Search Results (2,822)

Myeloproliferative neoplasms (MPNs) are clonal hematopoietic stem cell disorders driven mainly by somatic mutations in JAK2, CALR or MPL, but their clinical phenotype is also shaped by chronic inflammation, immune dysregulation, vascular complications and microenvironmental remodeling. Emerging evidence suggests that the gut microbiota may contribute to this inflammatory and immunometabolic landscape; however, the current literature remains heterogeneous and its translational relevance is still insufficiently defined. This critical narrative review maps the available evidence linking the gut microbiota, microbial metabolites and systemic microbial signatures to MPN biology. We distinguish direct human MPN data from indirect mechanistic evidence derived from studies of intestinal barrier dysfunction, thrombo-inflammation, hematopoietic regulation, allogeneic hematopoietic cell transplantation and infection risk. Across human MPN cohorts, the most consistent findings are not uniform changes in global microbial diversity, but rather alterations in specific immunoregulatory taxa, particularly reduced Firmicutes/Faecalibacterium-related communities and dysbiotic signatures associated with JAK2V617F status. Mechanistically, dysbiosis and impaired intestinal barrier integrity may facilitate low-grade endotoxemia, TLR4/NF-κB activation, cytokine amplification, endothelial activation and platelet priming. In parallel, microbial metabolites may influence hematopoietic stem cell programs, the bone marrow niche, megakaryopoiesis and thrombopoiesis. Treatment exposure and diet are relevant modifiers of the microbiota–inflammation axis, although available interventional data remain preliminary. Mendelian randomization and multi-omics studies provide hypothesis-generating evidence for microbiota–metabolome–MPN interactions, but require longitudinal validation, functional studies and contamination-aware analytical pipelines, especially for low-biomass blood and bone marrow samples. Microbiota-targeted strategies, including nutritional interventions and fecal or washed microbiota transplantation, represent promising but still investigational approaches, particularly in immunocompromised or post-transplant settings. Future studies should integrate microbiome, metabolome, genome, proteome, inflammatory biomarkers and clinical outcomes while controlling for diet, antibiotics, treatment exposure and driver mutation status. Such an approach may clarify whether the microbiota is a biomarker, mediator or therapeutic target in MPNs. Full article

The early-life lactational window is critical for gut microbial colonization, intestinal maturation, and long-term host metabolic and immune programming. Although antibiotic-induced microbiota perturbation models are widely applied to investigate microbiota function, the overall microbiota perturbation efficiency and comprehensive metabolic alterations induced by broad-spectrum antibiotics during the lactational stage remain poorly characterized. In this study, neonatal SD rat pups were continuously administered a broad-spectrum antibiotic cocktail to establish a lactational antibiotic-perturbed dysbiosis model. The early-life antibiotic intervention induced mild impairment of the intestinal structure and significantly increased the relative hindgut weight. 16S rRNA sequencing demonstrated significant reductions in microbial α-diversity, profound remodeling of gut microbial communities, extensive depletion of core beneficial genera including Akkermansia, Bifidobacterium, and Lactobacillus, and significant enrichment of opportunistic pathogens. Untargeted metabolomics further revealed widespread cecal metabolic perturbations following antibiotic-induced microbiota perturbation, including decreased biosynthesis of microbiota-derived vitamins, and comprehensive disorders in lipid, tyrosine, pteridine, and steroid hormone metabolism. Collectively, this study systematically characterized the microbiota perturbation efficiency and multiomic metabolic phenotypes of antibiotic-induced microbiota perturbation in suckling rats, clarifying the regulatory effects of lactational microbial perturbation on intestinal microecology and host metabolic homeostasis. These findings provide fundamental phenotypic data for the application of early-life antibiotic-perturbed dysbiosis models and further mechanistic exploration of host–microbe crosstalk during the critical developmental window. Full article

Grape-associated microbial communities are key contributors to wine quality and microbial terroir, yet their dynamics during withering, a critical post-harvest stage for premium sweet and fortified wine production, remain poorly characterized. Using high-throughput metabarcoding (16S rRNA and ITS), we monitored bacterial and fungal communities on Corvina grape berries throughout withering under controlled (C) and non-controlled (NC) dehydration conditions, integrating microbiome data with previously determined volatile organic compound (VOC) and stilbene profiles to uncover taxon–metabolite relationships. Microbial communities underwent progressive restructuring during dehydration. Moreover, the two withering conditions exhibited distinct dehydration kinetics, with C reaching 30% weight loss 14 days earlier than NC, with a significant effect on the abundance of several wine-relevant and spoilage-associated taxa. Metschnikowia was significantly more abundant under C conditions at 10% and 20% weight loss, while Botrytis reached 26.5% relative abundance at 30% weight loss under NC compared with 2.4% under C. A correlation network analysis identified significant associations between Lactobacillus, Acinetobacter, Clostridium, and metabolite accumulation, with Metschnikowia showing positive associations with bioactive compounds and negative associations with spoilage fungi. This first joint time-course analysis of mycobiome and bacteriome dynamics alongside metabolome changes during withering highlights significant associations between microbial succession and grape biochemical changes during withering. Full article

Pometia pinnata J.R. Forst. & G. Forst. is traditionally used throughout tropical Asia and the Pacific to manage diabetes-associated hyperglycemia. However, the metabolites responsible for its α-glucosidase inhibitory activity (AGI) remain poorly characterized. This study aimed to identify putative AGI-associated metabolites from P. pinnata stem bark through metabolomics-based prioritization and tentative annotation using untargeted LC–HRMS, followed by molecular docking to assess their interactions with α-glucosidase. Thirty ethyl acetate–methanol gradient fractions were analyzed by orthogonal partial least squares (OPLS) to prioritize LC–HRMS features associated with AGI activity, followed by molecular docking of the tentatively annotated metabolites against Saccharomyces cerevisiae α-glucosidase (3A4A) and human maltase-glucoamylase (3TOP). The 75% ethyl acetate in methanol fraction showed the strongest AGI, with an IC₅₀ of 5.53 μg/mL. Five AGI-associated metabolites, namely scopoletin, 3,4-dihydroxybenzaldehyde, fisetin, 4-methoxycinnamic acid, and lindetannin, were tentatively annotated in P. pinnata stem bark based on LC-HRMS/MS data. To the best of our knowledge, these annotations have not previously been reported in P. pinnata stem bark. Among these candidates, fisetin showed the most favorable binding interactions with both target enzymes. Metabolomics-guided isolation, followed by NMR analysis, confirmed the structure of scopoletin, although the isolated compound showed weak AGI activity (IC₅₀ > 200 μg/mL). The marked difference between the parent fraction and isolated scopoletin indicates that scopoletin alone is unlikely to account for the observed activity and that other constituents may contribute. Nevertheless, this study provides a promising metabolomics-guided framework for prioritizing and tentatively annotating candidate AGI-associated metabolites in the stem bark of P. pinnata. Full article

Environmental nanomaterials (ENMs) are increasingly entering agroecosystems through industrial discharges, agricultural chemicals, nanotechnology, and atmospheric deposition. Consequently, a comprehensive understanding of their interactions with plants across growth stages is essential. This narrative review synthesizes current insights into nanomaterial uptake pathways, translocation dynamics, and intracellular trafficking from seed germination to reproductive maturity. It highlights the use of integrative multi-omics techniques, namely transcriptomics, proteomics, metabolomics, and epigenomics, to elucidate molecular reprogramming in response to ENMs exposure. The data indicates that nanomaterials can significantly affect seed vigor, root architecture, photosynthetic efficiency, and other yield-related traits through coordinated regulation of stress-responsive genes, antioxidant defense mechanisms, and phytohormonal signaling pathways. Furthermore, the review underscores the role of epigenetic modifications, including DNA methylation and histone remodeling, as critical regulatory layers that govern both transient and heritable plant responses to ENMs. Metabolomic remodeling, particularly the biosynthesis of secondary metabolites and redox-related pathways, represents the primary adaptive response linking molecular disturbances to phenotypic outcomes. This manuscript proposes a systems-level framework for evaluating nano–plant interactions, bridging nanoscale physicochemical properties with physiological and yield-level outcomes. Collectively, this integrative perspective aims to enhance mechanistic clarity, support the development of predictive and sustainable nanotechnology applications in agriculture, and identify critical gaps in long-term ecological and transgenerational assessments. Full article

Hypertension (HTN) is often asymptomatic and difficult to detect using blood pressure (BP) measurements unless BP is substantially elevated. Given its association with metabolic alterations and complications, this study aimed to establish a metabolite risk score (MRS) as a molecular tool to complement BP-based diagnosis. Plasma samples and clinical data from healthy individuals and HTN patients were obtained through the Korea Biobank Network, and non-targeted metabolomics was performed. Eight HTN-associated key metabolites were selected by least absolute shrinkage and selection operator (LASSO) regression. An MRS was calculated as their weighted sum in the discovery set and subsequently validated in the replication set. The MRS showed strong discriminative performance for HTN status in the replication set [area under the curve (AUC) = 0.926, 95% confidence interval (CI): 0.876–0.976] and remained significantly associated with prevalent HTN after adjustment for age and BMI [odds ratio (OR) = 1.747, 95% CI: 1.317–2.318, p < 0.001]. At the MRS cut-off, classification accuracy in the replication set was approximately 84%, with 83.7% sensitivity and 84% specificity. The MRS also showed weak-to-moderate positive correlations with systolic BP in both the discovery set (r = 0.320, p = 0.001) and the replication set (r = 0.335, p < 0.001); however, these correlations were no longer statistically significant after adjustment for age and BMI. These findings support further evaluation of the MRS as a complementary molecular approach for HTN discrimination. Integration with other omics platforms may facilitate the development of more comprehensive molecular approaches for HTN. Further validation in larger prospective longitudinal cohorts is required before its potential clinical application. Full article

Climate change is intensifying drought, salinity, heat, chilling, flooding, and heavy-metal stresses across major fruit-producing regions, threatening yield stability and fruit quality in economically vital, perennial crops such as apple, grapevine, citrus, banana, strawberry, and peach. Because these species are long-lived, highly heterozygous, and polyploid, conventional breeding for climate resilience remains slow and often inadequate, necessitating molecular strategies informed by systems-level understanding. This review synthesizes recent advances in multi-omics research spanning genomics, transcriptomics, proteomics, metabolomics, epigenomics, ionomics, and phenomics that have collectively decoded the regulatory architecture underlying abiotic stress perception, signaling, and tolerance in fruit crops. Hormonal networks, particularly abscisic acid (ABA) crosstalk with jasmonate, salicylic acid, ethylene, and brassinosteroids, emerge as central integrators of stress responses, coordinating stomatal regulation, osmolyte accumulation, antioxidant defense, and secondary metabolite biosynthesis. Genomic and pangenomic approaches have identified stress-associated loci and cultivar-specific structural variants, while transcriptomic and proteomic studies reveal transcription factor networks (MdERF38–MdMYB1, MaMYB4–MaHDA2, VvDREB1, CsNAC29) and post-translational regulatory switches governing tolerance mechanisms across drought, cold, salinity, and flooding stress. Metabolomic and ionomic profiling link biochemical reprogramming to fruit quality traits, whereas epigenomic mechanisms including DNA methylation, histone modifications, and small RNA regulation provide a chromatin-level layer mediating stress memory across growing seasons. Integration of these omics layers through systems biology, machine learning, and high-throughput phenomics is enabling functional validation via CRISPR-Cas9 and marker-assisted selection, translating correlative associations into causally validated breeding targets. Despite this progress, challenges including batch effects, tissue heterogeneity, and methodological inconsistencies in data integration continue to constrain translational applications. This highlights convergent regulatory hubs across stress types and species, underscoring multi-omics-guided precision breeding as the most promising pathway toward developing climate-resilient, high-quality fruit crop cultivars for sustainable global production. Full article

Background/Objectives: Cytochrome P450(CYP)2C19 activity varies widely among individuals. As genetic factors, CYP2C19*2 and CYP2C19*3 alleles reduce CYP2C19 activity, while the CYP2C19*17 allele increases CYP2C19 activity. However, environmental and physiological factors can also influence individual CYP2C19 activity. In this study, we searched for novel endogenous biomarkers for CYP2C19 activity using CYP2C19 gene polymorphism data combined with results of untargeted metabolomic analysis. Methods: 431 general adults analyzed in the Kyoto J-MICC Study and 255 patients who visited Oita University Hospital were studied. Plasma samples were pretreated by solid-phase and liquid-liquid extraction and subjected to untargeted metabolomic analysis using ultra-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry. Based on CYP2C19 gene polymorphism data, participants were classified into extensive metabolizers (EM), intermediate metabolizers (IM), and poor metabolizers (PM). Compounds showing significant differences in abundance among the three groups were considered candidate compounds for predicting CYP2C19 activity. The predictive performance of candidate compounds for CYP2C19 PM status was evaluated using covariate-adjusted receiver operating characteristic (ROC) analysis. Results: The normalized abundance of compounds with m/z 160.1342, 303.2319 (a fatty acyl or prenol lipid), 314.2309, 449.3238, 653.3021, 792.5744, and 811.5988 (a glycerophospholipid or sphingolipid), and 902.5404 (a fatty acyl) differed significantly among CYP2C19 EM, IM, and PM groups (p < 0.05), and these eight compounds were considered candidate compounds. Covariate-adjusted ROC analysis showed that none of the candidate compounds significantly improved the discrimination of CYP2C19 PM status. Conclusions: Untargeted metabolomics combined with CYP2C19 gene polymorphism data yielded eight compounds associated with CYP2C19 phenotype. Further studies are needed to evaluate the usefulness of these compounds as biomarkers of CYP2C19 activity. Full article

GLP-1 receptor agonists (GLP-1RAs), dual GLP-1/GIP agonists, and the more recent triple GLP-1/GIP/glucagon agonists have transformed the treatment of type 2 diabetes mellitus (T2DM) and obesity, resulting in significant weight reduction. However, a substantial proportion (20–40%) of this weight loss is attributable to a decrease in lean mass, thereby raising concerns regarding potential sarcopenia-related risk. However, decreased lean mass is not sufficient to determine sarcopenia, which is now defined by the combined presence of decreased muscle mass, diminished strength, and impaired physical function, particularly in older or frail individuals. Thus, a further clarification of the potential mechanisms through which these molecules affect skeletal muscle is needed to optimize their use. The objective of this study is to synthesize preclinical, metabolomic, and clinical evidence on the effects of GLP-1RAs and dual/triple agonists on skeletal muscle, with a specific comparison between semaglutide and tirzepatide. This narrative review was based on a comprehensive literature search of PubMed/MEDLINE, Scopus, and Google Scholar, encompassing articles published through June 2026. This search was supplemented by manual citation tracking, which identified additional studies including preclinical and metabolomic investigations, randomized controlled trials, observational studies, and meta-analyses. Preclinical data suggest that GLP-1R/GIPR activation can positively modulate anabolic pathways, mitochondrial biogenesis, and muscle inflammation. Metabolomic evidence reveals lipid and amino acid remodeling compatible with improved mitochondrial function. Clinically, lean mass loss proportional to weight reduction is consistently observed, generally without meaningful declines in strength or performance; data for tirzepatide are more limited. Lean mass, however, is not synonymous with skeletal muscle. A paradox emerges between the presence of protective molecular signals and the clinical evidence of lean-mass loss. This phenomenon may be explained by a systemic energy/protein deficit rather than a direct catabolic effect of the drugs, although current evidence does not fully distinguish these mechanisms. The effectiveness of weight reduction should be considered a pivotal metric in clinical practice, particularly in populations susceptible to sarcopenia. Full article

Rabbit odontogenic abscesses are among the most challenging chronic infections encountered in exotic animal medicine because of their polymicrobial etiology, biofilm-associated persistence, and poor response to conventional antimicrobial therapy. Biofilm formation plays a central role in disease pathogenesis by promoting bacterial adhesion, extracellular polymeric substance (EPS) production, quorum sensing (bacterial cell-to-cell communication), metabolic heterogeneity, and the persister-cell formation (transiently antibiotic-tolerant bacterial subpopulations), collectively reducing antimicrobial susceptibility and contributing to treatment failure and recurrence. In addition to biofilm-mediated tolerance, antimicrobial resistance (AMR) further complicates disease management through mechanisms including horizontal gene transfer, efflux pump activation, enzymatic antibiotic degradation, reduced membrane permeability, and target modification. This review summarizes current knowledge on the microbiology, biofilm dynamics, and resistance mechanisms associated with rabbit odontogenic infections while examining recent advances in molecular diagnostics, including culture-independent sequencing technologies, metagenomics, and advanced imaging approaches. Current and emerging anti-biofilm strategies, such as local antimicrobial delivery systems, enzymatic biofilm disruption, quorum-sensing inhibitors, bacteriophage therapy, antimicrobial peptides, photodynamic therapy, and nanotechnology-based approaches, are critically discussed in the context of their potential application in rabbits. Comparative evidence from human endodontic infections and other veterinary biofilm-associated diseases highlights the translational relevance of rabbit odontogenic abscesses as a naturally occurring model for chronic polymicrobial infections. Finally, key research gaps are identified, emphasizing the need for standardized experimental models, integrated multi-omics analyses, combining genomic, transcriptomic, proteomic, and metabolomic data, longitudinal clinical investigations, and evidence-based antimicrobial stewardship. By integrating microbiology, biofilm biology, antimicrobial resistance, and One Health concepts, this review provides a comprehensive framework to support future research and improve the diagnosis, treatment, and prevention of rabbit odontogenic infections. Full article

Background: Hyperuricemic nephropathy (UAN) involves a systemic thromboinflammatory axis, yet the role of antithrombin (AT, SERPINC1) remains incompletely defined. While AT has anticoagulant and anti-inflammatory properties, whether it contributes to UAN as a disease-responsive molecular node remains uncertain. Methods: We integrated two-sample MR of serum urate and renal traits with complementary sensitivity analyses, cis-eQTL and pQTL analyses of SERPINC1, and exploratory transcriptomic, proteomic, metabolomic, and coexpression analyses. The available data were used to assess genetic associations and to distinguish genetic evidence from cross-dataset molecular patterns. Results: Genetically predicted serum urate showed positive or negative associations with BUN and eGFR, respectively, but the primary analyses showed substantial heterogeneity. Reverse-direction estimates were also associated with serum urate, representing reciprocal genetic relationships between related renal traits and urate rather than proof of a temporal feedback cycle. Available data did not demonstrate mediation through genetically predicted whole-blood SERPINC1 expression. Three deCODE cis-pQTL instruments gave inconsistent renal estimates: nominally lower BUN (β = −0.0290, p = 0.047), null eGFR (β = −0.0036, p = 0.472), and higher CKD risk (β = +0.3361, p = 0.020) with directional pleiotropy evidence. Exploratory multi-omics analyses showed higher PBMC SERPINC1 expression during acute gout and a nominal urinary proteomic difference that did not survive multiple-testing correction (FDR = 0.998). Conclusions: SERPINC1 is best interpreted as a responsive molecular feature requiring further validation, rather than as a demonstrated genetic mediator or renal-protective therapeutic target. The transcriptomic and urinary findings represent cross-dataset, stage-associated observations and should not be interpreted as proven sequential phases. Full article

Background: Obesity is a metabolic disorder characterized by excessive lipid accumulation, disrupted fatty acid homeostasis, and gut microbiota dysbiosis. Zanthoxylum bungeanum essential oil (ZBO) is a natural plant volatile oil with diverse bioactivities, but its anti-obesity effects and potential associations remain unclear. Methods: HFD-induced obese (DIO) mice were evaluated to determine the effects of ZBO. Physiological parameters, glucose tolerance, and serum biochemical markers were assessed. Potential correlates were explored using a multi-omics approach, including integrated serum untargeted metabolomics, 16S rRNA gene sequencing, and RT-qPCR analysis of key genes involved in lipid metabolism in the liver and white adipose tissue. Results: ZBO significantly mitigated HFD-induced body weight gain, visceral adiposity, hepatic steatosis, dyslipidemia, and glucose intolerance. Metabolomics indicated that ZBO administration was associated with alterations in the serum metabolic landscape, particularly in pathways related to fatty acid metabolism and AMPK/PPAR-α signaling. Consistently, ZBO treatment was associated with upregulated mRNA expression of lipid-oxidizing genes (AMPK, PPAR-α, CPT1) and downregulated lipogenic genes (SREBP-1c, ACC, FAS, SCD1, LPL). 16S rRNA sequencing suggested that ZBO was associated with increased gut microbial diversity, decreased the Firmicutes/Bacteroidota ratio, and enriched beneficial taxa (e.g., Ligilactobacillus, Alistipes) while suppressing pro-inflammatory genera. Correlation analysis established robust associations between ZBO-modulated microbes and key fatty acid metabolites, particularly acylcarnitines and AMPK/PPAR-α-related intermediates. Conclusions: Collectively, these multi-omics data suggest that ZBO administration is associated with remodeling of the gut microbiota and correlated changes in fatty acid metabolic pathways. These findings provide preliminary preclinical evidence supporting further investigation of ZBO in the context of dietary strategies for alleviating HFD-induced obesity. Full article

Background: Traditional bulk tissue analyses obscure the precise spatial compartmentalization of nicotine and its molecular effects within individual anatomical regions. This study aimed to develop and apply a high-resolution spatial multi-omics framework to characterize the localized disposition and functional responses induced by an acute nicotine challenge. Methods: We established a spatial multi-omics framework integrating matrix-assisted laser desorption/ionization time-of-flight mass spectrometry imaging (MALDI-TOF MSI), air-flow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI), laser microdissection (LMD)-based microscale data-independent acquisition (microDIA) proteomics, and targeted LC-MS/MS. This platform was used to analyze the kidney and five brain regions in rats subjected to an acute nicotine challenge following an adaptation regimen. Results: Spatial mapping revealed distinct peripheral and central distribution patterns: nicotine, cotinine, and nornicotine accumulated predominantly in the renal cortex and medulla, whereas their distribution in the brain is region-dependent, with a prominent 3-hydroxycotinine signal in the olfactory bulb. Avoiding tissue homogenization enabled these spatial distributions to be linked to localized functional responses. The striatal dopamine/DOPAC axis showed the strongest acute neurochemical response, consistent with increased dopamine turnover. Spatial metabolomics further demonstrated robust, region-specific metabolic reprogramming, with the hippocampus showing the greatest metabolic variance. LMD-resolved proteomics identified protein-level changes, particularly in the olfactory bulb and thalamus. Cross-omics revealed coordinated alterations in purine, pyrimidine, glycerophospholipid, and alanine/aspartate/glutamate metabolism, with the thalamus showing the greatest extensive metabolite–protein concordance. Conclusions: These findings characterize acute nicotine exposure as a spatially compartmentalized process involving renal handling, region-specific brain distribution, and localized molecular response programs. Full article

Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) has become the most common chronic liver disease in childhood, paralleling the global increase in pediatric obesity and metabolic dysfunction. Once considered a benign condition, pediatric MASLD is now recognized as a heterogeneous and potentially progressive disease that may advance from simple steatosis to steatohepatitis, fibrosis, and, rarely, cirrhosis, with lifelong hepatic and cardiometabolic consequences. Its pathogenesis is multifactorial, involving insulin resistance, adipose tissue dysfunction, chronic low-grade inflammation, genetic and epigenetic susceptibility, environmental factors, and alterations in the gut microbiome. Most affected children are asymptomatic, and diagnosis is often prompted by elevated liver enzymes or incidental imaging findings. Noninvasive tools, including ultrasonography, elastography, serum biomarkers, and emerging multi-omics approaches, are improving disease detection and risk stratification, although liver biopsy remains the reference standard in selected cases. Lifestyle modification, including dietary optimization, increased physical activity, and gradual weight reduction, remains the cornerstone of management, while pharmacological therapies are still under investigation in pediatric populations. The marked variability in disease susceptibility; progression; and treatment response underscores the need for a personalized medicine approach. Integrating clinical characteristics with genomic, epigenomic, metabolomic, and microbiome data may enable early identification of high-risk children, more accurate prognostic assessment, and individualized preventive and therapeutic strategies. Early detection and multidisciplinary care involving pediatricians, hepatologists, endocrinologists, dietitians, and families may help reduce disease progression and the risk of long-term hepatic and cardiometabolic complications. This review summarizes current evidence on the epidemiology, pathophysiology, clinical presentation, diagnosis, and management of pediatric MASLD, with a particular emphasis on precision diagnostics, biomarker discovery, and personalized therapeutic approaches. It also discusses current challenges and future directions for implementing personalized medicine to improve outcomes and reduce the lifelong burden of pediatric MASLD. Full article

Nuclear magnetic resonance (NMR)-based metabolomics has emerged as a robust and reproducible analytical platform for investigating the molecular mechanisms underlying disease and identifying candidate biomarkers with potential clinical relevance. Although initially developed for biomedical research, its application in veterinary medicine has expanded rapidly during the last decade, driven by the growing demand for precision medicine approaches capable of improving disease diagnosis, prognosis and therapeutic monitoring. This review summarizes the current landscape of NMR metabolomics in veterinary medicine, highlighting its applications across major clinical areas, including oncology, infectious, respiratory, digestive, renal, endocrine and musculoskeletal diseases. Collectively, the available evidence demonstrates that NMR metabolomics consistently identifies disease-associated metabolic alterations, providing novel insights into pathophysiology while supporting biomarker discovery in naturally occurring animal diseases. Beyond current clinical applications, we discuss the major challenges that continue to limit routine implementation, including biological variability, standardization of analytical workflows, multicentre validation and clinical translation. Particular attention is given to recent technological advances, such as benchtop NMR instrumentation, artificial intelligence-assisted data analysis, multi-omics integration and the development of collaborative networks and standardized platforms. Together, these advances position NMR metabolomics as a promising technology to support precision veterinary medicine, facilitating its transition from biomarker discovery to routine clinical implementation. Full article