BDNF controls cognitive processes related to neuropsychiatric manifestations via autophagic regulation of p62 and GABA <sub>A</sub> receptor trafficking
Bibliographic record
Abstract
Summary Reduced BDNF and GABAergic inhibition co-occur in neuropsychiatric diseases, including major depression. Genetic rodent studies show a causal link, suggesting the presence of biological pathways that mediate this co-occurrence. Here we show that mice with reduced Bdnf ( Bdnf +/- ) have upregulated expression of sequestosome-1/p62, an autophagy-associated stress response protein, and reduced surface presentation of α5 subunit-containing GABA A receptor (α5-GABA A R) in prefrontal cortex (PFC) pyramidal neurons. Reducing p62 gene dosage restored α5-GABA A R surface expression and rescued the PFC-relevant behavioral deficits of Bdnf +/- mice, including cognitive inflexibility and sensorimotor gating deficits. Increasing p62 levels was sufficient to recreate the molecular and behavioral profiles of Bdnf +/- mice. Finally, human postmortem corticolimbic transcriptome analysis suggested reduced autophagic activity in depression. Collectively, the data reveal that autophagy regulation through control of p62 dosage may serve as a mechanism linking reduced BDNF signaling, GABAergic deficits, and psychopathology associated with PFC functional deficits across psychiatric disorders. HIGHLIGHTS BDNF constitutively promotes autophagy in cortical pyramidal neurons Reduced BDNF causes elevated autophagy-regulator p62 expression, leading to lower surface α5-GABA A R presentation Increasing p62 levels mimics cognition-related behavioral deficits in Bdnf +/- mice Altered postmortem corticolimbic gene expression suggests reduced autophagic activity in depression
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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".