ABSTRACT
The COVID-19 pandemic caused by the severe acute coronavirus disease 2 (SARS-CoV-2) virus represents an ongoing threat to human health and well-being. Notably, many COVID-19 patients suffer from complications consistent with osteoporosis (OP) following disease resolution yet the mechanistic links between SARS-CoV-2 infection and OP remain to be clarified. The present study was thus developed to explore the potential basis for this link by employing transcriptomic analyses to identify signaling pathways and biomarkers associated with OP and SARS-CoV-2. Specifically, a previously published RNA-sequencing dataset (GSE152418) from Gene Expression Omnibus (GEO) was used to identify the differentially expressed genes (DEGs) in OP patients and individuals infected with SARS-CoV-2 as a means of exploring the underlying molecular mechanisms linking these two conditions. In total, 2,885 DEGs were identified by analyzing the COVID-19 patient dataset, with shared DEGs then being identified by comparison of these DEGs with those derived from an OP patient dataset. Hub genes were identified through a series of bioinformatics approaches and protein-protein interaction analyses. Predictive analyses of transcription factor/gene interactions, protein/drug interactions, and DEG/miRNA networks associated with these DEGs were also conducted. Together, these data highlight promising candidate drugs with the potential to treat both COVID-19 and OP.