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Association of Neonatal Hyperbilirubinemia with UGT1A1 Gene Polymorphisms: A Meta-Analysis

Zibi Yu, Kaichang Zhu, Li Wang, Ying Liu, Jianmei Sun

Songjiang Branch of The Affiliated Shuguang Hospital of Shanghai University of TCM, Shanghai, China (mainland)

Med Sci Monit 2015; 21:3104-3114

DOI: 10.12659/MSM.894043

Available online:

Published: 2015-10-15

BACKGROUND: The results of studies on association between the polymorphisms in the coding region and the promoter of uridine diphosphateglucuronosyl transferase 1A1 (UGT1A1) and neonatal hyperbilirubinemia are controversial. This study aimed to determine whether the UGT1A1 gene polymorphisms of Gly71Arg and TATA promoter were significant risk factors associated with neonatal hyperbilirubinemia.
MATERIAL AND METHODS: The PubMed, Cochrane Library, and Embase databases were searched for papers that describe the association between UGT1A1 polymorphisms and neonatal hyperbilirubinemia. Summary odds ratios and 95% confidence intervals (CI) were estimated based on a fixed-effects model or random-effects model, depending on the absence or presence of significant heterogeneity.
RESULTS: A total of 32 eligible studies and 6520 participants were identified. Among them, 24 studies focused on the association of neonatal hyperbilirubinemia with UGT1A1 Gly71Arg polymorphisms, and a significant difference was found for the comparison of AA vs. AG+GG (OR=3.47, 95% CI=2.29–5.28, P<0.0001). We included 19 studies on the association of neonatal hyperbilirubinemia with UGT1A1 TATA promoter polymorphism, which also found a statistically significant difference between 7/7 and 6/7 + 6/6 (OR=2.24, 95% CI=1.29–3.92, P=0.004).
CONCLUSIONS: This meta-analysis demonstrated that UGT1A1 polymorphisms (Gly71Arg and TATA promoter) significantly increase the risk of neonatal hyperbilirubinemia.

Keywords: Arginine - genetics, Algorithms, Gene Frequency, Glucuronosyltransferase - genetics, Glycine - genetics, Hyperbilirubinemia, Neonatal - genetics, Odds Ratio, Polymorphism, Genetic, Promoter Regions, Genetic, Regression Analysis, Risk Factors