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骨关节炎研究中基因组学和表观基因组学的发展与进步:我们已取得的进展。

Evolution and advancements in genomics and epigenomics in OA research: How far we have come.

作者信息

Ramos Yolande F M, Rice Sarah J, Ali Shabana Amanda, Pastrello Chiara, Jurisica Igor, Rai Muhammad Farooq, Collins Kelsey H, Lang Annemarie, Maerz Tristan, Geurts Jeroen, Ruiz-Romero Cristina, June Ronald K, Thomas Appleton C, Rockel Jason S, Kapoor Mohit

机构信息

Dept. Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands.

Biosciences Institute, International Centre for Life, Newcastle University, Newcastle upon Tyne, United Kingdom.

出版信息

Osteoarthritis Cartilage. 2024 Jul;32(7):858-868. doi: 10.1016/j.joca.2024.02.656. Epub 2024 Feb 28.

Abstract

OBJECTIVE

Osteoarthritis (OA) is the most prevalent musculoskeletal disease affecting articulating joint tissues, resulting in local and systemic changes that contribute to increased pain and reduced function. Diverse technological advancements have culminated in the advent of high throughput "omic" technologies, enabling identification of comprehensive changes in molecular mediators associated with the disease. Amongst these technologies, genomics and epigenomics - including methylomics and miRNomics, have emerged as important tools to aid our biological understanding of disease.

DESIGN

In this narrative review, we selected articles discussing advancements and applications of these technologies to OA biology and pathology. We discuss how genomics, deoxyribonucleic acid (DNA) methylomics, and miRNomics have uncovered disease-related molecular markers in the local and systemic tissues or fluids of OA patients.

RESULTS

Genomics investigations into the genetic links of OA, including using genome-wide association studies, have evolved to identify 100+ genetic susceptibility markers of OA. Epigenomic investigations of gene methylation status have identified the importance of methylation to OA-related catabolic gene expression. Furthermore, miRNomic studies have identified key microRNA signatures in various tissues and fluids related to OA disease.

CONCLUSIONS

Sharing of standardized, well-annotated omic datasets in curated repositories will be key to enhancing statistical power to detect smaller and targetable changes in the biological signatures underlying OA pathogenesis. Additionally, continued technological developments and analysis methods, including using computational molecular and regulatory networks, are likely to facilitate improved detection of disease-relevant targets, in-turn, supporting precision medicine approaches and new treatment strategies for OA.

摘要

目的

骨关节炎(OA)是影响关节组织的最常见肌肉骨骼疾病,会导致局部和全身变化,进而加剧疼痛并降低功能。多种技术进步最终促成了高通量“组学”技术的出现,使得能够识别与该疾病相关的分子介质的全面变化。在这些技术中,基因组学和表观基因组学——包括甲基化组学和微小核糖核酸组学,已成为帮助我们从生物学角度理解该疾病的重要工具。

设计

在本叙述性综述中,我们挑选了讨论这些技术在OA生物学和病理学方面的进展及应用的文章。我们讨论了基因组学、脱氧核糖核酸(DNA)甲基化组学和微小核糖核酸组学如何在OA患者的局部和全身组织或体液中发现与疾病相关的分子标记。

结果

对OA遗传联系的基因组学研究,包括使用全基因组关联研究,已发展到可识别100多个OA的遗传易感性标记。对基因甲基化状态的表观基因组学研究已确定甲基化对OA相关分解代谢基因表达的重要性。此外,微小核糖核酸组学研究已在与OA疾病相关的各种组织和体液中识别出关键的微小核糖核酸特征。

结论

在经过整理的储存库中共享标准化、注释完善的组学数据集,将是增强统计能力以检测OA发病机制潜在生物学特征中更小且可靶向变化的关键。此外,持续的技术发展和分析方法,包括使用计算分子和调控网络,可能会促进对疾病相关靶点的更好检测,进而支持OA的精准医学方法和新治疗策略。

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