Metabolomics最新文献

{"title":"Mass spectrometry-based characterisation of the cardiac microtissue metabolome and lipidome.","authors":"Tara J Bowen, Andrew R Hall, Andrew D Southam, Ossama Edbali, Ralf J M Weber, Amanda Wilson, Amy Pointon, Mark R Viant","doi":"10.1007/s11306-025-02252-0","DOIUrl":"https://doi.org/10.1007/s11306-025-02252-0","url":null,"abstract":"<p><strong>Introduction: </strong>The use of large, non-sample specific metabolite reference libraries often results in high proportions of false positive annotations in untargeted metabolomics.</p><p><strong>Objective: </strong>This study aimed to measure and curate a library of polar metabolites and lipids present in cardiac microtissues.</p><p><strong>Results: </strong>Untargeted ultra-high performance liquid chromatography-coupled mass spectrometry measurements of cardiac microtissue intracellular extracts were annotated by comparison against four spectral databases and a retention time library. The annotations were combined to create a library of 313 polar metabolites and 1004 lipids.</p><p><strong>Conclusions: </strong>The curated library will facilitate higher confidence metabolite annotation in mass spectrometry-based untargeted metabolomics of cardiac microtissues.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 3","pages":"54"},"PeriodicalIF":3.5,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12011886/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144034613","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":"The causal association between circulating metabolites and Alzheimer's disease: a systematic review and meta-analysis of Mendelian randomization studies.","authors":"Yuxuan Wu, Fangying Chen, Tingting Zhang, Mengrong Miao, Mengxin Zhang, Jiaqiang Zhang, Enqiang Chang","doi":"10.1007/s11306-025-02242-2","DOIUrl":"https://doi.org/10.1007/s11306-025-02242-2","url":null,"abstract":"<p><strong>Introduction/objective: </strong>Some Mendelian randomization (MR) studies have found that there may be a genetic causal relationship between circulating metabolites and Alzheimer 's disease (AD), but the strength of evidence and the direction of association are not always consistent. In this study, a systematic review and meta-analysis of all the literature using MR methods to study the causal relationship between metabolites and AD was conducted to enhance the robustness and correlation of predicting genetic causality.</p><p><strong>Methods: </strong>We conducted a comprehensive review of Mendelian randomization (MR) studies which are within the timeframe of all years to 20 December 2023. Circulating metabolites were considered as the exposure factor, and AD served as the outcome. Two researchers, each with relevant professional backgrounds, independently evaluated study quality and extracted data from the selected studies. Meta-analysis was carried out using R Studio version 4.3.1.</p><p><strong>Results: </strong>In total, 30 studies were included, with 13 selected for meta-analysis. The meta-analysis results revealed that genetically predicted high levels of some metabolites may be associated with a reduced risk of AD. (HDL-C: OR = 0.90, 95% CI 0.83-0.97, p = 0.004; Testosterone: OR = 0.93, 95% CI 0.90-0.97, p = 0.001; Male hormones _{exclude testosterone}: OR = 0.85, 95% CI 0.75-0.96, p = 0.007; Glutamine: OR = 0.85, 95% CI 0.81-0.89, p < 0.001) Meanwhile, genetically predicted high LDL-C levels are associated with an increased risk of AD. (LDL-C: OR = 1.52, 95% CI 1.15-2.00, p = 0.003). There is not enough evidence to prove that there is a genetic causal relationship between diabetes and AD. (OR = 1.02, 95% CI 1.00-1.03, p = 0.12).</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 3","pages":"53"},"PeriodicalIF":3.5,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12011960/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144033362","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 and morphometric analysis of allometric and total liver growth in Post-Hatch chickens.","authors":"Heidi Van Every, Carl J Schmidt","doi":"10.1007/s11306-025-02250-2","DOIUrl":"https://doi.org/10.1007/s11306-025-02250-2","url":null,"abstract":"<p><strong>Introduction: </strong>This study examines metabolic and morphometric changes in chicken liver metabolism during the post-hatch growth period (days 4-20). During this period, liver metabolism transitions from using yolk-derived lipids to feed derived carbohydrates and proteins. The period also encompasses distinct growth phases with implications for metabolic impacts on total and allometric (proportional) growth.</p><p><strong>Objectives: </strong>Identify shifts in metabolites and pathways that occur during the change in nutrients and relate these to patterns of total and allometric liver growth.</p><p><strong>Methods: </strong>Liver samples were collected every other day between days 4-20 and analyzed using metabolomic and morphometric approaches to relate metabolic changes to growth. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to identify trends in the data. Cross-validation ANOVA, and network analyses were applied to evaluate metabolic changes across the time periods.</p><p><strong>Results: </strong>Three liver growth periods were defined. Period A (days 4-8) exploited stored nutrients to support rapid growth. Period B (days 10-14) was transitional as stored nutrients were depleted and feed became the major metabolic driver. By period C (days 16-20) the liver is fully dependent on feed. Positive allometric growth occurs predominantly during period A while the organ continues to grow throughout the entire time.</p><p><strong>Conclusions: </strong>Metabolic pathways exhibit distinct networks as nutrient resources change over the early post-hatch period. These findings provide a framework for understanding how nutrient-driven metabolism influences liver scaling and functional maturation.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 3","pages":"52"},"PeriodicalIF":3.5,"publicationDate":"2025-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11993442/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144032873","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":"The 2025 Metabolomics publication awards.","authors":"Royston Goodacre","doi":"10.1007/s11306-025-02251-1","DOIUrl":"https://doi.org/10.1007/s11306-025-02251-1","url":null,"abstract":"","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 3","pages":"51"},"PeriodicalIF":3.5,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144027859","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":"SARS-CoV2 variants differentially impact on the plasma metabolome.","authors":"Tina Kramaric, Onn Shaun Thein, Dhruv Parekh, Aaron Scott, Andrine Vangberg, Manfred Beckmann, Helen Phillips, David Thickett, Luis A J Mur","doi":"10.1007/s11306-025-02238-y","DOIUrl":"10.1007/s11306-025-02238-y","url":null,"abstract":"<p><strong>Introduction: </strong>Infection with severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) leads to COVID19 disease and caused a worldwide pandemic in 2019. Since the first wave of infections, there has been significant antigenic shifts, leading to the emergence of new variants. Today, infections have shifted away from the severe, fatal infection seen in 2019.</p><p><strong>Objective: </strong>This study aimed to assess how the plasma metabolomes from patients varied with infection with different strains and could reflect disease severity.</p><p><strong>Methods: </strong>Patients with COVID19 not requiring intensive care were recruited between January 2021 and May 2022 from the Queen Elizabeth Hospital Birmingham; 33 patients with alpha, 13 delta and 14 omicron variants. These were compared to 26 age matched contemporaneously recruited controls. Plasma samples were extracted into chloroform/methanol/water (1:2.5/1 v/v) and assessed by flow injection electrospray mass spectrometry (FIE-MS) using an Exactive Orbitrap mass spectrometer. Derived data were assessed using the R based MetaboAnalyst platform.</p><p><strong>Results: </strong>Plasma metabolomes from COVID19 patients were clearly different from controls. Metabolite variation could be related to infection with different SARS-CoV2 variants. Variant showed different levels of some phospholipids, ganglioside GD1a and a dihydroxyvitamin D3 derivative. Correlations of the plasma metabolomes indicated negative correlations between selected phospholipids and the levels of C-reactive protein, creatinine, neutrophil and D-dimer.</p><p><strong>Conclusion: </strong>The plasma metabolomes of COVID19 patients show changes, particularly in phospholipids, which could reflect disease severity and SARS-CoV2 variant infection.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 2","pages":"50"},"PeriodicalIF":3.5,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11972186/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143788675","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":"Correction: Metabolomic heterogeneity of ageing with ethnic diversity: a step closer to healthy ageing.","authors":"Drupad Trivedi, Katherine A Hollywood, Yun Xu, Fredrick C W Wu, Drupad K Trivedi, Royston Goodacre","doi":"10.1007/s11306-025-02247-x","DOIUrl":"10.1007/s11306-025-02247-x","url":null,"abstract":"","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 2","pages":"48"},"PeriodicalIF":3.5,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11961457/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143753472","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":"A pilot study on hemodynamically stable isolated chest trauma patients reveals dysregulation of oxidative metabolism.","authors":"Arun Kumar Malaisamy, Ramesh Vaidyanathan, Anand Kumar, Narendra Choudhary, Pratyusha Priyadarshini, Dinesh Kumar Bagaria, Arulselvi Subramanian, Kapil Dev Soni, Abhinav Kumar, Neel Sarovar Bhavesh","doi":"10.1007/s11306-025-02241-3","DOIUrl":"10.1007/s11306-025-02241-3","url":null,"abstract":"<p><strong>Background: </strong>Metabolomic dysregulation precedes clinical deterioration following injury. However, despite receiving comparable treatment, patients with similar injury severity often follow different clinical trajectories and outcomes.</p><p><strong>Methods: </strong>This prospective cohort study at a level 1 trauma centre screened 4541 acutely injured patients with chest trauma between September 2019 and February 2023. Fifty hemodynamically stable patients with isolated chest trauma were recruited for the final analysis. Urine samples were collected on the injury days 1, 3, and 7. For healthy subjects, the urine sample was collected once. NMR-based metabolomics was performed.</p><p><strong>Results: </strong>The study found that the majority of injured patients were young (median age of 40 years), with road traffic injuries being the most common. The median time to presentation of the patient to the ED was 3.08 h, and 92% of patients had multiple rib fractures, pulmonary contusion (60%), and pleural involvement (88%). No patient died. The study found that twenty metabolites were dysregulated (p-value < 0.001). Twelve metabolites were upregulated, while the other eight showed downregulation. However, only five metabolites showed temporal association. 4-HPA, phenylalanine, aconitate, and carnitine represent a high potential for use as a biomarker in patients with isolated blunt trauma chest patients who remain hemodynamically stable. These differentially regulated metabolites were involved in Glyoxylate and dicarboxylate metabolism pathways, glycine, serine, and threonine metabolism, and the Citrate cycle (TCA cycle).</p><p><strong>Conclusions and relevance: </strong>Metabolomics can accurately characterize metabolism in isolated blunt chest trauma patients, revealing perturbed pathways of traits such as oxidative stress and amino acid metabolisms. These metabolites could serve as biomarkers to detect systemic changes following chest injuries early. Metabolic profiling following an injury can aid in detecting systemic changes early and identifying novel biomarkers, enabling targeted interventions to improve patient outcomes.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 2","pages":"49"},"PeriodicalIF":3.5,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143753414","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":"Progress and perspectives of metabolic biomarkers in blood sample for diabetic microvascular complications.","authors":"Li Yan, Xu Wang, Yujie Xiang, Shuyi Ru, Cheng Fang, Xiuhong Wu","doi":"10.1007/s11306-025-02245-z","DOIUrl":"10.1007/s11306-025-02245-z","url":null,"abstract":"<p><strong>Background: </strong>Diabetes mellitus refers to a group of metabolic diseases characterized by chronic hyperglycemia due to multiple etiological factors. As the disease progresses, patients gradually develop microvascular complications, including diabetic nephropathy, diabetic retinopathy, and diabetic neuropathy. However, current clinical methods for detecting these microvascular complications are limitations, thus primary prevention and early diagnosis are of great importance.</p><p><strong>Aim of review: </strong>This review summarizes the known blood biomarkers of diabetic microvascular complications, classified according to type of structure, including amino acid metabolism, lipid metabolism, carnitine metabolism, organic acid metabolism, etc., which can be used for the simultaneous typing of diabetes mellitus based on microvascular complications, and to search for the trend of changes to lay the foundation for early diagnosis and understanding of the pathogenesis of diabetic microvascular complications, including oxidative stress, and mitochondrial dysfunction. Searches for the trend of changes to lay the foundation for early diagnosis and understanding of the pathogenesis of diabetic microvascular complications, including oxidative stress, mitochondrial dysfunction.</p><p><strong>Key scientific concepts of review: </strong>Due to the limitations of diagnostic criteria for diabetic microvascular complications, some patients already have the disease for which they are being tested. Metabolomics reflects the physiological state of an organism by analyzing the small molecules metabolites present in a biological tissue that are related to clinical phenotypes, providing a snapshot of the physiological and pathophysiological metabolic processes occurring within that organism at any given time, thus opening the door for the development of diagnostic biomarkers and precise treatment. In clinical metabolomics, blood is considered a specialized type of connective tissue, which allows it to transport substances throughout the body, connecting different systems together. Also, blood components are probably the most frequently used matrix in metabolomics studies. Therefore, metabolomics is used to analyze blood biomarkers that reflect the course of diabetes and explore the pathways involved in the pathophysiology of the three most common diabetic microvascular complications. Finally, in this review, we discuss the current limitations of metabolomic analysis, and the integrative multi-omics data, including genomics, transcriptomics, and proteomics, required for developing specific biomarkers for diabetic microvascular complications.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 2","pages":"47"},"PeriodicalIF":3.5,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143753479","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":"Loss-of-functional mutation in ANGUSTIFOLIA3 causes leucine hypersensitivity and hypoxia response during Arabidopsis thaliana seedling growth.","authors":"Kensuke Kawade, Mamoru Nozaki, Gorou Horiguchi, Tomoko Mori, Katsushi Yamaguchi, Mami Okamoto, Hiromitsu Tabeta, Shuji Shigenobu, Masami Yokota Hirai, Hirokazu Tsukaya","doi":"10.1007/s11306-025-02249-9","DOIUrl":"10.1007/s11306-025-02249-9","url":null,"abstract":"<p><strong>Introduction: </strong>The ANGUSTIFOLIA3 (AN3) gene encodes a transcriptional co-activator for cell proliferation in Arabidopsis thaliana leaves. We previously showed that Physcomitrium patens AN3 orthologs promote gametophore shoot formation through arginine metabolism.</p><p><strong>Objectives: </strong>We analyzed the role of AN3 in Arabidopsis thaliana to understand how seedling growth is regulated by metabolic and physiological modulations.</p><p><strong>Methods: </strong>We first explored amino acids that affect the seedling growth of an3 mutants. Transcriptome and metabolome analyses were conducted to elucidate the metabolic and physiological roles of AN3 during seedling growth. Lastly, we examined the distribution of reactive oxygen species to corroborate our omics-based findings.</p><p><strong>Results: </strong>Our results indicated that an3 mutants were unable to establish seedlings when grown with leucine, but not arginine. Multi-omics analyses suggested that an3 mutants exhibit a hypoxia-like response. Abnormal oxidative status was confirmed by detecting an altered distribution of reactive oxygen species in the roots of an3 mutants.</p><p><strong>Conclusion: </strong>AN3 helps maintain the leucine metabolism and oxidative balance during seedling growth in Arabidopsis thaliana. Future research is necessary to explore the interaction between these processes.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 2","pages":"46"},"PeriodicalIF":3.5,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11958482/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143753476","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 the relationship between serum 25-hydroxyvitamin D levels and intestinal fungal communities and their metabolites in postmenopausal Chinese women.","authors":"Han Zhang, Jinhua Gong, Kunpeng Xu, Zixian Dang, Zhen Shang, Guanhong Chen, Haotian Feng, Yuying Zhang, Yingze Zhang, Tengbo Yu, Jianquan He, Wenxin Hong, Yongtao Zhang","doi":"10.1007/s11306-025-02244-0","DOIUrl":"10.1007/s11306-025-02244-0","url":null,"abstract":"<p><strong>Background: </strong>Research gaps persist in understanding the interactions between serum 25 (OH)D levels, intestinal fungi, and their metabolites in postmenopausal women.</p><p><strong>Methods: </strong>This study, approved by the Ethics Committee of Zhongshan Hospital, Xiamen University, recruited postmenopausal women from Xiamen. Clinical assessments included Body Mass Index (BMI) calculations and blood tests for various bone-related markers using Roche's electrochemiluminescence system. Bone density was measured via dual-energy X-ray absorptiometry. Fecal DNA was extracted for Internal Transcribed Spacer (ITS) sequencing with a two-stage PCR process and analyzed using high-throughput Illumina sequencing. Metabolites were extracted from fecal samples and analyzed by ultra-high-performance liquid chromatography combined with mass spectrometry. Statistical analyses and data visualization were performed using R, focusing on fungal community structure and correlations with metabolites.</p><p><strong>Results: </strong>The study analyzed 81 postmenopausal women, categorized into vitamin D deficient (VDD), insufficient (VDI), and sufficient (VDS) groups based on serum 25 (OH)D levels. Other health markers, including age and BMI, were consistent across groups. Notably, Linear discriminant analysis identified distinct fungal communities across VDD, VDI, and VDS groups. In the VDD group, notable fungi included Hanseniaspora occidentalis and Pichia. The VDI group showed enrichment of Candida, while the VDS group had higher abundances Such as Phanerochaete, and Nectriaceae. Alpha diversity metrics, such as the Chao1 index, differed significantly among the groups (p < 0.05). Correlation analysis (Spearman) revealed that fungi like Trichosporon and Penicillium positively associated with 25 (OH)D3, whereas fungi such as Cystofilobasidium were negatively correlated with bone mineral density (BMD). Metabolites like Glutaric acid positively correlated with 25 (OH)D3, while L-Citrulline and Deoxycholic acid were negatively correlated. Additionally, Argininosuccinic acid correlated positively with BMD, whereas Acamprosate and p-Hydroxyphenylacetic acid were negatively associated.</p><p><strong>Conclusion: </strong>In postmenopausal women, fungal community composition varies significantly with vitamin D status, potentially correlating with serum 25 (OH)D levels and BMD, indicating that specific fungal species may be relevant for therapeutic strategies with osteoporosis and offering insights into the broader bone health effects of vitamin D.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 2","pages":"45"},"PeriodicalIF":3.5,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143720225","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}