Depression in multiple sclerosis across the adult lifespan

Abstract

Objectives: The objective of this study is to examine the burden of depressive symptoms across the adult age span in people with multiple sclerosis (MS) and test if the relationship between depressive symptoms and MS characteristics vary across age groups. Methods: In analyses of the MS Partners Advancing Technology and Health Solutions (MS PATHS) network of adults with MS, we compared the prevalence of depression in MS PATHS with non-MS controls across age and evaluated for effect modification by age in the association between depressive symptoms and clinical and neuroperformance measures via multivariable-adjusted regression models. Results: In total, 13,821 individuals with MS were included. The prevalence of depression was higher in MS versus non-MS controls, but was similar between men/women across age. The association between depression and processing speed (PST; p for interaction = 0.009) or walking speed ( p for interaction = 0.04) varied by age. For example, younger depressed individuals had 0.45 standard deviation (SD) (95% confidence interval (CI) = −0.62, −0.29) worse PST Z-scores versus non-depressed younger participants, whereas older depressed individuals had 0.20 SD (95% CI = −0.32, −0.08) worse PST Z-scores versus non-depressed older participants. Conclusion: Depressive symptoms and age should be considered when interpreting measures of walking speed and cognitive function; these findings may have implications for analyses of neuroperformance change.

Lesion network localization of depression in multiple sclerosis

“…Rather, it is a continuous measure that quantifies variance in mood across the full distribution of patients. We used the term 'depression' in a manner that is consistent with its use in the Neuro-QoL and in the MS literature [37][38][39][40][41][42][43] but is not synonymous with a diagnosis of MDD. One advantage to using a continuous outcome is that our results are sensitive to lesions associated with either higher or lower mood.…”

“…Symptom severity was measured using tools and scales that have been previously validated in people with MS [37][38][39][40][41][42][43]47 . Most symptoms were assessed using Neuro-QoL, a self-report inventory of 12 neuropsychiatric symptom clusters, including ability, anxiety, emotional/behavioural dyscontrol, fatigue, lower-extremity function, upper-extremity function, stigma, positive affect/well-being, satisfaction with social roles/activities, cognitive function and sleep.…”

Predicting Multiple Sclerosis Outcomes During the COVID-19 Stay-at-home Period: Observational Study Using Passively Sensed Behaviors and Digital Phenotyping

“…People with MS have a significantly higher burden of mental health comorbidities than the general population. Moreover, people with MS have a 50% lifetime prevalence of depression, 2-3 times higher than the general population [11][12][13]. Given its association with higher disability and mortality, depression is a major comorbidity that lowers the quality of life [11,[14][15][16][17][18][19][20].…”

Mood-congruent negative thinking styles and cognitive vulnerability in depressed COVID-19 survivors: A comparison with major depressive disorder

“…A consistent literature described the same irrational thought patterns and cognitive errors both, in depressed patients with these conditions, and in major depressive disorder ( Lefebvre, 1981 ; Maxwell et al, 1998 ; Smith et al, 1994 ; Smith et al, 1990 ; Szigethy et al, 2007 ), thus suggesting that negative thinking styles associates with clinical depression independent of factors triggering the major depressive episode. This is of high clinical relevance, because clinical investigations show that in medical and neurological conditions negative thinking styles worsen prognosis by increasing disability, when stage of disease is controlled ( Benedetti et al, 2004 ; Chan et al, 2020 ; Clough, 1991 ; Mikocka-Walus et al, 2015 ; Smith et al, 1986 ). Cognitive vulnerability can moderate the effect of life stressors on depressive symptomatology, identifying a vulnerability factor ( Beevers, 2005 ; Losiak et al, 2019 ), while a ‘normal’ bias toward positive emotional processing predicts stress resilience ( Thoern et al, 2016 ).…”