Unveiling Multi-Omics and Immune Landscapes in COVID-19 Patients' Ovaries Microenvironment for Oocyte Competency Biomarkers Identification

Background: The outbreak of coronavirus disease 2019 (COVID-19) poses a considerable health threat to humanity, with potential implications for the ovarian microenvironment remaining uncertain. Methods: Transcriptomic and proteomic analyses of ovarian granulosa cells, along with metabolomic and lipidomic profiling of follicular fluid, were conducted on 17 non-COVID-19 cases and 9 COVID-19 cases. This study received approval from the ethics committee (KYLL-2022-581). Generalized estimating equations model was performed to identify oocyte competency biomarkers. Additionally, cell proliferation, apoptosis, and altered pathways were examined following lentivirus transfection. Methods: Transcriptomic and proteomic analyses of ovarian granulosa cells, along with metabolomic and lipidomic profiling of follicular fluid, were conducted on 17 non-COVID-19 cases and 9 COVID-19 cases. This study received approval from the ethics committee (KYLL-2022-581). Generalized estimating equations model was performed to identify oocyte competency biomarkers. Additionally, cell proliferation, apoptosis, and altered pathways were examined following lentivirus transfection. Conclusions: By integrating untargeted metabolomic and lipidomic features, we identified biomarkers indicative of oocyte competency influenced by COVID-19. Overall design: To investigate the influence of COVID-19 on ovarian granulosa cells, transcriptomic analyses of ovarian granulosa cells were conducted on 17 non-COVID-19 cases and 9 COVID-19 cases.