Genetic Blueprints for Psychiatric Success: The Pharmacogenomics Revolution

Written by: Alejandra Lopez

Edited by: Athena Ke

Illustrated by: Caroline Shen

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The prescription of psychiatric medication has long relied on a trial-and-error approach, where patients often undergo multiple medication trials before finding an effective treatment. This type of prescribing presents a core challenge of high variability in individual responses to psychiatric medications, meaning that a medication that works for one person may fail or cause adverse effects for another. Factors such as metabolism, genetic makeup, and individual neurobiology play crucial roles in how a person responds to antidepressants, antipsychotics, and mood stabilizers [1]. As a result, patients may endure prolonged suffering, severe side effects, or treatment resistance while providers work to identify the proper medication and dosage.

Pharmacogenomics—the study of how genes influence drug responses—offers a promising solution to this uncertainty [2]. By analyzing genetic variations that impact how medications are processed or how well they work (such as variations in the CYP450 enzyme system, serotonin transporters, or dopamine receptors), pharmacogenomic testing allows clinicians to transition from guesswork toward personalized prescribing strategies [3]. 

In psychiatric care, pharmacogenomic-guided treatment strategies include tailored antidepressant selection, optimized antipsychotic dosing, and risk reduction of medication-induced side effects [4]. Through personalized prescribing, pharmacogenomics has the potential to minimize medication-related complications, improve patient adherence to prescribed healthcare, and shorten the time needed to achieve therapeutic success. Simply put, when a treatment works well and doesn’t cause uncomfortable side effects, people are more willing to stick with it. For instance, in the treatment of depression, patients often go through a trial-and-error process with antidepressants that may last weeks or months. Pharmacogenomic testing can identify how a patient metabolizes certain selective serotonin reuptake inhibitors (SSRIs) or serotonin-norepinephrine reuptake inhibitors (SNRIs) (e.g., via CYP2D6 or CYP2C19 gene variants), helping prescribers select a medication that the patient is more likely to respond to and tolerate well from the outset [5]. Similarly, in oncology, pharmacogenomics helps determine which chemotherapy drugs a cancer patient is most likely to respond to, avoiding ineffective or toxic treatments and improving survival rates [6]. Success, therefore, can mean quicker symptom relief, fewer side effects, reduced hospitalizations, improved quality of life, and better overall treatment outcomes in psychiatry [7].

The process by which the body breaks down and eliminates these medications is called drug metabolism [8]. This system plays a crucial role in psychiatric treatment, but each person’s body processes medication in different ways. Some bodies break down drugs too slowly, causing the medication to build up in their system, and others process medication too quickly, reducing the drug’s effectiveness. This variation is largely due to differences in enzymes, which are proteins in the liver that help break down medications [7]. One of the most essential enzyme families involved in drug metabolism is cytochrome P450 (CYP450). This group of enzymes is responsible for breaking down many psychiatric medications, including antidepressants and antipsychotics [3]. However, differences in the genes encoding these enzymes affect how well a person metabolizes their medication.

Individuals can be categorized into four different groups based on how their CYP450 enzymes function [9]. The first group, poor metabolizers, includes those who have very little or no working enzyme activity. Drugs stay in their system much longer, increasing the risk of side effects. Intermediate metabolizers process drugs somewhat slowly, which can also lead to increased effectiveness but to a lesser degree. Extensive metabolizers, sometimes called normal metabolizers, process drugs at an expected rate and respond to medication as intended. Lastly, those who possess ultrarapid metabolizers break down medications so quickly that the drug may not stay in their system long enough to be absorbed properly [8]. For example, nortriptyline, a medication often used to treat depression, is broken down by the CYP2D6 enzyme. A poor metabolizer of CYP2D6 will have high levels of nortriptyline in their body, increasing the risk of side effects such as dizziness or drowsiness. On the other hand, someone who possesses ultrarapid metabolizers will break down the drug so quickly that they might not experience any benefits [10]. Similarly, escitalopram, another antidepressant processed by CYP2C19, may require dosage adjustments depending on the patient’s genetic variation to avoid side effects or improve effectiveness [1].

Clinical guidelines from the Clinical Pharmacogenetics Implementation Consortium (CPIC) now recommend using genetic testing to guide prescribing for certain antidepressants and other psychiatric medications to ensure that patients receive the right dose and the right medication for their genetic profile [1, 9]. Receiving the right dosage based on a patient’s genetic profile helps avoid the common pitfalls of underdosing or overdosing, both of which can delay the intended effects and increase the risk of side effects. A genetically appropriate dose ensures that the medication reaches therapeutic levels in the body without causing toxicity, which not only improves patient safety but also makes psychiatric treatment more efficient and effective [1,8].

Integrating pharmacogenomics into clinical practice significantly enhances the way psychiatric medications are prescribed, moving away from the outdated "one-size-fits-all" model [4]. Traditionally, physicians prescribed common medications, such as SSRIs or antidepressants, based largely on symptom presentation, general guidelines, and population averages rather than individual biology. While this approach helped many, it left a substantial number of patients with inadequate relief or harmful side effects due to genetic differences that affected how their bodies processed these drugs [1]. As a result, treatment was a prolonged process of patients cycling through different medications to find one that sticks. Pharmacogenomic testing addresses this issue by identifying key genetic variations, particularly in enzymes like CYP2D6 and CYP2C19, that influence drug metabolism. This allows clinicians to select medications and doses better suited to each patient’s genetic makeup, improving outcomes and minimizing adverse reactions [8].

Beyond optimizing medication selection, pharmacogenomic testing has been shown to significantly reduce adverse drug reactions (ADRs), which are a common cause of treatment failure and hospitalization in psychiatric care. The European Ubiquitous Pharmacogenomics (U-PGx) clinical implementation project found that patients who received pharmacogenomic-guided treatment experienced a lower incidence of ADRs than those treated with standard prescribing methods, reporting a reduction in ADRs from 27.7% in the control group to 21% in the pharmacogenomic-guided group, highlighting the impact of genotype-guided drug prescribing in improving patient safety [11]. Fewer ADRs not only lead to improved medication adherence, since patients are less likely to stop their treatment due to unpleasant side effects, but also increased long-term treatment success by ensuring that individuals stay on the most effective medication regimen.

In addition to minimizing ADRs, pharmacogenomic-guided prescribing has been linked to a substantial reduction in hospital readmissions and emergency room visits. A randomized controlled trial assessed the impact of pharmacogenomic testing on clinical outcomes and found that patients who received gene-guided prescribing experienced a 52% fewer rehospitalizations, 42% fewer emergency visits, and 48% fewer combined events within 60 days compared to those receiving standard care [12]. While personalized medication management improves treatment outcomes according to these findings, it simultaneously reduces healthcare costs by preventing medication-related complications that often require urgent medical intervention. Patients who receive pharmacogenomic-guided treatment are more likely to achieve symptom relief sooner, avoid unnecessary side effects, and experience greater overall satisfaction with their psychiatric care.

One of the primary concerns in employing pharmacogenomics is privacy and data security, as genetic information is highly sensitive and vulnerable to breaches. For example, the 2023 cyberattack on 23andMe, which exposed 6.9 million users’ personal information and genetic data, demonstrated the privacy concerns associated with storing sensitive data in large databases [13]. Stronger protections for genetic data security are needed. Without the proper safeguards, individuals may face unauthorized use of their genetic data, potentially leading to exploitation or discrimination.

Furthermore, data sharing with third parties presents additional ethical challenges. Genetic data collected for pharmacogenomic testing is often shared with research institutions, pharmaceutical companies, and even private entities. For example, Nebula Genomics was accused of sharing DNA data with companies like Meta and Google without proper consent, raising concerns about the commercial exploitation of genetic information [14]. Such incidents highlight the need for stricter regulations on sharing and using genetic data. To mitigate these ethical concerns, stronger data protection laws, enhanced informed consent processes, and greater transparency in data-sharing agreements are necessary. Without these safeguards, the integration of pharmacogenomics into psychiatric care could pose significant risks to patient privacy and trust.

Pharmacogenomics represents a transformative shift in psychiatric treatment by replacing the traditional trial-and-error approach with personalized, precision-based prescribing. Pharmacogenomic testing enables optimized medication selection and reduces ADRs and hospital readmissions, as seen by the Ubiquitous Pharmacogenomics project, and concurrently minimizes side effects and enhances medication adherence. However, alongside these advancements, ethical concerns surrounding privacy, data security, and informed consent must be addressed to ensure responsible implementation.

As research continues to validate its clinical utility, pharmacogenomics is set to become a cornerstone in psychiatric and broader medical care. Investing in wider accessibility, clinician education, and stronger data protection policies will be critical to making pharmacogenomics an integral part of modern healthcare. With its ability to revolutionize psychiatric prescribing, pharmacogenomics represents the next breakthrough in personalized treatment, offering hope for more effective, efficient, and patient-centered mental health care.

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References

[1] Hicks, J. K., Bishop, J. R., Sangkuhl, K., Müller, D. J., Ji, Y., Leckband, S. G., Leeder, J. S., Graham, R. L., Chiulli, D. L., LLerena, A., Skaar, T. C., Scott, S. A., Stingl, J. C., Klein, T. E., Caudle, K. E., Gaedigk, A., & Clinical Pharmacogenetics Implementation Consortium (2015). Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline for CYP2D6 and CYP2C19 Genotypes and Dosing of Selective Serotonin Reuptake Inhibitors. Clinical pharmacology and therapeutics, 98(2), 127–134. https://doi.org/10.1002/cpt.147

[2] National Human Genome Research Institute. (2022, August 16). A brief guide to genomics. U.S. Department of Health & Human Services. https://www.genomeweb.com/

[3] McDonnell, A. M., & Dang, C. H. (2013). Basic review of the cytochrome p450 system. Journal of the advanced practitioner in oncology, 4(4), 263–268. https://doi.org/10.6004/jadpro.2013.4.4.7

[4] National Library of Medicine. (2022, March 22). What is pharmacogenomics? MedlinePlus. U.S. National Institutes of Health. https://medlineplus.gov/genetics/understanding/pharmacogenomics/

[5] Bousman, C. A., et al. (2016). Commercial pharmacogenetic-based decision-support tools in psychiatry. The Lancet Psychiatry, 3(6), 585–590. https://doi.org/10.1016/S2215-0366(16)30077-1

[6] Relling, M. V., & Evans, W. E. (2015). Pharmacogenomics in the clinic. Nature, 526(7573), 343–350. https://doi.org/10.1038/nature15817

[7] Kabbani, D., Akika, R., Wahid, A., Daly, A. K., Cascorbi, I., & Zgheib, N. K. (2023). Pharmacogenomics in practice: a review and implementation guide. Frontiers in pharmacology, 14, 1189976. https://doi.org/10.3389/fphar.2023.1189976

[8] Le, J. (2024, November). Drug metabolism. In Pharmacokinetics (Professional Version). Merck Manual. https://www.merckmanuals.com/professional/clinical-pharmacology/pharmacokinetics/drug-metabolism

[9] Caudle, K. E., Dunnenberger, H. M., Freimuth, R. R., Peterson, J. F., Burlison, J. D., Whirl-Carrillo, M., Scott, S. A., Rehm, H. L., Williams, M. S., Klein, T. E., Relling, M. V., & Hoffman, J. M. (2017). Standardizing terms for clinical pharmacogenetic test results: consensus terms from the Clinical Pharmacogenetics Implementation Consortium (CPIC). Genetics in medicine : official journal of the American College of Medical Genetics, 19(2), 215–223. https://doi.org/10.1038/gim.2016.87

[10] Hicks, J. K., Sangkuhl, K., Swen, J. J., Ellingrod, V. L., Müller, D. J., Shimoda, K., Bishop, J. R., Kharasch, E. D., Skaar, T. C., Gaedigk, A., Dunnenberger, H. M., Klein, T. E., Caudle, K. E., & Stingl, J. C. (2017). Clinical pharmacogenetics implementation consortium guideline (CPIC) for CYP2D6 and CYP2C19 genotypes and dosing of tricyclic antidepressants: 2016 update. Clinical pharmacology and therapeutics, 102(1), 37–44. https://doi.org/10.1002/cpt.597

[11] van der Wouden, C. H., Cambon-Thomsen, A., Cecchin, E., Cheung, K. C., Dávila-Fajardo, C. L., Deneer, V. H., Dolžan, V., Ingelman-Sundberg, M., Jönsson, S., Karlsson, M. O., Kriek, M., Mitropoulou, C., Patrinos, G. P., Pirmohamed, M., Samwald, M., Schaeffeler, E., Schwab, M., Steinberger, D., Stingl, J., Sunder-Plassmann, G., … Ubiquitous Pharmacogenomics Consortium (2017). Implementing Pharmacogenomics in Europe: Design and Implementation Strategy of the Ubiquitous Pharmacogenomics Consortium. Clinical pharmacology and therapeutics, 101(3), 341–358. https://doi.org/10.1002/cpt.602

[12] Chenchula, S., Atal, S., & Uppugunduri, C. R. S. (2024). A review of real-world evidence on preemptive pharmacogenomic testing for preventing adverse drug reactions: a reality for future health care. The pharmacogenomics journal, 24(2), 9. https://doi.org/10.1038/s41397-024-00326-1

[13] Carballo, R., Schmall, E., & Tumin, R. (2024, January 26). 23andMe breach targeted Jewish and Chinese customers, lawsuit says. The New York Times. https://www.nytimes.com/2024/01/26/business/23andme-breach-lawsuit.html

[14] Scarcella, M. (2024, October 11). DNA testing company Nebula was accused of violating privacy in a US lawsuit. Reuters. https://www.reuters.com/article/nebula-privacy-lawsuit-idUSXXXXXX