UNASSIGNED: Warfarin has become the first choice for anticoagulation in patients who need lifelong anticoagulation due to its clinical efficacy and low price. However, the anticoagulant effect of warfarin is affected by many drugs, foods, etc. accompanied by a high risk of bleeding and embolism. The Vitamin K epoxide reductase complex 1 (VKORC1) and Cytochrome P450 2C9 (CYP2C9) genotypic variation can influence the therapeutic dose of warfarin. However, it is not clear whether there is a correlation between warfarin dose and liver function, kidney function and metabolic markers such as uric acid (UA) in patients with different genotypes. We performed a single-center retrospective cohort study to evaluate the factors affecting warfarin dose and to establish a dose conversion model for warfarin patients undergoing heart valve replacement.
UNASSIGNED: We studied 343 patients with a mechanical heart valve replacement, compared the doses of warfarin in patients with different warfarin-related genotypes (CYP2C9 and VKORC1), and analyzed the correlation between liver function, kidney function, UA and other metabolic markers and warfarin dose in patients with different genotypes following heart valve replacement.
UNASSIGNED: Genotype analysis showed that 72.01% of patients had CYP2C9*1/*1 and VKORC1 mutant AA genotypes. Univariate regression analysis revealed that the warfarin maintenance dose was significantly correlated with gender, age, body surface area (BSA), UA and genotype. There was no correlation with liver or kidney function. Multiple linear regression analysis showed that BSA, genotype and UA were the independent factors influencing warfarin dose.
UNASSIGNED: There is a significant correlation between UA content and warfarin dose in patients with heart valve replacement genotypes CYP2C9*1/*1/VKORC1(GA+GG), CYP2C9*1/*1/VKORC1AA and CYP2C9*1/*1/VKORC1AA.

BACKGROUND: Excessive free radicals are implicated in the pathophysiology of tardive dyskinesia (TD), and Ginkgo biloba extract (EGb761) scavenges free radicals, thereby enhancing antioxidant enzymes such as mitochondrial manganese superoxide dismutase (MnSOD). This study examined whether EGb761 treatment would improve TD symptoms and increase MnSOD activity, particularly in TD patients with specific MnSOD Val-9Ala genotype.
METHODS: An EGb761 (240 mg/day) 12-week double-blind clinical trial with 157 TD patients was randomized. The severity of TD was measured by the Abnormal Involuntary Movement Scale (AIMS) and plasma MnSOD activity was assayed before and after 12 weeks of treatment. Further, in an expanded sample, we compared MnSOD activity in 159 TD, 227 non-TD and 280 healthy controls, as well as the allele frequencies and genotypes for the MnSOD Ala-9Val polymorphism in 352 TD, 486 non-TD and 1150 healthy controls.
RESULTS: EGb761 significantly reduced TD symptoms and increased MnSOD activity in TD patients compared to placebo (both p < 0.01). Moreover, we found an interaction between genotype and treatment response (p < 0.001). Furthermore, in the EGb761 group, patients carrying the Ala allele displayed a significantly lower AIMS total score than patients with the Val/Val genotype. In addition, MnSOD activity was significantly lower at baseline in TD patients compared with healthy controls or non-TD patients.
CONCLUSIONS: EGb761 treatment enhanced low MnSOD activity in TD patients and produced greater improvement in TD symptoms in patients with the Ala allele of the MnSOD Ala-9Val polymorphism.

BACKGROUND: Determination of DPYD and UGT1A1 polymorphisms prior to 5-fluorouracil and irinotecan therapy is crucial for avoiding severe adverse drug effects. Hence, there is a pressing need for accurate and reliable genotyping methods for the most common DPYD and UGT1A1 polymorphisms. In this study, we introduce a novel polymerase chain reaction (PCR) melting curve analysis method for discriminating DPYD c.1236G > A, c.1679 T > G, c.2846A > T, IVS14 + 1G > A and UGT1A1*1, *28, *6 (G71R) genotypes.
METHODS: Following protocol optimization, this technique was employed to genotype 28 patients, recruited between March 2023 and October 2023, at the First Affiliated Hospital of Xiamen University. These patients included 20 with UGT1A1 *1/*1, 8 with UGT1A1 *1/*28, 4 with UGT1A1 *28/*28, 22 with UGT1A1*6 G/G, 6 with UGT1A1*6 G/A, 4 with UGT1A1*6 A/A, 27 with DPYD(c.1236) G/G, 3 with DPYD(c.1236) G/A, 2 with DPYD(c.1236) A/A, 27 with DPYD(c.1679) T/T, 2 with DPYD(c.1679) T/G, 3 with DPYD(c.1679) G/G, 28 with DPYD(c.2846A/T) A/A, 2 with DPYD(c.2846A/T) A/T, 2 with DPYD(c.2846A/T) T/T, 28 with DPYD(c.IVS14 + 1) G/G, 2 with DPYD(c.IVS14 + 1) G/G, and 2 with DPYD(c.IVS14 + 1) G/G, as well as 3 plasmid standards. Method accuracy was assessed by comparing results with those from Sanger sequencing or Multiplex quantitative PCR(qPCR). Intra- and inter-run precision of melting temperatures (Tms) were calculated to evaluate reliability, and sensitivity was assessed through limit of detection examination.
RESULTS: The new method accurately identified all genotypes and exhibited higher accuracy than Multiplex qPCR. Intra- and inter-run coefficients of variation for Tms were both ≤1.97 %, with standard deviations ≤0.95 °C. The limit of detection was 0.09 ng/μL of input genomic DNA.
CONCLUSIONS: Our developed PCR melting curve analysis offers accurate, reliable, rapid, simple, and cost-effective detection of DPYD and UGT1A1 polymorphisms. Its application can be easily extended to clinical laboratories equipped with a fluorescent PCR platform.

OBJECTIVE: Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) is currently used in clinical microbiology laboratories. This study aimed to determine whether dual-polarity time-of-flight mass spectrometry (DP-TOF MS) could be applied to clinical nucleotide detection.
METHODS: This prospective study included 40 healthy individuals and 110 patients diagnosed with cardiovascular diseases. We used DP-TOF MS and Sanger sequencing to evaluate 17 loci across 11 genes associated with cardiovascular drug responses. In addition, we used DP-TOF MS to test 998 retrospectively collected clinical DNA samples with known results.
RESULTS: A, T, and G nucleotide detection by DP-TOF MS and Sanger sequencing revealed 100% concordance, whereas the C nucleotide concordance was 99.86%. Genotyping based on the results of the two methods showed 99.96% concordance. Regarding clinical applications, DP-TOF MS yielded a 99.91% concordance rate for known loci. The minimum detection limit for DNA was 0.4 ng; the inter-assay and intra-assay precision rates were both 100%. Anti-interference analysis showed that aerosol contamination greater than 1013 copies/µL in the laboratory environment could influence the results of DP-TOF MS.
CONCLUSIONS: The DP-TOF MS platform displayed good detection performance, as demonstrated by its 99.96% concordance rate with Sanger sequencing. Thus, it may be applied to clinical nucleotide detection.

Individual may response to drug treatment differently due to their genetic variants located in enhancers. These variants can alter transcription factor\'s (TF) binding strength, affect enhancer\'s chromatin activity or interaction, and eventually change expression level of downstream gene. Here, we propose a computational framework, PERD, to Predict the Enhancers Responsive to Drug. A machine learning model was trained to predict the genome-wide chromatin accessibility from transcriptome data using the paired expression and chromatin accessibility data collected from ENCODE and ROADMAP. Then the model was applied to the perturbed gene expression data from Connectivity Map (CMAP) and Cancer Drug-induced gene expression Signature DataBase (CDS-DB) and identify drug responsive enhancers with significantly altered chromatin accessibility. Furthermore, the drug responsive enhancers were related to the pharmacogenomics genome-wide association studies (PGx GWAS). Stepping on the traditional drug-associated gene signatures, PERD holds the promise to enhance the causality of drug perturbation by providing candidate regulatory element of those drug associated genes.

UNASSIGNED: Adrenocortical carcinoma (ACC) is an aggressive endocrine malignancy with limited therapeutic options. Treating advanced ACC with mitotane, the cornerstone therapy, remains challenging, thus underscoring the significance to predict mitotane response prior to treatment and seek other effective therapeutic strategies.
UNASSIGNED: We aimed to determine the efficacy of mitotane via an in vitro assay using patient-derived ACC cells (PDCs), identify molecular biomarkers associated with mitotane response and preliminarily explore potential agents for ACC.
UNASSIGNED: In vitro mitotane sensitivity testing was performed in 17 PDCs and high-throughput screening against 40 compounds was conducted in 8 PDCs. Genetic features were evaluated in 9 samples using exomic and transcriptomic sequencing.
UNASSIGNED: PDCs exhibited variable sensitivity to mitotane treatment. The median cell viability inhibition rate was 48.4% (IQR: 39.3-59.3%) and -1.2% (IQR: -26.4-22.1%) in responders (n=8) and non-responders (n=9), respectively. Median IC50 and AUC were remarkably lower in responders (IC50: 53.4 µM vs 74.7 µM, P<0.0001; AUC: 158.0 vs 213.5, P<0.0001). Genomic analysis revealed CTNNB1 somatic alterations were only found in responders (3/5) while ZNRF3 alterations only in non-responders (3/4). Transcriptomic profiling found pathways associated with lipid metabolism were upregulated in responder tumors whilst CYP27A1 and ABCA1 expression were positively correlated to in vitro mitotane sensitivity. Furthermore, pharmacologic analysis identified that compounds including disulfiram, niclosamide and bortezomib exhibited efficacy against PDCs.
UNASSIGNED: ACC PDCs could be useful for testing drug response, drug repurposing and guiding personalized therapies. Our results suggested response to mitotane might be associated with the dependency on lipid metabolism. CYP27A1 and ABCA1 expression could be predictive markers for mitotane response, and disulfiram, niclosamide and bortezomib could be potential therapeutics, both warranting further investigation.

In recent years, the FDA has approved numerous anti-cancer drugs that are mutation-based for clinical use. These drugs have improved the precision of treatment and reduced adverse effects and side effects. Personalized therapy is a prominent and hot topic of current medicine and also represents the future direction of development. With the continuous advancements in gene sequencing and high-throughput screening, research and development strategies for personalized clinical drugs have developed rapidly. This review elaborates the recent personalized treatment strategies, which include artificial intelligence, multi-omics analysis, chemical proteomics, and computation-aided drug design. These technologies rely on the molecular classification of diseases, the global signaling network within organisms, and new models for all targets, which significantly support the development of personalized medicine. Meanwhile, we summarize chemical drugs, such as lorlatinib, osimertinib, and other natural products, that deliver personalized therapeutic effects based on genetic mutations. This review also highlights potential challenges in interpreting genetic mutations and combining drugs, while providing new ideas for the development of personalized medicine and pharmacogenomics in cancer study.

BACKGROUND: Diminished bioavailability of imatinib in leukemic cells contributes to poor clinical response. We examined the impact of genetic polymorphisms of imatinib on the pharmacokinetics and clinical response in 190 patients with chronic myeloid leukaemia (CML).
METHODS: Single nucleotide polymorphisms were genotyped using pyrophosphate sequencing. Plasma trough levels of imatinib were measured using liquid chromatography-tandem mass spectrometry.
RESULTS: Patients carrying the TT genotype for ABCB1 (rs1045642, rs2032582, and rs1128503), GG genotype for CYP3A5-rs776746 and AA genotype for ABCG2-rs2231142 polymorphisms showed higher concentration of imatinib. Patients with T allele for ABCB1 (rs1045642, rs2032582, and rs1128503), A allele for ABCG2-rs2231142, and G allele for CYP3A5-rs776746 polymorphisms showed better cytogenetic response and molecular response. In multivariate analysis, carriers of the CYP3A5-rs776746 G allele exhibited higher rates of complete cytogenetic response (CCyR) and major molecular response (MMR). Similarly, patients with the T allele of ABCB1-rs1045642 and rs1128503 demonstrated significantly increased CCyR rates. Patients with the A allele of ABCG2-rs2231142 were associated with higher MMR rates. The AA genotype for CYP3A5-rs776746, and the CC genotype for ABCB1-rs104562, and rs1128503 polymorphisms were associated with a higher risk of imatinib failure. Patients with the G allele for CYP3A5-rs776746 exhibited a higher incidence of anemia, and T allele for ABCB1-rs2032582 demonstrated an increased incidence of diarrhea.
CONCLUSIONS: Genotyping of ABCB1, ABCG2, and CYP3A5 genes may be considered in the management of patients with CML to tailor therapy and optimize clinical outcomes.

BACKGROUND: Lupus nephritis (LN) is a complication of SLE characterised by immune dysfunction and oxidative stress (OS). Limited options exist for LN. We aimed to identify LN-related OS, highlighting the need for non-invasive diagnostic and therapeutic approaches.
METHODS: LN-differentially expressed genes (DEGs) were extracted from Gene Expression Omnibus datasets (GSE32591, GSE112943 and GSE104948) and Molecular Signatures Database for OS-associated DEGs (OSEGs). Functional enrichment analysis was performed for OSEGs related to LN. Weighted gene co-expression network analysis identified hub genes related to OS-LN. These hub OSEGs were refined as biomarker candidates via least absolute shrinkage and selection operator. The predictive value was validated using receiver operating characteristic (ROC) curves and nomogram for LN prognosis. We evaluated LN immune cell infiltration using single-sample gene set enrichment analysis and CIBERSORT. Additionally, gene set enrichment analysis explored the functional enrichment of hub OSEGs in LN.
RESULTS: The study identified four hub genes, namely STAT1, PRODH, TXN2 and SETX, associated with OS related to LN. These genes were validated for their diagnostic potential, and their involvement in LN pathogenesis was elucidated through ROC and nomogram. Additionally, alterations in immune cell composition in LN correlated with hub OSEG expression were observed. Immunohistochemical analysis reveals that the hub gene is most correlated with activated B cells and CD8 T cells. Finally, we uncovered that the enriched pathways of OSEGs were mainly involved in the PI3K-Akt pathway and the Janus kinase-signal transducer and activator of transcription pathway.
CONCLUSIONS: These findings contribute to advancing our understanding of the complex interplay between OS, immune dysregulation and molecular pathways in LN, laying a foundation for the identification of potential diagnostic biomarkers and therapeutic targets.

To investigate the clinical application value of pharmacogenetic testing in individualized drug therapy for adult male patients with schizophrenia. A total of 186 adult patients with schizophrenia were enrolled and randomised into the pharmacogenetic (PGx) intervention group and the standard care group. In the PGx intervention group, PGx testing was performed, and the medication regimen was adjusted according to the results of the pharmacogenomic analysis. In contrast, in the standard care group, patients were treated according to the physician\'s medication experience. Differences in the primary indicator of schizophrenia, the Positive and Negative Symptom Scale (PANSS), and the secondary efficacy measures, the Clinical Global Impressions-Severity of Illness scale (CGI-SI) and Clinical Global Impressions-Global Improvement (CGI-GI) scale, were compared between the intervention and standard care groups. At baseline, the PGx intervention group consisted of 109 individuals, while the standard care group had 77 participants. After 12 weeks of treatment, 49 individuals withdrew from the PGx group (a dropout rate of 45.0%), and 34 withdrew from the standard care group (a dropout rate of 44.2%), with no significant difference in dropout rates between the two groups. The PANSS score reduction rate in the PGx intervention group significantly exceeded that of the standard care group during weeks 3, 6, and 12 of follow-up (P < 0.05). At the 12th week, the PGx intervention group achieved a treatment response rate of 81.7%, significantly surpassing the 48.8% of the standard care group (odds ratio of 4.67, 95% confidence interval of 1.96-11.41; P = 0.001). Furthermore, the PGx intervention was significantly more effective than standard care regardless of whether the patient had a first episode or a relapse (P < 0.05). Furthermore, the Global Assessment of Functioning (GAF) scores and the Personal and Social Performance Scale (PSP) score changes in the PGx intervention group were both significantly different from those in the standard care group (P < 0.05). It is noteworthy that the PGx intervention similarly improves the prognostic outcomes for patients with and without a family history of mental disorders. In conclusion, the application of a PGx intervention treatment model based on PGx testing can significantly improve medication efficacy and shorten the time to achieve the effects of medication in schizophrenia.