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Data Sheet 1_Modeling heterogeneity in cognitive trajectories in the Framingham Heart Study.pdf

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NIAID Data Ecosystem2026-05-02 收录
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https://figshare.com/articles/dataset/Data_Sheet_1_Modeling_heterogeneity_in_cognitive_trajectories_in_the_Framingham_Heart_Study_pdf/29400458
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IntroductionThe prevalence of cognitive impairment in the population is growing; however, there is substantial heterogeneity in the rate of decline across different cognitive domains. Harmonized factor scores measuring memory, executive function, and language domains have been created in the Framingham Heart Study (FHS). MethodsThis work identified FHS participants with two or more repeated factor scores after age 60 and fitted latent class mixed models (LCMM) to cluster cognitive trajectories within each domain. Non-linear shapes of trajectories were modeled piecewise linearly, followed by stepwise selections to select cluster-specific change points. ResultsWe identified different latent classes of participants with early cognitive decline, compared to late decliners, for each domain. Ten-fold cross-validation yielded stable subgroupings. Our findings show latent-class-related differential patterns in cognitive aging in the FHS. We also investigated the association between identified latent classes with existing protein biomarkers of cognitive aging in a subsample of the study and found elevated levels of CD40L and CD14 were associated with a higher risk of early decline in memory and executive function domain, respectively. DiscussionIn summary, our study advances the understanding of cognitive decline heterogeneity among FHS participants and sets the stage for further investigations into early intervention strategies and personalized approaches to mitigate cognitive aging risks.
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