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Li H, Jacob MA, Cai M, Kessels RPC, Norris DG, Duering M, de Leeuw FE, Tuladhar AM. Meso-cortical pathway damage in cognition, apathy and gait in cerebral small vessel disease. Brain 2024; 147:3804-3816. [PMID: 38709856 PMCID: PMC11531843 DOI: 10.1093/brain/awae145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 04/08/2024] [Accepted: 04/12/2024] [Indexed: 05/08/2024] Open
Abstract
Cerebral small vessel disease (SVD) is known to contribute to cognitive impairment, apathy and gait dysfunction. Although associations between cognitive impairment and either apathy or gait dysfunction have been shown in SVD, the inter-relations among these three clinical features and their potential common neural basis remain unexplored. The dopaminergic meso-cortical and meso-limbic pathways have been known as the important brain circuits for both cognitive control, emotion regulation and motor function. Here, we investigated the potential inter-relations between cognitive impairment, apathy and gait dysfunction, with a specific focus on determining whether these clinical features are associated with damage to the meso-cortical and meso-limbic pathways in SVD. In this cross-sectional study, we included 213 participants with SVD for whom MRI and comprehensive neurobehavioural assessments were performed. These assessments comprised six clinical measures: processing speed, executive function, memory, apathy (based on the Apathy Evaluation Scale) and gait function (based on the time and steps in the Timed Up and Go Test). We reconstructed five tracts connecting the ventral tegmental area (VTA) and dorsolateral prefrontal cortex (PFC), ventral lateral PFC, medial orbitofrontal cortex, anterior cingulate cortex (ACC) and nucleus accumbens within meso-cortical and meso-limbic pathways using diffusion weighted imaging. The damage along the five tracts was quantified using the free water (FW) and FW-corrected mean diffusivity indices. Furthermore, we explored the inter-correlations among the six clinical measures and identified their common components using principal component analysis (PCA). Linear regression analyses showed that higher FW values of tracts within meso-cortical pathways were related to these clinical measures in cognition, apathy, and gait (all P-corrected values < 0.05). The PCA showed strong inter-associations among these clinical measures and identified a common component wherein all six clinical measures loaded on. Higher FW values of tracts within meso-cortical pathways were related to the PCA-derived common component (all P-corrected values < 0.05). Moreover, FW values of the VTA-ACC tract showed the strongest contribution to the PCA-derived common component over all other neuroimaging features. In conclusion, our study showed that the three clinical features (cognitive impairment, apathy, and gait dysfunction) of SVD are strongly inter-related and that the damage in meso-cortical pathway could be the common neural basis underlying the three features in SVD. These findings advance our understanding of the mechanisms behind these clinical features of SVD and have the potential to inform novel management and intervention strategies for SVD.
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Affiliation(s)
- Hao Li
- Department of Neurology, Radboud Institute for Medical research and Innovation and Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Mina A Jacob
- Department of Neurology, Radboud Institute for Medical research and Innovation and Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Mengfei Cai
- Department of Neurology, Radboud Institute for Medical research and Innovation and Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, 510000 Guangzhou, China
| | - Roy P C Kessels
- Radboud University, Donders Institute for Brain, Cognition and Behaviour, Centre for Cognition, Radboud University, 6525 GD Nijmegen, The Netherlands
- Department of Medical Psychology and Radboudumc Alzheimer Center, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
- Centre of Excellence for Korsakoff and Alcohol-Related Cognitive Disorders, Vincent van Gogh Institute for Psychiatry, 5804 AV Venray, The Netherlands
| | - David G Norris
- Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University, 6525 GD Nijmegen, The Netherlands
| | - Marco Duering
- Medical Image Analysis Center (MIAC AG) and Department of Biomedical Engineering, University of Basel, 4051 Basel, Switzerland
- Institute for Stroke and Dementia Research (ISD), LMU University Hospital, 81377 LMU Munich, Germany
| | - Frank-Erik de Leeuw
- Department of Neurology, Radboud Institute for Medical research and Innovation and Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Anil M Tuladhar
- Department of Neurology, Radboud Institute for Medical research and Innovation and Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
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Danciut I, Rae CL, Rashid W, Scott J, Bozzali M, Iancu M, Garfinkel SN, Bouyagoub S, Dowell NG, Langdon D, Cercignani M. Understanding the mechanisms of fatigue in multiple sclerosis: linking interoception, metacognition and white matter dysconnectivity. Brain Commun 2024; 6:fcae292. [PMID: 39291169 PMCID: PMC11406465 DOI: 10.1093/braincomms/fcae292] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Revised: 06/25/2024] [Accepted: 09/10/2024] [Indexed: 09/19/2024] Open
Abstract
One of the most prominent symptoms in multiple sclerosis is pathological fatigue, often described by sufferers as one of the most debilitating symptoms, affecting quality of life and employment. However, the mechanisms of both, physical and cognitive fatigue in multiple sclerosis remain elusive. Here, we use behavioural tasks and quantitative MRI to investigate the neural correlates of interoception (the ability to sense internal bodily signals) and metacognition (the ability of the brain to assess its own performance), in modulating cognitive fatigue. Assuming that structural damage caused by multiple sclerosis pathology might impair the neural pathways subtending interoception and/or metacognition, we considered three alternative hypotheses to explain fatigue as a consequence of, respectively: (i) reduced interoceptive accuracy, (ii) reduced interoceptive insight or (iii) reduced global metacognition. We then explored associations between these behavioural measures and white matter microstructure, assessed by diffusion and magnetisation transfer MRI. Seventy-one relapsing-remitting multiple sclerosis patients participated in this cross-sectional study (mean age 43, 62% female). Patient outcomes relevant for fatigue were measured, including disability, disease duration, depression, anxiety, sleepiness, cognitive function, disease modifying treatment and quality of life. Interoceptive and metacognitive parameters were measured using heartbeat tracking and discrimination tasks, and metacognitive visual and memory tasks. MRI was performed in 69 participants, including diffusion tensor MRI, neurite orientation dispersion and density imaging and quantitative magnetisation transfer. Associations between interoception and metacognition and the odds of high cognitive fatigue were tested by unconditional binomial logistic regression. The odds of cognitive fatigue were higher in the people with low interoceptive insight (P = 0.03), while no significant relationships were found between fatigue and other interoceptive or metacognitive parameters, suggesting a specific impairment in interoceptive metacognition, rather than interoception generally, or metacognition generally. Diffusion MRI-derived fractional anisotropy and neurite density index showed significant (P < 0.05) negative associations with cognitive fatigue in a widespread bilateral white matter network. Moreover, there was a significant (P < 0.05) interaction between cognitive fatigue and interoceptive insight, suggesting that the poorer the white matter structure, the lower the interoceptive insight, and the worse the fatigue. The results point towards metacognitive impairment confined to the interoceptive domain, in relapsing-remitting patients with cognitive fatigue. The neural basis of this impairment is supported by a widespread white matter network in which loss of neurite density plays a role.
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Affiliation(s)
- Iulia Danciut
- Clinical Imaging Sciences Centre, Department of Clinical Neuroscience, Brighton and Sussex Medical School, University of Sussex, Falmer, Brighton BN1 9RR, UK
- Department of Neurology, Hull Royal Infirmary, Hull HU3 2JZ, UK
| | - Charlotte L Rae
- School of Psychology, University of Sussex, Falmer, Brighton BN1 9QH, UK
| | - Waqar Rashid
- Department of Neurology, St George's Teaching Hospitals, London SW17 0QT, UK
| | - James Scott
- Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AB, UK
| | - Marco Bozzali
- 'Rita Levi Montalcini' Department of Neuroscience, University of Torino, 10126 Turin, Italy
| | - Mihaela Iancu
- Department of Medical Informatics and Biostatistics, Faculty of Medicine, 'Iuliu Haţieganu' University of Medicine and Pharmacy, 400349 Cluj-Napoca, Romania
| | - Sarah N Garfinkel
- Institute of Cognitive Neuroscience, UCL, Queen Square, London WC1N 3AZ, UK
| | - Samira Bouyagoub
- Clinical Imaging Sciences Centre, Department of Clinical Neuroscience, Brighton and Sussex Medical School, University of Sussex, Falmer, Brighton BN1 9RR, UK
| | - Nicholas G Dowell
- Clinical Imaging Sciences Centre, Department of Clinical Neuroscience, Brighton and Sussex Medical School, University of Sussex, Falmer, Brighton BN1 9RR, UK
| | - Dawn Langdon
- Psychology Department, Royal Holloway University of London, Egham, Surrey TW20 0EX, UK
| | - Mara Cercignani
- Clinical Imaging Sciences Centre, Department of Clinical Neuroscience, Brighton and Sussex Medical School, University of Sussex, Falmer, Brighton BN1 9RR, UK
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff CF24 4HQ, UK
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Quan P, Mao T, Zhang X, Wang R, Lei H, Wang J, Liu W, Dinges DF, Jiang C, Rao H. Locus coeruleus microstructural integrity is associated with vigilance vulnerability to sleep deprivation. Hum Brain Mapp 2024; 45:e70013. [PMID: 39225144 PMCID: PMC11369684 DOI: 10.1002/hbm.70013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Revised: 07/29/2024] [Accepted: 08/17/2024] [Indexed: 09/04/2024] Open
Abstract
Insufficient sleep compromises cognitive performance, diminishes vigilance, and disrupts daily functioning in hundreds of millions of people worldwide. Despite extensive research revealing significant variability in vigilance vulnerability to sleep deprivation, the underlying mechanisms of these individual differences remain elusive. Locus coeruleus (LC) plays a crucial role in the regulation of sleep-wake cycles and has emerged as a potential marker for vigilance vulnerability to sleep deprivation. In this study, we investigate whether LC microstructural integrity, assessed by fractional anisotropy (FA) through diffusion tensor imaging (DTI) at baseline before sleep deprivation, can predict impaired psychomotor vigilance test (PVT) performance during sleep deprivation in a cohort of 60 healthy individuals subjected to a rigorously controlled in-laboratory sleep study. The findings indicate that individuals with high LC FA experience less vigilance impairment from sleep deprivation compared with those with low LC FA. LC FA accounts for 10.8% of the variance in sleep-deprived PVT lapses. Importantly, the relationship between LC FA and impaired PVT performance during sleep deprivation is anatomically specific, suggesting that LC microstructural integrity may serve as a biomarker for vigilance vulnerability to sleep loss.
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Affiliation(s)
- Peng Quan
- The First Dongguan Affiliated Hospital, School of Humanities and ManagementGuangdong Medical UniversityDongguanChina
- Center for Functional Neuroimaging, Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Tianxin Mao
- Center for Functional Neuroimaging, Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Brain‐Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and ManagementShanghai International Studies UniversityShanghaiChina
| | - Xiaocui Zhang
- Center for Functional Neuroimaging, Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Ruosi Wang
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Brain‐Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and ManagementShanghai International Studies UniversityShanghaiChina
| | - Hui Lei
- Center for Functional Neuroimaging, Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Jieqiong Wang
- Center for Functional Neuroimaging, Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Wanting Liu
- Center for Functional Neuroimaging, Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - David F. Dinges
- Chronobiology and Sleep InstituteUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Caihong Jiang
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Brain‐Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and ManagementShanghai International Studies UniversityShanghaiChina
| | - Hengyi Rao
- Center for Functional Neuroimaging, Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Brain‐Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and ManagementShanghai International Studies UniversityShanghaiChina
- Chronobiology and Sleep InstituteUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
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Margoni M, Valsasina P, Bacchetti A, Mistri D, Preziosa P, Rocca MA, Filippi M. Resting state functional connectivity modifications in monoaminergic circuits underpin fatigue development in patients with multiple sclerosis. Mol Psychiatry 2024; 29:2647-2656. [PMID: 38528072 DOI: 10.1038/s41380-024-02532-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 03/13/2024] [Accepted: 03/13/2024] [Indexed: 03/27/2024]
Abstract
Dysregulation of monoaminergic networks might have a role in the pathogenesis of fatigue in multiple sclerosis (MS). We investigated longitudinal changes of resting state (RS) functional connectivity (FC) in monoaminergic networks and their association with the development of fatigue in MS. Eighty-nine MS patients and 49 age- and sex-matched healthy controls (HC) underwent neurological, fatigue, and RS functional MRI assessment at baseline and after a median follow-up of 1.3 years (interquartile range = 1.01-2.01 years). Monoaminergic-related RS FC was estimated with an independent component analysis constrained to PET atlases for dopamine (DA), noradrenaline (NA), and serotonin (5-HT) transporters. At baseline, 24 (27%) MS patients were fatigued (F) and 65 were not fatigued (NF). Of these, 22 (34%) developed fatigue (DEV-FAT) at follow-up and 43 remained not fatigued (NO-FAT). At baseline, F-MS patients showed increased monoaminergic-related RS FC in the caudate nucleus vs NF-MS and in the hippocampal, postcentral, temporal, and occipital cortices vs NF-MS and HC. Moreover, F-MS patients exhibited decreased RS FC in the frontal cortex vs NF-MS and HC, and in the thalamus vs NF-MS. During the follow-up, no RS FC changes were observed in HC. NO-FAT patients showed limited DA-related RS FC modifications, whereas DEV-FAT MS patients showed increased DA-related RS FC in the left hippocampus, significant at time-by-group interaction analysis. In the NA-related network, NO-FAT patients showed decreased RS FC over time in the left superior frontal gyrus. This region showed increased RS FC in both DEV-FAT and F-MS patients; this divergent behavior was significant at time-by-group interaction analysis. Finally, DEV-FAT MS patients presented increased 5-HT-related RS FC in the angular and middle occipital gyri, while this latter region showed decreased 5-HT-related RS FC during the follow-up in F-MS patients. In MS patients, distinct patterns of alterations were observed in monoaminergic networks based on their fatigue status. Fatigue was closely linked to specific changes in the basal ganglia and hippocampal, superior frontal, and middle occipital cortices.
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Affiliation(s)
- Monica Margoni
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Paola Valsasina
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Anna Bacchetti
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Damiano Mistri
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Paolo Preziosa
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Vita-Salute San Raffaele University, Milan, Italy.
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy.
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Tanaka Y, Ikeda K, Kaneko Y, Ishiguro N, Takeuchi T. Why does malaise/fatigue occur? Underlying mechanisms and potential relevance to treatments in rheumatoid arthritis. Expert Rev Clin Immunol 2024; 20:485-499. [PMID: 38224064 DOI: 10.1080/1744666x.2024.2306220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Accepted: 01/12/2024] [Indexed: 01/16/2024]
Abstract
INTRODUCTION Fatigue and malaise are commonly associated with a wide range of medical conditions, including rheumatoid arthritis (RA). Evidence suggests that fatigue and malaise can be overwhelming for patients, yet these symptoms remain inadequately-managed, largely due to an incomplete elucidation of the underlying causes. AREAS COVERED In this assessment of the published literature relating to the pathogenesis of fatigue or malaise in chronic conditions, four key mechanistic themes were identified. Each theme (inflammation, hypothalamic-pituitary-adrenal axis, dysautonomia, and monoamines) is discussed, as well as the complex network of interconnections between themes which suggests a key role for inflammatory cytokines in the development and persistence of fatigue. EXPERT OPINION Fatigue is multifaceted, poorly defined, and imperfectly comprehended. Moreover, the cause and severity of fatigue may change over time, as a consequence of the natural disease course or pharmacologic treatment. This detailed synthesis of available evidence permits us to identify avenues for current treatment optimization and future research, to improve the management of fatigue and malaise in RA. Within the development pipeline, several new anti-inflammatory therapies are currently under investigation, and we anticipate that the next five years will herald much-needed progress to reduce the debilitating nature of fatigue in patients with RA.
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Affiliation(s)
- Yoshiya Tanaka
- The First Department of Internal Medicine, School of Medicine, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Kei Ikeda
- Department of Rheumatology, Dokkyo Medical University, Mibu, Tochigi, Japan
| | - Yuko Kaneko
- Division of Rheumatology, Department of Internal Medicine, Keio University School of Medicine, Tokyo, Japan
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Gharaylou Z, Shahbodaghy F, Kolivand P, Kolivand M, Azizzadeh F, Rostampour M. Reduced White Matter Fiber Density in Patients with Multiple Sclerosis. Brain Connect 2024; 14:172-181. [PMID: 38308478 DOI: 10.1089/brain.2023.0068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2024] Open
Abstract
Introduction: Improved understanding of multiple sclerosis (MS) symptomatology, disease mechanisms, and clinical effectiveness can be achieved by investigating microstructural damage. The aim was to gain deeper insights into changes in white matter (WM) tracts in MS patients. Methods: Diffusion magnetic resonance imaging-based tractography was utilized to segment WM tracts into regions of interest for further quantitative analysis. However, tractography is susceptible to false-positive findings, reducing its specificity and clinical feasibility. To address these limitations, the Convex Optimization Modeling for Microstructure Informed Tractography (COMMIT) technique was used. COMMIT was used to derive measures of intracellular compartment (IC) and isotropic compartments from multishell diffusion data of 40 healthy controls (HCs) and 40 MS patients. Results: The analysis revealed a widespread pattern of significantly decreased IC values in MS patients compared with HCs across 61,581 voxels (pFWE < 0.05, threshold-free cluster enhancement [TFCE] corrected). Similar WM structures studied using the fractional anisotropy (FA) value also showed a reduction in FA among MS patients compared with HCs across 57,304 voxels (pFWE < 0.05, TFCE corrected). Out of the 61,581 voxels exhibiting lower IC, a substantial overlap of 47,251 voxels (76.72%) also demonstrated lower FA in MS patients compared with HCs. Discussion: The data suggested that lower IC values contributed to the explanation of FA reductions. In addition, IC showed promising potential for evaluating microstructural abnormalities in WM in MS, potentially being more sensitive than the frequently used FA value.
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Affiliation(s)
| | - Fatemeh Shahbodaghy
- Biomedical Engineering Department, Amirkabir University of Technology, Tehran, Iran
| | - Pirhossein Kolivand
- Department of Health Economics, School of Medicine, Shahed University, Tehran, Iran
| | - Maryam Kolivand
- Medical School, Tehran University of Medical Sciences, Tehran, Iran
| | - Fatemeh Azizzadeh
- Medical School, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Masoumeh Rostampour
- Sleep Disorders Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran
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Mistri D, Valsasina P, Storelli L, Filippi M, Rocca MA. Monoaminergic network dysfunction and development of depression in multiple sclerosis: a longitudinal investigation. J Neurol 2024; 271:1618-1629. [PMID: 38112782 DOI: 10.1007/s00415-023-12138-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 11/23/2023] [Accepted: 11/24/2023] [Indexed: 12/21/2023]
Abstract
BACKGROUND Monoaminergic network dysfunction is thought to underpin depression in multiple sclerosis (MS) patients. However, longitudinal studies are lacking. OBJECTIVES Here, we investigated the association between development of depressive symptoms in MS and changes of resting-state functional connectivity (RS FC) within monoaminergic networks. METHODS Forty-nine MS patients without depression [Montgomery-Asberg Depression Scale (MADRS) ≤ 9] and 27 healthy controls underwent clinical and 3.0 T RS FC assessment at baseline and after a median follow-up of 1.6 years (interquartile range 1.0-2.1 years). Monoamine-related RS FC was derived by independent component analysis, constrained to PET atlases for dopamine, noradrenaline and serotonin transporters. Longitudinal changes of RS FC within monoaminergic networks and their correlations with MADRS scores were assessed. RESULTS At baseline, MS patients showed decreased RS FC vs healthy controls in all PET-guided monoaminergic networks in frontal, cingulate and cerebellar cortices, and increased RS FC in parieto-occipital regions. Fourteen (29%) MS patients developed depressive symptoms (MADRS > 9) at follow-up (D-MS) and exhibited widespread RS FC decrease over time in the PET-guided dopamine network, mainly in orbitofrontal, occipital, anterior cingulate and precuneal cortices compared to patients who did not develop depressive symptoms. In D-MS, decreased RS FC over time was also observed in parahippocampal and occipital regions of the PET-guided noradrenaline network. Decreased RS FC over time in dopamine and noradrenaline PET-guided networks correlated with concomitant increased MADRS scores (r = range - 0.65/- 0.61, p < 0.001). CONCLUSIONS The development of depressive symptoms in MS patients was associated with specific RS FC changes within the dopamine and noradrenaline networks.
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Affiliation(s)
- Damiano Mistri
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Paola Valsasina
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Loredana Storelli
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Vita-Salute San Raffaele University, Milan, Italy.
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Pinarello C, Elmers J, Inojosa H, Beste C, Ziemssen T. Management of multiple sclerosis fatigue in the digital age: from assessment to treatment. Front Neurosci 2023; 17:1231321. [PMID: 37869507 PMCID: PMC10585158 DOI: 10.3389/fnins.2023.1231321] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 09/18/2023] [Indexed: 10/24/2023] Open
Abstract
Fatigue is one of the most disabling symptoms of Multiple Sclerosis (MS), affecting more than 80% of patients over the disease course. Nevertheless, it has a multi-faceted and complex nature, making its diagnosis, evaluation, and treatment extremely challenging in clinical practice. In the last years, digital supporting tools have emerged to support the care of people with MS. These include not only smartphone or table-based apps, but also wearable devices or novel techniques such as virtual reality. Furthermore, an additional effective and cost-efficient tool for the therapeutic management of people with fatigue is becoming increasingly available. Virtual reality and e-Health are viable and modern tools to both assess and treat fatigue, with a variety of applications and adaptability to patient needs and disability levels. Most importantly, they can be employed in the patient's home setting and can not only bridge clinic visits but also be complementary to the monitoring and treatment means for those MS patients who live far away from healthcare structures. In this narrative review, we discuss the current knowledge and future perspectives in the digital management of fatigue in MS. These may also serve as sources for research of novel digital biomarkers in the identification of disease activity and progression.
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Affiliation(s)
- Chiara Pinarello
- Center of Clinical Neuroscience, Department of Neurology, University Hospital Carl Gustav Carus, Technical University of Dresden, Dresden, Germany
| | - Julia Elmers
- Center of Clinical Neuroscience, Department of Neurology, University Hospital Carl Gustav Carus, Technical University of Dresden, Dresden, Germany
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, Technical University of Dresden, Dresden, Germany
| | - Hernán Inojosa
- Center of Clinical Neuroscience, Department of Neurology, University Hospital Carl Gustav Carus, Technical University of Dresden, Dresden, Germany
| | - Christian Beste
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, Technical University of Dresden, Dresden, Germany
| | - Tjalf Ziemssen
- Center of Clinical Neuroscience, Department of Neurology, University Hospital Carl Gustav Carus, Technical University of Dresden, Dresden, Germany
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Martin EM, Rupprecht S, Schrenk S, Kattlun F, Utech I, Radscheidt M, Brodoehl S, Schwab M, Reuken PA, Stallmach A, Habekost T, Finke K. A hypoarousal model of neurological post-COVID syndrome: the relation between mental fatigue, the level of central nervous activation and cognitive processing speed. J Neurol 2023; 270:4647-4660. [PMID: 37356025 PMCID: PMC10511382 DOI: 10.1007/s00415-023-11819-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 06/09/2023] [Accepted: 06/11/2023] [Indexed: 06/27/2023]
Abstract
BACKGROUND Knowledge on the nature of post-COVID neurological sequelae often manifesting as cognitive dysfunction and fatigue is still unsatisfactory. OBJECTIVES We assumed that cognitive dysfunction and fatigue in post-COVID syndrome are critically linked via hypoarousal of the brain. Thus, we assessed whether tonic alertness as a neurocognitive index of arousal is reduced in these patients and how this relates to the level of central nervous activation and subjective mental fatigue as further indices of arousal. METHODS 40 post-COVID patients with subjective cognitive dysfunction and 40 matched healthy controls underwent a whole-report paradigm of briefly presented letter arrays. Based on report performance and computational modelling according to the theory of visual attention, the parameter visual processing speed (VPS) was quantified as a proxy of tonic alertness. Pupillary unrest was assessed as a measure of central nervous activation. The Fatigue Assessment Scale was applied to assess subjective mental fatigue using the corresponding subscale. RESULTS VPS was reduced in post-COVID patients compared to controls (p = 0.005). In these patients, pupillary unrest (p = 0.029) and mental fatigue (p = 0.001) predicted VPS, explaining 34% of the variance and yielding a large effect with f2 = 0.51. CONCLUSION In post-COVID patients with subjective cognitive dysfunction, hypoarousal of the brain is reflected in decreased processing speed which is explained by a reduced level of central nervous activation and a higher level of mental fatigue. In turn, reduced processing speed objectifies mental fatigue as a core subjective clinical complaint in post-COVID patients.
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Affiliation(s)
- Eva Maria Martin
- Department of Neurology, Jena University Hospital, Jena, Germany.
| | - Sven Rupprecht
- Department of Neurology, Jena University Hospital, Jena, Germany
- Interdisciplinary Centre for Sleep and Ventilatory Medicine, Jena University Hospital Jena, Jena, Germany
| | - Simon Schrenk
- Department of Neurology, Jena University Hospital, Jena, Germany
| | - Fabian Kattlun
- Department of Neurology, Jena University Hospital, Jena, Germany
| | - Isabelle Utech
- Department of Neurology, Jena University Hospital, Jena, Germany
| | - Monique Radscheidt
- Department of Neurology, Jena University Hospital, Jena, Germany
- Interdisciplinary Centre for Sleep and Ventilatory Medicine, Jena University Hospital Jena, Jena, Germany
| | - Stefan Brodoehl
- Department of Neurology, Jena University Hospital, Jena, Germany
| | - Matthias Schwab
- Department of Neurology, Jena University Hospital, Jena, Germany
| | - Philipp A Reuken
- Department of Internal Medicine IV (Gastroenterology, Hepatology and Infectious Diseases), Jena University Hospital, Jena, Germany
| | - Andreas Stallmach
- Department of Internal Medicine IV (Gastroenterology, Hepatology and Infectious Diseases), Jena University Hospital, Jena, Germany
| | - Thomas Habekost
- Center of Visual Cognition, University of Copenhagen, Copenhagen, Denmark
| | - Kathrin Finke
- Department of Neurology, Jena University Hospital, Jena, Germany
- Center for Sepsis Control and Care, Jena University Hospital, Jena, Germany
- Department of Psychology, Ludwig-Maximilians-University Munich, Munich, Germany
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10
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Jayanti S, Dalla Verde C, Tiribelli C, Gazzin S. Inflammation, Dopaminergic Brain and Bilirubin. Int J Mol Sci 2023; 24:11478. [PMID: 37511235 PMCID: PMC10380707 DOI: 10.3390/ijms241411478] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 07/07/2023] [Accepted: 07/11/2023] [Indexed: 07/30/2023] Open
Abstract
Dopamine is a well-known neurotransmitter due to its involvement in Parkinson's disease (PD). Dopamine is not only involved in PD but also controls multiple mental and physical activities, such as the pleasure of food, friends and loved ones, music, art, mood, cognition, motivation, fear, affective disorders, addiction, attention deficit disorder, depression, and schizophrenia. Dopaminergic neurons (DOPAn) are susceptible to stressors, and inflammation is a recognized risk for neuronal malfunctioning and cell death in major neurodegenerative diseases. Less is known for non-neurodegenerative conditions. Among the endogenous defenses, bilirubin, a heme metabolite, has been shown to possess important anti-inflammatory activity and, most importantly, to prevent DOPAn demise in an ex vivo model of PD by acting on the tumor necrosis factor-alpha (TNFα). This review summarizes the evidence linking DOPAn, inflammation (when possible, specifically TNFα), and bilirubin as an anti-inflammatory in order to understand what is known, the gaps that need filling, and the hypotheses of anti-inflammatory strategies to preserve dopamine homeostasis with bilirubin included.
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Affiliation(s)
- Sri Jayanti
- Italian Liver Foundation, Liver Brain Unit "Rita Moretti", Area Science Park, Bldg. Q, SS 14, Km 163,5, 34149 Trieste, Italy
- Eijkman Research Centre for Molecular Biology, Research Organization for Health, National Research and Innovation Agency, Cibinong 16915, Indonesia
| | - Camilla Dalla Verde
- Italian Liver Foundation, Liver Brain Unit "Rita Moretti", Area Science Park, Bldg. Q, SS 14, Km 163,5, 34149 Trieste, Italy
| | - Claudio Tiribelli
- Italian Liver Foundation, Liver Brain Unit "Rita Moretti", Area Science Park, Bldg. Q, SS 14, Km 163,5, 34149 Trieste, Italy
| | - Silvia Gazzin
- Italian Liver Foundation, Liver Brain Unit "Rita Moretti", Area Science Park, Bldg. Q, SS 14, Km 163,5, 34149 Trieste, Italy
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11
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Sungur M, Ovayolu N, Akçalı A. The Effect of Acupressure Applied to Patients With Multiple Sclerosis on Fatigue. Holist Nurs Pract 2023; 37:184-194. [PMID: 37335146 DOI: 10.1097/hnp.0000000000000588] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/21/2023]
Abstract
This study was conducted in order to examine the effect of acupressure applied to patients with multiple sclerosis on fatigue. The patients meeting the inclusion criteria were assigned to intervention (n = 30) and control (n = 30) groups. The data of the study were collected using a questionnaire and the Fatigue Severity Scale. During the study, the control group received its routine treatment; on the other hand, the intervention group received routine treatment and also the certified researcher, receiving the acupressure training, applied acupressure to the intervention group by using the points Li4, ST36 and SP6 3 times a week for a total of 4 weeks. The postacupressure fatigue mean score was 5.2 ± 0.7 in the intervention group and 5.9 ± 0.7 in the control group, and there was a significant difference in the control and intervention groups in terms of postacupressure fatigue mean scores (P < .05). According to these results of the study, it can be recommended to provide acupressure training to patients with multiple sclerosis in order to decrease the fatigue associated with multiple sclerosis.
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Affiliation(s)
- Meltem Sungur
- Department of Nursing, Yusuf Şerefoğlu Faculty of Health Sciences, Kilis 7 Aralık University, Kilis, Turkey (Ms Sungur); Faculty of Health Sciences, Sanko University, Gaziantep, Turkey (Dr Ovayolu); and Faculty of Medicine, Department of Internal Medicine, Department of Neurology, Gaziantep University, Gaziantep, Turkey (Dr Akçalı)
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12
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Rocca MA, Margoni M, Battaglini M, Eshaghi A, Iliff J, Pagani E, Preziosa P, Storelli L, Taoka T, Valsasina P, Filippi M. Emerging Perspectives on MRI Application in Multiple Sclerosis: Moving from Pathophysiology to Clinical Practice. Radiology 2023; 307:e221512. [PMID: 37278626 PMCID: PMC10315528 DOI: 10.1148/radiol.221512] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 11/28/2022] [Accepted: 01/17/2023] [Indexed: 06/07/2023]
Abstract
MRI plays a central role in the diagnosis of multiple sclerosis (MS) and in the monitoring of disease course and treatment response. Advanced MRI techniques have shed light on MS biology and facilitated the search for neuroimaging markers that may be applicable in clinical practice. MRI has led to improvements in the accuracy of MS diagnosis and a deeper understanding of disease progression. This has also resulted in a plethora of potential MRI markers, the importance and validity of which remain to be proven. Here, five recent emerging perspectives arising from the use of MRI in MS, from pathophysiology to clinical application, will be discussed. These are the feasibility of noninvasive MRI-based approaches to measure glymphatic function and its impairment; T1-weighted to T2-weighted intensity ratio to quantify myelin content; classification of MS phenotypes based on their MRI features rather than on their clinical features; clinical relevance of gray matter atrophy versus white matter atrophy; and time-varying versus static resting-state functional connectivity in evaluating brain functional organization. These topics are critically discussed, which may guide future applications in the field.
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Affiliation(s)
- Maria Assunta Rocca
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Monica Margoni
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Marco Battaglini
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Arman Eshaghi
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Jeffrey Iliff
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Elisabetta Pagani
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Paolo Preziosa
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Loredana Storelli
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Toshiaki Taoka
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Paola Valsasina
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Massimo Filippi
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
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13
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Zito GA, Tarrano C, Ouarab S, Jegatheesan P, Ekmen A, Béranger B, Valabregue R, Hubsch C, Sangla S, Bonnet C, Delorme C, Méneret A, Degos B, Bouquet F, Apoil Brissard M, Vidailhet M, Hasboun D, Worbe Y, Roze E, Gallea C. Fixel-Based Analysis Reveals Whole-Brain White Matter Abnormalities in Cervical Dystonia. Mov Disord 2023. [PMID: 37148555 DOI: 10.1002/mds.29425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 04/04/2023] [Accepted: 04/12/2023] [Indexed: 05/08/2023] Open
Abstract
BACKGROUND Cervical dystonia (CD) is a form of isolated focal dystonia typically associated to abnormal head, neck, and shoulder movements and postures. The complexity of the clinical presentation limits the investigation of its pathophysiological mechanisms, and the neural networks associated to specific motor manifestations are still the object of debate. OBJECTIVES We investigated the morphometric properties of white matter fibers in CD and explored the networks associated with motor symptoms, while regressing out nonmotor scores. METHODS Nineteen patients affected by CD and 21 healthy controls underwent diffusion-weighted magnetic resonance imaging. We performed fixel-based analysis, a novel method evaluating fiber orientation within specific fiber bundles, and compared fiber morphometric properties between groups. Moreover, we correlated fiber morphometry with the severity of motor symptoms in patients. RESULTS Compared to controls, patients exhibited decreased white matter fibers in the right striatum. Motor symptom severity negatively correlated with white matter fibers passing through inferior parietal areas and the head representation area of the motor cortex. CONCLUSIONS Abnormal white matter integrity at the basal ganglia level may affect several functional networks involved, for instance, in motor preparation and execution, visuomotor coordination, and multimodal integration. This may result in progressive maladaptive plasticity, culminating in overt symptoms of dystonia. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
| | - Clément Tarrano
- Movement Investigation and Therapeutics Team, Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR7225, Paris, France
- Department of Neurology, Assistance Publique-Hôpitaux de Paris, Pitié-Salpêtrière Hospital, Paris, France
| | - Salim Ouarab
- Movement Investigation and Therapeutics Team, Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR7225, Paris, France
| | - Prasanthi Jegatheesan
- Movement Investigation and Therapeutics Team, Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR7225, Paris, France
| | - Asya Ekmen
- Movement Investigation and Therapeutics Team, Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR7225, Paris, France
| | - Benoît Béranger
- Center for NeuroImaging Research (CENIR), Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR 7225, Paris, France
| | - Romain Valabregue
- Center for NeuroImaging Research (CENIR), Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR 7225, Paris, France
| | - Cécile Hubsch
- Movement Investigation and Therapeutics Team, Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR7225, Paris, France
| | - Sophie Sangla
- Movement Investigation and Therapeutics Team, Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR7225, Paris, France
| | - Cécilia Bonnet
- Movement Investigation and Therapeutics Team, Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR7225, Paris, France
| | - Cécile Delorme
- Movement Investigation and Therapeutics Team, Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR7225, Paris, France
| | - Aurélie Méneret
- Movement Investigation and Therapeutics Team, Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR7225, Paris, France
- DMU Neurosciences, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Bertrand Degos
- Movement Investigation and Therapeutics Team, Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR7225, Paris, France
- Neurology Unit, AP-HP, Avicenne University Hospital, Sorbonne Paris Nord, Bobigny, France
- Center for Interdisciplinary Research in Biology, Collège de France, CNRS UMR7241/INSERM U1050, Université PSL, Paris, France
| | - Floriane Bouquet
- Movement Investigation and Therapeutics Team, Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR7225, Paris, France
| | | | - Marie Vidailhet
- Movement Investigation and Therapeutics Team, Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR7225, Paris, France
- DMU Neurosciences, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Dominique Hasboun
- Movement Investigation and Therapeutics Team, Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR7225, Paris, France
- Department of Neurology, Assistance Publique-Hôpitaux de Paris, Pitié-Salpêtrière Hospital, Paris, France
| | - Yulia Worbe
- Movement Investigation and Therapeutics Team, Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR7225, Paris, France
- Department of Neurophysiology, Saint-Antoine Hospital, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Emmanuel Roze
- Movement Investigation and Therapeutics Team, Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR7225, Paris, France
- DMU Neurosciences, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Cécile Gallea
- Movement Investigation and Therapeutics Team, Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR7225, Paris, France
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14
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Carotenuto A, Valsasina P, Preziosa P, Mistri D, Filippi M, Rocca MA. Monoaminergic network abnormalities: a marker for multiple sclerosis-related fatigue and depression. J Neurol Neurosurg Psychiatry 2023; 94:94-101. [PMID: 36229193 DOI: 10.1136/jnnp-2022-330109] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Accepted: 10/01/2022] [Indexed: 11/07/2022]
Abstract
OBJECTIVE To investigate monoaminergic network abnormalities in patients with multiple sclerosis (MS) according to their fatigue and depressive status through a positron emission tomography (PET)-based constrained independent component analysis (ICA) on resting state (RS) functional MRI (fMRI). METHODS In this prospective study, 213 patients with MS (mean age=40.6±12.5 years; 94/119 men/women; 153 relapsing-remitting; 60 progressive) and 62 healthy controls (HCs, mean age=39.0±10.4 years; 30/32 men/women) underwent neurological, fatigue, depression and RS fMRI assessment. Patterns of dopamine, norepinephrine-related and serotonin-related RS functional connectivity (FC) were derived by ICA, constrained to PET atlases for dopamine, norepinephrine and serotonin transporters, obtained in HCs' brain. RESULTS Compared with HCs, patients with MS showed abnormalities in all three explored monoaminergic networks, mostly with decreased RS FC within PET-guided monoaminergic networks in frontal regions and subcortical areas including the cerebellum and thalamus, and increased RS FC in temporo-parieto-occipital cortical areas, including bilateral precunei.MS-related fatigue was associated with decreased RS FC within the PET-guided dopamine network in the left thalamus and left cerebellum, and with increased RS FC within the PET-guided serotonin network in the left middle occipital gyrus. MS-related depression was associated with more distributed abnormalities involving the three explored monoaminergic networks, resulting in overall reduced RS FC in the frontal lobe, limbic areas and the precuneus. CONCLUSIONS Patients with MS present diffuse dysregulation in the monoaminergic networks. Specific alterations in these networks were associated with fatigue and depression, providing a pathological marker for these bothersome symptoms and putative targets for their treatment.
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Affiliation(s)
- Antonio Carotenuto
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Paola Valsasina
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Paolo Preziosa
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milan, Italy.,Neurology Unit, IRCCS Ospedale San Raffaele, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
| | - Damiano Mistri
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milan, Italy.,Neurology Unit, IRCCS Ospedale San Raffaele, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy.,Neurorehabilitation Unit, IRCCS Ospedale San Raffaele, Milan, Italy.,Neurophysiology Service, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milan, Italy .,Neurology Unit, IRCCS Ospedale San Raffaele, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
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15
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Correspondence among gray matter atrophy and atlas-based neurotransmitter maps is clinically relevant in multiple sclerosis. Mol Psychiatry 2023; 28:1770-1782. [PMID: 36658334 DOI: 10.1038/s41380-023-01943-1] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Revised: 12/29/2022] [Accepted: 01/06/2023] [Indexed: 01/20/2023]
Abstract
In multiple sclerosis (MS), gray matter (GM) atrophy progresses in a non-random manner, possibly in regions with a high distribution of specific neurotransmitters involved in several relevant central nervous system functions. We investigated the associations among regional GM atrophy, atlas-based neurotransmitter distributions and clinical manifestations in a large MS patients' group. Brain 3 T MRI scans, neurological examinations and neuropsychological evaluations were obtained from 286 MS patients and 172 healthy controls (HC). Spatial correlations among regional GM volume differences and atlas-based nuclear imaging-derived neurotransmitter maps, and their associations with MS clinical features were investigated using voxel-based morphometry and JuSpace toolbox. Compared to HC, MS patients showed widespread GM atrophy being spatially correlated with the majority of neurotransmitter maps (false discovery rate [FDR]-p ≤ 0.004). Patients with a disease duration ≥ 5 vs < 5 years had significant cortical, subcortical and cerebellar atrophy, being spatially correlated with a higher distribution of serotoninergic and dopaminergic receptors (FDR-p ≤ 0.03). Compared to mildly-disabled patients, those with Expanded Disability Status Scale ≥ 3.0 or ≥ 4.0 had significant cortical, subcortical and cerebellar atrophy being associated with serotonergic, dopaminergic, opioid and cholinergic maps (FDR-p ≤ 0.04). Cognitively impaired vs cognitively preserved patients had widespread GM atrophy being spatially associated with serotonergic, dopaminergic, noradrenergic, cholinergic and glutamatergic maps (FDR-p ≤ 0.04). Fatigued vs non-fatigued MS patients had significant cortical, subcortical and cerebellar atrophy, not associated with neurotransmitter maps. No significant association between GM atrophy and neurotransmitter maps was found for depression. Regional GM atrophy with specific neurotransmitter systems may explain part of MS clinical manifestations, including locomotor disability, cognitive impairment and fatigue.
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16
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Fernandez CJ, Hanna FW, Pacak K, Nazari MA. Catecholamines and blood pressure regulation. ENDOCRINE HYPERTENSION 2023:19-34. [DOI: 10.1016/b978-0-323-96120-2.00010-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/06/2025]
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17
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Chitnis T, Vandercappellen J, King M, Brichetto G. Symptom Interconnectivity in Multiple Sclerosis: A Narrative Review of Potential Underlying Biological Disease Processes. Neurol Ther 2022; 11:1043-1070. [PMID: 35680693 PMCID: PMC9338216 DOI: 10.1007/s40120-022-00368-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 05/16/2022] [Indexed: 11/18/2022] Open
Abstract
Introduction Fatigue, cognitive impairment, depression, and pain are highly prevalent symptoms in multiple sclerosis (MS). These often co-occur and may be explained by a common etiology. By reviewing existing literature, we aimed to identify potential underlying biological processes implicated in the interconnectivity between these symptoms. Methods A literature search was conducted to identify articles reporting research into the biological mechanisms responsible for the manifestation of fatigue, cognitive impairment, depression, and pain in MS. PubMed was used to search for articles published from July 2011 to July 2021. We reviewed and assessed findings from the literature to identify biological processes common to the symptoms of interest. Results Of 693 articles identified from the search, 252 were selected following screening of titles and abstracts and assessing reference lists of review articles. Four biological processes linked with two or more of the symptoms of interest were frequently identified from the literature: (1) direct neuroanatomical changes to brain regions linked with symptoms of interest (e.g., thalamic injury associated with cognitive impairment, fatigue, and depression), (2) pro-inflammatory cytokines associated with so-called ‘sickness behavior,’ including manifestation of fatigue, transient cognitive impairment, depression, and pain, (3) dysregulation of monoaminergic pathways leading to depressive symptoms and fatigue, and (4) hyperactivity of the hypothalamic–pituitary-adrenal (HPA) axis as a result of pro-inflammatory cytokines promoting the release of brain noradrenaline, serotonin, and tryptophan, which is associated with symptoms of depression and cognitive impairment. Conclusion The co-occurrence of fatigue, cognitive impairment, depression, and pain in MS appears to be associated with a common set of etiological factors, namely neuroanatomical changes, pro-inflammatory cytokines, dysregulation of monoaminergic pathways, and a hyperactive HPA axis. This association of symptoms and biological processes has important implications for disease management strategies and, eventually, could help find a common therapeutic pathway that will impact both inflammation and neuroprotection. Supplementary Information The online version contains supplementary material available at 10.1007/s40120-022-00368-2.
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Affiliation(s)
- Tanuja Chitnis
- Department of Neurology, Brigham and Women's Hospital, 75 Francis Street, Boston, MA, 02115, USA.
| | | | - Miriam King
- Novartis Pharma AG, Fabrikstrasse 12-2, 4056, Basel, Switzerland
| | - Giampaolo Brichetto
- Associazione Italiana Sclerosi Multipla Rehabilitation Center, Via Operai, 30, 16149, Genoa, GE, Italy
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18
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Advanced diffusion-weighted imaging models better characterize white matter neurodegeneration and clinical outcomes in multiple sclerosis. J Neurol 2022; 269:4729-4741. [DOI: 10.1007/s00415-022-11104-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Revised: 03/23/2022] [Accepted: 03/24/2022] [Indexed: 10/18/2022]
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19
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Boshkovski T, Cohen‐Adad J, Misic B, Arnulf I, Corvol J, Vidailhet M, Lehéricy S, Stikov N, Mancini M. The Myelin-Weighted Connectome in Parkinson's Disease. Mov Disord 2022; 37:724-733. [PMID: 34936123 PMCID: PMC9303520 DOI: 10.1002/mds.28891] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 11/22/2021] [Accepted: 11/23/2021] [Indexed: 01/26/2023] Open
Abstract
BACKGROUND Even though Parkinson's disease (PD) is typically viewed as largely affecting gray matter, there is growing evidence that there are also structural changes in the white matter. Traditional connectomics methods that study PD may not be specific to underlying microstructural changes, such as myelin loss. OBJECTIVE The primary objective of this study is to investigate the PD-induced changes in myelin content in the connections emerging from the basal ganglia and the brainstem. For the weighting of the connectome, we used the longitudinal relaxation rate as a biologically grounded myelin-sensitive metric. METHODS We computed the myelin-weighted connectome in 35 healthy control subjects and 81 patients with PD. We used partial least squares to highlight the differences between patients with PD and healthy control subjects. Then, a ring analysis was performed on selected brainstem and subcortical regions to evaluate each node's potential role as an epicenter for disease propagation. Then, we used behavioral partial least squares to relate the myelin alterations with clinical scores. RESULTS Most connections (~80%) emerging from the basal ganglia showed a reduced myelin content. The connections emerging from potential epicentral nodes (substantia nigra, nucleus basalis of Meynert, amygdala, hippocampus, and midbrain) showed significant decrease in the longitudinal relaxation rate (P < 0.05). This effect was not seen for the medulla and the pons. CONCLUSIONS The myelin-weighted connectome was able to identify alteration of the myelin content in PD in basal ganglia connections. This could provide a different view on the importance of myelination in neurodegeneration and disease progression. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
| | - Julien Cohen‐Adad
- NeuroPoly Lab, Polytechnique MontréalMontréalQuebecCanada
- Mila – Quebec AI InstituteMontréalQuebecCanada
- Functional Neuroimaging Unit, Centre de Recherche de l'Institut Universitaire de Gériatrie de MontréalMontréalQuebecCanada
| | | | - Isabelle Arnulf
- Sorbonne Université, Paris Brain Institute – ICM, INSERM, CNRS, Assistance Publique Hôpitaux de Paris, Hôpital Pitié‐SalpêtrièreParisFrance
| | - Jean‐Christophe Corvol
- Sorbonne Université, Paris Brain Institute – ICM, INSERM, CNRS, Assistance Publique Hôpitaux de Paris, Hôpital Pitié‐SalpêtrièreParisFrance
| | - Marie Vidailhet
- Sorbonne Université, Paris Brain Institute – ICM, INSERM, CNRS, Assistance Publique Hôpitaux de Paris, Hôpital Pitié‐SalpêtrièreParisFrance
| | - Stéphane Lehéricy
- Sorbonne Université, Paris Brain Institute – ICM, INSERM, CNRS, Assistance Publique Hôpitaux de Paris, Hôpital Pitié‐SalpêtrièreParisFrance
| | - Nikola Stikov
- NeuroPoly Lab, Polytechnique MontréalMontréalQuebecCanada
- Montreal Heart InstituteMontréalQuebecCanada
| | - Matteo Mancini
- NeuroPoly Lab, Polytechnique MontréalMontréalQuebecCanada
- Department of NeuroscienceBrighton and Sussex Medical School, University of SussexBrightonUnited Kingdom
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff UniversityCardiffUnited Kingdom
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20
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Finkelstein A, Faiyaz A, Weber MT, Qiu X, Uddin MN, Zhong J, Schifitto G. Fixel-Based Analysis and Free Water Corrected DTI Evaluation of HIV-Associated Neurocognitive Disorders. Front Neurol 2021; 12:725059. [PMID: 34803875 PMCID: PMC8600320 DOI: 10.3389/fneur.2021.725059] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Accepted: 10/04/2021] [Indexed: 12/12/2022] Open
Abstract
Background: White matter (WM) damage is a consistent finding in HIV-infected (HIV+) individuals. Previous studies have evaluated WM fiber tract-specific brain regions in HIV-associated neurocognitive disorders (HAND) using diffusion tensor imaging (DTI). However, DTI might lack an accurate biological interpretation, and the technique suffers from several limitations. Fixel-based analysis (FBA) and free water corrected DTI (fwcDTI) have recently emerged as useful techniques to quantify abnormalities in WM. Here, we sought to evaluate FBA and fwcDTI metrics between HIV+ and healthy controls (HIV−) individuals. Using machine learning classifiers, we compared the specificity of both FBA and fwcDTI metrics in their ability to distinguish between individuals with and without cognitive impairment in HIV+ individuals. Methods: Forty-two HIV+ and 52 HIV– participants underwent MRI exam, clinical, and neuropsychological assessments. FBA metrics included fiber density (FD), fiber bundle cross section (FC), and fiber density and cross section (FDC). We also obtained fwcDTI metrics such as fractional anisotropy (FAT) and mean diffusivity (MDT). Tract-based spatial statistics (TBSS) was performed on FAT and MDT. We evaluated the correlations between MRI metrics with cognitive performance and blood markers, such as neurofilament light chain (NfL), and Tau protein. Four different binary classifiers were used to show the specificity of the MRI metrics for classifying cognitive impairment in HIV+ individuals. Results: Whole-brain FBA showed significant reductions (up to 15%) in various fiber bundles, specifically the cerebral peduncle, posterior limb of internal capsule, middle cerebellar peduncle, and superior corona radiata. TBSS of fwcDTI metrics revealed decreased FAT in HIV+ individuals compared to HIV– individuals in areas consistent with those observed in FBA, but these were not significant. Machine learning classifiers were consistently better able to distinguish between cognitively normal patients and those with cognitive impairment when using fixel-based metrics as input features as compared to fwcDTI metrics. Conclusion: Our findings lend support that FBA may serve as a potential in vivo biomarker for evaluating and monitoring axonal degeneration in HIV+ patients at risk for neurocognitive impairment.
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Affiliation(s)
- Alan Finkelstein
- Department of Biomedical Engineering, University of Rochester, Rochester, NY, United States
| | - Abrar Faiyaz
- Department of Electrical and Computer Engineering, University of Rochester, Rochester, NY, United States
| | - Miriam T Weber
- Department of Neurology, University of Rochester, Rochester, NY, United States
| | - Xing Qiu
- Department of Biostatistics and Computational Biology, University of Rochester, Rochester, NY, United States
| | - Md Nasir Uddin
- Department of Neurology, University of Rochester, Rochester, NY, United States
| | - Jianhui Zhong
- Department of Biomedical Engineering, University of Rochester, Rochester, NY, United States.,Department of Physics and Astronomy, University of Rochester, Rochester, NY, United States.,Department of Imaging Sciences, University of Rochester, Rochester, NY, United States
| | - Giovanni Schifitto
- Department of Electrical and Computer Engineering, University of Rochester, Rochester, NY, United States.,Department of Neurology, University of Rochester, Rochester, NY, United States.,Department of Imaging Sciences, University of Rochester, Rochester, NY, United States
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21
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Fixel-based Analysis of Diffusion MRI: Methods, Applications, Challenges and Opportunities. Neuroimage 2021; 241:118417. [PMID: 34298083 DOI: 10.1016/j.neuroimage.2021.118417] [Citation(s) in RCA: 127] [Impact Index Per Article: 31.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2020] [Revised: 07/11/2021] [Accepted: 07/20/2021] [Indexed: 12/13/2022] Open
Abstract
Diffusion MRI has provided the neuroimaging community with a powerful tool to acquire in-vivo data sensitive to microstructural features of white matter, up to 3 orders of magnitude smaller than typical voxel sizes. The key to extracting such valuable information lies in complex modelling techniques, which form the link between the rich diffusion MRI data and various metrics related to the microstructural organization. Over time, increasingly advanced techniques have been developed, up to the point where some diffusion MRI models can now provide access to properties specific to individual fibre populations in each voxel in the presence of multiple "crossing" fibre pathways. While highly valuable, such fibre-specific information poses unique challenges for typical image processing pipelines and statistical analysis. In this work, we review the "Fixel-Based Analysis" (FBA) framework, which implements bespoke solutions to this end. It has recently seen a stark increase in adoption for studies of both typical (healthy) populations as well as a wide range of clinical populations. We describe the main concepts related to Fixel-Based Analyses, as well as the methods and specific steps involved in a state-of-the-art FBA pipeline, with a focus on providing researchers with practical advice on how to interpret results. We also include an overview of the scope of all current FBA studies, categorized across a broad range of neuro-scientific domains, listing key design choices and summarizing their main results and conclusions. Finally, we critically discuss several aspects and challenges involved with the FBA framework, and outline some directions and future opportunities.
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22
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Melnikov M, Pashenkov M, Boyko A. Dopaminergic Receptor Targeting in Multiple Sclerosis: Is There Therapeutic Potential? Int J Mol Sci 2021; 22:ijms22105313. [PMID: 34070011 PMCID: PMC8157879 DOI: 10.3390/ijms22105313] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2021] [Revised: 05/14/2021] [Accepted: 05/17/2021] [Indexed: 02/07/2023] Open
Abstract
Dopamine is a neurotransmitter that mediates neuropsychological functions of the central nervous system (CNS). Recent studies have shown the modulatory effect of dopamine on the cells of innate and adaptive immune systems, including Th17 cells, which play a critical role in inflammatory diseases of the CNS. This article reviews the literature data on the role of dopamine in the regulation of neuroinflammation in multiple sclerosis (MS). The influence of dopaminergic receptor targeting on experimental autoimmune encephalomyelitis (EAE) and MS pathogenesis, as well as the therapeutic potential of dopaminergic drugs as add-on pathogenetic therapy of MS, is discussed.
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MESH Headings
- Animals
- Dopamine/immunology
- Dopamine/physiology
- Dopamine Agents/pharmacology
- Encephalomyelitis, Autoimmune, Experimental/drug therapy
- Encephalomyelitis, Autoimmune, Experimental/immunology
- Encephalomyelitis, Autoimmune, Experimental/physiopathology
- Humans
- Mice
- Models, Immunological
- Models, Neurological
- Multiple Sclerosis/drug therapy
- Multiple Sclerosis/immunology
- Multiple Sclerosis/physiopathology
- Neuroimmunomodulation/drug effects
- Neuroimmunomodulation/immunology
- Neuroimmunomodulation/physiology
- Receptors, Dopamine/drug effects
- Receptors, Dopamine/immunology
- Receptors, Dopamine/physiology
- Th17 Cells/drug effects
- Th17 Cells/immunology
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Affiliation(s)
- Mikhail Melnikov
- Department of Neurology, Neurosurgery and Medical Genetics, Pirogov Russian National Research Medical University, 117997 Moscow, Russia;
- Department of Neuroimmunology, Federal Center of Brain Research and Neurotechnology of the Federal Medical-Biological Agency of Russia, 117997 Moscow, Russia
- Laboratory of Clinical Immunology, National Research Center Institute of Immunology of the Federal Medical-Biological Agency of Russia, 115522 Moscow, Russia;
- Correspondence: ; Tel.: +7-926-331-8946
| | - Mikhail Pashenkov
- Laboratory of Clinical Immunology, National Research Center Institute of Immunology of the Federal Medical-Biological Agency of Russia, 115522 Moscow, Russia;
| | - Alexey Boyko
- Department of Neurology, Neurosurgery and Medical Genetics, Pirogov Russian National Research Medical University, 117997 Moscow, Russia;
- Department of Neuroimmunology, Federal Center of Brain Research and Neurotechnology of the Federal Medical-Biological Agency of Russia, 117997 Moscow, Russia
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23
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Carandini T, Cercignani M, Galimberti D, Scarpini E, Bozzali M. The distinct roles of monoamines in multiple sclerosis: A bridge between the immune and nervous systems? Brain Behav Immun 2021; 94:381-391. [PMID: 33662501 DOI: 10.1016/j.bbi.2021.02.030] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Revised: 02/24/2021] [Accepted: 02/25/2021] [Indexed: 12/20/2022] Open
Abstract
The monoaminergic neurotransmitters dopamine, noradrenaline, and serotonin are pivotal actors of the interplay between the nervous and the immune system due to their ability of binding to cell-receptors of both systems, crucially regulating their function within the central nervous system and the periphery. As monoamines are dysfunctional in many neurological and psychiatric diseases, they have been successfully used as pharmacological targets. Multiple sclerosis (MS) is one of the best examples of neurological disease caused by an altered interaction between the nervous and immune system and emerging evidence supports a dysregulation of monoaminergic systems in the pathogenesis of MS, secondary to both inflammation-induced reduction of monoamines' synthesis and structural damage to monoaminergic pathways within the brain. Here we review the evidence for monoamines being key mediators of neuroimmune interaction, affecting MS pathogenesis and course. Moreover, we discuss how the reduction/dysfunction of monoamines in MS may contribute to some clinical features typical of the disease, particularly fatigue and depression. Finally, we summarize different drugs targeting monoamines that are currently under evaluation for their potential efficacy to treat MS, as well as to alleviate fatigue and depression in MS.
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Affiliation(s)
- Tiziana Carandini
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.
| | - Mara Cercignani
- Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, UK; Neuroimaging Laboratory, Santa Lucia Foundation IRCCS, Rome, Italy
| | - Daniela Galimberti
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy; University of Milan, Dino Ferrari Center, Milan, Italy
| | - Elio Scarpini
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy; University of Milan, Dino Ferrari Center, Milan, Italy
| | - Marco Bozzali
- Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, UK; Rita Levi Montalcini Department of Neuroscience, University of Torino, Turin, Italy
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