Synaptotagmin-7 is a key factor for bipolar-like behavioral abnormalities in mice
Bibliographic record
Abstract
The pathogenesis of bipolar disorder (BD) has remained enigmatic, largely because genetic animal models based on identified susceptible genes have often failed to show core symptoms of spontaneous mood cycling. However, pedigree and induced pluripotent stem cell (iPSC)-based analyses have implicated that dysfunction in some key signaling cascades might be crucial for the disease pathogenesis in a subpopulation of BD patients. We hypothesized that the behavioral abnormalities of patients and the comorbid metabolic abnormalities might share some identical molecular mechanism. Hence, we investigated the expression of insulin/synapse dually functioning genes in neurons derived from the iPSCs of BD patients and the behavioral phenotype of mice with these genes silenced in the hippocampus. By these means, we identified synaptotagmin-7 (Syt7) as a candidate risk factor for behavioral abnormalities. We then investigated Syt7 knockout (KO) mice and observed nocturnal manic-like and diurnal depressive-like behavioral fluctuations in a majority of these animals, analogous to the mood cycling symptoms of BD. We treated the Syt7 KO mice with clinical BD drugs including olanzapine and lithium, and found that the drug treatments could efficiently regulate the behavioral abnormalities of the Syt7 KO mice. To further verify whether Syt7 deficits existed in BD patients, we investigated the plasma samples of 20 BD patients and found that the Syt7 mRNA level was significantly attenuated in the patient plasma compared to the healthy controls. We therefore concluded that Syt7 is likely a key factor for the bipolar-like behavioral abnormalities.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".