Targeted gene expression profiling for accurate endometrial receptivity testing

Alvin Meltsov, Merli Saare*, Hindrek Teder, Priit Paluoja, Riikka K. Arffman, Terhi Piltonen, Piotr Laudanski, Miroslaw Wielgos, Luca Gianaroli, Mariann Koel, Maire Peters, Andres Salumets, Kaarel Krjutškov, Priit Palta

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


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.
Original languageEnglish
Article number13959
Number of pages12
JournalScientific Reports
Issue number1
Publication statusPublished - 26 Aug 2023


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