Untargeted metabolomics on plasma from children with asthma, comparing exacerbation-prone to non-exacerbation-prone
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo Sapiens
TISSUE(S): Blood
DISEASE(S): Asthma
PROVIDER: ST002251 | MetabolomicsWorkbench |
REPOSITORIES: MetabolomicsWorkbench
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| mwtab | Other |
Items per page: 5 1 - 1 of 1 |
Similar Datasets
Project description:Diabetic nephropathy (DN) is one of the specific complications of diabetes mellitus and one of the leading kidney-related disorders, often requiring renal replacement therapy. Currently, the tests commonly used for the diagnosis of DN, albuminuria (AU) and glomerular filtration rate (GFR), have limited sensitivity and specificity and can usually be noted when typical morphological changes in the kidney have already been manifested. That is why the extreme urgency of the problem of early diagnosis of this disease exists. The untargeted metabolomics analysis of blood plasma samples from 80 patients with type 1 diabetes and early and late stages of DN according to GFR was performed using direct injection mass spectrometry and bioinformatics analysis for diagnosing signatures construction. Among the dysregulated metabolites, combinations of 15 compounds, including amino acids and derivatives, monosaccharides, organic acids, and uremic toxins were selected for signatures for DN diagnosis. The selected metabolite combinations have shown high performance for diagnosing of DN, especially for the late stage (up to 99%). Despite the metabolite signature determined for the early stage of DN being characterized by a diagnostic performance of 81%, these metabolites as potential biomarkers might be useful in the evaluation of treatment of the disease, especially at early stages that may reduce the risk of kidney failure development.
| S-EPMC9692474 | biostudies-literature
Project description:The rapidly increasing number of engineered nanoparticles (NPs), and products containing NPs, raises concerns for human exposure and safety. With this increasing, and ever changing, catalogue of NPs it is becoming more difficult to adequately assess the toxic potential of new materials in a timely fashion. It is therefore important to develop methods which can provide high-throughput screening of biological responses. The use of omics technologies, including metabolomics, can play a vital role in this process by providing relatively fast, comprehensive, and cost-effective assessment of cellular responses. These techniques thus provide the opportunity to identify specific toxicity pathways and to generate hypotheses on how to reduce or abolish toxicity.We have used untargeted metabolome analysis to determine differentially expressed metabolites in human lung epithelial cells (A549) exposed to copper oxide nanoparticles (CuO NPs). Toxicity hypotheses were then generated based on the affected pathways, and critically tested using more conventional biochemical and cellular assays. CuO NPs induced regulation of metabolites involved in oxidative stress, hypertonic stress, and apoptosis. The involvement of oxidative stress was clarified more easily than apoptosis, which involved control experiments to confirm specific metabolites that could be used as standard markers for apoptosis; based on this we tentatively propose methylnicotinamide as a generic metabolic marker for apoptosis.Our findings are well aligned with the current literature on CuO NP toxicity. We thus believe that untargeted metabolomics profiling is a suitable tool for NP toxicity screening and hypothesis generation.
| S-EPMC5017021 | biostudies-other
Project description:IntroductionUntargeted metabolomics holds significant promise for biomarker detection and development. In resource-limited settings, a dried blood spot (DBS)-based platform would offer significant advantages over plasma-based approaches that require a cold supply chain.ObjectivesThe primary goal of this study was to compare the ability of DBS- and plasma-based assays to characterize maternal metabolites. Utility of the two assays was also assessed in the context of a case-control predictive model in pregnant women living with HIV.MethodsUntargeted metabolomics was performed on archived paired maternal plasma and DBS from n = 79 women enrolled in a large clinical trial.ResultsA total of 984 named biochemicals were detected across both plasma and DBS samples, of which 627 (63.7%), 260 (26.4%), and 97 (9.9%) were detected in both plasma and DBS, plasma alone, and DBS alone, respectively. Variation attributable to study individual (R2 = 0.54, p < 0.001) exceeded that of the sample type (R2 = 0.21, p < 0.001), suggesting that both plasma and DBS were capable of differentiating individual metabolomic profiles. Log-transformed metabolite abundances were strongly correlated (mean Spearman rho = 0.51) but showed low agreement (mean intraclass correlation of 0.15). However, following standardization, DBS and plasma metabolite profiles were strongly concordant (mean intraclass correlation of 0.52). Random forests classification models for cases versus controls identified distinct feature sets with comparable performance in plasma and DBS (86.5% versus 91.2% mean accuracy, respectively).ConclusionMaternal plasma and DBS samples yield distinct metabolite profiles highly predictive of the individual subject. In our case study, classification models showed similar performance albeit with distinct feature sets. Appropriate normalization and standardization methods are critical to leverage data from both sample types. Ultimately, the choice of sample type will likely depend on the compounds of interest as well as logistical demands.
| S-EPMC8340475 | biostudies-literature
Project description:Asthma and postinfectious bronchiolitis obliterans (PIBO) are chronic lung diseases characterized by recurrent episodes of wheezing. Mycoplasma, adenovirus, and respiratory syncytial virus infections can trigger both asthma and PIBO. These two diseases have common etiologic mechanisms that cause airway epithelial injury. They are often difficult to differentiate clinically in preschool children because both are exacerbated by viral infections and respond similarly to steroids and β2 agonists. PIBO, which is occasionally observed in children, is diagnosed through characteristic findings of air trapping on computed tomography or in biopsy samples of lung tissue. However, researchers have not clearly identified the specific blood markers that can distinguish these diseases or the differences in the mechanisms of development. We performed proteomic analysis of plasma to identify specific biomarkers that can be helpful in differentiating asthma from PIBO. This study discovered plasma biomarker candidates by measuring plasma proteome sequential window acquisition of all theoretical mass spectra (SWATH-MS) and included 30 healthy children, 18 with asthma and 15 with PIBO. was used to measure proteins in plasma samples. We identified and quantified 354 proteins across all 63 samples in the SWATH-MS analysis.
2022-12-01 | PXD034996 | Pride
Project description:Despite considerable morbidity and mortality, numerous cases of endocrine hypertension (EHT) forms, including primary aldosteronism (PA), pheochromocytoma and functional paraganglioma (PPGL), and Cushing's syndrome (CS), remain undetected. We aimed to establish signatures for the different forms of EHT, investigate potentially confounding effects and establish unbiased disease biomarkers. Plasma samples were obtained from 13 biobanks across seven countries and analyzed using untargeted NMR metabolomics. We compared unstratified samples of 106 PHT patients to 231 EHT patients, including 104 PA, 94 PPGL and 33 CS patients. Spectra were subjected to a multivariate statistical comparison of PHT to EHT forms and the associated signatures were obtained. Three approaches were applied to investigate and correct confounding effects. Though we found signatures that could separate PHT from EHT forms, there were also key similarities with the signatures of sample center of origin and sample age. The study design restricted the applicability of the corrections employed. With the samples that were available, no biomarkers for PHT vs. EHT could be identified. The complexity of the confounding effects, evidenced by their robustness to correction approaches, highlighted the need for a consensus on how to deal with variabilities probably attributed to preanalytical factors in retrospective, multicenter metabolomics studies.
| S-EPMC9394285 | biostudies-literature
Project description:Chronic liver diseases, including non-alcoholic fatty liver disease (NAFLD), cirrhosis, and hepatocellular carcinoma (HCC), continue to be a global health burden with a rise in incidence and mortality, necessitating a need for the discovery of novel biomarkers for HCC detection. This study aimed to identify novel non-invasive biomarkers for these different liver disease states. We performed untargeted metabolomics in plasma (Healthy = 9, NAFLD = 14, Cirrhosis = 10, HCC = 34) and saliva samples (Healthy = 9, NAFLD = 14, Cirrhosis = 10, HCC = 22) to test for significant metabolite associations with each disease state. Additionally, we identified enriched biochemical pathways and analyzed correlations of metabolites between, and within, the two biofluids. We identified two salivary metabolites and 28 plasma metabolites significantly associated with at least one liver disease state. No metabolites were significantly correlated between biofluids, but we did identify numerous metabolites correlated within saliva and plasma, respectively. Pathway analysis revealed significant pathways enriched within plasma metabolites for several disease states. Our work provides a detailed analysis of the altered metabolome at various stages of liver disease while providing some context to altered pathways and relationships between metabolites.
| S-EPMC11432510 | biostudies-literature
Project description:IntroductionWhen analyzing the human plasma metabolome with Nuclear Magnetic Resonance (NMR) spectroscopy, the Carr-Purcell-Meiboom-Gill (CPMG) experiment is commonly employed for large studies. However, this process can lead to compromised statistical analyses due to residual macromolecule signals. In addition, the utilization of Trimethylsilylpropanoic acid (TSP) as an internal standard often leads to quantification issues, and binning, as a spectral summarization step, can result in features not clearly assignable to metabolites.ObjectivesOur aim was to establish a new complete protocol for large plasma cohorts collected with the purpose of describing the comparative metabolic profile of groups of samples.MethodsWe compared the conventional CPMG approach to a novel procedure that involves diffusion NMR, using the Longitudinal Eddy-Current Delay (LED) experiment, maleic acid (MA) as the quantification reference and peak picking for spectral reduction. This comparison was carried out using the ultrafiltration method as a gold standard in a simple sample classification experiment, with Partial Least Squares-Discriminant Analysis (PLS-DA) and the resulting metabolic signatures for multivariate data analysis. In addition, the quantification capabilities of the method were evaluated.ResultsWe found that the LED method applied was able to detect more metabolites than CPMG and suppress macromolecule signals more efficiently. The complete protocol was able to yield PLS-DA models with enhanced classification accuracy as well as a more reliable set of important features than the conventional CPMG approach. Assessment of the quantitative capabilities of the method resulted in good linearity, recovery and agreement with an established amino acid assay for the majority of the metabolites tested. Regarding repeatability, ~ 85% of all peaks had an adequately low coefficient of variation (< 30%) in replicate samples.ConclusionOverall, our comparison yielded a high-throughput untargeted plasma NMR protocol for optimized data acquisition and processing that is expected to be a valuable contribution in the field of metabolic biomarker discovery.
| S-EPMC7196944 | biostudies-literature
Project description:Wet age-related macular degeneration (wAMD) causes central vision loss and represents a major health problem in elderly people. Here we have used untargeted metabolomics using UHPLC-MS to profile plasma from 127 patients with wAMD (67 choroidal neovascularization (CNV) and 60 polypoidal choroidal vasculopathy (PCV)) and 50 controls. A total of 545 biochemicals were detected. Among them, 17 metabolites presented difference between patients with wAMD and controls. Most of them were oxidized lipids (N=6, 35.29%). Comparing to controls, 28 and 18 differential metabolites were identified in patients with CNV and PCV, respectively. Two metabolites, hyodeoxycholic acid and L-tryptophanamide, were differently distributed between PCV and CNV. We first investigated the genetic association with metabolites in wet AMD (CFH rs800292 and HTRA1 rs10490924). We identified six differential metabolites between the GG and AA genotypes of CFH rs800292, five differential metabolites between the GG and AA genotypes of HTRA1 rs10490924, and four differential metabolites between the GG and GA genotypes of rs10490924. We selected four metabolites (cyclamic acid, hyodeoxycholic acid, L-tryptophanamide and O-phosphorylethanolamine) for in vitro experiments. Among them, cyclamic acid reduced the activity, inhibited the proliferation, increased the apoptosis and necrosis in human retinal pigment epithelial cells (HRPECs). L-tryptophanamide affected the proliferation, apoptosis and necrosis in HRPECs, and promoted the tube formation and migration in primary human retinal endothelial cells (HRECs). Hyodeoxycholic acid and O-phosphorylethanolamine inhibited the tube formation and migration in HRECs. The results suggested that differential metabolites have certain effects on wAMD pathogenesis-related HRPECs and HRECs.
| S-EPMC8202859 | biostudies-literature
Project description:BackgroundThe metabolic defect in glycogen storage disease type I (GSDI) results in fasting hypoglycemia and typical secondary metabolic abnormalities (eg, hypertriglyceridemia, hyperlactatemia, hyperuricemia). The aim of this study was to assess further perturbations of the metabolic network in GSDI patients under ongoing treatment.MethodsIn this prospective observational study, plasma samples of 14 adult patients (11 GSDIa, 3 GSDIb. Mean age 26.4 years, range 16-46 years) on standard treatment were compared to a cohort of 31 healthy controls utilizing ultra-high performance liquid chromatography (UHPLC) in combination with high resolution tandem mass spectrometry (HR-MS/MS) and subsequent statistical multivariate analysis. In addition, plasma fatty acid profiling was performed by GC/EI-MS.ResultsThe metabolomic profile showed alterations of metabolites in different areas of the metabolic network in both GSD subtypes, including pathways of fuel metabolism and energy generation, lipids and fatty acids, amino acid and methyl-group metabolism, the urea cycle, and purine/pyrimidine metabolism. These alterations were present despite adequate dietary treatment, did not correlate with plasma triglycerides or lactate, both parameters typically used to assess the quality of metabolic control in clinical practice, and were not related to the presence or absence of complications (ie, nephropathy or liver adenomas).ConclusionThe metabolic defect of GSDI has profound effects on a variety of metabolic pathways in addition to the known typical abnormalities. These alterations are present despite optimized dietary treatment, which may contribute to the risk of developing long-term complications, an inherent problem of GSDI which appears to be only partly modified by current therapy.
| S-EPMC9299190 | biostudies-literature
Project description:Patients who are prone to exacerbations of asthma experience significant costs in terms of missed work and school, acute care visits, and hospitalizations. Exacerbations are largely driven by environmental exposures including pollutants, stress, and viral and bacterial pathogens. These exposures are most likely to induce acute severe "asthma attacks" in high-risk patients. These personal risk factors for exacerbations can vary with the phenotype of asthma and age of the patient. In children, allergic sensitization is a strong risk factor, especially for those children who develop sensitization early in life. Airway inflammation is an important risk factor, and biomarkers are under evaluation for utility in detecting eosinophilic and type 2 inflammation and neutrophilic inflammation as indicators of risk for recurrent exacerbations. Insights into inflammatory mechanisms have led to new approaches to prevent exacerbations using mAb-based biologics that target specific type 2 pathways. Challenges remain in developing an evidence base to support precision interventions with these effective yet expensive therapies, and in determining whether these treatments will be safe and effective in young children. Unfortunately, there has been less progress in developing treatments for acute exacerbations. Hopefully, greater understanding of mechanisms relating airway viruses, bacteria, mucin production, and neutrophilic inflammatory responses will lead to additional treatment options for patients experiencing acute exacerbations.
| S-EPMC6942520 | biostudies-literature