Human leukocyte antigen-DQ beta 1 chain (DQB1) gene polymorphisms are associated with dilated cardiomyopathy: a systematic review and meta-analysis

Differential leucocyte RNA expression in the coronary arteries compared to systemic circulation discriminates between patients with and those without coronary artery disease

AIMS

To test the hypothesis that the pattern of gene expression in circulating leukocytes may differ between vascular compartments, depending on the presence or absence of atherosclerosis, we evaluated the regional vascular differences in patterns of inflammatory cell activation.

METHODS

Patients (n=8) with angiographically-established coronary artery disease (CAD+) and 8 without (CAD-) had blood samples taken from a peripheral vein as well as from left and right coronary arteries. Samples were pooled resulting in 4 CAD+ samples versus 4 CAD- samples and hybridised to a Whole Human Genome Microarray 4×44K.

RESULTS

CAD- patients had a similar gene expression profile across the different sites. CAD+ patients had statistically significant different gene expression patterns in venous vs. right and left coronary artery compartments. The expression pattern observed in the right coronary was where the most differences in gene expression were observed in CAD+ vs. CAD- patients. Overall, 1964 genes were differentially expressed between CAD+ and CAD-. Of these, 1052 were less expressed in CAD+ and 912 were more expressed in CAD+. Up to 12 of the 20 most differentially expressed genes appeared to reflect different phases of the atherosclerosis process: endothelial dysfunction, lipid accumulation, and smooth muscle cell proliferation.

CONCLUSIONS

Gene expression of circulating leukocytes differentiates CAD+ from CAD- patients. Gene expression is significantly different between coronary arteries and the systemic circulation in CAD+ patients, but not in CAD- patients. Gene expression is significantly different between CAD+ and CAD- subjects, and appears to reflect the atherosclerosis process. These intra-individual differences may be an additional feature of established coronary artery disease.

Pathway-based variant enrichment analysis on the example of dilated cardiomyopathy

Genome-wide association (GWA) studies have significantly contributed to the understanding of human genetic variation and its impact on clinical traits. Frequently only a limited number of highly significant associations were considered as biologically relevant. Increasingly, network analysis of affected genes is used to explore the potential role of the genetic background on disease mechanisms. Instead of first determining affected genes or calculating scores for genes and performing pathway analysis on the gene level, we integrated both steps and directly calculated enrichment on the genetic variant level. The respective approach has been tested on dilated cardiomyopathy (DCM) GWA data as showcase. To compute significance values, 5000 permutation tests were carried out and p values were adjusted for multiple testing. For 282 KEGG pathways, we computed variant enrichment scores and significance values. Of these, 65 were significant. Surprisingly, we discovered the "nucleotide excision repair" and "tuberculosis" pathways to be most significantly associated with DCM (p = 10(-9)). The latter pathway is driven by genes of the HLA-D antigen group, a finding that closely resembles previous discoveries made by expression quantitative trait locus analysis in the context of DCM-GWA. Next, we implemented a sub-network-based analysis, which searches for affected parts of KEGG, however, independent on the pre-defined pathways. Here, proteins of the contractile apparatus of cardiac cells as well as the FAS sub-network were found to be affected by common polymorphisms in DCM. In this work, we performed enrichment analysis directly on variants, leveraging the potential to discover biological information in thousands of published GWA studies. The applied approach is cutoff free and considers a ranked list of genetic variants as input.

Systems analysis of gene ontology and biological pathways involved in post-myocardial infarction responses

Background

Pathway analysis has been widely used to gain insight into essential mechanisms of the response to myocardial infarction (MI). Currently, there exist multiple pathway databases that organize molecular datasets and manually curate pathway maps for biological interpretation at varying forms of organization. However, inconsistencies among different databases in pathway descriptions, frequently due to conflicting results in the literature, can generate incorrect interpretations. Furthermore, although pathway analysis software provides detailed images of interactions among molecules, it does not exhibit how pathways interact with one another or with other biological processes under specific conditions.

Methods

We propose a novel method to standardize descriptions of enriched pathways for a set of genes/proteins using Gene Ontology terms. We used this method to examine the relationships among pathways and biological processes for a set of condition-specific genes/proteins, represented as a functional biological pathway-process network. We applied this algorithm to a set of 613 MI-specific proteins we previously identified.

Results

A total of 96 pathways from Biocarta, KEGG, and Reactome, and 448 Gene Ontology Biological Processes were enriched with these 613 proteins. The pathways were represented as Boolean functions of biological processes, delivering an interactive scheme to organize enriched information with an emphasis on involvement of biological processes in pathways. We extracted a network focusing on MI to demonstrate that tyrosine phosphorylation of Signal Transducer and Activator of Transcription (STAT) protein, positive regulation of collagen metabolic process, coagulation, and positive/negative regulation of blood coagulation have immediate impacts on the MI response.

Conclusions

Our method organized biological processes and pathways in an unbiased approach to provide an intuitive way to identify biological properties of pathways under specific conditions. Pathways from different databases have similar descriptions yet diverse biological processes, indicating variation in their ability to share similar functional characteristics. The coverages of pathways can be expanded with the incorporation of more biological processes, predicting involvement of protein members in pathways. Further, detailed analyses of the functional biological pathway-process network will allow researchers and scientists to explore critical routes in biological systems in the progression of disease.

Association of tumor necrosis factor-α gene G-308A polymorphism with dilated cardiomyopathy: a meta-analysis

Published data on the association between tumor necrosis factor-α (TNF-α) G-308A gene polymorphism and dilated cardiomyopathy (DCM) risk are inconclusive. To clarify the association of TNF-α G-308A gene polymorphism and DCM, a meta-analysis of case-control studies was performed. Some databases, such as PubMed and Embase, were searched to indentify related studies. Search terms included dilated cardiomyopathy, tumor necrosis factor-alpha or TNF-α or TNF alpha or tumor necrosis factor alpha, and polymorphism or mutation. Eight case-control studies involving 1487 DCM cases and 1734 normal controls were included in the meta-analysis to assess the purported association between the TNF-α G-308A gene polymorphism and the risk of DCM. A dominant genetic model was used and the comparison of GA/AA genotype versus GG genotype was performed in the present meta-analysis. The odds ratio was 1.42 (95% confidence interval: 1.05, 1.93, P=0.02), manifesting frequency of the TNF-α-308 GA/AA genotype was higher in DCM patients than the control group. TNF-α G-308A nucleotide transition might be associated with the risk of DCM.