bioRxivBioinformaticsPreprint
Role of RSPO3 in Estrogen-mediated Sex Differences in Body Fat Distribution: A Single-cell Data-driven Study
Qian Xu, Yongjian YangiD, Shreyan GuptaiD, Bo-Jia CheniD, Guanxun LiiD, Mathew Chamberlain, James J. CaiiD
Abstract
Obesity is a global health concern affecting more than one-third of the adult population worldwide. Epidemiological studies indicate that body fat distribution, more than overall adiposity, is a key risk factor for obesity-related diseases. Genome-wide association studies revealed that RSPO3 is associated with body fat distribution. Additionally, marked sex differences in body fat distribution are largely influenced by estrogen, suggesting that exploring the relationship between estrogen and RSPO3 expression may illuminate the mechanisms underlying the sexual dimorphism of fat distribution. We revisited a comprehensive set of gene expression data from humans and mice to explore these mechanisms. We assessed RSPO3 expression in male and female adipose tissues and utilized single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics to examine RSPO3s function within different tissues. Our findings confirmed significantly higher RSPO3 expression in male adipose tissue compared to female. Furthermore, our data for the first time suggest that estrogen plays a crucial role in fat distribution, as blocking estrogen signaling upregulates RSPO3 expression. In mouse liver, we observed a correlation between sex-specific ADK overexpression and RSPO3 expression, resulting in increased obesity and hepatocyte expansion via WNT/{beta}-catenin signaling in male mice. This study sheds light on how estrogen influences sexual dimorphism in fat distribution and underscores RSPO3s vital role in this process. These insights open new avenues for targeted therapeutic interventions addressing obesity and metabolic diseases with a focus on sex-specific factors.
- organism: human
- organism: mouse
- assay: scRNA-seq
- assay: spatial transcriptomics
- research focus: differential expression
- approach: statistical model
- Citations
- 0
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