Do Genetic Tests Help?
Are genetic tests for depression treatment worthwhile? Or is this an expensive technology that is not ready for routine use?
Peter Roy-Byrne, writing in NEJM Journal Watch seems to say that they aren’t worth it.
Although some clinicians may argue that such testing “can’t hurt and might help,” current psychopharmacological practice is complex, usually including combinations of multiple medications, and patients can have multiple comorbidities, both psychiatric and medical. Hence the meager available evidence, although promising, does not support routine use of these kits (although testing in some treatment-resistant patients might be reasonable). Even in medical specialties (e.g., oncology) that are much farther along in the understanding of genetic factors in illness pathophysiology, genetic testing to guide treatment is still in its infancy.
Since we’ve been using these tests for a couple of years in patients who have failed to or more previous treatments or who have demonstrated significant and unusual adverse effects to treatment we wanted to get our hands on the article and read it carefully to see if we agreed with Dr. Roy-Byrne’s summary.
The review in Lancet begins by distinguishing between genetic tests and clinical support tools. A genetic test, like the Amplichip from Roche Pharmaceuticals, determines a person’s genotype, but does not provide any guidance about what the results mean.
Given the complexity of the literature on genetics, most clinicians do not have the ability to make clinical decisions based on genetic test results.
A pharmacogenetic decision-support tool takes the results from a panel of genetic tests and provides a clinical interpretation of the results that can be used to guide treatment selection.
The first question in assessing the value of a decision-support tool, is the selection of genetic tests included in the panel.
In the review, the author identified a total of 46 genes included in one or more of the 21 decision support tools available worldwide. Of the 21 tools, 15 were available in the United States.
Which Genes to Evaluate?
The complete list of genes includes 18 pharmacokinetic genes (genes that influence how drugs are metabolized) which are colored blue below and 28 pharmacodynamic genes (genes that influence how the body responds to medications) which are colored in red. There was much greater consistency in the choice of pharmacokinetic genes (9 out of 18 were included in more than 20% of the assays – these are bolded below) than in the pharmacodynamic genes (5 out of 28 were in 20% or more of the assays, also bolded below).
ABCB1=ATP-binding cassette, sub-family B, member 1.
ABCC1=ATP-binding cassette, sub-family C, member 1.
ADRA2A=adrenoceptor α 2A.
AKT1=v-akt murine thymoma viral oncogene homologue 1.
ANK3=ankyrin 3.
BDNF=brain-derived neurotrophic factor.
CACNA1C=calcium channel, voltage-dependent, L type, α 1C subunit.
CACNG2=calcium channel, voltage-dependent, gamma subunit 2.
COMT=catechol-O-methyltransferase.
CYP1A2=cytochrome P450, family 1, subfamily A, polypeptide 2.
CYP2B6=cytochrome P450, family 2, subfamily B, polypeptide 6.
* CYP2C9=cytochrome P450, family 2, subfamily C, polypeptide 9.
** CYP2C19=cytochrome P450, family 2, subfamily C, polypeptide 19.
** CYP2D6=cytochrome P450, family 2, subfamily D, polypeptide 6.
CYP3A4=cytochrome P450, family 3, subfamily A, polypeptide 4.
CYP3A5=cytochrome P450, family 3, subfamily A, polypeptide 5.
DDIT4=DNA-damage-inducible transcript 4.
DRD2=dopamine receptor D2.
DRD3=dopamine receptor D3.
* DPYD=dihydropyrimidine dehydrogenase.
EPHX1=epoxide hydrolase 1.
F2=coagulation factor II.
F5=coagulation factor V.
FHSD1=facio-scapulo-humeral dystrophy 1.
GRIA3=glutamate receptor, ionotropic, AMPA 3.
* G6PD=glucose-6-phosphate dehydrogenase.
* GRIK4=glutamate receptor, ionotropic, kainate 4.
HLA-A=major histocompatibility complex, class I, A.
** HLA-B=major histocompatibility complex, class I, B.
HTR2A=serotonin receptor 2A.
HTR2C=serotonin receptor 2C.
* IFNL3=interferon, lambda 3.
LPHN3=latrophilin 3.
MTHFR=methylenetetrahydrofolate reductase.
NAT2=N-acetyltransferase 2.
OPRM1=opioid receptor, mu 1.
RPTOR=regulatory associated protein of MTOR, complex 1.
SLC6A4=serotonin transporter.
* SLCO1B1=solute carrier organic anion transporter family, member 1B1.
SULT4A1=sulfotransferase family 4A, member 1.
* TPMT=thiopurine S-methyltransferase.
UGT1A1=UDP glucuronosyltransferase 1 family, polypeptide A1.
UGT1A4=UDP glucuronosyltransferase 1 family, polypeptide A4.
UGT2B15=UDP glucuronosyltransferase 2 family, polypeptide B15.
UGT2B7=UDP glucuronosyltransferase 2 family, polypeptide B7.
* VKORC1=vitamin K epoxide reductase complex, subunit 1.
Blue color – pharmacokinetic genes. Bolded meant included in more than 20% of tools.
Red color – pharmacodynamic genes. Bolded if included in more than 20% of tools.
* Single star if the evidence supporting use met the highest quality.
** Double star if the evidence was of the highest quality and relevant to many psychotropics routinely used.
Effectiveness of Pharmacogenomic Tests
For most of the panels there was limited evidence and not much evidence of an interest in collecting this evidence. However three of the tools had evidence supporting them, and this is summarized below.
Three tools (GeneSight, Genecept, and CNSDose), currently available only in the USA or Australia, are building a relatively strong evidence base for pre-emptive (ie, before first prescription) use in psychiatry via clinical trials or cost-effectiveness studies…
To the list of three with supporting evidence discussed in the Lancet article, we have added a newcomer (Tempus Pro) because it specifically implements the recommendations of the Clinical Pharmacogenetics Implementation Consortium (CPIC®) . CPIC is a group of scientists that carefully reviews all of the evidence about genetic tests and potential clinical implications. The goal is to apply a rigorous scientific analysis to the thousands of articles on the subject so that associations that are well supported are highlighted and those with suggestive but not conclusive evidence are identified as well. We have found this approach to be very useful.
A recent study (Brown, et al 2020) highlighted the importance of considering the interactions between genes when providing recommendations to practitioners. Combinatorial pharmacogenomic testing was found to improve care whereas tests that identified only single gene – drug interactions did not improve care. Combinatorial pharmacogenomic testing considers the net effect of several gene variants and provides the practitioner with an overall recommendation. Most of the tests in this set do not consistently integrate results in that way, unfortunately.
Tempus Pro
Tempus Pro distinguishes itself from the other tools in three ways:
- Tempus Pro does a complete genome analysis (something like 23 and Me) whereas all of the other companies just study a small number of genes.
- The data from this analysis is presented in a way that implements the CPIC guidelines. Strong associations are listed first and associations with weaker evidence are noted in a portion of the report entitled “Emerging Evidence.”
- Tempus Pro also provides patients, and clinicians, with tools for monitoring the results of medication trials.
Genesight
The GeneSight tool was examined in two prospective cohorts, one double-blind, randomised clinical trial (RCT), two cost-savings studies, and one cost-effectiveness study.
The two prospective cohort studies recruited patients (n=4416 and n=16515) with major depressive disorder (MDD) and showed between two and four times improvement in depressive symptoms among patients receiving treatment guided by GeneSight compared with patients receiving unguided treatment.
In an independent double-blind RCT of 49 MDD patients, five (20%) of 26 patients who received treatment guided by GeneSight achieved symptom remission (ie, Hamilton Depression Rating Scale-17 score less than or equal to 7) compared with 8% of patients receiving treatment as usual. Although this equates to a 2·5 times difference in remission rates, nine patients would need to be genotyped for one patient to remit. This number needed to genotype might be acceptable given findings from cost-saving and cost-effectiveness studies of the GeneSight decision-support tool.
People who received GeneSight-guided treatment saved an estimated $1035 in total medication costs and $5188 in direct and indirect health-care costs compared with those receiving treatment as usual.
Another meta-analysis of the Genesight data was presented at the American Society of Clinical Psychopharmacology Annual Meeting in 2020.
The researchers evaluated GeneSight Psychotropic’s impact on treatment outcomes among patients with MDD who had one or more prior medication failures. They identified two-arm, prospective studies that evaluated the clinical utility of this test and included patients aged 18 years or older diagnosed with MDD who had one or more prior medication failures. Daut and colleagues analyzed 1,556 patients from two open-label studies and two randomized controlled trials. Studies used the 17-item Hamilton Depression Rating Scale to assess symptom improvement, response and remission. The researchers used a random effects model to calculate the pooled mean effect of symptom improvement and pooled relative risk ratio of response and remission, and they performed sub-analyses according to study type.
Results showed significant improvements in outcomes for patients with MDD whose care was guided by GeneSight compared with unguided care. Daut and colleagues noted significant heterogeneity in effect size across studies, but it was moderate for symptom improvement and was not significant for response and remission. Symptoms and response improved significantly in the GeneSight Psychotropic guided-care group vs. the unguided care group when the researchers assessed the open-label studies separately. Moreover, all three evaluated outcomes improved significantly in the guided-care group vs. the unguided care group when the researchers restricted the analysis to randomized controlled trials.
“These findings are in alignment with two other recent meta-analyses that found a variety of pharmacogenetic decision support tools were significantly associated with achieving remission in MDD treatment compared with treatment as usual,” Daut told Healio Psychiatry. “However, the tests evaluated in these meta-analyses vary considerably in terms of genes included on the panel, genotype-to-phenotype conversion and algorithm. The present study provides robust evidence supporting the clinical utility of GeneSight Psychotropic.”
Genecept
The Genecept tool was evaluated in a large (n=685) 3-month, naturalistic, unblinded, prospective cohort as well as in a retrospective adherence and health-care costs study. The naturalistic cohort study showed significant decreases in depression and anxiety symptoms as well as decreases in side-effects. However, a treatment as usual comparator was not included, inhibiting any firm conclusions about Genecept’s effectiveness. The retrospective study examined health claims data in two independent cohorts and found those receiving Genecept guided treatment had a 6% greater increase in medication adherence compared with individuals receiving treatment as usual and demonstrated a relative saving of 9·5% ($562) in outpatient costs over a 4-month period.
CNSDose
The CNSDose tool was examined in a 12-week, double blind RCT in 148 white adults with MDD. Individuals who received CNSDose-guided prescribing remitted 2·5 times more than those receiving unguided prescribing. The number needed to genotype was only three, suggesting the CNSDose tool might be more cost-effective than GeneSight. However, to our knowledge no head-to-head comparisons of these tools or any others have been conducted.
Meta-Analyses of Randomized Controlled Trials
A review published in the journal Pharmacogenomics in 2019 summarizes the state of the data so far. Five randomized controlled trials were identified in the literature. A total of 1737 patients were included in the trials.
All of the studies looked at patients who had failed at least one antidepressant medication trial.
The studies looked at very different genes, but two genes were included in all the studies: CYP2D6 and CYP2C19, the only two genes with dosing guidelines for antidepressants.
Risk of Bias
In all of the studies the clinician was not blinded to whether or not the patient was in the active (pharmacogenetic guidance) arm of the study. In other words, there are no double-blind controlled trials.
All of the studies were industry supported.
Findings
The trials provided supportive evidence of a beneficial effect of pharmacogenomic guided antidepressant treatment on the likelihood of achieving remission of depressive symptoms (not the likelihood of achieving some response). Given the small number of patients studied and the lack of double-blind controlled trials these findings have to be regarded as preliminary. We need a good non-industry supported study.
Summary of Our Clinical Experience
We have had experience with GeneSight and Genecept and have found that using these tools provides information that is useful in about a quarter of the patients we test – patients who have failed two or more antidepressants (or psychotropic agents) or have had extreme and unusual side effects to medications.
Data from the STAR*D NIMH sponsored trial on the treatment of depression suggests that around 15% of patients who have failed two trials will respond to a third agent (or augmentation), and it is this group of patients who were shown to preferentially respond to TMS as opposed to another medication trial (TMS costs around 30,000$ for a course of treatment) so it seems reasonable to use these tools (which cost between 1500 and 3500$) to guide selection of a medication, if the tools can significantly increase the remission rate.
References
NEJM Journal Watch – The Pharmacogenetic Tool Kit to Guide Depression Treatment Decisions?
Bousman CA, Hopwood M. Commercial pharmacogenetic-based decision-support tools in psychiatry. Lancet Psychiatry. 2016 Jun;3(6):585-90. doi: 10.1016/S2215-0366(16)00017-1. Epub 2016 Apr 25. Review. PubMed PMID: 27133546.
“Genesight Pharmacogenomic Test Improves Outcomes in Treatment Resistant Depression,” Healio. 2020
Bousman, Chad A et al. “Pharmacogenetic Tests and Depressive Symptom Remission: a Meta-Analysis of Randomized Controlled Trials.” Pharmacogenomics 20.1 (2019): 37–47. Web.
For More Information
ABCB1 Gene Predicts Antidepressant Response
Genetic Testing for Depression Drugs
Clinical Pharmacogenetics Implementation Consortium (CPIC®)
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