A cognitive resilience gene expression signature in excitatory intratelencephalic cortical neurons
Bibliographic record
Abstract
Abstract Background Alzheimer’s disease (AD) is a devastating form of dementia, and its prevalence is rising as human lifespan increases. Our lab created the AD‐BXD mouse model, which expresses AD mutations across a genetically diverse reference panel (BXD), to identify factors that confer resilience to cognitive decline in AD. This model mimics key characteristics of human AD including variation in age of onset and severity of cognitive decline. Method To facilitate discovery of conserved mechanisms of resilience to AD, we generated a cross‐species single‐nuclei transcriptomic dataset from normal and AD human (ROSMAP) and AD‐BXD mouse frontal cortex tissue. We interrogated resilience‐associated gene expression signatures, validated resilience candidate genes with human reference data, and used a druggability ranking and drug repositioning pipeline to nominate drugs to promote resilience to AD. To learn more about the context of resilience gene expression, we used a hierarchical mapping algorithm to predict anatomical locations of cells expressing resilience gene signatures. Result We found the strongest gene expression signature associated with cognitive resilience to AD arises from excitatory layer 4/5 (eL4/5) cortical intratelencephalic neurons. This resilience signature includes genes involved in synaptic plasticity, vesicle transport, and axonal and dendritic development. We found that 27 of the 61 genes in the resilience signature are druggable and identified several candidate drugs for further investigation (Telpoukhovskaia et al., 2022). We also identified genes expressed across a continuum of cognitive performance. Our hierarchical mapping approach showed that the eL4/5 neurons expressing resilience signature genes are distributed throughout the frontal cortex, mainly in the somatomotor area. Conclusion We identified 61 candidate resilience genes to target with new or existing drugs. We also determined that expression of resilience candidate genes occurs in eL4/5 neurons in the somatomotor region of the cortex. Ongoing projects in the lab aim to evaluate efficacy of nominated drugs and profile learning‐specific proteomes of eL4/5 neurons in resilient and susceptible AD‐BXD strains. When integrated with existing genetic, behavioral, and pathological data, our work will elucidate the cellular, molecular, and genetic mechanisms that contribute to cognitive resilience in face of neurodegenerative disease pathology.
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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 | 0.001 | 0.001 |
| 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".