Metabolomic
Ontology highlight
ABSTRACT:
TISSUE(S): ['brain']
SUBMITTER: Ying Yu
PROVIDER: OEX00021176 | NODE | 2022-12-31
REPOSITORIES: NODE
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Project description:Primary outcome(s): Best clinical response (RECIST 1.1) Serum concentration of metabolomic markers
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Project description:High-density kinetic analysis of the metabolomic and transcriptomic response of Arabidopsis to temperature and light
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Project description:Although multiple gene and protein expression have been extensively profiled in human pulmonary arterial hypertension (PAH), the mechanism for the development and progression of pulmonary hypertension remains elusive. Analysis of the global metabolomic heterogeneity within the pulmonary vascular system leads to a better understanding of disease progression. Using a combination of high-throughput liquid-and-gas-chromatography-based mass spectrometry, we showed unbiased metabolomic profiles of disrupted glycolysis, increased TCA cycle, and fatty acid metabolites with altered oxidation pathways in the severe human PAH lung. The results suggest that PAH has specific metabolic pathways contributing to increased ATP synthesis for the vascular remodeling process in severe pulmonary hypertension. These identified metabolites may serve as potential biomarkers for the diagnosis of severe PAH. By profiling metabolomic alterations of the PAH lung, we reveal new pathogenic mechanisms of PAH in its later stage, which may differ from the earlier stage of PAH, opening an avenue of exploration for therapeutics that target metabolic pathway alterations in the progression of PAH. Global profiles were determined in human lung tissue and compared across 11 normal and 12 severe pulmonary arterial hypertension patients. Using a combination of microarray and high-throughput liquid-and-gas-chromatography-based mass spectrometry, we showed unbiased metabolomic profiles of disrupted glycolysis, increased TCA cycle, and fatty acid metabolites with altered oxidation pathways in the severe human PAH lung.
2014-11-14 | E-GEOD-53408 | biostudies-arrayexpress
Project description:Rationale: Sepsis is a leading cause of morbidity and mortality; early diagnosis and prediction of progression is difficult to determine. The integration of metabolomic and transcriptomic data in an experimental model of sepsis may be a novel method to identify molecular signatures of clinical sepsis. Objectives: Develop a biomarker panel for earlier diagnosis and prognostic characterization of sepsis patients to inform personalized clinical management and improve understanding of the pathophysiology of sepsis progression. Methods: Mild to severe sepsis, lung injury and death was recapitulated in Macaca fascicularis by intravenous inoculation of Escherichia coli. Plasma samples were obtained at time of challenge and at one, three, and five days later or time of euthanasia. Necropsy was performed and blood, lung, kidney and spleen samples were obtained. An integrative analysis of comprehensive metabolomic and transcriptomic datasets was performed to identify and parameterize a biomarker panel. Measurements and Main Results: Pathogen invasion, respiratory distress, lethargy and mortality was dose dependent. Severe infection and death were associated with metabolomic and transcriptomic changes indicative of mitochondrial, peroxisomal and liver dysfunction. Analysis of reciprocal pulmonary transcriptome and plasma metabolome data revealed an integrated host response that suggested dysregulated fatty acid catabolism resulting from peroxisome-proliferator activated receptor signaling. A representative 4-metabolite model effectively diagnosed sepsis in primates (AUC 0.966) and in two human sepsis cohorts (AUC=0.78 and 0.82). Conclusion: A model to guide early management of patients with sepsis was developed by analysis of reciprocal metabolomic and transcriptomic data in primates that diagnosed sepsis in humans. Transcriptomic analysis of lungs from Cynomolgus macaques challenged with E. coli
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Project description:Twenty metabolites across 6 studies, with 6 groups of experimental subjects
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Project description:Twenty metabolites across 6 studies, with 6 groups of experimental subjects
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Project description:This is a prospective, multi-centered study to assess whether urine metabolomics can play a role in the screening of colorectal cancer (CRC). Urine samples will be collected from 1000 patients going through an established CRC screening program, and from a further 500 patients who already have a diagnosis of CRC. Using nuclear magnetic resonance (NMR) spectroscopy, the 1H NMR spectrum of urine samples will be analyzed for specific metabolites, and establish the metabolomic signature of colorectal cancer. The results from metabolomic urinalysis of this screening cohort will be compared with results from colonoscopy, histological descriptions, fecal occult blood testing (FOBT), and fecal immune testing (FIT) to assess the accuracy of urine metabolomics in identifying patients with polyps and malignancies. The urine metabolomic results from the colorectal cancer group will be correlated with operative, histological and clinical staging to define the role of urine metabolomics in assessing colorectal cancer type, location and stage. Additionally approximately 300 urine samples from breast cancer patients and 300 from prostate cancer patients will be collected to validate that the colorectal cancer signature is unique.
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Project description:This study was performed by testing 21 wildtype genetic lines on four different diets to look at the transcriptomic, metabolomic, and gross phenotype variation. The diets used were Normal Cornmeal-molasses symbolized N, high sugar symbolized 4, high fat F, and control C a low sugar diet. Larvae were raised from hatching to 3rd instar on the respecitve diets at a density of 50 larvae per food vial. Larvae were then collected for metabolomics, transcriptomic, and gross phenotype measurements (e.g. trehalose concentration, triglyceride concentration). Samples for transcriptomic and metabolomic analyses were snap frozen in liquid nitrogen. 236 total samples were analyzed. In most cases the are unique technical replicates except in the cases where the line, diet, and biological replicate characterists are identical.
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