Back to Search
Start Over
Precision medicine in mood disorders
- Source :
- PCN Reports, Vol 1, Iss 1, Pp n/a-n/a (2022)
- Publication Year :
- 2022
- Publisher :
- Wiley, 2022.
-
Abstract
- Abstract The choice of the most appropriate psychoactive medication for each of our patients is always a challenge. We can use more than 100 psychoactive drugs in the treatment of mood disorders, which can be prescribed either alone or in combination. Response and tolerability problems are common, and much trial and error is often needed before achieving a satisfactory outcome. Precision medicine is therefore needed for tailoring treatment to optimize outcome. Pharmacological, clinical, and demographic factors are important and informative, but biological factors may further inform and refine prediction. Twenty years after the first reports of gene variants modulating antidepressant response, we are now confronted with the prospect of routine clinical pharmacogenetic applications in the treatment of depression. The scientific community is divided into two camps: those who are enthusiastic and those who are skeptical. Although it appears clear that the benefit of existing tools is still not completely defined, at least in the case of central nervous system gene variants, this is not the case for metabolic gene variants, which is generally accepted. Cumulative scores encompassing many variants across the entire genome will soon predict psychiatric disorder liability and outcome. At present, precision medicine in mood disorders may be implemented using clinical and pharmacokinetic factors. In the near future, a genome‐wide composite genetic score in conjunction with clinical factors within each patient is the most promising approach for developing a more effective way to target treatment for patients suffering from mood disorders.
Details
- Language :
- English
- ISSN :
- 27692558
- Volume :
- 1
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- PCN Reports
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.1d8d369eb0432880fedebc6076cdca
- Document Type :
- article
- Full Text :
- https://doi.org/10.1002/pcn5.1