Skip to content
DraconiticResearch
Search Sources API
197,693 studies31 sourcesUpdated 52 min ago
Peer-reviewedCC BYMedicina

Integrating Genetic Variants and Expression Profiles of Pharmacogenes to Investigate Resistance to Antidepressant Treatment

7 more authors

Abstract

Background and Objectives: Treatment-resistant depression (TRD) is a major clinical challenge in the management of major depressive disorder (MDD). While pharmacogenetics has been suggested to be clinically useful in guiding antidepressant treatment, few studies have explored if and how pharmacogenes can be involved in TRD pathophysiology and its clinical outcomes. Material amd Methods: We explored the role of differences in metabolizer phenotypes, gene expression levels, and microRNAs of three key pharmacogenes (CYP2D6, CYP2C19, CYP2B6) in TRD pathophysiology and antidepressant response in a cohort of 300 patients with MDD from the PROMPT consortium. Results: CYP2D6 phenotype distribution did not differ significantly between TRD and non-TRD groups, but mRNA expression was significantly upregulated in TRD. Hsa-miR-26b-5p, a microRNA predicted to regulate CYP2D6, was significantly downregulated in TRD. For CYP2C19, intermediate metabolizers (IMs) were underrepresented in TRD versus non-TRD (IMs vs. normal metabolizers (NMs): χ2 = 6.07, p = 0.019). microRNA hsa-let-7d-5p and hsa-miR-27a-3p, predicted to regulate CYP2C19, were significantly downregulated in TRD. No significant differences were found for CYP2B6. Conclusions: This study contributes valuable insights to the PROMPT project on how pharmacokinetic gene variants and their expression and regulatory mechanisms may influence antidepressant response and resistance in MDD.

Related

  1. An Immunocompetent Mouse Model of Degarelix Induced Chemical Castration to Investigate Acquired Resistance to Androgen Deprivation.
    A. Robotham, D. Costanzo-Garvey, G. Waldron +2
    bioRxivPreprintAll rights reservedFull textOncologybioRxiv
  2. Integrating multi-receptor and neuron–glia mechanisms of ketamine's antidepressant action: a convergence framework for understanding efficacy
    Zuzanna Sulej, Magdalena Zielińska
    Frontiers in Molecular NeurosciencePeer-reviewedCC BY 4.0Full textPharmacology & toxicologyPMC
  3. A bioinformatic approach to investigate placental and fetal gene expression during diabetic stress in pregnancy.
    Emily Larson, Aman Ullah
    In silico pharmacologyPeer-reviewedCC BYFull textObstetrics, gynaecology & paediatricsEurope PMC
  4. The antidepressant-like effect of adenosine A1 receptor over-expression in forebrain neurons does not involve an altered adenosine-mediated control of excitatory synaptic transmission
    Angelo Tomé, Joana Real, Daniel Rial +9
    NeuropharmacologyPeer-reviewedCC BYPhysiologyHAL
  5. Effects of sex, treatment resistance, and antidepressant treatment on monoamine oxidase B total distribution volume
    E. J. Kuik, C. Baena-Tan, S. Moriguchi +10
    medRxivPreprintCC BYFull textPsychiatry & mental healthmedRxiv
BibTeX
@article{pisanu2026integrating,
  title = {{Integrating Genetic Variants and Expression Profiles of Pharmacogenes to Investigate Resistance to Antidepressant Treatment}},
  author = {Claudia Pisanu and Alessio Squassina and Júlia Perera-Bel and Rosana Carvalho Silva and Lisa Buson and Anna Martinez Sires and Marco Bortolomasi and Valentina Menesello and Giulia Perusi and Bernardo Carpiniello and Ewa Ferensztajn-Rochowiak and Filip Rybakowski and Ferran Sanz and Mirko Manchia and Marie Claude Potier and Mara Dierssen and Bernhard Baune and Massimo Gennarelli and Alessandra Minelli},
  journal = {Medicina},
  year = {2026},
  month = may,
  doi = {10.3390/medicina62050965},
  url = {https://hal.science/hal-05844261v1},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - Integrating Genetic Variants and Expression Profiles of Pharmacogenes to Investigate Resistance to Antidepressant Treatment
AU  - Claudia Pisanu
AU  - Alessio Squassina
AU  - Júlia Perera-Bel
AU  - Rosana Carvalho Silva
AU  - Lisa Buson
AU  - Anna Martinez Sires
AU  - Marco Bortolomasi
AU  - Valentina Menesello
AU  - Giulia Perusi
AU  - Bernardo Carpiniello
AU  - Ewa Ferensztajn-Rochowiak
AU  - Filip Rybakowski
AU  - Ferran Sanz
AU  - Mirko Manchia
AU  - Marie Claude Potier
AU  - Mara Dierssen
AU  - Bernhard Baune
AU  - Massimo Gennarelli
AU  - Alessandra Minelli
PY  - 2026
DA  - 2026/05/15
JO  - Medicina
DO  - 10.3390/medicina62050965
UR  - https://hal.science/hal-05844261v1
AB  - Background and Objectives: Treatment-resistant depression (TRD) is a major clinical challenge in the management of major depressive disorder (MDD). While pharmacogenetics has been suggested to be clinically useful in guiding antidepressant treatment, few studies have explored if and how pharmacogenes can be involved in TRD pathophysiology and its clinical outcomes. Material amd Methods: We explored the role of differences in metabolizer phenotypes, gene expression levels, and microRNAs of three key pharmacogenes (CYP2D6, CYP2C19, CYP2B6) in TRD pathophysiology and antidepressant response in a cohort of 300 patients with MDD from the PROMPT consortium. Results: CYP2D6 phenotype distribution did not differ significantly between TRD and non-TRD groups, but mRNA expression was significantly upregulated in TRD. Hsa-miR-26b-5p, a microRNA predicted to regulate CYP2D6, was significantly downregulated in TRD. For CYP2C19, intermediate metabolizers (IMs) were underrepresented in TRD versus non-TRD (IMs vs. normal metabolizers (NMs): χ2 = 6.07, p = 0.019). microRNA hsa-let-7d-5p and hsa-miR-27a-3p, predicted to regulate CYP2C19, were significantly downregulated in TRD. No significant differences were found for CYP2B6. Conclusions: This study contributes valuable insights to the PROMPT project on how pharmacokinetic gene variants and their expression and regulatory mechanisms may influence antidepressant response and resistance in MDD.
SN  - 1010-660X
SN  - 1648-9144
ER  -