Reduced lipolysis in lipoma phenocopies lipid accumulation in obesity

Abstract

Background Elucidation of lipid metabolism and accumulation mechanisms is of paramount importance to understanding obesity and unveiling therapeutic targets. In vitro cell models have been extensively used for these purposes, yet, they do not entirely reflect the in vivo setup. Conventional lipomas, characterized by the presence of mature adipocytes and increased adipogenesis, could overcome the drawbacks of cell cultures. Also, they have the unique advantage of easily accessible matched controls in the form of subcutaneous adipose tissue (SAT) from the same individual. We aimed to determine whether lipomas are a good model to understand lipid accumulation. Methods We histologically compared lipomas and control SAT, followed by assessment of the lipidome using high-resolution 1H NMR spectroscopy and ESI-IT mass spectrometry. RNA-sequencing was used to obtain the transcriptome of lipomas and the matched SAT. Results We found a significant increase of small-size (maximal axis < 70 µm) and very big (maximal axis > 150 µm) adipocytes within lipomas. This suggests both enhanced adipocyte proliferation and increased lipid accumulation. We further show that there is no significant change in the lipid composition compared to matched SAT. To better delineate the pathophysiology of lipid accumulation, we considered two groups with different genetic backgrounds: (1) lipomas with HMGA2 fusions and (2) without gene fusions. To reduce the search space for genes that are relevant for lipid pathophysiology, we focused on the overlapping differentially expressed (DE) genes between the two groups. Gene Ontology analysis revealed that DE genes are enriched in pathways related to lipid accumulation. Conclusions We show that the common shared lipid accumulation mechanism in lipoma is a reduction in lipolysis, with most gene dysregulations leading to a reduced cAMP in the adipocyte. Superficial lipomas could thus be used as a model for lipid accumulation through altered lipolysis as found in obese patients.

Probabilistic outlier identification for RNA sequencing generalized linear models

“…The application of our model to a series of datasets gathered from public sources, including GSE137631 ( 27 ), GSE141027 ( 28 ), GSE99374 ( 29 ), GSE151005 ( 30 ), Mangiola_2018 ( 26 ) and Atkins_2019 ( 31 ), revealed that a median of 10.6%, 3.3% and 10.4% of differentially abundant transcripts inferred by edgeR, the robust edgeR implementation (using estimateGLMRobustDisp) and DESeq2 respectively (using recommended analysis pipelines for data filtering, normalisation and modelling ( 32 , 33 )) had inflated statistics caused by the presence of outliers (Figure 4A ). The analyses were performed using tidybulk framework ( 34 ) and broom ( 35 ).…”

URAT1-selective inhibition ameliorates insulin resistance by attenuating diet-induced hepatic steatosis and brown adipose tissue whitening in mice

“…Hematoxylin and eosin-stained sections were visualized using ECLIPS 80i (Nikon Co., Tokyo, Japan). Adipocytes images in WAT were analyzed for adipocyte size using BZ-X800 analyzer software (Keyence Corp., Osaka, Japan) following the manufacturer's instructions [ 26 ]. The size of approximately 800–1000 adipocytes in WAT per mouse was assessed by measuring the diameter of the lipid droplets and averaged [ 27 ].…”

Altered gene expression profiles impair the nervous system development in individuals with 15q13.3 microdeletion

“…To identify molecular pathways that may be affected by the gene expression profiles we performed GO enrichment analysis followed by protein-protein-interaction (PPI) networks, as previously described 37,38 . Using the mouse data, we identified general GO categories like cellular components or developmental processes to be enriched with DEGs (Supplementary Table S2).…”