Untargeted metabolomics of hypertrophic cardiomyopathy (part I)
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo Sapiens
TISSUE(S): Heart
DISEASE(S): Cardiomyopathy
PROVIDER: ST001886 | MetabolomicsWorkbench |
REPOSITORIES: MetabolomicsWorkbench
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| mwtab | Other |
Items per page: 5 1 - 1 of 1 |
Shared Molecules
Only show the datasets with similarity scores above: 0.5
Threshold
0.5
Similar Datasets
Project description:The study concerns untargeted metabolomics in gastric and colorectal cancer patients. It was analyzed using mass spectrometry.
2024-05-01 | PXD051921 | Pride
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:Hypertrophic cardiomyopathy (HCM) is the most prevalent monogenic heart disease, commonly caused by pathogenic MYBPC3 variants, and a significant cause of sudden cardiac death. Severity is highly variable, with incomplete penetrance among genotype-positive family members. Previous studies demonstrated metabolic changes in HCM. We aimed to identify metabolite profiles associated with disease severity in carriers of MYBPC3 founder variants using direct-infusion high-resolution mass spectrometry in plasma of 30 carriers with a severe phenotype (maximum wall thickness ≥20 mm, septal reduction therapy, congestive heart failure, left ventricular ejection fraction <50%, or malignant ventricular arrhythmia) and 30 age- and sex-matched carriers with no or a mild phenotype. Of the top 25 mass spectrometry peaks selected by sparse partial least squares discriminant analysis, XGBoost gradient boosted trees, and Lasso logistic regression (42 total), 36 associated with severe HCM at a p < 0.05, 20 at p < 0.01, and 3 at p < 0.001. These peaks could be clustered to several metabolic pathways, including acylcarnitine, histidine, lysine, purine and steroid hormone metabolism, and proteolysis. In conclusion, this exploratory case-control study identified metabolites associated with severe phenotypes in MYBPC3 founder variant carriers. Future studies should assess whether these biomarkers contribute to HCM pathogenesis and evaluate their contribution to risk stratification.
| S-EPMC9961357 | biostudies-literature
Project description:MicroRNAs are important negative regulators of protein coding gene expression, and have been studied intensively over the last few years. To this purpose, different measurement platforms to determine their RNA abundance levels in biological samples have been developed. In this study, we have systematically compared 12 commercially available microRNA expression platforms by measuring an identical set of 20 standardized positive and negative control samples, including human universal reference RNA, human brain RNA and titrations thereof, human serum samples, and synthetic spikes from homologous microRNA family members. We developed novel quality metrics in order to objectively assess platform performance of very different technologies such as small RNA sequencing, RT-qPCR and (microarray) hybridization. We assessed reproducibility, sensitivity, quantitative performance, and specificity. The results indicate that each method has its strengths and weaknesses, which helps guiding informed selection of a quantitative microRNA gene expression platform in function of particular study goals.
2013-09-01 | E-MTAB-1815 | biostudies-arrayexpress
Project description:Oncogene-associated metabolic signatures in prostate cancer, identified by an integrative analysis of cultured cells and murine and human tumors, suggest that AKT activation results in a glycolytic phenotype whereas MYC induces aberrant lipid metabolism. Heterogeneity in human tumors makes this simplistic interpretation obtained from experimental models more challenging. Metabolic reprogramming as a function of distinct molecular aberrations has major diagnostic and therapeutic implications.
| S-EPMC4905328 | biostudies-other
Project description: Not available
| S-BSST1397 | biostudies-other
Project description:Bottromycin A2 is a structurally unique ribosomally synthesized and post-translationally modified peptide (RiPP) that possesses potent antibacterial activity towards multidrug-resistant bacteria. The structural novelty of bottromycin stems from its unprecedented macrocyclic amidine and rare β-methylated amino acid residues. The N-terminus of a precursor peptide (BtmD) is converted into bottromycin A2 by tailoring enzymes encoded in the btm gene cluster. However, little was known about key transformations in this pathway, including the unprecedented macrocyclization. To understand the pathway in detail, an untargeted metabolomic approach that harnesses mass spectral networking was used to assess the metabolomes of a series of pathway mutants. This analysis has yielded key information on the function of a variety of previously uncharacterized biosynthetic enzymes, including a YcaO domain protein and a partner protein that together catalyze the macrocyclization.
| S-EPMC5103208 | biostudies-literature
Project description:Human milk (HM) is considered the gold standard for infant nutrition. HM contains macro- and micronutrients, as well as a range of bioactive compounds (hormones, growth factors, cell debris, etc.). The analysis of the complex and dynamic composition of HM has been a permanent challenge for researchers. The use of novel, cutting-edge techniques involving different metabolomics platforms has permitted to expand knowledge on the variable composition of HM. This review aims to present the state-of-the-art in untargeted metabolomic studies of HM, with emphasis on sampling, extraction and analysis steps. Workflows available from the literature have been critically revised and compared, including a comprehensive assessment of the achievable metabolome coverage. Based on the scientific evidence available, recommendations for future untargeted HM metabolomics studies are included.
| S-EPMC7074033 | biostudies-literature
Project description:Covering: 2014 to 2023 for metabolomics, 2002 to 2023 for information visualizationLC-MS/MS-based untargeted metabolomics is a rapidly developing research field spawning increasing numbers of computational metabolomics tools assisting researchers with their complex data processing, analysis, and interpretation tasks. In this article, we review the entire untargeted metabolomics workflow from the perspective of information visualization, visual analytics and visual data integration. Data visualization is a crucial step at every stage of the metabolomics workflow, where it provides core components of data inspection, evaluation, and sharing capabilities. However, due to the large number of available data analysis tools and corresponding visualization components, it is hard for both users and developers to get an overview of what is already available and which tools are suitable for their analysis. In addition, there is little cross-pollination between the fields of data visualization and metabolomics, leaving visual tools to be designed in a secondary and mostly ad hoc fashion. With this review, we aim to bridge the gap between the fields of untargeted metabolomics and data visualization. First, we introduce data visualization to the untargeted metabolomics field as a topic worthy of its own dedicated research, and provide a primer on cutting-edge visualization research into data visualization for both researchers as well as developers active in metabolomics. We extend this primer with a discussion of best practices for data visualization as they have emerged from data visualization studies. Second, we provide a practical roadmap to the visual tool landscape and its use within the untargeted metabolomics field. Here, for several computational analysis stages within the untargeted metabolomics workflow, we provide an overview of commonly used visual strategies with practical examples. In this context, we will also outline promising areas for further research and development. We end the review with a set of recommendations for developers and users on how to make the best use of visualizations for more effective and transparent communication of results.
| S-EPMC11610048 | biostudies-literature
Project description:Cancer-associated fibroblasts (CAFs) have been recognized as important contributors to cancer development and progression. However, opposing evidence has been published whether CAFs, in addition to epigenetic, also undergo somatic genetic alterations and whether these changes contribute to carcinogenesis and tumour progression. We combined multiparameter DNA flow cytometry, flow-sorting and 6K SNP-arrays to study DNA aneuploidy, % S-phase, loss of heterozygosity (LOH) and copy number alterations (CNAs) to study somatic genetic alterations in cervical cancer-associated stromal cell fractions (n = 58) from formalin-fixed, paraffin-embedded (FFPE) samples. Tissue sections were examined for the presence of CAFs. Microsatellite analysis was used to study LOH. By flow cytometry we found no proof for DNA aneuploidy in the vimentin-positive stromal cell fractions of any samples (CV G0G1 population 3.7% +/- 1.2; S-phase 1.4% +/- 1.8). The genotype concordance between the stromal cells and the paired normal endometrium samples was > 99.9%. No evidence for CNAs or LOH was found in the stromal cell fractions. In contrast, high frequencies of DNA content abnormalities (43/57), a significant higher S-phase (14.6% +/- 8.5)(p = 0.0001) and substantial numbers of CNAs and LOH were identified in the keratin-positive epithelial cell fractions (CV G0G1 population 4.1% +/- 1.0). Smooth muscle actin and vimentin immunohistochemistry verified the presence of CAFs in all cases tested. LOH hot-spots on chromosomes 3p, 4p and 6p were confirmed by microsatellite analysis but the stromal cell fractions showed retention of heterozygosity only. From our study we conclude that stromal cell fractions from cervical carcinomas are DNA diploid, have a genotype undistinguishable from patient-matched normal tissue and are genetically stable. Stromal genetic changes do not seem to play a role during cervical carcinogenesis and progression. In addition, the stromal cell fraction of cervical carcinomas can be used as reference allowing large retrospective studies of archival FFPE tissues for which no normal reference tissue is available. Paired experiment, Endometrial (non-tumor) cells vs stromal cells from cervical tumors. Biological replicates: 58 patients. From 5 tumors also the tumor fraction was profiled.
2011-11-08 | E-GEOD-29143 | biostudies-arrayexpress