GREM1,LRPPRC and SLC39A4 as Potential Biomarkers of Intervertebral Disc Degeneration:A Bioinformatics Analysis based on Multiple Microarray and Single-cell Sequencing Data

Abstract

Abstract Background:The issue of low back pain (LBP) has received considerable critical attention and has been a worldwide health problem. Intervertebral disc degeneration (IVDD) is always the subject of many classic studies in this field. The mechanistic basis of IVDD is poorly understood and has produced equivocal results. Methods: Gene expression profiles (GSE34095,GSE147383) of IVDD patients together with control groups were analyzed in order to identify differentially expressed genes (DEGs) in GEO database.GSE23130 and GSE70362 were applied to validate the obtained 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 correlation between overall immune infiltration levels with pfirmann grades and key genes. We also analyzed the upstream targeting miRNAs of key genes (GSE63492).We used single-cell transcriptome sequencing data (GSE160756) to define several cell clusters of nucleus pulposus (NP),annulus fibrosus (AF) and cartilaginous endplate (CEP) of degenerated disc and obtained the distribution of key genes in different cell clusters. Results: By developing appropriate p-values and logFC values, we obtained a total of 6 DEGs. We validated 3 key genes (LRPPRC, GREM1 and SLC39A4) 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 miRNet database and external GEO datasets. Finally, we plotted the spatial distribution of key genes in AF, CEP and NP. Conclusions: Our study offered a new perspective to identify the creadible and effective gene therapy targets in IVDD.