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| 骨质疏松症与银屑病之间的相互关系 |
| Relationship between osteoporosis and psoriasis |
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| DOI：10.3969/j.issn.1006.7108.2022.03.015 |
| 中文关键词: 骨质疏松症 银屑病 疾病关系 分子机制 |
| 英文关键词:osteoporosis psoriasis disease correlation molecular mechanism |
| 基金项目:国家自然科学基金资助项目(81473709)；山东省自然科学基金重点项目（ZR2020KH011）；济南市临床医学科技创新计划（202019148）；山东中医药大学青年创新团队项目 |
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| 中文摘要: |
| 目的 探讨骨质疏松症与银屑病之间在分子层面的相互作用关系。方法 将骨质疏松及银屑病输入不同疾病数据库以筛选相关基因，将两组靶点通过Venny分析得到关键靶点，并于STRING平台制作蛋白互作网络以区分出核心靶点，通过DAVID平台进行富集分析。结果 检索到骨质疏松症相关靶点875个，银屑病预测靶点478个，交集出关键靶点93个，以degree≥50筛选出Hub节点中的18个核心靶点，导入DAVID平台获得148项GO生物过程（P<0.05）及44条KEGG信号通路（P<0.05）。银屑病通过TNF、IL-6、IL-10、IL-2、IL-1B等核心靶点作用于炎性肠病信号通路、TNF信号通路等特异性通路发挥协调作用，调控骨代谢，诱发骨质疏松。 结论 两种复杂疾病在分子机制上有着密切联系，银屑病通过大量炎性靶点及通路影响患者骨代谢，诱发骨质疏松。借助各疾病数据库在分子层面进行探讨具有较高的置信度和参考价值，可更深层次探索复杂疾病间的网络样关系并开拓治疗新思路。 |
| 英文摘要: |
| Objective To explore the molecular interaction mechanism between osteoporosis and psoriasis. Methods Osteoporosis and psoriasis were input into different disease data bases to screen the related genes. Key targets were obtained through Venny analysis of the two groups of targets. A protein interaction network was constructed on the String platform to identify the core targets, and enrichment analysis was conducted on the David platform. Results 875 targets related to osteoporosis and 478 predictive targets for psoriasis were retrieved. 93 key targets were intersected. 18 core targets with degree≥50 in the Hub node were screened out. 148 GO biological processes (P<0.05) and 44 KEGG signal pathways (P<0.05) were obtained by importing them into the DAVID platform. Psoriasis played a coordinated role in specific pathways such as inflammatory bowel disease signaling pathway and TNF signaling pathway through core targets such as TNF, IL6, IL10, IL2, and IL1B, and regulated bone metabolism and induced osteoporosis. Conclusion The two complex diseases are closely related in molecular mechanism. Psoriasis affects the bone metabolism through a large number of inflammatory targets and pathways, and induces osteoporosis. With the help of disease databases, it has high confidence and reference value to explore the network-like relationship among complex diseases and may develop new ideas for the treatment. |
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