Deep nanoparticle protein corona plasma proteomics resolves a stage-specific peripheral signature of Alzheimer’s disease
Year: 2026
Type: preprint
Abstract: Structured Abstract INTRODUCTION Alzheimer’s disease (AD) progresses over decades, yet plasma biomarkers that resolve disease stage rather than simply detect disease remain scarce. This distinction is clinically consequential because effective AD intervention depends on identifying patients before disease biology has progressed beyond a therapeutically responsive stage. METHODS We used small-molecule-modulated protein corona proteomics to profile plasma from 90 individuals in the Australian Imaging, Biomarker and Lifestyle cohort, stratified by Centiloid (CL) Aβ-amyloid burden (30 amyloid- negative, CL < 15; 30 moderate-to-high, CL 26 to 100; 30 very high, CL > 100). We quantified 3,176 proteins and applied differential abundance and actual causality analyses to identify stage-specific and candidate causal proteins. RESULTS Differential protein abundance was exclusively captured during the moderate-to-high AD transition, revealing a discrete proteomic “switch.” The switch was marked by accumulation of the autophagy receptor CALCOCO1, together with coordinated depletion of the S100A8/S100A9 calprotectin complex and core erythroid-cytoskeletal network structural markers (e.g., SPTA1, SPTB, ANK1). Adhesion G protein-coupled receptor G6 (ADGRG6) showed a significant moderate positive monotonic association with absolute CL burden, providing a proportional molecular anchor for cumulative disease burden. Actual causality analysis identified COL6A2, FOXRED2, P3H1, PRR4, and GOLGA5 as candidate upstream drivers linking matrix remodeling, Golgi trafficking, and collagen processing to AD progression. DISCUSSION These findings suggest a candidate blood-accessible framework for staging AD by active disease biology, which, if replicated in independent cohorts, may have implications for therapeutic selection and mechanism-guided clinical trials. Abstract Figure
Authors: Negar Mahmoudi, Bahareh Ghaffari, Kenneth Rogale, Samuel Cheeseman, Danilo Ritz, Alexander Schmidt, Liuchenxin Han, Qingling Li, Jared Deyarmin, Stephanie N. Samra, Dmitry Leshchiner, Sachi Horibata, Christopher Fowler, Borzoo Bonakdarpour, George Perry, Amir Ata Saei, Colin L. Masters, Babak Borhan, David Nisbet, Morteza Mahmoudi
Language: English
Subfield: Physiology (medical)
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7171551564