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Background <p>Metabolic syndrome (MetS) is characterized by obesity, insulin resistance, and dyslipidemia with adipose tissue inflammation, yet its cellular heterogeneity and intercellular interactions remain poorly understood. We analyzed single-nucleus RNA sequencing data from subcutaneous adipose tissue of 84 individuals with MetS from the METSIM cohort, characterizing cell composition, inter-individual variation, adipocyte progenitor differentiation, and cell-cell communication networks.</p> Methods <p>We performed single-nucleus RNA sequencing on subcutaneous adipose tissue samples from 84 individuals with MetS. Clustering analysis was used to define cell types and subpopulations, inter-individual variation in cell composition was assessed, pseudotime trajectory analysis reconstructed adipocyte precursor differentiation pathways, and ligand–receptor interaction analysis mapped intercellular communication networks.</p> Results <p>We identified 12 distinct cell types in MetS adipose tissue and discovered two patient subgroups with differential enrichment of adipocytes/progenitors versus immune cells, suggesting subtypes of MetS with distinct adipose profiles. Pseudotime analysis revealed two adipocyte progenitor subpopulations with altered differentiation trajectories. Cell-cell communication analysis identified WNT signaling from progenitors to adipocytes as a potential differentiation driver, with extracellular matrix pathways mediating progenitor-adipocyte interactions.</p> Conclusion <p>This comprehensive single-cell atlas of MetS adipose tissue reveals previously unrecognized cellular heterogeneity and differentiation dynamics, offering new insights into MetS pathogenesis and highlighting potential therapeutic targets.</p>

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Integrative single-cell analysis of metabolic syndrome reveals novel cellular heterogeneity and differentiation dynamics in adipose tissue

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月22日

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  • Hui Jia,
  • Dandan Liu

摘要

Background

Metabolic syndrome (MetS) is characterized by obesity, insulin resistance, and dyslipidemia with adipose tissue inflammation, yet its cellular heterogeneity and intercellular interactions remain poorly understood. We analyzed single-nucleus RNA sequencing data from subcutaneous adipose tissue of 84 individuals with MetS from the METSIM cohort, characterizing cell composition, inter-individual variation, adipocyte progenitor differentiation, and cell-cell communication networks.

Methods

We performed single-nucleus RNA sequencing on subcutaneous adipose tissue samples from 84 individuals with MetS. Clustering analysis was used to define cell types and subpopulations, inter-individual variation in cell composition was assessed, pseudotime trajectory analysis reconstructed adipocyte precursor differentiation pathways, and ligand–receptor interaction analysis mapped intercellular communication networks.

Results

We identified 12 distinct cell types in MetS adipose tissue and discovered two patient subgroups with differential enrichment of adipocytes/progenitors versus immune cells, suggesting subtypes of MetS with distinct adipose profiles. Pseudotime analysis revealed two adipocyte progenitor subpopulations with altered differentiation trajectories. Cell-cell communication analysis identified WNT signaling from progenitors to adipocytes as a potential differentiation driver, with extracellular matrix pathways mediating progenitor-adipocyte interactions.

Conclusion

This comprehensive single-cell atlas of MetS adipose tissue reveals previously unrecognized cellular heterogeneity and differentiation dynamics, offering new insights into MetS pathogenesis and highlighting potential therapeutic targets.