A clinically relevant selective ERK-pathway inhibitor reverses core deficits in a mouse model of autism
Bibliographic record
Abstract
Extracellular signal-regulated kinase (ERK/MAPK) pathway in the brain is hypothesized to be a critical convergent node in the development of autism spectrum disorder. However, it is not clear whether selectively targeting this pathway is beneficial in autism. Here we tested a clinically relevant, selective inhibitor of ERK signaling in a mouse model of idiopathic autism. We report that treating juvenile mice with this inhibitor reduced ERK pathway activation, dose and duration-dependently reduced core disease-modeling deficits in sociability, vocalization and repetitive behavior, and reversed abnormal EEG signals. Further analysis revealed that subchronic treatment did not affect weight gain, locomotion, or neuronal density in the brain. Parallel treatment in the control mice did not alter their phenotype. Together, our data indicate that specifically inhibiting the ERK pathway is beneficial in this model, and suggest that selectively targeting ERK pathway could be a new approach for treating autism.Funding Information: This work was supported by Alberta Children’s Hospital Research Foundation (JMR & NC).Declaration of Interests: The authors declare no competing interests. Ethics Approval Statement: Breeder B6 (Jax stock No: 000664) and BTBR (Jax stock No: 002282) mice were obtained from the Jackson Laboratory (ME, USA) and maintained at the mouse facility of the Cumming School of Medicine, University of Calgary. Mice were group-housed up to five mice per cage in a humidity- and temperature-controlled room with a 12-h light/dark cycle and were fed ad libitum. Male mice were used as test subjects, as female mice made very few vocalizations in our setting irrespective of genetic backgrounds. Strain and number of mice used were indicated for each experiment. All procedures in this study were performed in accordance with the recommendations in the Canadian Council for Animal Care. The protocol of this study was approved by the Health Sciences Animal Care Committee of the University of Calgary.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".