Sex and the Estrous-Cycle Phase Influence the Expression of G Protein-Coupled Estrogen Receptor 1 (GPER) in Schizophrenia: Translational Evidence for a New Target
Bibliographic record
Abstract
Abstract Schizophrenia is a mental disorder with sex bias in disease onset and symptom severity. Recently, it was observed that females present more severe symptoms in the perimenstrual phase of the menstrual cycle. The administration of estrogen also alleviates schizophrenia symptoms. Despite this, little is known about symptom fluctuation over the menstrual cycle and the underlying mechanisms. To address this issue, we worked with the two-hit schizophrenia animal model induced by neonatal exposure to a virus-like particle, Poly I:C, in association with peripubertal unpredictable stress exposure. Prepulse inhibition of the startle reflex (PPI) in male and female mice was considered analogous to human schizophrenia-like behavior. Female mice were studied in the proestrus (high-estrogen estrous cycle phase) and diestrus (low-estrogen phase). Additionally, we evaluated the hippocampal mRNA expression of estrogen synthesis proteins, TSPO and aromatase, and estrogen receptors ERα, ERβ, and GPER. We also collected Peripheral Blood Mononuclear Cells (PBMCs) from male and female patients with schizophrenia and converted them to induced microglia-like cells (iMGs) to evaluate the expression of GPER. We observed raised hippocampal expression of GPER in two-hit female mice at the proestrus phase without PPI deficits and higher levels of proteins related to estrogen synthesis, TSPO, and aromatase. In contrast, two-hit adult males with PPI deficits presented lower hippocampal mRNA expression of TSPO, aromatase, and GPER. iMGs from male and female patients with schizophrenia showed lower mRNA expression of GPER than controls. Therefore, our results suggest that GPER alterations constitute an underlying mechanism for sex influence in schizophrenia.
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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) | 0.002 | 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".