Abstract
Is endometrial recurrent implantation failure (RIF) only a matter of an asynchronous (displaced) window of implantation (WOI), or could it also be a pathological (disrupted) WOI? Our predictive results demonstrate that both displaced and disrupted WOIs exist and can present independently or together in the same RIF patient. Since 2002, many gene expression signatures associated with endometrial receptivity and RIF have been described. Endometrial transcriptomics prediction has been applied to the human WOI in two previous studies. One study describes endometrial RIF to be the result of a temporal displacement of the WOI. The other indicates that endometrial RIF can also result from a molecularly disrupted WOI without temporal displacement. Retrospective analysis was undertaken to compare WOI endometrial transcriptomics predictions in controls (n = 72) and RIF patients (n = 43). RIF was clinically designated by the absence of implantation after four or more transfers of high quality embryos or after the placement of 10 or more embryos in multiple transfers. Endometrial tissue samples were collected from LH + 5 to LH + 8. We compared the two molecular causes of RIF to signatures currently described in the literature. We propose a new transcriptomic RIF taxonomy to fill the gap between the two hypotheses and to guide the development of clinical detection and determination of both types of RIF. Utilizing 115 gene expression profiles, two different predictive designs were developed: one considering RIF versus controls removing menstrual cycle timing, called the disrupted or pathological model, and another stratifying the WOI in transcriptomic profiles related to timing for predicting displacements. The predictive value of each model was compared between all signatures selected. We propose a new genomic approach that distinguishes between both types of RIF in the same sample cohort. From the 16 signatures analysed, we clearly predicted two causes of RIF-both a displaced WOI and an on-time but pathologically disrupted WOI. A high predictive value related to WOI profiles associated with menstrual cycle timing was found in most of the signatures. Specifically, 69% of the signatures analysed presented an accuracy higher than expected by chance in a range from 0.87 to 0.97. Displacements and disruptions were not molecularly independent, as some signatures were moderately associated with both causes. The gene and functional comparison between signatures revealed that they were not similar, although we did find functions in common and a cluster of moderate functional concordance between some of the signatures that predicted displacements (the highest Cohen's Kappa index were between 0.55 and 0.62 depending on the functional database). We propose a new transcriptomic RIF taxonomy to fill the gap between these prior studies and to establish methodology for detecting and distinguishing both types of RIF in clinical practice. Our findings indicate these two phenotypes could present independently or together in the same RIF patient. RIF patients designated by clinical criteria have been stratified transcriptomically as 18.6% with only a displaced WOI, 53.5% with a displaced and pathological WOI, 23.3% with only a disrupted WOI, and 4.7% could be a clinical RIF with non-endometrial origin. The new RIF transcriptomic taxonomy avoids menstrual cycle timing as a confounding variable that should be controlled for, distinguishing clearly between a disrupted and a displaced WOI for precision medicine in RIF. The main objective of this study was to use transcriptomics to detect both RIF causes and to understand the role of transcriptomic signatures in these phenotypes. The predictive value in absolute terms for each signature was not indicative in these prediction designs; instead, the comparison between signatures was most important for prediction capability in the same sample cohort for both RIF causes. Clinical follow up of the RIF taxonomies proposed has not been analysed in this study, so further prospective clinical studies are necessary to determine the prevalence and penetrance of these phenotypes. The main insight from this study is a new understanding of RIF taxonomy. Understanding how to classify RIF patients to distinguish clinically between a patient who could benefit from a personalized embryo transfer day and a patient with a disrupted WOI will enable identification and stratification for the research and development of new treatments. In addition, we demonstrate that basic research designs in endometrial transcriptomics cause masking of the study variable by the menstrual cycle timing. This research has been funded by IVI-RMA; the authors do not have any competing interests.
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