Background: Studies have revealed that coronavirus disease 2019 (COVID-19) could induce or aggravate osteoporosis (OP) which is the most common metabolic bone disease, and T cells participated in the progression of OP. Methods: OP and COVID-19 related RNA sequencing data (RNA-seq) were downloaded from the bioinformatics database. Firstly, differentially expressed genes between OP and control samples and between COVID-19 and healthy samples were screened out by differential analyses for further intersection to obtain intersected genes. Then, weighted gene co-expression network analysis (WGCNA) was applied based on T cell infiltrating scores (T-scores) calculated by “MCPcounter” package to screen T cell related genes (TRGs). Subsequently, these TRGs were intersected with intersected genes to obtain biomarkers. In addition, to figure out deeper mechanism of them, we conducted enrichment analyses and constructed miRNA-mRNA and TF-miRNA networks of biomarkers. Results: Based on the OP and COVID-19 datasets, totals of 14 intersected genes were obtained via differential analyses, and 459 TRGs were screened out after WGCNA. Then, 3 biomarkers including ITGA7, ZNF302, and LYRM7 were acquired by intersection between TRGs and intersected genes. Results of enrichment analyses demonstrated that biomarkers were mainly commonly enriched in “mitochondrial protein-containing complex”, “Proteasome”, and “Spliceosome” in OP, and “transmitter−gated channel activity”, “Nicotine addiction”, and so on in COVID-19. Otherwise, we predicted 7 micro RNAs (miRNAs) and 46 transcription factors (TFs) regulating the biomarkers, and constructed the miRNA-mRNA and TF-mRNA networks. Conclusion: In this study, we screened out 3 biomarkers associated with OP, COVID-19, and T cells, namely ITGA7, ZNF302, and LYRM7, that had preferable prediction performance of OP. The results could provide references for further studies and treatments of OP.