This meta-analysis integrated single-cell and spatial transcriptomic data to create a detailed cellular map of human white adipose tissue, identifying over 60 distinct cell types and linking specific cell populations to metabolic health parameters.
Nature Communications · 28 authors, 15 centres
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This meta-analysis integrated single-cell and spatial transcriptomic data to create a detailed cellular map of human white adipose tissue, identifying over 60 distinct cell types and linking specific cell populations to metabolic health parameters.
This study performed a comprehensive meta-analysis of newly generated and publicly available single-cell (scSeq) and single-nucleus (snSeq) RNA sequencing data to create a cellular meta-map of human white adipose tissue (WAT). The analysis included data from approximately 100 samples and was used to deconvolve spatial and bulk transcriptomic data from over 860 samples from clinical cohorts spanning a broad range of age, BMI, and metabolic states. The research defined over 60 distinct cell types, including immune cells, vascular cells, and fibro-adipogenic precursors (FAPs), and described their spatial organization. The study found that most cell subpopulations were present in subcutaneous, omental, and perivascular WAT, though proportions differed. It also identified specific cell types, such as CD55/PI16-expressing adipose precursors and immune cells like lipid-associated macrophages, that were enriched in individuals with a pernicious metabolic phenotype (e.g., high HOMA-IR), while other cell types, like intermediate FAPs and capillary endothelial cells, were negatively associated with these parameters. Limitations include the lack of investigation into the influence of age and disease states on the meta-analysis results and that spatial analyses were only performed in subcutaneous WAT.