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Several healthcare organizations across Minnesota have developed formal pharmacogenomic (PGx) clinical programs to increase drug safety and effectiveness. Healthcare professional and student education is strong and there are multiple opportunities in the state for learners to gain workforce skills and develop advanced competency in PGx. Implementation planning is occurring at several organizations and others have incorporated structured utilization of PGx into routine workflows. Laboratory-based and translational PGx research in Minnesota has driven important discoveries in several therapeutic areas. This article reviews the state of PGx activities in Minnesota including educational programs, research, national consortia involvement, technology, clinical implementation and utilization and reimbursement, and outlines the challenges and opportunities in equitable implementation of these advances.

Ensuring that patients have an adequate understanding of pharmacogenomic (PGx) test results is a critical component of implementing precision medicine into clinical care. However, no PGx-specific validated literacy assessment has yet been developed. To address this need, we developed and validated the Minnesota Assessment of Pharmacogenomic Literacy (MAPLTM). Foundational work included a scoping review of patient and general public attitudes and experiences with pharmacogenomic testing, three focus groups, readability assessments, and review by experts and members of the general public. This resulted in a 15-item assessment designed to assess knowledge in four domains: underlying concepts, limitations, benefits, and privacy. For validation, 646 participants completed the MAPL as a part of a larger survey about pharmacogenomic research and statewide PGx implementation. Two items were deemed to be “too easy” and dropped. The remaining 13 items were retained in the final MAPL with good internal reliability (Cronbach’s alpha = 0.75). Confirmatory factor analysis validated the four-domain construct of MAPL and suggested good model performance and high internal validity. The estimated coefficient loadings across 13 questions on the corresponding domains are all positive and statistically significant (p < 0.05). The MAPL covers multiple knowledge domains of specific relevance to PGx and is a useful tool for clinical and research settings where quantitative assessment of PGx literacy is of value.

Clinical symptom response to antipsychotic medications is highly variable. Genome-wide association studies (GWAS) provide a ‘hypothesis-free’ method of interrogating the genome for biomarkers of antipsychotic response. We performed a systematic review of GWAS findings for antipsychotic efficacy or effectiveness. 14 studies met our inclusion criteria, ten of which examined antipsychotic response using quantitative rating scales to measure symptom improvement. 15 genome-wide significant loci were identified, seven of which were replicated in other antipsychotic GWAS publications: CNTNAP5, GRID2, GRM7, 8q24 (KCNK9), PCDH7, SLC1A1 and TNIK. Notably, four replicated loci are involved in glutamatergic pathways. Additional validation and evaluation of the biological significance of these markers is warranted. These markers should also be evaluated for clinical utility, especially in the context of other validated pharmacogenomic variants (e.g., CYP450 genes). These findings may generate new avenues for development of novel antipsychotic treatments.

The use of pharmacogenomic (PGx) tests is increasing, but there are not standard approaches to counseling patients on their implications or results. To inform approaches for patient counseling, we conducted a scoping review of published literature on patient experiences with PGx testing and performed a thematic analysis of qualitative and quantitative reports. A structured scoping review was conducted using Joanna Briggs Institute guidance. The search identified 37 articles (involving n = 6252 participants) published between 2010 and 2021 from a diverse range of populations and using a variety of study methodologies. Thematic analysis identified five themes (reasons for testing/perceived benefit, understanding of results, psychological response, impact of testing on patient/provider relationship, concerns about testing/perceived harm) and 22 subthemes. These results provide valuable context and potential areas of focus during patient counseling on PGx. Many of the knowledge gaps, misunderstandings, and concerns that participants identified could be mitigated by pre- and post-test counseling. More research is needed on patients’ PGx literacy needs, along with the development of a standardized, open-source patient education curriculum and the development of validated PGx literacy assessment tools.

BACKGROUND Risperidone is a second-generation antipsychotic drug metabolized to an active metabolite, 9-hydroxyrisperidone, primarily by cytochrome P450 (CYP) 2D6 and to a lesser extent by CYP3A4. The extent to which drug metabolism genetics impacts risperidone and 9-hydroxyrisperidone exposure has not been clarified. OBJECTIVE A systematic review and meta-analysis evaluated the impact of genetically defined CYP2D6 function on risperidone pharmacokinetics applying a standardized genotype-phenotype translation system. METHODS A comprehensive electronic database search identified studies reporting relationships between genetically determined CYP2D6 metabolism and risperidone pharmacokinetic properties. The exposure of risperidone or active moiety (risperidone + 9-hydroxyrisperidone) was measured by dose-adjusted steady-state serum or plasma concentration or area under the concentration-time curve as primary outcomes. Subjects were assigned to CYP2D6 poor metabolizer, intermediate metabolizer, normal metabolizer, or ultrarapid metabolizer groups using a standardized genotype-phenotype translation method. Effect sizes between groups were pooled and stratified by single or multiple dosing regimens. RESULTS A total of 15 studies involving 2125 adult subjects were included in the meta-analysis. Following multiple-dose oral administration, compared with CYP2D6 normal metabolizers, the risperidone dose-adjusted steady-state serum/plasma concentration was 2.35-fold higher in intermediate metabolizers (95% confidence interval [CI] 1.77-3.13, p

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.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).Total pharmacy spend per member per year; adherence.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).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.

DNA of 258 patients with treatment-resistant depression was collected in three 8-10 week, two-arm, prospective clinical trials. Forty-four allelic variations were measured in genes for the cytochrome P450 (CYP) enzymes CYP2D6, CYPC19, and CYP1A2, the serotonin transporter (SLC6A4), and the 5-HT2A receptor (HTR2A). The combinatorial pharmacogenomic (CPGx™) GeneSight test results were provided to clinicians to support medication changes from baseline (guided arm), or they were provided at the end of each study to clinicians of unguided patients who were treated as usual (TAU). TAU subjects who at baseline were prescribed medications genetically discordant for them showed only a 12% symptom improvement, far less than the 32.5% or 28.5% improvements of the TAU subjects on yellow-category (‘use with caution'; p = 0.002) or green-category medications (‘use as recommended'; p = 0.02), respectively. The odds of a clinical response were increased 2.3-fold among all GeneSight-guided compared to all TAU subjects (p = 0.004), and overall, the guided group had a 53% greater improvement in depressive symptoms (p = 0.0002), a 1.7-fold relative improvement in response (p = 0.01), and a number needed to treat for one clinical response above that seen in the TAU group of 6.07.

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.

Objective: The aim of the study was to define the extent of current and lifetime smoking by diagnostic groups and suicide risk as reason for admission in a geographically defined psychiatric inpatient cohort. Design: The study used a population-based retrospective chart review. Methods: Smoking status and discharge diagnoses for Olmsted County, Minnesota, inpatients aged 18 to 65 admitted for psychiatric hospitalization in 2004 and 2005 were abstracted from the electronic medical record. Diagnostic groups were compared to each other using χ2 tests and Fisher exact test to analyze smoking status within the inpatient sample with significance defined as P ≤ .05. Results: Eighty percent (80.41) of our sample of 776 patients was hospitalized due to acute suicide risk. Discharge diagnostic group composition included affective disorders (80.3%), substance abuse disorders (36.1%), anxiety disorders (19%), psychotic disorders (16.4%), and personality disorders (10.3%). Of the sample, 72.2% had at least one comorbid disorder. Of the 776 patients, 356 (45.9%) were current smokers. Substance abuse and psychotic disorder diagnoses were significantly correlated with current smoking status (

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.

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.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.The guided group experienced greater percent improvement in depression scores from baseline on all three depression instruments (HAMD-17, P0.0001; QIDS-C16, P0.0001; PHQ-9, P0.0001) 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).These findings replicate previous studies and demonstrate significantly improved depression outcomes with use of GeneSight, an integrated, multigenetic pharmacogenomic testing platform.

The objective of this study was to evaluate the potential benefit of utilizing a pharmacogenomic testing report to guide the selection and dosing of psychotropic medications in an outpatient psychiatric practice. The non-randomized, open label, prospective cohort study was conducted from September 2009 to July 2010. In the first cohort, depressed patients were treated without the benefit of pharmacogenomic testing (the unguided group). A DNA sample was obtained from patients in the unguided group, but the results were not shared with either the physicians or patients until the end of the 8-week study period. In the second cohort (the guided group), testing results were provided at the beginning of the 8-week treatment period. Depression ratings were collected at baseline and after 2 weeks, 4 weeks and 8 weeks of treatment using the Quick Inventory of Depressive Symptomatology, Clinician Rated (QIDS-C16) and the 17-item Hamilton Rating Scale for Depression (HAM-D17). Clinician and patient satisfaction was also assessed. The reduction in depressive symptoms achieved within the guided treatment group was greater than the reduction of depressive symptoms in the unguided treatment group using either the QIDS-C16 (P=0.002) or HAM-D17 (P=0.04). We concluded that a rapidly available pharmacogenomic interpretive report provided clinical guidance that was associated with improved clinical outcomes for depressed patients treated in an outpatient psychiatric clinic setting.

Antidepressants are among the most widely prescribed medications, yet only 35–45% of patients achieve remission following an initial antidepressant trial. The financial burden of treatment failures in direct treatment costs, disability claims, decreased productivity, and missed work may, in part, derive from a mismatch between optimal and actual prescribed medications. The present 1 year blinded and retrospective study evaluated eight direct or indirect health care utilization measures for 96 patients with a DSM-IV-TR diagnosis of depressive or anxiety disorder. The eight measures were evaluated in relation to an interpretive pharmacogenomic test and reporting system, designed to predict antidepressant responses based on DNA variations in cytochrome P450 genes (CYP2D6, CYP2C19, CYP2C9 and CYP1A2), the serotonin transporter gene (SLC6A4) and the serotonin 2A receptor gene (5HTR2A). All subjects had been prescribed at least one of 26 commonly prescribed antidepressant or antipsychotic medications. Subjects whose medication regimen included a medication identified by the gene-based interpretive report as most problematic for that patient and are in the ‘red bin’ (medication status of ‘use with caution and frequent monitoring’), had 69% more total health care visits, 67% more general medical visits, greater than three-fold more medical absence days, and greater than four-fold more disability claims than subjects taking drugs categorized by the report as in the green bin (‘use as directed’) or yellow bin (‘use with caution’). There were no correlations between the number of medications taken and any of the eight healthcare utilization measures. These results demonstrate that retrospective psychiatric pharmacogenomic testing can identify past inappropriate medication selection, which led to increased healthcare utilization and cost.