A proposed new taxonomy of cognitive phenotypes in multiple sclerosis: The International Classification of Cognitive Disorders in MS (IC-CoDiMS). (April 2023)

• Record Type: Journal Article
• Authors: Hancock, Laura M; Galioto, Rachel; Samsonov, Alexey; Busch, Robyn M; Hermann, Bruce; Matias-Guiu, Jordi A
• Is Part Of: Multiple sclerosis. Volume 29:Number 4/5(2023)
• Page Start: 615
• Page End: 627
• Publication Date: 2023-04
• Subjects: Cognitive phenotypes -- cognitive impairment -- neuropsychology -- cognition -- memory -- processing speed -- executive functions -- IC-CoDiMS -- multiple sclerosis; Central nervous system -- Diseases -- Periodicals; Myelin sheath -- Diseases -- Periodicals; Inflammation -- Periodicals; Multiple sclerosis -- Periodicals; Central Nervous System Diseases -- Periodicals; Demyelinating Diseases -- Periodicals; Inflammation -- Periodicals; Multiple Sclerosis -- Periodicals; Système nerveux central -- Maladies -- Périodiques; Gaine de myéline -- Maladies -- Périodiques; Inflammation (Pathologie) -- Périodiques; Sclérose en plaques -- Périodiques; Electronic journals; 616.834005
• DOI: 10.1177/13524585221127941
• Languages: English
• ISSNs: 1352-4585

Abstract

Background: Characterization of cognitive impairment (CI) in multiple sclerosis into distinct phenotypes holds promise for individualized treatments and biomarker exploration. Objective: Apply a previously validated, neuropsychologically driven diagnostic algorithm to identify a taxonomy of the type of cognitive phenotypes in multiple sclerosis. Methods: An algorithm developed and validated in other neurological diseases was applied to a cohort of 1281 people with multiple sclerosis who underwent clinical neuropsychological evaluation across three multiple sclerosis centers. A domain was marked impaired if scores on two tests within the domain fell below one of the two thresholds of interest (compared to controls; −1.0 SD and −1.5 SD below the mean). Results were then tabulated for each participant to determine the type of impairments across the sample. Results: At −1 SD threshold, 48.7% were intact, 21.6% had single-domain, 14.3% bi-domain, and 15.4% multi-domain impairment. At −1.5 SD threshold, 72.9% were intact, 14.0% had single-domain, 8.2% bi-domain, and 5.0% multi-domain impairment. Processing speed was the most frequent single-domain impairment, followed by executive function and memory. Conclusions: These findings advance the taxonomy of cognitive phenotypes in multiple sclerosis and clarify the type and distribution of possible cognitive diagnoses, pave the way for further investigation of associated biomarkers, and provide clinically meaningful information to guide individualized treatment and rehabilitation.