ReviewHandbook of experimental pharmacology2022
The Role of Dynorphin and the Kappa Opioid Receptor in Schizophrenia and Major Depressive Disorder: A Translational Approach.
Review in Handbook of experimental pharmacology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 8 citations in OpenAlex.
- [Psychotropic drug research in Germany: challenges of early benefit assessment and precision psychiatry].Der Nervenarzt · 2026Review
- Can Buprenorphine Be Overdosed? The Ceiling Effect and Its Clinical Implications.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Review
- Exploring the Frontier of Cyclic Dipeptides: A Bioinformatics Approach to Potential Therapeutic Applications in Schizophrenia.International journal of molecular sciences · 2024Review
- Design of κ-Opioid Receptor Agonists for the Development of Potential Treatments of Pain with Reduced Side Effects.Molecules (Basel, Switzerland) · 2023Review
- Structural and Functional Diversity of Animal Toxins Interacting With GPCRs.Frontiers in molecular biosciences · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The kappa opioid receptor (KOR) and its endogenous ligands dynorphins (DYN) have been implicated in the development or symptomatology of a variety of neuropsychiatric disorders. This review covers a brief history of the development of KOR agonists and antagonists, their effects in healthy volunteers, and the potential role of DYN/KOR dysfunction in schizophrenia and major depressive disorder from a translational perspective. The potential role of DYN/KOR dysfunction in schizophrenia is based on several lines of evidence. Selective KOR agonists induce affective states in healthy volunteers with similarities to the symptoms of schizophrenia. Studies have shown increased DYN in patients with schizophrenia, although the data have been mixed. Finally, meta-analytic data have shown that opioid antagonists are associated with reductions in the symptoms of schizophrenia. The potential role of DYN/KOR dysfunction in major depressive disorder is also based on a combination of preclinical and clinical data. Selective KOR agonists have shown pro-depressive effects in human volunteers, while selective KOR antagonists have shown robust efficacy in several preclinical models of antidepressant activity. Small studies have shown that nonselective KOR antagonists may have efficacy in treatment-resistant depression. Additionally, recent clinical data have shown that the KOR may be an effective target for treating anhedonia, a finding relevant to both schizophrenia and depression. Finally, recommendations are provided for translating preclinical models for schizophrenia and major depressive disorder into the clinic.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.