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Refeat MM, Shalabi T, El-Bassyouni HT, Shaker M. The correlation of estrogen receptor 1 and progesterone receptor genes polymorphisms with recurrent pregnancy loss in a cohort of Egyptian women. Mol Biol Rep 2021; 48:4413-4420. [PMID: 34061327 DOI: 10.1007/s11033-021-06459-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 05/27/2021] [Indexed: 11/24/2022]
Abstract
Recurrent pregnancy loss (RPL) represents one of the pregnancy complications affecting 1-3% of women. Sex hormones, progesterone and estrogen play a critical role in the maintenance of pregnancy; they are mediated by estrogen receptor 1 (ESR1) and progesterone receptor (PR) genes respectively. Polymorphisms of (ESR1) and (PR) genes are linked to RPL. We aimed to explore the association of single nucleotide polymorphisms (SNPs) of (ESR1) gene and (PR) gene with RPL in a cohort of Egyptian population (50 infertile Egyptian women who experienced RPL and 50 healthy women), using polymerase chain reaction-restriction fragment length polymorphism analysis (PCR-RFLP) of (ESR1) gene and DNA sequencing of exons 1 and 5 of (PR) gene. Genotyping of ESR1 gene SNP's: (rs2234693) and (rs9340799) revealed higher significance in cases compared to controls of p value (p = 0.006 and p = 0.001) respectively. However, the frequencies of the two variants in (PG) gene; S344T (rs3740753) (p = 0.0001) and H770H (rs1042839) (p = 0.001) were significantly higher in women compared to the healthy control women. New polymorphism P352Q was observed in 2% of cases (p = 0.0001). There was a significant association of SNP's of ESR1 and PR genes with recurrent pregnancy loss RPL. Further demographics studies should be carried on a larger number of women at risk of recurrent implantation to elucidate this SNP's association and its role in RPL women.
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Affiliation(s)
- Miral M Refeat
- Human Genetics and Genome Research Division, Medical Molecular Genetics Department, National Research Centre, Cairo, Egypt.
| | - Taghreed Shalabi
- Human Genetics and Genome Research Division, Prenatal and Fetal Medicine Department, National Research Centre, Cairo, Egypt
| | - Hala T El-Bassyouni
- Human Genetics and Genome Research Division, Clinical Genetics Department, National Research Centre, Cairo, Egypt
| | - Mai Shaker
- Human Genetics and Genome Research Division, Prenatal and Fetal Medicine Department, National Research Centre, Cairo, Egypt
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Loizidou EM, Kucherenko A, Tatarskyy P, Chernushyn S, Livshyts G, Gulkovskyi R, Vorobiova I, Antipkin Y, Gorodna O, Kaakinen MA, Prokopenko I, Livshits L. Risk of Recurrent Pregnancy Loss in the Ukrainian Population Using a Combined Effect of Genetic Variants: A Case-Control Study. Genes (Basel) 2021; 12:64. [PMID: 33466305 PMCID: PMC7824779 DOI: 10.3390/genes12010064] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 12/22/2020] [Accepted: 12/23/2020] [Indexed: 01/26/2023] Open
Abstract
We assessed the predictive ability of a combined genetic variant panel for the risk of recurrent pregnancy loss (RPL) through a case-control study. Our study sample was from Ukraine and included 114 cases with idiopathic RPL and 106 controls without any pregnancy losses/complications and with at least one healthy child. We genotyped variants within 12 genetic loci reflecting the main biological pathways involved in pregnancy maintenance: blood coagulation (F2, F5, F7, GP1A), hormonal regulation (ESR1, ADRB2), endometrium and placental function (ENOS, ACE), folate metabolism (MTHFR) and inflammatory response (IL6, IL8, IL10). We showed that a genetic risk score (GRS) calculated from the 12 variants was associated with an increased risk of RPL (odds ratio 1.56, 95% CI: 1.21, 2.04, p = 8.7 × 10-4). The receiver operator characteristic (ROC) analysis resulted in an area under the curve (AUC) of 0.64 (95% CI: 0.57, 0.72), indicating an improved ability of the GRS to classify women with and without RPL. Ιmplementation of the GRS approach can help define women at higher risk of complex multifactorial conditions such as RPL. Future well-powered genome-wide association studies will help in dissecting biological pathways previously unknown for RPL and further improve the identification of women with RPL susceptibility.
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Affiliation(s)
- Eleni M. Loizidou
- Section of Genetics and Genomics, Department of Metabolism, Digestion and Reproduction, Imperial College London, London W12 0NN, UK; (E.M.L.); (M.A.K.)
| | - Anastasia Kucherenko
- Institute of Molecular Biology and Genetics NAS, 03143 Kiev, Ukraine; (A.K.); (P.T.); (S.C.); (G.L.); (R.G.); (O.G.)
| | - Pavlo Tatarskyy
- Institute of Molecular Biology and Genetics NAS, 03143 Kiev, Ukraine; (A.K.); (P.T.); (S.C.); (G.L.); (R.G.); (O.G.)
| | - Sergey Chernushyn
- Institute of Molecular Biology and Genetics NAS, 03143 Kiev, Ukraine; (A.K.); (P.T.); (S.C.); (G.L.); (R.G.); (O.G.)
| | - Ganna Livshyts
- Institute of Molecular Biology and Genetics NAS, 03143 Kiev, Ukraine; (A.K.); (P.T.); (S.C.); (G.L.); (R.G.); (O.G.)
| | - Roman Gulkovskyi
- Institute of Molecular Biology and Genetics NAS, 03143 Kiev, Ukraine; (A.K.); (P.T.); (S.C.); (G.L.); (R.G.); (O.G.)
| | - Iryna Vorobiova
- Institute of Paediatrics, Obstetrics and Gynaecology of the National Academy of Medical Sciences, 04050 Kiev, Ukraine; (I.V.); (Y.A.)
| | - Yurii Antipkin
- Institute of Paediatrics, Obstetrics and Gynaecology of the National Academy of Medical Sciences, 04050 Kiev, Ukraine; (I.V.); (Y.A.)
| | - Oleksandra Gorodna
- Institute of Molecular Biology and Genetics NAS, 03143 Kiev, Ukraine; (A.K.); (P.T.); (S.C.); (G.L.); (R.G.); (O.G.)
| | - Marika A. Kaakinen
- Section of Genetics and Genomics, Department of Metabolism, Digestion and Reproduction, Imperial College London, London W12 0NN, UK; (E.M.L.); (M.A.K.)
- Section of Statistical Multi-Omics, Department of Clinical & Experimental Medicine, School of Biosciences & Medicine, University of Surrey, Guildford GU2 7XH, UK
| | - Inga Prokopenko
- Section of Genetics and Genomics, Department of Metabolism, Digestion and Reproduction, Imperial College London, London W12 0NN, UK; (E.M.L.); (M.A.K.)
- Section of Statistical Multi-Omics, Department of Clinical & Experimental Medicine, School of Biosciences & Medicine, University of Surrey, Guildford GU2 7XH, UK
- Institute of Biochemistry and Genetics, Ufa Federal Research Centre Russian Academy of Sciences, 119192 Ufa, Russia
| | - Ludmila Livshits
- Institute of Molecular Biology and Genetics NAS, 03143 Kiev, Ukraine; (A.K.); (P.T.); (S.C.); (G.L.); (R.G.); (O.G.)
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Bosio M, Salembier P, Bellot P, Oliveras-Vergès A. Hierarchical clustering combining numerical and biological similarities for gene expression data classification. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2013; 2013:584-7. [PMID: 24109754 DOI: 10.1109/embc.2013.6609567] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
High throughput data analysis is a challenging problem due to the vast amount of available data. A major concern is to develop algorithms that provide accurate numerical predictions and biologically relevant results. A wide variety of tools exist in the literature using biological knowledge to evaluate analysis results. Only recently, some works have included biological knowledge inside the analysis process improving the prediction results.
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