DISCOVERING TRANSLATIONAL BIOMARKERS IN NEURODEVELOPMENTAL CONDITIONS - EEG PROFILE IN MOUSE MODELS OF IDIOPATHIC AND SYNDROMIC AUTISM
Bibliographic record
Abstract
Abstract Background Autism is one of the most prevalent neurodevelopmental disorders worldwide. It is predominantly idiopathic, while syndromic forms have also been identified. Fragile X Syndrome (FXS) is the most common monogenic cause of autism and intellectual disability. No cure currently exists for autism or FXS, and drug development has suffered many failures in clinical trials, which were based on promising preclinical findings. Thus, effective translational biomarkers that bridge animal and human studies are urgently needed. Both autism and FXS are more prevalent in males than females. In addition, fundamental sex and gender differences have been reported in these conditions regarding symptoms and the neural mechanisms. Recently, electroencephalography (EEG) has been proposed as a low-cost translational biomarker in neurodevelopmental conditions. Particularly, recent studies with FXS patients and rodent models indicated an increase in the EEG power of the gamma frequency band. However, there is still a dearth of EEG research in autism, especially in research using animal models and including the female population. Aims & Objectives Here, we aimed to characterize EEG profiles in mouse models of idiopathic and syndromic autism. Methods We compared the BTBR model of idiopathic autism with the control B6 mice, as well as the fmr1 knockout model of FXS and syndromic autism with the control wildtype mice. A custom-made stand-alone Open-Source Electrophysiology Recording system for Rodents (OSERR) was used for EEG recording. Results We found EEG power in the beta and gamma (including both high and low gamma) frequency bands was increased in juvenile male BTBR mice. In the male FXS model, we confirmed previous findings of an increase in the gamma (including both high and low gamma) power. Detailed analysis in the female FXS model indicated that at juvenile stage, increases in the alpha and beta power were present besides a robust increase in the gamma power; yet, at adult stage, only an increase in the alpha power was observed. Furthermore, we analyzed phase-amplitude cross frequency coupling between gamma band (30–100 Hz) and lower frequency oscillations (4–12 Hz), to quantify the modulation of the amplitude of gamma oscillation by the phase of the slow rhythm. Our results indicated that this phase-amplitude coupling was also altered in both the BTBR and the FXS models. Discussion and Conclusion Together, our findings revealed a consistent and robust increase in the gamma power in juvenile mouse models of both idiopathic and syndromic autism. In addition, we identified changes in the EEG signal that depended on sex and developmental stage. Collectively, our findings support further investigation of EEG signal as a translational biomarker in neurodevelopmental conditions, and that factors such as sex and developmental stage should be considered in these studies. Particularly, our results suggest that increased gamma power may be a consistent phenotype in certain autism subgroups and may be useful to stratify patients and monitor treatment outcome.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".