ITPA gene variants protect against anaemia in patients treated for chronic hepatitis C

Abstract

Chronic infection with the hepatitis C virus (HCV) affects 170 million people worldwide and is an important cause of liver-related morbidity and mortality. The standard of care therapy combines pegylated interferon (pegIFN) alpha and ribavirin (RBV), and is associated with a range of treatment-limiting adverse effects. One of the most important of these is RBV-induced haemolytic anaemia, which affects most patients and is severe enough to require dose modification in up to 15% of patients. Here we show that genetic variants leading to inosine triphosphatase deficiency, a condition not thought to be clinically important, protect against haemolytic anaemia in hepatitis-C-infected patients receiving RBV.

Impact of genetic SLC28 transporter and ITPA variants on ribavirin serum level, hemoglobin drop and therapeutic response in patients with HCV infection

“…Patients who are heterozygous for rs1127354 and rs7270101 have a lower risk for Hb drop > 3 g/dl during antiviral therapy [10]. This association was confirmed in our study for allelic and genotypic rs1127354 variants.…”

“…Among those 194 patients were from the Swiss Hepatitis C Cohort Study (SCCS) [22] al. [10], i.e. wildtype (100% ITPA activity), + (rs7270101 heterozygosity, 60% IPTA activity), ++ (rs1127354 heterozygosity and rs727101 homozygosity, 30% ITPA activity) and +++ (combined heterozygosity or rs1127354 homozygosity, very low residual ITPA activity.…”

“…A genome-wide association study identified two single nucleotide polymorphisms (SNPs) (rs1127354, rs7270101) in the gene coding for inosine triphosphatase (ITPA), which were associated with RBV related anemia [10].…”

Hepatitis C pharmacogenetics: State of the art in 2010

“…24 ITPA genotyping could help guide clinical decision-making, especially for patients in whom treatment with RBV is avoided or relatively contraindicated because of the high risk for developing anemia.…”

Local Joint Testing Improves Power and Identifies Hidden Heritability in Association Studies

“…In this work we investigate a local joint-testing approach to analysis of genetic data sets in which pairs of variants from the same locus are examined simultaneously for association with a phenotype. The motivation for our approach comes from the mounting evidence that complex traits are highly polygenic (Visscher et al 2012), that causal variants are not evenly distributed across the genome (Gusev et al 2013), that known associated loci often harbor multiple causal variants (Udler et al 2009;Fellay et al 2010;Trynka et al 2011;Wood et al 2011;Liu et al 2012;Patsopoulos et al 2013;Pickrell 2014), and that the underlying causal variants can be in linkage disequilibrium (LD) with each other (Corradin et al 2014).…”