Pharmacogenomics. 2025 Apr 9:1-6. doi: 10.1080/14622416.2025.2489920. Online ahead of print.

ABSTRACT

INTRODUCTION: Genotype-guided tacrolimus management is not routine in clinical practice despite the availability of Clinical Pharmacogenetics Implementation Consortium dosing guidelines. Prior surveys have evaluated patient and provider perspectives of pharmacogenetics (PGx) in transplant, but limited recent data exists on tacrolimus PGx implementation across United States transplant centers.

METHODS: An electronic survey was distributed to transplant pharmacists regarding utilization of tacrolimus PGx, methods of implementing PGx, and barriers to clinical implementation. A survey response was requested for each organ program within the transplant center.

RESULTS: A total of 90 programs from 69 transplant centers (28.1% of active U.S. transplant centers) responded to the survey. Tacrolimus PGx was utilized for patient care in 14 programs (15.6%). There was substantial variability in the implementation methods and application of tacrolimus PGx results among transplant programs. In programs that had not implemented tacrolimus PGx, common barriers for implementation included PGx testing cost and availability and lack of evidence for clinical utility.

CONCLUSION: Implementation of PGx guided tacrolimus in solid organ transplant centers remains limited with heterogeneity in the implementation approach. Additional research is needed to establish the clinical utility of PGx guided tacrolimus and education on reimbursement and testing resources may help to increase uptake.

PMID:40205800 | DOI:10.1080/14622416.2025.2489920

Pharmacogenomics J. 2025 Apr 9;25(3):8. doi: 10.1038/s41397-025-00368-z.

ABSTRACT

This review offers an overview of advanced in silico methods crucial for drug discovery, emphasizing their integration with data science, and investigates the effectiveness of data science, machine learning, and artificial intelligence via a thorough meta-analysis of existing technologies. This meta-analysis aims to rank these technologies based on their applications and accessibility of knowledge. Initially, a search strategy yielded 900 papers, which were then refined into two subsets: the top 300 most-cited papers since 2000 and papers selected for systematic review based on high impact. From these, 97 articles were identified for discussion, categorized by their influence on society. The focus remains on the qualitative impact of these disciplines rather than solely on metrics like new drug approvals. Ultimately, the review underscores the role of big data in enhancing our comprehension of drug candidate trajectories from development to commercialization, utilizing information stored in publicly available databases to chemical space. Graphical extrapolation of some keywords (Drug Discovery; Big Data; Database; Metadata) discussed in this article and their evolution (in terms of absolute items that are available) by time.

PMID:40204715 | DOI:10.1038/s41397-025-00368-z

Mol Metab. 2025 Apr 7:102136. doi: 10.1016/j.molmet.2025.102136. Online ahead of print.

ABSTRACT

Recent modifications to glucagon-like peptide 1 (GLP-1), known for its insulinotropic and satiety-inducing effects, have focused on conjugating small molecules to enable selective delivery into GLP-1R+ tissues to achieve targeted synergy and improved metabolic outcomes. Despite continued advancements in GLP-1/small molecule conjugate strategies, the intracellular mechanisms facilitating concurrent GLP-1R signaling and small molecule cargo release remain poorly understood. We evaluate an estradiol (E2)-conjugated GLP-1 (GLP-1-CEX/E2) for relative differences in GLP-1R signaling and trafficking, and elucidate endolysosomal dynamics that lead to estrogenic activity using various live-cell, reporter, imaging, and mass-spectrometry techniques. We find GLP-1-CEX/E2 does not differentially activate or traffic the GLP-1R relative to its unconjugated GLP-1 backbone (GLP-1-CEX), but uniquely internalizes the E2 moiety and stimulates estrogenic signaling. Endolysosomal pH-dependent proteolytic activity likely mediates E2 moiety liberation, as evidenced by clear amplification in estrogenic activity following co-administration with lysosomal VATPase activator EN6. The hypothesized liberated metabolite from GLP-1-CEX/E2, E2-3-ether, exhibits partial estrogenic efficacy through ERα, and is predisposed toward estrone-3-sulfate conversion. Finally, we identify relative increases in intracellular E2, estrone, and estrone-3-sulfate following GLP-1-CEX/E2 incubation in GLP-1R+ cells, demonstrating proof-of-principle for desired cargo release. Together, our data suggest that GLP-1-CEX/E2 depends on GLP-1R trafficking and lysosome acidification for estrogenic efficacy, with a likely conversion of the liberated E2-3-ether metabolite into estrone-3-sulfate, resulting in residual downstream flux into active estradiol. Our current findings aim to improve the understanding of small molecule targeting and the efficacy behind GLP-1/small molecule conjugates.

PMID:40204014 | DOI:10.1016/j.molmet.2025.102136

Am J Health Syst Pharm. 2025 Apr 9:zxaf090. doi: 10.1093/ajhp/zxaf090. Online ahead of print.

ABSTRACT

DISCLAIMER: In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time.

PURPOSE: Expanding access to pharmacogenomics (PGx) testing to veterans has been an emphasis in the Veterans Health Administration (VHA); using population dashboard tools (PDTs) may identify additional patients who qualify for testing. Involving pharmacy residents in PGx can help prepare them for precision medicine practice and more efficiently provide PGx care to patients.

METHODS: Veterans treated in the outpatient setting at the Lt. Col. Luke Weathers, Jr. Veterans Affairs (VA) Medical Center from March 2023 to June 2024 were included in this study. Upon creation of a virtual PGx clinic, a PGx PDT was used to identify patients newly prescribed medications on the VA PGx gene testing panel. The clinic was driven by a postgraduate year 2 pharmacy resident with a preceptor overseeing the practice, and patients were contacted for consent and testing. The number and type of PGx gene variants identified were assessed, with results discussed with patients and recommendations made to providers.

RESULTS: A total of 130 patients were screened, of whom 104 had PGx testing, corresponding to an 80% consent rate. Overall, 247 PGx gene variants were identified, including 149 informational and 78 actionable drug-gene variants, 18 variants indicating inheritable conditions, and 17 variants corresponding to phenoconversion. A total of 90 recommendations were made to providers, and patients had an average of 2.3 PGx-impacted medications prescribed. Of the actionable drug-gene variants, the majority were related to use of clopidogrel, statins, sertraline, and proton pump inhibitors.

CONCLUSION: Novel use of a PDT was helpful in identifying patients qualifying for PGx testing. Creation of the resident-driven clinic resulted in PGx interventions for the majority of patients who underwent testing.

PMID:40202453 | DOI:10.1093/ajhp/zxaf090

Front Pharmacol. 2025 Mar 25;16:1502379. doi: 10.3389/fphar.2025.1502379. eCollection 2025.

ABSTRACT

BACKGROUND: Dopamine replacement therapy is a cornerstone of Parkinson's disease treatment. In clinical practice, there is considerable variability in patients' responses, tolerability, and safety regarding anti-parkinsonian medications, which is largely influenced by genetic polymorphisms in pharmacokinetic and pharmacodynamic genes. However, the application of multigenetic pharmacogenomics-guided treatment (MPGT) to optimize therapeutic outcomes in Parkinson's disease (PD) remains under-explored. In this study, we conducted a prospective cohort investigation to evaluate the potential benefits of MPGT on motor symptoms in PD patients.

METHODS: A total of 28 patients with PD were followed for 4 weeks. Among them, 22 patients underwent multigenetic pharmacogenomic testing, with 13 receiving treatments based on the test results (MPGT group). The remaining 15 received standard care (TAU group). Baseline characteristics, as well as changes in Unified Parkinson's Disease Rating Scale (UPDRS) III scores and sub-scores, were compared between the two groups. Associations between various single nucleotide polymorphisms (SNPs) and treatment outcomes were analyzed using generalized linear models.

RESULTS: At the 4-week follow-up, the MPGT group showed significantly greater reductions in UPDRS III total scores (p < 0.05) and limb sub-scores (p < 0.01) compared to the TAU group. These differences remained significant after adjusting for increases in levodopa equivalent daily dose (p = 0.011 and p = 0.002, respectively) and piribedil use (p = 0.006 and p = 0.004, respectively). Patients homozygous for the major allele of rs4984241 (AA vs. AG+GG, p = 0.003), rs4680 (GG vs. GA+AA, p = 0.013), rs1076560/rs2283265 (CC vs. AC+AA, p = 0.039) and rs622342 (AA vs. AC, p = 0.043) showed greater improvement in total UPDRS III, postural instability and gait difficulty (PIGD), rigidity and tremor scores, respectively, compared to those carrying at least one minor allele.

CONCLUSION: MGPT demonstrates significant potential as a valuable tool for personalized treatment in PD patients. Additionally, we identified several SNPs associated with the responsiveness to chronic administration of multiple anti-parkinsonian drugs. However, to confirm these findings, well-designed studies with larger, well-characterized samples are necessary.

PMID:40201683 | PMC:PMC11975922 | DOI:10.3389/fphar.2025.1502379

Pharmacogenomics. 2025 Apr 9:1-5. doi: 10.1080/14622416.2025.2489916. Online ahead of print.

ABSTRACT

The development of polygenic risk scores (PRSs), which make use of genetic testing to assess an individual's risk of developing certain diseases or conditions based on collective genetic variant information, can be applied in drug development to enrich clinical trials or predict response to treatment. From querying documents submitted to the Food & Drug Administration, the landscape of use of PRSs across time shows increased use in guiding clinical trials. Of the clinical trial protocols submitted, most were in the therapeutic areas of neurology, radiology (imaging and diagnostic pharmaceuticals), psychiatry, and oncology. Use of PRSs in clinical trials is most frequent in early drug development (phase 1, phase 1/2, or phase 3) and generally supports secondary or exploratory analyses. Additionally, about half of the protocols developed novel PRSs, and the other half used preexisting PRSs. As researchers, regulators, and clinicians aim to understand the results and implications of PRSs in clinical trials, the continued use of PRSs, despite being less common, reinforces the need for further exploration.

PMID:40200755 | DOI:10.1080/14622416.2025.2489916

Stud Health Technol Inform. 2025 Apr 8;323:131-135. doi: 10.3233/SHTI250063.

ABSTRACT

Pharmacogenomics (PGx) enables personalized medication optimization, potentially improving clinical outcomes, particularly for older adults who frequently experience polypharmacy. CYP2D6 is an enzyme that plays a crucial role in the metabolism of many drugs. The prevalence of CYP2D6 variants and their impact on potential drug-gene interactions in patients with prostate cancer (PPC), who are mostly represented by older adults, have not been systematically investigated. In this study, we analyzed the genotypes and phenotypes for CYP2D6 gene and medical prescription of over 3000 PPC enrolled in the All of Us research program. We found that about 20% of the patients were identified as non-normal metabolizer types with increased or reduced function. 67% of the patients had at least one medication mainly or partly metabolized by CYP2D6. 13% of the patients had an actionable phenotype and prior exposure to an impacted medication. These findings suggest a potential roadmap for improvement of medication prescription in PPC using PGx guidelines in routine clinical practice.

PMID:40200460 | DOI:10.3233/SHTI250063

Biochem Pharmacol. 2025 Apr 6:116921. doi: 10.1016/j.bcp.2025.116921. Online ahead of print.

ABSTRACT

Oxidative stress-induced growth inhibitors (OSGINs) represent a new category of proteins that respond to oxidative stress and modulate redox balance. Growing evidence indicates that OSGINs have extensive physiological and pathological functions by regulating essential cellular processes, including proliferation, autophagy, apoptosis, and ferroptosis, thus influencing the progression of various diseases such as cancer, atherosclerosis, and pulmonary fibrosis. Moreover, research indicates that some contaminants, biomaterials, active compounds, and drugs can induce the expression of OSGINs, thereby exerting toxicity or therapeutic effects on the organism. These many functions make OSGINs attractive targets. However, a thorough analysis of the topic is still lacking. This paper presents a systematic review of current OSGINs research, with an emphasis on their molecular functions, regulatory mechanisms, disease roles, and environmental stressors. Furthermore, using virtual screening tools, we identified a series of active molecules with potential inhibitory effects on OSGINs, providing valuable references for further drug development. Our review presents novel insights and guidance for the ongoing investigation of the biological significance and potential clinical applications of OSGINs.

PMID:40199404 | DOI:10.1016/j.bcp.2025.116921

Yearb Med Inform. 2024 Aug;33(1):168-174. doi: 10.1055/s-0044-1800738. Epub 2025 Apr 8.

ABSTRACT

OBJECTIVES: Objective: Precision medicine uses individualized patient data, including genomic and social determinants of health SDoH), to provide optimized personalized patient treatment. In this scoping review, we summarize studies published in the last two years that reported on implementation of precision medicine in clinical decision support (CDS) related to precision medicine.

METHODS: We searched PubMed for manuscripts published in 2022 and 2023 to retrieve publications that included CDS and precision medicine keywords and Mesh terms. We reviewed the abstracts and full texts to apply the inclusion criteria that the study must have described the implementation of precision medicine related CDS within electronic health records. We extracted the domain, type of data used in CDS, target population included in the implementation from the final set of included manuscripts.

RESULTS: Our search retrieved 285 manuscripts and papers. Sixteen (16) papers met inclusion criteria after manual review of the full text. Eight of the reviewed papers studied the successful implementation of pharmacogenomics in CDS, four studies investigated the implementation of disease risk, and only one paper described the implementation of CDS integrating social determinants of health.

CONCLUSION: Our scoping review of recent literature highlighted several findings. Pharmacogenomics is the most implemented precision medicine intervention based on published studies. Few reports describing disease risk and polygenic risk scores were found and no study addressed CDS for continuous biometric monitoring. Despite the increasing attention to social determinants of health as a key predictor of health outcomes, only one CDS incorporating SDoH have been publicly reported. Regular updates to scoping reviews can investigate barriers to implementation and identify solutions.

PMID:40199302 | DOI:10.1055/s-0044-1800738

Support Care Cancer. 2025 Apr 8;33(5):362. doi: 10.1007/s00520-025-09392-y.

ABSTRACT

PURPOSE: Prior studies evaluating the genetic predisposition to chemotherapy induced peripheral neuropathy (CIPN) have been limited by small populations due to difficulty with real-world data extraction. This genome-wide association study (GWAS) evaluates the genetic differences between patients who developed CIPN against those unaffected, using an electronic health record (EHR) definition of CIPN.

METHODS: This study included all patients who received chemotherapy associated with CIPN and had germline genetic data within the biobank at the Colorado Center for Personalized Medicine. CIPN was defined by a new neuropathic pain medication or an ICD-diagnosis of neuropathy after specified chemotherapy initiation. GWAS were stratified by (1) total population, (2) platinum chemotherapy, (3) taxane chemotherapy, and (4) vinca alkaloid chemotherapy. Genes previously associated with CIPN were analyzed within each GWAS.

RESULTS: Nine hundred fifteen patients received chemotherapy associated with CIPN, with 528 patients (57%) developing CIPN. Median age at chemotherapy initiation was 60.5 years; female sex (n = 517, 56.5%) and White or Caucasian race (n = 822, 89.8%) were most common. Among single nucleotide polymorphisms (SNPs) that reached suggestive levels of genome-wide significance (p < 1 × 10-5), 60 SNPs occurred within 11 genes that may play a role in the development of or protection against CIPN, including RCOR1, CLDN14, TRIM5, and TMC2. No SNPs previously associated with CIPN achieved genome-wide significance in this population.

CONCLUSION: This pharmacogenomic study suggests several genomic loci that may modulate the development of CIPN. This EHR-definition may allow for increased sample sizes and improved statistical power in future genetic studies of CIPN.

PMID:40198382 | DOI:10.1007/s00520-025-09392-y

J Pathol Transl Med. 2025 Mar;59(2):105-114. doi: 10.4132/jptm.2024.11.05. Epub 2025 Feb 25.

ABSTRACT

BACKGROUND: The present research was designed to study the associations between genetic variants of TYMS and ENOSF1 genes with TYMS and ENOSF1 gene expression in neoadjuvant chemotherapy response among patients with gastric cancer.

METHODS: Formalin-embedded and paraffin-fixed matched tumor and normal gastric cancer tissue samples from patients who received neoadjuvant 5-fluorouracil (5-FU) treatment were obtained. DNA and RNA were extracted for all samples. A 28-bp variable number tandem repeat (VNTR) at the 5' untranslated region of TYMS gene and rs2612091 and rs2741171 variants in the ENOSF1 gene were genotyped for normal tissue samples. The real-time polymerase chain reaction method was used to study the expression of ENOSF1 and TYMS genes in both normal and tumor tissues. Data were analyzed using REST 2000 and SPSS ver. 26.0 software programs.

RESULTS: A significant association between TYMS 2R3R VNTR genotypes and 5-FU therapy was found (p = .032). The 3R3R and 2R2R genotypes were significantly associated with increased and decreased survival time, respectively (p = .003). The 3R3R genotype was significantly associated with TYMS overexpression (p < .001). Moreover, a significant association was found between the rs2612091 genotype and treatment outcome (p = .017).

CONCLUSIONS: This study highlights the impact of TYMS and ENOSF1 genes as predictive indicators for survival and response to 5-FU-based neoadjuvant chemotherapy in gastric cancer patients.

PMID:40195828 | DOI:10.4132/jptm.2024.11.05

Prostate Cancer Prostatic Dis. 2025 Apr 7. doi: 10.1038/s41391-025-00964-x. Online ahead of print.

ABSTRACT

BACKGROUND: The association between statin medication use and prostate cancer remains inconclusive. Evidence shows that genetic variation modifies lipid-lowering efficacy of statins, however, there are limited data on the pharmacogenomics of statins in prostate cancer chemoprevention.

METHODS: Clinical and germline data were extracted from the prostate biopsy database at the University Health Network, Toronto, Canada (1996-2014). A genome-wide association study (GWAS) and a custom array of 54 single nucleotide polymorphisms (SNPs) related to statin metabolism were performed. Using a case-control design, we examined the associations between statin use and overall and high-grade (Grade Group ≥2) prostate cancer risk. A case-only design was employed to explore interactions between candidate/GWAS SNPs and the statin-cancer association.

RESULTS: Among 3481 patients, 1104 (32%) were using statins at biopsy. Statin users were older and had higher body mass index, greater number of positive cores, and higher Gleason scores. In total, 2061 participants (59%) were diagnosed with prostate cancer, with 922 cases (45%) classified as high-grade. When adjusted for baseline characteristics, the use of statins was not associated with decreased risk of overall or high-grade prostate cancer. Two unique SNPs implicated in statin metabolism showed significant interaction with the statin-cancer association. In particular, statin users harboring the GG genotype (n = 668; 24%) of rs10276036 had significantly lower prostate cancer risk (HR 0.71, 95% CI 051-1.00). However, none of the SNPs achieved genome-wide significance.

CONCLUSIONS: In our study, statin use was not associated with either prostate cancer or high-grade prostate cancer risk. While one candidate SNP that influences statin metabolism may be associated with a lower cancer risk among statin users and thus warrants further study, neither this nor any other SNPs achieved genome-wide significance. Thus, our findings do not add evidence in support of a prostate cancer chemopreventive role for statins.

PMID:40195554 | DOI:10.1038/s41391-025-00964-x

Pharmacogenomics. 2025 Apr 7:1-8. doi: 10.1080/14622416.2025.2490465. Online ahead of print.

ABSTRACT

Pharmacogenomics (PGx) is an evolving field that integrates genetic information into clinical decision-making to optimize drug therapy and minimize adverse drug reactions (ADRs). Its application in rare disease (RD) drug development is promising, given the genetic basis of many RDs and the need for precision medicine approaches. Despite significant advancements, challenges persist in developing effective therapies for RDs due to small patient populations, genetic heterogeneity, and limited surrogate biomarkers. The Orphan Drug Act in the U.S. has incentivized RD drug development. However, the traditional drug approval process is constrained by logistical and economic challenges, necessitating innovative PGx-driven strategies. Identifying genetic biomarkers in the early drug development stages can optimize dose selection, enhance therapeutic efficacy, and reduce ADRs. Case studies such as eliglustat for Gaucher disease and ivacaftor for cystic fibrosis demonstrate the efficacy of PGx-guided treatment strategies. Integrating PGx into global drug development requires the harmonization of regulatory policies and increased diversity in genetic research. Artificial intelligence (AI) tools further enhance genetic analysis, disease prediction, and clinical decision-making. Modernizing drug labeling with PGx information is critical to ensuring safe and effective druguse. Collectively, PGx offers transformative potential in RD therapeutics by facilitating personalized medicine approaches and addressing unmet medical needs.

PMID:40194983 | DOI:10.1080/14622416.2025.2490465

Medicine (Baltimore). 2025 Apr 4;104(14):e42031. doi: 10.1097/MD.0000000000042031.

ABSTRACT

A laboratory-initiated preemptive and reactive cytochrome P450 and SLCO1B1 PGx testing protocol was evaluated in a private toxicology laboratory with the intent of identifying enzyme frequencies and associated adverse drug events. This study involved non-experimental observational research. During the retrospective medical chart review, patient demographics, statements of medical necessity, and PGx testing data were collected. Frequencies and percentages were calculated for the collected data, and statistical analysis was performed using Intellectus online software. A total of 192 PGx patient records from September 2019 to October 2021 were retrospectively reviewed. For patient demographics, men (n = 118; (61%)) were the majority gender identified among the patient population and Caucasians (n = 112; (58%)) followed by African Americans (n = 37; (19%)) were the most identified ancestry. The mean age of the patients was 69 (±9) years. CYP1A2 hyperinducers, followed by CYP3A5 poor metabolizers and CYP2B6 intermediate metabolizers, are the most encountered cytochrome P450 and SLCO1B1 enzymes. Regarding drug-gene interactions, 41 patients had 1 interaction, 29 had 2, and 31 had 3 or more interactions. For drug-drug interactions, 35 patients had 1 interaction, 15 had 2, and 30 had 3 or more interactions. Overall, 123 patients showed a minor or greater impact on drug-drug or drug-gene interactions. Overall, our study identified cytochrome P450 and SCLCO1B1 enzyme frequencies and patients experiencing actionable adverse drug events. By raising awareness of PGx test results through individualized clinician training, education, and interventions, these adverse events can be promptly identified and resolved.

PMID:40193664 | DOI:10.1097/MD.0000000000042031

J Clin Psychopharmacol. 2025 Apr 7. doi: 10.1097/JCP.0000000000002001. Online ahead of print.

ABSTRACT

BACKGROUND: Pharmacogenomic studies on antidepressant treatment outcomes could be conducted using previously collected data from electronic health record (EHR)-linked biobanks. However, absence of EHR based outcome measures is an unmet need in designing such studies We aimed to define EHR-derived antidepressant outcome measures and explore their utility in showing associations between treatment outcomes and Cytochrome P450 (CYP) metabolizer phenotypes in a proof-of-concept study.

METHODS: Using data from the EHR-linked cohort, Right Drug, Right Dose, Right Time: Using Genomic Data to Individualize Treatment (RIGHT 10K) Study, we collected prescription data and patient health questionnaire 9 (PHQ-9) scores to compute 3 proxy measures for antidepressant response, efficacy, and acceptability: change in PHQ-9 scores, longest treatment interval with a single antidepressant, and antidepressant non-refill. Subsequently, we tested the association of both prescription-based outcomes with DNA-predicted CYP metabolizer phenotypes in European-ancestry participants.

RESULTS: We identified 3920 RIGHT 10K participants with at least 1 antidepressant prescription and European-ancestry. Participants had a mean age of 61 years and 72% were women. Implementation of the PHQ-9 outcome was not feasible because of missingness. Of both prescription-based outcomes, antidepressant non-refill reproduced several known antidepressant-CYP interactions. However, the pilot was limited by small subgroups of participants with non-normal metabolizer phenotypes.

CONCLUSIONS: Derived from structured data, antidepressant non-refill is a promising outcome measure for EHR-linked biobanks that partially reproduced antidepressant-CYP interactions. However, testing on larger datasets is necessary to understand whether it would be a useful for pharmacogenomic research.

PMID:40193626 | DOI:10.1097/JCP.0000000000002001

J Biochem Mol Toxicol. 2025 Apr;39(4):e70247. doi: 10.1002/jbt.70247.

ABSTRACT

Alzheimer's disease (AD) is a chronic and progressive neurodegenerative disorder marked by memory deterioration and cognitive impairment. Bisphenol A (BPA), a common environmental pollutant, has been linked to neurotoxicity and may contribute to AD development. This study aims to uncover potential toxicological targets and molecular mechanisms of BPA-induced AD. BPA's potential neurotoxic effects were predicted using ProTox and ADMETlab. Target prediction for BPA was conducted through the STITCH and Swiss Target Prediction platforms, while AD-related targets were compiled from GeneCards, OMIM, and the Therapeutic Target Database (TTD). Protein-protein interaction (PPI) networks were constructed using STRING and visualized in Cytoscape, and gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed. Molecular docking was employed to evaluate the binding interactions between BPA and the identified core targets. Through systematic bioinformatics analyses, 137 candidate targets for BPA-elicited AD were identified. Screening via PPI network analysis highlighted five key targets: STAT3, AKT1, INS, EGFR, and PTEN. GO and KEGG pathway enrichment revealed significant involvement in oxidative stress, neuronal apoptosis, neurodegenerative processes, and pathways such as PI3K/AKT, MAPK, lipid and atherosclerosis, and AD signaling. Molecular docking simulations confirmed strong binding affinities between BPA and these core targets. This study sheds light on the molecular mechanisms underlying BPA's neurotoxic effects in the context of AD and provides a foundation for further research into preventive and therapeutic strategies. The integration of network toxicology and molecular docking offers a robust framework for unraveling toxic pathways of uncharacterized environmental and chemical agents.

PMID:40192506 | DOI:10.1002/jbt.70247

Cardiovasc Hematol Disord Drug Targets. 2025 Apr 4. doi: 10.2174/011871529X361464250319084053. Online ahead of print.

ABSTRACT

Atherosclerosis and ischemic events play a pivotal role in the pathogenesis of several cardiovascular diseases (CVD). The primary aim of preventing recurrent thrombosis in patients who underwent cardiovascular surgery is the antiplatelet agent administration. Nevertheless, despite the aspirin therapy or double (aspirin plus clopidogrel) therapy, the effectiveness of antithrombotic treatment remains controversial. In recent years, we have learned that some percentage of patients still demonstrate no clinical response to aspirin treatment and may experience a vascular complication. This article provides an overview of recent scientific studies that have focused on experimental detection and genotyping of single nucleotide polymorphisms (SNPs) in patients, involving the main therapeutic target genes: cyclooxygenase COX-1 and COX-2, guanylate cyclase GUCY1A3, the glycoprotein complex GPIIb-IIIa, and the platelet receptor protein PEAR1." The aspirin resistance (AR) ranges considerably from 0 % to 66% in patients with ischemic heart disease (IHD) and relatively healthy people (control group). SNP distribution analysis has been proposed to explain the inadequate high platelet reactivity (HPR) among patients with IHD under aspirin treatment. Various SNPs have been proposed to explain the development of CVD and the persistent HPR under aspirin treatment widely used in the prevention of recurrent cardiovascular thrombotic events. Meanwhile, the efficacy of aspirin therapy in secondary thrombosis prevention in patients with IHD is not strongly associated with known SNP. The inconsistent results of different AR clinical trials are likely due to the design of the experiments and methodological and quantitative issues; therefore, careful interpretation of the SNP genotyping results is necessary.

PMID:40192046 | DOI:10.2174/011871529X361464250319084053

J Intern Med. 2025 Apr 6. doi: 10.1111/joim.20087. Online ahead of print.

ABSTRACT

BACKGROUND: Methotrexate (MTX) is the mainstay initial treatment of rheumatoid arthritis (RA), but individual response varies and remains difficult to predict. The role of genetics remains unclear, but studies suggest its importance.

METHODS: Incident RA patients starting MTX-monotherapy were identified through a large-scale Swedish register linkage. Demographic, clinical, medical, and drug history features were combined with fully imputed genotype data and used to train and evaluate multiple learning models to predict key MTX treatment outcomes.

RESULTS: Among 2432 patients, we consistently observed an estimated area under the curve (AUC) of ∼0.62, outperforming models trained on sex and age. The best performance was observed for EULAR primary response (AUC = 0.67), whereas models struggled the most with predicting discontinuation. Genetics provided negligible improvements to prediction quality.

CONCLUSIONS: Despite an extensive study population with broad multi-modal data, predicting MTX treatment outcomes remains a challenge. Common genetic variants added minimal predictive power over clinical features.

PMID:40190030 | DOI:10.1111/joim.20087

Hum Vaccin Immunother. 2025 Dec;21(1):2488557. doi: 10.1080/21645515.2025.2488557. Epub 2025 Apr 6.

ABSTRACT

It is estimated that 40-50% of severe asthma has an atopic basis, representing a clinical challenge and a significant economic burden for healthcare systems. The most effective treatment has emerged with the use of biologic therapies such as omalizumab; however, the rate of therapy switching due to loss of efficacy is high, which has a negative impact on the healthcare system. The aim was to evaluate the influence of genetic polymorphisms as predictors of omalizumab survival. We conducted a retrospective observational cohort study of 110 patients with uncontrolled severe allergic asthma treated with omalizumab in a tertiary hospital. We analyzed FCER1A (rs2251746, rs2427837), FCER1B (rs1441586, rs573790, rs1054485, rs569108), C3 (rs2230199), FCGR2A (rs1801274), FCGR2B (rs3219018, rs1050501), FCGR3A (rs10127939, rs396991), IL1RL1 (rs1420101, rs17026974, rs1921622) and GATA2 (rs4857855) by real-time PCR using Taqman probes. Drug survival was defined as the time from initiation to discontinuation of omalizumab. Cox regression analysis adjusted for the presence of respiratory disease, GERD, SAHS and years with asthma showed that the SNPs FCER1B rs573790 - CT (p < .001; HR = 3.38; CI95% = 1.66-6.87), FCGR3A rs10127939-AC (p = .018; HR = 3.85; CI95% = 1.25-11.81) and FCGR3A rs396991-CC (p = .020; HR = 2.23; CI95% = 1.14-4.38) were the independent variables associated with worse survival in patients diagnosed with asthma. A trend toward statistical significance was also found between and FCGR3A rs10127939-CC (p = .080; HR = 0.13; CI95% = 0.01-1.28) and longer drug survival. The results of this study demonstrate the potential influence of the polymorphisms studied on omalizumab survival and the clinical benefit that could be achieved by defining predictive biomarkers of drug survival.

PMID:40189906 | DOI:10.1080/21645515.2025.2488557

Allergol Int. 2025 Apr 4:S1323-8930(25)00026-7. doi: 10.1016/j.alit.2025.03.002. Online ahead of print.

ABSTRACT

The association of human leukocyte antigen (HLA) with the risk of drug-induced skin eruptions has been extensively studied. The sensitivity of the association of specific HLA alleles with drug eruptions ranges from approximately 50 to 100%, indicating a significant influence of HLA alleles on the risk of developing such reactions. Consequently, HLA testing holds substantial clinical potential as a genetic diagnostic tool to avoid drug eruptions. For instance, when prescribing drugs like carbamazepine and lamotrigine, which are known to cause severe drug eruptions, preemptive HLA genetic testing can help predict an individual's risk. This approach enables clinicians to reduce the overall incidence of drug eruptions by selecting alternative therapeutic agents or adjusting dosages based on the results of HLA genetic testing.

PMID:40187963 | DOI:10.1016/j.alit.2025.03.002