Rapid Mechanistic Bridging of an Alzheimer’s Disease Plasma Protein Staging Panel Across Brain Proteomics Cohorts

Abstract

Background Blood-based biomarkers are transforming Alzheimer’s Disease (AD) diagnosis and staging. Recent multi-protein plasma panels accurately identify individuals with advanced Braak pathology, but whether these circulating biomarkers truly reflect the molecular remodeling underlying AD neuropathology remains unclear. Pre-existing datasets could answer such questions, but their reuse requires harmonized protein expression data, standardized sample annotations, and consistent study metadata. Methods A recently reported seven-protein plasma staging panel was evaluated across multiple post-mortem proteomics brain cohorts using pre-structured datasets on the Tesorai platform. Five datasets with Braak stage data were identified and re-analyzed. A linear model was used to distinguish late (V-VI) from early Braak stage (0-IV). Because phosphorylated tau 217 (p-tau217) and amyloid beta 1-40 (Aβ40) were not reported for any studies, raw spectra were reprocessed to quantify these proteoforms. Results Across the cohorts, the plasma-derived biomarker panel consistently discriminated early from late disease despite heterogeneous protein coverage. Reprocessing of raw spectra recovered tau phosphopeptides absent from the original protein summaries, enabling inclusion of p-tau217, while Aβ40 remained undetected. Together, these findings show that proteins comprising a recently proposed blood-based staging panel are associated with proteomic remodeling in the AD brain across independent cohorts. Conclusions These findings provide biological validation for a recently proposed blood-based seven-protein staging panel by demonstrating that its constituent biomarkers are associated with disease-stage proteomic changes in AD brain tissue. More broadly, re-mining legacy mass spectrometry data for disease-relevant proteoforms, combined with pre-structured datasets, can accelerate evaluation of emerging blood-based biomarkers against neuropathological and molecular features of disease.