Machine learning algorithm predicts fibrosis-related blood diagnosis markers of intervertebral disc degeneration

Abstract

Abstract Background The fibrosis of intervertebral disc cells has been proven to be relevant to intervertebral disc degeneration (IDD). This study is devoted to screening fibrosis-related diagnostic genes for IDD patients. Results CEP120, SPDL1 were screened as diagnostic genes. NK cells, neutrophils, and MDSC represented significantly different proportions between IDD and control samples. It was indicated that AC144548.1 could regulate the expression of SPDL1 and CEP120 by combining hsa-miR-5195-3p and hsa-miR-455-3p respectively. Additionally, TFs FOXM1, PPARG, ATF3 could regulate the transcription of SPDL1 and CEP120. A total of 56 drugs were predicted to target drug prediction. The down-regulations of SPDL1 and CEP120 were validated as well. Conclusion This study identified two fibrosis-related diagnostic genes for IDD patients and found their potential regulatory network and target drugs, which could theoretical basis and reference for further study of IDD in the fibrosis-related gene area.