在CKD和MASH中通过单细胞和空间转录组学的整合来识别连接体和受体相互作用
Jaime Moreno1, Lise Lotte Gluud2,3, Elisabeth D Galsgaard4
1Digital Science and Innovation, Computational Biology - AI & Digital Research, Novo Nordisk A/S, Maløv, Denmark.
PloS one
|May 20, 2024
概括
这项研究整合了单细胞和空间转录组学,在慢性病 (CKD) 和代谢功能障碍相关的脂肪肝炎 (MASH) 中绘制细胞通信图,确定了新的治疗点.
科学领域:
- 纤维炎症疾病的综合性多学科分析.
- 单细胞和空间转录学用于分子病理学.
背景情况:
- 慢性病 (CKD) 和与代谢功能障碍相关的脂肪肝炎 (MASH) 是复杂的代谢纤维炎症状况.
- 了解细胞特异性信号通路对于疾病洞察至关重要.
研究的目的:
- 使用转录基因数据开发CKD和MASH的综合分析框架.
- 在这些疾病中全面分析细胞特异性联体受体相互作用.
主要方法:
- 从人类队伍中对单细胞RNA测序 (scRNAseq) 和空间转录组学 (ST) 数据的综合分析.
- 识别和验证参与细胞交叉通话的联体受体 (L-R) 对.
- 使用空间共同存在和目标共同表达分析进行验证.
主要成果:
- 在CKD和MASH中确定了调解细胞交叉通话的关键连接体-受体对.
- 使用空间转录组学数据验证的相互作用,证实了细胞类型的同定位.
- 发现了新的潜在治疗点,包括以前只在动物模型中看到的.
结论:
- 整合多模式的转录基因数据可以增强对复杂疾病的分子理解.
- scRNAseq和ST的综合方法可视化细胞与细胞的相互作用,有助于治疗点的发现.
- 这一框架有助于开发用于CKD和MASH的有效疗法.
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