Introduction
Alzheimer’s disease (AD) remains a leading cause of dementia worldwide, with an urgent need for early detection strategies that can guide intervention before irreversible cognitive decline occurs. Traditionally, AD diagnosis has relied on clinical assessments complemented by neuroimaging and cerebrospinal fluid (CSF) biomarkers; however, these methods are often invasive, costly, or not widely accessible. Recent advances in blood-based biomarkers offer a promising avenue for scalable, minimally invasive screening, particularly in cognitively unimpaired populations at risk.
This review critically examines the findings from the study titled “Association of plasma Alzheimer’s disease biomarkers with cognitive decline in cognitively unimpaired individuals” by Cogswell et al., published in 2025. The study evaluates plasma phosphorylated tau217 (%p-tau217) and amyloid PET imaging in predicting transition from normal cognition to mild cognitive impairment (MCI), drawing data from the Mayo Clinic Study of Aging (MCSA) and BioFINDER-2 cohorts.
Study Design
The research analyzed two well-characterized cohorts: 381 participants from the MCSA and 584 individuals from BioFINDER-2, all initially cognitively unimpaired. Baseline plasma levels of AD-related biomarkers—%p-tau217, amyloid beta 42/40 ratio, and amyloid PET Centiloid—were measured. The cohorts were followed longitudinally, with progression to MCI as the primary endpoint.
Associations were assessed using Cox proportional hazards models, adjusting for age, sex, and education, to determine the predictive value of each biomarker for cognitive decline.
Key Findings
The study identified amyloid PET imaging and plasma %p-tau217 as the strongest predictors of progression from cognitive unimpaired to MCI in both cohorts. Specifically, hazard ratios (HRs) for these markers ranged from 1.23 to 1.72, indicating a significant increase in risk with higher biomarker levels.
In the MCSA cohort, amyloid PET had the highest predictive accuracy, with an HR of 1.49, emphasizing its role as a robust biomarker in this population. Plasma %p-tau217 also demonstrated a significant association, with HRs of 1.49 and 1.23.
In contrast, the BioFINDER-2 cohort showed that plasma %p-tau217 and amyloid PET both predicted progression, with HRs of 1.65 and 1.72, respectively. Notably, plasma amyloid beta 42/40 ratio was a significant predictor only in the BioFINDER-2 cohort (HR 2.20), suggesting possible cohort-specific differences or measurement variability.
The utility of plasma biomarkers was especially evident in the BioFINDER-2 cohort, where plasma AD biomarkers added value to amyloid PET imaging in predicting cognitive decline.
Discussion and Implications
The consistent association of plasma %p-tau217 with disease progression across both cohorts underscores its potential as a minimally invasive, scalable biomarker for early AD detection. This biomarker reflects tau pathology, which closely correlates with neurodegeneration and clinical symptoms.
However, differences observed between cohorts highlight the importance of factors such as cohort demographics, biomarker measurement techniques, and disease stage at baseline. The mass spectrometry-based measurement of plasma p-tau217 provides high specificity but may require standardization for broader clinical application.
While amyloid PET remains the strongest predictor within the MCSA, plasma biomarkers, particularly %p-tau217, could enhance risk stratification in settings where imaging is unavailable. The added predictive value of plasma biomarkers also points toward their potential role in screening asymptomatic at-risk populations to identify candidates for early intervention trials.
Limitations include potential measurement variability, cohort differences, and the need for longitudinal validation in diverse populations. Further studies should also explore how these biomarkers perform in preclinical stages and in conjunction with other risk factors.
Conclusion
Plasma phosphorylated tau217 emerges as a promising biomarker for predicting cognitive decline in unimpaired individuals, with amyloid PET providing robust concordant evidence. Integrating plasma biomarkers into clinical research and potential future screening programs can facilitate earlier detection of AD, ultimately improving management and therapeutic outcomes.
Continued validation, standardization, and understanding of biomarker dynamics across populations are crucial steps toward their routine clinical use. This research advances the goal of accessible, cost-effective tools for preclinical AD detection, with promising implications for personalized medicine approaches in neurodegeneration.
Funding and Clinical Trial Information
The study was supported by grants from the National Institutes of Health and other research foundations. Specific trial registration details are not provided, but the cohorts involved are part of ongoing longitudinal studies aligned with AD biomarker research initiatives.
References
1. Cogswell, PM et al. (2025). Association of plasma Alzheimer’s disease biomarkers with cognitive decline in cognitively unimpaired individuals. Alzheimer’s & Dementia. doi:10.1002/alz.70625.
2. Jack, C.R. et al. (2018). NIA-AA Research Framework: Toward a biological definition of Alzheimer’s disease. Alzheimer’s & Dementia, 14(4), 535-562.
3. Therneau, T. (2015). A Package for Survival Analysis in R. https://CRAN.R-project.org/package=survival
This article synthesizes current understanding and suggests future pathways for biomarkers in early AD detection, emphasizing their mixed but promising potential in transforming clinical practice.
