| Grant number: | 16/19690-5 |
| Support Opportunities: | Regular Research Grants |
| Start date: | February 01, 2017 |
| End date: | January 31, 2019 |
| Field of knowledge: | Health Sciences - Medicine |
| Principal Investigator: | Mariana Cavalheiro Magri |
| Grantee: | Mariana Cavalheiro Magri |
| Host Institution: | Faculdade de Medicina (FM). Universidade de São Paulo (USP). São Paulo , SP, Brazil |
| City of the host institution: | São Paulo |
Abstract
Infection by hepatitis C virus (HCV) is recognized as the major cause of chronic liver disease worldwide. The progression of chronic hepatitis C to liver fibrosis involves several factors and may be influenced by host, viral and environmental factors. Among the metabolic factors there is the hepatic steatosis, which is characterized by the accumulation of triglycerides in hepatocytes, and is present in about 40% of patients. In the host, there are some genetic determinants such as single nucleotide polymorphisms (SNPs) in the gene of microsomal triglyceride transfer protein (MTTP). The SNPs in MTTP seems to play an important role in the regulation of gene expression and can alter the concentration of low density lipoproteins in plasma, such as VLDL, which can increase degradation of apoB-lipoprotein and result in the metabolic deregulation of hepatic lipids. It is not clear the relationship between MTTP SNPs and the susceptibility to hepatic steatosis in patients with HCV. Therefore, the MTTP SNPs -400A/T, -164T/C, Q/H95, I/T128, Q/E244 e H/Q297 were selected to be researched their presence and analyzed if they have influence on hepatic steatosis and on lipids levels in plasma in patients with chronic hepatitis C. Finally, to evaluate if they could be possible biomarkers for early detection of hepatic steatosis. The study is retrospective with biological samples collected from patients with chronic hepatitis C from the Clinical Hospital, School of Medicine, USP (HC-FMUSP). The SNPs will be detected by polymerase chain reaction - restriction fragment length polymorphism (PCR-RFLP) analysis. Univariate and multivariate analyzes will be performed. (AU)
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