Faculty Bibliography

BACKGROUND:The Symbol Digit Modalities Test (SDMT) is a common screen of cognitive function for people with Multiple Sclerosis (pwMS) but growing acknowledgement that people with cognitive impairment are a heterogeneous population suggests that a single screen may provide limited information. OBJECTIVE:To assess the adequacy of the SDMT in capturing impairment across specific cognitive domains as measured by a multi-domain cognitive assessment battery (CAB, NeuroTrax). METHODS:113 pwMS were assessed with SDMT and the CAB. Cognitive impairment in each CAB domain was defined as ≥1.5 SD below the normalized mean. Logistic regression models were fit for each CAB domain with domain-specific cognitive impairment as the outcome and SDMT as the predictor, and a classifier created by selecting cutpoints using the Youden Index. Model performance was assessed by predicting domain-specific cognitive impairment in an independent data set consisting of 81 pwMS. RESULTS:SDMT was a significant predictor of cognitive impairment in all outcomes considered (Odds Ratio: 0.885-0.950), but prediction metrics such as area under the receiver operating curve (AUC) were modest (0.623-0.778), and the alignment between observed/predicted impairment was less than optimal. CONCLUSION/CONCLUSIONS:The SDMT is not sufficient to differentiate between impaired and non-impaired pwMS across several cognitive domains.

OBJECTIVE:Visual evoked potentials (VEPs) can provide insight into disease activity in people with multiple sclerosis (PwMS). However, few studies have tracked concurrent changes in VEPs and cognitive functioning over time in MS. To address this, we examined the longitudinal relationship between VEP and cognitive performance in PwMS over a two-year period. METHODS:At baseline (T1) and follow-up (T2, 2.14 years after baseline, on average), P100 peak latency and inter-ocular latency (IOL) between eyes were calculated from the VEP elicited for checkerboard pattern-reversal stimuli. Cognitive performance was assessed for seven different domains (NeuroTrax battery). The potential for VEP variables to predict the T1-to-T2 change in cognitive performance was assessed in a series of multiple linear regression models. RESULTS:Baseline IOL and VEP latency were significantly associated with T1-to-T2 change in information processing speed. Post-hoc analyses indicated that PwMS that had both prolonged VEP latency and elevated IOL at baseline tended to exhibit greater information processing speed decline. Increase in VEP latency from T1-to-T2 was also associated with decline in psychomotor function over time. CONCLUSIONS:These findings provide evidence that VEP measures can serve as valuable prognostic indicators of longitudinal cognitive change in PwMS. SIGNIFICANCE:Visual system neurophysiology corresponds with changes in speeded cognitive performance in MS.

BACKGROUND:Fatigue is a common problem experienced by people with multiple sclerosis (PwMS) and can impact physical, cognitive, and psychosocial aspects of daily living and quality of life. The tracking of meaningful longitudinal change in subjective fatigue that occurs as a result of MS activity may be enhanced by incorporating objective neurophysiological measures into longitudinal assessment. To examine this possibility, we examined the longitudinal relationship between visual evoked potential (VEP) measures and a variety of fatigue measures over an approximately two-year period in PwMS. METHODS:VEP measures were obtained using a checkerboard pattern-reversal paradigm. Fatigue was assessed with the Modified Fatigue Impact Scale (MFIS Global, Physical, Cognitive, and Psychosocial subscales) and the Fatigue Severity Scale (FSS) questionnaires. Multiple linear regression analyses were conducted in which the change in each fatigue scale score from baseline to follow-up (T1-to-T2) served as the outcome variables for separate models. Predictor variables included the peak latency of the P100 component of the VEP (maximum peak among the two eyes) and the inter-ocular latency (IOL) at T1, the T1-to-T2 change score for maximum VEP latency and IOL, and the fatigue score at T1 that corresponded to each outcome measure. RESULTS:Prolonged baseline VEP latency was a significant predictor of the T1-to-T2 increase in MFIS Global score, and increased VEP latency from baseline to follow-up was significantly associated with MFIS Cognitive score over the same time period. Furthermore, VEP latency measures in these two models were better predictors of changes in fatigue than baseline fatigue scores were, based on the magnitude of the standardized beta coefficients. Subsequent post-hoc analyses revealed that the relationship between change in VEP latency and change in MFIS Cognitive score was evident primarily for PwMS that had elevated MFIS Cognitive score at baseline. CONCLUSION/CONCLUSIONS:The present study provides novel evidence that prolonged VEP latency is predictive of worsening of global and cognitive fatigue in PwMS. VEP latency measures may therefore provide clinical utility for monitoring changes in fatigue in PwMS, when used in conjunction with other clinical tools.

Visual evoked potentials (VEP) index visual pathway functioning, and are often used for clinical assessment and as outcome measures in people with multiple sclerosis (PwMS). VEPs may also reflect broader neural disturbances that extend beyond the visual system, but this possibility requires further investigation. In the present study, we examined the hypothesis that delayed latency of the P100 component of the VEP would be associated with broader structural changes in the brain in PwMS. We obtained VEP latency for a standard pattern-reversal checkerboard stimulus paradigm, in addition to Magnetic Resonance Imaging (MRI) measures of whole brain volume (WBV), gray matter volume (GMV), white matter volume (WMV), and T2-weighted fluid attenuated inversion recovery (FLAIR) white matter lesion volume (FLV). Correlation analyses indicated that prolonged VEP latency was significantly associated with lower WBV, GMV, and WMV, and greater FLV. VEP latency remained significantly associated with WBV, GMV, and WMV even after controlling for the variance associated with inter-ocular latency, age, time between VEP and MRI assessments, and other MRI variables. VEP latency delays were most pronounced in PwMS that exhibited low volume in both white and gray matter simultaneously. Furthermore, PwMS that had delayed VEP latency based on a clinically relevant cutoff (VEP latency ≥ 113 ms) in both eyes had lower WBV, GMV, and WMV and greater FLV in comparison to PwMS that had normal VEP latency in one or both eyes. The findings suggest that PwMS that have delayed latency in both eyes may be particularly at risk for exhibiting greater brain atrophy and lesion volume. These analyses also indicate that VEP latency may index combined gray matter and white matter disturbances, and therefore broader network connectivity and efficiency. VEP latency may therefore provide a surrogate marker of broader structural disturbances in the brain in MS.

Prior studies have reported an association between visual evoked potentials (VEPs) and cognitive performance in people with multiple sclerosis (PwMS), but the specific mechanisms that account for this relationship remain unclear. We examined the relationship between VEP latency and cognitive performance in a large sample of PwMS, hypothesizing that VEP latency indexes not only visual system functioning but also general neural efficiency. Standardized performance index scores were obtained for the domains of memory, executive function, visual-spatial processing, verbal function, attention, information processing speed, and motor skills, as well as global cognitive performance (NeuroTrax battery). VEP P100 component latency was obtained using a standard checkerboard pattern-reversal paradigm. Prolonged VEP latency was significantly associated with poorer performance in multiple cognitive domains, and with the number of cognitive domains in which performance was ≥ 1 SD below the normative mean. Relationships between VEP latency and cognitive performance were significant for information processing speed, executive function, attention, motor skills, and global cognitive performance after controlling for disease duration, visual acuity, and inter-ocular latency differences. This study provides evidence that VEP latency delays index general neural inefficiency that is associated with cognitive disturbances in PwMS.

BACKGROUND:Computerized cognitive assessment facilitates the incorporation of multi-domain cognitive monitoring into routine clinical care. The predictive validity of computerized cognitive assessment among people with multiple sclerosis (PwMS) has scarcely been investigated. OBJECTIVE:To explore the associations between brain volumes and cognitive scores from a computerized cognitive assessment battery (CAB, NeuroTrax) among PwMS. METHODS:PwMS were evaluated with the CAB and underwent brain MRI within 40 days. Cognitive assessment yielded age- and education-adjusted scores in 9 cognitive domains: memory, executive function, attention, information processing speed, visual spatial, verbal function, motor skills, problem solving, and working memory. The global cognitive score (GCS) is the average of all domain scores. MRI brain and lesion volumes were assessed with icobrain ms, a fully automated tissue and lesion segmentation and quantification software. RESULTS:91 PwMS were included [Age: 52.1 ± 11.7 years, 64 (70%) female, EDSS: 3.4 ± 2.0, 79 (87%) with a relapsing remitting course]. Significant correlations were found between the GCS and whole brain, white matter, grey matter, thalamic, lateral ventricles, hippocampal and lesion volumes (Correlation coefficients: 0.46, 0.40, 0.25, 0.42, -0.36, 0.21, -0.3, respectively). Regression analysis revealed that lateral ventricles and thalamic volumes were the most consistent predictors of all cognitive domain scores. CONCLUSION:Computerized cognitive scores were significantly associated with quantified MRI. These findings support the predictive validity of multi-domain computerized cognitive assessment for people with multiple sclerosis.