SARS-CoV-2 and Implantation Window: Gene Expression Mapping of Human Endometrium and Preimplantation Embryo.
Delphine HaouziFrida EntezamiEdouard TuaillonAnna GalaAlice Ferrières-HoaSophie BrouilletAlain R ThierrySamir HamamahPublished in: Life (Basel, Switzerland) (2021)
Understanding whether SARS-CoV-2 could infect cells and tissues handled during ART is crucial for risk mitigation, especially during the implantation window when either endometrial biopsies are often practiced for endometrial receptivity assessment or embryo transfer is performed. To address this question, this review analyzed current knowledge of the field and retrospectively examined the gene expression profiles of SARS-CoV-2-associated receptors and proteases in a cohort of ART candidates using our previous Affymetrix microarray data. Human endometrial tissue under natural and controlled ovarian stimulation cycles and preimplantation embryos were analyzed. A focus was particularly drawn on the renin-angiotensin system, which plays a prominent role in the virus infection, and we compared the gene expression levels of receptors and proteases related to SARS-CoV-2 infection in the samples. High prevalence of genes related to the ACE2 pathway during both cycle phases and mainly during the mid-secretory phase for ACE2 were reported. The impact of COS protocols on endometrial gene expression profile of SARS-CoV-2-associated receptors and proteases is minimal, suggesting no additional potential risks during stimulated ART procedure. In blastocysts, ACE2 , BSG , CTSL , CTSA and FURIN were detectable in the entire cohort at high expression level. Specimens from female genital tract should be considered as potential targets for SARS-CoV-2, especially during the implantation window.
Keyphrases
- sars cov
- gene expression
- respiratory syndrome coronavirus
- endothelial cells
- genome wide
- endometrial cancer
- dna methylation
- hiv infected
- angiotensin ii
- angiotensin converting enzyme
- induced apoptosis
- antiretroviral therapy
- human health
- genome wide identification
- poor prognosis
- copy number
- mass spectrometry
- high resolution
- pregnant women
- machine learning
- transcription factor
- big data
- cell cycle arrest
- oxidative stress
- deep learning
- cell proliferation
- coronavirus disease
- endoplasmic reticulum stress
- data analysis
- pi k akt