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
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.-39C>G and c.415G>A), but according to Polyphen, none of them had potential pathogenicity[8]. We therefore conducted this study to fully screen GJA3 tag single-nucleotide polymorphisms (SNPs) in ARC patients and to determine correlations between the genotype and phenotype in ARC patients with GJA3 tag SNPs.
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.-39C>G and c.415G>A) identified in the study were found not to be pathogenic[14]. In the present study, we identified one novel variation (rs9506430) that has not been previously reported. This variation conferred a 4.4-fold decreased risk for PSC under the recessive model.
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 GJA3 in cataracts. In our study, rs9506430 was associated with an altered risk of the PSC subtype.
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 GJA3 in lens epithelial cells (LEC) was associated with ARC genesis through interference with H2O2-induced LEC apoptosis[22], and LEC apoptosis was reported to be the molecular basis for the initiation and subsequent progression of cataract formation[21]. Thus, we speculate that rs9506430 may enhance the activity of the GJA3 protein to suppress the apoptosis process in LEC. Further fundamental research is needed to confirm our hypothesis.
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.
Acknowledgments
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
- 1.Bourne RR, Stevens GA, White RA, Smith JL, Flaxman SR, Price H, Jonas JB, Keeffe J, Leasher J, Naidoo K, Pesudovs K, Resnikoff S, Taylor HR, Vision Loss Expert Group Causes of vision loss worldwide, 1990-2010: a systematic analysis. Lancet Glob Health. 2013;1(6):e339–e349. doi: 10.1016/S2214-109X(13)70113-X. [DOI] [PubMed] [Google Scholar]
- 2.West S. Epidemiology of cataract: accomplishments over 25 years and future directions. Ophthalmic Epidemiol. 2007;14(4):173–178. doi: 10.1080/09286580701423151. [DOI] [PubMed] [Google Scholar]
- 3.Tang Y, Wang X, Wang J, Huang W, Gao Y, Luo Y, Yang J, Lu Y. Prevalence of age-related cataract and cataract surgery in a Chinese adult population: the Taizhou eye study. Invest Ophthalmol Vis Sci. 2016;57(3):1193–1200. doi: 10.1167/iovs.15-18380. [DOI] [PubMed] [Google Scholar]
- 4.Asbell PA, Dualan I, Mindel J, Brocks D, Ahmad M, Epstein S. Age-related cataract. Lancet. 2005;365(9459):599–609. doi: 10.1016/S0140-6736(05)17911-2. [DOI] [PubMed] [Google Scholar]
- 5.Hammond CJ, Duncan DD, Snieder H, de Lange M, West SK, Spector TD, Gilbert CE. The heritability of age-related cortical cataract: the twin eye study. Invest Ophthalmol Vis Sci. 2001;42(3):601–605. [PubMed] [Google Scholar]
- 6.Hammond CJ, Snieder H, Spector TD, Gilbert CE. Genetic and environmental factors in age-related nuclear cataracts in monozygotic and dizygotic twins. N Engl J Med. 2000;342(24):1786–1790. doi: 10.1056/NEJM200006153422404. [DOI] [PubMed] [Google Scholar]
- 7.Wu X, Lai W, Lin H, Liu Y. Association of OGG1 and MTHFR polymorphisms with age-related cataract: a systematic review and meta-analysis. PLoS One. 2017;12(3):e0172092. doi: 10.1371/journal.pone.0172092. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Zhou Z, Wang B, Hu S, Zhang C, Ma X, Qi Y. Genetic variations in GJA3, GJA8, LIM2, and age-related cataract in the Chinese population: a mutation screening study. Mol Vis. 2011;17:621–626. [PMC free article] [PubMed] [Google Scholar]
- 9.Chylack LT, Jr, Leske MC, McCarthy D, Khu P, Kashiwagi T, Sperduto R. Lens opacities classification system II (LOCS II) Arch Ophthalmol. 1989;107(7):991–997. doi: 10.1001/archopht.1989.01070020053028. [DOI] [PubMed] [Google Scholar]
- 10.Klein BE, Klein R, Linton KL. Prevalence of age-related lens opacities in a population. The Beaver Dam Eye Study. Ophthalmology. 1992;99(4):546–552. doi: 10.1016/s0161-6420(92)31934-7. [DOI] [PubMed] [Google Scholar]
- 11.Goodenough DA. The crystalline lens. A system networked by gap junctional intercellular communication. Semin Cell Biol. 1992;3(1):49–58. doi: 10.1016/s1043-4682(10)80007-8. [DOI] [PubMed] [Google Scholar]
- 12.Jiang JX. Gap junctions or hemichannel-dependent and independent roles of connexins in cataractogenesis and lens development. Curr Mol Med. 2010;10(9):851–863. doi: 10.2174/156652410793937750. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Mathias RT, White TW, Gong X. Lens gap junctions in growth, differentiation, and homeostasis. Physiol Rev. 2010;90(1):179–206. doi: 10.1152/physrev.00034.2009. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Zhou Z, Wang B, Hu S, Zhang C, Ma X, Qi Y. Genetic variations in GJA3, GJA8, LIM2, and age-related cataract in the Chinese population: a mutation screening study. Mol Vis. 2011;17:621–626. [PMC free article] [PubMed] [Google Scholar]
- 15.Yao Y, Zheng X, Ge X, Xiu Y, Zhang L, Fang W, Zhao J, Gu F, Zhu Y. Identification of a novel GJA3 mutation in a large Chinese family with congenital cataract using targeted exome sequencing. PLoS One. 2017;12(9):e0184440. doi: 10.1371/journal.pone.0184440. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Micheal S, Niewold ITG, Siddiqui SN, Zafar SN, Khan MI, Bergen AAB. Delineation of novel autosomal recessive mutation in GJA3 and autosomal dominant mutations in GJA8 in Pakistani congenital cataract families. Genes (Basel) 2018;9(2):pii:E112. doi: 10.3390/genes9020112. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Berry V, Ionides ACW, Pontikos N, Moghul I, Moore AT, Cheetham ME, Michaelides M. Whole-genome sequencing reveals a recurrent missense mutation in the Connexin 46 (GJA3) gene causing autosomal-dominant lamellar cataract. Eye (Lond) 2018;32:1661–1668. doi: 10.1038/s41433-018-0154-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Zhang L, Qu X, Su S, Guan L, Liu P. A novel mutation in GJA3 associated with congenital Coppock-like cataract in a large Chinese family. Mol Vis. 2012;18:2114–2118. [PMC free article] [PubMed] [Google Scholar]
- 19.Shiels A, Hejtmancik JF. Mutations and mechanisms in congenital and age-related cataracts. Exp Eye Res. 2017;156:95–102. doi: 10.1016/j.exer.2016.06.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Hawse JR, Hejtmancik JF, Horwitz J, Kantorow M. Identification and functional clustering of global gene expression differences between age-related cataract and clear human lenses and aged human lenses. Exp Eye Res. 2004;79(6):935–940. doi: 10.1016/j.exer.2004.04.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Su D, Hu S, Guan L, Wu X, Shi C, Yang X, Ma X. Down-regulation of GJA3 is associated with lens epithelial cell apoptosis and age-related cataract. Biochem Biophys Res Commun. 2017;484(1):159–164. doi: 10.1016/j.bbrc.2017.01.050. [DOI] [PubMed] [Google Scholar]
- 22.Yao H, Tang X, Shao X, Feng L, Wu N, Yao K. Parthenolide protects human lens epithelial cells from oxidative stress-induced apoptosis via inhibition of activation of caspase-3 and caspase-9. Cell Res. 2007;17(6):565–571. doi: 10.1038/cr.2007.6. [DOI] [PubMed] [Google Scholar]