|Year : 2021 | Volume
| Issue : 1 | Page : 4-5
Application of pharmacogenomics in psychiatric practice: The road ahead
Prafull Mohan1, YK Gupta2, J Prakash3
1 Department of Pharmacology, AFMC, Pune, Maharashtra, India
2 President, AIIMS, Bhopal, Madhya Pradesh; President, AIIMS, Jammu and Kashmir; Department of Pharmacology, AIIMS, New Delhi, India
3 Department of Psychiatry, AFMC, Pune, Maharashtra, India
|Date of Submission||25-May-2021|
|Date of Acceptance||13-Jun-2021|
|Date of Web Publication||24-Jun-2021|
Dr. Prafull Mohan
Department of Pharmacology, AFMC, Pune, Maharashtra
Source of Support: None, Conflict of Interest: None
|How to cite this article:|
Mohan P, Gupta Y K, Prakash J. Application of pharmacogenomics in psychiatric practice: The road ahead. Ind Psychiatry J 2021;30:4-5
Drug response is multifactorial and depends on a number of variables. Different patients may respond differently to the same drug (interindividual variability) and the same individual may respond differently to the drug at different time points (intraindividual variability). However, the art and science of medicine lies in identifying the most suitable therapeutic intervention for a given patient. The tools for identifying such interventions are evolving through a pharmacogenomic approach aiming for personalized medicine. Genetic variations among patients have been identified as one of the major sources of response variability. For example, slow and fast acetylators metabolize isoniazid at different speeds. This led to different antitubercular dosage schedules used in different populations. This linkage of genetic characteristics of an individual patient/population with drug response has evolved into discipline of pharmacogenomics. Human genome sequencing in 2003 has led to deeper understanding and integration with the overall pursuit of personalized medicine.
Most of the drugs used in psychiatric disorders have a modest correlation between serum/plasma concentration and clinical response. To further add to complexity, clinical course and outcomes in psychiatry practice are less objectives. Since these drugs are usually given for longer durations, safety aspects become more important. Thus, the application of pharmacogenomics has become more relevant for clinical decision-making in psychiatry.
Hepatic microsomal enzymes were the initial targets of pharmacogenomics as they (singly or in combination) metabolize a majority of drugs used in psychiatry. Gene(s) coding for CYP2D6 was phenotyped and was found to be involved in metabolism of many tricyclic antidepressants and antipsychotic drugs. On the basis of CYP2D6 genotype, initially, two types of metabolizers (poor and extensive metabolizers) were identified which have now increased to four (poor, intermediate, rapid, and ultrarapid).
Every drug that is metabolized in the body will be affected by genetic makeup of the patient to some extent. However, not every altered genotype is clinically important. There are now well-recognized genetic characteristics/alterations that have a clinically important impact on metabolism of a given drug. Such identified genetic characteristics are known as pharmacogenomic markers of that drug. The United States Food and Drug Administration (FDA) lists 38 psychiatry drugs with pharmacogenomic markers, out of which 35 pertain to CYP2D6 and 3 to CYP2C19. Out of these, 10 psychiatry drugs (aripiprazole, lauroxil, atomoxetine, brexpiprazole, citalopram, clozapine, iloperidone, pitolisant, pimozide, and vortioxetine) have sufficient evidence regarding their pharmacogenomic aspects. FDA provides recommendations regarding their dosing and administration based on their associated pharmacogenomic markers. Such recommendations are evolving. As data accumulate, more such recommendations with respect to other drug/gene combinations will be available.
Clinically relevant pharmacogenomic information is also provided in Pharmacogenomics Knowledgebase (PharmGKB) of National Institute of Health, USA (NIH). As of now, four genes contribute to majority of clinically important pharmacogenomic information (CYP2D6, 2C19, HLA B * 15:02, and HLA A * 13:01). PharmGKB is a comprehensive database that draws information from various sources and suggests their effect on clinical decision-making. This database provides drug label annotations drawn from various sources.
Clinical Pharmacogenetics Implementation Consortium (CPIC) is an international group of volunteers that provides peer-reviewed, evidence–based, and updatable clinical practice guidelines of about 440 (as of date) gene/drug pairs. The platform assigns different evidence levels (A, B, C, and D). A and B levels have sufficient evidence for recommending changes in prescription whereas C and D are not considered to have adequate evidence and no prescribing recommendations are available. This classification augments the application of pharmacogenomics in clinical practice.
Identification of genetic mutation is the cornerstone of gathering pharmacogenomic information. Amplichip 450 test was the first US FDA approved commercially available platform for ascertaining phenotype of a patient with respect to CYP2D6 and 2C19 genes, using microarray technology. However, it was never extensively used as the number of identified polymorphism of these genes increased and the chip could not identify multiple copies of the gene. This paved the way for more gene panels, also known as psychiatric pharmacogenomic panels or combinatorial pharmacogenetic tests, such as CNSdose™, Genecept™, GeneSight™, and Neuropharmagen™. They claim to provide prescribing guidance to clinicians. While it sounds very exciting to have such information at hand, they are not without caveats.
All these panels look at different genes, not all of whom may possess the highest CPIC level of evidence. Different panels can give different dosing recommendations for the same patient. As on date, none of them are US FDA approved as they lack supporting clinical evidence. Hence, standardization and accreditation across panels is required. It is important that the gene panels are used only as a supplement tool to, and not as a replacement of, good clinical decision-making.
While the prospect of gene panels appears exciting, their application is compromised due to a lack of standardization, interchangeability, and clinical evidence supporting their role. In pursuit of offering the best and the most appropriate to our patients, we need to rely on well-recognized sources of pharmacogenomic information (such as PharmGKB and CPIC) [Table 1]. Pharmacogenomics-based dosing decisions should only be taken in those gene/drug combinations which have sufficient evidence, on a “case to case” basis. We need to develop our own pharmacogenomic data to optimally utilize genetic information for clinical decision-making. Vigorous multidisciplinary research with the integration of pharmacology, molecular biology, and psychiatry is vital for such data generation. It is a resource intensive endeavor; however, genetic information once generated will also be useful in other disciplines.
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