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Transcriptome profiling of human oocytes experiencing recurrent total fertilization failure.

ABSTRACT: There exist some patients who face recurrent total fertilization failure during assisted reproduction treatment, but the pathological mechanism underlying is elusive. Here, by using sc-RNA-seq method, the transcriptome profiles of ten abnormally fertilized zygotes were assessed, including five zygotes from one patient with recurrent Poly-PN zygotes, and five zygotes from a patient with pronuclear fusion failure. Four zygotes with three pronuclear (Tri-PN) were collected from four different patients as controls. After that, we identified 951 and 1697 significantly differentially expressed genes (SDEGs) in Poly-PN and PN arrest zygotes, respectively as compared with the control group. KEGG analyses indicated down regulated genes in the Poly-PN group included oocyte meiosis related genes, such as PPP2R1B, YWHAZ, MAD2L1, SPDYC, SKP1 and CDC27, together with genes associated with RNA processing, such as SF3B1, LOC645691, MAGOHB, PHF5A, PRPF18, DDX5, THOC1 and BAT1. In contrast, down regulated genes in the PN arrest group, included cell cycle genes, such as E2F4, DBF4, YWHAB, SKP2, CDC23, SMC3, CDC25A, CCND3, BUB1B, MDM2, CCNA2 and CDC7, together with homologous recombination related genes, such as NBN, XRCC3, SHFM1, RAD54B and RAD51. Thus, our work provides a better understanding of transcriptome profiles underlying RTFF, although it based on a limited number of patients.

SUBMITTER: Suo L

PROVIDER: S-EPMC6297154 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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Transcriptome profiling of human oocytes experiencing recurrent total fertilization failure.

Suo Lun L Zhou Yu Xiao YX Jia Li Ling LL Wu Hai Bo HB Zheng Jin J Lyu Qi Feng QF Sun Li Hua LH Sun Han H Kuang Yan Ping YP

Scientific reports 20181217 1

There exist some patients who face recurrent total fertilization failure during assisted reproduction treatment, but the pathological mechanism underlying is elusive. Here, by using sc-RNA-seq method, the transcriptome profiles of ten abnormally fertilized zygotes were assessed, including five zygotes from one patient with recurrent Poly-PN zygotes, and five zygotes from a patient with pronuclear fusion failure. Four zygotes with three pronuclear (Tri-PN) were collected from four different patie ...[more]

PMID: 30559372

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Project description:BackgroundThe molecular mechanisms underlying window of implantation (WOI) displacement in patients with recurrent implantation failure (RIF) remain unclear. This study aims to explore the transcriptomic signatures of endometrium with normal and displaced WOIs and to identify the causes of endometrial receptivity (ER) abnormalities and WOI displacement in RIF patients.MethodsIn this study, 40 RIF patients were recruited and underwent personalized embryo transfer (pET) guided by the predicted results of endometrial receptivity diagnosis (ERD) model. Transcriptome analysis of endometrium from patients with clinical pregnancies after pET was performed to identify differentially expressed genes (DEGs) associated with WOI displacement. Gene expression data from HRT and natural cycle endometrium were compared to identify specific gene expression patterns of ER-related genes during WOI.ResultsThe ERD results indicated that 67.5% of RIF patients (27/40) were non-receptive in the conventional WOI (P+5) of the HRT cycle. The clinical pregnancy rate in RIF patients improved to 65% (26/40) after ERD-guided pET, indicating the effectiveness of transcriptome-based WOI prediction. Among the 26 patients with clinical pregnancy, the gene expression profiles of P+5 endometrium from advanced (n=6), normal (n=10) and delayed (n=10) WOI groups were significantly different from each other. Furthermore, 10 DEGs identified among P+5 endometrium of 3 groups were involved in immunomodulation, transmembrane transport and tissue regeneration, which could accurately classify the endometrium with different WOIs. Additionally, a large number of ER-related genes showed significant correlation and similar gene expression patterns in P+3, P+5, and P+7 endometrium from HRT cycles and LH+5, LH+7, and LH+9 endometrium from natural cycles.ConclusionOur study shows that ER-related genes share similar gene expression patterns during WOI in both natural and HRT cycles, and their aberrant expression is associated with WOI displacements. The improvement of pregnancy outcomes in RIF patients by adjusting ET timing according to ERD results demonstrates the importance of transcriptome-based endometrial receptivity assessment and the clinical efficiency of ERD model.

Project description:BACKGROUND:Despite advances in pharmacologic therapy and devices, patients with heart failure (HF) continue to have significant rehospitalization rates and risk prediction remains challenging. We sought to explore the value of a multi-biomarker panel [including NT-proBNP, high-sensitivity cardiac troponin T (hs-TnT), and ST2] on top of clinical assessment for long-term prediction of recurrent hospitalizations in HF. METHODS AND RESULTS:NT-proBNP, hs-TnT, and ST2 (suppression of tumorigenicity-2) levels were measured in 891 consecutive ambulatory HF patients. The independent association between the multi-biomarker panel and recurrent hospitalizations was assessed through a multivariable negative binomial regression and expressed as incidence rates ratios. McFadden pseudo-R2 and goodness-of-fit measures were also used. The total number of unplanned hospitalizations [all-cause, cardiovascular (CV)-, and HF-related] were selected as the primary endpoints. At a mean follow-up of 4.2?±?2.1?years, 1623 all-cause hospitalizations in 498 patients (55.9%), 710 CV-related hospitalizations in 331 patients (37.2%), and 444 HF-related hospitalizations in 214 patients (24.1%) were registered. The crude incidence of all-cause, CV-, and HF-related recurrent hospitalizations was significantly higher for patients with the multi-biomarker panel above the cut-point (hs-TnT?>?14?ng/L, NT-proBNP?>?1000?ng/L, and ST2?>?35?ng/mL) (all P?<?0.001). For all-cause, CV-, and HF-related recurrent hospitalizations, the McFadden R2, Akaike information criterion, and Bayesian information criterion supported the superiority of incorporating the multi-biomarker panel into a clinical predictive model. CONCLUSION:A multi-biomarker approach based on NT-proBNP, hs-TnT, and ST2 better identifies HF patients at risk for recurrent hospitalizations as compared to approaches entailing just one or two of these biomarkers. Elucidation of new biophysiological predictors for recurrent hospitalizations may identify patient profiles for focused intervention.

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Transcriptome profiling of human oocytes experiencing recurrent total fertilization failure.

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Transcriptome profiling of human oocytes experiencing recurrent total fertilization failure.

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