Combinatorial pharmacogenomics and improved patient outcomes in depression: Treatment by primary care physicians or psychiatrists.

Failed medication trials are common in the treatment of major depressive disorder (MDD); however, the use of combinatorial pharmacogenomics to guide medication selection has been previously associated with improved outcomes in the psychiatric care setting. The utility of combinatorial pharmacogenomics in patients with MDD in primary care and psychiatric care settings was evaluated here. Patients enrolled in a naturalistic, open-label, prospective study [Individualized Medicine: Pharmacogenetics Assessment and Clinical Treatment (IMPACT)] with MDD were evaluated (N = 1871). Pharmacogenomic testing was performed for all patients and medications were categorized based on gene-drug interactions. Beck's Depression Inventory (BDI) was evaluated at baseline and follow-up (weeks 8-12). Symptom improvement (percent decrease in BDI), response (≥50% decrease in BDI), and remission (BDI≤10) at follow-up were evaluated according to provider type and whether medications were genetically congruent (little/no gene-drug interactions). There was a 27.9% reduction in depression symptoms at follow-up, as well as response and remission rates of 25.7% and 15.2%, respectively. Outcomes were significantly better among patients treated by primary care providers versus psychiatrists (symptom improvement 31.7% versus 24.9%, p < 0.01; response rate 30.1% versus 22.3%, p < 0.01; remission rate 19.5% versus 12.0%, p < 0.01). There was a 31% relative improvement in response rate among patients taking congruent versus incongruent medications, with slightly higher congruence among primary care providers (87.6%) versus psychiatrists (85.2%). Following combinatorial pharmacogenomic testing, outcomes were significantly improved among patients treated by primary care providers compared to psychiatrists, which supports the use of pharmacogenomics in broader treatment settings.

Genetic testing as a supporting tool in prescribing psychiatric medication: Design and protocol of the IMPACT study.

OBJECTIVE: Pharmacotherapy is one of the primary treatments for psychiatric disorders. Given the variation in individual response, a more personalized approach is needed. This paper will discuss methods for user-friendly referrals, recruitment criteria, data storage and dissemination, biological sample and clinical questionnaire collection, and advertising. METHODS: The Individualized Medicine: Pharmacogenetics Assessment and Clinical Treatment (IMPACT) study is one of the first to use pharmacogenetic testing on a large scale in psychiatry as a tool to predict individual drug response and tolerability. As IMPACT's eligibility criteria includes all diagnoses and comorbidities, the participant population will reflect the diversity amongst mental health consumers. IMPACT's innovative study design will demonstrate the utility of this testing within the health care system. RESULTS: IMPACT has successfully implemented pharmacogenetic testing on a relatively large scale, and in both tertiary level and primary care settings. It represents a novel approach to psychiatric care and from its initial stages the design has evolved to accommodate the nature and needs of the health care community. CONCLUSION: It is anticipated that IMPACT will continue to demonstrate the feasibility of pharmacogenetic testing and facilitate its introduction and implementation in routine healthcare practice.

Investigation of the HSPG2 Gene in Tardive Dyskinesia - New Data and Meta-Analysis.

Tardive dyskinesia (TD) is a movement disorder that may occur after extended use of antipsychotic medications. The etiopathophysiology is unclear; however, genetic factors play an important role. The Perlecan (HSPG2) gene was found to be significantly associated with TD in Japanese schizophrenia patients, and this association was subsequently replicated by an independent research group. To add to the evidence for this gene in TD, we conducted a meta-analysis specific to the relationship of HSPG2 rs2445142 with TD occurrence, while also adding our unpublished genotype data. Overall, we found a significant association of the G allele with TD occurrence (p = 0.0001); however, much of the effect appeared to originate from the discovery dataset. Nonetheless, most study samples exhibit the same trend of association with TD for the G allele. Our findings encourage further genetic and molecular studies of HSPG2 in TD.