Research Paper Volume 13, Issue 2 pp 2149—2167
Identification of SCARA3 with potential roles in metabolic disorders
- 1 Department of Endocrinology, Endocrinology Research Center, Xiangya Hospital of Central South University, Changsha, China
Received: July 22, 2020 Accepted: October 22, 2020 Published: December 9, 2020https://doi.org/10.18632/aging.202228
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Copyright: © 2020 Peng et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Obesity is characterized by the expansion of adipose tissue which is partially modulated by adipogenesis. In the present study, we identified five differentially expressed genes by incorporating two adipogenesis-related datasets from the GEO database and their correlation with adipogenic markers. However, the role of scavenger receptor class A member 3 (SCARA3) in obesity-related disorders has been rarely reported. We found that Scara3 expression in old adipose tissue-derived mesenchymal stem cells (Ad-MSCs) was lower than it in young Ad-MSCs. Obese mice caused by deletion of the leptin receptor gene (db/db) or by a high-fat diet both showed reduced Scara3 expression in inguinal white adipose tissue. Moreover, hypermethylation of SCARA3 was observed in patients with type 2 diabetes and atherosclerosis. Data from the CTD database indicated that SCARA3 is a potential target for metabolic diseases. Mechanistically, JUN was predicted as a transcriptional factor of SCARA3 in different databases which is consistent with our further bioinformatics analysis. Collectively, our study suggested that SCARA3 is potentially associated with age-related metabolic dysfunction, which provided new insights into the pathogenesis and treatment of obesity as well as other obesity-associated metabolic complications.
GEO: Gene Expression Omnibus; DEGs: Differentially expressed genes; WGCNA: Weighted Gene Co-Expression Network Analysis; TOM: topological overlap matrix; PPI: Protein–protein interaction; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; AP-1: activator protein 1; CTD: Comparative Toxicogenomics Database; GSEA: Gene Set Enrichment Analysis; HFD: High-fat diet; iWAT: inguinal white adipose tissue; Ad-MSCs: adipose tissue-derived mesenchymal stem cells; MSCs: Mesenchymal stem cells; GHR: growth hormone receptor; GPX3: glutathione peroxidase 3; SAA1: serum amyloid A1; SCARA3: scavenger receptor class A member 3; WFDC1: WAP four-disulfide core domain 1; qRT-PCR: Quantitative real-time reverse transcription PCR; NC: Negative control.