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Isolation, Expansion, and Adipogenic Induction of CD34+CD31+ Endothelial Cells from Human Omental and Subcutaneous Adipose Tissue
Published on: July 17, 2018
Gene expression profiling of subcutaneous adipose tissue reveals new biomarkers in acromegaly
Camilla M Falch1,2,3, Mai Christiansen Arlien-Søborg4,5, Jakob Dal6,7
1Section of Specialized Endocrinology, Oslo University Hospital (OUS), Postboks 4950 Nydalen, 0424 Oslo, Norway.
Context:
Active acromegaly is characterized by lipolysis-induced insulin resistance, which suggests adipose tissue (AT) as a primary driver of metabolic aberrations.
Objective:
To study the gene expression landscape in AT in patients with acromegaly before and after disease control in order to understand the changes and to identify disease-specific biomarkers.
Methods:
RNA sequencing was performed on paired subcutaneous adipose tissue (SAT) biopsies from six patients with acromegaly at time of diagnosis and after curative surgery. Clustering and pathway analyses were performed in order to identify disease activity-dependent genes. In a larger patient cohort (n = 23), the corresponding proteins were measured in serum by immunoassay. Correlations between growth hormone (GH), insulin-like growth factor I (IGF-I), visceral AT (VAT), SAT, total AT, and serum proteins were analyzed.
Results:
743 genes were significantly differentially expressed (P-adjusted < .05) in SAT before and after disease control. The patients clustered according to disease activity. Pathways related to inflammation, cell adhesion and extracellular matrix, GH and insulin signaling, and fatty acid oxidation were differentially expressed.Serum levels of HTRA1, METRNL, S100A8/A9, and PDGFD significantly increased after disease control (P < .05). VAT correlated with HTRA1 (R = 0.73) and S100A8/A9 (R = 0.55) (P < .05 for both).
Conclusion:
AT in active acromegaly is associated with a gene expression profile of fibrosis and inflammation, which may corroborate the hyper-metabolic state and provide a means for identifying novel biomarkers.

