PubMed

Comp Biochem Physiol Part D Genomics Proteomics. 2025 Feb 19;55:101448. doi: 10.1016/j.cbd.2025.101448. Online ahead of print.ABSTRACTUnderstanding metabolic adaptations to seasonal fluctuations in ectothermic organisms is challenging, especially in tropical species where physiological responses are more pronounced than in temperate or polar counterparts. Traditional analytical methods often fail to account for the complex metabolic adjustments that are present in these substantial responses, and the high-dimensional characteristics of metabolomic data complicate the interpretation process when using conventional statistical methods. We utilized Non-negative Matrix Factorization (NMF), an unsupervised machine learning algorithm, to analyze monthly serum metabolomics data from tilapia over a year in order to overcome these limits. A deeper analysis using NMF demonstrated that carbohydrates gained prominence during warmer months, as evidenced by consistently elevated weights of glycolysis intermediates in our quantitative analysis. Furthermore, fatty acids remained an important factor in both warm and cold seasons. Amino acids emerged as particularly versatile metabolites, exhibiting adaptability during seasonal transitions. This flexibility suggests their crucial role in coordinating energy-related adaptations and potentially facilitating epigenetic and reproductive responses to changing environments. Serum aspartate composition during the warm-cold transition indicated sex-specific metabolic strategies, as sexual dimorphism was observed in the seasonal utilization of fatty acids and aspartate. Collectively, NMF objectively assesses the metabolic tactics of tropical fish and reveals latent patterns in real-world metabolic dynamics. Consequently, it possesses the potential to facilitate metabolomics-driven species conservation in response to environmental changes.PMID:40020271 | DOI:10.1016/j.cbd.2025.101448

Medicine (Baltimore). 2025 Feb 28;104(9):e41651. doi: 10.1097/MD.0000000000041651.ABSTRACTHypertension continues to pose a huge burden to global public health. Abnormal metabolism not only serves as a risk factor for hypertension but also acts as a driving force in its aggravation. However, there remains a lack of large-scale causal demonstration based on extensive samples. Our study aims to investigate the causal relationship between metabolism and primary hypertension (PH) using Mendelian randomization analysis. We used genome-wide association studies instrumental variables for Mendelian randomization association analysis integrating the diagnosis results of PH in 3 populations from East Asia, the Middle East, and Africa with serum metabolites and metabolite ratios. This allowed us to identify predictive metabolites and metabolic pathways for diagnosing or treating PH. Inverse-variance weighting was the main model for establishing causal associations. In addition horizontal pleiotropy test, linkage disequilibrium test, and sensitivity analysis were employed to test the explanatory power of instrumental variables. A total of 10,922 cases of PH and 8299 cases of metabolomics detection cohorts were included in the study. In East Asian, Middle Eastern, and African populations, we found 36, 57, and 40 known metabolites respectively strongly associated with PH (P < .05). Cross-section and meta-analysis of these strongly correlated metabolites across the 3 ethnic groups revealed 7 common metabolites. Notably, elevated isoleucine (odds ratio = 0.74, 95% confidence interval: 0.56-0.96) was demonstrated as a potential protective factor against PH across 3 ethnic groups. The metabolites associated with PH have certain polymorphisms in different populations. Isoleucine may be a promising biomarker for PH diagnosis or treatment, but more clinical validation is needed.PMID:40020104 | DOI:10.1097/MD.0000000000041651

Curr Med Sci. 2025 Feb 28. doi: 10.1007/s11596-025-00023-5. Online ahead of print.ABSTRACTOBJECTIVE: This study aims to investigate the exosome-derived metabolomics profiles in systemic lupus erythematosus (SLE), identify differential metabolites, and analyze their potential as diagnostic markers for SLE and lupus nephritis (LN).METHODS: Totally, 91 participants were enrolled between February 2023 and January 2024 including 58 SLE patients [30 with nonrenal-SLE and 28 with Lupus nephritis (LN)] and 33 healthy controls (HC). Ultracentrifugation was used to isolate serum exosomes, which were analyzed for their metabolic profiles using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Endogenous metabolites were identified via public metabolite databases. Random Forest, Lasso regression and Support Vector Machine Recursive Feature Elimination (SVM-RFE) algorithms were employed to screen key metabolites, and a prediction model was constructed for SLE diagnosis and LN discrimination. ROC curves were constructed to determine the potential of these differential exosome-derived metabolites for the diagnosis of SLE. Furthermore, Spearman's correlation was employed to evaluate the potential links between exosome-derived metabolites and the clinical parameters which reflect disease progression.RESULTS: A total of 586 endogenous serum exosome-derived metabolites showed differential expression, with 225 exosome-derived metabolites significantly upregulated, 88 downregulated and 273 exhibiting no notable changes in the HC and SLE groups. Machine learning algorithms revealed three differential metabolites: Pro-Asn-Gln-Met-Ser, C24:1 sphingolipid, and protoporphyrin IX, which exhibited AUC values of 0.998, 0.992 and 0.969 respectively, for distinguishing between the SLE and HC groups, with a combined AUC of 1.0. In distinguishing between the LN and SLE groups, the AUC values for these metabolites were 0.920, 0.893 and 0.865, respectively, with a combined AUC of 0.931, demonstrating excellent diagnostic performance. Spearman correlation analysis revealed that Pro-Asn-Gln-Met-Ser and protoporphyrin IX were positively correlated with the SLE Disease Activity Index (SLEDAI) scores, urinary protein/creatinine ratio (ACR) and urinary protein levels, while C24:1 sphingolipid exhibited a negative correlation.CONCLUSIONS: This study provides the first comprehensive characterization of the exosome-derived metabolites in SLE and established a promising prediction model for SLE and LN discrimination. The correlation between exosome-derived metabolites and key clinical parameters strongly indicated their potential role in SLE pathological progression.PMID:40019633 | DOI:10.1007/s11596-025-00023-5

Eur J Nucl Med Mol Imaging. 2025 Feb 28. doi: 10.1007/s00259-025-07157-7. Online ahead of print.ABSTRACTBACKGROUND: Cardiac amyloidosis (CA) is a severe condition characterized by amyloid fibril deposition in the myocardium, leading to restrictive cardiomyopathy and heart failure. Differentiating between amyloidosis subtypes is crucial due to distinct treatment strategies. The individual conventional diagnostic methods lack the accuracy needed for effective subtype identification. This study aimed to evaluate the efficacy of combining 11C-PiB PET/CT and 99mTc-DPD scintigraphy in detecting CA and distinguishing between its main subtypes, light chain (AL) and transthyretin (ATTR) amyloidosis while assessing the association of imaging findings with patient prognosis.METHODS: We retrospectively evaluated the diagnostic efficacy of combining 11C-PiB PET/CT and 99mTc-DPD scintigraphy in a cohort of 50 patients with clinical suspicion of CA. Semi-quantitative imaging markers were extracted from the images. Diagnostic performance was calculated against biopsy results or genetic testing. Both machine learning models and a rationale-based model were developed to detect CA and classify subtypes. Survival prediction over five years was assessed using a random survival forest model. Prognostic value was assessed using Kaplan-Meier estimators and Cox proportional hazards models.RESULTS: The combined imaging approach significantly improved diagnostic accuracy, with 11C-PiB PET and 99mTc-DPD scintigraphy showing complementary strengths in detecting AL and ATTR, respectively. The machine learning model achieved an AUC of 0.94 (95% CI 0.93-0.95) for CA subtype differentiation, while the rationale-based model demonstrated strong diagnostic ability with AUCs of 0.95 (95% CI 0.88-1.00) for ATTR and 0.88 (95% CI 0.770-0.961) for AL. Survival prediction models identified key prognostic markers, with significant stratification of overall mortality based on predicted survival (p value = 0.006; adj HR 2.43 [95% CI 1.03-5.71]).CONCLUSION: The integration of 11C-PiB PET/CT and 99mTc-DPD scintigraphy, supported by both machine learning and rationale-based models, enhances the diagnostic accuracy and prognostic assessment of cardiac amyloidosis, with significant implications for clinical practice.PMID:40019577 | DOI:10.1007/s00259-025-07157-7

Funct Integr Genomics. 2025 Feb 28;25(1):46. doi: 10.1007/s10142-025-01549-6.ABSTRACTSaussurea costus (Falc.) is an endangered medicinal plant possessing diverse phytochemical compounds with clinical significance and used to treat numerous human ailments. Despite the source of enriched phytochemicals, molecular insights into spatialized metabolism are poorly understood in S. costus. This study investigated the dynamics of organ-specific secondary metabolite biosynthesis using deep transcriptome sequencing and high-throughput UHPLC-QTOF based untargeted metabolomic profiling. A de novo assembly from quality reads fetched 59,725 transcripts with structural (53.02%) and functional (66.13%) annotations of non-redundant transcripts. Of the 7,683 predicted gene families, 3,211 were categorized as 'single gene families'. Interestingly, out of the 4,664 core gene families within the Asterids, 4,560 families were captured in S. costus. Organ-specific differential gene expression analysis revealed significant variations between leaves vs. stems (23,102 transcripts), leaves vs. roots (30,590 transcripts), and roots vs. stems (21,759 transcripts). Like-wise, putative metabolites (PMs) were recorded with significant differences in leaves vs. roots (250 PMs), leaves vs. stem (350 PMs), and roots vs. stem (107 PMs). The integrative transcriptomic and metabolomic analysis identified organ-specific differences in the accumulation of important metabolites, including secologanin, menthofuran, taraxerol, lupeol, acetyleugenol, scopoletin, costunolide, and dehydrocostus lactone. Furthermore, a global gene co-expression network (GCN) identified putative regulators controlling the expression of key target genes of secondary metabolite pathways including terpenoid, phenylpropanoid, and flavonoid. The comprehensive functionally relevant genomic resource created here provides beneficial insights for upscaling targeted metabolite biosynthesis through genetic engineering, and for expediting association mapping efforts to elucidate the casual genetic elements controlling specific bioactive metabolites.PMID:40019562 | DOI:10.1007/s10142-025-01549-6

J Gastroenterol. 2025 Feb 28. doi: 10.1007/s00535-025-02226-y. Online ahead of print.ABSTRACTBACKGROUND: Hepatocellular carcinoma (HCC), the most common form of liver cancer, presents a challenging malignancy with scarce treatment options. Liver progenitor cells (LPCs) play a pivotal role in both liver regeneration and the progression of liver cancer, yet the specific functions of LPCs from different origins in liver cancer remain to be fully elucidated.METHODS: We explored the liver progenitor-like cells derived from human hepatocytes (HepLPCs) on the proliferation of HCC both in vitro and in vivo. The mitochondrial function was assessed through electron microscopy and functional experiments. Transcriptomic sequencing and western blot unveiled the fundamental mechanisms at play, whereas metabolomic sequencing pinpointed crucial effector molecules involved in the paracrine secretion of HepLPCs.RESULTS: By employing a co-culture system of HepLPCs and HCC cells, we found that HepLPCs markedly inhibited HCC growth by prompting mitochondrial dysfunction, which further led to the co-inhibition of the Notch1 and JAK1/STAT3 signaling pathways through paracrine actions involving S-adenosylmethionine (SAM) and Nicotinic acid (NA).CONCLUSIONS: This study has uncovered that HepLPCs have a suppressive influence on the proliferation of HCC cells. This is achieved through the impairment of mitochondrial function and the inhibition of key signaling pathways, namely, Notch1 and JAK1/STAT3, which are critical drivers of cancer progression. The secretion of the metabolites SAM and NA by HepLPCs appears to be instrumental in mediating these effects. These findings provide a solid foundation for identifying new therapeutic targets and clarifying the mechanisms through which HepLPCs can be harnessed to effectively treat HCC.PMID:40019515 | DOI:10.1007/s00535-025-02226-y

Ther Deliv. 2025 Feb 28:1-15. doi: 10.1080/20415990.2025.2470614. Online ahead of print.ABSTRACTAIMS: This study aimed to evaluate the potential of Eryngium maritimum L. (EM) callus media filtrate (ECMF) for enhanced skin delivery through multilayered liposomes (MLs).MATERIALS & METHODS: ECMF was applied to human skin cells to assess its antioxidant, anti-inflammatory, and skin barrier-enhancing properties. ECMF was encapsulated in MLs to enhance delivery efficiency, creating a formulation called Cellbiome. Clinical trials involving human participants were conducted to compare its effects with traditional formulations, assessing parameters such as skin density, hydration, elasticity, and wrinkle reduction.RESULTS: Cellbiome significantly improved skin density and moisturization, outperforming conventional formulations. ML encapsulation facilitated deeper penetration of active ingredients beyond the stratum corneum, leading to synchronized improvements in multiple skin parameters, including elasticity, wrinkle reduction, and overall skin health. Transcriptomic and metabolomic analyses further confirmed ECMF's bioactivity and its role in skin improvement.CONCLUSIONS: ML-based formulations, such as Cellbiome, offer superior efficacy in skincare applications compared to conventional methods. This study underscores the importance of advanced delivery technologies in cosmetics and highlights the need for further research to optimize the benefits of natural extracts like EM for human skin, potentially advancing dermatological and cosmeceutical applications.PMID:40019355 | DOI:10.1080/20415990.2025.2470614

Anal Chem. 2025 Feb 28. doi: 10.1021/acs.analchem.4c06375. Online ahead of print.ABSTRACTAccurate identification and quantification of fatty acids are critical for investigating their biological function in disease models. Although several derivatization methods have been proposed for identifying the positions of C═C bonds in unsaturated fatty acids, poor ionization efficiency of the carboxyl group leads to lower intensity of molecular ion peaks, making their identification difficult and interfering with the accuracy of quantification based on peak areas of characteristic ion pairs. In this study, a strategy of stable isotope-labeled carboxyl derivatization combined with C═C derivatization was employed for simultaneously the identification and quantification of fatty acids using d0/d9-5-amino-N,N,N-trimethylpentane-1-ammonium iodide (d0/d9-ATPAI) to label the carboxyl group and m-chloroperoxybenzoic acid to label C═C bonds. The stable isotope-labeled quaternary amine groups in the novel carboxyl derivatization reagent d0/d9-ATPAI can enhance the accuracy of the recognition of characteristic ion pairs to facilitate the structural elucidation of various fatty acids. The heavy isotope-labeled fatty acids can be served as internal standards to achieve accurate relative quantification of the C═C position isomers of individual unsaturated fatty acids among samples based on the peak area ratio of the characteristic ion pairs. Unsaturated fatty acid C═C positional isomers were quantified using aldehyde or alkenyl diagnostic ions. In addition, saturated fatty acids were quantified using the m/z 86.09679 cyclamine characteristic ion. This approach enhanced the detection sensitivity of fatty acids by 60,000 times, allowing for the characterization of 70 fatty acids in rat serum, including 26 unsaturated fatty acid C═C positional isomers. Pseudotargeted metabolomics analysis of serum fatty acids revealed alterations in the fatty acid metabolic pathway during diabetic cognitive dysfunction. Overall, the proposed method, with high sensitivity and wide coverage, could provide accurate identification and relative quantification of various fatty acids in complex matrices.PMID:40019293 | DOI:10.1021/acs.analchem.4c06375

Asian J Androl. 2025 Feb 28. doi: 10.4103/aja2024110. Online ahead of print.ABSTRACTIn contrast to the conventional spermiogram, metabolomics approaches give insights into the molecular composition of semen and may provide more detailed information on the fertility status of the respective donor. Given the intra-individual variability of spermiogram parameters between two donations, this study sought to elucidate the biological variability of the seminal plasma metabolome over an average period of 8 weeks. Two time-shifted semen samples from 15 healthy donors were compared by a targeted metabolomics approach utilizing the Biocrates AbsoluteIDQ p180 kit. Next to intraclass correlation coefficients (ICC), which represent a measure of reliability, coefficients of variation within individuals (CVW) and coefficients of variation between individuals (CVB) were calculated for each metabolite to demonstrate its stability. Furthermore, men were divided into two cohorts, a similar sperm concentration (SSC) and a differing sperm concentration (DSC) cohort, based on the observed variance in sperm concentration between the two semen donations. The ICC was higher in the SSC compared to the DSC cohort. The levels of 18 metabolites, primarily acylcarnitines, varied between the initial and subsequent donations. After subdivision into subgroups, only ornithine and phosphatidylcholine 40:5 exhibited differential levels between the two donations in the SSC group, compared to 14 metabolites in the DSC group. CVB was higher than CVW but both differed between the metabolite subclasses. Biogenic amines were identified as the least reliable analytes over time, exhibiting the highest CVW, compared to sphingomyelins, which demonstrated the highest reliability with the lowest variation. CVB was the highest for ether-bound glycerophosphatidylcholines and the lowest for amino acids.PMID:40019275 | DOI:10.4103/aja2024110

Appl Environ Microbiol. 2025 Feb 28:e0018025. doi: 10.1128/aem.00180-25. Online ahead of print.ABSTRACTSince cheese is one of the most commonly and globally consumed fermented foods, scientific investigations in recent decades have focused on determining the impact of this dairy product on human health and well-being. However, the modulatory effect exerted by the autochthonous cheese microbial community on the taxonomic composition and associated functional potential of the gut microbiota of human is still far from being fully dissected or understood. Here, through the use of an in vitro human gut-simulating cultivation model in combination with multi-omics approaches, we have shown that minor rather than dominant bacterial players of the cheese microbiota are responsible for gut microbiota modulation of cheese consumers. These include taxa from the genera Enterococcus, Bacillus, Clostridium, and Hafnia. Indeed, they contribute to expand the functional potential of the intestinal microbial ecosystem by introducing genes responsible for the production of metabolites with relevant biological activity, including genes involved in the synthesis of vitamins, short-chain fatty acids, and amino acids. Furthermore, tracing of cheese microbiota-associated bacterial strains in fecal samples from cheese consumers provided evidence of horizontal transmission events, enabling the detection of particular bacterial strains transferred from cheese to humans. Moreover, transcriptomic and metabolomic analyses of a horizontally transmitted (cheese-to-consumer) bacterial strain, i.e., Hafnia paralvei T10, cultivated in a human gut environment-simulating medium, confirmed the concept that cheese-derived bacteria may expand the functional arsenal of the consumer's gut microbiota. This highlights the functional and biologically relevant contributions of food microbes acquired through cheese consumption on the human health.IMPORTANCEDiet is universally recognized as the primary factor influencing and modulating the human intestinal microbiota both taxonomically and functionally. In this context, cheese, being a fermented food with its own microbiota, serves not only as a source of nourishment for humans, but also as a source of nutrients for the consumer's gut microbiota. Additionally, it may act as a vehicle for autochthonous food-associated microorganisms which undergo transfer from cheese to the consumer, potentially influencing host gut health. The current study highlights not only that cheese microbiota-associated bacteria can be traced in the human gut microbiota, but also that they may expand the functional repertoire of the human gut microbiota, with potentially significant implications for human health.PMID:40019271 | DOI:10.1128/aem.00180-25

Endocr Connect. 2025 Feb 1:EC-24-0681. doi: 10.1530/EC-24-0681. Online ahead of print.ABSTRACTOBJECTIVE: Women with gestational diabetes mellitus (GDM) often develop a metabolic memory that increases the risk of future metabolic disorders, even after blood glucose levels normalize following clinical intervention. However, the impact of this metabolic memory on susceptibility to SARS-CoV-2 remains unclear. Therefore, we aim to investigate the potential association between metabolic memory in GDM and susceptibility to SARS-CoV-2 infection.METHODS: We conducted a prospective cohort study with 1,675 pregnant women, including 197 (11.8%) with GDM. Postpartum SARS-CoV-2 infections were tracked via telephone follow-up and categorized into negative and positive groups. Logistic regression was used to explore risk factors for SARS-CoV-2 infection. Peripheral blood samples were collected from 30 GDM and 30 normal glucose-tolerant (NGT) pregnant women in three trimesters (T1, T2, T3) for longitudinal untargeted metabolomics to identify GDM and SARS-CoV-2-associated metabolites. Limma package was applied to find differential metabolites (DEMs) associated with SARS-CoV-2 infection and GDM.RESULTS: Among 1,675 women, 1,348 (80.5%) tested positive for SARS-CoV-2. GDM post-partum women had higher SARS-CoV-2 infection rates (88.3% vs. 79.4%, P = 0.003) than NGT women. GDM was associated with SARS-CoV-2 infection (T2: OR [95% CI]: 2.17 [1.26-3.54], P = 0.005; T3: OR [95% CI]: 1.70 [1.03-2.82], P = 0.040). Compared to the SARS-CoV-2 negative group, the positive group exhibited elevated levels of allantoic acid, LPE (0:0/22:6), LPC (15:0/0:0), 1-linoleoyl-sn-glycero-3-phosphorylcholine in T1 and T2, before clinical intervention. In T3, allantoic acid remained elevated post-intervention. A similar increase as described above was observed in the GDM compared to the NGT group.CONCLUSION: Compared to NGT, women with GDM are at a higher risk of postnatal SARS-CoV-2 infection. Metabolic memory from GDM may heighten susceptibility to SARS-CoV-2.PMID:40019194 | DOI:10.1530/EC-24-0681

J Agric Food Chem. 2025 Feb 28. doi: 10.1021/acs.jafc.4c04734. Online ahead of print.ABSTRACTThe amount of nitrogen (N) fertilization influences the content and composition of phytochemicals in plants. However, the influence of different chemical forms of N fertilizers on the phytochemical profiles of fruits remains less known. We investigated the effect of nitrate [NO3-; supplied as CaNO3], ammoniacal [NH4+; supplied as (NH4)2SO4], and organic-N (supplied as meat and bone meal [MBM]) fertilization on the profile of volatile compounds, primary, and secondary metabolites in the fruits of Alpine strawberries (Fragaria vesca "Reine des Vallées") using global metabolomic approaches. The form of plant-available soil N varied as a function of fertilization, with (NH4)2SO4 and MBM fertilization retaining a higher proportion of N as ammoniacal-N throughout the growing period. Leaf nitrate reductase activity was 5 times higher in CaNO3 treatments, suggesting NO3- as the major N form taken up by plants in this treatment. Although ammoniacal-N fertilization resulted in lower plant biomass, the fruit yield and tissue nutrient content were similar to those of nitrate-N treatments. The plant biomass of organic-N treatment was similar to that of nitrate-N fertilization, but the fruit yield was 30% lower. Compared to nitrate-N treatment, aroma-related volatile compounds increased under organic- and ammoniacal-N fertilization, including up to a 5-fold increase in esters, a 6-fold increase in alcohols, a 3-fold increase in volatile fatty acids, and a 60% increase in organic acids. The content of primary metabolites, especially sugar, sugar alcohol, and amino acids, exhibited an opposite trend and increased in nitrate-N than under ammoniacal- and organic-N fertilization. Compared to nitrate-N, the secondary metabolites generally were higher under ammoniacal- and organic-N fertilization, with an 80% increase in the activity of phenylalanine ammonia lyase, resulting in up to 38% increase in flavones, 28% increase in flavanols, and 33% increase in anthocyanins, except for dihydroflavonols and proanthocyanidins, which decreased by 6 and 13%, respectively. The hydrolyzable tannins, including galloyl glucosides, ellagitannins, and ellagic acids, were 25% abundant under organic-N fertilization. Our results indicate that while nitrate-N generally increased the primary metabolites, organic-N and ammoniacal-N fertilization enhanced the aroma-related volatiles and secondary metabolites in strawberry fruits. Thus, precise management of the chemical form of N fertilization can be a valuable tool to improve the phytonutrient content of strawberries.PMID:40019181 | DOI:10.1021/acs.jafc.4c04734

J Glob Health. 2025 Feb 28;15:04056. doi: 10.7189/jogh.15.04056.ABSTRACTBACKGROUND: Despite advances in metabolomic research on COVID-19, existing studies have small sample sizes and few have comprehensively described the metabolic characteristics of patients with COVID-19 at each stage. In this systematic review, we aimed to summarise the similarities and differences of biomarkers in patients with COVID-19 of different severity and describe their metabolic characteristics at different stages.METHODS: We retrieved studies from PubMed, Embase, Web of Science, and the Cochrane Library published by October 2022. We performed a meta-analysis on untargeted and targeted metabolomics research data, using the ratio of means as the effect size. We compared changes in metabolite levels between patients with varying severity and controls and investigated sources of heterogeneity through subgroup analyses and meta-regression analysis.RESULTS: We included 22 cohorts from 21 studies, comprising 2421 participants, including COVID-19 patients of varying severity and healthy controls. We conducted meta-analysis and heterogeneity analysis on the 1058 metabolites included in the study. The results indicated that, compared to the healthy control group, 23 biomarkers were associated with mild cases (P < 0.05), 3 biomarkers with moderate cases (P < 0.05), and 37 biomarkers with severe cases (P < 0.05). Pathway enrichment analysis revealed significant disturbances in amino acid metabolism, aminoacyl-tRNA biosynthesis, primary bile acid biosynthesis, pantothenate and CoA biosynthesis, the tricarboxylic acid cycle, taurine and hypotaurine metabolism, and nitrogen metabolism in patients with mild, moderate, and severe disease. Additionally, we found that each severity stage exhibited unique metabolic patterns (all P < 0.05) and that the degree of metabolic dysregulation progressively worsened with increasing disease severity (P < 0.05).CONCLUSIONS: The results of our meta-analysis indicate the similarities and differences of biomarkers and metabolic characteristics of patients with different severity in COVID-19, thereby providing new pathways for the study of pathogenesis, the development precise treatment, and the formulation of comprehensive strategies.REGISTRATION: PROSPERO: CRD42022369937.PMID:40019163 | DOI:10.7189/jogh.15.04056

Food Funct. 2025 Feb 28. doi: 10.1039/d4fo05757k. Online ahead of print.ABSTRACTMethionine restriction has received some attention in recent years as a novel mode of dietary intervention. Our previous study found that methionine restriction could inhibit the celiac toxic effects of wheat gluten in an in vitro model. However, the role of methionine restriction in gluten-induced celiac intestinal damage remains unclear. The aim of this study was to explore whether dietary methionine restriction could suppress the celiac toxic effects of gluten in an in vivo model, thereby mitigating intestine damage. This study systematically investigated the effects of dietary methionine restriction on celiac characteristic indicators such as symptoms, small intestine damage, and intestinal TG2 and IL-15 expression in a gluten-induced C57BL/6 mouse model. The availability of dietary methionine restriction in different ages (adolescent and adult) was also evaluated. Moreover, mouse cecum contents were assayed and co-analyzed for the metagenome of intestinal flora and target short-chain fatty acid metabolomics, with the goal of further exploring and elucidating critical pathways by which dietary methionine restriction plays a role. We discovered that dietary methionine restriction could effectively ameliorate the gluten-induced celiac-associated small intestine damage by modulating intestinal flora to inhibit butyric acid production. Specifically, dietary methionine restriction could inhibit butyric acid production with the help of s_CAG-485 sp002493045 and s_CAG-475 sp910577815, which in turn affected the mitochondrial function within the intestinal epithelial cells to assist in the repair of intestine damage. This study might provide new insights into modulating dietary patterns to mitigate intestinal damage in celiac disease and the production of novel gluten-free products.PMID:40018976 | DOI:10.1039/d4fo05757k

Mol Nutr Food Res. 2025 Feb 28:e70003. doi: 10.1002/mnfr.70003. Online ahead of print.ABSTRACTFecal volatile organic compounds (VOCs) offer insights into gut microbiota function that may drive the pathogenesis of ulcerative colitis (UC). This cross-sectional study aimed to compare dietary intake and VOC patterns in UC patients with an ileoanal pouch compared to those with an intact colon. Seven-day food records and fecal samples were collected from UC patients with an intact colon (n = 28) or an ileoanal pouch (n = 11). Fecal VOC profiles were analyzed using gas chromatography-mass spectrometry. Dietary intake in both groups was largely similar. The mean Jaccard similarity index of VOC was 0.55 (95% CI:0.53, 0.56) in the pouch compared with 0.48 (0.47, 0.49) in the colon group (p < 0.01). A lower proportion of VOC classes was detected in the pouch, including sulfide (9% vs. 57%; p < 0.01), branched-chain fatty acids (BCFAs; 45%-64% vs. 93%-96%; p < 0.01), and ketones (45%-64% vs. 93%-96%; p < 0.01), along with a higher proportion of butyric acid (91% vs. 29%; p < 0.001). Unrelated to diet, VOC profiles show less functional diversity, reduced protein and greater carbohydrate fermentation, and altered production of secondary metabolites in the UC-pouch compared with the intact colon. These differences in the metabolic environment of the gut microbiota provide insights into pathogenesis and suggest that microbial-targeted interventions should be tailored accordingly.PMID:40018833 | DOI:10.1002/mnfr.70003

Biomed Chromatogr. 2025 Apr;39(4):e70040. doi: 10.1002/bmc.70040.ABSTRACTBile-processed Coptidis Rhizoma (BPCR) exhibits stronger efficacy in treating T2DM than Coptidis Rhizoma(CR) alone. However, the synergistic mechanism of its processing remains unknown. This study utilized HPLC to determine the content and dissolution characteristics of alkaloid components in BPCR before and after processing. The results indicated that the diffusion of the alkaloids in BPCR is stronger than that of CR, and their dissolution conforms to the Weibull equation. Additionally, BPCR significantly reduced fasting blood glucose (FBG) and serum insulin (FINS) levels in T2DM rats induced by a high-fat diet (HFD) and streptozotocin (STZ), improved glucose and lipid metabolism, and mitigated liver damage. Serum metabolomics analysis based on UPLC-Q-TOF-MS revealed that BPCR significantly regulates 27 endogenous differential biomarkers. The underlying mechanism may be related to glycerophospholipid metabolism, linoleic acid metabolism, steroid biosynthesis, and arachidonic acid metabolism pathways.PMID:40018812 | DOI:10.1002/bmc.70040

Mol Nutr Food Res. 2025 Feb 28:e70007. doi: 10.1002/mnfr.70007. Online ahead of print.ABSTRACTThis study investigates the metabolic impact of skim milk whey-derived protein concentrate (SPC) for infant formula, including its heat-treated (HT-SPC) and stored (HTS-SPC) variants, on the plasma, urine, and gut metabolites of newborn piglets, compared to conventional whey protein concentrate (WPC). Preterm piglets were fed formula containing WPC, SPC, HT-SPC, or HT-SPC, HTS-SPC for 5 days. Metabolomic analysis of plasma, urine, and colon content was performed using 1H NMR. Relative to WPC, SPC mainly affected colon content metabolites, increasing 19 metabolites in the colon and tyrosine in plasma, while decreasing pyruvate in colon content and glycine in plasma. Heat-treatment and storage of SPC led to increased metabolite concentrations in colon contents and urine. Notably, significant correlations between gut metabolites and abundant gut bacteria genes were observed only in the SPC-fed pigs. SPC induced higher branched chain amino acid concentrations in the gut, but had minimal effects on plasma and urinary metabolites, likely due to differences in dietary proteins and in microbiota metabolism. While the clinical effects of SPC-induced gut branched chain amino acids remain unclear, the results from our study suggest that SPC-based infant formula is metabolically safe for sensitive newborns, comparable to WPC-based formulas.PMID:40018800 | DOI:10.1002/mnfr.70007

Cancer Med. 2025 Mar;14(5):e70730. doi: 10.1002/cam4.70730.ABSTRACTBACKGROUND: Esophageal squamous cell carcinoma (ESCC) is a predominant and highly lethal form of esophageal cancer, with a five-year survival rate below 20%. Despite advancements, most patients are diagnosed at advanced stages, limiting effective treatment options. Multi-omics integration, encompassing somatic genomic alterations, inherited genetic mutations, transcriptomics, proteomics, metabolomics, and single-cell sequencing, has enabled the identification of distinct molecular subtypes of ESCC.METHOD: This article systematically reviewed the current status of molecular subtyping of ESCC based on big data, summarized unique subtypes with differing treatment responses and prognostic outcomes.RESULT: Key findings included subtype-specific genetic mutations, signaling pathway alterations, and metabolomic profiles, which offer novel biomarkers and therapeutic targets. Furthermore, this review discusses the link between molecular subtypes and immunotherapy efficacy, chemotherapy response, and drug development.CONCLUSION: These insights highlight the potential of omics-based molecular typing to transform ESCC management and facilitate personalized treatment strategies.PMID:40018789 | DOI:10.1002/cam4.70730

Research (Wash D C). 2023 Feb 27;8:0629. doi: 10.34133/research.0629. eCollection 2025.ABSTRACTFamilial hypercholesterolemia (FH) is a lipoprotein disorder characterized by elevated plasma levels of low-density lipoprotein cholesterol (LDL-C) and an increased risk of premature atherosclerotic cardiovascular disease. Recent evidences have shown that several glycerophospholipid species were markedly altered in experimental FH animals and exhibited diverse bioactivities. Nevertheless, the glycerophospholipid profiles and their associated biological implications in human FH remain largely unknown. In this study, we sought to comprehensively delineate the glycerophospholipid phenotypes in human FH and to investigate the functional roles of key FH-altered glycerophospholipid molecules on cholesterol metabolism. Targeted analysis of 328 glycerophospholipid metabolites was used to profile the differentiated alterations in patients with homozygous FH (HoFH; n = 181), heterozygous FH (HeFH; n = 452), and non-FH hypercholesterolemia (n = 382). Our findings revealed that the glycerophospholipid phenotypes of FH and non-FH hypercholesterolemia were dominated by a spectrum of metabolites involved in the lysophosphatidic acid (LPA) metabolism. Among the LPA features, palmitoyl-LPA (16:0) showed significant association with the clinical levels of LDL-C and total cholesterol in HoFH and HeFH populations. Using functional metabolomic strategy and murine FH model, we demonstrated that supplementation with LPA 16:0 elevated the plasma levels of LDL and free/esterified cholesterol and exacerbated the atherosclerotic lesions. Conversely, inhibition of autotaxin-mediated LPA 16:0 production significantly ameliorated dyslipidemia. Mechanistically, we uncovered that LPA 16:0 could disrupt hepatic cholesterol homeostasis by impairing cholesterol excretion and inhibiting primary bile acid synthesis. In summary, our study offers novel insights into lipid metabolism in human FH and posits that targeting LPA metabolism may represent a promising therapeutic strategy for reducing cholesterol levels in the FH population.PMID:40018730 | PMC:PMC11865365 | DOI:10.34133/research.0629

Front Vet Sci. 2025 Feb 13;12:1496946. doi: 10.3389/fvets.2025.1496946. eCollection 2025.ABSTRACTINTRODUCTION: Understanding the impact of housing conditions on the stress responses in farmed saltwater crocodiles (Crocodylus porosus) is crucial for optimizing welfare and management practices.METHODS: This study employed a multi-omics methodology, combining targeted and untargeted LC-MS for metabolite, lipid, and hormone profiling with 16S rRNA gene sequencing for microbiome analysis, to compare stress responses and changes in fecal samples of crocodiles housed in single versus group pens. Metabolic responses to a startle test were evaluated through multivariate analysis, and changes post-stress were examined.RESULTS: A total of 564 metabolic features were identified. Of these, 15 metabolites were linked to the cortisol biosynthesis pathway. Metabolite origin analysis showed that 128 metabolites originated from the host, 151 from the microbiota, and 400 remained unmatched. No significant differences in fecal corticosterone levels were observed between single and group pens. However, metabolic profiling revealed distinct differences in stress responses: single pen crocodiles exhibited downregulation of certain compounds and upregulation of others, affecting pyrimidine and purine metabolism pathways when compared to grouped pen crocodiles, linked to altering energy associated induced stress. Additionally, fecal microbiome analysis indicated increased Firmicutes:Bacteroides (F:B) ratio in group-housed animals, suggesting greater stress.DISCUSSION: The study highlights that while traditional stress indicators like corticosterone levels may not differ significantly between housing conditions, metabolic and microbiome analyses provide deeper insights into stress responses. Single pens are associated with less metabolic disruption and potentially better health outcomes compared to group pens. These findings underscore the value of fecal microbiome and metabolomics in assessing animal welfare in farmed crocodiles.PMID:40018705 | PMC:PMC11865912 | DOI:10.3389/fvets.2025.1496946