基于生物信息学探讨骨质疏松症与肌少症的关系

目的基于生物信息学探讨骨质疏松症与肌少症的关系。方法通过7个大型疾病数据库(CTD、Disgenet、TTD、OMIM、GeneC ards、Drugbank、KEGG数据库)对骨质疏松症和肌少症的相关基因进行分析筛选,并对筛选结果进行基因GO富集分析以及KEGG通路分析,利用STRING网站对骨质疏松症与肌少症共同靶点基因进行蛋白互作网络分析,并进行基因富集分析和KEGG通路分析。结果通过疾病数据库筛选分别选出与骨质疏松症和肌少症相关基因1 782个、429个。通过基因富集分析和KEGG通路分析,骨质疏松症与肌少症相关通路集中在PI3K-Akt、Longevity调控、FoxO、AGE-RAGE、HIF-1、AMPK、JAK-STAT、MAPK、Insulin、TNF以及Apoptosis过程。结论骨质疏松症与肌少症均为复杂代谢性疾病,涵盖众多差异表达基因,但两种疾病发病过程中依然存在一些高度重合的差异基因表达,其可同时对两种疾病进行调控作用。这提示骨质疏松症与肌少症之间发病机制存在密切关联,共同靶点基因可作为同时干预两种疾病的治疗目标。

Study of the relationship between osteoporosis and sarcopenia based on bioinformatics

Objective To explore the relationship between osteoporosis and sarcopenia based on bioinformatics. Methods The co-expressed genes of osteoporosis and sarcopenia were analyzed and screened through seven disease databases (CTD, Disgenet, TDD, OMIM, GeneCards, Drugbank, and KEGG database). GO enrichment analysis and KEGG pathway analysis were carried out based on the filtering results. The STRING website was used for osteoporosis and sarcopenia common target gene analysis and protein interaction network analysis. Results 1782 genes related to osteoporosis and 429 genes to sarcopenia were selected through disease database screening. Through gene GO enrichment analysis and KEGG pathway analysis, the pathways related to osteoporosis and sarcopenia were concentrated in PI3K-Akt, longevity regulation, FoxO, AGE-RAGE, HIF-1, AMPK, JAK-STAT, MAPK, insulin, TNF, and apoptosis processes. Conclusion Osteoporosis and sarcopenia are both complex metabolic diseases, involving many differentially expressed genes. However, there are still some highly overlapping differentially expressed genes in the pathogenesis of the two diseases, which can regulate both diseases at the same time. This suggests that there is a close correlation between the pathogenesis of osteoporosis and sarcopenia, and the common target genes can be used as the therapeutic target to intervene in both diseases at the same time.