Association of Liver Injury From Specific Drugs, or Groups of Drugs, With Polymorphisms in HLA and Other Genes in a Genome-Wide Association Study

BACKGROUND & AIMS: We performed a genome-wide association study (GWAS) to identify genetic risk factors for druginduced liver injury (DILI) from licensed drugs without previously reported genetic risk factors. METHODS: We performed a GWAS of 862 persons with DILI and 10,588 population-matched controls. The first set of cases was recruited before May 2009 in Europe (n = 137) and the United States (n = 274). The second set of cases were identified from May 2009 through May 2013 from international collaborative studies performed in Europe, the United States, and South America. For the GWAS, we included only cases with patients of European ancestry associated with a particular drug (but not flucloxacillin or amoxicillin-clavulanate). We used DNA samples from all subjects to analyze HLA genes and single nucleotide polymorphisms. After the discovery analysis was concluded, we validated our findings using data from 283 European patients with diagnosis of DILI associated with various drugs. RESULTS: We associated DILI with rs114577328 (a proxy for A* 33: 01 a HLA class I allele; odds ratio [OR], 2.7; 95% confidence interval [CI], 1.9 - 3.8; P = 2.4 x 10(-8)) and with rs72631567 on chromosome 2 (OR, 2.0; 95% CI, 1.6 - 2.5; P = 9.7 x 10(-9)). The association with A* 33: 01 was mediated by large effects for terbinafine-, fenofibrate-, and ticlopidine-related DILI. The variant on chromosome 2 was associated with DILI from a variety of drugs. Further phenotypic analysis indicated that the association between DILI and A* 33: 01 was significant genome wide for cholestatic and mixed DILI, but not for hepatocellular DILI; the polymorphism on chromosome 2 was associated with cholestatic and mixed DILI as well as hepatocellular DILI. We identified an association between rs28521457 (within the lipopolysaccharide-responsive vesicle trafficking, beach and anchor containing gene) and only hepatocellular DILI (OR, 2.1; 95% CI, 1.6 - 2.7; P = 4.8 x 10(-9)). We did not associate any specific drug classes with genetic polymorphisms, except for statin-associated DILI, which was associated with rs116561224 on chromosome 18 (OR, 5.4; 95% CI, 3.0 - 9.5; P = 7.1 x 10(-9)). We validated the association between A* 33: 01 terbinafine-and sertraline-induced DILI. We could not validate the association between DILI and rs72631567, rs28521457, or rs116561224. CONCLUSIONS: In a GWAS of persons of European descent with DILI, we associated HLA-A* 33: 01 with DILI due to terbinafine and possibly fenofibrate and ticlopidine. We identified polymorphisms that appear to be associated with DILI from statins, as well as 2 non-drug-specific risk factors.Peer reviewe

<em>HLA-DQA1-HLA-DRB1</em> variants confer susceptibility to pancreatitis induced by thiopurine immunosuppressants

Functional dependencies (FDs) specify the intended data semantics while violations of FDs indicate deviation from these semantics. In this paper, we study a data cleaning problem in which the FDs may not be completely correct, e.g., due to data evolution or incomplete knowledge of the data semantics. We argue that the notion of relative trust is a crucial aspect of this problem: if the FDs are outdated, we should modify them to fit the data, but if we suspect that there are problems with the data, we should modify the data to fit the FDs. In practice, it is usually unclear how much to trust the data versus the FDs. To address this problem, we propose an algorithm for generating non-redundant solutions (i.e., simultaneous modifications of the data and the FDs) corresponding to various levels of relative trust. This can help users determine the best way to modify their data and/or FDs to achieve consistency