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Cognitive Profiles of Aging in Multiple Sclerosis

  • Dejan Jakimovski
  • , Bianca Weinstock-Guttman
  • , Shumita Roy
  • , Michael Jaworski
  • , Laura Hancock
  • , Alissa Nizinski
  • , Pavitra Srinivasan
  • , Tom A Fuchs
  • , Kinga Szigeti
  • , Robert Zivadinov
  • , Ralph H B Benedict
  • From the Department of Neurology & Corinne Goldsmith Dickinson Center for Multiple Sclerosis (J.F.S., M.I.), Icahn School of Medicine at Mount Sinai, New York; Department of Neurology (R.B.), School of Medicine and Biomedical Sciences, University of Buffalo, State University of New York (SUNY); Department of Neurology (C.E.), Medical University of Graz, Austria...
  • University of Wisconsin School of Medicine and Public Health
  • Department of Neurology
  • Jacobs School of Medicine and Biomedical Sciences, University at Buffalo
  • Buffalo Neuroimaging Analysis Center (BNAC)

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

BACKGROUND: Increasingly favorable mortality prognosis in multiple sclerosis (MS) raises questions regarding MS-specific cognitive aging and the presence of comorbidities such as Alzheimer's disease (AD).

OBJECTIVE: To assess elderly with MS (EwMS) and age-matched healthy controls (HCs) using both MS- and AD-specific psychometrics.

METHODS: EwMS (n = 104) and 56 HCs were assessed on a broad spectrum of language, visual-spatial processing, memory, processing speed, and executive function tests. Using logistic regression analysis, we examined cognitive performance differences between the EwMS and HC groups. Cognitive impairment (CI) was defined using a -1.5 SD threshold relative to age and education years-matched HCs, in two cognitive domains.

RESULTS: CI was observed in 47.1% of EwMS with differences most often seen on tests emphasizing cognitive processing speed as measured by Symbol Digit Modalities Test (SDMT) (d = 0.9, p < 0.001) and verbal fluency (both category-based d = 0.87, p < 0.001; letter-based d = 0.67, p < 0.001). After adjusting for age, sex and years of education, MS/HC diagnosis was best predicted (R 2 = 0.27) by differences in category-based verbal fluency (Wald = 9.935, p = 0.002) and SDMT (Wald = 13.937, p < 0.001).

CONCLUSION: This study confirms the common hallmark of slowed cognitive processing speed in MS among elderly patients. Defective verbal fluency, less often observed in younger cohorts, may represent emerging cognitive pathology due to other etiologies.

Original languageEnglish
Pages (from-to)105
JournalFrontiers in aging neuroscience
Volume11
DOIs
Publication statusPublished - 2019
Externally publishedYes

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