Using Genetic Biomarkers to Predict Patient Response and Side-Effect Profiles for SSRIs and Antipsychotics: A Comprehensive Review
Fuente:
Zenodo
Guardado en:
| Autor principal: | |
|---|---|
| Formato: | Recurso digital |
| Publicado: |
Zenodo
2026
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866901986244296704 |
|---|---|
| author | Bijoy Ghosh*, Meckie Khaliz Chapola, Saurav Kumar |
| author_facet | Bijoy Ghosh*, Meckie Khaliz Chapola, Saurav Kumar |
| contents | <p><span lang="EN-US">Selective serotonin reuptake inhibitors (SSRIS) and antipsychotic drugs continue to form the basis of pharmacotherapy of major depressive disorder, anxiety disorders, and psychotic spectrum disorders. Significant interindividual differences in drug response and adverse drug reactions (ADRs), however, restrict their clinical importance and add to their treatment discontinuation rates, relapse, and psychiatric morbidity. Pharmacogenomics, the study of the effect that genetic variation has on drug response, provides a logical scientific model upon which individual responses to drugs and the selection and dosing of drugs can be predicted. The present review of the literature on the research question will analyse the existing evidence regarding genetic biomarkers of SSRI and antipsychotic response, meta-analyses, and randomized controlled trials, and recommend clinical strategies based on the global pharmacogenetics recommendations. Our targets include cytochrome P450 (CYP2D6, CYP2C19) polymorphisms, serotonergic (HTTLPR, BDNF), dopaminergic (DRD2, DRD3, COMT), immune-related (HLA variants), and multivariate biomarker. The material justifies the fact that, when combined with therapeutic drug monitoring and clinical decision support systems, pharmacogenetic testing can contribute to a considerably enhanced treatment outcome, decreased adverse effects, and a faster recovery of the patient. Although there is strong scientific evidence, clinical application is still limited, indicating that education and integration of testing in standard psychiatric practice as well as subsequent validation studies, are necessary.</span></p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18208788 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Using Genetic Biomarkers to Predict Patient Response and Side-Effect Profiles for SSRIs and Antipsychotics: A Comprehensive Review Bijoy Ghosh*, Meckie Khaliz Chapola, Saurav Kumar pharmacogenomics, pharmacogenetics, SSRIs, antipsychotics, adverse drug reactions, CYP450 enzymes. <p><span lang="EN-US">Selective serotonin reuptake inhibitors (SSRIS) and antipsychotic drugs continue to form the basis of pharmacotherapy of major depressive disorder, anxiety disorders, and psychotic spectrum disorders. Significant interindividual differences in drug response and adverse drug reactions (ADRs), however, restrict their clinical importance and add to their treatment discontinuation rates, relapse, and psychiatric morbidity. Pharmacogenomics, the study of the effect that genetic variation has on drug response, provides a logical scientific model upon which individual responses to drugs and the selection and dosing of drugs can be predicted. The present review of the literature on the research question will analyse the existing evidence regarding genetic biomarkers of SSRI and antipsychotic response, meta-analyses, and randomized controlled trials, and recommend clinical strategies based on the global pharmacogenetics recommendations. Our targets include cytochrome P450 (CYP2D6, CYP2C19) polymorphisms, serotonergic (HTTLPR, BDNF), dopaminergic (DRD2, DRD3, COMT), immune-related (HLA variants), and multivariate biomarker. The material justifies the fact that, when combined with therapeutic drug monitoring and clinical decision support systems, pharmacogenetic testing can contribute to a considerably enhanced treatment outcome, decreased adverse effects, and a faster recovery of the patient. Although there is strong scientific evidence, clinical application is still limited, indicating that education and integration of testing in standard psychiatric practice as well as subsequent validation studies, are necessary.</span></p> |
| title | Using Genetic Biomarkers to Predict Patient Response and Side-Effect Profiles for SSRIs and Antipsychotics: A Comprehensive Review |
| topic | pharmacogenomics, pharmacogenetics, SSRIs, antipsychotics, adverse drug reactions, CYP450 enzymes. |
| url | https://doi.org/10.5281/zenodo.18208788 |