Psychol Med. 2025 May 22;55:e158. doi: 10.1017/S0033291725001096.

ABSTRACT

BACKGROUND: Precise stratification of patients into homogeneous disease subgroups could address the heterogeneity of phenotypes and enhance understanding of the pathophysiology underlying specific subtypes. Existing literature on subtyping patients with major depressive disorder (MDD) mainly utilized clinical features only. Genomic and imaging data may improve subtyping, but advanced methods are required due to the high dimensionality of features.

METHODS: We propose a novel disease subtyping framework for MDD by integrating brain structural features, genotype-predicted expression levels in brain tissues, and clinical features. Using a multi-view biclustering approach, we classify patients into clinically and biologically homogeneous subgroups. Additionally, we propose approaches to identify causally relevant genes for clustering.

RESULTS: We verified the reliability of the subtyping model by internal and external validation. High prediction strengths (PS) (average PS: 0.896, minimum: 0.854), a measure of generalizability of the derived clusters in independent datasets, support the validity of our approach. External validation using patient outcome variables (treatment response and hospitalization risks) confirmed the clinical relevance of the identified subgroups. Furthermore, subtype-defining genes overlapped with known susceptibility genes for MDD and were involved in relevant biological pathways. In addition, drug repositioning analysis based on these genes prioritized promising candidates for subtype-specific treatments.

CONCLUSIONS: Our approach successfully stratified MDD patients into subgroups with distinct clinical prognoses. The identification of biologically and clinically meaningful subtypes may enable more personalized treatment strategies. This study also provides a framework for disease subtyping that can be extended to other complex disorders.

PMID:40400388 | DOI:10.1017/S0033291725001096

J Biomed Sci. 2025 May 21;32(1):50. doi: 10.1186/s12929-025-01137-7.

ABSTRACT

BACKGROUND: Type 2 diabetes is an increasingly prevalent metabolic disorder with moderate to high heritability. Glycemic indices are crucial for diagnosing and monitoring the disease. Previous genome-wide association study (GWAS) have identified several risk loci associated with type 2 diabetes, but data from the Taiwanese population remain relatively sparse and primarily focus on type 2 diabetes status rather than glycemic trait levels.

METHODS: We conducted a comprehensive genome-wide meta-analysis to explore the genetics of glycemic traits. The study incorporated a community-based cohort of 145,468 individuals and a hospital-based cohort of 35,395 individuals. The study integrated genetics, transcriptomics, biological pathway analyses, polygenic risk score calculation, and drug repurposing for type 2 diabetes.

RESULTS: This study assessed hemoglobin A1c and fasting glucose levels, validating known loci (FN3K, SPC25, MTNR1B, and FOXA2) and discovering new genes, including MAEA and PRC1. Additionally, we found that diabetes, blood lipids, and liver- and kidney-related traits share genetic foundations with glycemic traits. A higher PRS was associated with an increased risk of type 2 diabetes. Finally, eight repurposed drugs were identified with evidence to regulate blood glucose levels, offering new avenues for the management and treatment of type 2 diabetes.

CONCLUSIONS: This research illuminates the unique genetic landscape of glucose regulation in Taiwanese Han population, providing valuable insights to guide future treatment strategies for type 2 diabetes.

PMID:40399988 | DOI:10.1186/s12929-025-01137-7

Sci Rep. 2025 May 21;15(1):17704. doi: 10.1038/s41598-025-00547-9.

ABSTRACT

This study explores the efficacy of glibenclamide, a KATP channel inhibitor, for treating Cantú syndrome (CS), a genetic disorder characterized by hypertrichosis and cardiovascular abnormalities. Treatment with glibenclamide for Cantú syndrome has only been reported in a single case report. In this study, we tested this repurposed drug in both a zebrafish model and an open-label trial with CS patients. CS zebrafish embryos, created using CRISPR/Cas9, were treated with glibenclamide. Their cardiac function was assessed using high-speed imaging. In the trial part of the study, four adults with CS used 2.5 mg glibenclamide daily for 8 months. Hypertrichosis, cardiac function, and edema were evaluated and glucose levels were monitored continuously. In the zebrafish model of CS glibenclamide reversed cardiac abnormalities. However, in the clinical trial, the effects on hypertrichosis were mixed, and there were no significant changes in cardiac phenotype or leg edema. One participant reported reduced facial erythema and puffiness, which relapsed post-trial. The treatment was generally safe, with multiple instances of level 1 hypoglycemia but no severe adverse events. In conclusion, glibenclamide can reverse cardiac abnormalities in a CS zebrafish model. Its effect on hypertrichosis and cardiovascular features in humans with CS are unclear and dosage increases are challenging due to hypoglycemia, which is important knowledge for treatment considerations in this rare genetic syndrome.Trial registration: EudraCT Number 2019-004651-36. Date of first registration 21/05/2021.

PMID:40399303 | DOI:10.1038/s41598-025-00547-9

Nutr Res Rev. 2025 May 21:1-54. doi: 10.1017/S0954422425100061. Online ahead of print.

ABSTRACT

To achieve infectivity, severe acute respiratory syndrome coronavirus 2 (SARS-CoV2), the virus responsible for COVID-19, must first traverse the upper respiratory tract mucosal barrier. Once infection is established, the cascading complexities of the pathophysiology of COVID-19 makes intervention extremely difficult. Thus, enhancing the defensive properties of the mucosal linings of the upper respiratory tract may reduce infection by SARS-CoV2 and indeed by other viruses such as influenza, which have been responsible for the two major pandemics of the last century. In this review we summarise potential opportunities for foods and nutrients to promote an adequate mucosal immune preparedness with an aim to assist protection against infection by SARS-CoV-2; to maximise the mucosal vaccination (IgA inducing) response to existing systemic vaccines; and to play a role as adjuvants to intranasal vaccines. We identify opportunities for vitamins A, and D, zinc, probiotics, bovine colostrum and resistant starch to promote mucosal immunity and enhance the mucosal response to systemic vaccines, and for vitamin A to also improve the mucosal response to intranasal vaccination. It is possible that an entirely different virus may in the future, by way of convergent evolution, utilise a similar upper respiratory tract infection pathway. A greater research focus on mucosal lymphoid immune protection in partnership with nutrition would result in greater preparedness for such an event.

PMID:40396597 | DOI:10.1017/S0954422425100061

Brain Commun. 2025 May 9;7(3):fcaf184. doi: 10.1093/braincomms/fcaf184. eCollection 2025.

ABSTRACT

Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative condition for which novel disease modifying therapies are urgently needed. Given the increasing bottlenecks in drug discovery pipelines, repurposing existing drugs for ALS may represent a path to expedite translation and improve disease outcomes. However, ALS is a heterogeneous disease for which the aetiology remains poorly characterized, complicating efforts to effectively repurpose drugs. We propose that the polygenic architecture of ALS genetic liability, which ranges from ultra-rare, high-impact variation to common frequency loci of small-individual effect, could be leveraged to prioritize drug repurposing candidates which are more generalizable to the ALS clinical population. Here, we utilize common and rare frequency ALS genetic risk with a novel approach to uncover therapeutic classes that may be prospective repurposing opportunities in ALS. The common variant-led analyses integrated both positional-based and functional gene-based tests on SNP-genotype data from a genome-wide association study of ALS and implicated mitogen-activated protein kinase signalling related downregulation through B-Raf inhibitors as a prospective target for repurposing. The rare variant-led approaches leveraged rare variant burden testing of exonic variation on whole genome-sequencing data from a subset of the common variant genome-wide association study cohort and prioritized B-vitamin related candidates, such as cobalamin and niacin. Clinical characterization of these putative repurposing opportunities revealed genetic support to existing biology for which related compounds are actively proceeding through ALS clinical studies. Moreover, leveraging transcriptomic data from ALS derived cell lines carrying a selection of pathogenic variants in genes that cause familial forms of ALS (C9orf72, SOD1, FUS and TARDBP) suggested that the action of B-Raf inhibitors may be of particular relevance to C9orf72 carriers, whilst the signal for B-vitamin signalling related targets was strongest in SOD1 carriers. In summary, we demonstrate the importance of considering the therapeutic actionability of both common and rare-variant mediated risk for ALS given the immense biological heterogeneity of this disorder. Future pre-clinical and clinical studies are now warranted to further characterize the tractability of these prioritized compounds.

PMID:40395632 | PMC:PMC12089939 | DOI:10.1093/braincomms/fcaf184

Int J Biol Macromol. 2025 May 18:144106. doi: 10.1016/j.ijbiomac.2025.144106. Online ahead of print.

ABSTRACT

Melioidosis, also known as Whitmore's disease, is caused by the deadly pathogen Burkholderia pseudomallei and remains a significant global health concern, particularly in South Asia. The disease is contracted through exposure to contaminated soil, water, air, and food. Infected individuals often present with abscesses in internal organs such as the lungs, spleen, and liver, and in soft tissues, with severe cases leading to septic shock and acute pneumonia. The rising incidence and mortality rates, coupled with B. pseudomallei's ability to form biofilms and develop resistance to antibiotics like cephalosporins, make treatment increasingly challenging. This highlights the urgent need for novel therapeutic approaches. D-Alanine-D-Alanine ligase (Ddl), a crucial enzyme involved in the final stage of bacterial cell wall synthesis, which protects the pathogen from the hostile cellular environment of the host. While many bacteria have two isoforms of this enzyme, B. pseudomallei possesses only the DdlB isoform, presenting a significant vulnerability. Our study represents the first successful attempt to target DdlB through a combination of molecular docking and molecular dynamics simulations. These investigations provide strong evidence that Conivaptan acts as an effective inhibitor of DdlB, offering a novel therapeutic approach for combating melioidosis.

PMID:40393604 | DOI:10.1016/j.ijbiomac.2025.144106

ChemMedChem. 2025 May 20:e202500117. doi: 10.1002/cmdc.202500117. Online ahead of print.

ABSTRACT

Cathepsins are lysosomal proteases with well-documented roles in the progression of various cancers. Among them, cathepsin B (CTSB), a cysteine protease, is notably involved in the development of breast cancer and neuroblastoma. In this study, we explored the potential of darifenacin as a repurposed therapeutic targeting CTSB, using molecular docking and simulation studies which demonstrated a significantly lower binding energy against CTSB (-456.268 kJ/mol) compared to its known inhibitor, aloxistatin (-36.601 kJ/mol). The cytotoxic efficacy of darifenacin was evaluated on IMR-32 (neuroblastoma) and MCF-7 (breast cancer) cells, yielding half-maximal inhibitory concentrations (IC50) of 38.14 and 39.96 µM, respectively. Darifenacin effectively inhibited CTSB enzymatic activity by ~1.82 and ~1.75-fold in IMR-32 and MCF-7 cells, respectively, triggering intracellular ROS generation, mitochondrial membrane potential depolarization, and cell cycle arrest. These events culminated in apoptosis-mediated cell death, with apoptotic populations reaching 51.39% in IMR-32 and 40.6% in MCF-7 cells, respectively. Additionally, darifenacin disrupted lipid droplet accumulation, cellular migration, and colony and sphere-forming abilities in both cell lines. Overall, this study identifies darifenacin as a promising therapeutic agent against CTSB-driven cancer progression.

PMID:40393029 | DOI:10.1002/cmdc.202500117

PLoS One. 2025 May 20;20(5):e0323761. doi: 10.1371/journal.pone.0323761. eCollection 2025.

ABSTRACT

Parkinson's disease (PD) is an increasingly prevalent neurologic condition for which symptomatic, but not preventative, treatment is available. Drug repurposing is an innovate drug discovery method that uncovers existing therapeutics to treat or prevent conditions for which they are not currently indicated, a method that could be applied to incurable diseases such as PD. A knowledge graph artificial intelligence prediction system was used to select potential drugs that could be used to treat or prevent PD, and amphetamine was identified as the strongest candidate. Retrospective cohort analysis on a large, electronic health record database of deidentified patients with attention deficit hyperactive disorder (the main diagnosis for which amphetamine is prescribed) revealed a significantly reduced hazard of developing PD in patients prescribed amphetamine versus patients not prescribed amphetamine at 2, 4, and 6 years: Hazard Ratio (95% Confidence Interval) = 0.59 (0.36, 0.98), 0.63 (0.42, 0.93), and 0.55 (0.38, 0.79). Pathway enrichment analysis confirmed that amphetamine targets many of the biochemical processes implicated in PD, such as dopaminergic synapses and neurodegeneration. Together, these observational findings suggest that therapeutic and legal amphetamine use may reduce the risk of developing PD, in contrast to previous work that found the inverse relationship in patients using amphetamine recreationally.

PMID:40392924 | DOI:10.1371/journal.pone.0323761

IEEE J Biomed Health Inform. 2025 May 20;PP. doi: 10.1109/JBHI.2025.3571801. Online ahead of print.

ABSTRACT

Drug repositioning, which identifies new therapeutic potential of approved drugs, is pivotal in accelerating drug discovery. Recently, growing efforts are devoted to applying graph neural networks (GNNs) for effectively modeling drug-disease associations (DDAs). However, current GNN-based methods are generally designed for unsigned graphs and fail to gain complementary insights provided by negative links. Despite the proposal of sign-aware GNNs in general fields, there exist two intractable challenges when indiscriminately deploying prior solutions into drug repositioning. (i) How to explicitly connect the nodes within the same set (disease-disease and drug-drug)? (ii) How to design the contrastive learning objective for signed graphs? To this end, we propose a novel sign-aware graph contrastive learning approach, namely SIGDR, which takes both the positive and negative links from signed biological networks into consideration to identify underlying DDAs. To handle the first challenge, we measure the drug and disease similarity and form signed unipartite graphs according to similarity scores. For the second challenge, a signed bipartite graph is then constructed from the annotated DDA dataset. Through dividing above obtained signed graphs into positive and negative subgraphs respectively, we devise the inter-view contrastive learning auxiliary task to enhance the consistency of node representations derived from partitioned subgraphs with the same link type. Extensive experiments conducted on three benchmarks under 10-fold cross-validation demonstrate the model effectiveness. Source code and datasets are available at https://github.com/OleCui/paper_SIGDR.

PMID:40392637 | DOI:10.1109/JBHI.2025.3571801

J Neurooncol. 2025 May 20. doi: 10.1007/s11060-025-05082-1. Online ahead of print.

ABSTRACT

The presence of hormonal receptors in meningiomas has been known for decades. More recently, evidence has shown increased prevalence of meningiomas in patients taking certain types of hormonal treatments, such as oral contraceptives, progestins or hormone replacement therapy. Epidemiological evidence suggests that patients undergoing hormonal therapy harbor higher mutational rates of the oncogene PIK3CA. Due to the relative paucity of literature describing the intersection of hormone therapy and mutated PIK3CA pathways in meningioma, we have conducted a narrative review on this topic. Similarly, the clinical trial landscape for hormonal therapies for meningioma currently focuses on somatostatin receptor-targeted therapies and peptide receptor radionucleotide therapy, and the PIK3CA-hormonal signaling axis has not been explicitly targeted. Given the role of PIK3CA mutations in promoting cancer progression in other hormone-sensitive tumors, such as breast and prostate cancer, exploring this axis could inform drug repurposing including hormonal therapy specifically for these tumors.

PMID:40392516 | DOI:10.1007/s11060-025-05082-1

Bioinformatics. 2025 May 20:btaf311. doi: 10.1093/bioinformatics/btaf311. Online ahead of print.

ABSTRACT

MOTIVATION: Single-cell and spatial transcriptomics provide unprecedented insight into diseases. Pharmacotranscriptomic approaches are powerful tools that leverage gene expression data for drug repurposing and discovery. Multiple databases attempt to connect human cellular transcriptional responses to small molecules for use in transcriptome-based drug discovery efforts. However, preclinical research often requires in vivo experiments in non-human species, which makes utilizing such valuable resources difficult. To facilitate both human orthologous conversion of non-human transcriptomes and the application of pharmacotranscriptomic databases to pre-clinical research models, we introduce OrthologAL. OrthologAL interfaces with BioMart to access different gene sets from the Ensembl database, allowing for ortholog conversion without the need for user-generated code.

RESULTS: Researchers can input their single-cell or other high-dimensional gene expression data from any species as a Seurat object, and OrthologAL will output a human ortholog-converted Seurat object for download and use. To demonstrate the utility of this application, we tested OrthologAL using single-cell, single-nuclei, and spatial transcriptomic data derived from common preclinical models, including patient-derived orthotopic xenografts of medulloblastoma, and mouse and rat models of spinal cord injury. OrthologAL can convert these data types efficiently to that of corresponding orthologs while preserving the dimensional architecture of the original non-human expression data. OrthologAL will be broadly useful for the simple conversion of Seurat objects and for applying preclinical, high-dimensional transcriptomics data to functional human-derived small molecule predictions.

AVAILABILITY: OrthologAL is available for download as an R package with functions to launch the Shiny GUI at https://github.com/AyadLab/OrthologAL or via Zenodo at https://doi.org/10.5281/zenodo.15225041. The medulloblastoma single-cell transcriptomics data were downloaded from the NCBI Gene Expression Omnibus with the identifier GSE129730. 10X Visium data of medulloblastoma PDX mouse models from Vo et al. were acquired by contacting the authors, and the raw data are available from ArrayExpress under the identifier E-MTAB-11720. The single-cell and single-nuclei transcriptomics data of rat and mouse spinal-cord injury were acquired from the Gene Expression Omnibus under the identifiers GSE213240 and GSE234774.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:40392208 | DOI:10.1093/bioinformatics/btaf311

Future Med Chem. 2025 May 20:1-17. doi: 10.1080/17568919.2025.2507564. Online ahead of print.

ABSTRACT

The Janus kinase (JAK)/Signal Transducer and Activator of Transcription (STAT) signaling pathway is essential for controlling immune function, blood cell formation, and cell growth. Dysregulation of this pathway is implicated in various diseases, including hematologic malignancies, autoimmune disorders, and chronic inflammatory conditions. This review provides a comprehensive overview of the structural and functional aspects of JAK/STAT signaling, with a particular focus on the role of JAK2. This manuscript explores the primary regulators of the JAK/STAT pathway, such as Suppressors Of Cytokine Signaling (SOCS), Protein Inhibitors of Activated STATs (PIAS), and Protein Tyrosine Phosphatases (PTPs), which play a crucial role in maintaining cellular balance and stability. Additionally, the therapeutic landscape of JAK2 inhibitors is explored, covering both approved and investigational drugs, including their mechanisms of action, efficacy, and safety profiles. Emerging strategies such as drug repositioning using computational approaches and experimental validation are also highlighted. By integrating insights from molecular docking studies, machine learning models, and kinase assays, this review emphasizes the potential of JAK2 inhibitors in disease management.

PMID:40392133 | DOI:10.1080/17568919.2025.2507564

J Antimicrob Chemother. 2025 May 20:dkaf157. doi: 10.1093/jac/dkaf157. Online ahead of print.

ABSTRACT

BACKGROUND: Bacterial vaginosis (BV) is associated with significant reproductive health risks and high recurrence rates after standard antibiotic treatment. Sulfadoxine/pyrimethamine, an antimalarial drug, demonstrated unexpected clearance of BV in clinical trials, suggesting potential antimicrobial effects. Drug repurposing, which leverages existing drugs for new therapeutic applications, offers a promising approach to address the challenges of antimicrobial resistance and high recurrence rates in BV.

OBJECTIVE: To determine the in vitro activity of sulfadoxine/pyrimethamine and its components, sulfadoxine and pyrimethamine, on key species associated with BV.

METHODS: Minimum inhibitory concentration (MIC) and minimum bactericidal concentration were determined for sulfadoxine/pyrimethamine (20:1 ratio), sulfadoxine, pyrimethamine, and standard-of-care antibiotics, metronidazole and clindamycin, against BV-associated species (Gardnerella spp., Fannyhessea vaginae, Prevotella bivia) and Lactobacillus crispatus (vaginal health marker). Gardnerella biofilms were also exposed to sulfadoxine/pyrimethamine, pyrimethamine, or metronidazole, and biofilm biomass and biofilm cells culturability were assessed.

RESULTS: Sulfadoxine had no effect, while pyrimethamine inhibited all Gardnerella strains with MIC values ranging from 0.125 to 4 mg/L, lower than MICs observed for metronidazole (2-128 mg/L). Pyrimethamine also outperformed metronidazole in inhibiting biofilm mass accumulation and reducing biofilm culturable cells in 3/4 Gardnerella strains. Sulfadoxine/pyrimethamine presented lower MICs than metronidazole for 5/8 Gardnerella strains. Sulfadoxine, pyrimethamine, and sulfadoxine/pyrimethamine showed no activity against other BV-associated species or L. crispatus.

CONCLUSIONS: These findings suggest that pyrimethamine (and sulfadoxine/pyrimethamine) could be promising alternative or adjuvant therapies for BV, warranting further clinical trials.

PMID:40391646 | DOI:10.1093/jac/dkaf157

J Genet Eng Biotechnol. 2025 Jun;23(2):100485. doi: 10.1016/j.jgeb.2025.100485. Epub 2025 Mar 29.

ABSTRACT

INTRODUCTION: Warts are dermal disorders resulting from HPV infection and can be transmitted by direct contact. Existing treatment approaches, such as topical treatment with salicylate, have low efficiency and demonstrate side effects. Thus, the discovery of potent drug treatments for skin warts is necessary. Here we propose the use of alternative medications for the possible treatment of skin warts with the help of comparative transcriptome analysis and drug repurposing approaches.

METHODS: Gene expression datasets related to HPV-induced warts and cervical cancer were extracted from the GEO database. Differentially expressed genes (DEGs) were identified using DESeq2 in the Galaxy database. Upregulated DEGs were assessed for druggability using the DGIdb tool. Gene ontology and enrichment analysis were performed to investigate the characteristics of druggable DEGs. A molecular docking virtual screening was conducted using PyRx software to identify potential therapeutic targets for skin warts. The interactions between selected drug candidates and the target protein were analyzed using the BIOVIA Discovery Studio. The physicochemical characteristics of potential pharmaceuticals were evaluated using the SwissADME database. Finally, the molecular dynamics (MD) simulation was performed to validate the stability and dynamic behavior of drug-protein interactions.

RESULTS: Based on the findings from gene expression profiling, Integrin Alpha-X (ITGAX, CD11c) has been identified as a candidate protein that is significantly upregulated in individuals afflicted with skin warts. Integrin Alpha-X plays a crucial role in mediating intercellular interactions during inflammatory processes and notably enhances the adhesion and chemotactic activity of monocytes. Through molecular docking, MD, and physicochemical analyses, it has been demonstrated that dihydroergotamine effectively inhibits the ITGAX protein, suggesting its potential as a therapeutic agent for the management of skin warts.

CONCLUSION: Dihydroergotamine can be repurposed as a potential drug in the treatment of skin warts by targeting Integrin Alpha-X protein.

PMID:40390498 | DOI:10.1016/j.jgeb.2025.100485

J Genet Eng Biotechnol. 2025 Jun;23(2):100502. doi: 10.1016/j.jgeb.2025.100502. Epub 2025 May 12.

ABSTRACT

Insomnia is a prevalent sleep disorder characterized by difficulty initiating or maintaining sleep, leading to severe health complications, increased mortality, and substantial socioeconomic burdens. Despite therapeutic advancements, effective pharmacological interventions remain limited, necessitating alternative approaches for drug discovery. This study aimed to identify potential therapeutic targets for insomnia by integrating gene network analysis, genomic data, and bioinformatics-driven drug repurposing strategies, aligning with the United Nations' Sustainable Development Goal (SDG) 3: Good Health and Well-being. Insomnia-associated Single Nucleotide Polymorphisms (SNPs) were retrieved from the GWAS catalog, yielding 3,952 loci. Insomnia risk genes were identified by linking these loci to proximal SNPs (r2 ≥ 0.8) in Asian populations using HaploReg v4.2, resulting in 1,765 candidate genes. A bioinformatics pipeline incorporating ten functional annotations and drug-gene interaction was employed to prioritize gene targets and identify novel repurposed drugs with potential biological relevance to insomnia. Drug-Gene Interaction Database (DGIdb) analysis identified seven druggable targets among 27 biologically significant insomnia risk genes, corresponding to 12 existing drugs. Notably, NRXN1 emerged as a highly promising target due to its strong functional annotation score and its known interaction with Duloxetine hydrochloride and nicotine polacrilex. This study underscores the potential of bioinformatics-driven gene network analysis in identifying drug repurposing candidates for insomnia. Further experimental validation is warranted to elucidate the therapeutic mechanisms of NRXN1 modulation in insomnia treatment.

PMID:40390493 | DOI:10.1016/j.jgeb.2025.100502

J Biomed Inform. 2025 May 17:104843. doi: 10.1016/j.jbi.2025.104843. Online ahead of print.

ABSTRACT

Drug repositioning, pivotal in current pharmaceutical development, aims to find new uses for existing drugs, offering an efficient and cost-effective path to drug discovery. In recent years, graph neural network-based deep learning methods have achieved significant success in drug repositioning tasks. However, few studies have analyzed the characteristics of datasets to mitigate potential data biases. In this paper, we analyzed three commonly used drug repositioning datasets and identified a consistent characteristic among them: a trend of node polarization, characterized by the presence of popular entities (those commonly occurring and extensively associated) and long-tail entities (those appearing less frequently with fewer associations). Based on this finding, we propose a deep learning framework with a debiasing mechanism, called DRDM. The framework excels in addressing popular entities' biases, which often overshadow the subtle patterns in long-tail entities-key for novel insights. DRDM dynamically adjusts association weights during training, enhancing long-tail entity representation and reducing bias. In addition, we employ dual-view contrastive learning to provide rich supervisory signals, thereby further enhancing the model's robustness. We conducted experiments with our method on these three datasets, and the results demonstrated that our approach exhibits strong competitiveness compared to competing models. Case studies further highlighted the potential of the model in practical applications, which could provide new insights for future drug discovery.

PMID:40389101 | DOI:10.1016/j.jbi.2025.104843

Medicine (Baltimore). 2025 May 16;104(20):e42411. doi: 10.1097/MD.0000000000042411.

ABSTRACT

Currently, there remains a significant gap in effective pharmacologic interventions for neonatal respiratory distress syndrome (NRDS). To address this critical unmet medical need, we aimed to systematically identify novel therapeutic targets and preventive strategies through comprehensive integration and analysis of multiple publicly accessible datasets. In this study, we employed an integrative approach combining druggable genome data, cis-expression quantitative trait loci (cis-eQTL) from human blood and lung tissues, and genome-wide association study summary statistics for neonatal respiratory distress. We performed two-sample Mendelian randomization (TSMR) analysis to investigate potential causal relationships between druggable genes and neonatal respiratory distress. To strengthen causal inference, we performed Bayesian co-localization analyses. Furthermore, we conducted phenome-wide Mendelian randomization (Phe-MR) to systematically evaluate potential side effects and alternative therapeutic indications associated with the identified candidate drug targets. Finally, we interrogated existing drug databases to identify actionable pharmacological agents targeting the identified genes. All 3 genes (LTBR, NAAA, CSNK1G2) were analyzed by Bayesian co-localization (PH4 > 75%). CSNK1G2 (lung eQTL, odds ratio [OR]: 0.419, 95% CI: 0.185-0.948, P = .037; blood eQTL, OR: 4.255, 95% CI: 1.346-13.455, P = .014; Gtex whole blood eQTL, OR: 4.966, 95% CI: 1.104-22.332, P = .037). LTBR (lung eQTL, OR: 0.550, 95% CI: 0.354-0.856, P = .008; blood eQTL, OR: 0.347, 95% CI: 0.179-0.671, P = .002; Gtex whole blood eQTL, OR: 0.059, 95% CI: 0.0.007-0.478, P = .008). NAAA (lung eQTL, OR: 0.717, 95% CI: 0.555-0.925, P = .011; Gtex whole blood eQTL, OR: 0.660, 95% CI: 0.476-0.913, P = .012). Drug repurposing analyses support the possibility that etanercept and asciminib hydrochloride may treat neonatal respiratory distress by activating LTBR. This study demonstrated that LTBR, NAAA, and CSNK1G2 may serve as promising biomarkers and therapeutic targets for NRDS.

PMID:40388790 | DOI:10.1097/MD.0000000000042411

Circulation. 2025 May 20;151(20):1449-1450. doi: 10.1161/CIRCULATIONAHA.125.074556. Epub 2025 May 19.

NO ABSTRACT

PMID:40388510 | DOI:10.1161/CIRCULATIONAHA.125.074556

J Vis Exp. 2025 May 2;(219). doi: 10.3791/67831.

ABSTRACT

RASopathies are genetic syndromes caused by ERK hyperactivation and resulting in multisystemic diseases that can also lead to cancer predisposition. Despite a broad genetic heterogeneity, germline gain-of-function mutations in key regulators of the RAS-MAPK pathway underlie the majority of the cases, and, thanks to advanced sequencing techniques, potentially pathogenic variants affecting the RAS-MAPK pathway continue to be identified. Functional validation of the pathogenicity of these variants, essential for accurate diagnosis, requires fast and reliable protocols, preferably in vivo. Given the scarcity of effective treatments in early childhood, such protocols, especially if scalable in cost-effective animal models, can be instrumental in offering a preclinical ground for drug repositioning/repurposing. Here we describe step-by-step the protocol for rapid generation of transient RASopathy models in zebrafish embryos and direct inspection of live disease-associated ERK activity changes occurring already during gastrulation through real-time multispectral Förster resonance energy transfer (FRET) imaging. The protocol uses a transgenic ERK reporter recently established and integrated with the hardware of commercial microscopes. We provide an example application for Noonan syndrome (NS) zebrafish models obtained by expression of the Shp2D61G. We describe a straightforward method that enables registration of ERK signal change in the NS fish model before and after pharmacological signal modulation by available low-dose MEK inhibitors. We detail how to generate, retrieve, and assess ratiometric FRET signals from multispectral acquisitions before and after treatment and how to cross-validate the results via classical immunofluorescence on whole embryos at early stages. We then describe how, via examining standard morphometric parameters, to query late changes in embryo shape, indicative of a resulting impairment of gastrulation, in the same embryos whose ERK activity is assessed by live FRET at 6 h post fertilization.

PMID:40388378 | DOI:10.3791/67831

medRxiv [Preprint]. 2025 May 7:2025.05.05.25326966. doi: 10.1101/2025.05.05.25326966.

ABSTRACT

Type 2 diabetes (T2D) is epidemiologically associated with a wide range of non-cardiovascular comorbidities, yet their shared etiology has not been fully elucidated. Leveraging eight non-overlapping mechanistic clusters of T2D genetic profiles, each representing distinct biological pathways, we investigate putative causal links between cluster-stratified T2D genetic predisposition and 21 non-cardiovascular comorbidities. Most of the identified putative causal effects are driven by distinct T2D genetic clusters. For example, the risk-increasing effects of T2D genetic predisposition on cataracts and erectile dysfunction are primarily attributed to obesity and glucose regulation mechanisms, respectively. When surveyed in populations across the globe, we observe opposing effect directions for depression, asthma and chronic obstructive pulmonary disease between populations. We identify a putative causal link between T2D genetic predisposition and osteoarthritis. To underscore the translational potential of our findings, we intersect high-confidence effector genes for osteoarthritis with targets of T2D-approved drugs and identify metformin as a potential candidate for drug repurposing in osteoarthritis.

PMID:40385452 | PMC:PMC12083600 | DOI:10.1101/2025.05.05.25326966