The Embryo-endometrium Multifaceted Interface: Endometrial Cavity Molecular Microbiobial and Transcriptomic Signatures in Predictinf Pregnancy Outcome in Infertile Patients Undergoing Assisted Reproduction Technology Procedures

Condition(s) studied

Study summary

In reproductive medicine, a fundamental challenge is to evaluate the endometrial health status during the embryo implantation window as a limiting step in predicting the success of treatments of assisted reproduction technology (ART). Some highthroughput tools, recently developed by private genomics companies, are available in the market even if they have not been independently validated and have different limitations. We propose a prospective cohort study with the aim of validating the reliability and increasing efficacy of these tools. Endometrial fluid samples will be collected non-invasively from women undergoing ART cycles and isolated genetic materials will be subjected to 16S rRNA gene sequencing for microbiota profiling and to RNAseq analysis of RNA content of extracellular vesicles previously recognized as a tissue proxy in predicting endometrial receptivity. Clinical pregnancy rate/first cycle will be the target outcome used to assess the resulting predictive models. Ultrasonographic features of the endometrium will also be collected and accounted for in the predictive model.

Eligibility

Primary outcome measure(s)

• Identification of endometrial microbiome diversity — through study completion, an average of 1 year
  Evaluation of the endometrial microbiome composition and diversity using 16S rRNA sequencing to assess the functional impact of the endometrial microbial community in predicting the clinical pregnancy rate in women undergoing ART cycles.
• Extracellular Vesicle (EV) RNA Profiles — through study completion, an average of 1 year
  Quantification of extracellular vesicle (EV) RNA expression profiles from uterine fluid samples using RNA sequencing (expressed in CPM). Confirmation of the good correlation between expression of genes in tissue samples and in endometrial-derived EVs.
• Integrated Predictive Model for Clinical Pregnancy — through study completion, an average of 1 year
  Development of a multivariable predictive model combining endometrial microbiome diversity, EV RNA profiles, and ultrasound-AI analysis to predict clinical pregnancy rates in ART cycles.

Trial sites (1)

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