Brief Bioinform. 2025 May 1;26(3):bbaf226. doi: 10.1093/bib/bbaf226.

ABSTRACT

Pharmacogenomics studies are attracting an increasing amount of interest from researchers in precision medicine. The advances in high-throughput experiments and multiplexed approaches allow the large-scale quantification of drug sensitivities in molecularly characterized cancer cell lines (CCLs), resulting in a number of open drug sensitivity datasets for drug biomarker discovery. However, a significant inconsistency in drug sensitivity values among these datasets has been noted. Such inconsistency indicates the presence of substantial noise, subsequently hindering downstream analyses. To address the noise in drug sensitivity data, we introduce a robust and scalable deep learning framework, Residual Thresholded Deep Matrix Factorization (RT-DMF). This method takes a single drug sensitivity data matrix as its sole input and outputs a corrected and imputed matrix. Deep matrix factorization (DMF) excels at uncovering subtle patterns, due to its minimal reliance on data structure assumptions. This attribute significantly boosts DMF's ability to identify complex hidden patterns among nuisance effects in the data, thereby facilitating the detection of signals that are therapeutically relevant. Furthermore, RT-DMF incorporates an iterative residual thresholding procedure, which plays a crucial role in retaining signals more likely to hold therapeutic importance. Validation using simulated datasets and real pharmacogenomics datasets demonstrates the effectiveness of our approach in correcting noise and imputing missing data in drug sensitivity datasets (open-source package available at https://github.com/tomwhoooo/rtdmf).

PMID:40420482 | DOI:10.1093/bib/bbaf226

Front Mol Biosci. 2025 May 9;12:1583992. doi: 10.3389/fmolb.2025.1583992. eCollection 2025.

ABSTRACT

Exosomes, small membranous vesicles naturally secreted by living cells, have garnered attention for their role in intercellular communication and therapeutic potential. Their low immunogenicity, high biocompatibility, and efficient biological barrier penetration make them promising drug delivery vehicles. This review spans research developments from 2010 to 2025, covering the engineering of exosomes to optimize cargo loading and targeting specificity. We discuss their applications in treating cardiovascular diseases, liver fibrosis, immune diseases, and neurological diseases, alongside ongoing clinical trials and industry progress. Future challenges include scalability, standardization, and minimizing off-target effects. We propose strategies to address these hurdles, such as bioengineering techniques and improved isolation methods. By synthesizing current knowledge and outlining future directions, this review aims to guide researchers toward harnessing exosomes for disease treatment.

PMID:40417062 | PMC:PMC12098103 | DOI:10.3389/fmolb.2025.1583992

Eur Psychiatry. 2025 May 26:1-28. doi: 10.1192/j.eurpsy.2025.10036. Online ahead of print.

NO ABSTRACT

PMID:40415581 | DOI:10.1192/j.eurpsy.2025.10036

Clin Pharmacokinet. 2025 May 25. doi: 10.1007/s40262-025-01528-x. Online ahead of print.

ABSTRACT

BACKGROUND AND OBJECTIVE: Nortriptyline, a tricyclic antidepressant, has an important role in the pharmacotherapy of major depressive disorder (MDD). Individualized dosing approaches, such as pharmacogenetics-based and phenotype-based dosing, may enhance early achievement of therapeutic plasma concentrations, but their comparative accuracy has not been investigated. Our objective was to compare the accuracy of three nortriptyline dosing strategies: pharmacogenetics-based, phenotype-based, and standard dosing.

METHODS: Using pharmacokinetic modeling based on data from a randomized controlled trial, we assessed and compared the following dosing strategies: pharmacogenetics-based dosing depending on the cytochrome P-450 (CYP) 2D6 genotype, phenotype-based dosing determined by the plasma concentration measured after a single nortriptyline administration, and standard dosing (125 mg/day). A population pharmacokinetic model was developed to assess phenotype-based dosing recommendations. We evaluated the dosing strategies by comparing the number of participants with predicted therapeutic, subtherapeutic, and supratherapeutic plasma concentrations using Chi-squared (χ2) tests. Variability in plasma concentrations was assessed using F-tests.

RESULTS: Both pharmacogenetics-based (χ2 (1) = 8.0, p = 0.01) and phenotype-based dosing (χ2 (1) = 5.3, p = 0.02) significantly increased the likelihood of achieving therapeutic plasma concentrations compared with standard dosing while reducing plasma concentration variability. No significant difference was found in the prediction of therapeutic concentrations between the two individualized dosing strategies (χ2 (1) = 0.33, p = 0.56).

CONCLUSIONS: Pharmacogenetics-based and phenotype-based dosing demonstrate greater accuracy in predicting therapeutic nortriptyline plasma concentrations than standard dosing. Further research is warranted to explore the clinical application of model-informed precision dosing for nortriptyline and other psychotropic medications.

PMID:40413686 | DOI:10.1007/s40262-025-01528-x

Pharmacogenomics J. 2025 May 24;25(3):15. doi: 10.1038/s41397-025-00369-y.

ABSTRACT

Childhood cancer survivors (CCS) often suffer from cardiac disease (CD) after treatment that included anthracycline and radiotherapy involving the heart. However, the variability in CD occurrence cannot be explained solely by these treatments, suggesting the existence of genetic predisposition. We conducted a systematic review searching on Medline-PubMed and Scopus, to identify studies reporting associations between genetic factors and CD in CCS. We included studies published up to 11 April 2023, with no lower limit, and assessed the quality of genetic associations by the Q-genie tool. As a result, 20 studies were included (15 case-control and five cohorts), revealing several genes and variants associated with cardiomyopathy, among which, SLC28A3-rs7853758, RARG-rs2229774, P2RX7-rs208294 and P2RX7-rs3751143 variants gave the most consistent findings. This review highlights the necessity to establish a set of clinically useful genes and variants to identify patients most at risk of developing cardiomyopathy, and to implement monitoring and prevention strategies.

PMID:40413218 | DOI:10.1038/s41397-025-00369-y

Eur Neuropsychopharmacol. 2025 May 22;96:17-27. doi: 10.1016/j.euroneuro.2025.05.004. Online ahead of print.

ABSTRACT

Proteomics has been scarcely explored for predicting treatment outcomes in major depressive disorder (MDD), due to methodological challenges and costs. Predicting protein levels from genetic scores provides opportunities for exploratory studies and the selection of targeted panels. In this study, we examined the association between genetically predicted plasma proteins and treatment outcomes - including non-response, non-remission, and treatment-resistant depression (TRD) - in 3559 patients with MDD from four clinical samples. Protein levels were predicted from individual-level genotypes using genetic scores from the publicly available OmicsPred database, which estimated genetic scores based on genome-wide genotypes and proteomic measurements from the Olink and SomaScan platforms. Associations between predicted protein levels and treatment outcomes were assessed using logistic regression models, adjusted for potential confounders including population stratification. Results were meta-analysed using a random-effects model. The Bonferroni correction was applied. We analysed 257 proteins for Olink and 1502 for SomaScan; 111 proteins overlapped between the two platforms. Despite no association was significant after multiple-testing correction, many top results were consistent across phenotypes, in particular seven proteins were nominally associated with all the analysed outcomes (CHL1, DUSP13, EVA1C, FCRL2, KITLG, SMAP1, and TIM3/HAVCR2). Additionally, three proteins (CXCL6, IL5RA, and RARRES2) showed consistent nominal associations across both the Olink and SomaScan platforms. The convergence of results across phenotypes is in line with the hypothesis of the involvement of immune-inflammatory mechanisms and neuroplasticity in treatment response. These results can provide hints for guiding the selection of protein panels in future proteomic studies.

PMID:40408832 | DOI:10.1016/j.euroneuro.2025.05.004

J Xenobiot. 2025 May 7;15(3):66. doi: 10.3390/jox15030066.

ABSTRACT

Cannabis sativa L. shows potent anti-inflammatory activity, resulting in an interesting pharmacological option for pain management. The aim of the study was to evaluate the association between pharmacogenetics, neurological and inflammatory biomarkers, and cannabinoid plasma exposure in patients treated with cannabis. A total of 58 patients with a diagnosis of neuropathic and chronic pain treated with medical cannabis were analyzed. Cannabis was administered as a decoction (n = 47) and as inhaled cannabis (n = 11): 30 patients were treated with cannabis with high THC, while 28 patients were treated with cannabis with reduced THC (plus CBD). Cannabinoid plasma concentrations were obtained with UHPLC-MS/MS. Allelic discrimination was assessed by real-time PCR. Inflammation biomarkers (e.g., interleukin-10) were analyzed by ELISA, neurofilaments light chain (NFL), and brain-derived neurotrophic factor (BDNF) by Single Molecule Array. A statistically significant difference in IL-10 (p = 0.009) and BDNF (p = 0.004) levels was observed comparing patients treated with decoction and inhaled cannabis. BDNF and NFL results correlated with cannabinoid concentrations. Concerning genetics, the COMT 680 T>C genetic variant influences cannabinoid plasma levels, including Δ9-THC (p = 0.017). Conclusions: This study shows a possible impact of some genetic variants on cannabinoid plasma exposure, other than a possible role of medical cannabis on inflammation-related and neuronal impairment factor levels. Further studies in larger cohorts are required.

PMID:40407530 | DOI:10.3390/jox15030066

JAMA Neurol. 2025 May 23. doi: 10.1001/jamaneurol.2025.1522. Online ahead of print.

ABSTRACT

IMPORTANCE: Nontraumatic subarachnoid hemorrhage (SAH) represents the third most common stroke type with unique etiologies, risk factors, diagnostics, and treatments. Nevertheless, epidemiological studies often cluster SAH with other stroke types leaving its distinct burden estimates obscure.

OBJECTIVE: To estimate the worldwide burden of SAH.

DESIGN, SETTING, AND PARTICIPANTS: Based on the repeated cross-sectional Global Burden of Disease (GBD) 2021 study, the global burden of SAH in 1990 to 2021 was estimated. Moreover, the SAH burden was compared with other diseases, and its associations with 14 individual risk factors were investigated with available data in the GBD 2021 study. The GBD study included the burden estimates of nontraumatic SAH among all ages in 204 countries and territories between 1990 and 2021.

EXPOSURES: SAH and 14 modifiable risk factors.

MAIN OUTCOMES AND MEASURES: Absolute numbers and age-standardized rates with 95% uncertainty intervals (UIs) of SAH incidence, prevalence, mortality, and disability-adjusted life-years (DALYs) as well as risk factor-specific population attributable fractions (PAFs).

RESULTS: In 2021, the global age-standardized SAH incidence was 8.3 (95% UI, 7.3-9.5), prevalence was 92.2 (95% UI, 84.1-100.6), mortality was 4.2 (95% UI, 3.7-4.8), and DALY rate was 125.2 (95% UI, 110.5-142.6) per 100 000 people. The highest burden estimates were found in Latin America, the Caribbean, Oceania, and high-income Asia Pacific. Although the absolute number of SAH cases increased, especially in regions with a low sociodemographic index, all age-standardized burden rates decreased between 1990 and 2021: the incidence by 28.8% (95% UI, 25.7%-31.6%), prevalence by 16.1% (95% UI, 14.8%-17.7%), mortality by 56.1% (95% UI, 40.7%-64.3%), and DALY rate by 54.6% (95% UI, 42.8%-61.9%). Of 300 diseases, SAH ranked as the 36th most common cause of death and 59th most common cause of DALY in the world. Of all worldwide SAH-related DALYs, 71.6% (95% UI, 63.8%-78.6%) were associated with the 14 modeled risk factors of which high systolic blood pressure (population attributable fraction [PAF] = 51.6%; 95% UI, 38.0%-62.6%) and smoking (PAF = 14.4%; 95% UI, 12.4%-16.5%) had the highest attribution.

CONCLUSIONS AND RELEVANCE: Although the global age-standardized burden rates of SAH more than halved over the last 3 decades, SAH remained one of the most common cardiovascular and neurological causes of death and disabilities in the world, with increasing absolute case numbers. These findings suggest evidence for the potential health benefits of proactive public health planning and resource allocation toward the prevention of SAH.

PMID:40406922 | DOI:10.1001/jamaneurol.2025.1522

Hosp Pharm. 2025 May 20:00185787251339360. doi: 10.1177/00185787251339360. Online ahead of print.

ABSTRACT

Background: Opioids are utilized for acute pain in hospitalized patients and carry the risk of unintentional toxicity. The relationship between unintentional toxicity within a hospital setting and genetic polymorphisms has not been fully evaluated within the literature to date. Assessment and utilization of pharmacogenetic data may be a way to prevent unintentional toxicity in hospitalized patients and reduce the need for naloxone administration. Objective: This study aimed to provide proof of concept for the comparison of allele frequencies of hospitalized patients who received naloxone for opioid reversal with lab control data allele frequencies to identify variations between groups. Methods: This single-center, exploratory, pilot study enrolled 15 patients. Genotype samples were collected via buccal swab and analyzed using a custom 13 gene panel of genes which impact opioid metabolism. Genes assessed include CYP1A2, CYP3A4/A5, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, UGT2B7, UGT1A3, ABCB1, COMT, OPRM1. The 15 patients were compared to an internal lab control group of 100 patients and separated into preventable and not preventable events for further analysis. Results: CYP3A5 genotype was found to be statistically significantly different between the experimental and control groups (P = .004). This statistically significant difference was also seen in CYP3A5 phenotypes (P = .038). When comparing preventable and not preventable events, a statistically significant difference was found in both the genotype (P = .030) and phenotype (P = .029) of CYP2C19. Other assessed risk factors included mean MME in the 24 hours preceding naloxone being higher among preventable events and hospital or emergency department admission percent risk being higher among not preventable events. Conclusion: Factors other than pharmacogenetics, including opioid route of administration, medication formulation, and overall hospital admission risk, may play an additive role in unintentional toxicity risk. Future research of genotype-guided opioid dosing in pain management services further adds to calculating the risk of unintentional opioid-related adverse effects with standard dosing of this drug class.

PMID:40406364 | PMC:PMC12092407 | DOI:10.1177/00185787251339360

Pharmacogenomics. 2025 May 22:1-12. doi: 10.1080/14622416.2025.2504863. Online ahead of print.

ABSTRACT

Pharmacogenomic variations in genes involved in drug disposition and in drug targets is a major determinant of inter-individual differences in drug response and toxicity. While the effects of common variants are well established, millions of rare variations remain functionally uncharacterized, posing a challenge for the implementation of precision medicine. Recent advances in machine learning (ML) have significantly enhanced the prediction of variant effects by considering DNA as well as protein sequences, as well as their evolutionary conservation and haplotype structures. Emerging deep learning models utilize techniques to capture evolutionary conservation and biophysical properties, and ensemble approaches that integrate multiple predictive models exhibit increased accuracy, robustness, and interpretability. This review explores the current landscape of ML-based variant effect predictors. We discuss key methodological differences and highlight their strengths and limitations for pharmacogenomic applications. We furthermore discuss emerging methodologies for the prediction of substrate-specificity and for consideration of variant epistasis. Combined, these tools improve the functional effect prediction of drug-related variants and offer a viable strategy that could in the foreseeable future translate comprehensive genomic information into pharmacogenetic recommendations.

PMID:40401639 | DOI:10.1080/14622416.2025.2504863

Br J Clin Pharmacol. 2025 May 21. doi: 10.1002/bcp.70078. Online ahead of print.

ABSTRACT

AIMS: Gene polymorphisms play a critical role in the variability of plasma concentrations of direct-acting oral anticoagulants (DOACs). In this study, we aimed to investigate the effects of genetic variants on the clinical outcomes of Chinese patients treated with DOACs.

METHODS: The retrospective study recruited 720 patients with nonvalvular atrial fibrillation who were receiving dabigatran, rivaroxaban or edoxaban. Cox regression models were employed to compare the clinical outcomes between carriers and noncarriers of the key single nucleotide polymorphisms.

RESULTS: Results revealed that the CES1 rs2244613 C allele significantly reduced bleeding events in patients treated with dabigatran (adjusted hazard ratio 0.33, 95% confidence interval 0.13-0.85, P = .021). The carriage of ABCB1 rs1045642 T allele was associated with a lower risk of thromboembolism in rivaroxaban users (adjusted hazard ratio 0.19, 95% confidence interval 0.07-0.57, P = .003). Additionally, a trend toward statistical significance (P = .052) was observed between the SLCO1B1 rs4149056 C allele and bleeding risk among the edoxaban users.

CONCLUSIONS: Our study showed that the CES1 rs2244613 and ABCB1 rs1045642 alleles were associated with outcome events in Chinese patients taking dabigatran and rivaroxaban, respectively. The findings could help predict clinical outcomes and develop personalized anticoagulation treatment strategies for Chinese patients taking DOACs.

PMID:40400080 | DOI:10.1002/bcp.70078

Child Adolesc Psychiatry Ment Health. 2025 May 21;19(1):60. doi: 10.1186/s13034-025-00915-3.

ABSTRACT

BACKGROUND: This study evaluated pharmacogenomic (PGx) testing in children and adolescents with autism spectrum disorder (ASD). ASD frequently presents with co-occurring depression and anxiety. This complex phenotype often results in psychotropic medication polypharmacy. Incorporating PGx testing into the medical work-up may reduce polypharmacy and improve quality of life with symptom reduction.

METHODS: A retrospective electronic health record (EHR) review between January 2017 and May 2023. Individuals either received PGx testing or treatment as usual (TAU). The co-primary outcomes were instance of polypharmacy and the Pediatric Quality of Life Enjoyment and Satisfaction Questionnaire (PQ-LES-Q). Secondary outcomes included length of stay, average number of psychotropic medications, readmissions and assessments measuring severity of symptoms or behavioral impact. When at least one daily psychotropic medication was prescribed and reported to have an increased probability of gene-drug interactions, the individual was classified as "incongruent" (PGx-I). Individuals were categorized as "congruent" (PGx-C) if all prescribed psychotropic medications were without potential gene-drug interactions. Polypharmacy was evaluated and compared within the PGx-C and PGx-I subgroups.

RESULTS: A total of 99 individuals with ASD were analyzed. At the time of admission, 93% of individuals were prescribed at least one psychotropic medication and over half of these individuals were prescribed medications with potential gene-drug interactions. Following PGx testing, there was an overall reduction in prescribed medications with potential gene-drug interactions. No differences were observed between the PGx and TAU groups in polypharmacy, quality of life, or symptom assessments of depression, anxiety, obsessive-compulsive disorder and body-focused repetitive behaviors. Subanalysis comparing congruent ("use as directed") or incongruent ("use with caution"), as well as exploratory analysis of only CYP2D6 and CYP2C19 gene-drug interactions, were observed to have a similar profile between treatment groups for all primary and secondary outcomes, except for the average number of psychotropic medications prescribed.

CONCLUSIONS: Incorporating PGx testing into the medical workup did not improve outcomes, with all treatment groups achieving similar levels of polypharmacy and quality of life. Analysis of secondary outcomes revealed some differences in medication prescribing when stratifying by congruency; however, no differences were observed between treatment groups for all other secondary outcomes.

PMID:40399951 | DOI:10.1186/s13034-025-00915-3

Sci Rep. 2025 May 21;15(1):17634. doi: 10.1038/s41598-025-02781-7.

ABSTRACT

This study examines the synthesis and biological evaluation of novel tetrazole derivatives of 3,3'-dimethoxybenzidine as potential anticancer agents, focusing on their cytotoxic, apoptotic, and anti-inflammatory properties. Ten derivatives were synthesized using thioureas as precursors, characterized through spectroscopic methods, and assessed for their in silico toxicological profiles using the ADMET-AI and ProTox 3.0 platforms. In vitro cytotoxic activity was evaluated against four human cancer cell lines (HTB-140, A549, HeLa, SW620) and one normal cell line (HaCaT) using MTT and LDH assays. Mechanistic studies included apoptosis assessment via flow cytometry and interleukin-6 (IL-6) analysis using ELISA. The synthesized tetrazole derivatives demonstrated significant anticancer potential, exhibiting selective cytotoxicity against cancer cell lines, robust induction of apoptosis, and a notable reduction in IL-6 levels. Their favorable toxicity profiles, as observed in both in silico and in vitro evaluations, support their potential as promising candidates for further development. The tested compounds showed strong inhibitory activity against the apoptosis regulator Bcl-2, with binding affinities comparable to those of native ligands. Western blot analysis revealed a dramatic loss of Bcl-2 protein expression in selected cancer cells during exposure to compound 5. Additionally, this research highlights the innovative use of hazardous substrates in drug discovery, aligning with the principles of green chemistry. Future efforts should focus on optimizing the most active derivatives and conducting in vivo studies to confirm their therapeutic potential and safety.

PMID:40399589 | DOI:10.1038/s41598-025-02781-7

Drug Resist Updat. 2025 May 13;81:101249. doi: 10.1016/j.drup.2025.101249. Online ahead of print.

ABSTRACT

AIMS: Genotoxic drug resistance is one of the major obstacles for cancer treatment. Our previous study demonstrates that cold shock domain containing E1 (CSDE1) is associated with drug resistance. In this study, we aim to demonstrate that CSDE1 regulates cellular response to genotoxic drugs and to investigate its mechanism of action in drug resistance.

METHODS: Tissues and blood samples from cancer patients were used to evaluate the relationship between CSDE1 and genotoxic drug response. Comet and immunofluorescence assays were conducted to investigate the role of CSDE1 in DNA damage repair. Systematic knockout mouse models were used to study the underlying mechanism involved. Biotin pull-down, EMSA and co-IP assays were used to probe the triplex structure of CSDE1-protein (eIF3a)-RNA (RPA2).

RESULTS: CSDE1 elevation correlates with poor response in patient and increased resistance in cell lines to genotoxic drugs. CSDE1 upregulated the nucleotide excision repair (NER) and homologous recombination (HR) pathways. In X-ray irradiation or bleomycin-induced DNA damage mouse model, systemic CSDE1 knockout resulted in increased DNA damage. In both a CSDE1 knockout mouse model and cancer cell lines, CSDE1 inhibited the cGAS-STING pathway through RPA2. Mechanistic studies indicated that CSDE1 serves as a hub for the binding of the CSDE1-protein (eIF3a)-RNA (RPA2) ternary complex.

CONCLUSIONS: This study reveals the new role of CSDE1 in enhancing resistance to genotoxic drugs, and the detailed zipper-like cross ternary structural of CSDE1. It provides a new strategy for enhancing genotoxic drugs sensitivity.

PMID:40398074 | DOI:10.1016/j.drup.2025.101249

Pharmacogenomics. 2025 May 21:1-14. doi: 10.1080/14622416.2025.2504862. Online ahead of print.

ABSTRACT

BACKGROUND: Pharmacogenetics uses individuals' genetic profiles to optimize drug treatment and prevent adverse reactions. One strategy to obtain information on pharmacogenes is to reuse sequencing data for a pharmacogenetic passport, providing information preemptively to healthcare professionals for utilization throughout a patient's lifetime.

AIM: To explore stakeholders' perceived barriers and facilitators and future perspectives of implementing a pharmacogenetic passport based on experiences from reusing sequencing data, in a Dutch University Medical Center.

METHODS: Semi-structured interviews were conducted among 21 stakeholders. Interviews were analyzed using thematic analysis, and themes were grouped under the constructs of structure, culture, and practice.

RESULTS: Perceived implementation barriers included inadequate data infrastructure, limited knowledge of pharmacogenetics, lack of (visible) guidelines, unequal access, unclear division of tasks and unclear procedures, and other hospital priorities. Perceived facilitators included the ease, efficiency, and affordability to obtain pharmacogenetic test results from reused sequencing data, stakeholders' positive attitudes about patient impacts of a pharmacogenetic passport, and that patient control of their health data is provided.

CONCLUSION: When considering the implementation of a pharmacogenetic passport, strategies can be developed to diminish barriers and strengthen facilitators. It is important to focus on data infrastructure, (visibility of) guidelines, clear division of tasks, and pharmacogenetic education.

PMID:40396487 | DOI:10.1080/14622416.2025.2504862

Autophagy Rep. 2022 Mar 22;1(1):47-50. doi: 10.1080/27694127.2022.2047268. eCollection 2022.

ABSTRACT

Dysfunction of macroautophagy/autophagy has been demonstrated to contribute to multiple fibrotic diseases. In a recent study, we show that lnc-PFAR, a fibrotic-related lncRNA, is upregulated in human chronic pancreatitis tissues and mouse models and can serve as a biomarker for pancreatic fibrosis detection in the clinic. Indeed, our data reveal that lnc-PFAR affects autophagy activation through controlling MIR141 maturation. Furthermore, lnc-PFAR binds with pre-MIR141 and suppresses MIR141 maturation, which releases RB1CC1 and induces autophagy activation. We address a novel perspective of lnc-PFAR-pre-MIR141-RB1CC1 axis in autophagy and pancreatic fibrosis, and discover a prospective pharmacogenomic biomarker for chronic pancreatitis. Our findings identify a potential therapeutic target in pancreatic fibrosis and provide more evidence to consider autophagy inhibitors for further application.

PMID:40396022 | PMC:PMC11864614 | DOI:10.1080/27694127.2022.2047268

J Clin Transl Sci. 2025 Apr 11;9(1):e89. doi: 10.1017/cts.2025.67. eCollection 2025.

ABSTRACT

OBJECTIVE: We sought to describe perspectives among Black nursing professionals and community leaders regarding the return of genetic test results, and place perspectives into context with aggregated findings in the All of Us Research Program's Data Browser.

METHODS: Semi-structured, virtual interviews were held with adults (≥18 years of age) self-identifying as Black. A 2-step thematic analysis process was used to assess interviewee perspectives with (sub)themes identified in the literature across two topics: drug/medication response and hereditary disease risk. Themes were placed into context with Data Browser content, focusing on genes and their respective alleles with frequencies ≥0.10 in African ancestry populations in All of Us.

RESULTS: Interviewee perspectives aligned with previously identified major themes in the literature (motivations to engage or disengage; integrating research and care), with five (5) subthemes emerging across major themes. Seven (7) alleles were observed with frequencies ≥0.10 for three (3) pharmacogenomic (PGx) biomarkers in the Data Browser for African ancestry populations: CYP2C19 (SNV, 10-94761900-C-T; SNV,10-94775367-A-G; SNV 10-94781859-G-A), DPYD (SNV, 1-97883329-A-G; SNV, 1-97515839-T-C), UGT1A1 (insertion, 2-233760233-C-CAT; SNV, 2-233757136-G-A). Four (4) alleles were observed with frequencies ≥0.10 for three (3) genes implicated in hereditary disease risk, two of which contemporaneously hold PGx implications for African ancestry populations: CACNA1S (PGx, SNV, 1-201112815-C-T; SNV, 1-201110107-C-T), SCN5A (no PGx, SNV, 3-38603929-T-C), TP53 (PGx, SNV, 17-7676154-G-C).

CONCLUSIONS: Our findings convey important clinical and translational science considerations for individuals and community leaders of African ancestry and researchers seeking reputable, publicly available information to understand, communicate, and act on genomic findings.

PMID:40395398 | PMC:PMC12089846 | DOI:10.1017/cts.2025.67

Cancer Gene Ther. 2025 May 21. doi: 10.1038/s41417-025-00914-8. Online ahead of print.

ABSTRACT

Glioblastoma (GBM) is one of the most aggressive primary brain tumors, characterized by extensive neovascularization and a highly infiltrative phenotype. Anti-vascular endothelial growth factor (VEGF) therapies, such as bevacizumab, have emerged as significant adjunct treatments for recurrent and high-grade GBM by targeting abnormal tumor vasculature. Despite demonstrated benefits in slowing tumor progression and alleviating peritumoral edema, these agents are associated with notable vascular complications, including hemorrhagic and ischemic events. Hemorrhagic complications range from minor intracranial microbleeds to life-threatening intracranial hemorrhages (ICH). Mechanistically, VEGF inhibition disrupts endothelial function and decreases vascular integrity, making already fragile tumor vessels prone to rupture. Glioma-associated vascular abnormalities, including disorganized vessel networks and compromised blood-brain barrier, further exacerbate bleeding risks. Concurrent use of anticoagulants, hypertension, and genetic predispositions also significantly elevate hemorrhagic risk. In addition to bleeding complications, ischemic events are increasingly recognized in patients receiving anti-VEGF therapy. Reduced vascular endothelial cells (ECs) survival and diminished microvascular density can lead to regional hypoperfusion and potentially precipitate cerebrovascular ischemia. Impaired vasoreactivity and increased vascular resistance, often accompanied by endothelial dysfunction and microvascular rarefaction, contribute to elevated stroke and arterial thrombotic risk. This review synthesizes current evidence on hemorrhagic and ischemic complications arising from anti-VEGF therapy in GBM. We discuss underlying pathophysiological mechanisms, risk factors, and clinically relevant biomarkers, as well as prevention strategies-such as rigorous blood pressure (BP) control and close monitoring of coagulation parameters. We further highlight emerging avenues in precision medicine, including pharmacogenomic profiling and targeted adjunct agents that protect vascular integrity, aimed at mitigating adverse vascular events while preserving therapeutic efficacy. The goal is to optimize outcomes for GBM patients by balancing the benefits of anti-VEGF therapy with vigilant management of its inherent vascular risks. In addition, this study analyzes existing clinical trials of the use of anti-VEGF drugs in the treatment of gliomas using data from the clinicaltirals.gov website.

PMID:40394233 | DOI:10.1038/s41417-025-00914-8

PLoS One. 2025 May 20;20(5):e0324360. doi: 10.1371/journal.pone.0324360. eCollection 2025.

ABSTRACT

BACKGROUND: Dolutegravir (DTG)-based antiretroviral therapy has demonstrated superior efficacy, tolerability, and durability when compared to other HIV treatment regimens. However, monitoring viral kinetics is critical for determining treatment efficacy and making sound judgments. The purpose of this study was to assess viral kinetics in people living with HIV (PLWH) on DTG-based ART and identify characteristics related to virologic response in the Cape Coast Metropolis, Ghana.

METHODS: Among people living with HIV (PLWH) attending HIV clinics between January 2020 and December 2023, a prospective and retrospective analysis of viral kinetics and clinical data were carried out. Data on viral loads, clinical laboratory results, ART regimen, and sociodemographic data were gathered. Viral loads analysis was undertaken using the COBAS AmpliPrep/COBAS TaqMan HIV-1 test, v2.0. Univariate and multivariate analyses were carried out to assess the variables related to virologic response.

RESULTS: Complete data was obtained for a total of 902 PLWH in this study. The average age was 45 ± 15.30 years, and 72.62% were female. The majority, 89.02% (835/902), had been on the DTG+3TC+TDF regimen. Over 60% had undetectable viral loads (<50 copies/mL). Univariate analysis shows a significant relationship between gender and virologic response, with females having a lower likelihood of virologic failure (OR: 0.60, 95% CI: 0.39-0.93, p-value = 0.024). In multivariate analysis, the duration of ART had various relationships with virologic response, with the odds ratio for two years reaching near significance (OR: 1.88, 95% CI: 0.98-3.59, p = 0.057). PLWH with viral loads >1000 copies/mL were 11.20% (101/902) while viral suppression, which was at detectable limits (>50 - ≤ 1000 cp/mL), was 13.08% (118/902) showing high rates of viral suppression.

CONCLUSION: The presence of virologic failures was of concern despite the high rates of viral suppression that DTG-based ART demonstrated. Undetectable viral suppression was higher than detectable viral suppression. Regular monitoring of viral kinetics, adherence, and comorbidities is essential to meeting the United Nations program on HIV/AIDS (UNAIDS) 95-95-95 targets and providing efficient therapeutic approaches for PLWH.

PMID:40392867 | DOI:10.1371/journal.pone.0324360

Clin Pharmacol Ther. 2025 May 20. doi: 10.1002/cpt.3712. Online ahead of print.

ABSTRACT

The Food and Drug Administration (FDA) Table of Inhibitors and the Flockhart Table™ are important references for identifying CYP2C19 inhibitors. Accurate inhibitor classification is essential for evaluating phenoconversion and managing drug-drug interactions. The objective of this study was to assess the concordance between inhibitor classifications according to the FDA and Flockhart tables and pharmacokinetic data from the primary literature. A scoping review of PubMed, product labels, and the Drug Interactions Database (DIDB®) up to April 2024 was conducted. Inhibitor-substrate pairs (e.g., fluoxetine-omeprazole) were assigned literature-reported classifications (i.e., weak, moderate, or strong) based on pharmacokinetic data. Concordance between literature-reported and listed classifications was evaluated. Of 90 inhibitor-substrate pairs identified, 66% involved sensitive substrates, which were the focus of our primary analysis. Among sensitive inhibitor-substrate pairs, 36% of FDA-listed and 45% of Flockhart-listed classifications were concordant with the literature. CYP2C19 phenotype appeared to impact concordance, with greater concordance among normal metabolizers for both FDA-listed (42%) and Flockhart-listed (50%) classifications. Steady state status and dosing also appeared to affect concordance. Discrepancies between listed and literature-reported classifications led to the following recommendations: (1) upgrade fluoxetine from moderate to strong in the Flockhart Table™, (2) upgrade fluconazole from moderate to strong in the Flockhart Table™, (3) downgrade omeprazole (and esomeprazole) from moderate to weak in the Flockhart Table™, and (4) include footnotes describing dose-dependent inhibition for fluvoxamine and fluconazole in both tables. These recommendations aim to improve the accuracy of CYP2C19 inhibitor classifications and the clinical utility of these tables.

PMID:40391533 | DOI:10.1002/cpt.3712