Targeted sequencing analysis of ACVR2A gene identifies novel risk variants associated with preeclampsia.

Background: Preeclampsia (PE) is the most common complication of pregnancy that remains to be a major cause of maternal and fetal mortality. Prediction and early diagnosis of PE would allow for timely initiation of preventive therapy. According to recent studies of ACVR2A gene polymorphism is associated with PE, but it is still unclear whether these findings reflect specific pathogenetic mechanisms of this disease. Methods: We performed targeted next-generation sequencing (NGS) sequencing of ACVR2A gene by means of Ion Torrent Personal Genome machine (PGM) Sequencer. A genetic analysis of patients with PE and control group was performed. Bioinformatics analysis using Polyphen2 (Boston, MA), SIFT (La Jolla, CA), and SnpSift software were used. To select genetic markers in PE patients two additive models and score analysis were applied. Results: Based on the score analysis, we detected two substitutions (rs145399059 and rs17692648) and one insertion insAA at position 148642724 that were associated with PE in our cohorts. We also detected a variant rs17742573 that can be considered as protective against preeclampsia. Conclusions: Our data suggest that some variants in ACVR2A gene are associated with PE. But more studies are required to reveal the role of ACVR2A gene in the pathogenesis of this disease during pregnancy.

Placental microRNA expression in pregnancies complicated by superimposed pre­eclampsia on chronic hypertension.

Pre-eclampsia (PE) is a complication of pregnancy that affects 5­8% 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 (CAP­miRSeq). 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 (miR­518a, miR­527, miR­518e and miR­4532) and 2 downregulated (miR­98 and miR­135b) 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.

Molecular association of pathogenetic contributors to pre-eclampsia (pre-eclampsia associome).

BACKGROUND: 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. RESULTS: The use of ANDSystem, Pathway Studio and STRING computer tools based on text-mining and database-mining approaches allowed us to reconstruct associative networks, representing molecular genetic interactions between genes, associated concurrently with comorbid disease pairs, including pre-eclampsia, diabetes mellitus, gestational diabetes and obesity. It was found that these associative networks statistically differed in the number of genes and interactions between them from those built for randomly chosen pairs of diseases. The associative network connecting all four diseases was composed of 16 genes (PLAT, ADIPOQ, ADRB3, LEPR, HP, TGFB1, TNFA, INS, CRP, CSRP1, IGFBP1, MBL2, ACE, ESR1, SHBG, ADA). Such an analysis allowed us to reveal differential gene risk factors for these diseases, and to propose certain, most probable, theoretical mechanisms of pre-eclampsia development in pregnant women. The mechanisms may include the following pathways: [TGFB1 or TNFA]-[IL1B]-[pre-eclampsia]; [TNFA or INS]-[NOS3]-[pre-eclampsia]; [INS]-[HSPA4 or CLU]-[pre-eclampsia]; [ACE]-[MTHFR]-[pre-eclampsia]. CONCLUSIONS: For pre-eclampsia, diabetes mellitus, gestational diabetes and obesity, we showed that the size and connectivity of the associative molecular genetic networks, which describe interactions between comorbid diseases, statistically exceeded the size and connectivity of those built for randomly chosen pairs of diseases. Recently, we have shown a similar result for inversely comorbid diseases. This suggests that comorbid and inversely comorbid diseases have common features concerning structural organization of associative molecular genetic networks.

Targeted next-generation sequencing (NGS) of nine candidate genes with custom AmpliSeq in patients and a cardiomyopathy risk group.

BACKGROUND: Hypertrophic cardiomyopathy is a common genetic cardiac disease. Prevention and early diagnosis of this disease are very important. Because of the large number of causative genes and the high rate of mutations involved in the pathogenesis of this disease, traditional methods of early diagnosis are ineffective. METHODS: We developed a custom AmpliSeq panel for NGS sequencing of the coding sequences of ACTC1, MYBPC3, MYH7, MYL2, MYL3, TNNI3, TNNT2, TPM1, and CASQ2. A genetic analysis of student cohorts (with and without cardiomyopathy risk in their medical histories) and patients with cardiomyopathies was performed. For the statistical and bioinformatics analysis, Polyphen2, SIFT, SnpSift and PLINK software were used. To select genetic markers in the patients with cardiomyopathy and in the students of the high risk group, four additive models were applied. RESULTS: Our AmpliSeq custom panel allowed us to efficiently explore targeted sequences. Based on the score analysis, we detected three substitutions in the MYBPC3 and CASQ2 genes and six combinations between loci in the MYBPC3, MYH7 and CASQ2 genes that were responsible for cardiomyopathy risk in our cohorts. We also detected substitutions in the TNNT2 gene that can be considered as protective against cardiomyopathy. CONCLUSION: We used NGS with AmpliSeq libraries and Ion PGM sequencing to develop improved predictive information for patients at risk of cardiomyopathy.