Pre-eclampsia (PE) is a complication of pregnancy that affects 5‑8% of women after 20 weeks of gestation. It is usually diagnosed based on the de novo onset of hypertension and proteinuria. Preexisting hypertension in women developing PE, also known as superimposed PE on chronic hypertension (SPE), leads to elevated risk of maternal and fetal mortality. PE is associated with an altered microRNA (miRNA) expression pattern in the placenta, suggesting that miRNA deregulation is involved in the pathogenesis of PE. Whether and how the miRNA expression pattern is changed in the SPE placenta remains unclear. The present study analyzed the placental miRNA expression profile in pregnancies complicated by SPE. miRNA expression profiles in SPE and normal placentas were investigated using an Ion Torrent sequencing system. Sequencing data were processed using a comprehensive analysis pipeline for deep miRNA sequencing (CAP‑miRSeq). A total of 22 miRNAs were identified to be deregulated in placentas from patients with SPE. They included 16 miRNAs previously known to be associated with PE and 6 novel miRNAs. Among the 6 novel miRNAs, 4 were upregulated (miR‑518a, miR‑527, miR‑518e and miR‑4532) and 2 downregulated (miR‑98 and miR‑135b) in SPE placentas compared with controls. The present results suggest that SPE is associated with specific alterations in the placental miRNA expression pattern, which differ from alterations detected in PE placentas, and therefore, provide novel targets for further investigation of the molecular mechanisms underlying SPE pathogenesis.

Preeclampsia (PE) is a multisystem heterogeneous complication of pregnancy remaining a leading cause of maternal and perinatal morbidity and mortality over the world. PE has a large spectrum of clinical features and symptoms, which make diagnosis challenging. Despite a long period of studying, PE etiology is still unclear and there are no reliable rapid tests for early diagnosis of this disease. During the last decade, it was shown that proteins misfolding and aggregation are associated with PE. Several proteins, including amyloid beta peptide, transthyretin, alpha-1 antitrypsin, albumin, IgG k-free light chains, and ceruloplasmin are dysregulated in PE, resulting in toxic deposition of amyloid-like aggregates in the placenta and body fluids. It is also possible that aggregated proteins induce defective trophoblast invasion, placental ischemia, ER stress, and promote PE manifestation. The fact that protein aggregation is an emerging biomarker of PE provides an opportunity to develop new diagnostic approaches based on amyloids special features, such as Congo red (CR) staining and thioflavin T (ThT) enhanced fluorescence.

Pre-eclampsia is the most common complication occurring during pregnancy. In the majority of cases, it is concurrent with other pathologies in a comorbid manner (frequent co-occurrences in patients), such as diabetes mellitus, gestational diabetes and obesity. Providing bronchial asthma, pulmonary tuberculosis, certain neurodegenerative diseases and cancers as examples, we have shown previously that pairs of inversely comorbid pathologies (rare co-occurrences in patients) are more closely related to each other at the molecular genetic level compared with randomly generated pairs of diseases. Data in the literature concerning the causes of pre-eclampsia are abundant. However, the key mechanisms triggering this disease that are initiated by other pathological processes are thus far unknown. The aim of this work was to analyse the characteristic features of genetic networks that describe interactions between comorbid diseases, using pre-eclampsia as a case in point.

Over the recent years, many advances have been made in the research of the genetic factors of pregnancy complications. In this work, we use publicly available data repositories, such as the National Human Genome Research Institute GWAS Catalog, HuGE Navigator, and the UK Biobank genetic and phenotypic dataset to gain insights into molecular pathways and individual genes behind a set of pregnancy-related traits, including the most studied ones—preeclampsia, gestational diabetes, preterm birth, and placental abruption. Using both HuGE and GWAS Catalog data, we confirm that immune system and, in particular, T-cell related pathways are one of the most important drivers of pregnancy-related traits. Pathway analysis of the data reveals that cell adhesion and matrisome-related genes are also commonly involved in pregnancy pathologies. We also find a large role of metabolic factors that affect not only gestational diabetes, but also the other traits. These shared metabolic genes include IGF2, PPARG, and NOS3. We further discover that the published genetic associations are poorly replicated in the independent UK Biobank cohort. Nevertheless, we find novel genome-wide associations with pregnancy-related traits for the FBLN7, STK32B, and ACTR3B genes, and replicate the effects of the KAZN and TLE1 genes, with the latter being the only gene identified across all data resources. Overall, our analysis highlights central molecular pathways for pregnancy-related traits, and suggests a need to use more accurate and sophisticated association analysis strategies to robustly identify genetic risk factors for pregnancy complications.

In recent years evidence has been accumulated showing that miRNAs can act as potential biomarkers or targets for therapy of preterm birth, one of the most important problems in modern obstetrics. We have performed a prospective study of the miRNA profile in the plasma during the first and second trimesters in pregnant women with high risk of preterm birth (n = 13 cases and n = 11 controls). For the study group plasma blood samples at 9–13 weeks before diagnosis and at 22–24 weeks after start of therapy were selected. Using high-throughput sequencing technology we detected differences in the levels of 15 miRNAs (3 upregulated—hsa-miR-122-5p, hsa-miR-34a-5p, hsa-miR-34c-5p; 12 downregulated—hsa-miR-487b-3p, hsa-miR-493-3p, hsa-miR-432-5p, hsa-miR-323b-3p, hsa-miR-369-3p, hsa-miR-134-5p, hsa-miR-431-5p, hsa-miR-485-5p, hsa-miR-382-5p, hsa-miR-369-5p, hsa-miR-485-3p, hsa-miR-127-3p) (log₂(FC) ≥ 1.5; FDR ≤ 0.05) during the first trimester compared with the control (non-high-risk of preterm birth pregnant women). All downregulated miRNAs in the first trimester from the placenta-specific C14MC cluster. During the second trimester no differentially expressed miRNAs were found. Our results suggest that the miRNA profile in plasma during early pregnancy may predict a high risk of preterm birth, which is important in preventing gestational problems as early as possible.

Although circulating microRNAs (miRNAs) in maternal blood may play an important role in regulation of pregnancy progression and serve as non-invasive biomarkers for different gestation complications, little is known about their profile in blood during normally developing pregnancy. In this study we evaluated the miRNA profiles in paired plasma and serum samples from pregnant women without health or gestational abnormalities at three time points using high-throughput sequencing technology. Sequencing revealed that the percentage of miRNA reads in plasma and serum decreased by a third compared to first and second trimesters. We found two miRNAs in plasma (hsa-miR-7853-5p and hsa-miR-200c-3p) and 10 miRNAs in serum (hsa-miR-203a-5p, hsa-miR-495-3p, hsa-miR-4435, hsa-miR-340-5p, hsa-miR-4417, hsa-miR-1266-5p, hsa-miR-4494, hsa-miR-134-3p, hsa-miR-5008-5p, and hsa-miR-6756-5p), that exhibit level changes during pregnancy (p-value adjusted < 0.05). In addition, we observed differences for 36 miRNAs between plasma and serum (p-value adjusted < 0.05), which should be taken into consideration when comparing the results between studies performed using different biosample types. The results were verified by analysis of three miRNAs using qRT-PCR (p < 0.05). The present study confirms that the circulating miRNA profile in blood changes during gestation. Our results set the basis for further investigation of molecular mechanisms, involved in regulation of pregnancy, and the search for biomarkers of gestation abnormalities.