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Association of genetic variants with rapid fibrosis: progression after liver transplantation for hepatitis C. Layden JE1, Tayo BO, Cotler SJ, et al. Transplantation. 2014 May 27;97(10):1072-8. doi: 10.1097/01.TP.0000440953.06886.a3. BACKGROUND: Recurrence of hepatitis C, the main indication for liver transplantation in the United States, leads to rapid fibrosis progression and worse outcomes compared to other indications. While clinical variables play a role, they are insufficient to explain all inter-patient variability in posttransplant fibrosis progression. Genetic factors associated with hepatitis C virus (HCV) outcomes have been identified, but limited studies have been conducted in the context of HCV-related liver transplantation. Therefore, the purpose of this study was to examine candidate genes related to the immune response and rate of fibrosis in subjects undergoing liver transplantation for HCV. METHODS: One hundred twelve recipients with detailed posttransplant fibrosis and clinical information were genotyped using 25 single nucleotide variants (SNVs), including five SNVs within the IL28B gene region. Associations between SNVs and rapid fibrosis progression were performed controlling for pertinent clinical variables and haplotype analyses for the IL28B gene were completed. RESULTS: Significant multivariable associations were found for rs8099917 (IL28B), rs1991401 (DDX5), rs4969168 (SOC3), and rs7976497 (MLEC). The minor allele was protective against rapid fibrosis progression for the IL28B SNV (G allele), MLEC SNV (T allele), and DDX5 SNV (G allele). For the SOC3 SNV, the minor allele (A) increased the risk for rapid fibrosis progression. Additionally, two recipient haplotype structures for IL28B were significantly associated with rapid fibrosis progression. CONCLUSIONS: These findings indicate that recipient genetic factors play a role in posttransplant HCV-related fibrosis progression. Molecular studies of these pathways may elucidate the pathogenesis of posttransplant fibrosis progression and provide risk prediction markers.