At CytoVive, we understand that addiction recovery is incredibly challenging. The road to sobriety is long and full of obstacles, thankfully now we can pinpoint and work around the obstacles written in our genetics. We are proud to offer industry leading diagnostics tools and reporting services that assure your patients receive the best personalized medication plans possible giving them the greatest chance of success on their road to recovery!
Pharmacological and Legal Need for Toxicology Assurance In Addiction Recovery
The incorporation of toxicology assurance screenings as part of a care plan for addiction recovery patients is both a medically and legally necessary component of the overall care plan. It is the standard of care. This type of urinalysis provides data regarding the presence or absence of corresponding medication metabolites and allows physicians to monitor and adjust the dose of prescribed medications on an individualized basis in order to ensure the best physiological outcome for each patient!
When a patient's body is not producing the proper active drug metabolites from their medication it alludes to one of several possibilities:
One: The patient is likely a variant metabolizer for that medication and could be at an elevated risk for an adverse drug reaction. A dosage adjustment or alternative medication may be recommended.
Two: The patient could be (knowingly or unknowingly) consuming a substance that either induces or inhibits a metabolic pathway necessary for their medication to be properly metabolized.
Three: The patient is not actively taking and potentially diverting their medication.
Qualitative toxicology can protect physicians from malpractice claims and is highly valuable in determining which patients qualify as prime candidates for pharmacogenetic testing. This screening is the first line of defense against potentially fatal adverse drug reactions, and serves as a responsible control that helps addiction recovery facilities ensure the highest standard of patient care as well as guard against potential medication abuse or diversion (5,7).
Opioid addiction is a widespread global health issue that has reached epidemic proportions. There are almost 2 million Americans living dependent on opioids. Opioids continue to be a leading drug of choice reported in substance abuse programs, and since 1999 the number of overdoses has quadrupled!(3) Opioid withdrawal symptoms can be incredibly severe and most patients in recovery will be prescribed some type of medication that is designed to help with detox or maintenance therapy for opioid dependence (8). It is important to remember that each patient will metabolize and respond differently to these medications based on their genetics. For example, A CYP3A4 "Poor Metabolizer" or "Intermediate Metabolizer" would receive little to no benefit from buprenorphine (AKA Suboxone), and would likely respond much better to methadone assuming they are a CYP2D6 "Extensive Metabolizer" (6,9). Selecting an optimal medication and dose at the start of treatment can be the difference between recovery and relapse.
"Normal Metabolizers": How Normal Is Normal?
Copyright PGXL Laboratories 2016
Studies have shown that the prevalence of psychiatric illnesses in opioid-dependent populations is many times greater than among the general population (6). These patients are sometimes given multiple medications to treat comorbid conditions. If the coadministered medications are metabolized through the same pathway there can be serious associated risks, especially if patient phenotypes are not identified. Methadone, Naltrexone, and Buprenorphine are among the most commonly prescribed medications for opioid dependent patients, however the coadministration of these medications with certain psychotropic drugs can be toxic. Benzodiazepines for example, have been identified in 50-80% of heroin-related deaths, in 63.7% of methadone-related deaths, and in up to 80% of buprenorphine-related deaths (6). This is why reporting drug-gene interactions, drug-drug interactions, as well as contraindicated pathway inducers and inhibitors is so important. That information can literally be the difference between life and death.
Opioid Addiction and Comorbid Psychiatric Illnesses
Addiction Recovery Relevant Genes In The PRIMER Panel
Gene - Gene Product Description
CYP2D6 – Metabolizes more than 25% of all drugs, including tamoxifen, many antidepressants, antipsychotics, beta-blockers, and opioids. Detecting variants of the CYP2D6 gene that cause altered enzymatic activity can identify patients who may be at increased risk of having adverse drug reactions or therapeutic failure to standard dosages of CYP2D6 substrates. Medications which require activation or inactivation by CYP2D6 should be used with caution in patients with CYP2D6 variants.
CYP2C19 – Metabolizes approximately 10-15% of all drugs, including clopidogrel, citalopram, diazepam, and many of the proton pump inhibitors. Detecting variants of the CYP2C19 gene that cause altered enzymatic activity can identify patients who may be at increased risk of having adverse drug reactions or therapeutic failure to standard dosages of CYP2C19 substrates.
CYP3A4 - A liver enzyme that, in concert with CYP3A5, metabolizes approximately 50% of medications, including many of the statins, benzodiazepines, antibiotics, and antipsychotics. Detecting variants of the CYP3A4 gene that cause altered enzymatic activity can identify patients who may be at increased risk of having adverse drug reactions while taking standard dosages of 3A4 substrates. Roughly 4-10% of the general population possesses inherited differences in 3A4 that cause decreased metabolism. These Decreased Metabolizers may be at increased risk for dose-dependent side effects to drugs normally inactivated by 3A4.
CYP3A5 – A liver enzyme that, in concert with CYP3A4, metabolizes approximately 50% of medications, including many of the statins, benzodiazepines, antibiotics, and antipsychotics. Detecting variants of the CYP3A5 gene that cause altered enzymatic activity can identify patients who may be at increased risk of having adverse drug reactions while taking standard dosages of 3A5 substrates. More than half of the general population (60-80%) possesses inherited differences in 3A5 that cause decreased metabolism. These Decreased Metabolizers may be at increased risk for dose-dependent side effects to drugs normally inactivated by 3A5.
CYP1A2 – Metabolizes many medications, including theophylline, diazepam, caffeine, and amitriptyline. CYP1A2 can be induced by several medications, substrates, and constituents of tobacco smoke. CYP1A2 can also be inhibited by several medications. Basal metabolic capacity remains relatively consistent among the different genotypes in the absence of an inducer. Detecting variants of the CYP1A2 gene that cause altered enzymatic induction in the presence of an inducer can identify patients who may be at increased risk of having adverse drug reactions or therapeutic failure to standard dosages of CYP1A2 substrates.
SLC6A4 – The 5-HTTLPR (5-hydroxytryptamine transporter linked polymorphic region) polymorphism is a 44-bp insertion/deletion in the promoter region of the serotonin transporter gene, 5-HTT or SLC6A4. The two most frequent alleles are defined by their length: the (L)ong allele, and the (S)hort allele characterized by a 43-bp deletion. The S allele results in 50% less expression of the active transporter protein as compared to the Long form. Presence of the short form may increase the time to therapeutic response with selective serotonin antidepressant therapy and may also affect efficacy. The short form has also been associated increased risk of side effects, and the nature and extent of depressive symptoms experienced. The Long allele of 5-HTTLPR contains an A>G polymorphism which generates a restriction site that may be detected by restriction fragment length polymorphism analysis. Presence of the G allele is thought to result in a phenotype similar to that of the Short 5-HTTLPR allele. Therefore, the presence of the LG allele is associated with the same risks as that of the Short allele.
OPRM1 – Opioid agonists, such as morphine, hydromorphone, and oxymorphone, exert their analgesic properties via stimulation of the mu-1 opioid receptor. Analgesic efficacy of mu-acting drugs has been linked to the 118A>G single nucleotide polymorphism (SNP) of OPRM1, the gene encoding the mu-1 receptor. The frequency of the variant G allele varies from 10% to 48% depending on the population studied. Studies show that patients carrying the GG (homozygous variant) genotype require much higher opioid doses to achieve pain relief. Additionally, patients with the AA genotype display higher relapse rates with respect to naltrexone treatment for alcohol dependence.
COMT – This enzyme degrades dopamine and norepinephrine, primarily in the prefrontal cortex of the brain. A common single nucleotide polymorphism (SNP) 472G>A, also referred to by the amino acid change 158 Val>Met, is associated with altered COMT enzymatic activity. The 158 Met allele has lower enzymatic activity resulting in less dopamine degradation and higher dopamine concentrations as compared to those carrying the Val allele. Conversely, the 158 Val allele has higher activity and results in lower dopamine levels in the prefrontal cortex. Low dopamine concentrations are associated with cognitive impairments including working memory deficits. Val/Val homozygotes with depression are less likely to achieve remission when treated with SSRI antidepressants, and Val/Val homozygotes with schizophrenia are less likely to demonstrate improved cognitive effects when treated with antipsychotics. In contrast, the Met/Met homozygotes are more likely to achieve remission and demonstrate cognitive improvement when treated with SSRIs and antipsychotics, respectively. The frequency of the 158 Met variant varies from 25-43% depending on the population studied.
1) Menu of Tests [Internet]Louisville, KY: PGXL Laboratories; c2016 [cited 2016 11/20]. Available from: http://www.pgxlab.com/test-menu/.
2) Medication lists by specialty. Louisville, KY: PGXL Laboratories; 2016:PGXL Primer. Personalized Medicine. Results For Life.
3) Opioid Overdoses Driving Increase in Drug Overdoses Overall [Internet]United States: Center for Disease Control and Prevention; c2014 [cited 2016 10/10]. Available from: www.cdc.gov/drugoverdose.
4) Pathways for common medications. Louisville, KY: PGXL Laboratories; 2016:PGXL Primer. Personalized Medicine. Results For Life.
5) Rifat MD. Pharmacological and Legal Need for Quantitative Drug Analysis. San Diego, CA: Alcala Testing and Analysis; 2016.
6) Saber-Tehrani A, Bruce RD, Altice FL. Pharmacokinetic drug interactions and adverse consequences between psychotropic medications and pharmacotherapy for the treatment of opioid dependence. American Journal of Drug & Alcohol Abuse 2011 01;37(1):1-11.
7)What is Toxicology? [Internet]: News Medical Life Sciences; c2016 [cited 2016 10/10]. Available from: http://www.news-medical.net/health/What-is-Toxicology.aspx.
8) Yiannakopoulou E. Pharmacogenomics and opioid analgesics: Clinical implications. International Journal of Genomics 2015 05/14;2015:1-8.
9) Yuferov V, Levran O, Proudnikov D, Nielsen DA, Kreek MJ. Search for genetic markers and functional variants involved in the development of opiate and cocaine addiction and treatment. Ann N Y Acad Sci 2010 02/15;1187(1):184-207.