Front Genet. 2025 Jan 9;15:1523071. doi: 10.3389/fgene.2024.1523071. eCollection 2024.

NO ABSTRACT

PMID:39850490 | PMC:PMC11754187 | DOI:10.3389/fgene.2024.1523071

Int J Biol Macromol. 2025 Jan 21:140204. doi: 10.1016/j.ijbiomac.2025.140204. Online ahead of print.

ABSTRACT

Colorectal cancer (CRC) affects the population worldwide, occupying the first place in terms of death and incidence. Synthetic peptides (SPs) emerged as alternative molecules due to their activity and low toxicity. Proteomic analysis of PepGAT-treated HCT-116 cells revealed a decreased abundance of proteins involved in ROS metabolism and energetic metabolisms, cell cycle, DNA repair, migration, invasion, cancer aggressiveness, and proteins involved in resistance to 5-FU. PepGAT induced earlier ROS and apoptosis in HCT-116 cells, cell cycle arrest, and inhibited HCT-116 migration. PepGAT enhances the action of 5-FU against HCT-116 cells by dropping down 6-fold the 5-FU toward HCT-116 and reduces its toxicity for non-cancerous cells. These findings strongly suggest the multiple mechanisms of action displayed by PepGAT against CRC cells and its potential to either be studied alone or in combination with 5-FU to develop new studies against CRC and might develop new drugs against it.

PMID:39848367 | DOI:10.1016/j.ijbiomac.2025.140204

Annu Rev Pharmacol Toxicol. 2025 Jan;65(1):111-130. doi: 10.1146/annurev-pharmtox-061724-080718.

ABSTRACT

Pharmacogenetic variation is common and an established driver of response for many drugs. There has been tremendous progress in pharmacogenetics knowledge over the last 30 years and in clinical implementation of that knowledge over the last 15 years. But there have also been many examples where translation has stalled because of the lack of available data sets for discovery or validation research. The recent availability of data from very large cohorts with linked genetic, electronic health record, and other data promises new opportunities to advance pharmacogenetics research. This review presents the stages from pharmacogenetics discovery to widespread clinical adoption using prominent gene-drug pairs that have been implemented into clinical practice as examples. We discuss the opportunities that the All of Us Research Program and other large biorepositories with genomic and linked electronic health record data present in advancing and accelerating the translation of pharmacogenetics into clinical practice.

PMID:39847465 | DOI:10.1146/annurev-pharmtox-061724-080718

Nature. 2025 Jan 22. doi: 10.1038/s41586-024-08468-9. Online ahead of print.

ABSTRACT

Bipolar disorder is a leading contributor to the global burden of disease1. Despite high heritability (60-80%), the majority of the underlying genetic determinants remain unknown2. We analysed data from participants of European, East Asian, African American and Latino ancestries (n = 158,036 cases with bipolar disorder, 2.8 million controls), combining clinical, community and self-reported samples. We identified 298 genome-wide significant loci in the multi-ancestry meta-analysis, a fourfold increase over previous findings3, and identified an ancestry-specific association in the East Asian cohort. Integrating results from fine-mapping and other variant-to-gene mapping approaches identified 36 credible genes in the aetiology of bipolar disorder. Genes prioritized through fine-mapping were enriched for ultra-rare damaging missense and protein-truncating variations in cases with bipolar disorder4, highlighting convergence of common and rare variant signals. We report differences in the genetic architecture of bipolar disorder depending on the source of patient ascertainment and on bipolar disorder subtype (type I or type II). Several analyses implicate specific cell types in the pathophysiology of bipolar disorder, including GABAergic interneurons and medium spiny neurons. Together, these analyses provide additional insights into the genetic architecture and biological underpinnings of bipolar disorder.

PMID:39843750 | DOI:10.1038/s41586-024-08468-9

J Pharm Biomed Anal. 2025 Jan 20;256:116684. doi: 10.1016/j.jpba.2025.116684. Online ahead of print.

ABSTRACT

Alkaptonuria (AKU) is a rare autosomal-recessive disease which is characterized through black urine and ochronosis. It is caused by deficiency of the enzyme Homogentisate 1,2-dioxygenase in the Phenylalanine/Tyrosine degradation pathway which leads to the accumulation of Homogentisic acid (HGA). Urine was provided by AKU patients and healthy controls. Several different methods were developed in this study each with a specific goal. Firstly, a simple and inexpensive RP-UHPLC-UV method for routine monitoring of HGA as a key metabolite employing a Phenylhexyl stationary phase chemistry. Validation was performed in accordance to FDA guidelines and method selectivity was further evaluated via on-line high-resolution sampling 2D-LC-QToF-MS, coupling the Phenylhexyl phase in the first dimension with a C18 phase in the second dimension. Secondly, a targeted and accurate RP-UHPLC-MRM-QTRAP assay, providing quantitative analysis of the relevant pathway metabolites based on a Phenylhexyl stationary phase, and lastly an untargeted HILIC-UHPLC-QToF-MS/MS method with SWATH (sequential window acquisition of all theoretical mass spectra) acquisition employing a sulfobetaine-type HILIC-Z superficially porous particle column, with the aim of uncovering more details about the metabolic profile of this genetic disorder. By untargeted analysis 204 metabolites could be detected and annotated in positive and negative ESI mode in total. Two separate LC methods were employed, differing in their conditions depending on the ionization mode (20 mM ammonium formate as buffer additive adjusted to a pH = 3.5 with formic acid in ESI+ mode and 20 mM ammonium acetate adjusted to a pH = 7.5 with acetic acid in ESI- mode). By effectively combining the aforementioned methods, a comprehensive workflow was developed, allowing the effective analysis of both patient and control urine samples.

PMID:39842076 | DOI:10.1016/j.jpba.2025.116684

Expert Opin Drug Metab Toxicol. 2025 Jan 22. doi: 10.1080/17425255.2025.2455388. Online ahead of print.

ABSTRACT

INTRODUCTION: . Idiosyncratic adverse drug reactions (IADRs) or drug hypersensitivity reactions (DHRs) represent a major health problem because they are unpredictable and can be severe with potential life-long or even lethal consequences. Their pathophysiology is not clear but thought to be immune mediated supported by the significant statistical association of these reactions with specific alleles of the human leukocyte antigen (HLA) gene.

AREA COVERED: This comprehensive update review summarizes the currently available evidence on the role of HLA gene locus in IADRs and discusses the present understanding of the pathophysiology of IADRs. We searched the available literature in PubMed and Google Scholar with no date restriction for publications on HLA and adverse drug reactions. Findings are summarized and discussed in the context of the currently available evidence.

EXPERT OPINION: The role of the immune system in IADRs and the role of pharmacogenetic testing in this field is evident. HLA genetic testing is a very promising in the management of these reaction. Many obstacles seem to prevent pharmacogenetic testing to meet its full potential including cost and healthcare providers education. Further work in needed to provide more evidence and allow widespread use of pharmacogenetic testing in the clinical practice.

PMID:39841586 | DOI:10.1080/17425255.2025.2455388

Clin Pract Epidemiol Ment Health. 2024 Dec 3;20:e17450179337258. doi: 10.2174/0117450179337258241031035148. eCollection 2024.

ABSTRACT

BACKGROUND: Many pharmacological treatments are considered effective in the treatment of panic disorder (PD), however, about 20 to 40% of the patients have treatment-resistant PD. Pharmacogenetics could explain why some patients are treatment-resistant.

OBJECTIVE: Our objective was to gather preliminary data on the clinical usefulness of pharmacogenetic testing in this disorder.

METHODS: Twenty patients with treatment-resistant PD were included in this observational study and submitted to commercial pharmacogenetic testing. Testing panel included gene polymorphisms related to CYP, genes EPHX1, UGT1A4, UGT2B15, ABCB1, ADRA2A, ANKK1, COMT, DRD2, FKBP5, GRIK4, GSK3B, HTR1A, HTR2A, HTR2C, MC4R, OPRM1, SCN1A, SLC6A4 and MTHFR. Participants received treatment-as-usual for PD before being enrolled in this study, including first-line and second-line medications for PD.

RESULTS: In 30% of the patients, the tests indicated reduced chance of response to the prescribed drug, while they indicated very low serum levels of the prescribed drug in 20% of the subjects. The pharmacogenetic tests predicted reduction of MTHFR enzyme activity in 74% of the patients. ABCB1 gene alleles associated to drug resistance were found in 90% of the samples.

CONCLUSION: Commercial pharmacogenetic testing failed to predict negative treatment outcome in most patients with PD. The association between treatment-resistance in PD and the genes CYP2C19, MTHFR and ABCB1 deserves further study.

PMID:39839219 | PMC:PMC11748058 | DOI:10.2174/0117450179337258241031035148

Front Psychiatry. 2025 Jan 7;15:1497565. doi: 10.3389/fpsyt.2024.1497565. eCollection 2024.

ABSTRACT

The application of personalized medicine in patients with first-episode psychosis (FEP) requires tools for classifying patients according to their response to treatment, considering both treatment efficacy and toxicity. However, several limitations have hindered its translation into clinical practice. Here, we describe the rationale, aims and methodology of Applied Pharmacogenetics to Predict Response to Treatment of First Psychotic Episode (the FarmaPRED-PEP project), which aims to develop and validate predictive algorithms to classify FEP patients according to their response to antipsychotics, thereby allowing the most appropriate treatment strategy to be selected. These predictors will integrate, through machine learning techniques, pharmacogenetic (measured as polygenic risk scores) and epigenetic data together with clinical, sociodemographic, environmental, and neuroanatomical data. To do this, the FarmaPRED-PEP project will use data from two already recruited cohorts: the PEPS cohort from the "Genotype-Phenotype Interaction and Environment. Application to a Predictive Model in First Psychotic Episodes" study (the PEPs study from the Spanish abbreviation) (N=335) and the PAFIP cohort from "Clinical Program on Early Phases of Psychosis" (PAFIP from the Spanish abbreviation) (N = 350). These cohorts will be used to create the predictor, which will then be validated in a new cohort, the FarmaPRED cohort (N = 300). The FarmaPRED-PEP project has been designed to overcome several of the limitations identified in pharmacogenetic studies in psychiatry: (1) the sample size; (2) the phenotype heterogeneity and its definition; (3) the complexity of the phenotype and (4) the gender perspective. The global reach of the FarmaPRED-PEP project is to facilitate the effective deployment of precision medicine in national health systems.

PMID:39839139 | PMC:PMC11747510 | DOI:10.3389/fpsyt.2024.1497565

Curr Hypertens Rev. 2025 Jan 20. doi: 10.2174/0115734021342501250107052350. Online ahead of print.

ABSTRACT

INTRODUCTION: Hypertension is a chronic medical state and a major determining factor for cardiovascular and renal diseases. Both genetic and non-genetic factors contribute to hypertensive conditions among individuals. The renin-angiotensin-aldosterone system (RAAS) is a major genetic target for the anti-hypertension approach.

PURPOSE OF THE STUDY: The majority of classical antihypertensive drugs were mainly focused on the RAAS signaling pathways. Though these antihypertensive drugs control blood pressure (BP), they have mild to severe life-threatening effects. Unrevealing effective hypertensive targets for BP management is essential. The effective targets could emerge either from RAAS-dependent or RAAS-independent pathways and/or through the cross-talks among them.

RESULTS: Analyzing the physiopathological mechanisms of hypertension has the benefit of understanding the interactions between these systems which helps in better understanding of drug targets and the importance of emergence of novel therapeutics.

CONCLUSION: This review is about the signaling pathways involved in hypertension pathogenesis and their cross-talks and it contributes to a better understanding of the etiology of hypertension.

PMID:39838689 | DOI:10.2174/0115734021342501250107052350

Recent Pat Biotechnol. 2025 Jan 20. doi: 10.2174/0118722083359334250116063638. Online ahead of print.

ABSTRACT

Personalized medicine is an evolving paradigm that aims to tailor therapeutic interventions to individual patient characteristics. With a growing understanding of the genetic, epigenetic, and molecular mechanisms underlying diseases, tailored therapies are becoming more feasible and effective. This review highlights the significant advancements in personalized medicine, focusing specifically on pharmacological strategies. The article explores the integration of genomics, transcriptomics, proteomics, and metabolomics in drug development and therapy optimization. Pharmacogenomics, the customization of drug therapy based on an individual's genetic makeup, receives particular emphasis. This leads to the identification of specific biomarkers that can predict therapeutic response, drug toxicity, and susceptibility to various diseases. Together with computational tools and artificial intelligence, these advancements contribute to tailored treatment plans for patients with conditions such as cancer, cardiovascular diseases, and neurological disorders. We also highlight the challenges and ethical considerations in implementing personalized medicine, such as data privacy, cost-effectiveness, and accessibility. We outline future prospects and ongoing research in this field, highlighting the importance of collaborative efforts between researchers, clinicians, pharmacists, and regulatory authorities.

PMID:39838664 | DOI:10.2174/0118722083359334250116063638

Transl Psychiatry. 2025 Jan 22;15(1):16. doi: 10.1038/s41398-025-03235-4.

ABSTRACT

The pace of biological aging varies between people independently of chronological age and mitochondria dysfunction is a key hallmark of biological aging. We hypothesized that higher functional impact (FI) score of mitochondrial DNA (mtDNA) variants might contribute to premature aging and tested the relationships between a novel FI score of mtDNA variants and epigenetic and biological aging in young adulthood. A total of 81 participants from the European Longitudinal Study of Pregnancy and Childhood (ELSPAC) prenatal birth cohort had good quality genetic data as well as blood-based markers to estimate biological aging in the late 20. A subset of these participants (n = 69) also had epigenetic data to estimate epigenetic aging in the early 20s using Horvath's epigenetic clock. The novel FI score was calculated based on 7 potentially pathogenic mtDNA variants. Greater FI score of mtDNA variants was associated with older epigenetic age in the early 20s and older biological age in the late 20s. These medium to large effects were independent of sex, current BMI, cigarette smoking, cannabis, and alcohol use. These findings suggest that elevated FI score of mtDNA variants might contribute to premature aging in young adulthood.

PMID:39837837 | DOI:10.1038/s41398-025-03235-4

Pediatr Infect Dis J. 2025 Jan 10. doi: 10.1097/INF.0000000000004683. Online ahead of print.

ABSTRACT

We investigated the steady-state pharmacokinetics of generic abacavir (ABC)/lamivudine (3TC) dispersible tablets (DTs) in young children living with HIV aged 3 months to <7 years, weighing 6 to <20 kg. Twenty-eight Thai children were enrolled and received ABC/3TC-DT plus pediatric dolutegravir-DT once daily. ABC/3TC was administered using WHO weight band (WB) doses: 180/90 mg, 240/120 mg and 300/150 mg for children weighing 6 to <10 kg (WB 1, n = 7), 10 to <14 kg (WB2, n = 9) and 14 to <20 kg (WB3, n = 12), respectively. ABC geometric mean (GM) AUC0-24 h (CV%) was 14.2 (50.5%), 15.6 (32.6%) and 20.7 (28.3%) mg.h/L, respectively, and 3TC GM AUC0-24 h was 14.8 (44.1%), 18.2 (28.0%) and 19.9 (26.2%) mg.h/L, respectively. ABC and 3TC exposures were within target ranges across WBs. These data supported current ABC/3TC-DT WHO-weight band dosing guidance for young children in Thailand.

PMID:39836566 | DOI:10.1097/INF.0000000000004683

Expert Opin Drug Metab Toxicol. 2025 Jan 21:1-28. doi: 10.1080/17425255.2024.2433626. Online ahead of print.

ABSTRACT

INTRODUCTION: Genetic load influences the therapeutic response to conventional drugs in Alzheimer's disease (AD). Pharmacogenetics (PGx) is the best option to reduce drug-drug interactions and adverse drug reactions in patients undergoing polypharmacy regimens. However, there are important limitations that make it difficult to incorporate pharmacogenetics into routine clinical practice.

AREAS COVERED: This article analyzes the pharmacogenetic apparatus made up of pathogenic, mechanistic, metabolic, transporter, and pleiotropic genes responsible for the efficacy and safety of pharmacological treatment, the impact of genetic load on the outcome of multifactorial treatments, and practical aspects for the effective use of PGx.

EXPERT OPINION: Over 120 genes are closely associated with AD. There is an accumulation of cerebrovascular (CVn) and neurodegenerative (ADn) genes in AD. APOE-4 carriers accumulate more deleterious genetic load related to other CVn and ADn genes, develop the disease earlier, and are at a biological disadvantage compared to APOE-4 non-carriers. CYP2D6-PMs and APOE-4 carriers are the worst responders to anti-dementia drugs. Some limitations hinder the implementation of PGx in clinical practice, including lack of pharmacogenetic information for many drugs, low number of genes in PGx screening protocols, and educational deficiencies in the medical community regarding PGx and genomic medicine.

PMID:39835706 | DOI:10.1080/17425255.2024.2433626

Front Endocrinol (Lausanne). 2025 Jan 6;15:1537014. doi: 10.3389/fendo.2024.1537014. eCollection 2024.

ABSTRACT

[This corrects the article DOI: 10.3389/fendo.2023.1184024.].

PMID:39835259 | PMC:PMC11744269 | DOI:10.3389/fendo.2024.1537014

Cureus. 2024 Dec 20;16(12):e76089. doi: 10.7759/cureus.76089. eCollection 2024 Dec.

ABSTRACT

Shock is a state of inadequate perfusion that affects vital organs. Cardiogenic shock (CS) predisposes patients to various arrhythmias. The adverse effect depends on intervention and pharmacogenomics. This narrative review sheds light on treatment strategies for arrhythmias caused by milrinone and dobutamine when managing CS. Dobutamine, through beta-1 agonism, and milrinone, by phosphodiesterase-3 inhibition, increase cardiac contractility by enhancing the availability of calcium to the myocardium. Dobutamine is also a beta-2 agonist, and milrinone is a phosphodiesterase-3 inhibitor; both result in peripheral vasodilation, leading to their use preferentially in patients with CS with normotensive blood pressure. To narrow down relevant literature, various electronic databases, including PubMed, Google Scholar, and Cochrane Library, were searched. The review revealed limited evidence favoring either milrinone or dobutamine as the preferred inotropic agent for managing CS, but it did reveal that though hospital stays using dobutamine were shorter, mortality from its induced arrhythmias led to an increase in all-cause mortality rates. Both proarrhythmic agents triggered ventricular and supraventricular tachyarrhythmias, some requiring cardioversion while others are non-sustained and managed medically or symptomatically. Though neither agent has a specific reversal agent, the effect of dobutamine was seen to be successfully aborted using intravenous ultrashort half-life beta-blockers (such as esmolol). The findings accentuated the critical need for a tailored approach to managing these iatrogenic arrhythmias, emphasizing clinical vigilance and individualized patient care.

PMID:39835019 | PMC:PMC11743927 | DOI:10.7759/cureus.76089

Genome Med. 2025 Jan 20;17(1):7. doi: 10.1186/s13073-025-01431-x.

ABSTRACT

BACKGROUND: Large-scale pharmacogenomic resources, such as the Connectivity Map (CMap), have greatly assisted computational drug discovery. However, despite their widespread use, CMap-based methods have thus far been agnostic to the biological activity of drugs as well as to the genomic effects of drugs in multiple disease contexts. Here, we present a network-based statistical approach, Pathopticon, that uses CMap to build cell type-specific gene-drug perturbation networks and integrates these networks with cheminformatic data and diverse disease phenotypes to prioritize drugs in a cell type-dependent manner.

METHODS: We build cell type-specific gene-drug perturbation networks from CMap data using a statistical procedure we call Quantile-based Instance Z-score Consensus (QUIZ-C). Using these networks and a large-scale disease-gene network consisting of 569 disease signatures from the Enrichr database, we calculate Pathophenotypic Congruity Scores (PACOS) between input gene signatures and drug perturbation signatures and combine these scores with cheminformatic data from ChEMBL to prioritize drugs. We benchmark our approach by calculating area under the receiver operating characteristic curves (AUROC) for 73 gene sets from the Molecular Signatures Database (MSigDB) using target gene expression profiles from the Comparative Toxicogenomics Database (CTD). We validate the drugs predicted in our proofs-of-concept using real-time polymerase chain reaction (qPCR) experiments.

RESULTS: Cell type-specific gene-drug perturbation networks built using QUIZ-C are topologically distinct, reflecting the biological uniqueness of the cell lines in CMap, and are enriched in known drug targets. Pathopticon demonstrates a better prediction performance than solely cheminformatic measures as well as state-of-the-art network and deep learning-based methods. Top predictions made by Pathopticon have high chemical structural diversity, suggesting their potential for building compound libraries. In proof-of-concept applications on vascular diseases, we demonstrate that Pathopticon helps guide in vitro experiments by identifying pathways that are potentially regulated by the predicted therapeutic candidates.

CONCLUSIONS: Our network-based analytical framework integrating pharmacogenomics and cheminformatics (available at https://github.com/r-duh/Pathopticon ) provides a feasible blueprint for a cell type-specific drug discovery and repositioning platform with broad implications for the efficiency and success of drug development.

PMID:39833831 | DOI:10.1186/s13073-025-01431-x

Pharmacogenet Genomics. 2025 Jan 21. doi: 10.1097/FPC.0000000000000558. Online ahead of print.

ABSTRACT

Ibrutinib treatment is often complicated by cardiovascular side effects (CVSEs). The objective of this retrospective pharmacogenetic study is to replicate a previously reported association of 'high-risk' patients, who are homozygous carriers of at least two of GATA4 rs804280 AA, KCNQ1 rs163182 GG, and KCNQ1 rs2237895 AA, with increased risk of hypertension or atrial fibrillation, and explore associations for other pharmacogenes (e.g. CYP3A4, CYP3A5, CYP2D6, and ABCB1) with ibrutinib CVSEs. Univariate associations with P < 0.05 were adjusted for significant pretreatment cardiovascular conditions. In total 57 patients were included in the analysis. In the primary analysis, 'high-risk' patients were not more likely to experience hypertension or atrial fibrillation (70 vs. 41%, chi-square P value = 0.06). In secondary analyses, 'high-risk' patients were more likely to experience any CVSE during treatment (75 vs. 41%, P = 0.013), develop a cardiac rhythm or function disorder (65 vs. 24%, P = 0.008), and have a treatment modification due to CVSE (45 vs. 8%, P = 0.004). Additionally, high-risk homozygous variant genotypes of KCNQ1 rs163182 GG and rs2237895 AA were each associated with an increased likelihood of treatment modifications due to CVSE (40 vs. 11%, P = 0.021 and 45 vs. 9%, P = 0.004, respectively) and cardiac rhythm or function disorders (60 vs. 27%, P = 0.037 and 60 vs. 27%, P = 0.037). This study found supportive evidence that 'high-risk' genotype was associated with increased ibrutinib CVSEs. Validation of these associations is necessary before prospective trials testing whether personalized ibrutinib treatment approaches improve clinical outcomes.

PMID:39832190 | DOI:10.1097/FPC.0000000000000558

Eur J Clin Pharmacol. 2025 Jan 17. doi: 10.1007/s00228-025-03805-x. Online ahead of print.

ABSTRACT

OBJECTIVE: The study aims to verify the usage of mathematical modeling in predicting patients' medication doses in association with their genotypes versus real-world data.

METHODS: The work relied on collecting, extracting, and using real-world data on dosing and patients' genotypes. Drug metabolizing enzymes, i.e., cytochrome CYP 450, were the focus. A total number of 1914 subjects from 26 studies were considered, and CYP2D6 and CYP2C19 gene polymorphisms were used for the verification.

RESULTS: Results show that the mathematical model was able to predict the reported optimal dosing of the values provided in the considered studies. Predicting patients' optimal doses circumvents trial and error in patients' treatments.

DISCUSSION: The authors discussed the advantages of using a mathematical model in patients' dosing and identified multiple issues that would hinder the usability of raw data in the future, especially in the era of artificial intelligence (AI). The authors recommend that researchers and healthcare professionals use simple descriptive metabolic activity terms for patients and use allele activity scores for drug dosing rather than phenotype/genotype classifications.

CONCLUSION: The authors verified that a mathematical model could assist in providing data for better-informed decision-making in clinical settings and drug research and development.

PMID:39832006 | DOI:10.1007/s00228-025-03805-x

Front Pharmacol. 2025 Jan 3;15:1540478. doi: 10.3389/fphar.2024.1540478. eCollection 2024.

NO ABSTRACT

PMID:39830351 | PMC:PMC11739166 | DOI:10.3389/fphar.2024.1540478

Front Pharmacol. 2025 Jan 3;15:1526101. doi: 10.3389/fphar.2024.1526101. eCollection 2024.

ABSTRACT

INTRODUCTION: The field of pharmacogenetics (PGx) is experiencing significant growth, with increasing evidence to support its application in psychiatric care, suggesting its potential to personalize treatment plans, optimize medication efficacy, and reduce adverse drug reactions. However, the perceived utility and practicability of PGx for psychiatric treatment in youth remains underexplored. This study investigated perceived barriers and attitudes in Australian young adults towards the implementation of PGx testing to guide antidepressant treatment in primary care.

METHODS: Semi-structured focus groups and interviews were conducted with 17 participants aged between 18 and 24 years. These sessions were recorded and transcribed before thematic analysis was used to identify collective themes.

RESULTS: Three key themes were identified, including attitudes towards the medication prescription process, concerns and attitudes towards PGx testing, and perceived barriers to its clinical implementation. Although PGx testing was positively perceived by most participants, all participants shared concerns about PGx testing. Participants voiced concerns about the financial impact of PGx testing, the potential for treatment delays, and the accuracy of PGx testing in guiding antidepressant treatment. Additionally, participants noted that the low awareness and willingness of general practitioners to incorporate PGx testing into routine practice could hinder successful clinical implementation.

DISCUSSION: Prior to the implementation of PGx testing into Australian primary practices, it is essential to acknowledge patient perspectives and ensure that clinical practices remain patient-focused. This study highlights important considerations for integrating PGx testing into antidepressant pharmacotherapy and emphasizes the need for future research to address and mitigate the perceived barriers of young adults.

PMID:39830342 | PMC:PMC11739104 | DOI:10.3389/fphar.2024.1526101