医学
表观遗传学
组学
代谢组
骨关节炎
基因组学
代谢组学
蛋白质组学
疾病
个性化医疗
转录组
人类遗传学
精密医学
生物信息学
计算生物学
病理
基因组
遗传学
生物
替代医学
基因
DNA甲基化
基因表达
作者
A. Ratneswaran,Jason S. Rockel,Mohit Kapoor
出处
期刊:Current Opinion in Rheumatology
[Ovid Technologies (Wolters Kluwer)]
日期:2020-01-01
卷期号:32 (1): 80-91
被引量:37
标识
DOI:10.1097/bor.0000000000000680
摘要
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.
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