Pharmacogenetics and medication decision support software can be used to find effective and safe antipsychotics for schizophrenia while preventing side effects.
Schizophrenia is a severe, chronic mental health condition characterized by a variety of psychological and psychotic symptoms. Some of these symptoms may include hallucinations, delusions, disordered thinking and changes in behavior. People with schizophrenia may have difficulty distinguishing their own thoughts and ideas from reality. Symptoms may vary over time, but schizophrenia usually requires life-long treatment.
Antipsychotic medications
Antipsychotic medications relieve the symptoms of schizophrenia and reduce the risk of future psychotic episodes by working on neurotransmitters in the brain such as dopamine and serotonin. Antipsychotics are commonly categorized into two drug classes: first-generation antipsychotics and second-generation antipsychotics. First-generation antipsychotics are dopamine antagonists and include medications such as chlorpromazine (Thorazine), fluphenazine (Prolixin), haloperidol (Haldol), pimozide (Orap), and zuclopenthixol (Clopixol). Second-generation antipsychotics have a higher affinity for serotonin receptors than dopamine receptors, which results in differences in the general side effect profile of this group of antipsychotics. Common second-generation antipsychotic drugs include aripiprazole (Abilify), asenapine (Saphris), olanzapine, (Zyprexa), quetiapine (Seroquel), and risperidone (Risperdal).
As with other medications, patients experience different responses and side effects while taking antipsychotics. Along with their beneficial therapeutic effects, antipsychotic drugs may cause weight gain, metabolic syndrome, tardive dyskinesia (shaking and other involuntary movements) and other unwanted side effects. For some individuals, these side effects may be moderate or very mild while for other people side effects can be very severe and can affect medication adherence. Many patients have to try multiple antipsychotics before they find one that works for them. A personalized medicine approach can help patients and health care providers find effective and safe antipsychotics for schizophrenia.
Using pharmacogenetics to select safe and effective antipsychotics
In schizophrenia, antipsychotics are often selected not only based on efficacy, but also on the basis of what is the most acceptable side effect profile for the patient. Using pharmacogenetic testing can help identify patients who are at increased risk of developing side effects such as weight gain, hyperprolactinemia, tardive dyskinesia and metabolic syndrome when using an antipsychotic. The patient’s pharmacogenetic profile can be used together with other patient information, and patient preferences, to select effective and safe antipsychotics for schizophrenia. This approach allows detecting antipsychotics with the lowest relative risk of the most unacceptable side effects.
The evidence behind pharmacogenetic (PGx) testing for schizophrenia
Pharmacogenetic testing can be used to help predict a patient’s risk of experiencing certain side effects and avoid adverse reactions. PharmGKB, an NIH-funded database that curates knowledge about the impact of genetic variation on drug response, has identified and aggregated evidence for interactions between antipsychotics and genetic variants in a number of genes including ANKK1, HTR2C, DRD2, and CYP2D6.
Read More about PGx in schizophrenia
One of the genetic variants showing interactions with antipsychotic response is in the ANKK1 gene (rs1800497, level 2B, PharmGKB accessed November 29, 2017). Individuals with the AA or AG genotypes in this single nucleotide polymorphism (SNP) have an increased risk of weight gain and hyperprolactinemia but decreased risk of tardive dyskinesia compared to those with the GG genotype. A study showed that rs1800497 was associated with 7% weight gain in patients of European ancestry taking clozapine or olanzapine (OR = 2.18, 95% CI: 1.00–4.75, P=0.046) [1]. Conversely, individuals with the GG genotype when treated with antipsychotics have higher risk to develop tardive dyskinesia (OR = 1.50, 95% CI: 1.17-1.92, P=0.001), a potentially irreversible movement disorder [2]. This information, combined with the baseline side effect profile of the individual antipsychotics, can help select which medications may be more tolerable for certain patients.
Another SNP that may predict response to antipsychotics is in the HTR2C gene which has been associated with increased risk of metabolic syndrome (rs1414334, level 2B, PharmGKB accessed November 29, 2017). Risselada and collaborators found that the C allele in this SNP is associated with an increased risk for the metabolic syndrome (OR 3.73; 95% CI 1.29–10.79, P=0.015) when patients are treated with antipsychotics [2,3]. Patients with the CC and CG genotypes have an increased risk of metabolic syndrome compared to those with the GG genotype. Mulder and collaborators also found that the increased risk for metabolic syndrome is particularly strong in carriers of the C allele (OR 3.08; 95% CI, 1.40-6.78) [4].
An SNP in the DRD2 gene has been associated with reduced response to risperidone (rs1799978, level 2A, PharmGKB accessed November 29, 2017). In two clinical trials, the allele T in this SNP showed association with increased response to risperidone in people with schizophrenia as compared to allele C [5,6]. Patients with the TT genotype who are treated with risperidone for schizophrenia may be more likely to have improvement in symptoms as compared to patients with the CC genotype.
The CYP2D6 gene has been included in guidelines and drug labels of certain antipsychotics. The Royal Dutch Pharmacists Association (DPWG) published a guideline with therapeutic recommendations for aripiprazole, clozapine, flupenthixol, haloperidol, olanzapine, risperidone, and zuclopenthixol [7]. One of their recommendations is to select an alternative drug to risperidone for patients who are CYP2D6 poor metabolizers, intermediate metabolizers, or ultrarapid metabolizers [8]. The FDA-approved drug label for pimozide recommends a reduced dose in patients who are CYP2D6 poor metabolizers [9].
In summary, current pharmacogenetic evidence shows that genetic variation may play an important role in inter-individual differences in antipsychotic response and toxicity.
Enabling precision medicine with pharmacogenetic testing could reduce side effects associated with antipsychotics and improve treatment efficacy. Advances in pharmacogenetics will continue to uncover gene and medication interactions to predict treatment response and ultimately facilitate the incorporation of pharmacogenetic testing as a standard of clinical care.
Personalizing antipsychotic medications with TreatGxPlus
TreatGxPlus offers pharmacogenetic testing and a decision support tool that helps tailor medications to the patient’s unique genetic makeup and health profile. TreatGxPlus detects interactions between medications, genetics and health information to minimize drug-related side effects and increase the likelihood of selecting an effective medication.
In schizophrenia, the TreatGx decision support tool includes information within each medication option regarding the side effect profile of the antipsychotic, as well as pharmacogenetic information to personalize treatment options.
Risk of weight gain is rated as negligible (-) to high (+++) for each antipsychotic and can be used to determine a baseline risk of weight gain.
The medication options can be personalized using the patient’s pharmacogenetic results from the genetic variants in a number of genes: ANKK1, HTR2C, DRD2, and CYP2D6.
All the results from the TreatGxPlus genetic report are automatically uploaded into the TreatGx decision support tool and are ready to use.
In Canada, TreatGxPlus is brought to you in partnership with LifeLabs
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References
1. Müller DJ E al. Systematic analysis of dopamine receptor genes (DRD1-DRD5) in antipsychotic-induced weight gain. – PubMed – NCBI [Internet]. [cited 18 Dec 2017]. Available: https://www.ncbi.nlm.nih.gov/pubmed/20714340
2. Zai CC E al. Meta-analysis of two dopamine D2 receptor gene polymorphisms with tardive dyskinesia in schizophrenia patients. – PubMed – NCBI [Internet]. [cited 18 Dec 2017]. Available: https://www.ncbi.nlm.nih.gov/pubmed/17767146
3. Risselada AJ E al. Association between HTR2C gene polymorphisms and the metabolic syndrome in patients using antipsychotics: a replication study. – PubMed – NCBI [Internet]. [cited 18 Dec 2017]. Available: https://www.ncbi.nlm.nih.gov/pubmed/20680028
4. Mulder H E al. HTR2C gene polymorphisms and the metabolic syndrome in patients with schizophrenia: a replication study. – PubMed – NCBI [Internet]. [cited 18 Dec 2017]. Available: https://www.ncbi.nlm.nih.gov/pubmed/19142101
5. Xing Q E al. The relationship between the therapeutic response to risperidone and the dopamine D2 receptor polymorphism in Chinese schizophrenia patients. – PubMed – NCBI [Internet]. [cited 18 Dec 2017]. Available: https://www.ncbi.nlm.nih.gov/pubmed/17105675
6. Ikeda M E al. Variants of dopamine and serotonin candidate genes as predictors of response to risperidone treatment in first-episode schizophrenia. – PubMed – NCBI [Internet]. [cited 18 Dec 2017]. Available: https://www.ncbi.nlm.nih.gov/pubmed/18855532
7. Swen JJ E al. Pharmacogenetics: from bench to byte–an update of guidelines. – PubMed – NCBI [Internet]. [cited 18 Dec 2017]. Available: https://www.ncbi.nlm.nih.gov/pubmed/21412232
8. Rogers HL E al. CYP2D6 genotype information to guide pimozide treatment in adult and pediatric patients: basis for the U.S. Food and Drug Administration’s new dosi… – PubMed – NCBI [Internet]. [cited 18 Dec 2017]. Available: https://www.ncbi.nlm.nih.gov/pubmed/23059146
9. FDA, Evaluation CFD, Research. Science & Research (Drugs) – Table of Pharmacogenomic Biomarkers in Drug Labeling. Center for Drug Evaluation and Research; Available: https://www.fda.gov/Drugs/ScienceResearch/ucm572698.htm