Bioinformatics Analysis and Experimental Verification Identify Downregulation of COL27A1 in Poor Segmental Congenital Scoliosis.

backgroundCongenital scoliosis (CS) represents the congenital defect disease, and poor segmental congenital scoliosis (PSCS) represents one of its types. Delayed intervention can result in disability and paralysis. In this study, we would identify the core biomarkers for PSCS progression through bioinformatics analysis combined with experimental verification.

methodsThis work obtained the GSE11854 expression dataset associated with somite formation in the GEO database, which covers data of 13 samples. Thereafter, we utilized the edgeR of the R package to obtain DEGs in this dataset. Then, GO annotation, KEGG analyses, and DO annotation of DEGs were performed by "clusterProfiler" of the R package. This study performed LASSO regression for screening the optimal predicting factors for somite formation. Through RNA sequencing based on peripheral blood samples from healthy donors and PSCS cases, we obtained the RNA expression patterns and screen out DEGs using the R package DESeq2. The present work analyzed COL27A1 expression in PSCS patients by the RT-PCR assay.

resultsA total of 443 genes from the GSE11854 dataset were identified as DEGs, which were involved in BP associated with DNA replication, CC associated with chromosomal region, and MF associated with ATPase activity. These DEGs were primarily enriched in the TGF-

conclusionThis work sheds novel lights on DEGs related to the PSCS pathogenic mechanism, and COL27A1 is the possible therapeutic target for PSCS. Findings in this work may contribute to developing therapeutic strategies for PSCS.