Differential interaction with <scp>TREM2</scp> modulates microglial uptake of modified Aβ species
Bibliographic record
Abstract
Rare coding variants of the microglial triggering receptor expressed on myeloid cells 2 (TREM2) confer an increased risk for Alzheimer's disease (AD) characterized by the progressive accumulation of aggregated forms of amyloid β peptides (Aβ). Aβ peptides are generated by proteolytic processing of the amyloid precursor protein (APP). Heterogeneity in proteolytic cleavages and additional post-translational modifications result in the production of several distinct Aβ variants that could differ in their aggregation behavior and toxic properties. Here, we sought to assess whether post-translational modifications of Aβ affect the interaction with TREM2. Biophysical and biochemical methods revealed that TREM2 preferentially interacts with oligomeric Aβ, and that phosphorylation of Aβ increases this interaction. Phosphorylation of Aβ also affected the TREM2 dependent interaction and phagocytosis by primary microglia and in APP transgenic mouse models. Thus, TREM2 function is important for sensing phosphorylated Aβ variants in distinct aggregation states and reduces the accumulation and deposition of these toxic Aβ species in preclinical models of Alzheimer's disease.
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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".