No abstract

Long non-coding RNAs (lncRNAs) belong to a recently discovered class of molecules proposed to regulate various cellular processes. Here, we systematically analyzed their expression in human subcutaneous white adipose tissue (WAT) and found that a limited set was differentially expressed in obesity and/or the insulin resistant state. Two lncRNAs herein termed adipocyte-specific metabolic related lncRNAs, ASMER-1 and ASMER-2 were enriched in adipocytes and regulated by both obesity and insulin resistance. Knockdown of either ASMER-1 or ASMER-2 by antisense oligonucleotides in in vitro differentiated human adipocytes revealed that both genes regulated adipogenesis, lipid mobilization and adiponectin secretion. The observed effects could be attributed to crosstalk between ASMERs and genes within the master regulatory pathways for adipocyte function including PPARG and INSR. Altogether, our data demonstrate that lncRNAs are modulators of the metabolic and secretory functions in human fat cells and provide an emerging link between WAT and common metabolic conditions.

To date, single-cell studies of human white adipose tissue (WAT) have been based on small cohort sizes and no cellular consensus nomenclature exists. Herein, we performed a comprehensive meta-analysis of publicly available and newly generated single-cell, single-nucleus, and spatial transcriptomic results from human subcutaneous, omental, and perivascular WAT. Our high-resolution map is built on data from ten studies and allowed us to robustly identify >60 subpopulations of adipocytes, fibroblast and adipogenic progenitors, vascular, and immune cells. Using these results, we deconvolved spatial and bulk transcriptomic data from nine additional cohorts to provide spatial and clinical dimensions to the map. This identified cell-cell interactions as well as relationships between specific cell subtypes and insulin resistance, dyslipidemia, adipocyte volume, and lipolysis upon long-term weight changes. Altogether, our meta-map provides a rich resource defining the cellular and microarchitectural landscape of human WAT and describes the associations between specific cell types and metabolic states.