The combinatorial, multi-gene GeneSight test has been found to better predict antidepressant treatment outcomes for patients with depression, and their use of health care resources, than any of the individual genes that comprise the test, according to a peer-reviewed analysis by investigators from the Mayo Clinic and Assurex Health, and published online by The Pharmacogenomics Journal .
The proprietary technology of the GeneSight Psychotropic test is based on combinatorial pharmacogenomics (CPGx™), the study of how variations in multiple genes collaborate to influence an individual's response to medications, and evidence-based medicine and the known clinical pharmacology of various drugs.
"This new publication shows that the combinatorial GeneSight test predicts which patients are likely to experience poorer antidepressant outcomes and use more health care services, whereas single gene diagnostics mostly did not," said lead author and Assurex Health Senior Vice President, C. Anthony Altar, Ph.D. "The robust evidence from these analyses reinforce the advantage of the combinatorial GeneSight test in helping clinicians guide antidepressant and anti-anxiety treatment decisions. This and other features of GeneSight distinguish our pharmacogenomic products from all others."
The GeneSight Psychotropic test helps inform clinicians' treatment selection for commonly prescribed medications including those for depression, post-traumatic stress disorder (PTSD), anxiety, bipolar disorder and schizophrenia. The test is covered by Medicare, the U.S. Department of Veterans Affairs, and a growing number of commercial payers.
Evaluating Drug Metabolism with Genetic Data
The CPGx approach that generates the GeneSight report examines DNA variations of multiple genes since these variations can change the efficacy, metabolism, and adverse effects of many psychiatric drugs. Using a patient's unique genetics, the GeneSight Psychotropic test creates a personalized report that places 38 U.S. Food and Drug Administration (FDA)-approved medications for depression and other mental health conditions into three color-coded categories for clinicians to review: "Use as Directed" in green, "Use with Caution" in yellow, or "Use with Increased Caution and with More Frequent Monitoring" in red. The GeneSight report also alerts healthcare providers to the implications of the patient's genetic information to a drug's dosage, and FDA-approved package insert information.
Most single gene tests have high variability and are less accurate in predicting patient responses to psychotropic medications. The GeneSight approach compensates for these limitations by aggregating predictions by the drug metabolism and response genes to better predict patient's responses.
"Nearly 90 percent of antidepressant and antipsychotic medications are metabolized by at least two of the liver cytochrome P450 (CYP) enzymes, and many interact with the brain serotonin transporter (SLC6A4) or the serotonin 2A receptor (HTR2A)," explained the authors. "The GeneSight Psychotropic test accounts for this complexity by measuring and combining the DNA sequence variations within drug response and drug metabolism genes. This analysis looked at the GeneSight test that included the liver metabolism genes CYP2D6, CYP2C19, CYP2C9, and CYP1A2, and the two drug response genes, SLC6A4 and HTR2A."
Since these studies were conducted, Assurex Health has enhanced the GeneSight test to include two more genes, CYP3A4 and CYP2B6, making it the first and only psychiatric pharmacogenomic test to offer CYP3A4 analysis distinct and separate from CYP3A5. The CYP2B6 gene affects medications including bupropion (Wellbutrin®), the third most commonly prescribed antidepressant.
GeneSight Outperforms Single Gene Tests in Predicting Patient Outcomes
In The Pharmacogenomics Journal article, the authors examined pooled data from three clinical trials, including two open-label studies and one randomized, double-blind controlled trial. Depression outcomes were recorded over 8 to 10 weeks for 119 fully blinded, treatment-resistant patients who were tested but neither they nor their clinicians received the GeneSight report. They were treated with standard of care and antidepressants were prescribed without pharmacogenomic guidance.
After the studies were completed, the investigators used the GeneSight test results for each patient to determine the GeneSight color classification of their medications. The antidepressant outcomes of the 119 patients were predicted by the GeneSight classification (p=0.008), based on improvements of depressive symptoms measured by the Hamilton Depression scale (HAM-D17). Patients who entered the studies on one or more GeneSight red category medications showed significantly less improvement in depressive symptoms than those prescribed medications classified as yellow or green.
The investigators then created five subgroups comprised of those patients who were prescribed one or more drugs that are metabolized by either of the CYP enzymes or either of the serotonin effector proteins. The GeneSight test again predicted the improvement in depressive symptoms for patients prescribed medications metabolized via the CYP2D6 (117 patients, p=0.003), CYP2C19 (80, p=0.04) or CYP1A2 (35, p=0.03) enzymes. In the exact same patient groups, clinical improvements were not predicted by either of the single gene tests based on their traditional classification of patients as poor, intermediate, extensive, or ultrarapid CYP metabolizers.
Healthcare Use and Disability Claims
This publication also reports similar findings from a retrospective chart review of medical information collected for one year of treatment for a different group of 96 depressed patients. Investigators found that the GeneSight test predicted more total healthcare visits, medical visits and disability claims among patients who had been prescribed one or more medications classified in the red category. Similar to results with depression outcomes, GeneSight predicted significantly more total healthcare visits and disability claims among patients prescribed red category medications metabolized by CYP2D6 (p=0.04, p=0.002, respectively) or CYP2C19 (p=0.04, p=0.001, respectively), and predicted total healthcare visits (p=0.01) and medical visits (p=0.02) for patients prescribed CYP1A2-metabolized drugs. In comparison, only one of the five single gene tests, that for CYP2C19, predicted differences, and only for total healthcare visits or medical visits.
Multiple peer-reviewed clinical studies have demonstrated the efficacy and utility of GeneSight. Compared with the current standard of care, pooled data from these peer-reviewed studiesii ,iii, iv show that patients whose treatment was guided by GeneSight experienced a 53 percent greater improvement in depressive symptoms and double the likelihood of response compared with those not guided by the test. Studies have also shown that clinicians who incorporate GeneSight when evaluating medication decisions for their depressed patients can help reduce annual health care costs per patient by more than $2,500, potentially saving millions of dollars in healthcare expenditures.
Altar's co-authors on the paper, "Clinical Validity: Combinatorial Pharmacogenomics Predicts Antidepressant Responses and Healthcare Utilizations Better than Single Gene Phenotypes," include Daniel Hall-Flavin, M.D., Associate Professor of Psychiatry at the Mayo Clinic, and Joseph Carhart, M.A., Josiah D. Allen, Bryan M. Dechairo, Ph.D. and Joel G. Winner, M.D., of Assurex Health. The full article can be viewed at http://genesight.com/reprint-combinatorial-pharmacogenomics. Assurex Health funded the paper.