ArticleDiabetology & metabolic syndrome2025
Integrative single-cell analysis of metabolic syndrome reveals novel cellular heterogeneity and differentiation dynamics in adipose tissue.
Article in Diabetology & metabolic syndrome, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Abstract
backgroundMetabolic 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.
methodsWe 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.
resultsWe 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.
conclusionThis 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.
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