Clinical validity: Combinatorial pharmacogenomics predicts antidepressant responses and healthcare utilizations better than single gene phenotypes

Abstract

In four previous studies, a combinatorial multigene pharmacogenomic test (GeneSight) predicted those patients whose antidepressant treatment for major depressive disorder resulted in poorer efficacy and increased health-care resource utilizations. Here, we extended the analysis of clinical validity to the combined data from these studies. We also compared the outcome predictions of the combinatorial use of allelic variations in genes for four cytochrome P450 (CYP) enzymes (CYP2D6, CYP2C19, CYP2C9 and CYP1A2), the serotonin transporter (SLC6A4) and serotonin 2A receptor (HTR2A) with the outcome predictions for the very same subjects using traditional, single-gene analysis. Depression scores were measured at baseline and 8-10 weeks later for the 119 fully blinded subjects who received treatment as usual (TAU) with antidepressant standard of care, without the benefit of pharmacogenomic medication guidance. For another 96 TAU subjects, health-care utilizations were recorded in a 1-year, retrospective chart review. All subjects were genotyped after the clinical study period, and phenotype subgroups were created among those who had been prescribed a GeneSight panel medication that is a substrate for either CYP enzyme or serotonin effector protein. On the basis of medications prescribed for each subject at baseline, the combinatorial pharmacogenomic (CPGx™) GeneSight method categorized each subject into either a green ('use as directed'), yellow ('use with caution') or red category ('use with increased caution and with more frequent monitoring') phenotype, whereas the single-gene method categorized the same subjects with the traditional phenotype (for example, poor, intermediate, extensive or ultrarapid CYP metabolizer). The GeneSight combinatorial categorization approach discriminated and predicted poorer outcomes for red category patients prescribed medications metabolized by CYP2D6, CYP2C19 and CYP1A2 (P=0.0034, P=0.04 and P=0.03, respectively), whereas the single-gene phenotypes failed to discriminate patient outcomes. The GeneSight CPGx process also discriminated health-care utilization and disability claims for these same three CYP-defined medication subgroups. The CYP2C19 phenotype was the only single-gene approach to predict health-care outcomes. Multigenic combinatorial testing discriminates and predicts the poorer antidepressant outcomes and greater health-care utilizations by depressed subjects better than do phenotypes derived from single genes. This clinical validity is likely to contribute to the clinical utility reported for combinatorial pharmacogenomic decision support.

Clinical Utility of Combinatorial Pharmacogenomics-Guided Antidepressant Therapy: Evidence from Three Clinical Studies

“…We evaluated the clinical validity of the CPGx test by how well it predicted clinical outcomes in the 119 TAU subjects or health care utilizations in another 96 subjects [14]. Using the multigenic composite CPGx phenotype, both types of outcomes were predicted for subgroups of patients prescribed medications metabolized by CYP2D6, CYP2C19, or CYP1A2, and to a lesser and statistically nonsignificant extent by SSRIs whose mechanism depends upon the product of the SLC6A4 PD gene, the high-affinity serotonin transporter.…”

“…A value of 1 was assigned and scored as ‘green' (e.g., ‘use as directed'); the second level was assigned a value of 2 and scored as ‘yellow' (e.g., ‘use with caution'), and the third level was assigned a 3 and scored as ‘red' (e.g., ‘use with caution and with more frequent monitoring') [11]. The test report, including the color categorization for each of the antidepressant and antipsychotic medications [12,14] (see online supplement; www.karger.com/doi/10.1159/000430915) as well as the genotypes and corresponding phenotypes for each of the 5 genes (online supplement) was sent within 48 h of sample collection to the clinician of each subject in the GeneSight-guided group to use at his or her discretion in guiding treatment. The report was not available to clinicians of subjects in the TAU (i.e., unguided) group until after completion of each study.…”

“…Based on the composite phenotype measured for each patient, the GeneSight test generates a report that provides prescribing options for 99% of all FDA-approved antidepressant and antipsychotic drugs used to treat depression. The test has predicted health care utilizations [10] and antidepressant outcomes [11,12,13] of patients with major depressive disorder, and does so with a precision that exceeds traditional pharmacogenomic associations based on single allelic variants [14]. …”

Proposed FDA Regulation of Clinical Laboratories and Clinical Implementation of Pharmacogenetics

“…The majority of earlier study designs examined a narrow objective, such as looking at only the relationship between a single gene variant of a single gene and a single outcome measure. It has been demonstrated that considering all relevant genes for a particular drug when using pharmacogenetically-guided drug selection, also known as combinatorial pharmacogenetics, results in better outcomes than when compared to either no pharmacogenetic guidance or single gene/single drug-based pharmacogenetic guidance [8,9]. It is reasonable to expect that adoption of combinatorial pharmacogenetic approaches in clinical practice will continue to show superior clinical benefit and become best practice in pharmacogenetic testing.…”

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“…It has been demonstrated that considering all relevant genes for a particular drug when using pharmacogenetically-guided drug selection, also known as combinatorial pharmacogenetics, results in better outcomes than when compared to either no pharmacogenetic guidance or single gene/single drug-based pharmacogenetic guidance. 8,9 It is reasonable to expect that adoption of combinatorial pharmacogenetic approaches in clinical practice will continue to show superior clinical benefit and become best practice in pharmacogenetic testing.…”