Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Hs_Plasma_Mixed-Mode-Bound

ABSTRACT: Human Plasma Mixed Mode Bound

REANALYSIS of: PXD000656

INSTRUMENT(S): LTQ Orbitrap Velos

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Plasma Non-glyco

SUBMITTER: Guldbrandsen A, Vethe H, Farag Y, Oveland E, Garberg H, Berle M, Myhr KM, Opsahl JA, Barsnes H, Berven FS

PROVIDER: PAe005201 | PeptideAtlas | 2014-12-31

REPOSITORIES: PeptideAtlas

ACCESS DATA

Json Xml

Publications

In-depth characterization of the cerebrospinal fluid (CSF) proteome displayed through the CSF proteome resource (CSF-PR).

Guldbrandsen Astrid A Vethe Heidrun H Farag Yehia Y Oveland Eystein E Garberg Hilde H Berle Magnus M Myhr Kjell-Morten KM Opsahl Jill A JA Barsnes Harald H Berven Frode S FS

Molecular & cellular proteomics : MCP 20140718 11

In this study, the human cerebrospinal fluid (CSF) proteome was mapped using three different strategies prior to Orbitrap LC-MS/MS analysis: SDS-PAGE and mixed mode reversed phase-anion exchange for mapping the global CSF proteome, and hydrazide-based glycopeptide capture for mapping glycopeptides. A maximal protein set of 3081 proteins (28,811 peptide sequences) was identified, of which 520 were identified as glycoproteins from the glycopeptide enrichment strategy, including 1121 glycopeptides ...[more]

PMID: 25038066

Similar Datasets

Hs_Plasma_Mixed-Mode-Depleted

Project description:Human Plasma Mixed Mode Depleted

2014-12-31 | PAe005184 | PeptideAtlas

Hs_CSF_Mixed-Mode_Depleted

Project description:Human CSF Mixed Mode Bound

2014-12-31 | PAe005111 | PeptideAtlas

Hs_CSF_Mixed-Mode-Bound

Project description:Human CSF Mixed Mode Depleted

2014-12-31 | PAe005114 | PeptideAtlas

Hs_CSF_Glyco_Mixed-Mode

Project description:Human CSF Glyco Mixed Mode

2014-12-31 | PAe005109 | PeptideAtlas

Comparative analyses of human saliva and plasma IgG antibody reactivities [HBV]

Project description:Saliva based diagnostics is a rapidly evolving field due to the large potential of saliva and the simple sample collection. A systematic comparison of IgG antibody profiles in saliva and plasma is currently lacking in scientific literature. Our hypothesis is that IgG profiles are equal in blood and saliva. By showing the equality of the profiles and relative IgG antigenic reactivities towards proteins and peptides we provide evidence that plasma IgG reactivities can be inferred from saliva IgG reactivities. IgG antibodies were isolated from human saliva and plasma samples. The reactivities of IgG isolates were analysed on peptide microarrays displaying linear epitopes of EBV (EBNA1 protein) and HBV (Large envelope protein) virus. Peptide arrays were printed by JPT Peptide Technologies (Berlin, Germany). We show high similarity of saliva and plasma IgG profiles on these two platforms and argue for generalisation from this subset to the whole immunological IgG antibody profile.

2018-07-17 | GSE117141 | GEO

Comparative analyses of human saliva and plasma IgG antibody reactivities [EBV]

2018-07-17 | GSE117140 | GEO

COVID-19 drives a distinct plasma proteome in pregnant and non-pregnant individuals

Project description:This study used SomaScan v 4.1 to profile>7000 proteins in human plasma and assess changes with Sars-Cov-2 infection and with Covid-19 disease severity in pregnant and non-pregnant individuals.

2023-03-03 | GSE207015 | GEO

Plasma and CSF Proteomic Signatures of Acutely Sleep-Deprived Humans: An Exploratory Study

Project description:Study objectives: Acute sleep deprivation affects both central and peripheral biological processes. Prior research has mainly focused on specific proteins or biological pathways that are dysregulated in the setting of sustained wakefulness. This pilotexploratory study’s objective wasaimed to provide a comprehensive view of the biological processes and proteins impacted by acute sleep deprivation in both plasma and cerebrospinal fluid (CSF). Methods: We collected plasma and CSF from human participants during one night of sleep deprivation and control normal sleep conditions. 1300 proteins were measured at hour 0 and hour 24 using a high-scale aptamer-based proteomics platform (SOMAomascan) and a systematics biological database tool (Metascape) was used to reveal dysregulated biological pathways. Results: Acute sleep deprivation lead to opposite effects in plasma and CSF, decreasingdecreased the number of upregulated and downregulated differential protein expression and biological pathways and proteins in plasma but increased upregulated and downregulated protein and biological pathwayssing them in CSF. Predominantly affected pProteins and n pathways were associated with that were predominantly affected by sleep deprivation included immune response, inflammation, phosphorylation, membrane signaling, cell-cell adhesion, and extracellular matrix organization. Conclusions: The identified modification across biofluids adds to evidence that acute sleep deprivation has important impacts on biological pathways and proteins that can negatively affect human health. As a hypothesis-driving study, these findings may help with the exploration of novel mechanisms that mediate sleep loss and associated conditions, drive the discovery of new sleep loss biomarkers, and ultimately aid in the identification of new targets for intervention to human diseases.

2023-12-14 | GSE244817 | GEO

Detection of early-stage Alzheimer’s pathology using blood-based autoantibody biomarkers in elderly hip fracture repair patients

Project description:Human plasma samples from CDR = 0 and CDR ≥ 0.5 patients, and serum samples from non-diseased, non-surgical controls were probed onto human protein microarrays to test the utility of a previously established panel of MCI-specific autoantibody (aAB) biomarkers to detect prodromal AD presurgically in individuals admitted into the hospital for hip fracture repair (HFR) surgery.

2020-04-14 | GSE137422 | GEO

Evaluating the utility of proteomics for the identification of circulating pharmacodynamic biomarkers of IFNβ-1 biologics

Project description:In this study, we evaluated the utility of proteomics to identify plasma proteins in healthy participants from a phase I clinical trial with IFNβ-1a and pegIFNβ-1a biologics to identify potential pharmacodynamic (PD) biomarkers. Using a linear mixed-effects model with repeated measurement for product-time interaction, we found that 248 and 528 analytes detected by the SOMAscan® assay were differentially expressed (p-value < 6.86E-06) between therapeutic doses of IFNβ-1a or pegIFNβ-1a, and placebo, respectively. We further prioritized signals based on peak change, area under the effect curve over the study duration, and overlap in signals from the two products. Analysis of prioritized datasets indicated activation of IFNB1 signaling and an IFNB signaling node with IL-6 as upstream regulators of the plasma protein patterns from both products. Increased TNF, IL-1B, IFNG, and IFNA signaling also occurred early in response to each product suggesting a direct link between each product and these upstream regulators. In summary, we identified longitudinal global PD changes in a large array of new and previously reported circulating proteins in healthy participants treated with IFNβ-1a and pegIFNβ-1a that may help identify novel single proteomic PD biomarkers and/or composite PD biomarker signatures as well as provide insight into the mechanism of action of these products. Independent replication is needed to confirm present proteomic results and to support further investigation of the identified candidate PD biomarkers for biosimilar product development.

2023-10-31 | GSE207945 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data