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PubMed2026

Memantine and its analogs: Potential applications in cancer therapy.

Drug repurposing refers to the process of using an existing drug or drug candidate for a new treatment or medical condition for which it was not indicated before. The process of "drug repurposing" usually involves an FDA-approved entity which has undergone clinical development and have a with well-established safety and toxicity profile in patients. Several convergent studies show that repurposed drugs may present a promising strategy for the management and therapy of several human cancers. Memantine is used to combat dementia in moderate-to-severe Alzheimer's disease (AD) patients. Several convergent studies show that memantine (and its analogs) may have applications in multiple disease conditions associated with human cancers. Memantine and its related compounds have shown promise as neuroprotective agents, anti-fatigue agents and pain-relieving agents to alleviate the toxic side effects of radiation therapy and chemotherapy. Recent publications have revealed that memantine displays anti-cancer activity by exerting direct growth-suppressive activity on the primary tumor as modulating the genomic/cellular landscape of the tumor microenvironment. Currently, clinical trials are in progress, which aim to evaluate the potential applications of memantine in cancer treatment. The adamantane scaffold in memantine has proved to be a versatile tool for the discovery of synthetic memantine analogs with robust anti-cancer activity. The discovery of second-generation memantine analogs may have wider applications in combating cancer recurrence and addressing clinical challenges in the treatment of drug-resistant and metastatic cancers.

Humans↗

PubMed2025

Novel approaches to clinical trial design in cancer neuroscience.

The emerging field of cancer neuroscience has revealed profound bidirectional interactions between the nervous system and cancer cells, identifying novel therapeutic vulnerabilities across diverse malignancies. This review examines the unique challenges and strategies for translating these insights into effective therapies. We propose innovative approaches to overcome these barriers through drug repurposing, enhanced biomarker development, and optimized trial designs. Repurposing neuroactive drugs with established safety profiles offers an accelerated path to clinical impact, particularly for targeting glutamatergic, adrenergic, and neurotrophic signaling pathways. Emphasizing mitigation of neurotoxicity and improved patient quality of life will be paramount moving forward. Repurposed agents that show preliminary potential for "dual use" (i.e., simultaneous toxicity mitigation and synergistic anti-tumor effects) are highlighted for special consideration. Master protocols and window-of-opportunity trials provide platforms to rapidly validate mechanisms while addressing patient-centered outcomes. By systematically addressing these foundational elements across disciplines, cancer neuroscience can translate its profound mechanistic insights into meaningful therapeutic advances for patients with treatment-resistant malignancies.

Humans↗

PubMed2025

Reproducibility of genetic risk factors identified for long COVID using combinatorial analysis across US and UK patient cohorts with diverse ancestries.

BACKGROUND: Long COVID is a major public health burden causing a diverse array of debilitating symptoms in tens of millions of patients globally. In spite of this overwhelming disease prevalence, staggering cost, severe impact on patients' lives and intense global research efforts, study of the disease has proved challenging due to its complexity. Genome-wide association studies (GWAS) have identified only four loci potentially associated with the disease, although these results did not statistically replicate between studies. A previous combinatorial analysis study identified a total of 73 genes that were highly associated with two long COVID cohorts in the predominantly (> 91%) white European ancestry Sano GOLD population, and we sought to reproduce these findings in the independent and ancestrally more diverse All of Us (AoU) population. METHODS: We assessed the reproducibility of the 5343 long COVID disease signatures from the original study in the AoU population. Because the very small population sizes provide very limited power to replicate findings, we initially tested whether we observed a statistically significant enrichment of the Sano GOLD disease signatures that are also positively correlated with long COVID in the AoU cohort after controlling for population substructure. RESULTS: For the Sano GOLD disease signatures that have a case frequency greater than 5% in AoU, we consistently observed a significant enrichment (77-83%, p < 0.01) of signatures that are also positively associated with long COVID in the AoU cohort. These encompassed 92% of the genes identified in the original study. At least five of the disease signatures found in Sano GOLD were also shown to be individually significantly associated with increased long COVID prevalence in the AoU population. Rates of signature reproducibility are strongest among self-identified white patients, but we also observe significant enrichment of reproducing disease associations in self-identified black/African-American and Hispanic/Latino cohorts. Signatures associated with 11 out of the 13 drug repurposing candidates identified in the original Sano GOLD study were reproduced in this study. CONCLUSION: These results demonstrate the reproducibility of long COVID disease signal found by combinatorial analysis, broadly validating the results of the original analysis. They provide compelling evidence for a much broader array of genetic associations with long COVID than previously identified through traditional GWAS studies. This strongly supports the hypothesis that genetic factors play a critical role in determining an individual's susceptibility to long COVID following recovery from acute SARS-CoV-2 infection. It also lends weight to the drug repurposing candidates identified in the original analysis. Together these results may help to stimulate much needed new precision medicine approaches to more effectively diagnose and treat the disease. This is also the first reproduction of long COVID genetic associations across multiple populations with substantially different ancestry distributions. Given the high reproducibility rate across diverse populations, these findings may have broader clinical application and promote better health equity. We hope that this will provide confidence to explore some of these mechanisms and drug targets and help advance research into novel ways to diagnose the disease and accelerate the discovery and selection of better therapeutic options, both in the form of newly discovered drugs and/or the immediate prioritization of coordinated investigations into the efficacy of repurposed drug candidates.

Humans↗

PubMed2024

Shared etiology of Mendelian and complex disease supports drug discovery.

BACKGROUND: Drugs targeting disease causal genes are more likely to succeed for that disease. However, complex disease causal genes are not always clear. In contrast, Mendelian disease causal genes are well-known and druggable. Here, we seek an approach to exploit the well characterized biology of Mendelian diseases for complex disease drug discovery, by exploiting evidence of pathogenic processes shared between monogenic and complex disease. One way to find shared disease etiology is clinical association: some Mendelian diseases are known to predispose patients to specific complex diseases (comorbidity). Previous studies link this comorbidity to pleiotropic effects of the Mendelian disease causal genes on the complex disease. METHODS: In previous work studying incidence of 90 Mendelian and 65 complex diseases, we found 2,908 pairs of clinically associated (comorbid) diseases. Using this clinical signal, we can match each complex disease to a set of Mendelian disease causal genes. We hypothesize that the drugs targeting these genes are potential candidate drugs for the complex disease. We evaluate our candidate drugs using information of current drug indications or investigations. RESULTS: Our analysis shows that the candidate drugs are enriched among currently investigated or indicated drugs for the relevant complex diseases (odds ratio = 1.84, p = 5.98e-22). Additionally, the candidate drugs are more likely to be in advanced stages of the drug development pipeline. We also present an approach to prioritize Mendelian diseases with particular promise for drug repurposing. Finally, we find that the combination of comorbidity and genetic similarity for a Mendelian disease and cancer pair leads to recommendation of candidate drugs that are enriched for those investigated or indicated. CONCLUSIONS: Our findings suggest a novel way to take advantage of the rich knowledge about Mendelian disease biology to improve treatment of complex diseases.

Humans↗

PubMed2026

Multivariate, Multi-Omic Analysis in 799,429 Individuals Identifies 134 Loci Associated with Somatoform Traits.

INTRODUCTION: Somatoform traits (e.g., health anxiety, somatic preoccupation, and bodily distress symptoms) are prevalent and pose challenges to clinical practice. Understanding their genetic basis could improve diagnostic and therapeutic approaches. METHODS: Using available summary statistics, we conducted a multivariate genome-wide association study (GWAS) and multi-omic analysis of four somatoform traits - fatigue, irritable bowel syndrome, pain intensity, and health satisfaction - in 799,429 individuals genetically similar to European reference panels. RESULTS: The GWAS identified 134 loci associated with a somatoform common factor, including 44 loci not significant in the input GWAS and 8 novel loci for somatoform traits. Novel loci were mechanistically informative, mapping to the DNM1 gene and the protocadherin gene cluster (PCDHA1-4), which are involved in nociceptor sensitization and synaptogenesis, respectively. Gene-property analyses highlighted an enrichment of genes involved in synaptic transmission and enriched expression in 11 brain tissues and the pituitary. Across two brain transcriptomic datasets, we identified 16 high-confidence genes whose expression in enriched tissues was associated with somatoform traits. There was substantial polygenic overlap (76-83%) between the somatoform and externalizing, internalizing, and general psychopathology factors. Somatoform polygenic scores were associated with obesity, type 2 diabetes, and tobacco use disorder in independent biobanks. Drug repurposing analyses suggested potential therapeutic targets, including MEK inhibitors, while Mendelian randomization analyses indicated potentially protective effects of gut microbiota. DISCUSSION: Consistent with emerging medical and genetic knowledge, somatoform traits have a shared etiology and considerable polygenic overlap with psychopathology. The biological insights from drug repurposing and Mendelian randomization analyses could provide promising avenues for treatment development.

Genetics↗

PubMed2026

Cross-tissue Mendelian randomization prioritizes RAB27B as a brain-derived candidate protein for postpartum depression.

OBJECTIVE: Postpartum depression (PPD) is one of the most common and debilitating complications of childbirth, yet the candidate proteins linking genetic risk to disease remain poorly defined. Building on recent genome-wide association studies (GWAS), we sought to integrate cross-tissue proteogenomic data to identify candidate proteins for PPD and explore therapeutic opportunities. METHODS: We conducted two-sample Mendelian randomization (MR) using genome-wide significant cis-protein QTLs from brain (n = 608 proteins), cerebrospinal fluid (CSF; n = 214), and plasma (n = 612). PPD summary statistics were obtained from FinnGen R8 (13,657 cases, 236,178 controls) and replicated in an independent GWAS. Phenome-wide association (PheWAS) was used to assess pleiotropy. Potential therapeutic targets were evaluated through DSigDB drug repurposing, molecular docking, and molecular dynamics simulations. RESULTS: Among all proteins tested, RAB27B was the only brain-derived protein surpassing Bonferroni correction (OR = 1.60; 95% CI: 1.30-1.96; P = 6.6 × 10⁻⁶), whereas no significant proteins were identified in CSF or plasma. This association was replicated in an independent GWAS (OR = 1.27; 95% CI: 1.02-1.58; P = 0.037). PheWAS identified no pleiotropic associations at genome-wide significance. In silico drug repurposing identified pregnenolone as a candidate ligand with computationally predicted stable binding to RAB27B, providing a starting point for future experimental validation. CONCLUSION: This study provides the first cross-tissue proteogenomic evidence that RAB27B is a brain-derived, reproducible candidate protein genetically associated with PPD. By extending GWAS signals to functional protein-level mechanisms and therapeutic inference, our findings nominate RAB27B and pregnenolone as promising directions for postpartum psychiatric research.

Humans↗

PubMed2025

Identification of a PRDM1-regulated T cell network to regulate atherosclerotic plaque inflammation.

BACKGROUND: Inflammation is a key driver of atherosclerosis, yet the mechanisms sustaining inflammation in human plaques remain poorly understood. This study uses a network-based approach to identify immune gene programs involved in the transition from low- to high-risk (rupture-prone) human atherosclerotic plaques. METHODS: Expression data from human carotid artery plaques, both stable (low-risk, n = 16) and unstable (high-risk, n = 27), were analyzed using Weighted Gene Co-expression Network Analysis (WGCNA). Bayesian network inference, operated on the eigengene values from the WGCNA, further extended the WGCNA analysis, and similarity to the signature of T cell subsets was validated in single-cell RNA sequencing data of human plaques, and a loss-of-function study in a mouse model of atherosclerosis. In silico drug repurposing was performed to identify potential therapeutic targets. RESULTS: Our analysis revealed a distinct gene module with a prominent T cell signature, particularly in unstable plaques. Key regulatory factors, RUNX3, IRF7 and in particular PRDM1, were significantly downregulated in plaque T cells from symptomatic versus asymptomatic patients, indicating a protective role. Additionally, as PRDM1 is downstream of IRF7, we opted for PRDM1 as a key target. T cell-specific Prdm1 deficiency in Western-type diet fed Ldlr knockout mice featured accelerated plaque progression. Finally, as PRDM1 targeting drugs are not yet available, we performed in silico drug repurposing, identifying EGFR inhibitors as promising therapeutic candidates. CONCLUSIONS: This study highlights a PRDM1-regulated T cell network that distinguishes high-risk from low-risk plaques and demonstrates the regulatory role of T cell PRDM1 in controlling atherosclerosis, positioning this pathway as a promising therapeutic target.

Plaque, Atherosclerotic↗

PubMed2025

Multi-omics Mendelian randomization integrating RNA-seq, eQTL and pQTL data revealed CPXM1 as a potential drug target for osteoporosis.

Osteoporosis, a prevalent skeletal disorder characterized by decreased bone mineral density and increased fracture risk, continues to be a major global health concern. Traditional treatments for osteoporosis have limited efficacy and safety profiles, highlighting the need for novel therapeutic targets. This study integrates multi-omics data, including RNA-seq, expression quantitative trait loci (eQTL), and protein quantitative trait loci (pQTL) data, through Mendelian randomization (MR) to identify potential drug targets for osteoporosis. By leveraging bidirectional two-sample MR analysis, we identified CPXM1 (Carboxypeptidase X, M14 family member 1) as a novel gene that is causally linked to osteoporosis risk. Through transcriptomic and proteomic validation, we demonstrate that CPXM1 was upregulated in aged bone tissues and osteoporotic conditions in both human and murine models. Gene set enrichment analysis (GSEA) revealed significant dysregulation of bone homeostasis pathways, including increased extracellular matrix degradation and suppression of osteoblast differentiation in aged mice. Furthermore, phenome-wide association studies (PheWAS) confirmed minimal off-target effects of CPXM1, reinforcing its potential as a therapeutic target. Finally, computational drug repurposing predicted several promising drug candidates, including Doxorubicin, 5-Fluorouracil, and 2-Methylcholine, which may target CPXM1 pathways for osteoporosis treatment. These findings highlight CPXM1 as a potential biomarker and therapeutic target, offering new avenues for osteoporosis therapy.

Osteoporosis↗

PubMed2026

Proteomic insights into Helicobacter pylori infection in stomach cells, revealing host response and host-targeted therapeutics repurposing.

BACKGROUND: Helicobacter pylori (H. pylori) is a globally prevalent gastric pathogen strongly associated with chronic gastritis, peptic ulcers, and gastric cancer. While bacterial factors have been extensively studied, host proteomic responses and their therapeutic potential remain largely underexplored. RESEARCH DESIGN AND METHODS: Current analyses employed a systematic proteomics-based data integration and harmonization approach (retrospective qualitative cohort study) to identify important differentially regulated host proteins. Proteomic datasets were curated from in vitro studies and analyzed for functional enrichment, protein-protein interaction networks, and hub protein identification. To explore therapeutic repurposing, drug repositioning was performed using the DrugBank database. RESULTS: Data summation describing protein differential regulation in human gastric cells as a result of the infection revealed 1672 perturbed host proteins. Bioinformatics analysis revealed 11 proteins including CSK, MET, RELA, MARK2, GRB2, FTO, PLCG1, CRKL, RPS5, RPS9, and RPS27A to be ideal host targets for therapeutic repurposing. Clinically approved drugs such as Dasatinib (targeting CSK) and Crizotinib (targeting MET) emerged as promising candidates due to favorable pharmacokinetics and known bioactivity. CONCLUSIONS: Host-directed therapeutics could offer alternative strategies to conventional antibiotic therapy, addressing challenges such as resistance and infection recurrence, providing a foundation for future experimental validation and development of host-targeted interventions for infection control.

Humans↗

PubMed2024

The effect of fampridine on working memory: a randomized controlled trial based on a genome-guided repurposing approach.

Working memory (WM), a key component of cognitive functions, is often impaired in psychiatric disorders such as schizophrenia. Through a genome-guided drug repurposing approach, we identified fampridine, a potassium channel blocker used to improve walking in multiple sclerosis, as a candidate for modulating WM. In a subsequent double-blind, randomized, placebo-controlled, crossover trial in 43 healthy young adults (ClinicalTrials.gov, NCT04652557), we assessed fampridine's impact on WM (3-back d-prime, primary outcome) after 3.5 days of repeated administration (10 mg twice daily). Independently of baseline cognitive performance, no significant main effect was observed (Wilcoxon P = 0.87, r = 0.026). However, lower baseline performance was associated with higher working memory performance after repeated intake of fampridine compared to placebo (rs = -0.37, P = 0.014, n = 43). Additionally, repeated intake of fampridine lowered resting motor threshold (F(1,37) = 5.31, P = 0.027, R2β = 0.01), the non-behavioral secondary outcome, indicating increased cortical excitability linked to cognitive function. Fampridine's capacity to enhance WM in low-performing individuals and to increase brain excitability points to its potential value for treating WM deficits.

Adult↗

PubMed2026

Influence of Major Histocompatibility Complex (MHC) Diversity on Immune Modulation, Pathogenesis, and Control of Lumpy Skin Disease Virus.

INTRODUCTION: Lumpy Skin Disease Virus (LSDV), a member of the genus Capripoxvirus within the family Poxviridae, is an economically important transboundary viral pathogen affecting cattle and water buffalo. The disease causes severe production losses through decreased milk yield, infertility, hide damage, reduced growth performance, and occasional mortality. The rapid geographic spread of LSDV, together with its vectorborne transmission and emerging recombinant strains, has intensified the need for improved understanding of viral pathogenesis, host immune responses, and effective prevention strategies. In particular, the role of the bovine Major Histocompatibility Complex (BoLA/MHC) in regulating antiviral immunity, disease susceptibility, and vaccine responsiveness has gained increasing scientific attention. METHODS: This review summarises the published literature related to the epidemiology, transmission, structure, pathogenesis, diagnosis, prevention, and control of LSDV, with special emphasis on the immunological and molecular role of bovine MHC molecules. Relevant studies concerning BoLA-mediated antigen presentation, immunoinformaticsbased epitope prediction, vaccine development, antiviral drug repurposing, molecular docking, genomic surveillance, and diagnostic approaches, including PCR- and ELISAbased assays, were critically evaluated. Recent advances in computational biology, molecular virology, and host-pathogen interaction studies were also reviewed. RESULTS: The reviewed studies demonstrate that Lumpy Skin Disease Virus (LSDV) possesses a complex double-stranded DNA genome enabling immune modulation and efficient transmission through arthropod vectors such as mosquitoes, ticks, and biting flies. Disease progression involves systemic viral replication, vascular injury, dermal necrosis, and inflammatory skin lesions. Real-time PCR remains the most sensitive diagnostic method for early detection, while ELISA supports surveillance. Evidence highlights the central role of bovine Major Histocompatibility Complex (BoLA) molecules in antigen presentation and T-cell activation. Computational studies identified promising BoLA-binding epitopes and repurposed antiviral candidates, including ivermectin, theaflavin, canagliflozin, and tepotinib, for future therapeutic development. DISCUSSION: Current evidence indicates that effective LSDV control requires integration of molecular diagnostics, vector management, vaccination, and host immunogenetics. BoLAguided immunoinformatics provides promising opportunities for developing multi-epitope vaccines, although experimental validation remains essential. Similarly, repurposed antiviral candidates require comprehensive in vivo and pharmacological evaluation before clinical application. Future research should focus on elucidating viral immune-evasion mechanisms, validating predicted epitopes, and translating computational findings into practical vaccines and therapeutics for sustainable disease control. CONCLUSION: Lumpy Skin Disease continues to pose a major threat to global cattle health and livestock economies. Advances in molecular diagnostics, genomic surveillance, antiviral drug discovery, and BoLA-guided vaccine design provide promising opportunities for improved disease control. Understanding the interaction between LSDV and the bovine MHC system is essential for developing next-generation vaccines, immunotherapeutics, and precision disease-management strategies. Future research should prioritise experimental validation of predicted epitopes, large-scale vaccine trials, and mechanistic studies on host-virus immune interactions to establish effective and sustainable global control programs for LSDV.

BoLA↗

PubMed2024

Evaluating culture-free targeted next-generation sequencing for diagnosing drug-resistant tuberculosis: a multicentre clinical study of two end-to-end commercial workflows.

BACKGROUND: Drug-resistant tuberculosis remains a major obstacle in ending the global tuberculosis epidemic. Deployment of molecular tools for comprehensive drug resistance profiling is imperative for successful detection and characterisation of tuberculosis drug resistance. We aimed to assess the diagnostic accuracy of a new class of molecular diagnostics for drug-resistant tuberculosis. METHODS: We conducted a prospective, cross-sectional, multicentre clinical evaluation of the performance of two targeted next-generation sequencing (tNGS) assays for drug-resistant tuberculosis at reference laboratories in three countries (Georgia, India, and South Africa) to assess diagnostic accuracy and index test failure rates. Eligible participants were aged 18 years or older, with molecularly confirmed pulmonary tuberculosis, and at risk for rifampicin-resistant tuberculosis. Sensitivity and specificity for both tNGS index tests (GenoScreen Deeplex Myc-TB and Oxford Nanopore Technologies [ONT] Tuberculosis Drug Resistance Test) were calculated for rifampicin, isoniazid, fluoroquinolones (moxifloxacin, levofloxacin), second line-injectables (amikacin, kanamycin, capreomycin), pyrazinamide, bedaquiline, linezolid, clofazimine, ethambutol, and streptomycin against a composite reference standard of phenotypic drug susceptibility testing and whole-genome sequencing. FINDINGS: Between April 1, 2021, and June 30, 2022, 832 individuals were invited to participate in the study, of whom 720 were included in the final analysis (212, 376, and 132 participants in Georgia, India, and South Africa, respectively). Of 720 clinical sediment samples evaluated, 658 (91%) and 684 (95%) produced complete or partial results on the GenoScreen and ONT tNGS workflows, respectively, with 593 (96%) and 603 (98%) of 616 smear-positive samples producing tNGS sequence data. Both workflows had sensitivities and specificities of more than 95% for rifampicin and isoniazid, and high accuracy for fluoroquinolones (sensitivity approximately ≥94%) and second line-injectables (sensitivity 80%) compared with the composite reference standard. Importantly, these assays also detected mutations associated with resistance to critical new and repurposed drugs (bedaquiline, linezolid) not currently detectable by any other WHO-recommended rapid diagnostics on the market. We note that the current format of assays have low sensitivity (≤50%) for linezolid and more work on mutations associated with drug resistance is needed. INTERPRETATION: This multicentre evaluation demonstrates that culture-free tNGS can provide accurate sequencing results for detection and characterisation of drug resistance from Mycobacterium tuberculosis clinical sediment samples for timely, comprehensive profiling of drug-resistant tuberculosis. FUNDING: Unitaid.

Humans↗

PubMed2026

Microglial PICALM: A novel genetic driver and therapeutic target in vascular dementia.

BACKGROUND: Vascular dementia (VaD) lacks well-defined genetic mechanisms. Cell-type-specific effects of GWAS loci remain unexplored. METHODS: We integrated single‑cell eQTL data (183 donors, eight cell types) with VaD GWAS (3624 cases, 475,484 controls) using Mendelian randomization and Bayesian colocalization, replicated in an independent cohort (2074 cases, 456,366 controls). Subtype, snRNA‑seq, cell‑cell communication, PheWAS, expression profiling, and drug prediction with BBB permeability assessment were performed. RESULTS: Microglial PICALM was the only robustly replicated signal (OR = 0.8334, p = 5.3 × 10⁻⁴; colocalization PP.H4 > 0.75). The effect was strongest in multiple infarctions dementia (OR = 0.7746). Exploratory snRNA-seq analysis (4 VaD vs. 4 controls; GSE282111) provided supporting evidence for microglial PICALM enrichment and downregulation (p < 0.001). PICALM‑high microglia showed enhanced neurovascular‑ and phagocytosis‑related communication (e.g., SPP1, GAS6, GRN). PheWAS revealed no pleiotropy. In silico drug repurposing prioritised three FDA-approved BBB-penetrant compounds (disopyramide, benzocaine, amantadine) as candidates warranting further mechanistic validation. CONCLUSIONS: Microglial PICALM is identified as a likely genetic determinant of VaD, especially in the multiple infarctions subtype. Upregulating PICALM may be associated with a neuroprotective microglial phenotype, highlighting PICALM as a candidate therapeutic target warranting further experimental validation.

Humans↗

PubMed2026

A comprehensive review of AI innovations for tackling antimicrobial resistance.

Antimicrobial resistance (AMR) represents a major global public health concern, rendering available antimicrobials ineffective and leading to infections that are difficult to treat. Artificial intelligence (AI) has been increasingly applied across the AMR continuum, including resistance prediction, rapid diagnostics, new antimicrobial discovery, drug repurposing, antimicrobial surveillance, and clinical decision support. In this review, we aim to highlight recent developments in the use of artificial intelligence (AI) to address antimicrobial resistance (AMR). In addition, we review computational methods that help interpret genomic, phenomic, clinical, and epidemiological data to support the development of treatment strategies and novel antimicrobial agents. The key issues addressed include data quality, model interpretability, external validation, regulatory requirements, privacy, and fairness. While AI is not a complete solution to AMR, it can certainly strengthen the global AMR response by complementing key areas of AMR such as antimicrobial stewardship, infection prevention, laboratory diagnostics, and global surveillance.

Antimicrobial resistance (AMR)↗

PubMed2026

Assessing the comorbidity between asthma and depression through polygenic risk scoring and time-to-event models.

BACKGROUND: Patients with asthma have an increased risk of developing depression, affecting their quality of life. To date, the processes contributing to this comorbidity remain unclear. METHODS: We integrated two large genome-wide association studies (88,486 patients with asthma and 447,859 controls; 412,024 patients with depression and 1,587,577 controls) with cross-sectional and longitudinal information available from the All of Us Research Program (N = 87,167) through polygenic risk scoring (PRS), Cox proportional-hazards models, one-sample Mendelian randomization (MR), and gene-set and drug-repurposing analyses. RESULTS: We observed that depression PRS was associated with increased asthma risk (hazard ratio, HR = 1.13, 95% CI = 1.09-1.17), also when accounting for comorbidity status (HR = 1.08, 95% CI = 1.04-1.12). Conversely, the effect of asthma PRS was null after accounting for comorbidity status. One-sample MR analysis showed an effect of depression genetic liability on asthma, ranging from beta = 0.36 ± 0.03 when considering a linear relationship to beta = 3.21 ± 0.31 when considering possible nonlinear relationships. Conversely, the effect of asthma genetic risk on depression was null after accounting for potential confounders. The gene-set analyses showed that asthma and depression polygenic risks share biological processes, molecular functions, and cellular components related to the immune system and the lung-brain axis. CONCLUSIONS: Genetic predisposition contributes to asthma-depression comorbidity through direct effects and shared pathogenic processes. These findings highlight the potential to develop targeted interventions to prevent and treat the co-occurrence of respiratory and neuropsychiatric disorders.

Comorbidity↗

PubMed2025

Genetic Architecture of Idiopathic Inflammatory Myopathies From Meta-Analyses.

OBJECTIVE: Idiopathic inflammatory myopathies (IIMs, myositis) are rare systemic autoimmune disorders that lead to muscle inflammation, weakness, and extramuscular manifestations, with a strong genetic component influencing disease development and progression. Previous genome-wide association studies identified loci associated with IIMs. In this study, we imputed data from two prior genome-wide myositis studies and analyzed the largest myositis data set to date to identify novel risk loci and susceptibility genes associated with IIMs and its clinical subtypes. METHODS: We performed association analyses on 14,903 individuals (3,206 patients and 11,697 controls) with genotypes and imputed data from the Trans-Omics for Precision Medicine reference panel. Fine-mapping and expression quantitative trait locus colocalization analyses in myositis-relevant tissues indicated potential causal variants. Functional annotation and network analyses using the random walk with restart (RWR) algorithm explored underlying genetic networks and drug repurposing opportunities. RESULTS: Our analyses identified novel risk loci and susceptibility genes, such as FCRLA, NFKB1, IRF4, DCAKD, and ATXN2 in overall IIMs; NEMP2 in polymyositis; ACBC11 in dermatomyositis; and PSD3 in myositis with anti-histidyl-transfer RNA synthetase autoantibodies (anti-Jo-1). We also characterized effects of HLA region variants and the role of C4. Colocalization analyses suggested putative causal variants in DCAKD in skin and muscle, HCP5 in lung, and IRF4 in Epstein-Barr virus (EBV)-transformed lymphocytes, lung, and whole blood. RWR further prioritized additional candidate genes, including APP, CD74, CIITA, NR1H4, and TXNIP, for future investigation. CONCLUSION: Our study uncovers novel genetic regions contributing to IIMs, advancing our understanding of myositis pathogenesis and offering new insights for future research.

Humans↗

PubMed2027

Screening of Antiviral Agents Against CHIKV Using Reporter Virus.

Chikungunya virus (CHIKV) causes a disease characterized by chronic musculoskeletal inflammation for which specific antivirals are not yet available. Currently, a supportive therapy to alleviate fever and pain is used, but it does not limit viral replication or the persistence of chronic arthritis symptoms. Thus, the identification and development of new active molecules against CHIKV is urgently needed. Here, we present a cell-based methodology that enables the implementation of a rapid and cost-effective strategy for high- and medium-throughput screening (HTS) of compounds, including repurposed drugs or novel molecules. This methodology allows for the identification of novel antiviral hits with a good activity and selectivity profile against CHIKV.

Antiviral Agents↗

PubMed2026

Association Between Ticagrelor and Glucose Homeostasis Regulation: Insights from Genetic and Transcriptomic Analyses.

Emerging evidence has demonstrated the additional therapeutic benefits of ticagrelor in acute coronary syndrome (ACS) patients with diabetes. However, the underlying mechanisms of this association remain elusive. Mendelian randomization (MR) analysis using genome-wide association study (GWAS) data on ticagrelor, plasma proteomics and type 2 diabetes was employed to identify causal mediator proteins. RNA sequencing (RNA-seq) of ticagrelor-treated HepG2 cells revealed the molecular pathways regulating glucose metabolism. Genetically proxied ticagrelor was significantly associated with a reduced risk of diabetes (OR = 0.859, 95% CI: 0.783-0.934, P = 7.98E-05), and 24.41% of this effect was mediated by upregulation of BDH2 protein. In vitro experiments confirmed the enhanced effect of ticagrelor on glucose consumption. Transcriptome analysis revealed that mitochondrial respiratory chain transfer and oxidative phosphorylation (OXPHOS) were significantly enriched, and genes related to ATP biosynthesis were significantly upregulated. These findings highlight the non-platelet function of ticagrelor in maintaining glucose homeostasis, providing insights into potential drug repurposing in the future.

Humans↗