University of Oulu

Meltsov, A., Saare, M., Teder, H. et al. Targeted gene expression profiling for accurate endometrial receptivity testing. Sci Rep 13, 13959 (2023).

Targeted gene expression profiling for accurate endometrial receptivity testing

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Author: Meltsov, Alvin1,2; Saare, Merli1,3; Teder, Hindrek1,4;
Organizations: 1Competence Centre On Health Technologies, 50411, Tartu, Estonia
2Department of Genetics and Cell Biology, GROW School for Oncology and Developmental Biology, Maastricht University, 6200 MD, Maastricht, The Netherlands
3Department of Obstetrics and Gynecology, Institute of Clinical Medicine, University of Tartu, 50406, Tartu, Estonia
4Institute of Biomedicine and Translational Medicine, University of Tartu, 50411, Tartu, Estonia
5Department of Obstetrics and Gynecology, PEDEGO Research Unit, Medical Research Center, Oulu University Hospital, University of Oulu, FI-90014, Oulu, Finland
6Oviklinika Infertility Center, 01-377, Warsaw, Poland
7Women’s Health Research Institute, Calisia University, 62-800, Kalisz, Poland
8Department of Obstetrics, Gynecology and Gynaecological Oncology, Medical University of Warsaw, 02-091, Warsaw, Poland
9Medical Faculty, Lazarski University, Warsaw, Poland
10SISMeR, Reproductive Medicine Institute, 40138, Bologna, Italy
11Institute of Genomics, University of Tartu, 51010, Tartu, Estonia
12Division of Obstetrics and Gynecology, Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institutet and Karolinska University Hospital, SE-141 52, Stockholm, Sweden
13Institute for Molecular Medicine Finland (FIMM), University of Helsinki, FI-00014, Helsinki, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 1.6 MB)
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Language: English
Published: Springer Nature, 2023
Publish Date: 2023-10-11


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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Series: Scientific reports
ISSN: 2045-2322
ISSN-E: 2045-2322
ISSN-L: 2045-2322
Volume: 13
Issue: 1
Article number: 13959
DOI: 10.1038/s41598-023-40991-z
Type of Publication: A1 Journal article – refereed
Field of Science: 3123 Gynaecology and paediatrics
Funding: This research was funded by the Estonian Research Council (grant PRG1076), Horizon 2020 innovation grant (ERIN, grant no. EU952516), the EU-FP7 Marie Curie Industry-Academia Partnerships and Pathways (IAPP, grant SARM, EU324509), the Enterprise Estonia (grant no. EU48695) and by Polish Ministry of Health (grant no. 6/6/4/1/NPZ/2017/1210/1352).
Copyright information: © The Author(s) 2023. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit