Molecular basis for the loss-of-function effects of the Alzheimer's disease–associated R47H variant of the immune receptor TREM2
Bibliographic record
Abstract
Triggering receptor expressed on myeloid cells 2 (TREM2) is an immune receptor expressed on the surface of microglia, macrophages, dendritic cells, and osteoclasts. The R47H TREM2 variant is a significant risk factor for late-onset Alzheimer's disease (AD), and the molecular basis of R47H TREM2 loss of function is an emerging area of TREM2 biology. Here, we report three high-resolution structures of the extracellular ligand-binding domains (ECDs) of R47H TREM2, apo-WT, and phosphatidylserine (PS)-bound WT TREM2 at 1.8, 2.2, and 2.2 Å, respectively. The structures reveal that Arg 47 plays a critical role in maintaining the structural features of the complementarity-determining region 2 (CDR2) loop and the putative positive ligand–interacting surface (PLIS), stabilizing conformations capable of ligand interaction. This is exemplified in the PS-bound structure, in which the CDR2 loop and PLIS drive critical interactions with PS via surfaces that are disrupted in the variant. Together with in vitro and in vivo characterization, our structural findings elucidate the molecular mechanism underlying loss of ligand binding, putative oligomerization, and functional activity of R47H TREM2. They also help unravel how decreased in vitro and in vivo stability of TREM2 contribute to loss of function in 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) | 0.001 | 0.000 |
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".