PubMed

Food Sci Nutr. 2025 Jan 31;13(2):e70001. doi: 10.1002/fsn3.70001. eCollection 2025 Feb.ABSTRACTTo clarify the impact of drought stress during germination on proso millet's physiological responses and metabolic features, this study used physiological and targeted-like metabolomics methods. With Longmi No. 7 (drought-tolerant, L1) and Longmi No. 15 (drought-sensitive, L2) as materials, we studied the enzyme activities, osmotic adjustment substances, and differential metabolites of proso millet. Results showed that under drought stress, L1's enzyme activities and osmotic adjustment substance contents were significantly higher than L2's, especially at 48-h treatment. 1085 known metabolites were identified from 24 samples, under normal germination, L1's main differential metabolites (amino acids, flavonoids, phytohormone, lipids, sugars, etc.) were enriched in amino acid, lipid, sugar, and energy metabolism pathways. L2's (amino acids, sugars, flavonoids, etc.) were in sugar, lipid metabolism, secondary metabolite biosynthesis, and amino acid metabolism pathways. At 24-h treatment, the metabolic pathways of L1 were mainly concentrated in carbohydrate and nucleotide metabolism, while those of L2 were mainly in carbohydrate and lipid metabolism. At 48 h, the metabolic pathways of L1 were mainly in carbohydrate, energy and lipid metabolism, and those of L2 were mainly in carbohydrate, lipid metabolism, biosynthesis of other secondary metabolites and amino acid metabolism. Under stress, L1's main differential metabolites were organic acids, sugars, flavonoids, amino acids, etc.; L2's were phytohormones, organic acids, sugars, flavonoids, amino acids. This study provides a new direction for the development of proso millet sprouts. Meanwhile, it offers new ideas and theoretical bases for the development of functional foods and the regulation of nutritional components of proso millet.PMID:39898120 | PMC:PMC11782973 | DOI:10.1002/fsn3.70001

iScience. 2025 Jan 2;28(2):111731. doi: 10.1016/j.isci.2024.111731. eCollection 2025 Feb 21.ABSTRACTSuccinate is a crucial metabolite in the TCA cycle and contributes to cancer development. However, the role of exogenous succinate in hepatocellular carcinoma (HCC) is unclear. Here, we report that the concentration of succinate in HCC tissues is lower compared to adjacent normal tissues, as determined by spatial metabolomics and quantitative metabolomics analysis. Succinate supplementation exhibits an anti-tumorigenic effect, inhibiting cell proliferation and colony formation in liver cancer cells but not in non-tumor LO2 cells. Additionally, succinate supplementation significantly reduces tumor formation in xenograft nude mice models and carcinogen-induced WT mice models. The anti-tumorigenic function of succinate is mechanistically mediated by FN1-activated SQLE-related cholesterol biosynthesis. Our study demonstrates that exogenous succinate acts as a cholesterol biosynthesis inhibitor to suppress HCC both in vitro and in vivo, highlighting its potential therapeutic applications.PMID:39898026 | PMC:PMC11787499 | DOI:10.1016/j.isci.2024.111731

Food Chem X. 2025 Jan 16;25:102185. doi: 10.1016/j.fochx.2025.102185. eCollection 2025 Jan.ABSTRACTBaijiu is prepared via solid fermentation and distillation, and volatile metabolites influence its flavor considerably. However, the volatile metabolites' transformational relationship during the fermentation process remains unclear. In this study, ultra-performance liquid chromatography-tandem mass spectrometry and gas chromatography-tandem mass spectrometry were used to analyze a widely targeted metabolome during the xiaoqu baijiu fermentation process. In total, 668 volatile metabolites comprising 16 subclasses were identified. Significant variations in metabolites were observed during the fermentation process, especially in the distillation stage, and the conversion intensity of volatile metabolites was consistent with the following order of stages: distillation > soaking > saccharification > fermentation > stewing. A total of 570 differential volatile metabolites were identified in the distillation stage, especially esters, terpenoids, and hydrocarbons. These results provide a theoretical basis that could guide the xiaoqu baijiu fermentation process based on desired quality and components.PMID:39897971 | PMC:PMC11786915 | DOI:10.1016/j.fochx.2025.102185

Food Chem X. 2025 Jan 13;25:102177. doi: 10.1016/j.fochx.2025.102177. eCollection 2025 Jan.ABSTRACTAmomum tsaoko is an important homologous medicinal and food plant, and its fruit is rich in flavonoids. However, few studies have reported the preparation and bioactivity of flavonoids in A. tsaoko (ATF). In this study, the optimal conditions for ultrasound-assisted extraction of ATF were identified through response surface optimization. HPD300 was identified as the best resin for the purification of ATF, as it exhibited a Freundlich model-conformative adsorption isotherm. Among the different concentrations of ethanol, 20 % and 30 % resulted in higher flavonoid purity (>90 %) and stronger antioxidant and α-glucosidase inhibition activities. A widely targeted metabolomics assay revealed that the relative abundance of flavonoids in a mixture of 20 % and 30 % ethanol eluates was greater than 73 %, which mainly contained (+)-epicatechin, isoquercitrin, astragalin kaempferol-3-O-rutinoside, and procyanidin B2. These findings provide a theoretical basis for the in-depth development and potential use of ATF in the functional food, cosmetic and pharmaceutical industries.PMID:39897968 | PMC:PMC11786917 | DOI:10.1016/j.fochx.2025.102177

Heliyon. 2025 Jan 6;11(2):e41715. doi: 10.1016/j.heliyon.2025.e41715. eCollection 2025 Jan 30.ABSTRACTMetabolomics and 16S rDNA sequencing have shown great potential in elucidating complex mechanisms associated with diseases. Currently, there is little research on the omics of gastric cancer and it lacks effective biomarkers.OBJECTIVE: Based on plasma metabolomics and 16S rDNA sequencing to evaluate the changes in metabolites and fecal microbiota of advanced gastric cancer.METHOD: Firstly, plasma metabolomics was used to screen for differential metabolites and metabolic pathways in gastric cancer. Then, 16S rDNA sequencing was performed on fecal samples to study the differential intestinal microbiota in gastric cancer patients. Finally, conduct a correlation analysis between them.RESULT: A total of 152 differential metabolites were identified, and we screened 10 of them. All metabolites were enriched into 42 differential metabolic pathways, of which 13 have P values less than 0.05. 16S rDNA sequencing showed significant differences in 4 microbial communities at the phylum level. There are significant differences in 23 communities at the genus level. We focus on Lactobacillales, Lactobacillus, Streptococcus, Veillonella, Bacilli and Megasphaera. Correlation analysis shows that the intestinal microbiota and plasma metabolites jointly affect the occurrence and development of gastric cancer.CONCLUSION: For the first time, we comprehensively used plasma metabolomics and 16S rDNA sequencing to reveal the changes and correlations between metabolites and intestinal microbiota in advanced gastric cancer. We have discovered new potential biomarkers for gastric cancer. This deepens our understanding of the physiological and pathological mechanisms of advanced gastric cancer and helps to improve the diagnosis and treatment of advanced gastric cancer.PMID:39897929 | PMC:PMC11783444 | DOI:10.1016/j.heliyon.2025.e41715

Heliyon. 2025 Jan 10;11(2):e41786. doi: 10.1016/j.heliyon.2025.e41786. eCollection 2025 Jan 30.ABSTRACTBACKGROUND: A growing number of studies have shown that hypertension symptoms are closely related to intestinal flora. The body's metabolites are closely related to disease states. Tianma Gouteng Granules (TG), a traditional Chinese medicine compound, has been proven to be an effective compound for the treatment of hypertension by traditional Chinese medicine diagnosis, but the target and therapeutic mechanism of TG on hypertension are still unclear.AIM OF THE STUDY: We explored the mechanism of action of TG on hypertension by 16S rDNA gene sequencing and non-targeted metabolomics, verified the correlation between hypertension and intestinal flora, searched for potential markers of intestinal flora, and screened for the correlation between different flora and different metabolites, which facilitates a more scientific and reasonable guidance for the administration of TG.MATERIALS AND METHODS: The hypertensive model rats were induced by L-NAME. After drug administration, 16S rDNA gene sequencing and non-targeted metabolomics were applied to detect and analyze the intestinal flora and fecal metabolites of the rats in each group. The Spearman coefficient method was used to construct the interactions system of different flora and metabolites, which explore the potential mechanism of TG treatment hypertension.RESULTS: After TG administration, the symptoms of hypertension were significantly reduced to normal in SD rats.16S rDNA gene sequencing and non-targeted metabolomics screened for differential flora p_Actinobacteriota, o_Micrococcaceae, f_ Micrococcales, g_Rothias_Rothia_unclassified, etc. and differential metabolites such as L-Alanine and Hydroxyprolyl-Leucine. TG treatment of hypertension was found to be associated with vitamin B6 metabolic pathway and lipid metabolic pathway.CONCLUSIONS: TG can treat hypertension by affecting differential strains and differential metabolites, providing a scientific basis for guiding the rational use of TG.PMID:39897797 | PMC:PMC11786837 | DOI:10.1016/j.heliyon.2025.e41786

Theranostics. 2025 Jan 2;15(5):1741-1759. doi: 10.7150/thno.104186. eCollection 2025.ABSTRACTRationale: Physical exercise is essential for skeletal integrity and bone health. The gut microbiome, as a pivotal modulator of overall physiologic states, is closely associated with skeletal homeostasis and bone metabolism. However, the potential role of intestinal microbiota in the exercise-mediated bone gain remains unclear. Methods: We conducted microbiota depletion and fecal microbiota transplantation (FMT) in ovariectomy (OVX) mice and aged mice to investigate whether the transfer of gut ecological traits could confer the exercise-induced bone protective effects. The study analyzed the gut microbiota and metabolic profiles via 16S rRNA gene sequencing and LC-MS untargeted metabolomics to identify key microbial communities and metabolites responsible for bone protection. Transcriptome sequencing and RNA interference were employed to explore the molecular mechanisms. Results: We found that gut microbiota depletion hindered the osteogenic benefits of exercise, and FMT from exercised osteoporotic mice effectively mitigated osteopenia. Comprehensive profiling of the microbiome and metabolome revealed that the exercise-matched FMT reshaped intestinal microecology and metabolic landscape. Notably, alterations in bile acid metabolism, specifically the enrichment of taurine and ursodeoxycholic acid, mediated the protective effects on bone mass. Mechanistically, FMT from exercised mice activated the apelin signaling pathway and restored the bone-fat balance in recipient MSCs. Conclusion: Our study underscored the important role of the microbiota-metabolic axis in the exercise-mediated bone gain, heralding a potential breakthrough in the treatment of osteoporosis.PMID:39897551 | PMC:PMC11780523 | DOI:10.7150/thno.104186

NAR Genom Bioinform. 2025 Jan 31;7(1):lqaf003. doi: 10.1093/nargab/lqaf003. eCollection 2025 Mar.ABSTRACTThe interpretation of multi-omics datasets obtained from high-throughput approaches is important to understand disease-related physiological changes and to predict biomarkers in body fluids. We present a new metabolite-centred genome-scale metabolic modelling algorithm, the Gene Expression-based Metabolite Centrality Analysis Tool (GEMCAT). GEMCAT enables integration of transcriptomics or proteomics data to predict changes in metabolite concentrations, which can be verified by targeted metabolomics. In addition, GEMCAT allows to trace measured and predicted metabolic changes back to the underlying alterations in gene expression or proteomics and thus enables functional interpretation and integration of multi-omics data. We demonstrate the predictive capacity of GEMCAT on three datasets and genome-scale metabolic networks from two different organisms: (i) we integrated transcriptomics and metabolomics data from an engineered human cell line with a functional deletion of the mitochondrial NAD transporter; (ii) we used a large multi-tissue multi-omics dataset from rats for transcriptome- and proteome-based prediction and verification of training-induced metabolic changes and achieved an average prediction accuracy of 70%; and (iii) we used proteomics measurements from patients with inflammatory bowel disease and verified the predicted changes using metabolomics data from the same patients. For this dataset, the prediction accuracy achieved by GEMCAT was 79%.PMID:39897103 | PMC:PMC11783570 | DOI:10.1093/nargab/lqaf003

Front Mol Biosci. 2025 Jan 17;11:1545016. doi: 10.3389/fmolb.2024.1545016. eCollection 2024.NO ABSTRACTPMID:39896930 | PMC:PMC11782019 | DOI:10.3389/fmolb.2024.1545016

Front Immunol. 2025 Jan 17;15:1471511. doi: 10.3389/fimmu.2024.1471511. eCollection 2024.ABSTRACTINTRODUCTION: Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease with a high mortality rate caused by Dabie bandavirus. The aspartate aminotransferase to platelet ratio index (APRI) is a biomarker of liver injury and inflammation. This study aimed to examine the correlation between APRI and SFTS prognosis using clinical data analysis and attempt to explain its prognostic significance through metabolic analysis.METHODS: Data from hospitalized patients with a confirmed diagnosis of SFTS virus infection at Wuhan Union Hospital were retrospectively collected. The low and high APRI groups were 1:1 matched using propensity score matching (PSM) analysis. Fresh plasma was collected from patients with SFTS on admission and used for metabolic tests.RESULTS: A total of 617 patients with SFTS who met the inclusion criteria were selected for analysis. Survival analysis revealed that patients with SFTS with high APRI (> 35.3) had a substantially higher death rate than those with low APRI (≤ 35.3). Receiver operating characteristic analysis showed the predictive performance of APRI for SFTS prognosis is 0.77, with a 95% CI of 0.73-0.80, which was superior to NLR (area under the curve (AUC): 0.65), platelet-to-lymphocyte ratio (AUC: 0.54), and systemic immune-inflammation index (AUC: 0.58). The prognostic value and predictive performance of APRI were more substantial after PSM than before PSM. Metabolomic testing identified several differential serum metabolites, with alanine, aspartate, glutamate, glycerophospholipid, and tryptophan metabolism being the most important metabolic pathways.CONCLUSION: A high APRI score was associated with relatively higher mortality in patients with SFTS, and its predictive performance for the survival outcome of SFTS was superior to that of well-recognized inflammatory scores. Alanine, aspartate, and glutamate metabolism are involved in the progression of SFTS.PMID:39896801 | PMC:PMC11781988 | DOI:10.3389/fimmu.2024.1471511

bioRxiv [Preprint]. 2025 Jan 23:2025.01.22.634403. doi: 10.1101/2025.01.22.634403.ABSTRACTSmall molecules (SMs) are integral to biological processes, influencing metabolism, homeostasis, and regulatory networks. Despite their importance, a significant knowledge gap exists regarding their downstream effects on biological pathways and gene expression, largely due to differences in scale, variability, and noise between untargeted metabolomics and sequencing-based technologies. To address these challenges, we developed a multi-omics framework comprising a machine learning-based protocol for data processing, a semi-supervised network inference approach, and network-guided analysis of complex traits. The ML protocol harmonized metabolomic, lipidomic, and transcriptomic data through batch correction, principal component analysis, and regression-based adjustments, enabling unbiased and effective integration. Building on this, we proposed a semi-supervised method to construct transcriptome-SM interaction networks (TSI-Nets) by selectively integrating SM profiles into gene-level networks using a meta-analytic approach that accounts for scale differences and missing data across omics layers. Benchmarking against three conventional unsupervised methods demonstrated the superiority of our approach in generating diverse, biologically relevant, and robust networks. While single-omics analyses identified 18 significant genes and 3 significant SMs associated with insulin sensitivity (IS), network-guided analysis revealed novel connections between these markers. The top-ranked module highlighted a cross-talk between fiber-degrading gut microbiota and immune regulatory pathways, inferred by the interaction of the protective SM, N-acetylglycine (NAG), with immune genes ( FCER1A , HDC , MS4A2 , and CPA3 ), linked to improved IS and reduced obesity and inflammation. Together, this framework offers a robust and scalable solution for multi-modal network inference and analysis, advancing SM pathway discovery and their implications for human health. Leveraging data from a population of thousands of individuals with extended longevity, the inferred TSI-Nets demonstrate generalizability across diverse conditions and complex traits. These networks are publicly available as a resource for the research community.PMID:39896668 | PMC:PMC11785221 | DOI:10.1101/2025.01.22.634403

bioRxiv [Preprint]. 2025 Jan 22:2025.01.20.633954. doi: 10.1101/2025.01.20.633954.ABSTRACTBACKGROUND: Right ventricular dysfunction (RVD) is a risk factor for death in multiple cardiovascular diseases, but RV-enhancing therapies are lacking. Inhibition of glycoprotein-130 (GP130) signaling with the small molecule SC144 improves RV function in rodent RVD via anti-inflammatory and metabolic mechanisms. However, SC144's efficacy and molecular effects in a translational large animal model of RVD are unknown.METHODS: 4-week-old castrated male pigs underwent pulmonary artery banding (PAB). After 3 weeks, PAB pigs were randomized into 2 groups (daily injections of SC144 [2.2 mg/kg, PAB-SC144, n =5] or vehicle [PAB-Veh, n =5] for 3 weeks). Five age-matched pigs served as controls. Cardiac MRI quantified RV size/function. Right heart catheterization evaluated hemodynamics. Single-nucleus RNA sequencing delineated cell-type specific changes between experimental groups. Electron microscopy evaluated RV mitochondrial morphology. Phosphoproteomics identified dysregulated RV kinases. Lipidomics and metabolomics quantified lipid species and metabolites in RV tissue. Quantitative proteomics examined RV mitochondrial protein regulation.RESULTS: SC144 significantly improved RV ejection fraction (Control: 60±4%, PAB-Veh: 22±10%, PAB-SC144: 37±6%) despite similar RV afterload. Single-nucleus RNA sequencing demonstrated PAB-Veh pigs had lower cardiomyocyte and higher macrophage/lymphocyte/pericyte/endothelial cell abundances as compared to control, and many of these changes were blunted by SC144. SC144 combatted the downregulation of cardiomyocyte metabolic genes induced by PAB. Kinome enrichment analysis suggested SC144 counteracted RV mTORC1 activation. Correspondingly, SC144 rebalanced RV autophagy pathway proteins and improved mitochondrial morphology. Integrated lipidomics, metabolomics, and proteomics analyses revealed SC144 restored fatty acid metabolism. Finally, CellChat analysis revealed SC144 restored pericyte-endothelial cell cross-talk.CONCLUSION: GP130 antagonism blunts elevated immune cell abundance, reduces pro-inflammatory gene transcription in macrophages and lymphocytes, rebalances autophagy and preserves fatty acid metabolism in cardiomyocytes, and restores endothelial cell and pericyte communication to improve RV function.PMID:39896622 | PMC:PMC11785131 | DOI:10.1101/2025.01.20.633954

bioRxiv [Preprint]. 2025 Jan 20:2025.01.16.633464. doi: 10.1101/2025.01.16.633464.ABSTRACTMetabolic adaptations and flexibility during development and disease play an essential in cardiomyocyte function and survival. We recently reported Glucocorticoid receptor (GR)-Krüppel-like factor 9 (Klf9) axis in mediating metabolic adaptations in cardiomyocytes stimulated with Dexamethasone. Klf9 expression decreases in hypertrophic and failing hearts, suggesting its importance in cardiac homeostasis and its potential contribution to dysfunction under pressure overload. Genome wide Klf9 occupancy in adult hearts revealed 2,242 genes directly associated with Klf9, with enrichment in metabolic pathways, autophagy, ubiquitin-mediated proteolysis, and cellular senescence. We generated and characterized a conditional cardiac specific Klf9 knock-In (Klf9KI) mice, which developed progressive cardiac hypertrophy, cardiac dysfunction and cardiac failure by 8wks of age, with mortality by 12-14wks. RNA-seq analysis at 1wk, 4wks, and 8wks showed stage-specific transcriptional changes. At 1 week, 64.81% of differentially expressed genes were downregulated, aligning with Klf9's predicted role as a transcriptional repressor. At 4wks and 8wks, more genes were upregulated, suggesting more of secondary targets in response to cardiac phenotype. KEGG pathway analysis showed dysregulation in lipid, carbohydrate and glutathione metabolism, transcriptional regulation, apoptosis, and innate immunity. Untargeted Metabolomics at 4wks identified significant alterations in tissue metabolite levels, particularly in pathways involving fatty acid metabolism, amino acids, and glucose, correlating with transcriptome data. Mitochondrial function assays revealed progressive dysregulation. At 2 weeks, complex I activity was significantly reduced, while complex II and IV activities were partially preserved. By 4 weeks, all measured respiratory complexes showed significant declines, consistent with decline in mitochondrial function. These mitochondrial deficits preceded overt cardiac dysfunction and likely contributed to the development of hypertrophy and failure. In conclusion, constitutive Klf9 overexpression disrupts transcriptional and metabolic homeostasis, driving progressive hypertrophy, cardiac dysfunction, and failure.PMID:39896585 | PMC:PMC11785073 | DOI:10.1101/2025.01.16.633464

bioRxiv [Preprint]. 2025 Jan 22:2025.01.22.634160. doi: 10.1101/2025.01.22.634160.ABSTRACTFrailty is an age-related geriatric syndrome, for which the mechanisms remain largely unknown. We performed a longitudinal study of aging female (n = 40) and male (n = 47) C57BL/6NIA mice, measured frailty index and derived metabolomics data from plasma samples. We identify differentially abundant metabolites related to aging, determine frailty related metabolites via a machine learning approach, and generate a union set of frailty features, both in the whole cohort and in sex-stratified subgroups. Using the features, we perform an association study and build a metabolomics-based frailty clock. We find that frailty related metabolites are enriched for amino acid metabolism and metabolism of cofactors and vitamins, include ergothioneine, tryptophan, and alpha-ketoglutarate, and present sex dimorphism. We identify B vitamin metabolism related flavin adenine dinucleotide and pyridoxate as female-specific frailty biomarkers, and lipid metabolism related sphingomyelins, glycerophosphoethanolamine and glycerophosphocholine as male-specific frailty biomarkers. These associations are confirmed in a validation cohort, with ergothioneine and perfluorooctanesulfonate identified as robust frailty biomarkers. In summary, our results identify sex-specific metabolite biomarkers of frailty in aging, and shed light on potential mechanisms involved in frailty.PMID:39896479 | PMC:PMC11785134 | DOI:10.1101/2025.01.22.634160

bioRxiv [Preprint]. 2025 Jan 22:2025.01.18.633745. doi: 10.1101/2025.01.18.633745.ABSTRACTGlaucoma polygenic risk scores (PRS) effectively identify disease risk, but some individuals with high PRS do not develop glaucoma. Factors contributing to this resilience remain unclear. Using 4,658 glaucoma cases and 113,040 controls in a cross-sectional study in the UK Biobank, we investigated whether plasma metabolites enhanced glaucoma prediction and if a metabolomic signature of resilience in high-genetic risk individuals existed. Logistic regression models incorporating 168 NMR-based metabolites into PRS-based glaucoma assessments were developed, with multiple comparison corrections applied. While metabolites weakly predicted glaucoma (Area Under the Curve=0.579), they offered modest prediction improvement in PRS-only-based models (P=0.004). We identified a metabolomic signature associated with resilience in the top PRS decile, with elevated glycolysis-related metabolites-lactate (P=8.8E-12), pyruvate (P=1.9E-10), and citrate (P=0.02)-linked to reduced glaucoma prevalence. These metabolites combined significantly modified the PRS-glaucoma relationship (P interaction =0.011). Higher total resilience metabolite levels within the highest PRS quartile corresponded to lower glaucoma prevalence (Odds Ratio highest vs. lowest total resilience metabolite quartile =0.71, 95% Confidence Interval [CI]=0.64-0.80). As pyruvate is a foundational metabolite linking glycolysis to tricarboxylic acid cycle metabolism and ATP generation, we pursued experimental validation for this putative resilience biomarker in a human-relevant Mus musculus glaucoma model. Dietary pyruvate mitigated elevated intraocular pressure (P=0.002) and optic nerve damage (P<0.0003) in Lmx1b V265D mice. These findings highlight the protective role of pyruvate-related metabolism against glaucoma and suggest potential avenues for therapeutic intervention.PMID:39896457 | PMC:PMC11785086 | DOI:10.1101/2025.01.18.633745

JACC CardioOncol. 2025 Jan 21;7(1):68-69. doi: 10.1016/j.jaccao.2024.11.005. eCollection 2025 Jan.NO ABSTRACTPMID:39896125 | PMC:PMC11782008 | DOI:10.1016/j.jaccao.2024.11.005

JACC CardioOncol. 2024 Dec 3;7(1):56-67. doi: 10.1016/j.jaccao.2024.10.004. eCollection 2025 Jan.ABSTRACTBACKGROUND: Anthracyclines, a highly effective chemotherapy for many pediatric malignancies, cause cardiomyopathy, a major late effect in adult survivors. Biomarkers are needed for early detection and targeted interventions for anthracycline-associated cardiomyopathy.OBJECTIVES: The aim of this study was to determine if serum proteins and/or metabolites in asymptomatic childhood cancer survivors can discriminate symptomatic cardiomyopathy.METHODS: Using an untargeted mass spectrometry-based approach, 867 proteins and 218 metabolites were profiled in serum samples of 75 asymptomatic survivors with subclinical cardiomyopathy and 75 individually matched survivors without cardiomyopathy from SJLIFE (St. Jude Lifetime Cohort Study). Models were developed on the basis of the most influential differentially expressed proteins and metabolites, using conditional logistic regression with a least absolute shrinkage and selection operator penalty. The best performing model was evaluated in 23 independent survivors with severe or symptomatic cardiomyopathy and 23 individually matched cardiomyopathy-free survivors.RESULTS: A 27-protein model identified using conditional logistic regression with a least absolute shrinkage and selection operator penalty discriminated symptomatic or severe cardiomyopathy requiring heart failure medications in independent survivors; 19 of 23 individually matched survivors with and without cardiomyopathy were correctly discriminated with 82.6% (95% CI: 71.4%-93.8%) accuracy. Pathway enrichment analysis revealed that the 27 proteins were enriched in various biological processes, many of which have been linked to anthracycline-related cardiomyopathy.CONCLUSIONS: A risk model was developed on the basis of the differential expression of serum proteins in subclinical cardiomyopathy, which accurately discriminated the risk for severe cardiomyopathy in an independent, matched sample. Further assessment of these proteins as biomarkers of cardiomyopathy risk should be conducted in external larger cohorts and through prospective studies.PMID:39896123 | PMC:PMC11782007 | DOI:10.1016/j.jaccao.2024.10.004

Front Pharmacol. 2025 Jan 17;16:1497988. doi: 10.3389/fphar.2025.1497988. eCollection 2025.ABSTRACTSkin repair and regeneration are crucial processes in restoring the integrity of the skin after injury, with significant implications for medical treatments and plastic surgery. Multiomics, an integrated approach combining genomics, transcriptomics, proteomics, and metabolomics, offers unprecedented insights into the complex molecular and cellular mechanisms involved in skin healing. This review explores the transformative role of multiomics in elucidating the mechanisms of skin repair and regeneration. While genomic studies identify the genetic basis of wound healing, transcriptomics and proteomics uncover the dynamic changes in gene and protein expression, and metabolomics provides a snapshot of metabolic alterations associated with wound healing. Integrative multiomics studies can also identify novel biomarkers and therapeutic targets for skin regeneration. Despite the technical and biological challenges, the future of multiomics in skin research holds great promise for advancing personalized medicine and improving wound healing strategies. Through interdisciplinary collaboration, multiomics has the potential to revolutionize our understanding of skin repair, paving the way for innovative treatments in plastic surgery and beyond.PMID:39896077 | PMC:PMC11782119 | DOI:10.3389/fphar.2025.1497988

Int J Rheum Dis. 2025 Feb;28(2):e70094. doi: 10.1111/1756-185X.70094.ABSTRACTBACKGROUND: Gout is a prevalent metabolic disorder characterized by a multifaceted process of development. Recent research has emphasized a robust correlation between the immune response and gout. Nevertheless, it is still uncertain if this connection is causative. Hence, the objective of this study was to investigate the causal relationship between immune cells and gout, while also analyzing the role of the plasma metabolome as metabolic mediators in this biological process.METHODS: This study explored the causal link between different subtypes of immune cells and gout using two-sample Mendelian randomization (MR). To confirm the reliability of the findings, reverse MR analysis, steiger test and sensitivity tests were conducted. A two-step mediation analysis was used to gain insight into the role of plasma metabolites as intermediate mediators.RESULTS: This two-sample, bidirectional, two-step MR analysis found a nominal causal link between 33 immune cells as well as 47 known plasma metabolites and gout. Reverse MR analysis and sensitivity tests demonstrated the reliability of the MR results. In addition, we found that Tetradecadienedioate (C14:2-DC) played a partially mediating role in the CD4 on activated CD4 regulatory T cell and gout pathways, with a mediating proportion of 13.16%, (95% CI = 0.65%-25.67%, p = 0.034).CONCLUSION: The objective of our research was to investigate the possible causative connection between immune cells and gout. Our findings indicate that certain plasma metabolites may play a role in mediating this association. This study offers novel insights and sources of information that may contribute to the early detection and proactive measures to avoid gout in the future.PMID:39895258 | DOI:10.1111/1756-185X.70094

Cancer Sci. 2025 Feb 2. doi: 10.1111/cas.16430. Online ahead of print.ABSTRACTEarly detection of esophageal cancer is essential for esophagogastroduodenoscopy and histopathological diagnosis. However, endoscopic examinations are sometimes invasive, which limits their clinical application and compliance, and traditional blood tumor markers are unsuitable for cancer screening. The current study aimed to evaluate the usefulness of sulfur metabolites as new biomarkers for esophageal cancer using blood samples and exhaled breath condensate (EBC), which can be readily obtained and is non-invasive. We collected EBC and plasma samples from 50 patients with esophageal cancer and 30 healthy controls. Sulfur metabolome analysis using tandem mass spectrometry was performed to compare the metabolic profile between the two groups. Supersulfide metabolic profiles were different between the two cohorts. Supersulfide metabolome analysis showed that cysteine hydropersulfide (CysSSH) and homocysteine hydropersulfide (HomoCysSSH) were increased in the plasma of patients with esophageal cancer. Elevated levels of HomoCysSSH could distinguish patients with esophageal cancer from healthy subjects (area under the curve [AUC]: 0.93, sensitivity: 89%, specificity: 96%). Interestingly, we also detected an elevation of supersulfides in the EBC analysis. CysSSH levels significantly increased in the EBC recovered from patients with esophageal cancer (AUC: 0.71, sensitivity: 60%, specificity: 96%). In addition, the observed level was correlated with that of HomoCysSSH in the plasma (r = 0.27). Supersulfides, such as CysSSH and HomoCysSSH, are potential biomarkers for detecting esophageal cancer. CysSSH from EBC may serve as a valuable non-invasive biomarker with similar detection ability but with superior precision and convenience compared with the currently available blood biomarkers.PMID:39895210 | DOI:10.1111/cas.16430