细胞外囊泡货物作为精神分裂症分子信号的潜力:范围综述。

IF 3 Q2 PSYCHIATRY
Shivaprakash Gangachannaiah, Smita Shenoy, Dinesh Upadhya, Elstin Anbu Raj Stanly, Nachiket Gudi, Pallavi Lakshmi Chandrashekar, Samir Kumar Praharaj
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引用次数: 0

摘要

精神分裂症(SCZ)的诊断主要依赖于由训练有素的专业人员进行的临床病史和精神状态评估。人们一直在寻找生物标志物来促进实验室诊断。由于细胞外囊泡(EVs)可以与脑细胞交流,并且可以很容易地穿过血脑屏障,因此专家们越来越感兴趣地探索它们作为疾病检测的潜在分子信号。我们进行了一项范围综述,对现有文献进行全面总结,以确定从SCZ患者分离的ev中差异表达的分子信号。Arksey和O'Malley提供的方法框架大纲被用于进行范围审查。在四个数据库中使用搜索字符串进行系统搜索,最终选择出24项相关研究。从生物体液和组织中提取的ev中鉴定出超过1122种差异表达的生物分子,主要可分为rna、蛋白质和代谢物。其中,83个生物分子被鉴定为有效的差异表达分子信号,包括代谢物、circRNAs、lncRNAs、miRNAs和蛋白质。这些生物分子可影响细胞受体和细胞内通路、神经递质、线粒体功能、免疫相关功能和代谢途径,可作为SCZ诊断的潜在生物标志物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Potential of extracellular vesicle cargo as molecular signals in Schizophrenia: a scoping review.

The diagnosis of schizophrenia (SCZ) primarily relies on clinical history and mental status assessments by trained professionals. There has been a search for biomarkers to facilitate laboratory diagnosis. Since extracellular vesicles (EVs) communicate with brain cells and can easily cross blood-brain barrier, there is increased interest among experts to explore them as potential molecular signals for disease detection. A scoping review was conducted to provide a comprehensive summary of the existing literature to identify the differentially expressed molecular signals in EVs isolated from SCZ patients. The methodological framework outline provided by Arksey and O'Malley was employed to conduct this scoping review. A systematic search was conducted using a search string across four databases, ultimately leading to selection of 24 relevant studies. Over 1122 differentially expressed biomolecules were identified in EVs extracted from biological fluids and tissues that can be primarily categorized as RNAs, proteins, and metabolites. Among them, 83 biomolecules were identified as validated differentially expressed molecular signals, which included metabolites, circRNAs, lncRNAs, miRNAs, and proteins. These biomolecules were found to affect cellular receptors and intracellular pathways, neurotransmitters, mitochondrial functions, immune-related functions, and metabolic pathways, which could serve as potential biomarkers for SCZ diagnosis.

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