An introduction to genes, genomes and disease

Integrated Gene Expression Profiling Analysis Reveals Potential Molecular Mechanisms and Candidate Biomarkers for Early Risk Stratification and Prediction of STEMI and Post-STEMI Heart Failure Patients

Objective: To explore the molecular mechanism and search for the candidate differentially expressed genes (DEGs) with the predictive and prognostic potentiality that is detectable in the whole blood of patients with ST-segment elevation (STEMI) and those with post-STEMI HF. Methods: In this study, we downloaded GSE60993, GSE61144, GSE66360, and GSE59867 datasets from the NCBI-GEO database. DEGs of the datasets were investigated using R. Gene ontology (GO) and pathway enrichment were performed via ClueGO, CluePedia, and DAVID database. A protein interaction network was constructed via STRING. Enriched hub genes were analyzed by Cytoscape software. The least absolute shrinkage and selection operator (LASSO) logistic regression algorithm and receiver operating characteristics analyses were performed to build machine learning models for predicting STEMI. Hub genes for further validated in patients with post-STEMI HF from GSE59867. Results: We identified 90 upregulated DEGs and nine downregulated DEGs convergence in the three datasets (|log₂FC| ≥ 0.8 and adjusted p < 0.05). They were mainly enriched in GO terms relating to cytokine secretion, pattern recognition receptors signaling pathway, and immune cells activation. A cluster of eight genes including ITGAM, CLEC4D, SLC2A3, BST1, MCEMP1, PLAUR, GPR97, and MMP25 was found to be significant. A machine learning model built by SLC2A3, CLEC4D, GPR97, PLAUR, and BST1 exerted great value for STEMI prediction. Besides, ITGAM and BST1 might be candidate prognostic DEGs for post-STEMI HF. Conclusions: We reanalyzed the integrated transcriptomic signature of patients with STEMI showing predictive potentiality and revealed new insights and specific prospective DEGs for STEMI risk stratification and HF development.

Identification of time‑series differentially expressed genes and pathways associated with heart failure post‑myocardial infarction using integrated bioinformatics analysis

Heart failure (HF) secondary to acute myocardial infarction (AMI) is a public health concern. The current study aimed to investigate differentially expressed genes (DEGs) and their possible function in HF post-myocardial infarction. The GSE59867 dataset included microarray data from peripheral blood samples obtained from HF and non-HF patients following AMI at 4 time points (admission, discharge, and 1 and 6 months post-AMI). Time-series DEGs were analyzed using R Bioconductor. Functional enrichment analysis was performed, followed by analysis of protein-protein interactions (PPIs). A total of 108 DEGs on admission, 32 DEGs on discharge, 41 DEGs at 1 month post-AMI and 19 DEGs at 6 months post-AMI were identified. Among these DEGs, 4 genes were downregulated at all the 4 time points. These included fatty acid desaturase 2, leucine rich repeat neuronal protein 3, G-protein coupled receptor 15 and adenylate kinase 5. Functional enrichment analysis revealed that these DEGs were mainly enriched in ‘inflammatory response’, ‘immune response’, ‘toll-like receptor signaling pathway’ and ‘NF-κβ signaling pathway’. Furthermore, PPI network analysis revealed that C-X-C motif chemokine ligand 8 and interleukin 1β were hub genes. The current study identified candidate DEGs and pathways that may serve important roles in the development of HF following AMI. The results obtained in the current study may guide the development of novel therapeutic agents for HF following AMI.

Potential biomarkers of acute myocardial infarction based on weighted gene co-expression network analysis

BACKGROUND

Acute myocardial infarction (AMI) is the common cause of mortality in developed countries. The feasibility of whole-genome gene expression analysis to identify outcome-related genes and dysregulated pathways remains unknown. Molecular marker such as BNP, CRP and other serum inflammatory markers have got the notice at this point. However, these biomarkers exhibit elevated levels in patients with thyroid disease, renal failure and congestive heart failure. In this study, three groups of microarray data sets (GES66360, GSE48060, GSE29532) were collected from GEO, a total of 99, 52 and 55 samples, respectively. Weighted gene co-expression network analysis (WGCNA) was performed to obtain a classifier which composed of related genes that best characterize the AMI.

RESULTS

Here, this study obtained three groups of microarray data sets (GES66360, GSE48060, GSE29532) on AMI blood samples, a total of 99, 52 and 24 samples, respectively. In all, 4672 genes, 3185 genes, 3660 genes were identified in GSE66360, GSE48060, GSE60993 modules, respectively. We preformed WGCNA, GO and KEGG pathway enrichment analysis on these three data sets, finding function enrichment of the differential expression gene on inflammation and immune response. Transcriptome analysis were performed in AMI patients at four time points compared to CAD patients with no history of MI, to determine gene expression profiles and their possible changes during the recovery from myocardial infarction.

CONCLUSIONS

The results suggested that three overlapping genes (FGFBP2, GFOD1 and MLC1) between two modules could be a potential use of gene biomarkers for the diagnose of AMI.

Transcriptome analysis of peripheral blood mononuclear cells from chronic hepatitis B and hepatocellular carcinoma patients: a network-based attitude

Aim: The aim of the study was constructing a protein–protein interaction network for chronic hepatitis B (CHB) and hepatocellular carcinoma (HCC) patients. Materials & methods: Comprehensive gene expression profile of peripheral blood mononuclear cells of CHB and HCC were obtained from Gene Expression Omnibus/NCBI database. Differentially expressed genes (DEGs) of samples were analyzed using GEO2R web application. Results: The majority of DEGs in both CHB and HCC has been enriched in immune system responses. However, there was a significant disparity between the enrichment of these genes (especially genes associated with Toll-like receptor-and-TNF) in CHB-HCC compared with normal-CHB. Conclusion: The transcriptome properties of peripheral blood mononuclear cells are changed in patients with HBV-HCC. The immune response genes are the most deregulated genes in HCC patients.

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Gene expression profiling reveals potential prognostic biomarkers associated with the progression of heart failure

Background

Heart failure (HF) is the most common cause of morbidity and mortality in developed countries. Here, we identify biologically relevant transcripts that are significantly altered in the early phase of myocardial infarction and are associated with the development of post-myocardial infarction HF.

Methods

We collected peripheral blood samples from patients with ST-segment elevation myocardial infarction (STEMI): n = 111 and n = 41 patients from the study and validation groups, respectively. Control groups comprised patients with a stable coronary artery disease and without a history of myocardial infarction. Based on plasma NT-proBNP level and left ventricular ejection fraction parameters the STEMI patients were divided into HF and non-HF groups. Microarrays were used to analyze mRNA levels in peripheral blood mononuclear cells (PBMCs) isolated from the study group at four time points and control group. Microarray results were validated by RT-qPCR using whole blood RNA from the validation group.

Results

Samples from the first three time points (admission, discharge, and 1 month after AMI) were compared with the samples from the same patients collected 6 months after AMI (stable phase) and with the control group. The greatest differences in transcriptional profiles were observed on admission and they gradually stabilized during the follow-up. We have also identified a set of genes the expression of which on the first day of STEMI differed significantly between patients who developed HF after 6 months of observation and those who did not. RNASE1, FMN1, and JDP2 were selected for further analysis and their early up-regulation was confirmed in HF patients from both the study and validation groups. Significant correlations were found between expression levels of these biomarkers and clinical parameters. The receiver operating characteristic (ROC) curves indicated a good prognostic value of the genes chosen.

Conclusions

This study demonstrates an altered gene expression profile in PBMCs during acute myocardial infarction and through the follow-up. The identified gene expression changes at the early phase of STEMI that differentiated the patients who developed HF from those who did not could serve as a convenient tool contributing to the prognosis of heart failure.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-015-0149-z) contains supplementary material, which is available to authorized users.

Will global transcriptome analysis allow the detection of novel prognostic markers in coronary artery disease and heart failure?

Coronary artery disease (CAD) is one of the leading causes of death in the developed countries. Myocardial infarction (MI) is an acute episode of CAD that results in myocardial injury and subsequent heart failure (HF). In the acute phase of MI several risk factors for future cardiovascular events have been found. The molecular mechanisms of these disorders are still unknown, but altered gene expression may play an important role in the development and progression of cardiovascular diseases. High-throughput techniques should greatly facilitate the elucidation of the mechanisms and provide novel insights into the pathophysiology of cardiovascular diseases. In this review we focus on the perspectives of gene-expression profiling conducted on cardiac tissues and blood for the determination of novel diagnostic and prognostic markers and therapeutic targets.

ChiTaRS: a database of human, mouse and fruit fly chimeric transcripts and RNA-sequencing data

Chimeric RNAs that comprise two or more different transcripts have been identified in many cancers and among the Expressed Sequence Tags (ESTs) isolated from different organisms; they might represent functional proteins and produce different disease phenotypes. The ChiTaRS database of Chimeric Transcripts and RNA-Sequencing data (http://chitars.bioinfo.cnio.es/) collects more than 16 000 chimeric RNAs from humans, mice and fruit flies, 233 chimeras confirmed by RNA-seq reads and ∼2000 cancer breakpoints. The database indicates the expression and tissue specificity of these chimeras, as confirmed by RNA-seq data, and it includes mass spectrometry results for some human entries at their junctions. Moreover, the database has advanced features to analyze junction consistency and to rank chimeras based on the evidence of repeated junction sites. Finally, ‘Junction Search’ screens through the RNA-seq reads found at the chimeras’ junction sites to identify putative junctions in novel sequences entered by users. Thus, ChiTaRS is an extensive catalog of human, mouse and fruit fly chimeras that will extend our understanding of the evolution of chimeric transcripts in eukaryotes and can be advantageous in the analysis of human cancer breakpoints.

Attitudes of health care professionals toward pharmacogenetic testing

BACKGROUND

Pharmacogenetics has emerged as a new tool for the optimization of drug therapy. Although the pharmacogenetics concept was first recognized at least 50 years ago, clinical testing to determine pharmacogenetic traits is still relatively rare, and many hurdles are markedly slowing its development. There is a lot of literature and speculation about potential ethical challenges in genetic and pharmacogenetic testing, yet few researchers have actually examined the attitudes of health care professionals regarding the clinical application of these tests.

OBJECTIVE

In this article, we aim to review the current literature on health care professionals' perceptions of the role of pharmacogenetic data and describe the attitudes of medical students when faced with a clinical pharmacogenetic testing scenario.

METHODS

A group of 59 third-year medical students from the American University of Beirut Medical Center were asked to answer a questionnaire about pharmacogenetic testing after being exposed to a clinical scenario of a patient who was diagnosed with mild Alzheimer Disease (AD) and hence was a candidate for therapy with one of the acetylcholinesterase (AChE) inhibitors.

RESULTS

The students indicated that they would respect patients' confidentiality and inform them about the test results and therapeutic plan, but they would not be as open about bad prognoses. They did not agree on the therapeutic plan that would follow a pharmacogenetic test result and were uncertain about potential patient discrimination in insurability.

CONCLUSION

Our and others' findings demonstrate the existence and seriousness of several challenges pertaining to pharmacogenetic applications in the clinical setting. Further training and education are needed for health care professionals, since they are the ones who will most probably request these tests in the near future.

Optimizing anti-gene oligonucleotide 'Zorro-LNA' for improved strand invasion into duplex DNA

Zorro-LNA (Zorro) is a newly developed, oligonucleotide (ON)-based, Z-shaped construct with the potential of specific binding to each strand of duplex DNA. The first-generation Zorros are formed by two hybridized LNA/DNA mixmers (2-ON Zorros) and was hypothesized to strand invade. We have now established a method, which conclusively demonstrates that an LNA ON can strand invade into duplex DNA. To make Zorros smaller in size and easier to design, we synthesized 3′–5′–5′–3′ single-stranded Zorro-LNA (ssZorro) by using both 3′- and 5′-phosphoramidites. With ssZorro, a significantly greater extent and rate of double-strand invasion (DSI) was obtained than with conventional 2-ON Zorros. Introducing hydrophilic PEG-linkers connecting the two strands did not significantly change the rate or extent of DSI as compared to ssZorro with a nucleotide-based linker, while the longest alkyl-chain linker tested (36 carbons) resulted in a very slow DSI. The shortest alkyl-chain linker (3 carbons) did not reduce the extent of DSI of ssZorro, but significantly decreased the DSI rate. Collectively, ssZorro is smaller in size, easier to design and more efficient than conventional 2-ON Zorro in inducing DSI. Analysis of the chemical composition of the linker suggests that it could be of importance for future therapeutic considerations.

Proteomic profiling of cancer--opportunities, challenges, and context

The article by Roesch-Ely and colleagues in a recent issue of The Journal of Pathology describes the use of proteomic techniques to examine mucosal biopsies in patients with head and neck squamous cell cancer (HNSCC) and in corresponding control samples. The authors were able to determine the anatomical site of origin of the biopsies based on modelling of multiplex protein datasets, and to use the information to analyse field cancerization as a means of predicting tumour recurrence. Although the study included only a relatively small number of cases, and will require future validation in a larger patient cohort, the results point to the potential of proteomics to increase our understanding of cancer biology, and in this instance to offer clinical value.