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Urinary proteomics identifying novel biomarkers for the diagnosis and phenotyping of carotid artery stenosis

ABSTRACT: We used the data-independent acquisition (DIA) technique to conduct a urinary proteomic study in patients with CAS and healthy controls.

ORGANISM(S): Homo Sapiens

SUBMITTER: Yuehong Zheng

PROVIDER: PXD026501 | iProX | Fri Jun 04 00:00:00 BST 2021

REPOSITORIES: iProX

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Urinary Proteomics Identifying Novel Biomarkers for the Diagnosis and Phenotyping of Carotid Artery Stenosis.

Wang Wei W Wu Jianqiang J Liu Peng P Tang Xiaoyue X Pang Haiyu H Xie Ting T Xu Fang F Shao Jiang J Chen Yuexin Y Liu Bao B Zheng Yuehong Y

Frontiers in molecular biosciences 20210810

<b>Background:</b> Carotid artery stenosis (CAS) is caused by the formation of atherosclerotic plaques inside the arterial wall and accounts for 20-30% of all strokes. The development of an early, noninvasive diagnostic method and the identification of high-risk patients for ischemic stroke is essential to the management of CAS in clinical practice. <b>Methods:</b> We used the data-independent acquisition (DIA) technique to conduct a urinary proteomic study in patients with CAS and healthy contr ...[more]

PMID: 34447787

Similar Datasets

Urinary Proteomics Identifying Novel Biomarkers for the Diagnosis and Phenotyping of Carotid Artery Stenosis.

Project description:Background: Carotid artery stenosis (CAS) is caused by the formation of atherosclerotic plaques inside the arterial wall and accounts for 20-30% of all strokes. The development of an early, noninvasive diagnostic method and the identification of high-risk patients for ischemic stroke is essential to the management of CAS in clinical practice. Methods: We used the data-independent acquisition (DIA) technique to conduct a urinary proteomic study in patients with CAS and healthy controls. We identified the potential diagnosis and risk stratification biomarkers of CAS. And Ingenuity pathway analysis was used for functional annotation of differentially expressed proteins (DEPs). Furthermore, receiver operating characteristic (ROC) analysis was performed to evaluate the diagnostic values of DEPs. Results: A total of 194 DEPs were identified between CAS patients and healthy controls by DIA quantification. The bioinformatics analysis showed that these DEPs were correlated with the pathogenesis of CAS. We further identified 32 DEPs in symptomatic CAS compared to asymptomatic CAS, and biological function analysis revealed that these proteins are mainly related to immune/inflammatory pathways. Finally, a biomarker panel of six proteins (ACP2, PLD3, HLA-C, GGH, CALML3, and IL2RB) exhibited potential diagnostic value in CAS and good discriminative power for differentiating symptomatic and asymptomatic CAS with high sensitivity and specificity. Conclusions: Our study identified novel potential urinary biomarkers for noninvasive early screening and risk stratification of CAS.

| S-EPMC8383446 | biostudies-literature

Urinary exosomal long noncoding RNAs may be novel biomarkers for the diagnosis of clear cell renal cell carcinoma

Project description:Background: Renal cell carcinoma, which presents no significant clinical manifestations at early stages, is one of the few tumors with an increasing worldwide incidence. This malignancy cannot be directly detected by tumor markers in body fluid without information from imaging examinations. Approximately 30–40% of patients with kidney cancer exhibit distant metastasis at diagnosis, and their 5-year survival rate is much lower than that of patients with early-stage renal cell carcinoma. Thus, the early diagnosis of renal cell carcinoma is extremely important. The aim of this study was to investigate the utility of urinary exosomal long noncoding RNA (lncRNA) as a new potential diagnostic marker for renal cell carcinoma. Methods: Exosomes were isolated by ultracentrifugation from 50-ml urine samples from 10 patients with clear cell renal cell carcinoma and 10 matched healthy donors. Differentially expressed lncRNAs were analyzed by next-generation sequencing and further validated in kidney cancer cell lines, tissues and urinary exosomes. Then, we evaluated the sensitivity, specificity, clinical diagnostic value and stability of the selected lncRNAs. Results: The levels of lncRNAs NR_040448 and NR_033390 in urinary exosomes can likely indicate the presence of renal cell carcinoma. In addition, RNA protected by exosomes was stable enough to serve as a biomarker. Conclusion: Urinary exosomal lncRNA is a promising marker for the early diagnosis of renal cell carcinoma.

2019-01-23 | GSE125442 | GEO

Identifying urinary RNA as non-invasive biomarkers for progression of chronic kidney disease

Project description:To identify urinary RNA as non-invasive biomarkers for progression of chronic kidney disease

2018-10-31 | GSE121978 | GEO

Identification of urinary exosomal non-coding RNAs as novel biomarkers in chronic kidney disease

Project description:We aimed to identify urinary exosomal ncRNAs as novel biomarkers for diagnosis of Chronic Kidney Disease (CKD) for this, we examined 15 exosomal ncRNA profiles in urine samples from CKD patients from four different stages (I, II, III and IV) and compared them to 10 healthy controls. We identified a significant number of novel, differentially expressed ncRNAs in CKD patients compared to healthy, which might be employed as early diagnostic markers in CKD in the future.

2016-11-30 | E-MTAB-5152 | biostudies-arrayexpress

Identifying urinary RNA from prospective urine as non-invasive biomarkers for kidney transplant patients

Project description:To identify urinary RNA from prospective urine as non-invasive biomarkers for kidney transplant patients

2019-03-16 | GSE128347 | GEO

Identifying urinary RNA from biopsy associated urine as non-invasive biomarkers for kidney transplant patients

Project description:To identify urinary RNA from biopsy associated urine as non-invasive biomarkers for kidney transplant patients

2019-03-16 | GSE128348 | GEO

Urinary Proteomics Identifying Novel Biomarkers for the Diagnosis of Adult-Onset Still's Disease.

Project description:Adult-onset Still's disease (AOSD) is a systemic, multigenic autoinflammatory disease, and the diagnosis of AOSD must rule out neoplasms, infections, and other autoimmune diseases. Development of a rapid and efficient but non-invasive diagnosis method is urgently needed for improving AOSD therapy. In this study, we first performed a urinary proteomic study using isobaric tags for relative and absolute quantification (iTRAQ) labeling combined with liquid chromatography-tandem mass spectrometry analysis in patients with AOSD and healthy control (HC) subjects. The urinary proteins were enriched in pathways of the innate immune system and neutrophil degranulation, and we identified that the α-1-acid glycoprotein 1 (LRG1), orosomucoid 1 (ORM1), and ORM2 proteins were highly expressed in patients with AOSD. The elevated urine levels of LRG1, ORM1, and ORM2 were further validated by enzyme-linked immunosorbent assay in active patients with AOSD, disease controls, and HC subjects. Receiver operating characteristic curves showed that the areas under the curve of LRG1, ORM1, and ORM2 were 0.700, 0.837, and 0.736, respectively (all p < 0.05). Furthermore, we found that the urine levels of LRG1, ORM1, and ORM2 were positively correlated with the systemic score and erythrocyte sedimentation rate and that the urine levels of LRG1 were positively correlated with interleukin 1β (IL-1β), IL-6, and IL-18 levels, whereas the urine levels of ORM1 were positively correlated with the IL-1β level. Together, our study identified novel urinary markers for non-invasive and simple screening of AOSD.

| S-EPMC7500098 | biostudies-literature

Development and validation of urinary exosomal microRNA biomarkers for the diagnosis of acute rejection in kidney transplant recipients

Project description:Acute rejection prediction classifiers were successfully constructed through expression profiling of a total of 개수 urinary exosomal microRNAs in 108 kidney transplant recipients.

2023-05-08 | GSE230858 | GEO

A novel urinary microRNA biomarker panel for detecting gastric cancer

Project description:Purpose: Gastric cancer (GC) is one of the most common causes of cancer deaths worldwide; however, reliable and non-invasive screening methods for GC are not established. Therefore, we conducted this study to develop a biomarker for GC detection, consisting of urinary microRNAs (miRNAs). Experimental Design: We matched 306 participants by age and sex (153 pairs consisting of patients with GC and healthy controls [HCs]), then randomly divided them across three groups: (1) the discovery cohort (4 pairs); (2) the training cohort (95 pairs); (3) the validation cohort (54 pairs). Moreover, 64 participants (32 pairs) with serum samples were also enrolled in the serum cohort. Result: There were 22 urinary miRNAs with significantly aberrant expressions between the two groups in the discovery cohort. Upon multivariate analysis of the training cohort, urinary expression levels of miR-6807-5p and miR-6856-5p were significantly independent biomarkers for diagnosis of GC, in addition to Helicobacter pylori (H. pylori) status. A diagnostic panel that combined the aberrant miRNAs and H. pylori status distinguished between HC and GC samples with an area under the curve (AUC) = 0.736. In the validation cohort, urinary miR-6807-5p and miR-6856-5p showed significantly higher expression levels in the GC group, and the combination biomarker panel of miR-6807-5p, miR-6856-5p, and H. pylori status also showed excellent performance (AUC = 0.885). In addition, serum levels of miR-6807-5p and miR-6856-5p were significantly higher in the GC group. Conclusion: This novel biomarker panel enables early and non-invasive detection of GC.

2019-12-22 | GSE128720 | GEO

Urinary exosomal miRNA signatures in type II diabetic nephropathy patients

Project description:Urinary exosomal miRNA profiling was conducted in urinary exosomes obtained from 8 healthy controls (C), 8 patients with type II diabetes (T2D) and 8 patients with type II diabetic nephropathy (DN) using AgilentÂ´s miRNA microarrays.

2016-11-03 | E-MTAB-4166 | biostudies-arrayexpress

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