Medical Policy: 02.04.67 

Original Effective Date: August 2017 

Reviewed: August 2017 

Revised:  

 

Benefit Application:

Benefit determinations are based on the applicable contract language in effect at the time the services were rendered. Exclusions, limitations or exceptions may apply. Benefits may vary based on contract, and individual member benefits must be verified. Wellmark determines medical necessity only if the benefit exists and no contract exclusions are applicable. This medical policy may not apply to FEP. Benefits are determined by the Federal Employee Program.

 

This Medical Policy document describes the status of medical technology at the time the document was developed. Since that time, new technology may have emerged or new medical literature may have been published. This Medical Policy will be reviewed regularly and be updated as scientific and medical literature becomes available.

 

Description:

Drug efficacy and toxicity vary substantially across individuals. Because drugs and doses are typically adjusted, if needed, by trial and error, clinical consequences may include a prolonged time to optimal therapy. In some cases, serious adverse events may result.

 

Various factors may influence the variability of drug effects, including age, liver function, concomitant diseases, nutrition, smoking, and drug-drug interactions. Inherited (germline) DNA sequence variation (polymorphisms) in genes coding for drug metabolizing enzymes, drug receptors, drug transporters, and molecules involved in signal transduction pathways also may have major effects on the activity of those molecules and thus on the efficacy or toxicity of a drug.

 

Pharmacogenomics is the study of how an individual's genetic inheritance affects the body's response to drugs. It may be possible to predict therapeutic failures or severe adverse drug reactions in individual patients by testing for important DNA polymorphisms (genotyping) in genes related to the metabolic pathway (pharmacokinetics) or signal transduction pathway (pharmacodynamics) of the drug. Potentially, test results could be used to optimize drug choice and/or dose for more effective therapy, avoid serious adverse effects, and decrease medical costs.

 

Genetically determined variability in drug response has been traditionally addressed using a trial and error approach to prescribing and dosing, along with therapeutic drugs monitoring (TDM) for drugs with a very narrow therapeutic range and/or potential serious adverse effects outside that range. However, TDM is not available for all drugs of interest, and a cautious trial and error approach can lengthen the time to achieving an effective dose.

 

To definitively show that pharmacogenomic testing has value in clinical practice, it is not enough to demonstrate that drug response varies by genotype. There must be an alternative treatment strategy, and proof that testing for the genotype and subsequently tailoring the treatment strategy based on genetic information are more clinically effective or cost effective (or both) than merely treating everyone in the same manner. Use of test to identify gene variants and affected populations must be more efficient than current practice in preventing serious adverse effects. After taking into account known non-genetic factors that cause variation in response, the remaining variability in patient response can often be managed with appropriate monitoring, or can be reversed by withdrawl of the drug by changing drugs or dosage. Adverse effects of available drugs are generally preventable. It has been proposed that testing (genotyping) for genetic variants may assist in tailoring drug selection and drug dosing for an individual based on their gene composition for drug metabolism which could lead to early selection and optimal dosing of the most effective drugs, while minimizing treatment failures and toxicities.

 

CYP450 Genotyping to Determine Drug Metabolizer Status

The cytochrome P450 (CYP450) family is involved in the metabolism of many currently administered drugs, and genetic variants in cytochrome P450 are associated with altered metabolism of many drugs. Testing (genotyping) for cytochrome P450 variants may assist in selecting and dosing drugs affected by these genetic variants. 

 

Genotyping for cytochrome P450 has been proposed for possible use in medical management of drug therapies including but not limited to antidepressants, anti-epileptics, antipsychotics, barbituates, clopidogrel (Plavix), opioid analgesics, proton pump inhibitors and tamoxifen. CYP2D6 metabolizes approximately 25% of all clinically used medications (e.g. dextromethorphan, beta blockers, antiarrhythmics, antidepressants and morphine derivatives), including many of the most prescribed drugs. CYP2C19 metabolizes several important drugs, including proton pump inhibitors, diazepam, propranolol, imipramine, and amitriptyline.

 

Some CYP450 enzyme genes are highly polymorphic, resulting in some enzyme variants that have variable metabolic capacities among individuals, and some with little to no impact on activity. Individuals with a lack of function activity in these enzymes (CYP2C19, CYP2D6, CYP2C9, etc.) can be classified according to how fast they metabolize medications:

  • Poor metabolizers (PMs): Lack active enzyme gene alleles, they will process a certain drug more slowly than normal because of the missing enzyme(s), the medication can build up in their system which can increase the likelihood that it will cause side effects. The individual might still be able to benefit from the medication, but at lower dosages.
  • Intermediate metabolizers (IMs): Have one active and one inactive enzyme gene allele, these individuals have a reduced enzyme function in processing drugs, they may not process some medications as well as a normal metabolizer would. This can increase risk of side effects and drug interactions.
  • Normal metabolizers (extensive metabolizers Ems): These individuals have 2 copies (alleles) of the most common (wild type) DNA sequence of a particular CYP450 enzyme gene resulting in an active molecule and are termed extensive metabolizers. Medications are processed normally, these individuals are more likely to benefit from treatment and have fewer side effects than people who don’t process the same medication(s) as well.
  • Ultra-rapid metabolizers (UMs): Individuals with more than 2 alleles of an active enzyme gene, which cause the medications to leave the body too quickly and often before they have had a chance to work properly. These individuals will likely need a higher than usual dose of medications.

 

Many drugs are metabolized to varying degrees by more than one enzyme, either within or outside of the CYP450 superfamily. In addition, interaction between different metabolizing genes, interaction of genes and environment, and interactions among different non-genetic factors also influence CYP450 specific metabolizing functions. Therefore, identification of a variant in a single gene in the metabolic pathway may be insufficient in all but a small proportion of drugs to explain inter-individual differences in metabolism and consequent efficacy or toxicity.

 

CYP450 enzyme phenotyping (identifying metabolizer status) can be accomplished by administering a test enzyme substrate to a patient and monitoring parent substrate and metabolite concentrations over time (e.g. in urine). However, testing and interpretation are time-consuming and inconvenient; as a result, phenotyping is seldom performed.

 

The clinical utility of CYP450 genotyping (i.e. the likelihood that genotyping will significantly improve drug choice, dosing, and patient outcomes) is favored when the drug under consideration has a narrow therapeutic dose range, when the consequences of treatment failure are severe, and/or when serious adverse reactions are more likely in patients with gene sequencing variants. Under these circumstances, genotyping may direct early selection of the most effective drug or dose, and/or avoid drugs or doses likely to cause toxicity. For example, warfarin, some neuroleptics, and tricyclic antidepressants have narrow therapeutic windows and can cause serious adverse events when concentrations exceed certain limits, resulting in cautious dosing protocols. Yet, the potential severity of the disease condition may call for immediate and sufficient therapy; genotyping might speed up the process of achieving a therapeutic dose and avoiding significant adverse events.

 

The purpose of P450 genotyping is to tailor drug selection and dosing to patients based on their gene composition for drug metabolism. In theory, this should lead to early selection and optimal dosing of the most effective drugs, while minimizing treatment failures or toxicities. This testing may be used for drug selection before treatment initiation. Consultations regarding choice of drug generally occur in the outpatient setting and a variety of specialists may be involved including primary care providers, cardiologists, psychiatrists, neurologists and endocrinologists.

 

Selection and/or Dosing of Clopidogrel (Plavix)

Clopidogrel (plavix) is an orally administered antiplatelet drug that is used to prevent blood clots that could lead to heart attacks or strokes in individuals with established atherosclerotic disease. The degree of platelet inhibition seen following use of clopidogrel (plavix) varies from patient to patient in a normal or bell-shaped distribution. The variability in non-response is such that, when laboratory measurements of platelet aggregation are performed, 4 to 30% of patients treated with clopidogrel (plavix) do not have an adequate anti-platelet response.

 

Guidelines from the American Heart Association and the American College of Cardiology recommend the use of dual antiplatelet therapy with aspirin and a P2Y12 inhibitor, such as clopidogrel (plavix), prasugrel or ticagrelor, for the prevention of atherothrombotic events after acute myocardial infarction (MI). However, a substantial number of subsequent ischemic events still occur, which may be least partly due to interindividual variability in the response to clopidogrel (plavix). Clopidogrel (plavix) is a prodrug which is converted by several CYP450 enzymes, CYP2C19 in particular, to an active metabolite. For this reason, genetic polymorphisms that inactive the CYP2C19 enzyme are associated with impaired pharmacodynamics response in healthy individuals. Previous studies have shown that persistent high platelet reactivity, despite clopidogrel (plavix) treatment at standard dosing, is associated with CYP2C19 variants that code for inactive enzymes, higher loading and/or maintenance doses decrease reactivity even in initial non-responders, presumed to be CYP2C19 PMs. Higher platelet reactivity has been associated with a higher rate of subsequent thrombotic events. However, the intrinsic variability of platelet monitoring is a known limitation of all tests measuring platelet aggregation, making it difficult to use these tests for treatment modulation.

 

In 2009, FDA expanded the pharmacogenetics section of the clopidogrel (plavix) label to include information on the metabolic impact of polymorphic CYP450 enzymes. However, no dosing or drug selection recommendations were made.  In March 2010, based on the available data at the time, the U.S. Food and Drug Administration issued a safety communication indicating it was adding a boxed warning to the label of clopidogrel (plavix) about diminished effectiveness in poor metabolizers. The boxed warning states that the effectiveness of clopidogrel (plavix) is dependent on its activation to an active metabolite by the cytochrome p450 (CYP450) system, principally CYP2C19. The labeling states that clopidogrel (plavix) at recommended doses forms less of that metabolite and has smaller effect on platelet function in patients who are CYP2C19 poor metabolizers. Citing cohort studies and retrospective analyses of clinical trials, the labeling states that poor metabolizers with acute coronary syndrome or undergoing percutaneous coronary intervention (PCI) treated with clopidogrel (plavix) at recommended doses exhibit higher cardiovascular event rates than do patients with normal CYP2C19 function. The labeling states that tests are available to identify a patient’s CYP2C19 genotype, and that these tests can be used as an aid in determining therapeutic strategy. The labeling states that clinicians should consider alternative treatment or treatment strategies in patients identified as CYP2C19 poor metabolizers.

 

A clinical alert in 2010 issued by the American College of Cardiology Foundation (ACCF) and the American Heart Assocation (AHA) regarding clopidogrel (plavix) boxed warning by the FDA, stated that the boxed warning leaves the issue of whether to perform CYP2C19 testing up to the individual physician. In summary, they indicate that clinicians must be aware that genetic variability in CYP enzymes alter clopidogrel (palvix) metabolism, which in turn can affect its inhibition of platelet function. Diminished responsiveness to clopidogrel (plavix) has been associated with adverse patient outcomes in registry experiences and clinical trials.  The evidence base is insufficient to recommend either genetic or platelet function testing at the present time. There is no information that routine testing improves outcome in large subgroups of patients. However, clinical judgement is required to assess clinical risk and variability in patients considered to be at increased risk. Genetic testing to determine if a patient is predisposed to poor clopidogrel (plavix) metabolism (poor metabolizers) may be considered before starting clopidogrel (plavix) therapy in patients believed to be at moderate or high risk for poor outcomes. This might include individuals undergoing elective high risk percutaneous coronary intervention (PCI) e.g. treatment of extensive and/or very complex disease. Moreover, if a person is identified as a potentially poor metabolizer (PM), other treatments should be considered i.e. alternative dosing of clopidogrel (plavix) or use of other available agents such as prasugrel (effient), if not contraindicated for the individual.

 

In 2012 ACCF/AHA issued an updated guideline for the management of patients with unstable angina/non-ST-elevation myocardial infarction, Class IIb recommendation which suggests “that a selective, limited approach to platelet genotype assessment of platelet function testing is more prudent course until better clinical evidence exists for us to provide a more scientific derived recommendation, in patients with unstable angina (UA) or non-ST-elevation myocardial infarction (NSTEMI).”

 

The evidence for testing for CYP2C19 metabolizer status by CYP2C19 genotyping in patients with need for antiplatelet therapy who are undergoing or being considered for clopidogrel (plavix) therapy includes randomized controlled clinical trials (RCTs), observational studies, systemic reviews and meta-analyses. Systemic reviews of observational studies report that genetic variants may be associated with modest increase in the rate of stent thrombosis and clinical end points. CYP2C19 genotype testing has been associated with increased risk of thrombosis in patients with coronary disease or cardiac interventions being considered as candidates for clopidogrel (plavix) treatment. This observation is most pronounced for stent thrombosis in patients undergoing percutaneous coronary intervention (PCI). The evidence addressing whether the use of CYP2C19 genotype directed therapy improves outcomes are limited. However, a number of publications have evaluated outcomes in patients treated with clopidogrel (plavix) according to their CYP2C19 genetic status. These studies showed that patients with genetic variants (poor metabolizers) exhibit higher cardiovascular event rates (worse outcomes) than those patients without genetic variants. This data raises the possibility that the efficacy of clopidogrel (plavix) was reduced in patients with genetic variants. Therefore, the evidence is sufficient to determine that this testing results in a meaningful improvement in the net health outcome (consider alternate treatment or dosing strategies) in patients identified as CYP2C19 poor metabolizers.

 

Selection and/or Dosing of Tetrabenazine

Huntington’s disease is an autosomal dominant genetic neurodegenerative disorder characterized by progressive cognitive and motor dysfunction, including chorea. In 2008, FDA approved tetrabenzine, a centrally acting vesicular monoamine transporter inhibitor, as an orphan drug for the treatment of chorea (abnormal involuntary movement) in Huntington’s disease, based on evidence from an RCT of improved chorea symptoms in ambulatory patients with Huntington’s disease. Tetrabenazine’s primary metabolites are metabolized mainly by CYP2D6.  FDA labeling for tetrabenazine includes recommendations for genotyping for CYP2D6 in patients who are being considered for doses over 50mg per day. The labeling states: “Patients requiring doses above 50 mg per day should be genotyped for the drug metabolizing enzyme CYP2D6 to determine if the patient is poor metabolizer (PM), poor metabolizers should not be given daily doses greater than 50 mg.”

 

Selection and/or Dosing of Eliglustat

Gaucher disease is a rare autosomal recessive lipid storage disease in which deficiency or absence of enzyme B-glucocerebrosidase leads to lysosomal accumulation of the glycosphingolipid glucosylceramide. Untreated, this accumulation can lead to a range of effects, including anemia and thrombocytopenia, splenomegaly, bone disease, pulmonary fibrosis, and central nervous system involvement. Gaucher disease has been treated through enzyme replacement, for which 3 drugs have been FDA approval as orphan drugs (imiglucerase, velaglucerase alfa, and taliglucerase alfa) or substrate reduction therapy, for which 2 drugs have FDA approval as orphan drugs (miglustat and eliglustat tartrate). Eliglustat (cerdelga) is an orally administered selective inhibitor of glucosylceramide synthase that received FDA approval in 2014 and has been found in 3 phase 3 clinical trials to lead to improvements in hematologic metrics and organomegaly.

 

Eliglustat (cerdelga) is metabolized by CYP2D6 and CYP3A. FDA labeling requires that patients be selected on the basis of CYP2D6 metabolizer status as determined by genotype, with recommendations based on genotype about dosage: CYP2D6 Ems (extensive metabolizers) or IMs (intermediate metabolizers) 84 mg orally twice daily; CYP2D6 PMs (poor metabolizers) 84 mg orally once daily. Eliglustat (cerdelga) is not indicated in patients who are CYP2D6 ultra-rapid metabolizers, since they may not achieve adequate concentrations of eliglustat (cerdelga) to achieve a therapeutic effect.

 

Selection and/or Dosing of Other Medications

The evidence for cytochrome P450 (CYP450) genotyping in patients with various clinical conditions undergoing or being considered for treatment with a drug metabolized CYP450 enzyme(s) includes prospective and retrospective observational studies reporting associations with CYP450 metabolizer status and medication response or adverse effects. Most published studies of CYP450 pharmacogenomics are retrospective evaluations of CYP450 genotype association with intermediate (e.g., circulating drug concentrations) or, less often, final outcomes (e.g., adverse events or efficacy) and are largely small and underpowered or not designed to examine the clinical effects of homozygous variant poor metabolizers and of ultra-rapid metabolizers, where the strongest effects, if any, would be seen. The hazards associated with different metabolizer status are therefore uncertain. There is limited evidence on the clinical validity of testing for CYP450 genotype. At present, the clinical utility is poorly defined, it is not known whether CYP450 genotyping guided clinical management improves patient outcomes such as therapeutic effect, time to effective dose, and adverse event rate compared to standard clinical management without genotyping. The evidence is insufficient to determine the effects of CYP450 genotyping for various clinical conditions on net health outcomes. Therefore, CYP450 genotyping including but not limited to the following would be considered investigational:

  • Selection or dose of selective serotonin reuptake inhibitor (SSRI)
  • Selection and dosing of serotonin norepinephrine reuptake inhibitors (SNRIs)
  • Selection and dosing of tricyclic antidepressant medications
  • Selection or dose of antipsychotic medications
  • Selection or dosing of opioid analgesics
  • Dose of efavirenz (common component of highly active antiretroviral therapy for HIV infection)
  • Dose of immunosuppressant for organ transplantation
  • Selection or dose of beta blockers
  • Dosing and management of antituberculosis medications
  • Selection or dosing of Tamoxifen

 

Testing for genetic polymorphisms has also been proposed for a wide array of other drugs, involving many different conditions and CYP450 enzyme(s).  At this time, the available literature addressing such testing is limited and insufficient to allow any assessment of clinical utility in the treatment of individuals. The outcomes that require further research attention include major adverse events, utilization of health resources, and time to clinically significant changes in condition using appropriate and validated measures.

 

While the potential of pharmacogenomics is intriguing for many clinical applications, it is not yet clear which are most likely to yield clinical benefit in the near future.  As this field evolves and matures, and if pre-prescription testing can be shown to be of clinical utility for specific drugs and individuals, it will be imperative to establish evidence-based guidelines for healthcare professionals delineating the most effective courses of action based on such genotype testing results.

 

Testing Panels to Determine Drug Metabolizer Status

Several commercial laboratories market multi-test panels for genetic polymorphisms that include analysis of multiple CYP450 mutations and other gene polymorphisms (variants) related to drug metabolizer status.  While the use of some individual tests included in these test panels may be reasonable under specific circumstances, the use of all the tests within a panel is rarely justified unless there is clinical evidence that the panel provides information that leads to meaningful impact on treatment.  At this time, the available published evidence addressing the use of such test panels is limited to a few panel and condition-specific studies. The results of these studies are limited by the study designs utilized by the investigators, with each having some combination of no blinding, small study population, retrospective methodology, selection bias, short follow-up periods, and subjective study outcomes.  The data from these studies is weak, and further investigation is warranted using better designed, larger study samples and double-blind randomized controlled methodology. The evidence is insufficient to determine the effects of this technology on net health outcomes.

 

Pharmacogenomic Testing For Pain Management

Pain is a universal human experience and an important contributor to outpatient and inpatient medical visits. The Institute of Medicine’s (IOM) reported in 2011 (revised in 2012) that chronic pain conditions affect at least 100 million adults in the United States. Chronic pain may be related to cancer, or be what is termed chronic non-cancer pain, which may be secondary to a wide range of conditions, such as migraines, low back pain or fibromyalgia. Multiple therapeutic options exist to manage pain, including pharmacotherapies, behavioral modifications, and physical and occupational therapy, and complementary/alternative therapies. Nonetheless, IOM has reported that many individuals receive inadequate pain prevention, assessment and treatment. Given that pain is an individual and subjective experience, assessing and predicting response to pain interventions, including pain medications, is challenging.

 

A variety of medication classes are available to manage pain: non-opioid analgesics, including acetaminophen and non-steroidal anti-inflammatory drugs (NSAIDs), opioid analgesics, which target nervous system pain perception, and classes of adjuvants, including anti-epileptic drugs (e.g. gabapentin, pregabalin), and topical analgesics. The management of chronic pain has been driven in part by the World Health Organization’s analgesic ladder for pain management, which was developed to manage cancer related pain but has been applied to other forms of pain. The ladder outlines a stepped approach to pain management in the following order: non-opioid analgesia and proceeding to a mild opioid (codeine) with or without an adjuvant for persisting pain, and subsequently to a strong opioid (e.g. fentanyl, morphine), with or without an adjuvant for persisting or worsening pain. Various opioids are available in short and long acting preparations and administered through different routes, including oral, intramuscular, subcutaneous, sublingual, and transdermal.

 

While multiple pharmacologic therapies are available for the management of acute and chronic pain, there is a high degree of heterogeneity in pain response, particularly in the management of chronic pain, and in adverse events. This has prompted interest in better targeting pain therapies based on pharmacogenomics testing of genes relevant to analgesic pharmacokinetics (i.e. how medications are absorbed, distributed, metabolized or excreted) or pharmacodynamics (i.e. medications effects on the body).  A number of panel tests have been developed to aid in pain management that includes several genes associated with pharmacokinetics and pharmacodynamics of analgesic medications.

 

Genetic factors may contribute to a range of aspects in pain and pain control, including predisposition to conditions that lead to pain, pain perception, and the development of comorbid conditions that may affect pain perception. Currently available genetic tests relevant to pain  management consist of panels of single genetic variants (polymorphisms, or single nucleotide variants (SNVs)) which include but are not limited to the following:

  • 5HT2C (serotonin receptor gene)
  • 5HT2A (serotonin receptor gene)
  • SLC6A4 (serotonin transporter gene)
  • DRD1 (dopamine receptor gene)
  • DRD2 (dopamine receptor gene)
  • DRD4 (dopamine receptor gene)
  • DAT1 or SLC6A3 (dopamine transporter gene)
  • DBH (dopamine beta-hydroxylase gene)
  • COMT (catechol O-methyltransferase gene)
  • MTHFR (methylenetetrahydrofolate reductase gene)
  • y-aminobutyric acid (GABA) A receptor gene
  • OPRM1 (u-opioid receptor gene)
  • OPRK1 (k-opioid receptor gene)
  • UGT2B15 (uridine diphosphate glycosyltransferase 2 family, member 15)
  • Cytochrome P450 genes: CYP2D6, CYP2C19, CYP2C9, CYP3A4, CYP2B6, CYP1A2

 

Several test labs market panel tests or individual tests designed to address one or more aspects of pain management, including but not limited to drug selection, drug dosing, or prediction of adverse events. The following are some commercially available labs that offer panel tests or individual tests related to pharmacogenomic testing for pain management:

 

OneSight (Assurex Health, Mason, OH)

GeneSight is a panel of genetic panel test intended to analyze “how patient’s genes can affect their metabolism and possible response to FDA approved opioids, NSAIDs and muscle relaxants commonly used to treat chronic pain. Results are provided with a color-coded report based on efficacy and tolerability, which displays those medications that should be used as directed, used with caution, or used with increased caution and more frequenting monitoring. The company’s website does not specify the testing methods. Publications describing the tests provided by the company specify that testing is conducted via SNV sequencing performed via multiplex polymerase chain reaction.

GeneSight tests include the following:

  • GeneSight Analgesic – The GeneSight Analgesic test analyzes how genes affect the way one’s body may respond to FDA approved opioids, NSAIDs and muscle relaxants commonly prescribed to treat acute and chronic pain, opioid dependency, osteoarthritis, rheumatoid arthritis, and juvenile rheumatoid arthritis. Panel includes the following: CYP2D6, CYP2C19, CYP2C9, CYP3A4, CYP2B6, CYP1A2, OPRM1

 

Proove Opioid Risk Panel (Proove Biosciences, Irvine, CA)

Proove Biosciences offers several genetic panels that address pain control to include but are not limited to the following:

  • Proove Addiction Risk Test: The Proove Addiction Risk Test identifies patients with increased risk of substance dependence based on genetic factors, and provides clinically actionable recommendations for treatment based on an individual genotype. The report includes the substance (alcohol, cocaine, heroin, nicotine, methamphetamine), the genetic variants that contribute to risk factors, addiction severity, side effects of use and explanation of why a patient was designated as having low, moderately increased, or increased genetic contribution towards risk. The company’s website does not specifically identify what genetic variants are tested in this profile. 
  • Proove Drug Metabolism: Suboptimal drug or dosing can result in at best ineffectual therapeutic responses to medications and at worst adverse drug events (ADEs). ADEs can lead to hospitalization or even death. The Proove Drug Metabolism profile identifies genetic variants in drug metabolizing enzymes that may result in altered response or reactions to certain medications. The metabolizer status of each enzyme is reported with icons and these results are used to generate selection and dosing recommendations. Enzyme tested includes the following: CYP1A2, CYP2CB, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5
  • Proove Opioid Response Profile: Is a comprehensive test designed to assess the likelihood of an individual to respond each of five opioid medications included in the test. There are several ways that genetics can influence a patient’s response to a drug, including variants in drug metabolism enzymes, drug transporters, and opioid receptors. Each response profile evaluates a panel of genetic markers in those categories to predict response to a specific medication and the optimal dose to prescribe for a patient.  It combines genetic predictions for enhancing efficacy and decreasing toxicity of a patients’ opioid therapy by incorporating genetic analysis of the target of drug action, modulation and/or metabolism. All these factors which are collectively called pharmacodynamic and pharmacokinetic factors are important to determining the effect that a drug is likely to have. Alternative opioids or pain control measures may be considered based on the results of this test, which could lead to better patient outcomes, decreased use of suboptimal medications, and shorter duration of therapy, all of which result in lower costs to patients and payer. Five most commonly prescribed opioids available on this report include: hydrocodone, oxycodone, morphine, tramadol and hydromorphone. The indicator bar on the report represents likelihood of favorable response and the pill icons represent dosing recommendations (increase, decrease, discontinue, etc.). The company’s website does not specifically identify what genetic variants are tested in this profile.
  • Proove Opioid Risk: Offers physicians a more objective alternative to existing assessment tools used to evaluate patients for opioid therapy. It is based in part on genetic information which cannot be manipulated, and powered by an evidence-based algorithm that takes into account all major risk factors found to contribute to risk of aberrant behavior with opioid use. Clinical recommendations are based on both genetic and non-genetic factor analysis. The genetic variable found to contribute to risk of opioid use disorder (OUD) are included in the algorithm and report of this profile: serotonin 2a receptor, catechol-o-methyltransferase, dopamine D2 receptor, dopamine D1 receptor, dopamine D4 receptor, dopamine transporter, dopamine beta hydroxylase, methylenetetrahydrofolate reductase, kappa opioid receptor, GABA receptor gamma 2, Mu1 opioid receptor and serotonin receptor 2A.
    • A patient at low risk of opioid use disorder, proceed with standard precautions.
    • A patient at moderate risk of opioid use disorder consider additional safeguards if proceeding with opioid therapy.
    • A patient at high risk of opioid use disorder consider alternative therapies to opioid use and/or implementing safeguards to mitigate risk              
  • Proove Pain Perception: This information provides a physician and the patient with more accurate information about the patient’s pain, which can help mitigate the subjective characteristics of pain perception, and enable the physician to better determine analgesic requirements. Understanding where an individual falls in the spectrum of pain sensitivity can guide decisions about which interventions be they pharmacological, behavioral or physical may result in best outcomes. 
    • Clinical recommendations are based on both genetic and phenotypic factors known to modify pain sensitivity
    • Genetic factors include single nucleotide polymorphisms (SNPs) in the Catechol-O-Methyltransferase gene (COMT). This test evaluates 5 SNPs known to alter the enzymatic activity of the COMT enzyme, which in turn effects pain processing. Other factors evaluated are gender, ethnicity and stress. These also contribute to the variability in how individual experiences and processes pain.
    • Results provided: low pain sensitivity; moderately low pain sensitivity; average pain sensitivity; moderately high pain sensitivity; or high pain sensitivity.
      • Patient is predisposed to low pain sensitivity and may be understating pain levels, this patient may require less pain medication.
      • Patient is predisposed to high pain sensitivity and may be perceiving an exaggerated level of pain, this patient may require more pain medication or consideration of alternative therapies such as beta blockers or cognitive behavioral therapy.  
  • Proove Non-Opioid Response: There are several ways that genetics can influence analgesic response, including drug metabolism enzymes, drug transporters, and receptors. Proove Non-Opioid Response Genetic Profile assesses a panel of markers in these categories in order to inform the likelihood of successful response to each of four non-opioid pain medications included in the test, as predicted by drug-receptor interactions and genetic predisposition to variable concentrations of the medication in the CNS and/or the blood stream. Alternative pain control measures may be considered based on the results of these tests, which may lead to better patient outcomes, decreased use of suboptimal medications, and shorter duration of therapy resulting in lower costs.   The four non-opioid pain medications included are the following: Ibuprofen, Gabapentin, Alprazolam, and Duloxetine. The indicator bar on the report represent likelihood of favorable response and the pill icons represent dosing recommendations (increase, decrease, discontinue, etc.). The company’s website does not specifically identify what genetic variants are tested in this profile.   
  • Proove NSAID Risk Profile: This profile provides a quick and easy evaluation of genetic risk associated with NSAID use, in addition to provider an avenue for identification of new measures that may lead to increased accuracy in patient risk stratification. The Proove NSAID Risk Profile focuses on polymorphisms in candidate genes involved in NSAID-mediated metabolism and inflammatory pathways to predict whether a patient is at risk for potential adverse drug events with NSAID use. The Proove NSAID Risk test focuses on 18 single nucleotide polymorphisms (SNPs) in candidate genes involved with innate immunity and inflammation (e.g., cyclooxygenase-1 (COX-1), toll-like receptor 4 (TLR4), C-reactive Protein (CRP), Nucleotide-Binding Oligomerization Domain (NOD1), Protein-Tyrosine Phosphatase, Nonreceptor-Type 11 (PTPN11), and genes involved in NSAID metabolism and efflux (Cytochrome P450 (CYP) 2C8, CYP2C9, UGT2B, and ATP-binding cassette sub-family B member (ABCB1)).

 

Millennium Pharmacogenetic Testing (PGT) (Millennium Health, San Diego, CA)

Millennium Pharmacogenetic Testing analyzes clinically relevant genetic variants for 14 genes related to medication response to help clinicians individualize prescribing decisions. The Millennium Analysis of Patient Phenotype (MAPP) Report provides clinicians with evidence based and clinically actionable information to support medication decisions for over 40 commonly prescribed medications across 13 medication classes which include but are not limited to alcohol, amphetamines, barbiturates, illicit substances (cocaine, heroin, MDMA, PCP, THC), muscle relaxants, NSAIDs, opiates and opioids.

  • Addiction Therapy (CYP2B6, OPRM1)
  • Muscle Relaxants (CYP2C19)
  • NSAIDs (CYP2C9)
  • Opioids (COMT, CYP2B6, CYP2D6, CYP3A4, CYP3A5, OPRM1)

 

YouScript Panels (Genelex, Seattle, WA)

Genelex currently offers 28 clinically actionable pharmacogenetic tests to help physicians target treatment and medication to patients genetics. Tests can be ordered as a panel or individually. Panels include the following which focus on genes relevant to pain management:

  • YouScript Analgesic: (CYP2D6, CYP2C9, CYP3A4, CYP3A5, CYP2B6, COMT, and OPRM1)

 

Pain Medication DNA Insight (Pathway Genomics, San Diego, CA)

Pain Medication DNA Insight is a panel test intended to identify genetic variants that affect how an individual will respond to the analgesic effects (pain relief) of 13 commonly prescribed pain medications. What is tested: opioids (CYP2D6, CYP2B6, OPRM1); NSAIDs (CYP2C9). Pain Medication DNA is for patients currently taking or considering taking a pain medication. This clinically-actionable genetic test can assist physicians in understanding patient’s response to certain pain medications and can help with identification of optimal treatment plans. The result report includes the gene tested, along with a description of the toxicity risk, dose required, medication efficacy or plasma concentration based on genotype results for a range of medications used for pain management.

 

ARUP Pain Management (ARUP Laboratories (Salt Lake City, UT)

ARUP Pain Management is a panel that tests CYP450 genes that affect how an individual may respond to pain medications. Drug testing determines the presence or absence of drugs and/or drug metabolites. Drug testing may be quantitative (useful for therapeutic drug monitoring (TDM)) or qualitative to verify compliance with prescribed therapy or identify inappropriate drug use. Pharmacogenetic testing may be performed to help explain an adverse drug reaction or to help guide selection of drugs for an individual patient. TDM can help optimize the dose of a therapeutic drug and is complementary to pharmacogenetic testing.

 

IDgenetix Pain Tests (AltheaDX, San Diego, CA)

IDgenetix Pain Tests analyze genes and genetic mutations involved in the metabolism of opioids, non-steroidal anti-inflammatory drugs, and other pain drugs as well as variations in pharmacodynamic genes, such as the u opioid receptor gene, or OPRM1.

 

PersonaGene Pain Management (AIBio Tech)

Targeted drug therapy can help reduce side effects and improve adherence. Genetic variations in cytochrome P450 enzymes can directly influence the effectiveness and tolerability of commonly prescribed pain medications to include opioids, muscle relaxants and narcotic analgesics. Panel includes CYP2D6, CYP3A4, CYP3A5

 

Pharmacogenomic Comprehensive Panel - Opioids (National Reference Laboratory for  Breast Health (NRLBH)

Certain genes have been identified has having an effect on drug metabolism and response. Of these, the most common are the P450 (CYP) genes. When a mutation occurs in a P450 (CYP) gene, the regular enzymatic activity that is controlled by this gene is changed, resulting in either a weakened, absent, or hyper enzymatic expression. This change in enzyme activity is significant because it can impact the metabolism and clearance of many prescribed therapies potentially hindering efficacy and inducing adverse drugs reactions.

 

PGxOne Plus Pain Management (Admera Health)

PGxOne Plus is a test that predicts how patients will respond to drug therapy based on their individual genetic make-up. PGxOne Plus comprehensively screens 50 well established pharmacogenomics genes allowing physicians to make effective treatment decisions.

PGxOne Plus Pain Management tests response to muscle relaxants, NSAIDs and opioids and includes the following genes in the panel: CYP1A2, CYP2C19, CYP2C9, CYP3A4, CYP2D6, CYP2B6, OPRM1, DRD2.

 

Kailos Test for Pain Medication (Kailos Genetics)

Many different genes contribute to how an individual responds to pain medications. Kailos genetics looks very carefully at all of the genes in order to help understand how an individual responds to NSAIDs, opioids and muscle relaxants. The following genes are included in this panel CYP2D6, CYP2C9, CYP2C19.

 

Genetic Testing for the Management of Acute and Chronic Pain

The purpose of genetic testing for management of acute and chronic pain is to:

  • Select appropriate pain medications or avoid use of inappropriate pain medications
    • To identify individuals likely or unlikely to respond to a specific medication.
    • To identify individuals at a high risk of adverse drug reactions.
    • To identify individuals at high risk of opioid addiction or abuse.
  • Optimize the dose selection or frequency by
    • Identifying individuals who are likely to require higher or lower dose of a drug.

 

Patients with acute and chronic pain are likely to be managed by a wide variety of specialists such as chiropractors, general physicians, physiatrists (rehabilitation physicians), rheumatologists, orthopedic surgeons, oncologist, pain management specialist, physical therapist, acupuncturists. Most patients are likely to be tested in an outpatient setting.

 

Summary Analytic Validity

No studies were identified that specifically addressed the analytic validity of commercially available tests.

 

Summary Clinical Validity

The evidence of clinical validity of genetic testing for pain management primary consist of genome-wide association studies (GWAS) that correlate specific genetic variants with pain medication requirements or measures of pain control and case-control and cohort studies that report differences in pain medication requirements or measures of pain control for different genotypes. A variety of studies have evaluated the association of various genes with pain sensitivity or efficacy of pain medication, either directly from reports of pain or indirectly from analgesic dose requirements. Studies that evaluate the association between single nucleotide variants (SNVs) and analgesic dose requirements may provide a more objective outcome measurement of pain control; although this design makes it difficult to separate the effects of genotype on pain sensitivity from those of genotype on pain medication efficacy, these types of studies most directly translate to the clinical use of dose optimization.

 

The evidence on the clinical validity of pharmacogentic testing for pain management is characterized by a large number of studies that have evaluated associations among many different genetic variants and drug responses, risk of adverse events and addiction risk. For genes in currently available panel tests, the largest body of evidence is related to the association between the OPRM1 A118G SNV and analgesic response and addiction risk. Studies evaluating OPRM1’s role in analgesic response are generally relatively small cross-sectional studies showing associations between OPRM1 genotype and analgesic dose and/or measures of pain intensity, and others showing no significant associations. Results of several meta-analyses have not consistently demonstrated an association between OPRM1 variants and addiction risk. For other genes, the body of evidence evaluating associations between variant and analgesic response, adverse events, or addiction risk is small and inconclusive.

 

Summary of Clinical Utility

Direct evidence of clinical utility is provided by studies that have compared health outcomes for patients managed with and without the test. Preferred evidence comes from RCTs.

 

Pharmacogenomic testing for pain management has a potential role for clinical utility in several settings, including drug selection, avoidance or in dose optimization. For drug selection, pharmacogenomic testing could be used to identify individuals not likely to respond to particular drug, or to identify individuals at high risk of an adverse drug reaction. For dose optimization, pharmacogenomic testing could be used to identify individuals who are likely to be sensitive or resistant to a particular drug, or to estimate dose and dosing frequency.

Because of the lack of established clinical validity, it is not possible to establish the clinical utility of genetic testing for pain management through a chain of evidence. Two studies were identified. The first reported on the use of preemptive genetic testing for CYP2D6 metabolizer status to guide prescribing codeine to pediatric patients, but the study did not report on the impact of the genetic testing algorithm on clinical end points such as adverse effects and pain control. The second study reported on the impact of genetic panel testing to guide the selection of analgesics and reported significant improvement in total scores of a composite end point that measures analgesia, patient satisfaction, and the impact of drug-associated side effects compared to a historical control. However, methodologic limitations of the study preclude assessment of the effect on health outcomes.

 

Summary

For individuals who have need for pharmacologic pain management who receive pharmacogenomic testing to target therapy, the evidence includes genome-wide association studies, which correlate specific genetic variants with pain medication requirements or measures of pain control, case-control and cohort studies that report differences in pain medication requirements or measures of pain control for different genotypes, as well as systematic reviews and meta-analysis. The evidence on clinical validity of pharmacogenomic testing for pain management is characterized by a large number of studies that have evaluated associations between many different genetic variants and response to analgesic medication, risk of adverse events and addiction risk. The largest body of evidence assesses the association between the OPRM1 A118G single nucleotide variant and analgesic response and addiction risk, which has not consistently demonstrated significant associations. For other genes included in commercially available pain management panel tests, the evidence evaluating associations between variant and analgesic response, adverse events, or addition risk is small. At present, the clinical utility of pharmacogeneomic testing in pain management is poorly defined. Two studies were identified that reported on ways clinical management of pain can be modified based on genetic testing. The first study reported the use of preemptive genetic test for CYP2D6 metabolizer status to guide prescribing of codeine in pediatric patients but did not report the impact of the genetic testing algorithm on clinical end points such as adverse effects and pain control. The second study reported on the impacts of a genetic panel test to guide selection of analgesics and reported significant improvement in total scores of a composite end point that measured analgesia, patient satisfaction, and the impact of drug-associated side effects compared to a historical control. However, methodologic limitations precluded assessment of the effects on net health outcomes. To determine clinical utility, evidence is needed showing that testing for genetic variants leads to changes in clinical management that improve net health outcomes. Additional studies are needed in larger number of patients with randomization and blinded outcome to assess that genotyping for pain management may be associated with improved clinical outcomes. The evidence is insufficient to determine the effects of the technology on net health outcomes.

 

Genetic Testing for Warfarin (Coumadin) Dose

Genetic variants in CYP2C9 and VKORC1 genes may impact an individual’s ability to metabolize warfarin (Coumadin). It has been proposed that using information regarding an individual’s CYP2C9 and VKORC1 genotypes, as well as other characteristics, to determine a personalized starting dose of warfarin (Coumadin), may reduce the time to a stable warfarin (Coumadin) dose and avoid serious bleeding events.

 

Patients requiring treatment with warfarin (Coumadin) are managed by multiple specialists, including but not limited to cardiologists, cardiovascular surgeons, pulmonologists, internists, critical care physicians, and neurologists based on the clinical indication. Warfarin (Coumadin) is used in both inpatient and outpatient settings.

 

Warfarin (Coumadin) is indicated for the prevention and treatment of thromboembolic events in high risk individuals; warfarin (Coumadin) dosing is a challenging process, due to the narrow therapeutic window, variable response to dosing, and serious bleeding events in 5% or more of patients. Patients are typically initiated on a starting dose of 2-5 mg and monitored frequently with dose adjustments until a stable international normalized ratio (INR) value (a standardized indicator of clotting time) between 2 and 3 is achieved. During this period of adjustment, a patient is at high risk for bleeding.

 

Stable or maintenance warfarin (Coumadin) dose varies among individuals; factors influencing stable dose include body mass index, age, interacting drugs, and indication for therapy. In addition, genetic variants of cytochrome p450 2C9 (CYP2C9) and vitamin K epoxide reductase subunit C1 (VKORC1) genes together account for a substantial proportion of inter-individual variability. More recently, a single nucleotide polymorphism (change in a single base-pair in a DNA sequence) in the CYP4F2 gene has been reported to account for a small proportion of the variability in stable dose; CYP4F2 encodes a protein involved in vitamin K oxidation.

 

Using the results of CYP2C9 and VKORC1 (and possibly CYP4F2) genetic testing to predict a warfarin (Coumadin) starting dose that approximates the patient’s likely maintenance dose may benefit patients by decreasing the risk of serious bleeding events and the time to stable INR. Algorithms have also been developed that incorporate not only genetic variation but also other significant factors to predict the best starting dose.

 

A systematic review, commissioned by the American College of Medical Genetics, evaluated CYP2C9 and VKORC1 genetic testing prior to warfarin dosing and concluded the following:

  • Clinical validity: CYP2C9 and VKORC1 genotypes contribute significant and independent information to the stable warfarin dose and, compared to the most common combination, some individuals with other genotype combinations will need more than the usual dose, while others will require less.
  • Clinical utility: The purpose of genetic testing in this clinical scenario is to predict an individual’s likely stable warfarin dose by incorporating demographic, clinical, and genotype data (CYP2C9 and VKORC1), and to initiate warfarin at that predicted dose in order to limit high International Normalized Ratio (INR) values (over-anticoagulation) that are associated with an increased risk of serious bleeding events. No large study has yet shown this to be acceptable or effective. Based on limited clinical data, the number needed to treat in order to avoid one serious bleeding event is estimated to range from 48 to 385.

 

Summary Clinical Validity

In primarily white populations, several retrospective and prospective cohort studies have documented that pharmocogenomic algorithms can explain 6% to 79% of the variance in warfarin (Coumadin) maintenance dosing. In ethnically diverse populations, such algorithms can explain 40% to 59% of the variance. Accuracy of the algorithms appears to depend on the alleles tested; number of reduced function alleles present; use of interacting drugs; ethnicity; time of warfarin (Coumadin) dosing after initiation; and maintenance dose eventually required (high or low). Evidence for the ability of pharmacogenomic algorithms to predict maintenance warfarin (Coumadin) dose and to increase time in the therapeutic INR range comes from retrospective and cohort studies and is inconsistent. A single dosing algorithm readily generalizable to a diverse population and prospectively tested in a large, representative validation cohort has not been developed.

 

Summary Clinical Utility

Randomized trials and meta-analyses of these trials have examined the use of pharmacogenomics to guide initial warfarin dosing and yielded inconsistent results. Several trials showed improved ability to predict maintenance dose when genetic information was added to clinical algorithms. However, effects on INR or clinical outcomes were not always statistically significant. The ability of pharmacogenomics algorithms to improve these outcomes and net health benefit compared with current clinical data monitoring approaches has not been demonstrated.

 

Summary

While there is supporting evidence of a strong association between genetic variants and stable warfarin (Coumadin) dose, and, to a lesser extent, between genetic variants and INR  (International Normalized Ratio) and bleeding outcomes, the clinical utility (clinical outcomes) is not currently established. Several large clinical trials, including some that are randomized, strive to address clinical utility. However, at this time, there does not appear to be a consensus for one single algorithm that can be generalized for a diverse patient population and that has been validated by large, prospective, representative cohort study. The evidence is insufficient to determine the effects of the technology on net health outcomes as it is not known how patient management would change based on test results compared to usual clinical management.

 

Pharmacogenomic and Genetic Testing for Mental Health Conditions

Pharmacogenomic Testing for Mental Health Conditions

Psychiatric disorders cover a wide range of clinical phenotypes and are generally classified by symptomology in systems such as the classification outlined in the American Psychiatric Association’s Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5). In addition to counseling and other forms of behavioral treatment, treatment commonly involves 1 or more psychotropic medications that are aimed at alleviating symptoms of the disorder. Although there are a wide variety of effective medications, treatment of psychiatric disease is characterized by relatively high rates of inadequate response. This often necessitates numerous trials of individual agents and combinations of medications to achieve optimal response.

 

Knowledge of the physiologic and genetic basis of psychiatric disorders is advancing rapidly and may substantially alter the way in which these disorders are classified and treated. Genetic testing could potentially be used in several ways including stratifying patients’ risks of developing a particular disorder, aiding diagnosis, targeting medication therapy, and optimally dosing medication. Better understanding of these factors may lead to an improved ability to target medications to the specific underlying abnormalities, with potential improvement in the efficiency and efficacy of treatment (pharmacogenomics). Several labs offer commercially available genetic tests either as panels or individual tests relevant for mental health disorders.

 

Mental health disorders encompass a wide range of conditions: the DSM-5 includes more than 300 different disorders. However, currently available genetic testing for mental health disorders is primarily related to several clinical situations:

  • Risk stratifying patients for one of several mental health conditions, including schizophrenia and related psychotic disorders, bipolar and related disorders, depressive disorders, obsessive-compulsive and related disorders, and substance-related and addictive disorders.
  • Pharmacogenomics - predicting patient’s response to, dose requirement for, or adverse effects from one of several medications (or classes of medications) used to treat mental health conditions, including: typical and atypical antipsychotic agents, serotonin and serotonin/norepinephrine reuptake inhibitors (SSRIs), and medications used to treat addiction, such as disulfiram.

 

Individual genes have been shown to be associated with risk of psychiatric disorders. Commercially available testing panels include several of these genes which are outlined below:

  • Serotonin Transporter (SLC6A4): The serotonin transporter gene (SLC6A4) is responsible for coding the protein that clears serotonin metabolites (5-HT) from the synaptic spaces in the central nervous system (CNS). This protein is the principle target for many of the SSRIs. By inhibiting the activity of the SLC6A4 protein, the concentration of 5-HT in the synaptic spaces is increased. A common polymorphism in this gene consists of insertion or deletion of 44 base pairs in the serotonin-transporter-linked polymorphic region (5-HTTLPR), leading to the terminology of the long (L) and short (S) variants of this gene. These polymorphisms have been studied in relation to a variety of psychiatric and non-psychiatric conditions, including anxiety, obsessive compulsive disorder, and response to SSRIs.
  • Serotonin Receptor (5HT2C): This gene codes for 1 of at least 6 subtypes of the serotonin receptor that is involved in the release of dopamine and norepinephrine. These receptors play a role in controlling mood, motor function, appetite, and endocrine secretion. Alterations in functional status have been associated with affective disorders such as anxiety and depression. Certain antidepressants, e.g., mirtazapine and nefazodone, are direct antagonists of this receptor. There is also interest in developing agonists of the 5HT2C receptor as treatment for obesity and schizophrenia, but no such medications are commercially available at present.
  • Serotonin Receptor (5HT2A): The 5HT2A gene codes for another subtype of the serotonin receptor. Variations in the 5HT2A gene have been associated with susceptibility to schizophrenia and obsessive compulsive disorder and response to certain antidepressants.
  • Sulfotransferase Family 4A, Member 1 (SULT4A1): SULT4A1 encodes a protein that is involved in the metabolism of monoamines, particularly dopamine and norepinephrine. This has been studied in schizotypical personality disorder and schizophrenia.
  • Dopamine Receptors (DRD1, DRD2, DRD4): The DRD2 gene codes for a subtype of the dopamine receptor, called the D2 subtype. The activity of this receptor is modulated by G-proteins, which inhibit adenyl cyclase. These receptors are involved in a variety of physiologic functions related to motor and endocrine processes. The D2 receptor is the target of certain antipsychotic drugs. Mutations in this gene have been associated with schizophrenia and myoclonic dystonia. Polymorphisms of the DRD2 gene have been associated with addictive behaviors, such as smoking and alcoholism.  
    • The DRD1 gene encodes another G protein coupled receptor that interacts with dopamine to mediate some behavioral responses and modulate D2 receptor-mediated events. Polymorphisms of the DRD1 gene have been associated with nicotine dependence and schizophrenia.
    • The DRD4 gene encodes a dopamine receptor with a similar structure; DRD4 polymorphisms have been associated with risk-taking behavior and attention deficit hyperactivity disorder.
  • Dopamine Transporter (DAT1 or SLC6A3): Similar to the SCL6A4 gene, the dopamine transporter gene (DAT1 or SLC6A3) encodes a transporter that mediates the active reuptake of dopamine from the synaptic spaces in the CNS. Polymorphisms in this gene are associated with Parkinson disease, Tourette syndrome, and addictive behaviors.
  • Dopamine Beta-Hydroxylase (DBH): The dopamine beta-hydroxylase protein encoded by this gene catalyzes the hydroxylase of dopamine to norepinephrine. It is primarily located in the adrenal medulla and in postganglionic sympathetic neurons. Variation in DBH gene has been investigated as a modular of psychotic symptoms in psychiatric disorders and in tobacco addiction.
  • Gated Calcium Channel (CACNA1C): The gated calcium channel gene (CACNA1C) is responsible for coding of a protein that controls activation of voltage-sensitive calcium channels. Receptors for this protein are found widely throughout the body, including skeletal muscle, cardiac muscle, and in neurons in the CNS. In the brain, different modes of calcium entry into neurons determine which signaling pathways are activated, thus modulating excitatory cellular mechanisms. Associations of polymorphisms of this gene have been most frequently studied in related to cardiac disorders. However, a large scale genetic analysis conducted in 2008 shows the possibility that CACNA1C has been associated with bipolar disorder and subsequently also with schizophrenia.
  • Ankyrin 3 (ANK3): Ankyrins are proteins that are components of the cell membrane and interconnect with the spectrum-based cell membrane skeleton. The ANK3 gene codes for the protein Ankyrin G, which has a role in regulating sodium channels in neurons. Alterations of this gene have been associated with cardiac arrhythmias such as Brugada syndrome. Polymorphisms of this gene have also been associated with bipolar disorder, cyclothymic depression, and schizophrenia.
  • Catechol O-Methyltransferase (COMT):  The catechol O-methyltransferase gene (COMT) codes for the COMT enzyme that is responsible for the metabolism of the catecholamine neurotransmitters, dopamine, epinephrine, and norepinephrine. COMT inhibitors, such as entacapone are currently used in the treatment of Parkinson disease. A polymorphism of the COMT gene, the Val158Met polymorphism, has been associated with alterations in emotional processing and executive function and has also been implicated in increasing susceptibility to schizophrenia.
  • Methylenetetrahydrofolate Reductase (MTHFR): The Methylenetetrahydrofolate Reductase gene (MTHFR) is a widely studied gene that codes for the protein that converts folic acid to methylfolate. Methylfolate is a precursor for the synthesis of norepinephrine, dopamine and serotonin. It is a key step in the metabolism of homocysteine to methionine, and deficiency of MTHFR can cause hyperhomocysteinemia and homocystinuria. The MTHFR protein also plays a major role in the epigenetics, through methylation of somatic genes. A number of polymorphisms have been identified that a result in altered activity of the MTHFR enzyme. These polymorphisms have been associated with a wide variety of clinical disorders, including vascular disease, neural tube defects, dementia, colon cancer and leukemia.
  • y-Aminobutyric Acid A Receptor: This gene encodes a ligand-gated chloride channel composed of 5 subunits that responds to GABA, a major inhibitory neurotransmitter. Mutations in the y-aminobutyric acid (GABA) receptor have been associated with several epilepsy syndromes.
  • u and k Opioid Receptors: OPRM1 encodes the u-opioid receptor, which is a G-protein coupled receptor that is the primary site of action for commonly used opioids, including morphine, heroin, fentanyl, and methadone. Polymorphisms in the OPRM1 gene have been associated with differences in dose requirements for opioids. OPRK1 encodes the k-opioid receptor, which binds the natural ligand dynorphin and a number of synthetic ligands.
  • Cytochrome p450 Genes: CYP2D6, CYP2C19, CYP3A4, CYP1A2, CYP2C9, and CYP2B6 code for hepatic enzymes that are members of the cytochrome p450 family and are responsible for the metabolism of a wide variety of medications, including many psychotropic agents. For each of these genes, polymorphisms exist that impact the rate of activity, and therefore the rapidity of elimination of drugs and their metabolites. Based on the presence or absence of polymorphisms, patients can be classified as rapid metabolizers (RM), intermediate metabolizers (IM), and poor metabolizers (PM).      
  • P-Glycoprotein Gene: The ABCB1 gene, also known as the MDR1 gene, encodes P-glycoprotein which is involved in the transport of most antidepressants across the blood-brain barrier. ABCB1 polymorphisms have been associated with differential response to antidepressants that are substrates of P-glycoprotein, but not to antidepressants that are not P-glycoprotein substrates.
  • UDP-Glucuronosyltransferase Gene: The UDP-glucuronosyltransferase gene, UGT1A4, encodes an enzyme of the glucuronidation pathway that transforms small lipophilic molecules into water-soluble molecules. Polymorphisms in UGT1A4 have been associated with variation in drug metabolism, including some drugs used for mental health disorders.

 

Panels of genetic tests have been developed and have been proposed for use of  predicting patient’s response to, dose requirement for, or adverse effects from one of several medications (or classes of medications) (pharmacogenomics) used to treat mental health conditions. Examples of specific panels and the genes included are summarized below.

 

GeneceptTM Assay (Genomid)

The GeneceptTM Assay is a genetic panel test that includes a range of genetic mutations and/or polymorphisms that have been associated with psychiatric disorders and/or response to psychotropic medication. The test consists of a group of individual genes, and the results are reported separately for each gene. There is no summary score or aggregate results derived from this test. The intent of the test is as a decision aid for treatment interventions, particularly in the choice and dosing of medications for a range of psychiatric conditions including depression, anxiety, obsessive compulsive disorder (OCD), attention deficit hyperactivity disorder (ADHD), bipolar disorder, post - traumatic stress disorder (PTSD), autism and schizophrenia. Interpretation of the results and any management changes as a result of the test are left to the judgement of the treating clinician. Genetic variants included in this panel are the following: SLC6A4, 5HT2C, DRD2, CACNA1C, ANK3, COMT, MTHFR, CYP2D6, CYP2C19. 

 

STA2R (Surgene Test for Antipsychotic and Antidepressant Response, Surgene, LLC, Louisville, KY) 

The STA2R is panel of genetic tests that gives prescribers additional information upon which to evaluate or help base medication selection. The test provides information regarding the potential response of individual patients to antipsychotic and antidepressant treatment based upon the information known about their genetic makeup and the influence of genetics on drug response. This response information covers three areas: clinical response, adverse event liability, and drug metabolism. Currently, the test provides detailed information for the most widely used atypical antipsychotics and antidepressants. While the test report describes the patient’s most likely response to the listed drugs, every patient is unique and not all patients will respond in a typical fashion. The specific genes included in this panel are the following: SULT4A1, SLC6A4, CYP2D6, CYP2C19.

 

GeneSight (Assurex Health, Mason, OH)

GeneSight Is a panel of genetic tests that helps the healthcare provider take a personalized approach to prescribing medications for patients. Because genes influence the way a person’s body responds to specific medications, they may not work the same for everyone. Using DNA gathered with a simple cheek swab, GeneSight analyzes a patient’s genes and provides individualized information to help healthcare providers select medication that better match their patient’s genes. The treating provider receives a report with the most common medications for the patient’ s diagnosed condition categorized by cautionary level, along with the report of the patient’s genetic variants. Details are not provided about the algorithm used by the manufacturer to generate risk levels. GeneSight tests include the following:

  • GeneSight Psychotropic – The GeneSight Psychotropic test analyzes how genes affect the way one’s body may respond to FDA-approved medications commonly prescribed to treat depression, anxiety, bipolar disorders, post-traumatic stress disorder (PTSD), premenstrual dysphoric disorder, obsessive compulsive disorder (OCD), schizophrenia or other behavioral health conditions. The specific gene included in this panel are the following: SLC6A4, 5HT2C, MTHFR, CYP2D6, CYP2C19, CYP3A4, CYP1A2, CYP2C9, CYP2B6.
  • GeneSight ADHD – The GeneSight ADHD test analyzes how genes affect the way one’s body may respond to FDA approved medicines commonly prescribed to treat ADHD or narcolepsy. Panel includes the following: CYP2D6, COMT, ADRA2A.    
  • GeneSight MTHFR – The GeneSight MTHFR test analyzes one gene to predict how the body converts folic acid into its active form. This information will assist the healthcare provider to decide is the patient may benefit from an additional folic acid supplement. Folate deficiency can result in abnormal homocysteine levels and may interfere with the creation of dopamine, norepinephrine and serotonin. Panel includes the following: MTHFR

 

Mental Health DNA Insight Panel (Pathway Genomics, San Diego, CA) 

Mental Health DNA Insight® analyzes patients DNA to identify specific genetic variants that can affect how they respond to over 50 psychiatric medications indicated for major depressive disorder (MDD), schizophrenia, bipolar disorder, epilepsy, seizures, attention deficit/hyperactivity disorder (ADHD), anxiety and other neurological disorders. Report indicates the following categories: green category the drug can be prescribed and used according to the FDA approved drug label; orange category signals caution – may indicate that the dosing levels need to be lowered or increased, or that the drug’s side effects may cause and adverse reaction for the patient; and the red category indicates that the drug should be used with caution and with more frequent monitoring due to the potential risk of a severe adverse reaction or lack of therapeutic response. Alternative medications are strongly recommended. The specific genes included in this panel are the following: SLC6A4, 5HT2A, UGT1A4, ABCB1, CYP2D6, CYP2C19, CYP1A2.

 

Alpha Genomic Psychiatry/ADHD Panel (Alpha Genomix Laboratory)

This panel provides patient-specific genetic information implicated in behavioral health. The report delivers dosing guidelines for currently affected medications and a listing of all risk-related medications commonly used in behavioral health to assist the clinicians in determining the most cost effective dose and medication, potentially eliminating multiple medication trials. Panel includes the following: CYP1A2, CYP2C9, CYP2D6, CYP3A4 and CYP3A5, ADRA2A and COMT.

 

Idgenetix (AltheaDx, San Diego, CA)

AltheaDX offers a number of IDgenetix-branded tests, which include several panels focusing on polymorphisms that affect medication pharmacokinetics for a variety of disorders, including psychiatric disorders. NeuroIDgenetix (psychiatric) panel appears to include the following: CYP2D6, CYP2C19, CYP2C9, HTR2A and HTR2C.

 

Ally Diagnostics Genetic Testing Panel (Ally Clinical Diagnostics, Farmers Beach, TX) 

Ally Diagnostics Genetic Testing Panel is a panel to evaluate genes that may affect a patient’s response to medications for the treatment of psychiatric or mental health symptoms or disorders. Specific mutations included in the panel were not easily identified on their website. 

 

Molecular Testing Labs Psychotropic Medication Panel (Molecular Testing Labs, Vancouver, WA)

The Molecular Testing Labs Psychotropic Medication Panel is a genetic testing panel that provides a comprehensive analysis of how a patient’s body responds/metabolizes many different psychotropic medications. The report lists the genes present in the patient, and will also include a clear and intuitive table that lists psychotropic medications that the patient should metabolize normally based on the genes listed; drugs which should be prescribed with caution, possibly altering dose and frequency; and a list of drugs for which the clinician may want to consider an alternative medication, whether for safety or efficacy reasons. The only specific gene mentioned in CYP2D6.

 

PGXL Multi-Drug Panel (PGXL Laboratories)

PGXL’s broad spectrum drug sensitivity panel covers the genes know to determine the efficacy of 95% of medications and identifies patients susceptible to adverse events and red-flags drug interactions that complicate patients care.

The PGXL Multi-Drug Panel includes CYP2D6, CYP2C9, CYP2C19, CYP1A2, CYP3A4, CYP3A5, SLC6A4, OPRM1, VKORC1, SLCOB1, Factor II (prothromib 20210 G>A), Factor V, MTHFR and COMT.

 

Genetic Technological Innovations Pharmacogenetic Testing 

Genetic Technological Innovations Pharmacogenetic Testing offers genetic testing for drug metabolism. The test report provides details on how the patient’s body metabolizes medications and suggests alternative prescriptions when increased sensitivity or reduced response is likely. Allows the clinician to tailor the treatment uniquely to the patient. Website does not specify the specific genetic mutations included in the panel.

 

Millennium Pharmacogenetic Testing (PGT) (Millennium Health)

Millennium Pharmacogenetic Testing analyzes clinically relevant genetic variants for 14 genes related to medication response to help clinicians individualize prescribing decisions. Benefits of Millennium PGT in Mental Health: Identifies potentially harmful drug interactions resulting from polypharmacy; and assists clinicians in determining the most effective medication and dose, potentially reducing multiple medication trials. Millennium PGT can be ordered by medical specialty, by medication/medication class, and by individual gene-drug pairs:

  • Antidepressants, Selective Serotonin Reuptake (SSRIs)/Serotonin-Norepinephrine Reuptake Inhibitors (SNRIs) (CYP2C19, CYP2D6, MTHFR)
  • Antidepressants, TCA (CYP2C19, CYP2D6)
  • Antipsychotics (CYP2D6, DRD2, HTR2C)
  • ADHD Therapy (CYP2D6)
  • Benzodiazepines (CYP2C19, UGT2B15)

 

YouScript Panels (Genelex)

Genelex currently offers 28 pharmacogenetic tests to help physicians target treatment and medication to patients genetics. Test can be ordered as a panel or individually. Panels include the following:

  • YouScript Psychotropic: (CYP2D6, CYP2C19, CYP1A2, HRT2A and SLC6A5/5-HTT)
  • YouScript Psychotropic Plus: (CYP2D6, CYP2C19, CYP3A4, ADRA2A, CYP1A2, CYP2B6, COMT, GRIk4, HTR2A, MTHFR, and SLC6A4/5-HTT)
  • YouScript ADHD: (CYP2D6, COMMT, ADRA2A)

 

PersonaGene Panel PsychiaGene (AIBio Tech)

Targeted drug therapy can help reduce side effects and improve adherence. Genetic variations in cytochrome P450 enzymes can directly influence the effectiveness and tolerability of commonly prescribed tricyclic antidepressants, SSRIs and antipsychotics. Panel includes CYP3A4, CYP2C19, CYP2C9, CYP2D6.

 

Pharmacogenomic Comprehensive Panel for Antidepressants or Antipsychotics (National Reference Laboratory for Breast Health (NRLBH))

Certain genes have been identified has having an effect on drug metabolism and response. Of these, the most common are the P450 (CYP) genes. When a mutation occurs in a P450 (CYP) gene, the regular enzymatic activity that is controlled by this gene is changed, resulting in either a weakened, absent, or hyper enzymatic expression. This change in enzyme activity is significant because it can impact the metabolism and clearance of many prescribed therapies potentially hindering efficacy and inducing adverse drugs reactions

 

PGxOne Plus Psychiatry (Admera Health)

PGxOne Plus is a test that predicts how patients will respond to drug therapy based on their individual genetic make-up. PGxOne Plus comprehensively screens 50 well established pharmacogenomics genes allowing physicians to make effective treatment decisions.

PGxOne Plus Psychiatry tests for response to anti-manic agents, antipsychotic agents, anti-anxity agents, SSRIs, SNRIs, Stimulants, ADHD and antidepressants and includes the following genes in the panel: ABCB1, COMT, OPRM1, CNR1, ANKK1, HTR2C, FAAH, SLC6A4, HTR1A, UGT2B15, DRD2, CYP3A5, CYP2C19, CYP2D6, CYP3A4, CYP1A2.

 

Kailos Test for Antidepressants (Kailos Genetics)

Many different genes contribute to how an individual responds to antidepressants. Kailos Genetics looks very carefully at all genes in order to help understand how the individual may respond to tricyclic antidepressants, SSRIs, and SNRIs. The panel include CYP2D6, CYP2C19, ABCB1.

 

Pharmacogenomic testing in patients who are being treated with or considered for therapy with a number of different medications used to treat mental illness is to inform a decision whether to start a particular drug, set or adjust dose, or change drugs when a therapy fails. Interventions of interest include testing for genes associated with medication pharmacokinetics and/or pharmacodynamics, either as single genes or as a panel. Currently decisions about medication management for mental illnesses are typically based on clinical response. The primary outcome of interest is change in disease outcomes resulting from more appropriate selection of specific drugs or doses for the patient’s condition. In addition, avoidance of adverse effects is an important outcome. Testing would generally occur in the primary care or mental health practice setting.

 

Genetic variants may alter medications pharmacokinetics (i.e. how medications are absorbed, distributed, metabolized or excreted) or pharmacodynamics (i.e. medications effects on the body); therefore, individual genetic differences may lead to variability in the effectiveness of medications used to treat mental health disorders. To distinguish genes predictive of treatment response, versus those prognostic (predictive of outcome independent of treatment), it is usually necessary for studies to evaluate outcomes in patients receiving treatment and in patients not receiving treatment (or receiving alternative treatment). A gene that is predictive will result in a study demonstrating an interaction between genotype and treatment. In many studies claiming to evaluate genotype and treatment response, only patients receiving treatment have been evaluated.

 

Based on review of the literature no studies were identified addressing analytic validity of commercially available tests for mental health panels or specific genes.

 

Genetic variants appear to have some association with response to medication, particularly for SLC6A4 variants and response to antidepressants. However, because many studies did not include untreated patients or patients treated with alternative therapies, one cannot determine from many of these studies whether the identified genes are predictive of treatment response or are simply prognostic factors (predictive of outcome independent of treatment).

 

Management changes that might be made in response to genetic testing information include selection of specific medications according to test results, discontinuation of medications, and change in dosing of medications. However, management changes made in response to genetic testing information are not well defined and may vary according to the judgement of the treating clinician. Currently there are no specific recommended changes in management linked to specific test results, making it difficult to assess whether test results lead to improvements in net health outcomes.

 

A limited number of studies have evaluated clinical outcomes associated with genetic testing panels for mental health disorders, primarily using the GeneSight panel test, with other studies using other tests. A small randomized controlled trial (RCT) did not show a difference in treatment outcomes. Nonrandomized studies that have provided evidence that a genotype report may be associated with differences in depression treatment outcomes; however, weaknesses in the studies limit the conclusions that can be drawn. Additional studies in larger number of patients with randomization and blinded outcome assessment will be needed to confirm findings that genotyping may be associated with improved clinical outcomes.

 

Summary

For individuals who have a mental health disorder who are undergoing drug treatment who receive genetic testing for genes associated with medication and pharmacokinetics (i.e. how medications are absorbed, distributed, metabolized or excreted) or pharmacodynamics (i.e. medications effects on the body), the evidence includes a large number of observational studies assessing specific genes and outcomes of drug treatment, and a limited number of studies comparing outcomes for patients who have undergone genetic testing with those who have not. Some studies comparing patients who have had and have not had genetic testing have shown that testing may be associated with differences in depression treatment outcomes. However, methodologic shortcomings limit the conclusions that can be drawn. Most studies are nonrandomized. One small randomized controlled trial did not show a difference in patient outcomes. Additional studies in larger number of patients with randomization and blinded outcome assessment will be needed to confirm findings that genotyping may be associated with improved clinical outcomes. The evidence is insufficient to determine the effects of this technology on net health outcomes.

 

Testing for Diagnosis or Risk of Mental Health Disorder 

The purpose of testing for genes associated with increased risk of mental illness in patients who are currently asymptomatic is to identify patients for whom an early intervention during a presymptomatic phase of the illness might facilitate improved outcomes. The relevant population of interest is an asymptomatic individual who would consider an intervention if a genetic variant were detected. The intervention of interest is testing for genes associated with increased risk of mental illness, either as a panel or a single gene.

 

At present, decisions about management of mental illnesses are made when patients present with symptoms, are typically diagnosed based on clinical evaluation according to standard criteria (i.e. Diagnostic and Statistical Manual of Mental Disorders. The primary outcome of interest is change in disease outcomes, which would result directly from changes in management that could be instituted because of earlier disease detection. For many mental illnesses, there are standardized outcome measures (e.g. Hamilton Depression Rating Scale). This testing would generally occur in the primary care or mental health practice setting.

 

The association between mental health disorders and individual genetic variants is an area of active investigation. For genes included in currently available genetic testing panels, the largest body of evidence appears to be related to the role of SLC6A4 and various dopamine receptor gene variants and multiple mental health disorders. The association with disease risks appears to be relatively weak and not consistently demonstrated across studies. Studies have not been conducted to determine the diagnostic capability or precise risk prediction, but to determine whether the particular genotype of interest is associated with mental health disorders. Diagnostic characteristics of the genes or validated risk estimates in clinically relevant populations are not available.

 

Although studies have suggested that there may be a number of genetic variants associated with increased risk of mental health disorders and/or response to specific treatment, estimates of the magnitude of the increased risk vary across studies. For the individual tests, results from GWAS and case-control studies are insufficient to determine clinical utility. There is no strong chain of indirect evidence supporting the clinical utility of any of the previously mentioned genes associated with disease risk. To determine clinical utility, evidence is needed showing that testing for variants in these genes leads to changes in clinical management that improve net health outcomes.

 

Summary

For individuals who are evaluated for diagnosis or risk of a mental health disorder who receive genetic testing for risk of that disorder, the evidence includes various observational studies evaluating the relation between the mental health disorder of interest and candidate genes. Most studies have evaluated the association between genotype and mental health disorders without a clinical perspective; thus diagnostic characteristics and validated risk predictions among specific clinical populations are unknown. The associations tend to be weak and would likely result in poor diagnostic characteristics. There is no clear clinical strategy for how the associations of specific genes and mental health disorders would be used to diagnose a specific patient or to manage a patient at higher risk of a specific disorder. The evidence is insufficient to determine the effects of this testing on net health outcomes.

 

Practice Guidelines and Position Statements 

Evaluation of Genomic Applications in Practice and Prevention (EGAPP) 

CYP450 Genotyping to Predict Response to SSRIs Used to Treat Non-psychotic Depression in Adults: EGAPP™ Recommendation

In 2007, the independent Evaluation of Genomic Applications in Practice and Prevention (EGAPP™) Working Group  determined that there was not enough evidence to state whether CYP450 genotyping should or should not be used to help health care providers make decisions about beginning SSRI treatment in adults with non-psychotic depression. They discouraged use of such testing until more studies evaluating potential harms and benefits are conducted.

The EGAPP recommendation statement was based on the following key points from the evidence review:

  • In studies of people undergoing SSRI treatment, the results of their CYP450 genotyping did not show a clear relationship with the actual levels of the SSRI drug in their blood.
  • CYP450 genotyping results were not clearly related to how well the SSRI worked or the presence or severity of negative side effects.
  • No evidence was found to indicate that the use of CYP450 genotyping improved health outcomes or helped patients or doctors make decisions about the use of SSRI drugs.
  • The potential harms of CYP450 genotyping are:
    • Increased health care costs without clear benefit to the patient.
    • Patients may receive less effective treatment with SSRI drugs.
    • Genotyping information may be used inappropriately for managing other drugs metabolized by CYP450 enzymes

 

American College of Cardiology Foundation (ACCF) and American Heart Association (AHA)

In 2010, the American College of Cardiology Foundation (ACCF) and the American Heart Association (AHA) issued a consensus statement on genetic testing for selection and dosing of clopidogrel, and their recommendation for practice included the following statements:

  • Adherence to existing ACCF/AHA guidelines for the use of antiplatelet therapy should remain the foundation for therapy. Careful clinical judgment is required to assess the importance of the variability in response to clopidogrel for an individual patient and its associated risk to the patient.
  • Clinicians must be aware that genetic variability in CYP enzymes alter clopidogrel metabolism, which in turn can affect its inhibition of platelet function. Diminished responsiveness to clopidogrel has been associated with adverse patient outcomes in registry experiences and clinical trials.
  • The specific impact of the individual genetic polymorphisms on clinical outcome remains to be determined.
  • Information regarding the predictive value of pharmacogenomic testing is very limited at this time; resolution of this issue is the focus of multiple ongoing studies. The selection of the specific test, as well as the issue of reimbursement, is both important additional considerations.
  • The evidence base is insufficient to recommend either routine genetic or platelet function testing at the present time. Clinical judgement is required to assess clinical risk and variability in patients considered to be at increased risk. Genetic testing to determine if a patient is predisposed to poor clopidogrel metabolism (poor metabolizers) may be considered before starting clopidogrel therapy in patients believed to be at moderate or high risk for poor outcomes. This might include, among others, patients undergoing elective high risk PCI procedures (e.g. treatment of extensive and/or very complex disease). If such testing identifies a potential poor metabolizer, other therapies, particularly prasugrel for coronary patients should be considered.  
  • There are several possible therapeutic options for patients who experience an adverse event while taking clopidogrel in the absence of any concern about medication compliance

 

In 2012, the American College of Cardiology Foundation (ACCF) and the American Heart Association (AHA) issued and updated guideline for the management of patients with unstable angina/non-ST-elevation myocardial infarction which stated the following:

  • Since the FDA announced a “Boxed Warning” on March 12, 2010, about the diminished effectiveness of clopidogrel in patients with an impaired ability to convert the drug into its active form, there has been interest in whether clinicians should perform routine testing in patients being treated with clopidogrel. The routine testing could be for genetic variants of the CYP2C19 allele and/or for overall effectiveness for inhibition of platelet activity.
  • The FDA label revision does not mandate testing for CYP2C19 genotypes or overall platelet function. The revision serves to warn clinicians that certain patient subgroups may exhibit reduced clopidogrel-mediated platelet inhibition and emphasizes that clinicians should be aware of alternative treatment strategies to tailor alternative therapies when appropriate.

 

Our recommendations for the use of genotype testing and platelet function testing seek to strike a balance between not imposing undue burden on clinicians, insurers, and society to implement these strategies in patients with unstable angina (UA) or non-ST-elevation myocardial infarction (NSTEMI) and that of acknowledging the importance of these issues to patients with UA/NSTEMI. Our recommendation that the use of either strategy may have some benefit should be taken in the context of the remarks in this update, as well as the more comprehensive analysis in the ACCF/AHA Clopidogrel Clinical Alert. The Class IIb recommendation of these strategies suggests that a selective, limited approach to platelet genotype assessment and platelet function testing is the more prudent course until better clinical evidence exists for us to provide a more scientific derived recommendation.

 

American Society of Clinical Oncology (ASCO)

In 2013, the American Society of Clinical Oncology (ASCO) issued a clinical practice guideline for the use of pharmacologic interventions for breast cancer risk reduction which states the following information:

  • Testing for CYP2D6 Allelic Variants in the Prevention Setting: Since the last guideline, additional data have been generated on the relationship between functional allele variants in cytochrome P450 2D6 gene (CYP2D6), use of CYP2D6 inhibitors including selective serotonin reuptake inhibitors, and breast cancer incidence. Data from the NSABP-P1 and STAR trials do not support the use of CYP2D6 testing to identify women not likely to benefit from tamoxifen therapy for breast cancer prevention.

 

National Comprehensive Cancer Network (NCCN)

Breast Cancer Risk Reduction Version 1.2017: It has been reported that certain CYP2D6 genotypes are markers of poor tamoxifen metabolism. Nevertheless, the consensus of the NCCN Breast Cancer Risk Reduction Panel is that further validation of this biomarker is needed before it can be used to select patients for tamoxifen therapy.

 

American College of Medical Genetics Policy Statement: Pharmacogenetic Testing of CYP2C9 and VKORC1 Alleles for Warfarin

The 2008 American College of Medical Genetics policy statement concluded: “There is insufficient evidence, at this time, to recommend for or against routine CYP2C9 and VKORC1 testing in warfarin-naive patients because no substantive prospective study has yet shown this intervention to be effective in reducing the incidence of high INR values, the time to stable INR, or the occurrence of serious bleeding events, while maintaining the ability of the drug to prevent thrombolytic events.”

 

American College of Chest Physicians

The 9th Edition of the American College of Chest Physicians Evidence Based Clinical Practice Guidelines on Antithrombotic Therapy and Prevention of Thrombosis, published in 2012, states:  “ For patients initiating VKA (vitamin K antagonist) therapy, the expert panel recommends against the routine use of pharmacogenetic testing for guiding doses of VKA.” (Grade 1B)

 

International Society of Psychiatric Genetics

In 2013, International Society of Psychiatric Genetics issued a statement regarding genetic testing for psychiatric disorders. This statement was revised on 1/26/2017 which states the following:

 

Summary Recommendations:
  • Single genetic variants are not sufficient to cause psychiatric disorders such as depression, bipolar disorder, substance dependence, or schizophrenia. Thus there are no genetic tests that can establish a diagnosis of these conditions.
  • Although they lack diagnostic specificity, certain copy number variants (CNVs) are more prevalent in individuals with autism spectrum disorders, schizophrenia, or other psychiatric disorders, especially when accompanied by intellectual disability. Identification of these CNVs may help diagnose rare conditions that have important medical and psychiatric implications for the individual patients and may inform family counseling. Identification of de novo CNVs may also have a place in the management of serious psychiatric disorders, especially those that present atypically or in the context of intellectual disability or certain medical syndromes.
  • Some pharmacogenomic tests are useful in reducing risk of adverse events in specific patients. Clinicians should be aware of and consider pharmacogenomics recommendations advanced by regulatory agencies, such as the U.S. Food and Drug Administration, and expert groups, such as the Clinical Pharmacogenetics Implementation Consortium (CPIC).
  • Emerging data regarding clinical utility and cost effectiveness of pharmacogenomics panels are trending in an encouraging direction, but their general use in unselected patients is not well supported by the present body of evidence. Double-blinded randomized clinical trials are needed to clarify whether patients benefit substantially from pharmacogenetic testing.
  • Professional counseling can play an important in the decision to undergo genetic testing and in the interpretation of genetic test results. We recommend that diagnostic and genome-wide genetic testing should include counseling by a professional with expertise in both mental health and in the interpretation of genetic tests. Medical genetics consultation may be indicated when test results uncover a recognized genetic disorder or other findings with reproductive or other broad health implications.
  • Whenever genome-wide testing is performed, the possibility of incidental (secondary) findings must be communicated in a clear and open manner, and procedures for dealing with such findings should be made explicit. The autonomy of competent patients regarding preferences for notification of incidental findings should be respected.
  • Expanded research efforts are needed to clarify the proper role of genetic testing and its clinical utility in psychiatric care.

 

Clinical Pharmacogenetics Implementation Consortium

In 2012, the Clinical Pharmacogenetics Implementation Consortium issued a guideline for cytochrome P450 2D6 genotype and codeine therapy, which was updated in 2014 to reflect U.S. Food and Drug Administration (FDA) labeling about codeine in children status post tonsillectomy with or without adenoidectomy and to include other opioids metabolized by CYP2D6. These guidelines did not specifically recommend CYP2D6 genotyping in particular patients, although they did provide the following codeine therapy recommendations based on CYP2D6 phenotype.

  • Ultrarapid metabolizer – avoid codeine use due to potential for toxicity.
  • Extensive metabolizer- use label recommended age or weight specific dosing.
  • Intermediate metabolizer – use label recommended age or weight specific dosing. If no response consider alternative analgesics (e.g. morphine or a non-opioid).
  • Poor metabolizer – avoid codeine use due to lack of efficacy.

 

Regulatory Status 

CYP450 Genotyping to Determine Drug Metabolizer Status

Diagnostic genotyping tests for certain CYP450 enzymes are now available. Some tests are offered as in-house laboratory developed test services, which do not require U.S. Food and Drug Administration (FDA) approval but which must meet Clinical Laboratory Improvement (CLIA) quality standards.
Several test kits for CYP450 genotyping have been cleared for marketing by the FDA (FDA product code: NTI). These include:

  • The AmpliChip® (Roche Molecular Systems, Inc.) is an FDA-cleared test for CYP450 genotyping. The AmpliChip® is a microarray consisting of many DNA sequences complementary to 2 CYP450 genes and applied in microscopic quantities at ordered locations on a solid surface (chip). The AmpliChip® tests the DNA from a patient’s white blood cells collected in a standard anticoagulated blood sample for 29 polymorphisms and mutations for the CYP2D6 gene and 2 polymorphisms for the CYP2C19 gene. CYP2D6 metabolizes approximately 25% of all clinically used medications (e.g., dextromethorphan, beta-blockers, antiarrhythmics, antidepressants, and morphine derivatives), including many of the most prescribed drugs. CYP2C19 metabolizes several important types of drugs, including proton-pump inhibitors, diazepam, propranolol, imipramine, and amitriptyline. FDA cleared the test “based on results of a study conducted by the manufacturers of hundreds of DNA samples as well as on a broad range of supporting peer-reviewed literature.” According to FDA labeling, “Information about CYP2D6 genotype may be used as an aid to clinicians in determining therapeutic strategy and treatment doses for therapeutics that are metabolized by the CYP2D6 product.”
  • The xTAG® CYP2D6 Kit (Luminex Molecular Diagnostics, Toronto, ON) was cleared for marketing in August 2010 based on substantial equivalence to the AmpliChip CYP450 test. It is designed to identify a panel of nucleotide variants within the polymorphic CYP2D6 gene on chromosome 22.
  • The INFINITI CYP2C19 Assay (AutoGenomics Inc., Vista, CA) was cleared for marketing in October 2010 based on substantial equivalence to the AmpliChip CYP450 test. It is designed to identify variants within the CYP2C19 gene (*2, *3, and *17)
  • Verigene CYP2C19 Nucleic Acid Test (Nanosphere Inc., Northbrook, IL) , designed to identify variants within the CYP2C19 gene, was cleared for marketing in November 2013 based on substantial equivalence to the INFINITI CYP2C19 Assay.
  • The Spartan RX CYP2C19 Test System Spartan Bioscience, Redwood Shores, CA), designed to identify variants in the CYP2C19 gene (*2, *3, and *17 alleles), was cleared for marketing in August 2013 based on substantial equivalence to the INFINITI CYP2C19 Assay.
  • The xTAG® CYP2C19 Kit v3 (Luminex Molecular Diagnostics, Toronto, ON), designed to identify variants in the CYP2C19 gene (*2, *3, and *17 alleles) was cleared for marketing in September 2013 based on substantial equivalence to the INFINITI CYP2C19 Assay.

 

FDA approval 2008 Tetrabenazine (xanazine): Patients requiring doses above 50 mg per day should be genotyped for the drug metabolizing enzyme CYP2D6 to determine if the patient is a poor metabolizer (PM) or an extensive metabolizer (EM). Maximum daily dose in PMs: 50 mg with a maximum single dose of 25 mg; Maximum daily dose in Ems and intermediate metabolizers (IMs): 100 mg with a maximum single dose of 37.5 mg.

 

FDA Approval 2014 Cerdelga (eliglustat): Select patients using an FDA cleared test for determining CYP2D6 genotype: CYP2D6 Ems or IMs: 84 mg orally twice daily. CYP2D6 PMs: 84 mg orally once daily.

 

Genetic Testing for Warfarin (Coumadin) Sensitivity

Several tests to help assess warfarin sensitivity, by determining the presence or absence of the relevant CYP2C9, VKORC1, and CYP4F2 variants, have been cleared by the U.S. Food and Drug Administration (FDA) for marketing. Similar tests also may be available as laboratory-developed services; laboratory-developed tests must meet the general regulatory standards of the Clinical Laboratory Improvement Amendments. The tests are not identical in terms of the specific variants and number of variants detected. Generally, such tests are not intended as stand-alone tools to determine optimum drug dosage but should be used with clinical evaluation and other tools, including the international normalized ratio, to predict the initial dose that best approximates the maintenance dose for patients.

 

In August 2007, FDA approved updated labeling for Coumadin® to include information on testing for gene variants that may help “personalize” the starting dose for each patient and reduce the number of serious bleeding events. The label was updated again in January 2010. With each update, manufacturers of warfarin (generic for Coumadin®) were directed to add similar information to their products’ labels. The 2010 update added information on personalizing initial dose by genotyping results for CYP2C9 and VKORC1, providing a table of genotypes, and suggested initial dose ranges for each. However, suggested starting doses are also provided when genotyping information is unavailable, indicating that genetic testing is not required. Furthermore, FDA did not include information on genetic variation in the label’s black box warning on bleeding risk.

 

Pharmacogenomic Testing for Mental Health Conditions

Clinical laboratories may develop and validate tests in-house and market them as a laboratory service; laboratory-developed tests (LDTs) must meet the general regulatory standards of the Clinical Laboratory Improvement Amendments (CLIA). The tests discussed in this section are available under the auspices of CLIA. Laboratories that offer LDTs must be licensed by CLIA for high-complexity testing. To date, the U.S. Food and Drug Administration has chosen not to require any regulatory review of this test.

 

Examples of commercially available panels include the following:

  • Genecept™ Assay (Genomind, Chalfont, PA);
  • STA2R test (SureGene Test for Antipsychotic and Antidepressant Response; Clinical Reference Laboratory, Louisville, KY). Specific variants included in the panel were not easily identified from the manufacturer’s website.
  • GeneSight® Psychotropic panel (Assurex Health, Mason, OH);
  • Proove Opioid Risk panel (Proove Biosciences, Irvine, CA);
  • Mental Health DNA Insight™ panel (Pathway Genomics, San Diego, CA);
  • IDgenetix-branded tests (AltheaDx, San Diego, CA). Specific variants included in the panel were not easily identified from the manufacturer’s website.
  • PersonaGene Panel PsychiaGene (AIBio Tech)
  • Pharmacogenomic Comprehensive Panel for Antidepressants and Antipsychotics (NRLBH – National Reference Laboratory for Breast Health)
  • PGxOne Plus Psychiatry (Admera Health)
  • Kailos Test for Antidepressants (Kalios Geneics)

 

In addition, many labs offer genetic testing for individual genes, including MTFHR (GeneSight Rx and other laboratories), CYP450 variants, and SULT4A1.

 

AltheaDx offers a number of IDgenetix-branded tests, which include several panels focusing on variants that affect medication pharmacokinetics for a variety of disorders, including psychiatric disorders.

 

Pharmacogenomic Testing for Pain Management

Clinical laboratories may develop and validate tests in-house and market them as laboratory service; laboratory-developed tests (LDTs) must meet the general regulatory standards of the Clinical Laboratory Improvement Amendments (CLIA). The Proove Narcotic Risk and Pain Perception panel, the GeneSight Analgesic Panel, the Pathway Genomics Pain Medication DNA Insight Panel, the Millennium PGT (Pain Management) panel, PersonaGene Pain Management (AIBio Tech), Pharmacogenomic Comprehenstive Panel – Opiods (NRLBH), PGxOne Plus (Admera Health) and Kailos Test for Pain Management (Kailos Genetics) are available under the auspices of CLIA. Laboratories that offer LDTs must be licensed by CLIA for high-complexity testing. To date, the U.S. Food and Drug Administraiton (FDA) has chosen not to require any regulatory review of this test.

 

Prior Approval:

Not applicable

 

Policy:

CYP450 Genotyping to Determine Drug Metabolizer Status

CYP450 genotyping for CYP2C19 for the purpose of aiding in the choice of clopidogrel (plavix) versus alternative antiplatelet agents or in decisions on the optimal dosing, for an individual at risk for adverse events and therefore requires assessment for CYP2C19 before undergoing treatment with clopidogrel (plavix) in order to identify his or her risk of poorly metabolizing clopidogrel (plavix) and his or her likelihood of exhibiting poor response to this drug may be considered medically necessary for any one of the following indications:

  • Patient with unstable angina; or
  • Patient with non-ST-elevation myocardial infarction; or
  • Patient who experiences recurrent acute coronary syndromes (unstable angina/myocardial infarction) despite ongoing therapy with clopidogrel (plavix); or
  • Patients undergoing high risk percutaneous coronary interventions (PCI) with extensive and/or very complex disease.

 

Note: Per American Heart Association: Acute Coronary Syndrome is defined as those situations where the blood supplied to the heart muscle is suddenly blocked.

CYP450 genotyping for CYP2D6 to determine drug metabolizer status may be considered medically necessary for individuals with the following:

  • Huntington’s disease being considered for treatment with a dosage of tetrabenazine (xenazine) greater than 50mg/day; or
  • Gaucher disease type I being considered for treatment with eliglustat (cerdelga)

 

Repeat CYP450 genotype testing for CYP2C19, CYP2D6 for the above medically necessary indications is considered not medically necessary.

 

CYP450 genotyping for (CYP2C19, CYP2D6, CYP2C9, etc.) for the purpose of aiding in the choice of drug and/or dosing to increase efficacy and/or avoid toxicity including but not limited to the following drugs is considered investigational:

  • Selection or dosing of selective serotonin reuptake inhibitors (SSRI)
  • Selection or dosing of antipsychotic drugs
  • Selection or dosing of opioid analgesics
  • Selection and dosing of selective norepinephrine reuptake inhibitors (SNRIs)
  • Selection and dosing of tricyclic antidepressants
  • Dosing of efavirenz (common component of highly active antiretroviral therapy for HIV)
  • Dosing of immunosuppressants for organ transplantation
  • Selection or dose of beta blockers
  • Dosing and management of antituberculosis medications 
  • Selection or dosing of Tamoxifen 
  • Selection or dosing of Clopidogrel (Plavix) except as indicated above
  • Dosing of Tetrabenzine (Xenazine) except as indicated above
  • Dosing of Eliglustat (Cerdelga) except as indicated above

 

Testing for genetic polymorphisms has also been proposed for a wide array of other drugs, involving many different conditions and CYP450 enzyme(s).  At this time, the available literature addressing such testing is limited and insufficient to allow any assessment of clinical utility in the treatment of individuals. The outcomes that require further research attention include major adverse events, utilization of health resources, and time to clinically significant changes in condition using appropriate and validated measures. While the potential of pharmacogenomics is intriguing for many clinical applications, it is not yet clear which are most likely to yield clinical benefit. As this field evolves and matures, and if pre-prescription testing can be shown to be of clinical utility for specific drugs and individuals, it will be imperative to establish evidence-based guidelines for healthcare professionals delineating the most effective courses of action based on such genotype testing results. The evidence is sufficient to determine the effects of this testing on net health outcomes and is considered investigational.

 

Testing Panels to Determine Drug Metabolizer Status

Use of genetic testing panels that include analysis of multiple CYP450 mutations and other gene polymorphisms for the purpose of aiding in the choice of drug and/or dosing to increase efficacy and/or avoid toxicity are considered investigational due to the lack of clinical evidence demonstrating an impact on improved health outcomes.

 

Several commercial laboratories market multi-test panels for genetic polymorphisms related to drug metabolizer status. While the use of some individual tests included in these test panels may be reasonable under specific circumstances, the use of all the tests within a panel is rarely justified unless there is clinical evidence that the panel provides information that leads to meaningful impact on treatment.  At this time, the available published evidence addressing the use of such test panels is limited in the form of retrospective validation studies with small heterogeneous patient populations and short term follow-ups. The results of these studies are limited by the study designs utilized by the investigators, with each having some combination of no blinding, small study population, retrospective methodology, selection bias, short follow-up periods, and subjective study outcomes. The data from these studies is weak, and further investigation is warranted using better designed, larger study samples and double-blind randomized controlled methodology. Further, there is lack of published professional consensus guidelines to demonstrate that use of such tests is a standard of care in routine clinical practice. The evidence is sufficient to determine the effects of this testing on net health outcomes and is considered investigational.

 

Pharmacogenomic Testing for Pain Management

Genetic testing to include single genetic variants or panel testing including but not limited to the following, for pain management is considered investigational for all indications, to include to inform the selection or dose of medication(s) to treat pain management.

  • ARUP Pain Management
  • GeneSight Analgesic
  • IDgenetix Pain Tests
  • Kailos Testing for Pain Medication (Kailos Genetics)
  • Millennium Pharmacogenetic Testing PGT – Millennium Analysis of Patient Phenotype (MAPP) report
  • Pain Medication DNA Insight
  • PersonaGene Pain Management
  • PGxOne Plus Pain Management
  • Pharmacogenomic Comprehensive Panel - Opioids
  • Proove Addiction Risk Test
  • Proove Drug Metabolism
  • Proove Opioid Response Profile
  • Proove Opioid Risk
  • Proove Pain Perception
  • Proove Non-Opioid Response
  • Proove NSAID Risk Profile
  • YouScript Analgesic

 

Single-nucleotid variants (SNVs) implicated in pain management include but are not limited to the following:

  • 5HT2C (serotonin receptor gene)
  • 5HT2A (serotonin receptor gene)
  • SLC6A4 (serotonin transporter gene)
  • DRD1 (dopamine receptor gene)
  • DRD2  (dopamine receptor gene)
  • DRD4 (dopamine receptor gene)
  • DAT1 or SLC6A3 (dopamine receptor gene)
  • DBH (dopamine beta-hydroxylase gene)
  • COMT (catechol O-methyltransferase gene)
  • MTHFR (methylenetetrahydrofolate reductase gene)
  • y-aminobutyric acid (GABA) A receptor gene
  • OPRM1 (u-opioid receptor gene)
  • OPRK1 (k-opioid receptor gene)
  • UGT2B15 (uridine diphosphate glycosyltransferase 2 family, member 15)
  • Cytochrome p450 genes: CYP2D6, CYP2C19, CYP2C9, CYP3A4, CYP2B6, CYP1A2

 

Based on review of the peer reviewed medical literature the clinical utility and benefit to net health outcomes for single genetic variants and panel testing for pain management has not been established. There is insufficient evidence in the peer reviewed medical literature to validate the effectiveness of this testing to inform on drug metabolism, dosing considerations or to demonstrate improved clinical outcomes. Further, there is lack of published professional consensus guidelines to demonstrate that use of such tests is a standard of care in routine clinical practice. The evidence is sufficient to determine the effects of this testing on net health outcomes and is considered investigational.

 

Genetic Testing for Warfarin (Coumadin) Dose

Genetic testing to determine cytochrome p450 2C9 (CYP2C9) and vitamin K epoxide reductase subunit C1 (VKORC1) genetic polymorphisms is considered investigational for the purpose of managing the administration and dosing of warfarin (Coumadin), including use in guiding initial warfarin (Coumadin) dose to decrease time to stable INR and reduce the risk of serious bleeding.

 

While the evidence suggests a strong association between genetic variants and stable warfarin (Coumadin) dose, and to a lesser extent, between genetic variants and INR and bleeding outcomes, the evidence is not sufficient to conclude that testing for CYP2C9 and VKORC1genetic variants improves health outcomes. Genetic testing may help predict the initial warfarin (Coumadin) dose within first week of warfarin (Coumadin) treatment, but the evidence, including several meta-analyses of randomized controlled trials, does not provide consistent evidence for the conclusion that clinically relevant outcomes (e.g. bleeding rates, thromboembolism) are improved. The evidence is insufficient to determine the effects of the technology on net health outcomes and is considered investigational.

 

Pharmacogenomic and Genetic Testing for Mental Health Conditions

Genetic testing for mutations associated with mental health disorders is considered investigational in all situations, including but not limited to the following:

  • To confirm a diagnosis of a mental health disorder in an affected individual
  • To predict future risk of a mental health disorder in an asymptomatic individual
  • In an affected individual to inform the selection or dose of medications used to treat mental health disorders

 

Note: Genetic mutations associated with mental health disorders include but are not limited to the following:  SULT4A1, SLC6A4, 5HT2C, 5HT2A, DRD1, DRD2, DRD4, DAT1, DA beta-hydroxylase, CACNA1C, ANK3, COMPT, MTHFR, GABA, OPRK1, OPRM1, UGT1A4, ABCB1, CYP450 genes: CYP2D6, CYP2C19, CYP3A4, CYP3A5, CYP1A2, CYP2C9, CYP2B6

 

Genetic testing panels to inform the selection or dose of medication(s) for mental health disorders including but not limited to the following are considered investigational:

  • Ally Diagnostics Genetic Testing Panel
  • Alpha Genomix Psychiatry/ADHD Panel
  • AltheaDX IDgenetix branded tests – IDgenetix, NeuroIDgenetix
  • Genecept Assay
  • GeneSight Psychotropic Panel; GeneSight ADHD; GeneSight MTHFR
  • Genetic Technological Innovations Pharmacogenetic Testing
  • Kailos Test for Antidressants
  • Mental Health Insight DNA
  • Millennium Pharmacogenetic Testing (PGT) in Mental Health
  • Molecular Testing Labs Psychotropic Medication Panel
  • PersonaGene Panel PsychiaGene
  • PGXL Multi-Drug Panel
  • PGxOne Plus Psychiatry
  • Pharmacogenomic Comprehensive Panel for Antidepressants and Antipsychotics
  • STA2R SureGene
  • YouScript Panel (YouScript Psychotropic, YouScript Psychotropic Plus, YouScript ADHD)

 

Based on review of the peer reviewed medical literature the evidence on clinical utility and benefit to net health outcomes for single genetic variants and panel testing for diagnosis and risk of mental health disorder and for pharmacogenomic testing for mental health disorders is lacking. Management changes that occur as a result of these assays are ill-defined, with uncertain impacts on clinical outcomes. In addition, it is not well-understood how unexpected results or unknown variants are handled and whether these type of results have an impact on diagnostic work-up, treatment decisions, and health outcomes. Additional studies in larger number of patients will be needed to confirm the findings that genotyping may be associated with improved clinical outcomes and determine the optimal change in treatment strategy that should occur following testing and the specific genes that should be evaluated. Also, there is lack of published professional consensus guidelines to demonstrate that use of such tests is a standard of care in routine clinical practice. Due to these deficiencies in the evidence, genetic testing for mutations associated with mental health disorders and genetic testing panels for mental health disorders are considered investigational for all indications.

 

Procedure Codes and Billing Guidelines:

To report provider services, use appropriate CPT* codes, Alpha Numeric (HCPCS level 2) codes, Revenue codes and / or diagnosis codes.

  • 0028U CYP2D6 (cytochrome P450, family 2, subfamily D, polypeptide 6) (eg, drug metabolism) gene analysis, copy number variants, common variants with reflex to targeted sequence analysis
  • 0029U Drug metabolism (adverse drug reactions and drug response), targeted sequence analysis (ie, CYP1A2, CYP2C19, CYP2C9, CYP2D6, CYP3A4, CYP3A5, CYP4F2, SLCO1B1, VKORC1 and rs12777823)
  • 0030U Drug metabolism (warfarin drug response), targeted sequence analysis (ie, CYP2C9, CYP4F2, VKORC1, rs12777823)
  • 0031U CYP1A2 (cytochrome P450 family 1, subfamily A, member 2)(eg, drug metabolism) gene analysis, common variants (ie, *1F, *1K, *6, *7)
  • 0032U COMT (catechol-O-methyltransferase)(drug metabolism) gene analysis, c.472G>A (rs4680) variant
  • 81225 CYP2C19 (cytochrome P450, family 2, subfamily C, polypeptide 19) (eg, drug metabolism), gene analysis common variants (e.g. *2, *3, *4, *8, *17) 
  • 81226 CYP2D6 (cytochrome P450, family 2, subfamily D, polypeptide 6) (eg. drug metabolism), gene analysis common variants (e.g. *2, *3, *4, *5, *6, *9, *10, *17, *19, *29, *35, *41, *1XN, *2XN, *4XN)   
  • 81227 CYP2C9 (cytochrome P450, family 2, subfamily C, polypeptide 9) (eg, drug metabolism), gene analysis, common variants (e.g., *2, *3, *5, *6)
  • 81230 CYP3A4 (cytochrome P450 family 3 subfamily A member 4) (eg, drug metabolism), gene analysis, common variant(s) (eg, *2, *22)
  • 81231 CYP3A5 (cytochrome P450 family 3 subfamily A member 5) (eg, drug metabolism), gene analysis, common variants (eg, *2, *3, *4, *5, *6, *7)
  • 81291 MTHFR (5, 10-methylenetetrahydrofolate reductase) (eg, hereditary hypercoagulability) gene analysis; common variants (e.g., 677T, 1298C)
  • 81350 UGT1A1 (UDP glucuronosyltransferase 1 family, polypeptide A1) gene analysis, common variants (e.g., *28, *36, *37)
  • 81355 VKORC1 (vitamin K epoxide reductase complex, subunit 1)(eg, warfarin metabolism), gene analysis, common variants (e.g., -1639G.A, c.173+1000C>T)
  • 81401 Molecular pathology procedure, level 2 (e.g. 2-10 SNPs, 1 methylated variant or 1 somatic variant (typically using non-sequencing target variant analysis], or detection of a dynamic mutation disorder/triplet repeat) includes:
    • CYP3A4 (cytochrome P450, family 3, subfamily A, polypeptide 4) (e.g. drug metabolism), common variants (e.g. *2, *3, *4, *5, *6)
    • CYP3A5 (cytochrome P450, family 3, subfamily A, polypeptide 5) (e.g. drug metabolism), common variants (e.g. *2, *3, *4, *5, *6)  
  • 81402 Molecular pathology procedure, Level 3 (e.g. > 10 SNPs, 2-10 methylated variants, or 2-10 somatic variants [typically using non-sequencing target variant analysis], immunoglobulin and T-cell receptor gene rearrangements, duplication/deletion variants of 1 exon, loss of heterozygosity [LOH], uniparental disomy [UPD] includes:
    • CYP21A2 (cytochrome P450, family 21, subfamily A, polypeptide 2) (e.g. congenital adrenal hyperplasia, 21  hydroxylase deficiency), common variants (e.g. IVS2-13G, P3OL, I172N, exon 6 mutation cluster [I235N, V236E, M238K,], V281L, L307FfsX6, Q318X, R356W, P453S, G110VfsX21, 30-kb deletion variant) 
  • 81404 Molecular pathology procedure, Level 5 (e.g. analysis of 2-5 exons by DNA sequencing analysis, mutation scanning or duplication/deletion variants of 6-10 exons, or characterization of a dynamic mutation disorder/triplet repeat by Southern blot analysis) includes:
    • CYP1B1 (cytochrome P450,family 1, subfamily B, polypeptide 1), e.g. primary congenital glaucoma), full gene sequence
  • 81405 Molecular pathology procedure Level 6 (e.g. analysis of 6-10 exons by DNA sequence analysis, mutation scanning or duplication/deletion variants of 11-25 exons, regionally targeted cytogenomic array analysis) includes:
    • CYP11B1 (cytochrome P450, family 11, subfamily B, polypeptide 1) (e.g. congenital adrenal hyperplasia), full gene sequence
    • CYP17A1 (cytochrome P450, family 17, subfamily A, polypeptide 2) (e.g. congenital adrenal hyperplasia), full gene sequence
    • CYP21A2 (cytochrome P450, family 21, subfamily A, polypeptide 2) e.g. steroid 21-hydroxylase isoform, congenital adrenal hyperplasia), full gene sequence
  • 81479 Unlisted molecular pathology procedure
  • 81599 Unlisted multi-analyte assay with algorithmic analysis
  • G9143  Warfarin responsiveness testing by genetic technique using any method, any number of specimen(s)

 

Selected References:

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Policy History:

August 2017 - New Medical Policy Created

 

This policy will replace the following policies:   

       02.04.48 CYP450 Genotyping to Determine Drug Metabolizer Status

       02.01.33 Genetic Testing for Warfarin Sensitivity

       02.04.54 Genetic Testing for Mental Health Conditions

Wellmark medical policies address the complex issue of technology assessment of new and emerging treatments, devices, drugs, etc.   They are developed to assist in administering plan benefits and constitute neither offers of coverage nor medical advice. Wellmark medical policies contain only a partial, general description of plan or program benefits and do not constitute a contract. Wellmark does not provide health care services and, therefore, cannot guarantee any results or outcomes. Participating providers are independent contractors in private practice and are neither employees nor agents of Wellmark or its affiliates. Treating providers are solely responsible for medical advice and treatment of members. Our medical policies may be updated and therefore are subject to change without notice.

 

*CPT® is a registered trademark of the American Medical Association.