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Qadri S, Sohail MU, Akhtar N, Pir GJ, Yousif G, Pananchikkal SV, Al-Noubi M, Choi S, Shuaib A, Haik Y, Parray A, Schmidt F. Mass spectrometry-based proteomic profiling of extracellular vesicle proteins in diabetic and non-diabetic ischemic stroke patients: a case-control study. Front Mol Biosci 2024; 11:1387859. [PMID: 38948080 PMCID: PMC11211575 DOI: 10.3389/fmolb.2024.1387859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2024] [Accepted: 05/23/2024] [Indexed: 07/02/2024] Open
Abstract
Acute ischemic stroke is the most common cause of neurologic dysfunction caused by focal brain ischemia and tissue injury. Diabetes is a major risk factor of stroke, exacerbating disease management and prognosis. Therefore, discovering new diagnostic markers and therapeutic targets is critical for stroke prevention and treatment. Extracellular vesicles (EVs), with their distinctive properties, have emerged as promising candidates for biomarker discovery and therapeutic application. This case-control study utilized mass spectrometry-based proteomics to compare EVs from non-diabetic stroke (nDS = 14), diabetic stroke (DS = 13), and healthy control (HC = 12) subjects. Among 1288 identified proteins, 387 were statistically compared. Statistical comparisons using a general linear model (log2 foldchange ≥0.58 and FDR-p≤0.05) were performed for nDS vs HC, DS vs HC, and DS vs nDS. DS vs HC and DS vs nDS comparisons produced 123 and 149 differentially expressed proteins, respectively. Fibrinogen gamma chain (FIBG), Fibrinogen beta chain (FIBB), Tetratricopeptide repeat protein 16 (TTC16), Proline rich 14-like (PR14L), Inhibitor of nuclear factor kappa-B kinase subunit epsilon (IKKE), Biorientation of chromosomes in cell division protein 1-like 1 (BD1L1), and protein PR14L exhibited significant differences in the DS group. The pathway analysis revealed that the complement system pathways were activated, and blood coagulation and neuroprotection were inhibited in the DS group (z-score ≥2; p ≤ 0.05). These findings underscore the potential of EVs proteomics in identifying biomarkers for stroke management and prevention, warranting further clinical investigation.
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Affiliation(s)
- Shahnaz Qadri
- Department of Pharmaceutical Sciences, Irma Lerma Rangel School of Pharmacy, Texas A&M University, Kingsville, TX, United States
- Sustainability Division, College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar
| | | | - Naveed Akhtar
- The Neuroscience Institute, Academic Health System, Hamad Medical Corporation, Doha, Qatar
| | - Ghulam Jeelani Pir
- The Neuroscience Institute, Academic Health System, Hamad Medical Corporation, Doha, Qatar
| | - Ghada Yousif
- College of Health and Life Sciences, Hamad Bin Khalifa University, Doha, Qatar
| | | | - Muna Al-Noubi
- Proteomics Core, Weill Cornell Medicine, Doha, Qatar
| | - Sunkyu Choi
- Proteomics Core, Weill Cornell Medicine, Doha, Qatar
| | - Ashfaq Shuaib
- Department of Medicine, University of Alberta, Edmonton, AB, Canada
| | - Yousef Haik
- Department of Mechanical and Nuclear Engineering, University of Sharjah, Sharjah, United Arab Emirates
| | - Aijaz Parray
- The Neuroscience Institute, Academic Health System, Hamad Medical Corporation, Doha, Qatar
| | - Frank Schmidt
- Proteomics Core, Weill Cornell Medicine, Doha, Qatar
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Abstract
PURPOSE OF REVIEW Diagnosis of stroke and understanding the mechanism of stroke is critical to implement optimal treatment. RNA expressed in peripheral blood cells is emerging as a precision biomarker to aid in stroke diagnosis and prediction of stroke cause. In this review, we summarize available data regarding the role of RNA to predict stroke, the rationale for these changes, and a discussion of novel mechanistic insight and clinical applications. RECENT FINDINGS Differences in RNA gene expression in blood have been identified in patients with stroke, including differences to distinguish ischemic from hemorrhagic stroke, and differences between cardioembolic, large vessel atherosclerotic, and small vessel lacunar stroke cause. Gene expression differences show promise as novel stroke biomarkers to predict stroke of unclear cause (cryptogenic stroke). The differences in RNA expression provide novel insight to stroke mechanism, including the role of immune response and thrombosis in human stroke. Important insight to regulation of gene expression in stroke and its causes are being acquired, including alternative splicing, noncoding RNA, and microRNA. SUMMARY Improved diagnosis of stroke and determination of stroke cause will improve stroke treatment and prevention. RNA biomarkers show promise to aid in the diagnosis of stroke and cause determination, as well as providing novel insight to mechanism of stroke in patients. While further study is required, an RNA profile may one day be part of the stroke armamentarium with utility to guide acute stroke therapy and prevention strategies and refine stroke phenotype.
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Zhao S, Jiang H, Liang ZH, Ju H. Integrating Multi-Omics Data to Identify Novel Disease Genes and Single-Neucleotide Polymorphisms. Front Genet 2020; 10:1336. [PMID: 32038707 PMCID: PMC6993083 DOI: 10.3389/fgene.2019.01336] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Accepted: 12/06/2019] [Indexed: 12/15/2022] Open
Abstract
Stroke ranks the second leading cause of death among people over the age of 60 in the world. Stroke is widely regarded as a complex disease that is affected by genetic and environmental factors. Evidence from twin and family studies suggests that genetic factors may play an important role in its pathogenesis. Therefore, research on the genetic association of susceptibility genes can help understand the mechanism of stroke. Genome-wide association study (GWAS) has found a large number of stroke-related loci, but their mechanism is unknown. In order to explore the function of single-nucleotide polymorphisms (SNPs) at the molecular level, in this paper, we integrated 8 GWAS datasets with brain expression quantitative trait loci (eQTL) dataset to identify SNPs and genes which are related to four types of stroke (ischemic stroke, large artery stroke, cardioembolic stroke, small vessel stroke). Thirty-eight SNPs which can affect 14 genes expression are found to be associated with stroke. Among these 14 genes, 10 genes expression are associated with ischemic stroke, one gene for large artery stroke, six genes for cardioembolic stroke and eight genes for small vessel stroke. To explore the effects of environmental factors on stroke, we identified methylation susceptibility loci associated with stroke using methylation quantitative trait loci (MQTL). Thirty-one of these 38 SNPs are at greater risk of methylation and can significantly change gene expression level. Overall, the genetic pathogenesis of stroke is explored from locus to gene, gene to gene expression and gene expression to phenotype.
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Affiliation(s)
- Sheng Zhao
- Department of Radiology, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Huijie Jiang
- Department of Radiology, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Zong-Hui Liang
- Department of Radiology, Jian'an District Centre Hospital of Fudan University, Shanghai, China
| | - Hong Ju
- Department of Information Engineering, Heilongjiang Biological Science and Technology Career Academy, Harbin, China
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