NTCP polymorphisms were associated with fibrosis development in patients with chronic HBV infection
Introduction: Sodium taurocholate cotransporting polypeptide has been identified as the hepatitis B virus (HBV) entry receptor. However, information regarding the role of sodium taurocholate cotransporting polypeptide variants in the development of HBV-related advanced cirrhosis and hepatocellular carcinoma is limited.
Methodology: Overall, 581 patients with chronic HBV infection were divided into the liver fibrosis or cirrhosis group based on the Fibrosis-4 index. Further, 183 patients with hepatocellular carcinoma were distributed into early/intermediate and advanced/end stage groups based on Barcelona Clinic Liver Cancer Staging approach. Three single nucleotide polymorphisms were genotyped by high resolution melting curve method. Serum biomarkers of liver function were detected, and hepatocellular carcinoma properties were collected as well.
Results: Subjects with GA+AA genotypes at the rs4646287 polymorphism site were associated with a significantly higher rate of fibrosis development (rs4646287 GA+AA genotypes were 13.7% and 20.0% in the non-fibrosis and fibrosis group, respectively; p = 0.038). There were no significant differences between sodium taurocholate cotransporting polypeptide polymorphisms and hepatocellular carcinoma progression. The GA+AA genotype carriers of rs7154439 had relatively high albumin levels (p = 0.035). The rs2296651 GA genotype carriers tended to have solitary tumor nodule and without metastasis (p = 0.004 and 0.015, respectively).
Conclusions: Rs4646287 was associated with HBV-related fibrosis development. Sodium taurocholate cotransporting polypeptide polymorphisms were correlated with serum albumin level as well as hepatocellular carcinoma multifocality and metastasis. Therefore, integrating sodium taurocholate cotransporting polypeptide polymorphisms to a risk stratification algorithm may help clinicians manage the chronic HBV infection patients better.
Copyright (c) 2022 Zhenzhen Su, Bei Cai, Xiaojuan Wu, Lixin Li, Bin Wei, Liye Meng, Lu Wang, Lanlan Wang
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