Accuracy in recognising happy facial expressions is associated with antidepressant response to a NOP receptor antagonist but not placebo treatment.


Journal

Journal of psychopharmacology (Oxford, England)
ISSN: 1461-7285
Titre abrégé: J Psychopharmacol
Pays: United States
ID NLM: 8907828

Informations de publication

Date de publication:
12 2021
Historique:
pubmed: 6 10 2021
medline: 22 2 2022
entrez: 5 10 2021
Statut: ppublish

Résumé

Clinical trials with putative antidepressants can be difficult to execute as it can take up to 8 weeks before differences emerge between drug and placebo, and long expensive trials often fail. Implementation of early response biomarkers could aid this process significantly with potential to identify new treatments. In a secondary analysis, we examined the association of early effects on emotional processing with later clinical outcome following treatment with the novel NOP antagonist LY2940094 versus placebo. We hypothesised that early induction of positive bias would be associated with reduced severity of depression after 8 weeks of treatment. This was a multicentre, randomised, double-blind, parallel-group, fixed-dose, placebo-controlled, 8 week study to assess sensitivity of the facial emotional recognition task (FERT) to early changes in emotional bias induced by LY2940094. Patients who met diagnostic criteria for major depression were randomised to receive LY2940094 ( Patients identified happy faces with higher accuracy (Wald χ These data suggest that emotional processing biomarkers may be sensitive to early effects of antidepressant treatment indicative of later clinical response. Further studies in this area may be useful in developing new treatments and clinical trial designs for predicting antidepressant response.

Sections du résumé

BACKGROUND
Clinical trials with putative antidepressants can be difficult to execute as it can take up to 8 weeks before differences emerge between drug and placebo, and long expensive trials often fail. Implementation of early response biomarkers could aid this process significantly with potential to identify new treatments.
AIMS
In a secondary analysis, we examined the association of early effects on emotional processing with later clinical outcome following treatment with the novel NOP antagonist LY2940094 versus placebo. We hypothesised that early induction of positive bias would be associated with reduced severity of depression after 8 weeks of treatment.
METHODS
This was a multicentre, randomised, double-blind, parallel-group, fixed-dose, placebo-controlled, 8 week study to assess sensitivity of the facial emotional recognition task (FERT) to early changes in emotional bias induced by LY2940094. Patients who met diagnostic criteria for major depression were randomised to receive LY2940094 (
RESULTS
Patients identified happy faces with higher accuracy (Wald χ
CONCLUSION
These data suggest that emotional processing biomarkers may be sensitive to early effects of antidepressant treatment indicative of later clinical response. Further studies in this area may be useful in developing new treatments and clinical trial designs for predicting antidepressant response.

Identifiants

pubmed: 34608842
doi: 10.1177/02698811211044684
doi:

Substances chimiques

Biomarkers 0
LY2940094 0
Narcotic Antagonists 0
Pyrans 0
Receptors, Opioid 0
Spiro Compounds 0
Nociceptin Receptor 0
OPRL1 protein, human 0

Types de publication

Journal Article Multicenter Study Randomized Controlled Trial Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1473-1478

Auteurs

Gerard R Dawson (GR)

P1vital Limited, Wallingford, Oxfordshire, UK.

Anke Post (A)

FeetMe SAS, Paris, France.

Trevor S Smart (TS)

UCB, Slough, UK.

Michael Browning (M)

University Department of Psychiatry, Warneford Hospital, Oxford, UK.
Oxford Health NHS Foundation Trust, Warneford Hospital, Oxford, UK.

Catherine J Harmer (CJ)

University Department of Psychiatry, Warneford Hospital, Oxford, UK.
Oxford Health NHS Foundation Trust, Warneford Hospital, Oxford, UK.

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Classifications MeSH