Home › Research › Digital health tools
Artificial intelligence and omics-based autoantibody profiling in dementia
Kazuki Mitsuru Matsuda, Yumi Umeda‐Kameyama, Kazuhiro Iwadoh, Masashi Miyawaki, Mitsutaka Yakabe, Masaki Ishii, Sumito Ogawa, Masahiro Akishita et al.. Frontiers in Immunology, 2025-05-08
Topic: Amyloid, tau and blood-test diagnosis
PWAbS revealed 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. 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.
Key findings
- PWAbS revealed 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.
Why it matters
This study found elevated autoantibody levels in people with Alzheimer's disease and dementia with Lewy bodies and used machine learning to classify patient groups with high accuracy. The authors note limitations including small sample size and lack of external validation, and it is a diagnostic approach, not a treatment, cure, or prevention.
New to this subject? Start with our plain-English guide: Digital health →
Study details
- Study designlongitudinal study
- Participants35
- Evidence strengthModerate
How this study scored 50/100
Published in a peer-reviewed journal, and it is a longitudinal study following the same people over time. Scored zero for effect reported and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Frontiers in Immunology) |
| Journal's citation record | 3 / 4 | Frontiers in Immunology: journal h-index 352 (OpenAlex, 2026-10-29) |
| Study design | 7 / 12 | A longitudinal study following the same people over time |
| Strength of evidence | 3 / 5 | Rated “moderate” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 4 / 5 | 2025 — within 3 year(s) of the newest study here |
| Sample size | 1 / 4 | 35 participants |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 3 / 3 | Studied in people (participant count stated) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 1 / 7 | Cited 3 times (OpenAlex, 2026-10-10) |
| Citations per year | 1 / 5 | 1.0 citations a year over 3 year(s) since 2025 |
| Impact for its field and year | 2 / 6 | Cited 1.9× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 0 / 6 | No other study in this library cites it |
| Still being cited | 1 / 4 | Cited 3 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 2 / 4 | Last-listed author Ayumi Yoshizaki: h-index 39 (OpenAlex, whole career) |
| Institution's track record | 1 / 3 | The University of Tokyo: institution h-index 1,463 (OpenAlex) |
| Multi-centre collaboration | 0 / 3 | OpenAlex lists 1 institution(s) in 1 country — scores zero (affiliation lists can be incomplete) |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 40406128) |
| Free to read | 2 / 2 | Free to read |
| Total | 50 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
- DOI: 10.3389/fimmu.2025.1537659
- PubMed: 40406128
- Original source →
- Free full text: Frontiers in Immunology →
Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record's author list ends in “et al.”, so not every author is named. Check the citation against the original before you use it.
APA 7th
Matsuda, K. M., Umeda‐Kameyama, Y., Iwadoh, K., Miyawaki, M., Yakabe, M., Ishii, M., et al. (2025). Artificial intelligence and omics-based autoantibody profiling in dementia. Frontiers in Immunology. https://doi.org/10.3389/fimmu.2025.1537659
Vancouver
Matsuda KM, Umeda‐Kameyama Y, Iwadoh K, Miyawaki M, Yakabe M, Ishii M, et al. Artificial intelligence and omics-based autoantibody profiling in dementia. Frontiers in Immunology. 2025. doi:10.3389/fimmu.2025.1537659. PMID: 40406128.
BibTeX
@article{matsuda2025-40406128,
author = {Matsuda, Kazuki Mitsuru and Umeda‐Kameyama, Yumi and Iwadoh, Kazuhiro and Miyawaki, Masashi and Yakabe, Mitsutaka and Ishii, Masaki and Ogawa, Sumito and Akishita, Masahiro and others},
title = {{Artificial intelligence and omics-based autoantibody profiling in dementia}},
journal = {Frontiers in Immunology},
year = {2025},
doi = {10.3389/fimmu.2025.1537659},
pmid = {40406128},
url = {https://doi.org/10.3389/fimmu.2025.1537659}
}
Studies this one cites
Referenced by this study and also in the alzhub library, so you can read them here. Showing 12 of 13.