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ORIGINAL RESEARCH article
Front. Immunol.
Sec. Autoimmune and Autoinflammatory Disorders : Autoimmune Disorders
Volume 16 - 2025 | doi: 10.3389/fimmu.2025.1537659
This article is part of the Research Topic Bioinformatics and Systems Biology Strategies in Disease Management with a Special Emphasis on Cancer, Alzheimer's Disease and Aging View all 4 articles
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Dementia is a neurodegenerative syndrome marked by the accumulation of disease-specific proteins and immune dysregulation, including autoimmune mechanisms involving autoantibodies. Current diagnostic methods are often invasive, time-consuming, or costly. This study explores the use of proteome-wide autoantibody screening (PWAbS) for noninvasive dementia diagnosis by analyzing serum samples from Alzheimer's disease (AD), dementia with Lewy bodies (DLB), and age-matched cognitively normal individuals (CNIs). Serum samples from 35 subjects were analyzed utilizing our original wet protein arrays displaying more than 13,000 human proteins, revealing elevated gross autoantibody levels in AD and DLB patients compared to CNIs. A total of 229 autoantibodies were differentially elevated in AD and/or DLB, effectively distinguishing between patient groups. Machine learning models showed high accuracy in classifying AD, DLB, and CNIs. Gene ontology analysis highlighted autoantibodies targeting neuroactive ligands/receptors in AD and lipid metabolism proteins in DLB. Notably, autoantibodies targeting neuropeptide B (NPB) and adhesion G protein-coupled receptor F5 (ADGRF5) showed significant correlations with clinical traits including Mini Mental State Examination scores, suggesting a role in dementia pathogenesis. The study demonstrates the potential of PWAbS and artificial intelligence integration as a noninvasive diagnostic tool for dementia, uncovering biomarkers that could enhance understanding of disease mechanisms. Limitations include demographic differences, small sample size, and lack of external validation. Future research should involve longitudinal observation in larger, diverse cohorts and functional studies to clarify autoantibodies' roles in dementia pathogenesis and their diagnostic and therapeutic potential.
Keywords: Autoantibody, artificial intelligence, machine learning, Dementia, Altzheimer's disease, Levy body dementia
Received: 01 Dec 2024; Accepted: 07 Apr 2025.
Copyright: © 2025 Matsuda, Kameyama, Iwadoh, Miyawaki, Yakabe, Ishii, Ogawa, Akishita, Sato and Yoshizaki. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Ayumi Yoshizaki, The University of Tokyo, Bunkyo, Japan
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
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