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理解骨关节炎发病机制:基于多组学系统的方法。

Understanding osteoarthritis pathogenesis: a multiomics system-based approach.

机构信息

Arthritis Program.

Division of Genetics and Development, Krembil Research Institute, University Health Network.

出版信息

Curr Opin Rheumatol. 2020 Jan;32(1):80-91. doi: 10.1097/BOR.0000000000000680.

Abstract

PURPOSE OF REVIEW

Osteoarthritis is a heterogeneous, multifactorial condition regulated by complex biological interactions at multiple levels. Comprehensive understanding of these regulatory interactions is required to develop feasible advances to improve patient outcomes. Improvements in technology have made extensive genomic, transcriptomic, epigenomic, proteomic, and metabolomic profiling possible. This review summarizes findings over the past 20 months related to omics technologies in osteoarthritis and examines how using a multiomics approach is necessary for advancing our understanding of osteoarthritis as a disease to improve precision osteoarthritis treatments.

RECENT FINDINGS

Using the search terms 'genomics' or 'transcriptomics' or 'epigenomics' or 'proteomics' or 'metabolomics' and 'osteoarthritis' from January 1, 2018 to August 31, 2019, we identified advances in omics approaches applied to osteoarthritis. Trends include untargeted whole genome, transcriptome, proteome, and metabolome analyses leading to identification of novel molecular signatures, cell subpopulations and multiomics validation approaches.

SUMMARY

To address the complexity of osteoarthritis, integration of multitissue analyses by multiomics approaches with the inclusion of longitudinal clinical data is necessary for a comprehensive understanding of the disease process, and for appropriate development of efficacious diagnostics, prognostics, and biotherapeutics.

摘要

目的综述

骨关节炎是一种异质性、多因素疾病,受多个层次的复杂生物学相互作用调控。为了开发可行的方法来改善患者的预后,需要全面了解这些调控相互作用。技术的进步使得广泛的基因组学、转录组学、表观基因组学、蛋白质组学和代谢组学分析成为可能。这篇综述总结了过去 20 个月中与骨关节炎中的组学技术相关的研究结果,并探讨了如何使用多组学方法来深入了解骨关节炎作为一种疾病,以改善精准骨关节炎治疗。

最近的发现

使用搜索词“genomics”或“transcriptomics”或“epigenomics”或“proteomics”或“metabolomics”和“osteoarthritis”,从 2018 年 1 月 1 日至 2019 年 8 月 31 日,我们确定了应用于骨关节炎的组学方法的进展。趋势包括针对整个基因组、转录组、蛋白质组和代谢组的非靶向分析,从而鉴定出新型的分子特征、细胞亚群和多组学验证方法。

总结

为了解决骨关节炎的复杂性,需要通过多组学方法整合多组织分析,并纳入纵向临床数据,以全面了解疾病过程,并为有效的诊断、预后和生物治疗方法的开发提供依据。

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