Identification of Blood Biomarkers in Ischemic Stroke by Integrated Analysis of Metabolomics and Proteomics DOI
Tian Zhao, Jingjing Zeng, Ruijie Zhang

и другие.

Journal of Proteome Research, Год журнала: 2024, Номер 23(9), С. 4082 - 4094

Опубликована: Авг. 21, 2024

We aimed to uncover the pathological mechanism of ischemic stroke (IS) using a combined analysis untargeted metabolomics and proteomics. The serum samples from discovery set 44 IS patients matched controls were analyzed specific detection method. same method was then used validate metabolites proteins in two validation sets: one with 30 controls, other 50 controls. A total 105 221 differentially expressed or identified, association between omics determined set. Enrichment top 25 two-way orthogonal partial least-squares discriminant analysis, which employed identify highly correlated biomarkers, highlighted 15 pathways relevant process. One metabolite seven exhibited differences groups binary logistic regression model, included 2-hydroxyhippuric acid APOM_O95445, MASP2_O00187, PRTN3_D6CHE9, achieved an area under curve 0.985 (95% CI: 0.966–1) This study elucidated alterations potential coregulatory influences blood patients.

Язык: Английский

Identification of Novel Biomarkers for Ischemic Stroke Through Integrated Bioinformatics Analysis and Machine Learning DOI

Juan Jia,

Liang Niu, Peng Feng

и другие.

Journal of Molecular Neuroscience, Год журнала: 2025, Номер 75(1)

Опубликована: Янв. 25, 2025

Язык: Английский

Процитировано

2

Identification of Cardiometabolic Protein Biomarkers for Acute Myocardial Infarction Using Olink Proteomics DOI Creative Commons

Xin Tan,

Xiangyu Wang,

Shuai Xu

и другие.

Journal of Inflammation Research, Год журнала: 2025, Номер Volume 18, С. 2629 - 2646

Опубликована: Фев. 1, 2025

Acute myocardial infarction (AMI) is a critical cardiovascular event characterized by sudden coronary blood flow interruption, leading to ischemia and necrosis. Despite advances in acute therapeutic measures, understanding the metabolic damage related AMI, particularly through specific protein expressions, remains limited. This study utilized Olink metabolomics technology explore metabolism-related biomarkers associated with aiming address clinical need for early diagnosis targeted therapy. analyze 92 proteins samples from 20 AMI patients 10 healthy controls. Differentially expressed were identified using statistical t-tests, followed functional enrichment analysis (GO KEGG) protein-protein interaction network construction. Five core validated plasma an additional 125 120 controls via enzyme-linked immunosorbent assay. To evaluate diagnostic performance, receiver operating characteristic curves generated GEO-related datasets, Mendelian randomization was employed investigate causal relationship between risk. The 32 significantly altered expression levels Among these, five proteins-PCOLCE, FCN2, REG1A, DEFA1, CRTAC1-were key biological processes such as metabolism, collagen formation, PI3K/AKT signaling pathway. These showed strong correlations indicators, including BMI, LVEF, NT-proBNP, CK-MB, cTnT. FCN2 DEFA1 further having risk, indicating their potential biomarkers. PCOLCE, CRTAC1 are risk assessment of AMI. findings suggest that these could serve targets future interventions aimed at mitigating

Язык: Английский

Процитировано

0

Olink Profiling of Intestinal Tissue Identifies Novel Biomarkers For Colorectal Cancer DOI Creative Commons
Chong Xiao, Hao Wu, Jing Long

и другие.

Journal of Proteome Research, Год журнала: 2025, Номер 24(2), С. 599 - 611

Опубликована: Янв. 6, 2025

Comprehensive protein profiling in intestinal tissues provides detailed information about the pathogenesis of colorectal cancer (CRC). This study quantified expression levels 92 oncology-related proteins tumors, paired para-carcinoma tissues, and remote normal from a cohort 52 CRC patients utilizing Olink technology. The proteomic profile closely resembled that while distinctly differing tumors. Among 68 differentially expressed (DEPs) identified between tumor WISP-1, ESM-1, TFPI-2 showed most pronounced alterations exhibited relatively strong correlations. These markers also presented highest AUC values for distinguishing tissue types. Bioinformatic analysis DEPs revealed plasma membrane PI3K-AKT signaling pathway were among enriched GO terms KEGG pathways. Furthermore, although is typically recognized as suppressor, both enzyme linked immunosorbent assay (ELISA) analyses have demonstrated its significantly elevated tumors compared with tissues. To best our knowledge, this first to proteome using work offers valuable insights into potential biomarkers therapeutic targets CRC, complementing circulating proteins.

Язык: Английский

Процитировано

0

Large-Scale Proteomics Improve Prediction of Chronic Kidney Disease in People With Diabetes DOI
Ziliang Ye, Yuanyuan Zhang, Yanjun Zhang

и другие.

Diabetes Care, Год журнала: 2024, Номер 47(10), С. 1757 - 1763

Опубликована: Июль 23, 2024

OBJECTIVE To develop and validate a protein risk score for predicting chronic kidney disease (CKD) in patients with diabetes compare its predictive performance validated clinical model (CKD Prediction Consortium [CKD-PC]) CKD polygenic score. RESEARCH DESIGN AND METHODS This cohort study included 2,094 who had proteomics genetic information no history of at baseline from the UK Biobank Pharma Proteomics Project. Based on nearly 3,000 plasma proteins, including 11 proteins was constructed training set (including 1,047 participants; 117 events). RESULTS The median follow-up duration 12.1 years. In test 112 events), positively associated incident (per SD increment; hazard ratio 1.78; 95% CI 1.44, 2.20). Compared basic (age + sex race, C-index, 0.627; 0.578, 0.675), (C-index increase 0.122; 0.071, 0.177), CKD-PC factors 0.175; 0.126, 0.217) significantly improved prediction CKD, but 0.007; −0.016, 0.025) significant improvement. Adding into largest C-index 0.825 0.802 to 0.825; difference 0.023; 0.006, 0.044), continuous 10-year net reclassification (0.199; 0.059, 0.299) integrated discrimination index (0.041; 0.007, 0.083). CONCLUSIONS diabetes.

Язык: Английский

Процитировано

2

Multi-targeted olink proteomics analyses of cerebrospinal fluid from patients with aneurysmal subarachnoid hemorrhage DOI Creative Commons
Rui Ding,

Liquan Wu,

Shanshan Wei

и другие.

Proteome Science, Год журнала: 2024, Номер 22(1)

Опубликована: Ноя. 27, 2024

The complexity of delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage (aSAH) may require the simultaneous analysis variant types protein biomarkers to describe it more accurately. In this study, we analyzed for first time alterations cerebrospinal fluid (CSF) proteins in patients with aSAH by multi-targeted Olink proteomics, aiming reveal pathophysiology DCI and provide insights into diagnosis treatment aSAH. Six six control were selected, CSF samples Proteomics (including 96-neurology panel 96-inflammation panel) based on Proximity Extension Assay (PEA). Differentially expressed (DEPs) acquired bioinformatics was performed. PCA revealed better intra- inter-group reproducibility groups. 23 neurology-related 31 inflammation-relevant differential identified. neurology panel, compared controls, up-regulated SAH predominantly included macrophage scavenger receptor 1 (MSR1), siglec-1, siglec-9, cathepsin C (CTSC), S (CTSS), etc. Meanwhile, inflammation group, incremental mainly contained interleukin-6 (IL-6), MCP-1, CXCL10, CXCL-9, TRAIL, Cluster exhibited significant differences between two GO function enrichment hinted that pertinent involved regulation defense response, vesicle-mediated transport immune response; while related largely connected cellular response chemokine, chemokine chemokine-mediated signaling pathway. Additionally, KEGG indicated significantly enriched phagosome, apoptosis microRNAs cancer And pathway, viral interaction cytokine toll-like These identified unique pathophysiological characteristics secondary Further characterization these aberrant pathways future research could enable their application as potential therapeutic targets

Язык: Английский

Процитировано

1

VASP, HCLS1, MSN, and EZR: Key molecular beacons in the pathophysiology of perihematomal edema Post-Intracerebral hemorrhage DOI Creative Commons
Jingjing Chen, Yi Zhong,

Xueshun Xie

и другие.

Brain Hemorrhages, Год журнала: 2024, Номер 5(5), С. 223 - 232

Опубликована: Апрель 17, 2024

Perihematomal edema (PHE) is one of the significant secondary cerebral damages, with blood–brain barrier's integrity playing a pivotal role in its progression. Strengthening tight junction (TJ) proteins enhances barrier integrity, yet complex genetics behind brain remain not fully understood. Our research endeavors to uncover genes and their roles following hemorrhage, investigate potential treatment strategies. By analyzing intracerebral hemorrhage (ICH) control samples using GSE216607 GSE206971 datasets, we identified differentially expressed genes. Cross-referencing KEGG database, aligned these those related junctions. Extensive enrichment analysis protein interactions were performed examine expression clinical significance study employed C57BL/6J mouse ICH model qRT-PCR for key gene validation. Notably, VASP, HCLS1, MSN, EZR, critical junctions, showed increased post-ICH, emphasizing BBB upkeep PHE Drug validation indicated therapeutic effects Testosterone enanthate, SELENIUM, LY 294002 on junction-related This sheds light involvement progression offering promising targets. Further needed deeper understanding.

Язык: Английский

Процитировано

0

Multiomics Profiling of Plasma Reveals Molecular Alterations Prior to a Diagnosis with Stroke Among Chinese Hypertension Patients DOI
Jingjing Zeng, Changyi Wang,

Jiamin Guo

и другие.

Journal of Proteome Research, Год журнала: 2024, Номер unknown

Опубликована: Окт. 28, 2024

We aimed to investigate the correlation between plasma proteins and metabolites occurrence of future strokes using mass spectrometry bioinformatics as well identify other biomarkers that could predict stroke risk in hypertensive patients. In a nested case-control study, baseline samples were collected from 50 subjects who developed gender-, age- body index-matched controls. Plasma untargeted metabolomics data independent acquisition-based proteomics analysis performed patients, 19 111 found be differentially expressed. Integrative analyses revealed molecular changes indicated dysregulation protein digestion absorption, salivary secretion, regulation actin cytoskeleton, along with significant metabolic suppression. C4BPA, Caprolactam, Col15A1, HBB identified predictors occurrence, Support Vector Machines (SVM) model was determined optimal predictive by integrating six machine-learning classification models. The SVM showed strong performance both internal validation set (area under curve [AUC]: 0.977, 95% confidence interval [CI]: 0.941-1.000) external (AUC: 0.973, CI: 0.921-0.999).

Язык: Английский

Процитировано

0

Identification of Blood Biomarkers in Ischemic Stroke by Integrated Analysis of Metabolomics and Proteomics DOI
Tian Zhao, Jingjing Zeng, Ruijie Zhang

и другие.

Journal of Proteome Research, Год журнала: 2024, Номер 23(9), С. 4082 - 4094

Опубликована: Авг. 21, 2024

We aimed to uncover the pathological mechanism of ischemic stroke (IS) using a combined analysis untargeted metabolomics and proteomics. The serum samples from discovery set 44 IS patients matched controls were analyzed specific detection method. same method was then used validate metabolites proteins in two validation sets: one with 30 controls, other 50 controls. A total 105 221 differentially expressed or identified, association between omics determined set. Enrichment top 25 two-way orthogonal partial least-squares discriminant analysis, which employed identify highly correlated biomarkers, highlighted 15 pathways relevant process. One metabolite seven exhibited differences groups binary logistic regression model, included 2-hydroxyhippuric acid APOM_O95445, MASP2_O00187, PRTN3_D6CHE9, achieved an area under curve 0.985 (95% CI: 0.966–1) This study elucidated alterations potential coregulatory influences blood patients.

Язык: Английский

Процитировано

0