Metabolomics最新文献

{"title":"Association of the HDL lipidome with HDL traits before and after exercise training: HERITAGE family study.","authors":"Prasun K Dev, Eric C Leszczynski, Charles S Schwartz, Jacob L Barber, Emanuel J Ayala, Xuewen Wang, Ciaran M Fairman, Sujoy Ghosh, Robert E Gerszten, Michael Olivier, Anand Rohatgi, Clary B Clish, Claude Bouchard, Mark A Sarzynski","doi":"10.1007/s11306-025-02330-3","DOIUrl":"10.1007/s11306-025-02330-3","url":null,"abstract":"<p><strong>Introduction: </strong>HDL particle functionality is influenced by its structure, including lipid composition. However, the effects of exercise training on the HDL lipidome and its relationship with HDL-related traits are largely unknown.</p><p><strong>Objective: </strong>To investigate the HDL lipidome of 154 adults before and after 20 weeks of endurance exercise training in the HERITAGE Family Study.</p><p><strong>Methods: </strong>The HDL-sized plasma fraction was isolated utilizing FPLC-SEC, followed by untargeted lipidomic analysis using LC/MS. A total of 11 HDL lipid classes were derived from the 341 identified known lipid species. Exercise response of the HDL lipidome and its associations with HDL-related traits were examined, with significance set to FDR < 0.05.</p><p><strong>Results: </strong>The abundance of 42 HDL lipid species at baseline and 43 at post-training were significantly different between males and females. Exercise training did not significantly alter the abundance of any HDL lipid class, although HDL phosphatidylethanolamine trended (FDR = 0.05) towards an increase. Two species of HDL diglycerides significantly decreased in the total sample. Sex-specific nominal (p < 0.05) changes in individual HDL lipid species included primarily HDL diglyceride and triglyceride species decreasing in males only, while HDL phosphatidylethanolamine species mostly increasing in females only. Higher abundance of HDL surface lipids was associated with larger size and cholesterol content of HDL particles before and in response to exercise training.</p><p><strong>Conclusion: </strong>Our analysis indicates that endurance exercise may have a limited impact on the HDL lipidome in healthy adults. However, the HDL lipidome differed across sex groups, which needs further investigation to identify potential mechanisms underlying the sex differences.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 5","pages":"120"},"PeriodicalIF":3.3,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12364975/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144883159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of altered metabolites in Rheumatic Heart Disease patients with atrial fibrillation and normal sinus rhythm using untargeted LC-MS metabolomics.","authors":"S Das, S Shruti, Y Kumar, S Gupta, A Jayamon, Srishty, G Sharma","doi":"10.1007/s11306-025-02268-6","DOIUrl":"10.1007/s11306-025-02268-6","url":null,"abstract":"<p><strong>Introduction & objective: </strong>Rheumatic Heart Disease (RHD) is the commonest cause of atrial fibrillation (AF) in India with higher prevalence in younger population. The clinical significance of the differential metabolites in RHD patients with AF is unknown. This is a tertiary hospital-based study aimed to discover the metabolites associated with AF and normal sinus rhythm (NSR) in RHD patients using untargeted LCMS approach.</p><p><strong>Methods: </strong>In this case control study, a total of 87 patients (38 persistent AF and 49 NSR) were incorporated after screening, including 12-lead ECG (electrocardiogram), 2D Echo (two-dimensional echocardiography) and a 24-hr Holter examination for NSR patients to exclude silent AF. Blood samples were collected and differentially expressed metabolites were identified using untargeted LCMS approach.</p><p><strong>Results: </strong>All the patients of our study belong to NYHA (New York Heart Association) classes II and III. The number of female patients was more in both groups. The mean age of the patients was 35.81 ± 7.96 and 29.61 ± 8.18 year in AF and NSR group respectively. 33 metabolites showed significantly altered expression - 15 upregulated and 18 down regulated metabolites. Pathway analysis showed that the altered metabolites were involved in Arginine, Phenylalanine tyrosine and tryptophan biosynthesis, D-Glutamine and D-glutamate, Alanine aspartate and glutamate metabolism, Arginine and proline metabolism.</p><p><strong>Conclusions: </strong>The findings suggest that differential metabolites in RHD patients may help in identifying the high-risk group and possible therapeutic targets.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 5","pages":"119"},"PeriodicalIF":3.3,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144855763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Biomarker discovery in NAFLD: insights from metabolomics and vote counting meta-analysis.","authors":"Pallavi Mudgal, Sonu Kumar Gupta, Sunny Malik, Rinkal B Nith, Sunil Kumar, Rahul K, Kartikey Chaturvedi, Yashwant Kumar","doi":"10.1007/s11306-025-02312-5","DOIUrl":"10.1007/s11306-025-02312-5","url":null,"abstract":"<p><strong>Background: </strong>Despite its prevalence and the significance of early diagnosis, non-alcoholic fatty liver disease (NAFLD), one of the most prevalent liver diseases globally and frequently linked to elements of metabolic syndrome, lacks robustly validated biomarkers for diagnosis, prognosis, and tracking of disease progression in response to a particular treatment.</p><p><strong>Objective: </strong>The aim of this study was to catalogue the metabolites from metabolomics data reported by different studies till date, and to find few majorly dysregulated metabolites that can potentially be used as progressive biomarkers of NAFLD in future.</p><p><strong>Methods: </strong>The clinical data published during last 13 years was investigated and further curated from established databases of MEDLINE, EMBASE and PUBMED on NAFLD. A vote-counting method was used to perform a semi-quantitative meta-analysis of metabolites in serum/blood from NAFLD subjects.</p><p><strong>Results: </strong>This analysis unveiled the well-unprecedented changes in the metabolites of different classes as amino acids Valine, isoleucine, glutamate, tyrosine, alpha-ketoglutarate and phenylalanine were found to be up-regulated whereas glycine, serine and arginine were observed to be down-regulated. This investigation envisaged role of a few metabolites which were significantly distinct in the progression of NAFLD condition.</p><p><strong>Conclusion: </strong>This study highlighted the role of different metabolites in the progression of NAFLD condition. However, the analysis also reveals certain limitations requiring better standardization of metabolomics investigations, signifying errors and lacunas of metabolic databases in identification and reporting. Additionally, inadequate publicly accessible metabolomics data, limits the discovery potential of meta-analyses of clinical studies.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 5","pages":"116"},"PeriodicalIF":3.3,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144822000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Blood metabolomics improves prediction of central nervous system damage in multiple sclerosis.","authors":"Jessica Rebeaud, Nicholas Edward Phillips, Guillaume Thévoz, Solenne Vigne, Sedreh Nassirnia, Aude Gauthier-Jaques, Pansy Lim-Dubois-Ferriere, Satchidananda Panda, Marie Théaudin, Renaud Du Pasquier, Gilbert Greub, Claire Bertelli, Jens Kuhle, Tinh-Hai Collet, Caroline Pot","doi":"10.1007/s11306-025-02315-2","DOIUrl":"10.1007/s11306-025-02315-2","url":null,"abstract":"<p><strong>Introduction: </strong>Multiple sclerosis (MS) is an autoimmune disorder with an unpredictable outcome at the time of diagnosis. The measurement of serum neurofilament light chain (sNfL) and glial fibrillary acidic protein (sGFAP) has introduced new biomarkers for assessing MS disease activity and progression. However, there is a need for additional diagnostic and prognostic tools. In this study, we investigated the predictive abilities of metabolomics, gut microbiota, as well as clinical and lifestyle factors for MS outcome parameters.</p><p><strong>Objectives: </strong>The aim of this study was to assess the predictive capacity of plasma metabolites, gut microbiota, and clinical/lifestyle factors on MS outcome measures including MS-related fatigue, MS disability, and sNfL and sGFAP concentrations.</p><p><strong>Methods: </strong>A prospective cohort study was conducted with 54 individuals with MS. Anthropometric, biological, and lifestyle parameters were collected. The least absolute shrinkage and selection operator (LASSO) algorithm with ten-fold cross-validation was used to identify predictors of MS disease outcome parameters based on plasma metabolomics, microbiota sequencing, and clinical and lifestyle measurements obtained from questionnaires and anthropometric measurements.</p><p><strong>Results: </strong>Circulating metabolites were found to be superior predictors for sNfL and sGFAP concentrations, while clinical and lifestyle data were associated with EDSS scores. Both plasma metabolites and clinical data significantly predicted MS-related fatigue. Combining multiple multi-omics data did not consistently improve predictive performance.</p><p><strong>Conclusions: </strong>This study highlights the value of plasma metabolites as predictors of sNfL, sGFAP, and fatigue in MS. Our findings suggest that prioritizing metabolomics over other methods can lead to more accurate predictions of MS disease outcomes.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 5","pages":"114"},"PeriodicalIF":3.3,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12343719/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144822001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metabolomic and lipidomic profiling of plasma in kidney stone patients: identification of potential biomarkers and therapeutic targets.","authors":"Ziyu Fang, Shenglan Gong, Ling Li, Shuwei Zhang, Wei He, Yuchen Gao, Yonghan Peng, Meng Shu, Yiying Jia, Bangyu Zou, Shaoxiong Ming, Min Liu, Hao Dong, Chenghua Yang, Xu Gao, Xiaofeng Gao","doi":"10.1007/s11306-025-02307-2","DOIUrl":"10.1007/s11306-025-02307-2","url":null,"abstract":"<p><strong>Background: </strong>Kidney stone are among the most common urologic diseases characterized with metabolic disorder. Biomarker for kidney stone detection and the metabolic variables in kidney stone development have attracted increasing attention.</p><p><strong>Methods: </strong>To explore the metabolomic and lipidomic characteristics of plasma in patients with kidney stones, we collected plasma samples from 200 participants, including 100 kidney stone patients and 100 healthy controls. We designated 59 patients with clearly defined stone compositions alongside matched healthy individuals as the training set (n = 118), while the remaining 41 patients with unclear stone compositions were paired with healthy individuals and served as the test set (n = 82).</p><p><strong>Results: </strong>A total of 333 and 270 metabolites were significantly altered in kidney stone patients under positive and negative ion modes, respectively, compared to healthy controls. KEGG analysis indicated that pathways such as Arginine and proline metabolism, Citrate cycle (TCA cycle), Alanine, aspartate and glutamate metabolism and phenylalanine metabolism, were closely associated with kidney stone formation. Moreover, a total of 416 lipids were significantly changed in the Kidney stone group and the control group. Using Lasso model, a panel of integrated 4 metabolites and 4 lipids showed effective discrimination between Kidney stone group and the control group. Among these metabolites, Isorhamnetin has the potential to effectively reduced oxalate-induecd acute kidney injury, hence lowering the likelihood of stone formation.</p><p><strong>Conclusions: </strong>These findings offer novel insights into the metabolic and lipidomic alterations associated with kidney stones, providing potential biomarkers for early diagnosis and therapeutic targets for intervention.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 5","pages":"117"},"PeriodicalIF":3.3,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12343701/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144822030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mycobacterium tuberculosis curli pili facilitates pathogenicity by modulating central carbon metabolism.","authors":"Tarien J Naidoo, Shinese Ashokcoomar, Barry Truebody, Jared S Mackenzie, Adrie J C Steyn, Manormoney Pillay","doi":"10.1007/s11306-025-02320-5","DOIUrl":"10.1007/s11306-025-02320-5","url":null,"abstract":"<p><strong>Introduction: </strong>Strategies specifically targeting the initial host-pathogen interactions, hold great promise in the identification of accurate biomarkers for tuberculosis (TB) prevention interventions. Mycobacterium tuberculosis (Mtb) curli pili (MTP) (encoded by mtp/Rv3312A), a surface adhesin utilised by the pathogen to interact with host receptor cells, has been reported as a suitable target for TB diagnostic and therapeutic strategies. Previous \"omics\" studies highlighted the role MTP potentially plays in Mtb central carbon metabolism (CCM). However, its precise contribution to metabolism remains unknown.</p><p><strong>Objectives: </strong>This study aimed to examine the role of MTP in the bioenergetic metabolism of Mtb, using bedaquiline (BDQ) to inhibit ATP production through oxidative phosphorylation (OXPHOS), extracellular flux analysis, Mtb wildtype (WT), ∆mtp deletion mutant, and mtp-complemented strains. The role of MTP in regulation of CCM was assessed using ¹³C₆-metabolic flux analysis.</p><p><strong>Results: </strong>MTP was associated with increased bacterial respiration and decreased carbon catabolism via glycolysis in response to the inhibition of ATP synthase by BDQ. The dependence of Mtb Δmtp on OXPHOS for energy production was demonstrated to be greater than the WT and mtp-complemented strains. In addition, metabolic flux profiles revealed that in the Δmtp mutant, CCM was dysregulated by decreasing flux through glycolysis, tricarboxylic acid cycle, glyoxylate and dicarboxylate metabolism, and the pentose phosphate pathway in comparison to the WT.</p><p><strong>Conclusion: </strong>These novel findings show that MTP is associated with the regulation of bioenergetics and metabolism pathways and substantiate MTP as a potential biomarker for TB diagnostics/therapeutics, and a novel target for vaccine/drug development.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 5","pages":"118"},"PeriodicalIF":3.3,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12343700/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144822031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring causal associations between nuclear magnetic resonance biomarkers and colorectal cancer risk.","authors":"Qingyi Zhou, Lichun Yang, Peiyu Zhu, Yutong Wang, Zilu Zhang, Liang Chu","doi":"10.1007/s11306-025-02305-4","DOIUrl":"https://doi.org/10.1007/s11306-025-02305-4","url":null,"abstract":"<p><strong>Background: </strong>Emerging evidence shows significant differences in plasma metabolites between colorectal cancer (CRC) patients and healthy controls. However, previous observational studies have been limited by small sample sizes and single sample sources, leading to an incomplete understanding of these metabolites' causal roles in CRC. This study systematically evaluated the causal relationships between 325 nuclear magnetic resonance (NMR) biomarkers and CRC risk using Mendelian randomization (MR), supplemented by colocalization analysis and an independent validation dataset to confirm key biomarkers.</p><p><strong>Methods: </strong>A genome-wide association study (GWAS) was conducted in a cohort of 250,341 participants from the UK Biobank. MR analysis identified NMR biomarkers with significant causal relationships with CRC. Colocalization analysis was then performed, revealing five biomarkers with high colocalization probabilities (PPH4 > 0.8). These findings were validated in an independent Finnish dataset to confirm the consistency of causal relationships and colocalization signals.</p><p><strong>Results: </strong>MR analysis identified 28 NMR biomarkers with significant causal associations with CRC risk (P_fdr < 0.05). Colocalization analysis highlighted five biomarkers with strong colocalization signals (PPH4 > 0.8), including Omega-6 fatty acids, Omega-6 to total fatty acids ratio, Omega-3 fatty acids, Linoleic acid to total fatty acids percentage, and Degree of unsaturation. Notably, in the Finnish validation dataset, Linoleic acid to total fatty acids percentage demonstrated a significant causal association with CRC (OR 0.77, 95% CI 0.67-0.87, P = 7.5 × 10^-5, P_fdr = 3.8 × 10^-4) while maintaining a high colocalization probability (PPH4 > 0.8), reinforcing its role as a key causal biomarker.</p><p><strong>Conclusions: </strong>This study provides the first comprehensive assessment of NMR biomarkers in relation to rectal cancer risk, identifying linoleic acid to total fatty acids percentage as a key causal biomarker. Additionally, omega-6 to omega-3 ratio, omega-6 to polyunsaturated fatty acids percentage, omega-3 to polyunsaturated fatty acids percentage, and degree of unsaturation were also identified, sharing genetic loci with CRC.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 5","pages":"110"},"PeriodicalIF":3.3,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144822006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"LC-MS/MS metabolomics unravels the resistant phenotype of carbapenemase-producing Enterobacterales.","authors":"Breanna Dixon, Waqar M Ahmed, Stephen J Fowler, Tim Felton, Drupad K Trivedi","doi":"10.1007/s11306-025-02300-9","DOIUrl":"10.1007/s11306-025-02300-9","url":null,"abstract":"<p><strong>Introduction: </strong>The degree of antimicrobial resistance demonstrated by carbapenemase-producing Enterobacterales (CPE) represents a growing public health challenge. Conventional methods for detecting CPE involve culture-based techniques with lengthy incubation steps. There is a need to develop rapid and accurate methods for the detection of resistance, for implementation into clinical diagnostics.</p><p><strong>Objectives: </strong>With cellular phenotype closely linked to the metabolome, the acquisition of resistance should result in detectable differences in microbial metabolism. Accordingly, we sought to profile the metabolome of Enterobacterales isolates belonging to both CPE and non-CPE groups to identify metabolites linked to CPE.</p><p><strong>Methods: </strong>We used liquid chromatography-mass spectrometry to profile the endo- and exometabolome of 32 Klebsiella pneumoniae and Escherichia coli isolates to identify metabolites which could predict CPE in antibiotic-free conditions after 6 h of growth.</p><p><strong>Results: </strong>Using supervised machine learning and multivariate analysis algorithms (partial least squares-discriminant analysis, k-nearest neighbour and random forest), we identified 21 metabolite biomarkers which displayed high performance metrics for the prediction of CPE (AUROCs ≥ 0.845). Results revealed a range of alterations between the metabolomes of CPE and non-CPE isolates. Pathway analysis revealed enrichment of microbial pathways including arginine metabolism, ATP-binding cassette transporters, purine metabolism, biotin metabolism, nucleotide metabolism, and biofilm formation, providing mechanistic insight into the resistance phenotype of CPE.</p><p><strong>Conclusion: </strong>Our models demonstrate the ability to distinguish CPE from non-CPE in under 7 h using metabolite biomarkers, showing potential for the development of a targeted diagnostic assay.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 5","pages":"115"},"PeriodicalIF":3.3,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12343662/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144822028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of myocardial revascularization surgery on the plasma metabolome.","authors":"Felipe Fernandes Pires Barbosa, Marco Antonio Coral Pinto, Álex Ap Rosini Silva, Luisa Oliveira Messias, Vanessa Bertolucci, Pedro Paulo Menezes Scariot, Lucas Miguel de Carvalho, José Geraldo Cardoso Junior, Andréia de Melo Porcari, Leonardo Henrique Dalcheco Messias","doi":"10.1007/s11306-025-02316-1","DOIUrl":"10.1007/s11306-025-02316-1","url":null,"abstract":"<p><strong>Introduction: </strong>Myocardial revascularization (MR) is recommended in acute myocardial infarction. Understanding the physiological disturbances caused by MR may be pertinent for future therapeutic strategies in the postoperative period.</p><p><strong>Objectives: </strong>This study aims to analyze the MR impact on plasma metabolites and investigate potential correlations between them with routinely measured biochemical and clinical parameters in MR, and with the cardiopulmonary bypass time (CPB).</p><p><strong>Methods: </strong>Twenty-five patients had plasma samples collected before and after MR for metabolomic analysis, performed by liquid chromatography coupled with high-resolution mass spectrometry.</p><p><strong>Results: </strong>One hundred eleven ions showed statistically significant differences due to MR and thirteen were identified. Only Pregnenolone Sulfate had its abundance in plasma decreased due to MR. Hydrocortisone succinate, Cortisone, and Corticosterone increased in response to the glucocorticoids administered during surgery. LysoPS 16:1, LysoPC 14:0, Phenylvaleric acid, 13-Hydroxyoctadecadienoic acid, N-Linoleoyl Glutamine, and N-Myristoyl Methionine, along with the significant increase in the white blood cell count are associated with inflammation processes, possibly caused by MR. Furthermore, Pregnenolone sulfate, Pentosidine, Phenylvaleric acid, and N-Myristoyl Methionine were correlated with biochemical/clinical parameters and CPB.</p><p><strong>Conclusion: </strong>These results open new horizons in the interpretation of physiological disturbances caused by MR, as well as provide support for future studies. The scientific community is invited to build upon the outcomes obtained to confirm the associations suggested in this study, advancing the realm of metabolomics and MR.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 5","pages":"111"},"PeriodicalIF":3.3,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144822008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Serum metabolomics identifies unique inflammatory signatures to distinguish rheumatoid arthritis responders and non-responders to TNF inhibitor therapy.","authors":"Michele Fresneda Alarcon, Yun Xu, Cassio Lima, Susanna Ford, Rudi Grosman, Royston Goodacre, Marie M Phelan, Helen L Wright","doi":"10.1007/s11306-025-02310-7","DOIUrl":"10.1007/s11306-025-02310-7","url":null,"abstract":"<p><strong>Introduction: </strong>Rheumatoid arthritis (RA) is an auto-immune disease which causes irreversible damage to tissue and cartilage within synovial joints. Rapid diagnosis and treatment with disease-modifying therapies is essential to reduce inflammation and prevent joint destruction. RA is a heterogeneous disease, and many patients do not respond to front-line therapies, requiring escalation of treatment onto biologics, of which TNF inhibitors (TNF-i) are the most common.</p><p><strong>Objectives/methods: </strong>In this study we determined whether serum metabolomics, using nuclear magnetic resonance (NMR) and Fourier transform infrared (FTIR) spectroscopy, could discriminate RA blood sera from healthy human controls and whether the technologies could be used to predict response or non-response to TNF inhibitor (TNF-i) therapy.</p><p><strong>Results: </strong>NMR spectroscopy identified 35 metabolites in RA sera, with acetic acid being significantly lower in RA sera compared to healthy controls (HC, FDR < 0.05). PLS-DA modelling identified 2-hydroxyisovalericacetic acid, acetoacetic acid, mobile lipids, alanine and leucine as important metabolites for discrimination of RA and HC sera by ¹H NMR spectroscopy (averaged 83.1% balanced accuracy, VIP score > 1). FTIR spectroscopy identified a significant difference between RA and HC sera in the 1000-1200 cm^- 1 spectral area, representing the mixed region of carbohydrates and nucleic acids (FDR < 0.05). Sera from RA patients who responded to TNF-i were significantly different from TNF-i non-responder sera in the 1600-1700 cm^- 1 region (FDR < 0.05).</p><p><strong>Conclusion: </strong>We propose that NMR and FTIR serum metabolomics could be used as a diagnostic tool alongside current clinical parameters to diagnose RA and to predict whether someone with severe RA will respond to TNF-i.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 5","pages":"112"},"PeriodicalIF":3.3,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12343672/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144822032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}