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Polymorphism of UDP-glucuronosyltransferase and drug metabolism

Journal

CURRENT DRUG METABOLISM
Volume 6, Issue 2, Pages 91-99

Publisher

BENTHAM SCIENCE PUBL LTD
DOI: 10.2174/1389200053586064

Keywords

UDP-glucuronosyltransferase; polymorphism; detoxification; glucuronidation; drug metabolism; Gilbert syndrome; Crigler-Najjar syndrome

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UDP-glucuronosyltransferase is a group of catabolic enzymes involved in the detoxification and excretion of many xenobiotic and endogeneous substances in intrahepatic and extrahepatic tissues. The group consists of two subfamilies. UGT1 and UGT2. UGT1 consists of 5 exons and has a unique gene structure. There are thirteen exon 1s from UGT1A1 to UGT1A13P, and exon 2 to exon 5 are used in common for all mRNAs expressed from the gene. Each isoform of UGT1 results from differential splicing of exon 1s to common exon 2-5, and has an unique spectrum of substrate specificity. In contrast, the genes of the UGT2 family consist of 6 exons, and all the enzymes have an individual set of exon 1 to exon 6. In UGT1 there are no reports of polymorphism in the common exons, although a number of polymorphisms have been reported for exon Is. The mutations of UGT1A1 cause hereditary unconjugated hyperbilirubinemias: Crigler-Najjar syndrome type I, type II and Gilbert syndrome. UGT1A1 has two major polymorphisms - a missense mutation of G71R and an insertion mutation of TATA box. Prevalence of Gilbert syndrome is attributed to these polymorphisms. Since UGT1A1 metabolizes not only bilirubin but also hormones and drugs, the mutations could be involved in carcinogenesis and adverse drug reactions. Recent studies also revealed a widespread presence of diverse polymorphisms in other isoforms of UGT1 as well as the UGT2 family, including UGT1A6, UGTG1A7, UGT1A8, UGT1A10, UGT2B4, UGT2B7 and UGT2B15. The incidences and types of the polymorphisms for these enzymes are quite different in region and ethnic groups. Understanding of these polymorphisms is essential for the prevention of adverse effects of a considerable number of drugs and to predict cancer risks.

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