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AutoCore:一种基于网络的人类自身免疫和自身炎症核心模块的定义。

AutoCore: A network-based definition of the core module of human autoimmunity and autoinflammation.

机构信息

Ludwig Boltzmann Institute for Rare and Undiagnosed Diseases, Zimmermannplatz 10, A-1090 Vienna, Austria.

CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Lazarettgasse 14, AKH BT 25.3, A-1090 Vienna, Austria.

出版信息

Sci Adv. 2023 Sep;9(35):eadg6375. doi: 10.1126/sciadv.adg6375. Epub 2023 Sep 1.

Abstract

Although research on rare autoimmune and autoinflammatory diseases has enabled definition of nonredundant regulators of homeostasis in human immunity, because of the single gene-single disease nature of many of these diseases, contributing factors were mostly unveiled in sequential and noncoordinated individual studies. We used a network-based approach for integrating a set of 186 inborn errors of immunity with predominant autoimmunity/autoinflammation into a comprehensive map of human immune dysregulation, which we termed "AutoCore." The AutoCore is located centrally within the interactome of all protein-protein interactions, connecting and pinpointing multidisease markers for a range of common, polygenic autoimmune/autoinflammatory diseases. The AutoCore can be subdivided into 19 endotypes that correspond to molecularly and phenotypically cohesive disease subgroups, providing a molecular mechanism-based disease classification and rationale toward systematic targeting for therapeutic purposes. Our study provides a proof of concept for using network-based methods to systematically investigate the molecular relationships between individual rare diseases and address a range of conceptual, diagnostic, and therapeutic challenges.

摘要

尽管对罕见的自身免疫和自身炎症性疾病的研究已经能够确定人类免疫中对稳态起非冗余调节作用的基因,但由于许多此类疾病都具有单基因-单疾病的特点,因此相关的致病因素大多是在先后顺序且不协调的单独研究中揭示的。我们使用基于网络的方法,将一组 186 种以自身免疫/自身炎症为主的遗传性免疫缺陷病整合到一个全面的人类免疫失调图谱中,我们称之为“AutoCore”。AutoCore 位于所有蛋白质-蛋白质相互作用的相互作用组的中央,连接并确定了一系列常见的、多基因自身免疫/自身炎症性疾病的多疾病标志物。AutoCore 可以细分为 19 个亚型,它们对应于具有分子和表型一致性的疾病亚群,为基于分子机制的疾病分类和有针对性的治疗提供了依据。我们的研究提供了一个概念验证,即使用基于网络的方法来系统地研究个体罕见疾病之间的分子关系,并解决一系列概念、诊断和治疗方面的挑战。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b2b/10848965/e7ec5fc2f453/sciadv.adg6375-f1.jpg

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