Metabolomics最新文献

{"title":"Treatment of achalasia led to normalisation of energy metabolism and proteosynthesis dependent on the pool of circulating amino acids; metabolomic monitoring and body composition analysis on insufficient nutrition.","authors":"Martin Duricek, Eva Baranovicova, Michal Demeter, Diana Vazanova, Lenka Nosakova, Marek Vojtko, Martin Kertys, Jan Lehotsky, Erika Halasova, Peter Banovcin","doi":"10.1007/s11306-025-02303-6","DOIUrl":"10.1007/s11306-025-02303-6","url":null,"abstract":"<p><strong>Introduction: </strong>Achalasia is a rare motility disorder of the esophagus characterized by the loss of the propulsive peristalsis and impaired relaxation of the lower esophageal sphincter. Patients with untreated achalasia suffer from dysphagia and regurgitation and, consequently, weight loss as they require dietary modifications related to impaired esophageal emptying. Peroral endoscopic myotomy (POEM) is considered the mainstay of therapy, leading to symptom relief, restoration of normal eating patterns and weight gain.</p><p><strong>Objectives: </strong>This study aims to describe the metabolic state of an organism in time of insufficient nutrition and the relation among levels of systemic metabolites and changes in body's composition in condition of normalised food intake.</p><p><strong>Methods: </strong>We monitored body composition, as well as biochemical parameters in 43 patients with achalasia before and 3 months after POEM intervention. We also determined the levels of circulating metabolites via NMR spectroscopy which were, besides comparison to controls, used to describe metabolic turnover before and after treatment.</p><p><strong>Results: </strong>After POEM, all patients except four individuals gained weight (p-value 3.07e-11), and accordingly, the BMI value changed (p-value 2.85e-9). Paired test revealed an increase in absolute fat (p-value 0.00176) and muscle mass (p-value 0.00201). Metabolic analysis in patients with untreated achalasia showed a ketotic-like state with inadequate glycolysis and gluconeogenesis, which partially normalized three months after POEM. Post-POEM muscle mass gain was positively (p < 0.05-0.0005) and increase in absolute fat mass was negatively correlated (p-value < 0.05-0.0005) with the levels of circulating amino acids before the intervention.</p><p><strong>Conclusion: </strong>Our observations provide complex insight into the metabolic shifts after successful treatment of achalasia that is directly related to the changes in the body composition. The metabolic alterations were not detectable through standard biochemical tests suggesting that conventional diagnostics may not fully reflect the metabolic condition of patients with achalasia.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 5","pages":"109"},"PeriodicalIF":3.3,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12339584/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144822033","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":"Metabolic profiling of amniotic fluid by differential ¹²C-/¹³C-isotope dansylation labeling LC-MS for application in trisomy 21 fetuses.","authors":"Ya-Ju Hsieh, Yao-Lung Chang, Yi-Hsin Wu, Cheng-Yu Hung, Liang Li, Jau-Song Yu, Chih-Hsiang Chang, Wei-Ju Tu, Yi-Ting Chen","doi":"10.1007/s11306-025-02298-0","DOIUrl":"https://doi.org/10.1007/s11306-025-02298-0","url":null,"abstract":"<p><strong>Introduction: </strong>Down syndrome, caused by the triplication of human chromosome 21 (trisomy 21 [T21]) or its distal segment, is the most prevalent chromosomal anomaly associated with intellectual disability in newborns.</p><p><strong>Objectives: </strong>To investigate the relationship between T21 and hydrops by analyzing metabolomic alterations, identifying correlations, and exploring pathway regulation mechanisms. This study goes beyond biomarker discovery, aiming to elucidate the pathogenesis of T21 and to explore the underlying mechanism.</p><p><strong>Methods: </strong>We developed a ¹²C₂-/¹³C₂-isotope dansylation labeling LC-MS workflow to profile amine/phenol-based metabolomic differences in amniotic fluid (AF) between T21 and euploid fetuses.</p><p><strong>Results: </strong>This workflow enabled the classification of AF specimens, revealing 138 increased and 116 decreased out of 2351 detected metabolites in T21 AF specimens. Metabolite identities were confirmed via LC-MS/MS spectral analysis using authentic standards. Dysregulated metabolites in T21 AF included markers of oxidative regulation and glutathione metabolism as well as those linked to fetal development. Further subgroup analysis identified 31 T21-associated metabolites, including significantly elevated androsterone sulfate in T21 AF both with and without hydrops. Among 30 hydrops-associated metabolites, most were reduced in hydrops AF, while hyaluronic acid (HA) was notably elevated only in T21 hydrops cases. Correlation analyses highlighted negative associations between HA and metabolites like kynurenine and homovanillic acid, suggesting potential roles in immune modulation and neuronal development in the fetal microenvironment.</p><p><strong>Conclusion: </strong>This study identifies T21-associated metabolites that may serve as early diagnostic markers or therapeutic targets, offering insights into the metabolic landscape of Down syndrome and a foundation for exploring fetal therapeutic strategies.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 5","pages":"106"},"PeriodicalIF":3.3,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144822029","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":"Exploratory investigation of urinary alkanes and other volatile organic compounds in paediatric patients with tuberculous meningitis.","authors":"Simon Isaiah, Du Toit Loots, A Marceline Tutu van Furth, Regan Solomons, Sabine van Elsland, Martijn van der Kuip, Shayne Mason","doi":"10.1007/s11306-025-02304-5","DOIUrl":"10.1007/s11306-025-02304-5","url":null,"abstract":"<p><strong>Background: </strong>Tuberculous meningitis (TBM) is a disease caused by Mycobacterium tuberculosis (M. tb) infection of the brain. Alkanes and other volatile organic compounds (VOCs) are biologically important metabolites that are used by infectious mycobacteria species for growth and survival strategies.</p><p><strong>Objective: </strong>This study investigated the altered alkanes and other VOCs in the urine from paediatric cases with TBM.</p><p><strong>Method: </strong>We used untargeted gas chromatography coupled with time-of-flight mass spectrometry (GC-TOFMS) to analyse and compare all volatile, underivatised compounds present in the urine from 27 confirmed cases of paediatric TBM over a treatment period of six months, as well as a control group (n = 13).</p><p><strong>Result: </strong>Four elevated alkanes (pentadecane, 5,7-dimethyl-undecane, 4,7-dimethyl-undecane, and 2,6-dimethyl-undecane), three alkenes (decreased 2,5-dimethyl-2-hexene and 4,4-dimethyl-1-pentene, and increased 3-methoxy-1-pentene), and three other VOCs of biological interest (decreased 2-butenoic acid methyl ester and 3-heptanone, and increased 2-pyrrolidinone) were identified as statistically significant. These volatile compounds remained perturbed during the TBM treatment.</p><p><strong>Conclusion: </strong>This study discovered new systemic metabolic information about M. tb in the host and the role of alkanes and VOCs in the potential persistence of M. tb. We demonstrate the value of targeting alkanes and other VOCs for future metabolomics studies of M. tb.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 5","pages":"107"},"PeriodicalIF":3.3,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12339628/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144822005","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":"Dysregulation of serum bile acids in liver cancer: a systematic review and meta-analysis.","authors":"Qing Peng, Liyuan Hao, Shenghao Li, Xiaoyu Hu","doi":"10.1007/s11306-025-02311-6","DOIUrl":"10.1007/s11306-025-02311-6","url":null,"abstract":"<p><strong>Background: </strong>Previous studies have indicated that certain bile acids (BAs) were associated with the occurrence and development of liver cancer. However, a comprehensive analysis of serum bile acid (BA) expression patterns and dysregulation in liver cancer remained unexplored.</p><p><strong>Aim of review: </strong>This meta-analysis aimed to evaluate serum BA profiles comprehensively and determine the association between specific BA molecular species and liver cancer.</p><p><strong>Key scientific concepts of review: </strong>BAs, key molecules in metabolism and signaling, have been increasingly recognized for their role in liver cancer pathogenesis. While prior studies have explored individual BAs, a systematic analysis of their dysregulation in liver cancer has remained unaddressed. This meta-analysis analyzed data from 14 original studies with a total of 2994 participants (1686 liver cancer cases and 1308 controls) and revealed significant alterations in both primary and secondary BAs, along with disrupted BA ratios in liver cancer patients. These findings underscored the profound metabolic dysregulation in liver cancer and presented critical insights that might aid in disease diagnosis and management.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 5","pages":"108"},"PeriodicalIF":3.3,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144822002","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":"A diagnostic algorithm for inherited metabolic disorders using untargeted metabolomics.","authors":"Qian Gao, Adnan Khan, Mette Christensen, Xiaomin Zhou, Allan Lund, Sabine Weller Grønborg, Flemming Wibrand, Elsebet Østergaard, Thomas Moritz","doi":"10.1007/s11306-025-02302-7","DOIUrl":"10.1007/s11306-025-02302-7","url":null,"abstract":"<p><strong>Introduction: </strong>Untargeted metabolomics is a powerful tool for detecting perturbations in biological systems, offering significant potential for screening for rare inherited metabolic disorders (IMDs). However, the rarity and vast diversity of these diseases, results in limited availability of samples and incomplete metabolic pathway knowledge for each condition. Current diagnostic procedures rely heavily on manual interpretation, which is time-consuming, and data driven approaches are insufficient for small sample sizes.</p><p><strong>Objectives: </strong>To develop a diagnostic algorithm for IMDs addressing the challenges posed by small sample sizes and continuously evolving datasets.</p><p><strong>Methods: </strong>77 IMD patients (35 different IMDs) and 136 control samples were collected from Copenhagen University Hospital, Rigshospitalet. The metabolome was analyzed using liquid chromatography-mass spectrometry. An algorithm partially based on sparse hierarchical clustering was designed to generate IMD-specific metabolic signatures from metabolomics data, enabling comparison with undiagnosed patient samples to provide diagnostic predictions. An iterative improvement strategy was employed, where new data are continuously integrated to refine the IMD-specific signatures. The algorithm's performance was evaluated through both the current study and a case study using literature-derived data.</p><p><strong>Results: </strong>The algorithm demonstrated iterative improvement with each training round, correctly identifying the diagnosis within top 3 potential IMDs in 60% of samples (top 1 in 42%). The case study applied the method to literature-based data comprising 95 IMD samples (11 different IMDs) and 68 controls, yielding a correct diagnosis in 73.5% of cases.</p><p><strong>Conclusion: </strong>These results demonstrate that the algorithm provides a flexible, data-driven framework for continuous improvement in IMD diagnosis, even with limited number of samples.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 4","pages":"101"},"PeriodicalIF":3.3,"publicationDate":"2025-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12301266/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144732172","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":"Feasibility of amino acid profiling in long-term stored formalin-fixed paraffin-embedded colorectal neoplasia tissue.","authors":"Roza C M Opperman, Puck E Bruchner, Sofie Bosch, Tim G J de Meij, Evelien Dekker, Nanne K H de Boer, Eduard A Struys","doi":"10.1007/s11306-025-02301-8","DOIUrl":"10.1007/s11306-025-02301-8","url":null,"abstract":"<p><strong>Introduction: </strong>Metabolic processes play a role in cancer development, with faecal amino acids emerging as potential biomarkers for colorectal neoplasia. While fresh frozen tissue is preferred for metabolomic analysis, formalin-fixed paraffin-embedded (FFPE) tissue is more widely available.</p><p><strong>Objectives: </strong>We aimed to evaluate amino acid profiles in FFPE tissue across different stages of the adenoma-carcinoma sequence.</p><p><strong>Method: </strong>A panel of 20 amino acids was measured using liquid chromatography-tandem mass spectrometry.</p><p><strong>Results: </strong>Fourteen amino acids were detected, with proline elevated in colorectal carcinoma versus advanced (FC 2.33, p = 0.04) and non-advanced adenomas (FC 2.42, p = 0.02).</p><p><strong>Conclusion: </strong>Despite analytical challenges, amino acid profiling in FFPE tissue is feasible.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 4","pages":"102"},"PeriodicalIF":3.3,"publicationDate":"2025-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12301268/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144718115","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":"Comparison of popular enrichment methods for untargeted in vitro metabolomics.","authors":"Yannik Schermer, Frederic Wagner, Simone Stegmüller, Elke Richling","doi":"10.1007/s11306-025-02309-0","DOIUrl":"10.1007/s11306-025-02309-0","url":null,"abstract":"<p><strong>Introduction: </strong>Untargeted metabolomics is a popular method by which researchers measure a large portion of the metabolites present in a biological system at once. This approach usually results in complex data sets containing tens to hundreds of thousands of observations which require sophisticated data analysis workflows. To help with the functional interpretation of the data, researchers often rely on enrichment analysis. However, little advice is available on what method to use, and, to the best of our knowledge, there is no comparison of popular approaches available for in vitro data with a focus on toxicological and pharmacological testing.</p><p><strong>Objectives: </strong>In this study, we compared three popular enrichment analysis approaches-Metabolite Set Enrichment Analysis (MSEA), Mummichog and Over Representation Analysis (ORA)-with data obtained by treating Hep-G2 cells with 11 compounds with five different mechanisms of action. We compared the results and assessed the consistency of the individual methods as well as their correctness.</p><p><strong>Methods: </strong>Hep-G2 cells were treated with subtoxic concentrations of 11 test compounds. After preparation, samples were measured on an Elute UHPLC coupled to a timsTOF Pro (both Bruker). Spectra were processed in MetaboScape (Bruker) and annotated using spectral library search. Datasets were further processed using R and enrichment analysis was performed in MetaboAnalyst.</p><p><strong>Results: </strong>Overall, we observed a low to moderate similarity between different enrichment methods with the highest similarity between MSEA and Mummichog. Further, Mummichog outperformed both MSEA and ORA in terms of consistency and correctness.</p><p><strong>Conclusion: </strong>In our comparison, Mummichog showed the best performance for in vitro untargeted metabolomics data.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 4","pages":"103"},"PeriodicalIF":3.3,"publicationDate":"2025-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12301278/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144732173","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":"Metabolite classification through novel metabolomics framework reveals mechanism underlying the therapeutic effects of PSD95-nNOS blockade for post-stroke depression.","authors":"Yudie Hu, Ran Xiao, Cong Wang, Huihui Meng, Benxing Yao, Qian Xu, Xi Xu, Junsong Wang","doi":"10.1007/s11306-025-02306-3","DOIUrl":"10.1007/s11306-025-02306-3","url":null,"abstract":"<p><strong>Introduction: </strong>Post-stroke depression (PSD) pathophysiology involves glutamate excitotoxicity mediated through 'postsynaptic density protein95-neuronal nitric oxide synthase' (PSD95-nNOS) coupling. However, the therapeutic mechanisms of targeting this complex remain incompletely understood.</p><p><strong>Objective: </strong>To elucidate the antidepressant mechanisms of the PSD95-nNOS decoupler ZL006 using an innovative integrated metabolomics approach.</p><p><strong>Methods: </strong>We developed an innovative integrated metabolomics approach to investigate the antidepressant mechanisms of ZL006, a selective PSD95-nNOS decoupler. Using a rat model of PSD, we employed untargeted liquid chromatography-mass spectrometry (LC-MS) metabolomics combined with a novel analytical framework that distinguished treatment efficacy-associated metabolites from drug bias-associated ones. This classification enabled identification of primary drug mechanisms versus secondary responses. Pathway analyses focused on proteins interacting with drug-specific metabolites, with key findings validated through quantitative polymerase chain reaction (qPCR).</p><p><strong>Results: </strong>ZL006 demonstrated dose-dependent antidepressant effects while modulating multiple neurotransmitter pathways, including tryptophan, tyrosine, and arginine metabolism, along with steroid hormone synthesis. Our integrated metabolomics approach revealed vascular endothelial growth factor (VEGF) signaling, hypoxia-inducible factor (HIF) pathway, and tight junction regulation as primary mechanisms of action.</p><p><strong>Conclusion: </strong>This novel metabolomics strategy, by discriminating between treatment-associated and compound-intrinsic pathways, provided unprecedented mechanistic insights into ZL006's therapeutic effects. The findings suggest that ZL006 alleviates PSD through coordinated modulation of neuroplasticity, angiogenesis, and stress responses via PSD95-nNOS targeting. This integrated analytical approach presents a valuable framework for mechanistic investigation of therapeutic compounds.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 4","pages":"100"},"PeriodicalIF":3.3,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144608744","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":"Plasma and ovarian metabolomic responses to chronic stress in female mice.","authors":"Nan Lin, Tianyi Huang, Chirag J Patel, Elizabeth M Poole, Clary B Clish, Guillermo N Armaiz-Pena, Archana S Nagaraja, A Heather Eliassen, Katherine H Shutta, Raji Balasubramanian, Laura D Kubzansky, Susan E Hankinson, Oana A Zeleznik, Anil K Sood, Shelley S Tworoger","doi":"10.1007/s11306-025-02287-3","DOIUrl":"10.1007/s11306-025-02287-3","url":null,"abstract":"<p><strong>Introduction: </strong>Chronic stress has been linked with higher risk of ovarian cancer and one posited pathway is through altered metabolism of amino acids, lipids, and other small molecule metabolites. However, the types of alterations that occur may not be uniform across tissue types.</p><p><strong>Objectives: </strong>We aim to examine and compare the impacts of chronic stress on metabolomic changes in circulation and ovarian tissue.</p><p><strong>Methods: </strong>Twelve-week-old, healthy, female, C57 black mice were randomly assigned to three-week of chronic stress using daily restraint (2-hours/day; n = 9) or normal care (n = 10). Metabolomic profiling was conducted on plasma and ovarian tissues via mass spectrometry. We utilized Wilcoxon Rank Tests, Metabolite Set Enrichment Analysis, Differential Network Analysis and a previously derived metabolite-based distress score to identify metabolomic alterations under restraint stress. We used the false discovery rate to account for testing multiple correlated comparisons.</p><p><strong>Results: </strong>In plasma, individual lysophosphatidylcholines and the metabolite class carnitines were positively associated while diacylglycerols and triacylglycerols were inversely associated with restraint stress (adjusted-p < 0.2). In contrast, in ovarian tissue, diacylglycerols and triacylglycerols were positively associated while carnitines were inversely associated with restraint stress (adjusted-p < 0.2). Other metabolites (cholesteryl esters, phosphatidylcholines/ phosphatidylethanolamines plasmalogens and multiple amino acids) were inversely associated with restraint stress in both plasma and ovarian tissue (adjusted-p < 0.2). A previously developed human metabolite-based distress score was higher in restraint stress mice compared to controls, with a larger difference observed in ovarian tissue than in plasma.</p><p><strong>Conclusion: </strong>These findings suggest research to understand the metabolic impact of chronic stress needs to consider both systemic and tissue-specific alterations.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 4","pages":"99"},"PeriodicalIF":3.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144540894","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":"Evaluation of normalization strategies for mass spectrometry-based multi-omics datasets.","authors":"Chi Yen Tseng, Jessica A Salguero, Joshua D Breidenbach, Emilia Solomon, Claire K Sanders, Tara Harvey, M Grace Thornhill, Salvator J Palmisano, Zachary J Sasiene, Brett R Blackwell, Ethan M McBride, Kes A Luchini, Erick S LeBrun, Marc Alvarez, Phillip M Mach, Emilio S Rivera, Trevor G Glaros","doi":"10.1007/s11306-025-02297-1","DOIUrl":"10.1007/s11306-025-02297-1","url":null,"abstract":"<p><strong>Introduction: </strong>Data normalization is crucial for multi-omics integration, reducing systematic errors and maximizing the likelihood of discovering true biological variation. Most studies assess normalization for a single omics type or use datasets from separate experiments. Few address time-course data, where normalization might bias temporal differentiation. In this study, we compared common normalization methods and a machine learning approach, Systematical Error Removal using Random Forest (SERRF), using multi-omics datasets generated from the same experiment-even from the same cell lysate.</p><p><strong>Objectives: </strong>To develop a straightforward process to assess normalization effects and identify the most robust methods across multi-omics datasets.</p><p><strong>Methods: </strong>We analyzed metabolomics, lipidomics, and proteomics datasets from primary human cardiomyocytes and motor neurons exposed to acetylcholine-active compounds over time. Normalization effectiveness was evaluated based on improvement in QC features consistency and observing the change in treatment and time-related variance.</p><p><strong>Results: </strong>Probabilistic Quotient Normalization (PQN) and Locally Estimated Scatterplot Smoothing (LOESS) QC were identified as optimal for metabolomics and lipidomics, while PQN, Median, and LOESS normalization excelled for proteomics. These methods consistently enhanced QC feature consistency in metabolomics and lipidomics, and preserved time-related variance or treatment-related variance in proteomics, demonstrating their effectiveness and robustness. SERRF normalization, applied only to metabolomics in this study, outperformed other methods in some datasets but inadvertently masked treatment-related variance in others.</p><p><strong>Conclusion: </strong>Our evaluation identified PQN and LoessQC as the top methods for metabolomics and lipidomics, and PQN, Median, and Loess normalization for proteomics, in multi-omics integration in a temporal study.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 4","pages":"98"},"PeriodicalIF":3.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12214035/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144540892","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}