The CD33 short isoform is a gain-of-function variant that enhances Aβ1–42 phagocytosis in microglia
Bibliographic record
Abstract
BACKGROUND: CD33 is genetically linked to Alzheimer's disease (AD) susceptibility through differential expression of isoforms in microglia. The role of the human CD33 short isoform (hCD33m), preferentially encoded by an AD-protective CD33 allele (rs12459419T), is unknown. Here, we test whether hCD33m represents a loss-of-function or gain-of-function variant. METHODS: We have developed two models to test the role of hCD33m. The first is a new strain of transgenic mice expressing hCD33m in the microglial cell lineage. The second is U937 cells where the CD33 gene was disrupted by CRISPR/Cas9 and complemented with different variants of hCD33. Primary microglia and U937 cells were tested in phagocytosis assays and single cell RNA sequencing (scRNAseq) was carried out on the primary microglia. Furthermore, a new monoclonal antibody was developed to detect hCD33m more efficiently. RESULTS: microglia are enriched in a cluster of cells defined by an upregulated expression and gene regulatory network of immediate early genes, which was further validated within microglia in situ. Using a new hCD33m-specific antibody enabled hCD33m expression to be examined, demonstrating a preference for an intracellular location. Moreover, this newly discovered gain-of-function role for hCD33m is dependent on its cytoplasmic signaling motifs, dominant over hCD33M, and not due to loss of glycan ligand binding. CONCLUSIONS: These results provide strong support that hCD33m represents a gain-of-function isoform and offers insight into what it may take to therapeutically capture the AD-protective CD33 allele.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".