Endometrial gene expression differences in women with coronavirus disease 2019
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Objective: To study the potential effect of COVID-19 on the endometrium of affected symptomatic women. Design: Preliminary study of the endometrial transcriptomes in women with COVID-19 through RNA sequencing. Setting: Hospital and university laboratories. Subjects: Women with COVID-19 lacking SARS-CoV-2 infection in endometrial tissue. Intervention/Exposure: Endometrial biopsy collection. Main outcomes measures: Endometrial gene expression and functional analysis of patients with COVID-19 versus uninfected individuals. Results: COVID-19 systemic disease alters endometrial gene expression in 75% of women, with patients exhibiting a preponderance of 163 up-regulated (e.g., UTS2, IFI6, IFIH1, BNIP3) and 72 down-regulated genes (e.g., CPZ, CDH3, IRF4) (FDR<0.05). A total of 161 dysregulated functions (36 up-regulated and 125 down-regulated) were typically enriched in COVID-19 endometria, including upregulation in pathways involved in response to virus and cytokine inflammation, highlighting upregulation of a COVID-19 response pathway. Conclusion: COVID-19 affects endometrial gene expression despite the absence of SARS-CoV-2 particles in endometrial tissues. A total of 24 endometrial samples were collected for this study. Fourteen biopsies (COVID-19 group) came from COVID-19 patients hospitalized at Hospital Universitari i Politècnic La Fe (Valencia, Spain) (14); these patients had a positive result (cycle threshold, CT < 37) for SARS-CoV-2 infection indicated by real-time polymerase chain reaction (RT-PCR) of nasopharyngeal swabs. The other ten endometria (control group) were derived from patients with benign gynecological disorders not related to endometrium (negative result in a COVID-19 RT-PCR diagnostic test of nasopharyngeal swabs) of the same hospital. Then, samples with a good RNA quality (DV200 > 30%) were analyzed through RNA-seq to detect gene expression changes with an untargeted approach between both groups (COVID-19 and control). Finally, sequencing raw data were preprocessed, normalized, and functionally interpreted using bioinformatics procedures for reporting which genes and functions are altered in the endometrium due to the disease.



