Prof. Chiara Fabbri
Università di Bologna, Itàlia & King’s College London, Regne Unit
Ponència | Fins on arriba la farmacogenètica? |
Data | Divendres, 21 d'abril, 2023 |
Hora | 18:05 - 18:50 |
Taula rodona 4 | Precisió en la teràpia farmacològica |
BIOGRAFIA
Chiara Fabbri, M.D Ph.D., is a psychiatrist and researcher working on the genetic factors involved in psychotropic drug response and in the heterogeneity of depression. She works as lecturer at the University of Bologna, Italy, and she is a visiting researcher at King’s College London, where she previously was a Marie Skłodowska-Curie fellow. She obtained a Ph.D. in psychiatric pharmacogenetics at the University of Maastricht, The Netherlands.
Dr Fabbri contributed to the identification of the genetic predictors of treatment-resistant depression (TRD) and to the genetic characterization of depression subtypes. Recently, she explored the use of genetic predictors of TRD for drug repositioning, and the use of electronic health records of primary care to identify individuals with TRD, leading to a relevant increase in sample size for pharmacogenetic studies. Currently, she is involved in several international projects that aim to identify biomarkers to stratify patients with psychiatric disorders and to provide personalised health care.
She is author or co-author of over 100 peer-reviewed articles in international journals, 11 book chapters, 20 oral presentations at international conferences and over 70 congress abstracts (H index 30).
https://publons.com/researcher/1239956/chiara-fabbri/
Dr Fabbri contributed to the identification of the genetic predictors of treatment-resistant depression (TRD) and to the genetic characterization of depression subtypes. Recently, she explored the use of genetic predictors of TRD for drug repositioning, and the use of electronic health records of primary care to identify individuals with TRD, leading to a relevant increase in sample size for pharmacogenetic studies. Currently, she is involved in several international projects that aim to identify biomarkers to stratify patients with psychiatric disorders and to provide personalised health care.
She is author or co-author of over 100 peer-reviewed articles in international journals, 11 book chapters, 20 oral presentations at international conferences and over 70 congress abstracts (H index 30).
https://publons.com/researcher/1239956/chiara-fabbri/
RESUM
The inclusion of genetic variants in the decision process leading to medication prescription has been long discussed in psychiatry. On one hand, the obvious importance of tailoring prescription on individual and objective characteristics, on the other hand the difficulties in identifying valid and reproducible genetic predictors for a complex phenotype such as treatment effects.
After decades of research, for many psychotropic drugs genetic variants have been included in prescription guidelines, such as those curated by the Clinical Pharmacogenetics Implementation Consortium, and they are often mentioned in the Summary of Product Characteristics. The genetic variants with recommendations are mostly in genes coding for cytochrome P450 enzymes, isoforms 2C19 and 2D6. The considered polymorphisms can alter the functionality of the coded enzyme, and affect drug metabolism, with an impact on response and risk of side effects, as demonstrated by multiple studies and meta-analyses.
However, genotyping is still very rarely used in clinical practice, due to financial and organisational challenges, despite promising cost-effectiveness estimates were provided. Some key points for clinical implementation include the creation of standardised decision support systems, linkage of genotyping results with electronic medical records, training/collaboration of different professionals. Importantly, there is still not a consensus about the group(s) of patients to whom genotyping should be offered, but the current evidence and different possibilities will be discussed.
Recent studies explored the use of genome-wide genotyping to predict treatment outcomes of psychotropic drugs, as well as for guiding drug development/repurposing. These studies confirmed the heritable component of treatment response/resistance, and they found interesting genetic overlap between these phenotypes and other psychiatric conditions, such as schizophrenia and attention-deficit hyperactivity disorder. Despite this is still research in progress, polygenic predictors are promising, as they capture genetic variation across the whole genome rather than a few genes only, and they can guide the identification of etiopathogenetic mechanisms. They can also be tested in complex models, using non-linear approaches such as machine learning, alone or combined with clinical variables.
Other recent research aims to improve predictive power by increasing sample homogeneity rather than sample size or by technological improvements. From the perspective of precision psychiatry, we should not consider patients as members of a group with the same categorical diagnosis but aim to identify their combination of different individual characteristics. As part of this approach, the genetic markers associated with specific symptom dimensions have been studied, with possible implications for treatment personalisation.
Finally, the limitations of previous studies, ongoing projects and future perspectives will be discussed.
After decades of research, for many psychotropic drugs genetic variants have been included in prescription guidelines, such as those curated by the Clinical Pharmacogenetics Implementation Consortium, and they are often mentioned in the Summary of Product Characteristics. The genetic variants with recommendations are mostly in genes coding for cytochrome P450 enzymes, isoforms 2C19 and 2D6. The considered polymorphisms can alter the functionality of the coded enzyme, and affect drug metabolism, with an impact on response and risk of side effects, as demonstrated by multiple studies and meta-analyses.
However, genotyping is still very rarely used in clinical practice, due to financial and organisational challenges, despite promising cost-effectiveness estimates were provided. Some key points for clinical implementation include the creation of standardised decision support systems, linkage of genotyping results with electronic medical records, training/collaboration of different professionals. Importantly, there is still not a consensus about the group(s) of patients to whom genotyping should be offered, but the current evidence and different possibilities will be discussed.
Recent studies explored the use of genome-wide genotyping to predict treatment outcomes of psychotropic drugs, as well as for guiding drug development/repurposing. These studies confirmed the heritable component of treatment response/resistance, and they found interesting genetic overlap between these phenotypes and other psychiatric conditions, such as schizophrenia and attention-deficit hyperactivity disorder. Despite this is still research in progress, polygenic predictors are promising, as they capture genetic variation across the whole genome rather than a few genes only, and they can guide the identification of etiopathogenetic mechanisms. They can also be tested in complex models, using non-linear approaches such as machine learning, alone or combined with clinical variables.
Other recent research aims to improve predictive power by increasing sample homogeneity rather than sample size or by technological improvements. From the perspective of precision psychiatry, we should not consider patients as members of a group with the same categorical diagnosis but aim to identify their combination of different individual characteristics. As part of this approach, the genetic markers associated with specific symptom dimensions have been studied, with possible implications for treatment personalisation.
Finally, the limitations of previous studies, ongoing projects and future perspectives will be discussed.
REFERÈNCIES
[Full paper] Zanardi R, Manfredi E, Montrasio C, Colombo C, Serretti A, Fabbri C. (2021). Pharmacogenetic-Guided Treatment of Depression: Real-World Clinical Applications, Challenges, and Perspectives. Clin Pharmacol Ther. 2021;110(3):573-581. doi: 10.1002/cpt.2315. PMID: 34047355.
[Full paper] Fabbri C, et al. (2018). Effect of cytochrome CYP2C19 metabolizing activity on antidepressant response and side effects: Meta-analysis of data from genome-wide association studies. Eur Neuropsychopharmacol. 2018;28(8):945-954. doi: 10.1016/j.euroneuro.2018.05.009. Epub 2018 Jun 28. PMID: 30135031.
[Full paper] Fabbri C, et al. (2021). Genetic and clinical characteristics of treatment-resistant depression using primary care records in two UK cohorts. Mol Psychiatry. 2021;26(7):3363-3373. doi: 10.1038/s41380-021-01062-9. PMID: 33753889; PMCID: PMC8505242.
[Full paper] Fabbri C, Pain O, Hagenaars SP, Lewis CM, Serretti A. (2021). Transcriptome-wide association study of treatment-resistant depression and depression subtypes for drug repurposing. Neuropsychopharmacology. 2021;46(10):1821-1829. doi: 10.1038/s41386-021-01059-6. PMID: 34158615; PMCID: PMC8357803.
[Full paper] Fabbri C, et al. (2018). Effect of cytochrome CYP2C19 metabolizing activity on antidepressant response and side effects: Meta-analysis of data from genome-wide association studies. Eur Neuropsychopharmacol. 2018;28(8):945-954. doi: 10.1016/j.euroneuro.2018.05.009. Epub 2018 Jun 28. PMID: 30135031.
[Full paper] Fabbri C, et al. (2021). Genetic and clinical characteristics of treatment-resistant depression using primary care records in two UK cohorts. Mol Psychiatry. 2021;26(7):3363-3373. doi: 10.1038/s41380-021-01062-9. PMID: 33753889; PMCID: PMC8505242.
[Full paper] Fabbri C, Pain O, Hagenaars SP, Lewis CM, Serretti A. (2021). Transcriptome-wide association study of treatment-resistant depression and depression subtypes for drug repurposing. Neuropsychopharmacology. 2021;46(10):1821-1829. doi: 10.1038/s41386-021-01059-6. PMID: 34158615; PMCID: PMC8357803.