GREM1, LRPPRC and SLC39A4 as potential biomarkers of intervertebral disc degeneration: a bioinformatics analysis based on multiple microarray and single-cell sequencing data

被引:0
作者
Zhang, ZhaoLiang [1 ]
Huo, JianZhong [2 ]
Ji, XingHua [1 ]
Wei, LinDong [1 ]
Zhang, Jinfeng [1 ]
机构
[1] Shanxi Med Univ, Shanxi Bethune Hosp, Tongji Shanxi Hosp, Shanxi Acad Med Sci,Hosp 1, Taiyuan 030032, Peoples R China
[2] Shanxi Med Univ, Taiyuan Cent Hosp, Hosp 9, Southern Fendong Rd 256, Taiyuan 030009, Shanxi, Peoples R China
关键词
Intervertebral disc degeneration; Transcriptomes; Immuno-infiltration; MicroRNAs; GREM1; LRPPRC; Single-cell sequencing; GENE-EXPRESSION OMNIBUS; IMMUNE PRIVILEGE; APOPTOSIS; THERAPY; BENCH;
D O I
10.1186/s12891-023-06854-4
中图分类号
R826.8 [整形外科学]; R782.2 [口腔颌面部整形外科学]; R726.2 [小儿整形外科学]; R62 [整形外科学(修复外科学)];
学科分类号
摘要
BackgroundLow back pain (LBP) has drawn much widespread attention and is a major global health concern. In this field, intervertebral disc degeneration (IVDD) is frequently the focus of classic studies. However, the mechanistic foundation of IVDD is unclear and has led to conflicting outcomes.MethodsGene expression profiles (GSE34095, GSE147383) of IVDD patients alongside control groups were analyzed to identify differentially expressed genes (DEGs) in the GEO database. GSE23130 and GSE70362 were applied to validate the yielded key genes from DEGs by means of a best subset selection regression. Four machine-learning models were established to assess their predictive ability. Single-sample gene set enrichment analysis (ssGSEA) was used to profile the correlation between overall immune infiltration levels with Thompson grades and key genes. The upstream targeting miRNAs of key genes (GSE63492) were also analyzed. A single-cell transcriptome sequencing data (GSE160756) was used to define several cell clusters of nucleus pulposus (NP), annulus fibrosus (AF), and cartilaginous endplate (CEP) of human intervertebral discs and the distribution of key genes in different cell clusters was yielded.ResultsBy developing appropriate p-values and logFC values, a total of 6 DEGs was obtained. 3 key genes (LRPPRC, GREM1, and SLC39A4) were validated by an externally validated predictive modeling method. The ssGSEA results indicated that key genes were correlated with the infiltration abundance of multiple immune cells, such as dendritic cells and macrophages. Accordingly, these 4 key miRNAs (miR-103a-3p, miR-484, miR-665, miR-107) were identified as upstream regulators targeting key genes using the miRNet database and external GEO datasets. Finally, the spatial distribution of key genes in AF, CEP, and NP was plotted. Pseudo-time series and GSEA analysis indicated that the expression level of GREM1 and the differentiation trajectory of NP chondrocytes are generally consistent. GREM1 may mainly exacerbate the degeneration of NP cells in IVDD.ConclusionsOur study gives a novel perspective for identifying reliable and effective gene therapy targets in IVDD.
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