to heterogeneity in both exposures and outcomes. The unique composition of the space radiation environment makes the translation of the evidence base from terrestrial exposures to space exposures difficult. Additional investigation and understanding of the impact of low-to-moderate doses of ionizing radiation including high (H) atomic number (Z) and energy (E) (HZE) ions on the cerebrovascular system is needed. Furthermore, investigation of how decrements in vascular systems may contribute to development of neurodegenerative diseases in independent or synergistic pathways is important for protecting the long-term health of astronauts.
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Affiliation(s)
| | | | - Gregory A. Nelson
- Department of Basic Sciences, Division of Biomedical Engineering Sciences, Loma Linda University, Loma Linda, CA, United States
- NASA Johnson Space Center, Houston, TX, United States
- KBR Inc., Houston, TX, United States
| | - Ryan B. Norman
- NASA Langley Research Center, Hampton, VA, United States
| | - Zarana S. Patel
- NASA Johnson Space Center, Houston, TX, United States
- KBR Inc., Houston, TX, United States
| | - Janice L. Huff
- NASA Langley Research Center, Hampton, VA, United States
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da Silva PHR, Paschoal AM, Secchinatto KF, Zotin MCZ, Dos Santos AC, Viswanathan A, Pontes-Neto OM, Leoni RF. Contrast agent-free state-of-the-art magnetic resonance imaging on cerebral small vessel disease - Part 2: Diffusion tensor imaging and functional magnetic resonance imaging. NMR IN BIOMEDICINE 2022; 35:e4743. [PMID: 35429070 DOI: 10.1002/nbm.4743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Accepted: 04/04/2022] [Indexed: 06/14/2023]
Abstract
Cerebral small vessel disease (cSVD) has been widely studied using conventional magnetic resonance imaging (MRI) methods, although the association between MRI findings and clinical features of cSVD is not always concordant. We assessed the additional contribution of contrast agent-free, state-of-the-art MRI techniques, particularly diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI), to understand brain damage and structural and functional connectivity impairment related to cSVD. We performed a review following the PICOS worksheet and Search Strategy, including 152 original papers in English, published from 2000 to 2022. For each MRI method, we extracted information about their contributions regarding the origins, pathology, markers, and clinical outcomes in cSVD. In general, DTI studies have shown that changes in mean, radial, and axial diffusivity measures are related to the presence of cSVD. In addition to the classical deficit in executive functions and processing speed, fMRI studies indicate connectivity dysfunctions in other domains, such as sensorimotor, memory, and attention. Neuroimaging metrics have been correlated with the diagnosis, prognosis, and rehabilitation of patients with cSVD. In short, the application of contrast agent-free, state-of-the-art MRI techniques has provided a complete picture of cSVD markers and tools to explore questions that have not yet been clarified about this clinical condition. Longitudinal studies are desirable to look for causal relationships between image biomarkers and clinical outcomes.
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Affiliation(s)
| | - André Monteiro Paschoal
- Department of Physics, FFCLRP, University of São Paulo, Ribeirão Preto, São Paulo, Brazil
- Department of Medical Imaging, Hematology and Clinical Oncology, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil
| | | | - Maria Clara Zanon Zotin
- Department of Medical Imaging, Hematology and Clinical Oncology, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil
- J Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Antônio Carlos Dos Santos
- Department of Medical Imaging, Hematology and Clinical Oncology, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil
| | - Anand Viswanathan
- J Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Octavio M Pontes-Neto
- Department of Neurosciences and Behavioral Science, Ribeirão Preto Medical School, University of Sao Paulo, Ribeirão Preto, São Paulo, Brazil
| | - Renata Ferranti Leoni
- Department of Physics, FFCLRP, University of São Paulo, Ribeirão Preto, São Paulo, Brazil
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Del Cuore A, Pacinella G, Riolo R, Tuttolomondo A. The Role of Immunosenescence in Cerebral Small Vessel Disease: A Review. Int J Mol Sci 2022; 23:ijms23137136. [PMID: 35806140 PMCID: PMC9266569 DOI: 10.3390/ijms23137136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Revised: 06/20/2022] [Accepted: 06/24/2022] [Indexed: 11/16/2022] Open
Abstract
Cerebral small vessel disease (CSVD) is one of the most important causes of vascular dementia. Immunosenescence and inflammatory response, with the involvement of the cerebrovascular system, constitute the basis of this disease. Immunosenescence identifies a condition of deterioration of the immune organs and consequent dysregulation of the immune response caused by cellular senescence, which exposes older adults to a greater vulnerability. A low-grade chronic inflammation status also accompanies it without overt infections, an “inflammaging” condition. The correlation between immunosenescence and inflammaging is fundamental in understanding the pathogenesis of age-related CSVD (ArCSVD). The production of inflammatory mediators caused by inflammaging promotes cellular senescence and the decrease of the adaptive immune response. Vice versa, the depletion of the adaptive immune mechanisms favours the stimulation of the innate immune system and the production of inflammatory mediators leading to inflammaging. Furthermore, endothelial dysfunction, chronic inflammation promoted by senescent innate immune cells, oxidative stress and impairment of microglia functions constitute, therefore, the framework within which small vessel disease develops: it is a concatenation of molecular events that promotes the decline of the central nervous system and cognitive functions slowly and progressively. Because the causative molecular mechanisms have not yet been fully elucidated, the road of scientific research is stretched in this direction, seeking to discover other aberrant processes and ensure therapeutic tools able to enhance the life expectancy of people affected by ArCSVD. Although the concept of CSVD is broader, this manuscript focuses on describing the neurobiological basis and immune system alterations behind cerebral aging. Furthermore, the purpose of our work is to detect patients with CSVD at an early stage, through the evaluation of precocious MRI changes and serum markers of inflammation, to treat untimely risk factors that influence the burden and the worsening of the cerebral disease.
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Affiliation(s)
- Alessandro Del Cuore
- Department of Promoting Health, Maternal-Infant, Excellence and Internal and Specialised Medicine (PROMISE) G. D’Alessandro, University of Palermo, 90133 Palermo, Italy; (G.P.); (R.R.); (A.T.)
- Internal Medicine and Stroke Care Ward, Policlinico “P. Giaccone”, 90127 Palermo, Italy
- Correspondence: ; Tel.: +39-091-655-2197
| | - Gaetano Pacinella
- Department of Promoting Health, Maternal-Infant, Excellence and Internal and Specialised Medicine (PROMISE) G. D’Alessandro, University of Palermo, 90133 Palermo, Italy; (G.P.); (R.R.); (A.T.)
- Internal Medicine and Stroke Care Ward, Policlinico “P. Giaccone”, 90127 Palermo, Italy
| | - Renata Riolo
- Department of Promoting Health, Maternal-Infant, Excellence and Internal and Specialised Medicine (PROMISE) G. D’Alessandro, University of Palermo, 90133 Palermo, Italy; (G.P.); (R.R.); (A.T.)
- Internal Medicine and Stroke Care Ward, Policlinico “P. Giaccone”, 90127 Palermo, Italy
| | - Antonino Tuttolomondo
- Department of Promoting Health, Maternal-Infant, Excellence and Internal and Specialised Medicine (PROMISE) G. D’Alessandro, University of Palermo, 90133 Palermo, Italy; (G.P.); (R.R.); (A.T.)
- Internal Medicine and Stroke Care Ward, Policlinico “P. Giaccone”, 90127 Palermo, Italy
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Dobrynina L, Gadzhieva Z, Shamtieva K, Kremneva E, Filatov A, Bitsieva E, Mirokova E, Krotenkova M. Predictors and integrative index of severity of cognitive disorders in cerebral microangiopathy. Zh Nevrol Psikhiatr Im S S Korsakova 2022; 122:52-60. [DOI: 10.17116/jnevro202212204152] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
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Egle M, Hilal S, Tuladhar AM, Pirpamer L, Bell S, Hofer E, Duering M, Wason J, Morris RG, Dichgans M, Schmidt R, Tozer DJ, Barrick TR, Chen C, de Leeuw FE, Markus HS. Determining the OPTIMAL DTI analysis method for application in cerebral small vessel disease. NEUROIMAGE: CLINICAL 2022; 35:103114. [PMID: 35908307 PMCID: PMC9421487 DOI: 10.1016/j.nicl.2022.103114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 05/24/2022] [Accepted: 07/10/2022] [Indexed: 11/23/2022] Open
Abstract
We were not able to identify a single optimal diffusion-weighted imaging analysis strategy across all 6 cohorts. Diffusion tensor imaging measures at baseline predicted dementia conversion in cerebral small vessel disease and mild cognitive impairment. Diffusion tensor imaging measures at baseline may be sensitive to differentiate between later vascular dementia vs Alzheimer’s disease dementia. Diffusion tensor imaging measures significantly changed over time in cohorts with cerebral small vessel disease and cohorts with mild cognitive impairment. Change in diffusion tensor imaging measures were only consistently associated with dementia conversion in severe SVD. The diffusion tensor imaging measures PSMD and DSEG required the lowest minimum sample sizes for a hypothetical clinical trial in patients with sporadic cerebral small vessel disease and mild cognitive impairment.
Background DTI is sensitive to white matter (WM) microstructural damage and has been suggested as a surrogate marker for phase 2 clinical trials in cerebral small vessel disease (SVD). The study’s objective is to establish the best way to analyse the diffusion-weighted imaging data in SVD for this purpose. The ideal method would be sensitive to change and predict dementia conversion, but also straightforward to implement and ideally automated. As part of the OPTIMAL collaboration, we evaluated five different DTI analysis strategies across six different cohorts with differing SVD severity. Methods Those 5 strategies were: (1) conventional mean diffusivity WM histogram measure (MD median), (2) a principal component-derived measure based on conventional WM histogram measures (PC1), (3) peak width skeletonized mean diffusivity (PSMD), (4) diffusion tensor image segmentation θ (DSEG θ) and (5) a WM measure of global network efficiency (Geff). The association between each measure and cognitive function was tested using a linear regression model adjusted by clinical markers. Changes in the imaging measures over time were determined. In three cohort studies, repeated imaging data together with data on incident dementia were available. The association between the baseline measure, change measure and incident dementia conversion was examined using Cox proportional-hazard regression or logistic regression models. Sample size estimates for a hypothetical clinical trial were furthermore computed for each DTI analysis strategy. Results There was a consistent cross-sectional association between the imaging measures and impaired cognitive function across all cohorts. All baseline measures predicted dementia conversion in severe SVD. In mild SVD, PC1, PSMD and Geff predicted dementia conversion. In MCI, all markers except Geff predicted dementia conversion. Baseline DTI was significantly different in patients converting to vascular dementia than to Alzheimer’ s disease. Significant change in all measures was associated with dementia conversion in severe but not in mild SVD. The automatic and semi-automatic measures PSMD and DSEG θ required the lowest minimum sample sizes for a hypothetical clinical trial in single-centre sporadic SVD cohorts. Conclusion DTI parameters obtained from all analysis methods predicted dementia, and there was no clear winner amongst the different analysis strategies. The fully automated analysis provided by PSMD offers advantages particularly for large datasets.
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Affiliation(s)
- Marco Egle
- Stroke Research Group, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom.
| | - Saima Hilal
- Department of Pharmacology, National University of Singapore, Singapore; Memory Ageing and Cognition Center, National University Health System, Singapore
| | - Anil M Tuladhar
- Department of Neurology, Donders Center for Medical Neuroscience, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Lukas Pirpamer
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Steven Bell
- Stroke Research Group, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
| | - Edith Hofer
- Department of Neurology, Medical University of Graz, Graz, Austria; Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria
| | - Marco Duering
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany; Medical Image Analysis Center (MIAC) and Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - James Wason
- Population Health Sciences Institute, Newcastle University, Baddiley-Clark Building, Newcastle Upon Tyne, United Kingdom
| | - Robin G Morris
- Department of Psychology (R.G.M.), King's College, Institute of Psychiatry, Psychology and Neuroscience, London, United Kingdom
| | - 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
| | - Reinhold Schmidt
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Daniel J Tozer
- Stroke Research Group, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
| | - Thomas R Barrick
- Neurosciences Research Centre, Institute for Molecular and Clinical Sciences, St George's, University of London, United Kingdom
| | - Christopher Chen
- Department of Pharmacology, National University of Singapore, Singapore; Memory Ageing and Cognition Center, National University Health System, Singapore
| | - Frank-Erik de Leeuw
- Department of Neurology, Donders Center for Medical Neuroscience, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Hugh S Markus
- Stroke Research Group, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
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Ueno Y, Saito A, Nakata J, Kamagata K, Taniguchi D, Motoi Y, Io H, Andica C, Shindo A, Shiina K, Miyamoto N, Yamashiro K, Urabe T, Suzuki Y, Aoki S, Hattori N. Possible Neuroprotective Effects of l-Carnitine on White-Matter Microstructural Damage and Cognitive Decline in Hemodialysis Patients. Nutrients 2021; 13:nu13041292. [PMID: 33919810 PMCID: PMC8070822 DOI: 10.3390/nu13041292] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 04/05/2021] [Accepted: 04/12/2021] [Indexed: 01/31/2023] Open
Abstract
Although l-carnitine alleviated white-matter lesions in an experimental study, the treatment effects of l-carnitine on white-matter microstructural damage and cognitive decline in hemodialysis patients are unknown. Using novel diffusion magnetic resonance imaging (dMRI) techniques, white-matter microstructural changes together with cognitive decline in hemodialysis patients and the effects of l-carnitine on such disorders were investigated. Fourteen hemodialysis patients underwent dMRI and laboratory and neuropsychological tests, which were compared across seven patients each in two groups according to duration of l-carnitine treatment: (1) no or short-term l-carnitine treatment (NSTLC), and (2) long-term l-carnitine treatment (LTLC). Ten age- and sex-matched controls were enrolled. Compared to controls, microstructural disorders of white matter were widely detected on dMRI of patients. An autopsy study of one patient in the NSTLC group showed rarefaction of myelinated fibers in white matter. With LTLC, microstructural damage on dMRI was alleviated along with lower levels of high-sensitivity C-reactive protein and substantial increases in carnitine levels. The LTLC group showed better achievement on trail making test A, which was correlated with amelioration of disorders in some white-matter tracts. Novel dMRI tractography detected abnormalities of white-matter tracts after hemodialysis. Long-term treatment with l-carnitine might alleviate white-matter microstructural damage and cognitive impairment in hemodialysis patients.
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Affiliation(s)
- Yuji Ueno
- Department of Neurology, Juntendo University Faculty of Medicine, Tokyo 113-8421, Japan; (D.T.); (Y.M.); (A.S.); (K.S.); (N.M.); (N.H.)
- Correspondence: ; Tel.: +81-3-3813-3111; Fax: +81-3-5800-0547
| | - Asami Saito
- Department of Radiology, Juntendo University Faculty of Medicine, Tokyo 113-8421, Japan; (A.S.); (K.K.); (C.A.); (S.A.)
- Department of Neurology and Stroke Medicine, Graduate School of Medicine, Yokohama City University, Yokohama 236-0004, Japan
| | - Junichiro Nakata
- Department of Nephrology, Juntendo University Faculty of Medicine, Tokyo 113-8421, Japan; (J.N.); (Y.S.)
| | - Koji Kamagata
- Department of Radiology, Juntendo University Faculty of Medicine, Tokyo 113-8421, Japan; (A.S.); (K.K.); (C.A.); (S.A.)
| | - Daisuke Taniguchi
- Department of Neurology, Juntendo University Faculty of Medicine, Tokyo 113-8421, Japan; (D.T.); (Y.M.); (A.S.); (K.S.); (N.M.); (N.H.)
| | - Yumiko Motoi
- Department of Neurology, Juntendo University Faculty of Medicine, Tokyo 113-8421, Japan; (D.T.); (Y.M.); (A.S.); (K.S.); (N.M.); (N.H.)
| | - Hiroaki Io
- Department of Nephrology, Juntendo University Nerima Hospital, Tokyo 177-8521, Japan;
| | - Christina Andica
- Department of Radiology, Juntendo University Faculty of Medicine, Tokyo 113-8421, Japan; (A.S.); (K.K.); (C.A.); (S.A.)
| | - Atsuhiko Shindo
- Department of Neurology, Juntendo University Faculty of Medicine, Tokyo 113-8421, Japan; (D.T.); (Y.M.); (A.S.); (K.S.); (N.M.); (N.H.)
| | - Kenta Shiina
- Department of Neurology, Juntendo University Faculty of Medicine, Tokyo 113-8421, Japan; (D.T.); (Y.M.); (A.S.); (K.S.); (N.M.); (N.H.)
| | - Nobukazu Miyamoto
- Department of Neurology, Juntendo University Faculty of Medicine, Tokyo 113-8421, Japan; (D.T.); (Y.M.); (A.S.); (K.S.); (N.M.); (N.H.)
| | - Kazuo Yamashiro
- Department of Neurology, Juntendo University Urayasu Hospital, Urayasu 279-0021, Japan; (K.Y.); (T.U.)
| | - Takao Urabe
- Department of Neurology, Juntendo University Urayasu Hospital, Urayasu 279-0021, Japan; (K.Y.); (T.U.)
| | - Yusuke Suzuki
- Department of Nephrology, Juntendo University Faculty of Medicine, Tokyo 113-8421, Japan; (J.N.); (Y.S.)
| | - Shigeki Aoki
- Department of Radiology, Juntendo University Faculty of Medicine, Tokyo 113-8421, Japan; (A.S.); (K.K.); (C.A.); (S.A.)
| | - Nobutaka Hattori
- Department of Neurology, Juntendo University Faculty of Medicine, Tokyo 113-8421, Japan; (D.T.); (Y.M.); (A.S.); (K.S.); (N.M.); (N.H.)
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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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Kivimäki M, Singh-Manoux A, Batty GD, Sabia S, Sommerlad A, Floud S, Jokela M, Vahtera J, Beydoun MA, Suominen SB, Koskinen A, Väänänen A, Goldberg M, Zins M, Alfredsson L, Westerholm PJM, Knutsson A, Nyberg ST, Sipilä PN, Lindbohm JV, Pentti J, Livingston G, Ferrie JE, Strandberg T. Association of Alcohol-Induced Loss of Consciousness and Overall Alcohol Consumption With Risk for Dementia. JAMA Netw Open 2020; 3:e2016084. [PMID: 32902651 PMCID: PMC7489835 DOI: 10.1001/jamanetworkopen.2020.16084] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
IMPORTANCE Evidence on alcohol consumption as a risk factor for dementia usually relates to overall consumption. The role of alcohol-induced loss of consciousness is uncertain. OBJECTIVE To examine the risk of future dementia associated with overall alcohol consumption and alcohol-induced loss of consciousness in a population of current drinkers. DESIGN, SETTING, AND PARTICIPANTS Seven cohort studies from the UK, France, Sweden, and Finland (IPD-Work consortium) including 131 415 participants were examined. At baseline (1986-2012), participants were aged 18 to 77 years, reported alcohol consumption, and were free of diagnosed dementia. Dementia was examined during a mean follow-up of 14.4 years (range, 12.3-30.1). Data analysis was conducted from November 17, 2019, to May 23, 2020. EXPOSURES Self-reported overall consumption and loss of consciousness due to alcohol consumption were assessed at baseline. Two thresholds were used to define heavy overall consumption: greater than 14 units (U) (UK definition) and greater than 21 U (US definition) per week. MAIN OUTCOMES AND MEASURES Dementia and alcohol-related disorders to 2016 were ascertained from linked electronic health records. RESULTS Of the 131 415 participants (mean [SD] age, 43.0 [10.4] years; 80 344 [61.1%] women), 1081 individuals (0.8%) developed dementia. After adjustment for potential confounders, the hazard ratio (HR) was 1.16 (95% CI, 0.98-1.37) for consuming greater than 14 vs 1 to 14 U of alcohol per week and 1.22 (95% CI, 1.01-1.48) for greater than 21 vs 1 to 21 U/wk. Of the 96 591 participants with data on loss of consciousness, 10 004 individuals (10.4%) reported having lost consciousness due to alcohol consumption in the past 12 months. The association between loss of consciousness and dementia was observed in men (HR, 2.86; 95% CI, 1.77-4.63) and women (HR, 2.09; 95% CI, 1.34-3.25) during the first 10 years of follow-up (HR, 2.72; 95% CI, 1.78-4.15), after excluding the first 10 years of follow-up (HR, 1.86; 95% CI, 1.16-2.99), and for early-onset (<65 y: HR, 2.21; 95% CI, 1.46-3.34) and late-onset (≥65 y: HR, 2.25; 95% CI, 1.38-3.66) dementia, Alzheimer disease (HR, 1.98; 95% CI, 1.28-3.07), and dementia with features of atherosclerotic cardiovascular disease (HR, 4.18; 95% CI, 1.86-9.37). The association with dementia was not explained by 14 other alcohol-related conditions. With moderate drinkers (1-14 U/wk) who had not lost consciousness as the reference group, the HR for dementia was twice as high in participants who reported having lost consciousness, whether their mean weekly consumption was moderate (HR, 2.19; 95% CI, 1.42-3.37) or heavy (HR, 2.36; 95% CI, 1.57-3.54). CONCLUSIONS AND RELEVANCE The findings of this study suggest that alcohol-induced loss of consciousness, irrespective of overall alcohol consumption, is associated with a subsequent increase in the risk of dementia.
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Affiliation(s)
- Mika Kivimäki
- Department of Epidemiology and Public Health, University College London, London, United Kingdom
- Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Archana Singh-Manoux
- Department of Epidemiology and Public Health, University College London, London, United Kingdom
- Epidemiology of Ageing and Neurodegenerative Diseases, INSERM U1153, Université de Paris, Paris, France
| | - G. David Batty
- Department of Epidemiology and Public Health, University College London, London, United Kingdom
- Oregon State University School of Biological and Population Health Sciences, Corvallis, Oregon
| | - Séverine Sabia
- Epidemiology of Ageing and Neurodegenerative Diseases, INSERM U1153, Université de Paris, Paris, France
| | - Andrew Sommerlad
- Division of Psychiatry, University College London, London, United Kingdom
- Camden and Islington NHS Foundation Trust, London, United Kingdom
| | - Sarah Floud
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Markus Jokela
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Jussi Vahtera
- Department of Public Health, University of Turku, Turku, Finland
- Centre for Population Health Research, Turku University Hospital, University of Turku, Turku, Finland
| | - May A. Beydoun
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Intramural Research Program, National Institute on Aging, National Institutes of Health, Baltimore, Maryland
| | - Sakari B. Suominen
- Department of Public Health, University of Turku, Turku, Finland
- University of Skövde School of Health and Education, Skövde, Sweden
| | - Aki Koskinen
- Finnish Institute of Occupational Health, Helsinki, Finland
| | - Ari Väänänen
- Finnish Institute of Occupational Health, Helsinki, Finland
| | - Marcel Goldberg
- Population-Based Epidemiological Cohorts Unit, INSERM UMS 011, Villejuif, France
| | - Marie Zins
- Population-Based Epidemiological Cohorts Unit, INSERM UMS 011, Villejuif, France
| | - Lars Alfredsson
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Centre for Occupational and Environmental Medicine, Region Stockholm, Stockholm, Sweden
| | | | - Anders Knutsson
- Department of Health Sciences, Mid Sweden University, Sundsvall, Sweden
| | - Solja T. Nyberg
- Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Finnish Institute of Occupational Health, Helsinki, Finland
| | - Pyry N. Sipilä
- Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Joni V. Lindbohm
- Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Jaana Pentti
- Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Turku, Turku, Finland
- Finnish Institute of Occupational Health, Helsinki, Finland
| | - Gill Livingston
- Division of Psychiatry, University College London, London, United Kingdom
- Camden and Islington NHS Foundation Trust, London, United Kingdom
| | - Jane E. Ferrie
- Department of Epidemiology and Public Health, University College London, London, United Kingdom
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, United Kingdom
| | - Timo Strandberg
- Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Medicine, Helsinki University Hospital, Helsinki, Finland
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
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Cremers LG, Wolters FJ, de Groot M, Ikram MK, van der Lugt A, Niessen WJ, Vernooij MW, Ikram MA. Structural disconnectivity and the risk of dementia in the general population. Neurology 2020; 95:e1528-e1537. [DOI: 10.1212/wnl.0000000000010231] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Accepted: 03/18/2020] [Indexed: 11/15/2022] Open
Abstract
ObjectiveThe disconnectivity hypothesis postulates that partial loss of connecting white matter fibers between brain regions contributes to the development of dementia. Using diffusion MRI to quantify global and tract-specific white matter microstructural integrity, we tested this hypothesis in a longitudinal population-based study.MethodsGlobal and tract-specific fractional anisotropy (FA) and mean diffusivity (MD) were obtained in 4,415 people without dementia (mean age 63.9 years, 55.0% women) from the prospective population-based Rotterdam Study with brain MRI between 2005 and 2011. We modeled the association of these diffusion measures with risk of dementia (follow-up until 2016) and with changes on repeated cognitive assessment after on average 5.4 years, adjusting for age, sex, education, macrostructural MRI markers, depressive symptoms, cardiovascular risk factors, and APOE genotype.ResultsDuring a median follow-up of 6.8 years, 101 participants had incident dementia, of whom 83 had clinical Alzheimer disease (AD). Lower global values of FA and higher values of MD were associated with an increased risk of dementia (adjusted hazard ratio [95% confidence interval (CI)] per SD increase for MD 1.79 [1.44–2.23] and FA 0.65 [0.52–0.80]). Similarly, lower global values of FA and higher values of MD related to more cognitive decline in people without dementia (difference in global cognition per SD increase in MD [95% CI] was −0.04 [−0.07 to −0.01]). Associations were most profound in the projection, association, and limbic system tracts.ConclusionsStructural disconnectivity is associated with an increased risk of dementia and more pronounced cognitive decline in the general population.
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