Gamal Eldin Esmat Gamil

BACKGROUND/AIMS: A polymorphism in the microsomal triglyceride transfer protein (MTP) is associated with hepatic fibrosis, and carriers showed higher levels of steatosis, higher levels of hepatitis C virus (HCV) RNA and advanced fibrosis. The aim of this study was to study MTP expression pattern in HCV patients and impact of the MTP polymorphism on the response to antiviral therapy.

METHODS: One hundred consecutive naive HCV genotype 4 patients were recruited to receive antiviral therapy, and 40 control subjects were also recruited. Demographic, laboratory, and histopathology data were collected. DNA was isolated, and the samples were subjected to polymerase chain reaction analysis and genotyping for MTP by restriction fragment length polymorphism analysis.

RESULTS: Patients and controls were age- and sex-matched (male/female, 56/44, age, 39.2±7.8 years for patients with HCV; male/female, 18/22, age, 38.1±8.1 years for controls). MTP single nucleotide polymorphisms (SNPs) (GG, GT, TT) and alleles (G, T) in the patients versus the controls were 70%, 21%, 9% & 80.5%, 19.5% versus 10%, 87.5%, 2.5% & 53.8%, 46.3%, respectively (p=0.0001). The sustained viral response (SVR) of the patients was 60%. SNPs in MTP genotypes (GG, GT, and TT) and alleles (G and T) in the responders and nonresponders were 71.7%, 25%, 3.3% & 84.2%, 15.8% versus 67.5%, 15%, 17.5% & 75%, 25% (p=0.038 and p=0.109, respectively). A multivariate analysis showed that the GT genotype was an independent predictor of SVR (area under the curve 90% and p=0.0001).

CONCLUSIONS: MTP could be a new predictor for SVR to antiviral therapy in patients with HCV genotype 4 infection.

Staging of liver fibrosis is an integral part of the management of HCV. Liver biopsy is hampered by its invasiveness and possibility of sampling error. Current noninvasive methods are disadvantaged by their cost and complexity. In this study, we aimed at developing a noninvasive method for the staging of liver fibrosis based only on routine laboratory tests and clinical data. Basic clinical and laboratory data and liver biopsies were collected from 994 patients presenting for the evaluation of HCV. Logistic regression was used to create a model predictive of fibrosis stages. A sequential test was then developed by combining our new model with APRI. In the training set (497) a model was created by logistic regression for the prediction of significant fibrosis (≥F2), it included platelets, AST and age (PLASA). The areas under the curve (AUC), sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were 0.753, 66.8, 71.4, 69.8, 68.4, respectively, while in the validation set (497), they were 0.777, 66.7, 72.8, 68.6 and 71, respectively. These were the best performance indicators when compared to APRI, FIB-4, King's score, platelets, fibrosis index, age-platelet index and Lok index in the same set of patients. A sequential test was then developed including APRI followed by PLASA [Cairo University Fibrosis Assessment (CUFA) algorithm], this allowed saving 20% and 34% of liver biopsies for patients being tested for significant fibrosis and cirrhosis, respectively. In conclusion, the CUFA algorithms at no cost allow saving a significant proportion of patients from performing a liver biopsy or a more complex costly test. These algorithms could be used as the first step in the assessment of liver fibrosis before embarking on the more costly advanced serum markers, Fibroscan or liver biopsy.