Abstract
Recurrent pregnancy loss (RPL) and implantation failure (RIF) are obstacles to livebirth and multifactorial conditions in which nearly half of the cases remain unexplained, and we aimed to identify maternal candidate gene variants and pathways for RPL and RIF by analyzing whole-exome sequencing (WES) data via a new detailed bioinformatics approach. A retrospective cohort study was applied to 35 women with normal chromosomal configuration diagnosed with unexplained RPL and/or RIF. WES and comprehensive bioinformatics analyses were performed. Published gene expression datasets (n = 46) were investigated for candidate genes. Variant effects on protein structure were analyzed for 12 proteins, and BUB1B was visualized in silico. WES and bioinformatics analyses are effective and applicable for studying URPL and RIF to detect mutations, as we suggest new candidates to explain the etiology. Forty-three variants in 39 genes were detected in 29 women, 7 of them contributing to oligogenic inheritance. These genes were related to implantation, placentation, coagulation, metabolism, immune system, embryological development, cell cycle-associated processes, and ovarian functions. WES, genomic variant analyses, expression data, and protein configuration studies offer new and promising ways to investigate the etiology of URPL and RIF. Discovering etiology-identifying genetic factors can help manage couples’ needs and develop personalized therapies and new pharmaceutical products in the future. The classical approach with chromosomal analysis and targeted gene panel testing is insufficient in these cases; the exome data provide a promising way to detect and understand the possible clinical effects of the variant and its alteration on protein structure.
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The data underlying this article will be shared on reasonable request to the corresponding author. The analyzed GEO datasets underlying this article and its online supplementary material are available in the paper.
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This work was supported by the Scientific Research Projects Coordination Unit of Istanbul University (Grant numbers TDK-2018-31561 and TSA-2018-32135).
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EGB: literature search, genomic study design, providing clinical data and blood samples, laboratory experiments, bioinformatics analyses, drafting the manuscript, preparing tables and figures, critique, and critical discussion of the manuscript. CVŞ: bioinformatics study design, bioinformatics analyses, protein structure studies, drafting the manuscript, preparing tables and figures, critique, and critical discussion of the manuscript. TK: providing clinical data and blood samples. ZOU: supervising laboratory experiments and variant analyses, critique, and critical manuscript discussion. G.BA: supervising protein structure studies and analyses, critique, and critical discussion of the manuscript, tables, and figures. SB: genomics study design, supervising the study, critique, and critical manuscript discussion.
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Berkay, E.G., Şoroğlu, C.V., Kalaycı, T. et al. A new enrichment approach for candidate gene detection in unexplained recurrent pregnancy loss and implantation failure. Mol Genet Genomics 298, 253–272 (2023). https://doi.org/10.1007/s00438-022-01972-5
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DOI: https://doi.org/10.1007/s00438-022-01972-5