Data‑driven cognitive composites predict Aβ‑related decline and progression to MCI: the ADOPIC study.
Cognitive composites offer greater sensitivity to amyloid beta (Aβ)-related decline compared to individual tests for tracking longitudinal cognitive change. We developed and validated data-driven composites from the harmonized Alzheimer's Dementia Onset and Progression in International Cohorts (ADOPIC) study, addressing gaps in psychometric reporting and multi-cohort validation.
The study included 1964 cognitively unimpaired (CU) participants at baseline (longitudinal subset = 1110). Principal component analysis-derived domain-specific and general cognitive composites were evaluated for psychometric properties, sensitivity to Aβ-related decline, and mild cognitive impairment (MCI) progression prediction compared to the Alzheimer's Disease Cooperative Study - Preclinical Alzheimer's Cognitive Composite (ADCS-PACC).
Proposed composites demonstrated good to excellent psychometric properties and sensitivity to differentiating CU Aβ trajectories (p < 0.001). General cognition demonstrated longitudinal sensitivity comparable to the ADCS-PACC (d = -0.20) and equivalent classification performance (area under the receiver operating characteristic curve = 0.70). All composites significantly predicted MCI progression (p < 0.001).
The composites perform comparably to the ADCS-PACC, developed for CU with Aβ, in longitudinal sensitivity while providing comprehensive psychometric characterization and domain-specific measurement, supporting their utility as outcome measures in preclinical Alzheimer's disease studies.
The study included 1964 cognitively unimpaired (CU) participants at baseline (longitudinal subset = 1110). Principal component analysis-derived domain-specific and general cognitive composites were evaluated for psychometric properties, sensitivity to Aβ-related decline, and mild cognitive impairment (MCI) progression prediction compared to the Alzheimer's Disease Cooperative Study - Preclinical Alzheimer's Cognitive Composite (ADCS-PACC).
Proposed composites demonstrated good to excellent psychometric properties and sensitivity to differentiating CU Aβ trajectories (p < 0.001). General cognition demonstrated longitudinal sensitivity comparable to the ADCS-PACC (d = -0.20) and equivalent classification performance (area under the receiver operating characteristic curve = 0.70). All composites significantly predicted MCI progression (p < 0.001).
The composites perform comparably to the ADCS-PACC, developed for CU with Aβ, in longitudinal sensitivity while providing comprehensive psychometric characterization and domain-specific measurement, supporting their utility as outcome measures in preclinical Alzheimer's disease studies.
Authors
Tallapragada Tallapragada, Galna Galna, Shishegar Shishegar, Markovic Markovic, Brown Brown, Dore Dore, Laws Laws, Porter Porter, Burnham Burnham, Lim Lim, Hassenstab Hassenstab, Rowe Rowe, Jin Jin, Fripp Fripp, Doecke Doecke, Tosun Tosun, Weiner Weiner, Martins Martins, Morris Morris, Masters Masters, Maruff Maruff, Sohrabi Sohrabi,
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