Improved Antidepressant Remission in Major Depression via a Pharmacokinetic Pathway Polygene Pharmacogenetic Report

Pharmacogenomic Clinical Support Tools for the Treatment of Depression

OBJECTIVE

In this review, the authors update the 2018 position statement of the American Psychiatric Association Council of Research Workgroup on Biomarkers and Novel Treatments on pharmacogenomic (PGx) tools for treatment selection in depression.

METHODS

The literature was reviewed for new clinical trials and meta-analyses, published from 2017 to 2022, of studies using PGx tools for treatment selection in depression. The blinding and control conditions, as well as primary and secondary outcomes and post hoc analyses, were summarized.

RESULTS

Eleven new clinical trials and five meta-analyses were identified; all studies had primary outcome measures related to speed or efficacy of treatment response. Three trials (27%) demonstrated efficacy on the primary outcome measure with statistical significance; the three studies used different PGx tools; one study was open-label and the other two were small single-blind trials. Five trials (45%) did not detect efficacy with statistical significance on either primary or secondary outcome measures. Only one trial (9%) used adverse events as a primary outcome measure. All studies had significant limitations; for example, none adopted a fully blinded study design, only two studies attempted to blind the treating clinician, and none incorporated measures to estimate the effectiveness of the blinds or the influence of lack of blinding on the study results.

CONCLUSIONS

The addition of these new data do not alter the recommendations of the 2018 report, or the advice of the U.S. Food and Drug Administration, that the evidence does not support the use of currently available combinatorial PGx tools for treatment selection in major depressive disorder. Priority efforts for future studies and the development and testing of effective tools include fully blinded study designs, inclusion of promising genetic variants not currently included in any commercially available tests, and investigation of other uses of pharmacogenomics, such as estimating the likelihood of rare adverse drug effects, rather than increasing the speed or magnitude of drug response.

Current level of evidence for improvement of antidepressant efficacy and tolerability by pharmacogenomic-guided treatment: A Systematic review and meta-analysis of randomized controlled clinical trials

The aim of the study was to assess the clinical utility of currently available pharmacogenomic (PGx) tools compared with treatment as usual (TAU), using a meta-analysis of dichotomous and continuous antidepressant efficacy and tolerability data from previously published clinical trials. MEDLINE, clinicaltrial.gov, EU Clinical Trials Register, WHO ICTRP and CENTRAL were systematically searched; of the 962 results originally reviewed, 15 trials were included. Antidepressant efficacy was quantified by relative and absolute changes in symptom severity after eight weeks of treatment and by response and remission rates, while tolerability was estimated by the rate of study discontinuation for any reason. In the PGx-guided patients, symptom severity reduced by an average of 31.0% after eight weeks of treatment, compared to an average reduction of 26.8% in the TAU group. Accordingly, PGx-guided patients experienced a greater reduction in symptom severity of 3.4% (95%CI: 1.6-5.3%), which corresponded to a reduction in the Hamilton Depression score of 0.75 (0.30-1.21), a 37% (15-63%) higher remission rate, and an 18% (5-33%) higher response rate compared with TAU patients, while no difference was observed in discontinuation rate between groups. Notably, the majority of associations lost statistical significance when restricting the dataset to low risk of bias studies, while certain funnel plots suggested a potential publication bias favoring the reporting of statistically significant results. In summary, PGx tools marginally enhance antidepressant efficacy, but not antidepressant tolerability; thus, additional research and advancement of PGx tools are needed to improve integration of PGx in clinical pharmacotherapy of depression.

A New Intervention for Implementation of Pharmacogenetics in Psychiatry: A Description of the PSY-PGx Clinical Study

(1) Background Pharmacological treatment for psychiatric disorders has shown to only be effective in about one-third of patients, as it is associated with frequent treatment failure, often because of side effects, and a long process of trial-and-error pharmacotherapy until an effective and tolerable treatment is found. This notion emphasizes the urgency for a personalized medicine approach in psychiatry. (2) Methods This prospective patient- and rater-blinded, randomized, controlled study will investigate the effect of dose-adjustment of antidepressants escitalopram and sertraline or antipsychotics risperidone and aripiprazole according to the latest state-of-the-art international dosing recommendations for CYP2C19 and CYP2D6 metabolizer status in patients with mood, anxiety, and psychotic disorders. A total sample of N = 2500 will be recruited at nine sites in seven countries (expected drop-out rate of 30%). Patients will be randomized to a pharmacogenetic group or a dosing-as-usual group and treated over a 24-week period with four study visits. The primary outcome is personal recovery using the Recovery Assessment Scale as assessed by the patient (RAS-DS), with secondary outcomes including clinical effects (response or symptomatic remission), side effects, general well-being, digital phenotyping, and psychosocial functioning. (3) Conclusions This is, to our knowledge, the first international, multi-center, non-industry-sponsored randomized controlled trial (RCT) that may provide insights into the effectiveness and utility of implementing pharmacogenetic-guided treatment of psychiatric disorders, and as such, results will be incorporated in already available dosing guidelines.

Effectiveness of pharmacogenomics on the response and remission of treatment-resistant depression: a meta-analysis of randomised controlled trials

Background

Pharmacogenomics (PGx) is a promising tool to realise tailored drug therapy for depression.

Aims

To investigate the treatment efficacy of PGx for treatment-resistant depression (TRD) compared with treatment as usual.

Methods

A systematic search was conducted in PubMed, Embase, the Cochrane Library, Web of Science and PsycINFO to identify relevant studies published from inception to 15 April 2023. Two-arm randomised controlled trials (RCTs) exploring the efficacy of PGx-guided versus unguided treatment for TRD were included. The risk of bias in the included studies was evaluated using the Cochrane risk of bias assessment tool. The overall quality of evidence was assessed using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach.

Results

Seven RCTs (n=3003) comparing PGx-guided (n=1492) and unguided (n=1511) groups were identified and analysed. PGx-guided treatment was superior to treatment as usual in response (relative risk (RR)=1.31; 95% confidence interval (95% CI): 1.15 to 1.49; p<0.001) and remission (RR=1.40; 95% CI: 1.09 to 1.80; p=0.009) improvements. Effect sizes for acceptability (RR=0.90; 95% CI: 0.80 to 1.02; p=0.100) and side effect burden (RR=0.58; 95% CI: 0.29 to 1.15; p=0.120) between the two groups were not statistically different. The overall quality of evidence was rated from 'very low' (25%) to 'low' (75%) based on the GRADE criteria.

Conclusions

PGx-guided treatment has shown a small overall effect in improving the response and remission rates for patients with TRD. However, these results should be interpreted cautiously because of the few included studies and the low quality of evidence. Further high-quality clinical trials are warranted to confirm the findings.

PROSPERO registration number

CRD42022340182.

The Effects of CYP2C19 Genotype on Proxies of SSRI Antidepressant Response in the UK Biobank

Selective serotonin reuptake inhibitors (SSRIs) are the most commonly used psychopharmaceutical treatment for major depressive disorder (MDD), but individual responses to SSRIs vary greatly. CYP2C19 is a key enzyme involved in the metabolism of several drugs, including SSRIs. Variations in the CYP2C19 gene are associated with differential metabolic activity, and thus differential SSRI exposure; accordingly, the CYP2C19 genotype may affect the therapeutic response and clinical outcomes, though existing evidence of this link is not entirely consistent. Therefore, we analysed data from the UK Biobank, a large, deeply phenotyped prospective study, to investigate the effects of CYP2C19 metaboliser phenotypes on several clinical outcomes derived from primary care records, including multiple measures of antidepressant switching, discontinuation, duration, and side effects. In this dataset, 24,729 individuals were prescribed citalopram, 3012 individuals were prescribed escitalopram, and 12,544 individuals were prescribed sertraline. Consistent with pharmacological expectations, CYP2C19 poor metabolisers on escitalopram were more likely to switch antidepressants, have side effects following first prescription, and be on escitalopram for a shorter duration compared to normal metabolisers. CYP2C19 poor and intermediate metabolisers on citalopram also exhibited increased odds of discontinuation and shorter durations relative to normal metabolisers. Generally, no associations were found between metabolic phenotypes and proxies of response to sertraline. Sensitivity analyses in a depression subgroup and metabolic activity scores corroborated results from the primary analysis. In summary, our findings suggest that CYP2C19 genotypes, and thus metabolic phenotypes, may have utility in determining clinical responses to SSRIs, particularly escitalopram and citalopram, though further investigation of such a relationship is warranted.

Pharmacogenomics and the Management of Mood Disorders-A Review

Due to the chronic relapsing nature of mental disorders and increased life expectancy, the societal burden of these non-communicable diseases will increase even further. Treatments for mental disorders, such as depression, are available, but their effect is limited due to patients' (genetic) heterogeneity, low treatment compliance and frequent side effects. In general, only one-third of the patients respond to treatment. Today, medication selection in psychiatry relies on a trial-and-error approach based mainly on physicians' experience. Pharmacogenetic (PGx) testing can help in this process by determining the person-specific genetic factors that may predict clinical response and side effects associated with genetic variants that impact drug-metabolizing enzymes, drug transporters or drug targets. PGxis a discipline that investigates genetic factors that affect the absorption, metabolism, and transport of drugs, thereby affecting therapy outcome. These genetic factors can, among other things, lead to differences in the activity of enzymes that metabolize drugs. Studies in depressed patients show that genotyping of drug-metabolizing enzymes can increase the effectiveness of treatment, which could benefit millions of patients worldwide. This review highlights these studies, gives recommendations and provides future perspectives on how to proceed with PGx testing. Finally, it is recommended to consider genotyping for CYP2D6 and CYP2C19, when there is an indication (side effects or inefficacy).

Effect of pharmacogenomics testing guiding on clinical outcomes in major depressive disorder: a systematic review and meta-analysis of RCT

BACKGROUND

Pharmacogenomic testing guided treatment have been developed to guide drug selection or conversion in major depressive disorder patients. Whether patients benefit from pharmacogenetic testing remains unclear. We aim to evaluates the effect of pharmacogenomic testing guiding on clinical outcomes of major depressive disorder.

METHODS

Pubmed, Embase, and Cochrane Library of Clinical Trials were searched from inception until August 2022. Key terms included pharmacogenomic and antidepressive. Odds ratios (RR) with 95% confidence intervals (95%CIs) were calculated using fixed-effects model for low or moderate heterogeneity or random-effects model for high heterogeneity.

RESULTS

Eleven studies (5347 patients) were included. Compared with usual group, pharmacogenomic testing guided group was associated with an increased response rate at week 8 (OR 1.32, 95%CI 1.15-1.53, 8 studies, 4328 participants) and week 12 (OR 1.36, 95%CI 1.15-1.62, 4 studies, 2814 participants). Similarly, guided group was associated with an increased rate of remission at week 8 (OR 1.58, 95%CI 1.31-1.92, 8 studies, 3971 participants) and week 12 (OR 2.23, 95%CI 1.23-4.04, 5 studies, 2664 participants). However, no significant differences were found between the two groups in response rate at week 4 (OR 1.12, 95%CI 0.89-1.41, 2 studies, 2261 participants) and week 24 (OR 1.16, 95%CI 0.96-1.41, 2 studies, 2252 participants), and remission rate at week 4 (OR 1.26, 95%CI 0.93-1.72, 2 studies, 2261 participants) and week 24 (OR 1.06, 95%CI 0.83-1.34, 2 studies, 2252 participants). Medication congruence in 30 days was significantly reduced in the pharmacogenomic guided group compared with the usual care group (OR 2.07, 95%CI 1.69-2.54, 3 studies, 2862 participants). We found significant differences between subgroups of target population in response and remission rate.

CONCLUSION

Patients with major depressive disorder may benefit from pharmacogenomic testing guided treatment by achieving target response and remission rates more quickly.

Pharmacokinetic Markers of Clinical Outcomes in Severe Mental Illness: A Systematic Review

The term severe mental illness (SMI) encompasses those psychiatric disorders exerting the highest clinical burden and socio-economic impact on the affected individuals and their communities. Pharmacogenomic (PGx) approaches hold great promise in personalizing treatment selection and clinical outcomes, possibly reducing the burden of SMI. Here, we sought to review the literature in the field, focusing on PGx testing and particularly on pharmacokinetic markers. We performed a systematic review on PUBMED/Medline, Web of Science, and Scopus. The last search was performed on the 17 September 2022, and further augmented with a comprehensive pearl-growing strategy. In total, 1979 records were screened, and after duplicate removal, 587 unique records were screened by at least 2 independent reviewers. Ultimately, forty-two articles were included in the qualitative analysis, eleven randomized controlled trials and thirty-one nonrandomized studies. The observed lack of standardization in PGx tests, population selection, and tested outcomes limit the overall interpretation of the available evidence. A growing body of evidence suggests that PGx testing might be cost-effective in specific settings and may modestly improve clinical outcomes. More efforts need to be directed toward improving PGx standardization, knowledge for all stakeholders, and clinical practice guidelines for screening recommendations.

Evaluating treatment outcomes in pharmacogenomic-guided care for major depression: A rapid review and meta-analysis

Pharmacogenomic (PGx) testing may increase the probability of remission and response in patients with major depressive disorder (MDD) undergoing pharmacotherapy. Given the potential implications of these outcomes and recent proliferation of PGx studies, we conducted a systematic review to evaluate the effectiveness of PGx testing on clinical outcomes in patients with MDD as compared to treatment as usual (TAU). MEDLINE, Embase, PsycInfo, and CENTRAL were searched for English-language articles from 2000 to 2021 for randomized controlled trials (RCTs) comparing PGx-guided treatment vs. TAU in patients with MDD. Meta-analyses were conducted in R. Ten RCTs were included: eight reported remission and seven reported response. The best available evidence suggests that PGx-guided care for moderate-to-severe adult depression is more likely to result in remission and response than TAU (both risk ratios significant). However, there are limitations in the evidence base, including high risk of bias and inconsistency between trials. Despite the consequent very low certainty in the magnitude of effect, there is confidence in the direction. Though modest, the beneficial effects of PGx for adults with moderate-severe MDD could - as a result of the scope and scale of the condition and its impacts - have important ramifications for patients and the health system.

Effectiveness of pharmacogenomic tests including CYP2D6 and CYP2C19 genomic variants for guiding the treatment of depressive disorders: Systematic review and meta-analysis of randomised controlled trials

Major depressive disorders are prevalent conditions with limited treatment response and remission. Pharmacogenomics tests including CYP2D6 and CYP2C19 genomic variants provide the most reliable actionable approach to guide choice and dosing of antidepressants in major depression to improve outcomes. We carried out a meta-analysis and meta-regression analyses of randomised controlled trials evaluating pharmacogenomic tests with CYP2D6 and CYP2C19 polymorphisms in major depression. A systematic review was conducted according to PRISMA and Cochrane guidelines to search several electronic databases. Logarithmically transformed odds ratios (OR) and confidence intervals (CI) for improvement, response and remission were calculated. A random-effects meta-analysis and meta-regression analyses were subsequently carried out. Twelve randomised controlled trials were included. Pharmacogenomic tests in the treatment of depression were more effective than treatment as usual for improvement (OR:1.63, CI: 1.19-2.24), response (OR: 1.46; CI: 1.16-1.85) and remission (OR: 1.85; CI: 1.23-2.76) with no evidence of publication bias. Remission was less favourable in recent studies. The results are promising but cautious use of pharmacogenomics in major depression is advisable. PROSPERO registration ID: CRD42021261143.

Clinical utility of pharmacogenetics in a psychiatric and primary care population

This study evaluated the timing, use, and clinical outcomes of the GeneFolio® Pharmacogenomic Panel in a healthcare setting with patients managed by primary care providers or by psychiatrists. Participants were randomized to receive a pharmacogenetics report at four weeks or 12 weeks. After DNA collection and genetic analysis, pharmacists produced a recommendation report which was given to providers at the randomization week. The four-week group decreased depression severity (PHQ-9 and BDI) faster than the 12-week group (p = 0.0196), and psychiatrists' patients decreased their depression severity faster than primary care patients (PHQ-9 p = 0.0005, BDI p = 0.0218). Mean mental quality of life increased over time (p < 0.0001), but it increased slower for patients taking drugs in the Significant drug-drug-gene interaction category (p = 0.0012). Mental quality of life, depression severity, and clinical outcomes were improved by GeneFolio® pharmacogenomic testing regardless of provider type, with earlier testing improving outcomes sooner.

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.

Pharmacogenomic Testing and Depressive Symptom Remission: A Systematic Review and Meta-Analysis of Prospective, Controlled Clinical Trials

Pharmacogenomic (PGx) testing has emerged as a compelling strategy that clinicians can use to inform antidepressant medication selection and dosing, but the clinical efficacy of this strategy has been questioned. We systematically reviewed and meta-analyzed clinical trials for an association between the use of PGx-guided antidepressant therapy and depressive symptom remission in patients with major depressive disorder (MDD). We included prospective, controlled clinical trials published in English up to July 12, 2022. Data extraction and synthesis adhered to the 2020 Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Each trial was assessed for risk of bias and a random-effects model was used to estimate pooled risk ratios. Thirteen trials comprising 4,767 patients were analyzed, including 10 randomized controlled trials, and three open label trials. Across all included trials, those that received PGx-guided antidepressant therapy (n = 2,395) were 1.41 (95% confidence interval (CI) = 1.15-1.74, P = 0.001) more likely to achieve remission compared with those that received unguided antidepressant therapy (n = 2,372). Pooled risk ratios for randomized controlled trials and open label trials were 1.46 (95% CI: 1.13-1.88) and 1.26 (95% CI = 0.84-1.88), respectively. These results suggest that PGx-guided antidepressant therapy is associated with a modest but significant increase in depressive symptom remission in adults with MDD. Efforts to address the heterogeneity in PGx test composition (i.e., genes and alleles tested) and accompanying prescribing recommendations across trials will likely reduce the uncertainty about the efficacy of PGx-guided antidepressant therapy in the literature.

Meta-analysis of pharmacogenetic clinical decision support systems for the treatment of major depressive disorder

The study aimed to conduct a meta-analysis of studies comparing pharmacogenetically guided dosing of antidepressants with empiric standard of care. Publications referring to genotype-guided antidepressant therapy were identified via PubMed, Google Scholar, Scopus, Web of Science, Embase, and Cochrane databases from the inception of the databases to 2021. In addition, bibliographies of all articles were manually searched for additional references not identified in primary searches. Studies comparing clinical outcomes between two groups of patients who received antidepressant treatment were included in meta-analysis. Analysis of the data revealed statistically significant differences between the experimental group receiving pharmacogenetically guided dosing and the empirically treated controls. Specifically, genotype-guided treatment significantly improved response and remission of patients after both eight and twelve weeks of therapy, whereas no effect on the development of adverse drug reactions was observed. This meta-analysis indicates that the use of preemptive genotyping to guide dosing of antidepressants might increase treatment efficacy.

Association between CYP metabolizer phenotypes and selective serotonin reuptake inhibitors induced weight gain: a retrospective cohort study

BACKGROUND

Prescription medications such as selective serotonin reuptake inhibitors (SSRIs), commonly used to treat depression, are associated with weight gain. The role of pharmacogenomics in predicting SSRI-induced weight gain is unclear.

METHODS

In this retrospective cohort study from participants in the Mayo Clinic RIGHT study who were prescribed citalopram, paroxetine, sertraline, or fluoxetine, our aim was to evaluate the association of metabolizer phenotype and total body weight after 6 months of SSRIs initiation. We evaluated the metabolizer phenotypes (poor/intermediate, normal, and rapid/ultra-rapid) of the cytochromes P450 enzymes genes: CYP2C9, CYP2C19, and CYP2D6 known to influence the metabolism of SSRI medications: CYP2C19 for citalopram, CYP2D6 for paroxetine, CYP2D6 and CYP2C19 for sertraline, and CYP2D6 and CYP2C9 fluoxetine. In addition, we assessed the association of metabolizer phenotype and total body weight change at six months following SSRI prescription using parametric analysis of covariance adjusted for baseline body weight and multivariate regression models.

RESULTS

CYP2C19 poor/intermediate metabolizers prescribed citalopram gained significantly more weight than normal or rapid/ultra-rapid metabolizers at 6 months (TBWG %: 2.6 [95% CI 1.3-4.1] vs. 0.4 [95% CI -0.5 - 1.3] vs. -0.1 [-95% CI -1.5-1.1]; p = 0.001). No significant differences in weight outcomes at six months of treatment with paroxetine, sertraline, or fluoxetine were observed by metabolizer status.

CONCLUSIONS

Weight gain observed with citalopram may be mediated by CYP2C19 metabolizer status.

Approaches and hurdles of implementing pharmacogenetic testing in the psychiatric clinic

Pharmacogenetic (PGx) testing has emerged as a tool for predicting a person's ability to process and react to drugs. Despite the growing evidence-base, enthusiasm, and successful efforts to implement PGx testing in psychiatry, a consensus on how best to implement PGx testing into practice has not been established and numerous hurdles to widespread adoption remain to be overcome. In this article, we summarize the most used approaches and commonly encountered hurdles when implementing PGx testing into routine psychiatric care. We also highlight effective strategies that have been used to overcome hurdles. These strategies include the development of user-friendly clinical workflows for test ordering, use, and communication of results, establishment of test standardization and reimbursement policies, and development of tailored curriculums for educating health-care providers and the public. Although knowledge and awareness of these approaches and strategies to overcome hurdles alone may not be sufficient for successful implementation, they are necessary to ensure the effective spread, scale, and sustainability of PGx testing in psychiatry and other areas of medicine.

Evaluating study designs and treatment outcomes of antidepressant pharmacogenetic clinical trials - Challenges and future perspectives. A critical review

Several data indicate that the success of pharmacological treatment in major depressive disorder (MDD) is still unsatisfactory. The reasons for the low response and remission rates are multiple and depend on environmental and biological factors intrinsic to the disease and drug treatments. Pharmacogenetic (PG) tests have the potential to increase efficacy predicting outcome and to reduce antidepressant discontinuation due to side effects. Several studies investigated the utility of PG tests for antidepressants in MDD with interesting but contrasting results. To date most of them are observational studies with no comparator group, and few are randomized controlled trials (RCTs). The aim of this review is to provide an evaluation of the state of art on clinical methodologic features of RCTs with PG tests for antidepressant drugs in MDD, offering suggestions and favoring new insights that could be useful in the implementation of future trials. Several limitations concerning study design, generalization of results, duration of trials, patients group studied, and cost-effectiveness ratio were found, and a number of barriers have been noted in the adoption of PG tests into clinical practice. Despite some preliminary positive results, there is the need for larger and longer-term RCT studies, with the goal to capture the real impact of PG tests, also with stratified analysis concerning MDD features in terms of severity and antidepressant treatment failures in different ethnicity cohorts.

Best-worst scaling methodology to evaluate constructs of the Consolidated Framework for Implementation Research: application to the implementation of pharmacogenetic testing for antidepressant therapy

Background

Despite the increased demand for pharmacogenetic (PGx) testing to guide antidepressant use, little is known about how to implement testing in clinical practice. Best–worst scaling (BWS) is a stated preferences technique for determining the relative importance of alternative scenarios and is increasingly being used as a healthcare assessment tool, with potential applications in implementation research. We conducted a BWS experiment to evaluate the relative importance of implementation factors for PGx testing to guide antidepressant use.

Methods

We surveyed 17 healthcare organizations that either had implemented or were in the process of implementing PGx testing for antidepressants. The survey included a BWS experiment to evaluate the relative importance of Consolidated Framework for Implementation Research (CFIR) constructs from the perspective of implementing sites.

Results

Participating sites varied on their PGx testing platform and methods for returning recommendations to providers and patients, but they were consistent in ranking several CFIR constructs as most important for implementation: patient needs/resources, leadership engagement, intervention knowledge/beliefs, evidence strength and quality, and identification of champions.

Conclusions

This study demonstrates the feasibility of using choice experiments to systematically evaluate the relative importance of implementation determinants from the perspective of implementing organizations. BWS findings can inform other organizations interested in implementing PGx testing for mental health. Further, this study demonstrates the application of BWS to PGx, the findings of which may be used by other organizations to inform implementation of PGx testing for mental health disorders.

Supplementary Information

The online version contains supplementary material available at 10.1186/s43058-022-00300-7.

Perspectives on the Clinical Use of Pharmacogenetic Testing in Late-Life Mental Healthcare: A Survey of the American Association of Geriatric Psychiatry Membership

OBJECTIVE

To assess perspectives on pharmacogenetic (PGx) testing among members of the American Association of Geriatric Psychiatry (AAGP).

DESIGN

Cross-sectional survey.

PARTICIPANTS

Members of the AAGP.

MEASUREMENTS

Anonymous web-based survey consisting of 41 items covering experiences, indications, barriers, facilitators and ethical, legal and social implications for PGx testing.

RESULTS

A total of 124 surveys were completed (response rate = 13%). Most respondents (60%) had used PGx testing but an equal proportion (58%) was uncertain about the clinical usefulness of PGx testing in late-life mental health. Despite self-reported confidence in the ability to order and interpret PGx testing, 60% of respondents felt there was not enough clinical evidence for them to use PGx testing in their practice. This was compounded by uncertainties related to their ethical obligation and legal liability when interpreting and using (or not using) PGx testing results. Respondents strongly affirmed that clinical and legal guidelines for PGx testing in older adults are needed and would be helpful.

CONCLUSION

The findings suggest additional PGx research and physician education in late-life mental healthcare settings is required to reconcile uncertainties related to the clinical efficacy and ethico-legal aspects of PGx testing as well as address current knowledge barriers to testing uptake. These efforts would be further facilitated by the development of clinical practice guidelines to ensure equitable access to testing and standardized implementation of PGx-informed prescribing in older adults.

Sub-Analysis of CYP-GUIDES Data: Assessing the Prevalence and Impact of Drug-Gene Interactions in an Ethnically Diverse Cohort of Depressed Individuals

Introduction: Minority groups are underrepresented in pharmacogenomics (PGx) research. Recent sub-analysis of CYP-GUIDES showed reduced length of stay (LOS) in depressed patients with CYP2D6 sub-functional status. Our primary objective was to determine whether PGx guided (G) versus standard treatment (S) influenced LOS among different race/ethnic groups. Secondary objectives included prevalence of drug-gene interactions (DGIs) and readmission rates (RAR).

Methods: Retrospective sub-analysis of CYP-GUIDES data comprising CYP2D6 phenotypes was reclassified using standardized CYP2D6 genotype to phenotype recommendations from the Clinical Pharmacogenetics Implementation Consortium (CPIC) and Dutch Pharmacogenetics Working Group (DPWG). The Mann-Whitney test was used to determine differences in LOS between groups G and S and Kruskal Wallis test to compare LOS among different race/ethnic groups. Logistic regression was used to determine covariates associated with RAR.

Results: This study included 1,459 patients with 67.3% in G group (n = 982). The majority of patients were White (57.5%), followed by Latinos (25.6%) and Blacks (12.3%). Although there were no differences in LOS between G and S groups, Latinos had significant shorter LOS than Whites (p = 0.002). LOS was significantly reduced by 5.6 days in poor metabolizers in group G compared to S (p = 0.002). The proportion of supra functional and ultra-rapid metabolizers (UMs) were 6 and 20.3% using CYP-GUIDES and CPIC/DPWG definitions, respectively. Prevalence of DGIs was 40% with significantly fewer DGIs in Blacks (p < 0.001). Race/ethnicity was significantly associated with RAR (aOR 1.30; p = 0.003).

Conclusion: A greater number of patients were classified as CYP2D6 UMs using CPIC/DPWG definitions as compared to CYP-GUIDES definitions. This finding may have clinical implications for using psychotropics metabolized by CYP2D6.

Pharmacogenetic testing among patients with depression in a US managed care population

Actionable drug–gene pairs relevant to depression treatment include CYP2D6 and CYP2C19 with specific antidepressants. While clinical use of pharmacogenetic testing is growing, little is known about pharmacogenetic testing for depression treatment in managed care. We determined the incidence of single‐gene CYP2D6 and CYP2C19 testing following a new depression episode among US managed care patients, and described characteristics and antidepressant use of patients receiving tests. We used paid medical and pharmacy claims for patients from commercial health plans in the US. For adult patients with a new depression episode from January 1, 2013 to June 30, 2018, we identified covered claims for single‐gene CYP2D6 and CYP2C19 pharmacogenetic tests and antidepressant fills. Fewer than 1% (n = 1795) of the depressed cohort (n = 438,534) received a single‐gene CYP2D6 or CYP2C19 test through their insurance within 365 days of their earliest depression episode. The percentage of patients who received a test nearly tripled from 0.2% in 2013 to 0.5% in 2014 before plateauing at 0.4% from 2014 to 2017. Among the patients who received a single‐gene CYP2D6 or CYP2C19 test and filled an antidepressant within 365 days of their depression diagnosis, up to 30% may have had their initial antidepressant informed by the test result. Our findings describe the use of antidepressants before and after pharmacogenetic testing, which is clinically relevant as pharmacogenomic testing becomes more common in clinical practice. Our study also emphasizes the need for procedure and billing codes that capture multiple‐gene panel tests to be more widely implemented in administrative databases.

Pharmacogenomics-Guided Pharmacotherapy in Patients with Major Depressive Disorder or Bipolar Disorder Affected by Treatment-Resistant Depressive Episodes: A Long-Term Follow-up Study

Treatment-resistant depression (TRD) reduces affected patients’ quality of life and leads to important social health care costs. Pharmacogenomics-guided treatment (PGT) may be effective in the cure of TRD. The main aim of this study was to evaluate the clinical changes after PGT in patients with TRD (two or more recent failed psychopharmacological trials) affected by bipolar disorder (BD) or major depressive disorder (MDD) compared to a control group with treatment as usual (TAU). We based the PGT on assessing different gene polymorphisms involved in the pharmacodynamics and pharmacokinetics of drugs. We analyzed, with a repeated-measure ANOVA, the changes between the baseline and a 6 month follow-up of the efficacy index assessed through the Clinical Global Impression (CGI) scale, and depressive symptoms through the Hamilton Depression Rating Scale (HDRS). The PGT sample included 53 patients (26 BD and 27 MDD), and the TAU group included 52 patients (31 BD and 21 MDD). We found a significant within-subject effect of treatment time on symptoms and efficacy index for the whole sample, with significant improvements in the efficacy index (F = 8.544; partial η² = 0.077, p < 0.004) and clinical global impression of severity of illness (F = 6.818; partial η² = 0.062, p < 0.01) in the PGT vs. the TAU group. We also found a significantly better follow-up response (χ² = 5.479; p = 0.019) and remission (χ² = 10.351; p = 0.001) rates in the PGT vs. the TAU group. PGT may be an important option for the long-term treatment of patients with TRD affected by mood disorders, providing information that can better define drug treatment strategies and increase therapeutic improvement.

Gene-drug pairings for antidepressants and antipsychotics: level of evidence and clinical application

Substantial inter-individual discrepancies exist in both therapeutic effectiveness and adverse effects of antidepressant and antipsychotic medications, which can, in part, be explained by genetic variation. Here, we searched the Pharmacogenomics Knowledge Base for gene-antidepressant and gene-antipsychotic pairs with the highest level of evidence. We then extracted and compared the associated prescribing recommendations for these pairs developed by the Clinical Pharmacogenomics Implementation Consortium, the Dutch Pharmacogenetics Working Group or approved product labels in the US, Canada, Europe, and Asia. Finally, we highlight key economical, educational, regulatory, and ethical issues that, if not appropriately considered, can hinder the implementation of these recommendations in clinical practice. Our review indicates that evidence-based guidelines are available to assist with the implementation of pharmacogenetic-guided antidepressant and antipsychotic prescribing, although the maximum impact of these guidelines on patient care will not be realized until key barriers are minimized or eliminated.

What Are the Barriers and Enablers to the Implementation of Pharmacogenetic Testing in Mental Health Care Settings?

In psychiatry, the selection of antipsychotics and antidepressants is generally led by a trial-and-error approach. The prescribing of these medications is complicated by sub-optimal efficacy and high rates of adverse drug reactions (ADRs). These both contribute to poor levels of adherence. Pharmacogenetics (PGx) considers how genetic variation can influence an individual’s response to a drug. Pharmacogenetic testing is a tool that could aid clinicians when selecting psychotropic medications, as part of a more personalized approach to prescribing. This may improve the use of and adherence to these medications. Yet to date, the implementation of PGx in mental health environments in the United Kingdom has been slow. This review aims to identify the current barriers and enablers to the implementation of PGx in psychiatry and determine how this can be applied to the uptake of PGx by NHS mental health providers. A systematic searching strategy was developed, and searches were carried out on the PsychInfo, EmBase, and PubMed databases, yielding 11 appropriate papers. Common barriers to the implementation of PGx included cost, concerns over incorporation into current workflow and a lack of knowledge about PGx; whilst frequent enablers included optimism that PGx could lead to precision medicine, reduce ADRs and become a more routine part of psychiatric clinical care. The uptake of PGx in psychiatric care settings in the NHS should consider and overcome these barriers, while looking to capitalize on the enablers identified in this review.

Pharmacogenomics Guided Prescription Changes Improved Medication Effectiveness in Patients With Mental Health-Related Disability: A Retrospective Cohort Analyses

Mental health problems are the leading cause of disability in Canadian workers. Medication ineffectiveness is hypothesized to increase the time to return-to-work in these workers. We assessed whether prescription changes based on pharmacogenomics profiling ( Report^®) improved medication effectiveness in patients on mental health-related disability. In this retrospective cohort analyses, we assessed the impact of pharmacogenomic profiling on patient outcomes in 84 Canadian workers who were on a mental health-related disability between May 2018 and May 2019. All patients completed an informed consent form and a standard questionnaire including medical history, medications, disease symptoms, and medication side effects. Licensed pharmacists made recommendations for prescription changes in 83 patients. The main study outcome was medication effectiveness defined on a scale of 0 to 10 (0 being most effective and 10 being most ineffective) based on reported mood toward regular work tasks and medication side effects. We compared the medication effectiveness at baseline and at 3 months after the pharmacogenomics-based prescription changes. This retrospective cohort analyses included 46 patients who completed the follow-up questionnaires. Of them, 54% (n = 25) were females, 67% (n = 31) were Caucasians, and the mean age was 38 years (standard deviation [SD] = 11). The average baseline effectiveness score was 8.39 (SD =1.22). Following the prescription changes, the medication effectiveness scores significantly improved to an average of 2.30 (SD = 1.01) at 3 months of follow-up (effect size r = 0.62, p = <0.001). Pharmacogenomics could help in improving treatment outcomes in patients on mental health-related disability.

Multi-gene Pharmacogenomic Testing That Includes Decision-Support Tools to Guide Medication Selection for Major Depression: A Health Technology Assessment

BACKGROUND

Major depression is a substantial public health concern that can affect personal relationships, reduce people's ability to go to school or work, and lead to social isolation. Multi-gene pharmacogenomic testing that includes decision-support tools can help predict which depression medications and dosages are most likely to result in a strong response to treatment or to have the lowest risk of adverse events on the basis of people's genes.We conducted a health technology assessment of multi-gene pharmacogenomic testing that includes decision-support tools for people with major depression. Our assessment evaluated effectiveness, safety, cost-effectiveness, the budget impact of publicly funding multi-gene pharmacogenomic testing, and patient preferences and values.

METHODS

We performed a systematic literature search of the clinical evidence. We assessed the risk of bias of each included study using the Cochrane Risk of Bias Tool and the Risk of Bias Assessment Tool for Nonrandomized studies (RoBANS) and the quality of the body of evidence according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) Working Group criteria.We performed a systematic literature search of the economic evidence to review published cost-effectiveness studies on multi-gene pharmacogenomic testing that includes a decision-support tool in people with major depression. We developed a state-transition model and conducted a probabilistic analysis to determine the incremental cost of multi-gene pharmacogenomic testing versus treatment as usual per quality-adjusted life-year (QALY) gained for people with major depression who had inadequate response to one or more antidepressant medications. In the reference case (with GeneSight-guided care), we considered a 1-year time horizon with an Ontario Ministry of Health perspective. We also estimated the 5-year budget impact of publicly funding multi-gene pharmacogenomic testing for people with major depression in Ontario.To contextualize the potential value of multi-gene pharmacogenomic testing that includes decision-support tools, we spoke with people who have major depression and their families.

RESULTS

We included 14 studies in the clinical evidence review that evaluated six multi-gene pharmacogenomic tests. Although all tests included decision-support tools, they otherwise differed greatly, as did study design, populations included in studies, and outcomes reported. Little or no improvement was observed on change in HAM-D17 depression score compared with treatment as usual for any test evaluated (GRADE: Low-Very Low). GeneSight- and NeuroIDgenetix-guided medication selection led to statistically significant improvements in response (GRADE: Low-Very Low) and remission (GRADE: Low-Very Low), while treatment guided by CNSdose led to significant improvement in remission rates (GRADE: Low), but the study did not report on response. Results were inconsistent and uncertain for the impact of Neuropharmagen, and no significant improvement was observed for Genecept or another unspecified test for either response or remission (GRADE: Low-Very Low). Neuropharmagen may reduce adverse events and CNSDose may reduce intolerability to medication, while no difference was observed in adverse events with GeneSight, Genecept, or another unspecified test (GRADE: Moderate-Very Low). No studies reported data on suicide, treatment adherence, relapse, recovery, or recurrence of depression symptoms.Our review included four model-based economic studies and found that multi-gene pharmacogenomic testing was associated with greater effectiveness and cost savings than treatment as usual, over long-term (i.e., 3-,5-year and lifetime) time horizons. Since none of the included studies was fully applicable to the Ontario health care system, we conducted a primary economic evaluation.Our reference case analysis over the 1-year time horizon found that multi-gene pharmacogenomic testing (with GeneSight) was associated with additional QALYs (0.03, 95% credible interval [CrI]: 0.005; 0.072) and additional costs ($1,906, 95% Crl: $688; $3,360). An incremental cost-effectiveness ratio was $60,564 per QALY gained. The probability of the intervention being cost-effective (vs. treatment as usual) was 36.8% at a willingness-to-pay amount of $50,000 per QALY (i.e., moderately likely not to be cost-effective), rising to 70.7% at a willingness-to-pay amount of $100,000 per QALY (i.e., moderately likely to be cost-effective). Evidence informing economic modeling of the reference case with GeneSight and other multi-gene pharmacogenomic tests was of low to very low quality, implying considerable uncertainty or low confidence in the effectiveness estimates. The price of the test, efficacy of the intervention on remission, time horizon, and analytic perspective were major determinants of the cost-effectiveness results. If the test price were assumed to be $2,162 (compared with $2,500 in the reference case), the intervention would be cost-effective at a willingness-to-pay amount of $50,000 per QALY; moreover, if the price decreased to $595, the intervention would be cost saving (or dominant) compared with treatment as usual.At an increasing uptake of 1% per year and a test price of $2,500, the annual budget impact of publicly funding multi-gene pharmacogenomic testing in Ontario over the next 5 years ranged from an additional $3.5 million in year 1 (at uptake of 1%) to $16.8 million in year 5. The 5-year budget impact was estimated at about $52 million.People with major depression and caregivers generally supported multi-gene pharmacogenomic testing because they believed it could provide guidance that fit their values. They hoped such guidance would speed symptom relief, would reduce side effects and help inform their medication choices. Some patients expressed concerns over maintaining confidentiality of test results and the possibility that physicians would sacrifice patient-centred care to follow pharmacogenomic guidance.

CONCLUSIONS

Multi-gene pharmacogenomic testing that includes decision-support tools to guide medication selection for depression varies widely. Differences between individual tests must be considered, as clinical utility observed with one test might not apply to other tests. Overall, effectiveness was inconsistent among the six multi-gene pharmacogenomic tests we identified. Multi-gene pharmacogenomic tests may result in little or no difference in improvement in depression scores compared with treatment as usual, but some tests may improve response to treatment or remission from depression. The impact on adverse events is uncertain. The evidence, however, is uncertain, and therefore our confidence that these observed effects reflect the true effects is low to very low.For the management of major depression in people who had inadequate response to at least one medication, some multi-gene pharmacogenomic tests that include decision support tools are associated with additional costs and QALYs over the 1-year time horizon, and maybe be cost-effective at the willingness-to-pay amount of $100,000 per QALY. Publicly funding multi-gene pharmacogenomic testing in Ontario would result in additional annual costs of between $3.5 million and $16.8 million, with a total budget impact of about $52 million over the next 5 years.People with major depression and caregivers generally supported multi-gene pharmacogenomic testing because they believed it could provide guidance that fit their values. They hoped such guidance would speed symptom relief, would reduce side and help inform their medication choices. Some patients expressed concerns over maintaining confidentiality of test results and the possibility that physicians would sacrifice patient-centred care to follow pharmacogenomic guidance.

A prospective study to determine the clinical utility of pharmacogenetic testing of veterans with treatment-resistant depression

BACKGROUND

Pharmacotherapies for depression are often ineffective and treatment-resistant depression (TRD) is common across bipolar disorder (BD), major depressive disorder (MDD), and post-traumatic stress disorder (PTSD). Patient genetic information can be used to predict treatment outcomes. Prospective studies indicate that pharmacogenetic (PGX) tests have utility in the treatment of depression. However, few studies have examined the utility of PGX in other diagnoses typified by depression, or in veterans, a cohort with high rates of medical comorbidity, social stress, and suicide.

AIM

To determine the efficacy of genetically guided pharmacological treatment of TRD.

METHODS

We conducted an 8-week, prospective, multisite, single-blind study in 182 veterans with TRD including patients with BD, MDD, and PTSD. Subjects were randomly assigned to PGX-guided treatment in which the clinician incorporated PGX information into decision-making, or treatment as usual (TAU).

RESULTS

Overall, the PGX group improved marginally faster compared to TAU, but the difference was not statistically significant. Secondary analyses revealed that only PTSD patients showed a potential benefit from PGX testing. Patients predicted by PGX testing to have moderate levels of genetic risk showed a significant benefit from the PGX-guided treatment, whereas other risk groups demonstrated no benefit. Clinicians generally found the PGX test was useful, particularly in more depressed patients and/or those with more warnings for significant or serious adverse outcomes. Clinicians more often used the results to select a drug, but only rarely to adjust dosing.

CONCLUSIONS

The data reveal possible group differences in the utility of PGX testing in veterans with TRD.ClinicalTrials.gov Identifier: NCT04469322.

Individualized Medication Management in Ontario Long-Term Care Clinical Impact on Management of Depression, Pain, and Dementia

OBJECTIVES

Assess the potential benefits of identifying drug-gene interactions in nursing home (NH) residents on multiple medications. Reduce the use of high-risk medications for residents with reduced drug metabolism.

DESIGN

Open-label, nonrandomized, mixed methods study.

SETTING

Four NHs in Ontario.

MEASUREMENTS

Potential drug therapy problems (DTPs) for study cohort were identified during a medication review by a pharmacist using pharmacogenetic (PGx) clinical decision support to identify medication change opportunities. The number of DTPs identified during a standard medication review was compared with the number of DTPs identified with a PGx clinical decision support. Analysis of medication dispensing data at enrollment compared with dispensing in a 60-day window following medication review were compared for the PGx-tested study cohort with controls.

RESULTS

Prescription patterns of 90 study participants were compared with 895 controls for the same time period. Study participants were on 7 to 47 drugs, of which drugs with PGx indications ranged from 1 to 17 medications. The average medication load was 4.6 medications with PGx indications per person, whereas the controls were on 3.5 PGx drugs. Furthermore, 94% of cases and 84% of controls were on 2 or more drugs with PGx indication during the study period. Pharmacogenetic analysis identified 114 distinct DTPs in the 90 study participants, of which 29 were classified as serious. In this study, over 35% of residents were treated with antidepressants; of these, 64% have altered CYP2C19 or CYP2D6 metabolism and could benefit from drug dose adjustment or from a switch to alternative antidepressants. Twenty percent of residents were treated with hydromorphone, of which 30% have reduced response to opioids because of variations in the OPRM1 gene.

CONCLUSIONS AND IMPLICATIONS

This study demonstrated the clinical potential of PGx-based medication optimization for NH residents, impacting the management of depression, chronic pain, heart disease, and gastrointestinal symptoms.

Policy and Practice Review: A First Guideline on the Use of Pharmacogenetics in Clinical Psychiatric Practice

Effective pharmacologic treatments for psychiatric disorders are available, but their effect is limited due to patients' genetic heterogeneity and low compliance-related to frequent adverse events. Only one third of patients respond to treatment and experience remission. Pharmacogenetics is a relatively young field which focusses on genetic analyses in the context of the metabolism and outcome of drug treatment. These genetic factors can, among other things, lead to differences in the activity of enzymes that metabolize drugs. Recently, a clinical guideline was authorized by the Dutch Clinical Psychiatric Association (NVvP) on the clinical use of pharmacogenetics in psychiatry. The main goal was to provide guidance, based on current evidence, on how to best use genotyping in clinical psychiatric practice. A systematic literature search was performed, and available publications were assessed using the GRADE methodology. General recommendations for psychiatric clinical practice were provided, and specific recommendations per medication were made available. This clinical guideline for caregivers prescribing psychotropic drugs is the product of a broad collaboration of professionals from different disciplines, making use of the information available at the Dutch Pharmacogenetics Working Group (DPWG) and the Clinical Pharmacogenetics Implementation Consortium (CPIC) so far. We summarize the relevant literature and all recommendations in this article. General recommendations are provided and also detailed recommendations per medication. In summary we advise to consider genotyping, when there are side effects or inefficacy for CYP2C19 and CYP2D6. When genotype information is available use this to select the right drug in the right dose for the right patient.

A Practical Utility and Benefit of Pharmacogenetic-based Antidepressant Treatment Strategy for Major Depressive Disorder Patients with Difficult-to-treat

Objective

We report the results of pharmacogenomics-based antidepressant treatment (PGXt) results in treating treatment-resistant major depressive disorder (TRD) patients in real practice.

Methods

Nine patients were prescribed Neuropharmagen^Ⓡ for selection of antidepressants for individual patient and their clinical outcomes were followed.

Results

After treatment by PGXt results from current antidepressants, substantial reduction of depressive symptoms was observed at some point and maintained during observation period in six patients.

Conclusion

Our case series potentially shows the clinical utility and benefit of PGXt for treatment of TRD patients.

Pharmacogenetic/Pharmacogenomic Tests for Treatment Prediction in Depression

Genetic factors play a significant but complex role in antidepressant (AD) response and tolerability. During recent years, there is growing enthusiasm in the promise of pharmacogenetic/pharmacogenomic (PGx) tools for optimizing and personalizing treatment outcomes for patients with major depressive disorder (MDD). The influence of pharmacokinetic and pharmacodynamic genes on response and tolerability has been investigated, including those encoding the cytochrome P450 superfamily, P-glycoprotein, monoaminergic transporters and receptors, intracellular signal transduction pathways, and the stress hormone system. Genome-wide association studies are also identifying new genetic variants associated with AD response phenotypes, which, combined with methods such as polygenic risk scores (PRS), is opening up new avenues for novel personalized treatment approaches for MDD. This chapter describes the basic concepts in PGx of AD response, reviews the major pharmacokinetic and pharmacodynamic genes involved in AD outcome, discusses PRS as a promising approach for predicting AD efficacy and tolerability, and addresses key challenges to the development and application of PGx tests.

The Application of a Machine Learning-Based Brain Magnetic Resonance Imaging Approach in Major Depression

Major depressive disorder (MDD) shows a high prevalence and is associated with increased disability. While traditional studies aimed to investigate global characteristic neurobiological substrates of MDD, machine learning-based approaches focus on individual people rather than a group. Therefore, machine learning has been increasingly conducted and applied to clinical practice. Several previous neuroimaging studies used machine learning for stratifying MDD patients from healthy controls as well as in differentially diagnosing MDD apart from other psychiatric disorders. Also, machine learning has been used to predict treatment response using magnetic resonance imaging (MRI) results. Despite the recent accomplishments of machine learning-based MRI studies, small sample sizes and the heterogeneity of the depression group limit the generalizability of a machine learning-based predictive model. Future neuroimaging studies should integrate various materials such as genetic, peripheral, and clinical phenotypes for more accurate predictability of diagnosis and treatment response.

How Can Drug Metabolism and Transporter Genetics Inform Psychotropic Prescribing?

Many genetic variants in drug metabolizing enzymes and transporters have been shown to be relevant for treating psychiatric disorders. Associations are strong enough to feature on drug labels and for prescribing guidelines based on such data. A range of commercial tests are available; however, there is variability in included genetic variants, methodology, and interpretation. We herein provide relevant background for understanding clinical associations with specific variants, other factors that are relevant to consider when interpreting such data (such as age, gender, drug-drug interactions), and summarize the data relevant to clinical utility of pharmacogenetic testing in psychiatry and the available prescribing guidelines. We also highlight areas for future research focus in this field.

Effect of Routine Cytochrome P450 2D6 and 2C19 Genotyping on Antipsychotic Drug Persistence in Patients With Schizophrenia: A Randomized Clinical Trial

IMPORTANCE

Genetic polymorphism of genes encoding the drug metabolizing enzymes, cytochrome P450 2D6 and 2C19 (CYP2D6 and CYP2C19), is associated with treatment failure of and adverse reactions to psychotropic drugs. The clinical utility of routine CYP2D6 and CYP2C19 genotyping (CYP testing) is unclear.

OBJECTIVE

To estimate whether routine CYP testing effects the persistence of antipsychotic drug treatment.

DESIGN, SETTING, AND PARTICIPANTS

This single-masked, 3-group randomized clinical trial included patients aged 18 years or older who had been diagnosed within the schizophrenic spectrum (International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes, F20-F29) and not previously genotyped. A total of 669 of 1406 potentially eligible patients from 12 psychiatric outpatient clinics in Denmark were approached between July 2008 and December 2009. Overall, 528 patients were genotyped and randomly allocated to 1 of 3 study groups or exclusion in a sequence of 1:1:1:3 using a predictive enrichment design, aiming to double the proportion of poor or ultrarapid metabolizers for CYP2D6 or CYP2C19. Outcome measurements were recorded at baseline and 1-year follow-up. Data analysis was performed in December 2012 and updated March 2019.

INTERVENTIONS

The trial included 2 intervention groups, where antipsychotic drug treatment was guided by either CYP test (CYP test-guided [CTG]) or structured clinical monitoring (SCM), in which adverse effects and factors influencing compliance were systematically recorded at least once quarterly, and 1 control group.

MAIN OUTCOMES AND MEASURES

Primary outcome was antipsychotic drug persistence, ie, days to first modification of the initial treatment. Secondary outcomes were number of drug and dose changes, adverse effects, and psychotic symptoms, ie, hallucinations and delusions.

RESULTS

A total of 528 participants were genotyped, and 311 (median [interquartile range {IQR} age, 41 [30-50] years; 139 [45%] women; median [IQR] duration of illness, 6 [3-13] years) were randomly allocated to 1 of 3 study groups. Overall, 61 participants (20%) were extreme metabolizers. There was no difference in antipsychotic drug persistence between the CTG group and the control group (hazard ratio [HR], 1.02; 95% CI, 0.71-1.45) or SCM and the control group (HR, 0.88; 95% CI, 0.61-1.26). Subanalyses among extreme metabolizers showed similar results (CTG: HR, 0.99; 95% CI, 0.48-2.03; SCM: HR, 0.93; 95% CI, 0.44-1.96).

CONCLUSIONS AND RELEVANCE

The results of this randomized clinical trial do not support routine CYP testing in patients with schizophrenia.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT00707382.

Pharmacogenetics in psychiatric care, a call for uptake of available applications

In this narrative, we evaluate the role of pharmacogenetics in psychiatry from a pragmatic clinical perspective and address current barriers of clinical implementation of pharmacogenetics. Pharmacogenetics has been successfully implemented to improve drug therapy in several clinical areas, but not psychiatry. Yet, psychotropics account for more than one-third of the drugs for which pharmacogenetic guidelines are available and drug therapy in mental disorders is suboptimal with insufficient effectiveness and frequent adverse events. The limited application of pharmacogenetics in psychiatry is influenced by several factors; e.g. the complexity of psychotropic drug metabolism, possibly impeding the clinical understanding of the benefits of pharmacogenetics. Also, recommendations for most psychotropics classify pharmacogenetic testing only as (potentially) beneficial, not as essential, possibly because life-threatening adverse events are often not involved in these drug-gene interactions. Implementing pharmacogenetics in psychiatry could improve the current practice of time-consuming switching of therapies causing undue delays associated with worse outcomes. We expect pharmacogenetics in psychiatry to expedite with panel-based genotyping, including clinically relevant variants, which will address the complex enzymatic metabolism of psychotropic drugs. Until then, we stress that available pharmacogenetic testing should be seen as an integrated companion, not a competitor, in current clinical psychiatric care.

Pharmacogenetics in Psychiatry: An Update on Clinical Usability

Using pharmacogenetics in guiding drug therapy experiences a steady increase in uptake, although still leads to discussions as to its clinical use. Psychiatry constitutes a field where pharmacogenomic testing might help in guiding drug therapy. To address current challenges, this minireview provides an update regarding genotyping (SNP analysis/arrays/NGS), structural variant detection (star-alleles/CNVs/hybrid alleles), genotype-to-phenotype translations, cost-effectiveness, and actionability of results (FDA/CPIC/PharmGKB) regarding clinical importance of pre-emptive pharmacogenomic testing for prescription of antidepressants and antipsychotics.

Randomized, controlled, participant- and rater-blind trial of pharmacogenomic test-guided treatment versus treatment as usual for major depressive disorder

BACKGROUND

Cohort and cost-effectiveness studies suggest that measuring variation in genes that influence metabolism of common drugs could improve antidepressant treatment outcomes. Prior randomized trials have yielded inconsistent results.

METHOD

Multicenter randomized double-blind (subject and rater), controlled trial of pharmacogenomic testing among outpatients with nonpsychotic major depressive disorder. Study participants (n = 304) were randomized 1:1 to assay-guided treatment (AGT; N = 151) or treatment-as-usual (TAU; N = 153). Participants and raters were blinded to study arm; unblinded clinicians received results of a pharmacogenomic test and adjusted treatment in light of the test report. Primary outcome was change over 8 weeks in Hamilton Depression Rating Scale (SIGH-D-17).

RESULTS

For the primary comparison of interest, change in SIGH-D-17, no significant difference was detected between AGT and TAU at Week 8 (p = .53). Rates of study completion also did not differ between the arms (AGT 92.7%, TAU 92.2% (χ²  = 0.03, df = 1, p = .86). Exploratory analyses suggested significantly fewer individuals experienced worsening of depressive symptoms following AGT, and that treatment concordant with assay results was associated with greater likelihood of remission.

CONCLUSION

Pharmacogenomic testing using a panel of pharmacokinetic and pharmacodynamic variants was not associated with significant improvement in the primary efficacy outcome when providers were unconstrained by the assay results. Further investigation is needed to understand the discordance with cost-effectiveness results and among randomized trials.

Using a pharmacogenetic clinical decision support system to improve psychopharmacotherapy dosing in patients with affective disorders

Objectives Although pharmacogenetic tests provide the information on a genotype and the predicted phenotype, these tests do not themselves provide the interpretation of data for a physician. Currently, there are approximately two dozen pharmacogenomic clinical decision support systems (CDSSs) used in psychiatry. Implementation of the CDSSs forming the recommendations on drug and dose selection according to the results of pharmacogenetic testing is an urgent task. Fulfillment of this task will allow increasing the efficacy of therapy and decreasing the risk of undesirable side effects. Methods The study included 118 male patients (48 in the main group and 70 in the control group) with affective disorders and comorbid alcohol use disorder. To evaluate the efficacy and safety of therapy, several international psychometric scales and rating scales to measure side effects were used. Genotyping was performed using the real-time polymerase chain reaction with allele-specific hybridization. Pharmacogenetic testing results were interpreted using free software PGX2 (LLE Medicine, Russian Federation, Biomedical Cluster of Skolkovo, Moscow Innovative Cluster; www.pgx2.com). Results The statistically significant differences across the scores on psychometric scales were revealed. For instance, the total score on the Hamilton Rating Scale for Depression by day 9 was 9.0 [8.0; 10.0] for the main group and 11.0 [10.0; 12.0] (p<0.001) for the control group and by day 16 it was 4.0 [2.0; 6.0] for the main group and 14.0 [13.0; 14.0] (p<0.001) for the control group. The UKU Side-Effect Rating Scale (UKU) also revealed a statistically significant difference. The total score on the UKU scale by day 9 was 4.0 [4.0; 5.0] for the main group and 5.0 [5.0; 6.0] (p<0.001) for the control group and by day 16 this difference grew significantly: 3.0 [0.0; 4.2] for the main group and 9.0 [7.0; 11.0] (p<0.001) for the control group. Conclusions Pharmacogenetic-guided personalization of the drug dose in patients with affective disorders and comorbid alcohol use disorder can reduce the risk of undesirable side effects and pharmacoresistance. It allows recommending the use of pharmacogenetic CDSSs for optimizing drug dosage.

Pharmacogenetic testing in psychiatric inpatients with polypharmacy is associated with decreased medication side effects but not via medication changes

In psychiatric patients, medication adverse effects are regularly attributed to psychosomatic causes. However, many psychotropic medications are metabolized by cytochrome P450 (CYP450) enzymes. In the setting of polypharmacy, the activity of these enzymes may produce unfavorable drug-drug interactions (DDI) and drug-genotype interactions (DGI) that contribute to morbidity and mortality. This study sought to estimate the risk of adverse DDI and DGI in psychiatric inpatients with polypharmacy. We assessed whether medication changes made after pharmacogenetics (PGx) testing correlated with changes in side effects and overall improvement. Adult psychiatry inpatients with polypharmacy, defined as 5 or more scheduled prescription medications, completed the 24-item Antidepressant Side Effect Checklist (ASEC) questionnaire on enrollment and underwent PGx testing. Analysis of PGx results focused on whether the CYP2D6 and CYP2C19 phenotypes were "extreme," defined as poor, poor to intermediate, or ultrarapid. Approximately 30 days after PGx results were sent to outpatient providers, patients were contacted to obtain their current medication list and ASEC and Clinical Global Impression Improvement (CGI-I) scores. A total of 80 patients were enrolled, and 52 (65%) completed follow-up. ASEC scores improved from 11.5 (±8.1) to 7.2 (±6.0) (p = 0.0009). Mean CGI-I score was 2.7 (±1.4), between "minimal" to "much improved." However, linear regression revealed that these improvements were not correlated with whether medications were changed. We concluded that the impact of drug-genotype interactions in this small sample of inpatients with polypharmacy was low, and that patient improvement was related not to PGx-guided medication changes but to other treatments during hospitalization.

Predicting treatment effects in unipolar depression: A meta-review

There is increasing interest in clinical prediction models in psychiatry, which focus on developing multivariate algorithms to guide personalized diagnostic or management decisions. The main target of these models is the prediction of treatment response to different antidepressant therapies. This is because the ability to predict response based on patients' personal data may allow clinicians to make improved treatment decisions, and to provide more efficacious or more tolerable medications to the right patient. We searched the literature for systematic reviews about treatment prediction in the context of existing treatment modalities for adult unipolar depression, until July 2019. Treatment effect is defined broadly to include efficacy, safety, tolerability and acceptability outcomes. We first focused on the identification of individual predictor variables that might predict treatment response, and second, we considered multivariate clinical prediction models. Our meta-review included a total of 10 systematic reviews; seven (from 2014 to 2018) focusing on individual predictor variables and three focusing on clinical prediction models. These identified a number of sociodemographic, phenomenological, clinical, neuroimaging, remote monitoring, genetic and serum marker variables as possible predictor variables for treatment response, alongside statistical and machine-learning approaches to clinical prediction model development. Effect sizes for individual predictor variables were generally small and clinical prediction models had generally not been validated in external populations. There is a need for rigorous model validation in large external data-sets to prove the clinical utility of models. We also discuss potential future avenues in the field of personalized psychiatry, particularly the combination of multiple sources of data and the emerging field of artificial intelligence and digital mental health to identify new individual predictor variables.

Genetics of Treatment Outcomes in Major Depressive Disorder: Present and Future

Pharmacogenetic testing is a useful and increasingly widespread tool to assist in antidepressant prescription. More than ten antidepressants (including tricyclics, selective serotonin reuptake inhibitors and venlafaxine) have already genetic biomarkers of response/side effects in clinical guidelines and drug labels. These are represented by functional genetic variants in genes coding for cytochrome enzymes (CYP2D6 and CYP2C19). Depending on the predicted metabolic activity, guidelines provide recommendations on drug choice and dosing. Despite not conclusive, the current evidence suggests that testing can be useful in patients who did not respond or tolerate at least one previous pharmacotherapy. However, the current recommendations are based on pharmacokinetic genes only (CYP450 enzymes), while pharmacodynamic genes (modulating antidepressant mechanisms of action in the brain) are still being studied because of their greater complexity. This may be captured by polygenic risk scores, which reflect the cumulative contribution of many genetic variants to a trait, and they may provide future clinical applications of pharmacogenetics. A more extensive use of genotyping in clinical practice may lead to improvement in treatment outcomes thanks to personalized treatments, but possible ethical issues and disparities should be taken into account and prevented.

Psychopharmacological Treatment of Obsessive-Compulsive Disorder (OCD)

Background:

Obsessive-compulsive disorder (OCD) is associated with affective and cognitive symptoms causing personal distress and reduced global functioning. These have considerable societal costs due to healthcare service utilization.

Objective:

Our aim was to assess the efficacy of pharmacological interventions in OCD and clinical guidelines, providing a comprehensive overview of this field.

Methods:

We searched the PubMed database for papers dealing with drug treatment of OCD, with a specific focus on clinical guidelines, treatments with antidepressants, antipsychotics, mood stabilizers, off-label medications, and pharmacogenomics.

Results:

Prolonged administration of selective serotonin reuptake inhibitors (SSRIs) is most effective. Better results can be obtained with a SSRI combined with cognitive behavioral therapy (CBT) or the similarly oriented exposure and response prevention (ERP). Refractory OCD could be treated with different strategies, including a switch to another SSRI or clomipramine, or augmentation with an atypical antipsychotic. The addition of medications other than antipsychotics or intravenous antidepressant administration needs further investigation, as the evidence is inconsistent. Pharmacogenomics and personalization of therapy could reduce treatment resistance.

Conclusions:

SSRI/clomipramine in combination with CBT/ERP is associated with the optimal response compared to each treatment alone or to other treatments. New strategies for refractory OCD are needed. The role of pharmacogenomics could become preponderant in the coming years.

Pharmacogenomics of Antidepressant and Antipsychotic Treatment: How Far Have We Got and Where Are We Going?

In recent decades, very few new psychiatric drugs have entered the market. Thus, improvement in the use of antidepressant and antipsychotic therapy has to focus mainly on enhanced and more personalized treatment with the currently available drugs. One important aspect of such individualization is emphasizing interindividual differences in genes relevant to treatment, an area that can be termed neuropsychopharmacogenomics. Here, we review previous efforts to identify such critical genetic variants and summarize the results obtained to date. We conclude that most clinically relevant genetic variation is connected to phase I drug metabolism, in particular to genetic polymorphism of CYP2C19 and CYP2D6. To further improve individualized pharmacotherapy, there is a need to take both common and rare relevant mutations into consideration; we discuss the present and future possibilities of using whole genome sequencing to identify patient-specific genetic variation relevant to treatment in psychiatry. Translation of pharmacogenomic knowledge into clinical practice can be considered for specific drugs, but this requires education of clinicians, instructive guidelines, as well as full attention to polypharmacy and other clinically relevant factors. Recent large patient studies (n > 1,000) have replicated previous findings and produced robust evidence warranting the clinical utility of relevant genetic biomarkers. To further judge the clinical and financial benefits of preemptive genotyping in psychiatry, large prospective randomized trials are needed to quantify the value of genetic-based patient stratification in neuropsychopharmacotherapy and to demonstrate the cost-effectiveness of such interventions.

Common CYP2D6, CYP2C9, and CYP2C19 Gene Variants, Health Anxiety, and Neuroticism Are Not Associated With Self-Reported Antidepressant Side Effects

Many patients prescribed an antidepressant stop taking it because of side effects. Genetic factors and psychological factors including state or trait anxiety, may explain variation in side effect outcomes. Our aim was to examine the relative contribution of genetic and psychological factors in people with self-reported antidepressant side effects. We undertook a case control study (n = 194) of people who took a selective serotonin reuptake inhibitor (SSRI) or serotonin/noradrenaline reuptake inhibitor (SNRI) in the past 2 years, recruited via social media advertising. Cases had previously not tolerated at least one trial of an SSRI or SNRI, evidenced by stopping the drug or reducing the dose by at least 50% because of a side effect. Control participants had taken an SSRI or SNRI but did not meet case criteria. Variation in the genes CYP2D6, CYP2C19, and CYP2C9 was analyzed by Sanger sequencing on DNA extracted from blood or saliva. Participants completed the Short Health Anxiety Inventory-18, K10, and NEO-FFI-3 personality questionnaire. Participants were 87.1% female. 70.8% had a current K10 score of 22 or more. There was no consistent evidence that cases had higher psychological distress, health anxiety, or neuroticism. There was low correspondence between participants' CYP2D6, CYP2C19, and CYP2C9 phenotypes and their history of antidepressant tolerability. For this cohort of patients a history of not tolerating SSRI or SNRI therapy was not associated with variation in the pharmacogenes we tested, nor was it associated with health anxiety or neuroticism.

Mood Disorders

PURPOSE OF REVIEW

This article discusses the prevalence of the major mood disorders (major depressive disorder and bipolar disorder) in the community and within neurologic settings, articulates the steps taken to make a diagnosis of major depressive disorder or bipolar disorder, and reviews old and newer treatment options with proven efficacy for the treatment of these two conditions.

RECENT FINDINGS

New medications are available as treatment options for major depressive disorder and bipolar disorder, such as intranasal and IV ketamine, and somatic treatments, such as deep brain stimulation and vagal nerve stimulators, are being used to target treatment-resistant depression.

SUMMARY

Mood disorders are common in neurologic settings. They are disabling and increase morbidity and mortality. Clinicians should have a high index of suspicion if they suspect their patients seem more distressed or incapacitated than would be warranted by their neurologic disorders. If a patient does have a mood disorder, validating the patient's experience, initiating treatment, and, if necessary, referring the patient to a primary care physician or psychiatrist are appropriate steps.

Preliminary Clinical Investigation of Combinatorial Pharmacogenomic Testing for the Optimized Treatment of Depression: A Randomized Single-Blind Study

This study aims to explore the potential benefits of antidepressant drugs related to metabolic enzyme and drug-targeted genes, identify the optimal treatment of major depression, and provide a reference for individualized medication selection. A prospective randomized single-blind investigation was conducted for 8 weeks. A pharmacogenomic-based interpretive report was provided to the treating physician in the guided group. Patients in this group were informed that their medication selection was directed by DNA testing. In the unguided group, treatment was provided based on the clinical experience of the physician without the guidance of pharmacogenomic testing. Pharmacogenomic-based interpretive report was not provided to these patients until treatment completion. The 17-item Hamilton depression scale (HAMD-17), Hamilton anxiety scale, and treatment emergent symptom scale were used to assess the clinical efficacy and side effects at baseline and after 2, 4, and 8 weeks of treatment. Among the 80 initially enrolled patients with depression, 71 participated in the full data analysis sets and were designated into guided (31) and unguided (40) groups, respectively. No significant difference (P > 0.05) in HAMD-17 total scores, response and remission rates was found between the guided and unguided groups at the end of the treatment. The incidence rate of adverse reaction was 55.56% in guided group and 57.89% in the unguided group. Our study suggested that pharmacogenomic testing might not considerably improve the clinical efficiency and safety for the guided group.