Untargeted Metabolomic Profiling Research Articles

Evaluating cardiovascular risk in metabolic steatosis with precision medicine non-invasive approaches: insights from a cohort study.

Metabolic associated steatotic liver disease (MASLD) is the most common liver condition. It is associated with increased liver-related morbidity and mortality, and also with high risk of cardiovascular events (CVD), representing itself an independent risk factor for it. This makes MASLD a presentation of high interest for internal medicine, also because of its association with metabolic syndrome (MetS). It is crucial to assess its risks in a noninvasive way. With the aim of finding specific risk profiles for CVD development in MASLD by performing a noninvasive assessment of: (1) preclinical signs of endothelial dysfunction (ED); (2) clinical assessment of CVD risk by Framingham Heart Risk Score (FHRs); (3) genomic characterization of MASLD associated polymorphisms; (4) specific untargeted metabolomic profiles, we enrolled 466 MASLD patients non-invasively classified in 4 group of liver fibrosis severity (group-A: low-fibrosis risk, group-B: high-fibrosis risk, group-C: MASLD-cirrhosis, group-D: MASLD-HCC) and 73 healthy controls. FHRs was similar in controls and low-fibrosis group and significantly higher in high-fibrosis patients, cirrhosis, and HCC, increasing among classes. At a multivariable regression, FHRs wasassociated with liver disease severity and diabetes. 38.2% of patients had altered EndoPAT,resembling ED.Patients with high FHRs (> 40%) and ED had different metabolomics compared to those without ED. Our study reveals that a deep, non-invasive characterization of MASLD patients through precision medicine approaches (untargeted metabolomics, SNPs, ED assessment) was able to show a peculiar pattern in MASLD patients with increased CVD risk, mostly correlated with liver disease severity.

Diagnostic utility of clinicodemographic, biochemical and metabolite variables to identify viable pregnancies in a symptomatic cohort during early gestation

A significant number of pregnancies are lost in the first trimester and 1–2% are ectopic pregnancies (EPs). Early pregnancy loss in general can cause significant morbidity with bleeding or infection, while EPs are the leading cause of maternal mortality in the first trimester. Symptoms of pregnancy loss and EP are very similar (including pain and bleeding); however, these symptoms are also common in live normally sited pregnancies (LNSP). To date, no biomarkers have been identified to differentiate LNSP from pregnancies that will not progress beyond early gestation (non-viable or EPs), defined together as combined adverse outcomes (CAO). In this study, we present a novel machine learning pipeline to create prediction models that identify a composite biomarker to differentiate LNSP from CAO in symptomatic women. This prospective cohort study included 370 participants. A single blood sample was prospectively collected from participants on first emergency presentation prior to final clinical diagnosis of pregnancy outcome: LNSP, miscarriage, pregnancy of unknown location (PUL) or tubal EP (tEP). Miscarriage, PUL and tEP were grouped together into a CAO group. Human chorionic gonadotrophin β (β-hCG) and progesterone concentrations were measured in plasma. Serum samples were subjected to untargeted metabolomic profiling. The cohort was randomly split into train and validation data sets, with the train data set subjected to variable selection. Nine metabolite signals were identified as key discriminators of LNSP versus CAO. Random forest models were constructed using stable metabolite signals alone, or in combination with plasma hormone concentrations and demographic data. When comparing LNSP with CAO, a model with stable metabolite signals only demonstrated a modest predictive accuracy (0.68), which was comparable to a model of β-hCG and progesterone (0.71). The best model for LNSP prediction comprised stable metabolite signals and hormone concentrations (accuracy = 0.79). In conclusion, serum metabolite levels and biochemical markers from a single blood sample possess modest predictive utility in differentiating LNSP from CAO pregnancies upon first presentation, which is improved by variable selection and combination using machine learning. A diagnostic test to confirm LNSP and thus exclude pregnancies affecting maternal morbidity and potentially life-threatening outcomes would be invaluable in emergency situations.

Comparative Analysis of Circulating Metabolomic Profiles Identifies Shared Metabolic Alterations Across Distinct Multi-Stressor Military Training Operations.

Military training provides insight into metabolic responses under unique physiological demands that can be comprehensively characterized by global metabolomic profiling to identify potential strategies for improving performance. This study identified shared changes in metabolomic profiles across three distinct military training exercises varying in magnitude and types of stress. Blood samples collected before and after three real or simulated military training exercises were analyzed using the same untargeted metabolomic profiling platform. Exercises included a three-week survival school course (ST, n=36), a four-day arctic cross country ski march (AT, n=24), and a 28-day controlled diet- and exercise-induced energy deficit (CED, n=26). Log2-fold changes of >±1 in 191, 121 and 64 metabolites were identified in the ST, AT and CED datasets, respectively. Most metabolite changes were within lipid (57-63%) and amino acid metabolism (18-19%) pathways, and changes in 87 were shared across studies. The largest and most consistent increases in shared metabolites were found in acylcarnitine, fatty acid, ketone, and glutathione metabolism pathways, whereas the largest decreases were in diacylglycerol and urea cycle metabolism pathways. Multiple shared metabolites were consistently correlated with biomarkers of inflammation, tissue damage, and anabolic hormones across studies. These three studies of real and simulated military training revealed overlapping alterations in metabolomic profiles despite differences in environment and the stressors involved. Consistent changes in metabolites related to lipid metabolism, ketogenesis and oxidative stress suggest a potential common metabolomic signature associated with inflammation, tissue damage and suppression of anabolic signaling that may characterize unique physiological demands of military training.

Free radical scavenging, α-amylase, α-glucosidase, and lipase inhibitory activities of metabolites from strawberry kombucha: Molecular docking and in vitro studies

Obesity, a global issue, is linked to cardiometabolic syndrome. Dietary modification is one of the recommended modes for managing cardiometabolic syndrome. Strawberries, a functional food, and kombucha, a fermented tea beverage, have gained attention for their health benefits. This study investigated the bioactive components of strawberry kombucha drink (SKD) and their effects on antioxidant activities and improving metabolic disorder markers. An in vitro experiment was performed to determine the effect of SKD on enzymatic parameters: lipase, α-glucosidase, and α-amylase activities. In addition, antioxidant activity using the DPPH method and quantification of the radical scavenging activity were also measured. Furthermore, untargeted metabolomic profiling of SKD and molecular docking simulation were conducted. The findings suggest that SKD, rich in secondary metabolites, can inhibit lipase, α-glucosidase, and α-amylase activities. It demonstrated in vitro anti-obesity, anti-diabetic, and antioxidant properties, potentially reducing metabolic and inflammatory issues. Thus, SKD could be a therapeutic beverage to alter metabolic issues associated with obesity. Nevertheless, further preclinical study is warranted to determine SKD’s potential in vivo.

Longitudinal plasma metabolome patterns and relation to kidney function and proteinuria in pediatric chronic kidney disease.

Understanding plasma metabolome patterns in relation to changing kidney function in pediatric chronic kidney disease (CKD) is important for continued research for identifying novel biomarkers, characterizing biochemical pathophysiology, and developing targeted interventions. There is a limited number of studies of longitudinal metabolomics, and virtually none in pediatric CKD. The Chronic Kidney Disease in Children (CKiD) study is a multi-institutional, prospective cohort that enrolled children aged six-months to 16-years with estimated glomerular filtration rate (eGFR) 30-90ml/min/1.73m2. Untargeted metabolomics profiling was performed on plasma samples from the baseline, two-, and four-year study visits. There were technologic updates in the metabolomic profiling platform used between the baseline and follow-up assays. Statistical approaches were adopted to avoid direct comparison of baseline and follow-up measurements.To identify metabolite associations with eGFR or urine protein:creatinine (UPCR) among all three timepoints, we applied linear mixed effects (LME) models. To identify metabolites associated with time, we applied LME models to the two- and four-year follow-up data. We applied linear regression analysis to examine associations between change in metabolite level over time (∆level) and change in eGFR (∆eGFR) and UPCR (∆UPCR). We reported significance based on both the False Discovery Rate (FDR) <0.05 and p<0.05. There were 1156 person-visits (N: baseline=626, 2-year=254, 4-year=276) included. There were 622 metabolites with standardized measurements at all three timepoints. In LME modeling, 406 and 343 metabolites associated with eGFR and UPCR at FDR<0.05 respectively. Among 530 follow-up person-visits, 158 metabolites showed differences over time at FDR<0.05. For participants with complete data at both follow-up visits (N=123), we report 35 metabolites with ∆level∼∆eGFR associations significant at FDR<0.05. There were no metabolites with significant ∆level∼∆UPCR associations at FDR<0.05. We report 16 metabolites with ∆level∼∆UPCR associations at p<0.05 and associations with UPCR in LME modeling at FDR<0.05. We characterized longitudinal plasma metabolomic patterns associated with eGFR and UPCR in a large pediatric CKD population. Many of these metabolite signals have been associated with CKD progression, etiology, and proteinuria in previous CKD Biomarkers Consortium studies. There were also novel metabolite associations with eGFR and proteinuria detected.

Abstract PO1-03-10: Differential microbial metabolic pathways associated with resistance to neoadjuvant immunotherapy in locally advanced triple negative breast cancer

Abstract Differential microbial metabolic pathways associated with resistance to neoadjuvant immunotherapy in locally advanced triple negative breast cancer Background: It has previously been shown that microbial metabolic pathways are differentially activated in immunotherapy resistance, hence can serve as potential targets for therapeutic intervention. With the advent of Immune Checkpoint Blockers in the neoadjuvant setting of locally advanced (LA) TNBC, we hypothesized that similar microbial metabolite mediated resistance may be at play. We are presenting the real world data for neoadjuvant treatment in early TNBC along with a subset of tumor metabolite analysis. Method: 35 patients who received neoadjuvant pembrolizumab and chemotherapy for LA TNBC were identified at Moffitt Cancer Center between July 2019 to January 2023. These included 22 Caucasian, 5 African American, 2 Hispanic and 6 patients with undisclosed race. The age range was 33-78 years. The weight and Body Mass Index range was 55.3 kg-127.3 kg and 20.96-45.43 kg/m2 respectively. Nine patients had stage III disease while 24 had stage II breast cancer. The response was assessed in 33 patients; 20 patients (60.6%) achieved pathological complete response (pCR) and 13 (39.4%) had residual disease (RD). 1 patient developed severe immune mediated toxicity with colitis, hepatitis, myasthenia gravis leading to death while 1 patient had disease progression leading to drug discontinuation. Six patients developed immune mediated adverse events. We conducted untargeted metabolomic profiling on 24 patients to identify differentially abundant metabolites associated with pCR (ypT0/is ypN0) vs RD; 16 vs 8 patients respectively. Formalin fixed paraffin embedded (FFPE) slides from tumor tissue vs tumor bed were retrieved and histopathological evaluation of tumor cells was performed. 20 μm sections of FFPE block were used for untargeted metabolomics via liquid chromatography/mass spectrometry. Among the 200 metabolites detected, 63 were differentially abundant between pCR and tumor samples with RD. After correcting for false discovery rate, we observed striking differential activation of two microbial metabolic pathways. Samples with RD had significantly elevated kynurenine (OR-3.64 X1034, P-1.94 X 10-74 and kynurenine/Tryptophan ratio). The tryptophan, kynurenine pathway has been known to be overexpressed in patients resistant to immunotherapy and modulated by the microbiome. Similarly, the purine metabolic pathway, specifically microbiota-derived immunostimulatory metabolites- inosine, hypoxanthine, uric acid were significantly depleted in patients with RD (Inosine OR-0.54, p-0.007, Hypoxanthine OR-0.5, p-0.00039, uric acid OR: 0.41, P-0.003). Previously Inosine has been shown to increase the anti-tumor effects of immune checkpoint blockade by enhancing CD8+ effector T-cell function. Hence depletion of inosine, hypoxanthine and uric acid signals lack of an effector CD8 T cell response. Conclusion: Despite being a small study, it corroborates pCR rates noted in KEYNOTE 522 in the real world setting but shows significant concern for serious immune mediated adverse effects. This highlights the importance of stratifying patients who might be resistant to ICB or develop significant toxicities, thus deriving little to no benefit from standard neoadjuvant treatment. This underscores the need to develop precision-based treatment algorithms. The study represents one of the first investigations of differential abundance of microbial metabolites with immunotherapy resistance in LA TNBC. Our results highlight two microbially mediated mechanisms that could be targeted to improve pCR rates in LA TNBC. We are working to identify microbial metabolic pathways associated with immune mediated toxicity. Citation Format: Humaira Sarfraz, Brian Czerniecki, Zena Jameel, Michael Jaglal, Mostafa Eysha, Turkan Ozkul, Jameel Muzaffar, Aditi Saha, Sara Sarfraz, Fatima Zahra, Min Liu, Khushali Jhaveri, Melissa Sur, Adrianna Bagos-Estevez, Shahla Bari. Differential microbial metabolic pathways associated with resistance to neoadjuvant immunotherapy in locally advanced triple negative breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-03-10.

Coronary Sinus Metabolite 12,13-diHOME Is a Novel Biomarker for Left Atrial Remodeling in Patients With Atrial Fibrillation.

12,13-dihydroxy-9Z-octadecenoic acid (12,13-diHOME) has shown potential in protecting against heart disease, but its relationship with atrial fibrillation (AF) remains unknown. Coronary sinus (CS) and femoral vein blood samplings were synchronously collected from AF and non-AF subjects (paroxysmal supraventricular tachycardia or idiopathic premature ventricular complexes) who underwent catheter ablation. First, untargeted metabolomic profiling was performed in a discovery cohort (including 12 AF and 12 non-AF subjects) to identify the most promising CS or femoral vein metabolite. Then, the selected metabolite was further measured in a validation cohort (including 119 AF and 103 non-AF subjects) to confirm its relationship with left atrium remodeling and 1-year postablation recurrence of AF. Finally, the biological function of the selected metabolite was validated in a rapid-paced cultured HL-1 atrial cardiomyocytes model. Metabolomic analysis identified CS 12,13-diHOME as the most pronounced change metabolite correlated with left atrium remodeling in the discovery cohort. In the validation cohort, CS 12,13-diHOME was significantly lower in patients with AF than non-AF controls (84.32±20.13 versus 96.24±23.56 pg/mL; P<0.01), and associated with worse structural, functional, and electrical remodeling of left atrium. Multivariable regression analyses further demonstrated that decreased CS 12,13-diHOME was an independent predictor of 1-year postablation recurrence of AF (odds ratio, 0.754 [95% CI, 0.648-0.920]; P=0.005). Biological function validations showed that 12,13-diHOME treatment significantly protect the cell viability, improved the expression of MHC (myosin heavy chain) and L-type calcium channel α1c, and attenuated mitochondrial damage in the rapid-paced cultured HL-1 cardiomyocytes model. CS metabolite 12,13-diHOME is decreased in patients with AF and can serve as a novel biomarker for left atrium remodeling.

Gut microbiome composition and metabolic activity in women with diverticulitis

The etiopathogenesis of diverticulitis, among the most common gastrointestinal diagnoses, remains largely unknown. By leveraging stool collected within a large prospective cohort, we performed shotgun metagenomic sequencing and untargeted metabolomics profiling among 121 women diagnosed with diverticulitis requiring antibiotics or hospitalizations (cases), matched to 121 women without diverticulitis (controls) according to age and race. Overall microbial community structure and metabolomic profiles differed in diverticulitis cases compared to controls, including enrichment of pro-inflammatory Ruminococcus gnavus, 1,7-dimethyluric acid, and histidine-related metabolites, and depletion of butyrate-producing bacteria and anti-inflammatory ceramides. Through integrated multi-omic analysis, we detected covarying microbial and metabolic features, such as Bilophila wadsworthia and bile acids, specific to diverticulitis. Additionally, we observed that microbial composition modulated the protective association between a prudent fiber-rich diet and diverticulitis. Our findings offer insights into the perturbations in inflammation-related microbial and metabolic signatures associated with diverticulitis, supporting the potential of microbial-based diagnostics and therapeutic targets.

Targeted and untargeted metabolomic profiles in wild rabbit does (Oryctolagus cuniculus) of different breeding states (pregnant and lactating).

Ecological nutrition aims to unravel the extensive web of nutritional links that drives animals in their interactions with their ecological environments. Nutrition plays a key role in the success of European wild rabbit (Oryctolagus cuniculus) and could be affected by the breeding status of the animals and reflected in the metabolome of this species. As nutritional needs are considerably increased during pregnancy and lactation, the main objective of this work was to determine how the breeding status (pregnant and lactating) of European wild rabbit does affects nutritional requirements and their metabolome (using targeted and untargeted metabolomics), aiming to find a useful biomarker of breeding status and for monitoring nutritional requirements. To address this gap, 60 wild European rabbits were studied. Animals were divided according to their breeding status and only pregnant (n = 18) and lactating (n = 11) rabbit does were used (n = 29 in total). The body weight and length of each animal were analyzed. The relative and absolute chemical composition of the gastric content and whole blood sample were taken, and targeted and untargeted metabolomics were analyzed. As a main result, there were no differences in biometric measurements, gastric content, and targeted metabolomics, except for live weight and nonesterified fatty acids (NEFA), as pregnant animals showed higher live weight (+12%; p = 0.0234) and lower NEFA acid levels (-46%; p = 0.0262) than lactating females. Regarding untargeted metabolomics, a good differentiation of the metabolome of the two breeding groups was confirmed, and it was proven that pregnant animals showed higher plasmatic levels of succinic anhydride (3.48 more times; p = 0.0236), succinic acid (succinate) (3.1 more times; p = 0.0068) and propionic acid (3.98 more times; p = 0.0121) than lactating animals. However, lactating animals showed higher levels of N-[(3a,5b,7b)-7-hydroxy-24-oxo-3-(sulfoxide) cholan-24-yl]-Glycine (cholestadien) (2.4 more times; p < 0.0420), 4-maleyl-acetoacetate (MAA) (3.2 more times; p < 0.0364) and irilone (2.2 more times; p = 0.0451) than pregnant animals, any of these metabolites could be used as a potential biomarker. From these results, it can be concluded that the most notable changes were observed in the metabolome of individuals, with most of the changes observed being due to energy and protein mobilisation.

The influence of maternal prepregnancy weight and gestational weight gain on the umbilical cord blood metabolome: a case–control study

BackgroundMaternal overweight/obesity and excessive gestational weight gain (GWG) are frequently reported to be risk factors for obesity and other metabolic disorders in offspring. Cord blood metabolites provide information on fetal nutritional and metabolic health and could provide an early window of detection of potential health issues among newborns. The aim of the study was to explore the impact of maternal prepregnancy overweight/obesity and excessive GWG on cord blood metabolic profiles.MethodsA case control study including 33 pairs of mothers with prepregnancy overweight/obesity and their neonates, 30 pairs of mothers with excessive GWG and their neonates, and 32 control mother-neonate pairs. Untargeted metabolomic profiling of umbilical cord blood samples were performed using UHPLC‒MS/MS.ResultsForty-six metabolites exhibited a significant increase and 60 metabolites exhibited a significant reduction in umbilical cord blood from overweight and obese mothers compared with mothers with normal body weight. Steroid hormone biosynthesis and neuroactive ligand‒receptor interactions were the two top-ranking pathways enriched with these metabolites (P = 0.01 and 0.03, respectively). Compared with mothers with normal GWG, in mothers with excessive GWG, the levels of 63 metabolites were increased and those of 46 metabolites were decreased in umbilical cord blood. Biosynthesis of unsaturated fatty acids was the most altered pathway enriched with these metabolites (P < 0.01).ConclusionsPrepregnancy overweight and obesity affected the fetal steroid hormone biosynthesis pathway, while excessive GWG affected fetal fatty acid metabolism. This emphasizes the importance of preconception weight loss and maintaining an appropriate GWG, which are beneficial for the long-term metabolic health of offspring.

Jian Gan powder ameliorates immunological liver injury in mice by modulating the gut microbiota and metabolic profiles

BackgroundImmunological liver injury (ILI) is a common liver disease associated with the microbiota-gut-liver axis. Jian Gan powder (JGP) exhibits both protective and therapeutic effects on hepatitis virus-induced ILI in the clinic. However, the underlying mechanisms remain elusive. The aim of this study is to investigate the hepatoprotective effects and associated mechanisms of JGP in the context of gut microbiota, utilizing a mouse model of ILI.MethodsThe mouse model was established employing Bacillus Calmette-Guérin (BCG) plus lipopolysaccharide (LPS). Following treatment with JGP (7.5, 15, or 30 g/kg), serum, liver, and fresh fecal samples were analyzed. 16S rRNA gene sequencing and untargeted metabolomics profiling were performed to assess the role of JGP on the gut microbiota and its metabolites.ResultsJGP treatment markedly reduced serum IFN-γ, IL-6, IL-22, and hepatic p-STAT3 (phosphorylated transducer and activator of transcription-3) expression. In contrast, JGP increased the percentage of proliferating cell nuclear antigen-positive liver cells in treated mice. Fecal 16S rRNA gene sequencing revealed that JGP treatment restored the levels of Alloprevotella, Burkholderia-Caballeronia-Paraburkholderia, Muribaculum, Streptococcus, and Stenotrophomonas. Additionally, metabolomics analysis of fecal samples showed that JGP restored the levels of allylestrenol, eplerenone, phosphatidylethanolamine (PE) (P-20:0/0:0), sphingomyelin (SM) d27:1, soyasapogenol C, chrysin, and soyasaponin I.ConclusionsJGP intervention improves ILI by restoring gut microbiota and modifying its metabolic profiles. These results provide a novel insight into the mechanism of JGP in treating ILI and the scientific basis to support its clinical application.

New insight on antioxidants and anti-obesity properties of two seagrasses Thalassia hemprichii and Zostera marina: an integrated molecular docking simulation with in vitro study

Background The oceans are teeming with a diverse range of marine organisms that offer unique health benefits, such as seagrass which is one of many key marine products that have garnered attention for their potential therapeutic properties. However, until now there have been few successful reports of seagrass’s metabolites profile and biological activity. Therefore, this work aims to profile metabolites or chemical constituents and assess the potential antioxidants and anti-obesity effects of two seagrasses, Thalassia hemprichii and Zostera marina. Methods Once authenticated, T. hemprichii and Z. marina were extracted with two different solvents, polar (ethanol) and nonpolar (hexane). Metabolite profiling was performed using untargeted metabolomic profiling via liquid chromatography coupled to high-resolution tandem mass spectrometry method analysis, and then antioxidant and anti-obesity capabilities were assessed by molecular docking and in vitro studies on selected receptors. Results A total of 9 and 11 metabolites were observed from T. hemprichii and Z. marina and continued molecular docking. Some of the observed compounds have promising potential as inhibitors of human inducible nitric oxide synthase, reactive oxygen species (ROS) 1 kinase, human pancreatic lipase, and fat mass and obesity-associated (FTO) proteins, including luteolin, 6-hydroxy compounds luteolin O-glucoside, luteolin-O-sulphate, Thalassiolin A, Thalassiolin C, kaempferol-7,4′-dimethylether-3-O-sulfate, apigenin, and diosmetin. T. hemprichii ethanol extract (THE) EC50 value shows antioxidant capabilities via ABTS radical scavenging activity of 76.00 μg/mL, a smaller value than standard antioxidant controls (Trolox, 76.54 μg/mL) and followed by EC50 of lipase inhibition activity by THE which has the same pattern (EC50 THE &lt; EC50 Orlistat). Conclusions This concludes that the two seagrasses have promising biological activity as candidates for functional food and/or drugs in combating free radicals and obesity.

Metabolites and Cognitive Decline in a Puerto Rican Cohort.

Recent studies have identified plasma metabolites associated with cognitive decline and Alzheimer's disease; however, little research on this topic has been conducted in Latinos, especially Puerto Ricans. This study aims to add to the growing body of metabolomics research in Latinos to better understand and improve the health of this population. We assessed the association between plasma metabolites and global cognition over 12 years of follow-up in 736 participants of the Boston Puerto Rican Health Study (BPRHS). Metabolites were measured with untargeted metabolomic profiling (Metabolon, Inc) at baseline. We used covariable adjusted linear mixed models (LMM) with a metabolite * time interaction term to identify metabolites (of 621 measured) associated with ∼12 years cognitive trajectory. We observed strong inverse associations between medium-chain fatty acids, caproic acid, and the dicarboxylic acids, azelaic and sebacic acid, and global cognition. N-formylphenylalanine, a tyrosine pathway metabolite, was associated with improvement in cognitive trajectory. The metabolites identified in this study are generally consistent with prior literature and highlight a role medium chain fatty acid and tyrosine metabolism in cognitive decline.

Metabolic Profiling Reveals the Importance of Arginine Metabolism via the Arginine Deiminase Pathway in Vancomycin-intermediate S. aureus

Gene mutations located in VraSR and GraSR, two-component regulatory systems have been reported to cause vancomycin resistance in vancomycin-intermediate Staphylococcus aureus (VISA). Subsequent comparative proteomic profiling between vancomycin-susceptible S. aureus (VSSA) and VISAs of the Mu50 genetic lineage revealed up-regulated level of catabolic ornithine carbamoyltransferase (ArcB) in the latter, suggesting a role of arginine catabolism in VISA development. This study aimed to further investigate metabolic pathways associated with VISA development using liquid chromatography mass spectrometry (LCMS)-based untargeted metabolomic profiling. Metabolite profiles were compared among 3 isogenic strains of the Mu50 lineage: Mu50Ω (VSSA), Mu50Ω-vraSm (VISA) and Mu50Ω-vraSm-graRm (VISA). Intracellular levels of α-hydroxyglutaric acid, choline, lysine, malic acid, N-acetylornithine, nicotinamide, and cystathionine were found to be significantly different between VISAs compared to VSSA. VISA cells were found to have lower levels of intracellular citrulline and extracellular arginine, with higher extracellular level of ornithine compared to VSSA. These differences in metabolite levels between VISA and VSSA suggested the importance of arginine metabolism. Activation of the arginine deiminase pathway (ADI) in VISAs of the Mu50 lineage could be further explored as a target for antibiotic development.

A universal plasma metabolites-derived signature predicts cardiovascular disease risk in MAFLD

BackgroundMetabolic associated fatty liver disease (MAFLD) is a novel concept proposed in 2020, which is more practical for identifying patients with fatty liver disease with high risk of disease progression. Fatty liver is a driver for extrahepatic complications, particularly cardiovascular diseases (CVD). Although the risk of CVD in MAFLD could be predicted by carotid ultrasound test, a very early stage prediction method before the formation of pathological damage is still lacking. MethodsStool microbiomes and plasma metabolites were compared across 196 well-characterized participants encompassing normal controls, simple MAFLD patients, MAFLD patients with carotid artery pathological changes, and MAFLD patients with diagnosed coronary artery disease (CAD). 16S rDNA sequencing data and untargeted metabolomic profiles were interrogatively analyzed using differential abundance analysis and random forest (RF) machine learning algorithm to identify discriminatory gut microbiomes and metabolomic. ResultsCharacteristic microbial changes in MAFLD patients with CVD risk were represented by the increase of Clostridia and Firmicutes-to-Bacteroidetes ratios. Faecalibacterium was negatively correlated with mean-intima-media thickness (IMT), TC, and TG. Megamonas, Bacteroides, Parabacteroides, and Escherichia were positively correlated with the exacerbation of pathological indexes. MAFLD patients with CVD risk were characterized by the decrease of lithocholic acid taurine conjugate, and the increase of ethylvanillin propylene glycol acetal, both of which had close relationship with Ruminococcus and Gemmiger. Biotin l-sulfoxide had positive correlation with mean-IMT, TG, and weight. The general auxin pesticide beta-naphthoxyacetic acid and the food additive glucosyl steviol were both positively correlated with the increase of mean-IMT. The model combining the metabolite signatures with 9 clinical parameters accurately distinguished MAFLD with CVD risk in the proband and validation cohort. It was found that citral was the most important discriminative metabolite marker, which was validated by both in vitro and in vivo experiments. ConclusionsSimple MAFLD patients and MAFLD patients with CVD risk had divergent gut microbes and plasma metabolites. The predictive model based on metabolites and 9 clinical parameters could effectively discriminate MAFLD patients with CVD risk at a very early stage.

Abstract 3625: Metabolic phenotypes of doxorubicin-induced cardiotoxicity in breast cancer patients

Abstract Background. Doxorubicin (DOX) is a highly effective chemotherapy agent that is commonly used in combination with other chemotherapy regimens to treat a wide range of cancers, including 32% of breast cancer (BC) cases. Although DOX has greatly increased the number of long-term cancer survivors, some DOX recipients have experienced DOX-induced cardiotoxicity (DIC). Currently, there are no validated markers that can predict the early development of DIC. Cardiac troponin released by cardiomyocytes has been used in non-clinical studies as a marker of myocardial injury; however, the false positive rates are high, and the predictive value on cardiotoxicity is limited. Therefore, novel biomarkers of DIC are urgently needed to identify patients who are at an increased risk, allowing early detection of the cardiotoxicity before it causes permanent cardiac damage. Methods. Untargeted metabolomics profiling was performed for plasma samples from a cohort of 28 breast cancer patients who developed abnormal cardiac function (ABN) and those who maintained normal cardiac function (NML). Blood samples were collected before, during, and after DOX-containing chemotherapy. Using both baseline observations and pre-post changes, machine-learning techniques were used to identify metabolite markers that can be used as early indicators of DIC in BC patients. Area under the receiver operating characteristic curve was reported to evaluate the performance of significant metabolites, and metabolite set enrichment analysis (MSEA) and network analysis were used to extrapolate known associations between metabolites and diseases. Results. Significant separation of plasma metabolomics profiles between ABN and NML patients at baseline was observed. From 1,124 metabolites, abundance of 59 metabolites were found to differ between ABN and NML patients at baseline. Across all patients, levels of 78 metabolites changed between baseline and after the 1st chemotherapy cycle. Of the 6 metabolites identified in both baseline and pre-post data, ABN patients had higher levels of dicarboxylic acids suberate and sebacate derived from ω-oxidation of fatty acids at baseline than NML patients. Enrichment analysis on the metabolites from the pre-post analysis suggested myocardio injury and carnitine palmitoyltransferase deficiency. Network analysis of metabolite-disease interactions further suggests potential impact on neurological health after chemotherapy. Conclusion. The metabolomics phenotype identified is indicative of impaired beta-oxidation at baseline for ABN patients. In addition, our findings suggest neurotoxic effect from DOX, implicating the potential brain-heart axis involved behind the cardiotoxicity phenotype. Citation Format: Se-Ran Jun, Katherine Wallis, Reid D. Landes, Valentina K. Todorova, L. Joseph Su, Sam Makhoul, Ping-Ching Hsu. Metabolic phenotypes of doxorubicin-induced cardiotoxicity in breast cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3625.

Abstract 4428: Integrated multi-omics analysis reveals systemic and localized metabolic disruptions in colorectal cancer

Abstract Despite technological advances in molecular medicine over the last 30 years, no single approach has proven to be sufficient to meet the diagnostic needs in cancer care. Here we use a multiomic approach leveraging proteomic, metabolomic, and transcriptomic technologies to study the metabolic shifts that occur during colorectal cancer (CRC) progression, Our integrated analysis identified systemic changes to beta oxidation pathways and localized changes to tyrosine metabolism within the tumor, creating a mechanistic, actionable description of the core CRC metabolic program. We conducted untargeted proteomics and metabolomics profiling on serum samples from CRC patients (n=10) and healthy controls (n=10). Our serum proteomics data is generated through sample enrichment on the Seer Proteograph system followed by LC/MS analysis with the Thermo Orbitrap Astral. Our metabolomics approach employs LC/MS assays for unbiased profiling of the serum metabolome, exposome, and lipidome. We supplemented this discovery work with both targeted serum and tumor-specific approaches including targeted proteomics to quantify select targets, inflammatory profiling with Alamar proteomics, public transcriptomics data from TCGA, and in vitro metabolic flux data. These large and diverse datasets were then integrated through joint pathway analysis and network integration. The global serum proteomics and metabolomics profiles generated show distinct separation between healthy and diseased individuals. Joint pathway analysis of these discovery datasets highlighted enrichment in beta oxidation pathways and tyrosine metabolism, among others. Interestingly, the Alamar inflammatory panel revealed that many of the analytes in the tyrosine metabolism pathway were well correlated with inflammatory status, while the beta oxidation signature had a lower correlation. To determine the relationship of these systemic findings from serum to tumor metabolism itself, we integrated tumor-specific transcriptomics data and found alterations to tyrosine metabolism with differences in tyrosine aminotransferase expression. The beta oxidation related genes, on the other hand, were not concordant with the serum findings. However, our in vitro metabolic flux studies have shown beta oxidation in CRC cells is upregulated to provide additional fuel for oxidative phosphorylation. This result suggests that beta oxidation may not be transcriptionally regulated in the tumor but rather a consequence of organismal metabolic rewiring. The results of this work, which is currently expanding into a larger and more diverse patient population, underscores the power of multiomic profiling for enhancing our understanding of metabolic dysregulation in CRC. Ultimately, a comprehensive model of the molecular alterations in CRC will yield a better understanding of tumor phenotypes and inform better diagnostics and therapies. Citation Format: Gary Patti, Ethan Stancliffe, Adam Richardson, Ashima Mehta, Monil Gandhi, Kevin Cho. Integrated multi-omics analysis reveals systemic and localized metabolic disruptions in colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4428.

Abstract 3429: Using metabolomics to identify biomarkers mediating the associations of adiposity in childhood and early adulthood with mammographic breast density in premenopausal women

Abstract Introduction: Mammographic breast density (MBD), a strong predictor of breast cancer risk, is highly influenced by body mass index (BMI) in childhood and early adulthood, but the mechanisms elucidating this relationship are undetermined. To our knowledge, no study has explored the mediating role of biomarkers on the relationship between early-life adiposity and MBD. The goal of this study is to discover metabolites that mediate the relationship between BMI at ages 10 and 18 with MBD in premenopausal women. Methods: This study includes premenopausal women who had their screening mammogram at Washington University in St. Louis, MO, and provided a fasting blood sample. Metabolon performed untargeted metabolomic profiling, detecting 1,074 metabolites. Metabolites missing &amp;gt;300 observations were excluded, leaving 828 metabolites; the other missing values were imputed using the nearest neighbor method. To mitigate batch effect, we normalized the metabolite peak area data using ComBat. Volumetric percent density (VPD) was calculated in 700 women using Volpara software. BMI at age 10 was estimated using the Stunkard pictogram, and BMI at age 18 was calculated from self-reported weight at 18 and height at study initiation. To assess the mediating role of the 828 metabolites, we performed high dimensional mediation analysis using the hima R package adjusting for potential confounders. Missing values in the covariates and BMI measures included in the mediation analysis were imputed using multivariate imputation by chain equations. Associations were considered significant if FDR p-value &amp;lt;0.1. Results: Four metabolites (glutamate, beta-cryptoxanthin, phytanate, and cortolone glucuronide (1)) mediated the relationship between BMI at age 10 and VPD; and 2 metabolites (glutamate, beta-cryptoxanthin) mediated the relationship between BMI at age 18 and VPD. Glutamate and beta-cryptoxanthin significantly mediated the relationship between both BMI measures and VPD, but glutamate was the strongest mediator across both time points. Glutamate mediated 6.7% (FDR p-value=0.06) and 9.3% (FDR p-value=0.008) of the total effect between BMI at age 10 and 18, respectively, on VPD. Beta-cryptoxanthin mediated 4.1% (FDR p-value=0.06) and 6.3% (FDR p-value=0.04), of the total effect between BMI at age 10 and 18, respectively, on VPD. Additionally, phytanate mediated 2.6% (FDR p-value=0.06) and cortolone glucuronide (1) mediated 2.0% (FDR p-value=0.07) of the total effect between BMI at age 10 and VPD. Conclusion: Amino acid, lipid, cofactor/vitamin, and xenobiotic metabolites mediated the associations of BMI in early-life and VPD in premenopausal women. This innovative study offers insight into the biological mechanisms underlying the link between early-life adiposity and MBD, which can support future research into breast cancer prevention. Citation Format: Kayla R. Getz, Myung Sik Jeon, Lili Liu, Lei Liu, Chongliang Luo, Jingqin Luo, Adetunji T. Toriola. Using metabolomics to identify biomarkers mediating the associations of adiposity in childhood and early adulthood with mammographic breast density in premenopausal women [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3429.

Metabolomic profiling of serum and tongue coating of pregnant women with intrahepatic cholestasis in pregnancy

Intrahepatic cholestasis of pregnancy (ICP) is associated with an increased risk of cesarean section and adverse fetal outcomes. Currently, ICP diagnosis depends largely on serum levels of bile acids and lacks sensitivity and specificity for accurate diagnosis. Tongue diagnosis is an important diagnostic tool in traditional Chinese medicine (TCM) and is used in our clinic as complementary treatment and personalized medicine for ICP. However, the molecular basis of the manifestation of greasy white tongue coatings in ICP remains unknown. In this study, we performed untargeted metabolomic profiling of the serum, tongue coating, and saliva of 66 pregnant women, including 22 with ICP. The metabolomic profiles of the serum and tongue coatings showed marked differences between the two clinical groups. Forty-six differentially abundant metabolites were identified, and their relative concentrations correlated with total bile acid levels. These differential metabolites included bile acids, lipids, microbiota- and diet-related metabolites, and exposomes. Conventional biochemical markers, including serum aminotransferases and bilirubin, were not significantly increased in the ICP group, whereas the total cholesterol and triglyceride levels were significantly increased as early as the first trimester. Our data provide insights into the pathophysiology of ICP and implicate the gut-liver axis and environmental exposure. Tongue coating has the potential to be a non-invasive diagnostic approach. Further studies are required to validate the clinical utility of these findings.

Untargeted metabolomic profiling of 100% malt beers versus those containing barley adjunct

Why was the work done: The incorporation of unmalted barley at high proportion in the grist can introduce unfavourable bitter and astringent characteristics to beer, resulting in an upper limit on the proportion used. The flavour active compounds from raw barley which contribute these characteristics to the beer remain to be identified. How was the work done: This study used non-targeted metabolomics to determine non-volatile metabolites which could contribute to flavour differences when brewing with barley. Three beers were analysed using ultra-high performance liquid chromatography (UHPLC) coupled to a quadrupole time-of-flight mass spectrometer (qTOF) with an electro-spray ionisation source (ESI). One beer was produced using 100% malt and two beers with a grist of 15% barley and 85% malt (beers A and B). The barley was used untreated (beer A) or treated using a proprietary process (beer B). The metabolomic profiles of the three beers were compared and statistically different molecular features were annotated via analysis of MS2 spectra. What are the main findings: Several of the main differential molecular features were nitrogenous peptides and purine derivatives. This was attributed to the lack of the malting process and associated proteolytic enzyme activity reducing the extent of protein and peptide breakdown in the unmalted barley. Several of the identified peptides had amino acid residues which are known to cause bitter and kokumi (rich) taste in beer, which could explain the bitterness when brewing with unmalted barley. Why is the work important: A non-targeted approach offers new insights into non-volatile molecular features in beer that have not been previously identified with targeted analyses. Accordingly, this work identifies metabolites and groups of compounds which have not been previously considered when investigating the unfavourable bitterness and astringency associated with the use of unmalted barley