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        A pilot exome-wide association study of age-related cataract in Koreans

        2016-12-13 11:16:09SangYongEomDongHyukYimJungHyunKimJooByungChaeYongDaeKimHeonKim
        THE JOURNAL OF BIOMEDICAL RESEARCH 2016年3期

        Sang-Yong Eom, Dong-Hyuk Yim, Jung-Hyun Kim, Joo-Byung Chae, Yong-Dae Kim, Heon Kim,?

        1Center for Farmer's Safety and Health, Chungbuk National University Hospital, Cheongju, Chungbuk 28644, Republic of Korea;

        2Department of Preventive Medicine, College of Medicine, Chungbuk National University, Cheongju, Chungbuk 28644, Republic of Korea;

        3Department of Optometry, Daejeon Health Science College, Daejeon 34504, Republic of Korea;

        4Department of Ophthalmology, College of Medicine, Chungbuk National University, Cheongju 28644, Republic of Korea.

        A pilot exome-wide association study of age-related cataract in Koreans

        Sang-Yong Eom1,2, Dong-Hyuk Yim1,2, Jung-Hyun Kim3, Joo-Byung Chae4, Yong-Dae Kim1,2, Heon Kim1,2,?

        1Center for Farmer's Safety and Health, Chungbuk National University Hospital, Cheongju, Chungbuk 28644, Republic of Korea;

        2Department of Preventive Medicine, College of Medicine, Chungbuk National University, Cheongju, Chungbuk 28644, Republic of Korea;

        3Department of Optometry, Daejeon Health Science College, Daejeon 34504, Republic of Korea;

        4Department of Ophthalmology, College of Medicine, Chungbuk National University, Cheongju 28644, Republic of Korea.

        Age-related cataract (ARC) is the most common cause of visual impairment and blindness worldwide. A previous study reported that genetic factors could explain approximately 50% of the heritability of cataract. However, a genetic predisposition to ARC and the contributing factors have not yet been elucidated in the Korean population. In this study, we assessed the influence of genetic polymorphisms on the risk of ARC in Koreans, including 156 cataract cases and 138 healthy adults. We conducted an exome-wide association study using Illumina Human Exome-12v1.2 platform to screen 244,770 single nucleotide polymorphisms (SNPs). No SNPs reached exome-wide significance level of association (P < 1×10-6). B3GNT4 rs7136356 showed the most significant association with ARC (P = 6.54×10-5). Two loci (MUC16 and P2RY2) among the top 20 ARC-associated SNPs were recognized as probably linked to cataractogenesis. Functions of these genes were potentially related to regulating dehydration or homeostasis of the eyes, and showed a potential association with dry eye disease. This finding suggests that mucin- and dry eye disease-related genes may play a significant role in cataractogenesis. Our study provides insight into the genetic predisposition of ARC in Koreans. Additional studies with larger sample sizes are required to confirm the results of this study.

        age-related cataract, exome-wide association study, single nucleotide polymorphism, genetic predisposition, dry eye disease

        Introduction

        Age-related cataract (ARC) is the primary cause of blindness worldwide[1]. Global prevalence of cataract is estimated to rise continuously due to increasing aging population[1-2]. Numerous studies have identified potential risk factors for ARC, such as increasing age, use of tobacco and alcohol, low socioeconomic status, diabetes, hypertension, and exposure to sunlight[1-4].

        Genetic factors are also associated with the pathogenesis of ARC. Twin studies have shown that genetic factors could explain approximately 50% of heritabilityof cataract, and those factors have a larger contribution to the variation of ARC compared to environmental factors[5-6]. Several studies have evaluated genetic predisposition for ARC using a candidate gene approach, but the results are inconsistent; thus, the causal genetic factors remain inconclusive at present[6-7].

        Recently, Liao et al. conducted the first genome-wide association study for age-related nuclear cataract in a multi-ethnic Asian population, and identified two susceptibility loci that were suggested to be located in KCNAB1 on chromosome 3q25.31 and in the proximity of CRYAA on chromosome 21[8]. However, they also found significant heterogeneity in the associations across ethnicities, even among Asians. These inter-ethnic differences in genetic predisposition or gene-environment interactions in ARC may contribute to the observed differences in the prevalence or age at onset for ARC among studies and populations[9-10].

        Prevalence of ARC in Korean population is higher than that in any other ethnic group, and approximately 90% of individuals aged 70 years and older have a high possibility for developing ARC[11]. This suggests a strong influence of a genetic factor or a geneenvironment interaction effect for ARC in general, and that these effects might be particularly important in the Korean population. However, genetic predisposition for ARC in Koreans has not been elucidated to date. Hence, in this pilot study, we assessed the influence of genetic polymorphisms on the risk of ARC in a Korean population using an exome-wide screening method.

        Materials and methods

        Study subjects

        The study subjects included 294 residents in rural villages or Cheongju City in Chungbuk Province, Korea. Trained interviewers filled out a questionnaire including items on demographic factors, working history, smoking habit, alcohol drinking, and history of major systemic diseases, eye diseases, and cataract surgery. All of the subjects provided informed consent and underwent an assessment of corrected and uncorrected visual acuity and reflective error measurement with an auto-reflector (model ARK-530A, Nidek, Japan). Cataracts were identified by slit-lamp examination with a portable slit lamp (model XL-1, Shin-Nippon, Japan). Subjects with cataracts or cataract extraction upon slit-lamp examination were classified as cataract-prevalent cases. Finally, 156 cataract cases and 138 healthy controls were included in this study. Peripheral blood samples were collected from all the subjects for genetic analysis. The study followed the tenets of the Declaration of Helsinki and the protocol was approved by the Institutional Review Board of Chungbuk National University Hospital (CBNUH-2015-06-019). All subjects provided informed consent.

        Exome-wide association screening and quality control

        Genomic DNA was isolated from peripheral blood using a DNA purification kit (DNA Extractor WB, Wako, Osaka, Japan) according to the manufacturer's protocol. All DNA samples were electrophoresed on 1% agarose gel, and samples with intact genomic DNA showing no smearing on agarose gel electrophoresis were selected for further analysis. Exome-wide association screening was conducted using Human Exome Chip v1.2 platform (Illumina, San Diego, CA, USA) in which 244,770 single nucleotide polymorphisms (SNPs) could be simultaneously analyzed. SNP chip data were checked for quality using the call rate and Hardy-Weinberg equilibrium test.

        Statistical analysis

        Associations between ARC and SNPs were estimated by unconditional logistic regression analysis with an additive genetic model. To maximize the opportunity to detect an association between SNPs and the risk of ARC, we identified a subgroup with an extreme phenotype, designated as "super-cases" (early onset cases; age at diagnosis <65 years), which were compared to corresponding “super-controls” (healthy elderly controls; age ≥65 years), and further conducted subgroup analysis. We used Bonferroni correction for multiple tests (n = 32,865 tests) and set the statistical significance and suggestive threshold to a P-value less than 1.0×10-6and 1.0×10-4, respectively. All genetic association analyses were performed using PLINK v 1.07 software. Manhattan plot of results of exomewide association study was generated using Haploview 4.2 software. In silico analysis was performed using Polyphen-2 and SIFT program to predict the potential effect of each SNP on protein function[12-13].

        Results

        The average call rate of all samples was greater than 99.92%. Monomorphic SNPs (n = 199,391), 54 SNPs not in Hardy-Weinberg equilibrium (P < 0.001), or SNPs with call rates less than 95% (n = 5,719) were excluded. The 32,865 SNPs located on autosomal chromosomes that satisfied the criterion of a minor allele frequency >1% were selected for final analysis.

        The Manhattan plot of P-values (in –log-10 scales) derived from the association analysis between ARC and SNPs using unconditional logistic regression analysis with an additive genetic model is shown in Fig. 1. The peak signal was observed at the rs7136356 locus inexon 2 of the UDP-GlcNAc:betaGal beta-1,3-N-acetylglucosaminyltransferase 4 (B3GNT4) gene on chromosome 12. B3GNT4 rs7136356 showed the strongest association with ARC and achieved the suggestive association level applied in this study (P = 6.54×10-5).

        Fig. 1 Manhattan plot for the exome-wide association study of age-related cataract. P-values in –log10 scale are plotted against their chromosomal locations. The blue horizontal line indicates the suggestive association level (P = 1.00×10-4). The arrow indicates B3GNT4 rs7136356, which showed the strongest association with age-related cataract (P = 6.54×10-5).

        The top 20 most significantly associated SNPs in the analysis of 156 cataract cases and 138 healthy controls are presented in Table 1. Among them, four nonsynonymous SNPs (rs2547065, rs60106152, rs1108380, and rs17000957) of the mucin 16, cell surface-associated (MUC16) gene and rs663263 of the chemokine (C-C motif) ligand 25 (CCL25) gene were located on chromosome 19. There were also four other SNPs (rs663263, rs2505323, rs2505327, and rs2429485) in patched domain containing 3 (PTCHD3) on chromosome 10 that showed significant associations with ARC.

        In the subgroup analysis comparing super-cases and super-controls, there were no significant SNPs associated with ARC after adjustment for multiple testing. Furthermore, there were no shared SNPs among the top 20 most significantly associated SNPs in the total analysis and subgroup analysis. The intergenic SNP rs10240278 between ADP-ribosylation factor-like GTPase 4A (ARL4A) and ribosomal protein L26 pseudogene 21 (RPL26P21), located on chromosome 7, showed a suggestive association with ARC (odds ratio = 0.37, P = 9.00×10-5) (data not shown).

        Discussion

        To the best of our knowledge, this pilot study presents the first potential evidence of an association between genetic variants and ARC in Korean population. Although no SNPs reached the threshold for statistical significance of an exome-wide association study (P <1.0×10-6), our study nevertheless provides some insight into the genetic predisposition of ARC in Koreans.

        In our study, B3GNT4 rs7136356 was suggestively associated with ARC. B3GNT4 rs7136356 is a nonsynonymous SNP that results in the substitution from proline to alanine at position 8. In silico analysis using PolyPhen-2 estimated that this amino acid change is “possibly damaging” (score: 0.679), and may have a regulatory role of exon splicing enhancement or silencing. However, the roles of this SNP in cataract, as well as in eye diseases in general or other diseases, remain unknown. B3GNT4 is a member of the beta-1,3-N-acetylglucosaminyl transferase protein family and is able to catalyze the initiation and elongation of poly-N-acetyllactosamine sugar chains[14].

        Interestingly, 13 of the genes included in the list of the 20 most highly associated SNPs in this study (e.g., B3GNT4, MUC16, HHLA2, FAM118A, ALK, PTCHD3, P2RY2, and SLC10A2) functionally clustered as glycosylation-associated genes or transmembrane proteins.

        MUC16 is a membrane-associated mucin protein that is expressed on the human ocular surface[15]. MUC16 is also well known as an ovarian tumor cell antigen (CA125)[16], and has been detected in human tears as well as an important component of the glycocalyx barrier at the ocular surface[15]. Therefore, MUC16 might play a significant role in this barrier as a defense molecule. Blalock et al. demonstrated that MUC16 plays a pivotal role in preventing bacterial adherence[17]. MUC16 has also been reported to be involved in themaintenance of hydration and lubrication of the epithelial surface[18]. Moreover, MUC16 expression was significantly decreased in patients with an unstable tear film or aqueous deficiency, and alteration of MUC16 has been associated with dry eye syndrome[15,19].

        Table 1 Top 20 SNPs most significantly associated with age-related cataract.

        Furthermore, purinergic receptor P2Y, G-protein coupled, 2 (P2RY2), which harbored the 12thranked associated SNP (rs7111814) in this study, is also linked to dry eye syndrome through its role in regulation of mucin secretion at the ocular surface[20-21]. Recently, an agonist of P2Y2 receptor (diquafosol) was developed as a new pharmacologic agent for dry eye disease[20]. In addition, B3GNT4, which was the most strongly associated locus in the present study, shows glycosyl transferase activity that helps to regulate the formation of mucin by O-glycosylation[22].

        These facts suggest that mucin- and dry eye disease-related genes might play a significant role in cataractogenesis. Although there is no direct evidence that dry eye disease causes cataract, both of these conditions commonly occur in the elderly population, and share similar risk factors such as smoking and inflammation[2,23]. In particular, corticosteroid use, which is one of the treatments for dry eye disease, is a risk factor for cataract[2,23]. Dry eye disease increases oxidative stress in ocular tissues, because human tears contain various nonenzymatic and enzymatic antioxidants such as ascorbic acid, uric acid, glutathione, l-cysteine and l-tyrosine, and superoxide dismutase[24]. Oxidative stress is directly associated with the development of ARC through damage to lens proteins and lipids[25]. The human tear film is composed of 99% water, and primarily functions to absorb ultraviolet radiation from sunlight. Consequently, an individual with dry eyes might have a higher level of exposure to ultraviolet radiation in the cornea and lens, due to loss of the tear film water[26-27]. Therefore, SNPs in dry eye disease-related genes may contribute to genetic susceptibility for ARC by influencing the dehydration condition in the eyes.

        In subgroup analysis, the intergenic SNP rs10240278 between ARL4A and RPL26P21 showed a suggestive association with ARC. RPL26P21 is a pseudogene that might be unexpressed and functionless. ARL4A is a member of the ADP-ribosylation factor family of GTP-binding proteins[28], and there is little information about this gene with respect to human cataractogenesis. However, one study showed that ethyl pyruvate inhibited ARL4A expression in human corneal keratocytes, which protects cataract formation by decreasing oxidative stress, in a rodent model[29].

        This pilot study has limited statistical power due to the small sample size and uneven distribution of age in the cases and controls. We also cannot exclude the possibility of outcome heterogeneity. There are three mainsubtypes of cataract, which included cortical, nuclear, and posterior subcapsular, but we did not classify the cases according to cataract subtypes[2]. As different subtypes have different etiologies and risk factors, a genetic association study among subjects with a homogenous cataract type is needed to identify a more specific genetic susceptibility marker[3]. This heterogeneity in outcome might bias the observed association toward a null result. Therefore, our results should be interpreted with caution and require further investigation for confirmation.

        In conclusion, this pilot exome-wide association study has identified potentially plausible genes linked to cataractogenesis. Functions of these genes are associated with mechanisms of the regulation of dehydration or homeostasis of the eyes, indicating a connection with dry eye syndrome. Additional studies with larger sample sizes are needed to detect a significant association between the candidate SNPs and risk of ARC.

        References

        [1] Pascolini D, Mariotti SP. Global estimates of visual impairment: 2010[J]. Br J Ophthalmol, 2012,96(5):614-618.

        [2] Asbell PA, Dualan I, Mindel J, et al. Age-related cataract [J]. Lancet, 2005,365(9459):599-609.

        [3] West S. Epidemiology of cataract: accomplishments over 25 years and future directions[J]. Ophthalmic Epidemiol, 2007,14(4):173-178.

        [4] Rim TH, Kim DW, Kim SE, et al. Factors Associated with Cataract in Korea: A Community Health Survey 2008-2012[J]. Yonsei Med J, 2015,56(6):1663-1670.

        [5] Hammond CJ, Duncan DD, Snieder H, et al. The heritability of age-related cortical cataract: the twin eye study[J]. Invest Ophthalmol Vis Sci, 2001,42(3):601-605.

        [6] Hammond CJ, Snieder H, Spector TD, et al. Genetic and environmental factors in age-related nuclear cataracts in monozygotic and dizygotic twins[J]. N Engl J Med, 2000,342(24):1786-1790.

        [7] Hamada N, Fujimichi Y. Role of carcinogenesis related mechanisms in cataractogenesis and its implications for ionizing radiation cataractogenesis[J]. Cancer Lett, 2015,368(2):262-274.

        [8] Liao J, Su X, Chen P, et al. Meta-analysis of genome-wide association studies in multiethnic Asians identifies two loci for age-related nuclear cataract[J]. Hum Mol Genet, 2014,23(22):6119-6128.

        [9] Congdon N, Vingerling JR, Klein BE, et al. Prevalence of cataract and pseudophakia/aphakia among adults in the United States[J]. Arch Ophthalmol, 2004,122(4):487-494.

        [10] Sacca SC, Bolognesi C, Battistella A, et al. Geneenvironment interactions in ocular diseases[J]. Mutat Res, 2009,667(1-2):98-117.

        [11] Rim TH, Kim MH, Kim WC, et al. Cataract subtype risk factors identified from the Korea National Health and Nutrition Examination survey 2008-2010[J]. BMC Ophthalmol, 2014,14:4. doi: 10.1186/1471-2415-14-4

        [12] Adzhubei IA, Schmidt S, Peshkin L, et al. A method and server for predicting damaging missense mutations[J]. Nat Methods, 2010,7(4):248-249.

        [13] Kumar P, Henikoff S, Ng PC. Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm[J]. Nat Protoc, 2009,4(7):1073-1081.

        [14] Shiraishi N, Natsume A, Togayachi A, et al. Identification and characterization of three novel beta 1,3-N-acetylglucosaminytransferases structurally related to the beta 1,3-galactosyltransferase family[J]. J Biol Chem, 2001,276(5):3498-3507.

        [15] Perez BH, Gipson IK. Focus on Molecules: human mucin MUC16[J]. Exp Eye Res, 2008,87(5):400-401.

        [16] Yin BW, Lloyd KO. Molecular cloning of the CA125 ovarian cancer antigen: identification as a new mucin, MUC16[J]. J Biol Chem, 2001,276(29):27371-27375.

        [17] Blalock TD, Spurr-Michaud SJ, Tisdale AS, et al. Functions of MUC16 in corneal epithelial cells[J]. Invest Ophthalmol Vis Sci, 2007,48(10):4509-4518.

        [18] Govindarajan B, Gipson IK. Membrane-tethered mucins have multiple functions on the ocular surface[J]. Exp Eye Res, 2010,90(6):655-663.

        [19] Shimazaki-Den S, Dogru M, Higa K, et al. Symptoms, visual function, and mucin expression of eyes with tear film instability[J]. Cornea, 2013,32(9):1211-1218.

        [20] Lau OC, Samarawickrama C, Skalicky SE. P2Y2 receptor agonists for the treatment of dry eye disease: a review[J]. Clin Ophthalmol, 2014,8:327-334. doi: 10.2147/OPTH.S39699

        [21] Jumblatt JE, Jumblatt MM. Regulation of ocular mucin secretion by P2Y2 nucleotide receptors in rabbit and human conjunctiva[J]. Exp Eye Res, 1998,67(3):341-346.

        [22] Bennett EP, Mandel U, Clausen H, et al. Control of mucin-type O-glycosylation: a classification of the polypeptide GalNActransferase gene family[J]. Glycobiology, 2012,22(6):736-756.

        [23] Javadi MA, Feizi S. Dry eye syndrome[J]. J Ophthalmic Vis Res, 2011,6(3):192-198.

        [24] Chen Y, Mehta G, Vasiliou V. Antioxidant defenses in the ocular surface[J]. Ocul Surf, 2009,7(4):176-185.

        [25] Vinson JA. Oxidative stress in cataracts[J]. Pathophysiology, 2006,13(3):151-162.

        [26] Behar-Cohen F, Baillet G, de Ayguavives T, et al. Ultraviolet damage to the eye revisited: eye-sun protection factor (E-SPF(R)), a new ultraviolet protection label for eyewear[J]. Clin Ophthalmol, 2014;8:87-104. doi: 10.2147/OPTH.S46189

        [27] Choy CK, Cho P, Benzie IF. Antioxidant content and ultraviolet absorption characteristics of human tears[J]. Optom Vis Sci, 2011,88(4):507-511.

        [28] Hofmann I, Thompson A, Sanderson CM, et al. The Arl4 family of small G proteins can recruit the cytohesin Arf6 exchange factors to the plasma membrane[J]. Curr Biol, 2007,17(8):711-716.

        [29] Harvey SA, Guerriero E, Charukamnoetkanok N, et al. Responses of cultured human keratocytes and myofibroblasts to ethyl pyruvate: a microarray analysis of gene expression[J]. Invest Ophthalmol Vis Sci, 2010,51(6):2917-2927.

        ? Professor Heon Kim, Center for Farmer's Safety and Health, Chungbuk National University Hospital, Cheongju, Chungbuk, Republic of Korea. Tel: +82-10-8271-2130, E-mail:kimheon@cbu.ac.kr.

        06 January 2016, Revised 26 January 2016, Accepted 30 January 2016, Epub 20 May 2016

        R776, Document code: A.

        The authors reported no conflict of interest.

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