Bayesian latent time joint mixed‐effects model of progression in the Alzheimer's Disease Neuroimaging Initiative. Issue 1 (29th August 2018)

• Record Type: Journal Article
• Authors: Li, Dan; Iddi, Samuel; Thompson, Wesley K.; Rafii, Michael S.; Aisen, Paul S.; Donohue, Michael C.
• Is Part Of: Alzheimer's & dementia. Volume 10:Issue 1(2018)
• Page Start: 657
• Page End: 668
• Publication Date: 2018-08-29
• Subjects: Alzheimer's disease -- Hierarchical Bayesian models -- Joint mixed‐effects models -- Latent disease time -- Multicohort longitudinal data -- Multiple outcomes; Alzheimer's disease -- Periodicals; Alzheimer's disease -- Diagnosis -- Periodicals; Dementia -- Periodicals; Dementia -- Diagnosis -- Periodicals; 616.831
• DOI: 10.1016/j.dadm.2018.07.008
• Languages: English
• ISSNs: 2352-8729

Abstract

Abstract: Introduction: We characterize long‐term disease dynamics from cognitively healthy to dementia using data from the Alzheimer's Disease Neuroimaging Initiative. Methods: We apply a latent time joint mixed‐effects model to 16 cognitive, functional, biomarker, and imaging outcomes in Alzheimer's Disease Neuroimaging Initiative. Markov chain Monte Carlo methods are used for estimation and inference. Results: We find good concordance between latent time and diagnosis. Change in amyloid positron emission tomography shows a moderate correlation with change in cerebrospinal fluid tau ( ρ = 0.310) and phosphorylated tau ( ρ = 0.294) and weaker correlation with amyloid‐β 42 ( ρ = 0.176). In comparison to amyloid positron emission tomography, change in volumetric magnetic resonance imaging summaries is more strongly correlated with cognitive measures (e.g., ρ = 0.731 for ventricles and Alzheimer's Disease Assessment Scale). The average disease trends are consistent with the amyloid cascade hypothesis. Discussion: The latent time joint mixed‐effects model can (1) uncover long‐term disease trends; (2) estimate the sequence of pathological abnormalities; and (3) provide subject‐specific prognostic estimates of the time until onset of symptoms.