1409-P: Revealing Heterogeneity in Human White Adipose Tissue at Single-Cell Level

Abstract

White adipose tissue is characterized by substantial functional heterogeneity based on anatomic location and developmental lineages. Such differences may contribute to depot-dependent differences in adipose regulation of systemic metabolism and the relative impact of adipose distribution (e.g. subcutaneous, SQ, vs. intraabdominal, IA) on risk for type 2 diabetes. While mouse adipose depot heterogeneity at the single-cell level has recently been explored, comparative analysis of human white fat depots is still in its infancy.Hereby, we establish a single-nucleus RNA sequencing (snRNA Seq) method for isolating and sequencing intact single nuclei from frozen human WAT biopsies. Using this approach, we analyzed the transcriptome of individual nuclei from 22 WAT SQ or IA biopsies (SQ, 12 IA, 3 paired) acquired from subjects (16 females, 3 males) with or without type 2 diabetes (T2D) across a wide BMI range (Mean+/-SD = 45.4+/-10.3 kg/m2. Range: 23.6 - 60.9 kg/m2) . We show that both SQ and IA human fat depots demonstrate substantial cell-to-cell heterogeneity, and identify multiple adipose and non-adipose-related cell types resident in both tissues. Our analysis identifies several novel subclusters, including two distinct mature adipocyte subclusters, characterized by low vs. high adiponectin expression and thus potentially contributing to adipose-mediated effects on systemic metabolism. Moreover, we identify a novel cluster present in both SQ and IA depots, with a unique transcriptomic signature marked by DAPK1 and enrichment for hedgehog signaling and endocytosis KEGG terms. Comprehensive cross-sample integrative bioinformatics analysis using the software tools scVI and VISION reveals distinct molecular markers and transcriptomic signatures between depots, between clusters, and across a range of BMI, that may serve as promising targets for understanding the mechanism by which specific adipose-resident cell populations mediate metabolic risk associated with adiposity. Disclosure V.Efthymiou: None. S.Kodani: None. A.Gupta: None. F.Shamsi: None. A.Streets: None. Y.Tseng: Consultant; Cellarity. M.Patti: Consultant; AstraZeneca, Eiger BioPharmaceuticals, Hanmi Pharm. Co., Ltd., MBX Biosciences, Poxel SA, Other Relationship; Fractyl Health, Inc., Xeris Pharmaceuticals, Inc., Research Support; Dexcom, Inc. Funding Chan Zuckerberg Initiative (CZI)