Exploration of the common genetic landscape of COVID-19 and male infertility - Chen, Yinwei; Sun, Taotao; Liu, Kang; Yuan, Penghui; Liu, Chang (Frontiers in Immunology, 2023)
Background COVID-19 has spread widely across continents since 2019, causing serious damage to human health. Accumulative research uncovered that SARS-CoV-2 poses a great threat to male fertility, and male infertility (MI) is a common comorbidity for the COVID-19 pandemic. The aim of the study was to explore the cross-talk molecular mechanisms between COVID-19 and MI. Materials and methods A total of four transcriptome data regarding COVID-19 and MI were downloaded from the Gene Expression Omnibus (GEO) repository, and were divided for two purposes (initial analysis and external validation). Differentially expressed genes (DEGs) analysis, GO and pathway annotation, protein-protein interaction (PPI) network, connectivity ranking, ROC analysis, immune infiltration, and translational and post-translational interaction were performed to gain hub COVID-19-related DEGs (CORGs). Moreover, we recorded medical information of COVID-19 patients with MI and matched healthy controls, and harvested their sperm samples in the university hospital. Expressions of hub CORGs were detected through the qRT-PCR technique. Results We identified 460 overlapped CORGs in both the COVID-19 DEGs and MI DEGs. CORGs were significantly enriched in DNA damage and repair-associated, cell cycle-associated, ubiquitination-associated, and coronavirus-associated signaling. Module assessment of PPI network revealed that enriched GO functions were closely related to cell cycle and DNA metabolism processes. Pharmacologic agent prediction displayed protein-drug interactions of ascorbic acid, biotin, caffeine, and L-cysteine with CORGs. After connectivity ranking and external validation, three hub CORGs (ENTPD6, CIB1, and EIF3B) showed good diagnostic performance (area under the curve > 0.75). Subsequently, three types of immune cells (CD8+ T cells, monocytes, and macrophages M0) were dominantly enriched, and 24 transcription factor-CORGs interactions and 13 miRNA-CORGs interactions were constructed in the network. Finally, qRT-PCR analysis confirmed that there were significant differences in the expression of hub CORGs (CIB1 and EIF3B) between the patient and control groups. Conclusion The present study identified and validated hub CORGs in COVID-19 and MI, and systematically explored molecular interactions and regulatory features in various biological processes. Our data provide new insights into the novel biomarkers and potential therapeutic targets of COVID-19-associated MI.