moyamoya病的多组学和基于血液的生物标记物:Moyamoya Omics Atlas(MOYAOMICS)协议。

Q2 Medicine
Peicong Ge, Zihan Yin, Chuming Tao, Chaofan Zeng, Xiaofan Yu, Shixiong Lei, Junsheng Li, Yuanren Zhai, Long Ma, Qiheng He, Chenglong Liu, Wei Liu, Bojian Zhang, Zhiyao Zheng, Siqi Mou, Zhikang Zhao, Shuang Wang, Wei Sun, Min Guo, Shuai Zheng, Jia Zhang, Xiaofeng Deng, Xingju Liu, Xun Ye, Qian Zhang, Rong Wang, Yan Zhang, Shaosen Zhang, Chengjun Wang, Ziwen Yang, Nijia Zhang, Mingxing Wu, Jian Sun, Yujia Zhou, Zhiyong Shi, Yonggang Ma, Jianpo Zhou, Shaochen Yu, Jiaxi Li, Junli Lu, Faliang Gao, Wenjing Wang, Yanming Chen, Xingen Zhu, Dong Zhang, Jizong Zhao
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引用次数: 0

摘要

背景:莫亚莫亚病(MMD)是一种罕见而复杂的脑血管疾病,其特点是颈内动脉逐渐狭窄,并形成代偿性侧支血管。梅诺卡亚病的病因至今仍是个谜,因此诊断和治疗都具有挑战性。MOYAOMICS项目旨在研究MMD的分子基础,并探索潜在的诊断和治疗策略:方法:MOYAOMICS 项目采用多学科方法,整合了包括基因组学、转录组学、蛋白质组学和代谢组学在内的各种 omics 技术,全面研究与 MMD 发病机制相关的分子特征。此外,我们还将研究肠道微生物群和脑-肠肽对多发性硬化症发病的潜在影响,评估它们是否适合作为治疗策略和饮食干预的目标。放射组学是医学成像的一个专业领域,我们将利用它来分析神经成像数据,以便及早发现和描述与多发性硬化症相关的脑部变化。我们采用深度学习算法来区分多发性硬化症和其他疾病,使诊断过程自动化。我们还利用单细胞组学和质控细胞仪精确研究了多发性硬化症患者外周血样本中的细胞异质性:结论:MOYAOMICS 项目是朝着了解 MMD 分子基础迈出的重要一步。这种多学科方法有望彻底改变麻风病的早期诊断、患者分层和靶向疗法的开发。基于血液的生物标志物的鉴定和多种 omics 数据的整合对于改善 MMD 的临床管理和提高这种复杂疾病的患者预后至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multiomics and blood-based biomarkers of moyamoya disease: protocol of Moyamoya Omics Atlas (MOYAOMICS).

Background: Moyamoya disease (MMD) is a rare and complex cerebrovascular disorder characterized by the progressive narrowing of the internal carotid arteries and the formation of compensatory collateral vessels. The etiology of MMD remains enigmatic, making diagnosis and management challenging. The MOYAOMICS project was initiated to investigate the molecular underpinnings of MMD and explore potential diagnostic and therapeutic strategies.

Methods: The MOYAOMICS project employs a multidisciplinary approach, integrating various omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, to comprehensively examine the molecular signatures associated with MMD pathogenesis. Additionally, we will investigate the potential influence of gut microbiota and brain-gut peptides on MMD development, assessing their suitability as targets for therapeutic strategies and dietary interventions. Radiomics, a specialized field in medical imaging, is utilized to analyze neuroimaging data for early detection and characterization of MMD-related brain changes. Deep learning algorithms are employed to differentiate MMD from other conditions, automating the diagnostic process. We also employ single-cellomics and mass cytometry to precisely study cellular heterogeneity in peripheral blood samples from MMD patients.

Conclusions: The MOYAOMICS project represents a significant step toward comprehending MMD's molecular underpinnings. This multidisciplinary approach has the potential to revolutionize early diagnosis, patient stratification, and the development of targeted therapies for MMD. The identification of blood-based biomarkers and the integration of multiple omics data are critical for improving the clinical management of MMD and enhancing patient outcomes for this complex disease.

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来源期刊
CiteScore
2.70
自引率
0.00%
发文量
224
审稿时长
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