Metabolites最新文献

Background/objectives: Silicosis remains a major occupational health concern worldwide and is characterized by notable clinical heterogeneity in terms of disease progression and complications. However, the underlying metabolic mechanisms contributing to this heterogeneity remain poorly understood.

Methods: We conducted a case-control study involving 156 silicosis patients and 132 silica-exposed controls. The plasma samples were analyzed via untargeted metabolomics based on liquid chromatography-mass spectrometry (LC-MS/MS). To explore disease subtypes and potential biomarkers, we applied non-negative matrix factorization (NMF) clustering, weighted gene co-expression network analysis (WGCNA), and machine learning approaches.

Results: A total of 860 differentially abundant metabolites, including elevated pathogen-associated compounds, were identified in silicosis patients. Unsupervised NMF clustering revealed two distinct metabolic subtypes with different clinical features. Patients in the NMF2 subgroup had a 5.3-fold greater risk of pulmonary infections (p = 0.026) than those in the NMF1 subgroup. Metabolomic analysis revealed that NMF2 was enriched in arachidonic acid and unsaturated fatty acid metabolism pathways, with prominent LysoPC accumulation, suggesting inflammation-related lipid peroxidation. In contrast, NMF1 was characterized by increased spermidine biosynthesis and urea cycle activity, along with suppressed saturated fatty acid metabolism and reduced LysoPC processing, potentially affecting membrane integrity and promoting fibrosis. A machine learning-derived dual-metabolite panel, tyrosocholic acid and PI (20:4/0:0), achieved AUC values above 0.85 for both silicosis detection and subtype classification.

Conclusions: These findings highlight metabolic heterogeneity in silicosis and suggest clinically relevant subtypes, providing a foundation for improved stratification, early detection, and targeted interventions.

Background/Objectives: Itaconic acid (ITA) is an immunometabolite with anti-inflammatory and metabolic regulatory functions, but its cellular source and role in brown adipose tissue (BAT) remain unclear. This study aims to reveal the expression patterns of the key ITA synthesis gene Irg1 in BAT at different developmental stages and to investigate the effects of cold exposure and exogenous ITA on BAT metabolic function and cardioprotection. Methods: Single-cell RNA sequencing was used to analyze the gene expression profiles of stromal vascular fraction (SVF) cells in BAT from P7 neonatal and adult mice. Bioinformatic methods were applied to identify cell types expressing Irg1. Cold exposure (4 °C) and exogenous ITA treatment were employed to evaluate BAT morphology, and the ITA content in BAT was detected using gas chromatography-triple quadrupole mass spectrometry, UCP1 protein expression, and body temperature changes. A transverse aortic constriction (TAC) surgery model was established to induce cardiac dysfunction, and BAT excision was performed to explore the BAT-dependent effects of ITA on myocardial hypertrophy, fibrosis, and cardiac function. Results: In P7 neonatal mouse BAT, Irg1 was predominantly expressed in a subset of interferon-responsive activated macrophages (macrophage27), while in adult mice, it was mainly expressed in neutrophils and a functionally similar macrophage subset (macrophage25). Cold exposure significantly suppressed Irg1 expression in neutrophils but did not affect its expression in macrophages, also resulting in a significant decrease in ITA content in BAT. Exogenous ITA significantly enhanced BAT thermogenesis under cold conditions, which manifested as reduced lipid droplets, upregulated UCP1 expression, and increased body temperature. In the TAC model, ITA treatment markedly improved cardiac function, attenuated myocardial hypertrophy and fibrosis, and these protective effects were significantly diminished after BAT excision. Conclusions: ITA promotes cold adaptation and ameliorates cardiac injury by enhancing BAT metabolic function, and its effects depend on the presence of BAT. This study provides new insights for the treatment of metabolic cardiovascular diseases.

Background/Objectives: Schizophrenia (SCH) and bipolar disorder (BD) share overlapping symptoms and genetic factors, making differential diagnosis challenging and often leading to misdiagnosis. This study aimed to identify potential lipid biomarkers of serum capable of distinguishing BD from SCH. Methods: Lipid profiles of serum from 30 SCH and 31 BD patients were analyzed in triplicates using liquid chromatography-high-resolution mass spectrometry (LC-HRMS). Chemometric analysis was applied, including class and gender identifiers. Orthogonal partial least squares (OPLS) models with 1000 cross-validations were used to validate feature subsets. Results: The chemometric analysis included the most relevant metabolites in the comparison between all samples of SCH and BD patients, identifying five key biomarkers (LPC 16:0, SM 33:1, SM 32:1, compound C30H58O3, and PC 30:0) with VIP scores > 1 for distinguishing BD from SCH. Gender-specific models revealed five biomarkers in males (SM 32:1, SM 33:1, PC 32:1, PC 30:0, and FA 16:1) and two in females (LPC 16:0 and C30H58O3). These biomarkers primarily belonged to glycerophospholipids (GPs) and sphingophospholipids (SPs). Conclusions: Comparative lipid profiling between SCH and BD, including gender-specific subgroups, enabled identification of potential diagnosis-specific biomarkers. Elevated levels of GPs and SPs in SCH patients suggest lipid metabolism differences that may support improved diagnostic accuracy and personalized treatment strategies.

Background: Distinguishing between osteoarthritis (OA), rheumatoid arthritis (RA), and psoriatic arthritis (PsA) remains challenging despite different underlying mechanisms. Synovial fluid reflects metabolic changes within affected joints, yet comprehensive metabolomic comparisons across these conditions are limited. We aimed to identify disease-specific metabolic signatures in synovial fluid that could improve differential diagnosis and reveal therapeutic targets.

Methods: We collected synovial fluid from 39 patients (20 OA, 5 RA, and 14 PsA) during routine knee arthrocentesis between January 2023 and February 2024. Following metabolite extraction, we performed untargeted metabolomic profiling using quadrupole time-of-flight liquid chromatography-mass spectrometry (Q-TOF LC/MS). Data underwent multivariate statistical analysis, including principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA), to identify discriminatory metabolites.

Results: While unsupervised analysis showed overlap between groups, supervised PLS-DA achieved clear metabolic separation. RA samples showed elevated itaconic acid, indicating inflammatory macrophage activation, and increased O-acetylserine, suggesting altered one-carbon metabolism. Hypoxanthine was decreased, which reflected severe metabolic stress. PsA exhibited the unique elevation of 4,4-dimethylcholestane and 2-oxoarginine. These metabolites have previously been unreported in this disease. OA demonstrated increased hippuric acid and indoleacetic acid, which are both gut microbiota products, supporting the gut-joint axis hypothesis.

Conclusions: Each arthritis type displayed distinct metabolic fingerprints in synovial fluid. Candidate discriminatory metabolites, including gut-derived metabolites in OA and specific lipid alterations in PsA, open new diagnostic and therapeutic avenues. Given the limited RA sample size (n = 5), RA-related results should be viewed as exploratory and requiring validation in larger independent cohorts. These metabolites may, after rigorous validation in larger and independent cohorts, contribute to multi-metabolite biomarker panels for earlier diagnosis and to the rational design of targeted therapeutics addressing disease-specific metabolic disruptions.

Background: Colorectal cancer (CRC) is a malignancy that ranks among the top three in terms of both global mortality and incidence. Although numerous studies have demonstrated that gut microbes are implicated in CRC pathogenesis, the precise mechanisms underlying host-microbiota metabolic crosstalk remain poorly understood.

Objective: This study aims to identify and delineate key co-metabolites and their associated metabolic pathways that modulate the biomass of CRC-related gut bacteria within healthy individuals, through the construction of host-gut microbiota co-metabolic network models. We seek to elucidate the underlying mechanisms of metabolic interplay between the host and CRC-related gut microbiota, thereby offering novel perspectives on the microbial involvement in the initiation and progression of CRC.

Methods: We coupled a colon tissue-specific host Genome-Scale Metabolic Model (GEM), which utilized transcriptomic data from healthy human colon tissues, with 12 CRC-associated pro-/anti-carcinogenic gut bacterial GEMs to construct a co-metabolic network. Through a comparative analysis of the network structure and systemic methods (including Flux Sampling and metabolic difference analysis), we simulated scenarios of constrained host co-metabolite supply. Finally, metabolic subsystem enrichment analysis was employed to elucidate the specific molecular mechanisms by which key co-metabolites affect microbial function.

Results: The 17 key co-metabolites identified include chloride ions, zinc ions, and acetate. Among these, thirteen metabolites (e.g., ferric iron, succinate, and acetate) were confirmed by literature to be associated with CRC. All 17 key co-metabolites were found to significantly modulate the biomass of CRC-associated gut bacteria. These regulatory effects primarily influence microbial function through core pathways such as glycerophospholipid metabolism and folate metabolism.

Conclusion: This research provides a systemic perspective for elucidating the mechanisms of host-gut microbiota metabolic interplay in CRC, thereby complementing the existing theoretical framework concerning microbial regulation by the host genetic background.

Metabolomics and lipidomics have emerged as essential tools in systems biology, providing comprehensive insights into small-molecule metabolites and lipids within biological systems [...].

Background/objectives: Mitochondrial dysfunction is a major cause of brain injury in patients with primary mitochondrial disease. New mitochondrial therapeutics and non-invasive tools for efficacy monitoring are urgently needed. To these ends, succinate prodrug NV354 (methyl 3-[(2-acetylaminoethylthio)carbonyl]propionate) and diffuse optical techniques are promising. In this proof-of-concept study, we characterize NV354's effects on microdialysis metrics of cerebral metabolism in a swine model of mitochondrial dysfunction and assess the associations of diffuse optical metrics with mitochondrial dysfunction and metabolic improvement.

Methods: One-month-old swine received a four-hour co-infusion of rotenone with either the succinate prodrug NV354 (n = 5) or placebo (n = 5). Rotenone is a mitochondrial complex I inhibitor. Before and during co-infusion, cerebral metabolism was probed with microdialysis and diffuse optics. Microdialysis acquired interstitial lactate and pyruvate levels invasively, while diffuse optics measured changes in oxygen extraction fraction (OEF) and oxidized cytochrome-c-oxidase concentration (oxCCO).

Results: Interstitial lactate continually increased in the placebo group (p < 0.01), but lactate levels plateaued in the NV354 group (p = 0.90). oxCCO also increased in the placebo group (p = 0.05), but OEF remained constant (p = 0.80). In the NV354 group, oxCCO increased (p < 0.01) while OEF decreased (p < 0.01).

Conclusions: Microdialysis results suggest that NV354 treatment can increase oxygen metabolism in large animals with mitochondrial dysfunction. The optical oxCCO metric was also sensitive to metabolic changes induced by rotenone and NV354 administration.

Background: Uncontrolled diabetes is characterised by a loss of blood glucose control and increased oxidation of fatty acids to produce ATP. Use of metabolic inhibitors to blunt fatty acid oxidation and restore glucose metabolism is a poorly studied intervention for diabetes. Methods: Steptozotocin-induced diabetes was developed in Wistar male rats. A subset was supplemented with mildronate (100 mg/kg-14 days). Exploiting liquid chromatography-mass spectrometry for workflows including ion exchange-, C18-reverse phase- and HILIC-based chromatography methods, metabolite levels were quantified in plasma liver and brain tissue. Using both untargeted and targeted metabolomic analysis changes to the global tissue metabolome and individual metabolic pathways were estimated. Results: We document that an inhibitor of carnitine synthesis, mildronate, decreased plasma (50% p < 0.01) carnitine abundance and decreased plasma glucose concentration by one-third compared to streptozotocin (STZ)-treated rats (p < 0.001). Targeted metabolomic analysis of the liver showed decreased alpha-ketoglutarate abundance (35% p < 0.05) by STZ diabetes that was further decreased following mildronate treatment (50% p < 0.05). For both beta-hydroxybutyrate and succinate levels, STZ diabetes increased hepatic abundance by 50% (p < 0.05 for both), which was restored to control levels by mildronate (p < 0.05 for both). In contrast, brain TCA intermediate abundances were unaffected by either STZ diabetes or mildronate (NS for all). STZ diabetes also decreased abundance of pentose phosphate pathway (PPP) metabolites in the liver (glucose-6-phosphate, 6-phosphogluconolactone, 6-phosphogluconate 50% for all; p < 0.05), which was not restored by mildronate treatment. However, brain PPP metabolite abundance was unchanged by STZ diabetes or mildronate (NS for all). However, mildronate treatment did not affect the increased abundance of brain sorbitol, sorbitol-6-phosphate and glucose-6-phosphate as a result of STZ diabetes. Conclusions: Together, these observations highlight the potential role that metabolic inhibitors, like mildronate, may play in restoring blood glucose for diabetic patients, without a direct effect of tissues that represent obligate consumers of glucose (e.g., brain) whilst manipulating fat oxidation in tissues such as the liver.

Breast cancer is a significant public health concern, with triple-negative breast cancer (TNBC) being the most aggressive subtype characterized by considerable heterogeneity and the absence of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) expression. Currently, there are no practical alternatives to chemotherapy, which is associated with a poor prognosis. Therefore, developing new treatments for TNBC is an urgent need. Reactive oxygen species (ROS) and redox adaptation play central roles in TNBC biology. Targeting the redox state has emerged as a promising therapeutic approach, as it is vital to the survival of tumors, including TNBC. Although TNBC does not produce high levels of ROS compared to ER- or PR-positive breast cancers, it relies on mitochondria and oxidative phosphorylation (OXPHOS) to sustain ROS production and create an environment conducive to tumor progression. As a result, novel treatments that can modulate redox balance and target organelles essential for redox homeostasis, such as mitochondria, could be promising for TNBC, an area not yet reviewed in the current scientific literature, thus representing a critical gap. This review addresses that gap by synthesizing current evidence on TNBC biology and its connections to redox state and mitochondrial metabolism, with a focus on innovative strategies such as metal-based compounds (e.g., copper, gold), redox nanoparticles that facilitate anticancer drug delivery, mitochondrial-targeted therapies, and immunomodulatory peptides like GK-1. By integrating mechanistic insights into the redox state with emerging therapeutic approaches, I aim to highlight new redox-centered opportunities to improve TNBC treatments. Moreover, this review uniquely integrates mitochondrial metabolism, redox imbalance, and emerging regulated cell-death pathways, including ferroptosis, cuproptosis, and disulfidptosis, within the context of TNBC metabolic heterogeneity, highlighting translational vulnerabilities and subtype-specific therapeutic opportunities.