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Targeted gene expression profiling for accurate endometrial receptivity testing
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 clust...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10460380/ https://www.ncbi.nlm.nih.gov/pubmed/37633957 http://dx.doi.org/10.1038/s41598-023-40991-z |
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author | Meltsov, Alvin Saare, Merli Teder, Hindrek Paluoja, Priit Arffman, Riikka K. Piltonen, Terhi Laudanski, Piotr Wielgoś, Mirosław Gianaroli, Luca Koel, Mariann Peters, Maire Salumets, Andres Krjutškov, Kaarel Palta, Priit |
author_facet | Meltsov, Alvin Saare, Merli Teder, Hindrek Paluoja, Priit Arffman, Riikka K. Piltonen, Terhi Laudanski, Piotr Wielgoś, Mirosław Gianaroli, Luca Koel, Mariann Peters, Maire Salumets, Andres Krjutškov, Kaarel Palta, Priit |
author_sort | Meltsov, Alvin |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10460380 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-104603802023-08-28 Targeted gene expression profiling for accurate endometrial receptivity testing Meltsov, Alvin Saare, Merli Teder, Hindrek Paluoja, Priit Arffman, Riikka K. Piltonen, Terhi Laudanski, Piotr Wielgoś, Mirosław Gianaroli, Luca Koel, Mariann Peters, Maire Salumets, Andres Krjutškov, Kaarel Palta, Priit Sci Rep Article 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. Nature Publishing Group UK 2023-08-26 /pmc/articles/PMC10460380/ /pubmed/37633957 http://dx.doi.org/10.1038/s41598-023-40991-z Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access 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 http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Meltsov, Alvin Saare, Merli Teder, Hindrek Paluoja, Priit Arffman, Riikka K. Piltonen, Terhi Laudanski, Piotr Wielgoś, Mirosław Gianaroli, Luca Koel, Mariann Peters, Maire Salumets, Andres Krjutškov, Kaarel Palta, Priit Targeted gene expression profiling for accurate endometrial receptivity testing |
title | Targeted gene expression profiling for accurate endometrial receptivity testing |
title_full | Targeted gene expression profiling for accurate endometrial receptivity testing |
title_fullStr | Targeted gene expression profiling for accurate endometrial receptivity testing |
title_full_unstemmed | Targeted gene expression profiling for accurate endometrial receptivity testing |
title_short | Targeted gene expression profiling for accurate endometrial receptivity testing |
title_sort | targeted gene expression profiling for accurate endometrial receptivity testing |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10460380/ https://www.ncbi.nlm.nih.gov/pubmed/37633957 http://dx.doi.org/10.1038/s41598-023-40991-z |
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