Analytical validation of a psychiatric pharmacogenomic test.

AIM: The aim of this study was to validate the analytical performance of a combinatorial pharmacogenomics test designed to aid in the appropriate medication selection for neuropsychiatric conditions. MATERIALS & METHODS: Genomic DNA was isolated from buccal swabs. Twelve genes (65 variants/alleles) associated with psychotropic medication metabolism, side effects, and mechanisms of actions were evaluated by bead array, MALDI-TOF mass spectrometry, and/or capillary electrophoresis methods (GeneSight Psychotropic, Assurex Health, Inc.). RESULTS: The combinatorial pharmacogenomics test has a dynamic range of 2.5-20 ng/µl of input genomic DNA, with comparable performance for all assays included in the test. Both the precision and accuracy of the test were >99.9%, with individual gene components between 99.4 and 100%. CONCLUSION: This study demonstrates that the combinatorial pharmacogenomics test is robust and reproducible, making it suitable for clinical use.

Use of combinatorial pharmacogenomic testing in two cases from community psychiatry.

This report describes two cases in which pharmacogenomic testing was utilized to guide medication selection for difficult to treat patients. The first patient is a 29-year old male with bipolar disorder who had severe akathisia due to his long acting injectable antipsychotic. The second patient is a 59-year old female with major depressive disorder who was not responding to her medication. In both cases, a proprietary combinatorial pharmacogenomic test was used to inform medication changes and improve patient outcomes. The first patient was switched to a long acting injectable that was not affected by his genetic profile and his adverse effects abated. The second patient had her medications discontinued due to the results of the genetic testing and more intense psychotherapy initiated. While pharmacogenomic testing may be helpful in cases such as these presented here, it should never serve as a proxy for a comprehensive biopsychosocial approach. The pharmacogenomic information may be selectively added to this comprehensive approach to support medication treatment.

Combinatorial Versus Individual Gene Pharmacogenomic Testing in Mental Health: A Perspective on Context and Implications on Clinical Utility.

Pharmacogenomic testing in mental health has not yet reached its full potential. An important reason for this involves differentiating individual gene testing (IGT) from a combinatorial pharmacogenomic (CPGx) approach. With IGT, any given gene reveals specific information that may, in turn, pertain to a smaller number of medications. CPGx approaches attempt to encompass more complete genomic information by combining moderate risk alleles and synergistically viewing the results from the perspective of the medication. This manuscript will discuss IGT and CPGx approaches to psychiatric pharmacogenomics and review the clinical validity, clinical utility, and economic parameters of both.

Combinatorial pharmacogenomic guidance for psychiatric medications reduces overall pharmacy costs in a 1 year prospective evaluation.

OBJECTIVES: The objective of this project was to determine pharmacy cost savings and improvement in adherence based on a combinatorial pharmacogenomic test (CPGx ) in patients who had switched or added a new psychiatric medication after having failed monotherapy for their psychiatric disorder. RESEARCH DESIGN AND METHODS: The prospective project compared 1 year pharmacy claims between a GeneSight CPGx guided cohort and a propensity-matched control group. Patients were project eligible if they augmented or switched to a different antidepressant or antipsychotic medication within the previous 90 days. Following the medication switch or augmentation, pharmacogenomic (PGx) testing was offered to each patient's treating clinician. Pharmacy claims were extracted from the Medco pharmacy claims database for each patient (n = 2168) for 1 year following testing and compared to a 5-to-1 propensity-matched treatment as usual (TAU), standard of care control group (n = 10,880). MAIN OUTCOME MEASURES: Total pharmacy spend per member per year; adherence. RESULTS: Patients who received PGx testing saved $1035.60 in total medication costs (both CNS and non-CNS medications) over 1 year compared to the non-tested standard of care cohort (p = 0.007). PGx testing improved adherence compared to standard of care (ΔPDCCPGx = 0.11 vs ΔPDCTAU = -0.01; p < 0.0001). Pharmacy cost savings averaged $2774.53 for patients who were changed to a CPGx congruent medication regimen, compared to those who were not (p < 0.0001). CONCLUSIONS: PGx testing provides significant 'real world' cost savings, while simultaneously improving adherence in a difficult to treat psychiatric population. Limitations of this study include the lack of therapeutic efficacy follow-up data and possible confounding due to matching only on demographic and psychiatric variables.

The clinical validity and utility of combinatorial pharmacogenomics: Enhancing patient outcomes.

Prescribing safe and effective medications is a challenge in psychiatry. While clinical use of pharmacogenomic testing for individual genes has provided some clinical benefit, it has largely failed to show clinical utility. However, pharmacogenomic testing that integrates relevant genetic variation from multiple loci for each medication has shown clinical validity, utility and cost savings in multiple clinical trials. While some challenges remain, the evidence for the clinical utility of "combinatorial pharmacogenomics" is mounting. Expanding education of pharmacogenomic testing is vital to implementation efforts in psychiatric treatment settings with the overall goal of improving medication selection decisions.

A prospective, randomized, double-blind study assessing the clinical impact of integrated pharmacogenomic testing for major depressive disorder.

OBJECTIVE: A prospective double-blind randomized control trial (RCT) to evaluate the benefit of a combinatorial, five gene pharmacogenomic test and interpretive report (GeneSight) for the management of psychotropic medications used in the treatment of major depression in an outpatient psychiatric practice. METHODS: Depressed adult outpatients were randomized to a treatment as usual (TAU, n=25) arm or a pharmacogenomic-informed GeneSight (n=26) arm. Subjects were blinded to their treatment group and depression severity was assessed by blinded study raters. Within two days of enrollment, clinicians of subjects in the guided group received the GeneSight report that categorized each of 26 psychotropic medications within a green, yellow, or red "bin" based on the relationship of each medication to a subject's pharmacokinetic and pharmacodynamic combinatorial gene variant profile. Antidepressant medication changes began within 2 weeks after baseline assessments. Depression severity was assessed by blinded study raters using the HAMD-17, PHQ-9, QIDS-SR, and QIDS-CR administered 4, 6, and 10 weeks after baseline assessment. RESULTS: Between-group trends were observed with greater than double the likelihood of response and remission in the GeneSight group measured by HAMD-17 at week 10. Mean percent improvement in depressive symptoms on HAMD-17 was higher for the GeneSight group over TAU (30.8% vs 20.7%; p=0.28). TAU subjects who had been prescribed medications at baseline that were contraindicated based on the individual subject's genotype (i.e., red bin) had almost no improvement (0.8%) in depressive symptoms measured by HAMD-17 at week 10, which was far less than the 33.1% improvement (p=0.06) in the pharmacogenomic guided subjects who started on a red bin medication and the 26.4% improvement in GeneSight subjects overall (p=0.08). CONCLUSIONS: Pharmaco-genomic-guided treatment with GeneSight doubles the likelihood of response in all patients with treatment resistant depression and identifies 30% of patients with severe gene-drug interactions who have the greatest improvement in depressive symptoms when switched to genetically suitable medication regimens.

Utility of integrated pharmacogenomic testing to support the treatment of major depressive disorder in a psychiatric outpatient setting.

OBJECTIVE: The objective was to evaluate the potential benefit of an integrated, five-gene pharmacogenomic test and interpretive report (GeneSight) for the management of psychotropic medications used to treat major depression in an outpatient psychiatric practice. METHODS: The open-label study was divided into two groups. In the first (unguided) group (n = 113), pharmacogenomic information was not shared until all participants completed the study. In the second (guided) group (n = 114), the pharmacogenomic report was provided to physicians for clinical use. Three depression ratings, the 17-item Hamilton Rating Scale for Depression (HAMD-17), the Quick Inventory of Depressive Symptomatology - Clinician Rated (QIDS-C16), and the Patient Health Questionnaire (PHQ-9), were collected at baseline, and at 2, 4, and 8 weeks. RESULTS: The guided group experienced greater percent improvement in depression scores from baseline on all three depression instruments (HAMD-17, P < 0.0001; QIDS-C16, P < 0.0001; PHQ-9, P < 0.0001) compared with the unguided group. Eight-week response rates were higher in the guided group than in the unguided group on all three measurements (HAMD-17, P = 0.03; QIDS-C16, P = 0.005; PHQ-9, P = 0.01). Eight-week QIDS-C16 remission rates were higher in the guided group (P = 0.03). Participants in the unguided group who at baseline were prescribed a medication that was most discordant with their genotype experienced the least improvement compared with other unguided participants (HAMD-17, P = 0.007). Participants in the guided group and on a baseline medication most discordant with their genotype showed the greatest improvement compared with the unguided cohort participants (HAMD-17, P = 0.01). CONCLUSION: These findings replicate previous studies and demonstrate significantly improved depression outcomes with use of GeneSight, an integrated, multigenetic pharmacogenomic testing platform.

Training in psychiatric genomics during residency: a new challenge.

OBJECTIVE: The authors ascertained the amount of training in psychiatric genomics that is provided in North American psychiatric residency programs. METHODS: A sample of 217 chief residents in psychiatric residency programs in the United States and Canada were identified by e-mail and surveyed to assess their training in psychiatric genetics and genomics. RESULTS: Eighty chief residents completed the survey for a response rate of 37%. Forty-five respondents (56%) reported that during their residency training they received 3 or fewer hours of training in genomics. Of these, 13 reported that they had received no training in genomics. Chief residents who received 3 or fewer hours of training were more likely to indicate that they had not actively participated in a multidisciplinary team which utilized genetic/genomic specialists than residents who had received more didactic training in genomics (p<0.001). Although 67% of 77 respondents indicated that they understood the concept of genetic predisposition to psychiatric disease, only 14% of 80 respondents indicated that they understood the role a genetic counselor could play on a clinical team. CONCLUSION: Training in the clinical applications of genomic testing has not been thoroughly implemented in some residency programs.