PubMed

Cancer Commun (Lond). 2024 Dec 2. doi: 10.1002/cac2.12633. Online ahead of print.ABSTRACTBACKGROUND: Recurrence and metastasis remain significant challenges in lung adenocarcinoma (LUAD) after radical resection. The mechanisms behind the recurrence and metastasis of LUAD remain elusive, and deregulated cellular metabolism is suspected to play a significant role. This study explores the metabolic and epigenetic regulation mediated by nicotinamide N-methyl transferase (NNMT) in LUAD.METHODS: Untargeted metabolomic analyses were performed to detect metabolism irregularities. Single-cell RNA sequencing (RNA-seq) databases and multiplex immunofluorescence analysis were used to identify the location of NNMT within the tumor microenvironment. The biological functions of NNMT were investigated both in vitro and in vivo, with RNA-seq and chromatin immunoprecipitation-PCR providing insights into underlying mechanisms. Finally, single-cell RNA-seq data and immunohistochemistry of primary tumors were analyzed to validate the main findings.RESULTS: Untargeted metabolomic analyses revealed metabolic aberrations in amino acids, organic acids, lipids, and nicotinamide pathways, which are linked to metastasis of non-small cell lung cancer. NNMT is a key enzyme in nicotinamide metabolism, and we found the bulk tissue mRNA level of NNMT gene was inversely associated with LUAD metastasis. NNMT was proved to be predominantly expressed in cancer-associated fibroblasts (CAFs) within the stromal regions of LUAD, and a low stromal NNMT expression was identified as a predictor of poor disease-free survival following radical resection of LUAD. The isolation and primary culture of CAFs from LUAD enabled in vitro and in vivo experiments, which confirmed that NNMT negatively regulated the metastasis-promoting properties of CAFs in LUAD. Mechanistically, the downregulation of NNMT led to an increase in intracellular methyl groups by reducing the activity of the methionine cycle, resulting in heightened methylation at H3K4me3. This alteration triggered the upregulation of genes involved in extracellular matrix remodeling in CAFs, including those encoding collagens, integrins, laminins, and matrix metalloproteinases, thereby facilitating cancer cell invasion and metastasis. Reanalysis of single-cell RNA-seq data and immunohistochemistry assays of primary LUAD tissues substantiated NNMT's negative regulation of these genes in CAFs.CONCLUSIONS: This study provides novel insights into the metabolic and epigenetic regulatory functions of NNMT in CAFs, expanding the current understanding of LUAD metastasis regulation and suggesting potential avenues for future research and therapeutic development.PMID:39623600 | DOI:10.1002/cac2.12633

Zhonghua Gan Zang Bing Za Zhi. 2024 Nov 20;32(11):1053-1056. doi: 10.3760/cma.j.cn501113-20240223-00088.ABSTRACTThe activation of hepatic stellate cells (HSCs) and excessive deposition of extracellular matrix are the keys to the occurrence and development of liver fibrosis. Metabolic reprogramming supports the activation process of HSCs, which requires substantial energy to meet the corresponding energy requirements for liver fibrosis formation. This review focuses on the effect of metabolomic changes characterized by metabolic reprogramming on HSC activation and summarizes the characteristics of HSC energy metabolism reprogramming during the formation of liver fibrosis, with the aim to summarize research evidence for exploring the mechanism and developing strategies for the prevention and treatment of liver fibrosis.PMID:39623584 | DOI:10.3760/cma.j.cn501113-20240223-00088

Hum Vaccin Immunother. 2024 Dec 31;20(1):2430087. doi: 10.1080/21645515.2024.2430087. Epub 2024 Dec 2.ABSTRACTSome patients may develop adverse events during neoadjuvant chemoradiotherapy combined with immunotherapy, influencing response rates. The roles of intestinal microbiome and its metabolites in therapeutic adverse events remain unclear. We collected baseline fecal samples from 21 patients with adverse events (AE group) and 11 patients without adverse events (Non-AE group). Their microbiota and metabolome were characterized using metagenomic shotgun sequencing and untargeted metabolomics. At the species level, the gut microbiota in the Non-AE group exhibits significantly higher abundance of Clostridium sp. Alistipes sp. and lower abundance of Lachnoclostridium sp. Weissella cibaria, Weissella confusa, compared to the AE group (p < .05). A total of 58 discriminative metabolites were identified between groups. Beta-alanine metabolism was scattered. Boc-beta-cyano-L-alanine and CoQ9 were significantly increased in patients without adverse events, while linoleic acid increased in patients with adverse events. The increased Alistipes sp. in the Non-AE group was positively correlated with Boc-beta-cyano-L-alanine and negatively correlated with linoleic acid (p < .05). We constructed a combined microbiome-metabolite model to distinguish Non-AE and AE patients with an AUC of 0.963 via the random forest algorithm. Our findings provided a novel insight into the interplay of multispecies microbial cluster and metabolites of rectal patients with adverse events in neoadjuvant chemoradiotherapy combined with immunotherapy. These microbiota and metabolites deserve further investigations to reveal their roles in adverse events, providing clues for better treatment scenarios.Trial registration number: ClinicalTrials.gov identifier: NCT05368051.PMID:39623529 | DOI:10.1080/21645515.2024.2430087

Mass Spectrom Rev. 2024 Dec 2. doi: 10.1002/mas.21917. Online ahead of print.ABSTRACTA large part of the Human chemical exposome is now well characterized, and its health effects has been widely documented, although precise causal links remain difficult to establish. In parallel, genetic factors only were shown to contribute less than 30% to various pathologies. Therefore, environmental factors may represent the predominant cause of chronic diseases. Mass Spectrometry has been established for many years as a main "gold standard" in this field due to its performances both in sensitivity and selectivity. However, some unstable or highly reactive compounds may escape their detection in the biological samples because of their short half-life although some of their stable metabolites, if any, can be used for the exposure assessment. These electrophilic molecules are known to bind covalently to nucleophilic molecules in the body to form what are commonly called adducts. The study of adducts formed with DNA, proteins or with glutathione, nowadays called adductomics, can provide additional toxicologically relevant information in biomonitoring studies. This review describes this particular part of the reactive exposome and the related mass spectrometric methods developed therein. Three dedicated parts of this review are devoted to the contribution of mass spectrometry respectively to the assessment of DNA modifications, protein modifications, and reaction with glutathione.PMID:39623480 | DOI:10.1002/mas.21917

Allergy Asthma Immunol Res. 2024 Nov;16(6):668-681. doi: 10.4168/aair.2024.16.6.668.ABSTRACTPURPOSE: Atopic dermatitis (AD) is a chronic inflammatory skin condition influenced by various factors, such as the skin microbiome and metabolome. However, specific contributions of these factors to scalp involvement in AD still need to be explored. In this study, we aimed to assess the associations between the skin microbiome and metabolome in AD patients with scalp dermatitis and healthy controls (HCs).METHODS: A total of 20 AD patients with scalp involvement and 16 HCs were recruited, and their skin samples were collected for analysis. Bioinformatic analysis and 16S rRNA metagenomic sequencing were performed, with gas chromatography time-of-flight mass spectrometry (GC-TOF-MS) conducted for AD-associated skin metabolites. Spearman correlation analysis was used to identify the correlations between AD-associated skin bacteria and metabolites.RESULTS: The results revealed significant differences in bacterial taxa and metabolites between the lesional and non-lesional scalp skin samples of AD patients (groups LS and NL, respectively) and those of HCs (group HC). Notably, group LS showed a significantly increased relative abundance of the genus Staphylococcus and a decreased abundance of Cutibacterium compared to group HC. The reduced abundance of Cutibacterium was also observed when comparing LS to NL. The GC-TOF-MS analysis identified 33 significantly decreased metabolites and 17 significantly increased metabolites in groups LS and NL compared with group HC. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that amino acid-related metabolism was significantly altered in the metabolic pathway between groups LS, NL, and HC. Furthermore, Spearman correlation analysis showed significant correlations of the altered bacteria genera and skin metabolites between the 3 groups.CONCLUSIONS: The results of this research provide valuable insights into the associations the skin microbiome and metabolome between groups LS, NL, and HC. Identifying these specific contributions may offer new avenues for understanding the pathogenesis of scalp involvement in AD patients and potentially lead to improving management strategies.PMID:39622690 | DOI:10.4168/aair.2024.16.6.668

Biomed Environ Sci. 2024 Oct 20;37(10):1204-1207. doi: 10.3967/bes2024.145.NO ABSTRACTPMID:39622669 | DOI:10.3967/bes2024.145

Diabetes. 2024 Dec 2:db240501. doi: 10.2337/db24-0501. Online ahead of print.ABSTRACTThe accumulation of mitochondria in thermogenic adipose tissue (i.e., brown and beige fat) increases energy expenditure, which can aid in alleviating obesity and metabolic disorders. However, recent studies have shown that knocking out key proteins required to maintain mitochondrial function inhibits the energy expenditure in thermogenic fat, and yet the knockout mice are unexpectedly protected from developing obesity or metabolic disorders when fed a high-fat diet (HFD). In the present study, non-biased sequencing-based screening revealed the importance of YY1 in the transcription of electron transport chain genes and the enhancement of mitochondrial function in thermogenic adipose tissue. Specifically, adipocyte YY1 null (YAKO) mice showed lower energy expenditure and were intolerant to cold stress. Interestingly, YAKO mice showed alleviation of HFD-induced metabolic disorders, which can be attributed to a suppression of adipose tissue inflammation. Metabolomic analysis revealed that blocking YY1 directed glucose metabolism toward lactate, enhanced the uptake of glutamine, and promoted the production of anti-inflammatory spermidine. Conversely, blocking spermidine production in YAKO mice reversed their resistance to HFD-induced disorders. Thus, although blocking adipocyte YY1 impairs the thermogenesis, it promotes spermidine production and alleviates adipose tissue inflammation, therefore leads to an uncoupling of adipose tissue energy expenditure from HFD-induced metabolic disorders.PMID:39621859 | DOI:10.2337/db24-0501

PLoS One. 2024 Dec 2;19(12):e0313894. doi: 10.1371/journal.pone.0313894. eCollection 2024.ABSTRACTThe Sterile Insect Technique (SIT) is revolutionizing pest control through its environmentally friendly approach, which involves rearing and sterilizing male insect pests using ionizing radiation and subsequently releasing them into the field to mate with wild females without producing offspring. Recent research has unveiled a groundbreaking enhancement in the quality of released Ceratitis capitata (medfly) males through the addition of probiotics to their larval diet. To thoroughly examine the impact of probiotic supplementation on the medfly larval diet, we conducted an in-depth analysis with GC-MS from medfly extract supplemented with probiotic Enterobacter sp. strain. The supplementation revealed a notable difference in the metabolomic signature compared to non-supplemented extract across all medfly life stages. We identified 37 known metabolites for all the stages, 12 of them were identified as biomarkers for the larval stage, 12 for the pupal stage, and 13 for the adult stage exhibiting crucial activities such as anti-bacterial, anti-fungal, and sexual and aggregation pheromone. These findings underscore the considerable potential of SIT combined with probiotic supplementation for enhancing sustainable pest control strategies worldwide.PMID:39621595 | DOI:10.1371/journal.pone.0313894

JAMA Pediatr. 2024 Dec 2. doi: 10.1001/jamapediatrics.2024.5049. Online ahead of print.ABSTRACTIMPORTANCE: Particulate matter exposure has been linked to impaired respiratory health in children, but the respiratory benefits of air purification have not been fully elucidated.OBJECTIVES: To assess the respiratory health outcomes among children exposed to multisetting air purification vs sham purification.DESIGN, SETTING, AND PARTICIPANTS: This cluster randomized, double-blind, crossover trial was conducted among healthy school-aged children (10-12 years) in China from April to December 2021. Data were analyzed from December 2021 to July 2024.INTERVENTIONS: A multisetting (both in classrooms and bedrooms) air purification intervention compared with sham purification in a 2-stage intervention with more than 2 months (76 days) for each period and a washout period (88 days) to estimate the respiratory benefits of air purification.MAIN OUTCOMES AND MEASURES: The primary outcomes were pulmonary function, airway inflammation markers, and metabolites in exhaled breath condensate (EBC) before and after the air purification intervention. Linear mixed-effects models were used to estimate the respiratory benefits of children related to air purification. Differential metabolites in EBC were identified using metabolomics analysis to explore their possible mediation roles.RESULTS: A total of 79 children (38 male [48%]; mean [SD] age, 10.3 [0.5] years) were included in the statistical analyses. During the study period, the mean (SD) concentration of outdoor fine particulate matter (PM2.5) at the school site was 32.53 (24.06) μg/m3. The time-weighted personal PM2.5 concentration decreased by 45.14% during the true air purification period (mean [SD], 21.49 [8.72] μg/m3) compared with the sham air purification period (mean [SD], 39.17 [14.25] μg/m3). Air purification improved forced expiratory volume in 1 second by 8.04% (95% CI, 2.15%-13.93%), peak expiratory flow by 16.52% (95% CI, 2.76%-30.28%), forced vital capacity (FVC) by 5.73% (95% CI, 0.48%-10.98%), forced expiratory flow at 25% to 75% of FVC by 17.22% (95% CI, 3.78%-30.67%), maximal expiratory flow at 75% of FVC by 14.60% (95% CI, 0.35%-28.85%), maximal expiratory flow at 50% of FVC by 17.86% (95% CI, 3.65%-32.06%), and maximal expiratory flow at 25% of FVC by 18.22% (95% CI, 1.73%-34.70%). Fractional exhaled nitric oxide in the true air purification group decreased by 22.38% (95% CI, 2.27%-42.48%). Several metabolites in EBC (eg, L-tyrosine and β-alanine) were identified to mediate the effect of air purification on respiratory health.CONCLUSIONS AND RELEVANCE: This randomized clinical trial provides robust and holistic evidence that indoor air purification notably improved pulmonary health in children, highlighting the importance of intensified indoor air purification in regions with high air pollution levels.TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04835337.PMID:39621320 | DOI:10.1001/jamapediatrics.2024.5049

Methods Mol Biol. 2025;2860:273-285. doi: 10.1007/978-1-0716-4160-6_18.ABSTRACTVaccinia virus (VACV), the prototype member of the Poxviridae family, has played a crucial role in medicine as a key component in the development of smallpox vaccines, contributing to the eradication of this deadly disease. Beyond its historical significance, VACV continues to be pivotal in researching metabolic alterations induced by viral infections. Studies have revealed that VACV can impact pathways such as glycolysis, the tricarboxylic acid (TCA) cycle, and lipid metabolism in host cells, offering valuable insights into host-virus interactions and broader cellular metabolism. The preference for primary cells, such as human foreskin fibroblasts (HFFs), over cancer cells in metabolic studies is justified for their physiological relevance, representing native cell types with genetic stability. Metabolic profiling is an ideal tool for studying virus-induced metabolic alterations, providing a comprehensive analysis of changes in cellular metabolism triggered by viral infections. This chapter outlines a protocol for extracting HFFs, culturing, infecting them with VACV, and conducting untargeted global metabolic profiling to elucidate detailed metabolic statuses of the infected cells. This protocol may be modified for understanding the intricacies of host-virus interactions at the metabolic interface for other poxviruses and non-poxviruses.PMID:39621274 | DOI:10.1007/978-1-0716-4160-6_18

Diabetologia. 2024 Dec 2. doi: 10.1007/s00125-024-06334-x. Online ahead of print.ABSTRACTAIMS/HYPOTHESIS: Precision medicine approaches to gestational diabetes mellitus (GDM) have categorised patients according to disease pathophysiology (insulin resistance, insulin insufficiency or both), and demonstrated associations with clinical outcomes. We aimed to assess whether using enhanced processing to determine indices of insulin secretion and sensitivity is analytically robust, reproducible in a different population, and useful diagnostically and prognostically in clinical practice.METHODS: A total of 1308 pregnant women with one or more risk factors for GDM who underwent a 75 g OGTT at one of nine hospital sites were recruited to this observational study. Specimens were collected for determination of glucose levels using standard and enhanced procedures, HbA1c and insulin analysis. GDM diagnosis and management followed National Institute for Health and Care Excellence guidance. We categorised women into pathophysiological subtypes: insulin-resistant GDM (HOMA2-S < 25th centile of the population with normal glucose tolerance [NGT]), insulin-insufficient GDM (HOMA2-B < 25th centile), both or neither. We assessed associations with pregnancy outcomes using logistic regression.RESULTS: Using enhanced specimen handling, 1027/1308 (78.5%) women had NGT, with 281/1308 (21.5%) being classified as having GDM. Of this group, 135/281 (48.0%) had insulin-resistant GDM, 73/281 (26.0%) had insulin-insufficient GDM and 2/281 (0.7%) had both insulin-resistant and insulin-insufficient GDM. Unexpectedly, 71 patients (25.3%) had GDM with both HOMA2-S and HOMA2-B ≥ 25th centile (GDM-neither). This novel subgroup appeared to be relatively insulin-sensitive in the fasting state but developed marked post-load hyperglycaemia and hyperinsulinaemia, suggesting an isolated postprandial defect in insulin sensitivity that was not captured by HOMA2-B or HOMA2-S. Women within most GDM subgroups had comparable pregnancy outcomes to those of normoglycaemic women, and HOMA2-B and HOMA2-S were weak predictors of pregnancy outcomes. Maternal BMI predicted a similar number of outcomes to HOMA2-S, suggesting that there was no additional predictive value in adding HOMA2-S. Similar findings were obtained when using different indices and standard specimen handling techniques.CONCLUSIONS/INTERPRETATION: Precision categorisation of GDM using HOMA2-S and HOMA2-B does not provide useful diagnostic or prognostic information, but did distinguish a novel subgroup of patients with GDM, characterised by an isolated postprandial defect in insulin sensitivity.PMID:39621104 | DOI:10.1007/s00125-024-06334-x

Diabetologia. 2024 Dec 2. doi: 10.1007/s00125-024-06324-z. Online ahead of print.ABSTRACTAIMS/HYPOTHESIS: This study aims to explore the association between plasma metabolites and chronic kidney disease progression in individuals with type 2 diabetes.METHODS: We performed a comprehensive metabolomic analysis in a prospective cohort study of 5144 multi-ancestral individuals with type 2 diabetes in Singapore, using eGFR slope as the primary outcome of kidney function decline. In addition, we performed genome-wide association studies on metabolites to assess how these metabolites could be genetically influenced by metabolite quantitative trait loci and performed colocalisation analysis to identify genes affecting both metabolites and kidney function.RESULTS: Elevated levels of 61 lipids with long unsaturated fatty acid chains such as phosphatidylethanolamines, triacylglycerols, diacylglycerols, ceramides and deoxysphingolipids were prospectively associated with more rapid kidney function decline. In addition, elevated levels of seven amino acids and three lipids in the plasma were associated with a slower decline in eGFR. We also identified 15 metabolite quantitative trait loci associated with these metabolites, within which variants near TM6SF2, APOE and CPS1 could affect both metabolite levels and kidney functions.CONCLUSIONS/INTERPRETATION: Our study identified plasma metabolites associated with prospective renal function decline, offering insights into the underlying mechanism by which the metabolite abnormalities due to fatty acid oversupply might reflect impaired β-oxidation and associate with future chronic kidney disease progression in individuals with diabetes.PMID:39621102 | DOI:10.1007/s00125-024-06324-z

Crit Rev Food Sci Nutr. 2024 Dec 2:1-27. doi: 10.1080/10408398.2024.2435597. Online ahead of print.ABSTRACTThis review systematically explores the emerging perspectives on analytical techniques and machine learning applications in food metabolomics, with a focus on their roles in the era of Industry 4.0. The study emphasizes the utilization of chromatography-mass spectrometry and proton nuclear magnetic resonance spectroscopy as primary tools for metabolic profiling, highlighting their respective strengths and limitations. LC-MS, known for its high sensitivity and specificity, faces challenges such as complex data interpretation and the need for advanced computational tools.1H NMR offers reproducibility and quantitative accuracy but struggles with lower sensitivity compared to mass spectrometry. The review also delves into the integration of multivariate data analysis techniques like principal component analysis and partial least squares-discriminant analysis, which enhance data dimensionality reduction and pattern recognition, yet require careful validation to avoid overfitting. Furthermore, the application of machine learning algorithms, including random forests and support vector machines, is discussed in the context of improving classification and predictive tasks in food metabolomics. Practical applications of these technologies are demonstrated in areas such as quality control, nutritional studies, and food adulteration detection. The review emphasizes the need for standardization in methodologies and the development of more accessible and cost-effective analytical workflows. Future research directions include enhancing the sensitivity of 1H NMR, integrating metabolomics with other omics technologies, and fostering data sharing to build comprehensive reference libraries. This review aims to provide a comprehensive and critical overview of the current advancements and future potentials of analytical techniques and machine learning in food metabolomics, aligning with the goals of Industry 4.0.PMID:39621023 | DOI:10.1080/10408398.2024.2435597

Pediatrics. 2024 Dec 1;154(Suppl 4):S12. doi: 10.1542/peds.2024-069114DI.NO ABSTRACTPMID:39620763 | DOI:10.1542/peds.2024-069114DI

J Agric Food Chem. 2024 Dec 2. doi: 10.1021/acs.jafc.4c07461. Online ahead of print.ABSTRACTGinsenosides and lipids are both bioactive ingredients for ginseng. Targeting these two categories of components, this study was designed to develop desorption electrospray ionization-mass spectrometry imaging approaches and spatial metabolomics strategies, achieving the visualization and differentiation among different parts of Panax ginseng root (e.g., rhizome, main root, lateral root, fibrous root, and adventitious root). Potential chemical markers were identified by searching an in-house ginsenoside library and online Lipid Maps database, together with high-resolution MS2 data analysis. Six ginsenosides and 11 lipids were diagnostic to differentiate five different parts of the P. ginseng root. Additionally, three ginsenosides and 20 lipids were identified as differential markers among the six positions of the main root of P. ginseng. High-abundance malonyl- and oleanolic acid-ginsenosides were observed in the rhizome. These results assist in understanding the accumulation of bioactive molecules all through the root of P. ginseng, which can benefit its quality control and rational use.PMID:39620636 | DOI:10.1021/acs.jafc.4c07461

Nat Prod Rep. 2024 Dec 2. doi: 10.1039/d4np00039k. Online ahead of print.ABSTRACTCovering: 2014 to 2023 for metabolomics, 2002 to 2023 for information visualizationLC-MS/MS-based untargeted metabolomics is a rapidly developing research field spawning increasing numbers of computational metabolomics tools assisting researchers with their complex data processing, analysis, and interpretation tasks. In this article, we review the entire untargeted metabolomics workflow from the perspective of information visualization, visual analytics and visual data integration. Data visualization is a crucial step at every stage of the metabolomics workflow, where it provides core components of data inspection, evaluation, and sharing capabilities. However, due to the large number of available data analysis tools and corresponding visualization components, it is hard for both users and developers to get an overview of what is already available and which tools are suitable for their analysis. In addition, there is little cross-pollination between the fields of data visualization and metabolomics, leaving visual tools to be designed in a secondary and mostly ad hoc fashion. With this review, we aim to bridge the gap between the fields of untargeted metabolomics and data visualization. First, we introduce data visualization to the untargeted metabolomics field as a topic worthy of its own dedicated research, and provide a primer on cutting-edge visualization research into data visualization for both researchers as well as developers active in metabolomics. We extend this primer with a discussion of best practices for data visualization as they have emerged from data visualization studies. Second, we provide a practical roadmap to the visual tool landscape and its use within the untargeted metabolomics field. Here, for several computational analysis stages within the untargeted metabolomics workflow, we provide an overview of commonly used visual strategies with practical examples. In this context, we will also outline promising areas for further research and development. We end the review with a set of recommendations for developers and users on how to make the best use of visualizations for more effective and transparent communication of results.PMID:39620439 | DOI:10.1039/d4np00039k

Gut Microbes. 2024 Jan-Dec;16(1):2429267. doi: 10.1080/19490976.2024.2429267. Epub 2024 Dec 2.ABSTRACTThroughout gestation, the female body undergoes a series of transformations, including profound alterations in intestinal microbial communities. Changes gradually increase toward the end of pregnancy and comprise reduced α-diversity of microbial communities and an increased propensity for energy harvest. Despite the importance of the intestinal microbiota for the pathophysiology of inflammatory bowel diseases, very little is known about the relationship between these microbiota shifts and pregnancy-associated complications of the disease. Here, we explored the longitudinal dynamics of gut microbiota composition and functional potential during pregnancy and after lactation in Atg16l1∆IEC mice carrying an intestinal epithelial deletion of the Crohn's disease risk gene Atg16l1. Using 16S rRNA amplicon and shotgun metagenomic sequencing, we demonstrated divergent temporal shifts in microbial composition between Atg16l1 wildtype and Atg16l1∆IEC pregnant mice in trimester 3, which was validated in an independent experiment. Observed differences included microbial genera implicated in IBD such as Lachnospiraceae, Roseburia, Ruminococcus, and Turicibacter. Changes partially recovered after lactation. Additionally, metagenomic and metabolomic analyses suggest an increased capacity for chitin degradation, resulting in higher levels of free N-acetyl-glucosamine products in feces, alongside reduced glucose and myo-inositol levels in serum around the time of delivery. On the host side, we found that the immunological response of Atg16l1∆IEC mice is characterized by higher colonic mRNA levels of TNFα and CXCL1 in trimester 3 and a lower weight of offspring at birth. Understanding pregnancy-dependent microbiome changes in the context of IBD may constitute the first step in the identification of fecal microbial biomarkers and microbiota-directed therapies that could help improve precision care for managing pregnancies in IBD patients.PMID:39620359 | DOI:10.1080/19490976.2024.2429267

Rapid Commun Mass Spectrom. 2025 Feb;39(4):e9955. doi: 10.1002/rcm.9955.ABSTRACTBACKGROUND: Asthma, a prevalent chronic inflammatory respiratory disease among children, was the focus of this study. Serum metabolism profiles were examined in patients diagnosed with both asthma and bronchiolitis by using ultra-high performance liquid chromatography-mass spectrometry.METHODS: In this study, the serum samples from three distinct groups-comprising patients diagnosed with asthma, bronchiolitis, and a healthy control group-underwent comprehensive non-targeted metabolomics analysis and targeted eicosanoid profiling.RESULTS: Through both univariate and multivariate analyses, significant associations were observed between the pathophysiology of both asthma and bronchiolitis and aberrations in the metabolism of polyunsaturated fatty acids, amino acids, purines, and pathways involving cyclooxygenases and lipoxygenases, indicative of inflammatory processes and immune responses. Furthermore, metabolic changes in phosphatidylethanolamine, saturated and monounsaturated fatty acids, and bile acids were observed in the asthma group. Bronchiolitis was distinguished by disruptions in acyl carnitine and phosphatidylcholine metabolism.CONCLUSION: This study offers a new perspective on understanding the interplay of pathogenic mechanisms underlying both asthma and bronchiolitis. Its findings are significant for enhancing the diagnostic and therapeutic strategies tailored to asthma stemming from bronchiolitis.PMID:39620356 | DOI:10.1002/rcm.9955

Rapid Commun Mass Spectrom. 2025 Feb;39(4):e9959. doi: 10.1002/rcm.9959.ABSTRACTChlorphenesin carbamate is a skeletal muscle relaxant, and one of its metabolites is 4-chlorophenoxyacetic acid (4-CPA), which is included on the Prohibited List of the World Anti-Doping Agency (WADA). The non-prohibited substance, chlorphenesin carbamate, as a potential source of 4-CPA, needs to be identified more strongly in doping control protocols. In this paper, the metabolism of chlorphenesin carbamate in human urine was studied. Ten volunteers were recruited to take chlorphenesin carbamate tablets orally, and urine samples were collected before and after being tested. The urine samples were detected by liquid chromatography-Q Exactive HF orbitrap mass spectrometry (LC-Q Exactive HF-MS) in full MS and full MS-ddMS2 scanning modes. Based on accurate molecular formulae determination and fragmentation pattern analysis by mass spectrometry, a total of 29 chlorphenesin carbamate metabolites were found, comprising 18 newly identified metabolites and 11 previously reported metabolites. There were five potential metabolic processes listed: hydroxylation, amide hydrolysis, C-oxidation, O-glucuronidation, sulfation, and their combinations. Chlorphenesin carbamate and the 29 metabolites were compared for their detection windows, and the findings indicated that the two recently reported metabolites, M9 and M10, had longer detection windows than the metabolites documented by the WADA. These metabolites are anticipated to be long-lasting biomarkers for the detection of chlorphenesin carbamate intake. By analyzing the results of metabolomic profiling, it was found that the metabolites with significant changes were mainly related to histidine metabolism and β-alanine metabolism pathways. This paper provides a comprehensive report on the metabolic profile of urinary chlorphenesin carbamate and reveals a point of view the changes in the metabolic in the human body, which is conducive to supporting the detection of chlorphenesin carbamate and meclofenoxate for doping control, as well as a better understanding of the mechanism of action of chlorphenesin carbamate as a drug.PMID:39620316 | DOI:10.1002/rcm.9959

Stress. 2024 Jan;27(1):2401788. doi: 10.1080/10253890.2024.2401788. Epub 2024 Dec 2.ABSTRACTAdverse Childhood Experiences (ACEs) are very common and presently implicated in 9 out of 10 leading causes of death in the United States. Despite this fact, our mechanistic understanding of how ACEs impact health is limited. Moreover, interventions for reducing stress presently use a one-size-fits-all approach that involves no treatment tailoring or precision. To address these issues, we developed a combined cross-sectional study and randomized controlled trial, called the California Stress, Trauma, and Resilience Study (CalSTARS), to (a) characterize how ACEs influence multisystem biological functioning in adults with all levels of ACE burden and current perceived stress, using multiomics and other complementary approaches, and (b) test the efficacy of our new California Precision Intervention for Stress and Resilience (PRECISE) in adults with elevated perceived stress levels who have experienced the full range of ACEs. The primary trial outcome is perceived stress, and the secondary outcomes span a variety of psychological, emotional, biological, and behavioral variables, as assessed using self-report measures, wearable technologies, and extensive biospecimens (i.e. DNA, saliva, blood, urine, & stool) that will be subjected to genomic, transcriptomic, proteomic, metabolomic, lipidomic, immunomic, and metagenomic/microbiome analysis. In this protocol paper, we describe the scientific gaps motivating this study as well as the sample, study design, procedures, measures, and planned analyses. Ultimately, our goal is to leverage the power of cutting-edge tools from psychology, multiomics, precision medicine, and translational bioinformatics to identify social, molecular, and immunological processes that can be targeted to reduce stress-related disease risk and enhance biopsychosocial resilience in individuals and communities worldwide.PMID:39620249 | DOI:10.1080/10253890.2024.2401788