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Zekibakhsh Mohammadi N, Kianimoghadam AS, Mikaeili N, Asgharian SS, Jafari M, Masjedi-Arani A. Sleep Disorders and Fatigue among Patients with MS: The Role of Depression, Stress, and Anxiety. Neurol Res Int 2024; 2024:6776758. [PMID: 38322749 PMCID: PMC10843872 DOI: 10.1155/2024/6776758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 01/07/2024] [Accepted: 01/18/2024] [Indexed: 02/08/2024] Open
Abstract
Sleep disorders and fatigue represent prominent symptoms frequently experienced by individuals with multiple sclerosis (MS). Some psychological factors such as depression, stress, and anxiety seem to have a relationship with such problems. This study aimed to examine the role of depression, stress, and anxiety in predicting sleep disorders and fatigue among patients with MS. Employing a cross-sectional descriptive-correlational design, the study involved a sample size of 252 participants selected through purposive sampling based on inclusion and exclusion criteria. We utilized a demographic information questionnaire along with the Mini-Sleep Questionnaire (MSQ), Fatigue Severity Scale (FSS), and Depression, Anxiety, and Stress Scale (DASS-21) to collect data and analyzed them applying SPSS22, incorporating statistical measures including Pearson correlation and regression. The results of the Pearson correlation coefficient showed that sleep disorders had a positive and significant relationship with depression (r = 0.56; P < 0.001), stress (r = 0.40; P < 0.001), and anxiety (r = 0.52; P < 0.001). There was no significant relationship between age and the development of sleep disorders in total score (r = -0.001; P < 0.985), but age had a relationship with insomnia (r = -0.146; P < 0.021) and oversleeping (r = 0.153; P < 0.015). Age and fatigue did not have a significant relationship as well (r = -0.044; P < 0.941). In addition, fatigue had a positive and significant relationship with depression (r = 0.52; P < 0.001), stress (r = 0.48; P < 0.001), and anxiety (r = 0.54; P < 0.001). The results of the regression analysis also showed that depression, stress, and anxiety predict 0.37% of the total variance of sleep disorders (F = 48.34; P < 0.001) and 0.35% of the total variance of fatigue (F = 44.64; P < 0.001). Our findings suggest that depression, stress, and anxiety play a significant role in predicting sleep disorders and fatigue among patients with MS. This study has been reported in accordance with the TREND checklist for nonrandomized trials.
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Affiliation(s)
- Nassim Zekibakhsh Mohammadi
- Department of Psychology, Faculty of Educational Sciences and Psychology, University of Mohaghegh Ardabili, Ardabil, Iran
| | - Amir Sam Kianimoghadam
- Department of Clinical Psychology, Religion and Health Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Niloofar Mikaeili
- Department of Psychology, Faculty of Educational Sciences and Psychology, University of Mohaghegh Ardabili, Ardabil, Iran
| | | | - Mahdieh Jafari
- Department of Psychology, Faculty of Educational Sciences and Psychology, University of Mohaghegh Ardabili, Ardabil, Iran
| | - Abbas Masjedi-Arani
- Department of Clinical Psychology, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
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Antypa D, Simos NJ, Panou T, Spyridaki E, Kagialis A, Kosteletou E, Kavroulakis E, Mastorodemos V, Papadaki E. Distinct hemodynamic and functional connectivity features of fatigue in clinically isolated syndrome and multiple sclerosis: accounting for the confounding effect of concurrent depression symptoms. Neuroradiology 2023:10.1007/s00234-023-03174-1. [PMID: 37301785 DOI: 10.1007/s00234-023-03174-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 06/04/2023] [Indexed: 06/12/2023]
Abstract
PURPOSE This study aims to identify common and distinct hemodynamic and functional connectivity (FC) features for self-rated fatigue and depression symptoms in patients with clinically isolated syndrome (CIS) and relapsing-remitting multiple sclerosis (RR-MS). METHODS Twenty-four CIS, 29 RR-MS patients, and 39 healthy volunteers were examined using resting-state fMRI (rs-fMRI) to obtain whole-brain maps of (i) hemodynamic response patterns (through time shift analysis), (ii) FC (via intrinsic connectivity contrast maps), and (iii) coupling between hemodynamic response patterns and FC. Each regional map was correlated with fatigue scores, controlling for depression, and with depression scores, controlling for fatigue. RESULTS In CIS patients, the severity of fatigue was associated with accelerated hemodynamic response in the insula, hyperconnectivity of the superior frontal gyrus, and evidence of reduced hemodynamics-FC coupling in the left amygdala. In contrast, depression severity was associated with accelerated hemodynamic response in the right limbic temporal pole, hypoconnectivity of the anterior cingulate gyrus, and increased hemodynamics-FC coupling in the left amygdala. In RR-MS patients, fatigue was associated with accelerated hemodynamic response in the insula and medial superior frontal cortex, increased functional role of the left amygdala, and hypoconnectivity of the dorsal orbitofrontal cortex, while depression symptom severity was linked to delayed hemodynamic response in the medial superior frontal gyrus; hypoconnectivity of the insula, ventromedial thalamus, dorsolateral prefrontal cortex, and posterior cingulate; and decreased hemodynamics-FC coupling of the medial orbitofrontal cortex. CONCLUSION There are distinct FC and hemodynamic responses, as well as different magnitude and topography of hemodynamic connectivity coupling, associated with fatigue and depression in early and later stages of MS.
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Affiliation(s)
- Despina Antypa
- Department of Psychiatry, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
| | - Nicholas John Simos
- Computational Bio-Medicine Laboratory, Institute of Computer Science, Foundation for Research and Technology, Hellas, Heraklion, Crete, Greece
| | - Theodora Panou
- Department of Psychiatry, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
| | - Eirini Spyridaki
- Department of Psychiatry, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
| | - Antonios Kagialis
- Department of Psychiatry, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
| | - Emmanouela Kosteletou
- Institute of Applied Mathematics, Foundation for Research and Technology, Hellas, Heraklion, Crete, Greece
| | - Eleftherios Kavroulakis
- Department of Radiology, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
| | - Vasileios Mastorodemos
- Department of Neurology, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
| | - Efrosini Papadaki
- Computational Bio-Medicine Laboratory, Institute of Computer Science, Foundation for Research and Technology, Hellas, Heraklion, Crete, Greece.
- Department of Radiology, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece.
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Opelt BL, Lewis C, Hughes AJ. Discrepancies between self-report and objective sleep outcomes are associated with cognitive impairment and fatigue in people with multiple sclerosis and insomnia. Mult Scler Relat Disord 2023; 71:104588. [PMID: 36841176 DOI: 10.1016/j.msard.2023.104588] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 02/03/2023] [Accepted: 02/19/2023] [Indexed: 02/24/2023]
Abstract
OBJECTIVES The primary aim of this study was to assess the degree to which discrepancies between self-reported and actigraphy-based measures of sleep are associated with specific demographic, disease characteristics, and clinical features in a sample of individuals with multiple sclerosis (MS) reporting clinically significant insomnia symptoms. METHODS Participants were 90 community-based participants with MS and insomnia. Measures included the Pittsburgh Sleep Quality Index (PSQI), Beck Depression Inventory-Fast Screen (BDI-FS), Modified Fatigue Impact Scale (MFIS), and MS Neuropsychological Screening Questionnaire (MSNQ), and wrist actigraphy-derived sleep parameters. Discrepancy scores were calculated by subtracting actigraphy-derived values from PSQI-derived values for sleep latency (SL), total sleep time (TST), and sleep efficiency (SE). RESULTS Correlations between PSQI and actigraphy-derived values were weak. Significant discrepancies, with moderate-to-large effect sizes, were observed between PSQI and actigraphy for SL, TST, and SE, whereby the PSQI yielded longer SL, shorter TST, and less SE than actigraphy. MSNQ elevations correlated with greater PSQI-actigraphy discrepancies in SL and TST. MFIS elevations correlated with greater discrepancies in TST. Discrepancies were not significantly related to BDI-FS, gender, race, education level, or MS type. CONCLUSIONS Results emphasize the importance of assessing fatigue with sleep, and when feasible, inclusion of both self-report and actigraphy measures.
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Affiliation(s)
- Brett L Opelt
- Department of Physical Medicine and Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, USA.
| | - Christa Lewis
- Department of Psychology, University of Maryland, Baltimore County, Baltimore, USA
| | - Abbey J Hughes
- Department of Physical Medicine and Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, USA
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Wang J, Sun L, Chen L, Sun J, Xie Y, Tian D, Gao L, Zhang D, Xia M, Wu T. Common and distinct roles of amygdala subregional functional connectivity in non-motor symptoms of Parkinson's disease. NPJ Parkinsons Dis 2023; 9:28. [PMID: 36806219 PMCID: PMC9938150 DOI: 10.1038/s41531-023-00469-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 02/02/2023] [Indexed: 02/19/2023] Open
Abstract
Neuroimaging studies suggest a pivotal role of amygdala dysfunction in non-motor symptoms (NMS) of Parkinson's disease (PD). However, the relationship between amygdala subregions (the centromedial (CMA), basolateral (BLA) and superficial amygdala (SFA)) and NMS has not been delineated. We used resting-state functional MRI to examine the PD-related alterations in functional connectivity for amygdala subregions. The left three subregions and right BLA exhibited between-group differences, and were commonly hypo-connected with the frontal, temporal, insular cortex, and putamen in PD. Each subregion displayed distinct hypoconnectivity with the limbic systems. Partial least-squares analysis revealed distinct amygdala subregional involvement in diverse NMS. Hypo-connectivity of all four subregions was associated with emotion, pain, olfaction, and cognition. Hypo-connectivity of the left SFA was associated with sleepiness. Our findings highlight the hypofunction of the amygdala subregions in PD and their preliminary associations with NMS, providing new insights into the pathogenesis of NMS.
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Affiliation(s)
- Junling Wang
- grid.24696.3f0000 0004 0369 153XCenter for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070 China
| | - Lianglong Sun
- grid.20513.350000 0004 1789 9964State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100091 China ,grid.20513.350000 0004 1789 9964Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100091 China ,grid.20513.350000 0004 1789 9964IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100091 China
| | - Lili Chen
- grid.24696.3f0000 0004 0369 153XCenter for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070 China
| | - Junyan Sun
- grid.24696.3f0000 0004 0369 153XCenter for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070 China
| | - Yapei Xie
- grid.20513.350000 0004 1789 9964State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100091 China ,grid.20513.350000 0004 1789 9964Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100091 China ,grid.20513.350000 0004 1789 9964IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100091 China
| | - Dezheng Tian
- grid.20513.350000 0004 1789 9964State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100091 China ,grid.20513.350000 0004 1789 9964Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100091 China ,grid.20513.350000 0004 1789 9964IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100091 China
| | - Linlin Gao
- grid.417031.00000 0004 1799 2675Department of General Medicine, Tianjin Union Medical Center, Tianjin, 300122 China
| | - Dongling Zhang
- grid.24696.3f0000 0004 0369 153XCenter for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070 China
| | - Mingrui Xia
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100091, China. .,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100091, China. .,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100091, China.
| | - Tao Wu
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China.
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Abstract
INTRODUCTION Fatigue is a common and debilitating symptom among multiple sclerosis (MS) patients with a prevalence up to 81% and with a considerable impact on quality of life. However, its subjective nature makes it difficult to define and quantify in clinical practice. Research aimed at a more precise definition and knowledge of this construct is thus continuously growing. AREAS COVERED This review summarizes the most relevant updates available on PubMed up to July 1st 2022 regarding: the assessment methods that aim to measure the concept of fatigue (as opposed to fatigability), the possible treatment pathways currently available to clinicians, interconnection with the pathophysiological substrates and with the common comorbidities of MS, such as depression and mood disorders. EXPERT OPINION The in-depth study of fatigue can help to better understand its actual impact on MS patients and can stimulate clinicians towards a more valid approach, through a targeted analysis of this symptom. Considering fatigue from a multidimensional perspective allows the use of patient-tailored methods for its identification and subsequent treatment by different professional figures. Better identification of methods and treatment pathways would reduce the extremely negative impact of fatigue on MS patients' quality of life.
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Affiliation(s)
- Olga Marchesi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Carmen Vizzino
- 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 and 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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Ruiz-Rizzo AL, Bublak P, Kluckow S, Finke K, Gaser C, Schwab M, Güllmar D, Müller HJ, Witte OW, Rupprecht S. Neural distinctiveness of fatigue and low sleep quality in multiple sclerosis. Eur J Neurol 2022; 29:3017-3027. [PMID: 35699354 DOI: 10.1111/ene.15445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 06/08/2022] [Indexed: 11/30/2022]
Abstract
BACKGROUND AND PURPOSE Fatigue and low sleep quality in multiple sclerosis (MS) are closely related symptoms. Here, the associations between the brain's functional connectivity (FC) and fatigue and low sleep quality were investigated to determine the degree of neural distinctiveness of these symptoms. METHOD A hundred and four patients with relapsing-remitting MS (age 38.9 ± 10.2 years, 66 females) completed the Modified Fatigue Impact Scale and the Pittsburgh Sleep Quality Index and underwent resting-state functional magnetic resonance imaging. FC was analyzed using independent-component analysis in sensorimotor, default-mode, fronto-parietal and basal-ganglia networks. Multiple linear regression models allowed us to test the association between FC and fatigue and sleep quality whilst controlling for one another as well as for demographic, disease-related and imaging variables. RESULTS Higher fatigue correlated with lower sleep quality (r = 0.54, p < 0.0001). Higher fatigue was associated with lower FC of the precentral gyrus in the sensorimotor network, the precuneus in the posterior default-mode network and the superior frontal gyrus in the left fronto-parietal network, independently of sleep quality. Lower sleep quality was associated with lower FC of the left intraparietal sulcus in the left fronto-parietal network, independently of fatigue. Specific associations were found between fatigue and the sensorimotor network's global FC and between low sleep quality and the left fronto-parietal network's global FC. CONCLUSION Despite the high correlation between fatigue and low sleep quality in the clinical picture, our findings clearly indicate that, on the neural level, fatigue and low sleep quality in MS are associated with decreased FC in distinct functional brain networks.
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Affiliation(s)
- Adriana L Ruiz-Rizzo
- Department of Psychology, General and Experimental Psychology Unit, LMU Munich, Munich, Germany.,Department of Neurology, Jena University Hospital, Jena, Germany
| | - Peter Bublak
- Department of Neurology, Jena University Hospital, Jena, Germany
| | - Steffen Kluckow
- Department of Neurology, Jena University Hospital, Jena, Germany
| | - Kathrin Finke
- Department of Psychology, General and Experimental Psychology Unit, LMU Munich, Munich, Germany.,Department of Neurology, Jena University Hospital, Jena, Germany
| | - Christian Gaser
- Department of Neurology, Jena University Hospital, Jena, Germany
| | - Matthias Schwab
- Department of Neurology, Jena University Hospital, Jena, Germany
| | - Daniel Güllmar
- Department of Neurology, Jena University Hospital, Jena, Germany
| | - Hermann J Müller
- Department of Psychology, General and Experimental Psychology Unit, LMU Munich, Munich, Germany
| | - Otto W Witte
- Department of Neurology, Jena University Hospital, Jena, Germany
| | - Sven Rupprecht
- Department of Neurology, Jena University Hospital, Jena, Germany
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Fuchs TA, Vaughn CB, Benedict RHB, Weinstock-Guttman B, Bergsland N, Jakimovski D, Ramasamy D, Zivadinov R, Dwyer MG. Patient-Reported Outcome Severity and Emotional Salience Network Disruption in Multiple Sclerosis. Brain Imaging Behav 2022; 16:1252-1259. [PMID: 34985619 DOI: 10.1007/s11682-021-00614-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/02/2021] [Indexed: 11/25/2022]
Abstract
BACKGROUND Overall burden of white matter damage is associated with increased self-report fatigue severity in people with multiple sclerosis. However, a paradoxically opposite association was reported for white matter damage to tracts in specific subnetworks including the amygdala, temporal pole, and insula. Based on neuroanatomical principles and other data from the literature, we hypothesized that these results might be indicative of a broader relationship between damage to these subnetworks and impaired recognition of negative emotional salience central to patient-reported outcomes. OBJECTIVE We examined whether damage in the same previously-identified subnetworks is also associated with lower self-report depressive symptoms, something which may be decreased in individuals with impaired recognition of negative emotional salience. Other patient characteristics were also explored. METHODS In a cohort of 137 people with multiple sclerosis, we measured location-specific network white matter tract damage in the proposed negative emotional salience network, along with self-report severity of depressive symptoms and cognitive problems, personality characteristics, objective cognitive performance, and physical disability. We applied regression analyses, accounting for lesion burden, to explore the relationship between damage in the proposed negative emotional salience network and these factors. RESULTS We found disruption within the negative emotional salience network is associated with lower self-report depressive symptoms (β = -0.277, p = 0.036), cognitive complaints (r = -0.196, p = 0.024) and personality trait Neuroticism (r = -0.179, p = 0.042). In contrast, damage within this network was not significantly associated with objective cognitive processing speed, personality trait Openness, or physical disability. CONCLUSION The identified network may be a generalizable network which corresponds to the recognition of negative emotional salience, but not to objective factors such as processing speed and physical disability. Damage to this network may paradoxically buffer against negative emotional perception of symptom severity, central to patient-reported outcomes.
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Affiliation(s)
- Tom A Fuchs
- Jacobs Multiple Sclerosis Center for Treatment and Research, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), 100 High St, Buffalo, NY, 14203, USA.
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), 100 High St, Buffalo, NY, 14203, USA.
| | - Caila B Vaughn
- Jacobs Multiple Sclerosis Center for Treatment and Research, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), 100 High St, Buffalo, NY, 14203, USA
| | - Ralph H B Benedict
- Jacobs Multiple Sclerosis Center for Treatment and Research, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), 100 High St, Buffalo, NY, 14203, USA
| | - Bianca Weinstock-Guttman
- Jacobs Multiple Sclerosis Center for Treatment and Research, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), 100 High St, Buffalo, NY, 14203, USA
| | - Niels Bergsland
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), 100 High St, Buffalo, NY, 14203, USA
- IRCSS, Fondazione Don Carlo Gnocchi, Milan, Italy
| | - Dejan Jakimovski
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), 100 High St, Buffalo, NY, 14203, USA
| | - Deepa Ramasamy
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), 100 High St, Buffalo, NY, 14203, USA
| | - Robert Zivadinov
- Jacobs Multiple Sclerosis Center for Treatment and Research, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), 100 High St, Buffalo, NY, 14203, USA
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), 100 High St, Buffalo, NY, 14203, USA
- Center for Biomedical Imaging, Clinical Translational Science Institute, University at Buffalo, State University of New York (SUNY), Buffalo, NY, USA
| | - Michael G Dwyer
- Jacobs Multiple Sclerosis Center for Treatment and Research, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), 100 High St, Buffalo, NY, 14203, USA
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), 100 High St, Buffalo, NY, 14203, USA
- Center for Biomedical Imaging, Clinical Translational Science Institute, University at Buffalo, State University of New York (SUNY), Buffalo, NY, USA
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Newland P, Chen L, Sun P, Zempel J. Neurophysiological Correlates of Fatigue in Multiple Sclerosis. J Nurse Pract 2021. [DOI: 10.1016/j.nurpra.2021.02.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Berard JA, Walker LAS. Increasing the Clinical Utility of the Paced Auditory Serial Addition Test: Normative Data for Standard, Dyad, and Cognitive Fatigability Scoring. Cogn Behav Neurol 2021; 34:107-16. [PMID: 34074865 DOI: 10.1097/WNN.0000000000000268] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Accepted: 09/24/2020] [Indexed: 11/26/2022]
Abstract
BACKGROUND No normative data currently exist that would allow clinicians to decide whether the degree of cognitive fatigability (CF) experienced in individuals with neurologic disease is greater than expected when compared with a healthy population. OBJECTIVE To establish discrete and regression-based normative data for CF as defined by an objective decrement in performance over the course of a cognitive task; namely, the Paced Auditory Serial Addition Test (PASAT). In addition, to develop discrete and regression-based normative data for PASAT performance scores-dyad and percent dyad-for which data do not currently exist. METHOD One hundred and seventy-eight healthy individuals completed the PASAT as part of a larger neuropsychological battery. PASAT performance scores including total correct responses, total dyads, and percent dyad were calculated. CF scores were calculated by comparing the individuals' performance on the first half (or third) of the test to their performance on the last half (or third) in order to capture any within-task performance decrements over time. RESULTS Both age- and education-based discrete normative data and demographically adjusted (sex, age, and education) regression-based formulas were established for the PASAT performance scores and the CF scores. CONCLUSION The development of these normative data will allow for greater interpretation of an individual's performance on the PASAT, beyond just the total correct score, through the use of dyad and percent dyad scores. With respect to CF, these data will allow clinicians to objectively quantify decrements in cognitive performance over time better in individuals with neurologic diseases.
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Ulrichsen KM, Kolskår KK, Richard G, Alnæs D, Dørum ES, Sanders AM, Tornås S, Sánchez JM, Engvig A, Ihle-Hansen H, de Schotten MT, Nordvik JE, Westlye LT. Structural brain disconnectivity mapping of post-stroke fatigue. Neuroimage Clin 2021; 30:102635. [PMID: 33799271 PMCID: PMC8044723 DOI: 10.1016/j.nicl.2021.102635] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Revised: 02/15/2021] [Accepted: 03/15/2021] [Indexed: 01/04/2023]
Abstract
We tested for associations between post stroke fatigue (PSF) and both lesion characteristics and brain structural disconnectome in 84 S patients. Results provided no evidence supporting a simple association between PSF severity and lesion characteristics or disconnectivity. PSF was strongly correlated with depression. Further studies including patients with more severe symptoms are needed to generalize the findings across a wider clinical spectrum.
Stroke patients commonly suffer from post stroke fatigue (PSF). Despite a general consensus that brain perturbations constitute a precipitating event in the multifactorial etiology of PSF, the specific predictive value of conventional lesion characteristics such as size and localization remains unclear. The current study represents a novel approach to assess the neural correlates of PSF in chronic stroke patients. While previous research has focused primarily on lesion location or size, with mixed or inconclusive results, we targeted the extended structural network implicated by the lesion, and evaluated the added explanatory value of a structural disconnectivity approach with regards to the brain correlates of PSF. To this end, we estimated individual structural brain disconnectome maps in 84 S survivors in the chronic phase (≥3 months post stroke) using information about lesion location and normative white matter pathways obtained from 170 healthy individuals. PSF was measured by the Fatigue Severity Scale (FSS). Voxel wise analyses using non-parametric permutation-based inference were conducted on disconnectome maps to estimate regional effects of disconnectivity. Associations between PSF and global disconnectivity and clinical lesion characteristics were tested by linear models, and we estimated Bayes factor to quantify the evidence for the null and alternative hypotheses, respectively. The results revealed no significant associations between PSF and disconnectome measures or lesion characteristics, with moderate evidence in favor of the null hypothesis. These results suggest that symptoms of post-stroke fatigue among chronic stroke patients are not simply explained by lesion characteristics or the extent and distribution of structural brain disconnectome, and are discussed in light of methodological considerations.
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Affiliation(s)
- Kristine M Ulrichsen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway; Department of Psychology, University of Oslo, Norway; Sunnaas Rehabilitation Hospital HT, Nesodden, Norway.
| | - Knut K Kolskår
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway; Department of Psychology, University of Oslo, Norway; Sunnaas Rehabilitation Hospital HT, Nesodden, Norway
| | - Geneviève Richard
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway
| | - Dag Alnæs
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway; Bjørknes College, Oslo, Norway
| | - Erlend S Dørum
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway; Department of Psychology, University of Oslo, Norway; Sunnaas Rehabilitation Hospital HT, Nesodden, Norway
| | - Anne-Marthe Sanders
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway; Department of Psychology, University of Oslo, Norway; Sunnaas Rehabilitation Hospital HT, Nesodden, Norway
| | | | - Jennifer Monereo Sánchez
- Faculty of Health, Medicine and Life Sciences, Maastricht University, Netherlands; Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Netherlands
| | - Andreas Engvig
- Department of Nephrology, Oslo University Hospital, Ullevål, Norway
| | | | - Michel Thiebaut de Schotten
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France; Groupe d'Imagerie Neurofonctionnelle, Institut Des Maladies Neurodégénératives- UMR 5293, CNRS, CEA University of Bordeaux, Bordeaux, France
| | | | - Lars T Westlye
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway; Department of Psychology, University of Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Norway.
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11
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Dacosta-aguayo R, Wylie G, Deluca J, Genova H, Trojano L. Anatomical Covariance Analysis: Detection of Disrupted Correlation Network Related to Clinical Trait Fatigue in Multiple Sclerosis: A Pilot Study. Behav Neurol 2020; 2020:1-9. [PMID: 32175581 PMCID: PMC7775148 DOI: 10.1155/2020/5807496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Background Fatigue is one of the most distressing symptoms among persons with multiple sclerosis (PwMS). The experience of fatigue is inherently interoceptive, yet no study to date has explicitly investigated the insular cortex (IC) as a primary goal in the experience of fatigue in PwMS. In addition, it is unknown how brain regions such as IC play a role in state or trait fatigue. Objective Assess the involvement of the IC in trait fatigue and state fatigue in PwMS with and without clinical fatigue. Methods Trait and state fatigue, cognitive status, and structural MRI were assessed in 27 PwMS. PwMS were stratified into nonclinical fatigue (nF-MS, FSS ≤ 4.0) (n = 10) and clinical fatigue (F-MS, FSS ≥ 5.0) (n = 10). Voxel-based morphometry analysis (VBM) for the whole sample (n = 20) and for the two groups was performed. Anatomical covariance analysis (ACA) analysis was conducted by selecting different volumes included in the corticostriatal network (CoStN) and analyzing interhemispheric correlations between those volumes to explore the state of the CoStN in both groups. Results In the VBM analysis, when considering the whole sample of PwMS, higher levels of trait fatigue were negatively associated with grey matter (GM) volume in the left dorsal anterior insula (dAI) (rho = −0.647; p = 0.002; R2 = 0.369). When comparing nF-MS versus F-MS, significant differences were found in the left dAI, where the F-MS group showed less GM volume in the left dAI. In the ACA analysis, the F-MS group showed fewer significant interhemispheric correlations in comparison with the Low-FSS group. Conclusions The present results provide support to the interoceptive component of self-reported fatigue and suggest that changes in the relationship between the different anatomical regions involved in the CoStN are present even in nonclinical trait fatigue. Those changes might be responsible for the experience of trait fatigue in PwMS. Future studies with larger samples and multimodal MRI acquisitions should be considered to fully understand the changes in the CoStN and the specific role of the IC in trait fatigue.
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12
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Zhao L, Abrigo J, Chen Q, Au C, Ng A, Fan P, Mok V, Qiu W, Kermode AG, Lau AY. Advanced MRI features in relapsing multiple sclerosis patients with and without CSF oligoclonal IgG bands. Sci Rep 2020; 10:13703. [PMID: 32792656 DOI: 10.1038/s41598-020-70693-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Accepted: 08/03/2020] [Indexed: 01/07/2023] Open
Abstract
Oligoclonal IgG bands (OCB) in cerebrospinal fluid (CSF) are important in diagnosis of multiple sclerosis (MS). We evaluated the MRI features of clinically definite MS subjects with and without CSF-OCB. Relapsing MS subjects were recruited from a prospective registry in a university center. CSF-OCB were detected using isoelectric focusing and lgG-specific immunofixation. MRI metrics including brain volumes, lesion volumes and microstructural measures, were analyzed by FMRIB Software Library (FSL) and Statistical Parametric Mapping (SPM). Seventy-five subjects with relapsing MS were analyzed. Forty-four (59%) subjects had an interval MRI at around 1 year. CSF-OCB were detected in 46 (61%) subjects. The OCB-positive group had a higher proportion of cerebellar lesions than the OCB-negative group (23.9% vs. 3.4%, p = 0.057). Except for amygdala volumes which were lower in the OCB-positive group (p = 0.034), other regional brain volumes including the subcortical deep gray matter and corpus callosum were similar. The two groups also showed comparable brain atrophy rate. For DTI, the OCB-positive group showed significantly higher mean diffusivity (MD) value in perilesional normal-appearing white matter (p = 0.043). Relapsing MS patients with and without CSF-OCB shared similar MRI features regarding volumetric analyses and DTI microstructural integrity.
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13
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Sun J, Zhao R, Yang X, Deng H, Zhu Y, Chen Y, Yuan K, Xi Y, Yin H, Qin W. Alteration of Brain Gray Matter Density After 24 h of Sleep Deprivation in Healthy Adults. Front Neurosci 2020; 14:754. [PMID: 32903801 PMCID: PMC7438917 DOI: 10.3389/fnins.2020.00754] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2019] [Accepted: 06/26/2020] [Indexed: 12/19/2022] Open
Abstract
It has been reported that one night of acute sleep deprivation (SD) could induce brain structural changes at the synaptic and neuronal levels in animal studies, and could lead to white matter microstructure and cortical thickness change in human neuroimaging studies. In this study, we focused on changes of brain gray matter density (GMD) after one night of acute SD, which has not been explored previously. Twenty-three normal young participants completed the experiment. Each participant underwent twice T1-weighted structural image scanning with one at 08:00 after normal sleep [resting wakeful (RW)] and the other at 08:00 after 24 h of SD. Using voxel-based morphometry (VBM) analysis by FSL-VBM software, we compared GMD between RW and SD. In addition, the gray matter volume (GMV) and cortical thickness (CT) were also calculated based on volumetric and surface measures with FreeSurfer software. The psychomotor vigilance test (PVT) and the Karolinska Sleepiness Scale (KSS) were performed and evaluated for correlation analysis with GMD, GMV, and CT of the significant regions. Our results showed that the GMD in the right frontal pole (FP), right superior frontal gyrus (SFG), and right middle frontal gyrus significantly increased and GMV and CT in the right temporal pole (TP) significantly decreased after 24 h of acute SD. SD-induced changes in GMD in the right middle frontal gyrus were positively correlated with the changes of KSS scores (Spearman’s correlation r = 0.625, p = 0.0014, Bonferroni correction with p < 0.05/25). Taken together, our findings suggested that one night of acute SD could induce substantial brain structure changes and the alterations in GMD in the right middle frontal gyrus (MFG) might be implicated in sleepiness after SD.
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Affiliation(s)
- Jinbo Sun
- Engineering Research Center of Molecular and Neuro Imaging of the Ministry of Education, School of Life Sciences and Technology, Xidian University, Xi'an, China
| | - Rui Zhao
- School of Electronics and Information, Xi'an Polytechnic University, Xi'an, China
| | - Xuejuan Yang
- Engineering Research Center of Molecular and Neuro Imaging of the Ministry of Education, School of Life Sciences and Technology, Xidian University, Xi'an, China
| | - Hui Deng
- Engineering Research Center of Molecular and Neuro Imaging of the Ministry of Education, School of Life Sciences and Technology, Xidian University, Xi'an, China
| | - Yuanqiang Zhu
- Department of Radiology, Xijing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Yao Chen
- Engineering Research Center of Molecular and Neuro Imaging of the Ministry of Education, School of Life Sciences and Technology, Xidian University, Xi'an, China
| | - Kai Yuan
- Engineering Research Center of Molecular and Neuro Imaging of the Ministry of Education, School of Life Sciences and Technology, Xidian University, Xi'an, China
| | - Yibin Xi
- Department of Radiology, Xijing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Hong Yin
- Department of Radiology, Xijing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Wei Qin
- Engineering Research Center of Molecular and Neuro Imaging of the Ministry of Education, School of Life Sciences and Technology, Xidian University, Xi'an, China
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14
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Dacosta-Aguayo R, Wylie G, DeLuca J, Genova H. Changes in plant function and root mycobiome caused by flood and drought in a riparian tree. Behav Neurol 2020; 40:886-903. [PMID: 32175581 PMCID: PMC7775148 DOI: 10.1093/treephys/tpaa031] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2019] [Revised: 02/21/2020] [Accepted: 02/26/2020] [Indexed: 06/10/2023] Open
Abstract
Under increasingly harsh climatic conditions, conservation of threatened species requires integrative studies to understand stress tolerance. Riparian Ulmus minor Mill. populations have been massively reduced by Dutch Elm disease (DED). However, resistant genotypes were selected to restore lost populations. To understand the acclimation mechanisms to the succession of abiotic stresses, ramets of five DED-tolerant U. minor genotypes were subjected to flood and subsequently to drought. Physiological and biochemical responses were evaluated together with shifts in root-fungal assemblages. During both stresses, plants exhibited a decline in leaf net photosynthesis and an increase in percentage loss of stem hydraulic conductivity and in leaf and root proline content. Stomatal closure was produced by chemical signals during flood and hydraulic signals during drought. Despite broad similarities in plant response to both stresses, root-mycobiome shifts were markedly different. The five genotypes were similarly tolerant to moderate drought, however, flood tolerance varied between genotypes. In general, flood did not enhance drought susceptibility due to fast flood recovery, nevertheless, different responses to drought after flood were observed between genotypes. Associations were found between some fungal taxonomic groups and plant functional traits varying with flood and drought (e.g. proline, chlorophyll and starch content) indicating that the thriving of certain taxa depends on host responses to abiotic stress.
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Affiliation(s)
- Rosalia Dacosta-Aguayo
- Neuropsychology and Neuroscience, Kessler Foundation, 120 Eagle Rock Avenue, Suite 100, East Hanover, New Jersey 07936, USA
- Department of Physical Medicine and Rehabilitation, Rutgers University, New Jersey Medical School, Newark, NJ 07101, USA
| | - Glenn Wylie
- Department of Physical Medicine and Rehabilitation, Rutgers University, New Jersey Medical School, Newark, NJ 07101, USA
- Rocco Ortenzio Neuroimaging Center, Kessler Foundation, West Orange, NJ, USA
| | - John DeLuca
- Neuropsychology and Neuroscience, Kessler Foundation, 120 Eagle Rock Avenue, Suite 100, East Hanover, New Jersey 07936, USA
- Department of Physical Medicine and Rehabilitation, Rutgers University, New Jersey Medical School, Newark, NJ 07101, USA
- Rocco Ortenzio Neuroimaging Center, Kessler Foundation, West Orange, NJ, USA
| | - Helen Genova
- Neuropsychology and Neuroscience, Kessler Foundation, 120 Eagle Rock Avenue, Suite 100, East Hanover, New Jersey 07936, USA
- Department of Physical Medicine and Rehabilitation, Rutgers University, New Jersey Medical School, Newark, NJ 07101, USA
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Palotai M, Cavallari M, Koubiyr I, Morales Pinzon A, Nazeri A, Healy BC, Glanz B, Weiner HL, Chitnis T, Guttmann CR. Microstructural fronto-striatal and temporo-insular alterations are associated with fatigue in patients with multiple sclerosis independent of white matter lesion load and depression. Mult Scler 2019; 26:1708-1718. [PMID: 31418637 DOI: 10.1177/1352458519869185] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
BACKGROUND Fatigue in multiple sclerosis (MS) has been inconsistently associated with disruption of specific brain circuitries. Temporal fluctuations of fatigue have not been considered. OBJECTIVE The aim of this study was to investigate the association of fatigue with brain diffusion abnormalities, using robust criteria for patient stratification based on longitudinal patterns of fatigue. METHODS Patient stratification: (1) sustained fatigue (SF, n = 26): latest two Modified Fatigue Impact Scale (MFIS) ⩾ 38; (2) reversible fatigue (RF, n = 25): latest MFIS < 38 and minimum one previous MFIS ⩾ 38; and (3) never fatigued (NF, n = 42): MFIS always < 38 (five assessments minimum). 3T brain magnetic resonance imaging (MRI) was used to perform voxel-wise comparison of fractional anisotropy (FA) between the groups controlling for age, sex, disease duration, physical disability, white matter lesion load (T2LV), and depression. RESULTS SF and, to a lesser extent, RF patients showed lower FA in multiple brain regions compared to NF patients, independent of age, sex, disease duration, and physical disability. In cingulo-postcommissural-striato-thalamic regions, the differences in FA between SF and NF (but not between RF and NF or SF) patients were independent of T2LV, and in ventromedial prefronto-precommissuro-striatal and temporo-insular areas, independent of T2LV and depression. CONCLUSION Damage to ventromedial prefronto-precommissuro-striatal and temporo-insular pathways appears to be a specific substrate of SF in MS.
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Affiliation(s)
- Miklos Palotai
- Center for Neurological Imaging, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Michele Cavallari
- Center for Neurological Imaging, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ismail Koubiyr
- Center for Neurological Imaging, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA/INSERM U1215, Neurocentre Magendie, Bordeaux, France
| | - Alfredo Morales Pinzon
- Center for Neurological Imaging, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Aria Nazeri
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Brian C Healy
- Partners Multiple Sclerosis Center, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA/Biostatistics Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Bonnie Glanz
- Partners Multiple Sclerosis Center, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Howard L Weiner
- Partners Multiple Sclerosis Center, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Tanuja Chitnis
- Partners Multiple Sclerosis Center, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Charles Rg Guttmann
- Center for Neurological Imaging, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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Browne RW, Jakimovski D, Ziliotto N, Kuhle J, Bernardi F, Weinstock-Guttman B, Zivadinov R, Ramanathan M. High-density lipoprotein cholesterol is associated with multiple sclerosis fatigue: A fatigue-metabolism nexus? J Clin Lipidol 2019; 13:654-663.e1. [PMID: 31307953 DOI: 10.1016/j.jacl.2019.06.003] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2019] [Revised: 05/31/2019] [Accepted: 06/04/2019] [Indexed: 12/11/2022]
Abstract
BACKGROUND Fatigue is a frequent symptom in multiple sclerosis (MS). The role of cholesterol and lipids in MS fatigue has not been investigated. OBJECTIVE To investigate the associations of cholesterol biomarkers and serum neurofilament light chain (sNfL) with fatigue in relapsing-remitting MS. METHODS This cross-sectional study included 75 relapsing-remitting MS patients (69% female, mean age ± SD: 49.6 ± 11 years and median Expanded Disability Status Scale score: 2.0). Fatigue, disability, and depression were assessed with Fatigue Severity Scale (FSS), Expanded Disability Status Scale, and the Beck Depression Index-Fast Screen, respectively. sNfL was measured using single-molecule array technology. Plasma total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and an apolipoprotein panel data were obtained. Soluble intercellular adhesion molecule-1 (sICAM-1), soluble vascular adhesion molecule-1 (sVCAM-1), chemokine (C-C motif) ligand 5 (CCL5 or RANTES), and CCL18 levels were measured to assess inflammation. RESULTS The mean FSS was 4.27 ± 1.73, and 57% had severe fatigue status (SFS, FSS ≥ 4.0). In regression analyses adjusted for age, sex, disability, and depression, lower FSS and SFS were associated with greater HDL-C (P = .006 for FSS, and P = .016 for SFS) and lower TC to HDL-C ratio (P = .011 for FSS, and P = .009 for SFS). Apolipoprotein A-II was also associated with FSS (P = .022). sNfL, CCL5, CCL18, sICAM-1, and sVCAM-1 levels were not associated with fatigue after adjusting for disability and depression. CONCLUSIONS TC to HDL-C ratio is associated with MS fatigue. Our results implicate a potential role for the HDL-C pathway in MS fatigue and could provide possible targets for the treatment of MS fatigue.
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Affiliation(s)
- Richard W Browne
- Department of Biotechnical and Clinical Laboratory Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA.
| | - Dejan Jakimovski
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Nicole Ziliotto
- Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy
| | - Jens Kuhle
- Neurologic Clinic and Policlinic, Departments of Medicine, Biomedicine and Clinical Research, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Francesco Bernardi
- Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy
| | | | - Robert Zivadinov
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA; Department of Neurology, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Murali Ramanathan
- Department of Biotechnical and Clinical Laboratory Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA; Department of Pharmaceutical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
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