Spatial multiomics atlas reveals smooth muscle phenotypic transformation and metabolic reprogramming in diabetic macroangiopathy.

IF 8.5 1区 医学 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS
Yongjiang Qian, Shizheng Xiong, Lihua Li, Zhen Sun, Lili Zhang, Wei Yuan, Honghua Cai, Guoquan Feng, Xiaoguang Wang, Haipeng Yao, Yun Gao, Li Guo, Zhongqun Wang
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引用次数: 0

Abstract

Background: Diabetic macroangiopathy has been the main cause of death and disability in diabetic patients. The mechanisms underlying smooth muscle cell transformation and metabolic reprogramming other than abnormal glucose and lipid metabolism remain to be further explored.

Method: Single-cell transcriptome, spatial transcriptome and spatial metabolome sequencing were performed on anterior tibial artery from 11 diabetic patients with amputation. Multi-omics integration, cell communication analysis, time series analysis, network analysis, enrichment analysis, and gene expression analysis were performed to elucidate the potential molecular features.

Result: We constructed a spatial multiomics map of diabetic blood vessels based on multiomics integration, indicating single-cell and spatial landscape of transcriptome and spatial landscape of metabolome. At the same time, the characteristics of cell composition and biological function of calcified regions were obtained by integrating spatial omics and single cell omics. On this basis, our study provides favorable evidence for the cellular fate of smooth muscle cells, which can be transformed into pro-inflammatory chemotactic smooth muscle cells, macrophage-like smooth muscle cells/foam-like smooth muscle cells, and fibroblast/chondroblast smooth muscle cells in the anterior tibial artery of diabetic patients. The smooth muscle cell phenotypic transformation is driven by transcription factors net including KDM5B, DDIT3, etc. In addition, in order to focus on metabolic reprogramming apart from abnormal glucose and lipid metabolism, we constructed a metabolic network of diabetic vascular activation, and found that HNMT and CYP27A1 participate in diabetic vascular metabolic reprogramming by combining public data.

Conclusion: This study constructs the spatial gene-metabolism map of the whole anterior tibial artery for the first time and reveals the characteristics of vascular calcification, the phenotypic transformation trend of SMCs, and the transcriptional driving network of SMCs phenotypic transformation of diabetic macrovascular disease. In the perspective of combining the transcriptome and metabolome, the study demonstrates the activated metabolic pathways in diabetic blood vessels and the key genes involved in diabetic metabolic reprogramming.

空间多组学图谱揭示了糖尿病大血管病变中平滑肌的表型转变和代谢重编程。
背景:糖尿病大血管病变是导致糖尿病患者死亡和残疾的主要原因。除了葡萄糖和脂质代谢异常外,平滑肌细胞转化和代谢重编程的机制仍有待进一步探索:方法:对 11 名糖尿病截肢患者的胫前动脉进行单细胞转录组、空间转录组和空间代谢组测序。为了阐明潜在的分子特征,我们进行了多组学整合、细胞通讯分析、时间序列分析、网络分析、富集分析和基因表达分析:结果:基于多组学整合,我们构建了糖尿病血管的空间多组学图谱,显示了转录组的单细胞空间图谱和代谢组的空间图谱。同时,通过整合空间组学和单细胞组学,获得了钙化区域的细胞组成特征和生物学功能。在此基础上,我们的研究为糖尿病患者胫前动脉平滑肌细胞的细胞命运提供了有利的证据,糖尿病患者的胫前动脉平滑肌细胞可转化为促炎趋化平滑肌细胞、巨噬细胞样平滑肌细胞/泡沫样平滑肌细胞和成纤维细胞/成软骨细胞平滑肌细胞。平滑肌细胞表型的转变是由转录因子网(包括 KDM5B、DDIT3 等)驱动的。此外,为了关注糖脂代谢异常之外的代谢重编程,我们构建了糖尿病血管活化的代谢网络,并结合公开数据发现HNMT和CYP27A1参与了糖尿病血管代谢重编程:该研究首次构建了整个胫前动脉的空间基因代谢图谱,揭示了糖尿病大血管病变的血管钙化特征、SMC表型转化趋势以及SMC表型转化的转录驱动网络。从转录组和代谢组结合的角度,该研究展示了糖尿病血管中被激活的代谢通路,以及参与糖尿病代谢重编程的关键基因。
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来源期刊
Cardiovascular Diabetology
Cardiovascular Diabetology 医学-内分泌学与代谢
CiteScore
12.30
自引率
15.10%
发文量
240
审稿时长
1 months
期刊介绍: Cardiovascular Diabetology is a journal that welcomes manuscripts exploring various aspects of the relationship between diabetes, cardiovascular health, and the metabolic syndrome. We invite submissions related to clinical studies, genetic investigations, experimental research, pharmacological studies, epidemiological analyses, and molecular biology research in this field.
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