UC Davis

Background

Plasma biomarkers have demonstrated excellent performances in detecting AD/ADRD-related brain pathology. However, their relationship with cognitive decline remains unclear. We examined this in a large memory clinic cohort with baseline plasma biomarkers and repeated cognitive assessments over approximately three decades.

Method

Participants at the University of Pittsburgh Alzheimers Disease Research Center underwent blood collection and Clinical Dementia Rating (CDR) Sum of Boxes-based cognitive assessment cross-sectionally, followed by annual CDR assessments for up to 29 years (3.0 [IQR 1.9-5.9]). Plasma p-tau181, p-tau217, brain-derived tau (BD-tau), GFAP and NfL, were measured using SIMOA assays. Linear/logistic regression and Fishers exact were employed for statistical inference.

Result

We included 4,073 participants (59.9% female; 90.2% self-identified non-Hispanic White), aged 71.9 ± 9.8 years, with 2160 being non-demented (CDR≤0.5) at baseline. Cross-sectionally, higher levels of all biomarkers were significantly associated with worse CDR scores. Longitudinally, baseline p-tau181 and GFAP levels best predicted cognitive decline at 0-2, 2-5, 5-10, and >10 years. In contrast, p-tau217 was superior at predicting whether cognitive decline would happen at all within 2, 5, or 10 years, with AUCs up to 0.810. Participants with above-median p-tau217 levels had the highest odds of cognitive decline (2.57, 4.53, and 10.34 times within 2, 5 and 10 years, respectively). p-tau217, and p-tau217/BD-tau ratio accounting for CNS-derived p-tau217, were most effective in predicting cognitive decline in participants who were cognitively non-demented at baseline. Importantly, cognitively stable individuals had lower levels of all plasma biomarkers vs. progressors, with p-tau217 best at separating these groups.

Conclusion

Leveraging a large cohort with extensive longitudinal data, our findings underscore the significant value of blood-based biomarkers in predicting cognitive decline to aid personalized clinical management and ultimately improve patient outcomes.