节点文献
基于生物信息学探讨肥胖与不孕症的关系
To explore the relationship between obesity and infertility based on bioinformatics
【摘要】 目的 通过生物信息学技术方法探讨肥胖与不孕症的关系。方法 在GeneCards、TTD、OMIM疾病数据库中挖掘并筛选肥胖和不孕症的相关基因,结合Uniprot数据库得到相关基因靶点,去重、映射后得到关键靶点,基于STRING数据库构建关键靶点的PPI网络图,筛选出核心靶点,利用DAVID数据库进行GO和KEGG富集分析。结果 搜索与筛选不孕症相关靶点312个及肥胖相关靶点483个,包括关键靶点61个,以Degree值≥16筛选出核心靶点17个,得到33项GO富集结果及13条KEGG信号通路。结论 胰岛素、促阿片-黑素细胞皮质素原、瘦素、白细胞介素6、肿瘤坏死因子等核心靶点通过脂肪细胞因子信号通路、Janu激酶/信号转导与转录激活子信号通路、胰岛素抵抗信号通路、腺苷酸激活蛋白激酶信号通路、卵巢类固醇生成信号通路、磷脂酰肌醇3-激酶/蛋白激酶B信号通路、哺乳动物雷帕霉素靶蛋白信号通路等多个通路对两个疾病起到调控作用。肥胖与不孕症两疾病之间内分泌通讯是双向的,本文以期为后续机制进一步的探讨和实验设计的优化等提供思路。
【Abstract】 Objective To explore the relationship between obesity and infertility through bioinformatics techniques. Methods The genes related to infertility and obesity were mined and screened in GeneCards, TTD and OMIM disease databases. The related gene targets were obtained by combining Uniprot database, and the key targets were obtained by deduplicating and mapping. PPI network diagrams of the key targets were constructed based on STRING database, and the core targets were selected for GO and KEGG enrichment analysis with DAVID database. Results There were 312 infertility related targets and 483 obesity-related targets, including 61 key targets. 17 core targets were screened with Degree value ≥16, 33 GO enrichment results, and 13 KEGG signaling pathways were obtained. Conclusion INS, POMC, LEP, IL6, TNF and other core targets play a regulatory role in the two diseases through adipocytokine, JAK-STAT, insulin resistance, AMPK, ovarian steroid generation, PI3 K-Akt, mTOR and other signaling pathways. Endocrine communication between obesity and infertility is bidirectional. We aims to provide ideas for further discussion of the follow-up mechanism and optimization of experimental design.
- 【文献出处】 中国生育健康杂志 ,Chinese Journal of Reproductive Health , 编辑部邮箱 ,2022年05期
- 【分类号】R711.6;Q811.4;R589.2
- 【下载频次】120