Twin and adoption studies have consistently demonstrated significant genetic contribution to psychiatric disorders ranging from roughly 30% for major depression to approximately 80% in bipolar disorder. While modern research is far from explaining the precise mechanisms through which genetic variations account for psychiatric disorders, it is clear that biological factors are critical in the development of psychopathology. In light of this genetic contribution, it is likely that genetic variation will substantially impact treatment response, particularly to medications. The field of pharmacogenetics is devoted to uncovering genetic factors related to medication response. Genetics will likely contribute to both pharmacokinetics (how the medication travels through and is metabolized by the body) and pharmacodynamics (how the medication causes its intended effects).
While the field of pharmacogenetics is in its infancy, several examples of pharmacogenetic successes exist. In breast cancer, the FDA has recently approved genetic testing of the HER gene in order to predict response to Herceptin. Similarly, genetic variation in BCL-ABR has been used as a clinical predictor of treatment response in patients with chronic myeloid leukemia. Owing to the relative complexity of psychiatric disorders and their pharmacological treatments, pharmacogenetics has had a smaller impact on behavioral medicine, although some examples do exist. For instance, genetic variations related to metabolism of antipsychotics have been used in order to reduce the rate of side effects by as much as 20% in schizophrenia. While not clinically employed at present, extensive clinical and laboratory based research has shown that genetic variation in the mu opioid receptor gene (OPRM1) are predictive of response to naltrexone, a medication approved for treatment of alcohol dependence. While only modestly effective on the aggregate, alcohol dependent individuals who possess at least one of the minor alleles for a particular polymorphism of OPRM1 have a better response to naltrexone and thus better clinical outcomes.

Modern genetic methodology stands to uncover many more pharmacogenetic factors that would serve to enhance treatment optimization. However, there exist several hurdles that must be overcome before pharmacogenetics can truly improve clinical outcomes.

First, significant research efforts are warranted in order to discover genetic predictors of treatment response. Such research efforts would benefit tremendously from a clinical neuroscience perspective in which neuroscience informs clinically relevant intermediate phenotypes. By proposing theoretical mechanisms of medication efficacy, a neuroscientific approach would provide candidate pharmacogenetic genes.

Second, physicians and health care providers need to embrace genetic testing and the utility of genetically informed treatment planning. At present, a majority of physicians are uncomfortable with providing their patients with results of genetic testing and some are averse to genotyping in the first place. Clearly for genetically informed personalized medicine to take off, physicians must be willing to genotype their patients and use genetics as prescriptive indicators.

Finally, the issue of health disparities needs to be addressed, as pharmacogenetics could potentially amplify existing disparities. For example, allelic frequency of potentially informative genes differs between ethnicities thus potentially exacerbating ethnic health discrepancies. Furthermore access to genetic testing will likely vary by socioeconomic status thus potentiating economic-based discrepancies in behavioral medicine.  While these concerns are clearly important to consider, it is my opinion that they should not hamper the development of pharmacogenetics. Firstly, it is inevitable in nearly every branch of medicine that cutting edge treatments are not universally available; however this fact shouldn’t necessarily prevent medical advancement as treatments originally unattainable to most become more and more attainable with time. Secondly, the concern of allelic imbalance between ethnic groups may mean that some groups are under prescribed certain medications relative to others. While initially this may seem inherently unjust, it is necessary to understand that the driving force behind this discrepancy is treatment efficacy. If a group is less likely to possess genetic variants predictive of treatment response, you would not want to prescribe medication that will not work for them. The central tenant behind pharmacogenetics is not to prescribe medication only to people who are most likely to respond, but it is instead to prescribe medication that is optimally suited toward individual patients. If researchers can adequately demonstrate that a patient will not respond well to particular interventions, then there is no case in prescribing that medication in the first place. Alternatively, if only one treatment exists and a particular patient does not possess genetic variants predictive of enhanced response, it is perfectly reasonable to prescribe the medication and settle for suboptimal response.

In summary, the burgeoning field of pharmacogenetics stands to revolutionize psychiatric treatment via optimization of patient treatment matching. At present, relatively few examples exist that can attest to the clinical utility of pharmacogenetics. That being said the few examples currently available are promising. In the coming years researchers should advance the field of pharmacogenetics in order to discover genetic variants predictive of treatment response across a variety of ailments, psychiatric or otherwise. While several impediments exist, they are not insurmountable, especially considering the potential benefits of personalized medicine in optimizing response and minimizing side effects.

 

1.            Hutchison, K.E., Substance use disorders: realizing the promise of pharmacogenomics and personalized medicine. Annual review of clinical psychology, 2010. 6: p. 577-89.

2.            Ray, L.A., et al., Pharmacogenetics of alcoholism: a clinical neuroscience perspective. Pharmacogenomics, 2012. 13(2): p. 129-32.