Real-world keystroke dynamics are a potentially valid biomarker for clinical disability in multiple sclerosis.

BACKGROUND: Clinical measures in multiple sclerosis (MS) face limitations that may be overcome by utilising smartphone keyboard interactions acquired continuously and remotely during regular typing. OBJECTIVE: The aim of this study was to determine the reliability and validity of keystroke dynamics to assess clinical aspects of MS. METHODS: In total, 102 MS patients and 24 controls were included in this observational study. Keyboard interactions were obtained with the Neurokeys keyboard app. Eight timing-related keystroke features were assessed for reliability with intraclass correlation coefficients (ICCs); construct validity by analysing group differences (in fatigue, gadolinium-enhancing lesions on magnetic resonance imaging (MRI), and patients vs controls); and concurrent validity by correlating with disability measures. RESULTS: Reliability was moderate in two (ICC = 0.601 and 0.742) and good to excellent in the remaining six features (ICC = 0.760-0.965). Patients had significantly higher keystroke latencies than controls. Latency between key presses correlated the highest with Expanded Disability Status Scale (r = 0.407) and latency between key releases with Nine-Hole Peg Test and Symbol Digit Modalities Test (ρ = 0.503 and r = -0.553, respectively), ps < 0.001. CONCLUSION: Keystroke dynamics were reliable, distinguished patients and controls, and were associated with clinical disability measures. Consequently, keystroke dynamics are a promising valid surrogate marker for clinical disability in MS.

Is impaired information processing speed a matter of structural or functional damage in MS?

OBJECTIVE: Cognitive deficits, especially those of information processing speed (IPS), are common in multiple sclerosis (MS), however, the underlying neurobiological mechanisms remain poorly understood. In this study, we examined structural and functional brain changes separately, but also in an integrative manner, in relation to IPS performance. METHODS: IPS was measured using the symbol digit modalities test (SDMT) in 330 MS patients and 96 controls. Patients with IPS impairment (IPS-I, z-score < -1.5) were compared to patients with preserved IPS performance (IPS-P) on volumetric measures, white matter integrity loss (using diffusion tensor imaging) and the severity of functional connectivity changes (using resting-state fMRI). Significant predictors of IPS performance were used to create groups of mild or severe structural and/or functional damage to determine the relative effect of structural and/or functional changes on IPS. RESULTS: IPS-I patients, compared to IPS-P patients, showed lower deep gray matter volume and less WM integrity, but stronger increases in functional connectivity. Patients with predominantly structural damage had worse IPS (z-score = -1.49) than patients with predominantly functional changes (z-score = -0.84), although both structural and functional measures remained significant in a regression model. Patients with severe structural and functional changes had worst IPS (z-score = -1.95). CONCLUSION: The level of structural damage explains IPS performance better than functional changes. After integrating functional and structural changes, however, we were able to detect more subtle and stepwise decline in IPS. In subgroups with a similar degree of structural damage, more severe functional changes resulted in worse IPS scores than those with only mild functional changes.

Patterns of white matter damage are non-random and associated with cognitive function in secondary progressive multiple sclerosis.

In multiple sclerosis (MS), white matter damage is thought to contribute to cognitive dysfunction, which is especially prominent in secondary progressive MS (SPMS). While studies in healthy subjects have revealed patterns of correlated fractional anisotropy (FA) across white matter tracts, little is known about the underlying patterns of white matter damage in MS. In the present study, we aimed to map the SPMS-related covariance patterns of microstructural white matter changes, and investigated whether or not these patterns were associated with cognitive dysfunction. Diffusion MRI was acquired from 30 SPMS patients and 32 healthy controls (HC). A tensor model was fitted and FA maps were processed using tract-based spatial statistics (TBSS) in order to obtain a skeletonised map for each subject. The skeletonised FA maps of patients only were decomposed into 18 spatially independent components (ICs) using independent component analysis. Comprehensive cognitive assessment was conducted to evaluate five cognitive domains. Correlations between cognitive performance and (1) severity of FA abnormalities of the extracted ICs (i.e. z-scores relative to FA values of HC) and (2) IC load (i.e. FA covariance of a particular IC) were examined. SPMS patients showed lower FA values of all examined patterns of correlated FA (i.e. spatially independent components) than HC (p < 0.01). Tracts visually assigned to the supratentorial commissural class were most severely damaged (z = - 3.54; p < 0.001). Reduced FA was significantly correlated with reduced IC load (i.e. FA covariance) (r = 0.441; p < 0.05). Lower mean FA and component load of the supratentorial projection tracts and limbic association tracts classes were associated with worse cognitive function, including executive function, working memory and verbal memory. Despite the presence of white matter damage, it was possible to reveal patterns of FA covariance across SPMS patients. This could indicate that white matter tracts belonging to the same cluster, and thus with similar characteristics, tend to follow similar trends during neurodegeneration. Furthermore, these underlying FA patterns might help to explain cognitive dysfunction in SPMS.