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Abstract
Expressional profiling of the endometrium enables the personalised timing of the window of implantation (WOI). This study presents and evaluates a novel analytical pipeline based on a TAC-seq (Targeted Allele Counting by sequencing) method for endometrial dating. The expressional profiles were clustered, and differential expression analysis was performed on the model development group, using 63 endometrial biopsies spanning over proliferative (PE, n = 18), early-secretory (ESE, n = 18), mid-secretory (MSE, n = 17) and late-secretory (LSE, n = 10) endometrial phases of the natural cycle. A quantitative predictor model was trained on the development group and validated on sequenced samples from healthy women, consisting of 52 paired samples taken from ESE and MSE phases and five LSE phase samples from 31 individuals. Finally, the developed test was applied to 44 MSE phase samples from a study group of patients diagnosed with recurrent implantation failure (RIF). In validation samples (n = 57), we detected displaced WOI in 1.8% of the samples from fertile women. In the RIF study group, we detected a significantly higher proportion of the samples with shifted WOI than in the validation set of samples from fertile women, 15.9% and 1.8% (p = 0.012), respectively. The developed model was evaluated with an average cross-validation accuracy of 98.8% and an accuracy of 98.2% in the validation group. The developed beREADY screening model enables sensitive and dynamic detection of selected transcriptome biomarkers, providing a quantitative and accurate prediction of endometrial receptivity status.
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1 Competence Centre On Health Technologies, Tartu, Estonia (GRID:grid.487355.8); Maastricht University, Department of Genetics and Cell Biology, GROW School for Oncology and Developmental Biology, Maastricht, The Netherlands (GRID:grid.5012.6) (ISNI:0000 0001 0481 6099)
2 Competence Centre On Health Technologies, Tartu, Estonia (GRID:grid.487355.8); Institute of Clinical Medicine, University of Tartu, Department of Obstetrics and Gynecology, Tartu, Estonia (GRID:grid.10939.32) (ISNI:0000 0001 0943 7661)
3 Competence Centre On Health Technologies, Tartu, Estonia (GRID:grid.487355.8); University of Tartu, Institute of Biomedicine and Translational Medicine, Tartu, Estonia (GRID:grid.10939.32) (ISNI:0000 0001 0943 7661)
4 Medical Research Center, Oulu University Hospital, University of Oulu, Department of Obstetrics and Gynecology, PEDEGO Research Unit, Oulu, Finland (GRID:grid.10858.34) (ISNI:0000 0001 0941 4873)
5 Oviklinika Infertility Center, Warsaw, Poland (GRID:grid.10858.34); Calisia University, Women’s Health Research Institute, Kalisz, Poland (GRID:grid.467042.3) (ISNI:0000 0001 0054 1382); Medical University of Warsaw, Department of Obstetrics, Gynecology and Gynaecological Oncology, Warsaw, Poland (GRID:grid.13339.3b) (ISNI:0000 0001 1328 7408)
6 Lazarski University, Medical Faculty, Warsaw, Poland (GRID:grid.445556.3) (ISNI:0000 0004 0369 1337)
7 SISMeR, Reproductive Medicine Institute, Bologna, Italy (GRID:grid.445556.3)
8 University of Tartu, Institute of Genomics, Tartu, Estonia (GRID:grid.10939.32) (ISNI:0000 0001 0943 7661)
9 Competence Centre On Health Technologies, Tartu, Estonia (GRID:grid.487355.8); Intervention and Technology (CLINTEC), Karolinska Institutet and Karolinska University Hospital, Division of Obstetrics and Gynecology, Department of Clinical Science, Stockholm, Sweden (GRID:grid.4714.6) (ISNI:0000 0004 1937 0626); Institute of Clinical Medicine, University of Tartu, Department of Obstetrics and Gynecology, Tartu, Estonia (GRID:grid.10939.32) (ISNI:0000 0001 0943 7661)
10 Competence Centre On Health Technologies, Tartu, Estonia (GRID:grid.487355.8); University of Tartu, Institute of Genomics, Tartu, Estonia (GRID:grid.10939.32) (ISNI:0000 0001 0943 7661); University of Helsinki, Institute for Molecular Medicine Finland (FIMM), Helsinki, Finland (GRID:grid.7737.4) (ISNI:0000 0004 0410 2071)