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用于心血管疾病大规模血浆分析的基于亲和力的新兴蛋白质组学技术

Emerging Affinity-Based Proteomic Technologies for Large-Scale Plasma Profiling in Cardiovascular Disease.

作者信息

Smith J Gustav, Gerszten Robert E

机构信息

From Molecular Epidemiology and Cardiology, Clinical Sciences, Lund University and Skåne University Hospital, Sweden (J.G.S.); Department of Heart Failure and Valvular Disease, Skåne University Hospital, Lund, Sweden (J.G.S.); Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge (J.G.S., R.E.G.); and Cardiovascular Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA (R.E.G.).

出版信息

Circulation. 2017 Apr 25;135(17):1651-1664. doi: 10.1161/CIRCULATIONAHA.116.025446.


DOI:10.1161/CIRCULATIONAHA.116.025446
PMID:28438806
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5555416/
Abstract

Plasma biomarkers that reflect molecular states of the cardiovascular system are central for clinical decision making. Routinely used plasma biomarkers include troponins, natriuretic peptides, and lipoprotein particles, yet interrogate only a modest subset of pathways relevant to cardiovascular disease. Systematic profiling of a larger portion of circulating plasma proteins (the plasma proteome) will provide opportunities for unbiased discovery of novel markers to improve diagnostic or predictive accuracy. In addition, proteomic profiling may inform pathophysiological understanding and point to novel therapeutic targets. Obstacles for comprehensive proteomic profiling include the immense size and structural heterogeneity of the proteome, and the broad range of abundance levels, as well. Proteome-wide, untargeted profiling can be performed in tissues and cells with tandem mass spectrometry. However, applications to plasma are limited by the need for complex preanalytical sample preparation stages limiting sample throughput. Multiplexing of targeted methods based on capture and detection of specific proteins are therefore receiving increasing attention in plasma proteomics. Immunoaffinity assays are the workhorse for measuring individual proteins but have been limited for proteomic applications by long development times, cross-reactivity preventing multiplexing, specificity issues, and incomplete sensitivity to detect proteins in the lower range of the abundance spectrum (below picograms per milliliter). Emerging technologies to address these issues include nucleotide-labeled immunoassays and aptamer reagents that can be automated for efficient multiplexing of thousands of proteins at high sample throughput, coupling of affinity capture methods to mass spectrometry for improved specificity, and ultrasensitive detection systems to measure low-abundance proteins. In addition, proteomics can now be integrated with modern genomics tools to comprehensively relate proteomic profiles to genetic variants, which may both influence binding of affinity reagents and serve to validate the target specificity of affinity assays. The application of deep quantitative proteomic profiling to large cohorts has thus become increasingly feasible with emerging affinity methods. The aims of this article are to provide the broad readership of with a timely overview of emerging methods for affinity proteomics and recent progress in cardiovascular medicine based on such methods.

摘要

反映心血管系统分子状态的血浆生物标志物是临床决策的核心。常规使用的血浆生物标志物包括肌钙蛋白、利钠肽和脂蛋白颗粒,但它们仅涉及与心血管疾病相关的一小部分途径。对更大比例的循环血浆蛋白(血浆蛋白质组)进行系统分析,将为无偏倚地发现新型标志物提供机会,以提高诊断或预测准确性。此外,蛋白质组分析可能有助于深入了解病理生理学,并指向新的治疗靶点。全面蛋白质组分析的障碍包括蛋白质组的巨大规模和结构异质性,以及丰度水平的广泛范围。全蛋白质组的非靶向分析可在组织和细胞中通过串联质谱进行。然而,由于需要复杂的分析前样品制备阶段,限制了样品通量,因此其在血浆中的应用受到限制。因此,基于特定蛋白质捕获和检测的靶向方法的多重分析在血浆蛋白质组学中受到越来越多的关注。免疫亲和测定是测量单个蛋白质的主要方法,但由于开发时间长、交叉反应性妨碍多重分析、特异性问题以及对丰度谱较低范围(低于皮克每毫升)蛋白质检测的灵敏度不足,在蛋白质组学应用中受到限制。解决这些问题的新兴技术包括核苷酸标记免疫测定和适体试剂,它们可以自动化以实现数千种蛋白质的高效多重分析,且样品通量高;将亲和捕获方法与质谱联用可提高特异性;以及超灵敏检测系统来测量低丰度蛋白质。此外,蛋白质组学现在可以与现代基因组学工具整合,以全面关联蛋白质组谱与遗传变异,这可能既影响亲和试剂的结合,又有助于验证亲和测定的靶标特异性。因此,随着新兴亲和方法的出现,深度定量蛋白质组分析在大型队列中的应用变得越来越可行。本文的目的是为广大读者及时概述亲和蛋白质组学的新兴方法以及基于此类方法在心血管医学方面的最新进展。

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本文引用的文献

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