Dr. Kung is assistant professor of psychiatry and consultant in psychiatry, and Dr. Li is psychiatry resident, both in the Department of Psychiatry and Psychology at the Mayo Clinic in Rochester, Minnesota.

Disclosures: The authors report no affiliation with or financial interest in any organization that may pose a conflict of interest.

Please direct all correspondence to: Simon Kung, MD, Mayo Clinic, 200 First St SW, Rochester, MN 55905; Tel: 507-255-7184; Fax: 507-284-3933; E-mail: kung.simon@mayo.edu.


Pharmacogenomic testing is clinically available to assist with medication selection in treatment-resistant depression (TRD). Common tests include the cytochrome P450 (CYP) 2D6 and 2C19 enzymes, the serotonin transporter gene, and the serotonin receptor gene. There are practical recommendations of interventions which can be supported from the literature. Identification of a CYP2D6 poor metabolizer would result in recommending a lower dosage of medications metabolized by CYP2D6, or avoiding the use of CYP2D6 medications. Identification of a serotonin transporter gene short/short genotype suggests more adverse effects, less response, or longer time to respond to selective serotonin reuptake inhibitors (SSRIs), and may warrant focusing treatment with non-SSRIs. Numerous other genotypes have been studied but with mixed implications. The use of pharmacogenomic testing can help the clinician rationalize medication selection and reduce the numerous medication combinations used in TRD. Further research and clinical experience will continue to define the clinical utility of this testing.

Focus Points

• Pharmacogenomic testing can be clinically used in guiding medication selection for treatment-resistant depression.
• Cytochrome P450 metabolizer status can guide whether the clinician uses medications metabolized by a specific pathway or uses different dosing ranges.
• The serotonin transporter gene short/short genotype has been associated with adverse reactions and less response to selective serotonin reuptake inhibitors (SSRIs), thus clinicians might choose a non-SSRI for such patients.
• Further research and clinical practice will help define the utility of pharmacogenomic testing.



Treatment-resistant depression (TRD) is a common occurrence in clinical practice. Depending on the operational definitions, studied populations and analytic methods used, prevalence ranges from 15% to 80%.1 Results from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study suggest that ~50% of “real world” patients with psychiatric and medical comorbidity who meet criteria for major depressive disorder (MDD) fail to achieve remission, even after four carefully monitored sequenced treatments.2

The most commonly adopted definition of TRD evolved from >15 historic definitions is “major depression with poor response to two adequate trials with different classes of antidepressants, given in an adequate dose for sufficient time.”3 Staging models of TRD reflect the severity of treatment resistance, factoring in the number of failed trials and intensity or optimization of each trial.4

Numerous strategies are used in TRD, including psychotherapy, pharmacotherapy using augmentation strategies, and brain stimulation techniques such as transcranial magnetic stimulation, vagus nerve stimulation, and electroconvulsive therapy. Deep brain stimulation and magnetic seizure therapy are investigational treatments.5 However, the most common treatment for TRD is the selection of alternative antidepressant trials. Algorithms have been developed to guide pharmacotherapy.6

Given the trial-and-error nature of medication treatment for TRD, a method which could decrease the number of trials needed to achieve remission would be valuable. There has been much research into the use of genotyping to predict drug metabolism (pharmacokinetic) and genotyping to determine serotonin gene variants (pharmacodynamic) associated with drug response. Both strategies provide information that can increase the likelihood that a medication trial will be helpful.

This article reviews our current knowledge of pharmacogenomic testing designed to predict antidepressant adverse effects and response. Clinical implications for the care of patients with MDD and TRD are discussed.



Cytochrome P450 (CYP) enzymes are involved with the metabolism of most medications, including antidepressants. Some medications, such as codeine and tamoxifen, are pro-drugs which require activation by CYP enzyme. Several CYP isoenzymes are involved with antidepressant metabolism, mainly the 2D6 and 2C19, and to a lesser extent, 2C9 and 1A2.7 Polymorphisms in the genes that code for these enzymes result in varying drug levels in an individual. The phenotypes typically range from a “poor” metabolizer (PM) with little or no enzyme activity, to an “intermediate” metabolizer with less than normal activity, to the “extensive” normal type, and to the “ultra-rapid” metabolizer (UM) with greatly increased activity. In patients of European ancestry, the distribution for CYP2D6 is ~10% PMs and 2% to 3% UMs. The phenotype frequencies for patients of European ancestry for CYP2C19 are ~3% PMs and 4% UMs. Drug metabolizing enzyme gene polymorphisms play a role in the interethnic variations in drug metabolism given that up to 20% of patients of Asian ancestry are CYP2C19 PMs.8 Generally, poor metabolizers experience more side effects and ultra-rapid metabolizers are less likely to respond to treatment with an antidepressant that is a substrate of the enzyme.

A clinical laboratory test for CYP2D6 genotyping has been available since 2003. Subsequently, clinical laboratory tests for CYP enzymes 2C19, 2C9, and 1A2 have become available. CYP 3A4 is an important enzyme involved in medication metabolism as well, but does not have many polymorphisms of functional significance.9

A current problem is that there is not a single standard for predicting the phenotype based on genotype. Consequently, different laboratories provide differing phenotype interpretations for the same genotype. This problem is compounded because different laboratories analyze for different sets of alleles. Another less problematic issue is that new alleles continue to be identified.10


Associations with Plasma Concentrations, Adverse Effects, and Treatment Response

The consequence of the CYP genotype on the pharmacokinetics of many antidepressants has been demonstrated. Desipramine,11 venlafaxine,12,13 nortriptyline,14 doxepin,15 imipramine,16 paroxetine,17 fluvoxamine,18 fluoxetine and paroxetine,19 and amitriptyline and nortriptyline20 have significant correlations between CYP2D6 genotypes and their plasma concentrations. However, the implications of these variable serum concentrations are not completely correlated with side effects or therapeutic response.11,13,21-23

CYP2C19 genotypes have been associated with metabolism of imipramine,24 sertraline,25,26 citalopram/escitalopram,27 and clomipramine.28 A study combining genotypes 2D6, 2C19, and 2C9 found significant influence of the 2D6 genotype, minor influence of the 2C19 genotype, and no influence of the 2C9 genotype on plasma concentrations of citalopram, paroxetine, fluvoxamine, and sertraline.29

Many studies show that poor and intermediate 2D6 metabolizers have been associated with more adverse effects to CYP2D6-dependent antidepressants.30-35 However, in some reports the risk for adverse effects have not reached statistical significance.13,36-38 These negative studies have had issues related to comprehensiveness of genotyping and sample size.

There are mixed reports of CYP2D6 genotyping associations with antidepressant response. UMs have been associated with non-response to antidepressants in several studies.17,31,39 However, in a retrospective study40 of 81 responders and 197 non-responders, CYP2D6 metabolizer status was not associated with either response or remission rates.


Practical Recommendations

Pharmacokinetic genotyping provides probabilistic estimates of side effects and efficacy in patients with PM and UM phenotypes. Its usefulness includes guiding certain antidepressant dosage and understanding and avoiding drug-drug interactions (DDIs), especially when 34% of patients in a primary care setting are on an antidepressant and ≥3 medications.41 The current standard clinical practice in using tricyclic antidepressants (TCAs) is to dose until reaching a pre-determined “therapeutic” serum drug level. For newer antidepressants, clinicians sometimes titrate the dose until a patient experiences benefit or uncomfortable side effects. Consequently, patients can be placed on dosages exceeding the manufacturer’s recommended usual dosages. The determination that a patient is an ultra-rapid metabolizer provides a rationale for a patient’s capacity to tolerate higher than recommended doses. Conversely, clinicians should be more cautious with substrate medications if a patient is not able to produce sufficient active enzyme necessary for the metabolism of the drug.

Pharmacokinetic reviews have suggested decreasing by ~50% the dosages of TCAs and risperidone in patients who are CYP2D6 PM, and using higher dosages of a TCA in UM.42-45 More specific dose adjustments have been proposed for the antidepressants imipramine, desipramine, nortriptyline, clomipramine, paroxetine, venlafaxine, amitriptyline, buproprion, citalopram, sertraline, and fluvoxamine, as well as the antipsychotics perphenazine, thioridazine, olanzapine, aripiprazole, haloperidol, and risperidone.44 Another review41 estimates the potential for antidepressants to be the perpetrator of a DDI mediated by effects on CYP2D6 enzymes as substantial (>150%) for paroxetine and fluoxetine; moderate (50% to 150%) for duloxetine; and mild (20% to 50%) for venlafaxine, sertraline, citalopram, and escitalopram.

Fortunately, for the newer antidepressants, clinically significant drug interactions from CYP inhibition are less frequent.46 Psychotropic medications which are not metabolized by CYP2D6 have been developed (eg, desvenlafaxine).

There is one psychotropic medication for which the Food and Drug Administration has made a firm recommendation for genetic testing (HLA-B*1502). Carbamazepine in patients with Asian ancestry with this variant have been shown to be at increased risk of life-threatening skin reactions such as Stevens-Johnson syndrome.47



In addition to CYP enzyme genes, several genes in the serotonin pathway have been studied for their potential role in the susceptibility to depression, adverse effects, and treatment response to psychotropic medications. Commonly studied genes include the 5-HTTLPR promoter region of the serotonin transporter gene (SLC6A4) and the serotonin receptor gene subtypes 5-HT2A and 5-HT2C.


Adverse Effects of Psychotropic Medications

Several studies reported that 5-HTTLPR L alleles are associated with fewer selective serotonin reuptake inhibitor (SSRI) side effects.48 In a study49 comparing the SSRI paroxetine versus the non-SSRI mirtazapine, patients with 5-HTTLPR S alleles had worse side effects with paroxetine but tolerated mirtazapine better. A possible interaction of 5-HTTLPR L allele and oral contraceptives associated with sexual side effects has also been reported.50 5-HTTLPR S alleles have also been associated with antidepressant-induced mania.51

The serotonin receptor genes 5-HT2A and 5-HT2C have also been associated with psychotropic adverse effects. Paroxetine side-effect severity and discontinuation was associated with the number of 5-HT2A C alleles.38 Various 5-HT2A polymorphisms have also been associated with fewer SSRI side effects including gastrointestinal side effects52 or increased side effects such as sexual side effects.53 An 5-HT2C polymorphism was reported to be protective against significant antipsychotic-induced weight gain54 and associated with tardive dyskinesia, although the association was not significant.55


Response to Treatment

A 2007 meta-analysis of 5-HTTLPR and SSRI treatment reported that the L allele is associated with a better response independent of ethnic differences, and patients with the S/S genotype take >4 weeks to respond and have difficulties reaching remission.56 While there is conflicting data related to the effects of SLC6A4 in patients of African-American or Hispanic ancestry,57,58 an analysis of STAR*D patients restricted to the white non-Hispanic subgroup confirmed an association of SLC6A4 activity level and remission with citalopram.59

Ethnic and gender differences can be seen in various reports. A 2009 study60 of Mexican Americans reported a SLC6A4 haplotype associated with remission using desipramine or fluoxetine. Korean patients with the SLC6A4 S/S genotype responded better to mirtazapine compared to those with the L/L or L/S genotype.61 Chinese patients with the L/L genotype experienced better clinical response to SSRIs compared to serotonin norepinephrine reuptake inhibitors.62 Regarding gender, in women with the SLC6A4 S/S genotype, lower efficacy was reported for SSRIs as well as non-SSRIs.63,64

Other reports of SLC6A4 associations with antidepressant response are interesting. In geriatric patients, SLC6A4 was reported to interact with serum paroxetine levels to influence antidepressant response.65 In a positron emission tomography imaging study, higher serotonin transporter occupancy was associated with clinical improvement with paroxetine in patients with L/L.66 In patients with S/S genotype, antidepressant augmentation with pindolol and lithium was associated with better response.67,68

For 5-HT2A, meta-analysis of antidepressant treatment response showed a contribution to better response with a specific polymorphism, particularly in Asians.52 In the STAR*D data,69 participants who were homozygous for the 5-HT2A A allele of a newly identified variant (rs7997012) had an 18% reduction in absolute risk of having no response to treatment, compared with those homozygous for the other allele. The A allele was over six times more frequent in white than in black participants, and treatment was less effective among black participants.


Practical Recommendations

Pharmacodynamic reviews of SLC6A4 suggest that patients with the S/S genotype do not respond as well to SSRI antidepressants, and may experience more side effects.48,52,70 Thus, a practical approach is to use a non-SSRI in a patient who is SLC6A4 S/S or S/L. A decision analytic model of pre-treatment testing for SLC6A4 concluded that such testing would result in more patients experiencing remission earlier in treatment.71

Knowledge of 5-HT2A alleles might suggest the clinician try citalopram, or if generalization is possible, an SSRI, in patients who are homozygous for the 5-HT2A A allele.69 If a clinician is making a decision whether to augment an antidepressant with an antipsychotic, results of the 5-HT2C might not support an antipsychotic if the patient has the allele associated with increased weight gain with antipsychotics.


Pharmacogenomics in the Perspective of TRD

TRD represents a major public health concern, since it is associated with higher rates of relapse, poorer quality of life, deleterious personal and societal economic ramifications, and increased mortality rates.72,73 In the biopsychosocial model of depression treatment, the biologic standard of care is the medication trial. Numerous algorithms are available for guidance.6,74 Using the example of the Texas Medication Algorithm Project (TMAP), given that each adequate medication trial is ~2 months, and if a patient tries at least 3 SSRIs and 3 non-SSRIs, that would already be 1 year of medication trials. For each antidepressant, augmenting with two different medications such as a mood stabilizer or an antipsychotic for each of the antidepressants tried increases each medication trial by a few more months, and one can appreciate how patients might go through 4 or 5 years of medication trials. By incorporating genotyping results into an algorithm such as TMAP, one should be able to reduce the number of medication trials needed.

Genotyping can also explain some of the adverse events associated with medications. Consider the case example of a 58-year-old Caucasian woman with depression who has not responded to citalopram and bupropion. The clinician selects nortriptyline as the next medication trial, and titrates to a therapeutic dose based on serum level. As her depression is not improving, the clinician adds fluoxetine, noting that the combination of an SSRI and a TCA is listed in Stage 3 of the TMAP. Two weeks later, the patient experiences lethargy and unsteadiness, to the point of falling and sustaining a wrist fracture. A nortriptyline serum level shows it is now in the toxic range, and both medications are held. Two weeks later, the patient returns to her baseline state. Genotyping is obtained, and reveals that the patient is an intermediate metabolizer of CYP2D6. The explanation in this situation is that nortriptyline and fluoxetine are both metabolized by CYP2D6, and additionally, fluoxetine is a strong inhibitor of 2D6. The patient was already an intermediate metabolizer, and by inhibiting that state, effectively converted the patient to a poor metabolizer, which resulted in the nortriptyline toxicity and side effects. Adverse effects are common reasons for switching antidepressants, which leads to more medication trials and a sense of medication “resistance.” Understanding and predicting adverse effects can improve the patient’s experience and compliance with medications, leading to a better outcome.

A patient’s genetic makeup is only one of the many complex factors involved in his or her response to antidepressants. Other factors include diet, caffeine, nicotine, age, medical illness, and concurrent medications. In addition, appropriate attention should be given to the psychological and social stresses aspects of the patients’ illness. Psychotherapies such as cognitive behavioral therapy and acceptance and commitment therapy can be helpful.75,76 Patients with aversive social contexts for their depression also have consistently lower remission rates, indicating the need for social interventions.77



Depression can be difficult to treat, especially with its biopsychosocial contributors. From the biologic perspective, clinicians rely on medication trials which might span several years because of the large number of antidepressants available and the various augmentation strategies. Patients understandably become frustrated with such treatment techniques and look towards methods which might help them identify the optimal medication or combination to treat their depression.

There has been much research into whether pharmacogenomic testing might provide sufficient clinical information to guide psychotropic medication choices and thus decrease the trial and error approach of medication management. With regards to pharmacokinetic testing, specifically CYP2D6 and CYP2C19, identifying poor metabolizers in order to help with medication selection and dosage adjustments can be helpful. In patients presenting with numerous side effects, it can also confirm whether a patient is experiencing side effects because of metabolizer status. From the pharmacodynamic perspective, many genes have been studied, with the most common being the serotonin transporter and serotonin receptor genes. Patients of European ancestry with a serotonin transporter gene S/S or S/L genotype seem to not tolerate or not respond as well to SSRIs compared to patients with the L/L genotype. Various serotonin receptor gene alleles have also been associated with increased or decreased response to SSRIs as well as side effects.

The response of an individual to antidepressant treatment is not only influenced by the limited number of genes that are currently tested. Genome-wide association studies (GWAS) to investigate the entire genome without focus on a specific hypothesis and genomic area represent a new and promising methodologic strategy. A recent GWAS found remission associated with the number of predicted “response” alleles, and supported that antidepressant response emerges from a multitude of genetic variants.78,79 Further research is predicted to reveal additional clinical applications to guide treatment.  PP


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