Schizophrenia-related dysbindin-1 gene is required for innate immune response and homeostasis in the developing subventricular zone
Bibliographic record
Abstract
Schizophrenia is a neurodevelopmental disorder likely caused by environmental and genetic risk factors but functional interactions between the risk factors are unclear. We tested the hypothesis that dysbindin-1 (Dtnbp1) gene mutation combined with postnatal exposure to viral mimetic polyI:C results in schizophrenia-related behavioural changes in adulthood, and mediates polyI:C-induced inflammation in the subventricular zone (SVZ). Adult Sandy (Sdy, Dtnbp1 mutant) mice given early postnatal polyI:C injections displayed reduced prepulse inhibition of startle, reduced locomotion and deficits in novel object recognition. PolyI:C induced a canonical immune response in the SVZ; it increased mRNA expression of its toll-like receptor 3 (Tlr3) and downstream transcription factors RelA and Sp1. PolyI:C also increased SVZ Dtnbp1 mRNA expression, suggesting dysbindin-1 regulates immune responses. Dysbindin-1 loss in Sdy mice blocked the polyI:C-induced increases in mRNA expression of Tlr3, RelA and Sp1 in the SVZ. Dtnbp1 overexpression in SVZ-derived Sdy neurospheres rescued Tlr3, RelA and Sp1 mRNA expression supporting a functional interaction between dysbindin-1 and polyI:C-induced inflammation. Immunohistochemistry showed higher Iba1+ immune cell density in the SVZ of Sdy mice than in WT postnatally. PolyI:C did not alter SVZ Iba1+ cell density but increased CD45+/Iba1- cell numbers in the SVZ of Sdy mice. Finally, polyI:C injections in Sdy, but not WT mice reduced postnatal and adult SVZ proliferation. Together, we show novel functional interactions between the schizophrenia-relevant dysbindin-1 gene and the immune response to polyI:C. This work sheds light on the molecular basis for amplified abnormalities due to combined genetic predisposition and exposure to environmental schizophrenia risk factors.
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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".