Int J Mol Sci. 2025 Jun 25;26(13):6112. doi: 10.3390/ijms26136112.

ABSTRACT

Recently, marketing authorizations were granted by the Federal Drug Administration (FDA) for pegcetacoplan and avacincaptad pegol, which inhibit C3 and C5 complement components, respectively. These two drugs were demonstrated to slow down the growth of atrophic areas in the retina. These authorizations represent a huge breakthrough for patients suffering from geographic atrophy (GA), the late stage of the dry form of Age-related Macular Degeneration (AMD). Until then, no treatment was available to treat this blinding disease. However, these two new compounds inhibiting the complement system are still not available for patients outside of the United States, and they are not devoid of drawbacks, including a poor effect on vision improvement, an increased risk of occurrence of the neovascular form of AMD and the burden of patients receiving recurrent intravitreal injections. Thus, the important medical need posed by GA remains incompletely answered, and new therapeutic options with alternative modes of action are still required. Oxidative stress and inflammation are two major potential targets to limit the progression of atrophic retinal lesions. Dimethyl fumarate, dimethyl itaconate and other activators of the transcription factor nuclear factor erythroid 2-related factor 2 (Nrf2) display antioxidants and immunomodulatory properties that have shown evidence of efficacy in in vitro and in vivo models of dry AMD. Tecfidera®, whose active principle is dimethyl fumarate, is already commercialized for the treatment of autoimmune diseases such as multiple sclerosis and psoriasis. The aim of this review is to present the rationale and the design of the clinical trial we initiated to test the effectiveness and safety of repurposing Tecfidera®, which could represent a new therapeutic alternative in patients with the dry form of AMD.

PMID:40649894 | DOI:10.3390/ijms26136112

Int J Mol Sci. 2025 Jun 23;26(13):6019. doi: 10.3390/ijms26136019.

ABSTRACT

The limited efficacy of antipsychotics in treating the negative and cognitive symptoms of schizophrenia has prompted the exploration of adjuvant therapies. Several drugs developed for other indications-including caffeine, metformin, and furosemide-have shown procognitive potential. This study evaluated the effects of these agents on behavioral parameters using the reward-based Ambitus test, and on the cerebral D2 dopamine receptor (D2R) expression and binding. The drugs were administered individually and in combination in a schizophrenia-like triple-hit animal model (Lisket rats), derived from the Long Evans (LE) strain. Lisket rats received 14 days of drug treatment via drinking water; water-drinking LE rats served as the controls. The Ambitus test was conducted before treatment and on days 11-14. Caffeine enhanced activity without affecting learning or memory. Metformin and furosemide reduced exploratory behavior but improved reference memory; these effects were inhibited by caffeine co-administration. Although no statistically significant behavioral differences were found compared to water-treated Lisket rats, a trend toward reduced exploratory visits was observed in the triple-combination group. Lisket rats exhibited moderately reduced D2R binding in the cortex and increased binding in the hippocampus. Caffeine alone and in combination enhanced hippocampal D2R binding, while furosemide increased cortical D2R expression. This study is the first to highlight the behavioral and molecular effects of these non-antipsychotic agents in a schizophrenia model, supporting their potential for adjunctive use.

PMID:40649798 | DOI:10.3390/ijms26136019

Int J Mol Sci. 2025 Jun 21;26(13):5962. doi: 10.3390/ijms26135962.

ABSTRACT

Influenza is still a chronic global health threat, inducing a sustained search for effective antiviral therapeutics. Computational methods have played a pivotal role in developing small molecule therapeutics. In this study, we applied a combined in silico and in vitro approach to explore the potential anti-influenza activity of cyproheptadine, a clinically used histamine H1 receptor antagonist. Virtual screening based on the average quasivalence number (AQVN) and electron-ion interaction potential (EIIP) descriptors suggests similarities between cyproheptadine and several established anti-influenza agents. The subsequent ligand-based pharmacophore screening of a focused H1 antagonist library was aligned with the bioinformatics prediction, and further experimental in vitro evaluation of cyproheptadine demonstrated its anti-influenza activity. These findings provide proof of concept for cyproheptadine's in silico-predicted antiviral potential and underscore the value of integrating computational predictions with experimental validation. The results of the current study provide a preliminary proof of concept for the predicted anti-influenza potential based on computational analysis and emphasize the utility of integrating in silico screening with experimental validation in the early stages of drug repurposing efforts.

PMID:40649744 | DOI:10.3390/ijms26135962

Sci Rep. 2025 Jul 11;15(1):25166. doi: 10.1038/s41598-025-10416-0.

ABSTRACT

The activation of the PPARG transcription factor is linked to reduced non-small cell lung cancer (NSCLC) growth. Bioinformatics, cheminformatics, and molecular docking/dynamics studies assessing pioglitazone and telmisartan as repurposed PPARG agonists for treating NSCLC with a targeted delivery system was done. Bioinformatics confirmed that the expression of the PPARG gene can predict outcomes in lung adenocarcinoma and is related to immune cells present in the tumor. Cheminformatics data showed that pioglitazone and telmisartan have a strong attraction to the PPARG receptor, with good efficiency as ligands. Both drugs were found to be lipophilic, suggesting compatibility with a targeted delivery formulation that may include albumin. Further cheminformatics predictions highlighted systemic toxicity values and the need for targeted delivery to minimize toxic side effects. Molecular docking and dynamics simulations showed that the telmisartan-MyoVc cargo domain complex was strong and stable during an 18 ns simulation period. Bioinformatics and cheminformatics data support pioglitazone and telmisartan as promising repurposed drugs for LUAC, highlighting their lipophilicity and compatibility with exosomal components like albumin. Cheminformatics also pointed out potential off-target effects and hepatotoxicity, emphasizing the importance of exosomal targeted delivery. Molecular docking and MD simulations confirmed the affinity and stability of drug-exosomal vehicle complexes. The proposed engineering of exosomal cargo for targeted delivery of these drugs to lung cells could enhance NSCLC treatment and address drug resistance while minimizing systemic toxicity.

PMID:40646269 | DOI:10.1038/s41598-025-10416-0

Comput Biol Med. 2025 Jul 10;196(Pt A):110694. doi: 10.1016/j.compbiomed.2025.110694. Online ahead of print.

ABSTRACT

Drug repurposing accelerates microbial therapy development by bypassing the costly and time-consuming traditional drug discovery process. However, existing computational methods for predicting drug-microbe associations (MDAs) struggle to capture complex feature distributions and lack mechanistic interpretability. To overcome these challenges, we propose the Scholar-guided and Multi-dimensional Moment Neural Network (GSSMMT), a novel MDA prediction framework. First, biomedical data (e.g., chemical structures, microbial genomes, interaction databases) are integrated into drug and microbe homogeneous graphs. Second, multi-view random walk algorithms are applied to combine multimodal drug and microbial features from these homogeneous graphs, followed by constructing a heterogeneous network with drug-microbe interaction data. Third, GSSMMT employs a dual-path architecture: a scholar-guided network extracts domain-specific features from the homogeneous graphs, while a multi-dimensional moment neural network captures higher-order statistical patterns from the heterogeneous graph. Cross-graph fusion, driven by attention-based transpose matrices, dynamically adjusts interaction weights. Finally, a dual-tower support vector machine decodes the fused representations to predict MDA likelihoods, ensuring accuracy and traceability. Experiments on three benchmark datasets show GSSMMT outperforms five state-of-the-art baselines in prediction accuracy. Ablation studies further confirm the contributions of its key components, and case studies on three clinically relevant drugs reveal over 80 % alignment with PubMed-reported interactions. Overall, these results highlight GSSMMT's reliability in identifying latent MDAs with both computational rigor and biological interpretability.

PMID:40644894 | DOI:10.1016/j.compbiomed.2025.110694

Neurology. 2025 Aug 12;105(3):e213783. doi: 10.1212/WNL.0000000000213783. Epub 2025 Jul 11.

ABSTRACT

BACKGROUND AND OBJECTIVES: There are currently no treatments that can halt or slow the progression of Parkinson disease (PD). The aim of this study was to identify new drug repurposing candidates for PD among existing prescription drugs that could be used to modify the disease course.

METHODS: This nationwide observational cohort study (2004-2020) used Norwegian health registries and was conducted as a high-throughput drug screen using an emulated target trial design. All individuals who met our prescription-based classification criteria for PD, were older than 25 years at the time of diagnosis, and were not prescribed the target drug in the past 2 years were included. We emulated a target trial for any drug filled by a minimum of 100 individuals at any pharmacy in Norway, which amounted to a total of 219 drugs. Mortality was used as an outcome to indicate disease progression. We estimated the effect of drug initiation, an observational analog of the intention-to-treat effect, on the 8-year risk of death, comparing initiators of the target drug with initiators of drugs within the same Anatomical Therapeutic Chemical classification system level 1 group. Inverse probability of treatment weighting was used to adjust for potential confounders.

RESULTS: The study included 14,289 individuals with PD (mean age 72 at diagnosis, 59% male) and identified 23 drugs associated with reduced mortality risk at 8 years. These drugs included ranitidine (histamine-2 blocker); pantoprazole and esomeprazole (proton pump inhibitors); losartan (angiotensin receptor blocker); atorvastatin (for high cholesterol); tadalafil (for erectile dysfunction); levothyroxine sodium (thyroid hormone); phenoxymethylpenicillin, erythromycin, and azithromycin (antibiotics); 4 nonsteroidal anti-inflammatory drugs; combined codeine/paracetamol and tramadol (opioid analgesics); zopiclone and melatonin (sleep aids); mianserin (antidepressant); mometasone (nasal corticosteroid); 2 opium-derived cough medicines; and dexamethasone (ophthalmologic corticosteroid).

DISCUSSION: Our study identified several drugs with potential disease-modifying properties that could be candidates for future clinical trials. It highlights the potential of repurposing existing medications to advance drug development. While these findings are exploratory and, therefore, insufficient to justify immediate clinical application, they warrant further investigation and potential inclusion in clinical trials.

PMID:40644656 | DOI:10.1212/WNL.0000000000213783

Neurology. 2025 Aug 12;105(3):e213972. doi: 10.1212/WNL.0000000000213972. Epub 2025 Jul 11.

NO ABSTRACT

PMID:40644655 | DOI:10.1212/WNL.0000000000213972

Pharmaceut Med. 2025 Jul 11. doi: 10.1007/s40290-025-00572-z. Online ahead of print.

ABSTRACT

Antimicrobial resistance is a pressing global health threat fueled by a complex interplay of biological, social, and economic factors. Despite widespread recognition of its impact, the antimicrobial resistance crisis continues to deepen because of inadequate innovation, poor access to effective treatments, and irrational antimicrobial use. Effectively combating antimicrobial resistance requires a multisectoral, multistakeholder, and multidimensional approach, with the pharmaceutical industry playing a pivotal role in new antimicrobial discovery along with diagnostic and other stakeholders. This review critically examines the central role of the pharmaceutical industry in addressing antimicrobial resistance, focusing on drug discovery, manufacturing practices, and stewardship efforts. While the industry has made notable contributions through the development of new antimicrobials and alternative approaches such as drug repurposing, artificial intelligence-driven discovery, and improved diagnostics, major challenges persist-including a declining antibiotic pipeline, limited access in low- and middle-income countries, antimicrobial pollution, irrational fixed-dose combinations, and the prevalence of substandard or falsified drugs. To overcome these barriers, this review explores strategic directions, including public-private partnerships, delinked incentive models, small-molecule innovation, ethical marketing, and equitable access strategies. It also underscores the industry's responsibility in promoting antimicrobial stewardship, participating in global surveillance systems, and educating prescribers and the public on responsible use. Future directions highlight the need for diversified funding, global collaboration, and the adoption of the "triple shield" approach-integrating infection prevention and control, antimicrobial stewardship, and robust surveillance to combat antimicrobial resistance. This review presents an integrated analysis of pharmaceutical accountability, highlighting actionable pathways that align innovation with equitable access, environmental safety, and ethical governance. By bridging gaps between discovery and delivery, the pharmaceutical sector can become a driving force in the global response to antimicrobial resistance.

PMID:40643776 | DOI:10.1007/s40290-025-00572-z

ACS Infect Dis. 2025 Jul 11. doi: 10.1021/acsinfecdis.5c00319. Online ahead of print.

ABSTRACT

Widespread drug resistance necessitates the prioritization of novel scaffolds with alternate mechanisms as possible partner drugs to artemisinin to combat malaria. We utilized the Pandemic Response Box chemical library of the Medicines for Malaria Venture, launched in 2019, to identify inhibitors with stage-specific potency and phenotypic signatures against the blood stage development of Plasmodium falciparum (P. falciparum) toward exploring drug repurposing. From this screening, we initially identified 60 molecules active at 10 μM against both drug-sensitive (3D7) and chloroquine-resistant (Dd2) strains of P. falciparum. Furthermore, 28 compounds active below 3 μM were prioritized, several of which specifically impaired stage transitions of ring (MMV001014), trophozoite (MMV1593540 and MMV1634402), and schizonts (MMV1580844, MMV1580496, MMV1580173, and MMV1580483), confirmed through microscopic phenotypes and flow cytometry. The ring stage inhibitor, MMV001014, was irreversible, led to no recrudescence, and showed antagonistic effects with artemisinin, indicative of overlapping mechanisms. Both the trophozoite inhibitors, MMV1593540 and MMV1634402, exhibited nanomolar EC50, among which MMV1593540 was additive with artemisinin while antagonistic with chloroquine. Two of the schizont stage inhibitors (MMV1580844 and MMV1580173) appeared to operate through a mechanism driven by the generation of reactive oxygen species, and all of them with molecule-specific effects on infected red blood cell (iRBC) membrane integrity, confirmed through confocal microscopy. Taken together, these results highlight interesting starting points with likely unique modes of action from MMV's pandemic response box for drug repurposing to combat human malaria that continues to impact the developing world.

PMID:40643161 | DOI:10.1021/acsinfecdis.5c00319

BMC Bioinformatics. 2025 Jul 10;26(1):171. doi: 10.1186/s12859-025-06213-1.

ABSTRACT

BACKGROUND: Predicting protein structural similarity and detecting homologous sequences remain fundamental and challenging tasks in computational biology. Accurate identification of structural homologs enables function inference for newly discovered or unannotated proteins. Traditional approaches often require full 3D structural data, which is unavailable for most proteins. Thus, there is a need for sequence-based methods capable of inferring structural similarity efficiently and at scale.

RESULT: We present Rprot-Vec (Rapid Protein Vector), a deep learning model that predicts protein structural similarity and performs homology detection using only primary sequence data. The model integrates bidirectional GRU and multi-scale CNN layers with ProtT5-based encoding, enabling accurate and fast similarity estimation. Rprot-Vec achieves a 65.3% accurate similarity prediction rate in the homologous region (TM-score > 0.8), with an average prediction error of 0.0561 across all TM-score intervals. Despite having only 41% of the parameters of TM-vec, Rprot-Vec outperforms both public and locally trained TM-vec baselines in all tested settings. Additionally, we constructed and released three curated training datasets (CATH_TM_score_S/M/L), supporting further research in this area.

CONCLUSION: Rprot-Vec offers a fast and lightweight solution for sequence-based structural similarity prediction. It can be applied in protein homology detection, structure-function inference, drug repurposing, and other downstream biological tasks. Its open-source availability and released datasets facilitate broader adoption and further development by the research community.

PMID:40640710 | DOI:10.1186/s12859-025-06213-1

BMC Microbiol. 2025 Jul 11;25(1):430. doi: 10.1186/s12866-025-04130-0.

ABSTRACT

BACKGROUND: It is evident that various drugs influence the gut microbiota, yet the precise mechanism driving these effects remain ambiguous. Considering the growing recognition of gut microbiota's role in health and disease, it is important to explore how commonly used drugs, such as antihistamines, may alter microbial composition and function. Histamine, an essential interkingdom signaling molecule, shapes bacterial virulence, biofilm formation, and immune regulation. However, the effects of antihistamines on bacterial colonization are mostly unknown. This study aimed to investigate the potential effects of antihistamine exposure on critical factors which affect the pathogenicity and colonization of selected gut bacterial species, such as growth, biofilm formation, and adherence to cell lines, at intestinal concentrations. If antihistamines influence bacterial metabolism or composition, they may consequently affect Short Chain Fatty Acid (SCFA) production, which could have downstream effects on gut homeostasis and immune function. Specifically, we examined the impact of three antihistamines - fexofenadine HCl, cyproheptadine HCl, and desloratadine -on bacteria from the four dominant gut phyla: Bifidobacterium longum, Limosilactobacillus reuteri, Bacteroides fragilis, and Escherichia coli.

RESULTS: Our results showed that cyproheptadine HCl and desloratadine inhibited the growth of all tested bacteria, whereas fexofenadine HCl promoted the growth of all species except B. longum. Furthermore, cyproheptadine HCl and desloratadine reduced the biofilm-forming capacity of these bacterial species and altered their effects on adherence to Caco-2/HT-29 cell lines aligning with changes in cell surface hydrophobicity: increased cell surface hydrophobicity correlated with greater bacterial adherence to surfaces. In contrast, fexofenadine HCl enhanced biofilm formation and adherence of B. longum and L. reuterii in Caco-2/HT-29 co-cultures. It also led to increased production of lactic and propionic acids, with a statistically significant increase observed in acetic acid levels (p < 0.05).

CONCLUSION: In summary, our findings suggest that fexofenadine HCl, unlike cyproheptadine HCl and desloratadine, supports the growth, and colonization of probiotic bacteria such as L. reuteri and B. longum with potential anti allergic benefits, and enhancing their SCFA production. Conversely, cyproheptadine HCl and desloratadine suppressed bacterial growth, hinting at potential antimicrobial properties that may warrant exploration for drug repurposing.

PMID:40640705 | DOI:10.1186/s12866-025-04130-0

Biomed J. 2025 Jul 8:100886. doi: 10.1016/j.bj.2025.100886. Online ahead of print.

ABSTRACT

BACKGROUND: Areca nut is a significant risk factor for head and neck cancer (HNC), yet its molecular mechanisms, particularly miRNA-mediated regulation, remain poorly understood. This study investigates the regulatory networks underlying areca nut-induced HNC and explores therapeutic strategies through computational drug repurposing.

MATERIALS AND METHODS: Arecoline was used to assess its effects on invasion, migration, and cisplatin resistance in HNC cells and normal keratinocytes. Differentially expressed miRNAs and mRNAs were identified using high-throughput profiling, followed by integrative network analysis using TCGA-HNSC dataset and multiMiR. OncoPredict was used for drug repurposing to identify therapeutic agents targeting dysregulated miRNA-mRNA networks.

RESULTS: Arecoline exposure promoted invasion and cisplatin resistance, with more pronounced effects in normal keratinocytes, indicating a potential role in early tumorigenesis. Integrative transcriptomic analysis revealed a miRNA-mRNA regulatory network comprising 1,971 oncogenes, 604 tumor suppressors, 35 oncogenic miRNA (OncomiRs), and 36 tumor suppressive miRNA (TSmiRs) regulating pathways related to cell motility and stress response. A tumor-suppressive network with miR-212-3p as a central hub and an oncogenic network modulated by miR-410 and miR-1-3p as critical hubs were identified. Drug repurposing analysis identified four potential therapeutic candidates (MK-2206, BYL-719, MG-132, and FGIN-1-27), with MK-2206 emerging as the most promising. MK-2206 effectively reversed arecoline-induced miRNA-mRNA dysregulation, mitigated malignant phenotypes, and selectively targeted HNC cells while sparing normal keratinocytes.

CONCLUSIONS: This integrative approach elucidates areca nut-driven carcinogenesis through miRNA-mRNA interactions and highlights MK-2206 as a promising therapeutic strategy for areca nut-associated HNC.

PMID:40639775 | DOI:10.1016/j.bj.2025.100886

Mol Biol Rep. 2025 Jul 10;52(1):695. doi: 10.1007/s11033-025-10776-w.

ABSTRACT

Epilepsy is a neurological disorder characterised by aberrant synchronised neuronal activity in the brain and affects millions of people globally. The renin-angiotensin system (RAS) has been implicated in epilepsy pathophysiology, with angiotensin receptors playing pivotal role in seizure modulation and neuroprotection. This review explores the angiotensin-epilepsy axis, and elaborates upon the role of angiotensin receptors (AT-1, AT-2, AT-4, and Mas) in the CNS. AT-1 receptor stimulation is related to neuroinflammation, oxidative stress, and propagation of seizures, whereas their blockade by angiotensin receptor blockers (ARBs) demonstrated anticonvulsant and neuroprotective effects in preclinical model. AT-2 receptor activation down-regulates pro-inflammatory cytokines & protects the blood-brain barrier and induces neuronal survival and differentiation. They also interact with the AT-4 receptor identified as insulin-regulated amino peptidase (IRAP), a receptor that is implicated in its neuroinflammatory modulation, oxidative stress, and excitotoxicity. Against this background, the Mas receptor was recognized as the receptor for angiotensin-(1-7), leading to vasodilator, anti-inflammatory and anti-oxidant effects that oppose angiotensin II actions. This intricate interplay between these receptors and ligands accompanies the dynamic regulation of neurotransmitters, neuroinflammation, and neuroprotection in epileptic seizures. The role of the RAS in epilepsy may present new therapeutic targets in addressing this devastating disorder, especially in patients with coexisting cardiovascular illnesses.

PMID:40637915 | DOI:10.1007/s11033-025-10776-w

Epilepsia Open. 2025 Jul 10. doi: 10.1002/epi4.70101. Online ahead of print.

ABSTRACT

Epilepsy represents a significant medical challenge, with a third of patients failing to achieve seizure freedom despite the use of multiple different anti-seizure medications (ASM). Drug resistance is common in genetically caused epilepsies. Patients are faced with repeated, long-lasting, and frequently frustrating drug testing, necessitating targeted therapies and drug repurposing. While in silico tools offer some insight, novel and often genetic epilepsies require preclinical models, which are expensive and time-consuming. Here, we propose Drosophila melanogaster as a rapid in vivo model for preclinical ASM efficacy testing using the sodium channel-associated epilepsies, Dravet syndrome (DS), and generalized epilepsy with febrile seizures plus (GEFS+) as model disorders. We utilize vinegar fly models of DS and GEFS+ that exhibit phenotypic similarities to human patients, including seizures and increased morbidity. Moreover, treatment with ASM effective in humans (clobazam, stiripentol, fenfluramine) reduces seizures, while the application of sodium channel blocking ASM (phenytoin) was deleterious, underlining the model's utility. The utilization of Drosophila as a preclinical model offers a promising avenue for studying genetic epilepsies and assessing ASM efficacy. This approach has the potential to facilitate the development of tailored treatments for patients using a rapidly available in vivo model. PLAIN LANGUAGE SUMMARY: Epilepsy is a challenging condition, with about one-third of patients unable to control seizures despite trying multiple drug treatments. This is especially common in genetic epilepsies. Developing new treatments is expensive and slow, highlighting the need for faster, targeted approaches. This study uses the fly (Drosophila melanogaster) as a rapid, cost-effective model to study genetic epilepsies like Dravet syndrome (DS). These fly models mimic key symptoms seen in humans, including seizures and shorter lifespans. Effective human anti-seizure medications (e.g., clobazam, stiripentol, and fenfluramine) reduced seizures, while sodium channel blockers like phenytoin worsened them. The Drosophila model offers a promising and efficient way to study genetic epilepsies and test treatments, accelerating the development of more targeted therapies.

PMID:40637098 | DOI:10.1002/epi4.70101

Commun Med (Lond). 2025 Jul 9;5(1):285. doi: 10.1038/s43856-025-00991-8.

ABSTRACT

BACKGROUND: Combinations of common drugs may, when taken together, have unexpected effects on incidence of diseases like cancer. It is not feasible to test for all combination drug effects in clinical trials, but in the real world, drugs are frequently taken in combination. Then, undiscovered effects may protect users of drug combinations from cancer-or increase their risk. By analyzing massive health data containing numerous people exposed to drug combinations, we have an opportunity to discover these associations.

METHOD: We describe, apply, and evaluate an approach for discovering drug combination associations with cancer using health data. Our approach builds on marginal structural model methods to emulate a randomized trial where one arm is assigned to take a drug alone, while the other arm takes that drug in combination with a second drug.

RESULTS: Here, we perform drug combination-wide analysis to estimate effects of over 9000 drug combinations on incidence of all common cancer types, using claims data covering more than 100 million people. But, because the discovery of associations from observational data is always prone to confounding, we develop a number of strategies to distinguish confounding from biomedically relevant findings. We describe a robustly supported beneficial drug combination that may synergistically impact lipid levels to reduce the risk of cancer.

CONCLUSIONS: These findings can suggest new clinical uses for drug combinations to prevent or treat cancer. Our approach can be adapted to mine electronic health records for interactive effects on other late-onset common diseases.

PMID:40634542 | DOI:10.1038/s43856-025-00991-8

NPJ Aging. 2025 Jul 9;11(1):61. doi: 10.1038/s41514-025-00247-8.

ABSTRACT

Aging is the primary risk factor for many cancer types, including lung adenocarcinoma (LUAD). To understand how aging-related alterations in the regulation of key cellular processes might affect LUAD risk and survival, we built individual-specific gene regulatory networks integrating gene expression, transcription factor protein-protein interaction, and sequence motif data, using PANDA/LIONESS algorithms, for non-cancerous lung samples from GTEx project and LUAD samples from TCGA. In healthy lung, pathways involved in cell proliferation and immune response were increasingly targeted with age; these aging-associated alterations were accelerated by smoking and resembled oncogenic shifts observed in LUAD. Aging-associated genes showed greater aging-biased targeting patterns in individuals with LUAD compared to healthier counterparts, a pattern suggestive of age acceleration. Using drug repurposing tool CLUEreg, we found small molecule drugs that may potentially alter the accelerating aging profiles we found. We defined a network-informed aging signature that was associated with survival in LUAD.

PMID:40634311 | DOI:10.1038/s41514-025-00247-8

Epilepsy Res. 2025 Jul 1;217:107621. doi: 10.1016/j.eplepsyres.2025.107621. Online ahead of print.

ABSTRACT

Monogenetic epilepsies are seizure disorders with a single-gene etiology. More than 500 genes are linked to epilepsy. As many as 40 % of epilepsies are caused by variants in one of these genes. Single gene-linked epilepsies have a wide phenotypic spectrum and may be accompanied by comorbidities such as developmental and motor delays. Epilepsy is often pharmacoresistant and does not respond to existing drug therapies. Preclinical data suggests that 4-phenylbutyrate (PBA) may produce an anti-seizure effect in individuals with genetic epilepsies, including STXBP1, SLC6A1, SLC6A8, GABA(A) disorders, Dravet Syndrome (SCN1A), and LGI1 variants. Clinical data also suggests that PBA may have a therapeutic effect for SYNGAP1. This literature review describes the clinical profiles of several monogenetic epilepsies and the pathogenesis of seizure activity in these disorders. We focus on gene-linked epilepsy syndromes that may benefit from treatment with PBA according to several proposed theories of the drug's mechanism and functional impact.

PMID:40633241 | DOI:10.1016/j.eplepsyres.2025.107621

FEBS Lett. 2025 Jul 9. doi: 10.1002/1873-3468.70107. Online ahead of print.

ABSTRACT

Retinitis pigmentosa (RP) is a heterogeneous group of inherited retinal degenerative diseases caused by mutations in over 90 genes. The complexity of its genetic background and economic barriers limit the broad application of targeted gene therapies. Therefore, general pharmacological strategies to slow disease progression, regardless of the underlying mutation, are needed. Cyclic nucleotide second messengers, such as cyclic guanosine monophosphate (cGMP) and cyclic adenosine monophosphate (cAMP), are important for normal retinal function. This includes phototransduction, for which cGMP signaling is essential. Dysregulation of the cyclic nucleotide systems is associated with retinal degeneration, and the inhibition of cGMP or cAMP signaling has shown beneficial effects in several retinal degeneration disease models. Here, we propose these systems as drug targets for RP. Impact statement This perspective proposes targeting cyclic nucleotide signaling (cGMP and cAMP) as a mutation-independent therapeutic strategy for retinitis pigmentosa, offering broad potential for disease-modifying treatment potentially through drug repurposing and novel drug delivery systems.

PMID:40631959 | DOI:10.1002/1873-3468.70107

Circulation. 2025 Jul 9. doi: 10.1161/CIRCULATIONAHA.125.074544. Online ahead of print.

ABSTRACT

BACKGROUND: Abdominal aortic aneurysms (AAA) present with high morbidity and mortality when they occasionally rupture. No medical therapy has successfully been proven to reduce AAA growth, though both metformin and statins have been identified as potential treatments in multiple meta-analysis. This study aimed to investigate a potential relationship between statin use and AAA growth rates and risk of undergoing repair, rupture, or death.

METHODS: The study population included all men with screening-detected AAAs (30-55 mm) from the 2 large, population-based, randomized screening trials; the Viborg Vascular Screening trial (inclusion, 2008-2011) and the Danish Cardiovascular Screening trial (inclusion, 2014-2018). The clinical database was supplemented with data from the nationwide Danish Healthcare Registries, including prescription and outcome data. Statin exposure was quantified by defined daily doses (DDD). The primary outcome was AAA growth rate, whereas secondary outcomes included the need for repair and a composite of repair, rupture, and all-cause death. Growth rates were calculated using linear regression. To evaluate the risk of repair, patients were followed from inclusion until surgery, rupture, death, 5-year follow-up, or December 31, 2021.

RESULTS: A total of 998 aneurysmal men (median age, 69.5 [interquartile range (IQR), 67-72] years; median AAA diameter, 35.4 [IQR, 32-41.2] mm) were included. Statin use was significantly associated with reduced AAA growth rate; an increase of 1 DDD statin per day was associated with an adjusted change in growth rate of -0.22 mm/year [95% CI, -0.39 to -0.06]; P=0.009). The 5-year adjusted hazard ratio for undergoing repair per doubling of statin dose presented a significantly reduced adjusted hazard ratio (HR) of 0.82 ([95% CI, 0.70-0.97]; P=0.023), which was significant after 2.5 years. Statin use was associated with a significantly lower risk of the composite outcome (surgery, rupture, and death) in a dose-dependent manner, with an adjusted HR of 0.83 ([95% CI, 0.73-0.94]; P=0.003) per doubling of statin dose. Findings were robust in a variety of sensitivity analyses.

CONCLUSIONS: High-dose statin use was associated with decreased AAA growth rates and lowered risk of undergoing repair, rupture, and death. This nonrandomized study suggests that patients with AAA could benefit from high-dose statin use, beyond only targeting associated risk factors.

PMID:40631665 | DOI:10.1161/CIRCULATIONAHA.125.074544

bioRxiv [Preprint]. 2025 Jul 4:2025.07.01.662580. doi: 10.1101/2025.07.01.662580.

ABSTRACT

BACKGROUND: Phosphoglucomutase-1 (PGM1) plays a pivotal role in glycolysis, glycogen metabolism, and glycosylation. Pathogenic variants in PGM1 cause PGM1-congenital disorder of glycosylation (PGM1-CDG), a multisystem disorder with cardiac involvement. While glycosylation abnormalities in PGM1-CDG are treatable with galactose, cardiomyopathy does not improve suggesting a glycosylation-independent pathomechanism. Recently, mitochondrial abnormalities have been shown in a heart of a PGM1-deficicient patient and PGM1-mouse model. In addition, PGM1 has been associated with LDB3 (ZASP/Cypher), a sarcomeric Z-disk protein also associated with cardiomyopathy. However, the cardiac-specific role of PGM1 remains poorly understood, and targeted therapies for PGM1-related cardiomyopathy are currently lacking.

METHODS: Induced pluripotent stem cell-derived cardiomyocytes (iCMs) were generated from PGM1-deficient patient fibroblasts. Multielectrode array (MEA) recordings, untargeted (glyco)proteomics, and pathway analysis were performed to assess functional and molecular changes. Key findings were validated using tracer metabolomics and mitochondrial respiration assays.

RESULTS: PGM1-deficient iCMs exhibited reduced beating frequency, impaired contractility, and prolonged contraction kinetics. Proteomic analyses revealed depletion of Z-disk components, including LDB3. AlphaFold3 structural modeling predicted a direct interaction between PGM1 and LDB3, implicating PGM1 in Z-disk integrity, which was confirmed in vitro . In addition, mitochondrial proteins were severely depleted, prompting us to investigate mitochondrial function. Functional validation confirmed extensive metabolic rewiring, energy depletion, and severely impaired mitochondrial respiration. Finally, the in silico drug repurposing identified possible therapeutic options that could target PGM1-deficient cardiomyopathy.

CONCLUSION: PGM1 is a key regulator of cardiomyocyte function, linking sarcomeric Z-disk integrity with mitochondrial metabolism. These mechanistic insights offer a foundation for developing targeted therapies for PGM1-CDG and potentially other cardiomyopathies involving Z-disk dysfunction.

PMID:40631269 | PMC:PMC12236660 | DOI:10.1101/2025.07.01.662580