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Identification of a predictive/prognostic genetic signature in Chagas cardiomyopathy: a systems biology approach (FAPESP/ANR-BLANC-BR-FR-CHAGAS)

Grant number: 16/11149-3
Support type:Research Grants - Visiting Researcher Grant - International
Duration: October 19, 2016 - November 08, 2016
Field of knowledge:Biological Sciences - Immunology
Principal Investigator:Edecio Cunha Neto
Grantee:Edecio Cunha Neto
Visiting researcher: Christophe Chevillard
Visiting researcher institution: Génétique et Immunologie des Maladies Parasitaires, France
Home Institution: Instituto do Coração Professor Euryclides de Jesus Zerbini (INCOR). Hospital das Clínicas da Faculdade de Medicina da USP (HCFMUSP). Secretaria da Saúde (São Paulo - Estado). São Paulo , SP, Brazil

Abstract

Chagas disease, caused by the protozoan Trypanosoma cruzi, affects ca. 15 million people. About 30% of Chagas disease patients develop Chronic Chagas disease cardiomyopathy (CCC), an particularly lethal inflammatory cardiomyopathy that occurs decades after the initial infection, while most patients remain asymptomatic (ASY;60%). Clinical severity in Chagas disease is correlated with the occurrence of myocarditis, and survival is worse than for that of non-inflammatory cardiomyopathy. CCC heart lesions present a Th1 T cell-rich myocarditis, with cardiomyocyte hypertrophy and prominent fibrosis. Data suggest that the myocarditis plays a major pathogenetic role in disease progression. Chagas thus remains a neglected disease, with no vaccines or anti-parasitic drugs proven efficient in chronically infected adults, when most patients are diagnosed. Development of effective drugs for CCC is hampered by the limited knowledge of Its pathogenesis. Familial aggregation of CCC cases, as well as the fact that only 30% of infected patients develop CCC, suggest there might be a genetic component to disease susceptibility. Moreover, previous case-control studies have identified some genes associated to human susceptibility to CCC.The outcome of Chagas disease is ultimately defined in the patients' hearts, a consequence of inflammation and myocardial tissue response. We thus hypothesize that expression of many pathogenetically relevant genes and proteins in the myocardial tissue of CCC patients is controlled by genetic polymorphisms. The corollary is that it may be possible to establish a host genetic signature with prognostic value based on such polymorphic genes. For that matter, we will use a systems biology approach to identify 1) genes/proteins that are differentially expressed in CCC myocardium 2) functional polymorphisms that may control their expression or function. This application is based on two independent aims. First, we will identify differentially expressed genes and proteins in the already available fresh-frozen CCC heart samples. Proteomic and transcriptomic analysis of such samples will allow identification of differentially expressed genes. Methylation analysis and miRNA profiling will be performed to "filter out" genes regulated by these two mechanisms (the characterization of such genes could be an application by itself). The resulting list will be targeted by the genetic approaches. The partners have previously engaged to enroll a large Brazilian chagasic population. So far we have DNA samples for 688 CCC and 253 ASY patients; our goal is to increase numbers to get a main cohort (700 CCC/400 ASY control subjects) and an independent replication cohort (300 CCC and 300 ASY subjects).The second objective is the identification of genetic variants associated to disease. The first approach is a case-control study based on common SNPs from the stongest candidate genes identified in Aim 1, where common Tag single nucleotide polymorphisms (SNP) will be genotyped using the Sequenom technology. We will also characterize multicase nuclear families (including two CCC and one ASY sibs) by exome sequencing, to identify rare functional variants shared only by the cases but not by the internal controls (ASY subjects); the partners have access to the families at an endemic area. This approach will benefit from the data analysis expertise of the second French partner. Univariate and multivariate analyses will be conducted to identify associated markers. Functional analyses will assess whether SNPs affect gene expression, function or protein structure. The identification of these marker sets will have a combined prognostic value for disease progression at the individual patient level, allowing close follow up and early treatment of those carrying high-risk genetic signatures. Moreover, this study will provide significant information to decipher mechanisms underlying chronic disease progression and to identify future therapeutic targets. (AU)