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69 results for “plasma proteome”
Reprocessing of the dataset "Plasma Proteome Profiling Reveals the Effects of Weight Loss on the Apolipoprotein Family and Systemic Inflammation Status"
<p>Reprocessing of the MassIVE repository MSV000080596, originally generated to investigate the dynamic changes in the plasma proteomes of a cohort of individuals with obesity following weight loss and maintenance. The reprocessing included all samples from 52 individuals taken right after the weight-loss process and during the weight maintenance phase of the study (Weeks 0, 4, 13, 26, 39, and 52).</p> <p>We used the sequence database generated by ProHap (<a href="https://github.com/ProGenNo/ProHap">https://github.com/ProGenNo/ProHap</a>) representing all populations from the 1000 Genomes Project (doi.org/10.5281/zenodo.10149277). For the search, SearchGUI version 4.3.1 and PeptideShaker version 3.0.0 were used with the X!Tandem and Tide search engines. The modification settings specified were carbamidomethylation of C as fixed and oxidation of M, deamidation of N and Q, Pyrrolidone of E and Q, and acetylation of protein N-terminus as variable modifications. The maximum peptide length was set to 40 amino acids and the precursor and fragment ion tolerances were set to 7 and 20 ppm, respectively. Resulting PSMs were processed as described in (doi.org/10.1021/acs.jproteome.3c00243) using Percolator version 3.5 provided with features based on peptide retention time (DeepLC version 1.1.2) and fragmentation predictors (MS2PIP version 3.9.0), and filtered at a 1% estimated FDR.</p> <p>The attached file contains all the peptide-spectrum matches identified at 1% FDR. The peptides have been annotated with transcripts, genes, and alleles using the ProHap Peptide Annotator v1.1 (<a href="https://github.com/ProGenNo/ProHap_PeptideAnnotator">https://github.com/ProGenNo/ProHap_PeptideAnnotator</a>).</p>
Proteomic data (SWATH-MS) of mouse uterine horns treated with different types of plasma
<p>This dataset contains the proteomic data (SWATH-MS) from 48 mouse uterine horns corresponding to a murine model of Asherman'Syndrome (presence of intrauterine adhesions). These 48 uterine horns correspond to 26 NOD-SCID mice (mouse uterus are bicornuate - 2 uterine horns per mouse) distributed in 4 groups (n = 6 /group), attending to the treatment received: Control (n = 6; milliQ H2O was injected), non-activated umbilical cord plasma (n = 6), activated umbilical cord plasma (n = 6), and activated platelet-rich plasma from adult blood (n = 6). To simulate Asherman's Syndrome, we induced endometrial damage (using a needle) inside the lumen of left uterine horns from all animals, while right horns were left undamaged.</p>
Proteomic data (LC-MS/MS) of human plasma samples
<p>LC-MS/MS analysis of 8 different samples of plasma: 4 samples correspond to the activated platelet-rich plasma (PRP) fractions from 4 different patients with infertility due to Asherman's syndrome and/or endometrial atrophy; 2 samples correspond to the activated and not-activated, respectively, PRP fractions from a control fertile patient; 2 samples correspond to the activated and not-activated, respectively, fractions from a commercial umbilical cord plasma.</p>
Revealing the lipidome and proteome of Arabidopsis thaliana plasma membrane
<p>This table contains peaks aera values from GC-MS, TLC-GC-MS and LC-MS for characterization of Arabidopsis thaliana plasma membrane. These data were used for Fig. 6, 7, 8, 9 and S1, S2, S3 and S4 of Bahammou et al. 2023: Revealing the lipidome and proteome of Arabidopsis thaliana plasma membrane</p>
Copy number variations and their effect on the plasma proteome | Associations
<p>Results and supplementary data from a GWAS investigation the relationship of CNVs and blood protein measurements.</p>
Data from: Pre- and post- treatment fold change plasma proteomics in metastatic NSCLC patients
<p>Blood plasma samples were collected from advanced-stage NSCLC patients as part of a clinical study (PROPHETIC; NCT04056247). All clinical sites received IRB approval for the study protocol. Patient blood samples were drawn at baseline (referred to as T0) and, on average, 4 weeks after the treatment commenced, prior to the second dose of treatment (referred to as T1). Blood samples were drawn into tubes containing EDTA as an anticoagulant, and plasma was separated from the whole blood. The protocol adheres to the Clinical and Laboratory Standards Institute (CLSI) guidelines.</p>
Comparative proteomic and metabolomic analyses of plasma reveal the novel biomarker panels for thyroid dysfunction
<p><strong>Abstract</strong><strong>:</strong></p> <p><em>Objectives: </em>Thyroid dysfunction such as hypothyroidism (THO) and hyperthyroidism (THE) are the disease caused by pathological processes in the thyroid. The current diagnosis of thyroid dysfunction is variable because of ages and genders. The aim of this study was to explore the novel candidate biomarker panels for hypothyroidism and hyperthyroidism screening with mass spectrometry and bioinformatics.</p> <p><em>Methods:</em> Plasma samples were collected from 15 THE patients, 9 THO patients, and 15 healthy controls. DIA-based proteomic and untargeted metabolomic analyses were performed to identify the novel biomarker panels for THO and THE. Finally, three candidate biomarkers were verified by ELISA in 34 samples.</p> <p><em>Results:</em> A total of 2738 proteins and 6103 metabolites were identified, and 173 proteins and 2487 metabolites were found to be differentially expressed among THE, THO and control groups. The results of the ensemble feature selection, K-means clustering and the least absolute shrinkage and selection operator (LASSO) regression model showed that four proteins (C4A, C3/C5 convertase, APOL1, and ITIH4) and four metabolites (L-arginine, L-proline, cortisol, and cortisone) identified by plasma proteomics and metabolomics could help distinguish THO and THE patients from healthy controls.</p> <p><em>Conclusions:</em> This study identified and verified two pairs of biomarker panels that can distinguish the THE and THO patients regardless of ages and genders. Consequently, our findings represent a comprehensive analyses of thyroid dysfunction plasma, which is significant for the clinical diagnosis.</p> <p> </p>
Integrated plasma proteomic and single-cell immune signaling network signatures demarcate mild, moderate, and severe COVID-19
<p>The biological determinants underlying the range of COVID-19 clinical manifestations are not fully understood. Here, over 1400 plasma proteins and 2600 single-cell immune features comprising cell phenotype, endogenous signaling activity, and signaling responses to inflammatory ligands are cross-sectionally assessed in peripheral blood from 97 patients with mild, moderate, and severe COVID-19 and 40 uninfected patients. Using an integrated computational approach to analyze the combined plasma and single-cell proteomic data, we identify and independently validate a multivariate model classifying COVID-19 severity (multi-class AUC<sub>training</sub> = 0.799, p-value = 4.2e-6; multi-class AUC<sub>validation</sub> = 0.773, p-value = 7.7e-6). Examination of informative model features reveals novel biological signatures of COVID-19 severity, including the dysregulation of JAK/STAT, MAPK/mTOR, and NF-κB immune signaling networks in addition to recapitulating known hallmarks of COVID-19. These results provide a set of early determinants of COVID-19 severity that may point to therapeutic targets for prevention and/or treatment of COVID-19 progression.</p>
Unveiling the autoreactome: Proteome-wide immunological fingerprints reveal the promise of plasma cell depleting therapy
<p>The prevalence and burden of autoimmune and autoantibody mediated disease continues to rise, yet the etiologies of many of these diseases remain unclear. Despite numerous new targeted immunomodulatory therapies, comprehensive approaches to apply and evaluate the effects of these treatments longitudinally are lacking. Here, we leverage advances in PhIPseq methodology to explore the modulation, or lack thereof, for autoreactive antibodies proteome-wide in both health and disease. We demonstrate that each individual, regardless of disease state, possesses a distinct set of autoreactivities constituting a unique immunological fingerprint, or "autoreactome", that is remarkably stable over years. In addition to uncovering important new biology, the autoreactome can be used to better evaluate the relative effectiveness of various therapies in altering autoantibody repertoires. We find that therapies targeting B-Cell Maturation Antigen (BCMA) profoundly alter an individual's autoreactome, while anti-CD19 and CD-20 therapies have minimal effects, strongly suggesting a rationale for BCMA or other plasma cell targeted therapies in autoantibody mediated diseases.</p>
Reassessment of the proteomic composition and function of extracellular vesicles in the seminal plasma
<p>Seminal plasma contains a high concentration of extracellular vesicles (EVs). The heterogeneity of small EVs or the presence of non-vesicular extracellular matter(NV) pose major obstacles in understanding the composition and function of seminal EVs. In this study, we employed high-resolution density gradient fractionation to accurately characterize the composition and function of seminal EVs and NV. We found that the seminal EVs could be divided into three different subtypes, namely high-density EV (EV-H), medium-density EV (EV-M), and low-density EV (EV-L) after purification using iodixanol,while NV was successfully isolated. EVs and NV display different features in size, shape and expression of some classic exosome markers. Both EV-H and NV could markedly promote sperm motility and capacitation compared with EV-M and EV-L, whereas only the NV fraction induced sperm acrosome reaction. Proteomic analysis results showed that EV-H, EV-M, EV-L, and NV had different protein components and were involved in different physiological functions. Further study showed that EV-M might reduce the production of sperm intrinsic reactive oxygen species (ROS) through Glutathione S-transferase Mu 2 (GSTM2).This study provides novel insights into important aspects of seminal EVs constituents and sounder footing to explore their functional properties in male fertility.</p>
Proteome association studies of breast, prostate, ovarian, and endometrial cancers implicate plasma protein regulation in cancer susceptibility
<p>Full results datasets for Proteome association studies of breast, prostate, ovarian, and endometrial cancers implicate plasma protein regulation in cancer susceptibility:</p> <p>ALL*all_pheno.csv are TOPMed-MESA combined-ancestry models, discovery and replication cohorts</p> <p>ARIC_EA_all_pheno.csv is ARIC European-American ancestry models, discovery cohort</p> <p>ARIC*meta_all.txt is ARIC European-American ancestry models, discovery and replication cohorts, with meta-analysis of disc+rep</p>
Code. Midlife proteome-wide analysis identifies plasma biomarkers for 25-year dementia risk linked to diverse pathophysiology
<p>The code used for the analyses for the paper entitled "Midlife proteome-wide analysis identifies plasma biomarkers for 25-year dementia risk linked to diverse pathophysiology". </p>
Data from: Plasma proteomic signatures of enteric permeability among hospitalized and community children under two years of age in Kenya and Pakistan
<p class="MsoNormal">We aimed to establish if enteric permeability was associated with similar biological processes in children recovering from hospitalization and relatively healthy children in the community. Extreme gradient-boosted models predicting the lactulose rhamnose ratio, a biomarker of enteric permeability, using 7,500 plasma proteins and 34 fecal biomarkers of enteric infection among 89 hospitalized and 60 community children aged 2-23 months were built. The R<sup>2</sup> were calculated in test sets. The models performed better among community (R<sup>2</sup>: 0·27 [min-max: 0·19, 0·53]) than hospitalized children (R<sup>2</sup>: 0·07 [min-max: 0·03, 0·11]). In the community, LRR was associated with biomarkers of humoral antimicrobial and cellular lipopolysaccharide responses, and inversely associated with anti-inflammatory and innate immunological responses. Among hospitalized children, the selected biomarkers had few shared functions.<strong> </strong>This suggests enteric permeability among community children was associated with a host response to pathogens, but this association was not observed among hospitalized children.</p>
Genomic atlas of the human proteome from brain, CSF and plasma: Improvement with TOPMed imputed genomics
<p>Abstract</p> <p>Comprehensive expression quantitative trait loci (eQTL) studies have been instrumental for understanding tissue-specific gene regulation and pinpointing functional genes for disease-associated GWAS loci in a tissue-specific manner. Compared to gene expressions, proteins more directly affect various biological processes, often dysregulated in disease, and are important drug targets. We previously performed and identified tissue-specific protein QTL (pQTL) in neurologically relevant tissues. We now enhance this work by analyzing more proteins (1,300 versus 1,079) and an almost twofold increase in high-quality imputed genetic variants (8.4 million versus 4.4 million) by using TOPMed reference panel. We identified 38 genomic regions associated with 43 proteins in brain, 150 regions associated with 247 proteins in CSF, and 95 regions associated with 145 proteins in plasma. Compared to our previous study, this study newly identified 12 pQTL in brain, 30 pQTL in CSF, and 22 pQTL in plasma. Our improved genomic atlas uncovers the genetic control of protein regulation across multiple tissues. These pQTL findings are assessable through the Online Neurodegenerative Trait Integrative Multi-Omics Explorer (ONTIME) for use by the scientific community.</p>
Genomic atlas of the human proteome from brain, CSF and plasma: Improvement with TOPMed imputed genomics
<p>Abstract</p> <p>Comprehensive expression quantitative trait loci (eQTL) studies have been instrumental for understanding tissue-specific gene regulation and pinpointing functional genes for disease-associated GWAS loci in a tissue-specific manner. Compared to gene expressions, proteins more directly affect various biological processes, often dysregulated in disease, and are important drug targets. We previously performed and identified tissue-specific protein QTL (pQTL) in neurologically relevant tissues. We now enhance this work by analyzing more proteins (1,300 versus 1,079) and an almost twofold increase in high-quality imputed genetic variants (8.4 million versus 4.4 million) by using TOPMed reference panel. We identified 38 genomic regions associated with 43 proteins in brain, 150 regions associated with 247 proteins in CSF, and 95 regions associated with 145 proteins in plasma. Compared to our previous study, this study newly identified 12 pQTL in brain, 30 pQTL in CSF, and 22 pQTL in plasma. Our improved genomic atlas uncovers the genetic control of protein regulation across multiple tissues. These pQTL findings are assessable through the Online Neurodegenerative Trait Integrative Multi-Omics Explorer (ONTIME) for use by the scientific community.</p>
Genomic atlas of the human proteome from brain, CSF and plasma: Improvement with TOPMed imputed genomics
<p>Abstract</p> <p>Comprehensive expression quantitative trait loci (eQTL) studies have been instrumental for understanding tissue-specific gene regulation and pinpointing functional genes for disease-associated GWAS loci in a tissue-specific manner. Compared to gene expressions, proteins more directly affect various biological processes, often dysregulated in disease, and are important drug targets. We previously performed and identified tissue-specific protein QTL (pQTL) in neurologically relevant tissues. We now enhance this work by analyzing more proteins (1,300 versus 1,079) and an almost twofold increase in high-quality imputed genetic variants (8.4 million versus 4.4 million) by using TOPMed reference panel. We identified 38 genomic regions associated with 43 proteins in brain, 150 regions associated with 247 proteins in CSF, and 95 regions associated with 145 proteins in plasma. Compared to our previous study, this study newly identified 12 pQTL in brain, 30 pQTL in CSF, and 22 pQTL in plasma. Our improved genomic atlas uncovers the genetic control of protein regulation across multiple tissues. These pQTL findings are assessable through the Online Neurodegenerative Trait Integrative Multi-Omics Explorer (ONTIME) for use by the scientific community.</p>
Genomic atlas of the human proteome from brain, CSF and plasma: Improvement with TOPMed imputed genomics
<p>Abstract</p> <p>Comprehensive expression quantitative trait loci (eQTL) studies have been instrumental for understanding tissue-specific gene regulation and pinpointing functional genes for disease-associated GWAS loci in a tissue-specific manner. Compared to gene expressions, proteins more directly affect various biological processes, often dysregulated in disease, and are important drug targets. We previously performed and identified tissue-specific protein QTL (pQTL) in neurologically relevant tissues. We now enhance this work by analyzing more proteins (1,300 versus 1,079) and an almost twofold increase in high-quality imputed genetic variants (8.4 million versus 4.4 million) by using TOPMed reference panel. We identified 38 genomic regions associated with 43 proteins in brain, 150 regions associated with 247 proteins in CSF, and 95 regions associated with 145 proteins in plasma. Compared to our previous study, this study newly identified 12 pQTL in brain, 30 pQTL in CSF, and 22 pQTL in plasma. Our improved genomic atlas uncovers the genetic control of protein regulation across multiple tissues. These pQTL findings are assessable through the Online Neurodegenerative Trait Integrative Multi-Omics Explorer (ONTIME) for use by the scientific community.</p>
Genomic atlas of the human proteome from brain, CSF and plasma: Improvement with TOPMed imputed genomics
<p>Abstract</p> <p>Comprehensive expression quantitative trait loci (eQTL) studies have been instrumental for understanding tissue-specific gene regulation and pinpointing functional genes for disease-associated GWAS loci in a tissue-specific manner. Compared to gene expressions, proteins more directly affect various biological processes, often dysregulated in disease, and are important drug targets. We previously performed and identified tissue-specific protein QTL (pQTL) in neurologically relevant tissues. We now enhance this work by analyzing more proteins (1,300 versus 1,079) and an almost twofold increase in high-quality imputed genetic variants (8.4 million versus 4.4 million) by using TOPMed reference panel. We identified 38 genomic regions associated with 43 proteins in brain, 150 regions associated with 247 proteins in CSF, and 95 regions associated with 145 proteins in plasma. Compared to our previous study, this study newly identified 12 pQTL in brain, 30 pQTL in CSF, and 22 pQTL in plasma. Our improved genomic atlas uncovers the genetic control of protein regulation across multiple tissues. These pQTL findings are assessable through the Online Neurodegenerative Trait Integrative Multi-Omics Explorer (ONTIME) for use by the scientific community.</p>
Genomic atlas of the human proteome from brain, CSF and plasma: Improvement with TOPMed imputed genomics
<p>Abstract</p> <p>Comprehensive expression quantitative trait loci (eQTL) studies have been instrumental for understanding tissue-specific gene regulation and pinpointing functional genes for disease-associated GWAS loci in a tissue-specific manner. Compared to gene expressions, proteins more directly affect various biological processes, often dysregulated in disease, and are important drug targets. We previously performed and identified tissue-specific protein QTL (pQTL) in neurologically relevant tissues. We now enhance this work by analyzing more proteins (1,300 versus 1,079) and an almost twofold increase in high-quality imputed genetic variants (8.4 million versus 4.4 million) by using TOPMed reference panel. We identified 38 genomic regions associated with 43 proteins in brain, 150 regions associated with 247 proteins in CSF, and 95 regions associated with 145 proteins in plasma. Compared to our previous study, this study newly identified 12 pQTL in brain, 30 pQTL in CSF, and 22 pQTL in plasma. Our improved genomic atlas uncovers the genetic control of protein regulation across multiple tissues. These pQTL findings are assessable through the Online Neurodegenerative Trait Integrative Multi-Omics Explorer (ONTIME) for use by the scientific community.</p>
Genomic atlas of the human proteome from brain, CSF and plasma: Improvement with TOPMed imputed genomics
<p>Abstract</p> <p>Comprehensive expression quantitative trait loci (eQTL) studies have been instrumental for understanding tissue-specific gene regulation and pinpointing functional genes for disease-associated GWAS loci in a tissue-specific manner. Compared to gene expressions, proteins more directly affect various biological processes, often dysregulated in disease, and are important drug targets. We previously performed and identified tissue-specific protein QTL (pQTL) in neurologically relevant tissues. We now enhance this work by analyzing more proteins (1,300 versus 1,079) and an almost twofold increase in high-quality imputed genetic variants (8.4 million versus 4.4 million) by using TOPMed reference panel. We identified 38 genomic regions associated with 43 proteins in brain, 150 regions associated with 247 proteins in CSF, and 95 regions associated with 145 proteins in plasma. Compared to our previous study, this study newly identified 12 pQTL in brain, 30 pQTL in CSF, and 22 pQTL in plasma. Our improved genomic atlas uncovers the genetic control of protein regulation across multiple tissues. These pQTL findings are assessable through the Online Neurodegenerative Trait Integrative Multi-Omics Explorer (ONTIME) for use by the scientific community.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.