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通过表观组学改变疾病特异性相互作用组:以阿尔茨海默病为例。

Disease-specific interactome alterations via epichaperomics: the case for Alzheimer's disease.

机构信息

Center for Dementia Research, Nathan Kline Institute, Orangeburg, NY, USA.

Departments of Psychiatry, Neuroscience & Physiology, The NYU Neuroscience Institute, New York University Grossman School of Medicine, NY, USA.

出版信息

FEBS J. 2022 Apr;289(8):2047-2066. doi: 10.1111/febs.16031. Epub 2021 Jun 12.

Abstract

The increasingly appreciated prevalence of complicated stressor-to-phenotype associations in human disease requires a greater understanding of how specific stressors affect systems or interactome properties. Many currently untreatable diseases arise due to variations in, and through a combination of, multiple stressors of genetic, epigenetic, and environmental nature. Unfortunately, how such stressors lead to a specific disease phenotype or inflict a vulnerability to some cells and tissues but not others remains largely unknown and unsatisfactorily addressed. Analysis of cell- and tissue-specific interactome networks may shed light on organization of biological systems and subsequently to disease vulnerabilities. However, deriving human interactomes across different cell and disease contexts remains a challenge. To this end, this opinion article links stressor-induced protein interactome network perturbations to the formation of pathologic scaffolds termed epichaperomes, revealing a viable and reproducible experimental solution to obtaining rigorous context-dependent interactomes. This article presents our views on how a specialized 'omics platform called epichaperomics may complement and enhance the currently available conventional approaches and aid the scientific community in defining, understanding, and ultimately controlling interactome networks of complex diseases such as Alzheimer's disease. Ultimately, this approach may aid the transition from a limited single-alteration perspective in disease to a comprehensive network-based mindset, which we posit will result in precision medicine paradigms for disease diagnosis and treatment.

摘要

在人类疾病中,复杂应激源与表型的关联越来越受到重视,这就需要更好地了解特定应激源如何影响系统或互作网络的特性。许多目前无法治疗的疾病是由于遗传、表观遗传和环境性质的多种应激源的变异以及它们的组合而产生的。不幸的是,这些应激源如何导致特定的疾病表型,或者对某些细胞和组织造成易损性,而对其他细胞和组织没有影响,在很大程度上仍然未知,也没有得到令人满意的解决。分析细胞和组织特异性互作网络可以揭示生物系统的组织方式,进而揭示疾病易损性。然而,在不同的细胞和疾病背景下获得人类互作网络仍然是一个挑战。为此,本文将应激源诱导的蛋白质互作网络扰动与病理支架(称为表观组)的形成联系起来,提出了一种可行且可重复的实验解决方案,以获得严格依赖于上下文的互作网络。本文介绍了我们的观点,即一种特殊的“组学”平台——表观组学,如何补充和增强当前可用的常规方法,并帮助科学界定义、理解和最终控制阿尔茨海默病等复杂疾病的互作网络。最终,这种方法可以帮助从疾病的有限单一改变的角度过渡到基于网络的全面思维,我们认为这将导致疾病诊断和治疗的精准医学范例。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae29/8611103/94ea9b7b8ebb/nihms-1714946-f0001.jpg

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