在细胞类型分辨率上进行多omics集成,揭示了骨关节炎异质性背后的基因代谢机制
Abhishek Ojha1, Paramita Chatterjee2,3, Linda E Kippner2,3
1The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
bioRxiv : the preprint server for biology
|November 19, 2025
概括
这项研究透露了关键的代谢途径和细胞类型参与骨关节炎 (OA) 发病因子通过分析患者的多omics数据. 了解这些基因代谢物链接为OA异质性和疾病进展提供了新的见解.
科学领域:
- 生物化学 生物化学
- 基因组学就是基因组学.
- 免疫学 免疫学 免疫学
背景情况:
- 代谢失调与骨关节炎 (OA) 的发病有关.
- 对OA分子机制和途径的全面研究是有限的.
研究的目的:
- 研究骨关节炎病变的基础分子机制和途径.
- 通过使用多omics数据,识别导致OA异质性的关键分子因素.
- 在OA中探索细胞类型特定的基因代谢物协会.
主要方法:
- 对来自119名OA患者的代谢学和单细胞转录学数据的分析.
- 在细胞类型分辨率下重建基因代谢物关联网络.
- 机器学习模型的应用,以识别特定代谢物相关的细胞类型.
主要成果:
- 在基因代谢物网络中识别细胞类型特定和全细胞类型枢纽.
- 鉴定了甘油脂,甘油脂和脂代谢途径以及脂质信号传递的重要作用.
- 发现了与OA疾病严重程度相关的免疫细胞亚型的转变.
结论:
- 在患者队伍中的基因代谢物共变分析可以揭示潜在的OA分子机制.
- 这种方法克服了多omics数据的高维度所带来的挑战.
- 这些发现强调了脂质代谢和特定免疫细胞亚型在OA病变发生过程中的重要性.
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