Activated complement protein C5a does not affect brain-derived endothelial cell viability and zonula occludens-1 levels following oxygen-glucose deprivation

BACKGROUND AND PURPOSE:

Ischemic brain injury induces both functional and structural disarray affecting the blood–brain barrier (BBB) which in return aggravates stroke outcomes. Complement system and its bioactive proteins are important molecular responders to ischemia. C5a protein along with its receptor C5a receptor 1 is a key component of this system with potent pro-inflammatory and chemoattractant properties. The purpose of this study is to investigate the role of C5a protein and its receptor which are believed to participate in the inflammatory response that follows ischemic insult.

MATERIALS AND METHODS:

To mimic an ischemic in vivo event in which C5a may contact brain endothelial cells after injury, we studied oxygen-glucose deprivation (OGD) followed by reperfusion in brain microvascular endothelial cells (b.End. 3) by only added C5a at the time of reperfusion. Cell death and viability were estimated by trypan blue and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assays, respectively. Tight junction protein zonula occluden (ZO-1) levels were analyzed by Western blot analysis, and nitric oxide (NO) was assessed using the Griess reagent.

RESULTS:

Brain-derived endothelial cell was susceptible to OGD-induced injury in a duration-dependent manner as was the presence of ZO-1 protein. However, the addition of C5a protein had no notable effects even when used at high concentrations up to 100 nM. While OGD led to reduction in ZO-1 protein levels, no change was seen following the addition of C5a. Finally, OGD led unexpectedly to small decreases in NO generation, but this was again unaltered by C5a.

CONCLUSIONS:

Our study suggests that complement system protein C5a may not have a direct role in the disruption of BBB, following brain ischemia. This is in contrary with previous literature that suggests a possible role of this protein in the inflammatory response to ischemia.

Analysis of Extracellular Vesicles Using Magnetic Nanoparticles in Blood of Patients with Acute Coronary Syndrome

Extracellular vesicles (EVs) are released from various cell types and play an important role in intercellular interactions. In our study, we investigated abundance of individual EVs in patients with acute forms of ischemic heart disease. Previously, we developed an approach for individual analysis of EVs conjugated with magnetic nanoparticles (MNPs), which was applied in the current study for analyzing phenotypic composition of EVs (by staining for markers CD31, CD41a, and CD63). EVs were isolated using fluorescently labeled MNPs containing anti-CD31, CD41a, or CD63 antibodies and analyzed by combining fluorescently labeled anti-CD41a and CD63, CD31 and CD63, or CD41a and CD31 antibodies, respectively. EVs were analyzed in 30 individuals: 17 healthy volunteers and 13 patients with acute coronary syndrome (ACS). Six and seven ACS patients were with acute myocardial infarction and unstable angina, respectively. It was found that patients with ACS and healthy volunteers contained a dominant subset of EVs expressing surface CD41a antigen, suggesting that they originated from platelets. In addition, the total number of EVs isolated using either of the surface markers examined in our study was higher in patients with ACS compared to healthy volunteers. The subgroup of patients with acute myocardial infarction was found to contain significantly higher number of blood EVs compared to the control group. Moreover, increased number of EVs in patients with ACS is mainly due to the increased number of EVs in the subset of EVs bearing CD41a. By analyzing individual EVs, we found that plasma of patients with ACS, particularly upon developing of myocardial infarction, contained dominant platelet-derived EVs fraction, which may reflect activation of platelets in such patients.

Characterization of BRCA1/2 mutations in patients with family history of breast cancer in Armenia

Background. Breast cancer is one of the most common cancers in women worldwide. The germline mutations of the BRCA1 and BRCA2 genes are the most significant and well characterized genetic risk factors for hereditary breast cancer. Intensive research in the last decades has demonstrated that the incidence of mutations varies widely among different populations. In this study we attempted to perform a pilot study for identification and characterization of mutations in BRCA1 and BRCA2 genes among Armenian patients with family history of breast cancer and their healthy relatives.  Methods. We performed targeted exome sequencing for BRCA1 and BRCA2 genes in 6 patients and their healthy relatives. After alignment of short reads to the reference genome, germline single nucleotide variation and indel discovery was performed using GATK software. Functional implications of identified variants were assessed using ENSEMBL Variant Effect Predictor tool.  Results. In total, 39 single nucleotide variations and 4 indels were identified, from which 15 SNPs and 3 indels were novel. No known pathogenic mutations were identified, but 2 SNPs causing missense amino acid mutations had significantly increased frequencies in the study group compared to the 1000 Genome populations.  Conclusions. Our results demonstrate the importance of screening of BRCA1 and BRCA2 gene variants in the Armenian population in order to identity specifics of mutation spectrum and frequencies and enable accurate risk assessment of hereditary breast cancers.

Synthesis, characterization and toxicity studies of pyridinecarboxaldehydes and L-tryptophan derived Schiff bases and corresponding copper (II) complexes

Schiff bases and their metal-complexes are versatile compounds exhibiting a broad range of biological activities and thus actively used in the drug development process. The aim of the present study was the synthesis and characterization of new Schiff bases and their copper (II) complexes, derived from L-tryptophan and isomeric (2-; 3-; 4-) pyridinecarboxaldehydes, as well as the assessment of their toxicity in vitro. The optimal conditions of the Schiff base synthesis resulting in up to 75-85% yield of target products were identified. The structure-activity relationship analysis indicated that the location of the carboxaldehyde group at 2-, 3- or 4-position with regard to nitrogen of the pyridine ring in aldehyde component of the L-tryptophan derivative Schiff bases and corresponding copper complexes essentially change the biological activity of the compounds. The carboxaldehyde group at 2- and 4-positions leads to the higher cytotoxic activity, than that of at 3-position, and the presence of the copper in the complexes increases the cytotoxicity. Based on toxicity classification data, the compounds with non-toxic profile were identified, which can be used as new entities in the drug development process using Schiff base scaffold.

Cartography of Pathway Signal Perturbations Identifies Distinct Molecular Pathomechanisms in Malignant and Chronic Lung Diseases

Lung diseases are described by a wide variety of developmental mechanisms and clinical manifestations. Accurate classification and diagnosis of lung diseases are the bases for development of effective treatments. While extensive studies are conducted toward characterization of various lung diseases at molecular level, no systematic approach has been developed so far. Here we have applied a methodology for pathway-centered mining of high throughput gene expression data to describe a wide range of lung diseases in the light of shared and specific pathway activity profiles. We have applied an algorithm combining a Pathway Signal Flow (PSF) algorithm for estimation of pathway activity deregulation states in lung diseases and malignancies, and a Self Organizing Maps algorithm for classification and clustering of the pathway activity profiles. The analysis results allowed clearly distinguish between cancer and non-cancer lung diseases. Lung cancers were characterized by pathways implicated in cell proliferation, metabolism, while non-malignant lung diseases were characterized by deregulations in pathways involved in immune/inflammatory response and fibrotic tissue remodeling. In contrast to lung malignancies, chronic lung diseases had relatively heterogeneous pathway deregulation profiles. We identified three groups of interstitial lung diseases and showed that the development of characteristic pathological processes, such as fibrosis, can be initiated by deregulations in different signaling pathways. In conclusion, this paper describes the pathobiology of lung diseases from systems viewpoint using pathway centered high-dimensional data mining approach. Our results contribute largely to current understanding of pathological events in lung cancers and non-malignant lung diseases. Moreover, this paper provides new insight into molecular mechanisms of a number of interstitial lung diseases that have been studied to a lesser extent.

Quantitative trait association study for mean telomere length in the South Asian genomes

MOTIVATION

Mean telomere length (MTL) is associated with cancers and age-related diseases, which necessitates identification of genomic and environmental factors that impact telomere length dynamics. Here, we present a pilot genome wide association (GWA) study for MTL in South Asian population using publicly available next generation whole genome sequences (WGS), both for MTL and genotype calculations.

RESULTS

MTL in the studied population was not correlated with age, which is in accordance with previous reports. Further, we identified that individuals with Sikh religion had longer telomeres, which may be the result of complex interaction between genetic background and environmental factors. Finally, we identified 51 MTL-associated SNPs residing in five loci. The top ones were located in ADARB2 gene, which has previously been implicated with extreme old age.

CONCLUSION

Our results show that WGS data can be used in telomere length studies. In addition, we introduce novel loci implicated in MTL that may be worth considering in further telomere studies.

CONTACT

aarakelyan@sci.am

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

PSFC: a Pathway Signal Flow Calculator App for Cytoscape

Cell signaling pathways are sequences of biochemical reactions that propagate an input signal, such as a hormone binding to a cell-surface receptor, into the cell to trigger a reactive process. Assessment of pathway activities is crucial for determining which pathways play roles in disease versus normal conditions. To date various pathway flow/perturbation assessment tools are available, however they are constrained to specific algorithms and specific data types. There are no accepted standards for evaluation of pathway activities or simulation of flow propagation events in pathways, and the results of different software are difficult to compare. Here we present Pathway Signal Flow Calculator (PSFC), a Cytoscape app for calculation of a pathway signal flow based on the pathway topology and node input data. The app provides a rich framework for customization of different signal flow algorithms to allow users to apply various approaches within a single computational framework.

PSFC: a Pathway Signal Flow Calculator App for Cytoscape

Cell signaling pathways are sequences of biochemical reactions that propagate an input signal, such as a hormone binding to a cell-surface receptor, into the cell to trigger a reactive process. Assessment of pathway activities is crucial for determining which pathways play roles in disease versus normal conditions. To date various pathway flow/perturbation assessment tools are available, however they are constrained to specific algorithms and specific data types. There are no accepted standards for evaluation of pathway activities or simulation of flow propagation events in pathways, and the results of different software are difficult to compare. Here we present Pathway Signal Flow Calculator (PSFC), a Cytoscape app for calculation of a pathway signal flow based on the pathway topology and node input data. The app provides a rich framework for customization of different signal flow algorithms to allow users to apply various approaches within a single computational framework.

Time-course human urine proteomics in space-flight simulation experiments

BACKGROUND

Long-term space travel simulation experiments enabled to discover different aspects of human metabolism such as the complexity of NaCl salt balance. Detailed proteomics data were collected during the Mars105 isolation experiment enabling a deeper insight into the molecular processes involved.

RESULTS

We studied the abundance of about two thousand proteins extracted from urine samples of six volunteers collected weekly during a 105-day isolation experiment under controlled dietary conditions including progressive reduction of salt consumption. Machine learning using Self Organizing maps (SOM) in combination with different analysis tools was applied to describe the time trajectories of protein abundance in urine. The method enables a personalized and intuitive view on the physiological state of the volunteers. The abundance of more than one half of the proteins measured clearly changes in the course of the experiment. The trajectory splits roughly into three time ranges, an early (week 1-6), an intermediate (week 7-11) and a late one (week 12-15). Regulatory modes associated with distinct biological processes were identified using previous knowledge by applying enrichment and pathway flow analysis. Early protein activation modes can be related to immune response and inflammatory processes, activation at intermediate times to developmental and proliferative processes and late activations to stress and responses to chemicals.

CONCLUSIONS

The protein abundance profiles support previous results about alternative mechanisms of salt storage in an osmotically inactive form. We hypothesize that reduced NaCl consumption of about 6 g/day presumably will reduce or even prevent the activation of inflammatory processes observed in the early time range of isolation. SOM machine learning in combination with analysis methods of class discovery and functional annotation enable the straightforward analysis of complex proteomics data sets generated by means of mass spectrometry.

CyKEGGParser: tailoring KEGG pathways to fit into systems biology analysis workflows

The KEGG pathway database is a widely accepted source for biomolecular pathway maps. In this paper we present the CyKEGGParser app ( http://apps.cytoscape.org/apps/cykeggparser) for Cytoscape 3 that allows manipulation with KEGG pathway maps. Along with basic functionalities for pathway retrieval, visualization and export in KGML and BioPAX formats, the app provides unique features for computer-assisted adjustment of inconsistencies in KEGG pathway KGML files and generation of tissue- and protein-protein interaction specific pathways. We demonstrate that using biological context-specific KEGG pathways created with CyKEGGParser makes systems biology analysis more sensitive and appropriate compared to original pathways.

Gene Set- and Pathway- Centered Knowledge Discovery Assigns Transcriptional Activation Patterns in Brain, Blood, and Colon Cancer

Genome-wide ‘omics'-assays provide a comprehensive view on the molecular landscapes of healthy and diseased cells. Bioinformatics traditionally pursues a ‘gene-centered' view by extracting lists of genes differentially expressed or methylated between healthy and diseased states. Biological knowledge mining is then performed by applying gene set techniques using libraries of functional gene sets obtained from independent studies. This analysis strategy neglects two facts: (i) that different disease states can be characterized by a series of functional modules of co-regulated genes and (ii) that the topology of the underlying regulatory networks can induce complex expression patterns that require analysis methods beyond traditional genes set techniques. The authors here provide a knowledge discovery method that overcomes these shortcomings. It combines machine learning using self-organizing maps with pathway flow analysis. It extracts and visualizes regulatory modes from molecular omics data, maps them onto selected pathways and estimates the impact of pathway-activity changes. The authors illustrate the performance of the gene set and pathway signal flow methods using expression data of oncogenic pathway activation experiments and of patient data on glioma, B-cell lymphoma and colorectal cancer.

Functional genetic polymorphisms of monocyte chemoattractant protein 1 and C-C chemokine receptor type 2 in ischemic stroke

Recent findings indicated that monocyte chemoattractant protein 1 (MCP1) and its C-C chemokine receptor type 2 (CCR2) play a key role in ischemic stroke (IS) progression. This study was aimed at evaluating the potential association of the MCP1 gene (MCP1) rs1024611 (-2518 A>G) and CCR2 gene (CCR2) rs1799864 (V64I; 190 G>A) functional single nucleotide polymorphisms (SNPs) with IS in the Armenian population. For the purpose of this study, genomic DNA samples of 100 patients with the first-episode IS and 115 healthy subjects (controls) were genotyped for the selected SNPs using a polymerase chain reaction with sequence-specific primers. The results obtained demonstrated that while the CCR2 rs1799864 SNP genotypes were equally distributed among patients and controls, the frequency and carriage rate of the of the MCP1 rs1024611*G minor allele were higher in patients. While a potential association between IS and CCR2 rs1799864 SNP was evaluated for the first time, the latest finding was in agreement with the earlier data reported for some other populations. In summary, this study revealed no association of CCR2 rs1799864 SNP with IS, and a positive association between G minor allele of MCP1 rs1024611 SNP and IS in the Armenian population. Based on the present and earlier reported data, we concluded that the minor G allele of the MCP1 rs1024611 SNP might be considered a risk factor for IS.

Normalizing to GADPH jeopardises correct quantification of gene expression in ovarian tumours - IPO8 and RPL4 are reliable reference genes

Background

To ensure a correct interpretation of results obtained with quantitative real-time reverse transcription-polymerase chain reaction (RT-qPCR), it is critical to normalize to a reference gene with stable mRNA expression in the tissue of interest. GADPH is widely used as a reference gene in ovarian tumour studies, although lacking tissue-specific stability. The aim of this study was to identify alternative suitable reference genes for RT-qPCR studies on benign, borderline, and malignant ovarian tumours.

Methods

We assayed mRNA levels for 13 potential reference genes – ABL1, ACTB, CDKN1A, GADPH, GUSB, HPRT1, HSP90AB, IPO8, PPIA, RPL30, RPL4, RPLPO, and TBP –with RT-qPCR in 42 primary ovarian tumours, using commercially pre-designed RT-qPCR probes. Expression stability was subsequently analysed with four different statistical programs (GeNorm, NormFinder, BestKeeper, and the Equivalence test).

Results

Expression of IPO8, RPL4, TBP, RPLPO, and ACTB had the least variation in expression across the tumour samples according to GeNorm, NormFinder, and BestKeeper. The Equivalence test found variation in expression within a 3-fold expression change between tumour groups for: IPO8, RPL40, RPL30, GUSB, TBP, RPLPO, ACTB, ABL1, and CDKN1A. However, only IPO8 satisfied at a 2-fold change as a cut-off. Overall, IPO8 and RPL4 had the highest, whereas GADPH and HPRT1 the lowest expression stability. Employment of suitable reference genes (IPO8, RPL4) in comparison with unsuitable ones (GADPH, HPRT1), demonstrated divergent influence on the mRNA expression pattern of our target genes − GPER and uPAR.

Conclusions

We found IPO8 and RPL4 to be suitable reference genes for normalization of target gene expression in benign, borderline, and malignant ovarian tumours. Moreover, IPO8 can be recommended as a single reference gene. Neither GADPH nor HPRT1 should be used as reference genes in studies on ovarian tumour tissue.

Tobacco and other factors have a negative impact on quality of life in hepatitis C patients

Hepatitis C virus (HCV) is known to adversely affect general, social, emotional and mental health domains. This study was designed to identify variables that may be associated with these measurable outcomes. We conducted a cross-sectional retrospective review of demographic and clinical data from 800 patients with HCV evaluated between January 1998 and November 2007. Data were collected using a standardized questionnaire filled out by the patients at the first encounter. Variables evaluated included fibrosis stages (i.e. FS0/1/2 vs FS3/4), demographics, comorbid health conditions, tobacco and alcohol use, high-risk social behaviours and laboratory data. Variables assessed were depression, fatigue, problems sleeping and loss of interest in sex. Statistical analysis was performed using univariate and multivariate logistic regression. Depression (29.3%) in our HCV study population was associated with female gender, tobacco use, hyperlipidemia, history of heavy alcohol use and intravenous drug use. Fatigue (44.6%) was associated with end-stage renal disease, past and current tobacco use and current alcohol use. Difficulty sleeping (13.8%) was associated with past and current tobacco use, current alcohol use and diabetes. Loss of interest in sex (7.7%) was associated with current tobacco use, multiple risk factors for HCV and age at time of evaluation. Fibrosis stage (FS) also had a significant positive association with alcohol use (OR 2.61; P = 0.003) and tobacco use (OR 2.00; P = 0.002). Smoking and alcohol use have a significant negative impact on the presence of depression, fatigue, difficulty sleeping and loss of interest in sex in HCV patients. Practitioners should be aware of these associations, particularly tobacco use, which significantly and negatively impacted every variable evaluated.

Association of C1QB gene polymorphism with schizophrenia in Armenian population

Background

Schizophrenia is a complex, multifactorial psychiatric disorder. Our previous findings indicated that altered functional activity of the complement system, a major mediator of the immune response, is implicated in the pathogenesis of schizophrenia. In order to explore whether these alterations are genetically determined or not, in the present study we evaluated the possible association of complement C1Q component gene variants with susceptibility to schizophrenia in Armenian population, focusing on four frequent single nucleotide polymorphisms (SNPs) of C1QA and C1QB genes.

Methods

In the present study four SNPs of the complement C1Q component genes (C1QA: rs292001, C1QB rs291982, rs631090, rs913243) were investigated in schizophrenia-affected and healthy subjects. Unrelated Caucasian individuals of Armenian nationality, 225 schizophrenic patients and the same number of age- and sex-matched healthy subjects, were genotyped. Genotyping was performed using polymerase chain reaction with sequence-specific primers (PCR-SSP) and quantitative real-time (qRT) PCR methods.

Results

While there was no association between C1QA rs292001, C1QB rs913243 and rs631090 genetic variants and schizophrenia, the C1QB rs291982*G minor allele was significantly overrepresented in schizophrenic patients (G allele frequency 58%) when compared to healthy subjects (46%, OR = 1.64, p_corr = 0.0008). Importantly, the susceptibility for schizophrenia was particularly associated with C1QB rs291982 GG genotype (OR = 2.5, p_corrected = 9.6E-5).

Conclusions

The results obtained suggest that C1QB gene may be considered as a relevant candidate gene for susceptibility to schizophrenia, and its rs291982*G minor allele might represent a risk factor for schizophrenia at least in Armenian population. Replication in other centers/populations is necessary to verify this conclusion.

Functional characterization of the complement receptor type 1 and its circulating ligands in patients with schizophrenia

BACKGROUND

Whereas the complement system alterations contribute to schizophrenia, complement receptors and regulators are little studied. We investigated complement receptor type 1 (CR1) expression on blood cells, the levels of circulating immune complexes (CIC) containing ligands of CR1, C1q complement protein and fragments of C3 complement protein (C1q-CIC, C3d-CIC), and CR1 C5507G functional polymorphism in schizophrenia patients and controls.

RESULTS

We found an increased C1q-CIC level and CR1 expression on blood cells, elevated number of CR1 positive erythrocytes and reduced number of CR1 positive lymphocytes and monocytes in patients compared to controls. No difference in the levels of C3d-CIC between groups was observed. Higher CR1 expression on erythrocytes in CC genotype versus CG+GG for both groups was detected, whereas no difference was observed for other cell populations. Our results indicated that schizophrenia is associated with the increased CR1 expression and C1q-CIC level.

CONCLUSIONS

Our study for the first time indicated that schizophrenia is associated with the increased CR1 expression and C1q-CIC level. Further studies in other ethnic groups are needed to replicate these findings.

Genetic variants of the inflammatory C-reactive protein and schizophrenia in Armenian population: a pilot study

C-reactive protein (CRP) is an inflammation marker implicated in the pathogenesis of schizophrenia. To investigate association of the CRP rs1417938, rs1800947, rs1205 variants with susceptibility to schizophrenia 208 unrelated Armenians (103 patients and 105 healthy controls) were genotyped. In this pilot study, none of studied variants was associated with schizophrenia.

The CR1 C5507G polymorphism is not involved in susceptibility to idiopathic pulmonary fibrosis in two European populations

Idiopathic pulmonary fibrosis (IPF), a severe lung disease with unknown aetiology, is thought to have an important genetic component. Single nucleotide polymorphism, C5507G, of the complement receptor 1 (CR1) gene, which affects the number of CR1 molecules on erythrocytes, has been associated with susceptibility to IPF in a single European population. To replicate this finding, 53 Czech IPF patients with 203 Czech healthy control subjects and 70 English IPF patients with 149 English controls were investigated. In both populations, there were no significant differences in distribution of CR1 C5507G variants between IPF patients and their appropriate control groups. In conclusion, the association of the CR1 C5507G polymorphism with susceptibility to IPF was not reproducible in Czech and English populations.