Acta Biochim Biophys Sin (Shanghai). 2025 Apr 28. doi: 10.3724/abbs.2025013. Online ahead of print.

ABSTRACT

Platinum-based chemotherapy remains the mainstay for non-small cell lung cancer (NSCLC), but it frequently causes dose-limiting myelosuppression, with significant individual variability in susceptibility. However, the genetic basis of myelosuppression side effects remains elusive, greatly hindering personalized therapeutic approaches. In this study, we perform a comprehensive genome-wide association analysis on 491 NSCLC patients receiving platinum-based chemotherapy, examining 4,690,998 single-nucleotide polymorphisms (SNPs) to identify relevant genetic variants. LDBlockShow, FUMA, and MAGMA are utilized to explore linkage disequilibrium, expression quantitative trait loci (eQTLs), chromatin interaction, and conduct gene-based and gene set-based analysis of candidate SNPs. The GWAS results reveal that rs6856089 and its linked SNPs are significantly associated with platinum-based chemotherapy-induced myelosuppression. Specifically, patients with the A allele of rs6856089 have a significantly lower risk of myelosuppression (odds ratio (OR) = 0.1300, P = 7.59 × 10 -8). Furthermore, gene-based analysis reveals that EMCN ( P = 2.47 × 10 -5), which encodes endomucin, a marker for hematopoietic stem cells, might mediate myelosuppression. This study provides a scientific basis for the individual differences in platinum-based chemotherapy-induced myelosuppression.

PMID:40296719 | DOI:10.3724/abbs.2025013

BMC Cardiovasc Disord. 2025 Apr 28;25(1):330. doi: 10.1186/s12872-025-04768-8.

ABSTRACT

BACKGROUND: Genetic variations in the CYP2C19 gene, which encodes the major enzyme responsible for activating clopidogrel, may influence response to Clopidogrel antiplatelet therapy. This study aimed to assess the prevalence of CYP2C19 variants in Syrian patients with coronary artery disease (CAD) and evaluate the impact of these variants on the clinical efficacy of a doubled maintenance dose of clopidogrel following percutaneous coronary intervention (PCI).

METHODS: This study included 50 Syrian CAD patients on dual antiplatelet therapy (DAPT) with a doubled maintenance dose of clopidogrel. CYP2C19 genotypes were determined by PCR, followed by Sanger sequencing. Clinical outcomes, including major acute cardiovascular events (MACE) and bleeding events, were monitored over 18-24 months.

RESULTS: The allele frequencies were 8% for CYP2C19*2, 0% for CYP2C19*3, and 17% for CYP2C19*17. The distribution of our study population by CYP2C19 genotype-predicted metabolizer phenotypes was 56% for normal metabolizers (NMs), 26% for intermediate metabolizers (IMs), 12% for rapid metabolizers (RMs), and 2% for ultra-rapid metabolizers (UMs). No association was found between the CYP2C19*2 allele and recurrent ischemic events or between the CYP2C19*17 allele and bleeding complications in patients treated with a doubled maintenance dose of clopidogrel.

CONCLUSIONS: In Syrian patients undergoing PCI, a doubled maintenance dose of clopidogrel (150 mg/day) may help mitigate variability in response due to CYP2C19*2 carrier status, offering potential benefits in optimizing antiplatelet therapy. However, given the study's limited sample size, these findings should be interpreted with caution, and larger studies are needed to confirm this potential benefit.

PMID:40295977 | DOI:10.1186/s12872-025-04768-8

Sci Rep. 2025 Apr 28;15(1):14906. doi: 10.1038/s41598-025-96457-x.

ABSTRACT

Metastasis is one of the leading causes of cancer-related death worldwide. Fascin, a protein that bundles actin filaments to produce protrusions in cancer cells, plays a significant role in the enhancement of cell migration. This protein has been shown that the overexpression of this protein is related to the appearance of different types of cancer, such as colorectal cancer. In this study, we conducted in silico screening of the Enamine library, a compound library with a broad chemical space. Using a ligand-based virtual screening approach based on the pharmacophore model of G2, we identified the predicted inhibitors. First, these compounds were validated by physicochemical analysis. Differential scanning calorimetry (DSF) was used to study the binding between the predicted compounds and fascin protein, followed by an F-actin bundling assay to determine which compounds inhibited the bundling function of fascin. Z1362873773, which exhibited binding to fascin and inhibited F-actin bundling, was further tested in cell cultures to assess its effects on cancer cell viability and migration as well as in organoid models to evaluate potential cytotoxicity. Finally, we established a protocol that can be applied to discover anti-fascin agents from diverse compound libraries. A new molecule has been identified with considerable fascin inhibitory and migration-arresting capacity, which may lead to the development of new therapies to treat cancer.

PMID:40295602 | DOI:10.1038/s41598-025-96457-x

Medicine (Baltimore). 2025 Apr 25;104(17):e42240. doi: 10.1097/MD.0000000000042240.

ABSTRACT

Pharmacogenomics, the study of genetic influences on drug response, advances personalized medicine by tailoring therapy to individual genetic profiles, reducing adverse effects and optimizing efficacy. Pharmacists, as accessible healthcare providers, are well-positioned to facilitate the integration of pharmacogenomics into clinical practice. This study assesses Saudi pharmacists' knowledge, attitudes, and practices regarding pharmacogenomics and identifies key barriers and facilitators affecting their readiness. A cross-sectional survey was conducted between July and October 2024 among 426 licensed pharmacists across various practice settings in Saudi Arabia: a validated, structured questionnaire assessed demographics, pharmacogenomics knowledge, attitudes, and implementation practices. Snowball sampling facilitated participant recruitment. Descriptive statistics summarized the findings, and Chi-square tests were applied to examine associations between socio-demographic variables and pharmacogenomics-related responses. Among 426 participants, while most pharmacists recognized the value of pharmacogenomics, knowledge gaps were notable, particularly in interpreting genetic tests and applying clinical recommendations. Only 52.3% received pharmacogenomics training, mainly through university courses, and 40.6% had never consulted pharmacogenomics resources in practice. Key barriers included limited access to genetic testing (74.2%) and lack of reimbursement (64.5%). Socio-demographics, such as age and practice setting, significantly impacted knowledge and attitudes. Saudi pharmacists face considerable barriers to pharmacogenomics readiness, including knowledge gaps, limited access to genetic testing, and insufficient institutional support. Addressing these challenges requires targeted education, structured policy initiatives, and enhanced resource availability to facilitate the effective integration of pharmacogenomics into pharmacy practice. Strengthening pharmacists' competencies in this field will be essential to optimizing patient care and advancing precision medicine in Saudi Arabia.

PMID:40295244 | DOI:10.1097/MD.0000000000042240

Infect Dis Now. 2025 Apr 26:105076. doi: 10.1016/j.idnow.2025.105076. Online ahead of print.

ABSTRACT

INTRODUCTION: The recommended gentamicin peak plasma concentration range is 32-40 mg/L; we aimed to determine how frequently it was reached, and for which gentamicin doses.

PATIENTS AND METHODS: We retrospectively reviewed 601 gentamicin peak plasma concentrations in 501 patients aged ≥15 in our institution between 2013 and 2023.

RESULTS: Median gentamicin dose was 5.9 mg/kg [IQR 4.1-7.9]. Median peak plasma concentration was 16.5 mg/L [IQR 10.8-22.8] and was strongly correlated with dose (p < 0.0001). Only 5.7 % of values were ≥32 mg/L, including 22.8 % for dose ≥10 mg/kg.

CONCLUSION: This suggests that existing recommendations regarding either dose or target concentration for gentamicin should be modified.

PMID:40294703 | DOI:10.1016/j.idnow.2025.105076

Annu Rev Genomics Hum Genet. 2025 Apr 28. doi: 10.1146/annurev-genom-111522-013953. Online ahead of print.

ABSTRACT

Breast cancer is a major public health burden that disproportionately affects women of African descent. Substantial progress has been made in understanding the genetic and biological drivers of breast cancer worldwide. However, this knowledge is unevenly distributed among all women with breast cancer, particularly those of African descent. The highlights of nearly three decades of research among women of African descent point mainly to a young age at diagnosis, aggressive disease, and distinct biomarkers, as well as a clear geographical distribution of disease subtypes and genetic variants. Despite this growing wealth of information, the African population's access to genetic care and understanding of inherited risk and disease biology remain limited. This review summarizes the state of knowledge on genetic risk in African populations with breast cancer, evaluates the strengths and limitations of the methodological approaches used, and suggests innovative strategies to ensure equitable participation in cancer genetic and genomic research. We discuss genotype-phenotype correlations and the inherited risk of breast cancer, including both rare and common genetic variants. We also address the role of somatic drivers of breast cancer, disease biomarkers, treatment targets, and pharmacogenomics in this population. Finally, we provide recommendations to enable future progress in diagnosis and treatment.

PMID:40294412 | DOI:10.1146/annurev-genom-111522-013953

Mol Neurobiol. 2025 Apr 28. doi: 10.1007/s12035-025-04957-8. Online ahead of print.

ABSTRACT

L-3,4-Dihydroxyphenylalanine (L-DOPA) is effective at alleviating motor impairments in Parkinson's disease (PD) patients but has mixed effects on nonmotor symptoms and causes adverse effects after prolonged treatment. Here, we analyzed the spatial profile of L-DOPA-induced gene expression in the forebrain of mice with an inducible progressive loss of dopaminergic neurons (the TIF-IADATCreERT2 strain), with a focus on the similarities and differences in areas relevant to different PD symptoms. The animals received a 14-day L-DOPA treatment, and 1 h after the final drug injection, a spatial transcriptome analysis was performed on coronal forebrain sections. A total of 121 genes were identified as being regulated by L-DOPA. We found that the treatment had widespread effects extending beyond the primary areas involved in dopamine-dependent movement control. An unsupervised clustering analysis of the transcripts recapitulated the forebrain anatomy and indicated both ubiquitous and region-specific effects on transcription. The changes were most pronounced in layers 2/3 and 5 of the dorsal cortex and the dorsal striatum, where a robust increase in the abundance of activity-regulated transcripts, including Fos, Egr1, and Junb, was observed. Conversely, transcripts with a decreased abundance, e.g., Plekhm2 or Pgs1, were identified primarily in the piriform cortex, the adjacent endopiriform nucleus, and the claustrum. Taken together, our spatial analysis of L-DOPA-induced alterations in gene expression reveals the anatomical complexity of treatment effects, identifying novel genes affected by the drug, as well as molecular activation in brain areas relevant to the nonmotor symptoms of PD.

PMID:40293707 | DOI:10.1007/s12035-025-04957-8

Front Pharmacol. 2025 Apr 1;16:1519383. doi: 10.3389/fphar.2025.1519383. eCollection 2025.

ABSTRACT

BACKGROUND: Aspirin is a cornerstone medication for acute ischemic stroke (AIS), but its efficacy varies significantly among individuals. This study aimed to develop a pharmacogenetic polygenic response score (PgxRS) to predict the incidence of adverse outcomes in aspirin-treated AIS patients.

METHODS: We conducted a retrospective study involving 828 AIS patients who received aspirin therapy. Fifteen candidate single nucleotide variants (SNPs) in genes related to aspirin's mechanism of action, transport, metabolism, and platelet function were genotyped. The association between SNPs and the risk of unfavorable prognosis (defined as modified Rankin Scale score >1 at 90 days) was assessed using logistic regression analysis. Multivariable models incorporating SNPs and clinical factors were developed to predict adverse outcomes.

RESULTS: The rs1045642GG genotype in the ABCB1 gene was significantly associated with a lower risk of unfavorable prognosis, while the rs1371097T allele in the P2Y1 gene was linked to a higher risk. A prediction model incorporating these two SNPs along with clinical variables demonstrated moderate diagnostic accuracy for predicting unfavorable prognosis (AUC = 0.78, 95% CI: 0.74-0.81).

CONCLUSION: Our findings suggest that rs1045642 and rs1371097 genotypes contribute to variability in aspirin response among AIS patients. The developed PgxRS, incorporating these SNPs and clinical factors, can potentially aid in risk stratification and guide personalized antiplatelet therapy decisions. However, further validation in larger, diverse cohorts is warranted.

PMID:40290439 | PMC:PMC12023276 | DOI:10.3389/fphar.2025.1519383

Front Pharmacol. 2025 Apr 11;16:1548991. doi: 10.3389/fphar.2025.1548991. eCollection 2025.

ABSTRACT

The sequencing of the human genome in 2003 marked a transformative shift from a one-size-fits-all approach to personalized medicine, emphasizing patient-specific molecular and physiological characteristics. Advances in sequencing technologies, from Sanger methods to Next-Generation Sequencing (NGS), have generated vast genomic datasets, enabling the development of tailored therapeutic strategies. Pharmacogenomics (PGx) has played a pivotal role in elucidating how the genetic make-up influences inter-individual variability in drug efficacy and toxicity discovering predictive and prognostic biomarkers. However, challenges persist in interpreting polymorphic variants and translating findings into clinical practice. Multi-omics data integration and bioinformatics tools are essential for addressing these complexities, uncovering novel molecular insights, and advancing precision medicine. In this review, starting from our experience in PGx studies performed by DMET microarray platform, we propose a guideline combining machine learning, statistical, and network-based approaches to simplify and better understand complex DMET PGx data analysis which can be adapted for broader PGx applications, fostering accessibility to high-performance bioinformatics, also for non-specialists. Moreover, we describe an example of how bioinformatic tools can be used for a comprehensive integrative analysis which could allow the translation of genetic insights into personalized therapeutic strategies.

PMID:40290426 | PMC:PMC12022492 | DOI:10.3389/fphar.2025.1548991

Br J Clin Pharmacol. 2025 Apr 27. doi: 10.1002/bcp.70057. Online ahead of print.

ABSTRACT

AIMS: Pharmacogenomics enables personalization of drug therapy improving effectiveness and/or safety. Dihydropyrimidine dehydrogenase [DPYD] testing prior to fluoropyrimidine chemotherapy was commissioned by NHS England in response to an update from the Medicines and Healthcare products Regulatory Agency.

METHODS: A questionnaire developed and approved by the National DPYD Working Group investigated processes of testing, receiving and responding to results. The survey was distributed to Genomics Medicine Service Alliance (GMSA) Clinical Directors and Pharmacy Senior Responsible Officers for dissemination in their geography. Data were collected June-September 2021. All hospitals delivering fluoropyrimidines across the UK were invited to participate.

RESULTS: 131/138 (94.9%) organizations reported testing all patients receiving fluoropyrimidines. In England 76.7% of hospitals sent samples to centrally commissioned genomics laboratories. In the devolved nations, 73.9% sent samples to regional genomics laboratories. Multidisciplinary staff including oncologists, independent non-medical prescribers, clinical nurse specialists, screening pharmacists and chemotherapy nurses requested the test, checked and actioned the result. Self-reported turnaround times varied from <2 days where a regional laboratory was colocated with a chemotherapy centre to >10 days.

CONCLUSION: Through multiprofessional, national collaboration, this is the first report studying the large-scale rollout of a nationally commissioned pharmacogenetic test. Whilst DPYD testing has been successfully implemented, there is a need to standardize and improve end-to-end turnaround times. This has led to the development of a best practice pathway. Critically, GMSAs must build on this implementation to deliver its priorities, in supporting equitable access to future pharmacogenomic testing across a wider cohort of therapies.

PMID:40289265 | DOI:10.1002/bcp.70057

Clin Pharmacokinet. 2025 Apr 26. doi: 10.1007/s40262-025-01502-7. Online ahead of print.

ABSTRACT

BACKGROUND AND OBJECTIVE: Metoprolol is primarily metabolized via the polymorphic cytochrome P450-2D6 (CYP2D6) enzyme, which underlies interindividual variation in conversion rates and may benefit from pharmacogenetics-driven therapy personalization. However, the field relies heavily on knowledge of a drug's metabolism, often originating from early-phase clinical trials with single-dose administration in small samples of healthy volunteers. Pharmacogenetics could thus benefit from real-world drug metabolism studies.

METHODS: We conducted a real-world drug metabolism study for metoprolol in 18 (potential) living kidney donors and 374 kidney transplant recipients from the Transplant Lines Food and Nutrition Biobank and Cohort Study (NCT02811835) using existing liquid chromatography-high resolution mass spectrometry pharmacometabolomic data.

RESULTS: In both groups, we confirmed the presence of seven expected metabolites, including the high-abundance substances metoprolol acid and hydroxymetoprolol. We were unable to detect deisopropylmetoprolol and a metabolite known as "H 119/68". However, we did find putative further oxidized forms, namely the expected variant of deisopropylmetoprolol in which the primary amine is removed and the leftover methyl group is oxidized into a carboxylic acid ("H 104/83") and an unknown/unreported metoprolol metabolite that we refer to as "metoprolol benzoic acid". Moreover, we found nine other previously unknown/unreported metabolites, putatively reflecting N-glucuronidated metoprolol, four glucuronidated versions of hydroxymetoprolol, and a formylated, a glucuronidated, and two hydroxylated versions of metoprolol acid. Interestingly, the same metabolites were detected in potential living kidney donors and kidney transplant recipients, and metabolite profiles did not differ between both groups in principal component analysis.

CONCLUSION: We found more metoprolol metabolites than previously reported, calling for replication studies and evaluation of pharmacogenetic testing approaches to realize safer, more effective metoprolol therapy.

PMID:40285825 | DOI:10.1007/s40262-025-01502-7

Drug Dev Res. 2025 May;86(3):e70093. doi: 10.1002/ddr.70093.

ABSTRACT

Recent advances in pharmacology are revolutionizing drug discovery and treatment strategies through personalized medicine, pharmacogenomics, and artificial intelligence (AI). The objective of the present study is to review the role of personalized medicine, pharmacogenomics, and AI-based strategies in optimizing patient outcomes with improved drug efficacy and reduced side effects. A comprehensive review was performed to debate the utility of pharmacogenomics in the prediction of drug response, the role of AI in drug discovery, and the utility of personalized medicine in the clinic. This review highlights how drug discovery and treatment techniques are evolving with the aid of personalized medicine, pharmacogenomics, and AI. Personalized medicine makes the treatment fit the DNA pattern for higher efficacy and minimal side effects. Pharmacogenomics forecasts the action of a drug in terms of genetic difference. AI speeds up drug discovery to enhance the effectiveness and accuracy of finding and evaluating drug leads. Studies show that customized medicine charts therapy to an individual patient's individual genetic profile, resulting in better therapy. Pharmacogenomics facilitates precise drug selection by considering genetic variations, reducing adverse reactions. AI speeds up drug discovery by applying predictive modeling and data-driven evaluation to propel optimized drug development pathways. Together, these advances are enabling more efficient and safer treatment practices across medical disciplines. The combination of pharmacology, genomics, and AI is revolutionizing contemporary healthcare through the personalization of treatments, improved drug safety, and therapeutic outcomes. The future of research should be on optimizing these techniques and overcoming ethical and regulatory issues to facilitate broader clinical implementation.

PMID:40285487 | DOI:10.1002/ddr.70093

Clin Transl Sci. 2025 May;18(5):e70239. doi: 10.1111/cts.70239.

ABSTRACT

Previous pharmacogenetic findings for beta-blocker pharmacodynamic candidate genes (ADRB1, ADRB2, ADRA2C, GRK4, and GRK5) have been inconsistent. Therefore, the purpose of this study was to determine whether interactions of pharmacodynamic variants with beta-blocker exposure significantly associated with survival in patients with heart failure with reduced ejection (HFrEF). The 893 patients were 51% self-reported African American and 49% self-reported White race, 36% female, and 240 died (27%) over a median follow-up of 2.8 years. The primary outcome was all-cause mortality. Using Cox proportional hazards models with time-varying beta-blocker exposure and adjusted for clinical risk factors and ancestry, interactions of ADRB1 Arg389Gly, ADRB1 Ser49-Arg389Gly haplotype, ADRA2C Del322-325, and GRK4 Ala486Val with beta-blocker exposure were significant before correction for multiple comparisons (p < 0.1), but only GRK4 Ala486Val remained significant in African Americans after correction for multiple comparisons using the adaptive Hochberg method (p = 0.022). Beta-blocker exposure only associated with a significant reduction in the risk of mortality in the African American HFrEF patients with the GRK4 Ala486/Ala486 genotype (HR = 0.44; 95% CI = 0.20-0.96; p = 0.04). In conclusion, the interaction of GRK4 Ala486Val with beta-blocker exposure significantly associated with survival in African American HFrEF patients. Larger sample sizes or meta-analyses are needed to have more statistical power to better assess beta-blocker pharmacogenetic interactions for ADRB1 Arg389Gly, ADRB1 Ser49-Arg389Gly haplotype, and ADRA2C Del322-325 in the future.

PMID:40285373 | DOI:10.1111/cts.70239

Brief Bioinform. 2025 Mar 4;26(2):bbaf195. doi: 10.1093/bib/bbaf195.

ABSTRACT

The rapidly emerging large-scale data in diverse biological research fields present valuable opportunities to explore the underlying mechanisms of tissue development and disease progression. However, few existing methods can simultaneously capture common and condition-specific association between different types of features across different biological conditions, such as cancer types or cell populations. Therefore, we developed the sparse tensor-based partial least squares (sTPLS) method, which integrates multiple pairs of datasets containing two types of features but derived from different biological conditions. We demonstrated the effectiveness and versatility of sTPLS through simulation study and three biological applications. By integrating the pairwise pharmacogenomic data, sTPLS identified 11 gene-drug comodules with high biological functional relevance specific for seven cancer types and two comodules that shared across multi-type cancers, such as breast, ovarian, and colorectal cancers. When applied to single-cell data, it uncovered nine gene-peak comodules representing transcriptional regulatory relationships specific for five cell types and three comodules shared across similar cell types, such as intermediate and naïve B cells. Furthermore, sTPLS can be directly applied to tensor-structured data, successfully revealing shared and distinct cell communication patterns mediated by the MK signaling pathway in coronavirus disease 2019 patients and healthy controls. These results highlight the effectiveness of sTPLS in identifying biologically meaningful relationships across diverse conditions, making it useful for multi-omics integrative analysis.

PMID:40285361 | DOI:10.1093/bib/bbaf195

Pharmaceuticals (Basel). 2025 Apr 7;18(4):539. doi: 10.3390/ph18040539.

ABSTRACT

Background: Studying single-nucleotide polymorphisms (SNPs) in xenobiotic-transporting and metabolizing enzyme genes before administering the doxorubicin hydrochloride and cyclophosphamide (AC) regimen may help optimize breast cancer (BC) treatment for individual patients. Objective: Genotyping specific SNPs on genes encoding for the transport and metabolism of the AC regimen and study their association with its chemotherapeutic toxicity. Method: This prospective cohort study was conducted in two hospitals in Egypt. Before receiving AC therapy, venous blood was collected from female patients with BC for DNA extraction and the genotyping of four SNPs: rs2228100 in ALDH3A1 gene, rs12248560 in CYP2C19 gene, rs1045642 in ABCB1 gene, and rs6907567 in SLC22A16 gene. Patients were then prospectively monitored for hematological, gastrointestinal, and miscellaneous toxicities throughout the treatment cycles. Results: The ALDH3A1 gene polymorphism demonstrated a significant increase in nausea, stomachache, and peripheral neuropathy among patients carrying the GC+CC genotype, compared to those with the GG genotype (p = 0.023, 0.036, and 0.008, respectively). Conversely, patients with the GG genotype exhibited significantly higher fever grades after cycles 1, 2, and 3 of the AC regimen compared to those with the GC+CC genotype (p = 0.009, 0.017, and 0.018, respectively). Additionally, fatigue severity was significantly increased among patients with the GG genotype compared to those with the GC+CC genotype following AC administration (p = 0.008). Conclusions: The SNP variation of ALDH3A1 (rs2228100) gene significantly influenced AC regimen toxicity in female BC patients. Meanwhile, SNPs in CYP2C19 (rs12248560), ABCB1 (rs1045642), and SLC22A16 (rs6907567) genes showed a significant influence on the recurrence rate of certain toxicities.

PMID:40283974 | DOI:10.3390/ph18040539

Pharmaceuticals (Basel). 2025 Apr 1;18(4):515. doi: 10.3390/ph18040515.

ABSTRACT

Background/Objectives: Fluoropyrimidine derivatives, 5-fluorouracil (5-FU) and its prodrugs (capecitabine and tegafur), are widely used in patients suffering from colorectal cancer. The enzyme responsible for their metabolization, dihydropyrimidine dehydrogenase (DPD), is encoded by the DPYD gene, which is highly polymorphic and may contain polymorphisms which could severely compromise its function. This article aims to describe the prevalence of the four main DPYD polymorphisms in the Galician population (Spain) and to compare these frequencies with data obtained from European cohorts in genetic databases and a Spanish study. Methods: Galician data frequencies for the four main DPYD polymorphisms recommended by the European Medicine Agency (EMA) and the Spanish Agency for Medicines and Health Products (AEMPS) (rs3918290 (c.1905+1G>A), rs55886062 (c.1679T>G), rs56038477 (c.1236G>A) and rs67376798 (c.2846A>T)) were collected, as well as data from the genomic databases 1000 Genomes and gnomAD. Additionally, the results from a Spanish DPYD study were included. Results: Significant differences in DPYD variant allele frequencies were observed in the Galician population compared to the frequencies reported in the European population, as well as in the Spanish PhotoDPYD study. Specifically, the rs56038477-T variant (most prevalent) along with the rs3918290-T variant, exhibited significantly lower frequencies than anticipated in the Galician cohort, with a high degree of statistical significance. Conclusions: Observed allele frequencies for the four DPYD variants suggest that Europeans and Spanish frequencies may not be fully applicable to the Galician population. These results emphasize the emerging need for incorporating the genetic information of populations that might be underrepresented into populational databases available worldwide.

PMID:40283950 | DOI:10.3390/ph18040515

Pharmaceuticals (Basel). 2025 Mar 29;18(4):499. doi: 10.3390/ph18040499.

ABSTRACT

Lysergic acid diethylamide (LSD) is gaining renewed interest as a potential treatment for anxiety, depression, and alcohol use disorder, with clinical trials reporting significant symptom reductions and long-lasting effects. LSD modulates serotonin (5-HT2A) receptors, which, in turn, influence dysfunctional brain networks involved in emotional processing and cognition. It has also shown promise in psychedelic-assisted psychotherapy, where mystical-type experiences are linked to improved psychological well-being. This review examines LSD's pharmacokinetics, neurobiological mechanisms, and safety considerations, including cardiovascular risks, emotional vulnerability, and the potential for hallucinogen-persisting perception disorder (HPPD). Challenges such as small sample sizes, variable dosing protocols, and regulatory restrictions limit large-scale trials. Future research should focus on standardization, pharmacogenetic influences, and personalized treatment strategies to ensure its safe and effective integration into clinical practice.

PMID:40283936 | DOI:10.3390/ph18040499

Genes (Basel). 2025 Apr 15;16(4):453. doi: 10.3390/genes16040453.

ABSTRACT

BACKGROUND/OBJECTIVES: Lung cancer has a high mortality rate worldwide, with non-small cell lung cancer (NSCLC) being the most prevalent. Carboplatin and paclitaxel are key treatments for NSCLC; however, adverse drug reactions (ADRs) pose significant challenges. This study examined the impact of genetic variations in ABCB1 and ABCC2 genes on the incidence of ADRs and survival in NSCLC patients treated with carboplatin and paclitaxel.

METHODS: Variants were identified using RT-PCR, and ADRs classified according to the Common Toxicity Criteria for Adverse Events, Version 4.03.

RESULTS: The ABCB1 rs1128503 (c.1236C>T) CC genotype was associated with a higher chance of nausea (OR: 3.5, 95% CI 1.367-9.250, p = 0.0093), vomiting (OR: 13.553, 95% CI 1.705-107.723, p = 0.0137), and a higher risk of death in CT or TT genotypes (HR: 1.725, 95% CI 1.036-2.871, p = 0.0361). The ABCC2 rs717620 (c.-24C>T) TT genotype was associated with increased ALP levels (OR: 14.6, 95% CI 1.234-174.236, p = 0.0335). The ABCB1 rs2032582 non-CC genotypes (TT+AA+TA+CA+CT) were associated with an increased risk of death (HR: 1.922, 95% CI 1.093-3.377, p = 0.0232). Patients with hypocalcemia (HR: 2.317, 95% IC 1.353-3.967, p = 0.022), vomiting (HR: 3.047, 95% IC 1.548-5.997, p = 0.0013), and diarrhea (HR: 2.974, 95% IC 1.590-5.562, p = 0.0006) were associated with lower overall survival.

CONCLUSIONS: The data suggest that ABCB1 variants may influence gastrointestinal ADRs and patient survival, highlighting the importance of pharmacogenomics in predicting ADRs and drug resistance. This approach offers more precise pharmacotherapy, reduces ADRs, and enhances the patients' quality of life and survival.

PMID:40282412 | DOI:10.3390/genes16040453

Genes (Basel). 2025 Mar 30;16(4):403. doi: 10.3390/genes16040403.

ABSTRACT

BACKGROUND/OBJECTIVES: This review examines the role of pharmacogenomics in individual responses to the pharmacotherapy of various drugs of abuse, including alcohol, cocaine, and opioids, to identify genetic variants that contribute to variability in substance use disorder treatment outcomes. In addition, it explores the pharmacomicrobiomic aspects of substance use, highlighting the impact of the gut microbiome on bioavailability, drug metabolism, pharmacodynamics, and pharmacokinetics.

RESULTS: Research on pharmacogenetics has identified several promising genetic variants that may contribute to the individual variability in responses to existing pharmacotherapies for substance addiction. However, the interpretation of these findings remains limited. It is estimated that genetic factors may account for 20-95% of the variability in individual drug responses. Therefore, genetic factors alone cannot fully explain the differences in drug responses, and factors such as gut microbiome diversity may also play a significant role. Drug microbial biotransformation is produced by microbial exoenzymes that convert low molecular weight organic compounds into analogous compounds by oxidation, reduction, hydrolysis, condensation, isomerization, unsaturation, or by the introduction of heteroatoms. Despite significant advances in pharmacomicrobiomics, challenges persist including the lack of standardized methodologies, inter-individual variability, limited understanding of drug biotransformation mechanisms, and the need for large-scale validation studies to develop microbiota-based biomarkers for clinical use.

CONCLUSIONS: Progress in the pharmacogenomics of substance use disorders has provided biological insights into the pharmacological needs associated with common genetic variants in drug-metabolizing enzymes. The gut microbiome and its metabolites play a pivotal role in various stages of drug addiction including seeking, reward, and biotransformation. Therefore, integrating pharmacogenomics with pharmacomicrobiomics will form a crucial foundation for significant advances in precision and personalized medicine.

PMID:40282363 | DOI:10.3390/genes16040403

Genes (Basel). 2025 Mar 24;16(4):372. doi: 10.3390/genes16040372.

ABSTRACT

BACKGROUND/OBJECTIVES: The CYP2C9 enzyme is involved in the metabolism of warfarin. The CYP2C9 gene harbors several single-nucleotide polymorphisms (SNPs), including CYP2C9*2 (rs1799853), which is known to affect warfarin's therapeutic response. So, it is important to develop analytical tools capable of genotyping these SNPs to adjust warfarin's therapeutic outcomes. In this work, an electrochemical DNA-based sensor was constructed and optimized for the detection of the CYP2C9*2 polymorphism.

METHODS: Using bioinformatic database platforms, two 71 base pair DNA target probes with the polymorphic variants A and G were chosen and designed. A DNA-based sensor was composed by mercaptohexanol and the CYP2C9*2 DNA capture probe in a self-assembled monolayer connected to screen-printed gold electrodes. Two independent hybridization events of the CYP2C9*2 allele were designed using complementary fluorescein-labeled DNA signaling to improve selectivity and avoid secondary structures. Three human samples with the homozygous variant (G/G) and non-variant (A/A) and heterozygous (G/A) genotypes were amplified by PCR and then applied to the developed genosensor.

RESULTS: Chronoamperometry measurements were performed for both polymorphic probes. A calibration curve in the 0.25 to 2.50 nM (LOD of 13 pM) and another in the 0.15 to 5.00 nM range (LOD of 22.6 pM) were obtained for the homozygous non-variant and variant probes, respectively. This innovative tool was capable of identifying the hybridization reaction between two complementary strands of immobilized DNA, representing a genotyping alternative to the classical PCR methodology.

CONCLUSIONS: The developed electrochemical DNA-based sensor was able to discriminate two synthetic SNP target sequences (Target-A and Target-G) and detect, with specificity, the three patients' genotypes (G/G, G/A, and A/A). This tool is therefore a promising, sensitive, and cost-effective analytical way to determine and discriminate an individual's genotype and predict the appropriate warfarin dose.

PMID:40282332 | DOI:10.3390/genes16040372