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Single-Cell Transcriptomic Identification of SYK Kinase as a Therapeutic Target in Disease-Associated Microglia for Alzheimer's Disease Treatment
Glen Charles Ritsachel, Claude. Zenodo (CERN European Organization for Nuclear Research), 2026-03-23
Topic: Brain proteins, microglia and lab models
Alzheimer's disease (AD) affects over 55 million people worldwide and lacks effective disease-modifying therapies targeting neuroinflammation. Disease-associated microglia (DAM) are central effectors of AD neuroinflammation, yet cell-type-specific druggable kinase targets in human AD prefrontal cortex microglia have not been systematically identified at single-cell resolution. Here we apply a computational drug screening pipeline to the human prefrontal cortex snRNA-seq dataset GSE138852 (Mathys et al., Nature 2019) to identify SYK kinase as the top druggable target in microglial clusters of AD brain. ScVI dimensionality reduction and Leiden clustering of 13,096 high-quality nuclei from 6 AD and 6 control donors identified 7 cell populations; cluster 4 was confirmed as microglia by P2RY12 (0.992), CX3CR1 (0.666), CSF1R (0.816), and AIF1 (0.390) expression. Wilcoxon differential expression yielded 624 upregulated genes including SYK, CLEC7A, CD86, DOCK8, and SORL1. ChEMBL screening across 8 microglial DAM-relevant targets identified 6,230 NOVEL_ALL inhibitor candidates. Lead SYK inhibitors: CHEMBL3415598 (pChEMBL 11.00), fostamatinib (FDA-approved for ITP, pChEMBL 7.77), entospletinib (8.11), lanraplenib (8.21), mivavotinib (8.70). P2RY12 inhibitors: cangrelor (9.40) and ticagrelor (8.70), both FDA-approved. All confirmed NOVEL_ALL for the Alzheimer's disease / microglial indication. Patent pending. Pipeline: github.com/glenritschel/alzheimers-scrna.
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APA 7th
Ritsachel, G. C., & Claude. (2026). Single-Cell Transcriptomic Identification of SYK Kinase as a Therapeutic Target in Disease-Associated Microglia for Alzheimer's Disease Treatment. Zenodo (CERN European Organization for Nuclear Research). https://doi.org/10.5281/zenodo.19194339
Vancouver
Ritsachel GC, Claude. Single-Cell Transcriptomic Identification of SYK Kinase as a Therapeutic Target in Disease-Associated Microglia for Alzheimer's Disease Treatment. Zenodo (CERN European Organization for Nuclear Research). 2026. doi:10.5281/zenodo.19194339.
BibTeX
@article{ritsachel2026-eb49b3ac,
author = {Ritsachel, Glen Charles and Claude},
title = {{Single-Cell Transcriptomic Identification of SYK Kinase as a Therapeutic Target in Disease-Associated Microglia for Alzheimer's Disease Treatment}},
journal = {Zenodo (CERN European Organization for Nuclear Research)},
year = {2026},
doi = {10.5281/zenodo.19194339},
url = {https://doi.org/10.5281/zenodo.19194339}
}
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Key findings
- ChEMBL screening across 8 microglial DAM-relevant targets identified 6,230 NOVEL_ALL inhibitor candidates.
- Lead SYK inhibitors: CHEMBL3415598 (pChEMBL 11.00), fostamatinib (FDA-approved for ITP, pChEMBL 7.77), entospletinib (8.11), lanraplenib (8.21), mivavotinib (8.70).
- P2RY12 inhibitors: cangrelor (9.40) and ticagrelor (8.70), both FDA-approved.
- All confirmed NOVEL_ALL for the Alzheimer's disease / microglial indication.
- Pipeline: github.com/glenritschel/alzheimers-scrna.
Why it matters
This is a computational analysis of existing human brain data that identifies SYK kinase as a possible drug target and lists candidate inhibitors, so it does not test any treatment in patients. No clinical benefit, cure or prevention is shown.
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Study details
- Evidence strengthLow
How this study scored 41/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded because the record does not state it. We have no data on journal's citation record, times cited, citations per year, impact for its field and year, still being cited, senior author's track record, institution's track record and multi-centre collaboration, so those were left out: it earned 26 of the 64 points we could judge it on, which is 41 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Zenodo (CERN European Organization for Nuclear Research)) |
| Journal's citation record | — / 4 | No journal record from OpenAlex — left out of this score |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 5 / 5 | 2026 — within 1 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | — / 7 | No citation count (not found in OpenAlex) — left out of this score |
| Citations per year | — / 5 | No citation count or no year — left out of this score |
| Impact for its field and year | — / 6 | No field-weighted citation impact (OpenAlex has none yet) — left out of this score |
| Cited by studies here | 0 / 6 | No other study in this library cites it |
| Still being cited | — / 4 | No yearly citation counts — left out of this score |
| Senior author's track record | — / 4 | Senior author's record not available — left out of this score |
| Institution's track record | — / 3 | No institution listed in OpenAlex — left out of this score |
| Multi-centre collaboration | — / 3 | Institutions not listed — left out of this score |
| Indexed in PubMed | 1 / 2 | Not in PubMed, but has a DOI |
| Free to read | 2 / 2 | Free to read |
| Points | 26 / 64 | Scored on 12 of 20 parts. We have no data for the rest, so they are left out: 26 of the 64 points we could judge it on is 41 out of 100. |
| Total | 41 / 100 | — |
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