Cortical thickness and cognition in older people with multiple sclerosis

Dejan Jakimovski; Robert Zivadinov; Zachary Weinstock; Tom A Fuchs; Alexander Bartnik; Michael G Dwyer; Niels Bergsland; Bianca Weinstock-Guttman; Ralph H B Benedict

doi:10.1007/s00415-023-11945-2

Cortical thickness and cognition in older people with multiple sclerosis

J Neurol. 2023 Nov;270(11):5223-5234. doi: 10.1007/s00415-023-11945-2. Epub 2023 Aug 27.

Authors

Dejan Jakimovski¹, Robert Zivadinov^{2

3}, Zachary Weinstock², Tom A Fuchs², Alexander Bartnik², Michael G Dwyer², Niels Bergsland², Bianca Weinstock-Guttman⁴, Ralph H B Benedict⁴

Affiliations

¹ Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, 100 High St., Buffalo, NY, 14203, USA. djakimovski@bnac.net.
² Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, 100 High St., Buffalo, NY, 14203, USA.
³ Center for Biomedical Imaging at the Clinical Translational Science Institute, University at Buffalo, State University of New York, Buffalo, NY, USA.
⁴ Department of Neurology, Jacobs Comprehensive MS Treatment and Research Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA.

PMID: 37634161
DOI: 10.1007/s00415-023-11945-2

Abstract

Background: The structural changes associated with cognitive performance in older people with multiple sclerosis (PwMS; age ≥ 50 years old) remain unknown.

Objective: To determine the relationship between whole-brain (WBV), thalamus as the largest deep gray matter nuclei, and cortex-specific volume measurements with both cognitive impairment and numerical performance in older PwMS. The main hypothesis is that cognitive impairment (CI) in older PwMS is explained by cortical thinning in addition to global and thalamic neurodegenerative changes.

Methods: A total of 101 older PwMS underwent cognitive and neuroimaging assessment. Cognitive assessment included tests established as sensitive in MS samples (Minimal Assessment of Cognitive Function in MS; MACFIMS), as well as those tests often utilized in Alzheimer's dementia studies (Wechsler's Memory Scale, Boston Naming Test, Visual Motor Integration and language). Cognitive impairment (CI) was based on -1.5 standard deviations in at least 2 cognitive domains (executive function, learning and memory, spatial processing, processing speed and working memory and language) when compared to healthy controls. WBV and thalamic volume were calculated using SIENAX/FIRST and cortical thickness using FreeSurfer. Differences in cortical thickness between CI and cognitively preserved (CP) were determined using age, sex, education, depression and WBV-adjusted analysis of covariance (ANCOVA). The relationship between domain-specific cognitive performance and cortical thickness was analyzed by linear regression models adjusted for age, sex, education, depression, WBV and thalamic volume. Benjamini-Hochberg-adjusted p-values lower than 0.05 were considered significant.

Results: The average age of the study population was 62.6 (5.9) years old. After adjustment, CI PwMS had significantly thinner left fusiform (p = 0.0003), left inferior (p = 0.0032), left transverse (p = 0.0013), and bilateral superior temporal gyri (p = 0.002 and p = 0.0011) when compared to CP PwMS. After adjusting for age, sex, education, depression WBV, and thalamic volume, CI status was additionally predicted by the thickness of the left fusiform (p = 0.001) and left cuneus gyri (p = 0.004). After the adjustment, SDMT scores were additionally associated with left fusiform gyrus (p < 0.001) whereas letter-based verbal fluency performance with left pars opercularis gyrus (p < 0.001).

Conclusion: In addition to global and thalamic neurodegenerative changes, the presence of CI in older PwMS is additionally explained by the thickness of multiple cortical regions.

Keywords: Aging; Cognitive impairment; Cortical thinning; Language impairment; Multiple sclerosis; Processing speed.