The circadian system: A neglected player in neurodevelopmental disorders
Bibliographic record
Abstract
Patients with neurodevelopmental disorders, such as autism spectrum disorder, often display abnormal circadian rhythms. The role of the circadian system in these disorders has gained considerable attention over the last decades. Yet, it remains largely unknown how these disruptions occur and to what extent they contribute to the disorders' development. In this review, we examine circadian system dysregulation as observed in patients and animal models of neurodevelopmental disorders. Second, we explore whether circadian rhythm disruptions constitute a risk factor for neurodevelopmental disorders from studies in humans and model organisms. Lastly, we focus on the impact of psychiatric medications on circadian rhythms and the potential benefits of chronotherapy. The literature reveals that patients with neurodevelopmental disorders display altered sleep-wake cycles and melatonin rhythms/levels in a heterogeneous manner, and model organisms used to study these disorders appear to support that circadian dysfunction may be an inherent characteristic of neurodevelopmental disorders. Furthermore, the pre-clinical and clinical evidence indicates that circadian disruption at the environmental and genetic levels may contribute to the behavioural changes observed in these disorders. Finally, studies suggest that psychiatric medications, particularly those prescribed for attention-deficit/hyperactivity disorder and schizophrenia, can have direct effects on the circadian system and that chronotherapy may be leveraged to offset some of these side effects. This review highlights that circadian system dysfunction is likely a core pathological feature of neurodevelopmental disorders and that further research is required to elucidate this relationship.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".