Systematic analysis of cellular crosstalk reveals a role for SEMA6D-TREM2 regulating microglial function in Alzheimer’s disease
Bibliographic record
Abstract
Abstract Cellular crosstalk, mediated by membrane receptors and their ligands, is crucial for brain homeostasis and can contribute to neurodegenerative diseases such as Alzheimer’s disease (AD). To discover crosstalk dysregulations in AD, we reconstructed crosstalk networks from single-nucleus transcriptional profiles from 67 clinically and neuropathologically well-characterized controls and AD brain donors. We predicted a significant role for TREM2 and additional AD risk genes mediating neuron-microglia crosstalk in AD. The gene sub-network mediating SEMA6D-TREM2 crosstalk is activated near Aβ plaques and SEMA6D -expressing cells and is disrupted in late AD stages. Using CRISPR-modified human induced pluripotent stem cell-derived microglia, we demonstrated that SEMA6D induces microglial activation in a TREM2 -dependent manner. In summary, we demonstrate that characterizing cellular crosstalk networks can yield novel insights into AD biology. One Sentence Summary We investigate cell-to-cell communication in Alzheimer’s disease to characterize disease biology and suggest new avenues for therapeutic intervention.
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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 | 0.000 |
| 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".