Presentation is loading. Please wait.

Presentation is loading. Please wait.

Cognitive Biomarker of MS

Similar presentations


Presentation on theme: "Cognitive Biomarker of MS"— Presentation transcript:

1 Cognitive Biomarker of MS
Intra-Individual Variability in Information Processing Reaction Time is a Cognitive Biomarker of MS Margaret Kasschau1, Ge Song1, Michael Shaw1, Michael Porter2, Leigh Charvet1 1NYU Langone Medical Center Department of Neurology 2NYIT, College of Osteopathic Medicine Objective Results A total of n=104 MS participants (Table 1) were compared to a total of n=56 healthy controls. Preliminary analysis showed the IIV method to have a high level of test-retest reliability (n=56, r=0.756, p<0.01), indicating the precision of the method and measure. Controlling for age, IIV but not the attention network scores differentiated the MS from control groups, with the MS participants having significantly greater variability across trials (Table 2 and Figure 1). Among the MS participants, ANT-I IIV was correlated with the SDMT (Figure 2, p<0.01) and EDSS (Figure 3, p<0.001). To evaluate the sensitivity of intra-individual variability (IIV) in reaction time (RT) as a marker of early cognitive involvement in multiple sclerosis (MS). Table 1. Characteristics of the MS Sample Clinical Characteristics MS Participants (n=104) Sex (% Female) 72 Age (mean ± SD, years) 45.2±14.9 Disease Duration (mean ± SD, years) 15.9±18.7 EDSS (median and range) 3.5 (0-8) Background Cognitive impairment remains a challenging symptom to both detect and ameliorate in MS. Sensitive and reliable measures are needed to identify cognitive involvement at its earliest stages and link to disease activity.  IIV in reaction time is an easily-administered computer-based measurement of consistency in cognitive processing independent from overall speed or accuracy. Analyses were completed to determine whether IIV was sensitive in MS participants with the earliest disease activity. When comparing only the MS participants who did not meet screening criteria for clinical cognitive impairment (as indicated by SDMT z scores greater than -1.0), IIV continued to significantly differentiate the MS group from controls, p=0.01. We then compared performances in those with earliest disease activity (n=32 relapsing remitting, ≤35 years in age, median EDSS of 2.0 (n=32).   IIV significantly predicted MS group membership (r=0.29) Figure 4, with IIV correctly classifying 68.4% of the MS participants. Methods Table 2. Attention Network Scores and IIV ANT-I Scores MS (n=104) Control (n=56) p Alerting 49.60 (34.82) 34.82 (32.18) 0.37 Orienting 54.00 (22.52) 42.28 (41.94) 0.55 Executive (82.00) 84.32 (53.54) 0.40 IIV 6.58 (3.96) 4.42 (2.19) 0.03 We measured IIV using the Attention Network Test- Interaction (ANT-I) that uses a combination of a cued RT task and flanker paradigm (Figure 1). The test measures the efficiency of the orienting and alerting networks by means of the cueing task through different types of visual signals, and the efficiency of the executive control network by means of the flanker task . Participants were administered 6 blocks of the task, each with 48 trials with a total administration time of about 24 minutes. Figure 1. ANT-I congruent and incongruent arrow tasks *= p<0.05 Conclusions IIV in reaction time is a sensitive marker of cognitive involvement in MS at its earliest stages. IIV may serve as a cognitive marker and as an outcome for future intervention. IIV scores were calculated by removing outliers (>3 SD) and imputing individual scores using the group mean RT. All RTs were fitted using a linear regression model accounting for trial, block, and group membership and their two-way and three-way interaction terms as covariates. Standardized residuals from the regression model were converted to t-scores, and the standard deviation of all t-scores from each individual were calculated as the IIV score. References  1. Callejas A, Lupianez J, Funes MJ, Tudela P. Modulations among the alerting, orienting and executive control networks. Exp Brain Res 2005;167:27-37. 2. Wojtowicz M, Omisade A, Fisk JD. Indices of cognitive dysfunction in relapsing-remitting multiple sclerosis: intra-individual variability, processing speed, and attention network efficiency. Journal of the International Neuropsychological Society : JINS 2013;19: Research supported by The Lourie Center, Inc.


Download ppt "Cognitive Biomarker of MS"

Similar presentations


Ads by Google