Dataset Information

Can we predict cognitive decline after initial diagnosis of multiple sclerosis? Results from the German National early MS cohort (KKNMS).

ABSTRACT:

Background

Cognitive impairment (CI) affects approximately one-third of the patients with early multiple sclerosis (MS) and clinically isolated syndrome (CIS). Little is known about factors predicting CI and progression after initial diagnosis.

Methods

Neuropsychological screening data from baseline and 1-year follow-up of a prospective multicenter cohort study (NationMS) involving 1123 patients with newly diagnosed MS or CIS were analyzed. Employing linear multilevel models, we investigated whether demographic, clinical and conventional MRI markers at baseline were predictive for CI and longitudinal cognitive changes.

Results

At baseline, 22% of patients had CI (impairment in ?2 cognitive domains) with highest frequencies and severity in processing speed and executive functions. Demographics (fewer years of academic education, higher age, male sex), clinical (EDSS, depressive symptoms) but no conventional MRI characteristics were linked to baseline CI. At follow-up, only 14% of patients showed CI suggesting effects of retesting. Neither baseline characteristics nor initiation of treatment between baseline and follow-up was able to predict cognitive changes within the follow-up period of 1 year.

Conclusions

Identification of risk factors for short-term cognitive change in newly diagnosed MS or CIS is insufficient using only demographic, clinical and conventional MRI data. Change-sensitive, re-test reliable cognitive tests and more sophisticated predictors need to be employed in future clinical trials and cohort studies of early-stage MS to improve prediction.

SUBMITTER: Johnen A

PROVIDER: S-EPMC6373354 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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Publications

Can we predict cognitive decline after initial diagnosis of multiple sclerosis? Results from the German National early MS cohort (KKNMS).

Johnen Andreas A Bürkner Paul-Christian PC Landmeyer Nils C NC Ambrosius Björn B Calabrese Pasquale P Motte Jeremias J Hessler Nicole N Antony Gisela G König Inke R IR Klotz Luisa L Hoshi Muna-Miriam MM Aly Lilian L Groppa Sergiu S Luessi Felix F Paul Friedemann F Tackenberg Björn B Bergh Florian Then FT Kümpfel Tania T Tumani Hayrettin H Stangel Martin M Weber Frank F Bayas Antonios A Wildemann Brigitte B Heesen Christoph C Zettl Uwe K UK Zipp Frauke F Hemmer Bernhard B Meuth Sven G SG Gold Ralf R Wiendl Heinz H Salmen Anke A

Journal of neurology 20181204 2

<h4>Background</h4>Cognitive impairment (CI) affects approximately one-third of the patients with early multiple sclerosis (MS) and clinically isolated syndrome (CIS). Little is known about factors predicting CI and progression after initial diagnosis.<h4>Methods</h4>Neuropsychological screening data from baseline and 1-year follow-up of a prospective multicenter cohort study (NationMS) involving 1123 patients with newly diagnosed MS or CIS were analyzed. Employing linear multilevel models, we i ...[more]

PMID: 30515631

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Project description:ObjectiveBased on the theories of brain reserve and cognitive reserve, we investigated whether larger maximal lifetime brain growth (MLBG) and/or greater lifetime intellectual enrichment protect against cognitive decline over time.MethodsForty patients with multiple sclerosis (MS) underwent baseline and 4.5-year follow-up evaluations of cognitive efficiency (Symbol Digit Modalities Test, Paced Auditory Serial Addition Task) and memory (Selective Reminding Test, Spatial Recall Test). Baseline and follow-up MRIs quantified disease progression: percentage brain volume change (cerebral atrophy), percentage change in T2 lesion volume. MLBG (brain reserve) was estimated with intracranial volume; intellectual enrichment (cognitive reserve) was estimated with vocabulary. We performed repeated-measures analyses of covariance to investigate whether larger MLBG and/or greater intellectual enrichment moderate/attenuate cognitive decline over time, controlling for disease progression.ResultsPatients with MS declined in cognitive efficiency and memory (p < 0.001). MLBG moderated decline in cognitive efficiency (p = 0.031, ?p (2) = 0.122), with larger MLBG protecting against decline. MLBG did not moderate memory decline (p = 0.234, ?p (2) = 0.039). Intellectual enrichment moderated decline in cognitive efficiency (p = 0.031, ?p (2) = 0.126) and memory (p = 0.037, ?p (2) = 0.115), with greater intellectual enrichment protecting against decline. MS disease progression was more negatively associated with change in cognitive efficiency and memory among patients with lower vs higher MLBG and intellectual enrichment.ConclusionWe provide longitudinal support for theories of brain reserve and cognitive reserve in MS. Larger MLBG protects against decline in cognitive efficiency, and greater intellectual enrichment protects against decline in cognitive efficiency and memory. Consideration of these protective factors should improve prediction of future cognitive decline in patients with MS.

Project description:Tau pathology, neuroinflammation, and neurodegeneration are key aspects of Alzheimer's disease. Understanding whether these features predict cognitive decline, alone or in combination, is crucial to develop new prognostic measures and enhanced stratification for clinical trials. Here, we studied how baseline assessments of in vivo tau pathology (measured by 18F-AV-1451 PET), neuroinflammation (measured by 11C-PK11195 PET) and brain atrophy (derived from structural MRI) predicted longitudinal cognitive changes in patients with Alzheimer's disease pathology. Twenty-six patients (n?=?12 with clinically probable Alzheimer's dementia and n?=?14 with amyloid-positive mild cognitive impairment) and 29 healthy control subjects underwent baseline assessment with 18F-AV-1451 PET, 11C-PK11195 PET, and structural MRI. Cognition was examined annually over the subsequent 3 years using the revised Addenbrooke's Cognitive Examination. Regional grey matter volumes, and regional binding of 18F-AV-1451 and 11C-PK11195 were derived from 15 temporo-parietal regions characteristically affected by Alzheimer's disease pathology. A principal component analysis was used on each imaging modality separately, to identify the main spatial distributions of pathology. A latent growth curve model was applied across the whole sample on longitudinal cognitive scores to estimate the rate of annual decline in each participant. We regressed the individuals' estimated rate of cognitive decline on the neuroimaging components and examined univariable predictive models with single-modality predictors, and a multi-modality predictive model, to identify the independent and combined prognostic value of the different neuroimaging markers. Principal component analysis identified a single component for the grey matter atrophy, while two components were found for each PET ligand: one weighted to the anterior temporal lobe, and another weighted to posterior temporo-parietal regions. Across the whole-sample, the single-modality models indicated significant correlations between the rate of cognitive decline and the first component of each imaging modality. In patients, both stepwise backward elimination and Bayesian model selection revealed an optimal predictive model that included both components of 18F-AV-1451 and the first (i.e. anterior temporal) component for 11C-PK11195. However, the MRI-derived atrophy component and demographic variables were excluded from the optimal predictive model of cognitive decline. We conclude that temporo-parietal tau pathology and anterior temporal neuroinflammation predict cognitive decline in patients with symptomatic Alzheimer's disease pathology. This indicates the added value of PET biomarkers in predicting cognitive decline in Alzheimer's disease, over and above MRI measures of brain atrophy and demographic data. Our findings also support the strategy for targeting tau and neuroinflammation in disease-modifying therapy against Alzheimer's disease.

Dataset Information

Can we predict cognitive decline after initial diagnosis of multiple sclerosis? Results from the German National early MS cohort (KKNMS).

Background

Methods

Results

Conclusions

Publications

Can we predict cognitive decline after initial diagnosis of multiple sclerosis? Results from the German National early MS cohort (KKNMS).

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