Cognitive performance in healthy clinical trial participants and patients with the NeuroCart, a neurodegenerative disease measured with an automated neuropsychological and neurophysiological test battery

Prins, S.; Borghans, L.; Kam, M.L. de; Groeneveld, G.J.; Gerven, J. van

doi:doi:10.1016/j.jns.2023.120658

Background The prevalence of neurodegenerative diseases increases significantly with increasing age. Neurodegeneration is the progressive loss of function of neurons that eventually leads to cell death, which in turn leads to cognitive disfunction. Cognitive performance can therefore also be considered age dependent. The current study investigated if the NeuroCart can detect age related decline on drug-sensitive CNS-tests in healthy volunteers (HV), and whether there are interactions between the rates of decline and sex. This study also investigated if the NeuroCart was able to differentiate disease profiles of neurodegenerative diseases, compared to age-matched HV and if there is age related decline in patient groups. Methods This retrospective study encompassed 93 studies, performed at CHDR between 2005 and 2020 that included NeuroCart measurements, which resulted in data from 2729 subjects. Five NeuroCart tests were included in this analysis: smooth and saccadic eye movements...Show more Background The prevalence of neurodegenerative diseases increases significantly with increasing age. Neurodegeneration is the progressive loss of function of neurons that eventually leads to cell death, which in turn leads to cognitive disfunction. Cognitive performance can therefore also be considered age dependent. The current study investigated if the NeuroCart can detect age related decline on drug-sensitive CNS-tests in healthy volunteers (HV), and whether there are interactions between the rates of decline and sex. This study also investigated if the NeuroCart was able to differentiate disease profiles of neurodegenerative diseases, compared to age-matched HV and if there is age related decline in patient groups. Methods This retrospective study encompassed 93 studies, performed at CHDR between 2005 and 2020 that included NeuroCart measurements, which resulted in data from 2729 subjects. Five NeuroCart tests were included in this analysis: smooth and saccadic eye movements, body sway, adaptive tracking, VVLT and N-back. Data from 84 healthy male and female volunteer studies, aged 16-90, were included. Nine studies were performed in patients with Alzheimer’s disease (AD), Parkinson’s disease (PD), Huntington’s disease (HD) or vascular dementia (VaD). The data were analyzed with regression analyses on age by group, sex, sex by age, group by sex and group by sex by age. Least square means (LSMs) and 95% confidence intervals (CIs) were calculated for each group at the average age of the group, and at the average age of each of the other groups, and per sex. Results Mean age and standard deviation (SD) for all groups was: HV 36.2 years (19.3), AD 68.3 years (8), PD 62.7 years (8.5), HD 51.4 years (9.8) and VaD 66.9 years (8.1). Performance on all NeuroCart tests decreased significantly each year in HV. Saccadic peak velocity (SPV) was increased in AD compared to age-matched HV (+26.28 degrees/s, p =0.007), while SPV was decreased for PD and HD compared to age-matched HV (PD: -15.87 degrees/s, p=0.038, HD: -22.52 degrees/s, p=0.018). In HD patients SPV decreased faster with age compared to HV. On saccadic peak velocity the slopes between HD vs HV were significantly different, indicating a faster decline in performance on this task for HD patients compared to HV per age year. Smooth pursuit showed an overall significant difference between subject groups (p=0.037. Significantly worse performance was found for AD (-12.87%, p=<0.001), PD (-4.45%, p=<0.001) and VaD (-5.69%, p=0.005) compared to age-matched HV. Body sway significantly increased with age (p=0.021). Postural stability was decreased for both PD and HD compared to age-matched HV (PD: +38.8%, p=<0.001, HD: 154.9%, p=<0.001). The adaptive tracking was significantly decreased with age (p=<0.001). Adaptive tracking performance by AD (-7.54%, p=<0.001), PD (-8.09%, p=<0.001), HD (-5.19%, p=<0.001) and VaD (-5.80%, p=<0.001) was decreased compared to age-matched HV. Adaptive tracking in PD patients vs HV and in PD vs HD patients was significantly different, indicating a faster decline on this task per age year for PD patients compared to HV and HD. The VVLT delayed word recall showed an overall significant effect of subject group (p=0.006. Correct delayed word recall was decreased for AD (-5.83 words, p=<0.001), HD (-3.40 words, p=<0.001) and VaD (-5.51 words, p=<0.001) compared to age-matched HV. Conclusion This study showed that the NeuroCart can detect age-related decreases in performance in HV, which were not affected by sex. The NeuroCart was able to detect significant differences in performance between AD, PD, HD, VaD and age-matched HV. Disease durations were unknown, therefore this cross-sectional study was not able to show age-related decline after disease onset. This article shows the importance of investigating age-related decline on digitalized neurocognitive test batteries. Performance declines with age, which emphasizes the need to correct for age when including HV in clinical trials. Patients with different neurogenerative diseases have distinct performance patterns on the NeuroCart , which this should be considered when performing NeuroCart tasks in patients with AD, PD, HD and VaD.
Show less

Leiden University Scholarly Publications

View statistics

Documents

In Collections

Cognitive performance in healthy clinical trial participants and patients with the NeuroCart, a neurodegenerative disease measured with an automated neuropsychological and neurophysiological test battery