Spatial Transcriptomic Analysis of Human Visceral Adipose Tissue in Different Metabolic Status: Methodological Validation and Application

Background: Adipose tissue consists predominantly of lipid-filled adipocytes with limited cytoplasmic space, posing challenges for spatial transcriptomic analysis. Spatially-resolved laser-activated cell sorting (SLACS) enables precise isolation of tissue sections, offering a strategy to overcome these challenges. Methods: Human visceral adipose tissue (VAT) samples from lean individuals and those with obesity and type 2 diabetes mellitus (Ob-DM) were analyzed. SLACS was used to isolate perivascular (PV) and adipocyte-rich (AD) areas, followed by full-length RNA sequencing to investigate pathways, cellular composition, and post-transcriptional regulation. Results: PV and AD areas exhibited distinct transcriptional patterns. Fibro-inflammatory signatures and vascular remodeling pathways were enriched in the PV, while lipid metabolism and antioxidant pathways were predominant in the AD. Cellular deconvolution suggested area- and disease-specific cell composition. Post-transcriptional modifications, including adenosine-to-inosine (A-to-I) RNA editing and isoform switching in metabolic genes were observed in Ob-DM, suggesting a potential contributor to adipose dysfunction. Conclusion: This study demonstrates the technical feasibility of SLACS-based spatial transcriptomic profiling in human VAT, with exploratory biological findings that warrant validation in larger cohorts.