Drug hypersensitivity reactions (DHRs) represent a significant concern in the use of psychiatric medications, often leading to treatment discontinuation, prolonged hospitalization, and, in severe cases, life-threatening conditions such as Stevens-Johnson syndrome (SJS) or drug reaction with eosinophilia and systemic symptoms (DRESS) (Alchakee et al., 2022; Bousman et al., 2021; Wei et al., 2024). These adverse immune-mediated responses can occur with a wide range of psychotropic drugs, including anticonvulsants, antidepressants, and antipsychotics (Böhm and Cascorbi, 2016). The unpredictable nature of DHRs poses a major clinical challenge, as they are not dose-dependent and can manifest even after prior uneventful exposure (Elzagallaai and Rieder, 2022). Given the increasing reliance on pharmacotherapy in mental healthcare, understanding the mechanisms and risk factors of DHRs is crucial to improving patient safety and treatment outcomes.

Pharmacogenomics has emerged as a powerful tool in elucidating the genetic underpinnings of drug hypersensitivity, offering insights into interindividual variability in drug metabolism and immune response. Key genetic markers, such as human leukocyte antigen (HLA) alleles and polymorphisms in drug-metabolizing enzymes (e.g., CYP2C19, CYP2D6), have been strongly associated with DHR risk (Alchakee et al., 2022). For instance, the HLA-B*15:02 and HLA-A*31:01 variants are well-established predictors of carbamazepine-induced severe cutaneous reactions (Kaniwa and Saito, 2013). By integrating pharmacogenomic testing into clinical practice, clinicians may pre-emptively identify high-risk patients, enabling personalized drug selection and dose optimization to minimize adverse events.

This narrative review aims to synthesize current evidence on the pharmacogenomics of DHRs in psychiatric medications, focusing on genetic risk factors, mechanistic pathways, and clinical implications. We will examine HLA and non-HLA genetic associations across major psychotropic drug classes, evaluate the role of pharmacogenomic testing in preventing hypersensitivity reactions, and discuss challenges in implementation. Finally, we highlight future directions, including the integration of next-generation sequencing and global collaborative efforts to advance precision psychiatry. By bridging the gap between research and clinical practice, this review underscores the potential of pharmacogenomics to enhance drug safety and therapeutic efficacy in mental healthcare.

The HLA system, located within the major histocompatibility complex (MHC) on the short arm of chromosome 6 (6p21.3), plays a central role in immune recognition and response. The HLA molecules enable the immune system to distinguish between ‘self’ and ‘non-self’ antigens—essential for complement activation, cytotoxic T cell function, and the coordination of both cellular and humoral immunity (Crux and Elahi, 2017). While vital for host defense, the HLA system is also implicated in various autoimmune and inflammatory diseases, as well as hypersensitivity reactions to drugs.

The HLA genes are categorized into three primary classes, namely: Class I (HLA-A, -B, -C): Present intracellular peptides to CD8⁺ cytotoxic T lymphocytes, Class II (HLA-DR, -DQ, -DP): Present extracellular antigens to CD4⁺ helper T cells, and Class III: Encode immune-related proteins such as components of the complement system (Crux and Elahi, 2017). Importantly, the HLA region is the most polymorphic in the human genome, with over 9,000 alleles identified to date (Anaya et al., 2013). These polymorphisms, particularly in the peptide-binding domains, significantly influence antigen presentation and subsequent T cell activation.

Certain drugs can bind directly to specific HLA molecules or to HLA-bound peptides, a mechanism described by the pharmacological interaction (p-i) hypothesis. This non-covalent interaction can activate T cells independently of antigen processing, leading to hypersensitivity reactions (Meng et al., 2018).

Ethnic diversity plays a critical role in the distribution of HLA alleles, directly influencing individual susceptibility to drug hypersensitivity. This variation underscores the importance of population-based pharmacogenomics in guiding safe drug prescribing (Alfirevic and Pirmohamed, 2010). For instance, alleles associated with severe cutaneous adverse reactions (SCARs), such as Stevens–Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN), are expressed at differing frequencies across populations in the Middle East and North Africa (MENA), including the United Arab Emirates (UAE) (Masmoudi et al., 2022).

The Clinical Pharmacogenetics Implementation Consortium (CPIC) has identified several HLA alleles linked to psychiatric and antiepileptic drug hypersensitivity:

• HLA-B*15:02 – Strongly associated with carbamazepine-induced SJS/TEN. Though rare in Near Eastern populations (frequency: 0.0002), its clinical significance remains high due to the severity of reactions. In addition, a strong association has also been reported between HLA-B15:02 and phenytoin-induced SJS/TEN (Locharernkul et al., 2008).

Whilst these data offer insight into regional allele prevalence, they lack the ethnicity-specific granularity necessary for precise pharmacogenetic recommendations. This highlights the urgent need for nation-specific studies in the MENA region, particularly in the UAE, to better understand HLA distribution and improve personalized drug safety. Currently, the UAE faces limitations in terms of resources and data availability related to HLA-associated drug hypersensitivity, underscoring the importance of integrating pharmacogenomic testing and research into clinical and public health practice. The ongoing Emirati Genome Program is expected to provide valuable resource for pharmacogenomics studies in the near future.

Table 2 summarizes the key associations between specific HLA gene variants and adverse hypersensitivity reactions to psychiatric and antiepileptic drugs. Understanding these gene–drug interactions is crucial for identifying patients at increased risk and guiding pharmacogenetic-informed prescribing to improve drug safety (Q. Wang et al., 2011).

DHRs in psychiatric medications exhibit significant variability across drug classes, with distinct pharmacogenomic risk factors influencing susceptibility (Athanasiu et al., 2015; Cacabelos et al., 2013). Understanding these genetic associations is critical for risk stratification and personalized treatment approaches (Li et al., 2021). Pharmacogenomic research has identified key genetic markers for DHRs across major psychiatric drug classes, particularly for anticonvulsants and clozapine. However, gaps remain in understanding the genetic basis of hypersensitivity to newer antidepressants and some antipsychotics. Recent advances in psychopharmacology have introduced novel rapid-acting antidepressants, such as esketamine (a ketamine derivative) and psilocybin (a serotonergic psychedelic), offering new hope for treatment-resistant depression. However, their pharmacogenomic profiles and potential hypersensitivity risks remain understudied. Emerging evidence suggests that genetic variability in drug metabolism and receptor interactions may influence both therapeutic response and adverse reactions.

There is a myriad of general factors related to the drug and the patient, which interact to determine the occurrence and severity of the DHR. Drug-related factors include protein reactivity, the ability of the compound/drug to induce a danger/stress signal, the presence of a T-cell repertoire to recognize the antigen, and the frequency and route of the drug administration (Naisbitt et al., 2000).

Drugs of low molecular weight may directly react with proteins or undergo UV-light activation in the case of photosensitivity (bioactivation) to become protein-reactive. The hapten-protein bioconjugates formed through direct binding, bioactivation, or UV-light-dependent activation can be immunogenic; however, the mechanism of the immune response remains to be elucidated (Adair et al., 2021; Tailor et al., 2016). Interestingly, the hapten-protein complexes could be found in allergic and non-allergic individuals. On the other hand, some medications can induce or activate the stress/danger signals by activating the dendritic cells through increasing the expression of CD40. The damage-associated molecular pattern (DAMP) molecules, such as HMGB1, serve as a biomarker for adverse drug reactions (ADRs) (Carr and Pirmohamed, 2018). The HMGB1 serum levels are usually elevated in DRESS and SJS/TEN (Fujita et al., 2014; Nakajima, 2011), whereas IL-33 increases in early stages of TEN (Adachi et al., 2019). Whether the level of rise of HMGB1 can be used a biomarker for the severity of such reactions should be further evaluated.

Some models have been developed to recognize the drug-related hypersensitivity reactions using THP-1 cells and IL-8 production by mature dendritic cells (Kim and Naisbitt, 2016; Pallardy and Bechara, 2017).

Two important points are noteworthy; first, the presence of T-cell programming or a specific repertoire of T-cells (e.g., in the case of benzylpenicillin). In such case, the related peptides can be immunodominant and recognized by peripheral blood polymorphic Cells (PBMC) of the allergic patients, and can be used in immunization of such patients (Azoury et al., 2018). Second, in many cases, intermittent and repeated administrations of some drugs lead to more sensitization than uninterrupted treatment. Moreover, parenteral administration appears to be more sensitizing than the oral route.

In addition to genetics as a major determinant of DHR, several other patient-related factors exist. Drug-specific T-cell responses in allergic patients have been studied, in addition to the drug-responsive naïve T cells. To address specific T-cell responses to drugs using ex vivo samples from allergic patients, several protocols have been established, with the lymphocyte transformation test being the most frequently used assay (Naisbitt et al., 2014). Noteworthy, elderly patients and those on polypharmacy have a higher risk of developing allergic diseases (Cardona et al., 2011). The risk of DHR is also related to concurrent infections (Castrejon et al., 2010). Individual variations of T-regulatory cell number and the immune checkpoint expression (e.g., PD-1 and CTLA4) can explain the wide range of presentations of allergic reactions, despite the presence of several risk factors (Hammond et al., 2022; Line et al., 2022).

Pharmacogenomic (PGx) testing is playing an increasingly important role in psychiatric care, especially in preventing ADRs and optimizing treatment outcomes. One of its most promising applications is pre-emptive genetic screening to reduce the risk of DHRs and improve the tolerability of psychotropic medications.

Despite the growing promise of pharmacogenomics in improving drug safety and therapeutic outcomes, several significant challenges and limitations continue to hinder its widespread clinical adoption. One major obstacle is the variability in the availability and interpretation of genetic testing (Bousman et al., 2021). Access to pharmacogenomic testing remains uneven across different healthcare systems and regions, often limited to well-resourced or urban settings. Even when tests are available, inconsistencies in test platforms, reporting formats, and the interpretation of results can lead to confusion among healthcare providers. This variability reduces the reliability and clinical utility of test outcomes and contributes to hesitation in using pharmacogenomic data for therapeutic decisions.

Another critical concern involves the ethical and economic implications of pharmacogenomic testing (Karamperis et al., 2021; Pardiñas et al., 2021). From an ethical standpoint, questions about patient privacy, data security, and potential genetic discrimination remain unresolved. Genetic data is inherently sensitive, and its misuse could lead to social stigma or discrimination in insurance and employment. Economically, the high upfront cost of testing and the lack of reimbursement by many insurance systems pose substantial barriers. Although PGx testing may lead to long-term healthcare savings by reducing adverse drug reactions and improving treatment efficacy, the initial expense can deter healthcare institutions from incorporating these services, especially in lower-income or resource-constrained settings.

Furthermore, the lack of standardized guidelines and protocols for pharmacogenomic implementation continues to limit its integration into routine care (Alchakee et al., 2022; Kabbani et al., 2023). While organizations like CPIC and DPWG offer valuable recommendations, these are not uniformly adopted or enforced across national or institutional frameworks. Many healthcare systems lack cohesive policies regarding when and how to perform genetic testing, how to interpret the results, and how to apply them to prescribing decisions. This inconsistency contributes to underutilization and clinical uncertainty, as physicians may lack both the confidence and the tools to translate pharmacogenomic data into actionable insights.

Together, these challenges highlight the need for improving infrastructure, regulatory frameworks, clinician education, and cross-disciplinary collaboration to support the responsible, equitable, and effective integration of pharmacogenomics into clinical practice.

This review examined the underlying mechanisms of drug hypersensitivity reactions, with a particular focus on immunological pathways, the formation of reactive drug metabolites, and genetic susceptibility factors. These include well-established associations with HLA alleles and polymorphisms in drug-metabolizing enzymes such as those in the cytochrome P450 family. We explored the pharmacogenomics of key psychiatric medications, particularly anticonvulsants (e.g., carbamazepine, lamotrigine), antidepressants (e.g., SSRIs and novel agents), and antipsychotics (e.g., clozapine and newer generation drugs)—and identified several genetic variants linked to increased risk of adverse drug reactions. The clinical utility of pharmacogenomic testing was emphasized, especially in its capacity to pre-emptively identify individuals at high risk for DHRs and guide safer, more personalized prescribing practices. Nevertheless, several challenges persist, including the variability in test availability, differences in interpretation standards, ethical concerns surrounding genetic data use, and the absence of universally accepted guidelines for pharmacogenomic implementation.

Looking ahead, recent advances in genomic technology, particularly next-generation sequencing (NGS), have transformed the field by enabling the rapid and cost-effective analysis of genetic variation across diverse populations (Behjati and Tarpey, 2013). Beyond individual gene-drug interactions, NGS provides a foundational platform for multiomic approaches that integrate genomic, epigenomic, transcriptomic, proteomic, and metabolomic data to yield a comprehensive view of disease biology and drug response (Hasin et al., 2017). These multilayered datasets offer enhanced predictive power over single-layer genomic analyses, particularly for complex psychiatric disorders where treatment outcomes are influenced by diverse biological systems. A recent multiomic study in schizophrenia exemplifies this promise. By integrating DNA methylation data with genetic risk scores, researchers developed a robust predictive model for antipsychotic drug (APD) response, using epigenetic and genetic markers from six cortical genes. Validated in over 3,600 patients, this model demonstrated strong accuracy and clinical applicability, underscoring the potential of multiomic pharmacogenomics in personalizing psychiatric treatment (Guo et al., 2023).

Regionally, initiatives like the Emirati Genome Program are laying the groundwork for precision medicine by cataloging population-specific genetic variants through large-scale NGS efforts (Ateia et al., 2023). This localized reference data is crucial for tailoring pharmacogenomic applications to regional populations and may eventually support future multiomic analyses to refine clinical decision-making.

To maximize the global impact of these developments, international collaboration and equitable data sharing are essential. Pharmacogenomic insights must be drawn from diverse populations to ensure applicability and fairness in precision medicine (Relling and Klein, 2011). Open-access resources such as PharmGKB and collaborative efforts from CPIC and DPWG play pivotal roles in translating genomic evidence into clinical guidance. However, global uptake of these frameworks remains inconsistent. Expanding participation through international partnerships and prioritizing research in underrepresented populations will be key. By developing shared, globally accessible pharmacogenomic databases, we can transform localized discoveries into scalable, real-world tools for personalized psychiatric care.

In conclusion, pharmacogenomics holds transformative potential to optimize psychiatric drug therapy, reduce adverse reactions, and improve treatment outcomes. Continued investment in research, infrastructure, and international collaboration will be vital to translating this promise into routine clinical practice worldwide.