MétaCan
Menu
Back to cohort

A Dual Noradrenergic Mechanism for the Relief of Neuropathic Allodynia by the Antidepressant Drugs Duloxetine and Amitriptyline

2018· article· en· W2894405759 on OpenAlexafffund
Mélanie Kremer, İpek Yalçın, Yannick Goumon, Xavier Wurtz, Laurent Nexon, Dorothée Daniel, Salim Megat, Rhian Alice Ceredig, Carl Ernst, Gustavo Turecki, Virginie Chavant, Jean‐François Théroux, Adrien Lacaud, Lauriane-Elisabeth Joganah, Vincent Lelièvre, Dominique Massotte, Pierre-Éric Lutz, Ralf Gilsbach, Éric Salvat, Michel Barrot

Bibliographic record

VenueJournal of Neuroscience · 2018
Typearticle
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsMcGill UniversityDouglas Mental Health University Institute
FundersFondation Pierre Deniker pour la Recherche et la Prévention en Santé MentaleCentre National de la Recherche ScientifiqueAgence Nationale de la RechercheMcGill University
KeywordsDuloxetineNeuropathic painAntidepressantAllodyniaMedicineAmitriptylinePharmacologyOpioidNeuroscienceAnesthesiaHyperalgesiaNociceptionReceptorInternal medicinePsychologyHippocampus

Abstract

fetched live from OpenAlex

In addition to treating depression, antidepressant drugs are also a first-line treatment for neuropathic pain, which is pain secondary to lesion or pathology of the nervous system. Despite the widespread use of these drugs, the mechanism underlying their therapeutic action in this pain context remains partly elusive. The present study combined data collected in male and female mice from a model of neuropathic pain and data from the clinical setting to understand how antidepressant drugs act. We show two distinct mechanisms by which the selective inhibitor of serotonin and noradrenaline reuptake duloxetine and the tricyclic antidepressant amitriptyline relieve neuropathic allodynia. One of these mechanisms is acute, central, and requires descending noradrenergic inhibitory controls and α2Aadrenoceptors, as well as the mu and delta opioid receptors. The second mechanism is delayed, peripheral, and requires noradrenaline from peripheral sympathetic endings and β2adrenoceptors, as well as the delta opioid receptors. We then conducted a transcriptomic analysis in dorsal root ganglia, which suggested that the peripheral component of duloxetine action involves the inhibition of neuroimmune mechanisms accompanying nerve injury, including the downregulation of the TNF-α–NF-κB signaling pathway. Accordingly, immunotherapies against either TNF-α or Toll-like receptor 2 (TLR2) provided allodynia relief. We also compared duloxetine plasma levels in the animal model and in patients and we observed that patients' drug concentrations were compatible with those measured in animals under chronic treatment involving the peripheral mechanism. Our study highlights a peripheral neuroimmune component of antidepressant drugs that is relevant to their delayed therapeutic action against neuropathic pain. SIGNIFICANCE STATEMENTIn addition to treating depression, antidepressant drugs are also a first-line treatment for neuropathic pain, which is pain secondary to lesion or pathology of the nervous system. However, the mechanism by which antidepressant drugs can relieve neuropathic pain remained in part elusive. Indeed, preclinical studies led to contradictions concerning the anatomical and molecular substrates of this action. In the present work, we overcame these apparent contradictions by highlighting the existence of two independent mechanisms. One is rapid and centrally mediated by descending controls from the brain to the spinal cord and the other is delayed, peripheral, and relies on the anti-neuroimmune action of chronic antidepressant treatment.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.019
GPT teacher head0.276
Teacher spread0.257 · 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 designBench or experimental
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

Citations99
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueJournal of NeuroscienceSame topicPain Mechanisms and TreatmentsFrench-language works237,207