Combining tau-PET and fMRI meta-analyses for patient-centered prediction of cognitive decline in Alzheimer’s disease - Alzheimer's Research & Therapy

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A study published in AlzheimersRes demonstrates that tau-PET combined with fMRI-based mapping of cognitive functions is a promising tool for individualized prediction of cognitive decline in Alzheimer’s Disease.

Statistical analysisDifferences in baseline characteristics between diagnostic groups were tested using ANOVAs for continuous and chi-squared tests for categorical data.

To compare the accuracy of different tau-PET ROIs for predicting cognitive decline, we performed bootstrapped linear regression with 1000 iterations per cognitive domain and tau-PET ROI. Within each iteration, cognitive changes on MEM/LAN/EF/VS were included as dependent variables, and tau-PET ROIs as independent variables. For ADNI, all models were controlled for age, sex, education, clinical status, APOE4 status, and baseline performance of the respective cognitive composite.

Next, we aimed to determine patient-specific cognitive composites that are informed by the baseline tau-PET-based prediction of cognitive decline, using ADNI as a discovery sample and A05 as a validation sample. Within ADNI Aβ+, we ran 1000 bootstrapped regressions controlled for age, sex, clinical status, and APOE4 status to extract 1000 beta-values of the association between cognitive-domain-specific tau-PET and cognitive changes for each variable of the regression model ).

Next, we entered patient-specific baseline data of both ADNI and A05 subjects in the 1000 linear model equations to determine mean patient-specific estimates of cognitive decline. To generate a personalized cognitive composite, we computed squared ranks of predicted cognitive changes across MEM/LAN/EF/VS for each subject , in order to maximize the information weight of cognitive domains with fast predicted cognitive decline.

 

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