Integrated analysis of gene modulation profile identifies pathogenic factors and pathways in the liver of diabetic mice

基因调控谱综合分析确定糖尿病小鼠肝脏致病因素及途径

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作者:Thai Quoc Tran, Yuan-Man Hsu, Yu-Chuen Huang, Chao-Jung Chen, Wei-De Lin, Ying-Ju Lin, Wen-Ling Liao, Wei-Yong Lin, Jai-Sing Yang, Jinn-Chyuan Sheu, Shih-Yin Chen, Fuu-Jen Tsai

Conclusion

These findings provide valuable reference data that can facilitate further detailed investigations to elucidate the pathogenic mechanism of obesity-induced diabetes in mice, which can be associated with the human condition to inform new prevention and treatment strategies.

Methods

The KK.Cg-Ay mouse strain is one such model that has offered insight into obesity-related T2D pathogenesis. To comprehensively assess the association between obesity and T2D, in the present study, we performed microarray analysis on liver tissue samples of KK.Cg-Ay and KK-α/α wild-type mice to examine differences in gene expression and methylation patterns and their related biological processes and pathways.

Purpose

Type-2 diabetes mellitus (T2D) is a metabolic disorder that can progress to a serious chronic disease and frequently develops in obese individuals in association with various pathogenic complications that shorten the lifespan of these patients. The liver is an important organ regulating lipid metabolism, which is damaged in both obesity and T2D; however, the specific pathways involved in these pathogenic effects remain unclear. Establishing a suitable animal model that effectively mimics the human biological condition is a critical factor to allow for precise identification of T2D-related genes.

Results

We found that inflammation accompanied by abnormal lipid metabolism led to the spontaneous mechanism of obesity-induced diabetes, resulting in differential expression of some genes related to the terms of insulin resistance and glucose tolerance. Surprisingly, disruption of steroid biosynthesis strongly facilitated the diabetic pathogenesis. To support these findings, we highlighted some candidate genes and determined their relationships in biological networks of obesity-induced T2D.

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