Analytical validation of a psychiatric pharmacogenomic test

Nucleic acid sample preparation techniques for bead-based suspension arrays

Multiplexing in biological assays allows the simultaneous detection of multiple analytes in a single reaction, which reduces time, labor, and cost as compared to single reaction-based detection methods. Microsphere- or bead-based suspension array technologies, such as the Luminex® xMAP® system, offer high-throughput detection of nucleic acids through a variety of different assay chemistries. Common with most nucleic acid chemistries, for bead-based or other microarray technologies, is the need for efficient extraction and purification of the nucleic acids from the specimen of interest. Often, the optimal method will be dictated by the requirements of the up-front enzymatic chemistry, such as PCR, primer extension, branched DNA (bDNA), etc. For bead-based microarray platforms, the user must also be cognizant of proteins and other contaminants present in reactions that require heat denaturation, as that can lead to bead aggregation or agglutination, preventing the reading of assay results. This review describes and highlights some of the nucleic acid extraction and purification methods that have been used successfully for bead-based nucleic acid analysis, for both prokaryotic and eucaryotic nucleic acids, from a variety of sample types.

Analytical validation of GenoPharm a clinical genotyping open array panel of 46 pharmacogenes inclusive of variants unique to people of African ancestry

Pharmacogenomic testing may be used to improve treatment outcomes and reduce the frequency of adverse drug reactions (ADRs). Population specific, targeted pharmacogenetics (PGx) panel-based testing methods enable sensitive, accurate and economical implementation of precision medicine. We evaluated the analytical performance of the GenoPharm® custom open array platform which evaluates 120 SNPs across 46 pharmacogenes. Using commercially available reference samples (Coriell Biorepository) and in-house extracted DNA, we assessed accuracy, precision, and linearity of GenoPharm®. We then used GenoPharm® on 218 samples from two Southern African black populations and determined allele and genotype frequencies for selected actionable variants. Across all assays, the GenoPharm® panel demonstrated 99.5% concordance with the Coriell reference samples, with 98.9% reproducibility. We observed high frequencies of key genetic variants in people of African ancestry: CYP2B6*6 (0.35), CYP2C9*8, *11 (0.13, 0.03), CYP2D6*17 (0.21) and *29 (0.11). GenoPharm® open array is therefore an accurate, reproducible and sensitive test that can be used for clinical pharmacogenetic testing and is inclusive of variants specific to the people of African ancestry.

Multigenetic Pharmacogenomics-Guided Treatment vs Treatment As Usual Among Hospitalized Men With Schizophrenia: A Randomized Clinical Trial

Importance

Limited evidence supports multigenetic pharmacogenomics-guided treatment (MPGT) in schizophrenia.

Objective

To evaluate the clinical effectiveness of MPGT in schizophrenia in a randomized clinical trial (RCT).

Design, Setting, and Participants

This RCT was conducted from March 2020 to March 2022. Male Chinese Han inpatients aged 18 to 60 years diagnosed with schizophrenia with a Positive and Negative Symptom Scale (PANSS) score of 60 or more from 2 selected study hospitals were included. Patients and raters were masked to MPGT or treatment as usual (TAU) randomization.

Interventions

Participants were randomly assigned in a 1:1 ratio to receive either MPGT or TAU for 12 weeks.

Main Outcomes and Measures

The primary efficacy outcome was the percentage change in PANSS total scores (range, 30 to 210) from baseline to week 6 analyzed by a modified intention-to-treat mixed model for repeated measures. The secondary outcome included response and symptomatic remission rates.

Results

A total of 210 participants (mean [SD] age, 29.2 [8.8] years) were enrolled and analyzed, with 113 assigned to MPGT and 97 to TAU. Compared with those randomized to TAU, participants randomized to MPGT demonstrated a significantly higher percentage change in PANSS score (74.2% vs 64.9%; adjusted mean difference, 9.2 percentage points; 95% CI, 4.4-14.1 percentage points; P < .001) and a higher response rate (93 of 113 [82.3%] vs 63 of 97 [64.9%]; adjusted odds ratio, 2.48; 95% CI, 1.28-4.80; P = .01) at the end of week 6.

Conclusions and Relevance

In this RCT of MPGT, MPGT was more effective than TAU in treating patients with schizophrenia. These findings suggest that multigenetic pharmacogenomic testing could serve as an effective tool to guide the treatment of schizophrenia.

Trial Registration

Chinese Clinical Trial Registry Identifier: ChiCTR2000029671.

Pharmacogenomic Profiling of Pediatric Patients on Psychotropic Medications in an Emergency Department

OBJECTIVE

The aim of the study was to evaluate the ability of a combinatorial pharmacogenomic test to predict medication blood levels and relative clinical improvements in a selected pediatric population.

METHODS

This study enrolled patients between ages 3 to 18 years who presented to a pediatric emergency department with acute psychiatric, behavioral, or mental health crisis and/or concerns, and had previously been prescribed psychotropic medications. Patients received combinatorial pharmacogenomic testing with medications categorized according to gene-drug interactions (GDIs); medications with a GDI were considered "incongruent," and medications without a GDI were considered "congruent." Blood levels for escitalopram, fluoxetine, aripiprazole, and clonidine were evaluated according to level of GDI. Relative clinical improvements in response to the prescribed psychotropic medications were measured using a parent-rated Clinical Global Impression of Improvement (CGI-I) assessment, where lower scores corresponded with greater improvement.

RESULTS

Of the 100 patients enrolled, 73% reported taking ≥1 incongruent medication. There was no significant difference in CGI-I scores between patients prescribed congruent versus incongruent medications (3.37 vs 3.68, P = 0.343). Among patients who presented for depression or suicidal ideation, those prescribed congruent medications had significantly lower CGI-I scores compared with those taking incongruent medications ( P = 0.036 for depression, P = 0.018 for suicidal ideation). There was a significant association between medication GDI and blood levels for aripiprazole (n = 15, P = 0.01) and escitalopram (n = 10, P = 0.01).

CONCLUSIONS

Our preliminary findings suggest that combinatorial pharmacogenomic testing can predict medication blood levels and relative outcomes based on medication congruency in children presenting to an emergency department with acute psychiatric/behavioral crises. Additional studies will be needed to confirm these findings.

Pharmacogenomics in treatment of depression and psychosis: an update

Genetic factors can, to a certain extent, successfully predict the therapeutic effects, metabolism, and adverse reactions of drugs. This research field, pharmacogenomics, is well developed in oncology and is currently expanding in psychiatry. Here, we summarize the latest development in pharmacogenomic psychiatry, where results of several recent large studies indicate a true benefit and cost-effectiveness of pre-emptive genotyping for more successful psychotherapy. However, it is apparent that we still lack knowledge of many additional heritable genetic factors of importance for explanation of the interindividual differences in response to psychiatric drugs. Thus, more effort to further develop pharmacogenomic psychiatry should be invested to achieve a broader clinical implementation.

Clinical utility of combinatorial pharmacogenomic testing in depression: A Canadian patient- and rater-blinded, randomized, controlled trial

The pharmacological treatment of depression consists of stages of trial and error, with less than 40% of patients achieving remission during first medication trial. However, in a large, randomized-controlled trial (RCT) in the U.S. ("GUIDED"), significant improvements in response and remission rates were observed in patients who received treatment guided by combinatorial pharmacogenomic testing, compared to treatment-as-usual (TAU). Here we present results from the Canadian "GAPP-MDD" RCT. This 52-week, 3-arm, multi-center, participant- and rater-blinded RCT evaluated clinical outcomes among patients with depression whose treatment was guided by combinatorial pharmacogenomic testing compared to TAU. The primary outcome was symptom improvement (change in 17-item Hamilton Depression Rating Scale, HAM-D17) at week 8. Secondary outcomes included response (≥50% decrease in HAM-D17) and remission (HAM-D17 ≤ 7) at week 8. Numerically, patients in the guided-care arm had greater symptom improvement (27.6% versus 22.7%), response (30.3% versus 22.7%), and remission rates (15.7% versus 8.3%) compared to TAU, although these differences were not statistically significant. Given that the GAPP-MDD trial was ultimately underpowered to detect statistically significant differences in patient outcomes, it was assessed in parallel with the larger GUIDED RCT. We observed that relative improvements in response and remission rates were consistent between the GAPP-MDD (33.0% response, 89.0% remission) and GUIDED (31.0% response, 51.0% remission) trials. Together with GUIDED, the results from the GAPP-MDD trial indicate that combinatorial pharmacogenomic testing can be an effective tool to help guide depression treatment in the context of the Canadian healthcare setting (ClinicalTrials.gov NCT02466477).

Combinatorial pharmacogenomic algorithm is predictive of sertraline metabolism in patients with major depressive disorder

Pharmacogenomic testing can be used to guide medication selection in patients with major depressive disorder (MDD). Currently, there is no consensus on which gene or genes to consider in medication management. Here, we assessed the clinical validity of the combinatorial pharmacogenomic algorithm to predict sertraline blood levels in a subset of patients enrolled in the Genomics Used to Improve DEpression Decisions (GUIDED) trial. Patients who reported taking sertraline within ≤2 weeks of the screening blood draw were included. All patients received combinatorial pharmacogenomic testing, which included a weighted assessment of individual phenotypes for multiple pharmacokinetic genes relevant for sertraline (CYP2C19, CYP2B6, and CYP3A4). Sertraline blood levels were compared between phenotypes based on: 1) the pharmacokinetic portion of the combinatorial pharmacogenomic algorithm, and 2) individual genes. When evaluated separately, individual genes (for CYP2C19 and CYP2B6) and the combinatorial algorithm were significant predictors of sertraline blood levels. However, in multivariate analyses that included individual genes and the combinatorial pharmacogenomic algorithm, only the combinatorial pharmacogenomic algorithm remained a significant predictor of sertraline blood levels. These findings support the clinical validity of the combinatorial pharmacogenomic algorithm, in that it is a superior predictor of sertraline blood levels compared to individual genes.

Real-world experience of using combinatorial pharmacogenomic test in children and adolescents with depression and anxiety

OBJECTIVE

To evaluate the real-world impact of using a commercially available combinatorial pharmacogenomic (CPGx) test on medication management and clinical outcomes in children and adolescents treated at a tertiary care psychiatry practice.

METHODS

A retrospective cohort study using our prospectively maintained database of patients undergoing CPGx testing was performed. Only patients with clinical data at the time of ordering CPGx test (pre-baseline), potential medication change visit (baseline) and 8-weeks follow-up (post-baseline) visit were included. Clinical Global Impression (CGI) scores for each visit were calculated. Appropriate statistical analysis, including one-sample t-test, paired t-test and Chi-square test was performed.

RESULTS

Based on the inclusion criteria, 281 (75.9%) of the 370 patients with CPGx testing were included. Their mean age was 15.8 ± 4.5 years (111 females; 39.5%). The average number of medications significantly increased to 2.4 ± 1.2 on the post-baseline visit [t(280) = 8.34, p < 0.001). Medications were added in 123 (43.7%), replaced in 92 (32.7%) patients and remained unchanged in rest. There was no significant association between medication-related adverse effects and psychotropic medication change group (p = 0.27). The study population showed a significant improvement (p < 0.001) in the CGI severity, efficacy, and global improvement indices.

CONCLUSION

In our experience of using CPGx test in a large cohort of children and adolescents during routine clinical practice, three-quarter of them underwent medication change. Additionally, we noted an improvement in clinical outcomes without impacting adverse effects. While the role of clinical judgement in medication changes in our cohort is likely, CPGx may supplement clinical decision making. However, the best use and benefit of CPGx in routine clinical practice needs further investigation.

A Randomized Controlled Trial of Combinatorial Pharmacogenetics Testing in Adolescent Depression

OBJECTIVE

Numerous commercial pharmacogenetics panels are now widely available for clinical use in psychiatric practice. However, there is a paucity of literature evaluating the use of combinatorial pharmacogenetics panels to enhance outcomes in the treatment of adolescents with depression. This study sought to prospectively evaluate the clinical impact of combinatorial pharmacogenetics testing in a double-blind, randomized, controlled effectiveness study for the pharmacologic treatment of adolescents with depression.

METHOD

Adolescents aged 13 to 18 years (N = 176) with moderate to severe major depressive disorder (MDD) were randomized to treatment arm guided by testing in which pharmacogenetic testing results were available at the baseline visit (GENE arm, n = 84) or a treatment-as-usual arm (TAU arm, n = 92) in which testing results were not available until an 8-week visit. Raters, participants, and families were blinded to group allocation. Symptom improvement, side effects, and satisfaction were assessed throughout the study at 4 weeks, 8 weeks, and 6 months.

RESULTS

There were no differences between the GENE and TAU arms at 8 weeks or 6 months for symptom improvement, side effect burden, or satisfaction. Selective serotonin reuptake inhibitors were prescribed at higher rates in the TAU arm compared to the GENE arm (p = .024).

CONCLUSION

Combinatorial pharmacogenetics-guided treatment did not demonstrate improved outcomes compared to TAU in adolescents with MDD. Future research should examine how specific medication-gene pairs may affect clinical outcomes in the treatment of adolescents with depression and how best to integrate pharmacogenetics into clinical practice.

CLINICAL TRIAL REGISTRATION INFORMATION

A PK/PD Genetic Variation Treatment Algorithm Versus Treatment As Usual for Adolescent Management Of Depression; https://www.clinicaltrials.gov; NCT02286440.

Clinical Implications of Combinatorial Pharmacogenomic Tests Based on Cytochrome P450 Variant Selection

Despite the potential to improve patient outcomes, the application of pharmacogenomics (PGx) is yet to be routine. A growing number of PGx implementers are leaning toward using combinatorial PGx (CPGx) tests (i.e., multigene tests) that are reusable over patients’ lifetimes. However, selecting a single best available CPGx test is challenging owing to many patient- and population-specific factors, including variant frequency differences across ethnic groups. The primary objective of this study was to evaluate the detection rate of currently available CPGx tests based on the cytochrome P450 (CYP) gene variants they target. The detection rate was defined as the percentage of a given population with an “altered metabolizer” genotype predicted phenotype, where a CPGx test targeted both gene variants a prospective diplotypes. A potential genotype predicted phenotype was considered an altered metabolizer when it resulted in medication therapy modification based on Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines. Targeted variant CPGx tests found in the Genetic Testing Registry (GTR), gene selection information, and diplotype frequency data from the Pharmacogenomics Knowledge Base (PharmGKB) were used to determine the detection rate of each CPGx test. Our results indicated that the detection rate of CPGx tests covering CYP2C19, CYP2C9, CYP2D6, and CYP2B6 show significant variation across ethnic groups. Specifically, the Sub-Saharan Africans have 63.9% and 77.9% average detection rates for CYP2B6 and CYP2C19 assays analyzed, respectively. In addition, East Asians (EAs) have an average detection rate of 55.1% for CYP2C9 assays. Therefore, the patient’s ethnic background should be carefully considered in selecting CPGx tests.

The Utility of Pharmacogenetic-Guided Psychotropic Medication Selection for Pediatric Patients: A Retrospective Study

BACKGROUND

To describe trends and clinical experiences in applying commercial pharmacogenetic testing among pediatric patients with neuropsychiatric disorders.

METHODS

Demographic and clinical data of patients receiving GeneSight^® testing from January 2015 to November 2016 at an urban pediatric hospital were retrospectively extracted from medical charts. Outcome data included pharmacogenetic test results and medication prescriptions before and after the test.

RESULTS

A total of 450 patients (12.1 ± 4.3 years) diagnosed with anxiety disorder, attention deficit hyperactivity disorder, developmental disorders including autism, and/or a mood disorder received testing, and 435 of them were prescribed medications. Comparing data before and after testing, the total number of psychotropic prescriptions were reduced by 27.2% and the number of prescribed medications with severe gene-drug interactions decreased from 165 to 95 (11.4% to 8.9% of total medications prescribed). Approximately 40% of actionable genetic annotation were related to CYP2CD6 and CYP2C19. Patients of Asian descent had significantly higher likelihood than other races of being classified as poor to intermediate metabolizers of antidepressants, mood stabilizers, and antipsychotics (p = 0.008, 0.007, and 0.001, respectively). Diagnoses, including autism spectrum disorder, were not associated with increased risks of severe gene-drug interactions.

CONCLUSIONS

Pharmacogenetic testing in child and adolescent psychiatry is currently based on few clinically actionable genes validated by CPIC and/or FDA. Although this approach can be moderately utilized to guide psychotropic medication prescribing for pediatric patients with psychiatric disorders, clinicians should cautiously interpret test results while still relying on clinical experience and judgment to direct the final selection of medication.

Prevalence of predicted gene-drug interactions for antidepressants in the treatment of major depressive disorder in the Precision Medicine in Mental Health Care Study

BACKGROUND

Pharmacogenetic (PGx) testing is a potentially important, but understudied approach to precision medicine that could improve prescribing practices for antidepressants (ADs) in patients with Major Depressive Disorder (MDD). Thus, it is important to understand the scope of its potential impact and to identify patients who may benefit most from PGx-guided care.

METHODS

Participants were treatment-seeking US veterans (N=1149) with MDD enrolled in the Precision Medicine in Mental Health Care study, a pragmatic multi-site, randomized, controlled trial that examines the utility of PGx testing in the context of pharmacotherapy for MDD. We report the prevalence of ADs with predicted moderate and clinically significant gene-drug interaction potential based on next-intended treatment. We also examined demographic and treatment history characteristics as predictors of the gene-drug interaction potential of participants' next-intended treatment.

RESULTS

Prevalence of the next-intended AD with moderate or clinically significant gene-drug interaction was 45.1% and19.3%. Previous treatment with an AD in the past two years was associated with a 1.59 increased likelihood of having a next-intended AD treatment with predicted clinically significant gene-drug interaction (95% CI: 1.08-2.35).

LIMITATIONS

The gene-drug interaction potential of ADs is specific to the PGx test panel used in this study and may not generalize to other PGx test panels.

CONCLUSIONS

PGx testing could benefit one in five patients prescribed ADs with clinically significant gene-drug interaction potential. Patients with prior AD treatment are more likely to have an AD with significant gene-drug interaction potential as their next-intended treatment and therefore may benefit most from PGx testing.

Treatment-Resistant Depression Revisited: A Glimmer of Hope

Major Depressive Disorder (MDD) is a highly prevalent psychiatric disorder worldwide. It causes individual suffering, loss of productivity, increased health care costs and high suicide risk. Current pharmacologic interventions fail to produce at least partial response to approximately one third of these patients, and remission is obtained in approximately 30% of patients. This is known as Treatment-Resistant Depression (TRD). The burden of TRD exponentially increases the longer it persists, with a higher risk of impaired functional and social functioning, vast losses in quality of life and significant risk of somatic morbidity and suicidality. Different approaches have been suggested and utilized, but the results have not been encouraging. In this review article, we present new approaches to identify and correct potential causes of TRD, thereby reducing its prevalence and with it the overall burden of this disease entity. We will address potential contributory factors to TRD, most of which can be investigated in many laboratories as routine tests. We discuss endocrinological aberrations, notably, hypothalamic-pituitary-adrenal (HPA) axis dysregulation and thyroid and gonadal dysfunction. We address the role of Vitamin D in contributing to depression. Pharmacogenomic testing is being increasingly used to determine Single Nucleotide Polymorphisms in Cytochrome P450, Serotonin Transporter, COMT, folic acid conversion (MTHFR). As the role of immune system dysregulation is being recognized as potentially a major contributory factor to TRD, the measurement of C-reactive protein (CRP) and select immune biomarkers, where testing is available, can guide combination treatments with anti-inflammatory agents (e.g., selective COX-2 inhibitors) reversing treatment resistance. We focus on established and emerging test procedures, potential biomarkers and non-biologic assessments and interventions to apply personalized medicine to effectively manage treatment resistance in general and TRD specifically.

Clinical validation of combinatorial pharmacogenomic testing and single-gene guidelines in predicting psychotropic medication blood levels and clinical outcomes in patients with depression

We evaluated the clinical validity of a combinatorial pharmacogenomic test and single-gene Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines against patient outcomes and medication blood levels to assess their ability to inform prescribing in major depressive disorder (MDD). This is a secondary analysis of the Genomics Used to Improve DEpression Decisions (GUIDED) randomized-controlled trial, which included patients with a diagnosis of MDD, and ≥1 prior medication failure. The ability to predict increased/decreased medication metabolism was validated against blood levels at screening (adjusted for age, sex, smoking status). The ability of predicted gene-drug interactions (pharmacogenomic test) or therapeutic recommendations (single-gene guidelines) to predict patient outcomes was validated against week 8 outcomes (17-item Hamilton Depression Rating Scale; symptom improvement, response, remission). Analyses were performed for patients taking any eligible medication (outcomes N=1,022, blood levels N=1,034) and the subset taking medications with single-gene guidelines (outcomes N=584, blood levels N=372). The combinatorial pharmacogenomic test was the only significant predictor of patient outcomes. Both the combinatorial pharmacogenomic test and single-gene guidelines were significant predictors of blood levels for all medications when evaluated separately; however, only the combinatorial pharmacogenomic test remained significant when both were included in the multivariate model. There were no substantial differences when all medications were evaluated or for the subset with single-gene guidelines. Overall, this evaluation of clinical validity demonstrates that the combinatorial pharmacogenomic test was a superior predictor of patient outcomes and medication blood levels when compared with guidelines based on individual genes.

Combinatorial Pharmacogenomic Testing Improves Outcomes for Older Adults With Depression

(Reprinted with permission from Am J Geriatr Psychiatry 2020; 28:933-945).

Considerations When Applying Pharmacogenomics to Your Practice

Many practitioners who have not had pharmacogenomic education are required to apply pharmacogenomics to their practices. Although many aspects of pharmacogenomics are similar to traditional concepts of drug-drug interactions, there are some differences. We searched PubMed with the search terms pharmacogenomics and pharmacogenetics (January 1, 2005, through December 31, 2019) and selected articles that supported the application of pharmacogenomics to practice. For inclusion, we gave preference to national and international consortium guidelines for implementation of pharmacogenomics. We discuss special considerations important in the application of pharmacogenomics to assist clinicians with ordering, interpreting, and applying pharmacogenomics in their practices.

Liver enzyme CYP2D6 gene and tardive dyskinesia

Background: Tardive dyskinesia (TD) is an iatrogenic involuntary movement disorder occurring after extended antipsychotic use with unclear pathogenesis. CYP2D6 is a liver enzyme involved in antipsychotic metabolism and a well-studied gene candidate for TD. Materials & methods: We tested predicted CYP2D6 metabolizer phenotype with TD occurrence and severity in our two samples of European chronic schizophrenia patients (total n = 198, of which 82 had TD). Results: TD occurrence were associated with extreme metabolizer phenotype, controlling for age and sex (p = 0.012). In other words, individuals with either increased and no CYP2D6 activity were at higher risk of having TD. Conclusion: Unlike most previous findings, TD occurrence may be associated with both extremes of CYP2D6 metabolic activity rather than solely for poor metabolizers.

Combinatorial Pharmacogenomic Testing Improves Outcomes for Older Adults With Depression

OBJECTIVE

Evaluate the clinical utility of combinatorial pharmacogenomic testing for informing medication selection among older adults who have experienced antidepressant medication failure for major depressive disorder (MDD).

DESIGN

Post hoc analysis of data from a blinded, randomized controlled trial comparing two active treatment arms.

SETTING

Psychiatry specialty and primary care clinics across 60 U.S. community and academic sites.

PARTICIPANTS

Adults age 65 years or older at baseline (n = 206), diagnosed with MDD and inadequate response to at least one medication on the combinatorial pharmacogenomic test report during the current depressive episode.

INTERVENTION

Combinatorial pharmacogenomic testing to inform medication selection (guided-care), compared with treatment as usual (TAU).

OUTCOMES

Mean percent symptom improvement, response rate, and remission rateat week 8, measured using the 17-item Hamilton Depression Rating Scale; medication switching; and comorbidity moderator analysis.

RESULTS

At week 8, symptom improvement was not significantly different for guided-care than for TAU (∆ = 8.1%, t = 1.64, df = 187; p = 0.102); however, guided-care showed significantly improved response (∆ = 13.6%, t = 2.16, df = 187; p = 0.032) and remission (∆ = 12.7%, t = 2.49, df = 189; p = 0.014) relative to TAU. By week 8, more than twice as many patients in guided-care than in TAU were on medications predicted to have no gene-drug interactions (χ² = 19.3, df = 2; p <0.001). Outcomes in the guided-care arm showed consistent improvement through the end of the open-design 24-week trial, indicating durability of the effect. Differences in outcomes between arms were not significantly impacted by comorbidities.

CONCLUSIONS

Combinatorial pharmacogenomic test-informed medication selection improved outcomes over TAU among older adults with depression.

Literature Review Concerning the Challenges of Implementing Pharmacogenetics in Primary Care Practice

Since President Obama signed the Precision Medicine Initiative in 2015, endeavors to integrate pharmacogenetics in clinical practice and psychiatric care have been evolving rapidly. The nature of general practice and psychiatric medicine, including psychopharmacotherapy and the long-term care necessary for chronic diseases, renders these fields in desperate need of the implementation of pharmacogenetics. This article presents some of the challenges facing pharmacogenetics implementation in family medicine and psychiatric care. Reputable research websites were used to extract papers, data, and lectures concerning this topic. The results reveal that three main challenges are facing this integration: the evaluation of pharmacogenetic testing in general and psychiatric practice, cost-effectiveness, and regulatory burdens. Although considerable advances are being made to address these issues, it is time to gather these efforts under one umbrella to create guidelines based on previous and upcoming research.

Combinatorial Pharmacogenomic Algorithm is Predictive of Citalopram and Escitalopram Metabolism in Patients with Major Depressive Disorder

Pharmacogenomic tests used to guide clinical treatment for major depressive disorder (MDD) must be thoroughly validated. One important assessment of validity is the ability to predict medication blood levels, which reflect altered metabolism. Historically, the metabolic impact of individual genes has been evaluated; however, we now know that multiple genes are often involved in medication metabolism. Here, we evaluated the ability of individual pharmacokinetic genes (CYP2C19, CYP2D6, CYP3A4) and a combinatorial pharmacogenomic test (GeneSight Psychotropic®; weighted assessment of all three genes) to predict citalopram/escitalopram blood levels in patients with MDD. Patients from the Genomics Used to Improve DEpression Decisions (GUIDED) trial who were taking citalopram/escitalopram at screening and had available blood level data were included (N=191). In multivariate analysis of the individual genes and combinatorial pharmacogenomic test separately (adjusted for age, smoking status), the F statistic for the combinatorial pharmacogenomic test was 1.7 to 2.9-times higher than the individual genes, showing that it explained more variance in citalopram/escitalopram blood levels. In multivariate analysis of the individual genes and combinatorial pharmacogenomic test together, only the combinatorial pharmacogenomic test remained significant. Overall, this demonstrates that the combinatorial pharmacogenomic test was a superior predictor of citalopram/escitalopram blood levels compared to individual genes.

The clinical utility of combinatorial pharmacogenomic testing for patients with depression: a meta-analysis

Aim: To perform a meta-analysis of prospective, two-arm studies examining the clinical utility of using the combinatorial pharmacogenomic test, GeneSight Psychotropic, to inform treatment decisions for patients with major depressive disorder (MDD). Patients & methods: The pooled mean effect of symptom improvement and pooled relative risk ratio (RR) of response and remission were calculated using a random effect model. Results: Overall, 1556 patients were included from four studies, with outcomes evaluated at week 8 or week 10. Patient outcomes were significantly improved for patients with MDD whose care was guided by the combinatorial pharmacogenomic test results compared with unguided care (symptom improvement Δ = 10.08%, 95% CI: 1.67-18.50; p = 0.019; response RR = 1.40, 95% CI: 1.17-1.67; p < 0.001; remission RR = 1.49, 95% CI: 1.17-1.89; p = 0.001). Conclusion: GeneSight Psychotropic guided care improves outcomes among patients with MDD.

Comparing sensitivity to change using the 6-item versus the 17-item Hamilton depression rating scale in the GUIDED randomized controlled trial

BACKGROUND

Previous research suggests that the 17-item Hamilton Depression Rating Scale (HAM-D17) is less sensitive in detecting differences between active treatment and placebo for major depressive disorder (MDD) than is the HAM-D6 scale, which focuses on six core depression symptoms. Whether HAM-D6 shows greater sensitivity when comparing two active MDD treatment arms is unknown.

METHODS

This post hoc analysis used data from the intent-to-treat (ITT) cohort (N = 1541) of the Genomics Used to Improve DEpression Decisions (GUIDED) trial, a rater- and patient-blinded randomized controlled trial. GUIDED compared combinatorial pharmacogenomics-guided care with treatment as usual (TAU) in patients with MDD. Percent of symptom improvement, response rate and remission rate from baseline to week 8 were evaluated using both scales. Analyses were performed for the full cohort and for the subset of patients who at baseline were taking medications predicted by the test to have moderate or significant gene-drug interactions. A Mokken scale analysis was conducted to compare the homogeneity of HAM-D17 with that of HAM-D6.

RESULTS

At week 8, the guided-care arm demonstrated statistically significant benefit over TAU when the HAM-D6 (∆ = 4.4%, p = 0.023) was used as the continuous measure of symptom improvement, but not when using the HAM-D17 (∆ = 3.2%, p = 0.069). Response rates increased significantly for guided-care compared with TAU when evaluated using both HAM-D6 (∆ = 7.0%, p = 0.004) and HAM-D17 (∆ = 6.3%, p = 0.007). Remission rates also were significantly greater for guided-care versus TAU using both measures (HAM-D6 ∆ = 4.6%, p = 0.031; HAM-D17 ∆ = 5.5%, p = 0.005). Patients in the guided-care arm who at baseline were taking medications predicted to have gene-drug interactions showed further increased benefit over TAU at week 8 for symptom improvement (∆ = 7.3%, p = 0.004) response (∆ = 10.0%, p = 0.001) and remission (∆ = 7.9%, p = 0.005) using HAM-D6. All outcomes showed continued improvement through week 24. Mokken scale analysis demonstrated the homogeneity and unidimensionality of HAM-D6, but not of HAM-D17, across treatment arms.

CONCLUSIONS

The HAM-D6 scale identified a statistically significant difference in symptom improvement between combinatorial pharmacogenomics-guided care and TAU, whereas the HAM-D17 did not. The demonstrated utility of pharmacogenomics-guided treatment over TAU as detected by the HAM-D6 highlights its value for future biomarker-guided trials comparing active treatment arms.

TRIAL REGISTRATION

Clinicaltrials.gov: NCT02109939. Registered 10 April 2014.

Early adoption of pharmacogenetic testing for veterans prescribed psychotropic medications

Aim: Describe the characteristics of providers ordering, patients receiving, and clinical impact of a psychotropic pharmacogenetic test on veteran care. Patients & methods: Observational cohort study linking veterans' laboratory results to electronic health record data. Changes in psychotropic medication prescribing were measured as a function of test results. Results: A total of 38 providers tested 181 veterans between 10/6/2014 and 2/1/2018. Prescriptions for medications with severe gene–drug interactions decreased; however, 11 such medications were used after testing. For 43 patients, documentation of the results was missing. Conclusion: Most prescribing decisions were congruent with test results, but in a nontrivial number of cases, prescribers appeared not to act on the results. Poor result documentation impeded the potential of results to inform clinical care.

Impact of pharmacogenomics on clinical outcomes in major depressive disorder in the GUIDED trial: A large, patient- and rater-blinded, randomized, controlled study

Current prescribing practices for major depressive disorder (MDD) produce limited treatment success. Although pharmacogenomics may improve outcomes by identifying genetically inappropriate medications, studies to date were limited in scope. Outpatients (N = 1167) diagnosed with MDD and with a patient- or clinician-reported inadequate response to at least one antidepressant were enrolled in the Genomics Used to Improve DEpression Decisions (GUIDED) trial - a rater- and patient-blind randomized controlled trial. Patients were randomized to treatment as usual (TAU) or a pharmacogenomics-guided intervention arm in which clinicians had access to a pharmacogenomic test report to inform medication selections (guided-care). Medications were considered congruent ('use as directed' or 'use with caution' test categories) or incongruent ('use with increased caution and with more frequent monitoring' test category) with test results. Unblinding occurred after week 8. Primary outcome was symptom improvement [change in 17-item Hamilton Depression Rating Scale (HAM-D17)] at week 8; secondary outcomes were response (≥50% decrease in HAM-D17) and remission (HAM-D17 ≤ 7) at week 8. At week 8, symptom improvement for guided-care was not significantly different than TAU (27.2% versus 24.4%, p = 0.107); however, improvements in response (26.0% versus 19.9%, p = 0.013) and remission (15.3% versus 10.1%, p = 0.007) were statistically significant. Patients taking incongruent medications prior to baseline who switched to congruent medications by week 8 experienced greater symptom improvement (33.5% versus 21.1%, p = 0.002), response (28.5% versus 16.7%, p = 0.036), and remission (21.5% versus 8.5%, p = 0.007) compared to those remaining incongruent. Pharmacogenomic testing did not significantly improve mean symptoms but did significantly improve response and remission rates for difficult-to-treat depression patients over standard of care (ClinicalTrials.gov NCT02109939).