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人类巨噬细胞的转录编程:迈向系统免疫学之路

Transcriptional programming of human macrophages: on the way to systems immunology.

作者信息

Schultze Joachim L

机构信息

Genomics and Immunoregulation, LIMES-Institute, University of Bonn, Carl-Troll-Str. 31, 53115, Bonn, Germany,

出版信息

J Mol Med (Berl). 2015 Jun;93(6):589-97. doi: 10.1007/s00109-015-1286-y. Epub 2015 Apr 16.

Abstract

Many of the major common diseases such as atherosclerosis, diabetes, obesity, numerous autoimmune diseases, as well as neurodegenerative diseases such as Alzheimer's disease and many cancer types are characterised by a chronic inflammatory component termed sterile inflammation. Myeloid cells, particularly macrophages, are an important cellular component of chronic inflammation in these diseases. For almost all of these disease conditions, previous reports suggested that macrophages can exert either so-called pro-inflammatory or anti-inflammatory functions, thereby either fighting or feeding the disease. This apparent dichotomy of reactions of macrophages led to a dichotomous definition of macrophage activation classified as macrophage polarisation. However, analysis of large transcriptomics data derived from human and murine macrophages show that macrophage functions are shaped in a very tissue- and signal-input specific manner, allowing these cells to develop extremely specific functional programmes. Integrating global views on macrophage activation on the transcriptome, the epigenome, the proteome or the metabolome will finally lead to a data-driven approach to understand macrophage biology in context of major diseases. We are indeed on the way to a systems immunology approach that integrates -omics data with mathematical and bioinformatical modelling as the pre-requisite to generate data-driven hypotheses. This approach opens completely new avenues for the development of tailored diagnostics and therapies targeting macrophages in sterile inflammations of the major common diseases. I will also discuss some of the next developments that will be necessary to reach these important goals.

摘要

许多主要的常见疾病,如动脉粥样硬化、糖尿病、肥胖症、众多自身免疫性疾病,以及神经退行性疾病如阿尔茨海默病和多种癌症类型,其特征都在于一种被称为无菌性炎症的慢性炎症成分。髓样细胞,尤其是巨噬细胞,是这些疾病中慢性炎症的重要细胞组成部分。对于几乎所有这些疾病状况,先前的报告表明巨噬细胞可以发挥所谓的促炎或抗炎功能,从而要么对抗疾病,要么助长疾病。巨噬细胞这种明显的反应二分法导致了巨噬细胞活化的二分法定义,即巨噬细胞极化。然而,对源自人类和小鼠巨噬细胞的大量转录组学数据的分析表明,巨噬细胞的功能是以一种非常依赖组织和信号输入的特定方式形成的,这使得这些细胞能够发展出极其特定的功能程序。整合转录组、表观基因组、蛋白质组或代谢组水平上关于巨噬细胞活化的整体观点,最终将促成一种数据驱动的方法,以在主要疾病的背景下理解巨噬细胞生物学。我们确实正朝着一种系统免疫学方法迈进,该方法将组学数据与数学和生物信息学建模相结合,作为生成数据驱动假设的先决条件。这种方法为开发针对主要常见疾病无菌性炎症中巨噬细胞的定制诊断和治疗方法开辟了全新的途径。我还将讨论为实现这些重要目标所需的一些后续进展。

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