Qi Yan1, Quan Xiao1,2, Jun Ge1, Cenhao Wu1, Yingjie Wang1, Hao Yu1, Huilin Yang1, Jun Zou1. 1. Department of Orthopaedic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China. 2. Department of Orthopaedic Surgery, The Affiliated Lianshui People's Hospital of Kangda College of Nan Jing Medical Universty, Lianshui, Jiangsu, China.
Abstract
OBJECTIVE: To find out the pathways and key genes and to reveal disc degeneration pathogenesis based on bioinformatic analyses. DESIGN: The GSE70362 dataset was downloaded from the GEO (Gene Expression Omnibus) database. Differentially expressed genes (DEGs) between the patients having disc degeneration and healthy controls were screened by Limma package in R language. Critical genes were identified by adopting gene ontologies (GOs), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and protein-protein interaction (PPI) networks. RESULTS: We identified 112 DEGs, including 60 genes which were upregulated and 52 that were downregulated. Analyses, such as GO and KEGG demonstrated that the DEGs got enriched in 4 biological processes and 2 signaling pathways, mainly related to disc degeneration. The PPI network analyses identified 5 key proteins, CCND1 (cyclin D1), GATA3, TNFSF11, LEF1, and DKK1 (Dickkopf related protein 1). CONCLUSION: In this study, the DEGs and pathways determined promoted us understand the disc degeneration mechanisms. Also, the study may contribute novel biomarkers for the diagnosis and prevention of disc degeneration, and seek new treatment methods to repair and even regenerate degenerative intervertebral disc.
OBJECTIVE: To find out the pathways and key genes and to reveal disc degeneration pathogenesis based on bioinformatic analyses. DESIGN: The GSE70362 dataset was downloaded from the GEO (Gene Expression Omnibus) database. Differentially expressed genes (DEGs) between the patients having disc degeneration and healthy controls were screened by Limma package in R language. Critical genes were identified by adopting gene ontologies (GOs), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and protein-protein interaction (PPI) networks. RESULTS: We identified 112 DEGs, including 60 genes which were upregulated and 52 that were downregulated. Analyses, such as GO and KEGG demonstrated that the DEGs got enriched in 4 biological processes and 2 signaling pathways, mainly related to disc degeneration. The PPI network analyses identified 5 key proteins, CCND1 (cyclin D1), GATA3, TNFSF11, LEF1, and DKK1 (Dickkopf related protein 1). CONCLUSION: In this study, the DEGs and pathways determined promoted us understand the disc degeneration mechanisms. Also, the study may contribute novel biomarkers for the diagnosis and prevention of disc degeneration, and seek new treatment methods to repair and even regenerate degenerative intervertebral disc.