Pharmacogenomic Characterization in Bipolar Spectrum Disorders.
Stefano FortinguerraVincenzo SorrentiPietro GiustiMorena ZussoAlessandro BurianiPublished in: Pharmaceutics (2019)
The holistic approach of personalized medicine, merging clinical and molecular characteristics to tailor the diagnostic and therapeutic path to each individual, is steadily spreading in clinical practice. Psychiatric disorders represent one of the most difficult diagnostic challenges, given their frequent mixed nature and intrinsic variability, as in bipolar disorders and depression. Patients misdiagnosed as depressed are often initially prescribed serotonergic antidepressants, a treatment that can exacerbate a previously unrecognized bipolar condition. Thanks to the use of the patient's genomic profile, it is possible to recognize such risk and at the same time characterize specific genetic assets specifically associated with bipolar spectrum disorder, as well as with the individual response to the various therapeutic options. This provides the basis for molecular diagnosis and the definition of pharmacogenomic profiles, thus guiding therapeutic choices and allowing a safer and more effective use of psychotropic drugs. Here, we report the pharmacogenomics state of the art in bipolar disorders and suggest an algorithm for therapeutic regimen choice.
Keyphrases
- bipolar disorder
- major depressive disorder
- clinical practice
- end stage renal disease
- spectrum disorder
- clinical decision support
- chronic kidney disease
- ejection fraction
- machine learning
- depressive symptoms
- single molecule
- genome wide
- emergency department
- deep learning
- prognostic factors
- dna methylation
- combination therapy
- sleep quality
- neural network