Personalized medicine in major depressive disorder —Opportunities and pitfalls
Published Date:Sep 26 2012
Source:Metabolism. 62(0 1):S34-S39.
Cytochrome P-450 Enzyme System
Depressive Disorder, Major
Genome-Wide Association Study
Molecular Targeted Therapy
Nerve Growth Factors
Primary Health Care
Surveys And Questionnaires
United States Food And Drug Administration
Pubmed Central ID:PMC4672728
Funding:CC999999/Intramural CDC HHS/United States
Description:The sequencing of the human genome in the early days of this millennium was greeted with great fanfare as this accomplishment was expected to revolutionize medicine and result in individualized treatments based on the genetic make-up of the patient. The ultimate promise of personalized medicine would be fulfilled with the identification of disease biomarkers that would be widely available for use in diagnosis and treatment. Progress, however, has been slow in providing disease biomarkers or approved diagnostic tests. This is true for major depressive disorder (MDD), despite its prevalence in the general population and the widespread acceptance of its biological basis. Studies using strategies like genome-wide association and candidate gene analyses have identified a number of possible biomarkers of MDD, including serum levels of neurotrophic factors, inflammatory cytokines and HPA axis hormones, but none have proven sufficiently powerful for clinical use. The lack of biologically based tests available for use in identifying patients with MDD is a significant impediment to personalized and more effective treatment, because it means diagnosis continues to be driven by subjective symptoms. While genetic studies of MDD have not yet led to diagnostic and treatment biomarkers, progress in determining the role of the genome in drug metabolism heralds the first effort in personalized prescribing for the antidepressants. The FDA suggested and approved genotyping tests for common variants of drug metabolism genes, such as the cytochrome p450s. By using these tests a physician can select an appropriate antidepressant for a given patient, as differences in clearance, half-life, and peak blood concentrations are controlled by genetic variability in drug metabolism. Personalization in drug choice can be achieved because these tests: (1) identify responders and non-responders; (2) provide alerts to possible adverse drug events; and (3) help optimize dose. Improved ways of diagnosing and prescribing effective treatments for MDD are needed, as the available methods are inadequate and symptom based. In the foreseeable future, further interrogation of the genome may serve as the basis for development of new personalized medicine strategies for diagnosis and treatment of MDD.
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