Serum exosomes lncRNAs: TCONS_I2_00013502 and ENST00000363624 are new diagnostic markers for rheumatoid arthritis
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE271161 | GEO | 2024/07/04
REPOSITORIES: GEO
Similar Datasets
Project description:: Tuberculosis (TB) is a transmissible disease listed as one of the 10 leading causes of death worldwide (10 million infected in 2019). A swift and precise diagnosis is essential to forestall its transmission, for which is crucial the discovery of effective diagnostic biomarkers. In this study, we aimed to discover molecular biomarkers for the early diagnosis of tuberculosis. Two independent cohorts comprising 29 and 34 subjects were assayed by proteomics, and 49 were included for metabolomic analysis. All subjects were arranged into 3 experimental groups – healthy controls (Controls), Latent TB infection (LTBI) and TB patients. LC-MS/MS blood serum protein and metabolite levels were submitted to univariate, multivariate and ROC analysis. From the 149 proteins quantified in the discovery set, 25 were found to be differentially abundant between Controls and TB patients. The AUC, specificity and sensitivity, determined by ROC statistical analysis of the model composed by four of these proteins considering both proteomic sets, were 0.96; 93% and 91%, respectively. The five metabolites (9-methyluric acid, indole-3-lactic acid, trans-3-indoleacrylic acid, hexanoylglycine and N-acetyl-L-leucine) that better discriminate the control and TB patient groups (VIP > 1.75) from a total of 92 metabolites quantified in both ionization modes, were submitted to ROC analysis. An AUC=1 was determined with all samples being correctly assigned to the respective experimental group. An integrated ROC analysis enrolling 1 protein and 4 metabolites was also performed for the common control and TB patients in the proteomic and metabolomic groups. This combined signature has correctly assigned the 12 controls and 12 patients used only for prediction (AUC=1, specificity=100% and sensitivity=100%). This multi-omics approach has revealed a biomarker signature for tuberculosis diagnosis that could be potentially used for developing a point-of-care diagnosis clinical test.
2023-03-11 | PXD037341 | Pride
Project description:Long noncoding RNAs (lncRNAs) belong to a new class of noncoding RNAs. Emerging evidence has shown that lncRNAs play a crucial role in the regulation of autoimmunity. During the past few years, the modifying effects of lncRNAs in rheumatoid arthritis (RA) have drawn much attention. However, the underlying molecular mechanisms involved in RA pathogenesis remain largely unknown. Herein, we aim to investigate the expression profile of lncRNAs in patients with RA and identify promising targets for RA diagnosis and treatment.Microarray screening and real-time PCR of lncRNAs were performed in the serum from 3 RA patients and 3 healthy controls. Significantly differentially expressed lncRNAs were selectively verified in 43 RA patients and 40 healthy controls by real-time PCR. LncRNA-mRNA co-expression and gene-pathway networks were assured in the bioinformatics analysis.After microarray analysis, there were a total of 73 up-regulated and 61 down-regulated lncRNAs as well as 128 up-regulated and 37 down-regulated mRNAs in the serum of RA patients. After validated by real-time PCR, 5 of these lncRNAs were found to be significantly up-regulated in the serum of RA patients including RNA143598, RNA143596, HIX0032090, IGHCgamma1, and XLOC_002730. Significant association was observed between these lncRNAs and the disease course, erythrocyte sedimentation rate (ESR), rheumatoid factor (RF) as well as anti-cyclic citrullinated peptide (anti-CCP) antibody. Computational analysis revealed that 55 of the differentially expressed mRNAs were associated with 41 lncRNAs involved in signaling pathways of toll like receptors (TLRs), nuclear factor-kappa B (NF-κB), and cytokine, especially the IRF3/IRF7 mediated signaling transduction.
2019-12-31 | GSE94519 | GEO
Project description:This study aimed to identify key circulating long non-coding RNAs (lncRNAs) as novel biomarkers for diagnosis of GDM at the early stages. First, lncRNA microarray analysis was conducted for plasma samples of GDM women before delivery and 48 h after delivery. The expression of differentially expressed lncRNAs in clinical samples at different trimesters was randomly validated by quantitative PCR. Moreover, the correlation between lncRNA expression and oral glucose tolerance test (OGTT) level in GDM women during the second trimester was analyzed, and the diagnostic value of key lncRNAs for GDM during different trimesters was evaluated by receiver operating characteristic (ROC) curve. The plasma level of NONHSAT054669.2 and ENST00000525337 may be used as novel diagnostic biomarkers for early diagnosis of GDM.
2022-11-07 | GSE217299 | GEO
Project description:Malondialdehyde-modified epitopes (MDA-epitopes) can elicit specific autoantibody that expressed oxidative stress arising in rheumatoid arthritis (RA). The purpose of this study was to discover and validate MDA-peptide adducts as novel biomarkers using concanavalin A affinity chromatography, 1D SDS-PAGE, in-gel digestion, and label-free nano-LC-MS, and evaluate levels of serum MDA, MDA-protein adducts, proteins and autoantibody isotypes against an unmodified and MDA-peptide from Taiwanese female patients with RA and healthy controls (HCs). Levels of serum MDA and MDA-protein adducts were significantly higher in RA patients versus HCs. Four differentially expressed novel MDA-peptides were selected that relative modification ratio were 2-fold differences to examine protein levels and assess autoantibodies to MDA-peptides in RA patients compared with HCs. Four of peptides are autoantigens. Furthermore, 4 MDA-peptides can induce more autoantibody isotypes that are statistical significance in RA patients compared to HCs. Serum IgG and IgM against MDA-peptides showed excellent diagnostic performance in discriminating among RA patients and HCs: area under the curve (AUC, 0.96 ~ 0.98), sensitivity (88.9% ~ 97.8%) and specificity (88.9% ~ 100%). Autoantibodies to MDA-epitopes indicate oxidative modifications occurring in RA, and might be useful as clinical markers fro RA diagnosis if further investigated.
2021-02-25 | PXD004546 | Pride
Project description:Objective:This study aims to discover circulating exosomal miRNAs as potential noninvasive biomarkers early detection of fetus with ventricular septal defect (VSD). Method:A total of 182 pregnant women including 91 VSD cases and 91 matched controls were included in this study. Exosomes were isolated and next-generation sequencing was used to obtain a profile of dysregulated exosomal miRNA. The differential abundance was verified by quantitative real-time PCR (q RT-PCR). . Receiver operating characteristic (ROC) curves were conducted to evaluate the diagnostic accucary Results: 77 serum exosomal miRNA were uncovered to be differentially expressed in the VSD group as compared to the control group. Among these, five down-regulated exosomal miRNA were validated by qRT-PCR. hsa-miR-146a-5p was identified to be capable of distinguishing VSDs from controls (area under the ROC (AUC): 0.997; p < 2.2e-16). Conclusion: circulating exosomal miRNA, in particular, hsa-miR-146a-5pmay be a predictive biomarker for non-invasive prenatal diagnosis of fetal VSDs.
2021-06-05 | GSE176134 | GEO
Project description:Purpose: The purpose of this study is to apply RNA-Seq to identify diffeerentially expressed RNA in hepatocellular-derived serum exosomes compared with non hepatocellular carcinoma derived serum exosomes to evaluate prognosis-related and tumorigenesis-related potential biomarkers. Methods: Genome profiles of serum exosomes isolated from liver cirrohosis subjects, early-stage HCC subjects amd advanced stage HCC subjects respectively were generated by deep sequencing, using Illumina. The sequence reads that passed quality filters were aligned and analyzed using HISAT2 and STRINGTIE. The constructed transcriptome profiles were conveyed to further analysis. Results: With the help of RNA-Seq technology, 58,243 genes and 200,478 transcripts were aligned, and genome and transcriptome RNA-Seq archives were constructed, showcasing the abundance and depth of our sequencing. Then we systematically screened the RNA type, and selected long non-coding RNA (lncRNA) expression profiles. We used DESeq2 algorithm and set |log2 (fold-change)|>1 and P-value <0.05 as criteria. Finally we discovered 2,070 genes, 6,543 transcripts, 942 lncRNAs were differentially expressed in group advanced stage HCC compared with group liver cirrohosis. 1,600 genes, 6,904 transcripts, 1,067 lncRNAs were differentially expressed in group early stage HCC compared with group liver cirrohosis. Conclusions: Our study creatively represented the detailed analysis of serum exosomes genomes and transcriptomes, which were generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that compared with liver cirrohosis serum exosome samples, the early-stage and advanced stage hepatocellular carcinoma groups detected some unique differential mRNAs and miRNAs, which can be potential biomarkers.
2022-03-30 | GSE199509 | GEO
Project description:Purpose: This study aimed to explore the differential expression profiles of exosomal lncRNAs and evaluated their potential utility in the accurate diagnosis of LAA stroke. Methods: LncRNA profiles of exosomes in large artery atherosclerosis stroke and controls were generated by high-throughput sequencing. The sequence reads that passed quality filters were analyzed at the transcript isoform level with Hisat2, Trapnell, STAR. qRT–PCR validation was performed using TaqMan and SYBR Green assays. Results: A total of 1020 differentially expressed lncRNAs were identified in LAA stroke patients. GO and KEGG pathway analyses indicated that their target genes are involved in atherosclerosis-related pathways, including inflammation, cell adhesion, and cell migration. 8 exosomal lncRNAs were confirmed with qRT–PCR.The result showed that the expression trend of differential expressed lncRNAs in validation was consistent with RNA-seq.Conclusion: Our study showed the differential expression of lncRNAs in plasma exosomes and presented related diagnostic potential for LAA stroke for the first time. The results suggested that exosomal lncRNA could be potential diagnostic tools in LAA stroke. Circular RNAs (circRNAs), novel endogenous noncoding RNAs, play diverse roles in ischemic stroke. Recently, the abundance and stability of circRNAs in exosomes have been identified. However, a comprehensive analysis of exosomal circRNAs in large artery atherosclerotic (LAA) stroke has not yet been reported. We performed RNA sequencing (RNA-Seq) to comprehensively identify differentially expressed exosomal circRNAs in five paired LAA and normal controls. RNA-Seq identified a total of 462 circRNAs in peripheral exosomes; there were 25 differentially expressed circRNAs among them. Additionally, circRNA competing endogenous RNA (ceRNA) network and translatable analysis revealed the potential functions of the exosomal circRNAs in LAA progression. Two ceRNA pathways involving 5 circRNAs, 2 miRNAs, and 3 mRNAs were confirmed by qRT-PCR. In the validation cohort, receiver operating characteristic (ROC) curve analysis identified two circRNAs as possible novel biomarkers, and a logistic model combining two and four circRNAs increased the area under the curve compared with the individual circRNAs.
2021-06-08 | GSE173719 | GEO
Project description:Cardiac myxoma (CM) is an important aetiology of stroke in young adults, and its diagnosis is difficult in patients having stroke because of the lack of diagnostic biomarkers. Tumour-derived exosomes play a crucial role in tumour growth, metastasis, and immune regulation, and monitor disease development. We established an RNA-sequencing dataset for long non-coding RNA (lncRNA), microRNA (miRNA), and messenger RNA (mRNA) in the plasma and tumour-derived exosomes from four patients with cardiac myxoma-related ischaemic stroke (CM-IS) and six patients with cardiac myxoma without ischaemic stroke (non-IS CM). Clean data (15.48 Gb) were obtained for lncRNAs and mRNAs. Moreover, 5,533 lncRNAs, 1,331 known miRNAs, and 412 new miRNAs were identified. Finally, gene expression profiles and differentially expressed genes were analysed in 20 samples. In the plasma samples, 74 miRNAs, 12 lncRNAs, and 693 mRNAs were identified. Tumour-derived tissue samples contained 61 miRNAs, 67 lncRNAs, and 433 mRNAs. This dataset provides a significant resource for relevant researchers to explore the potential dysregulated lncRNAs, miRNAs, and mRNAs of plasma and tumour-derived exosomes in CM-IS versus CM without stroke.
2024-10-25 | GSE272078 | GEO
Project description:Cardiac myxoma (CM) is an important aetiology of stroke in young adults, and its diagnosis is difficult in patients having stroke because of the lack of diagnostic biomarkers. Tumour-derived exosomes play a crucial role in tumour growth, metastasis, and immune regulation, and monitor disease development. We established an RNA-sequencing dataset for long non-coding RNA (lncRNA), microRNA (miRNA), and messenger RNA (mRNA) in the plasma and tumour-derived exosomes from four patients with cardiac myxoma-related ischaemic stroke (CM-IS) and six patients with cardiac myxoma without ischaemic stroke (non-IS CM). Clean data (15.48 Gb) were obtained for lncRNAs and mRNAs. Moreover, 5,533 lncRNAs, 1,331 known miRNAs, and 412 new miRNAs were identified. Finally, gene expression profiles and differentially expressed genes were analysed in 20 samples. In the plasma samples, 74 miRNAs, 12 lncRNAs, and 693 mRNAs were identified. Tumour-derived tissue samples contained 61 miRNAs, 67 lncRNAs, and 433 mRNAs. This dataset provides a significant resource for relevant researchers to explore the potential dysregulated lncRNAs, miRNAs, and mRNAs of plasma and tumour-derived exosomes in CM-IS versus CM without stroke.
2024-10-25 | GSE272079 | GEO
Project description:Rheumatoid arthritis (RA) causes serious disability and productivity loss, and there is an urgent need for appropriate biomarkers for diagnosis, treatment assessment, and prognosis evaluation. To identify serum markers of RA, we performed mass spectrometry (MS)-based proteomics, and we obtained 24 important markers in normal and RA patient samples using a random forest machine learning model and 11 protein-protein interaction (PPI) network topological analysis methods. Re-analyze markers using additional proteomics datasets, immune infiltration status, tissue specificity, subcellular localization, correlation analysis with disease activity-based diagnostic indications, diagnostic receiver-operating characteristic analysis We discovered that ORM1 in serum is significantly differentially expressed in normal and RA patient samples, which is positively correlated with disease activity, and is closely related to CD56dim natural killer cell, effector memory CD8+ T cell and natural killer cell in the pathological mechanism, which can be better utilized for diagnosis, monitoring disease progression and efficacy assessment. This study supplies a comprehensive strategy for discovering potential serum biomarkers of RA, and provides a different perspective for comprehending the pathological mechanism of RA, identifying potential therapeutic targets, and disease management.
2022-04-19 | PXD032912 | Pride