Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Platelet microRNA expression profiles of acute coronary syndrome patients with high and low platelet reactivity

ABSTRACT: To explore the diverse platelet microRNA (miRNA) expression between high platelet reactivity (HPR) and low platelet reactivity (LPR) patients with acute coronary syndromes (ACS), we enrolled a cohort of ACS patients and performed miRNA expression profiling of platelets from four HPR and four LPR patients using human miRNA microarray system. VerifyNow P2Y12 assay was applied to indentify HPR and LPR. Venous blood was drawn from the patients and was centrifuged to prepare platelets. Among the candidate differentially expressed miRNAs, miR-15b expression was further confirmed to be lower in platelets of 22 HPR patients than 17 LPR by quantitative reverse-transcription polymerase chain reaction (RT-qPCR).

ORGANISM(S): Homo sapiens

PROVIDER: GSE59488 | GEO | 2014/07/17

SECONDARY ACCESSION(S): PRJNA255420

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Shared Molecules

Only show the datasets with similarity scores above: 0.5

Threshold

0.5

Similar Datasets

Platelet microRNA expression profiles of acute coronary syndrome patients with high and low platelet reactivity

Project description:To explore the diverse platelet microRNA (miRNA) expression between high platelet reactivity (HPR) and low platelet reactivity (LPR) patients with acute coronary syndromes (ACS), we enrolled a cohort of ACS patients and performed miRNA expression profiling of platelets from four HPR and four LPR patients using human miRNA microarray system. VerifyNow P2Y12 assay was applied to indentify HPR and LPR. Venous blood was drawn from the patients and was centrifuged to prepare platelets. Among the candidate differentially expressed miRNAs, miR-15b expression was further confirmed to be lower in platelets of 22 HPR patients than 17 LPR by quantitative reverse-transcription polymerase chain reaction (RT-qPCR). We enrolled a consecutive cohort of 290 ACS patients and assessed the platelet reactivity using VerifyNow P2Y12 assay. In this study, HPR was defined as M-bM-^IM-%300 platelet reactivity unit (PRU) while LPR <170 PRU. miRNA microarray analysis was performed in platelets of four HPR and four LPR patients with ACS.

2014-07-17 | E-GEOD-59488 | biostudies-arrayexpress

Screening on Platelet Non-coding RNA Expression Profiles Discloses Its Correlations with Low Residual Platelet Reactivity

Project description:Double anti-platelet therapy (DAPT) has wide inter-individual variabilities in coronary heart disease (CHD) patients’ responses, which undermines the prognosis effect in clinical practice. Noncoding RNAs are present in platelets, albeit their potential roles in platelet responses to DAPT largely remains in the realm of the unknown. This study aims to screen differential noncoding RNAs responsible for low residual platelet reactivities under DAPT. We enrolled 144 CHD patients that received DAPT and assigned them to high platelet reactivity (HPR) group and baseline group according to their residual platelet reactivities. Through microarray analysis, we detected a total of 22,424 kinds of co-expressed lncRNAs in three pairs of the patients between the HPR and baseline groups.

2020-01-01 | GSE130492 | GEO

Platelet microRNA-mRNA Co-Expression Profiles Correlate with Platelet Reactivity

Project description:MicroRNAs (miRNAs) regulate cell physiology by altering protein expression, but the biology of platelet miRNAs is largely unexplored. We tested whether platelet miRNA levels were associated with platelet reactivity by genome-wide profiling using platelet RNA from 19 healthy subjects. We found that human platelets express 284 miRNAs. Unsupervised hierarchical clustering of miRNA profiles resulted in 2 groups of subjects that appeared to cluster by platelet aggregation phenotypes. Seventy-four miRNAs were differentially expressed (DE) between subjects grouped according to platelet aggregation to epinephrine, a subset of which predicted the platelet reactivity response. Using whole genome mRNA expression data on these same subjects, we computationally generated a high-priority list of miRNA-mRNA pairs in which the DE platelet miRNAs had binding sites in 3'UTRs of DE mRNAs, and the levels were negatively correlated. Three miRNA-mRNA pairs (miR-200b:PRKAR2B, miR-495:KLHL5 and miR-107:CLOCK) were selected from this list and all 3 miRNAs knocked down protein expression from the target mRNA. Reduced activation from platelets lacking PRKAR2B supported these findings. In summary, (1) platelet miRNAs are able to repress expression of platelet proteins, (2) miRNA profiles are associated with and may predict platelet reactivity, and (3) bioinformatic approaches can successfully identify functional miRNAs in platelets. Total RNA from the platelets of 19 donors was harvested and labeled with Hy3. Reference RNA (a pool of all samples) was labeled with Hy5. This submission represents the miRNA expression component of the study.

2011-09-26 | E-GEOD-27917 | biostudies-arrayexpress

Platelet microRNA-mRNA Co-Expression Profiles Correlate with Platelet Reactivity

2011-09-27 | GSE27917 | GEO

platelet hyperreactivity project

Project description:The aim of this study is to identify candidate genes modulating platelet reactivity in aspirin-treated cardiovascular patients using an integrative network-based approach. Platelet reactivity was assessed in 110 cardiovascular patients treated with aspirin 100mg/d by aggregometry using several agonists. Patients with extreme high or low PR were selected for further analysis. Data derived from quantitative proteomic of platelets and platelet sub-cellular fractions, as well as from transcriptomic analysis were integrated with a network biology approach.

2019-03-14 | MSV000083572 | MassIVE

TNFα Downregulates STX17 Blocking Autophagy and Impairing Platelet Metabolism and Clot Contraction

Project description:Platelets are key players in hemostasis and thrombosis. In inflammatory conditions, platelets are hyperreactive and patients have an overal increased thrombotic risk. Our previous research demonstrated that TNFα significantly increases mitochondrial mass and platelet reactivity, emphasizing the crucial role of TNFα in modulating platelet metabolism and function.We hypothesized that TNFα disrupts platelet metabolism and function by inhibiting autophagy and mitophagy, which are critical processes for preserving mitochondrial mass, integrity, and energy production. We investigated the function, metabolism, and autophagy of human and mouse platelets in myeloproliferative neoplasms, rheumatoid arthritis, and aseptic inflammation. Our analysis reveled a blocked

2025-03-31 | GSE282993 | GEO

Platelet micro-RNA expression in type 2 diabetes mellitus

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

New molecular insights into modulation of platelet reactivity in aspirin-treated patients using a network-based approach [Affymetrix]

Project description:Platelet reactivity (PR) in cardiovascular (CV) patients is variable between individuals and modulates clinical outcome. However, the determinants of platelet reactivity are largely unknown. Integration of data derived from high-throughput omics technologies may yield novel insights into the molecular mechanisms that govern platelet reactivity. The aim of this study was to identify candidate genes modulating platelet reactivity in aspirin-treated cardiovascular patients PR was assessed in 110 CV patients treated with aspirin 100mg/d by aggregometry using several agonists. 12 CV patients with extreme high or low PR were selected for transcriptomics, proteomics and miRNA analysis. 2 extreme patient groups, 6 samples per group

2016-02-18 | E-GEOD-66426 | biostudies-arrayexpress

New molecular insights into modulation of platelet reactivity in aspirin-treated patients using a network-based approach [NanoString]

2016-02-18 | E-GEOD-66427 | biostudies-arrayexpress

A Role for IFITM3 in Regulating Fibrinogen Endocytosis and Platelet Reactivity in Non-Viral Sepsis

Project description:Platelets and megakaryocytes are critical players in immune responses. Recent reports suggest infection and inflammation alter the megakaryocyte and platelet transcriptome to induce altered platelet reactivity. We examined if non-viral sepsis induces differential platelet gene expression and reactivity. Non-viral sepsis significantly upregulated IFITM3, an interferon responsive gene that restricts viral replication

2022-12-01 | GSE210797 | 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