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. 2020:27:102282.
doi: 10.1016/j.nicl.2020.102282. Epub 2020 May 26.

Dynamic association between AT(N) profile and cognition mediated by cortical thickness in Alzheimer's continuum

Jae-Won Jang  1 , Yeshin Kim  2 , Seongheon Kim  3 , Sang Won Park  4 , Sung Ok Kwon  5 , Young Ho Park  6 , Jae-Sung Lim  7 , Young Chul Youn  8 , Sung Hun Kim  9 , SangYun Kim  10 ; Alzheimer's Disease Neuroimaging Initiative
Affiliations

Dynamic association between AT(N) profile and cognition mediated by cortical thickness in Alzheimer's continuum

Jae-Won Jang et al. Neuroimage Clin. 2020.

Abstract

Background: The recently-proposed National Institute on Aging and Alzheimer's Association research framework organizes Alzheimer's disease (AD) biomarkers based on amyloid/tau/neurodegeneration (AT(N)). This study investigated the mediating effect of structural change in brain MRI on changes in cognitive function according to initial AT(N) profiles.

Methods: We included 576 subjects (cognitively unimpaired (N = 136), mild cognitive impairment (N = 294), dementia (N = 146)) from the Alzheimer's disease Neuroimaging Initiative study. The parallel-process latent growth curve model was applied to test the mediational effect of cortical thickness growth trajectory between the initial AT(N) profiles and cognitive growth trajectory.

Results: In Alzheimer's continuum, only the A + T + (N)+ profile showed a mediational effect of the cortical thickness growth trajectory. A + T - (N)- was not sufficient to induce direct or indirect effects on cognitive dysfunction, and A + T + (N)- showed a significant direct path from an altered cortical thickness to cognitive decline.

Conclusion: The sequential effect between changes in brain MRI and cognition varied by baseline AT(N) profile, suggesting the dynamic changes in the relationships among biomarkers in the current cascade model.

Keywords: Alzheimer’s disease; Beta amyloid; Brain MRI; CSF biomarkers; Mild cognitive impairment; Parallel process latent growth curve model; Structural equation modeling; Tau.

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Figures

Fig. 1
Fig. 1
Schematic figure of the parallel process growth curve model to test the effect of CSF measures on the rate of cognitive change via rate of change in cortical thickness over time. The subscripts for AD-signature and ADAS cog refer to the months collected in the ADNI data. Latent variable slopes (circles) were regressed on the observed variables (squares) of the CSF adjusted by age, sex, APOE, educational level, and initial clinical diagnosis. Residual error variances are represented by two-headed curved arrows for observed and latent variables.
Fig. 2
Fig. 2
Bivariate correlation matrix between variables. The red color indicates a positive correlation, whereas the yellow indicates a negative correlation. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Fig. 3
Fig. 3
Mediational effects of brain magnetic resonance imaging (MRI) on baseline cerebrospinal fluid (CSF) to cognitive slope The diagram of the mediation model pathways is presented above the table. Showing direct pathways among initial CSF, MRI slope, and cognitive slope (i.e., a, b, and c). The strength of the mediation pathway (i.e., i) is the multiplication product of the component edge weights in these pathways (i.e., βa*βb). Abbreviations: CSF, cerebrospinal fluid, CI, confidential interval NOTE. Regression coefficients are computed by bootstrap sampling with 10,000 iteration after adjusted for age, gender, education, ApoE and diagnosis at entry. In the table, β coefficients and 95% confidence intervals are displayed. Coefficients significance at 95% confidence level are in bold.
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