Chronic Chagas' disease cardiomyopathy is a leading cause of congestive heart failure in Latin America, affecting more than 3 million people. Chagas' cardiomyopathy is more aggressive than other cardiomyopathies, but little is known of the molecular mechanisms responsible for its severity. We characterized gene expression profiles of human Chagas' cardiomyopathy and dilated cardiomyopathy to identify selective disease pathways and potential therapeutic targets. Both our customized cDNA microarray (Cardiochip) and real-time reverse transcriptase-polymerase chain reaction analysis showed that immune response, lipid metabolism, and mitochondrial oxidative phosphorylation genes were selectively up-regulated in myocardial tissue of the tested Chagas' cardiomyopathy patients. Interferon (IFN)-gamma-inducible genes represented 15% of genes specifically up-regulated in Chagas' cardiomyopathy myocardial tissue, indicating the importance of IFN-gamma signaling. To assess whether IFN-gamma can directly modulate cardio-myocyte gene expression, we exposed fetal murine cardiomyocytes to IFN-gamma and the IFN-gamma-inducible chemokine monocyte chemoattractant protein-1. Atrial natriuretic factor expression increased 15-fold in response to IFN-gamma whereas combined IFN-gamma and monocyte chemoattractant protein-1 increased atrial natriuretic factor expression 400-fold. Our results suggest IFN-gamma and chemokine signaling may directly up-regulate cardiomyocyte expression of genes involved in pathological hypertrophy, which may lead to heart failure. IFN-gamma and other cytokine pathways may thus be novel therapeutic targets in Chagas' cardiomyopathy.

Recent advances have facilitated the use of blood-derived RNA to conduct genomic analyses of human diseases. This emerging technology represents a rigorous and convenient alternative to traditional tissue biopsy-derived RNA, as it allows for larger sample sizes, better standardization of technical procedures, and the ability to non-invasively profile human subjects. In the present pilot study, we have collected RNA from blood of patients diagnosed with schizophrenia or bipolar disorder (BPD), as well as normal control subjects. Using microarray analysis, we found that each disease state exhibited a unique expressed genome signature, allowing us to discriminate between the schizophrenia, BPD, and control groups. In addition, we validated changes in several potential biomarker genes for schizophrenia and BPD by RT-PCR, and some of these were found to code to chromosomal loci previously linked to schizophrenia. Linear and non-linear combinations of eight putative biomarker genes (APOBEC3B, ADSS, ATM, CLC, CTBP1, DATF1, CXCL1, and S100A9) were able to discriminate between schizophrenia, BPD, and control samples, with an overall accuracy of 95%-97% as indicated by receiver operating characteristic (ROC) curve analysis. We therefore propose that blood cell-derived RNA may have significant value for performing diagnostic functions and identifying disease biomarkers in schizophrenia and BPD.

Despite similar clinical endpoints, heart failure resulting from dilated cardiomyopathy (DCM) or hypertrophic cardiomyopathy (HCM) appears to develop through different remodeling and molecular pathways. Current understanding of heart failure has been facilitated by microarray technology. We constructed an in-house spotted cDNA microarray using 10,272 unique clones from various cardiovascular cDNA libraries sequenced and annotated in our laboratory. RNA samples were obtained from left ventricular tissues of precardiac transplantation DCM and HCM patients and were hybridized against normal adult heart reference RNA. After filtering, differentially expressed genes were determined using novel analyzing software. We demonstrated that normalization for cDNA microarray data is slide-dependent and nonlinear. The feasibility of this model was validated by quantitative real-time reverse transcription-PCR, and the accuracy rate depended on the fold change and statistical significance level. Our results showed that 192 genes were highly expressed in both DCM and HCM (e.g., atrial natriuretic peptide, CD59, decorin, elongation factor 2, and heat shock protein 90), and 51 genes were downregulated in both conditions (e.g., elastin, sarcoplasmic/endoplasmic reticulum Ca2+-ATPase). We also identified several genes differentially expressed between DCM and HCM (e.g., alphaB-crystallin, antagonizer of myc transcriptional activity, beta-dystrobrevin, calsequestrin, lipocortin, and lumican). Microarray technology provides us with a genomic approach to explore the genetic markers and molecular mechanisms leading to heart failure.

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