The dynamic nature of human endometrial tissue presents unique challenges in analysis. Despite extensive research into endometrial disorders such as endometriosis and infertility, recent systematic reviews have highlighted concerning issues with the reproducibility of omics studies attempting to identify biomarkers. This review examines factors contributing to poor reproducibility in endometrial omics research. Hormonal fluctuations in the menstrual cycle lead to widespread molecular changes in the endometrium, most notably in gene expression profiles. In this review, we examine the variability in omics data due to the menstrual cycle and highlight the importance of accurate menstrual cycle dating for effective statistical modelling. The current standards of endometrial dating lack precision and we make the case for using molecular-based modelling methods to estimate menstrual cycle time for endometrium tissue samples. Additionally, we discuss statistical considerations such as confounding and interaction effects, as well as the importance of recording the detailed and accurate clinical information of patients. By addressing these methodological challenges, we aim to establish more robust and reproducible research practises, increasing the reliability of endometrial omics research and biomarker discovery.
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