Subjective cognition trajectories, Alzheimer biomarkers, and incident mild cognitive impairment

Subjective cognitive decline is common in older adults and may represent an early clinical signal along the Alzheimer's disease continuum. The clinical relevance of longitudinal changes in subjective cognitive decline remains unclear.

To determine whether trajectories of self- or study partner-reported cognitive decline predict progression to mild cognitive impairment and reflect Alzheimer's disease-specific biological patterns.

Data were pooled from two observational cohorts. Cognitively unimpaired participants with baseline amyloid status, repeated assessments of subjective cognitive decline, and clinical follow-up were included. The study included 770 participants with a median follow-up of 5.0 years (interquartile range 4.0-7.0).

Subjective cognitive decline was assessed using the Everyday Cognition questionnaire completed by participants and study partners. Linear mixed-effects models examined associations with amyloid status and progression to mild cognitive impairment. Cox proportional hazards models tested whether one-year changes predicted progression.

Amyloid-positive participants and those who progressed to mild cognitive impairment showed steeper increases in self- and study partner-reported cognitive difficulties over time. Among amyloid-positive participants, only increases in study partner-report differentiated progressors from non-progressors. One-year increases in study partner-report predicted a higher risk of mild cognitive impairment compared with unchanged scores (hazard ratio 3.24; 95% confidence interval 1.73-6.07]), with effects confined to amyloid-positive participants.

Short-term increases in study partner-reported cognitive difficulties identify amyloid-positive cognitively unimpaired older adults at increased risk of near-term progression to mild cognitive impairment. Longitudinal monitoring using study partner reports may provide a low-burden and clinically relevant approach for early risk stratification and surveillance in aging populations.