Comparative Effectiveness of Pharmacogenomics for Treatment of Depression

Depressive disorders are the fourth leading cause of the burden of disease worldwide and is projected to be the first cause by 2030 1. According to the World Health Organization depression carries the greatest burden of disability among all mental and behavioral disorders. Specifically, depression accounts for 3.7% of all U.S. disability-adjusted life years and 8.3% of all U.S. years lived with disability. In 2014, it was estimated that 15.7 million adults in the United States had at least one major depressive episode in the past year and 43% people with severe depressive symptoms reported serious difficulties in work, home, and social activities 2. The current standard of care is based on trial-and-error of a multitude of medications; this approach often leads to patient and clinician frustration after each treatment failure (side effects or non-response) and can decrease compliance and engagement in treatment. One way to reduce this trial-and-error process, is to use pharmacogenomic (PGx) testing to guide medication treatment and increase the likelihood of response by reducing the number of ineffective medication trials.

Pharmacogenomics, the use of genetic information by patients, clinicians, and healthcare systems to match patients with pharmacologic treatments, is an important step towards precision/personalized medicine. Pharmacogenomics can make the practice of medicine more efficient by giving the right medications specifically to those who are most likely to benefit from them and to avoid giving the wrong medications to those who are most likely not to benefit based on each patient's individual genetic makeup. The PGx test for the treatment of depression is now commercially available and is reimbursable by insurance, including Medicaid and Medicare. A recent comprehensive overview of the state of PGx testing for depression, its promise, and limitations concluded that more research is needed in this rapidly-developing field3. Specifically, the gap is that while PGx-guided antidepressant treatment results in better outcomes compared to treatment as usual in tightly controlled clinical trials, it has not yet been tested in real world settings, nor has it been compared to best practice guidelines. It is less clear how well PGx tests make a difference in short and long-term patient-centered outcomes compared to guideline-concordant care of depression.

For this study, the investigators are collaborating with Assurex Health and their product GeneSight® Psychotropic powered by CPGx® technology, the only test for depression reimbursable by Medicaid and Medicare. GeneSight® is a neuropsychiatric, combinatorial, PGx test that provides recommendations for psychotropic medications (antidepressants, mood stabilizers, hypnotics for insomnia, and antipsychotics) based on a patient's individual genetic profile. The test combines pharmacokinetic (PK) metabolism genes (how drugs are metabolized) as well as pharmacodynamic (PD) genes (how drugs work) to predict dosing adjustments and response.

GeneSight® classifies medications based on the severity of the gene-drug interactions in color-coded categories: green "use as directed," yellow "moderate gene-drug interaction," and red "significant gene-drug interaction." The results are presented in a report which is easily understandable by patients and clinicians. Furthermore, GeneSight® addresses concerns reported by individuals in MoodNetwork: alleviating symptoms, identifying effective alternative treatments, reducing barriers to care/treatment, and using genetic studies to identify responders to treatment. This study answers questions that patients and clinicians care about and has the potential to improve outcomes.

Cogito, Inc. is the industry leader in the mobile sensing technology of mood. Cogito has developed a mobile phone application that assesses depression by tracking everyday usage of mobile phones, without the need to actively input data (e.g., rating depression). The application uses indicators such as phone call/text frequency or voice parameters to deduce depression severity. To date, this application has been tested in two studies: Defense Advanced Research Projects Agency (DARPA) funded a study in 73 patients with major depression and PTSD3, and a more recent NIMH funded study with 200 patients with major depression and bipolar disorder in collaboration with the MoodNetwork PPRN. The application is highly sensitive and specific in detecting depression. However, given the preliminary nature of these findings, the study investigators will use the Cogito platform as a secondary (more exploratory) outcome measure and the use of this application will be optional. The use of passive sensing technology has the advantage that it does not rely on patients' self-report and can be used for low cost longitudinal monitoring of patients for the changes in depression symptoms.