Search Results (101)

Equine asthma is a chronic respiratory disease characterised by neutrophilic inflammation, airway hyperresponsiveness, and impaired pulmonary function. Obesity, increasingly prevalent among domestic horses, has been identified as a potential risk factor for exacerbating inflammatory conditions. This study aimed to explore whether obesity modifies neutrophil metabolism and inflammatory responses in horses affected by asthma. Six asthmatic horses in clinical remission were categorised into two groups: obese and non-obese, based on body condition score. Serum levels of interleukin-1β (IL-1β) and peripheral blood neutrophil counts were significantly higher in obese horses, indicating a heightened systemic inflammatory state. Neutrophils from obese horses displayed a stronger oxidative burst following zymosan stimulation and elevated IL-1β gene expression in response to lipopolysaccharide, suggesting a hyperinflammatory phenotype. Metabolomic profiling of neutrophils identified 139 metabolites, with notable differences in fatty acids, branched-chain amino acids, and tricarboxylic acid (TCA) cycle intermediates. Pathway enrichment analysis revealed significant alterations in fatty acid biosynthesis, amino acid metabolism, and glutathione-related pathways. Elevated levels of itaconate, citraconic acid, and citrate in obese horses indicate profound metabolic reprogramming within neutrophils. These results suggest that obesity promotes a distinct neutrophil phenotype marked by increased metabolic activity and heightened responsiveness to inflammatory stimuli. This altered profile may contribute to the persistence or worsening of airway inflammation in asthmatic horses. The findings underscore the importance of addressing obesity in the clinical management of equine asthma and open avenues for further research into metabolic-targeted therapies in veterinary medicine. Full article

Short-chain fatty acids (SCFAs) are microbial metabolites involved in immune regulation, energy metabolism, and intestinal barrier integrity. Among them, the role of hexanoic acid (C6), predominantly derived from dietary sources, remains poorly understood in chronic heart failure (CHF) and sarcopenia. A total of 636 patients with confirmed CHF were screened between 2019 and 2021. Sarcopenia was diagnosed in 114 patients, with 74 meeting the inclusion criteria for analysis. Plasma levels of SCFAs—including butanoic, propanoic, isobutyric, 2- and 3-methylbutanoic, hexanoic, pentanoic, and 4-methylpentanoic acids—were measured using HPLC-MS/MS. Muscle strength, mass, and physical performance were assessed using handgrip dynamometry, bioelectrical impedance analysis, and SPPB, respectively. All patients showed elevated SCFA levels compared to reference values. Butanoic acid levels exceeded reference values by 32.8-fold, propanoic acid by 10.9-fold, and hexanoic acid by 1.09-fold. Patients with plasma hexanoic acid levels above the 50th percentile had a seven-fold increased mortality risk (OR = 7.10; 95% CI: 1.74–28.9; p < 0.01). Kaplan–Meier analysis confirmed significantly lower survival in this group (p = 0.00051). The mean left ventricular ejection fraction was 41.2 ± 7.5%, and the mean SPPB score was 6.1 ± 1.8, indicating impaired physical performance. Elevated plasma hexanoic acid is associated with poor prognosis in CHF patients with sarcopenia. These findings suggest that C6 may serve as a potential prognostic biomarker and therapeutic target in this population. Full article

Background and Objectives: Breast cancer accounts for 12.5% of all new cancer cases in women worldwide. Early detection significantly improves survival rates, but traditional biomarkers like CA 15-3 and HER2 lack sensitivity and specificity, particularly for early-stage disease. Advances in metabolomics and machine learning, particularly explainable artificial intelligence (XAI), offer new opportunities for identifying robust biomarkers and improving diagnostic accuracy. This study aimed to identify and validate serum-based metabolic biomarkers for breast cancer using advanced metabolomic profiling techniques and a Light Gradient Boosting Machine (LightGBM) model. Additionally, SHapley Additive exPlanations (SHAP) were applied to enhance model interpretability and biological insight. Materials and Methods: The study included 103 breast cancer patients and 31 healthy controls. Serum samples underwent liquid and gas chromatography–time-of-flight mass spectrometry (LC-TOFMS and GC-TOFMS). Mutual Information (MI), Sparse Partial Least Squares (sPLS), Boruta, and Multi-Objective Feature Selection (MOFS) approaches were applied to the data for biomarker discovery. LightGBM, AdaBoost, and Random Forest were employed for classification and to identify class imbalance with the Synthetic Minority Oversampling Technique (SMOTE). SHAP analysis ranked metabolites based on their contribution to model predictions. Results: Compared to other feature selection approaches, the MOFS approach was more robust in terms of predictive performance, and metabolites identified by this method were used in subsequent analyses for biomarker discovery. LightGBM outperformed the AdaBoost and Random Forest models, achieving 86.6% accuracy, 89.1% sensitivity, 84.2% specificity, and an F1-score of 87.0%. SHAP analysis identified 2-Aminobutyric acid, choline, and coproporphyrin as the most influential metabolites, with dysregulation of these markers associated with breast cancer risk. Conclusions: This study is among the first to integrate SHAP explainability with metabolomic profiling, bridging computational predictions and biological insights for improved clinical adoption. This study demonstrates the effectiveness of combining metabolomics with XAI-driven machine learning for breast cancer diagnostics. The identified biomarkers not only improve diagnostic accuracy but also reveal critical metabolic dysregulations associated with disease progression. Full article

Objectives: Equol, a gut-derived metabolite of soy isoflavones with estrogenic activity, may influence bladder aging. However, the association between overactive bladder (OAB), which is closely linked to bladder aging, and the estrogenic effects of equol remains unknown. Therefore, this study investigated the association between endogenous equol production and onset and severity of OAB in postmenopausal women. Methods: The study included 128 postmenopausal women, newly diagnosed with OAB, who were categorized into equol- and non-equol-producing groups based on urinary equol levels as measured by enzyme-linked immunosorbent assay. Patient clinical characteristics, OAB Symptom Score (OABSS), and urodynamic parameters were assessed. Propensity score matching was performed to minimize confounding factors related to the timing of lower urinary tract symptom (LUTS) onset. Results: Equol producers exhibited a significantly later onset of LUTS than non-producers (68.7 ± 10.9 vs. 62.7 ± 10.7 years, p = 0.002). Equol producers were more prevalent in the late-onset group (58.6% vs. 31.0%, p = 0.002), which had significantly higher urinary equol concentrations than the early-onset group (p = 0.014). No significant differences were observed in total OABSS or subscale scores between the groups, suggesting that equol did not affect symptom severity. Propensity score-matched analysis (n = 104) confirmed that equol non-production was an independent risk factor for early-onset LUTS (OR, 1.930; 95% CI, 1.248–4.049; p = 0.014). Conclusions: Endogenous equol production was significantly associated with the delayed onset of OAB in postmenopausal women. Thus, equol may serve as a protective factor and non-invasive biomarker to guide individualized prevention and early intervention strategies in urological care for women. Full article

Background: Walking ability is important for the quality of life of older adults. A self-reported walking ability index (WAI) covering the difficulty and ease of walking captures a broader spectrum of walking ability in healthy older persons. Methods: Using metabolomics in the Health, Aging and Body Composition study, we identified Year 2 metabolites cross-sectionally and longitudinally related to WAI (0–9, higher scores indicate better walking ability) using probabilistic index models and multinomial logistic models, respectively. Results: Among 2334 participants (mean age 74.6 years, 51% women, 37% Black), 27% scored 0–5, 36% scored 6–8, and 37% scored 9 at Year 2. Over 4 years, 52% maintained a stable WAI, 6% improved, while 42% declined (22% 1–2 points and 20% >2 points decline). We identified 81 metabolites significantly associated with both poorer concurrent WAI and faster decline, including higher acylcarnitine species, shorter-chain saturated diglycerides and triglycerides, and TCA cycle intermediates (cis-aconitic, fumaric, and malic acids), and lower phospholipids levels. Eighteen additional metabolites were only associated with faster WAI decline: higher short-chain saturated triglycerides and energy metabolism markers (ATP/ADP/AMP) and lower margaric acid and glycine levels. Notably, those with improved WAI, despite poorer baseline WAI and lifestyles, showed more favorable metabolic profiles than others. Conclusions: Metabolites linked to the TCA cycle and energy metabolism, as well as inflammation and protein catabolism, were related to mobility function. Some metabolites might be particularly important for the early detection of older adults at risk of mobility decline. Metabolic profiles may also help identify older individuals (i.e., with improving WAI) with greater metabolic resilience to lifestyle risk factors and health conditions. Full article

Rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) are autoimmune diseases associated with chronic inflammation and cardiovascular risk. This study aimed to identify metabolic alterations in Colombian women with RA and SLE to discover potential biomarkers. Plasma samples were analyzed using LC-QTOF-MS and GC-QTOF-MS. Correlation network analysis assessed relationships between metabolites, cytokines, and HDL levels. A generalized linear model (GLM) combined metabolite scores, and ROC analysis evaluated their predictive performance. Significant metabolic changes were observed, including decreased phospholipids and sphingolipids, and increased glycerolipids in RA and SLE compared to healthy controls. The metabolite–cytokine network revealed correlations between FA 18:0 and DG 37:7 with cytokines, linking lipid metabolism to inflammation. PS O-40:3 and FA 18:0 in RA and PC O-28:0 and DG 37:7 in SLE distinguished patients from healthy controls. The combination of PS O-40:3 and FA 18:0 in RA (AUC = 0.997) and PC O-28:0 and DG 37:7 in SLE (AUC = 0.949) demonstrated high predictive performance. PE O-42:5 was positively correlated with HDL, suggesting a potential protective role against cardiovascular disease. These findings highlight lipid metabolism’s role in RA and SLE and support specific metabolites as biomarkers for disease differentiation, inflammation, and cardiovascular risk. These insights could lead to improved diagnostics and targeted treatments for these autoimmune diseases. Full article

Background/Objectives: Metabolite risk score (MRS), which considers the collective effects of metabolites closely reflecting a phenotype, is a new approach for disease assessment, moving away from focusing solely on individual biomarkers. This study aimed to investigate a metabolite panel for dyslipidemia and verify the diagnostic efficacy of MRS on dyslipidemia. Methods: Key metabolite identification and MRS establishment were conducted in the discovery set, and MRS validation was performed in the replication set, with 50 healthy individuals and 50 dyslipidemia patients in each set. The MRS was constructed using key metabolites, identified via UPLC-MS/MS analysis, employing a weighted approach based on linear regression analysis. Results: N-acetylisoputreanine-γ-lactam and eicosapentaenoic acid were identified as key metabolites for dyslipidemia and were utilized for establishing the MRS. In addition to the MRS model, a conventional dyslipidemia diagnostic model based on lipid profiles, as well as a combined model (MRS + lipid profiles), were also established. In the discovery set, the MRS model diagnosed dyslipidemia with 85.4% accuracy. When combined with lipid profiles, accuracy improved to 91.8%. In the replication set, the MRS demonstrated diagnostic power with 76.1% accuracy, while the combined model achieved 86.0% accuracy for dyslipidemia assessment. Conclusions: The MRS alone indicated sufficient assessment power in a real-world setting, despite a slight reduction in assessment ability when validated in the replication set. At this stage, therefore, the MRS serves as an auxiliary tool for disease diagnosis. This first attempt to apply MRS for dyslipidemia may offer a foundational concept for MRS in this disease. Full article

The numerous side effects and adverse health implications associated with chemotherapies have long plagued the field of cancer care. Whilst in some cases a curative measure, this highly toxic intervention consistently scores poorly on quantitative measures of tolerability and safety. Of these side effects, cardiac and microvascular defects pose the greatest health risk and are the leading cause of death amongst cancer survivors who do not succumb to relapse. In fact, in many low-grade cancers, the risk of recurrence is far outweighed by the cardiovascular risk of morbidity. As such, there is a pressing need to improve outcomes within these populations. Polyphenols are a group of naturally occurring metabolites that have shown potential vasoprotective effects. Studies suggest they possess antioxidant and anti-inflammatory activities, in addition to directly modulating vascular signalling pathways and gene expression. Leveraging these properties may help counteract the vascular toxicity induced by chemotherapy. In this review, we outline the main mechanisms by which the endothelium is damaged by chemotherapeutic agents and discuss the ability of polyphenols to counteract such side effects. We suggest future considerations that may help overcome some of the published limitations of these compounds that have stalled their clinical success. Finally, we briefly explore their pharmacological properties and how novel approaches could enhance their efficacy while minimising treatment-related side effects. Full article

Background/Objectives: Purinergic signaling, which involves extracellular ATP (eATP), its metabolites, purinergic receptors and ectonucleotidases, plays a pivotal role in the tumor microenvironment (TME), impacting tumor progression and the antineoplastic immune response. In this study, the CD39, CD73, P2X4, and P2X7 expression in NSCLC tumor cells and the surrounding stroma of 139 resected patients was examined. Methods: The study included tissue samples from 139 NSCLC patients. Tissue microarrays (TMAs) were constructed using 1.0 mm cores from annotated tumor regions. Immunohistochemical staining for CD39, CD73, P2X4, and P2X4 was performed on 2 µm sections. TMA slides were digitized and analyzed with QuPath, where staining intensity was evaluated using a semi-quantitative H-score. Statistical analysis, including survival analysis, was performed using R, to assess the impact of biomarker expression on patient outcomes. Results: High CD39 expression in both tumor and stromal cells was significantly associated with prolonged PFS (respectively: p = 0.0058 and p = 0.0067), particularly in adenocarcinoma (ADC) patients (respectively: p = 0.01 and p = 0.023). In the multivariable Cox model, low CD73 expression in tumor cells correlated with longer PFS (HR: 0.47; 95% CI: [0.28, 0.8], p = 0.005), while low CD73 expression in stromal cells was linked to increased progression risk (HR: 4.81; 95% CI: [1.61, 14.4], p = 0.001). Neither P2X7 nor P2X4 demonstrated a consistent effect on PFS in univariable analyses; however, multivariable analyses suggested that P2X4 might play a prognostic role in NSCLCs (HR: 0.37; 95% CI: [0.19, 0.73], p = 0.003). Conclusions: These findings underscore the importance of purinergic signaling in NSCLC prognosis and highlight the role of the ectonucleotidases CD39 and CD73 as potential therapeutic targets to enhance antineoplastic immune responses. Full article

Background: Patients with relapsed or refractory (R/R) diffuse large B-cell lymphoma (DLBCL) who are ineligible for high-dose chemotherapy have limited treatment options and poor life expectancy. The purpose of this study is to identify a serum metabolomic profile that may be predictive of outcome in patients with R/R-DLBCL. Methods: This study included 69 R/R DLBCL patients from the R2-GDP-GOTEL trial (EudraCT 2014-001620-299). Serum samples were collected at baseline, and the mean length of follow-up was 41 months. Serum metabolites were analyzed by nuclear magnetic resonance (NMR). Metabolites were correlated with treatment response, progression-free survival (PFS), and overall survival (OS). Results: Serum levels of 3-hydroxybutyrate (3OHB) and acetone were significantly (p < 0.001) associated with PFS (3OHB: hazard ratio [HR] 7.7, 95% confidence interval [CI] 2.5–24.1; acetone: HR 9.32, 95% CI 2.75–31.6) and OS (3OHB: HR 9.32, 95% CI 2.75–31.6; acetone: HR 1.92, 95% CI 1.36–2.69). Serum values of 141 µM for 3OHB and 40 µM for acetone were the optimal cutoffs associated with the survival outcomes. Elevated 3OHB levels (>141 μM) were specific to the ABC subtype of DLBCL, while acetone levels were elevated in both types of DLCBL but more pronounced in ABC cases. In a multivariate survival analysis, including the International Prognostic Index (IPI) score and refractoriness status (R/R), 3OHB and acetone remained significant. To aid oncologists employing the R2-GDP regime, we constructed PFS and OS nomograms for R/R-DLBCL risk stratification, incorporating 3OHB levels or acetone levels, IPI score, and refractoriness status. The nomogram with 3OHB and refractoriness status showed a time-dependent AUC of 0.86 for 6-month PFS and 0.84 for 12-month OS. These nomograms provide a comprehensive tool for individualized risk assessment and treatment optimization. Conclusions: The ketone bodies 3OHB and acetone are potential prognostic biomarkers of poor outcome in R/R DLBCL patients treated with the R2-GDP regimen, independently of IPI score and chemorefractoriness status. Full article

Objectives: Growing evidence suggests a link between organophosphate insecticides and depression disorder. These chemicals are metabolized and subsequently expelled through the urinary tract. The present study aims to investigate whether dialkyl phosphate metabolites associate with depression score and severity among the general population. Methods: This cross-sectional study used data from the National Health and Nutrition Examination Survey (NHANES). Depression was evaluated by the Patient Health Questionnaire-9 (PHQ-9). All urinary dialkyl phosphate metabolites were quantitatively analyzed. The survey’s complex design parameters and sampling weights were considered. Results: 3035 eligible individuals were included. The estimated prevalence of mild and major depression was 18.3% (95% confidence interval [CI]: 16.9–19.7%) and 9.9% (95% CI: 8.7–11.0%). For each incremental unit in the level of urinary dimethyl phosphate (DMP), individuals were found to have a higher depression score of 0.77 and a significantly increased odds ratio (OR) of 1.13 (95% CI: 1.12–1.13) for mild depression and 2.75 (95% CI: 2.74–2.76) for major depression. Conclusions: Our findings indicate positive and independent associations between urinary dialkyl phosphate metabolites and an elevated risk of depression among the general population. Full article

Background/Objectives: Those with the genetic disorder Down syndrome are at high risk of developing Alzheimer’s disease. Previous work shows group differences in magnetic resonance spectroscopy metabolite measures in adults with Down syndrome who have Alzheimer’s disease-related dementia compared to those who do not. In this pilot study, we assess relationships between metabolites and measures related to dementia status in a sample of adults with Down syndrome. Methods: Seventeen adults with Down syndrome were scanned using a 3 tesla MRI scanner. Magnetic resonance spectroscopy scans focused on the hippocampus and dorsal lateral prefrontal cortex. Metabolites of interest, including myo-inositol and N-acetyl-aspartate, were correlated with scores on the Dementia Questionnaire for People with Learning Disabilities, cortical thickness, and a measure of cognitive ability. In addition, cortical thickness was compared to an age- and sex-matched cohort of 17 previously scanned adults without Down syndrome. Results: Metabolite measures were not significantly related to cognitive/behavioral measures or to cortical thickness in this small cohort. Participants with Down syndrome showed widespread increases in cortical thickness compared to controls, even after accounting for potential differences in grey matter/white matter contrast. Conclusions: Metabolite values were not related to two continuous measures that have previously been associated with dementia status in those with Down syndrome. Full article

Background/Objectives: Alzheimer’s disease (AD) is the most common form of dementia and affects approximately 50 million individuals worldwide. Interest in coconut oil (CO) as a potential dietary intervention has surged owing to its substantial medium-chain triglyceride (MCT) content. Therefore, sustaining cognitive function and potentially slowing the progression of AD are crucial. This systematic review and meta-analysis evaluated the effects of CO and its bioactive metabolites on AD and dementia. Methods: The review protocol is registered in PROSPERO (CRD42023450435). Relevant research articles published between January 2015 and June 2023 were systematically searched. Seven studies met the predetermined eligibility criteria. Thematic analysis was utilized to synthesis the data about the qualitative features, while meta-analysis was employed for the quantitative findings. A meta-analysis was conducted to assess the standardized mean difference (SMD) and the corresponding 95% confidence interval (CI). Forest plots were generated using Review Manager 5.3 (RevMan 5.3). Results: The analysis revealed that all studies showed consistent results regarding the effects of CO on cognitive scores, with little variability in the true effects of CO on cognitive scores across the studies included in the meta-analysis. Conclusions: CO improved cognitive scores in patients with AD compared with those in the control group (p < 0.05). The results of this study add to the increasing amount of evidence indicating that MCTs found in CO might be a way to improve abilities and potentially slow the advancement of AD. The findings of this study may encourage the development of targeted dietary strategies and interventions for individuals at risk of or diagnosed with AD. Full article

Background: Although healthy lifestyle has been linked with a reduced risk of cardiovascular diseases (CVDs), the potential metabolic mechanism underlying this association remains unknown. Methods: We included 161,018 CVD-free participants from the UK Biobank. Elastic net regression was utilized to generate a healthy lifestyle-related metabolic signature. The Cox proportional hazards model was applied to investigate associations of lifestyle-related metabolic signature with incident CVDs, and mediation analysis was conducted to evaluate the potential mediating role of metabolic profile on the healthy lifestyle-CVD association. Mendelian randomization (MR) analysis was conducted to detect the causality. Results: During 13 years of follow-up, 17,030 participants developed incident CVDs. A healthy lifestyle-related metabolic signature comprising 123 metabolites was established, and it was inversely associated with CVDs. The hazard ratio (HR) was 0.83 (95% confidence interval [CI]: 0.81, 0.84) for CVD, 0.83 (95% CI: 0.81, 0.84) for ischemic heart disease (IHD), 0.86 (95% CI: 0.83, 0.90) for stroke, 0.86 (95% CI: 0.82, 0.89) for myocardial infarction (MI), and 0.75 (95% CI: 0.72, 0.77) for heart failure (HF) per standard deviation increase in the metabolic signature. The metabolic signature accounted for 20% of the association between healthy lifestyle score and CVD. Moreover, MR showed a potential causal association between the metabolic signature and stroke. Conclusions: Our study revealed a potential link between a healthy lifestyle, metabolic signatures, and CVD. This connection suggests that identifying an individual’s metabolic status and implementing lifestyle modifications may provide novel insights into the prevention of CVD. Full article

Maternal nutrition during the critical period of pregnancy increases the susceptibility of offspring to the development of diseases later in life. This study aimed to analyze metabolite profiles to investigate the effect of maternal diet during pregnancy on changes in offspring plasma metabolites and to identify correlations with metabolic parameters. Pregnant Sprague-Dawley rats were exposed to under- and overnutrition compared to controls, and their offspring were fed a standard diet after birth. Plasma metabolism was profiled in offspring at 16 weeks of age using liquid chromatography–mass spectrometry (LC-MS/MS) and gas chromatography–tandem mass spectrometry (GC-MS/MS). We analyzed 80 metabolites to identify distinct metabolites and metabolic and neurodegenerative disease-associated metabolites that were sex-differentially altered in each group compared to controls (p < 0.05, VIP score > 1.0). Specifically, changes in 3-indolepropionic acid, anthranilic acid, linoleic acid, and arachidonic acid, which are involved in tryptophan and linoleic acid metabolism, were observed in male offspring and correlated with plasma leptin levels in male offspring. Our results suggest that fatty acids involved in tryptophan and linoleic acid metabolism, which are altered by the maternal diet during pregnancy, may lead to an increased risk of metabolic and neurodegenerative diseases in the early life of male offspring. Full article