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Record W4306156305

A pilot study of serotonin-1A receptor genotypes and rapid eye movement sleep sensitivity to serotonergic/cholinergic imbalance in humans: a pharmacological model of depression

2015· article· en· W4306156305 on OpenAlexaboutno aff
K Biard, Douglass AB, R Robillard, De Koninck J

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2015
Typearticle
Languageen
FieldNeuroscience
TopicSleep and Wakefulness Research
Canadian institutionsnot available
Fundersnot available
KeywordsSerotonergicCholinergicSerotoninSleep (system call)Depression (economics)Rapid eye movement sleepNeuroscienceEye movementPsychologyMedicineReceptorInternal medicineComputer science
DOInot available

Abstract

fetched live from OpenAlex

Kathleen Biard,1,2 Alan B Douglass,2,3 Rébecca Robillard,2 Joseph De Koninck1,2 1School of Psychology, University of Ottawa, 2University of Ottawa Institute for Mental Health Research, 3Royal Ottawa Mental Health Center, University of Ottawa Institute for Mental Health Research, Ottawa, ON, Canada Rationale: The serotonergic and cholinergic systems are jointly involved in regulating sleep but this system is theorized to be disturbed in depressed individuals. We previously reported that cholinergic and serotonergic agents induce sleep changes partially consistent with monoamine models of sleep disturbances in depression. One potential cause of disturbed neurotransmission is genetic predisposition. The G(-1019) allele of the serotonin-1A (5-HT1A) receptor promoter region predicts an increased risk for depression compared to the wild-type C(-1019) allele. Objective: The goal of this study was to investigate how serotonin-1A receptor genotypes mediate sleep sensitivity to pharmacological probes modeling the serotonergic/cholinergic imbalance of depression. Methods: Seventeen healthy female participants homozygous for either C (n=11) or G (n=6) alleles aged 18–27 years were tested on four nonconsecutive nights. Participants were given galantamine (an anti-acetylcholinesterase), buspirone (a serotonergic agonist), both drugs together, or placebos before sleeping. Results: As reported previously, buspirone significantly increased rapid eye movement (REM) latency (P<0.001), as well as awakenings, percentage of time spent awake, and percentage of time asleep spent in stage N1 (P<0.019). Galantamine increased awakenings, percentage of time spent awake, percentage of time asleep spent in stage N1, and percentage of time asleep spent in REM, and decreased REM latency and percentage of time asleep spent in stage N3 (P<0.019). Galantamine plus buspirone given together disrupted sleep more than either drug alone, lowering sleep efficiency and percentage of time asleep spent in stage N3 and increasing awakenings, percentage of time spent awake, and percentage of time asleep spent in stage N1 (P<0.019). There was no main effect of genotype nor was there a significant multivariate interaction between genotype and drug condition. Conclusion: These findings are partially consistent with the literature about sleep in depression, notably short REM latency, higher percentage of total sleep time spent in REM, lower percentage of time asleep spent in stage N3, and increased sleep fragmentation. The C/G mutation in the serotonin-1A receptor promoter region does not appear to cause noticeable differences in the sleep patterns of a relatively small sample of healthy young females. Future studies with larger sample sizes are required. Keywords: depression, sleep, serotonin, acetylcholine, buspirone, galantamine

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.423
GPT teacher head0.558
Teacher spread0.135 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2015
Admission routes1
Has abstractyes

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