Four Common Late-Life Cognitive Trajectories Patterns Associate with Replicable Underlying Neuropathologies

Article type: Research Article

Authors: Karanth, Shama D.^{a; b; *} | Schmitt, Frederick A.^{b; c} | Nelson, Peter T.^{b; d} | Katsumata, Yuriko^{b; e} | Kryscio, Richard J.^{b; e; f} | Fardo, David W.^{b; e} | Harp, Jordan P.^{b; c} | Abner, Erin L.^{a; b; e}

Affiliations: [a] Department of Epidemiology, University of Kentucky, Lexington, KY, USA | [b] Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY, USA | [c] Department of Neurology, University of Kentucky, Lexington, KY, USA | [d] Department of Pathology, University of Kentucky, Lexington, KY, USA | [e] Department of Biostatistics, University of Kentucky, Lexington, KY, USA | [f] Department of Statistics, University of Kentucky, Lexington, KY, USA

Correspondence: [*] Correspondence to: Shama D. Karanth, MDS, PhD, Department of Epidemiology, Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY 40536, USA. Tel.: +1 415 988 2994; E-mail: shama.karanth@uky.edu.

Abstract: Background:Late-life cognitive function is heterogeneous, ranging from no decline to severe dementia. Prior studies of cognitive trajectories have tended to focus on a single measure of global cognition or individual tests scores, rather than considering longitudinal performance on multiple tests simultaneously. Objective:The current study aimed to examine cognitive trajectories from two independent datasets to assess whether similar patterns might describe longitudinal cognition in the decade preceding death, as well as what participant characteristics were associated with trajectory membership. Methods:Data were drawn from autopsied longitudinally followed participants of two cohorts (total N = 1,346), community-based cohort at the University of Kentucky Alzheimer’s Disease Research Center (n = 365) and National Alzheimer’s Coordinating Center (n = 981). We used group-based multi-trajectory models (GBMTM) to identify cognitive trajectories over the decade before death using Mini-Mental State Exam, Logical Memory-Immediate, and Animal Naming performance. Multinomial logistic and Random Forest analyses assessed characteristics associated with trajectory groups. Results:GBMTM identified four similar cognitive trajectories in each dataset. In multinomial models, death age, Braak neurofibrillary tangles (NFT) stage, TDP-43, and α-synuclein were associated with declining trajectories. Random Forest results suggested the most important trajectory predictors were Braak NFT stage, cerebral atrophy, death age, and brain weight. Multiple pathologies were most common in trajectories with moderate or accelerated decline. Conclusion:Cognitive trajectories associated strongly with neuropathology, particularly Braak NFT stage. High frequency of multiple pathologies in trajectories with cognitive decline suggests dementia treatment and prevention efforts must consider multiple diseases simultaneously.

Keywords: Cognitive decline, dementia, neurodegenerative disorders, neuropsychological tests, trajectories

DOI: 10.3233/JAD-210293

Journal: Journal of Alzheimer's Disease, vol. 82, no. 2, pp. 647-659, 2021