Evidence for association of the rs605059 polymorphism of HSD17B1 gene with recurrent spontaneous abortions

Trophectoderm non-coding RNAs reflect the higher metabolic and more invasive properties of young maternal age blastocysts

Increasing female age is accompanied by a corresponding fall in her fertility. This decline is influenced by a variety of factors over an individual's life course including background genetics, local environment and diet. Studying both coding and non-coding RNAs of the embryo could aid our understanding of the causes and/or effects of the physiological processes accompanying the decline including the differential expression of sub-cellular biomarkers indicative of various diseases. The current study is a post-hoc analysis of the expression of trophectoderm RNA data derived from a previous high throughput study. Its main aim is to determine the characteristics and potential functionalities that characterize long non-coding RNAs. As reported previously, a maternal age-related component is potentially implicated in implantation success. Trophectoderm samples representing the full range of maternal reproductive ages were considered in relation to embryonic implantation potential, trophectoderm transcriptome dynamics and reproductive maternal age. The long non-coding RNA (lncRNA) biomarkers identified here are consistent with the activities of embryo-endometrial crosstalk, developmental competency and implantation and share common characteristics with markers of neoplasia/cancer invasion. Corresponding genes for expressed lncRNAs were more active in the blastocysts of younger women are associated with metabolic pathways including cholesterol biosynthesis and steroidogenesis.

SCRIBER: accurate and partner type-specific prediction of protein-binding residues from proteins sequences

Motivation

Accurate predictions of protein-binding residues (PBRs) enhances understanding of molecular-level rules governing protein–protein interactions, helps protein–protein docking and facilitates annotation of protein functions. Recent studies show that current sequence-based predictors of PBRs severely cross-predict residues that interact with other types of protein partners (e.g. RNA and DNA) as PBRs. Moreover, these methods are relatively slow, prohibiting genome-scale use.

Results

We propose a novel, accurate and fast sequence-based predictor of PBRs that minimizes the cross-predictions. Our SCRIBER (SeleCtive pRoteIn-Binding rEsidue pRedictor) method takes advantage of three innovations: comprehensive dataset that covers multiple types of binding residues, novel types of inputs that are relevant to the prediction of PBRs, and an architecture that is tailored to reduce the cross-predictions. The dataset includes complete protein chains and offers improved coverage of binding annotations that are transferred from multiple protein–protein complexes. We utilize innovative two-layer architecture where the first layer generates a prediction of protein-binding, RNA-binding, DNA-binding and small ligand-binding residues. The second layer re-predicts PBRs by reducing overlap between PBRs and the other types of binding residues produced in the first layer. Empirical tests on an independent test dataset reveal that SCRIBER significantly outperforms current predictors and that all three innovations contribute to its high predictive performance. SCRIBER reduces cross-predictions by between 41% and 69% and our conservative estimates show that it is at least 3 times faster. We provide putative PBRs produced by SCRIBER for the entire human proteome and use these results to hypothesize that about 14% of currently known human protein domains bind proteins.

Availability and implementation

SCRIBER webserver is available at http://biomine.cs.vcu.edu/servers/SCRIBER/.

Supplementary information

Supplementary data are available at Bioinformatics online.

Can trophectoderm RNA analysis predict human blastocyst competency?

A systematic review of the literature showed that trophectoderm biopsy could assist in the selection of healthy embryos for uterine transfer without affecting implantation rates. However, previous studies attempting to establish the relationship between trophectoderm gene expression profiles and implantation competency using either microarrays or RNA sequencing strategies, were not sufficiently optimized to handle the exceptionally low RNA inputs available from biopsied material. In this pilot study, we report that differential gene expression in human trophectoderm biopsies assayed by an ultra-sensitive next generation RNA sequencing strategy could predict blastocyst implantation competence. RNA expression profiles from isolated human trophectoderm cells were analysed with established clinical pregnancy being the primary endpoint. Following RNA sequencing, a total of 47 transcripts were found to be significantly differentially expressed between the trophectoderm cells from successfully implanted (competent) versus unsuccessful (incompetent) blastocysts. Of these, 36 transcripts were significantly down-regulated in the incompetent blastocysts, including Hydroxysteroid 17-Beta Dehydrogenase 1 (HSD17B1) and Cytochrome P450 Family 11 Subfamily A Member 1 (CYP11A1), while the remaining 11 transcripts were significantly up-regulated, including BCL2 Antagonist/Killer 1 (BAK1) and KH Domain Containing 1 Pseudogene 1 (KHDC1P1) of which the latter was always detected in the incompetent and absent in all competent blastocysts. Ontological analysis of differentially expressed RNAs revealed pathways involved in steroidogenic processes with high confidence. Novel differentially expressed transcripts were also noted by reference to a de novo sequence assembly. The selection of the blastocyst with the best potential to support full-term pregnancy following single embryo transfer could reduce the need for multiple treatment cycles and embryo transfers. The main limitation was the low sample size (N = 8). Despite this shortcoming, the pilot suggests that trophectoderm biopsy could assist with the selection of healthy embryos for embryo transfer. A larger cohort of samples is needed to confirm these findings.

Abbreviations: AMA: advanced maternal age; ART: assisted reproductive technology; CP: clinical pregnancy; DE: differential expression; FDR: false discovery rate; IVF: in vitro fertilization; LD PCR: long distance PCR; qRT-PCR: quantitative real-time PCR; SET: single embryo transfer; TE: trophectoderm

Role of hydroxysteroid (17beta) dehydrogenase type 1 in reproductive tissues and hormone-dependent diseases

Abnormal synthesis and metabolism of sex steroids is involved in the pathogenesis of various human diseases, such as endometriosis and cancers arising from the breast and uterus. Steroid biosynthesis is a multistep enzymatic process proceeding from cholesterol to highly active sex steroids via different intermediates. Human Hydroxysteroid (17beta) dehydrogenase 1 (HSD17B1) enzyme shows a high capacity to produce the highly active estrogen, estradiol, from a precursor hormone, estrone. However, the enzyme may also play a role in other steps of the steroid biosynthesis pathway. In this article, we have reviewed the literature on HSD17B1, and summarize the role of the enzyme in hormone-dependent diseases in women as evidenced by preclinical studies.

Estrogen-related receptor γ regulates expression of 17β-hydroxysteroid dehydrogenase type 1 in fetal growth restriction

INTRODUCTION

Estrogen-related receptor γ (ERRγ) and 17β-hydroxysteroid dehydrogenase type 1 (HSD17B1) have important roles in cell invasion and in the proliferation of many types of cancer cells. However, it remains unknown whether ERRγ and HSD17B1 contribute to abnormal placental structure and dysfunction which characterize fetal growth restriction (FGR). Therefore, the aim of this study was to investigate the expression profiles of ERRγ and HSD17B1 in placenta tissues affected by FGR and to examine a possible molecular mechanism by which ERRγ is able to regulate HSD17B1 during development of FGR.

METHODS

Placenta tissues were collected from women affected by FGR (n = 28) and from women with appropriately gestational age (AGA) (n = 30). Relative mRNA and protein levels of ERRγ and HSD17B1 in both groups were assessed by quantitative real-time PCR, immunohistochemistry, and Western blot analyses. The effect of ERRγ on trophoblast function and its associated mechanistic details were studied in the trophoblast cell line, HTR-8/SVneo, which was transfected with small interfering RNA (siRNA) targeting ERRγ.

RESULTS

Both mRNA and protein levels of ERRγ and HSD17B1 were significantly lower in FGR placentae (P < 0.05). When ERRγ expression was knocked down in HTR-8/SVneo cells with siRNA, invasion and proliferation were inhibited. In addition, HSD17B1 expression was significantly decreased. In dual luciferase reporter assays, ERRγ stimulated transcription of HSD17B1 by targeting the ERRγ response element within its 5'-flanking promoter region.

DISCUSSION

Aberrant ERRγ expression may contribute to the pathogenesis of FGR by regulating the transcriptional activity of HSD17B1.

Involvement of 17β-hydroxysteroid dehydrogenase type gene 1 937 A>G polymorphism in infertility in Polish Caucasian women with endometriosis

Purpose

Endometriosis is considered to be an estrogen-related chronic inflammatory disease. The 17β-hydroxysteroid dehydrogenase 1 (HSD17B1) converts estrone to 17β estradiol. The role of HSD17B1 937 A>G (rs605059) single nucleotide polymorphism (SNP) in development of endometriosis is still disputable. This study evaluated the association of the HSD17B1 937 A>G (rs605059) SNP with infertile women affected by endometriosis from Polish Caucasian population.

Methods

The genotyping of cases (n = 290) and fertile women (n = 410) was conducted by high-resolution melting curve analysis.

Results

Statistical analysis demonstrated that the HSD17B1 937 A>G SNP is associated with endometriosis in stages I and II. The p_trend and p_allelic values calculated for the HSD17B1 937 A>G polymorphism were statistically significant and were equal to 0.001 and 0.0009, respectively. There was a significant association for the dominant model: (AG + GG vs AA) OR = 1.973 (95% CI = 1.178–3.304), p = 0.009, and for the recessive model: (GG vs AG + AA) OR = 1.806 (95% CI = 1.178–2.770), p = 0.006. However, we did not find statistical association of HSD17B1 937 A>G polymorphism with all infertile women with endometriosis or infertile women with endometriosis in stages III and IV.

Conclusion

Our genetic study demonstrated HSD17B1 937 G variant as a risk factor for infertility in women with stage I and II endometriosis in Polish Caucasian patients.

Electronic supplementary material

The online version of this article (doi:10.1007/s10815-017-0911-9) contains supplementary material, which is available to authorized users.