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EndoTime: Non-categorical timing estimates for luteal endometrium

By Julia Lipecki, Andrew Mitchell, Joanne Muter, Emma Lucas, Komal Makwana, Katherine Fishwick, Joshua Odendaal, Amelia Hawkes, Pavle Vrljicak, Jan J Brosens, Sascha Ott

Posted 05 Aug 2021
medRxiv DOI: 10.1101/2021.08.02.21261452

STUDY QUESTION Can the accuracy of timing of luteal phase endometrial biopsies based on urinary ovulation testing be improved by measuring the expression of a small number of genes and a continuous, non-categorical modelling approach? SUMMARY ANSWER Measuring the expression levels of six genes (IL2RB, IGFBP1, CXCL14, DPP4, GPX3, and SLC15A2) is sufficient to obtain substantially more accurate timing estimates and assess the reliability of timing estimates for each sample. WHAT IS KNOWN ALREADY Commercially available endometrial timing approaches based on gene expression require much larger gene sets and use a categorical approach that classifies samples as pre-receptive, receptive, or post-receptive. STUDY DESIGN, SIZE, DURATION Gene expression was measured by RT-qPCR in 260 endometrial biopsies obtained 4 to 12 days after a self-reported positive home ovulation test. A further 36 endometrial samples were profiled by RT-qPCR as well as RNA-sequencing. PARTICIPANTS/MATERIALS, SETTING, METHODS A computational procedure, named 'EndoTime', was established that models the temporal profile of each gene and estimates the timing of each sample. Iterating these steps, temporal profiles are gradually refined as sample timings are being updated, and confidence in timing estimates is increased. After convergence, the method reports updated timing estimates for each sample while preserving the overall distribution of time points. MAIN RESULTS AND THE ROLE OF CHANCE The Wilcoxon Rank Sum Test was used to confirm that ordering samples by EndoTime estimates yields sharper temporal expression profiles for held-out genes (not used when determining sample timings) than ordering the same expression values by patient-reported times (GPX3: p < 0.005; CXCL14: p < 2.7e-6; DPP4: p < 3.7e-13). Pearson correlation between EndoTime estimates for the same sample set but based on RT-qPCR or RNA-sequencing data showed high degree of congruency between the two (p = 8.6e-10, R2 = 0.687). LIMITATIONS, REASONS FOR CAUTION Timing estimates are predominantly informed by glandular gene expression and will only represent the temporal state of other endometrial cell types if in synchrony with the epithelium. Methods that estimate the day of ovulation are still required as these data are essential inputs in our method. Our approach - in its current iteration - performs batch correction such that larger sample batches impart greater accuracy to timing estimations. In theory, our method requires endometrial samples obtained at different days in the luteal phase. In practice, however, this is not a concern as timings based on urinary ovulation testing are associated with a sufficient level of noise to ensure that a variety of time points will be sampled. WIDER IMPLICATIONS OF THE FINDINGS Our method is the first to assay the temporal state of luteal-phase endometrial samples on a continuous domain. It is freely available with fully shared data and open source software. EndoTime enables accurate temporal profiling of any gene in luteal endometrial samples for a wide range of research applications and, potentially, clinical use.

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