Li et al. BMC Medical Genetics(2020) 21:218
https://doi.org/10.1186/s12881-020-01155-2

RESEARCH ARTICLE

Open Access

The role of UGT1A1 (c.-3279 T > G) gene
polymorphisms in neonatal
hyperbilirubinemia susceptibility
Zijin Li1†, Li Song2† and Lihong Hao2*

Abstract
Background: Neonatal hyperbilirubinemia (NNH) is a common disease in newborns. This research study aimed toassess the associations between uridine diphospho-glucuronate-glucuronosyltransferase 1A1 (UGT1A1, c.-3279 T > G)polymorphisms and NNH risk.
Methods: We searched PubMed, the Cochrane Library, and the Embase electronic databases. All published eligible
studies before July 1, 2019, were searched for this meta-analysis.
Results: We identified 7 independent studies including 1560 cases. The data showed that in the general
population, compared with the GT + GG vs TT and GG vs TT, c.-3279 T > G (rs4124874) was significantly related to ahigher NNH risk (GG vs TT: OR = 1.865, 95% CI: 1.031–3.373, P = 0.039; GT + GG vs TT: OR = 1.331, 95% CI: 1.055–
1.679, P = 0.016). Although not statistically significant, the data showed that c.3279 T > G had a tendency to be
associated with NNH under the allele model and GG vs GT + TT in the overall population (G vs T: OR = 1.288, 95%
CI: 0.982–1.689, P = 0.067; GG vs TT + GT: OR = 1.583, 95% CI: 0.947–2.647, P = 0.080).
Conclusion: The UGT1A1 gene c.-3279 T > G (rs4124874) polymorphism increased susceptibility to NNH, especiallyfor the comparison of GT + GG vs TT and GG vs TT. In the future, we can use homozygous state of the UGT1A1
gene c.-3279 T > G (rs4124874) polymorphism for the diagnosis and screening of molecular biomarkers in NNH
patients.
Keywords: UGT1A1, Neonatal hyperbilirubinemia, Neonatal jaundice, C.-3279 T > G, Polymorphism

Background
Neonatal hyperbilirubinemia (NNH) is complex and involves multiple environmental and genetic risk factors [1–4]. Immature red blood cells and the liver and gastrointestinal tract are associated with benign transitions in hyperbilirubinemia [5]. Although considerable research effort
has been focused on NNH, the pathophysiology of the disease remains incompletely understood. An increasing* Correspondence: lihonghao321@163.com†
Zijin Li and Li Song contributed equally to this work.
2
Department of Neonatology, Tianjin Children’s Hospital, No. 238 Longyan
Road, Beichen district, Tianjin 300074, China
Full list of author information is available at the end of the article

number of clinically relevant genetically identified diseases
are recognized [6–8].
The uridine diphospho-glucuronate-glucuronosyltransferase 1A1 (UGT1A1) gene encodes bilirubin UDP glucuronosyltransferase, which is the enzyme responsible for bilirubin
glucuronidation [9]. Recently, researchers have paid widespread attention to genetic factors that are particularly affected by UGT1A1 variants [4, 8, 10]. Approximately 113
UGT1A1 gene variants have been identified. In recent years,
a c.-3279 T > G mutation (UGT1A1 * 60; rs4124874) was
found in the UGT1A1 promoter, and some sequences inthis promoter are related to NNH [11]. UGT1A1 * 60 is thenucleotide at the 3279 T-to-G substitution of UGT1A1,© The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License,
which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give
appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate ifchanges were made. The images or other third party material in this article are included in the article's Creative Commonslicence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commonslicence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain
permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to thedata made available in this article, unless otherwise stated in a credit line to the data.

Li et al. BMC Medical Genetics(2020) 21:218

which is the reactive enhancer module phenobarbital.
Nearly 60% of transcriptional activity is reduced at UGT1A1* 60, so the increased risk of hyperbilirubinemia is inextricably linked to its presence [12].
In recent years, many studies have shown the role ofc.-3279 T > G gene polymorphisms in NNH [8, 11, 13–16]. However, the results of these studies have not been
determined. A single study of polymorphisms on NNH
may not be sufficient to verify with a separate study. To
show the impact of c.-3279 T > G gene polymorphisms
on NNH risk, we identified eligible case-control studies
and performed a meta-analysis.

Methods
Search strategy

The following keywords were used to research the articles in the Cochrane Library, PubMed and Embase electronic databases: “UGT1A1” OR “uridine diphosphoglucuronate-glucuronosyltransferase 1A1” OR “c.-3279

Fig. 1 Flow diagram detailed procedures of selecting eligible studies

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T > G” AND “polymorphism” OR “variant” OR “allele”
OR “genotype” OR “neonatal hyperbilirubinemia” OR“neonatal jaundice” OR “hyperbilirubinemia”. All eligible
studies were published before July 1, 2019. In addition,
the reference lists were manually searched for additional
studies. When multiple articles contained studies of thesame population, only the most recent or complete
study was used in the meta-analysis. The language of the
publications was limited to English.
Inclusion criteria and exclusion criteria

Articles had to meet the following criteria to be included in
the meta-analysis: (1) The relationship between the genetic
polymorphism of UGT1A1 (c.-3279 T > G) and the risk of
NNH was evaluated; (2) a case-control study; and (3) thecontrol group complies with Hardy-Weinberg equilibrium.
The exclusion criteria strongly adhere to the following: (1)lack of valid raw data; (2) data had serious deviations; and(3) reproduction of publications.

Li et al. BMC Medical Genetics(2020) 21:218

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Table 1 Basic information of the original articles included in this meta-analysis
AuthorWatchko et al.

Ethnicity
Caucasian

Year
2009

Study
design

Methods

HBC

IBS

Case

Control

GG

AA

GA

GG

AA

GA

41

35

77

89

74

135

Yusoff et al.

Asian

2010

HBC

PCR-RFLP

18

19

29

4

28

38

Tiwari et al.

Asian

2013

HBC

PCR-RFLP

21

35

44

26

28

46

Tiwari et al.

Asian

2014

HBC

PCR-RFLP

32

21

60

45

69

104

D’Silva et al.

Asian

2014

PBC

PCR-RFLP

46

25

55

52

61

68

Tomerak et al.

African2016

HBC

PCR-RFLP

20

32

11

2

18

18

Yanagi et al.

Asian

2017

HBC

PCR-RFLP

0

3

1

1

16

13

PCR—RFLP Polymerase chain reaction—restriction fragment length polymorphism, IBS Internet-based system, HBC Hospital-based study, PBC
Population-based study

Table 2 Summary ORs (95% CI) of UGT1A1 (c.-3279 T > G) gene polymorphisms and neonatal hyperbilirubinemia risk
Genetic model

Subgroup analysis

No. of studies

OR (95% CI)

P

I2%

P (Q test)

G vs T

Total

7

1.288 (0.982–1.689)

0.067

63.9

0.011

Asian

5

1.334 (0.939–1.896)

0.108

66.3

0.018

African1

1.669 (0.907–3.072)

0.100

0

1.000

Caucasian

1

0.978 (0.742–1.289)

0.874

0

1.000

Total

7

1.865 (1.031–3.373)

0.039

67.5

0.005

Asian

5

1.958 (0.946–4.052)

0.070

67.3

0.016

African1

5.625 (1.177–26.877)

0.030

0

1.000

Caucasian1

0.974 (0.564–1.682)

0.925

0

1.000

Total

7

1.557 (0.883–2.745)

0.126

71.3

0.002

Asian

7

1.365 (0.806–2.314)

0.247

51.5

0.083

African1

16.364 (3.188–83.993)

0.001

0

1.000

Caucasian10.808 (0.508–1.284)

0.367

0

1.000

Total

7

1.100 (0.720–1.681)

0.660

58.6

0.024

Asian

5

1.322 (0.849–2.057)

0.216

43.3

0.133

African1

0.344 (0.133–0.886)

0.027

0

1.000

Caucasian1

1.206 (0.739–1.968)

0.454

0

1.000

Total

7

1.331 (1.055–1.679)

0.016

49.1

0.067

Asian

5

1.427 (0.875–2.326)

0.154

58

0.049

African1

0.872 (0.389–1.952)

0.739

0

1.000

Caucasian1

1.114 (0.703–1.764)

0.646

0

1.000

Total

7

1.583 (0.947–2.647)

0.080

69.5

0.003

Asian

5

1.549 (0.894–2.685)

0.119

60.1

0.040

African1

8.372 (1.832–38.260)

0.006

0

1.000

Caucasian10.860 (0.556–1.329)

0.496

0

1.000

Total

7

0.903 (0.631–1.293)

0.578

59.2

0.023

Asian

5

1.062 (0.821–1.374)

0.648

0

0.434

African1

0.235 (0.095–0.584)

0.002

0

1.000

Caucasian11.223 (0.828–1.808)

0.312

0

1.000

GG vs TT

GG vs GTGT vs TT

GT + GG vs TT

GG vs TT + GT

GT vs TT + GG

OR Odds ratio, CI Confidence interval, vs versus, P (Q test) P value of Q test for heterogeneity test

Egger’s test

Begg’s test

0.766

1.000

0.203

0.368

0.057

0.072

0.331

0.368

0.603

0.764

0.084

0.072

0.061

0.133

Li et al. BMC Medical Genetics(2020) 21:218

Data extraction

The data were independently evaluated by two reviewers.
The difference was not resolved until the consensus ofeach item was reached. Information such as author
name, year of publication, country of origin, ethnic origin, source of the control population, genotyping
method, matching factors and adjustment factors, number of cases and controls were recorded in each item.

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Egger’s and Begg’s tests were used to detect publicationbias, and P < 0.05 was considered a publication bias. A
funnel graph and Egger’s test were used to display publication bias. All control groups were in Hardy-Weinberg
equilibrium. STATA software was required for all metaanalyses (version 14.0; University City, Texas, USA).
There were two sides for all tests.

Results
Statistical analysis

This study was conducted independently by two researchers based on the information collected throughreading relevant articles. Whether to include the studies
in the meta-analysis was decided in strict accordancewith the inclusion and exclusion criteria and discussion.
ORs (odds ratios) and 95% CIs were used to estimate
the relationships between the c.-3279 T > G gene polymorphism and NNH. To assess whether the results ofthe data set were heterogeneous, we used the Q test andI2. A heterogeneity P value below 0.05 was considered
statistically significant for heterogeneity. The subgroup
analysis of ethnicity was divided into Asians, Caucasians,
and Africans. The random effects model was applied
when the results of the heterogeneity test were P < 0.05
or I2 > 50%; otherwise, a fixed effect model was applied.

Study selection

Figure 1 shows that we searched the bibliographic database and found 203 related records. After several roundsof screening, 25 articles were found that met the search
criteria. After applying the inclusion and exclusion
evaluation criteria to the articles, a total of 7 studies met
the criteria [8, 11, 13–17].
Study characteristics

Seven independent studies were identified, which included 1560 cases. Table 1 lists the main characteristics
of all eligible studies. There are 7 case-control studies onc.-3279 T > G (rs4124874) [8, 11, 13–17]. The seven independent studies included 5 studies on Asian populations [8, 11, 14–16], 1 African study [17] and 1
Caucasian study [13].

Fig. 2 Random-effects meta-analysis on NNH risk and c.-3279 T > G (rs4124874) polymorphism in overall population (GG versus TT)

Li et al. BMC Medical Genetics(2020) 21:218

C.-3279 T > G (rs4124874)

For c.-3279 T > G (rs4124874), the main results areshown in Table 2. These data show that c.-3279 T > G(rs4124874) was significantly related to a higher NNH
risk in the overall population (GG vs TT and GT + GG
vs TT) (GG vs TT: OR = 1.865, 95% CI: 1.031–3.373,
P = 0.039, Fig. 2; GT + GG vs TT: OR = 1.331, 95% CI:
1.055–1.679, P = 0.016, Fig. 3). Although not statisticallysignificant, the data showed that c.-3279 T > G had atendency to be associated with NNH under the allele
model and GG vs GT + TT in the overall population (Gvs T: OR = 1.288, 95% CI: 0.982–1.689, P = 0.067; GG vs
TT + GT: OR = 1.583, 95% CI: 0.947–2.647, P = 0.080).

Page 5 of 8

1.832–38.260, P = 0.006, Fig. 4). However, an association
with a lower NNH risk was detected in the comparisonof GT vs TT and GT vs TT + GG in the African population (GT vs TT: OR = 0.344, 95% CI: 0.133–0.886, P =0.027; GT vs TT + GG: OR = 0.235, 95% CI: 0.095–0.584,
P = 0.002).
Sensitivity analyses

One-way sensitivity analysis was performed on thedata involved in this meta-analysis. Each single studyof the meta-analysis was deleted each time to reflect
the overall impact on the individual data sets, and thecorresponding combined results were not substantiallychanged.

Subgroup analysis

The subgroup analysis in this paper is mainly based on
ethnic differences, and Asians, Caucasians and Africans
were grouped separately. The prevalence of the G and T
alleles among different races is shown in Supplemental
Table S1. A correlation with a higher NNH risk wasfound in the subgroup analysis, which was comparedwith GG vs TT and GG vs GT + TT in the African
population (GG vs TT: OR = 5.625, 95% CI: 1.177–
26.877, P = 0.03; GG vs TT + GT: OR = 8.372, 95% CI:

Publication bias

Publication bias was assessed by Begg’s test and Egger’s
test (Table 2). A graph of Egger’s linear regression test
was compared to the allele model (Fig. 5a). The contrastof GG vs TT (Fig. 5b) and GT + GG vs TT (Fig. 5c) forc.-3279 T > G gene polymorphisms was evaluated to intuitively show publication bias. In addition, evidence of
publication bias could not be found in any other analysis
in various comparative models.

Fig. 3 Fixed-effects meta-analysis on NNH risk and c.-3279 T > G (rs4124874) polymorphism under GT + GG vs TT in overall population (GT + GG vs TT)

Li et al. BMC Medical Genetics(2020) 21:218

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Fig. 4 Random-effects meta-analysis on NNH risk and c.-3279 T > G (rs4124874) polymorphism under GG vs GT + TT in African population (GGvs TT + GT)

Discussion
This study showed that the modifiable risk of neonatal
hyperbilirubinemia includes multiple genetic and clinicalrisk factors. Genes that can exacerbate mutations havelower transcriptional activity in the first few days of life
because their liver UGT1A1 is natural and immature.
UGT1A1 is regulated in a developmental manner. Its

activity can increase from 0.1% at 17–30 weeks of gestation to 1% at 30–40 weeks, reaching the adult level only
14 weeks after birth [18]. It has been shown thatUGT1A1 (c.-3279 T > G) gene polymorphisms might
have an effect on NNH risk [15, 17, 19]. However, a single study of the relationship between NNH and genes iscontroversial. Some studies reported that the UGT1A1

Fig. 5 The Egger linear regression test for c.-3279 T > G (rs4124874) compared with the (a) allele model, b the contrast of GG vs TT and c GT +GG vs TT to show publication bias

Li et al. BMC Medical Genetics(2020) 21:218(c.-3279 T > G) gene polymorphisms did not have a rolein NNH risk [13, 14]. The problem of low statisticalpower in a single study can be solved by meta-analysis,
and stronger conclusions can be drawn. UGT1A1 gene
polymorphisms are associated with many diseases andhave been confirmed by meta-analysis [20–23].
Moreover, a meta-analysis confirmed that the TATAbox polymorphism and c.211G > A (Gly71Arg) of theUGT1A1 gene polymorphism are associated with NNH[24–27]. Therefore, we evaluated the role of UGT1A1 inthis meta-analysis (c.-3279 T > G) gene polymorphism inneonatal hyperbilirubinemia susceptibility. Seven casecontrol studies contained in this meta-analysis showedthat the c.-3279 T > G (rs4124874) UGT1A1 gene polymorphism was related to the risk of GG vs. TT and GT +GG vs TT in the overall population. Although not statistically significant, the data showed that c.-3279 T > G has atendency to be associated with NNH under the allele
model and GG vs GT + TT in the overall population.
One disturbing problem is the analysis of populationgroups, which is often not very reliable in the presenceof evidence of disease, which indicates that the environment and race affect genetic background differently [28].
Simultaneously, although different populations have thesame polymorphisms in racial subgroup analysis, susceptibility plays different roles in the population. We analyzed the prevalence of the G and T alleles between
different races. Differences between different races havelittle effect on the overall results. However, there aresome differences between the African population and
the Asian or Caucasian populations in this study. Therefore, it should be noted that the results of the subgroup
analysis of the African population need to be further
confirmed. The number of African studies included issmall, and more literature should be included in the future to verify this result.
This meta-analysis has some limitations. First, heterogeneity may have interfered with the results of thismeta-analysis. Nonetheless, we use specific researchstandards to strictly perform data extraction and analysis
to minimize this possibility. In addition, published studies were included in this meta-analysis, and results with
nonsignificant or negative results might not be published, so the possibility of bias may be increased in publication. Finally, our results have not been adjusted. If
more research data can be obtained, a more accurate
analysis could be performed. Other variables can beused, including race, age, family history, environmental
factors and lifestyle [29–32].
Although there were limitations in this meta-analysis, wefound that the UGT1A1 gene c.-3279 T > G (rs4124874)
polymorphism is associated with NNH risk. Therefore, it
can be used as a screening index for NNH. In the future,
we should consider using a larger sample size to confirm

Page 7 of 8

our results. In addition, the effects of gene-environmentand gene-gene interactions must be researched in the future. An in-depth analysis of these factors provides a more
complete understanding and more reliable results of thelinkage between the UGT1A1 gene c.-3279 T > G(rs4124874) polymorphism and the risk of NNH.

Conclusion
In summary, the UGT1A1 gene c.-3279 T > G (rs4124874)
polymorphism increased susceptibility to NNH, especiallyfor the comparison of GT + GG vs TT and GG vs TT. In
the future, we can use homozygous state of the UGT1A1
gene c.-3279 T > G (rs4124874) polymorphism for the
diagnosis and screening of molecular biomarkers in NNH
patients.
Supplementary Information
The online version contains supplementary material available at https://doi.
org/10.1186/s12881-020-01155-2.
Additional file 1 : Supplemental Table S1. The prevalence of G and T
allele among different races
Abbreviations
NNH: Neonatal hyperbilirubinemia; UGT1A1: Uridine diphospho-glucuronateglucuronosyltransferase 1A1; OR: Odds ratio; CI: Confidence interval
Acknowledgments
Not applicable.
Authors’ contributions
ZL performed the analysis. LS drafted the manuscript. LH was involved inresearch design and supervision of the analysis. All authors read andapproved the final manuscript.
Funding
Not applicable.
Availability of data and materials
The datasets used and analyzed in the present study are available from thecorresponding author upon reasonable request.
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Author details
1
Department of Internal Medicine, Tianjin Children’s Hospital, Tianjin 300074,
China. 2Department of Neonatology, Tianjin Children’s Hospital, No. 238
Longyan Road, Beichen district, Tianjin 300074, China.
Received: 22 February 2020 Accepted: 21 October 2020

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