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Enregistrement W4407418509 · doi:10.1093/ijnp/pyae059.183

PHARMACOGENETIC TESTING IN TREATMENT-RESISTANT PANIC DISORDER: A PILOT STUDY

2025· article· en· W4407418509 sur OpenAlexaff
Rafael C. Freire, Marcos Fidry, Morena Mourao Zugliani, Mariana Costa do Cabo, Clara V. Faria, Antônio Egídio Nardi

Notice bibliographique

RevueThe International Journal of Neuropsychopharmacology · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueHormonal Regulation and Hypertension
Établissements canadiensKingston Health Sciences CentreKingston General HospitalQueen's University
Organismes subventionnairesnon disponible
Mots-clésPanic disorderPharmacogeneticsPanicPsychologyClinical psychologyMedicinePsychiatryGenotypeAnxietyGeneticsBiologyGene

Résumé

récupéré en direct d'OpenAlex

Abstract Background Pharmacological treatment is considered effective in the treatment of panic disorder (PD). However, about 20 to 40% of PD patients do not respond to the first pharmacological treatment. Trials with multiple drugs are often required before response to treatment is achieved. Pharmacogenetic testing is a promising new tool to aid clinicians in finding the right medication and the right dose for each patient. It could be especially useful in the treatment of treatment-resistant patients with PD. Aims and Objectives Ascertain the usefulness of pharmacogenetic testing in treatment-resistant PD. Methods 20 PD patients who did not respond to treatment-as-usual (TAU) were included in this study. Only patients who were on medications with known efficacy for PD, on adequate dose, and received treatment for at least 8 weeks were considered eligible. Patients with Clinical Global Impression – Improvement (CGI-I) of 1 (very much improved) or 2 (much improved) were considered responders, patients with scores higher than 2 were considered non-responders. The key enzymes’ genetic polymorphisms evaluated were: CYP2D6, CYP2C19, CYP2C9, CYP1A2, CYP3A4, CYP3A5, CYP2B6, FKBP5, HTR2A, ANKK1, HTR1A, HTR2C, DRD2, GRIK4, ADRA2A, OPRM1, COMT, SLC6A4 e ABCB1, FKBS, GSK3B, EPHX1, UGT1A4, UGT2B15, MC4R, SCN1A, SLC6A4, MTHFR (rs1801131 e rs1811133). We retrospectively compared the recommendations of the pharmacogenetic analysis with the treatment the patient actually received. Results The recommendation from the pharmacogenetic analysis regarding the actual prescribed drug was “use according to the label” in 40% of the cases, “use with attention” in 55% of the cases and “use with caution and attention” in 5% of the cases. Pharmacogenetic testing indicated reduced chance of response to the prescribed drug in 30% of the subjects, while they indicated very low serum levels of the prescribed drug (fast metabolism) in 20% of the subjects. The CYP3A4 and CYP2D6 activity was normal for most patients. CYP2C19 phenotype indicated slower enzyme activity in 25%, faster enzyme activity in 40%, and normal enzyme activity in 35% of patients. The pharmacogenetic tests predicted a small reduction of methylenetetrahydrofolate reductase (MTHFR) enzyme activity in 75% of the patients. Discussion and Conclusion If the pharmacogenetic was made before the treatment, if would have interfered on the medication choice and changed treatment outcome only in 5% of the subjects. Since the polymorphism associated with low MTHFR activity was very prevalent, this finding raises the question of a possible association between this polymorphism and treatment resistance in PD. Low MTHFR activity was associated with treatment resistance in mood disorders. Administering L-methylfolate would bypass the enzyme and correct the vitamin deficiency in the intracellular level, making these patients treatment responsive. Given the findings from the current study, pharmacogenetic tests would not have aided clinicians in finding the right pharmacological treatments for each patient. High prevalence of CYP2C19 and MTHFR polymorphisms in PD patients requires further study. References Baldwin, D.S., Anderson, I.M., Nutt, D.J., Allgulander, C., Bandelow, B., Den Boer, J.A., Christmas, D.M., Davies, S., Fineberg, N., Lidbetter, N., Malizia, A., McCrone, P., Nabarro, D., O’ Neill, C., Scott, J., Van Der Wee, N., Wittchen, H.U., 2014. Evidence-based pharmacological treatment of anxiety disorders, post- traumatic stress disorder and obsessive-compulsive disorder: A revision of the 2005 guidelines from the British Association for Psychopharmacology. J. Psychopharmacol. 28, 403–439. https://doi.org/10.1177/0269881114525674 Bjelland, I., Tell, G.S., Vollset, S.E., Refsum, H., Ueland, P.M., 2003. Folate, vitamin B12, homocysteine, and the MTHFR 677C→ T polymorphism in anxiety and depression. The Hordaland Homocysteine Study. Arch. Gen. Psychiatry. https://doi.org/10.1001/archpsyc.60.6.618 Blaya, C., Salum, G.A., Lima, M.S., Leistner-Segal, S., Manfro, G.G., 2007. Lack of association between the Serotonin Transporter Promoter Polymorphism (5-HTTLPR) and Panic Disorder: a systematic review and meta-analysis. Behav Brain Funct 3, 41. https://doi.org/1744-9081-3-41 [pii]\n10.1186/1744-9081-3- 41 Caldirola, D., Perna, G., 2015. Is there a role for pharmacogenetics in the treatment of panic disorder? Pharmacogenomics. https://doi.org/10.2217/pgs.15.66 Freire, R.C., Hallak, J.E., Crippa, J.A., Nardi, A.E., 2011. New treatment options for panic disorder: clinical trials from 2000 to 2010. Expert Opin. Pharmacother. https://doi.org/10.1517/14656566.2011.562200 Froese, D.S., Huemer, M., Suormala, T., Burda, P., Coelho, D., Gué ant, J.L., Landolt, M.A., Kož ich, V., Fowler, B., Baumgartner, M.R., 2016. Mutation Update and Review of Severe Methylenetetrahydrofolate Reductase Deficiency. Hum. Mutat. https://doi.org/10.1002/humu.22970 He, Q., Mei, Y., Liu, Y., Yuan, Z., Zhang, J., Yan, H., Shen, L., Zhang, Y., 2019. Effects of Cytochrome P450 2C19 Genetic Polymorphisms on Responses to Escitalopram and Levels of Brain-Derived Neurotrophic Factor in Patients with Panic Disorder. J. Clin. Psychopharmacol. https://doi.org/10.1097/JCP.0000000000001014

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,004
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Essai non randomisé · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,002
Score d'incertitude au seuil0,013

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,004
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,000
Études des sciences et des technologies0,0010,001
Communication savante0,0000,000
Science ouverte0,0000,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,059
Tête enseignante GPT0,379
Écart entre enseignants0,320 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeEssai non randomisé
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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