Alterations in endometrial DNA methylation profile have been proposed as one potential mechanism initiating the development of endometriosis. However, the normal endometrial methylome is influenced by the cyclic hormonal changes, and the menstrual cycle phase-dependent epigenetic signature should be considered when studying endometrial disorders. So far, no studies have been performed to evaluate the menstrual cycle influences and endometriosis-specific endometrial methylation pattern at the same time. Infinium HumanMethylation 450K BeadChip arrays were used to explore DNA methylation profiles of endometrial tissues from various menstrual cycle phases from 31 patients with endometriosis and 24 healthy women. The DNA methylation profile of patients and controls was highly similar and only 28 differentially methylated regions (DMRs) between patients and controls were found. However, the overall magnitude of the methylation differences between patients and controls was rather small (Δβ ranging from –0.01 to –0.16 and from 0.01 to 0.08, respectively, for hypo- and hypermethylated CpGs). Unsupervised hierarchical clustering of the methylation data divided endometrial samples based on the menstrual cycle phase rather than diseased/non-diseased status. Further analysis revealed a number of menstrual cycle phase-specific epigenetic changes with largest changes occurring during the late-secretory and menstrual phases when substantial rearrangements of endometrial tissue take place. Comparison of cycle phase- and endometriosis-specific methylation profile changes revealed that 13 out of 28 endometriosis-specific DMRs were present in both datasets. The results of our study accentuate the importance of considering normal cyclic epigenetic changes in studies investigating endometrium-related disease-specific methylation patterns.

The endometrium undergoes extensive changes to prepare for embryo implantation and microRNAs (miRNAs) have been described as playing a significant role in the regulation of endometrial receptivity. However, there is no consensus about the miRNAs involved in mid-secretory endometrial functions. We analysed the complete endometrial miRNome from early secretory (pre-receptive) and mid-secretory (receptive) phases from fertile women and from patients with recurrent implantation failure (RIF) to reveal differentially expressed (DE) miRNAs in the mid-secretory endometrium. Furthermore, we investigated whether the overall changes during early to mid-secretory phase transition and with RIF condition could be reflected in blood miRNA profiles. In total, 116 endometrial and 114 matched blood samples collected from two different population cohorts were subjected to small RNA sequencing. Among fertile women, 91 DE miRNAs were identified in the mid-secretory vs. early secretory endometrium, while no differences were found in the corresponding blood samples. The comparison of mid-secretory phase samples between fertile and infertile women revealed 21 DE miRNAs from the endometrium and one from blood samples. Among discovered novel miRNAs, chr2_4401 was validated and showed up-regulation in the mid-secretory endometrium. Besides novel findings, we confirmed the involvement of miR-30 and miR-200 family members in mid-secretory endometrial functions.

MicroRNA (miRNA) expression level alterations between endometrial tissue and endometriotic lesions indicate their involvement in endometriosis pathogenesis. However, as both endometrium and endometriotic lesions consist of different cell types in various proportions, it is not clear which cells contribute to variability in miRNA levels and the overall knowledge about cell-type specific miRNA expression in ectopic cells is scarce. Therefore, we utilized fluorescence-activated cell sorting to isolate endometrial stromal cells from paired endometrial and endometrioma biopsies and combined it with high-throughput sequencing to determine miRNA alterations in endometriotic stroma. The analysis revealed 149 abnormally expressed miRNAs in endometriotic lesions, including extensive upregulation of miR-139-5p and downregulation of miR-375 compared to eutopic cells. miRNA transfection experiments in the endometrial stromal cell line ST-T1b showed that the overexpression of miR-139-5p resulted in the downregulation of homeobox A9 (HOXA9) and HOXA10 expression, whereas the endothelin 1 (EDN1) gene was regulated by miR-375. The results of this study provide further insights into the complex molecular mechanisms involved in endometriosis pathogenesis and demonstrate the necessity for cell-type-specific analysis of ectopic tissues to understand the interactions between different cell populations in disease onset and progression.

The aetiology of endometriosis is still unclear and to find mechanisms behind the disease development, it is important to study each cell type from endometrium and ectopic lesions independently. The objective of this study was to uncover complete mRNA profiles in uncultured stromal cells from paired samples of endometriomas and eutopic endometrium. High-throughput mRNA sequencing revealed over 1300 dysregulated genes in stromal cells from ectopic lesions, including several novel genes in the context of endometriosis. Functional annotation analysis of differentially expressed genes highlighted pathways related to cell adhesion, extracellular matrix–receptor interaction and complement and coagulation cascade. Most importantly, we found a simultaneous upregulation of complement system components and inhibitors, indicating major imbalances in complement regulation in ectopic stromal cells. We also performed in vitro experiments to evaluate the effect of endometriosis patients’ peritoneal fluid (PF) on complement system gene expression levels, but no significant impact of PF on C3, CD55 and CFH levels was observed. In conclusion, the use of isolated stromal cells enables to determine gene expression levels without the background interference of other cell types. In the future, a new standard design studying all cell types from endometriotic lesions separately should be applied to reveal novel mechanisms behind endometriosis pathogenesis.

Targeted next-generation sequencing based biomarker detection methods have become essential for biomedical diagnostics. In addition to their sensitivity and high-throughput capacity, absolute molecule counting based on unique molecular identifier (UMI) has high potential to increase biomarker detection accuracy even further through the reduction of systematic technical biases. Here, we present TAC-seq, a simple and cost-effective targeted a llele c ounting by seq uencing method that uses UMIs to estimate the original molecule counts of different biomarker types like mRNAs, microRNAs and cell-free DNA. We applied TAC-seq in three different applications and compared the results with standard sequencing technologies. RNA samples extracted from human endometrial biopsies were analyzed using previously described 57 mRNA-based receptivity biomarkers and 49 selected microRNAs at different expression levels. Cell-free DNA aneuploidy testing was based on cell line (47,XX,+21) genomic DNA. TAC-seq mRNA biomarker profiling showed identical clustering results to full transcriptome RNA sequencing, and microRNA detection demonstrated significant reduction in amplification bias, allowing to determine minor expression changes between different samples that remained undetermined by standard sequencing. The mimicking experiment for cell-free DNA fetal aneuploidy analysis showed that TAC-seq can be applied to count highly fragmented DNA, detecting significant ( p =4.8×10 ⁻¹¹ ) excess of molecules in case of trisomy 21. Based on three proof-of-principle applications we show that TAC-seq is a highly accurate and universal method for targeted nucleic acid biomarker profiling.

Objective: The study aimed to validate a whole-genome sequencing-based NIPT method and our newly developed NIPTmer analysis software with the potential to integrate the pipeline into prenatal clinical care in Estonia. Method: In total, 447 maternal blood samples were included to the study. Analysis pipeline involved whole-genome library preparation and massively parallel sequencing on Illumina NextSeq 500. Aneuploidy status was determined with NIPTmer software, which is based on counting pre-defined per-chromosome sets of unique k-mers from raw sequencing data. To estimate fetal fraction (FF) from total cell-free DNA SeqFF was implemented. Results: NIPTmer software allowed to identify correctly all samples of non-mosaic T21 (15/15), T18 (9/9) and T13 (4/4) cases. However, one mosaic T18 remained undetected. Six false positive results were observed, including three for T18 (specificity 99.3%) and three for T13 (specificity 99.3%). FF < 4% (2.8-3.99%) was estimated in eight samples, including two samples with T13 and T18. Despite low FF, these two samples were determined as aneuploid with NIPTmer software. Conclusion: Our NIPT analysis pipeline proved to perform efficiently in detecting common fetal aneuploidies T21, T18 and T13 and is feasible for implementation into clinical service in Estonia.