scholarly journals Data-driven analysis shows robust links between fatigue and depression in early multiple sclerosis

2022 ◽  
Author(s):  
Yuan Ting Chang ◽  
Patrick K.A. Kearns ◽  
Alan Carson ◽  
David Gillespie ◽  
Rozanna Meijboom ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Depressive Symptoms ◽  
Sleep Quality ◽  
Brain Imaging ◽  
Cognitive Performance ◽  
Subjective Sleep Quality ◽  
Fatigue Severity ◽  
Relapsing Remitting Multiple Sclerosis ◽  
Structural Brain ◽  
Structural Brain Imaging

Fatigue is common and disabling in multiple sclerosis, yet its mechanisms are poorly understood. In particular, overlap in measures of fatigue and depression complicates interpretation. A clearer understanding of relationships between fatigue and key clinical, neuropsychiatric and imaging variables including depression could yield clinically relevant mechanistic insight. We applied a data-driven multivariate network approach to quantify relationships between fatigue and other variables in early multiple sclerosis. Data were collected from Scottish patients with newly diagnosed, immunotherapy-naive, relapsing-remitting multiple sclerosis at baseline and month 12 follow-up in FutureMS, a nationally representative multicentre cohort. Subjective fatigue was assessed using the validated Fatigue Severity Scale. Detailed phenotyping included measures assessing physical disability, affective disorders, objective cognitive performance, subjective sleep quality, and structural brain imaging. Bivariate correlations between fatigue and other variables were calculated. Network analysis was then conducted to estimate partial correlations between variables, after accounting for all other included variables. Secondary networks included individual depressive symptoms, to control for overlapping symptom items in measures of fatigue and depression. Data from 322 participants at baseline, and 323 at month 12, were included. At baseline, 49.5% of the cohort reported clinically significant fatigue. Bivariate correlations confirmed that fatigue severity was significantly correlated with all included measures of physical disability, affective disturbance (anxiety and depression), cognitive performance (processing speed and memory/attention), and sleep quality, but not with structural brain imaging variables including normalized lesion and grey matter volumes. In the network analysis, fatigue showed strong correlations with depression, followed by Expanded Disability Status Scale. Weak connections with walking speed, subjective sleep quality and anxiety were identified. After separately controlling for measurement of tiredness in our measure of depression, some key depressive symptoms (anhedonia, subjective concentration deficits, subjectively altered speed of movement, and appetite) remained linked to fatigue. Conversely, fatigue was not linked to objective cognitive performance, white matter lesion volume, or grey matter volumes (cortical, subcortical or thalamic). Results were consistent at baseline and month 12. Depression was identified as the most central variable in the networks. Correlation stability coefficients and bootstrapped confidence intervals of the edge weights supported stability of the estimated networks. Our findings support robust links between subjective fatigue and depression in early relapsing-remitting multiple sclerosis, despite absence of links between fatigue and either objective cognitive performance, or structural brain imaging variables. Depression, including specific depressive symptoms, could be a key target of treatment and research in multiple sclerosis-related fatigue.

Predicting Neuropsychological Impairment in Relapsing Remitting Multiple Sclerosis: The Role of Clinical Measures, Treatment, and Neuropsychiatry Symptoms

2020 ◽  
Author(s):  
Elena Lozano-Soto ◽  
Álvaro Javier Cruz-López ◽  
Rafael Gutiérrez ◽  
Macarena González ◽  
Florencia Sanmartino ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Depressive Symptoms ◽  
Cognitive Performance ◽  
Disease Duration ◽  
Neuropsychological Impairment ◽  
Disease Stage ◽  
Relapsing Remitting ◽  
Remitting Multiple Sclerosis ◽  
Clinical Measures ◽  
Relapsing Remitting Multiple Sclerosis

Abstract Objective This retrospective observational study aimed to define neuropsychological impairment (NI) profiles and determine the influence of clinical, demographic, and neuropsychiatric measures in specific cognitive domains in a cohort of relapsing–remitting multiple sclerosis (RRMS) patients. Methods Ninety-one RRMS patients underwent a neurological examination and a brief neuropsychological assessment. Patients were classified according to the disease-modifying therapies (DMTs) received (platform or high-efficacy). Differences between groups and multiple regression analyses were performed to determine the predictive value of the assessed measures in cognitive performance. Results More than two-thirds of the patients showed NI. Specifically, mild to moderate NI was presented in approximately half of the participants. Paced Auditory Serial Addition Test (PASAT-3) and Symbol Digit Modalities Test (SDMT) were the most frequently impaired cognitive tests (45.3% and 41.3%, respectively) followed by phonemic verbal fluency (PVF) (27.8%). Expanded Disability Status Scale (EDSS), age, depressive symptoms, and disease duration were the best predictors of SDMT (R2 = .34; p < .01), whereas disease duration, EDSS, and anxiety-state levels predicted PASAT-3 (R2 = .33, p < .01). Educational level, age, EDSS, and depressive symptoms demonstrated the strongest association with PVF (R2 = .31, p < .01). Conclusions Our results indicated a significant prevalence of NI in RRMS patients that was not dependent on the DMT type. In addition to the meaningful working memory (PASAT-3) and information processing speed (SDMT) impairments found, PVF deficits may also be an important marker of cognitive impairment in RRMS patients. This study supports the relevance of standard clinical measures and reinforces the importance of quantifying clinical and neuropsychiatric symptoms to predict subsequent cognitive performance on a similar multiple sclerosis phenotype and disease stage.

scholarly journals Adolescents with tetralogy of Fallot: neuropsychological assessment and structural brain imaging

2014 ◽  
Vol 25 (2) ◽  
pp. 338-347 ◽  
Author(s):  
David C. Bellinger ◽  
Michael J. Rivkin ◽  
David DeMaso ◽  
Richard L. Robertson ◽  
Christian Stopp ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Brain Imaging ◽  
Tetralogy Of Fallot ◽  
Resonance Imaging ◽  
Neurodevelopmental Outcomes ◽  
Visual Spatial ◽  
Referent Group ◽  
Structural Brain ◽  
Structural Brain Imaging

AbstractBackground: Few data are available on the neuropsychological, behavioural, or structural brain imaging outcomes in adolescents who underwent corrective surgery in infancy for tetralogy of Fallot. Methods: In this single-centre cross-sectional study, we enrolled 91 adolescents (13–16 years old) with tetralogy of Fallot and 87 referent subjects. Assessments included tests of academic achievement, memory, executive functions, visual-spatial skills, attention, and social cognition, as well as brain magnetic resonance imaging. Results: Genetic abnormalities or syndromes were present in 25% of tetralogy of Fallot patients, who had markedly greater neuropsychological morbidities than did patients without a syndrome. However, even patients without a syndrome performed significantly worse than the referent group or population norms in all of the neuropsychological domains assessed. In multivariable regression in those without a genetic/phenotypic syndrome, the strongest predictors of adverse late neurodevelopmental outcomes included a greater number of complications at the first operation, more total surgical complications across all operations, and occurrence of post-operative seizures. The presence of at least one abnormality on structural magnetic resonance imaging was more frequent in tetralogy of Fallot patients than the referent group (42% versus 8%). Conclusions: Adolescents with tetralogy of Fallot are at increased neurodevelopmental risk and would benefit from ongoing surveillance and educational supports even after childhood.

scholarly journals The influence of subjective sleep quality on the association between eveningness and depressive symptoms.

2018 ◽  
Author(s):  
Charlotte Mary Horne ◽  
Ray Norbury
Keyword(s):  
Depressive Symptoms ◽  
Sleep Quality ◽  
Mediation Analysis ◽  
Depression Scale ◽  
Well Being ◽  
Poor Sleep ◽  
Subjective Sleep Quality ◽  
Subjective Sleep ◽  
Increased Risk ◽  
Healthy Participants

Increasing evidence suggests that eveningness is associated with increased risk for depression. Eveningness, however, is also associated with poor sleep quality and the unique role of eveningness in depressive symptomatology remains to be elucidated. The goal of the current study, therefore, was to examine the inter-relationships between eveningness, subjective sleep quality and depressive symptoms in healthy participants free of current or previous depression and sleep disorder. Here, 167 healthy participants (mean age 24.16, 129/38 females/males) completed the reduced Morningness-Eveningness Questionnaire (rMEQ), the Pittsburgh Sleep Quality Index (PSQI) and the Centre for Epidemiological Studies Depression Scale (CES-D). Bootstrap mediation analysis for a simple mediation model including rMEQ, PSQI and CES-D was applied. Eveningness was associated with increased depressive symptoms and mediation analysis showed that this relationship was partly mediated by sleep quality. Our results suggest that indicators of depression observed in evening-type individuals cannot be attributed exclusively to disturbed sleep. We suggest that interventions that target both sleep quality and dysfunctionl cognitive styles would be optimal to promote well-being in evening-type individuals.

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