Forkhead box protein p1 is a transcriptional repressor of immune signaling in the CNS: implications for transcriptional dysregulation in Huntington disease
Bibliographic record
Abstract
Forkhead box protein p1 (Foxp1), a transcription factor showing highly enriched expression in the striatum, has been implicated in central nervous system (CNS) development, but its role in the mature brain is unknown. In order to ascertain functional roles for Foxp1 in the CNS, we have identified gene targets for Foxp1 both in vitro and in vivo using genome-wide expression microarrays and chromatin-immunoprecipitation followed by high-throughput sequencing (ChIP-seq) assays. We found that mouse Foxp1 overexpression in striatal cells elicited expression changes of genes related to immune signaling, transcriptional regulation and a manually curated Huntington's disease (HD)-signaling pathway. Similar results were found when the gene expression data set was integrated with Foxp1-binding data determined from ChIP-seq analysis. In vivo lentiviral-mediated overexpression of human FOXP1 in the context of mutant huntingtin (Htt) protein resulted in a robust downregulation of glial cell-associated, immune genes, including those encoding a variety of cytokines and chemokines. Furthermore, Foxp1-induced expression changes were significantly negatively correlated with those changes elicited by mutant Htt protein in several different HD mouse models, and most significantly in post-mortem caudate from human HD subjects. We finally show that Foxp1 interacts with mutant Htt protein in mouse brain and is present in nuclear Htt aggregates in the striatum of R6/1 transgenic mice. These findings implicate Foxp1 as a key repressor of immune signaling in the CNS and suggest that the loss of Foxp1-mediated gene regulation in HD contributes to the immune dysfunction in this disease. We further suggest that Foxp1-regulated pathways might be important mediators of neuronal-glial cell communication.
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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".