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Concordance between actual and pharmacogenetic predicted desvenlafaxine dose needed to achieve remission in major depressive disorder: a 10-week open-label study

Bousman, Chad A.; Müller, Daniel J.; Ng, Chee H.; Byron, Keith; Berk, Michael; Singh, Ajeet B.

Pharmacogenetics and Genomics: January 2017 - Volume 27 - Issue 1 - p 1–6
doi: 10.1097/FPC.0000000000000253

Background Pharmacogenetic-based dosing support tools have been developed to personalize antidepressant-prescribing practice. However, the clinical validity of these tools has not been adequately tested, particularly for specific antidepressants.

Objective To examine the concordance between the actual dose and a polygene pharmacogenetic predicted dose of desvenlafaxine needed to achieve symptom remission.

Materials and methods A 10-week, open-label, prospective trial of desvenlafaxine among Caucasian adults with major depressive disorder (n=119) was conducted. Dose was clinically adjusted and at the completion of the trial, the clinical dose needed to achieve remission was compared with the predicted dose needed to achieve remission.

Results Among remitters (n=95), there was a strong concordance (Kendall’s τ-b=0.84, P=0.0001; Cohen’s κ=0.82, P=0.0001) between the actual and the predicted dose need to achieve symptom remission, showing high sensitivity (≥85%), specificity (≥86%), and accuracy (≥89%) of the tool.

Conclusion Findings provide initial evidence for the clinical validity of a polygene pharmacogenetic-based tool for desvenlafaxine dosing.

Supplemental Digital Content is available in the text.

Departments of aPsychiatry

bGeneral Practice

cFlorey Institute of Neuroscience and Mental Health, University of Melbourne

dDepartment of Psychological Sciences, Centre for Human Psychopharmacology, Swinburne University of Technology, Hawthorne

eMolecular Genetics, Healthscope Pathology

fSchool of Medicine, IMPACT Strategic Research Centre, Deakin University, Geelong, Victoria, Australia

gCentre for Addiction and Mental Health, Campbell Family Research Institute

hDepartment of Psychiatry, University of Toronto, Toronto, Ontario, Canada

Correspondence to Chad A. Bousman, MPH, PhD, Department of Psychiatry, Melbourne Neuropsychiatry Centre, University of Melbourne, 161 Barry Street, Level 3, Melbourne, VIC 3053, Australia Tel: +61 3 9035 6667; fax: +61 3 9035 8842; e-mail:

This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.

Received August 17, 2016

Accepted October 5, 2016

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The effectiveness of antidepressants and their dosing in practice is variable. This variability, in part, can be attributed to genetic polymorphisms that influence antidepressant bioavailability – phase I and II metabolism, and the active efflux at the blood–brain barrier 1. The most studied of these are the CYP2D6 and CYP2C19 genetic polymorphisms, which encode enzymes involved in phase I metabolism of most second-generation antidepressants, and commonly show functional variance between individuals 2,3. In fact, independent expert groups such as the Clinical Pharmacogenetics Implementation Consortium have developed dosing guidelines for serotonin selective reuptake inhibitors and tricyclic antidepressants exclusively on the basis of CYP2D6 and CYP2C19 genetic variation 4–6. These guidelines have contributed toward the ‘personalized psychiatry’ movement and have stimulated the development of several commercial pharmacogenetic-based decision support tools, all of which contain CYP2D6 and CYP2C19 to aid in the optimization of antidepressant prescribing practices 7. However, not all antidepressants are metabolized by CYP2D6 and CYP2C19, suggesting that pharmacogenetic-based decision support tools may need to include additional pharmacokinetic genes.

One such commercial pharmacogenetic-based decision support tool is CNSDose. In addition to genetic variation in CYP2D6 and CYP2C19, CNSDose also measures genetic variation in the UGT1A1 (UDP-glucuronosyltransferase 1A1) gene that encodes a phase II metabolism enzyme as well as two ATP-binding cassette (ABC) genes (ABCB1 and ABCC1) that encode efflux transporters that restrict permeability of drugs at the blood–brain barrier 8. These additional genes are particularly relevant to the pharmacokinetics of desvenlafaxine, the active metabolite of venlafaxine and a serotonin norepinephrine reuptake inhibitor. Desvenlafaxine is not subject to CYP450 metabolism 9, but is subject to UGT1A1 metabolism 10, and genetic variation in UGT1A1’s promoter region has been shown to affect its function 11. Furthermore, there is some evidence suggesting that the ABCB1 (also known as P-glycoprotein) efflux transporter moderates desvenlafaxine concentrations in the brain 12, and functional genetic variants in both ABCB1 and ABCC1 (also known as multidrug resistance-associated protein 1, MRP1) have been associated with antidepressants’ efficacy 13–21.

The clinical utility of CNSDose was examined recently in a 12-week double-blind randomized clinical trial. Individuals diagnosed with major depressive disorder (MDD) who received CNSDose-guided prescribing were 2.5 times more likely to achieve symptom remission compared with those receiving unguided prescribing 22. However, a limited proportion (6%) of participants in that trial were prescribed desvenlafaxine and as such the usefulness of the CNSDose tool for guiding desvenlafaxine dosing is unclear. Therefore, we carried out a 10-week, open-label, prospective cohort study of desvenlafaxine in MDD and compared the CNSDose predicted dose with the actual dose required for symptom remission to estimate the clinical validity and performance of the CNSDose for guiding desvenlafaxine dosing.

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Materials and methods


Participants were antidepressant-naive, self-identified Caucasian outpatients aged 18 years and older with a principal Diagnostic and Statistical Manual of Mental Disorders, 5th ed. (DSM-5) diagnosis of MDD (semistructured psychiatrist assessment) and a 17-item Hamilton Depression Rating Scale (HDRS) score greater than or equal to 18. Participants with a history of childhood trauma or active psychiatric diagnoses other than MDD were excluded, specifically those with anxiety disorder, adjustment disorder with depressed mood, persistent depressive disorder, and patients with a principal clinical diagnosis of a personality disorder. Additional exclusion criteria included pregnancy or breastfeeding, hepatic or renal impairments, coprescription of commonly prescribed UGT1A1 or ABCB1 inducers/inhibitors in the mood disorder care setting (i.e. valproate, carbamazepine, and lamotrigine) as well as St Johns wort, regular grapefruit juice consumption, and current smoking as these may influence appropriate dosing 23–27. Participants were allowed to have hypnotics (i.e. temazepam or zolpidem CR), but no other psychotropic medications were permitted. A total of 131 individuals were screened for eligibility criteria. Seven individuals did not fulfill the inclusion/exclusion criteria and an additional five failed to return for inclusion in the study, resulting in a final study sample of 119 participants.

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Study procedures

All participants received desvenlafaxine in an open-label manner during the 10-week study period. At baseline, age, sex, duration of the current depressive episode, and number of depressive episodes was recorded. Desvenlafaxine dose was increased, decreased, or left unchanged every 2 weeks (from baseline) on the basis of subjectively reported tolerability and clinical assessment of symptom improvement. Dose increases were limited to 50 mg increments every 2 weeks to mitigate potential adverse events (e.g. orthostatic hypotension) and the dosing range followed Australian pharmaceutical prescribing recommendations (50–200 mg/day) 28. Symptom severity was assessed with the HDRS at baseline and weeks 2, 4, 6, 8, and 10 postbaseline. Remission was defined as an HDRS score of 7 or less 29 by week 10 of the study. Physicians and the symptom rater were blinded to genotypes. All participants provided written informed consent and procedures were in accordance with the Declaration of Helsinki and were approved by an ethics committee at Deakin University, Australia.

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Pharmacogenetic interpretive report

A commercially available pharmacogenetic interpretive report (CNSDose; Baycrest Biotechnology Pty Ltd, Melbourne, Victoria, Australia) was ordered at the conclusion of the trial (week 10) for each participant using a proprietary algorithm described previously 22 (Fig. 1). The interpretive report predicted each participant’s optimal desvenlafaxine dose range as low (≤50 mg), medium (>50 and <150 mg), or high (≥150 mg) on the basis of genetic variation in ABCB1 (rs1045642), ABCC1 (rs212090), CYP2C19, CYP2D6, and UGT1A1 (rs8175347), albeit for this study, CYP2C19 and CYP2D6 genetic information was not used because of its lack of relevance to desvenlafaxine pharmacokinetics. DNA was extracted from participant self-administered buccal brush samples using the QIAamp DNA Mini Kit (QIAGEN Inc., Chadstone, Victoria, Australia). Genotyping was performed by PCR, followed by single primer extension and analysis on a Sequenom Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry 384-well genetic analysis system by Healthscope Molecular (Clayton, Victoria, Australia).

Fig. 1

Fig. 1

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Among remitters, performance of the CNSDose tool was estimated by comparing the predicted desvenlafaxine dosing range derived from the interpretive report with the actual desvenlafaxine dose required to achieve symptom remission. Concordance between received and predicted dose was estimated using two approaches: (a) the nonparametric Kendall’s τ-b (T b) correlation coefficient was used to compare the actual dose in milligrams with the dose range predicted by CNSDose and (b) the Cohen’s κ was used to compare the actual dose range with the CNSDose predicted dose range. Sensitivity, specificity, false positive, and false negative rates, as well as accuracy of the CNSDose predicted dose range relative to the actual dose range were also calculated. In addition, individual genes/variants comprising the CNSDose tool were compared with the actual dose required for remission to determine whether any one gene/variant performed better than the CNSDose tool. Among nonremitters who showed a 50% reduction in the HDRS score from baseline, exploratory analyses were carried out using the same analytical methods as those used in the remitted sample.

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After 10 weeks of desvenlafaxine treatment, 80% (n=95) of participants achieved symptom remission (Table 1). The average time to remission was 8.4 (SD=1.4) weeks. Those predicted to required a high dose had significant longer times (mean=9.3, SD=1.0 weeks) to remission compared with those in the low (mean=8.1, SD=1.3 weeks; Bonferroni’s P=0.01) and medium (mean=8.2, SD=1.4 weeks; Bonferroni’s P=0.006) predicted dose groups. Of the 95 participants who achieved symptom remission, 22 (23%) received a low dose; 53 (56%) received a medium dose; and 20 (21%) received a high dose. The CNSDose tool predicted that 22 (23%) required a low dose, 55 (58%) required a medium dose, and 18 (19%) required a high dose to achieve remission. Comparison of the actual and CNSDose predicted doses required for remission indicated strong concordance (T b=0.84, P=0.0001; κ=0.82, P=0.0001) (Fig. 2). In addition, the CNSDose predicted dose showed high sensitivity (85–92%), specificity (86–92%), and accuracy (89–96%) relative to the actual dose required for symptom remission (Table 2). Examination of the individual genes/variants included in CNSDose showed moderate concordance between the actual dose and predicted dose for ABCB1 (T b=0.54, P=0.0001; κ=0.40, P=0.0001) and ABCC1 (T b=0.48, P=0.0001; κ=0.25, P=0.001), but weak concordance for UGT1A1 (T b=0.14, P=0.149; κ=0.15, P=0.03). Sensitivity and specificity of each individual gene/variant were more variable and accuracy estimates were lower than observed for CNSDose (Table 3).

Table 1

Table 1

Fig. 2

Fig. 2

Table 2

Table 2

Table 3

Table 3

Among the 24 participants who did not achieve symptom remission by week 10, 42% (n=10) had a greater than 50% reduction in HDRS from the baseline. Among these nonremitted responders, two (20%) received a low dose, six (60%) received a medium dose, and two (20%) received a high dose. The CNSDose tool predicted that three (30%) patients would require a low dose, five (50%) patients would require a medium dose, and two (20%) patients would require a high dose. Similar to the remitter analysis, comparison of the actual and CNSDose predicted doses required for response indicated strong concordance (T b=0.87, P=0.004; κ=0.83, P=0.0001; Supplementary Fig. S1, Supplemental digital content 1, However, among the nonresponders (n=14), concordance was only moderate (T b=0.86, P=0.005; κ=0.39, P=0.006), although all nonresponders were prescribed the CNSDose predicted dose or a higher dose by week 10 (Supplementary Fig. S2, Supplemental digital content 2, Performance estimates (i.e. sensitivity, specificity, and accuracy) were not calculated within the nonremitted responder and nonresponder samples because of concerns of the reliability of such estimates, given the extremely small sample sizes 30.

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Our results tentatively suggest that the CNSDose tool may have clinical utility in guiding desvenlafaxine dosing in a subset of individuals with moderate to severe depressive symptoms. We found that clinically driven (unguided by CNSDose) dosing of desvenlafaxine needed, on average, 8 weeks to find the dose required for remission. Importantly, the CNSDose predicted dose had high concordance with the actual dose required for remission, suggesting that the use of CNSDose at the commencement of desvenlafaxine treatment has the potential to shorten the time to remission, particularly among patients requiring a high dose (≥150 mg). To our knowledge, no other genetically based desvenlafaxine dosing tools have been reported in the literature. However, genetic-based dosing tools for drugs other than antidepressants such as warfarin have reported comparable concordance between actual and predicted dose (Pearson’s r=0.54–0.67) 31.

Our results, in part, also support findings from a double-blinded, randomized clinical trial that showed that the CNSDose tool improved MDD outcomes among individuals prescribed a variety of first-generation and second-generation antidepressant pharmacotherapy, although few received desvenlafaxine 22. As noted above, desvenlafaxine is not subject to phase I CYP450 metabolism 9 and the evidence supporting ABCB1 and ABCC1 as regulators of desvenlafaxine concentrations in the brain is modest. Thus, two of the genes (CYP2D6 and CYP2C19) included in the CNSDose tool are not used to predict desvenlafaxine dosing and the relevance of ABCB1 and ABCC1 is uncertain because of conflicting results in the literature. Therefore, the underlying mechanism(s) by which CNSDose confers its predictive value would presumably involve the phase II hepatic UGT1A1 gene. However, our results suggest that UGT1A1 on its own has limited ability to predict the actual dose needed to achieve remission, suggesting that the predictive value of CNSDose requires a combinatorial approach. This notion is supported by a previous work by Assurex Health (Mason, Ohio, USA), developers of the GeneSight test, that showed that a combinatorial pharmacogenetic approach had superior predictive value compared with a single-gene approach 32, albeit single genes/variants not tested to date may prove to have stronger predictive value for particular drugs in particular settings.

Interestingly, UGT1A1, ABCB1, and ABCC1 are under-represented in the antidepressant pharmacogenetic literature 1 and are typically not included in commercially available pharmacogenetic gene panels. In fact, of the 22 commercially available pharmacogenetic tools relevant to psychiatry, UGT1A1 is included on two (CNSDose and PGxOne; Admera Health, South Plainfield, New Jersey, USA), ABCB1 on three (CNSDose; PGxPredict, Transgenomic, Omaha, Nebraska, USA; and HMNC Brain Health, Munich, Germany), and ABCC1 on one (CNSDose) pharmacogenetic gene panel 7. Arguably, the exclusion of these genes in previous antidepressant pharmacogenetic studies may, in part, influence the mixed findings in the literature to date. Further, commercial pharmacogenetic gene panels including these genes may be more clinical applicable, particularly for clinicians who prescribe desvenlafaxine.

The current study does have some notable limitations. The exclusion of patients with current or previous exposure to antidepressants, a history of childhood trauma and comorbidities, particularly personality disorders with dysthymia and adjustment disorder with depressed mood, may limit the application of these findings to larger real-world clinical settings – settings where comorbidity is very common. This is supported by a response and remission rate that was considerably higher than that observed in most antidepressant trials. In addition to these exclusion criteria, the high response and remission rate could, in part, be attributed to the use of doses up to 150 mg above the recommended effective dose (i.e. 50 mg) 33. In addition, dose adjustments were based on clinical judgment rather than specific criteria, which may hamper the reproducibility of our findings. Our findings are also limited to Caucasians of a relatively older and more chronic population than may be seen in other settings. Furthermore, our trial used an open-label design and as such study participants were not blinded to the dosage adjustments, which may have influenced the symptom rating. Thus, generalization of our findings should be performed with caution. It should also be noted that only a small selection of the known polymorphisms in ABCB1, ABCC1, and UGT1A1 were assessed. It is likely that other polymorphisms in these genes as well as other unexamined genes are relevant to desvenlafaxine pharmacokinetics. In fact, several ABCB1 polymorphisms have been linked to antidepressant efficacy 19 and four other UGTs (UGT1A3, UGT2B4, UGT2B15, and UGT2B17) have been implicated in the metabolism of desvenlafaxine, with genetic variation in UGT1A3 and UGT2B17 linked to the mRNA expression of these genes 34. In fact, one in every 10 of our participants did not respond to desvenlafaxine despite being prescribed the CNSDose predicted dose or higher dose. This may suggest that genetic variation in the above-mentioned genes may improve dose prediction or could indicate that nonresponse was a result of nongenetic factors such as adherence or tolerability. Unfortunately, measurements of treatment adherence and tolerability as well as desvenlafaxine blood levels were not available. Although typical adverse effects reported included diaphoresis, constipation, light-headedness, and agitation, no severe adverse reactions occurred. Furthermore, the CNSDose tool, unlike other currently available tools 7, does not include genes associated with the pharmacodynamics of antidepressants, which raises the question of whether the CNSDose dosing support tool represents a significant improvement over other currently available tools. Addressing this issue was beyond the scope of the current study, but future head-to-head trials with other tools are warranted. Importantly, personal (e.g. age, sex) and environmental factors (e.g. abuse history) were not included in the CNSDose dosing tool. Given the known role that personal and environmental factors play in antidepressant response, inclusion of such factors may further improve the performance of the tool 35.

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Our results serve as initial evidence for the clinical validity of CNSDose for the dosing of desvenlafaxine and, pending replication, suggest potential clinical utility. However, future pharmacogenetic-based dosing support tool development and evaluation that address the limitations of this study are warranted and are necessary before universal adoption into clinical practice.

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This study was supported in part by a 2012 Pfizer Australia NSR grant (A.S.). C.B. was supported by a University of Melbourne, Ronald Phillip Griffith Fellowship. M.B. is supported by an NHMRC Senior Principal Research Fellowship (1059660).

Authors’ contribution: A.S. designed the study, K.B. performed genotyping, and C.B. analyzed the data and wrote the first draft. D.M., C.N., K.B., M.B., and A.S. revised the first draft. All authors approved the final draft of the manuscript.

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Conflicts of interest

A.S. owns shares in the ABC Life Pty Ltd and Baycrest Technology Pty Ltd (developer of the CNSDose tool), and is on the speakers bureau for Servier, Australia. For the remaining authors there are no conflicts of interest.

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antidepressants; desvenlafaxine; major depression; personalized medicine; pharmacogenetics; pharmacogenomics; precision medicine

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