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Happy and Healthy: A 48 Year Old Woman With Major Depressive Disorder

Happy and Healthy: A 48 Year Old Woman With Major Depressive Disorder

Case Studies
A GeneSight® Psychotropic Case Study

Background

Behavioral health drug selection and dosing is a trial and error process that often leads to delayed response time, frustration and increased medical costs. There is a high degree of variability in response to behavioral health medications, some of which is due to individual genetics. Assurex Health utilizes its GeneSight proprietary CPGx® combinatorial pharmacogenomics technology to understand how unique inherited traits might influence a patient’s response to medication. GeneSight Psychotropic is a pharmacogenomic test developed to help healthcare providers select medications commonly prescribed to treat behavioral health conditions. There have been multiple studies published in peer reviewed journals addressing the clinical utility of GeneSight Psychotropic.1–4

The Patient

  • 48 year old woman presents with major depressive disorder, which she has had most of her life.
  • Her current medication trial has led to sexual side effects, fatigue, and weight gain. Her depression has only marginally improved.
  • Past medical history: no reported chronic illness.
  • Family history: no formal psychiatric diagnoses known in immediate family.
  • Social History: no reported substance abuse.
  • Previous medication trials: fluoxetine (Prozac®), paroxetine (Paxil®), and sertraline (Zoloft®).

GeneSight® Psychotropic Results

The patient’s genetic results for each of the genes were identified as:

CYP2D6 Extensive Metabolizer *1A/*41
CYP2C19 Extensive Metabolizer *1/*17
CYP2C9 Intermediate Metabolizer *1/*3
CYP3A4 Extensive Metabolizer *1/*1
CYP2B6 Extensive Metabolizer *1/*1
CYP1A2 Extensive Metabolizer -163 C>A – C/A, 5347C>T – C/T
SLC6A4 Reduced Response S/S
HTR2A Normal Activity A/A

PHARMACOGENOMIC INSIGHT

The gene that encodes the serotonin transporter is one of the most studied pharmacodynamic genes in psychiatric pharmacogenomics. There are two forms of the promoter region of this gene – “short” and “long”. Several meta-analyses have shown a poorer response to SSRIs for individuals who have one or two “short” variants5,6, as well as increased side effects7. For this individual case, the provider noted the presence of two “short” alleles, which can decrease efficacy of the medication the patient was on at the time of GeneSight testing as well as her three previous medication trials. The provider chose to switch to bupropion (Wellbutrin®) because it does not work primarily through the serotonergic pathway.

Pharmacogenomic-Informed Decision Making

  • The healthcare provider noted that escitalopram was found in the yellow (“Use with Caution”) category for this patient. It was labeled with the footnote: “Genotype may impact drug mechanism of action and result in reduced efficacy.”
  • With this information, the healthcare provider discontinued the escitalopram and switched to bupropion.

MEDICATIONS AT TESTING CHANGE IN MEDICATIONS
escitalopram (Lexapro®) 10mg daily Discontinued escitalopram
L-methylfolate (Deplin®) 15mg daily Continued l-methylfolate
Added bupropion (Wellbutrin®)
150mg daily
Added trazodone (Desyrel®)
25mg QHS prn insomnia

Conclusions

The patient’s depression improved and her side effects decreased. She found she had more energy and started losing weight. The healthcare provider reports “she is feeling happy and healthy”.

  1. Hall-Flavin DK, Winner JG, Allen JD, et al. Using a pharmacogenomic algorithm to guide the treatment of depression. Transl Psychiatry. 2012;2(March):e172. doi:10.1038/tp.2012.99.
  2. Hall-Flavin DK, Winner JG, Allen JD, et al. Utility of integrated pharmacogenomic testing to support the treatment of major depressive disorder in a psychiatric outpatient setting. Pharmacogenet Genomics. 2013;23(10):535-548. doi:10.1097/FPC.0b013e3283649b9a.
  3. Winner J, Allen JD, Anthony Altar C, Spahic-Mihajlovic a. Psychiatric pharmacogenomics predicts health resource utilization of outpatients with anxiety and depression. Transl Psychiatry. 2013;3(3):e242. doi:10.1038/tp.2013.2.
  4. Winner JG, Carhart JM, Altar CA, Allen JD, Dechairo BM. A prospective, randomized, double-blind study assessing the clinical impact of integrated pharmacogenomic testing for major depressive disorder. Discov Med. 2013;16(89):219-227. https://www.ncbi.nlm.nih.gov/pubmed/24229738.
  5. Karlović D. Serotonin transporter gene (5-HTTLPR) polymorphism and efficacy of selective serotonin reuptake inhibitors–do we have sufficient evidence for clinical practice. Acta Clin Croat. 2013;52(3):353-362. https://www.ncbi.nlm.nih.gov/pubmed/24558768. Accessed December 18, 2014.
  6. Porcelli S, Fabbri C, Serretti A. Meta-analysis of serotonin transporter gene promoter polymorphism (5-HTTLPR) association with antidepressant efficacy. Eur Neuropsychopharmacol. 2012;22(4):239-258. doi:10.1016/j.euroneuro.2011.10.003.
  7. Kato M, Serretti a. Review and meta-analysis of antidepressant pharmacogenetic findings in major depressive disorder. Mol Psychiatry. 2010;15(5):473-500. doi:10.1038/mp.2008.116.
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