Evidence map›Paper›PMID 20406250›Full record

ReviewCNS neuroscience & therapeutics2010

Relevance of norepinephrine-dopamine interactions in the treatment of major depressive disorder.

Mostafa El Mansari, Bruno P Guiard, Olga Chernoloz, Ramez Ghanbari, Noam Katz, Pierre Blier

Abstract readReview
In one paragraph

Review in CNS neuroscience & therapeutics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers.

0numbers the graph read from it
0cells of the map it votes in
59citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

59 citing papers in PubMed.

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  11. The Formation and Function of the VTA Dopamine System.International journal of molecular sciences · 2024
    Review
  12. Article
  13. Frontiers in pharmacology · 2024
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Mostafa El MansariUniversity of Ottawa Institute of Mental Health Research, Ontario, Canada. mostafa.elmansari@rohcg.on.ca <mostafa.elmansari@rohcg.on.ca>
Bruno P Guiard
Olga Chernoloz
Ramez Ghanbari
Noam Katz
Pierre Blier

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Central dopaminergic and noradrenergic systems play essential roles in controlling several forebrain functions. Consequently, perturbations of these neurotransmissions may contribute to the pathophysiology of neuropsychiatric disorders. For many years, there was a focus on the serotonin (5-HT) system because of the efficacy of selective serotonin reuptake inhibitors (SSRIs), the most prescribed antidepressants in the treatment of major depressive disorder (MDD). Given the interconnectivity within the monoaminergic network, any action on one system may reverberate in the other systems. Analysis of this network and its dysfunctions suggests that drugs with selective or multiple modes of action on dopamine (DA) and norepinephrine (NE) may have robust therapeutic effects. This review focuses on NE-DA interactions as demonstrated in electrophysiological and neurochemical studies, as well as on the mechanisms of action of agents with either selective or dual actions on DA and NE. Understanding the mode of action of drugs targeting these catecholaminergic neurotransmitters can improve their utilization in monotherapy and in combination with other compounds particularly the SSRIs. The elucidation of such relationships can help design new treatment strategies for MDD, especially treatment-resistant depression.

Indexed as

AnimalsAntidepressive AgentsCentral Nervous SystemDopamineHumansMajor Depressive DisorderModels, BiologicalNeuronsNorepinephrineAntidepressive AgentsDopamineNorepinephrine

Identifiers

PMID20406250
PMCPMC2904493

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.