Metabolomics Workbench ST000329 - GNPS - Minimal change disease and focal segmental sclerosis in urine
Ontology highlight
ABSTRACT:
INSTRUMENT(S): Q-TOF - NEGATIVE, Q-TOF - POSITIVE
ORGANISM(S): Homo Sapiens
SUBMITTER: 
Oliver Fiehn
PROVIDER: MSV000082711 | GNPS | Thu Aug 02 17:15:00 BST 2018
REPOSITORIES: GNPS
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2015-02-12 | ST000329 | MetabolomicsWorkbench
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.
| 2116822 | ecrin-mdr-crc
Project description:Early diagnosis and treatment is pivotal to the management of kidney disease, whereas the pathological mechanisms and minimally invasive diagnostic method still need to be investigated. In the present study, single-cell RNA sequencing (scRNA-seq) was used to evaluate the heterogeneity of kidney diseases in single cell level. Cellular gene expression profiles of cells of renal tissue, peripheral blood mononuclear cells (PBMCs) and urine from four nephritis patients were performed. Our analysis revealed 12 subsets of renal cells and leukocytes, including fibroblast cells, mesangial cells, epithelial cells, proximal tubule cells (PTCs), and 6 types of immune cells, CD8+ T cell, macrophages (MC), nature killer cells (NK), dendritic cells (DC), B cell and neutrophils. PTCs were detected in both PBMC and urine, while PTC was negative in healthy blood sample. Multiple populations of fibroblast cells, mesangial cells and PTCs demonstrated pro-inflammatory or pro-apoptotic responses. Gene expression analysis suggested that chemotactic and activating effect of inflammatory PTCs and fibroblasts on neutropils were critical for the development and progress of nephritis, which was supported by the widely overexpressed pro-inflammatory genes in these cells. Gene expression profiles of inflammatory PTCs in PBMC, urine and kidney are highly correlated, indicating the high possibility of urine and PBMC PTCs in serving as a surrogate for kidney biopsies.
2022-05-23 | GSE203406 | GEO
Project description:Urine passes through the entire kidney and urinary tract system starting from the glomerulus and ending to the urethra. Cells in the kidney and urinary tract could be exfoliated from the epithelium into the urine, while leukocyte could infiltrate from the local tissue into the urine, which makes the urine a useful subject for clinical evaluation of relevant diseases. We performed scRNA-seq on voided urine samples. 50–100 mL middle stream urine samples were collected from 12 Chinese healthy adults and combined for droplet-based single-cell RNA sequencing after flow cytometric sorting of live cells. We presented the first single-cell atlas of adult human urine and identified multiple previously unrecognized cell types. Based on our scRNA-seq analysis data, a SOX9+ cell population was identified in adult human urine which we speculated to have progenitor potential.
2021-01-25 | GSE165396 | GEO
Project description:Background: Urine is a potential source of biomarkers for diseases of the kidneys and urinary tract. RNA, including microRNA, is present in the urine enclosed in detached cells or in extracellular vesicles (EVs) or bound and protected by extracellular proteins. Detection of cell- and disease-specific microRNA in urine may aid early diagnosis of organ-specific pathology. In this study, we applied barcoded deep sequencing to profile microRNAs in urine of healthy volunteers, and characterized the effects of sex, urine fraction (cells vs. EVs) and repeated voids by the same individuals. Results: Compared to urine-cell-derived small RNA libraries, urine-EV-derived libraries were relatively enriched with miRNA, and accordingly had lesser content of other small RNA such as rRNA, tRNA and sn/snoRNA. Unsupervised clustering of specimens in relation to miRNA expression levels showed prominent bundling by specimen type (urine cells or EVs) and by sex, as well as a tendency of repeated (first and second void) samples to neighbor closely. Likewise, miRNA profile correlations between void repeats, as well as fraction counterparts (cells and EVs from the same specimen) were distinctly higher than correlations between miRNA profiles overall. Differential miRNA expression by sex was similar in cells and EVs. Conclusions: miRNA profiling of both urine EVs and sediment cells can convey biologically important differences between individuals. However, to be useful as urine biomarkers, careful consideration is needed for biofluid fractionation and sex-specific analysis, while the time of voiding appears to be less important.
2016-01-28 | GSE72183 | GEO
Project description:The deposited data were collected from 148 patients and 133 family members accepted into the Undiagnosed Diseases Network (https://undiagnosed.hms.harvard.edu/). The NIH Common Fund Undiagnosed Diseases Network (UDN) seeks to provide diagnoses for individuals with undiagnosed disease. Here, we report and provide the mass spectrometry-based metabolomics (GC-MS) and lipidomics (LC-MS/MS) analyses of urine from 148 patients and 133 family members. We have deposited mass spectrometry-based metabolomics and lipidomics files including instrument files, normalized data processed files to allow for statistical analysis, and metabolomics and lipidomics results for each patient and associated relatives. In addition, as part of the mass spectrometry data made available, we have included mass spectrometry analyses and results from a reference population of individuals with no known metabolic diseases. UDN patients suffer from undiagnosed diseases and thus are typically represented as a sample size of one; therefore, understanding normal variation within a proband's condition needs to be measured against of dataset of normal individuals, which is included here.
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Project description:Interventions: Control Group:none;Advanced Adenoma Group:none;Early Colorectal Cancer Group:none
Primary outcome(s): urine metabolomics
Study Design: Factorial
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Project description:Background Metabolic associated fatty liver disease (MAFLD) was recently proposed to replace non-alcoholic fatty liver disease (NAFLD), which is defined as ectopic fat deposition in the liver. Hepatic steatosis is an independent predictor for insulin resistance and cardiovascular risk and hence mortality. The aim of present study was to investigate the urine molecular pattern and potential urine biomarker to distinguish healthy control, mild and severe hepatic steatosis in MAFLD patients using proteomic data. Method Hepatic steatosis was measured by Magnetic resonance imaging (MRI) that measure the proton density fat fraction (MRI-PDFF). Proteomic measurements of urine samples were done by mass spectrometry. Linear regression analyses were used to detect significant associations between the biomarkers and clinical parameters. Western blot and Elisa were performed for validation. Results Multiple pathways have been compromised in MAFLD, including the carbohydrate derivative catabolic process, glycosaminoglycan process, aminoglycan metabolic process, inflammatory response, insulin-like growth factor receptor and GTPase complex. Alpha-1-acid glycoprotein 1 (ORM1) and ceruloplasmin were finally identified to be potential urine biomarkers to detect mild/severe hepatic steatosis.
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