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

Reconstruction of the regulatory hypermethylation network controlling hepatocellular carcinoma development during hepatitis C viral infection

Hepatocellular carcinoma (HCC) has been associated with hepatitis C viral (HCV) infection as a potential risk factor. Nonetheless, the precise genetic regulatory mechanisms triggered by the virus, leading to virus-induced hepatocarcinogenesis, remain unclear. We hypothesized that HCV proteins might modulate the activity of aberrantly methylated HCC genes through regulatory pathways. Virus-host regulatory pathways, interactions between proteins, gene expression, transport, and stability regulation, were reconstructed using the ANDSystem. Gene expression regulation was statistically significant. Gene network analysis identified four out of 70 HCC marker genes whose expression regulation by viral proteins may be associated with HCC: DNA-binding protein inhibitor ID - 1 (ID1), flap endonuclease 1 (FEN1), cyclin-dependent kinase inhibitor 2A (CDKN2A), and telomerase reverse transcriptase (TERT). It suggested the following viral protein effects in HCV/human protein heterocomplexes: HCV NS3(p70) protein activates human STAT3 and NOTC1; NS2-3(p23), NS5B(p68), NS1(E2), and core(p21) activate SETD2; NS5A inhibits SMYD3; and NS3 inhibits CCN2. Interestingly, NS3 and E1(gp32) activate c-Jun when it positively regulates CDKN2A and inhibit it when it represses TERT. The discovered regulatory mechanisms might be key areas of focus for creating medications and preventative therapies to decrease the likelihood of HCC development during HCV infection.

Primary and Secondary micro-RNA Modulation the Extrinsic Pathway of Apoptosis in Hepatocellular Carcinoma

Abstract-One of the most common malignant liver diseases is hepatocellular carcinoma, which has a high recurrence rate and a low five-year survival rate. It is very heterogeneous both in structure and between patients, which complicates the diagnosis, prognosis and response to treatment. In this regard, an individualized, patient-centered approach becomes important, in which the use of mimetics and hsa-miRNA inhibitors involved in the pathogenesis of the disease may be determinative. From this point of view hsa-miRNAs are of interest, their aberrant expression is associated with poor prognosis for patients and is associated with tumor progression due to dysregulation of programmed cell death (apoptosis). However, the effect of hsa-miRNA on tumor development depends not only on its direct effect on expression of genes, the primary targets, but also on secondary targets mediated by regulatory pathways. While the former are actively studied, the role of secondary targets of these hsa-miRNAs in modulating apoptosis is still unclear. The present work summarizes data on hsa-miRNAs whose primary targets are key genes of the extrinsic pathway of apoptosis. Their aberrant expression is associated with early disease relapse and poor patient outcome. For these hsa-miRNAs, using the software package ANDSystem, we reconstructed the regulation of the expression of secondary targets and analyzed their impact on the activity of the extrinsic pathway of apoptosis. The potential effect of hsa-miRNAs mediated by action on secondary targets is shown to negatively correlate with the number of primary targets. It is also shown that hsa-miR-373, hsa-miR-106b and hsa-miR-96 have the highest priority as markers of hepatocellular carcinoma, whose action on secondary targets enhances their anti-apoptotic effect.

Computer analysis of regulation of hepatocarcinoma marker genes hypermethylated by HCV proteins

Hepatitis C virus (HCV) is a risk factor that leads to hepatocellular carcinoma (HCC) development. Epigenetic changes are known to play an important role in the molecular genetic mechanisms of virus-induced oncogenesis. Aberrant DNA methylation is a mediator of epigenetic changes that are closely associated with the HCC pathogenesis and considered a biomarker for its early diagnosis. The ANDSystem software package was used to reconstruct and evaluate the statistical significance of the pathways HCV could potentially use to regulate 32 hypermethylated genes in HCC, including both oncosuppressor and protumorigenic ones identified by genome-wide analysis of DNA methylation. The reconstructed pathways included those affecting protein-protein interactions (PPI), gene expression, protein activity, stability, and transport regulations, the expression regulation pathways being statistically significant. It has been shown that 8 out of 10 HCV proteins were involved in these pathways, the HCV NS3 protein being implicated in the largest number of regulatory pathways. NS3 was associated with the regulation of 5 tumor-suppressor genes, which may be the evidence of its central role in HCC pathogenesis. Analysis of the reconstructed pathways has demonstrated that following the transcription factor inhibition caused by binding to viral proteins, the expression of a number of oncosuppressors (WT1, MGMT, SOCS1, P53) was suppressed, while the expression of others (RASF1, RUNX3, WIF1, DAPK1) was activated. Thus, the performed gene-network reconstruction has shown that HCV proteins can influence not only the methylation status of oncosuppressor genes, but also their transcriptional regulation. The results obtained can be used in the search for pharmacological targets to develop new drugs against HCV-induced HCC.

The New Version of the ANDDigest Tool with Improved AI-Based Short Names Recognition

The body of scientific literature continues to grow annually. Over 1.5 million abstracts of biomedical publications were added to the PubMed database in 2021. Therefore, developing cognitive systems that provide a specialized search for information in scientific publications based on subject area ontology and modern artificial intelligence methods is urgently needed. We previously developed a web-based information retrieval system, ANDDigest, designed to search and analyze information in the PubMed database using a customized domain ontology. This paper presents an improved ANDDigest version that uses fine-tuned PubMedBERT classifiers to enhance the quality of short name recognition for molecular-genetics entities in PubMed abstracts on eight biological object types: cell components, diseases, side effects, genes, proteins, pathways, drugs, and metabolites. This approach increased average short name recognition accuracy by 13%.

Plasma metabolomics and gene regulatory networks analysis reveal the role of nonstructural SARS-CoV-2 viral proteins in metabolic dysregulation in COVID-19 patients

Metabolomic analysis of blood plasma samples from COVID-19 patients is a promising approach allowing for the evaluation of disease progression. We performed the metabolomic analysis of plasma samples of 30 COVID-19 patients and the 19 controls using the high-performance liquid chromatography (HPLC) coupled with tandem mass spectrometric detection (LC-MS/MS). In our analysis, we identified 103 metabolites enriched in KEGG metabolic pathways such as amino acid metabolism and the biosynthesis of aminoacyl-tRNAs, which differed significantly between the COVID-19 patients and the controls. Using ANDSystem software, we performed the reconstruction of gene networks describing the potential genetic regulation of metabolic pathways perturbed in COVID-19 patients by SARS-CoV-2 proteins. The nonstructural proteins of SARS-CoV-2 (orf8 and nsp5) and structural protein E were involved in the greater number of regulatory pathways. The reconstructed gene networks suggest the hypotheses on the molecular mechanisms of virus-host interactions in COVID-19 pathology and provide a basis for the further experimental and computer studies of the regulation of metabolic pathways by SARS-CoV-2 proteins. Our metabolomic analysis suggests the need for nonstructural protein-based vaccines and the control strategy to reduce the disease progression of COVID-19.

Prevention of intrauterine fetal growth restriction by administrating C1q/TNF-related protein 6, a specific inhibitor of the alternative complement pathway

PURPOSE

The latest treatments do not sufficiently prevent miscarriage and fetal growth restriction (FGR) in pregnant women. Here, we assessed the effects of a human protein, CTRP6, that specifically inhibits the activation of the alternative complement pathway on miscarriage, fetal and placental development.

METHODS

Pregnant CBA/J mice mated with DBA/2 male mice as a model of spontaneous abortion and FGR were randomly divided into the control and CTRP6 groups. In the CTRP6 group, the mice were intravenously administered CTRP6 on days 4.5 and 6.5 post-conception (dpc). The abortion rate and fetal and placental weights on 14.5 dpc were examined. Remodeling of the spiral artery was also assessed.

RESULTS

The abortion rate in the CTRP6 group (13%) was reduced compared to the control group (21%), but there was no statistical difference. The placental and fetal weights in the CTRP6 group were also heavier than those in the control (P < 0.05). Moreover, the thickness of the blood vessel wall in the CTRP6 group was significantly thinner than that in the control (P < 0.05) and comparable to that in the non-abortion model (CBA/J x BALB). The ratio of the inner-per-the-outer diameter of the spiral artery increased more in the CTRP6 group than that in the control (P < 0.05). As well, the Th1/Th2 cytokine ratio was significantly reduced by CTRP6 treatment.

CONCLUSIONS

Taken together, the supplementation with a protein that regulates the alternative complement pathway in vivo improves FGR and promotes spiral artery remodeling in a mouse model of miscarriage and FGR.

Targeting Nrf2-Mediated Oxidative Stress Response in Traumatic Brain Injury: Therapeutic Perspectives of Phytochemicals

Traumatic brain injury (TBI), known as mechanical damage to the brain, impairs the normal function of the brain seriously. Its clinical symptoms manifest as behavioral impairment, cognitive decline, communication difficulties, etc. The pathophysiological mechanisms of TBI are complex and involve inflammatory response, oxidative stress, mitochondrial dysfunction, blood-brain barrier (BBB) disruption, and so on. Among them, oxidative stress, one of the important mechanisms, occurs at the beginning and accompanies the whole process of TBI. Most importantly, excessive oxidative stress causes BBB disruption and brings injury to lipids, proteins, and DNA, leading to the generation of lipid peroxidation, damage of nuclear and mitochondrial DNA, neuronal apoptosis, and neuroinflammatory response. Transcription factor NF-E2 related factor 2 (Nrf2), a basic leucine zipper protein, plays an important role in the regulation of antioxidant proteins, such as oxygenase-1(HO-1), NAD(P)H Quinone Dehydrogenase 1 (NQO1), and glutathione peroxidase (GPx), to protect against oxidative stress, neuroinflammation, and neuronal apoptosis. Recently, emerging evidence indicated the knockout (KO) of Nrf2 aggravates the pathology of TBI, while the treatment of Nrf2 activators inhibits neuronal apoptosis and neuroinflammatory responses via reducing oxidative damage. Phytochemicals from fruits, vegetables, grains, and other medical herbs have been demonstrated to activate the Nrf2 signaling pathway and exert neuroprotective effects in TBI. In this review, we emphasized the contributive role of oxidative stress in the pathology of TBI and the protective mechanism of the Nrf2-mediated oxidative stress response for the treatment of TBI. In addition, we summarized the research advances of phytochemicals, including polyphenols, terpenoids, natural pigments, and otherwise, in the activation of Nrf2 signaling and their potential therapies for TBI. Although there is still limited clinical application evidence for these natural Nrf2 activators, we believe that the combinational use of phytochemicals such as Nrf2 activators with gene and stem cell therapy will be a promising therapeutic strategy for TBI in the future.

Evaluation of the PLAC8 Gene in Mexican Women With and Without Preeclampsia and Obesity

Preeclampsia (PE) is a leading cause of maternal-fetal mortality worldwide, and obesity is an important risk factor. Genes associated with pathophysiological events common to preeclampsia and obesity, such as PLAC8, remain to be studied; therefore, the aim of the present study was to evaluate this gene in the placentas of women affected with preeclampsia and healthy pregnant women. This case-controlled study included 71 healthy and 64 preeclampsia pregnancies. Gene expression was evaluated in primary human cytotrophoblasts (PHCT) from six normal and six preeclampsia pregnancies, and protein expression was verified in placentas from five healthy and six preeclampsia pregnancies. The whole coding and 5′ regions of the PLAC8 gene were sequenced from healthy (n = 10) and preeclamptic (n = 10) pregnancies. The presence of the observed nucleotide variations was analyzed by RT-PCR in the total population. Statistical analyses were performed accordingly. Obesity was associated with severe preeclampsia (SPE) (OR = 3.34; CI 95% 1.3–8.2, p < 0.01). Significantly higher mRNA and protein expression was observed in preeclamptic vs. healthy placentas (p < 0.05). After sequencing, a single nucleotide variation was identified in 10 cases and one control (p < 0.01), which was then evaluated in the total population showing no association with preeclampsia. This preliminary study confirms the association of SPE with obesity and suggests higher expression of PLAC8 mRNA and protein in placentas from preeclampsia. No differences in nucleotide variations between cases and controls of the whole population were observed. Further research is required to evaluate the implications of higher gene/protein expression in preeclampsia and the causes of such variation.

Maternal Periodontal Disease: A Possible Risk Factor for Adverse Pregnancy Outcomes in the Qassim Region of Saudi Arabia

BACKGROUND AND AIMS

In periodontal disease, pathogenic inflammatory factors hold a vital part in adverse pregnancy outcomes. In recent years, there has been a large amount of literature concerning the association between periodontal disease and adverse pregnancy outcomes such as preterm birth (PTB) and low-birth-weight baby (LBWB). In the Middle-east region, reports indicate a higher rate of adverse pregnancy outcomes, and periodontitis is believed to be one of several risk factors for adverse pregnancy outcomes. This cross-sectional, epidemiological study aimed to investigate the prevalence of periodontal diseases among pregnant women in the Qassim region and its association as a possible risk factor for adverse pregnancy outcomes.

MATERIALS AND METHODOLOGY

This was a cross-sectional, epidemiological study of 380 pregnant women from the 8^th week postconception to parturition who were attending to Maternal and Children's Hospital in Buraidah, Qassim, KSA. The data were collected through questionnaire and oral examination. Plaque scores (Silness and Loe) and gingival disease scores (Ramfjord Periodontal Disease Index [PDI]) were used to assess oral hygiene status. The questionnaire data collected included gestational age, plaque control habits, previous incidences of premature birth, and awareness of expectant mothers about periodontal disease.

RESULTS

Data were collected for 380 participants. Our results based on the plaque index and PDI showed that all (100%) of these 380 pregnant women suffered periodontal diseases (gingivitis 78.9% and periodontitis 21.1%). The distribution of gingivitis was the highest among 3^rd trimester patients and lowest among 1^st trimester patients. Mild-to-moderate types of periodontitis (4 mm-5 mm) were more prevalent among the participants compared with severe (more than 6 mm) forms of periodontitis with a higher prevalence in the 3^rd trimester (7-9 months) of gestational age.

CONCLUSIONS

A very strong significant association of pregnancy and periodontal disease in the Saudi population (Qassim Region) and periodontal disease is risk factor for PTB and LBWB for these patients.

The Secretive Liaison of Particulate Matter and SARS-CoV-2. A Hypothesis and Theory Investigation

As the novel coronavirus disease sweeps across the world, there is growing speculation on the role that atmospheric factors may have played on the different distribution of SARS-CoV-2, and on the epidemiological characteristics of COVID-19. Knowing the role that environmental factors play in influenza virus outbreaks, environmental pollution and, in particular, atmospheric airborne (particulate matter, PM) has been considered as a potential key factor in the spread and mortality of COVID-19. A possible role of the PM as the virus carrier has also been debated. The role of PM in exacerbating respiratory and cardiovascular disease has been well recognized. Accumulating evidence support the hypothesis that PM can trigger inflammatory response at molecular, cellular and organ levels. On this basis, we developed the hypothesis that PM may play a role as a booster of COVID-19 rather than as a carrier of SARS-CoV-2. To support our hypothesis, we analyzed the molecular signatures detected in cells exposed to PM samples collected in one of the most affected areas by the COVID-19 outbreak, in Italy. T47D human breast adenocarcinoma cells were chosen to explore the global gene expression changes induced by the treatment with organic extracts of PM 2.5. The analysis of the KEGG's pathways showed modulation of several gene networks related to the leucocyte transendothelial migration, cytoskeleton and adhesion system. Three major biological process were identified, including coagulation, growth control and immune response. The analysis of the modulated genes gave evidence for the involvement of PM in the endothelial disease, coagulation disorders, diabetes and reproductive toxicity, supporting the hypothesis that PM, directly or through molecular interplay, affects the same molecular targets as so far known for SARS-COV-2, contributing to the cytokines storm and to the aggravation of the symptoms triggered by COVID-19. We provide evidence for a plausible cooperation of receptors and transmembrane proteins, targeted by PM and involved in COVID-19, together with new insights into the molecular interplay of chemicals and pathogens that could be of importance for sustaining public health policies and developing new therapeutic approaches.

Bioinformatic Reconstruction and Analysis of Gene Networks Related to Glucose Variability in Diabetes and Its Complications

Glucose variability (GV) has been recognized recently as a promoter of complications and therapeutic targets in diabetes. The aim of this study was to reconstruct and analyze gene networks related to GV in diabetes and its complications. For network analysis, we used the ANDSystem that provides automatic network reconstruction and analysis based on text mining. The network of GV consisted of 37 genes/proteins associated with both hyperglycemia and hypoglycemia. Cardiovascular system, pancreas, adipose and muscle tissues, gastrointestinal tract, and kidney were recognized as the loci with the highest expression of GV-related genes. According to Gene Ontology enrichment analysis, these genes are associated with insulin secretion, glucose metabolism, glycogen biosynthesis, gluconeogenesis, MAPK and JAK-STAT cascades, protein kinase B signaling, cell proliferation, nitric oxide biosynthesis, etc. GV-related genes were found to occupy central positions in the networks of diabetes complications (cardiovascular disease, diabetic nephropathy, retinopathy, and neuropathy) and were associated with response to hypoxia. Gene prioritization analysis identified new gene candidates (THBS1, FN1, HSP90AA1, EGFR, MAPK1, STAT3, TP53, EGF, GSK3B, and PTEN) potentially involved in GV. The results expand the understanding of the molecular mechanisms of the GV phenomenon in diabetes and provide molecular markers and therapeutic targets for future research.

ANDDigest: a new web-based module of ANDSystem for the search of knowledge in the scientific literature

BACKGROUND

The rapid growth of scientific literature has rendered the task of finding relevant information one of the critical problems in almost any research. Search engines, like Google Scholar, Web of Knowledge, PubMed, Scopus, and others, are highly effective in document search; however, they do not allow knowledge extraction. In contrast to the search engines, text-mining systems provide extraction of knowledge with representations in the form of semantic networks. Of particular interest are tools performing a full cycle of knowledge management and engineering, including automated retrieval, integration, and representation of knowledge in the form of semantic networks, their visualization, and analysis. STRING, Pathway Studio, MetaCore, and others are well-known examples of such products. Previously, we developed the Associative Network Discovery System (ANDSystem), which also implements such a cycle. However, the drawback of these systems is dependence on the employed ontologies describing the subject area, which limits their functionality in searching information based on user-specified queries.

RESULTS

The ANDDigest system is a new web-based module of the ANDSystem tool, permitting searching within PubMed by using dictionaries from the ANDSystem tool and sets of user-defined keywords. ANDDigest allows performing the search based on complex queries simultaneously, taking into account many types of objects from the ANDSystem's ontology. The system has a user-friendly interface, providing sorting, visualization, and filtering of the found information, including mapping of mentioned objects in text, linking to external databases, sorting of data by publication date, citations number, journal H-indices, etc. The system provides data on trends for identified entities based on dynamics of interest according to the frequency of their mentions in PubMed by years.

CONCLUSIONS

The main feature of ANDDigest is its functionality, serving as a specialized search for information about multiple associative relationships of objects from the ANDSystem's ontology vocabularies, taking into account user-specified keywords. The tool can be applied to the interpretation of experimental genetics data, the search for associations between molecular genetics objects, and the preparation of scientific and analytical reviews. It is presently available at https://anddigest.sysbio.ru/ .

Periodontal disease and adverse pregnancy outcomes

Periodontal diseases are considered not only to affect tooth-supporting tissues but also to have a cause-and-effect relationship with various systemic diseases and conditions, such as adverse pregnancy outcomes. Mechanistic studies provide strong evidence that periodontal pathogens can translocate from infected periodontium to the feto-placental unit and initiate a metastatic infection. However, the extent and mechanisms by which metastatic inflammation and injury contribute to adverse pregnancy outcomes still remain unclear. The presence of oral bacteria in the placenta of women with term gestation further complicates our understanding of the biology behind the role of periodontal pathogens in pregnancy outcomes. Epidemiological studies demonstrate many methodological inconsistencies and flaws that render comparisons difficult and conclusions insecure. Therefore, despite the fact that a number of prospective studies show a positive association between periodontal diseases and various adverse pregnancy outcomes, the evidence behind it is still weak. Future well-designed explanatory studies are necessary to verify this relationship and, if present, determine its magnitude. The majority of high-quality randomized controlled trials reveal that nonsurgical periodontal therapy during the second trimester of gestation does not improve pregnancy outcomes. From a biological standpoint, this can be partially explained by the fact that therapy rendered at the fourth to sixth months of pregnancy is too late to prevent placental colonization by periodontal pathogens and consequently incapable of affecting pathogen-induced injury at the feto-placental unit. Thus, interventions during the preconception period may be more meaningful. With the increase in our understanding on the potential association between periodontal disease and adverse pregnancy outcomes, it is clear that dental practitioners should provide periodontal treatment to pregnant women that is safe for both the mother and the unborn child. Although there is not enough evidence that the anti-infective therapy alters pregnancy outcomes, it improves health-promoting behavior and periodontal condition, which in turn advance general health and risk factor control.

Prioritization of genes involved in endothelial cell apoptosis by their implication in lymphedema using an analysis of associative gene networks with ANDSystem

BACKGROUND

Currently, more than 150 million people worldwide suffer from lymphedema. It is a chronic progressive disease characterized by high-protein edema of various parts of the body due to defects in lymphatic drainage. Molecular-genetic mechanisms of the disease are still poorly understood. Beginning of a clinical manifestation of primary lymphedema in middle age and the development of secondary lymphedema after treatment of breast cancer can be genetically determined. Disruption of endothelial cell apoptosis can be considered as one of the factors contributing to the development of lymphedema. However, a study of the relationship between genes associated with lymphedema and genes involved in endothelial apoptosis, in the associative gene network was not previously conducted.

METHODS

In the current work, we used well-known methods (ToppGene and Endeavour), as well as methods previously developed by us, to prioritize genes involved in endothelial apoptosis and to find potential participants of molecular-genetic mechanisms of lymphedema among them. Original methods of prioritization took into account the overrepresented Gene Ontology biological processes, the centrality of vertices in the associative gene network, describing the interactions of endothelial apoptosis genes with genes associated with lymphedema, and the association of the analyzed genes with diseases that are comorbid to lymphedema.

RESULTS

An assessment of the quality of prioritization was performed using criteria, which involved an analysis of the enrichment of the top-most priority genes by genes, which are known to have simultaneous interactions with lymphedema and endothelial cell apoptosis, as well as by genes differentially expressed in murine model of lymphedema. In particular, among genes involved in endothelial apoptosis, KDR, TNF, TEK, BMPR2, SERPINE1, IL10, CD40LG, CCL2, FASLG and ABL1 had the highest priority. The identified priority genes can be considered as candidates for genotyping in the studies involving the search for associations with lymphedema.

CONCLUSIONS

Analysis of interactions of these genes in the associative gene network of lymphedema can improve understanding of mechanisms of interaction between endothelial apoptosis and lymphangiogenesis, and shed light on the role of disturbance of these processes in the development of edema, chronic inflammation and connective tissue transformation during the progression of the disease.

A new version of the ANDSystem tool for automatic extraction of knowledge from scientific publications with expanded functionality for reconstruction of associative gene networks by considering tissue-specific gene expression

BACKGROUND

Consideration of tissue-specific gene expression in reconstruction and analysis of molecular genetic networks is necessary for a proper description of the processes occurring in a specified tissue. Currently, there are a number of computer systems that allow the user to reconstruct molecular-genetic networks using the data automatically extracted from the texts of scientific publications. Examples of such systems are STRING, Pathway Commons, MetaCore and Ingenuity. The MetaCore and Ingenuity systems permit taking into account tissue-specific gene expression during the reconstruction of gene networks. Previously, we developed the ANDSystem tool, which also provides an automated extraction of knowledge from scientific texts and allows the reconstruction of gene networks. The main difference between our system and other tools is in the different types of interactions between objects, which makes the ANDSystem complementary to existing well-known systems. However, previous versions of the ANDSystem did not contain any information on tissue-specific expression.

RESULTS

A new version of the ANDSystem has been developed. It offers the reconstruction of associative gene networks while taking into account the tissue-specific gene expression. The ANDSystem knowledge base features information on tissue-specific expression for 272 tissues. The system allows the reconstruction of combined gene networks, as well as performing the filtering of genes from such networks using the information on their tissue-specific expression. As an example of the application of such filtering, the gene network of the extrinsic apoptotic signaling pathway was analyzed. It was shown that considering different tissues can lead to changes in gene network structure, including changes in such indicators as betweenness centrality of vertices, clustering coefficient, network centralization, network density, etc. CONCLUSIONS: The consideration of tissue specificity can play an important role in the analysis of gene networks, in particular solving the problem of finding the most significant central genes. Thus, the new version of ANDSystem can be employed for a wide range of tasks related to biomedical studies of individual tissues. It is available at http://www-bionet.sscc.ru/and/cell /.

Preconditioning in the Rhesus Macaque Induces a Proteomic Signature Following Cerebral Ischemia that Is Associated with Neuroprotection

Each year, thousands of patients are at risk of cerebral ischemic injury, due to iatrogenic responses to surgical procedures. Prophylactic treatment of these patients as standard care could minimize potential neurological complications. We have shown that protection of brain tissue, in a non-human primate model of cerebral ischemic injury, is possible through pharmacological preconditioning using the immune activator D192935. We postulate that preconditioning with D192935 results in neuroprotective reprogramming that is evident in the brain following experimentally induced cerebral ischemia. We performed quantitative proteomic analysis of cerebral spinal fluid (CSF) collected post-stroke from our previously published efficacy study to determine whether CSF protein profiles correlated with induced protection. Four groups of animals were examined: naïve animals (no treatment or stroke); animals treated with vehicle prior to stroke; D192935 treated and stroked animals, further delineated into two groups, ones that were protected (small infarcts) and those that were not protected (large infarcts). We found that distinct protein clusters defined the protected and non-protected animal groups, with a 16-member cluster of proteins induced exclusively in D192935 protected animals. Seventy percent of the proteins induced in the protected animals have functions that would enhance neuroprotection and tissue repair, including several members associated with M2 macrophages, a macrophage phenotype shown to contribute to neuroprotection and repair during ischemic injury. These studies highlight the translational importance of CSF biomarkers in defining mechanism and monitoring responses to treatment in development of stroke therapeutics.

Novel candidate genes important for asthma and hypertension comorbidity revealed from associative gene networks

BACKGROUND

Hypertension and bronchial asthma are a major issue for people's health. As of 2014, approximately one billion adults, or ~ 22% of the world population, have had hypertension. As of 2011, 235-330 million people globally have been affected by asthma and approximately 250,000-345,000 people have died each year from the disease. The development of the effective treatment therapies against these diseases is complicated by their comorbidity features. This is often a major problem in diagnosis and their treatment. Hence, in this study the bioinformatical methodology for the analysis of the comorbidity of these two diseases have been developed. As such, the search for candidate genes related to the comorbid conditions of asthma and hypertension can help in elucidating the molecular mechanisms underlying the comorbid condition of these two diseases, and can also be useful for genotyping and identifying new drug targets.

RESULTS

Using ANDSystem, the reconstruction and analysis of gene networks associated with asthma and hypertension was carried out. The gene network of asthma included 755 genes/proteins and 62,603 interactions, while the gene network of hypertension - 713 genes/proteins and 45,479 interactions. Two hundred and five genes/proteins and 9638 interactions were shared between asthma and hypertension. An approach for ranking genes implicated in the comorbid condition of two diseases was proposed. The approach is based on nine criteria for ranking genes by their importance, including standard methods of gene prioritization (Endeavor, ToppGene) as well as original criteria that take into account the characteristics of an associative gene network and the presence of known polymorphisms in the analysed genes. According to the proposed approach, the genes IL10, TLR4, and CAT had the highest priority in the development of comorbidity of these two diseases. Additionally, it was revealed that the list of top genes is enriched with apoptotic genes and genes involved in biological processes related to the functioning of central nervous system.

CONCLUSIONS

The application of methods of reconstruction and analysis of gene networks is a productive tool for studying the molecular mechanisms of comorbid conditions. The method put forth to rank genes by their importance to the comorbid condition of asthma and hypertension was employed that resulted in prediction of 10 genes, playing the key role in the development of the comorbid condition. The results can be utilised to plan experiments for identification of novel candidate genes along with searching for novel pharmacological targets.

FunGeneNet: a web tool to estimate enrichment of functional interactions in experimental gene sets

Background

Estimation of functional connectivity in gene sets derived from genome-wide or other biological experiments is one of the essential tasks of bioinformatics. A promising approach for solving this problem is to compare gene networks built using experimental gene sets with random networks. One of the resources that make such an analysis possible is CrossTalkZ, which uses the FunCoup database. However, existing methods, including CrossTalkZ, do not take into account individual types of interactions, such as protein/protein interactions, expression regulation, transport regulation, catalytic reactions, etc., but rather work with generalized types characterizing the existence of any connection between network members.

Results

We developed the online tool FunGeneNet, which utilizes the ANDSystem and STRING to reconstruct gene networks using experimental gene sets and to estimate their difference from random networks. To compare the reconstructed networks with random ones, the node permutation algorithm implemented in CrossTalkZ was taken as a basis. To study the FunGeneNet applicability, the functional connectivity analysis of networks constructed for gene sets involved in the Gene Ontology biological processes was conducted. We showed that the method sensitivity exceeds 0.8 at a specificity of 0.95. We found that the significance level of the difference between gene networks of biological processes and random networks is determined by the type of connections considered between objects. At the same time, the highest reliability is achieved for the generalized form of connections that takes into account all the individual types of connections. By taking examples of the thyroid cancer networks and the apoptosis network, it is demonstrated that key participants in these processes are involved in the interactions of those types by which these networks differ from random ones.

Conclusions

FunGeneNet is a web tool aimed at proving the functionality of networks in a wide range of sizes of experimental gene sets, both for different global networks and for different types of interactions. Using examples of thyroid cancer and apoptosis networks, we have shown that the links over-represented in the analyzed network in comparison with the random ones make possible a biological interpretation of the original gene/protein sets. The FunGeneNet web tool for assessment of the functional enrichment of networks is available at http://www-bionet.sscc.ru/fungenenet/.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4474-7) contains supplementary material, which is available to authorized users.

Risk factors for preeclampsia in infertile Chinese women with polycystic ovary syndrome: A prospective cohort study

To explore preconception risk factors for preeclampsia (PE) in women with polycystic ovary syndrome (PCOS), a prospective cohort study was conducted in 92 infertile Chinese women with PCOS who had a singleton pregnancy by ovulation induction and were followed up for 6 weeks after delivery. The patients underwent assessment of physical, endocrine, and metabolic features before ovulation induction. Fifteen (16.3%) patients were diagnosed with PE. Logistic regression analysis showed that preconception sex hormone–binding globulin (SHBG), insulin level at 120 minutes, and body mass index were three independent risk factors for PE (odds ratio [OR], 0.981; 95% confidence interval [CI], 0.964–0.998 [P=.027]; OR, 1.011; 95% CI, 1.000–1.021 [P=.048]; and OR, 1.249; 95% CI, 0.992–1.572 [P=.059], respectively). Receiver operator characteristic analysis indicated the risk value of prepregnancy SHBG, insulin level at 120 minutes, and body mass index (area under the curve=.788, .686, and .697, respectively). Preconception low SHBG levels, overweight/obesity, and hyperinsulinism might be correlated with the subsequent development of PE in patients with PCOS.

Novel tuberculosis susceptibility candidate genes revealed by the reconstruction and analysis of associative networks

Tuberculosis (TB) is a common infectious disease caused by M. tuberculosis. The risk of the disease is dependent on complex interactions between host genetics and environmental factors. Accumulated genomic data, along with novel methodological approaches such as associative networks, facilitate studies into the inherited basis of TB. In the current study, we carried out the reconstruction and analysis of an associative network representing molecular interactions between proteins and genes associated with TB. The network predominantly comprises of well-studied key proteins and genes which are able to govern the immune response against M. tuberculosis. However, this approach also allowed us to reveal 12 proteins encoded by genes, the polymorphisms of which have never been studied in relation to M. tuberculosis infection. These proteins include surface antigens (CD4, CD69, CD79, CD80, MUC16) and other important components of the immune response, inflammation, pathogen recognition, cell migration and activation (HCST, ADA, CP, SPP1, CXCR4, AGER, PACRG). Thus, the associative network approach enables the discovery of new candidate genes for TB susceptibility.

Placental microRNA expression in pregnancies complicated by superimposed pre‑eclampsia on chronic hypertension

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.

MOLECULAR GENETIC STUDIES OF COMORBIDITY

This review focuses at the problem of the genetic basis of comorbidity. We discuss the concepts and terms relating to combinations of diseases. The guidelines of the study of comorbidity using modern high throughput methods and approaches of genetics, molecular biology and bioinformatics are designated. In this review we present results of studies showing genetic specificity for the combined phenotypes dif-ferent from the isolated disease, we considergene-gene and gene-environment interactions in comorbidity. We also discuss the role of single nucleotide polymorphisms and structural genome variations in the development of comorbidity. Own results of researching shared genes of inversely comorbid diseases like as bronchial asthma and tuberculosis are presented.

Prediction of tissue-specific effects of gene knockout on apoptosis in different anatomical structures of human brain

BACKGROUND

An important issue in the target identification for the drug design is the tissue-specific effect of inhibition of target genes. The task of assessing the tissue-specific effect in suppressing gene activity is especially relevant in the studies of the brain, because a significant variability in gene expression levels among different areas of the brain was well documented.

RESULTS

A method is proposed for constructing statistical models to predict the potential effect of the knockout of target genes on the expression of genes involved in the regulation of apoptosis in various brain regions. The model connects the expression of the objective group of genes with expression of the target gene by means of machine learning models trained on available expression data. Information about the interactions between target and objective genes is determined by reconstruction of target-centric gene network. STRING and ANDSystem databases are used for the reconstruction of gene networks. The developed models have been used to analyse gene knockout effects of more than 7,500 target genes on the expression of 1,900 objective genes associated with the Gene Ontology category "apoptotic process". The tissue-specific effect was calculated for 12 main anatomical structures of the human brain. Initial values of gene expression in these anatomical structures were taken from the Allen Brain Atlas database. The results of the predictions of the effect of suppressing the activity of target genes on apoptosis, calculated on average for all brain structures, were in good agreement with experimental data on siRNA-inhibition.

CONCLUSIONS

This theoretical paper presents an approach that can be used to assess tissue-specific gene knockout effect on gene expression of the studied biological process in various structures of the brain. Genes that, according to the predictions of the model, have the highest values of tissue-specific effects on the apoptosis network can be considered as potential pharmacological targets for the development of drugs that would potentially have strong effect on the specific area of the brain and a much weaker effect on other brain structures. Further experiments should be provided in order to confirm the potential findings of the method.