Proteomic evidence of depression-associated astrocytic dysfunction in the human male olfactory bulb
Bibliographic record
Abstract
Abstract The olfactory bulb (OB), a major structure of the limbic system, has been understudied in human investigations of psychopathologies such as depression. To explore more directly the molecular features of the OB in depression, a global comparative proteome analysis was carried out with human post-mortem OB samples from 11 males having suffered from depression and 12 healthy controls. We identified 188 differentially abundant proteins (with adjusted p<0.05) between depressed cases and controls. Gene ontology and gene enrichment analyses suggested that these proteins are involved in biological processes including the complement and coagulation cascades. Cell type enrichment analysis displayed a significant reduction in several canonical astrocytic proteins in OBs from depressed patients. Furthermore, using RNA-fluorescence in-situ hybridization, we observed a decrease in the percentage of ALDH1L1 + cells expressing canonical astrocytic markers including ALDOC , NFIA , GJA1 (connexin 43) and SLC1A3 (EAAT1) . These results are consistent with previous reports of downregulated astrocytic marker expression in other brain regions in depressed patients. We also conducted a comparative phosphoproteomic analysis of OB samples and found a dysregulation of proteins involved in neuronal and astrocytic functions. To determine whether OB astrocytic abnormalities is specific to humans, we also performed proteomics on the OB of socially defeated male mice, a commonly used model of depression. Cell-type specific analysis revealed that in socially defeated animals, the most striking OB protein alterations were associated with oligodendrocyte- lineage cells rather than with astrocytes, highlighting an important species difference. Overall, this study further highlights cerebral astrocytic abnormalities as a consistent feature of depression in humans.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".