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用于自身免疫性疾病的人抗体分析技术。

Human antibody profiling technologies for autoimmune disease.

机构信息

School of Medical Sciences, Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand.

Maurice Wilkins Centre, The University of Auckland, Auckland, New Zealand.

出版信息

Immunol Res. 2023 Aug;71(4):516-527. doi: 10.1007/s12026-023-09362-8. Epub 2023 Jan 24.

Abstract

Autoimmune diseases are caused by the break-down in self-tolerance mechanisms and can result in the generation of autoantibodies specific to human antigens. Human autoantigen profiling technologies such as solid surface arrays and display technologies are powerful high-throughput technologies utilised to discover and map novel autoantigens associated with disease. This review compares human autoantigen profiling technologies including the application of these approaches in chronic and post-infectious autoimmune disease. Each technology has advantages and limitations that should be considered when designing new projects to profile autoantibodies. Recent studies that have utilised these technologies across a range of diseases have highlighted marked heterogeneity in autoantibody specificity between individuals as a frequent feature. This individual heterogeneity suggests that epitope spreading maybe an important mechanism in the pathogenesis of autoimmune disease in general and likely contributes to inflammatory tissue damage and symptoms. Studies focused on identifying autoantibody biomarkers for diagnosis should use targeted data analysis to identify the rarer public epitopes and antigens, common between individuals. Thus, utilisation of human autoantigen profiling technology, combined with different analysis approaches, can illuminate both pathogenesis and biomarker discovery.

摘要

自身免疫性疾病是由于自身耐受机制的破坏而引起的,可以导致针对人类抗原的自身抗体的产生。人类自身抗原分析技术,如固相阵列和展示技术,是用于发现和绘制与疾病相关的新型自身抗原的强大高通量技术。本综述比较了人类自身抗原分析技术,包括这些方法在慢性和感染后自身免疫性疾病中的应用。每种技术都有其优点和局限性,在设计新的项目来分析自身抗体时应加以考虑。最近的研究利用这些技术在一系列疾病中的应用,突出了个体之间自身抗体特异性的明显异质性,这是一个常见特征。这种个体异质性表明,表位扩展可能是一般自身免疫性疾病发病机制中的一个重要机制,并可能导致炎症性组织损伤和症状。专注于识别自身抗体生物标志物用于诊断的研究应使用靶向数据分析来识别个体之间更常见的罕见公共表位和抗原。因此,利用人类自身抗原分析技术,结合不同的分析方法,可以阐明发病机制和生物标志物的发现。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf01/10425289/1b1affafced6/12026_2023_9362_Fig1_HTML.jpg

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