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Recent Advances in Metabolomics and Lipidomics Studies in Human and Animal Models of Multiple Sclerosis
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Improvements in Insulin Resistance and Glucose Metabolism Related to Breastfeeding Are Not Mediated by Subclinical Inflammation
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Detection and Validation of Organic Metabolites in Urine for Clear Cell Renal Cell Carcinoma Diagnosis
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Comparative Metabolic Profiling in Drosophila suzukii by Combined Treatment of Fumigant Phosphine and Low Temperature
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Resistant Potato Starch Supplementation Reduces Serum Free Fatty Acid Levels and Influences Bile Acid Metabolism
Journal Description
Metabolites
Metabolites
is an international, peer-reviewed, open access journal of metabolism and metabolomics, published monthly online by MDPI.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), PubMed, PMC, Embase, CAPlus / SciFinder, and other databases.
- Journal Rank: JCR - Q2 (Biochemistry and Molecular Biology) / CiteScore - Q2 (Endocrinology, Diabetes and Metabolism)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 16.1 days after submission; acceptance to publication is undertaken in 2.9 days (median values for papers published in this journal in the second half of 2024).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
3.5 (2023);
5-Year Impact Factor:
4.0 (2023)
Latest Articles
Matrix Linear Models for Connecting Metabolite Composition to Individual Characteristics
Metabolites 2025, 15(2), 140; https://doi.org/10.3390/metabo15020140 - 19 Feb 2025
Abstract
Background/Objectives: High-throughput metabolomics data provide a detailed molecular window into biological processes. We consider the problem of assessing how association of metabolite levels with individual (sample) characteristics, such as sex or treatment, depend on metabolite characteristics such as pathways. Typically, this is done
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Background/Objectives: High-throughput metabolomics data provide a detailed molecular window into biological processes. We consider the problem of assessing how association of metabolite levels with individual (sample) characteristics, such as sex or treatment, depend on metabolite characteristics such as pathways. Typically, this is done using a two-step process. In the first step, we assess the association of each metabolite with individual characteristics. In the second step, an enrichment analysis is performed by metabolite characteristics. Methods: We combine the two steps using a bilinear model based on the matrix linear model (MLM) framework previously developed for high-throughput genetic screens. Our method can estimate relationships in metabolites sharing known characteristics, whether categorical (such as type of lipid or pathway) or numerical (such as number of double bonds in triglycerides). Results: We demonstrate the flexibility and interoperability of MLMs by applying them to three metabolomic studies. We show that our approach can separate the contribution of the overlapping triglyceride characteristics, such as the number of double bonds and the number of carbon atoms. Conclusion: The matrix linear model offers a flexible, efficient, and interpretable framework for integrating external information and examining complex relationships in metabolomics data. Our method has been implemented in the open-source Julia package, MatrixLM. Data analysis scripts with example data analyses are also available.
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(This article belongs to the Section Bioinformatics and Data Analysis)
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Open AccessArticle
Green Tea with Rhubarb Root Reduces Plasma Lipids While Preserving Gut Microbial Stability in a Healthy Human Cohort
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Amanda J. Lloyd, MJ Pilar Martinez-Martin, Alina Warren-Walker, Matthew D. Hitchings, Odin M. Moron-Garcia, Alison Watson, Bernardo Villarreal-Ramos, Laura Lyons, Thomas Wilson, Gordon Allison and Manfred Beckmann
Metabolites 2025, 15(2), 139; https://doi.org/10.3390/metabo15020139 - 19 Feb 2025
Abstract
Background/Objectives: Cardiovascular diseases remain a leading cause of mortality and morbidity, and dyslipidaemia is one of the major risk factors. The widespread use of herbs and medicinal plants in traditional medicine has garnered increasing recognition as a valuable resource for increasing wellness
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Background/Objectives: Cardiovascular diseases remain a leading cause of mortality and morbidity, and dyslipidaemia is one of the major risk factors. The widespread use of herbs and medicinal plants in traditional medicine has garnered increasing recognition as a valuable resource for increasing wellness and reducing the onset of disease. Several epidemiologic and clinical studies have shown that altering blood lipid profiles and maintaining gut homeostasis may protect against cardiovascular diseases. Methods: A randomised, active-controlled parallel human clinical trial (n = 52) with three herbal tea infusions (green (Camellia sinensis) tea with rhubarb root, green tea with senna, and active control green tea) daily for 21 days in a free-living healthy adult cohort was conducted to assess the potential for health benefits in terms of plasma lipids and gut health. Paired plasma samples were analysed using Afinion lipid panels (total cholesterol, LDL (low-density lipoprotein) cholesterol, HDL (high-density lipoprotein) cholesterol, triglycerides, and non-HDL cholesterol) and paired stool samples were analysed using 16S rRNA amplicon sequencing to determine bacterial diversity within the gut microbiome. Results: Among participants providing fasting blood samples before and after the intervention (n = 47), consumption of herbal rhubarb root tea and green tea significantly lowered total cholesterol, LDL-cholesterol, and non-HDL cholesterol (p < 0.05) in plasma after 21 days of daily consumption when compared with concentrations before the intervention. No significant change was observed in the senna tea group. In participants providing stool samples (n = 48), no significant differences in overall microbial composition were observed between pre- and post-intervention, even at the genus level. While no significant changes in overall microbial composition were observed, specific bacterial genera, such as Dorea spp., showed correlations with LDL cholesterol concentrations, suggesting potential microbiota-mediated effects of tea consumption. Diet and BMI was maintained in each of the three groups before and after the trial. Conclusions: It was found that drinking a cup of rhubarb root herbal or green tea infusion for 21 days produced beneficial effects on lipid profiles and maintained gut eubiosis without observable adverse effects in a healthy human cohort. More studies are needed to fully understand the effects of rhubarb root and green tea in fatty acid metabolism and gut microbial composition.
Full article
(This article belongs to the Special Issue The Roles of Diet, Gut Microbiome and Microbial Metabolome in Precision Nutrition)
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Open AccessReview
From Microbes to Metabolites: Advances in Gut Microbiome Research in Type 1 Diabetes
by
Lente Blok, Nordin Hanssen, Max Nieuwdorp and Elena Rampanelli
Metabolites 2025, 15(2), 138; https://doi.org/10.3390/metabo15020138 - 19 Feb 2025
Abstract
Background: Type 1 diabetes (T1D) is a severe chronic T-cell mediated autoimmune disease that attacks the insulin-producing beta cells of the pancreas. The multifactorial nature of T1D involves both genetic and environmental components, with recent research focusing on the gut microbiome as a
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Background: Type 1 diabetes (T1D) is a severe chronic T-cell mediated autoimmune disease that attacks the insulin-producing beta cells of the pancreas. The multifactorial nature of T1D involves both genetic and environmental components, with recent research focusing on the gut microbiome as a crucial environmental factor in T1D pathogenesis. The gut microbiome and its metabolites play an important role in modulating immunity and autoimmunity. In recent years, studies have revealed significant alterations in the taxonomic and functional composition of the gut microbiome associated with the development of islet autoimmunity and T1D. These changes include reduced production of short-chain fatty acids, altered bile acid and tryptophan metabolism, and increased intestinal permeability with consequent perturbations of host (auto)immune responses. Methods/Results: In this review, we summarize and discuss recent observational, mechanistic and etiological studies investigating the gut microbiome in T1D and elucidating the intricate role of gut microbes in T1D pathogenesis. Moreover, we highlight the recent advances in intervention studies targeting the microbiota for the prevention or treatment of human T1D. Conclusions: A deeper understanding of the evolution of the gut microbiome before and after T1D onset and of the microbial signals conditioning host immunity may provide us with essential insights for exploiting the microbiome as a prognostic and therapeutic tool.
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(This article belongs to the Special Issue The Role of Gut Microbes in Metabolism Regulation: 2nd Edition)
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Broussonetia papyrifera Pollen Metabolome Insights, Allergenicity, and Dispersal in Response to Climate Change Variables
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Muhammad Humayun, Saadia Naseem, Richard E. Goodman and Zahid Ali
Metabolites 2025, 15(2), 137; https://doi.org/10.3390/metabo15020137 - 18 Feb 2025
Abstract
Background/Objectives: Broussonetia papyrifera is a tree-producing allergenic pollen that grows in varied climatic conditions worldwide and causes pollen allergies in susceptible humans. This study aimed to investigate B. papyrifera pollen morphology, pollen metabolome, pollen allergenicity, and climate change’s impact on the plant
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Background/Objectives: Broussonetia papyrifera is a tree-producing allergenic pollen that grows in varied climatic conditions worldwide and causes pollen allergies in susceptible humans. This study aimed to investigate B. papyrifera pollen morphology, pollen metabolome, pollen allergenicity, and climate change’s impact on the plant habitat suitability in the future. Methods: Tree pollen was collected in spring from different regions of Pakistan. Pollen samples were subjected to morphological analysis, Fourier transform infrared spectroscopy (FTIR), liquid chromatography–mass spectrometry (LC-MS/MS), and immunoblotting. Results: MaxEnt modeling predicted the tree’s future-growth invasion into new regions. Scanning electron microscopy (SEM) and FTIR displayed regional differences in pollen morphology and metabolome correlated to shifts in climatic variables. LC-MS/MS analysis detected four lipids that can potentially stimulate inflammatory responses. Pollen protein immunoblotting studies identified a putative 15 kDa novel allergen and verified previously known 40 kDa, 33 kDa, and 10 kDa allergens. B. papyrifera MaxEnt modeling through ACCESS1.0 and CCSM4 under 2-greenhouse gas emissions scenarios {representative concentration pathway (RCP) 4.5 and 8.5} projected the tree invasion by the years 2050 and 2070. Conclusions: The study findings demonstrate that differences in climatic variables affect B. papyrifera-pollen metabolome and predict the habitat suitability of the tree for invasion in the future. The study results provide a model system for studying other species’ pollen morphology, metabolome, future habitat suitability for plant invasion, and associated allergies in response to climate change.
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(This article belongs to the Section Plant Metabolism)
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The Adaptation of MCF-7 Breast Cancer Spheroids to the Chemotherapeutic Doxorubicin: The Dynamic Role of Phase I Drug Metabolizing Enzymes
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Daniel Crispim, Carolina Ramos, Francisco Esteves and Michel Kranendonk
Metabolites 2025, 15(2), 136; https://doi.org/10.3390/metabo15020136 - 18 Feb 2025
Abstract
Background/Objectives: Drug resistance (DR) is a major challenge in cancer therapy, contributing to approximately 90% of cancer-related deaths. While alterations in drug metabolism are known to be key drivers of DR, their role—particularly in the early stages of acquired chemoresistance—remains understudied. Phase I
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Background/Objectives: Drug resistance (DR) is a major challenge in cancer therapy, contributing to approximately 90% of cancer-related deaths. While alterations in drug metabolism are known to be key drivers of DR, their role—particularly in the early stages of acquired chemoresistance—remains understudied. Phase I drug-metabolizing enzymes (DMEs), especially cytochrome P450s (CYPs), significantly influence the metabolic fate of chemotherapeutic agents, directly affecting drug response. This study aimed to investigate the role of Phase I DMEs in the early metabolic adaptation of breast cancer (BC) MCF-7 cells to doxorubicin (DOX). Methods: Four types of spheroids were generated from MCF-7 cells that were either DOX-sensitive (DOXS) or adapted to low concentrations of the chemotherapeutic agent (DOXA 25, 35, and 45 nM). The expression levels of 92 Phase I DMEs and the activities of specific CYP isoforms were assessed in both DOXS and DOXA spheroids. Results: A total of twenty-four DMEs, including fifteen CYPs and nine oxidoreductases, were found to be differentially expressed in DOXA spheroids. Pathway analysis identified key roles for the differentially expressed DMEs in physiologically relevant pathways, including the metabolism of drugs, arachidonic acid, retinoic acid, and vitamin D. Conclusions: The deconvolution of these pathways highlights a highly dynamic process driving early-stage DOX resistance, with a prominent role of CYP3A-dependent metabolism in DOX adaptation. Our findings provide valuable insights into the underlying molecular mechanisms driving the early adaptation of MCF-7 cells to DOX exposure.
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(This article belongs to the Special Issue Drug Metabolism: Latest Advances and Prospects)
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Open AccessArticle
Integrated Analyses of the Mechanism of Flower Color Formation in Alfalfa (Medicago sativa)
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Zhaozhu Wen, Huancheng Liu, Qian Zhang, Xuran Lu, Kai Jiang, Qinyan Bao, Zhifei Zhang, Guofeng Yang and Zeng-Yu Wang
Metabolites 2025, 15(2), 135; https://doi.org/10.3390/metabo15020135 - 17 Feb 2025
Abstract
Background: Alfalfa (Medicago sativa) is one of the most valuable forages in the world. As an outcrossing species, it needs bright flowers to attract pollinators to deal with self-incompatibility. Although various flower colors have been observed and described in alfalfa a
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Background: Alfalfa (Medicago sativa) is one of the most valuable forages in the world. As an outcrossing species, it needs bright flowers to attract pollinators to deal with self-incompatibility. Although various flower colors have been observed and described in alfalfa a long time ago, the biochemical and molecular mechanism of its color formation is still unclear. Methods: By analyzing alfalfa lines with five contrasting flower colors including white (cream-colored), yellow, lavender (purple), dark purple and dark blue, various kinds and levels of anthocyanins, carotenoids and other flavonoids were detected in different colored petals, and their roles in color formation were revealed. Results: Notably, the content of delphinidin-3,5-O-diglucoside in lines 3, 4 and 5 was 58.88, 100.80 and 94.07 times that of line 1, respectively. Delphinidin-3,5-O-diglucoside was the key factor for purple and blue color formation. Lutein and β-carotene were the main factors for the yellow color formation. By analyzing differentially expressed genes responsible for specific biochemical pathways and compounds, 27 genes were found to be associated with purple and blue color formation, and 14 genes were found to play an important role in yellow color formation. Conclusions: The difference in petal color between white, purple and blue petals was mainly caused by the accumulation of delphinidin-3,5-O-diglucoside. The difference in petal color between white and yellow petals was mainly affected by the production of lutein and β-carotene. These findings provide a basis for understanding the biochemical and molecular mechanism of alfalfa flower color formation.
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(This article belongs to the Section Plant Metabolism)
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Metabolomic Profiling of the Striatum in Shank3 Knockout ASD Rats: Effects of Early Swimming Regulation
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Yunchen Meng, Yiling Hu, Yaqi Xue and Zhiping Zhen
Metabolites 2025, 15(2), 134; https://doi.org/10.3390/metabo15020134 - 16 Feb 2025
Abstract
Objectives: This study aimed to investigate the regulatory impact of early swimming intervention on striatal metabolism in Shank3 gene knockout ASD model rats. Methods: Shank3 gene knockout exon 11–21 male 8-day-old SD rats were used as experimental subjects and randomly divided into
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Objectives: This study aimed to investigate the regulatory impact of early swimming intervention on striatal metabolism in Shank3 gene knockout ASD model rats. Methods: Shank3 gene knockout exon 11–21 male 8-day-old SD rats were used as experimental subjects and randomly divided into the following three groups: a Shank3 knockout control group (KC), a wild-type control group (WC) from the same litter, and a Shank3 knockout swimming group (KS). The rats in the exercise group received early swimming intervention for 8 weeks starting at 8 days old. LC-MS metabolism was employed to detect the changes in metabolites in the striatum. Results: There were 17 differential metabolites (14 down-regulated) between the KC and WC groups, 19 differential metabolites (18 up-regulated) between the KS and KC groups, and 22 differential metabolites (18 up-regulated) between the KS and WC groups. Conclusions: The metabolism of striatum in Shank3 knockout ASD model rats is disrupted, involving metabolites related to synaptic morphology, and the Glu and GABAergic synapses are abnormal. Early swimming intervention regulated the striatal metabolome group of the ASD model rats, with differential metabolites primarily related to nerve development, synaptic membrane structure, and synaptic signal transduction.
Full article
(This article belongs to the Special Issue Interactions between Exercise Physiology and Metabolism)
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Open AccessReview
Metabolomic Insights into Attention Deficit Hyperactivity Disorder: A Scoping Review
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Maria Jose Muñoz-Zabaleta, Nicolás Garzón Rodríguez, Luis Eduardo Díaz-Barrera and Maria Fernanda Quiroz-Padilla
Metabolites 2025, 15(2), 133; https://doi.org/10.3390/metabo15020133 - 16 Feb 2025
Abstract
Background /Objectives Attention deficit hyperactivity disorder (ADHD) is the most common neurodevelopmental condition, and symptoms persist into adulthood. Its etiology, though recognized as multifactorial, is still under discussion. Metabolomics helps us to identify pathways associated with functional and structural changes that may be
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Background /Objectives Attention deficit hyperactivity disorder (ADHD) is the most common neurodevelopmental condition, and symptoms persist into adulthood. Its etiology, though recognized as multifactorial, is still under discussion. Metabolomics helps us to identify pathways associated with functional and structural changes that may be related to symptomatology. This study aimed to characterize potentially altered metabolic pathways and associated biochemical reactions in ADHD. Methods: A scoping review of experimental research was conducted using PubMed, Web of Science, and Scopus using PRISMA ScR. Fifty-five studies were eligible for data extraction, of which fifteen met the criteria for inclusion in the review. Subsequently, the identified metabolites were analyzed in the context of the literature to recognize possible discordant pathways in the disorder. Results: Two groups of relevant neuromodulators of ADHD were found: precursors of monoamines and polyunsaturated fatty acids. The literature was reviewed to discover potential implicated pathways and new metabolites of interest. Conclusions: The study of ADHD biomarkers should focus on measuring precursor, intermediate, and final metabolites of polyunsaturated fatty acids and monoamines in panels or through untargeted analysis to improve the understanding of the pathology and individualization of treatments.
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(This article belongs to the Topic Application of Chromatography for Point of Care Diagnosis of Noncommunicable Diseases)
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Deep Learning-Based Molecular Fingerprint Prediction for Metabolite Annotation
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Hoi Yan Katharine Chau, Xinran Zhang and Habtom W. Ressom
Metabolites 2025, 15(2), 132; https://doi.org/10.3390/metabo15020132 - 14 Feb 2025
Abstract
Background/Objectives: Liquid chromatography coupled with mass spectrometry (LC-MS) is a commonly used platform for many metabolomics studies. However, metabolite annotation has been a major bottleneck in these studies in part due to the limited publicly available spectral libraries, which consist of tandem mass
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Background/Objectives: Liquid chromatography coupled with mass spectrometry (LC-MS) is a commonly used platform for many metabolomics studies. However, metabolite annotation has been a major bottleneck in these studies in part due to the limited publicly available spectral libraries, which consist of tandem mass spectrometry (MS/MS) data acquired from just a fraction of known compounds. Application of deep learning methods is increasingly reported as an alternative to spectral matching due to their ability to map complex relationships between molecular fingerprints and mass spectrometric measurements. The objectives of this study are to investigate deep learning methods for molecular fingerprint based on MS/MS spectra and to rank putative metabolite IDs according to similarity of their known and predicted molecular fingerprints. Methods: We trained three types of deep learning methods to model the relationships between molecular fingerprints and MS/MS spectra. Prior to training, various data processing steps, including scaling, binning, and filtering, were performed on MS/MS spectra obtained from National Institute of Standards and Technology (NIST), MassBank of North America (MoNA), and Human Metabolome Database (HMDB). Furthermore, selection of the most relevant m/z bins and molecular fingerprints was conducted. The trained deep learning models were evaluated on ranking putative metabolite IDs obtained from a compound database for the challenges in Critical Assessment of Small Molecule Identification (CASMI) 2016, CASMI 2017, and CASMI 2022 benchmark datasets. Results: Feature selection methods effectively reduced redundant molecular and spectral features prior to model training. Deep learning methods trained with the truncated features have shown comparable performances against CSI:FingerID on ranking putative metabolite IDs. Conclusion: The results demonstrate a promising potential of deep learning methods for metabolite annotation.
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(This article belongs to the Special Issue Machine Learning in Metabolomics: Unlocking the Future of Data Analysis)
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Meta-Analysis of Abiotic Conditions Affecting Exopolysaccharide Production in Cyanobacteria
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Shijie Wu, Fuwen Wang, Hong Wang, Cong Shen and Kaiqiang Yu
Metabolites 2025, 15(2), 131; https://doi.org/10.3390/metabo15020131 - 14 Feb 2025
Abstract
Background: cyanobacterial exopolysaccharides (EPSs) exhibit diverse biological and physicochemical properties, making them valuable for applications in environmental remediation, soil improvement, wastewater treatment, and bioenergy production. Results: the production of cyanobacterial EPSs is significantly influenced by various factors, including abiotic factors and
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Background: cyanobacterial exopolysaccharides (EPSs) exhibit diverse biological and physicochemical properties, making them valuable for applications in environmental remediation, soil improvement, wastewater treatment, and bioenergy production. Results: the production of cyanobacterial EPSs is significantly influenced by various factors, including abiotic factors and strains. Recent research has focused on optimizing EPS production by regulating key abiotic factors such as light, temperature, pH, and nutritional conditions. This review systematically compiles and analyzes published data on the effects of abiotic factors on cyanobacterial EPS biosynthesis, with a focus on genus-specific responses. Using meta-analysis techniques, we provide a comprehensive overview of the key factors influencing EPS production. Light and nutrient conditions are the most significant factors affecting EPS production, with high light intensities and optimal nutrient conditions enhancing EPS synthesis. Optimal temperature ranges and pH levels are essential for maximizing EPS production, and cyanobacteria exhibit genus-specific responses to variations in these factors. The addition of specific nutrients, such as NaCl, trace metals (e.g., Mg, Zn, Cu), and elevated CO2 levels, significantly impacts EPS production. Conclusions: the response to these factors varies among different cyanobacterial genera, highlighting the need for genus-specific optimization strategies. This review provides a theoretical basis for optimizing EPS production across diverse cyanobacterial genera and for understanding multi-factor interactions and practical applications in future research.
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(This article belongs to the Section Microbiology and Ecological Metabolomics)
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Use of Saliva Analytes as a Predictive Model to Detect Diseases in the Pig: A Pilot Study
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Eva Llamas-Amor, Alba Ortín-Bustillo, María José López-Martínez, Alberto Muñoz-Prieto, Edgar García Manzanilla, Julián Arense, Aida Miralles-Chorro, Pablo Fuentes, Silvia Martínez-Subiela, Antonio González-Bulnes, Elena Goyena, Andrea Martínez-Martínez, José Joaquín Cerón and Fernando Tecles
Metabolites 2025, 15(2), 130; https://doi.org/10.3390/metabo15020130 - 13 Feb 2025
Abstract
Background/Objectives: Saliva is gaining importance as a diagnostic sample in pigs. The aim of this research was to evaluate a panel of salivary analytes in three porcine diseases and establish predictive models to detect them. Methods: Saliva samples were obtained from healthy pigs
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Background/Objectives: Saliva is gaining importance as a diagnostic sample in pigs. The aim of this research was to evaluate a panel of salivary analytes in three porcine diseases and establish predictive models to detect them. Methods: Saliva samples were obtained from healthy pigs (n = 97) and pigs affected by meningitis due to Streptococcus suis (n = 118), diarrhea due to enterotoxigenic Escherichia coli (ETEC, n = 77), and porcine reproductive and respiratory syndrome (PRRS, n = 52). The following biomarkers were analyzed: adenosine deaminase (ADA), haptoglobin (Hp), calprotectin (Calp), aldolase, alpha-amylase (sAA), lactate dehydrogenase (LDH), total protein (TP), and advanced oxidation protein products (AOPPs). Predictive models based on binary logistic regression and decision trees combining those analytes for detecting specific diseases were constructed. Results: The results showed a different biomarker profile between the groups. S. suis and ETEC pigs showed higher values of ADA, Hp, Calp, aldolase, sAA, LDH, and TP than healthy pigs. Pigs with PRRS showed higher values of Hp, Calp, sAA, and LDH than healthy animals. The constructed predictive models showed overall accuracies of over 78% and 87% for differentiating ETEC and PRRS, respectively, whereas the models did not accurately predict S. suis infection. Conclusions: Salivary analytes show different changes in pigs depending on the disease, and the combination of these analytes can contribute to the prediction of different diseases. Further studies should be conducted in larger populations to confirm these findings and evaluate their possible practical applications.
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(This article belongs to the Section Animal Metabolism)
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Development of a Dispersive Liquid–Liquid Microextraction Method for Quantification of Volatile Compounds in Wines Using Gas Chromatography–Mass Spectrometry
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Dinesha Katugampala Appuhamilage, Rebecca E. Jelley, Emma Sherman, Lisa I. Pilkington, Farhana R. Pinu and Bruno Fedrizzi
Metabolites 2025, 15(2), 129; https://doi.org/10.3390/metabo15020129 - 13 Feb 2025
Abstract
Background/Objectives: This study reports the development of a straightforward, efficient, and cost-effective dispersive liquid–liquid microextraction (DLLME) method for the gas chromatography–mass spectrometry (GC-MS) analysis of volatile compounds present in wine. Methods: Four critical parameters were optimised using a D-optimal design to
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Background/Objectives: This study reports the development of a straightforward, efficient, and cost-effective dispersive liquid–liquid microextraction (DLLME) method for the gas chromatography–mass spectrometry (GC-MS) analysis of volatile compounds present in wine. Methods: Four critical parameters were optimised using a D-optimal design to maximise extraction outcomes of the targeted analytes from a 10 mL sample, while minimising interference from other compounds. The analytical characteristics of the method were assessed using 36 target compounds. Results: The method provided satisfactory linearity (correlation coefficients > 0.990), good repeatability for both for intra- and inter-day measurements (RSD < 10.3%), and suitable recoveries of target analytes from both model (83–110%) and real matrices (80–120%). The validated method was subsequently applied to analyse the aroma profile of 30 New Zealand Pinot noir (PN) wine samples. Conclusions: This study contributes to the advancement of analytical techniques available to both industry and researchers to explore the complex aroma profiles of wines.
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(This article belongs to the Special Issue Metabolomics in Plant Natural Products Research)
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Brain Glycogen—Its Metabolic Role in Neuronal Health and Neurological Disorders—An Extensive Narrative Review
by
Ana Isabel Beltran-Velasco
Metabolites 2025, 15(2), 128; https://doi.org/10.3390/metabo15020128 - 13 Feb 2025
Abstract
Background: Brain glycogen is imperative for neuronal health, as it supports energy demands and metabolic processes. This review examines the pathways involved in glycogen storage and utilization in the central nervous system, emphasizing their role in both physiology and pathology. It explores how
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Background: Brain glycogen is imperative for neuronal health, as it supports energy demands and metabolic processes. This review examines the pathways involved in glycogen storage and utilization in the central nervous system, emphasizing their role in both physiology and pathology. It explores how alterations in glycogen metabolism contribute to neurological disorders, including neurodegenerative diseases, epilepsy, and metabolic conditions while highlighting the bidirectional interaction between neurons and glia in maintaining brain homeostasis. Methods: A comprehensive search of articles published between 2015 and 2025 was conducted using the following databases: ScienceDirect, Scopus, Wiley, Web of Science, Medline, and PubMed. The selection of relevant studies was based on their focus on brain glycogen metabolism and its role in neurological conditions, with studies that did not meet the inclusion criteria being excluded. Results: The metabolic processes of brain glycogen are subject to rigorous regulation by astrocyte–neuron interactions, thereby ensuring metabolic homeostasis and energy availability. The dysregulation of glycogen storage and mobilization has been implicated in the development of synaptic dysfunction, excitotoxicity, and neurodegeneration in a variety of disorders. For instance, aberrant glycogen accumulation in diseases such as Lafora disease has been associated with severe neurodegeneration, while impaired glycogen mobilization has been shown to exacerbate energy deficits in Alzheimer’s and epilepsy. Conclusions: Targeting brain glycogen metabolism represents a promising approach for therapeutic intervention in neurological disorders. However, the translation of these strategies to human models remains challenging, particularly with regard to the long-term safety and specificity of glycogen-targeted therapies.
Full article
(This article belongs to the Special Issue Cellular Metabolism in Neurological Disorders)
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Therapeutic Strategies to Modulate Gut Microbial Health: Approaches for Chronic Metabolic Disorder Management
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Mariangela Rondanelli, Sara Borromeo, Alessandro Cavioni, Clara Gasparri, Ilaria Gattone, Elisa Genovese, Alessandro Lazzarotti, Leonardo Minonne, Alessia Moroni, Zaira Patelli, Claudia Razza, Claudia Sivieri, Eugenio Marzio Valentini and Gaetan Claude Barrile
Metabolites 2025, 15(2), 127; https://doi.org/10.3390/metabo15020127 - 13 Feb 2025
Abstract
Numerous recent studies have suggested that the composition of the intestinal microbiota can trigger metabolic disorders, such as diabetes, prediabetes, obesity, metabolic syndrome, sarcopenia, dyslipidemia, hyperhomocysteinemia, and non-alcoholic fatty liver disease. Since then, considerable effort has been made to understand the link between
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Numerous recent studies have suggested that the composition of the intestinal microbiota can trigger metabolic disorders, such as diabetes, prediabetes, obesity, metabolic syndrome, sarcopenia, dyslipidemia, hyperhomocysteinemia, and non-alcoholic fatty liver disease. Since then, considerable effort has been made to understand the link between the composition of intestinal microbiota and metabolic disorders, as well as the role of probiotics in the modulation of the intestinal microbiota. The aim of this review was to summarize the reviews and individual articles on the state of the art regarding ideal therapy with probiotics and prebiotics in order to obtain the reversion of dysbiosis (alteration in microbiota) to eubiosis during metabolic diseases, such as diabetes, prediabetes, obesity, hyperhomocysteinemia, dyslipidemia, sarcopenia, and non-alcoholic fatty liver diseases. This review includes 245 eligible studies. In conclusion, a condition of dysbiosis, or in general, alteration of the intestinal microbiota, could be implicated in the development of metabolic disorders through different mechanisms, mainly linked to the release of pro-inflammatory factors. Several studies have already demonstrated the potential of using probiotics and prebiotics in the treatment of this condition, detecting significant improvements in the specific symptoms of metabolic diseases. These findings reinforce the hypothesis that a condition of dysbiosis can lead to a generalized inflammatory picture with negative consequences on different organs and systems. Moreover, this review confirms that the beneficial effects of probiotics on metabolic diseases are promising, but more research is needed to determine the optimal probiotic strains, doses, and administration forms for specific metabolic conditions.
Full article
(This article belongs to the Special Issue Targeting Microbiota and Metabolites for Prevention and Treatment of Human Diseases)
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Physiology-Related Variations in the Blood Hormone and Metabolome of Endangered Hog Deer (Axis porcinus)
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Juan Wen, Bo Zhao, Yuqin Cao, Yu Qu, Liming Chang, Jie Mao, Yufei Li, Ruoyao Ni, Runliang Zhai, Jianping Jiang, Wei Zhu and Xuanzhen Liu
Metabolites 2025, 15(2), 126; https://doi.org/10.3390/metabo15020126 - 13 Feb 2025
Abstract
Background/Objectives: The hog deer (Axis porcinus) is an endangered species facing significant threats from habitat loss and fragmentation, with only captive populations remaining in China. Expanding breeding programs and restoring wild populations are critical strategies for the species’ conservation. Achieving
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Background/Objectives: The hog deer (Axis porcinus) is an endangered species facing significant threats from habitat loss and fragmentation, with only captive populations remaining in China. Expanding breeding programs and restoring wild populations are critical strategies for the species’ conservation. Achieving this requires the development of an effective health database and the identification of molecular biomarkers for their physiological traits. Methods: In this study, we present the largest blood metabolomics dataset to date for captive hog deer, comprising 73 healthy individuals. We conducted targeted metabolomics to quantify blood hormone levels and untargeted metabolomics to characterize blood metabolic profiles, aiming to evaluate the associations of sex, age, and weight with metabolic profiles. Results: Our results reveal distinct growth patterns between females and males, with males reaching their body weight plateau at a larger size. We observed significant sex differences (p < 0.05) in blood hormones and metabolic profiles. Females exhibited higher levels of progesterone, hydroxyprogesterone, stress hormones (e.g., cortisol), and proline, while males had higher levels of testosterone, uric acid, phenylalanine, and guanidinosuccinic acid. Notably, body weight emerged as a more important factor than gender in explaining variations in the metabolome, particularly in males. Several blood biomarkers were identified as correlating with age and body weight. Specifically, blood progesterone levels in females were linked to both age and body weight, while in males, uric acid, prolylhydroxyproline, and 3-methylhistidine were associated with these factors. The potential significance of these results for the artificial breeding and conservation of hog deer were discussed. Conclusions: Our study provides a metabolic reference for identifying abnormal individuals and offers potential biomarkers for determining the gender, age, and body weight of hog deer. These findings may have significant implications for the artificial breeding and conservation efforts of the species.
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(This article belongs to the Section Animal Metabolism)
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Open AccessArticle
Central Hypothyroidism with Low TSH Compared to Normal TSH Is Associated with More Advanced Pituitary Disease and Less Favorable Metabolic Profile
by
Aleksandra E. Matusiak, Jan Stępniak, Krzysztof C. Lewandowski, Andrzej Lewiński and Małgorzata Karbownik-Lewińska
Metabolites 2025, 15(2), 125; https://doi.org/10.3390/metabo15020125 - 13 Feb 2025
Abstract
Background: Central hypothyroidism is characterized by either decreased TSH or, more commonly, normal TSH. This study aims to check whether this biochemical difference related to the severity of the pituitary disease, metabolic processes and general well-being. Methods: A retrospective analysis was performed on
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Background: Central hypothyroidism is characterized by either decreased TSH or, more commonly, normal TSH. This study aims to check whether this biochemical difference related to the severity of the pituitary disease, metabolic processes and general well-being. Methods: A retrospective analysis was performed on 108 inpatients with hypopituitarism, aged 18–80, hospitalized (1 January 2020, through 31 December 2022) in the Department of Endocrinology and Metabolic Diseases, Medical University of Lodz, Poland. Hypopituitary patients with central hypothyroidism (n = 90) were divided into two subgroups: patients with TSH below normal ranges (low TSH; n = 52) and patients with TSH in reference ranges (normal TSH; n = 38). Results: Among patients with central hypothyroidism, surgical treatment due to pituitary disease was performed more commonly in those with low TSH than in those with normal TSH (65 vs. 42%, p = 0.010). Expectedly, five pituitary deficiencies were diagnosed more commonly in patients with low TSH than in those with normal TSH (46 vs. 13%, p = 0.001). In a regression analysis, the ACTH concentration was the only independent determinant negatively associated with low TSH (also after limiting the analysis to non-treated patients). Regarding lipid profile, decreased HDL cholesterol occurred more commonly in patients with low TSH vs. normal TSH (44% vs. 23%; p = 0.033), which was also observed after the limitation to non-treated patients (47% vs. 21%; p = 0.013). Conclusions: Low TSH in patients with central hypothyroidism is associated with more advanced pituitary disease and less favorable metabolic profile.
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(This article belongs to the Section Endocrinology and Clinical Metabolic Research)
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Open AccessReview
Polyphenols, Alkaloids, and Terpenoids Against Neurodegeneration: Evaluating the Neuroprotective Effects of Phytocompounds Through a Comprehensive Review of the Current Evidence
by
Enzo Pereira de Lima, Lucas Fornari Laurindo, Vitor Cavallari Strozze Catharin, Rosa Direito, Masaru Tanaka, Iris Jasmin Santos German, Caroline Barbalho Lamas, Elen Landgraf Guiguer, Adriano Cressoni Araújo, Adriana Maria Ragassi Fiorini and Sandra Maria Barbalho
Metabolites 2025, 15(2), 124; https://doi.org/10.3390/metabo15020124 - 13 Feb 2025
Abstract
Neurodegenerative diseases comprise a group of chronic, usually age-related, disorders characterized by progressive neuronal loss, deformation of neuronal structure, or loss of neuronal function, leading to a substantially reduced quality of life. They remain a significant focus of scientific and clinical interest due
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Neurodegenerative diseases comprise a group of chronic, usually age-related, disorders characterized by progressive neuronal loss, deformation of neuronal structure, or loss of neuronal function, leading to a substantially reduced quality of life. They remain a significant focus of scientific and clinical interest due to their increasing medical and social importance. Most neurodegenerative diseases present intracellular protein aggregation or their extracellular deposition (plaques), such as α-synuclein in Parkinson’s disease and amyloid beta (Aβ)/tau aggregates in Alzheimer’s. Conventional treatments for neurodegenerative conditions incur high costs and are related to the development of several adverse effects. In addition, many patients are irresponsive to them. For these reasons, there is a growing tendency to find new therapeutic approaches to help patients. This review intends to investigate some phytocompounds’ effects on neurodegenerative diseases. These conditions are generally related to increased oxidative stress and inflammation, so phytocompounds can help prevent or treat neurodegenerative diseases. To achieve our aim to provide a critical assessment of the current literature about phytochemicals targeting neurodegeneration, we reviewed reputable databases, including PubMed, EMBASE, and COCHRANE, seeking clinical trials that utilized phytochemicals against neurodegenerative conditions. A few clinical trials investigated the effects of phytocompounds in humans, and after screening, 13 clinical trials were ultimately included following PRISMA guidelines. These compounds include polyphenols (flavonoids such as luteolin and quercetin, phenolic acids such as rosmarinic acid, ferulic acid, and caffeic acid, and other polyphenols like resveratrol), alkaloids (such as berberine, huperzine A, and caffeine), and terpenoids (such as ginkgolides and limonene). The gathered evidence underscores that quercetin, caffeine, ginkgolides, and other phytochemicals are primarily anti-inflammatory, antioxidant, and neuroprotective, counteracting neuroinflammation, neuronal oxidation, and synaptic dysfunctions, which are crucial aspects of neurodegenerative disease intervention in various included conditions, such as Alzheimer’s and other dementias, depression, and neuropsychiatric disorders. In summary, they show that the use of these compounds is related to significant improvements in cognition, memory, disinhibition, irritability/lability, aberrant behavior, hallucinations, and mood disorders.
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(This article belongs to the Special Issue Plants and Plant-Based Foods for Metabolic Disease Prevention)
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Open AccessReview
Metabolomics Profiling and Advanced Methodologies for Wheat Stress Research
by
Zhen Liu, Jiahui You, Peiying Zhao, Xianlin Wang, Shufang Sun, Xizhen Wang, Shubo Gu and Qian Xu
Metabolites 2025, 15(2), 123; https://doi.org/10.3390/metabo15020123 - 13 Feb 2025
Abstract
Metabolomics is an omics technology that studies the types, quantities, and changes of endogenous metabolic substances in organisms affected by abiotic and biotic factors. Background/Objectives: Based on metabolomics, small molecule metabolites in biological organisms can be qualitatively and quantitatively analysed. This method analysis
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Metabolomics is an omics technology that studies the types, quantities, and changes of endogenous metabolic substances in organisms affected by abiotic and biotic factors. Background/Objectives: Based on metabolomics, small molecule metabolites in biological organisms can be qualitatively and quantitatively analysed. This method analysis directly correlates with biological phenotypes, facilitating the interpretation of life conditions. Wheat (Triticum aestivum L.) is one of the major food crops in the world, and its quality and yield play important roles in safeguarding food security. Methods: This review elaborated on the significance of metabolomics research techniques and methods in enhancing wheat resilience against biotic and abiotic stresses. Results: Metabolomics plays an important role in identifying the metabolites in wheat that respond to diverse stresses. The integrated examination of metabolomics with other omics disciplines provides new insights and approaches for exploring resistance genes, understanding the genetic basis of wheat metabolism, and revealing the mechanisms involved in stress responses. Conclusions: Emerging metabolomics research techniques to propose innovative avenues of research is important to enhance wheat resistance.
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(This article belongs to the Section Plant Metabolism)
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Open AccessArticle
Metabolomics Analysis Reveals Characteristic Functional Components in Pigeon Eggs
by
Rui Zhang, Lingling Chang, Xinyue Shen, Qingping Tang, Chunyu Mu, Shengyong Fu and Zhu Bu
Metabolites 2025, 15(2), 122; https://doi.org/10.3390/metabo15020122 - 12 Feb 2025
Abstract
We aimed to identify the characteristic functional components of pigeon eggs and the differences among pigeon, chicken, and quail eggs. We analyzed the metabolite profiles of three kinds of eggs using an untargeted metabolomics-based approach to better understand the differences in metabolites among
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We aimed to identify the characteristic functional components of pigeon eggs and the differences among pigeon, chicken, and quail eggs. We analyzed the metabolite profiles of three kinds of eggs using an untargeted metabolomics-based approach to better understand the differences in metabolites among pigeon, chicken, and quail eggs. Then, we quantitatively validated the differences in abundance of partial metabolites through a targeted metabolomics-based approach. A total of 692 metabolites were identified in the three types of eggs. A total of 263 significantly differentially abundant metabolites were found between pigeon eggs and chicken eggs, and 263 significantly differentially abundant metabolites were found between pigeon eggs and quail eggs. The metabolites that were significantly more abundant in pigeon eggs than in other eggs were mainly lipids, lipid-like molecules, nucleosides, nucleotides, and their analogues. We identified the eight metabolites that were significantly greater in abundance in pigeon eggs than in chicken eggs and quail eggs and quantitatively validated the differences in abundance of these metabolites. Our study demonstrates that there are more functional components in pigeon eggs than chicken eggs and quail eggs, especially for the prevention and treatment of various disordered glucose and lipid metabolism-related diseases. The discovery of these differentially abundant metabolites paves the way for further research on the unique nutritional functions of pigeon eggs and the further utilization of pigeon egg products.
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(This article belongs to the Section Food Metabolomics)
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Open AccessArticle
Multifluid Metabolomics Identifies Novel Biomarkers for Irritable Bowel Syndrome
by
Daniel Kirk, Panayiotis Louca, Ilias Attaye, Xinyuan Zhang, Kari E. Wong, Gregory A. Michelotti, Mario Falchi, Ana M. Valdes, Frances M. K. Williams and Cristina Menni
Metabolites 2025, 15(2), 121; https://doi.org/10.3390/metabo15020121 - 12 Feb 2025
Abstract
Background/Objectives: Irritable bowel syndrome (IBS) is a complex disorder affecting 10% of the global population, but the underlying mechanisms remain poorly understood. By integrating multifluid metabolomics, we aimed to identify metabolite markers of IBS in a large population-based cohort. Methods: We
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Background/Objectives: Irritable bowel syndrome (IBS) is a complex disorder affecting 10% of the global population, but the underlying mechanisms remain poorly understood. By integrating multifluid metabolomics, we aimed to identify metabolite markers of IBS in a large population-based cohort. Methods: We included individuals from TwinsUK with and without IBS, ascertained using the Rome III criteria, and analysed serum (232 cases, 1707 controls), urine (185 cases, 1341 controls), and stool (186 cases, 1284 controls) metabolites (Metabolon Inc.). Results: After adjusting for covariates, and multiple testing, 44 unique metabolites (25 novel) were associated with IBS, including lipids, amino acids, and xenobiotics. Androsterone sulphate, a sulfated steroid hormone precursor, was associated with lower odds of IBS in both urine (0.69 [95% confidence interval = 0.56–0.85], p = 2.34 × 10−4) and serum (0.75 [0.63–0.90], p = 1.54 × 10−3. Moreover, suberate (C8-DC) was associated with higher odds of IBS in serum (1.36 [1.15–1.61]; p = 1.84 × 10−4) and lower odds of IBS in stool (0.76 [0.63–0.91]; p = 2.30 × 10−3). On the contrary, 32 metabolites appeared to be fluid-specific, including indole, 13-HODE + 9-HODE, pterin, bilirubin (E,Z or Z,Z), and urolithin. The remaining 10 metabolites were associated with IBS in one fluid with suggestive evidence (p < 0.05) in another fluid. Finally, we identified androgenic signalling, dicarboxylates, haemoglobin, and porphyrin metabolism to be significantly over-represented in individuals with IBS compared to controls. Conclusions: Our results highlight the utility of a multi-fluid approach in IBS research, revealing distinct metabolic signatures across biofluids.
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(This article belongs to the Special Issue Advances in Metabolomics and Multi-Omics Integration)
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