Differential effects of donor and recipient IL28B and DDX58 SNPs on severity of HCV after liver transplantation.

BACKGROUND & AIMS: IL28B single nucleotide polymorphisms are strongly associated with spontaneous HCV clearance and treatment response in non-transplant populations. A DDX58 single nucleotide polymorphism is associated with the antiviral response of innate lymphocytes. We aimed at evaluating the associations of donor and recipient IL28B (rs12979860 and rs8099917) and DDX58 (rs10813831) genotypes with severity of HCV recurrence after liver transplantation. METHODS: In a case-control study of 523 liver transplantation recipients with HCV, we matched severe with mild recurrent HCV based on 2-year clinical and histologic follow-up. A total of 440 liver transplantation recipients (severe, n=235; mild, n=205) with recipient DNA and 225 (severe, n=123; mild, n=102) with both recipient and donor DNA were analyzed. RESULTS: IL28B [rs12979860, non-CC (vs. CC) and rs8099917, non-TT (vs. TT)] in the recipient-only analysis had higher risk of severe recurrent HCV [OR 1.57 and 1.58, p<0.05]. However, for the 225 with donor and recipient DNA, IL28B rs12979860 CC (vs. non-CC) and rs8099917 TT (vs. non-TT) and DDX58 rs10813831 non-GG (vs. GG) were associated with more (not less) severe recurrent HCV. The greatest risk of severe recurrent HCV was for rs12979860 CC donors in non-CC recipients (OR 7.02, p <0.001, vs. non-CC donor/recipient) and for rs8099917 TT donors in non-TT recipients (OR 5.78, p=0.001, vs. non-TT donor/recipient). These associations persisted after controlling for donor age, donor race, and donor risk index. CONCLUSIONS: IL28B and DDX58 single nucleotide polymorphisms that are favorable when present in the non-transplant setting or in the recipient are unfavorable when present in a donor liver graft.

Testing and estimating gene-environment interactions in family-based association studies.

We propose robust and efficient tests and estimators for gene-environment/gene-drug interactions in family-based association studies in which haplotypes, dichotomous/quantitative phenotypes, and complex exposure/treatment variables are analyzed. Using causal inference methodology, we show that the tests and estimators are robust against unmeasured confounding due to population admixture and stratification, provided that Mendel's law of segregation holds and that the considered exposure/treatment variable is not affected by the candidate gene under study. We illustrate the practical relevance of our approach by an application to a chronic obstructive pulmonary disease study. The data analysis suggests a gene-environment interaction between a single nucleotide polymorphism in the Serpine2 gene and smoking status/pack-years of smoking. Simulation studies show that the proposed methodology is sufficiently powered for realistic sample sizes and that it provides valid tests and effect size estimators in the presence of admixture and stratification.