Analysis Of Serum Metabolites Research Articles

Decoding polyphenol metabolism in patients with Crohn’s disease: Insights from diet, gut microbiota, and metabolites

Crohn’s disease (CD) is a chronic and progressive inflammatory disease that can involve any part of the gastrointestinal tract. The protective role of dietary polyphenols has been documented in preclinical models of CD. Gut microbiota mediates the metabolism of polyphenols and affects their bioactivity and physiological functions. However, it remains elusive the capacity of microbial polyphenol metabolism in CD patients and healthy controls (HCs) along with its correlation with polyphenols intake and polyphenol-derived metabolites. Thus, we aimed to decode polyphenol metabolism in CD patients through aspects of diet, gut microbiota, and metabolites. Dietary intake analysis revealed that CD patients exhibited decreased intake of polyphenols. Using metagenomic data from two independent clinical cohorts (FAH-SYSU and PRISM), we quantified abundance of polyphenol degradation associated bacteria and functional genes in CD and HCs and observed a lower capacity of flavonoids degradation in gut microbiota residing in CD patients. Furthermore, through analysis of serum metabolites and enterotypes in participants of FAH-SYSU cohort, we observed that CD patients exhibited reduced levels of serum hippuric acid (HA), one of polyphenol-derived metabolites. HA level was higher in healthier enterotypes (characterized by dominance of Ruminococcaceae and Prevotellaceae, dominant by HCs) and positively correlated with multiple polyphenols intake and abundance of bacteria engaged in flavonoids degradation as well as short-chain fatty acid production, which could serve as a biomarker for effective polyphenol metabolism by the gut microbiota and a healthier gut microbial community structure. Overall, our findings provide a foundation for future work exploring the polyphenol-based or microbiota-targeted therapeutic strategies in CD.

LC-MS metabolomics analysis of serum metabolites during neoadjuvant chemoradiotherapy in locally advanced rectal cancer.

This study aimed to investigate the serum metabolite profiles during neoadjuvant chemoradiotherapy (NCRT) in locally advanced rectal cancer (LARC) using liquid chromatography-mass spectrometry (LC-MS) metabolomics analysis. 60 serum samples were collected from 20 patients with LARC before, during, and after radiotherapy. LC-MS metabolomics analysis was performed to identify the metabolite variations. Functional annotation was applied to discover altered metabolic pathways. The key metabolites were screened and their ability to predict sensitivity to radiotherapy was calculated using random forests and ROC curves. The results showed that NCRT led to significant changes in the serum metabolite profiles. The serum metabolic profiles showed an apparent separation between different time points and different sensitivity groups. Moreover, the functional annotation showed that the differential metabolites were associated with a series of important metabolic pathways. Pre-radiotherapy (3Z,6Z)-3,6-Nonadiena and pro-radiotherapy 1-Hydroxyibuprofen showed good predictive performance in discriminating the sensitive and non-sensitive group to NCRT, with an AUC of 0.812 and 0.75, respectively. Importantly, the combination of different metabolites significantly increased the predictive ability. This study demonstrated the potential of LC-MS metabolomics for revealing the serum metabolite profiles during NCRT in LARC. The identified metabolites may serve as potential biomarkers and therapeutic targets for the management of this disease. Furthermore, the understanding of the affected metabolic pathways may help design more personalized therapeutic strategies for LARC patients.

Analysis of differential metabolites in serum metabolomics of patients with aortic dissection

BackgroundPathogenesis and diagnostic biomarkers of aortic dissection (AD) can be categorized through the analysis of differential metabolites in serum. Analysis of differential metabolites in serum provides new methods for exploring the early diagnosis and treatment of aortic dissection.ObjectivesThis study examined affected metabolic pathways to assess the diagnostic value of metabolomics biomarkers in clients with AD.MethodThe serum from 30 patients with AD and 30 healthy people was collected. The most diagnostic metabolite markers were determined using metabolomic analysis and related metabolic pathways were explored.ResultsIn total, 71 differential metabolites were identified. The altered metabolic pathways included reduced phospholipid catabolism and four different metabolites considered of most diagnostic value including N2-gamma-glutamylglutamine, PC(phocholines) (20:4(5Z,8Z,11Z,14Z)/15:0), propionyl carnitine, and taurine. These four predictive metabolic biomarkers accurately classified AD patient and healthy control (HC) samples with an area under the curve (AUC) of 0.9875. Based on the value of the four different metabolites, a formula was created to calculate the risk of aortic dissection. Risk score = (N2-gamma-glutamylglutamine × -0.684) + (PC (20:4(5Z,8Z,11Z,14Z)/15:0) × 0.427) + (propionyl carnitine × 0.523) + (taurine × -1.242). An additional metabolic pathways model related to aortic dissection was explored.ConclusionMetabolomics can assist in investigating the metabolic disorders associated with AD and facilitate a more in-depth search for potential metabolic biomarkers.

Effect of Lactiplantibacillus plantarum CCFM8661 on serum metabolites and gut microbiota in a lead-exposed population

In this study, we investigated the impact of Lactiplantibacillus plantarum (L. plantarum) CCFM8661 on the gut microbiota, and the serum and fecal metabolomes in lead (Pb)-exposed individuals. The volunteers recruited for this study were divided into two treatment groups, (i) the placebo (control) and (ii) the L. plantarum CCFM8661 treatment groups. The analysis revealed that probiotic intervention reversed some of the changes in Pb exposure-induced intestinal bacterial abundance, including the abundance of Parabacteroides, Bacteroides, Clostridiaceae, and Erysipelotrichaceae. An analysis of the fecal metabolome identified 26 differential metabolites involved in purine metabolism, unsaturated fatty acid metabolism, and other pathways. Serum metabolite analysis showed that L. plantarum CCFM8661 treatment altered the serum metabolite levels of various metabolic pathways, such as the glycerophospholipid, amino acid, and glutathione metabolism pathways. These results suggest that L. plantarum CCFM8661 may have beneficial effects on Pb-exposed populations by modulating the gut microbiota, host serum metabolism, and the metabolism of the gut microbiota.

Long-term physical inactivity induces significant changes in biochemical pathways related to metabolism of proteins and glycerophospholipids in mice.

Physical inactivity affects multiple organ systems, including the musculoskeletal system, which upsets the delicate balance of several secretory factors leading to metabolic derailment. This reduces contractile recruitment of the skeletal muscle with dampening of its oxidative capacity resulting in impaired intramuscular lipid metabolism and substrate utilization. We hypothesized that this altered phenotype would also have an indispensable effect on circulatory cytokines and the level of metabolic intermediates. In this study, comparison between sedentary (SED) and exercised (EXER) animal models showed that organismal metabolic parameters (body mass, oxygen utilization and glucose tolerance) are altered based on physical activity. Our data suggest that cytokines linked to glycemic excursions (insulin, c-peptide, glucagon) and their passive regulators (leptin, BDNF, active ghrelin, and GIP) exhibit changes in the SED group. Furthermore, some of the proinflammatory cytokines and myokines were upregulated in SED. Interestingly, serum metabolite analysis showed that the levels of glucogenic amino acids (alanine, glycine, tryptophan, proline and valine), nitrogenous amino acids (ornithine, asparagine, and glutamine) and myogenic metabolites (taurine, creatine) were altered due to the level of physical activity. A pyrimidine nucleoside (uridine), lipid metabolite (glycerol) and ketone bodies (acetoacetate and acetate) were found to be altered in SED. A Spearman rank correlation study between SED and CTRL showed that cytokines build a deformed network with metabolites in SED, indicating significant modifications in amino acids, phosphatidylinositol phosphate and glycerophospholipid metabolic pathways. Overall, long-term physical inactivity reorganizes the profile of proinflammatory cytokines, glucose sensing hormones, and protein and glycerophospholipid metabolism, which might be the initial factors of metabolic diseases due to SED.

Metabolomic Insights into the Pathogenesis and Prognostic Potential of Adult Acute Lymphoblastic Leukemia

Acute lymphoblastic leukemia (ALL) comprises hematological malignancies affecting B or T cell precursors (BCP-ALL or T-ALL). Despite considerable progress made over the past three decades in the treatment of childhood ALL [5-year disease survival rate (5-y DFS): 90%], the prognosis of adult ALL remains relatively poor (5-y DFS: 50-70%). Hence, gaining a deeper understanding of the pathogenic factors is of timely importance. Recent advancements in next-generation genome sequencing technologies have facilitated the refinement of disease diagnosis and prognosis. However, due to the inherent genetic diversity among patients, additional tools are needed to unravel the complex etiological basis and improve risk stratification for personalized therapeutic interventions, particularly in adult ALL. Metabolomics offers a powerful approach that enables the comprehensive exploration of cellular states by analyzing metabolites quantitatively and qualitatively, which reflects altered enzyme kinetic activities and changes in metabolic reactions. It was previously reported that most bone marrow metabolites could be detected in plasma in BCP-ALL (81%). In this study, we reported an integrated analysis of serum metabolites using liquid chromatography/mass spectrometry as well as the metabolic gene expression profiles from RNA-sequencing data of bone marrow blasts, generating a comprehensive metabolic information dataset (CMID) in 211 adult ALL patients (BCP-ALL: n=160; T-ALL: n=51) who participated in our recent clinical trial (ChiCTR-ONRC-14004968). The graphical abstract is depicted in Figure 1A. Serum metabolomic landscape of adult ALL was obtained at various time points during treatment, including samples at diagnosis (Day 0, D0, n=198), during the induction phase (D14, n=177 and D28, n=147) and the early consolidation phase (Cons, n=58). These samples were subject to comparison to those from 164 age/sex-matched healthy controls (HC). Using CMID, we further subtyped BCP-ALL (clusters BC1 and BC2, and a special cluster of Ph + ALL) and T-ALL (clusters TC1 and TC2), revealing that BC2 and TC1 were associated with relatively favorable outcome, compared respectively to BC1 (OS: P<0.05) and TC2 (OS: P<0.05). Regarding serum metabolomic profiles over the treatment course, we found a number of featured disturbances ( Figure 1B). Aberrant lipid-related metabolisms, such as steroid metabolism, were detectable throughout different phases. In contrast, the metabolism of amino acids and a number of metabolites pumped by ATP-binding cassette transporter were severely impacted by therapeutic agents during the induction phase (on D14). Notably, at the time of diagnosis, primary bile acid biosynthesis was enriched, consistent with a previous study on pediatric ALL. In our functional experiment, inhibiting the synthesis of bile acid precursors such as cholesterol with Simvastatin suppressed leukemic cell viability in 10 ALL cell lines, indicating a potential role of this pathway in leukemogenesis. In addition, we identified arachidonic acid (AA) metabolism enrichment in the favorable BC2 subgroup. Coincidentally, glycerophospholipid metabolism, which provides substrates for AA synthesis, was also enriched in the TC1 subgroup, together with an active AA metabolism. Increasing data suggests that AA metabolites act as immunoregulators in cancer, thus we hypothesize that they could play a role in ALL prognosis by regulating the immune reaction against leukemic cells in the hematopoietic microenvironment. In our further efforts to address the correlation between CMID-based subtypes and known genetic events in Ph --BCP-ALL and T-ALL leukemogenesis, we discovered that some favorable genetic markers (ZNF-384/362 fusions and high ploidy) tended to fall into BC2, while NRAS mutations were only observed in TC1. On the other hand, both CMID-based subtypes and genetic events-based ones stand as independent factors in multivariate Cox analysis for risk stratification of BCP-ALL, demonstrating an added value of the CMID subtypes in the prognosis of adult BCP-ALL. Our work has thus highlighted the significance of altered metabolome in ALL pathogenesis, proved its clinical relevance for prognosis stratification, and identified its potential vulnerabilities for improving tailored therapy.

The Effects of Milk Replacer Supplemented with Ascophyllum nodosum as a Novel Ingredient to Prevent Neonatal Diarrhea in Dairy Calves and Improve Their Health Status.

Nutrition and health during pre-weaning affect the calves' future fertility, calving age, production, and carrier length. Calves are highly susceptible to neonatal calf diarrhea (NCD), which can be fatal. NCD is due to hypovolemia and acidosis, which may involve anorexia and ataxia. The One Health principle calls for a drastic reduction in antimicrobial use. One approach is to improve animal health and reduce the use of antibiotics and functional ingredients that have beneficial effects due to bioactive compounds. Several functional ingredients and additives can be considered, and, in particular for this study, Ascophyllum nodosum was considered. The present study aimed to evaluate the role of A. nodosum as a functional ingredient implemented into the milk replacer in neonatal calves. Twelve pre-weaned Holstein Frisian calves, housed in twelve individual pens in the same environmental conditions, were divided into two groups of six animals: a control group (CTRL, n = 6) fed with a milk replacer, and a treatment group receiving milk enriched with 10 g of A. nodosum in their diet (TRT, n = 6) for 42 days. The fecal score was evaluated daily (3-0 scale) to monitor the incidence of diarrhea in the two groups. The body weight was evaluated weekly, and every two weeks feces were collected for microbiological evaluation using a selective medium for plate counting of total, lactic acid, and coliform bacteria. To verify the presence of Lactobacillus, Bifidobacterium, and Escherichia coli, real-time qPCR was used. At the beginning and at the end of the trial, blood samples were obtained for serum metabolite analysis. The growth performance did not differ in either of the two groups, but significant differences were observed in the incidence of moderate diarrhea (p-value < 0.0113), where the TRT group showed a lower incidence of cases during the 42-day period. Serum analysis highlighted higher contents of albumin, calcium, phosphorus, and total cholesterol in the TRT group compared to CTRL (p-value < 0.05). In conclusion, implementation of A. nodosum in the diet of calves can lead to better animal welfare and may reduce the use of antibiotics.

Metabolomics analysis of serum metabolites during endometrial transformation: association with recurrent implantation failure in hormonal replacement therapy-frozen embryo transfers cycles.

The purpose of this study was to investigate alterations in serum metabolites during endometrial transformation and possibleassociations with recurrent implantation failure (RIF) in hormonal replacement therapy (HRT)-frozen embryo transfer (FET) cycles. We performed a prospective study involving 100 patients scheduled for HRT-FET cycles during January 2022 to April 2022. Blood serum samples were collected on the day of progesterone administration (dPA) and on the third day of progesterone administration (d3PA). Gas chromatography-mass spectrometry (GC-MS) analysis was performed to identify and quantify serum metabolites. A nested case-control study including 19 RIF patients and 19 matching controls was conducted to explore the predictive value of serum metabolites for RIF. Partial least squares discriminant analysis (PLS-DA) and receiver operating characteristic (ROC) curve analysis were performed to establish prediction models. We identified 105 serum metabolites, with 76 of them exhibiting significant alterations during the initial 3 days of endometrial transformation. Metabolites involved in amino acid metabolism and tricarboxylic acid (TCA) cycle showed lower levels during endometrial transformation. In the nested case-control study, the prediction model based on the ratio of serum metabolites between d3PA and dPA showed the highest area under the ROC curve (AUC), accuracy, and R2 and Q2 values. Eight metabolites, including indol-3-propionic acid, beta-alanine, myristoleic acid, malic acid, indole, DL-isocitric acid, proline, and itaconic acid, exhibited high predictive values for RIF. This study demonstrates alterations in serum metabolites during endometrial transformation, particularly in amino acid metabolism and TCA cycle. The identified metabolites, especially indol-3-propionic acid and malic acid, show potential as predictive markers for RIF. These findings contribute to a better understanding of the metabolic changes associated with endometrial receptivity and provide insights for the development of personalized approaches to improve implantation outcomes in FET cycles.

Urinary microbiota and serum metabolite analysis in patients with diabetic kidney disease

BackgroundDiabetic kidney disease (DKD) is a common and potentially fatal consequence of diabetes. Chronic renal failure or end-stage renal disease may result over time. Numerous studies have demonstrated the function of the microbiota in health and disease. The use of advanced urine culture techniques revealed the presence of resident microbiota in the urinary tract, undermining the idea of urine sterility. Studies have demonstrated that the urine microbiota is related with urological illnesses; nevertheless, the fundamental mechanisms by which the urinary microbiota influences the incidence and progression of DKD remain unclear. The purpose of this research was to describe key characteristics of the patients with DKD urinary microbiota in order to facilitate the development of diagnostic and therapeutic for DKD. MethodsWe evaluated the structure and composition of the microbiota extracted from urine samples taken from DKD patients (n = 19) and matched healthy controls (n = 15) using 16S rRNA gene sequencing. Meanwhile, serum metabolite profiles were compared using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Associations between clinical characteristics, urine microbiota, and serum metabolites were also examined. Finally, the interaction between urine microbiota and serum metabolites was clarified based on differential metabolite abundance analysis. ResultsThe findings indicated that the DKD had a distinct urinary microbiota from the healthy controls (HC). Taxonomic investigations indicated that the DKD microbiome had less alpha diversity than a control group. Proteobacteria and Acidobacteria phyla increased in the DKD, while Firmicutes and Bacteroidetes decreased significantly (P < 0.05). Acidobacteria was the most prevalent microbiota in the DKD, as determined by the Linear discriminant analysis Effect Size (LEfSe) plot. Changes in the urinary microbiota of DKD also had an effect on the makeup of metabolites. Short-chain fatty acids (SCFAs) and protein-bound uremic toxins (PBUTs) were shown to be specific. Then we discovered that arginine and proline metabolism was the primary mechanism involved in the regulation of diabetic kidney disease. ConclusionsThis study placed the urinary microbiota and serum metabolite of DKD patients into a functional framework and identified the most abundant microbiota in DKD (Proteobacteria and Acidobacteria). Arginine metabolites may have a major effect on DKD patients, which correlated with the progression of DKD.

Serum metabolomic signatures of fatty acid oxidation defects differentiate host-response subphenotypes of acute respiratory distress syndrome

BackgroundFatty acid oxidation (FAO) defects have been implicated in experimental models of acute lung injury and associated with poor outcomes in critical illness. In this study, we examined acylcarnitine profiles and 3-methylhistidine as markers of FAO defects and skeletal muscle catabolism, respectively, in patients with acute respiratory failure. We determined whether these metabolites were associated with host-response ARDS subphenotypes, inflammatory biomarkers, and clinical outcomes in acute respiratory failure.MethodsIn a nested case–control cohort study, we performed targeted analysis of serum metabolites of patients intubated for airway protection (airway controls), Class 1 (hypoinflammatory), and Class 2 (hyperinflammatory) ARDS patients (N = 50 per group) during early initiation of mechanical ventilation. Relative amounts were quantified by liquid chromatography high resolution mass spectrometry using isotope-labeled standards and analyzed with plasma biomarkers and clinical data.ResultsOf the acylcarnitines analyzed, octanoylcarnitine levels were twofold increased in Class 2 ARDS relative to Class 1 ARDS or airway controls (P = 0.0004 and < 0.0001, respectively) and was positively associated with Class 2 by quantile g-computation analysis (P = 0.004). In addition, acetylcarnitine and 3-methylhistidine were increased in Class 2 relative to Class 1 and positively correlated with inflammatory biomarkers. In all patients within the study with acute respiratory failure, increased 3-methylhistidine was observed in non-survivors at 30 days (P = 0.0018), while octanoylcarnitine was increased in patients requiring vasopressor support but not in non-survivors (P = 0.0001 and P = 0.28, respectively).ConclusionsThis study demonstrates that increased levels of acetylcarnitine, octanoylcarnitine, and 3-methylhistidine distinguish Class 2 from Class 1 ARDS patients and airway controls. Octanoylcarnitine and 3-methylhistidine were associated with poor outcomes in patients with acute respiratory failure across the cohort independent of etiology or host-response subphenotype. These findings suggest a role for serum metabolites as biomarkers in ARDS and poor outcomes in critically ill patients early in the clinical course.

Identification of Serum Metabolites as Prognostic Biomarkers Following Spinal Cord Injury: A Pilot Study

The assessment, management, and prognostication of spinal cord injury (SCI) mainly rely upon observer-based ordinal scales measures. 1H nuclear magnetic resonance (NMR) spectroscopy provides an effective approach for the discovery of objective biomarkers from biofluids. These biomarkers have the potential to aid in understanding recovery following SCI. This proof-of-principle study determined: (a) If temporal changes in blood metabolites reflect the extent of recovery following SCI; (b) whether changes in blood-derived metabolites serve as prognostic indicators of patient outcomes based on the spinal cord independence measure (SCIM); and (c) whether metabolic pathways involved in recovery processes may provide insights into mechanisms that mediate neural damage and repair. Morning blood samples were collected from male complete and incomplete SCI patients (n = 7) following injury and at 6 months post-injury. Multivariate analyses were used to identify changes in serum metabolic profiles and were correlated to clinical outcomes. Specifically, acetyl phosphate, 1,3,7-trimethyluric acid, 1,9-dimethyluric acid, and acetic acid significantly related to SCIM scores. These preliminary findings suggest that specific metabolites may serve as proxy measures of the SCI phenotype and prognostic markers of recovery. Thus, serum metabolite analysis combined with machine learning holds promise in understanding the physiology of SCI and aiding in prognosticating outcomes following injury.

A multi-angle analysis of injury induced by supplementation of soybean meal in Litopenaeus vannamei diets

Soybean meal is considered as one of the major components of Litopenaeus vannamei diets. However, most previous studies have focused on evaluating the effects of soybean meal on L. vannamei from the perspective of growth, physiology, and feed utilization; information regarding the analysis of serum metabolites, antioxidant and immune response, and intestinal microbiota is limited. Five diets were prepared, comprising 20% (T20), 28% (T28), 35% (T35), 42% (T42), and 50% (T50) soybean meal. A total of 600 shrimp were randomly distributed into 20 tanks (i.e., 30 shrimp per tank), with four tanks assigned to each dietary group. Shrimp were fed to apparent satiation during the 42-day feeding trial. The results showed that levels of serum globulin, alanine aminotransferase, and aspartate aminotransferase linearly increased (p &amp;lt; 0.01), but levels of high-density lipoprotein cholesterol linearly decreased (p &amp;lt; 0.001) as the proportion of soybean meal in the diet increased. Supplementation of shrimp diets with soybean meal linearly and quadratically increased (p &amp;lt; 0.05) serum total antioxidant capacity, levels of malondialdehyde, and activities of catalase, nitric oxide synthase and phenoloxidase. Hepatocytes in T35, T42, and T50 were shown to have different degrees of vacuolar degeneration, hepatic corpuscle atrophy, and star-like lumen loss. Dietary inclusion of soybean meal altered the composition of intestinal bacterial microbiota at phylum level, especially increasing the abundance of on other bacterial genera, whereas it had minimal impact on other bacterial genera and had no significant influence on the bacterial diversity. This study suggests that dietary supplementation of L. vannamei diets with soybean meal at concentrations exceeding 28% induces inflammation and oxidant damage of the hepatopancreas, and increases the risk of intestinal disease.

Identification of metabolite shifts and early serum predictors for indicators of remodelling in diabetes and nondiabetic models of cardiac hypertrophy

Background: Cardiac hypertrophy (CH) is the asymptomatic enlargement of ventricular walls witnessed in diabetes and hypertension, for which early metabolite differences and prediction are less stated previously. Aim: The aim of the study was (i) to understand the metabolic and ventricular events in diabetes and nondiabetes induced CH at the end of 2 weeks and (ii) to identify significant metabolite predictors and pathways that influence the seven metabolic and physiological responders of CH, namely, 3-hydroxybutyrate (3-HB); lactic acid; urea; and electrocardiography (ECG) waves (QRS complex, R amplitude, R-R interval, and heart rate). Methods: Diabetic rat models of CH using streptozotocin (40 mg/kg, i. p., single dose), and nondiabetic models using adrenaline (0.3 mg/kg, i. p, 2 weeks) were developed. Blood glucose levels, ECG, heart weight/body weight ratio, histopathological analysis, and serum metabolite analysis using gas chromatography mass spectrometry were performed at the end of 2 weeks. Strong metabolite predictors and pathways were identified using Pearson's correlation, multiple regression (MRA) and metabolite set enrichment (MSEA) analyses. Results: The prevalence of CH was observed through preliminary screenings at the end of 2 weeks. Galactose, leucine, erythrose, sorbitol, and valine were identified as significant (P < 0.05) predictors in SZ model, whereas isoleucine, galactose, leucine, inositol, and palmitic acid were identified in ADR model. However, galactose metabolism, branched-chain amino acid, and lactose degradation pathways were mapped as the highly influential apparent pathways during early CH remodeling in both the models. Conclusion: This study identified putative initial metabolite shifts, significant predictors pathways that can aid in forecasting, intervention, and prevention of CH.

Modulating gut microbiota and metabolites with dietary fiber oat β-glucan interventions to improve growth performance and intestinal function in weaned rabbits.

The effect of oat β-glucan on intestinal function and growth performance of weaned rabbits were explored by multi-omics integrative analyses in the present study. New Zealand White rabbits fed oat β-glucan [200 mg/kg body weight (BW)] for 4 weeks, and serum markers, colon histological alterations, colonic microbiome, colonic metabolome, and serum metabolome were measured. The results revealed that oat β-glucan increased BW, average daily gain (ADG), average daily food intake (ADFI), and decreased serum tumor necrosis factor-α (TNF-α) interleukin-1β (IL-1β), and lipopolysaccharide (LPS) contents, but did not affect colonic microstructure. Microbiota community analysis showed oat β-glucan modulated gut microbial composition and structure, increased the abundances of beneficial bacteria Lactobacillus, Prevotellaceae_UCG-001, Pediococcus, Bacillus, etc. Oat β-glucan also increased intestinal propionic acid, valeric acid, and butyric acid concentrations, decreased lysine and aromatic amino acid (AAA) derivative contents. Serum metabolite analysis revealed that oat β-glucan altered host carbohydrate, lipid, and amino acid metabolism. These results suggested that oat β-glucan could inhibit systemic inflammation and protect intestinal function by regulating gut microbiota and related metabolites, which further helps to improve growth performance in weaned rabbits.

Human blood metabolites and lacunar stroke: A Mendelian randomization study.

Lacunar stroke accounts for a quarter of all strokes, but little is known about the underlying pathological mechanisms. Analysis of serum metabolites may allow better understanding of the underlying biological processes. Mendelian randomization (MR) can provide information on the causality of associations. To identify causal relationships between serum metabolites and lacunar stroke. We applied a two-sample MR analysis to evaluate relationships between 486 serum metabolites and lacunar stroke. The inverse-variance weighted (IVW) method was used to estimate the causal relationship of the exposure on the outcome, while sensitivity analyses were performed using MR-Egger, weighted median, and MR-PRESSO to eliminate the pleiotropy. We also performed a metabolic pathway analysis to identify potential metabolic pathways. We identified 15 known (8 risk and 7 protective) and 14 unknown serum metabolites associated with lacunar stroke. Among the known risk metabolites, two were lipids (1-linoleoylglycerophosphoethanolamine and dihomo-linolenate (20:3n3 or n6)), five amino acids (kynurenine, isobutyrylcarnitine, aspartate, trans-4-hydroxyproline, and 3-methyl-2-oxovalerate), and one peptide (ADSGEGDFXAEGGGVR). The known protective metabolites included four lipids (4-androsten-3beta,17beta-diol disulfate 1, 1-palmitoleoylglycerophosphocholine, adrenate (22:4n6), and glycodeoxycholate), one amino acid (methionine), and two exogenous metabolites (homostachydrine and 2-methoxyacetaminophen sulfate). Metabolic pathway analysis identified several pathways that might be involved in the disease. We identified eight risk and seven protective human serum metabolites associated with lacunar stroke. Isobutyrylcarnitine was positively associated with an increased risk of lacunar stroke. In addition, 3-methyl-2-oxovalerate and aspartate may be involved in the disease pathogenesis through metabolic pathways.

Psychophysiological Responses of Humans during Seed-Sowing Activity Using Soil Inoculated with Streptomyces rimosus.

Electroencephalogram (EEG) responses and serum metabolite levels were used to investigate the effects of horticultural activities (seed-sowing) on the psychophysiological aspects of adults based on the presence or absence of the soil microorganism Streptomyces rimosus. In this case, 31 adults were subjected to seed-sowing activities using S. rimosus inoculated (experimental group) and medium (control group) soils. EEG was measured to analyze the resulting psychophysiological response, and blood samples (5 mL) were collected. The relative gamma power (RG), relative high beta (RHB), and SEF 50 and SEF 90 were significantly higher in the right than in the left occipital lobe (p < 0.05). In both occipital lobes, ratios of SMR to theta (RST), mid beta to theta (RMT), and SMR-mid beta to theta (RSMT) were high (p < 0.05). GC-TOF-MS-based serum metabolite analysis detected 33 metabolites. Compared to the control group, the experimental group showed a lower content of amino acids (except aspartic acid), lipids, and C6 sugar monomers after the activity (p < 0.05). Aminomalonic acid was decreased, and aspartic acid was increased (p < 0.05). This study confirmed a positive effect on improving the concentration and attention of adults when seed-sowing activity was performed using S. rimosus-inoculated soil.

Serum metabolites associate with biofluid neurofilament light chain in Alzheimer’s disease

AbstractBackgroundNeurodegeneration is one of the main components of A/T/N (amyloid/ tau/ neurodegeneration) classification. Recently, neurofilament light chain (NFL), a neuronal protein that is expressed in myelinated axons, has been increasingly recognized as a biomarker of neurodegeneration. In this study, we performed large‐scale association analysis of serum metabolites with NFL in Alzheimer’s disease.MethodWe performed cross‐sectional and longitudinal association analysis of serum metabolome with plasma and CSF NFL in Alzheimer’s disease (AD), after adjusting for multiple testing (N=1,317 for 140 metabolites). Subjects who had both NFL and metabolomics panel data were included. Metabolites were measured using a targeted metabolomics approach using the AbsoluteIDQ‐p180 kit.ResultWe identified 70 metabolites including acylcarnitines sphingomyelins, biogenic amines, amino acids, and glycerophospholipids as significantly associated with baseline plasma NFL, where we identified sex‐specific and APOE ε4‐specific metabolites. Of those, eight metabolites (C16:1, C18:1, SM(OH) C14:1, SM(OH) C16:1, SM C20:2, PC.aa.C28.1, PC.ae.C30.2, and PC.ae. C32.2) were also associated with baseline cerebrospinal fluid NFL and 10 metabolites (C9, C10:2, citrulline, creatinine, SDMA, PC.ae.C34.2, PC.ae.C36.2, PC.ae. C36.3, SM C20:2, and SM C16:0) were associated with change rates of plasma NFL in AD. Metabolites with significant associations were related to biological functions including amyloid precursor protein processing, neuroinflammation, nitric oxide production, and renal function. There were two significant interactions between sex and two medium‐chain acylcarnitine metabolites (C8 and C10) on plasma NFL levels.ConclusionOur present study provides insight into the association of serum‐based circulating metabolites with biofluid biomarker evidence of neurodegeneration, which is closely related to overt clinical symptoms in AD. Metabolites found in our study are related to various biological functions or associated with known risk factors of AD.

Studies on the Comparative Effect of Organic and Synthetic Feed on the Growth and Serum Metabolites of Broiler Chicks

Introduction: Modern broiler production efficiency is built on the improved feed for high growth and egg output. Growth performance of broilers greatly influenced by the feed contents. Objective: The objective of this study was to analyze the impact of organic and synthetic feed on the growth, feed utilization and serum metabolites of broilers chicken. Material and Methods: This experiment was conducted for 28 days on broiler chickens. Broilers were divided into five treatments such as T0, T1, T2, T3 and T4. Control group T0 received basal diet. T1 and T2 received organic feed. T3 and T4 received synthetic feed. Results: All the feed were given at the levels of 3% and 6%. Feed were given orally in the form of pellets. Practical implication: Growth performance were observed and recorded at weekly basis. After the completion of trial, blood sample were taken for the analysis of serum metabolites. Conclusion: Results showed that value of WG, absolute weight gain and SGR were increased significantly (p&lt;0.05) in combine treatment T2 (6% organic feed) with respect to T0 (control group). Feed intake and FCR was significantly (p&lt;0.05) in treatment T2. Serum metabolites i.e. cholesterol, triglycerides, glucose and total protein were significantly analyzed (p&lt;0.05).The result of present study explained that T2 having organic feed showed better growth performance of broiler chickens. Keywords: broilers chicken, feed requirement, weight gain, FCR, serum metabolites,

Serum metabolomics reveals an innovative diagnostic model for salivary gland tumors

An early diagnosis of salivary gland tumors (SGTs) and determination of their malignancy are conducive to developing individualized therapeutic strategies and thus improving prognosis. The aim of this study was to investigate the difference of serum metabolic profiles in patients with SGTs to better understand the mechanism of this disease and disease risk stratification. We used ultrahigh-performance liquid chromatography Q Exactive mass spectrometry and multivariate statistical analyses to conduct a comprehensive analysis of serum metabolites in a population with normal control and SGTs. 32 differentially expressed metabolites were identified, while the level of serine and lactic acid were investigated to gradually upregulate in benign SGTs and malignant SGTs. Then, the expression of serine and lactic acid were assessed in validation cohort using multiple reaction monitoring (MRM) based targeted metabolite analysis. A risk score formula based on the amount of serine and lactic acid was developed and explored to be significantly related to benign SGTs and malignant SGTs in discovery and validation cohort. Our work highlights the possible use of the risk score assessment based on the serum metabolites not only reveal in the early diagnosis of SGTs but also assist in enhancing current therapeutic strategies in the clinic.

Alteration of Bile Acids and Omega-6 PUFAs Are Correlated With the Progression and Prognosis of Drug-Induced Liver Injury.

Background & AimsDrug-induced liver injury (DILI) is one of the leading causes of liver failure with some of the patients progressed to chronic DILI. The mechanisms underlying the severity and chronicity of DILI are poorly elucidated and the biomarkers are limited. Metabolites and gut microbiota played a crucial role in the development of various liver diseases. Herein, a systematic analysis of serum metabolites and gut microbiota was performed in DILI patients, aiming to identify metabolites correlated with the progression and clinical prognosis of DILI.MethodsVarious serum metabolites were quantitated using a metabolite array technology in this prospective study. Gut microbiome compositions and the expression profiles of liver genes were determined in patients with DILI and healthy controls.ResultsMetabolomic analysis revealed that bile acids (BAs) and polyunsaturated fatty acids (PUFAs) were closely related to DILI severity and chronicity respectively. The ratios of serum primary/secondary BAs and omega-6/omega-3 PUFAs were elevated in DILI patients. A model established by adrenic acid (AdA) and aspartic acid (Asp) exerts good performance for predicting the chronicity of DLIL. Hepatic transcriptome revealed enhanced expression of PUFA peroxidation and supressed expression of BA synthesis related genes in DILI patients. In addition, Lactic acid bacteria and BA converting bacteria were increased in gut of DILI patients. Besides, elevated serum malondialdehyde (MDA) and fibroblast growth factor 19 (FGF19) was observed in DILI patients.ConclusionBAs and PUFAs could be potent markers for the severity and chronicity of DILI respectively. The panel of AdA and Asp could be ideal predictive model for the risk of chronicity at the acute stage of DILI. Gut microbiota might act as a negative feedback mechanism to maintain the homeostasis of BAs and PUFAs via FGF19 signalling and PUFA saturation, respectively. Our study revealed novel biomarkers for severe and chronic DILI and provided new therapeutic targets for DILI.