2021 Trauma plasma H14 depleted proteomics
Ontology highlight
ABSTRACT:
INSTRUMENT(S): LTQ Orbitrap Velos
ORGANISM(S): Homo Sapiens (ncbitaxon:9606)
SUBMITTER: 
Yi Wang
PROVIDER: MSV000086942 | MassIVE | Tue Feb 23 23:46:00 GMT 2021
SECONDARY ACCESSION(S): PXD024333
REPOSITORIES: MassIVE
Similar Datasets
Project description:Background. Coagulopathic bleeding is a major cause of mortality after trauma, and platelet dysfunction contributes to this problem. The causes of platelet dysfunction are relatively unknown, but a great deal can be learned from the plasma environment about the possible pathways involved.
Objective. Describe the changes in plasma proteomic profile associated with platelet dysfunction after trauma.
Methods. Citrated blood was collected from severely injured trauma patients at the time of their arrival to the Emergency Department. Samples were collected from 110 patients, and a subset of twenty-four patients was identified by a preserved (n=12) or severely impaired (n=12) platelet aggregation response to five different agonists. Untargeted proteomics was performed by nanoflow liquid chromatography tandem mass spectrometry. Protein abundance levels for each patient were normalized to total protein concentration to control for hemodilution by crystalloid fluid infusion prior to blood draw.
Results. Patients with platelet dysfunction were more severely injured but otherwise demographically similar to those with retained platelet function. Of 232 proteins detected, twelve were significantly different between groups. These proteins fall into several broad categories related to platelet function, including microvascular obstruction with platelet activation, immune activation, and protease activation.
Conclusions. This observational study provides a description of the change in proteomic profile associated with platelet dysfunction after trauma and identifies twelve proteins with the most profound changes. The pathways involving these proteins are salient targets for immediate investigation to better understand platelet dysfunction after trauma and identify targets for intervention.
2021-02-24 | MSV000086948 | MassIVE
Project description:The TAR DNA Binding Protein (TDP-43) has been implicated in the pathogenesis of human neurodegenerative diseases and exhibits hallmark neuropathology in amyotrophic lateral sclerosis (ALS). Here, we explore its tractability as a plasma biomarker of disease and describe its localization and possible functions in the cytosol of platelets. Novel TDP-43 immunoassays were developed on three different technical platforms and qualified for specificity, signal-noise ratio, detection range, variation, spike recovery and dilution linearity in human plasma samples. Fractionation studies revealed that >95% of plasma TDP-43 protein [RL1] was located within the platelet cytosol, together with numerous RNAs. Platelet-derived TDP-43 exhibits TDP-43 proteoforms detected in neurodegenerative diseases, TARDBP RNA splice variants and TDP-43 RNA targets found in the central nervous system (CNS). We propose that TDP-43 serves similar functional roles in platelets and synapses, suggesting that the study of platelet TDP-43 might provide a window into TDP-43 proteinopathies within the CNS. The restricted compartmentalization of plasma TDP-43 in platelets provides a highly concentrated substrate for further biochemical analyses. Moreover, our results suggest that current plasma biobanking protocols are subject to considerable heterogeneity in platelet recovery and measurements of TDP-43 in plasma.
2024-09-25 | GSE245303 | GEO
Project description:Background---For decades, plasma lipid levels have been known risk factors of atherosclerosis. Recently, inflammation has gained acceptance as a crucial event in the pathogenesis and development of atherosclerosis. A number of studies have provided some insights into the relationships between the two aspects of atherosclerosis: plasma lipids --- the risk factors, and circulating leukocytes --- the effectors of inflammation. In this study, we investigate the relationships between plasma lipids and leukocytes. Methods and Results---No significant correlation was found between leukocyte counts and plasma lipid levels in 74 individuals. Profiling and analyzing the leukocyte gene expression of 32 individuals revealed distinctive patterns in response to plasma lipid levels: 1) genes involved in lipid metabolism and in the electron transport chain were positively correlated with triglycerides and low-density lipoprotein cholesterol levels, and negatively correlated with high-density lipoprotein cholesterol levels; 2) genes involved in platelet activation were negatively correlated with high-density lipoprotein cholesterol levels; 3) transcription factors regulating lipidgenesis-related genes were correlated with plasma lipid levels; 4) a number of genes correlated to plasma lipid levels were found located in the regions of known QTLs associated with hyperlipemia. Conclusions--- We discovered interesting patterns of leukocyte gene expression in response to plasma lipid levels. Most importantly, genes involved in lipid metabolism, the electron transportation chain, and platelet activation were found correlated with plasma lipid levels. We suggest that leukocytes respond to changing plasma lipid levels by regulating a network of genes, including genes involved in lipid and fatty acid metabolism, through the activation of key transcription factors, such as sterol regulatory element binding transcription factors and peroxisome proliferative activated receptors. Experiment Overall Design: 1. Profile gene expression in human peripheral blood cells. Experiment Overall Design: 2. Test blood biochemistry and blood cell differential counts Experiment Overall Design: 3. Examine the correlation between blood gene expression and blood lipid levels. Experiment Overall Design: 4. Explore possible pathways with significant genes. Experiment Overall Design: 5. Validate a number of significant genes with RT-PCR
2008-06-12 | E-GEOD-3059 | biostudies-arrayexpress
Project description:To fully interrogate mechanism of the platelet-rich plasma microneedles(PRP-MNs) in promoting hair regrowth in mice skin, we sought to perform a thorough and comprehensive transcripotome profiling of PRP-MNs,platelet-rich plasma(PRP) and microneedles(MNs) treatments of mice skin, with nective control(NC).
2023-07-01 | GSE204878 | GEO
Project description:Results Platelets in non-diabetic patients demonstrated miRNA expression profiles comparable to previously published data. The miRNA expression profiles of platelets in diabetics were similar. Statistical analysis unveiled only three miRNAs (miR-377-5p, miR-628-3p, miR-3137) with high reselection probabilities in resampling techniques, corresponding to signatures with only modest discriminatory performance. Functional annotation of predicted targets for these miRNAs pointed towards an influence of diabetes mellitus on mRNA processing. Conclusions/interpretation We did not find any major differences in platelet miRNA profiles between diabetics and non-diabetics. Minor differences pertained to miRNAs associated with mRNA processing. Thus, previously described differences in plasma miRNAs between diabetic and nondiabetic patients cannot be explained by plain changes in the platelet miRNA profile. Platelet miRNA profiles were assessed in clinically stable diabetic and nondiabetic patients (each n=30). Platelet miRNA was isolated from leucocyte-depleted platelet-rich plasma, and miRNA profiling was performed using LNA micro-array technology (miRBase 18.0, containing 1,917 human miRNAs). Effects of diabetes mellitus were explored by univariate statistical tests for each miRNA, adjusted for potential confounders, and by developing a multivariable signature, which was evaluated by resampling techniques. Platelet phenotype was assessed by light transmission aggregometry and impedance aggregometry.
2014-03-14 | E-GEOD-44093 | biostudies-arrayexpress
Project description:Background---For decades, plasma lipid levels have been known risk factors of atherosclerosis. Recently, inflammation has gained acceptance as a crucial event in the pathogenesis and development of atherosclerosis. A number of studies have provided some insights into the relationships between the two aspects of atherosclerosis: plasma lipids --- the risk factors, and circulating leukocytes --- the effectors of inflammation. In this study, we investigate the relationships between plasma lipids and leukocytes. Methods and Results---No significant correlation was found between leukocyte counts and plasma lipid levels in 74 individuals. Profiling and analyzing the leukocyte gene expression of 32 individuals revealed distinctive patterns in response to plasma lipid levels: 1) genes involved in lipid metabolism and in the electron transport chain were positively correlated with triglycerides and low-density lipoprotein cholesterol levels, and negatively correlated with high-density lipoprotein cholesterol levels; 2) genes involved in platelet activation were negatively correlated with high-density lipoprotein cholesterol levels; 3) transcription factors regulating lipidgenesis-related genes were correlated with plasma lipid levels; 4) a number of genes correlated to plasma lipid levels were found located in the regions of known QTLs associated with hyperlipemia. Conclusions--- We discovered interesting patterns of leukocyte gene expression in response to plasma lipid levels. Most importantly, genes involved in lipid metabolism, the electron transportation chain, and platelet activation were found correlated with plasma lipid levels. We suggest that leukocytes respond to changing plasma lipid levels by regulating a network of genes, including genes involved in lipid and fatty acid metabolism, through the activation of key transcription factors, such as sterol regulatory element binding transcription factors and peroxisome proliferative activated receptors. Keywords: Atherosclerosis, leukocyte, lipid, gene expression
2006-08-04 | GSE3059 | GEO
Project description:Osteosarcoma (OS) is the primary bone tumor in children and young adults. Currently, there are no reliable, non-invasive biological markers to detect the presence or progression of disease, assess therapy response, or provide upfront prognostic insights. Using a qPCR-based platform that analyzes more than 750 miRNAs, we analyzed control and diseased-associated plasma from a genetically engineered mouse model of OS to identify a profile of four plasma miRNAs. Plasma from mice with OS were profiled for miRNAs and compared with the profile of plasma from disease-free mice
2015-01-24 | E-GEOD-65236 | biostudies-arrayexpress
Project description:Plasma proteomics in preterm birth and normal pregnancy
| PRJNA631286 | ENA
Project description:Maternal plasma samples collected longitudinally from pregnant women were profiled using SomaLogic aptamer-based assays in women with normal pregnancy and those who delivered preterm. DiagnosisGA is the gestational age at diagnosis with any disease indicated by the Group variable, and it is set to NA for normal pregnancies. In the Group variable, sPTD stands for spontaneous preterm delivery, and PPROM for preterm premature rupture of membranes. Additional longitudinal samples of the controls, including the two samples included herein, are also available and described in PMID: 28738067.
2021-05-24 | GSE150167 | GEO
Project description:ABSTRACT FOR BOTH PLASMA AND PLATELET-LYSATE In this article we describe the involvement of exchange factor activated by cAMP 1 (Epac1) in hemostasis and platelet activation. We have used plasma and platelet-lysate from EPAC1 knockout mice and wild-type control mice in label-free proteomics with an Orbitrap Velos Pro. Blood was obtained from wild-type and Epac1-/- mice euthanized with CO2. Approximately 1000 ul was drawn from the left ventricle into a 2 ml syringe, containing 100 ul ACD and 200 ul modified Tyrode`s buffer. The blood was centrifuged at 200g for 5 minutes at room temperature, and the resulting platelet-rich plasma (PRP) centrifuged at 700g for another 10 minutes in the presence of 10 ul ACD. The resulting platelet-poor plasma (PPP) was transferred to Eppendorf tubes and the pelleted platelets resuspended in modified Tyrode`s buffer and adjusted to 2.5 x 108 platelets/ml. Platelets were allowed to rest at room temperature before experimentation. For proteomics analysis, platelets were further purified by size-exclusion through Sepharose CL-2B gel (Pharmacia Biotec, Sweden) as previously described by Jensen et al. in Blood 2004; 104. Plasma was crude or depleted for Albumin prior to trypsination and LCMS with quantification using Progenesis LCMS. The platelet-lysates were fractioned on SDS-PAGE prior to trypsination and LC-MS analysis with MaxQuant quantification. Label-free protein quantification for plasma The software Progenesis LC-MS® Ver 2.7 (Nonlinear Dynamics Ltd, Newcastle, UK) was used for label-free quantification and comparison of LC-MS proteomics data based on the volume, m/z and retention time of the MS1 features (peptides). In Progenesis, the LC-MS runs were automatically aligned, and only features with charges between +2 to +7 and containing associated MSMS spectra were accepted for export as an mgf file for identification. The mgf file was search against the human SwissProt Mus musculus database (version September 2012) using SearchGUI Ver 1.8.9. The search criteria were: trypsin as the protease with no miss-cleavages accepted, fixed carbamidomethylation on cystein, variable oxidation on methionine, precursor mass tolerance of 10 ppm, fragment mass tolerance of 0.7 and OMSSA as the search engine. The search result and associated spectra were combined and assigned to proteins in Peptide Shaker Ver 0.17.3 (http://peptideshaker.googlecode.com) at 1% FDR. The results were exported from PeptideShaker as validated PSMs in a Phenyx format, and imported back into Progenesis. The protein abundances reported from Progenesis were based on the sum of the normalized abundance of the unique identified petides. The proteomics raw files and PRIDE XML identification files were uploaded to PRIDE using ProteomeXchange ver 1.0.4, and the projects are public available. Two PRIDE XML files were generated using PeptideShaker, one for crude plasma and one for albumin-depleted plasma.
2017-07-25 | PXD000282 | Pride