Dataset Information

Large-Scale Profiling on lncRNAs in Human Platelets: Correlation with Platelet Reactivity.

ABSTRACT: Recently, long noncoding RNAs (lncRNAs) have been key regulators for both mRNAs and proteins in nucleated cells. However, the expression profiles of lncRNAs in non-nucleated cells such as platelets are currently unclear. In this study, we determined the expression profiles of lncRNAs in human platelets. We found that 6109 lncRNAs were expressed in human platelets. Interestingly, 338 lncRNAs were differentially expressed in hyperreactive and hyporeactive platelets. Bioinformatics' analysis revealed that these aberrantly expressed lncRNAs might be related to platelet activity and other platelet functions. To provide a proof of concept, we measured the expression levels of PARLncRNA-1, a down-regulated lncRNA of hyperreactive platelets, in platelets from 12 patients with acute myocardial infarction and their controls. We found that the lncRNA was also significantly down-regulated in platelets from patients, which was partially reversed by treatment with aspirin a known antiplatelet drug. LncRNAs may represent a novel class of modulators for platelet functions.

SUBMITTER: Sun Y

PROVIDER: S-EPMC9319970 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Large-Scale Profiling on lncRNAs in Human Platelets: Correlation with Platelet Reactivity.

Sun Yeying Y Liu Rongrong R Xia Xiangwen X Xing Luchuan L Jiang Jing J Bian Weihua W Zhang Wendy W Wang Chunhua C Zhang Chunxiang C

Cells 20220721 14

Recently, long noncoding RNAs (lncRNAs) have been key regulators for both mRNAs and proteins in nucleated cells. However, the expression profiles of lncRNAs in non-nucleated cells such as platelets are currently unclear. In this study, we determined the expression profiles of lncRNAs in human platelets. We found that 6109 lncRNAs were expressed in human platelets. Interestingly, 338 lncRNAs were differentially expressed in hyperreactive and hyporeactive platelets. Bioinformatics' analysis reveal ...[more]

PMID: 35883699

Similar Datasets

Project description:The aim was to study the genetic correlation and causal relationship between spondyloarthritis (SpA) and blood metabolites based on the large-scale genome-wide association study (GWAS) summary data. The GWAS summary data (3966 SpA and 448,298 control cases) of SpA were from the UK Biobank, and the GWAS summary data (486 blood metabolites) of human blood metabolites were from a published study. First, the genetic correlation between SpA and blood metabolites was analyzed by linkage disequilibrium score (LDSC) regression. Next, we used Mendelian randomization (MR) analysis to perform access causal relationship between SpA and blood metabolites. Random effects inverse variance weighted (IVW) was the main analysis method, and the MR Egger, weighted median, simple mode, and weighted mode were supplementary methods. The MR analysis results were dominated by the random effects IVW. The Cochran's Q statistic (MR-IVW) and Rucker's Q statistic (MR Egger) were used to check heterogeneity. MR Egger and MR pleiotropy residual sum and outlier (MR-PRESSO) were used to check horizontal pleiotropy. The MR-PRESSO was also used to check outliers. The "leave-one-out" analysis was used to assess whether the MR analysis results were affected by a single SNP and thus test the robustness of the MR results. Finally, we identified seven blood metabolites that are genetically related to SpA: X-10395 (correlation coefficient = -0.546, p = 0.025), pantothenate (correlation coefficient = -0.565, p = 0.038), caprylate (correlation coefficient = -0.333, p = 0.037), pelargonate (correlation coefficient = -0.339, p = 0.047), X-11317 (correlation coefficient = -0.350, p = 0.038), X-12510 (correlation coefficient = -0.399, p = 0.034), and X-13859 (Correlation coefficient = -0.458, p = 0.015). Among them, X-10395 had a positive genetic causal relationship with SpA (p = 0.014, OR = 1.011). The blood metabolites that have genetic correlation and causal relationship with SpA found in this study provide a new idea for the study of the pathogenesis of SpA and the determination of diagnostic indicators.

Project description:BackgroundEvolving evidence suggests that besides signaling pathways, platelet activation involves a complex interplay between metabolic pathways to support thrombus growth. Selective targeting of metabolic checkpoints may inhibit platelet activation and provide a novel antiplatelet strategy. We, therefore, examined global metabolic changes that occur during the transition of human platelets from resting to an activated state to identify metabolites and associated pathways that contribute to platelet activation.MethodsWe performed metabolic profiling of resting and convulxin-stimulated human platelet samples. The differential levels, pathway analysis, and PCA (principal component analysis) were performed using Metaboanalyst. Metascape was used for metabolite network construction.ResultsOf the 401 metabolites identified, 202 metabolites were significantly upregulated, and 2 metabolites were downregulated in activated platelets. Of all the metabolites, lipids scored highly and constituted ≈50% of the identification. During activation, aerobic glycolysis supports energy demand and provides glycolytic intermediates required by metabolic pathways. Consistent with this, an important category of metabolites was carbohydrates, particularly the glycolysis intermediates that were significantly upregulated compared with resting platelets. We found that lysophospholipids such as 1-palmitoyl-GPA (glycero-3-phosphatidic acid), 1-stearoyl-GPS (glycero-3-phosphoserine), 1-palmitoyl-GPI (glycerophosphoinositol), 1-stearoyl-GPI, and 1-oleoyl-GPI were upregulated in activated platelets. We speculated that platelet activation could be linked to 1-carbon metabolism, a set of biochemical pathways that involve the transfer and use of 1-carbon units from amino acids, for cellular processes, including nucleotide and lysophospholipid synthesis. In alignment, based on pathway enrichment and network-based prioritization, the metabolites from amino acid metabolism, including serine, glutamate, and branched-chain amino acid pathway were upregulated in activated platelets, which might be supplemented by the high levels of glycolytic intermediates.ConclusionsMetabolic analysis of resting and activated platelets revealed that glycolysis and 1-carbon metabolism are necessary to support platelet activation.

Dataset Information

Large-Scale Profiling on lncRNAs in Human Platelets: Correlation with Platelet Reactivity.

Publications

Large-Scale Profiling on lncRNAs in Human Platelets: Correlation with Platelet Reactivity.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets