Background: The pharmacogenetic testing based on next generation sequencing (NGS) allows better coverage of pharmacogenetic (PGx) alleles present in diverse populations and provides opportunities to reanalyze the data when new PGx relevant genes/variants are discovered.

Aims: To create an end-to-end bioinformatics solution to support NGS data analysis and clinical decisions aligned with Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines.

Methods: The CPIC database was integrated with Pgxtools, our pharmacogenetic data analysis and reporting pipeline developed in-house via the Representational State Transfer Abstract Programming Interface (RESTful APIs). It expanded the coverage to 131 genes and 322 drugs with comprehensive variant annotations. The accuracy of variant calls, PGx diplotyping, and clinical interpretation was verified by both long and short read datasets.

Results: A graphical user interface (GUI) was designed for simplicity, secure user management, and access control over input data and output reports. Users can choose three categories for analysis and reporting: “Actionable” (25 genes well characterized by CPIC guidelines), “Twist PGx” (50 genes included in Twist PGx panel) and “All CPIC” (131 genes in CPIC database). The pipeline can accommodate both BAM and VCF data files. Preliminary results of variant calls and genotypes on 15 genes from 12 reference genomes showed very high concordance between PacBio HiFi long read sequencing datasets, corresponding Whole Genome Sequences (WGS) on GRCh38 in the 1000 Genomes Project (G1K), and previously reported PGx star allele assignment.

Conclusions: This bioinformatics pipeline, Pgxtools, provides a comprehensive computational solution to support NGS data analysis and PGx clinical decisions.

Objective: To explore the health and economic value of detecting SNP to guide olanzapine treatment in schizophrenia, and provide a basis for rational clinical use of olanzapine.

Method: 1000 patients with schizophrenia were retrospectively collected, and the distribution of SNP was analyzed. Divide into individualized treatment group and conventional treatment group based on whether CYP1A2 rs762551 SNP testing was performed, and analyze the treatment effects and adverse reactions of the two groups. Furthermore, two health economics models were established to evaluate the economic costs of different treatment options for olanzapine.

Result: Both groups showed a significant decrease in PANSS scores before and after treatment with olanzapine, but there was no significant difference in PANSS scores between the two groups. The incidence of various adverse reactions and total rate in the individualized treatment group was lower than those in the conventional treatment group. Hypothesis test results of Model 1: The individualized treatment cost and related adverse reaction treatment cost of olanzapine guided by SNP testing are lower than the conventional treatment plan of olanzapine without SNP testing; Model 2 analysis showed that the treatment cost and related adverse reaction treatment cost of the conventional olanzapine treatment group were higher than the individualized olanzapine treatment group.

Conclusion: In the clinical use of olanzapine for the treatment of schizophrenia, detecting CYP1A2 rs762551 SNP is of health and economic significance for the rational development of olanzapine treatment plans, reducing the incidence of adverse reactions, and promoting clinical rational drug use.

Background: The PGx-CardioDrug study investigates the impact of drug-drug-gene interactions on cardiovascular drug adverse reactions (ADRs).

Aim: To assess the influence of pharmacogenomics and drug-drug interactions (DDIs) on ADR risk in patients prescribed direct oral anticoagulants (DOACs), platelet aggregation inhibitors (PAIs), and statins over a four-years period.

Methods: Patients newly prescribed DOACs, PAIs, or statins were enrolled. Cases experienced ADRs (haemorrhage, myotoxicity, hepatotoxicity, or other severe reactions) within three months; controls had no ADRs. Relevant ADME gene variants (CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, CYP2J2, CES1, ABCB1, ABCG2, SLCO1B1) were genotyped. DDIs were assessed using Lexicomp®.

Results: Among 1,586 analysed patients (980 statin, 710 DOAC, 296 PAI users), 312 ADRs were recorded: myotoxicity (n=159, 16%), hepatotoxicity (n=57, 6%), bleeding (n=126, 13%). High-risk DDIs were identified in 380/980 statins, 580/710 DOACs, and 205/296 PAIs users. Patients were genotyped for relevant ADME genes: CYP2C9 (38%), CYP2C19 (52%), CYP3A4 (76%), CYP3A5 (68%), CYP2D6 (8%), CYP2J2 (36%), CES1 (6%), ABCB1 (45%), ABCG2 (67%), and SLCO1B1 (47%). So far, the study has resulted in five publications on pharmacogenomics in cardiovascular therapy and has contributed to three master’s and two PhD theses.

Conclusion: Interim findings suggest that drug-drug-gene interactions play a significant role in ADRs risk, highlighting the potential of pharmacogenomics for therapy individualization. However, further research is essential to refine predictive models and enhance clinical implementation.

Background: Brivaracetam is an antiepileptic drug metabolized primarily through hydrolysis, with minor pathways involving CYP2C19 and CYP2C9, and their genetic variability may influence brivaracetam pharmacokinetic.

Aims: To investigate the association between CYP2C9 and CYP2C19 genotypes/phenotypes and brivaracetam serum concentrations in a real-life clinical setting.

Methods: This retrospective study analysed data from epilepsy patients treated with brivaracetam. Patients were genotyped for CYP2C9*2, CYP2C9*3, CYP2C19*2, CYP2C19*17 using TaqMan Real-Time PCR, their serum steady-state trough brivaracetam concentrations were measured by HPLC-DAD, all methods validated in clinical laboratory. Brivaracetam concentrations, dose-adjusted concentration (D/C) ratios, clinical data, drug interactions, and genotype/phenotype data were analysed in univariate statistical analysis.

Results: We analysed data from 50 patients (29 males, 21 females) aged 6-76 years (mean=31), receiving brivaracetam doses 50-200 mg/day, brivaracetam concentrations ranged 0-21.6 µmol/L. CYP2C19 poor metabolizers (*2/*2, n=2) exhibited 55% higher D/C ratios compared to normal metabolizers (*1/*1, n=20; p=0.02), while intermediate metabolizers (*1/*2/*17, n=11) showed 20% higher exposure (p=0.04), ultra-rapid metabolizers (*17/*17, n=3) had subtherapeutic concentrations (median: 2.8 µmol/L at 200 mg; p=0.03).
CYP2C9 heterozygous carriers (*1/*2, *1/*3, n=18) demonstrated 22% higher D/C ratios compared to wild-type (*1/*1, n=32; p=0.12), reaching significance in patients on CYP2C9 inhibitors (valproate) (Δ=38%, p=0.01). Enzyme inducers (carbamazepine, phenobarbital) reduced brivaracetam concentrations by 40–60% in normal metabolizers (p<0.01).

Conclusions: This small real-life study showed that genetic variations in CYP2C19, and less in CYP2C9, influence brivaracetam concentrations, and their interaction with inducers/inhibitors necessitates vigilance. These findings warrant further investigation in larger cohorts.

Keywords: brivaracetam, pharmacogenetics, CYP2C9, CYP2C19, therapeutic drug monitoring

Background: miRNAs are small non-coding RNAs that regulate gene expression and are implicated in drug resistance and toxicity in cancers such as colorectal cancer (CRC). miR-145, miR-106a, and miR-17-3p show significant differential expression between pre- and post-operative stage II/III CRC patients. High levels of miR-17-3p and miR-106a correlate with shorter disease-free survival, suggesting their potential as biomarkers for prognosis and recurrence. Additionally, miR-27a and miR-27b may regulate dihydropyrimidine dehydrogenase (DPD), an enzyme involved in 5-fluorouracil (5-FU) metabolism, with miR-27a rs895819 potentially predicting fluoropyrimidine toxicity.

Aims: This study aimed to evaluate miRNA expression profiles in colorectal cancer patients carrying DPYD variants (DPYD 85T>C and DPYD 1896T>C) who are treated with 5-FU.

Methods: EDTA blood samples were collected from 16 CRC patients for DNA extraction. TaqMan® RT-PCR detected three DPYD gene SNPs: 85T>C, 1627 A>G, and 1896T>C. For miRNA extraction, 100 µL of plasma was used, and cDNA was synthesized from 200 ng RNA. miRNA profiles associated with the 5-FU pathway were analyzed using a customized miRNA array, real-time PCR, and QIAGEN's GeneGlobe portal.

Results: Differential miRNA expression was observed between DPYD 85T>C variants and wild-type patients, with 9 up-regulated and 11 down-regulated miRNAs. A similar expression pattern was noted in DPYD 1896T>C variants, with 5 up-regulated and 9 down-regulated miRNAs.

Conclusions: The findings suggest that miRNAs could serve as biomarkers for predicting 5-FU toxicity, facilitating personalized treatment strategies for CRC patients.

Keywords: miRNA, DPYD polymorphisms, 5-FU, colorectal cancer, toxicity.

Background: Mavacamten is currently used as early access drug in obstructive hypertrophic cardiomyopathy and its exposure is affected by CYP2C19 polymorphisms. Genotyping of CYP2C19 is then recommended before treatment initiation.
Aims: The objective of this study was to describe CYP2C19 genetic polymorphisms and evaluate their impact on clinical outcomes.
Methods: A retrospective study was performed during 2024 in the Cardiology Unit of Timone hospital (Marseille, France). CYP2C19*2, *3 and *17 alleles were determined using LAMP assays. Patients were categorized as poor, intermediate (IM), extensive (EM), rapid (RM) or ultra-rapid (UM) metabolizers. Impact of CYP2C19 metabolic profiles on clinical outcomes at the end of the titration period were studied (Kruskal-Wallis/Dunn tests).
Results: Allelic frequencies of 40% and 14% were described for CYP2C19*17 and CYP2C19*2, respectively (n=101 patients). Titration period was achieved in 56 patients (33/23 females/males), with a median age of 66 years (20-88). We identified 14(25%) IM, 13(23%) RM, 1(2%) UM and 28(50%) EM patients (initial dose of 5mg/d). Titration period delay, dose at the end of titration and Left Ventricular Ejection Fraction were not different between metabolic profiles. Good response to therapy (residual Left Ventricular Outflow Tract gradient < 30mmHg) was achieved in 52 of 56 patients. A significant difference of residual LVOT obstruction after titration was observed between RM and IM (residual gradient= 19.2 vs 11.6mmHg; p=0.029).
Conclusion: Although regression of LV obstruction was achieved in most patients, our results suggest that CYP2C19 genotyping profile may impact the degree of response to mavacamten.
Keywords: pharmacogenetics, CYP2C19, mavacamten, HOCM

Background: The TLR4 rs11536889 polymorphism may influence tuberculosis (TB) susceptibility. This study evaluates the association between TLR4 rs11536889 and TB risk in Thai patients to clarify genetic contributions to TB susceptibility.

Aims: To assess the genotypic distribution of the TLR4 rs11536889 polymorphism and its influence on TB susceptibility in a healthy Thai population.

Methods: This case-control study included 38 Thai TB patients and 51 healthy controls. Following ethical approval and informed consent, 3 mL of whole blood was collected in EDTA tubes, and genomic DNA was extracted using the PureLink™ Genomic DNA Mini Kit. Genotyping was performed using TaqMan® SNP assays on the QuantStudio™ 3 Real-Time PCR System. Logistic regression analysis compared genotypic frequencies between groups, adjusting for age, sex, and BMI (p < 0.05).

Results: In the TB group, genotype frequencies were 37% Homozygous G/G, 53% Heterozygous C/G, and 10% Homozygous C/C, while the control group showed 39% G/G, 43% C/G, and 18% C/C. Allele frequencies were 63% G and 37% C in the TB group, compared to 61% G and 39% C in the control group. There were no significant differences in the C/C genotype compared to the wild-type G/G (p = 0.548), suggesting no association between the TLR4 rs11536889 polymorphism and TB susceptibility.

Conclusions: The TLR4 rs11536889 polymorphism may not significantly influence TB susceptibility in the Thai population. Further research with larger sample size is needed to validate these findings and draw more definitive conclusions.