Systematic analysis of Long non-coding RNAs reveals diagnostic biomarkers and potential therapeutic drugs for intervertebral disc degeneration

• Main Authors: Jiawen Zhan, Shangquan Wang, Xu Wei, Minshan Feng, Xunlu Yin, Jie Yu, Tao Han, Guangwei Liu, Wangwen Xuan, Xiaobo Wang, Rui Xie, Kai Sun, Liguo Zhu
• Format: Article
• Language: English
• Published: Taylor & Francis Group 2021-01-01
• Series: Bioengineered
• Subjects: intervertebral disc degeneration; lncrna; support vector machine; weighted gene co-expression network analysis
• Online Access: http://dx.doi.org/10.1080/21655979.2021.1950258
• ISSN: 2165-5979; 2165-5987

Long non-coding RNAs (lncRNAs) are related to a variety of human diseases. However, little is known about the role of lncRNA in intervertebral disc degeneration (IDD). LncRNA expression profile of human IDD were downloaded from Gene Expression Omnibus (GEO) database. Potential biomarkers and therapeutic drugs for IDD were analyzed by weighted gene co-expression network analysis (WGCNA), R software package Limma, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). We identified 1455 differentially expressed genes and 423 differentially expressed lncRNAs. Twenty-six co-expression modules were obtained, among them, the tan, brown, and turquoise modules were most closely related to IDD. The turquoise module contained a large number of differential expressed lncRNAs and genes, these genes were mainly enriched in the MAPK signaling pathway, TGF-beta signaling pathway. Furthermore, we obtained 11,857 LmiRM-Degenerated, these lncRNAs and genes showed higher differential expression multiples and higher expression correlation. After constructing a disease-gene interaction network, 25 disease-specific genes and 9 disease-specific lncRNAs were identified. Combined with the drug-target gene interaction network, three drugs, namely, Calcium citrate, Calcium Phosphate, and Calcium phosphate dihydrate, which may have curative effects on IDD, were determined. Finally, a genetic diagnosis model and lncRNA diagnosis model with 100% diagnostic performance in both the training data set and the validation data set were established based on these genes and lncRNA. This study provided new diagnostic features for IDD and could help design personalized treatment of IDD.