空间多组学图谱揭示糖尿病大血管病变中平滑肌表型转化和代谢重编程。

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

机构信息

Department of Cardiology, Affiliated Hospital of Jiangsu University, Zhenjiang, 212001, China.

Institue of Cardiovascular Diseases, Jiangsu University, Zhenjiang, 212001, China.

出版信息

Cardiovasc Diabetol. 2024 Oct 12;23(1):358. doi: 10.1186/s12933-024-02458-x.

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.

摘要

背景

糖尿病大血管病变一直是糖尿病患者死亡和残疾的主要原因。除了异常的糖脂代谢外,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 例截肢糖尿病患者的胫骨前动脉进行单细胞转录组、空间转录组和空间代谢组测序。通过多组学整合、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,阐明潜在的分子特征。

结果

我们构建了基于多组学整合的糖尿病血管空间多组学图谱,显示了单细胞和空间转录组以及空间代谢组图谱。同时,通过整合空间组学和单细胞组学,获得了钙化区域细胞组成和生物学功能的特征。在此基础上,我们的研究为平滑肌细胞的细胞命运提供了有利的证据,即在糖尿病患者的胫骨前动脉中,平滑肌细胞可以转化为促炎趋化性平滑肌细胞、巨噬细胞样平滑肌细胞/泡沫样平滑肌细胞和成纤维细胞/软骨样平滑肌细胞。平滑肌细胞表型转化受 KDM5B、DDIT3 等转录因子 net 驱动。此外,为了关注除异常糖脂代谢外的代谢重编程,我们构建了糖尿病血管激活的代谢网络,并结合公共数据发现 HNMT 和 CYP27A1 通过参与糖尿病血管代谢重编程。

结论

本研究首次构建了整个胫骨前动脉的空间基因-代谢图谱,揭示了血管钙化的特征、SMCs 表型转化趋势以及糖尿病大血管疾病中 SMCs 表型转化的转录驱动网络。从转录组和代谢组结合的角度来看,该研究展示了糖尿病血管中激活的代谢途径以及涉及糖尿病代谢重编程的关键基因。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c2e/11471023/21d0cff3545f/12933_2024_2458_Fig1_HTML.jpg

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