Lumbar spinal stenosis (LSS) is a common skeletal system disease that has been partly attributed to genetic variation. However, the correlation between genetic variation and pathological changes in LSS is insufficient, and it is difficult to provide a reference for the early diagnosis and treatment of the disease. We conducted a transcriptome-wide association study (TWAS) of spinal canal stenosis by integrating genome-wide association study summary statistics (including 661 cases and 178,065 controls) derived from Biobank Japan, and pre-computed gene expression weights of skeletal muscle and whole blood implemented in FUSION software. To verify the TWAS results, the candidate genes were furthered compared with messenger RNA (mRNA) expression profiles of LSS to screen for common genes. Finally, Metascape software was used to perform enrichment analysis of the candidate genes and common genes.Aims
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This study aimed, through bioinformatics analysis and in vitro experiment validation, to identify the key extracellular proteins of intervertebral disc degeneration (IDD). The gene expression profile of GSE23130 was downloaded from the Gene Expression Omnibus (GEO) database. Extracellular protein-differentially expressed genes (EP-DEGs) were screened by protein annotation databases, and we used Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) to analyze the functions and pathways of EP-DEGs. STRING and Cytoscape were used to construct protein-protein interaction (PPI) networks and identify hub EP-DEGs. NetworkAnalyst was used to analyze transcription factors (TFs) and microRNAs (miRNAs) that regulate hub EP-DEGs. A search of the Drug Signatures Database (DSigDB) for hub EP-DEGs revealed multiple drug molecules and drug-target interactions.Aims
Methods