Journal of Psychosocial Nursing and Mental Health Services

Psychopharmacology Supplemental Data

Genetic Testing for Psychopharmacology: Is It Ready for Prime Time?

Laura G. Leahy, DrNP, APRN, PMH-CNS/FNP, BC

Abstract

This article has been amended to include factual corrections. To read the erratum, click here. The online article and its erratum are considered the version of record.

Genetic testing in psychiatric practice may be a beneficial adjunct to the nursing toolbox of considerations used to improve patient outcomes. Since 2004, the psychiatric community has used genotyping to personalize medication options for their patients. Although not a definitive or exact science, pharmacogenetic testing for psychopharmacological treatment options offers nurses and their patients insights into potential treatments that will reduce the current trial-and-error prescribing practices and more quickly improve patients' quality of life. The current article guides nurses through the process of conducting genetic testing, interpreting the results, and applying the results in clinical practice using a fictitious case example. [Journal of Psychosocial Nursing and Mental Health Services, 55(3), 19–23.]

Abstract

This article has been amended to include factual corrections. To read the erratum, click here. The online article and its erratum are considered the version of record.

Genetic testing in psychiatric practice may be a beneficial adjunct to the nursing toolbox of considerations used to improve patient outcomes. Since 2004, the psychiatric community has used genotyping to personalize medication options for their patients. Although not a definitive or exact science, pharmacogenetic testing for psychopharmacological treatment options offers nurses and their patients insights into potential treatments that will reduce the current trial-and-error prescribing practices and more quickly improve patients' quality of life. The current article guides nurses through the process of conducting genetic testing, interpreting the results, and applying the results in clinical practice using a fictitious case example. [Journal of Psychosocial Nursing and Mental Health Services, 55(3), 19–23.]

Exploring psychotherapeutic issues and agents in clinical practice

Unlike medical ailments, psychiatric disorders do not have easily identifiable biological markers to confirm a diagnosis. Thus, determining which psychotropic medication may be most beneficial to a patient is often reduced to trial-and-error prescribing, taking weeks to determine whether therapeutic benefit will occur and/or if side effects will persist. To date, there are no definitive laboratory tests or imaging scans that prove conclusively what disorder a patient may be experiencing. Yet, it is widely known that heredity, otherwise known as genetics, plays a role in psychiatric disorders. Family studies published by Lohoff (2010) show that among first-degree relatives, there is a two- to three-fold increase in the lifetime risk of developing major depressive disorder. Similarly, according to Smoller and Finn (2003), the heritability of bipolar disorder among twins is between 60% and 80%. With this in mind, genetic testing to assist in the selection of psychotropic medication therapies may prove beneficial to those experiencing psychiatric symptoms.

Background on Genetics

Although human beings are unique individuals, 99.9% of their genetic code is shared with other human beings, and approximately 96% of their DNA is shared with chimpanzees and approximately 60% with bananas (National Human Genome Project, 2002). In addition, <10% of human beings' genetic code offers regulatory information (Bojrab, 2013) on how the body and brain are supposed to think, feel, and behave. And, because only 0.1% of their DNA is unique, it is the allele, a variant form of a given gene inherited from each parent, that provides an individual's distinct differences. The genetic variants or polymorphisms are precisely what genetic testing offers to psychiatric practitioners to guide pharmacological decision making.

Genetic Testing in Psychiatric Practice

So how does the testing of patients' DNA help in the pharmacological management of psychiatric symptoms? According to Frueh et al. (2008), more than 25% of all common medications have genetic information that can be tested and used to personalize medical treatment. Genotyping of genetic variants is not a new science; it has been used to identify genetic polymorphisms in psychiatry in both the United States and Europe since 2004 (GENDEP, 2008; Kaplan, 2011). Genetic testing in psychiatric nursing practice is used to determine variations among genetic alleles to help aid in identifying psychopharmacological treatments. Genetic testing uses a salivary sample of the patient's unique DNA, which is invariable from birth to death and unaffected by medications or other treatments. As no single gene allele variant taken in isolation offers definitive information regarding the medication therapy that will prove effective without adverse events, the prudent nurse must explore the interactions of multiple genetic polymorphisms, the patient's clinical and medical histories, as well as current and prior medication trials, including over-the-counter agents and complementary and alternative treatments.

Currently available pharmacogenetic testing for psychiatric purposes explores the interactions of pharmacokinetics (i.e., how the body affects a drug and drug metabolism via the liver's cytochrome P450 [CYP450] system), and pharmacodynamics (i.e., how the drug affects the body). This interplay can offer information on the patient's potential response to psychopharmacological therapy as well as information for drug dosing and frequency of medication administration. The most commonly tested pharmacokinetic and pharmacodynamic genes applicable to psychiatric practice are presented in Table A (available in the online version of this article).


            Commonly Tested Pharmacodynamic & Pharmacokinetic Genes
            Commonly Tested Pharmacodynamic & Pharmacokinetic Genes
            Commonly Tested Pharmacodynamic & Pharmacokinetic Genes
            Commonly Tested Pharmacodynamic & Pharmacokinetic Genes
            Commonly Tested Pharmacodynamic & Pharmacokinetic Genes

Table A:

Commonly Tested Pharmacodynamic & Pharmacokinetic Genes

Conducting Pharmacogenetic Testing in Psychiatric Nursing Practice

To illustrate the use of psychiatric genotyping in clinical practice, a hypothetical case example is presented.

Case Study

Jane is a 38-year-old married, White female who has been treated for depression and anxiety since the age of 22. She has a medical history of migraine headaches, borderline obesity, and post-partum depression following the birth of her son 5 years ago. She has no known medication allergies. She has had no surgeries, seizures, head traumas, or concussions.

Jane's past psychotropic medications include:

  • Fluoxetine (Prozac®) up to 80 mg daily—“It just stopped working after 4 years.”
  • Venlafaxine (Effexor® XR) up to 300 mg daily—“My blood pressure started to increase.”
  • Paroxetine (Paxil®) up to 40 mg daily—“I couldn't stand the ‘brain zaps’ when I missed a dose.”
  • Alprazolam (Xanax®) 1 mg three times per day—“I would take more so my doctor cut me off.”
  • Quetiapine (Seroquel®) 50 mg three times per day—“I gained weight because I would wake up and eat at night and became pre-diabetic.”

Jane's current symptoms include: difficulty falling and staying asleep, low motivation, feeling fatigued, depressed mood, irritability, headaches occurring two to three times per week, and decreased attention and concentration. Jane has also started drinking two glasses of wine per night on weeknights and “more on the weekends…I just feel better and I sleep, but I'm still tired.” She has not previously shared her tendency to abuse alcohol. She does not like the way she feels and wants to stop drinking.

Jane's current medications include:

  • Sertraline (Zoloft®) 250 mg daily—“It helps a little, but I think it makes me more tired.”
  • Aripiprazole (Abilify®) 5 mg daily—“I'm gaining weight and eating at night again, and I'm worried that I'll get diabetes.”
  • Ortho Tri-Cyclen™ (oral contraceptive) daily—“I think it makes my headaches worse.”
  • Tramadol (Ultram®) 50 mg up to four times per day as needed for headaches—“It doesn't really do much unless I take double the dose.”

Jane is a new client who has heard about “the testing to tell what drugs might work,” and has requested to be tested. She comes to the office prepared and has not had anything in her mouth (no smoking, candies, gum, drinks, food) for the past hour and requests the testing during her initial evaluation. She is counseled regarding the genes to be tested and how the test will be used, as well as the storage of the DNA sample. Jane consents to be tested. The inside of her cheeks are swabbed for 1 minute and the sample is sealed and sent overnight delivery to the testing laboratory, with results anticipated within 1 week. Jane's results are returned in 5 days and an appointment is scheduled to discuss the results. Jane's results, their implications, and potential treatment options are illustrated in the Table.

Table:

Genetic Testing Results, Implications, and Options from Case Example

Interpreting Pharmacogenetic Testing in Clinical Practice

In the following sections, information related to the metabolism of each drug via the liver's CYP450 enzyme system is based on the pharmacology of the specific drug as presented in www.ePocrates.com, a free evidence-based medication information program.

The psychiatric advanced practice nurse meets with Jane to review and develop a personalized medication plan. Over the years, Jane has been prescribed three different selective serotonin reuptake inhibitor (SSRI) antidepressant agents. Her testing reveals the S/S variant of the SLC6A4 gene, which indicates the potential for treatment resistance and adverse events. In addition, Jane's genetic profile reveals ultrarapid metabolism of drugs metabolized by CYP450 2C19. Jane's failure with SSRIs and high doses of fluoxetine and sertraline (both metabolized by the 2C19 enzyme) and her lack of response to tramadol (metabolized by the 2B6 enzyme) at lower doses make sense; thus, treating her depressive symptoms and headaches going forward will require an alternate approach.

Jane reports gaining weight when prescribed the atypical antipsychotic medications as add-ons for treatment-resistant depression. Her genetic testing reveals the C/C variant for the 5HT2C gene, the C/A variant for the MC4R gene, and the C/Del variant for the DRD2 gene. All of these variants indicate that Jane may experience adverse events, including weight gain, related to the antipsychotic medications and that alternative mood stabilizing agents should be considered. Jane's profile also reveals the val/val variant on the COMT gene. This genotype implies that Jane has decreased dopamine and executive function in the prefrontal cortex and may be more susceptible to the euphoric effects of abused substances. Similarly, Jane has the C/G variant for the ADRA2A gene, which also contributes to decreased executive function. These results explain Jane's complaints of decreased attention and concentration as well as her experiences of taking more than the prescribed doses of alprazolam and tramadol and her increasing consumption of alcohol.

A majority of the medications Jane has been prescribed are CYP450 3A4 substrates, including the oral contraceptive and tramadol for her headaches. Although Jane is an extensive (normal) metabolizer of the CYP3A4 system, it is the most prevalent in humans and many drugs are substrates of CYP3A4 (“Clinically significant drug interaction,” n.d.). Polypharmacy with multiple agents that are CYP3A4 substrates may increase serum drug concentrations and result in serious adverse events (“Clinically significant drug interaction,” n.d.). The combinations of Jane's past and current medications may be contributing to the headaches, weight gain, elevated blood pressure, and other side effects she has experienced. Attempts should be made to reduce the number of drugs an individual is prescribed that compete for the same CYP450 metabolic enzyme.

Finally, Jane's genotype reveals a C/C variant for GRIK1, met/met variant for COMT, and an A/G variant for OPRM1, all of which offer insights into potential risks and treatments related to substance use. As Jane has required greater doses of tramadol to relieve her headaches, increased doses of alprazolam, and has also been increasing her alcohol consumption, her results offer recommendations for treating these substance use disorders.

Applying Genetic Testing to Personalize Psychopharmacotherapy

Cross-titrating to initiate and discontinue medications should be accomplished in a systemized manner. Discontinuing and initiating one agent at a time will not only minimize the risk of adverse events but also allow the practitioner to determine which agent may be contributing to any potential adverse effects. As Jane's profile indicates the potential for decreased response to SSRIs and weight gain related to antipsychotic agents, tapering and discontinuing the sertraline and aripiprazole would be indicated. In addition, because Jane has “needed” to take double the dose of tramadol for relief from her headaches, it should also be tapered and discontinued. As Jane remains depressed with low motivation, fatigue, decreased attention and concentration, as well as chronic headaches and increased alcohol use to the point of being diagnosed with Alcohol Use Disorder, a new pharmacotherapy regimen is required.

As Jane will remain on the Ortho Tri-Cyclen, the addition of drugs that are CYP3A4 substrates should be minimized to avoid adverse events. Consideration might be given to a trial of bupropion XL, a non-SSRI antidepressant agent, which enhances dopamine in the prefrontal cortex through the inhibition of reuptake. This choice would be consistent with Jane's COMT, OPRM1, ADRA2A, and ANK3 genotypes, as it would enhance executive functioning without the risk of abuse. As bupropion XL is metabolized by CYP2B6 and Jane is an ultra-rapid metabolizer for that enzyme, she may require higher doses or more frequent dosing to experience the full benefit of the medication. Consideration may also be given to a trial of topiramate, as Jane's C/C variant for GRIK1 indicates that she, being of European descent, should respond to this agent for abstinence from alcohol abuse. As topiramate is also a U.S. Food and Drug Administration–approved medication for migraine headache prophylaxis and an off-label treatment for sleep-related eating, which is contributing to her weight gain, Jane may experience multiple benefits from this single agent. However, caution is advised, as topiramate is a CYP3A4 substrate, which may increase the potential for adverse events when taken with the oral contraceptive. Lastly, if Jane's headaches persist, a non-opioid and non-controlled medication would be consistent with her genotypes on OPRM1 and COMT. Consideration may be given to naproxen, a nonsteroidal anti-inflammatory analgesic metabolized by CYP2C9. As Jane is a poor metabolizer for CYP2C9, lower doses or less frequent dosing of naproxen would be indicated.

Conclusion

Genetic testing for personalized pharmacotherapy in psychiatry has been in use for more than 10 years and although this technology is not an exact science, it offers practitioners and patients insights into potential treatment options to reduce symptoms and improve quality of life. As can be seen through the case example, interpreting and applying genetic testing in clinical practice is complex. Becoming familiar with the various genes, their variants, implications, and potential treatment options is essential. Finally, the complexities of human genetic variants implores us, as clinicians, to explore our patients' genes collectively, as opposed to individually, to obtain the best possible personalized medication outcomes. Although a single genetic variant may offer a glimpse into the individual's potential response to psychotropic medications, examining a patient's multiple genetic variants will provide greater insights into the potential risks, benefits, dosing, and side effects of the mediations prescribed while leading to better efficacy and quality of life.

References

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Genetic Testing Results, Implications, and Options from Case Example

Gene Results (Variant) Implications Potential Treatment Options
SLC6A4 S/S Increased treatment resistance and adverse events Non-SSRI antidepressant agents
5HT2C C/C Weight gain and metabolic syndrome with psychotropic agents Caution with antipsychotic agents
CACNA1C G/G Normal genotype, no implications Anticonvulsant mood stabilizers, lithium
ANK3 C/C Normal genotype, no implications Anticonvulsant, mood stabilizer, psychostimulant, and wake- promoting agents
ADRA2A C/G Decreased executive function Psychostimulant or alpha-2 adrenergic agents
MC4R C/A Increased risk of adverse events and antipsychotic-induced weight gain Non-antipsychotic mood stabilizing agents
BDNF Val/Val Normal genotype, no implications Exercise to aide in maintaining working memory
GRIK1 C/C Increased response to topiramate for alcohol abuse Topiramate for alcohol abuse
OPRM1 A/G Reduced response to opioid agonist medications Monitor for opioid agent tolerance and dependence
COMT Met/Met Decreased dopamine and executive function in prefrontal cortex, increased sensitivity to euphoric effects of abused substances Bupropion, wake-promoting agents, atomoxetine Monitor psychostimulant agents
DRD2 C/Del Increased risk for adverse events and decreased response to atypical antipsychotic agents Non-antipsychotic mood stabilizing agents
MTHFR C/C Normal genotype, no implications No specific treatments
CYP450 EM 2D6 No implications None
UM 2C19 Increased side effects, unpredictable treatment response May need increased or more frequent dosing
EM 3A4/5 No implications None
UM 2B6 Increased side effects, unpredictable treatment response May need increased or more frequent dosing
PM 2C9 Increased failure and side effects due to increased exposure to drug metabolites May need decreased or less frequent dosing
EM 1A2 No implications None

Commonly Tested Pharmacodynamic & Pharmacokinetic Genes

GENE (pharmacodynamic) PURPOSE GENOTYPES INTERPRETATION HYPOTHETICAL IMPLICATIONS PERSONALIZED MEDICATION OPTIONS
SLC6A4 Serotonin Transporter (Smits, Smits, Schouten, Peeters, & Prins 2007) presynaptic serotonin reuptake S/S, S/LG, LG/LG or LA/S, LA/LG Normal LA/LA “S or LG” short allele variant “LA” long allele variant <inline-graphic xlink:href="10.3928_02793695-20170301-02-fig1.jpg" xlink:type="simple" xmlns:xlink="http://www.w3.org/1999/xlink"></inline-graphic> SSRI response <inline-graphic xlink:href="10.3928_02793695-20170301-02-fig2.jpg" xlink:type="simple" xmlns:xlink="http://www.w3.org/1999/xlink"></inline-graphic> risk depression or PTSD ⇧transcription activity protective for adverse events Non-SSRI antidepressants caution initiating or discontinuing SSRI SSRI antidepressants
5HT2C Serotonin Receptor (Sicard et al., 2010) satiety signaling activity C/C or C/T normal T/T “C” allele antagonism “T” allele variant ⇧risk weight gain & metabolic syndrome with psychotropics protective for adverse events monitor for metabolic syndrome & weight use caution with atypical antipsychotics SSRI antidepressants
CACNA1C Glutamate Pathway & Calcium Channels (Ferreira et al., 2008) regulation ofcalcium influxalong cellmembrane G/A or A/A normal G/G “A” allele variant “G” allele variant ⇧excitatory neurotransmission ⇧risk mood disorder ⇧risk bipolar, schizophrenia, ⇧response to mood stabilizing anticonvulsants & atypical antipsychotics no clinical implications Anticonvulsant mood stabilizers Atypical antipsychotic mood stabilizers Lithium
ANK3 Sodium Channels (Schulze et al., 2008) stabilization of sodium channels and excitatory neurotransmission T/T or C/T normal C/C “T” allele variant “C” allele variant ⇧risk for bipolar disorder, schizophrenia & cyclothymic mood disorders no clinical implications Anticonvulsant mood stabilizers psychostimulants or Wake-promoting agents
ADRA2A Alpha 2A Adrenergic Receptor (Cinnamon Bidwell, Dew, & Kollins, 2010) working memory & executive functioning C/G or G/G normal C/C “G” allele variant “C ” allele variant Risk of decreased response & decreased executive functioning in prefrontal cortex, decreased stimulation of norepinephrine No clinical implications Psychostimulant medications A2A agonist medications
MC4R Melanocortin 4 Receptor (Cole et al., 2010) control of food intake & energy expenditure C/A or A/A normal C/C “A” allele variant “C” allele variant Increased risk adverse events Increased risk antipsychotic induced weight gain Non-antipsychotic mood stabilizers
BDNF Brain Derived neural development & Met/Met Met/Val “Met” allele variant Increase risk of depression, impaired working memory & decreased stress response Increase physical activity
Neurotrophic Factor (Martinez-Levy & Cruz-Fuentes, 2014) neural plasticity normal Val/Val “Val” allele variant Met/Met genotype increases response to exercises & improves working memory Antidepressants
GRIK1 Glutamate Receptor Ionotropic Kainate (Kranzler et al., 2014) Excitatory neurotransmission May identify patient at increased risk for Alcohol Abuse C/C or C/A normal A/A “C” allele variant “A” allele variant Increased response to Topamax® (topiramate) for alcohol abuse in European descendants with C/C genotype C/A genotype reduced response Topiramate for alcohol abuse
OPRM1 μ-Opioid Receptor (Haerian & Haerian, 2013) response of natural & synthetic opioid compounds from nucleus accumbens G/G or A/G normal A/A “G” allele variant “A” allele variant Reduced response to opioid agonist medications, may increase risk of tolerance & dependence increase sensitivity to opioid antagonists used to treat substance use disorders A/A genotype use opioids as directed G/G or A/G genotypes Monitor tolerance & dependence Use opioid antagonists to treat substance use disorders
COMT Catechol-O-Methyl-transferase Dopamine Pathway (Hamidovic, Dlugos, Palmer, & de Wit, 2010) regulation of dopamine & norepinephrine levels in prefrontal cortex impacting memory, attention, judgment & other “executive” functions Val/Val or Met/Met normal Val/Met “Val” allele variant “Met” allele variant <inline-graphic xlink:href="10.3928_02793695-20170301-02-fig1.jpg" xlink:type="simple" xmlns:xlink="http://www.w3.org/1999/xlink"></inline-graphic> dopamine in PFC <inline-graphic xlink:href="10.3928_02793695-20170301-02-fig1.jpg" xlink:type="simple" xmlns:xlink="http://www.w3.org/1999/xlink"></inline-graphic> executive functioning <inline-graphic xlink:href="10.3928_02793695-20170301-02-fig1.jpg" xlink:type="simple" xmlns:xlink="http://www.w3.org/1999/xlink"></inline-graphic>dopamine in PFC ⇧sensitivity to euphoric effects of abused substances Psychostimulants Bupropion Atomoxetine Wake-promoting agents
DRD2 Dopamine Receptor (Strange, 2001) movement and perception Del/Del or C/Del normal C/C “Del” allele variant “C” allele variant ⇧risk for adverse effects & <inline-graphic xlink:href="10.3928_02793695-20170301-02-fig1.jpg" xlink:type="simple" xmlns:xlink="http://www.w3.org/1999/xlink"></inline-graphic> response to atypical antipsychotics protective for adverse events Non-antipsychotic mood stabilizers Atypical mood stabilizers
MTHFR Metabolism Gilbody, Lewis & Lightfoot, 2007) conversion of folic acid to its most usable/active form methylfolate which crosses the blood brain barrier T/T or C/T C/C or A/C normal C/C A/A “T” allele variant “C” allele variant Inefficient production of methylfolate➔ <inline-graphic xlink:href="10.3928_02793695-20170301-02-fig1.jpg" xlink:type="simple" xmlns:xlink="http://www.w3.org/1999/xlink"></inline-graphic>ability to regulate flow of monoamines across synapse ⇧ risk for depression, autism, bipolar & schizophrenia l-methylfolate
GENE (pharmacokinetic)
CYP450 Genes Metabolism CYP2D6 CYP2C19 CYP3A4/3A5 CYP2B6 CYP2C9 CYP1A2 (Samer, Lorenzini, Rollason, & Desmeules, 2013) enzymes responsible for metabolism of medications in the liver normal EM Intermediate IM low activity PM high activity UM extensive metabolizers intermediate & poor metabolizers ultra-rapid metabolizers “normal” drug metabolism variations in one or both alleles increases drug induced side effects & unpredictable treatment response higher drug metabolism ⇧ risk therapeutic failure & drug induced side effects 2° ⇧ exposure to drug metabolites Clinically indicated medications Dosage adjustments of substrate drugs Dosage adjustments of substrate medications
Authors

Dr. Leahy is Family Psychiatric Advanced Practice Nurse and Master Clinician in Psychopharmacology, APNSolutions, LLC, Sewell, New Jersey.

The author has disclosed no potential conflicts of interest, financial or otherwise.

Address correspondence to Laura G. Leahy, DrNP, APRN, PMH-CNS/FNP, BC, Family Psychiatric Advanced Practice Nurse and Maser Clinician in Psychopharmacology, APNSolutions, LLC, 123 Egg Harbor Road, Suite 703, Sewell, NJ 08080; e-mail: lgleahy@apnsolutions.com.

10.3928/02793695-20170301-02

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