Metabolomics最新文献

{"title":"The MassBank contributions of the mFam collaboration.","authors":"Anusha Ahlendorf, Asaph Aharoni, Khabat Vahabi, Tillmann G Fischer, Pierre-Marie Allard, Megan Augustin, Ulschan Bathe, David I Broadhurst, Corey Broeckling, Joerg Buescher, Adrian Covaci, Katyeny Manuela da Silva, Ric C H de Vos, Micha Gracianna Devi, Stefanie Döll, Maximilian Frey, Andrej Frolov, Emmanuel Gaquerel, Vasuk Gautam, Esteban Charria-Girón, Alain Goossens, Jeremy Grosjean, Maria Halabalaki, Elias Iturrospe, Kim Kultima, Stephanie Herman, Toni M Kutchan, Romain Larbat, René Meier, Eleni V Mikropoulou, Gregory Mouille, Luca Nicolotti, Nir Shahaf, François Perreau, Pierre Pétriacq, Michael Reichelt, Stacey N Reinke, Rani Robeyns, Alena Soboleva, Otmar Spring, Akshai Parakkal Sreenivasan, Alain Tissier, Jean Chrisologue Totozafy, Hiroshi Tsugawa, Josep Valls-Fonayet, Maria van de Lavoir, Justin J J van der Hooft, Fredd Vergara, David Wishart, Ludger A Wessjohann, Jean-Luc Wolfender, Jörg Ziegler, Gerd Ulrich Balcke, Steffen Neumann","doi":"10.1007/s11306-026-02480-y","DOIUrl":"10.1007/s11306-026-02480-y","url":null,"abstract":"<p><strong>Introduction: </strong>The analysis of metabolic profiles using high resolution mass spectrometry (MS) data provides deep insights into biological processes. In metabolomics, MS analysis generates a large number of features that represent metabolites. However, identifying specific metabolites from these features can be challenging. One of the major bottlenecks in the metabolomics field is the identification of MS features, which is a prerequisite for any biochemical interpretation. By identifying similarities and differences within a metabolite family (mFam), evaluating MS features at the metabolite family level can help assigning functional roles to individual MS features. These data can help interpreting metabolic pathways and processes within a biological system. For the assignment of metabolite families to MS features, it is important to have good quality, reliable, and comprehensive spectral libraries.</p><p><strong>Objective: </strong>We initiated a global effort to collect high-resolution MS/MS spectra of metabolites from labs working in different fields, including metabolomics of animals, microorganisms, and plants. The mFam-MS/MS collection delivers valuable training data to assign machine-readable classified information on the unknown metabolites.</p><p><strong>Results: </strong>The mFam collaboration used a standardized metadata template and has developed a globally curated MS/MS spectral library of 7,872 spectra with 2,126 unique metabolites. This library was compiled from 47 datasets contributed by 25 laboratories measured on 12 instrument types, including QTOF, Orbitrap, and Ion Mobility-QTOF systems. It comprises 4,646 spectra in positive mode and 3,226 in negative mode. This standardized resource significantly enhances metabolite identification capabilities, supports the development of machine learning-based annotation tools, and accelerates the discovery of novel metabolites. All spectra are available under the collective contributor label mFam in the MassBank system, including the web interface and the 2025.10 data release available at GitHub and Zenodo.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"22 4","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13328316/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148369111","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":"Secondary metabolite profiling of rare Micromonospora spp. from cold desert of NW Himalayas via multi-omics analysis.","authors":"Neha Sharma, Devtulya Chander, Nawaz Hussain, Asha Chaubey","doi":"10.1007/s11306-026-02468-8","DOIUrl":"10.1007/s11306-026-02468-8","url":null,"abstract":"<p><strong>Introduction: </strong>The genus Micromonospora is a prolific producer of specialized metabolites with pharmacological and agronomic relevance. Natural products derived from the genus Micromonospora have a distinctive chemical diversity and enormous therapeutic potential, thus represent a potential source for drugs and drug leads.</p><p><strong>Objective: </strong>To explore the biosynthetic potential of four Micromonospora strains isolated from cold desert of NW Himalayas through genome mining and to correlate predicted biosynthetic gene clusters with chemical features detected by untargeted LC-HRMS metabolomics.</p><p><strong>Method: </strong>High-quality genomes were annotated for BGCs and matched against untargeted LC-HRMS features (peak picking, alignment, and annotation to chemical classes). Each isolate was grown in triplicate, and fermented broth was pooled for further metabolomic studies.</p><p><strong>Results: </strong>By integrating genomic and metabolomic approaches, specialized biosynthetic gene clusters and strain-based putative metabolite classes were identified. LRS1 showed elevated xanthines (RiPP/siderophore), LRS3 had phenolic glycosides (hybrid PKS/NRPS), LRS4 showed 70-fold hydroxycinnamate enrichment (Type II PKS), and LRS5 displayed p-benzoquinone enrichment (Type III PKS). The metabolite profile of each strain aligned with its predicted biosynthetic gene cluster composition.</p><p><strong>Conclusion: </strong>Under a single growth regime, each Micromonospora strain exhibits a distinct metabolomic profile. This metabologenomics workflow can be further explored to isolate specialized metabolites with potential therapeutic and agricultural value.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"22 4","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13323859/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148361411","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":"Fecal metabolome alterations in infants at risk of developing allergies during the first year of life.","authors":"Mariyana V Savova, Pingping Zhu, Alida Kindt, Harm Wopereis, Clara Belzer, Amy C Harms, Thomas Hankemeier","doi":"10.1007/s11306-026-02478-6","DOIUrl":"10.1007/s11306-026-02478-6","url":null,"abstract":"<p><strong>Introduction: </strong>Disturbances in the infant gut microbiome (GM) may increase the risk of developing allergies. This critical developmental period is characterized by rapid microbial colonization, which is influenced by factors like delivery mode and infant feeding practices.</p><p><strong>Objectives: </strong>The present study investigated changes in key GM taxa and fecal metabolites in relation to allergy development, delivery mode, age, and infant feeding practices during the first year of life.</p><p><strong>Methods: </strong>Seventy-two infants at risk of allergies, exclusively breastfed for at least 16 weeks, were followed in their first year. During this period, allergy manifestations were recorded and fecal samples collected at three time points. The samples were subjected to metabolic profiling covering host and microbial metabolites and fluorescent in situ hybridization to quantify Bifidobacterium spp. and the Eubacterium rectale/Clostridium coccoides group.</p><p><strong>Results: </strong>Strong age-associated metabolic shifts were observed, particularly in aromatic amino acid metabolites, bile acids, B vitamins, and short and long-chain fatty acids. Feeding practices, specifically the introduction of complementary feeding and the cessation of breastfeeding were significantly associated with changes to the fecal metabolome. Delivery mode had a pronounced impact on the metabolome, with differences between vaginal and Cesarean deliveries persisting until 6 months of age. Infants who developed an allergy during this period had lower Bifidobacterium spp. and significantly higher polyunsaturated fatty acid levels before the age of 16 weeks.</p><p><strong>Conclusion: </strong>This study offers valuable insights into the longitudinal development of the fecal metabolome and factors influencing it during infancy, a critical period for immune system development.</p><p><strong>Clinical trial registration: </strong>Clinicaltrials.gov identifier: NCT03067714, registered: 01/02/2017.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"22 4","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13323787/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148361342","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":"Characterizing the effect of short wavelengths on the floral flavonoid metabolome of medicinal cannabis using a comparative computational metabolomics workflow.","authors":"Willy Contreras-Avilés, Laura Rosina Torres-Ortega, Ep Heuvelink, Leo F M Marcelis, Justin J J van der Hooft, Iris F Kappers","doi":"10.1007/s11306-026-02500-x","DOIUrl":"10.1007/s11306-026-02500-x","url":null,"abstract":"<p><strong>Background: </strong>Controlled-environment cultivation of medicinal cannabis (Cannabis sativa L.) typically optimizes light conditions to enhance the biosynthesis of pharmaceutically important metabolites like cannabinoids. Such experimental strategies may also influence other specialized metabolites like terpenoids, flavonoids, alkaloids, among others. Previous untargeted metabolomics studies testing short-wavelength conditions like UV and blue light have shown that terpenoids and prenylated flavonoids in cannabis leaves respond differentially. However, since metabolomic studies in cannabis have so far mostly focused on floral cannabinoids, a comprehensive untargeted study into cannabis' floral metabolome response to short wavelengths is currently lacking.</p><p><strong>Objectives: </strong>Our study investigates the impact of short-wavelength usage on cannabis specialized metabolism, and in particular the influence of UVB, UVA, and blue light on the cannabis floral flavonoid metabolome and associated glycosylation moieties.</p><p><strong>Methods: </strong>Cannabis plants were grown under a white background light and exposed to supplemental UVB, UVA, or blue light during the generative phase of the cultivation cycle. Treatments were compared to a reference white background light without UV or blue light. Metabolites from floral tissue were extracted and analysed via ultra-performance liquid chromatography-tandem mass spectrometry. A comparative metabolomics workflow was designed and used to characterize the floral flavonoid metabolome and associated glycosylation moieties.</p><p><strong>Results: </strong>Our results demonstrate how short wavelengths differentially affect the metabolism of natural product compound classes including polyketides and phenylpropanoids/shikimates. Blue light induced flavonoids similarly to how UVB did, while both UVA and blue light specifically induced flavanones accumulation. UVB showed the strongest regulatory effect on flavonoids production and glycosylation patterns.</p><p><strong>Conclusions: </strong>UVB reshapes the cannabis floral flavonoid metabolome by selectively stimulating the accumulation and structural modification of flavonoids. Therefore, UVB represents a potential horticultural strategy to enhance flavonoid-related aspects of medicinal cannabis inflorescence phytochemical quality, without affecting cannabinoid levels.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"22 4","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13323782/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148369083","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":"Lipid reprogramming of stratified squamous epithelium by the high-risk HPV E6 and E6/E7 oncoproteins.","authors":"Megan E Spurgeon, Taylor E Lange, Alexandra Baty, Helena Li, Paul F Lambert, Kenneth D R Setchell, Susanne I Wells, Xueheng Zhao","doi":"10.1007/s11306-026-02498-2","DOIUrl":"10.1007/s11306-026-02498-2","url":null,"abstract":"<p><strong>Introduction: </strong>High risk human papillomavirus (HPV) infection and genome integration with pronounced expression of the viral E6/E7 oncogenes is the major cause of cervical cancer. Emerging evidence suggests that HPV reprograms host metabolism to support viral persistence and cellular transformation. However, global HPV oncogene-induced lipidomic reprogramming remains poorly understood, particularly at early stages of HPV-induced transformation.</p><p><strong>Objective: </strong>We sought to define the regulation of lipid metabolism in squamous epithelia of transgenic mice expressing the HPV16 oncogene E6 alone or in conjunction with E7.</p><p><strong>Methods: </strong>Untargeted lipidomics was used to identify novel lipid biomarkers in the skin and female reproductive tract (FRT) of HPV16 E6 and E6/E7 transgenic compared to wild-type (WT) mice. To investigate enzymatic dysregulation of lipids by HPV oncogene expression, we employed Lipid Network Explorer (LINEX²), which analyzes lipidomics data through lipid enrichment analysis. We also used the Global Natural Product Social Molecular Networking (GNPS) platform to enhance lipid identification, exploring molecular networking to improve feature annotation.</p><p><strong>Results: </strong>Our lipidomic analysis produced several new observations. First, E6 expression caused a consistent alteration of glycerophospholipids, with particularly significant substrate-product shifts in the phosphatidylcholine (PC) to lysophosphatidylcholine (LPC) pathway in the skin. Second, E6/E7 expression caused a dysregulation of glucosylceramide (GlcCer) biosynthesis. Third, both E6/E7 expressing skin and FRT tissues exhibited a redox imbalance and increased levels of oxidized lipids, including oxylipins and several oxidized PCs. These findings suggest that HPV oncoproteins drive lipid reprogramming, potentially contributing to early HPV-related tumorigenesis.</p><p><strong>Conclusions: </strong>These findings provide new insights into HPV‑induced lipid reprogramming and establish a framework for future studies examining the functional and clinical relevance of lipid alterations in HPV‑associated cancers.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"22 4","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13323514/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148361359","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":"Serum metabolomic signatures integrating sphingosine-1-phosphate and tetrahydrocortisone improve prognostic assessment in non-ischemic cardiomyopathy.","authors":"Fanglu Wang, Benchen Ye, Ligang Fang, Wei Chen, Ning-Yi Shao, Xiaowei Yan, Xue Lin","doi":"10.1007/s11306-026-02497-3","DOIUrl":"10.1007/s11306-026-02497-3","url":null,"abstract":"<p><strong>Introduction: </strong>Dilated cardiomyopathy (DCM) and left ventricular non-compaction (LVNC) are major non-ischemic cardiomyopathy (NICM) subtypes with heterogeneous outcomes. Conventional clinical and echocardiographic markers remain insufficient for long-term risk stratification.</p><p><strong>Objectives: </strong>This study aimed to identify serum metabolites associated with adverse cardiovascular outcomes and evaluate their incremental prognostic value in NICM.</p><p><strong>Methods: </strong>Thirty-two patients with DCM or LVNC and left ventricular ejection fraction < 50% were enrolled and followed for a median of 45.5 months. The primary endpoint was a composite of cardiovascular death, heart failure-related hospitalization, or clinically indicated cardiovascular device implantation. Baseline serum samples underwent liquid chromatography-mass spectrometry-based untargeted metabolomic profiling. Differential metabolites were identified using OPLS-DA and KEGG enrichment analysis. Prognostic metabolites were screened using Cox regression, Kaplan-Meier analysis, correlation filtering, and ROC analysis. An integrated Cox model combining clinical and metabolic markers was evaluated using bootstrapping, calibration, and time-dependent ROC analysis.</p><p><strong>Results: </strong>A total of 299 differential metabolites were identified and enriched in bile secretion, steroid hormone biosynthesis, and neuroactive ligand-receptor interaction pathways. Sphingosine-1-phosphate (S1P) and tetrahydrocortisone (THE) were selected as final prognostic metabolite biomarkers, with ROC AUCs of 0.777 and 0.793, respectively. The integrated model incorporating S1P, THE, tricuspid annular plane systolic excursion, and total protein achieved a bootstrap-corrected C-index of 0.772, with time-dependent AUCs of 0.92 and 0.86 at 3 and 5 years.</p><p><strong>Conclusions: </strong>Serum metabolomics may provide complementary prognostic information in NICM. S1P and THE are exploratory biomarkers linked to remodeling and stress, supporting risk stratification in NICM with reduced ejection fraction.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"22 4","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13323191/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148361338","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":"Characterization of three new antiproliferative shikimic acid derivatives and known pyrrolizidine alkaloids from Senecio oleosus guided by diagnostic ions and molecular networking.","authors":"Nathália da Silva Malaco, Anderson Valdiney Gomes Ramos, Bruno Toschi Valeze, Bianca Del Bianco Sahm, Marta Regina Barrotto do Carmo, Letícia Veras Costa-Lotufo, Maria Helena Sarragiotto, Debora Cristina Baldoqui","doi":"10.1007/s11306-026-02492-8","DOIUrl":"10.1007/s11306-026-02492-8","url":null,"abstract":"<p><strong>Introduction: </strong>The genus Senecio comprises more than 1,200 species, at least 25 of which are known to be toxic due to the presence of pyrrolizidine alkaloids. In Brazil, approximately 68 species occur, predominantly in rural and mountainous regions.</p><p><strong>Objective: </strong>This study was performed to investigate the specialized metabolites of Senecio oleosus using isolation and dereplication strategies and to evaluate their antiproliferative activity against tumor cell lines.</p><p><strong>Methods: </strong>A phytochemical investigation of S. oleosus was conducted using various chromatographic techniques. Structural elucidation was based on spectroscopic analyses and comparison with literature data. Dereplication was performed using UHPLC-HRMS/MS. Molecular networking was generated through GNPS2 and analyzed using Cytoscape. Antiproliferative activity was assessed using the MTT assay.</p><p><strong>Results: </strong>The study led to the isolation of three new esterified shikimic acid derivatives. Dereplication of pyrrolizidine alkaloids was guided by the diagnostic fragment ions at m/z 120 and m/z 138. Diagnostic ions for esterified shikimic acid derivatives were established based on the fragmentation patterns observed in the MS/MS spectra of the isolated compounds. Molecular networking analysis enabled the annotation of 36 additional putative esterified shikimic acid derivatives. One triesterified shikimic acid derivative exhibited promising antiproliferative activity against the HCT-116 cell line, with an IC₅₀ value of 10.5 µg.mL^- 1 (20.2 µM).</p><p><strong>Conclusions: </strong>In total, 82 compounds were identified in S. oleosus. Except for N-oxide retrorsine and N-oxide senecionine, all compounds are reported for the first time in this species. Esterified shikimic acid derivatives emerged as the major group of specialized metabolites in S. oleosus, and triesterified derivatives demonstrated promising antiproliferative activity.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"22 4","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13323267/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148361403","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":"Urinary volatile organic compounds as potential non-invasive markers for childhood obesity.","authors":"Adebowale Samuel Oyerinde, Jeremy Carson, Mallory Gibson, JackQuoia Baulding, Melissa Boersma, Robert A Oster, Jeganathan Ramesh Babu, Thangiah Geetha","doi":"10.1007/s11306-026-02494-6","DOIUrl":"10.1007/s11306-026-02494-6","url":null,"abstract":"<p><strong>Background: </strong>Childhood obesity is a complex disease and adversely affects multiple organ systems and increases the risk for several health problems, including diabetes, cancer, atherosclerosis, and premature cardiovascular disease in adulthood. This study aimed to identify differences in volatile organic compounds (VOCs) between normal weight (NW) and overweight/obese (OW/OB) children, as well as between European American and African American children.</p><p><strong>Methods: </strong>A total of 159 children participated in this cross-sectional study. Urine samples were analyzed using solid-phase microextraction gas chromatography-mass spectrometry (SPME-GC-MS) following glucuronidase and sulfatase treatment to capture a broad range of urinary volatiles with diverse physicochemical properties. Multiple linear regression was used to examine associations between urinary VOCs and BMI z-scores, and to identify VOCs that differentiated NW from OW/OB children.</p><p><strong>Results: </strong>Sixty-five VOCs were identified as differing between NW and OW/OB children, with ten remaining significant predictors of obesity after adjusting for race and socioeconomic status. These compounds exhibited area under the curve values ranging from 0.503 and 0.737, with sensitivity and specificity above 0.60.</p><p><strong>Conclusions: </strong>Key VOCs, including benzaldehyde, furan, hexanal, 4-heptanone and 2-pentylfuran, were positively associated with BMI z-score and may contribute to the low-grade chronic inflammation characteristic of obesity. These findings highlight the potential of urinary VOCs as non-invasive biomarkers for childhood obesity.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"22 4","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13323280/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148361420","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":"Association of handgrip strength with the plasma metabolomic profile: secondary analysis of a protein intervention study.","authors":"Tilde Martinsen, Janine Wirth, Lorraine Brennan","doi":"10.1007/s11306-026-02496-4","DOIUrl":"10.1007/s11306-026-02496-4","url":null,"abstract":"<p><strong>Introduction: </strong>There is interest in the potential impact of increased protein intake on muscle function in older adults. However, there is paucity of information on effects of different protein types.</p><p><strong>Objectives: </strong>To determine the impact of protein sources (plant vs dairy) on the plasma metabolomic profile, and to explore associations between metabolites and handgrip strength.</p><p><strong>Methods: </strong>In this secondary analysis of a 12-week double-blinded RCT, 171 healthy adults (≥50 years) were assigned to high plant protein (23 g/d), high dairy protein (22 g/d) or low protein (2 g/d) supplement. Plasma samples were collected pre- and post-intervention and analysed using a targeted LC-MS platform. Main and interaction effects were estimated using ANOVA-simultaneous component analysis (ASCA). Spearman correlation analysis evaluated associations between metabolites and handgrip strength, with false discovery rate correction (q < 0.05).</p><p><strong>Results: </strong>ASCA revealed no significant main effect of group (p = 0.23) or group × time interaction (p = 1.00), while time had a significant effect on the metabolomic profile (p < 0.05). After FDR correction, 26 metabolites were significantly correlated with baseline handgrip strength. The strongest positive correlations were observed for creatinine (r = 0.53), leucine (r = 0.38), proline (r = 0.35) and isoleucine (r = 0.33). Baseline levels of leucine, isoleucine, PCaeC322 and SMOHC222 were associated with positive changes in handgrip strength (p < 0.05).</p><p><strong>Conclusions: </strong>Metabolomic changes were not related to protein type. However, metabolite levels were correlated with handgrip strength outcomes, suggesting the necessity to evaluate the metabolic state of individuals prior to interventions.</p><p><strong>Trial registration: </strong>This study is registered on isrctn.com as ISRCTN16651067.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"22 4","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13319504/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148352566","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":"Next-generation newborn screening: feasibility of combined genetic and biochemical testing for 95 treatable inherited metabolic disorders.","authors":"Abigail Veldman, C Edel Arar, M B Gea Kiewiet, Els Voorhoeve, Martijn E T Dollé, Monique de Sain-van der Velden, Rose E Maase, Francjan J van Spronsen, Birgit Sikkema-Raddatz, M Rebecca Heiner-Fokkema","doi":"10.1007/s11306-026-02486-6","DOIUrl":"10.1007/s11306-026-02486-6","url":null,"abstract":"<p><strong>Introduction: </strong>Next-generation sequencing (NGS) is gaining attention in newborn screening (NBS) for its ability to detect treatable genetic disorders, especially those without a biochemical footprint. However, NGS-NBS requires interpreting variants without phenotype information or family trio analysis. Biochemical tests, preferably in dried blood spots (DBS), are therefore useful to confirm the pathogenicity of variants identified by NGS-NBS and increase its specificity and sensitivity.</p><p><strong>Objectives: </strong>We aimed to explore the potential of combined genetic-biochemical testing for 95 treatable Inherited Metabolic Disorders (IMD) considered eligible for NGS-NBS (100 genes) previously identified by our research group.</p><p><strong>Methods: </strong>We reviewed the Collaborative Laboratory Integrated Reports (CLIR) and carried out systematic literature reviews in PubMed and Embase to identify biochemical tests for 95 IMD. Biochemical tests conducted on DBS were differentiated from tests that require referral.</p><p><strong>Results: </strong>We identified DBS-biochemical tests for 72 of the 95 IMD (77/100 genes). DBS-based biochemical tests for 55 IMD (60 genes) are already implemented in NBS. For the other 23 IMD, biochemical tests in non-DBS specimens are reported, although some are less sensitive when measured at neonatal age in presymptomatic infants.</p><p><strong>Conclusion: </strong>We present a comprehensive overview of current biochemical tests for 95 IMD. These tests can be used to confirm inconclusive NGS-NBS results, and combined genetic-biochemical testing is expected to improve both the negative and positive predictive values of NBS programs.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"22 4","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13303320/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148318243","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}