Abstract
Background: Subjective cognitive concerns (SCC) have emerged as important early indicators of Alzheimer’s disease (AD) risk. Traditional measures of SCC rely on recall-based assessments, which may be limited in capturing real-time fluctuations in cognitive concerns. Ecological Momentary Assessment (EMA) offers a promising alternative by providing real-time data. This study aimed to link SCC assessed via EMA and traditional measures with blood-based AD biomarkers in a diverse, dementia-free, community-based sample based in the Bronx, NY. Methods: Einstein Aging Study (EAS) participants underwent in-person, recall-based assessments of SCC during an in-clinic visit. Additionally, EMA SCC assessments were collected once per day over two weeks. Linear regressions were conducted to examine the relationships between SCC variables and plasma biomarkers adjusted for demographics and mild cognitive impairment (MCI) status. Results: In N = 254 participants, EMA-reported SCCs demonstrated significant associations with AD biomarkers, particularly p-tau181 (β = 0.21, p = 0.001). Further, significant associations remain across both cognitive (cognitively unimpaired vs. MCI) and racial groups. In contrast, traditional SCC measures exhibited limited associations with these biomarkers. The findings highlight the added value of EMA in capturing SCCs that could indicate early ADRD risk. Conclusions: EMA provides a more dynamic and potentially sensitive method for detecting early AD risk compared to traditional SCC assessments. These real-time measures could enhance early detection and clinical intervention, particularly in diverse and under-resourced populations. This study underscores the potential of EMA for broad applicability and inclusivity in monitoring AD progression and facilitating early therapeutic interventions.
| Original language | English (US) |
|---|---|
| Article number | 82 |
| Journal | Alzheimer's Research and Therapy |
| Volume | 17 |
| Issue number | 1 |
| DOIs | |
| State | Published - Dec 2025 |
All Science Journal Classification (ASJC) codes
- Neurology
- Clinical Neurology
- Cognitive Neuroscience
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