Citation: Tang XJ, Shentu XC, Tang YL, Ping XY, Yu XN. The impact of GJA3 SNPs on susceptibility to
age-related cataract. Int
J Ophthalmol 2019;12(6):1008-1011
DOI:10.18240/ijo.2019.06.21
·Investigation·
The
impact of GJA3 SNPs on susceptibility to age-related cataract
Xia-Jing Tang1,2, Xing-Chao Shentu1,2,
Ye-Lei Tang3, Xi-Yuan Ping1,2, Xiao-Ning Yu1,2
1Eye Center
of the Second Affiliated Hospital, School of Medicine, Zhejiang University,
Hangzhou 310009, Zhejiang Province, China
2Zhejiang
Provincial Key Lab of Ophthalmology, Hangzhou 310009, Zhejiang Province, China
3The Second
Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310009,
Zhejiang Province, China
Correspondence
to: Xiao-Ning
Yu. Eye Center of the Second Affiliated Hospital, School of Medicine, Zhejiang
University; Zhejiang Provincial Key Lab of Ophthalmology, Hangzhou 310009,
Zhejiang Province, China. yxnzju@zju.edu.cn
Received:
Abstract
AIM: To determine the association of gap junction protein alpha 3 (GJA3)
gene tag single-nucleotide polymorphisms (SNPs) with susceptibility to
age-related cataract (ARC).
METHODS: In total, 486 ARC patients were matched with 500
healthy controls. All the participants underwent complete ophthalmic
examinations. Haplotype-tagging SNPs of GJA3 gene were selected from the HapMap Beijing Han Chinese population.
Genomic DNA was extracted from the peripheral blood leukocytes of all the
subjects. Under three different genetic models: dominant, recessive, and
additive, the association between SNPs and ARC was examined. After adjusting
for age and sex, the genetic effects of the GJA3 SNPs were evaluated
with logistic regression analysis.
RESULTS: Four tag GJA3 SNPs (rs6490519, rs9506430,
rs9509053, and rs9552089) were included in the present study. None of the SNPs
showed a significant relationship with an altered risk of total ARC under the
dominant, recessive, or additive models. In the subgroup analysis, rs9506430
had a significant effect on the formation of a posterior subcapsular cataract (P=0.002,
OR: 0.227, 95%CI: 0.088-0.590) under the recessive model.
CONCLUSION: Our study indicates that GJA3 variants may
influence the development of posterior subcapsular cataracts. Further studies
need to be designed to confirm this possibility.
KEYWORDS: gap junction protein alpha 3; single-nucleotide polymorphisms;
age-related cataract
DOI:10.18240/ijo.2019.06.21
Citation: Tang XJ, Shentu XC, Tang YL, Ping XY, Yu XN. The impact of GJA3 SNPs on susceptibility to
age-related cataract. Int
J Ophthalmol 2019;12(6):1008-1011
INTRODUCTION
Age-related
cataract (ARC) is one of the leading causes of avoidable vision impairment
worldwide, accounting for about 80% of senile blindness[1-2]. Although substantial progress has been achieved in
cataract surgery technology, advanced cataract surgery with less complications,
and that is more effective and stable (such as phacoemulsification and
intraocular lens implantation), still caused economical burden to patients in
developing countries[3-4]. With
the global increase in the elderly population, ARC has become a severe public
health challenge around the world, especially in developing countries. It is
therefore critical to investigate the potential factors influencing the
development of ARC.
The precise
etiology of ARC is not currently fully understood. It is reportedly related to
multiple risk factors, including diabetes, myopia, blood pressure, smoking,
drinking, and high myopia, among others. Notwithstanding, genetic variations
are also considered integral to the complex cataractogenesis process. Some
studies have suggested that broad-sense heritability is 48% for the nuclear
subtype of ARC and 58% for the cortical subtype of ARC[5-6]. Thus far, several genes, such as glutathione S
transferase (GST), xeroderma pigmentosum complementation group D (XPD),
and X-ray cross-complementing group 1 (XRCC1), are thought to be
related to ARC susceptibility[7].
The gap
junction protein alpha 3 (GJA3) gene encodes the CX46 protein, which
consists of gap junctions, and is critical to maintain the ionic and water
balance and transparency and optical properties of the lens. At present, most
previous GJA3-related studies have focused on congenital cataracts. The
only study that focused on ARC patients detected two variations in GJA3
(c.
SUBJECTS AND METHODS
Ethical
Approval This study was conducted in
accordance with the Declaration of Helsinki and was approved by the Ethics
Committee of the Second Affiliated Hospital, Medical College of Zhejiang
University, Hangzhou, China. In addition, informed consent was obtained from
each participant.
Study
Participants In this study, 986 unrelated
participants, with 486 ARC patients and 500 healthy controls, were included.
All the participants were Han Chinese and were recruited from the Eye Center of
the Second Affiliated Hospital, Medical College of Zhejiang University, Hangzhou,
China.
Complete
ophthalmic examinations were underwent in all the ARC patients, including best
corrected visual acuity measurements, fundus photography, and lens examinations
using a slit lamp biomicroscope after mydriasis. The lens opacities classification
system II is the base of all clinical diagnoses and classifications[9]. According to the degenerative regions of the lens,
four subtypes of ARC were classified: cortical cataract (CC), posterior
subcapsular cataract (PSC), nuclear cataract (NC) and mixed cataract (MC),
which means more than one cataract subtype in an eye[10].
However, if patients suffered with cataracts caused by uveitis, trauma, high
myopia, diabetes or other nongenetic causes were excluded.
The control
subjects had received routine health examinations at the Second Affiliated
Hospital, Medical College of Zhejiang University, Hangzhou, China as healthy
individuals. All the control subjects also underwent complete ophthalmic
evaluations to confirm lens transparency.
Single-nucleotide
Polymorphism Selection Haplotype-tagging SNPs in the GJA3
gene were selected from the HapMap Beijing Han Chinese population (HapMap
Genome Browser release #27, accessed on April 29, 2014; available at
http://hapmap.ncbi.nlm.nih.gov/). Four SNPs in GJA3 were selected, based
on the tagger-pairwise method, with a minor allele frequency (MAF) >0.10 and
an R square (r2) >0.8. Genomic DNA was extracted via
the Simgen Blood DNA mini kit (Simgen, Hangzhou, China), from the peripheral
blood leukocytes of all the subjects.
Statistical
Analysis The Hardy-Weinberg equilibrium (HWE)
of each SNP was assessed with the χ2 test using PLINK (v1.07;
available at http://pngu.mgh.harvard.edu/~purcell/plink/). The continuous
variables of the subjects’ characteristics were presented as the mean±standard
deviation (SD). Additionally, the association between ARC and the SNPs was
tested under three different genetic models: recessive, dominant and additive.
The allelic distributions of the control subjects and the ARC patients were compared
via the χ2 test. Then, in order to evaluate the
genetic effects of the GJA3 SNPs after adjusting for sex and age, the
logistic regression analysis was operated. Moreover, the Bonferroni correction
for multiple testing was also used to reduce the rate of type I errors. All the
other statistical analyses were performed by SPSS software (version 11.0, USA).
Two-tailed P value <0.05 was considered as a statistical
significance, unless indicated.
RESULTS
The General
Demographic Characteristics of the Involved Participants Overall, 486 ARC patients (PSC=73,
NC=126, CC=130, MC=157) and 500 healthy controls were included in this study.
The general demographic characteristics of the 986 participants are summarized
in Table 1. Statistically significant differences were detected between the two
groups in terms of age and sex (P<0.05).
Table 1 The
general demographic characteristics of the participants involved in the present
study
Group |
n |
Gender |
Age (y) |
||
Male (%) |
Female (%) |
Mean±SD |
Range |
||
Control |
500 |
57.40 |
42.60 |
63.39±6.57 |
49-87 |
ARC |
486 |
41.98 |
58.02 |
69.45±9.72 |
38-91 |
CC |
130 |
34.62 |
65.38 |
67.78±8.41 |
43-88 |
NC |
126 |
38.10 |
61.90 |
68.26±9.86 |
45-87 |
PSC |
73 |
45.21 |
54.79 |
66.48±10.27 |
45-90 |
MC |
157 |
49.68 |
50.32 |
73.20±9.24 |
38-91 |
ARC:
Age-related cataract; CC: Cortical cataract; PSC: Posterior subcapsular
cataract; NC: Nuclear cataract; MC: Mixed cataract.
The
Bioinformatics Characteristics of GJA3 Tag SNPs Four tag SNPs in GJA3 were
selected for genotyping in accordance with the screening technique described in
the Materials and Methods section of this paper, and their bioinformatics characteristics
are summarized in Table 2. No SNPs showed departure from the HWE.
Table 2 The
four involved GJA3 SNPs bioinformatics characteristics
SNPs |
Minor allele |
Call rate |
MAF |
Test for HWE (P) |
Control (MAF) |
ARC (MAF) |
rs6490519 |
G |
0.99696 |
0.319 |
0.3362 |
0.303 |
0.334 |
rs9506430 |
T |
0.99696 |
0.439 |
0.6244 |
0.457 |
0.420 |
rs9509053 |
T |
0.99696 |
0.221 |
0.2835 |
0.217 |
0.224 |
rs9552089 |
G |
0.99696 |
0.122 |
0.7045 |
0.121 |
0.122 |
SNPs:
Single-nucleotide polymorphisms; GJA3: Gap junction protein alpha 3;
MAF: Minor allele frequency; HWE: Hardy-Weinberg equilibrium; ARC:
Age-related cataract.
Association
Between the SNPs and the Risk of ARC
As indicated
in Table 3, none of the SNPs showed a significant relationship with an altered
risk of ARC under the dominant, recessive, or additive models using the
logistic model. In the subgroup analysis, rs9506430 had a significant effect on
the formation of PSC (P=0.002, OR: 0.227, 95%CI: 0.088-0.590) under the
recessive model, and the result remained significant after the Bonferroni
correction.
Table 3 The
relationship between GJA3 tag SNPs and the risk of ARC under three
different genetic models
SNPs |
Subtype |
Genetic model |
χ2 test (P) |
Logistic regression |
|
P |
OR (95%CI) |
||||
rs6490519 |
CC |
Dominant |
0.467 |
- |
- |
Recessive |
0.146 |
- |
- |
||
Additive |
0.333 |
- |
- |
||
MC |
Dominant |
0.353 |
- |
- |
|
Recessive |
0.151 |
- |
- |
||
Additive |
0.313 |
- |
- |
||
NC |
Dominant |
0.664 |
- |
- |
|
Recessive |
0.230 |
- |
- |
||
Additive |
0.350 |
- |
- |
||
PSC |
Dominant |
0.116 |
- |
- |
|
Recessive |
0.556 |
- |
- |
||
Additive |
0.288 |
- |
- |
||
rs9506430 |
CC |
Dominant |
0.268 |
- |
- |
Recessive |
0.318 |
- |
- |
||
Additive |
0.437 |
- |
- |
||
MC |
Dominant |
0.268 |
- |
- |
|
Recessive |
0.388 |
- |
- |
||
Additive |
0.475 |
- |
- |
||
NC |
Dominant |
0.364 |
- |
- |
|
Recessive |
0.950 |
- |
- |
||
Additive |
0.612 |
- |
- |
||
PSC |
Dominant |
0.167 |
- |
- |
|
Recessive |
0.003 |
0.002 |
0.227 (0.088, 0.590) |
||
Additive |
0.011 |
- |
- |
||
rs9509053 |
CC |
Dominant |
0.960 |
- |
- |
Recessive |
0.900 |
- |
- |
||
Additive |
0.992 |
- |
- |
||
MC |
Dominant |
0.730 |
- |
- |
|
Recessive |
0.630 |
- |
- |
||
Additive |
0.794 |
- |
- |
||
NC |
Dominant |
0.858 |
- |
- |
|
Recessive |
0.550 |
- |
- |
||
Additive |
0.790 |
- |
- |
||
PSC |
Dominant |
0.184 |
- |
- |
|
Recessive |
0.439 |
- |
- |
||
Additive |
0.371 |
- |
- |
||
rs9552089 |
CC |
Dominant |
0.639 |
- |
- |
Recessive |
0.275 |
- |
- |
||
Additive |
0.407 |
- |
- |
||
MC |
Dominant |
0.917 |
- |
- |
|
Recessive |
0.767 |
- |
- |
||
Additive |
0.956 |
- |
- |
||
NC |
Dominant |
0.377 |
- |
- |
|
Recessive |
0.555 |
- |
- |
||
Additive |
0.476 |
- |
- |
||
PSC |
Dominant |
0.162 |
- |
- |
|
Recessive |
0.491 |
- |
- |
||
Additive |
0.352 |
- |
- |
SNPs:
Single-nucleotide polymorphisms; GJA3: Gap junction protein
alpha 3; ARC: Age-related cataract; CC: Cortical cataract; MC: Mixed
cataract; NC: Nuclear cataract; PSC: Posterior subcapsular cataract.
DISCUSSION
Multiple
genes have been implicated in influencing ARC formation[11].
In the present study, we focused on GJA3, which is a major component of
gap junction channels and hemi-channels in the lens. GJA3 also plays a
vital role in lens homeostasis and lens transparency maintenance[12-13]. Up to now, there is no study
has thoroughly explored the relationship between GJA3-tagged SNPs and
ARC. Therefore, this study investigated the association between GJA8-tagged
SNPs and ARC in a Chinese population. None of the SNPs were significantly
associated with an altered risk of ARC under the dominant, recessive, or
additive models. However, rs9506430 played a significant role in PSC formation
in ARC, which has not been reported in previous studies.
GJA3 belongs to the connexin gene
family, which is the main component of gap junctions[14].
More than 30 GJA3 variants are reported to associate with congenital
cataracts, which makes GJA3 one of the most frequently mutated genes
related to lens opacity[15-17].
To date, only one study has focused on the relationship between GJA3 and
ARC. Two variations (c.
Generally,
connexin, like the GJA3 protein, consists of four conserved domains, namely,
two extracellular loop domains, one intracellular loop domain, and cytoplasmic
NH2- and COOH-terminal domains[18]. It is worth
noting that the majority of the variants located in the extracellular loop
domains of the GJA3 protein are phenotypically the NC subtype, whereas the
variants located in the COOH-terminal domain are the NC or cortical subtype[15]. These findings point to a possible correlation
between the genotype and phenotype of GJA
Overall,
those variants in lens proteins, causing proteins to aggregate rapidly and
directly, tend to more likely lead to congenital cataracts. By way of contrast,
variants that merely increase susceptibility to environmental risk factors
usually contribute to the development of ARC[19].
It is interesting that GJA3 variants are associated with both congenital
cataracts and ARC. Importantly, in this study, the rs9506430 variation played a
significant role in PSC formation in ARC. To date, many GJA3 variants
have been reported to be associated with an increased risk of cataracts[19-20]. Su et al[21] found that downregulation of GJA
In summary,
the results of the current study demonstrate a new inheritance pattern of GJA3
gene variants in ARC. However, as the single population and limited sample size
in our study, further studies with larger and ethical diverse populations are
warranted. Furthermore, the relationship between GJA3 and ARC needs to
be addressed by elucidating the interactive molecules in detail in future
studies.
ACKNOWLEDGEMENTS
Foundations: Supported by National Natural
Science Foundation of China (No.81371000; No.81670834; No.81800807;
No.81800869); the Natural Science Foundation of Zhejiang Province
(No.LY17H090004); the Zhejiang Traditional Chinese Medicine Project
(No.2013ZA080); the Fundamental Research Funds for the Central Universities
(No.2018FZA7007).
Conflicts of
Interest: Tang XJ,
None; Shentu XC, None; Tang YL, None; Ping XY, None;
Yu XN, None.
REFERENCES