June 2012
Volume 53, Issue 7
Free
Genetics  |   June 2012
Association of TP53 Polymorphisms with Primary Open-Angle Glaucoma: A Meta-Analysis
Author Affiliations & Notes
  • Yatu Guo
    From the Tianjin Medical University, Tianjin, China; the
    Tianjin Eye Hospital, Tianjin Eye Institute, Tianjin Key Lab of Ophthalmology and Visual Science, Tianjin, China; the
    Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, Maryland; and the
  • Hongtuan Zhang
    Second Hospital of Tianjin Medical University, Tianjin, China; the
  • Xia Chen
    Tianjin Eye Hospital, Tianjin Eye Institute, Tianjin Key Lab of Ophthalmology and Visual Science, Tianjin, China; the
  • Xiong Yang
    Second Hospital of Tianjin Medical University, Tianjin, China; the
  • Wenbo Cheng
    From the Tianjin Medical University, Tianjin, China; the
    Department of Ophthalmology, The People's Hospital of Changzhi, Shanxi, China.
  • Kanxing Zhao
    Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, Maryland; and the
  • Corresponding author: Kanxing Zhao, Tianjin Eye Hospital, Tianjin Eye Institute, Tianjin Key Lab of Ophthalmology and Visual Science, Tianjin, China 300020; zhaokanxing@yahoo.com.cn.  
Investigative Ophthalmology & Visual Science June 2012, Vol.53, 3756-3763. doi:10.1167/iovs.12-9818
  • Views
  • PDF
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Yatu Guo, Hongtuan Zhang, Xia Chen, Xiong Yang, Wenbo Cheng, Kanxing Zhao; Association of TP53 Polymorphisms with Primary Open-Angle Glaucoma: A Meta-Analysis. Invest. Ophthalmol. Vis. Sci. 2012;53(7):3756-3763. doi: 10.1167/iovs.12-9818.

      Download citation file:


      © ARVO (1962-2015); The Authors (2016-present)

      ×
  • Supplements
Abstract

Purpose.: To offer a comprehensive evaluation of the potential associations of TP53 polymorphisms with primary open-angle glaucoma (POAG) through a systematic review and meta-analysis of candidate genetic association study.

Methods.: Medline, Embase, Science Citation Index, the Cochrane Library, and other databases (up to January 20, 2012) were searched by two investigators independently. Pooled odd ratios (ORs) and 95% confidence interval (CI) were used to assess the strength of the associations between two TP53 polymorphisms (codon 72 in exon 4 and 16 base-pair [bp] insertion in intron 3) and POAG. Statistical analysis was performed with a commercial statistical and data analysis software package.

Results.: Nine independent studies on TP codon 72 (1930 cases and 1463 controls) and four articles on TP intron 3 16-bp insertion (858 cases and 683 controls) were identified. The overall results showed that there was significant association between TP53 codon 72 genotype and POAG risk in the recessive model (OR = 1.31, 95% CI 1.05−1.64, P = 0.017). Also, our analysis suggested that TP53 intron 3 16-bp insertion polymorphism was associated with decreased POAG risk in overall population when examining the contrast of Ins versus Del (OR 0.75, 95% CI = 0.57–0.97, P = 0.031). In subgroup analyses for ethnicity (Caucasian, Asian), we detected the association between codon 72 polymorphism and risk for POAG in Asian populations (recessive model: OR = 1.36, 95% CI 1.03−1.80, P = 0.026) but not in Caucasian populations. However, no significant finding was noted between P53Arg72Pro and risk for open-angle glaucoma either in high tension glaucoma or in normal tension glaucoma. Because of insufficient studies on TP53 16-bp insertion polymorphism, no subgroup analyses were conducted according to ethnicity and glaucoma subtype to detect the effect of this polymorphism on the susceptibility to POAG.

Conclusions.: This meta-analysis showed the evidence that TP53 codon 72 (CC versus CG+GG) and intron 3 16-bp insertion (Ins versus Del) polymorphisms may affect individual susceptibility to POAG. Moreover, stratified analyses that detected the effect of TP53 codon 72 polymorphism seemed to be varied by ethnicity. Given the limited sample size, further investigations are needed to validate the association.

Introduction
As the second leading cause of blindness in the world, glaucoma is characterized by visual field defects, retinal ganglion cell death, and progressive degeneration of the optic nerve. 1,2 Primary open-angle glaucoma (POAG) is the major type of primary glaucoma in most populations, and affects 67 million individuals worldwide. 35 It is recognized that POAG is a multifactorial disorder involving the role of multiple genes as well as environmental factors. 614 Family studies and mutations in three genes (myocilin [MYOC], optineurin [OPTN], and WD repeat domain 36 [WDR36]) support a high heritability of POAG, thus suggesting a definite genetic basis for POAG. 1520 Quite a number of POAG susceptibility genes have been identified. 2128 The majority of findings are conflicting, including those for the Tumor Protein 53 (TP53) gene located on the short arm of chromosome 17. 29,30  
The TP53 (OMIM/191170) is a prototypical tumor suppressor gene encoding a 53-kDa protein (p53) with important functions in cell cycle control, apoptosis, and maintenance of DNA integrity (4–6). 31,32 The importance of p53 in cell cycle regulation (via gene transcription) and DNA integrity is such that it has been called the “guardian of the genome.” 33,34 It has been considered as the key regulatory gene for apoptosis, which may be involved in the death of retinal ganglion cells in glaucoma. 35,36  
In the past years, as a good potential candidate susceptibility gene for glaucoma, TP53 polymorphisms have attracted widespread attention. Although several TP53 polymorphisms have been investigated as risk factors for POAG, by far the most extensively investigated would be two polymorphisms: one is a single nucleotide polymorphism (SNP) in exon 4 of p53 at codon 72, where a cytosine (C; variant allele) for guanine (G) substitution (Arg72Pro); another is a 16 base-pair (bp) insertion/deletion polymorphism located within TP53 intron 3. However, whether TP53 gene polymorphisms may contribute to the pathogenesis of POAG is still strongly debated. Lin et al. 37 first reported the p53 codon 72 polymorphism to be associated with POAG. However, the association between such polymorphisms in p53 and POAG remains controversial according to previous reports. 3844  
To date, no meta-analysis has been conducted to elevate the association of the polymorphisms of TP53 with POAG. Thus, it stimulated us to conduct a meta-analysis based on a total of nine independent studies, which may provide the evidence for the association of p53 polymorphisms with POAG susceptibility. 
Methods
Publication Search
A systematic literature search was performed for articles regarding TP53 polymorphisms with POAG. The MEDLINE, EMBASE, Science Citation Index, the Cochrane Library, and Chinese National Knowledge Infrastructure were simultaneously used with key terms “TP53” or “tumor suppressor protein gene”; “P53”; “polymorphism,” “SNP,” or “single nucleotide polymorphism”; “variation” or “mutation”; “glaucoma,” “primary open-angle glaucoma,” or “POAG”; or “high tension glaucoma” or “normal tension glaucoma.” Relevant publications were examined for references until no further studies were found. The electronic databases were last searched on January 20th, 2012. 
Inclusion Criteria
The following inclusion criteria were used to select literatures for the meta-analysis: (1) case-control, nested case-control, or cohort studies; (2) description of the association of P53 polymorphisms with POAG; and (3) the number of cases and controls, number of different genotypes for p53 codon 72, intron 3 16-bp insertion in cases and controls, as well as the information that can help infer the results in the published studies. 
Data Extraction
Two observers (YTG, HTZ) independently abstracted data from all eligible publications onto paper data collection forms. Two reviewers were blinded to the details (title, author, and academic address) of these studies during assessment. Disagreements were resolved by discussion or consensus involving a third reviewer (XC) when required. The following items were collected from each study: first author's surname, year of publication, statistical data, ethnicity, total number of cases and controls, as well as numbers of cases and controls for each TP53 genotypes, respectively. 
Statistical Analysis
All statistical analyses were performed using a commercial statistical software package (Stata Statistics Software, Version 10.0; StataCorp LP, College Station, TX). Two-sided P values < 0.05 were considered statistically significant. 
Hardy–Weinberg equilibrium (HWE) in controls was calculated again in our meta-analysis. The χ 2 goodness of fit was used to test deviation from HWE (significant at the 0.05 level). 
The effect measure of choice was a pooled odds ratio (OR) with its corresponding 95% confidence interval (CI). Heterogeneity assumption was checked by Q-test. A value of P < 0.10 for the Q-test indicated lack of heterogeneity among the studies. Based on Q-test value, two models of meta-analysis were applied for dichotomous outcomes: A fixed-effects model, using the Mantel–Haenszel (M-H) method, was used to calculate the pooled ORs when the Q-test value was ≥0.1. By contrast, a random-effects (DerSimonian and Laird [D+L]) model was utilized if the Q-test value was <0.1. First, we compared allele frequencies (Allele C versus Allele G; Ins versus Del) between cases and controls. Then, we examined TP53 genotypes using additive (CC versus GG; Ins/Ins versus Del/Del), recessive (CC versus GC+ GG; Ins/Ins versus Del/Ins+Del/Del), and dominant (GC + CC versus GG; Del/Ins+Ins/Ins versus Del/Del) genetic models for C and Ins alleles. Furthermore, subgroup analyses were performed by ethnicity (Asian, Caucasian) and glaucoma subtypes (high tension glaucoma [HTG]; normal tension glaucoma [NTG]). 
Finally, publication bias was assessed by performing Begg's funnel plots qualitatively and evaluated by Egger's test quantitatively (P < 0.05 was considered representative of statistically significant publication bias). 
Results
Literature Search and Characteristics
The initial search yielded 228 articles. Based on the title, the content of the abstract, and key words, 218 studies were excluded. Ten articles were reviewed in their entirety. One arm had to be excluded because of no useful data available. Finally, nine studies that met our inclusion criteria were included in this review. 3745 The flow chart of literature search is shown in Figure 1. Nine studies 3745 were included in the meta-analysis of p53 codon 72 genotype (1930 cases, 1463 controls), of which, in two studies, 43,44 the distribution of the genotypes in the control group were not in HWE (Fisher's exact test, P < 0.05). Four case-control studies 3840,42 were included in the meta-analysis of intron 3 16-bp insertion genotype (858 cases, 683 controls). Similarly, one study's distribution of the genotypes in the control group was not in HWE. 42 For the meta-analysis of TP53 codon 72, four studies on Caucasians, 40,41,43,44 four studies on Asians, 37,38,42,45 and one study on Brazilians were included. 44 Also four studies 4042,45 on HTG and NTG were included in the meta-analysis of p53 codon 72. For the TP53 intron 3 16-bp insertion, subgroup analyses included that two Caucasian studies 39,40 and two Asian studies 38,42 for ethnicity as well as two studies 40,42 for subtype of POAG. Detailed study characteristics are summarized in Table 1
Figure 1. 
 
Flow chart of literature search and study selection.
Figure 1. 
 
Flow chart of literature search and study selection.
Table 1.  
 
Main Characteristics of Studies Included in This Meta-Analysis
Table 1.  
 
Main Characteristics of Studies Included in This Meta-Analysis
P53 Codon72
Author Year Ethnicity HWE Cases Control
GG GC CC GG GC CC
 Lin et al. 2002 Asian 0.96 12 26 20 25 26 8
 Acharva et al. 2002 Asian 0.98 23 30 14 30 57 25
 Dimasi et al. 2005 Caucasian 0.49 296 186 41 109 57 12
 Mabuchi et al. 2009 Asian 0.95 177 197 51 83 83 23
 Daugherty et al. 2009 Caucasian 0.87 124 55 12 82 72 13
 Saglar et al. 2009 Caucasian 0.02 19 44 12 41 69 9
 Silva et al. 2009 Brazilian 0.0003 24 78 2 18 40 0
 Fan et al. 2010 Asian 0.51 100 176 121 55 108 38
 Blanco-Marchite et al. 2011 Caucasian 0.57 148 106 14 252 111 17
HTG
 Dimasi et al. 2005 Caucasian 0.49 158 101 24 109 57 12
 Mabuchi et al. 2009 Asian 0.95 85 102 25 83 83 23
 Daugherty et al. 2009 Caucasian 0.88 89 40 10 82 72 13
 Fan et al. 2010 Asian 0.51 64 114 74 55 108 38
NTG
 Dimasi et al. 2005 Caucasian 0.49 29 28 5 109 57 12
 Mabuchi et al. 2009 Asian 0.95 92 95 26 83 83 23
 Daugherty et al. 2009 Caucasian 0.88 36 15 1 82 72 13
 Fan et al. 2010 Asian 0.51 22 43 34 55 108 38
P53 Intron 3 16-bp Insertion
Del/Del Del/Ins Ins/Ins Del/Del Del/Ins Ins/Ins
 Acharva et al. 2002 Asian 0.14 56 11 0 67 33 0
 Mabuchi et al. 2009 Asian 425 0 0 189 0 0
 Daugherty et al. 2009 Caucasian 0.51 145 42 4 117 43 7
 Blanco-Marchite et al. 2011 Caucasian 0.98 135 38 2 167 55 5
HTG
 Mabuchi et al. 2009 Asian 212 0 0 189 0 0
 Daugherty et al. 2009 Caucasian 0.51 107 29 3 117 43 7
NTG
 Mabuchi et al. 2009 Asian 213 0 0 189 0 0
 Daugherty et al. 2009 Caucasian 0.51 38 14 0 117 43 7
Meta-Analysis Results
The overall analysis investigating the recessive model for the C allele (CC versus CG+GG) showed significant association between TP53 codon 72 polymorphism and increased open-angle glaucoma risk (OR = 1.31, 95% CI 1.05−1.64, P = 0.017; Fig. 2), although no evidence of associations was detected in the allelic, additive, and dominant models (allelic model: OR = 1.10, 95% CI 0.99–1.22, P = 0.054; additive model: OR = 1.23, 95% CI 0.97–1.56, P = 0.079; dominant model: OR = 1.06, 95% CI 0.94–1.19, P = 0.317) On the other hand, the association between the 16-bp insertion and decreased risk for POAG relative to the 16-bp deletion (Ins versus Del) revealed a significant association (OR 0.75, 95% CI = 0.57–0.97, P = 0.031; Fig. 3). No significant associations were observed between TP53 intron 3 16-bp insertion genotype and risk for POAG in the additive (OR = 0.49, 95% CI 0.18−1.32, P = 0.16), recessive (OR = 0.51, 95% CI 0.19−1.37, P = 0.18), and dominant models (OR = 1.01, 95% CI 0.87−1.17, P = 0.91). Because the Q-test of heterogeneity among studies was nonsignificant in all genetic models, a fixed-effects model was used (Table 2). 
Figure 2. 
 
Forest plot of the association between TP53 codon 72 polymorphism (CC versus CG+GG) and risk for POAG in order of publication year. The size of the square indicates the relative weight of each study. Bars, 95% CI.
Figure 2. 
 
Forest plot of the association between TP53 codon 72 polymorphism (CC versus CG+GG) and risk for POAG in order of publication year. The size of the square indicates the relative weight of each study. Bars, 95% CI.
Figure 3. 
 
Forest plot of the association between TP53 16-bp insertion polymorphism (Ins versus Del) and risk for POAG in order of publication year. The size of the square indicates the relative weight of each study. Bars, 95% CI.
Figure 3. 
 
Forest plot of the association between TP53 16-bp insertion polymorphism (Ins versus Del) and risk for POAG in order of publication year. The size of the square indicates the relative weight of each study. Bars, 95% CI.
Table 2.  
 
Results of Meta-Analysis for TP Polymorphisms and Risk of Primary Open-Angle Glaucoma
Table 2.  
 
Results of Meta-Analysis for TP Polymorphisms and Risk of Primary Open-Angle Glaucoma
Comparisons Number of Studies OR 95% CI P Value Heterogeneity Effects Model Egger's Test
I 2 P Value P > | t |
P53 Codon72
C vs. G 9 1.1 1.00–1.22 0.054 0.1264 0.125 Fixed 0.979
 Caucasian 4 1.07 0.82–1.40 0.609 9.11% 0.028 Random 0.609
 Asian 4 1.11 0.96–1.27 0.154 3.92% 0.27 Fixed 0.73
 HTG 4 1.05 0.91–1.20 0.535 4.63% 0.201 Fixed 0.225
 NTG 4 1.03 0.78–1.38 0.817 7.30% 0.063 Random 0.5
CC vs. GG 9 1.23 0.98–1.56 0.079 7.97% 0.437 Fixed 0.7
 Caucasian 4 1.2 0.81–1.77 0.36 3.67% 0.299 Fixed 0.768
 Asian 4 1.24 0.93–1.66 0.156 3.84% 0.279 Fixed 0.763
 HTG 4 1.16 0.85–1.58 0.361 1.53% 0.675 Fixed 0.278
 NTG 4 1.13 0.78–1.65 0.519 3.96% 0.266 Fixed 0.5
CC vs. CG+GG 9 1.31 1.05–1.63 0.017 7.99% 0.434 Fixed 0.96
 Caucasian 4 1.19 0.82–1.74 0.365 2.42% 0.49 Fixed 0.56
 Asian 4 1.37 1.03–1.80 0.026 5.06% 0.168 Fixed 0.964
 HTG 4 1.26 0.94–1.69 0.125 2.14% 0.544 Fixed 0.22
 NTG 4 1.25 0.88–1.78 0.22 4.89% 0.18 Fixed 0.252
CC+CG vs. GG 9 1.06 0.94–1.19 0.317 8.75% 0.364 Fixed 0.906
 Caucasian 4 1.05 0.80–1.39 0.716 7.34% 0.062 Random 0.5
 Asian 4 1.04 0.88–1.24 0.636 1.30% 0.73 Fixed 0.653
 HTG 4 1 0.85–1.18 0.999 3.41% 0.332 Fixed 0.32
 NTG 4 1.02 0.83–1.25 0.17 4.15% 0.246 Fixed 0.63
P53 Intron 3 16-bp Insertion
 Ins vs. Del 4 0.75 0.57–0.97 0.031 1.55% 0.46 Fixed 0.169
 Ins/Ins vs. Del/Del 4 0.49 0.18–1.32 0.156 0 0.96 Fixed
 Ins/Ins vs. Del/Del+Del/Ins 4 0.51 0.19–1.37 0.181 0 0.97 Fixed
 Ins/Ins+Del/Ins vs. Del/Del 4 1.01 0.87–1.17 0.91 0 1 Fixed 0.579
Next, stratified analyses by ethnicity were performed between TP53 codon 72 polymorphism and POAG risk. A significant association between TP53 Arg72Pro polymorphism and POAG susceptibility was found in Asian populations in the recessive model (OR = 1.36, 95% CI 1.03−1.80, P = 0.026), but not in Caucasian populations (Fig. 4A). Furthermore, we investigated the effect of the TP53 codon 72 genotype on the susceptibility to subtypes of POAG. Overall, no evidence of association was observed in any genetic model between TP53 Arg72Pro polymorphism and risk of NTG and HTG (Fig. 4B). Because each subgroup of TP53 16-bp insertion polymorphism studies included only two studies, the analysis was not performed and solid results need to be obtained from more large-sample and better-designed studies. 
Figure 4. 
 
Subgroup analyses of the association between TP53 codon 72 and risk for POAG in order of publication year. The size of the square indicate the relative weight of each study. Bars, 95% CI (A) Subgroup analysis stratified by ethnicity. (B) Subgroup analysis stratified by glaucoma subtype.
Figure 4. 
 
Subgroup analyses of the association between TP53 codon 72 and risk for POAG in order of publication year. The size of the square indicate the relative weight of each study. Bars, 95% CI (A) Subgroup analysis stratified by ethnicity. (B) Subgroup analysis stratified by glaucoma subtype.
Publication Bias
Publication biases were assessed by Begg's funnel plot qualitatively and Egger's test quantitatively. Neither Begg's funnel plot nor Egger's test detected any obvious evidence of publication bias in the overall and subgroup analyses for all genetic models (Fig. 5; data available in Table 2). 
Figure 5. 
 
Begg's funnel plot of TP53 codon 72 polymorphism and POAG for overall CC versus CG+GG. Each circle represents a separate study for the indicated association, and its size is proportional to the sample size of each study. The study by Silva et al. was excluded because of no homozygous subjects (CC) in the control group.
Figure 5. 
 
Begg's funnel plot of TP53 codon 72 polymorphism and POAG for overall CC versus CG+GG. Each circle represents a separate study for the indicated association, and its size is proportional to the sample size of each study. The study by Silva et al. was excluded because of no homozygous subjects (CC) in the control group.
Discussion
Primary open-angle glaucoma (POAG) is considered to be a multifactorial disease, and is estimated to have a significant heritable component. 46,47 TP53 protein product is a core component to control the apoptosis and play a vital role in the regulation of the cell cycle. 48 Thus, the TP53 polymorphisms, one of the most widely investigated polymorphisms in genetic epidemiology, have been thought to constitute a good candidate genetic risk factor for POAG. 37 Since the identification of the TP53 polymorphisms, a number of studies have investigated the genetic effect of the TP53 polymorphisms on POAG susceptibility with conflicting results. Meta-analysis, as a powerful statistical method, can provide a quantitative approach for pooling the variant results on the same topic to estimate and explain their diversity. 49,50 This led us to conduct this meta-analysis of nine published case-control studies, which may help us to distinguish the truth from the false, to explore a more robust estimate of the effects of these polymorphisms on POAG. 
The main finding of the pooled analyses showed that TP53 Arg72Pro polymorphism was a likely risk factor for POAG; meanwhile, intron 3 16-bp insertion polymorphism was detected to be associated with reduced POAG risk. However, it should be noted that genetic distributions of the controls in two studies 43,44 of Arg72Pro group and in one study 42 of 16-bp insertion group deviated from Hardy–Weinberg equilibrium, which may have been the genotyping errors or selection bias in control and/or population stratification. Therefore, as recommended by Attia and colleagues, 51 we conducted the meta-analysis again when these studies were removed. The results indicated that estimates before or after the deletion of these studies were similar, suggesting high stability of the meta-analysis results with little effect of these studies. 
The results of many studies have represented that the ethnic differences may affect genetic predisposition to POAG. 37,40 Subgroup analysis on different ethnicity was performed. Our data showed that the TP53 codon 72 polymorphisms from studies of Asian individuals were significantly associated with POAG. By contrast, it was not found in Caucasian populations. This indicates a possible role of ethnic difference in genetic background and the environment they live in. Moreover, the discrepancy may arise because studies with small sample sizes may be underpowered to detect a slight effect or may have generated a fluctuated risk estimate. 
Furthermore, the studies reported by Daugherty, 40 Fan, 45 Mabuchi, 42 and Dimasi 41 investigated the effect of this polymorphism on subtypes of open-angle glaucoma. Some of them 40 reported that higher frequencies of the Arginine allele was observed in POAG cases with NTG compared with HTG, suggesting a genetic mechanism favoring apoptosis would have a greater role in NTG. However, no evidence was found that the association was significant in NTG or HTG, probably because of small size samples and limited trials. For an insufficient number of studies, subgroup analyses could not be conducted on different races and subtypes for TP53 intronic insertion polymorphisms. Further analysis should be performed in more large-scale cohorts or case-control studies. 
Although no obvious publication bias showed some limitations in our study should be addressed and the results should be interpreted with caution. First, controls were not uniformly defined. Thus, some inevitable selection bias might exist in the results and they may not be representative of the general population. Second, this meta-analysis was limited by the number of cases and controls as well as small sample size, especially in subgroup analysis. Third, our results were based on unadjusted estimates, whereas a more precise analysis of the various groups should be conducted according to other factors. Fourth, genotyping methods were different among these studies, which might have affected the results. This discrepancy between genotyping methods highlights the need for implementing rigorous quality control procedures in future studies. Fifth, the existing studies are the lack of information about potential gene–gene or gene–environment interactions. Given that the role of several environment factors in the pathogenesis of open-angle glaucoma is established, further research should be performed in this direction. 
In conclusion, the results of this meta-analysis suggest that TP53 codon 72 polymorphism is associated with increased risk for POAG in the recessive model and 16-bp insertion polymorphism has the association with a statistically significant decrease in POAG susceptibility under the allelic model but not in other models. Meanwhile, it is worthwhile to note that TP53 codon 72 polymorphism may be involved in the pathogenesis of POAG in Asians but not in Caucasians. Due to the limitations shown earlier, well-designed studies with large sample sizes are warranted to confirm our findings. 
References
Sharts-Hopko NC Glynn-Milley C . Primary open-angle glaucoma. Am J Nurs . 2009;109:40–47 ; quiz 48. [CrossRef] [PubMed]
Coleman AL Brigatti L . The glaucomas. Minerva Med . 2001;92:365–379. [PubMed]
Cedrone C Mancino R Cerulli A Cesareo M Nucci C . Epidemiology of primary glaucoma: prevalence, incidence, and blinding effects. Prog Brain Res . 2008;173:3–14. [PubMed]
Rouland JF Berdeaux G Lafuma A . The economic burden of glaucoma and ocular hypertension: implications for patient management: a review. Drugs Aging . 2005;22:315–321. [CrossRef] [PubMed]
Quigley HA Broman AT . The number of people with glaucoma worldwide in 2010 and 2020. Br J Ophthalmol . 2006;90:262–267. [CrossRef] [PubMed]
Bonovas S Peponis V Filioussi K . Diabetes mellitus as a risk factor for primary open-angle glaucoma: a meta-analysis. Diabet Med . 2004;21:609–614. [CrossRef] [PubMed]
Bron A Chaine G Villain M Risk factors for primary open-angle glaucoma [in French]. J Fr Ophtalmol . 2008;31:435–444. [CrossRef] [PubMed]
Ozcura F Aydin S . Is diabetes mellitus a risk factor or a protector for primary open angle glaucoma? Med Hypotheses . 2007;69:233–234. [CrossRef] [PubMed]
Zanon-Moreno V Garcia-Medina JJ Zanon-Viguer V Moreno-Nadal MA Pinazo-Duran MD . Smoking, an additional risk factor in elder women with primary open-angle glaucoma. Mol Vis . 2009;15:2953–2959. [PubMed]
Charliat G Jolly D Blanchard F . Genetic risk factor in primary open-angle glaucoma: a case-control study. Ophthalmic Epidemiol . 1994;1:131–138. [CrossRef] [PubMed]
Fan BJ Wang DY Lam DS Pang CP . Gene mapping for primary open angle glaucoma. Clin Biochem . 2006;39:249–258. [CrossRef] [PubMed]
Fingert JH . Primary open-angle glaucoma genes. Eye . 2011;25:587–595. [CrossRef] [PubMed]
Liu Y Allingham RR . Molecular genetics in glaucoma. Exp Eye Res . 2011;93:331–339. [CrossRef] [PubMed]
van Koolwijk LM Despriet DD van Duijn CM Genetic contributions to glaucoma: heritability of intraocular pressure, retinal nerve fiber layer thickness, and optic disc morphology. Invest Ophthalmol Vis Sci . 2007;48:3669–3676. [CrossRef] [PubMed]
Bergen AA Leschot NJ Hulsman CA De Smet MD De Jong PT . From gene to disease; primary open-angle glaucoma and three known genes: MYOC, CYP1B1 and OPTN [in Dutch]. Ned Tijdschr Geneeskd . 2004;148:1343–1344. [PubMed]
Fingert JH Heon E Liebmann JM Analysis of myocilin mutations in 1703 glaucoma patients from five different populations. Hum Mol Genet . 1999;8:899–905. [CrossRef] [PubMed]
Pasutto F Mardin CY Michels-Rautenstrauss K Profiling of WDR36 missense variants in German patients with glaucoma. Invest Ophthalmol Vis Sci . 2008;49:270–274. [CrossRef] [PubMed]
Rezaie T Child A Hitchings R Adult-onset primary open-angle glaucoma caused by mutations in optineurin. Science . 2002;295:1077–1079. [CrossRef] [PubMed]
Fingert JH Honkanen RA Shankar SP Familial cavitary optic disk anomalies: identification of a novel genetic locus. Am J Ophthalmol . 2007;143:795–800. [CrossRef] [PubMed]
Markandaya M Ramesh TK Selvaraju V Genetic analysis of an Indian family with members affected with juvenile-onset primary open-angle glaucoma. Ophthalmic Genet . 2004;25:11–23. [CrossRef] [PubMed]
Fernandez-Martinez L Letteboer S Mardin CY Evidence for RPGRIP1 gene as risk factor for primary open angle glaucoma. Eur J Hum Genet . 2011;19:445–451. [CrossRef] [PubMed]
Junemann AG von Ahsen N Reulbach U C677T variant in the methylentetrahydrofolate reductase gene is a genetic risk factor for primary open-angle glaucoma. Am J Ophthalmol . 2005;139:721–723. [CrossRef] [PubMed]
Wirtz MK Samples JR Kramer PL Mapping a gene for adult-onset primary open-angle glaucoma to chromosome 3q. Am J Hum Genet . 1997;60:296–304. [PubMed]
Monemi S Spaeth G DaSilva A Identification of a novel adult-onset primary open-angle glaucoma (POAG) gene on 5q22.1. Hum Mol Genet . 2005;14:725–733. [CrossRef] [PubMed]
Juronen E Tasa G Veromann S Polymorphic glutathione S-transferase M1 is a risk factor of primary open-angle glaucoma among Estonians. Exp Eye Res . 2000;71:447–452. [CrossRef] [PubMed]
Wirtz MK Samples JR Rust K GLC1F, a new primary open-angle glaucoma locus, maps to 7q35-q36. Arch Ophthalmol . 1999;117:237–241. [CrossRef] [PubMed]
Trifan OC Traboulsi EI Stoilova D A third locus (GLC1D) for adult-onset primary open-angle glaucoma maps to the 8q23 region. Am J Ophthalmol . 1998;126:17–28. [CrossRef] [PubMed]
Sarfarazi M Child A Stoilova D Localization of the fourth locus (GLC1E) for adult-onset primary open-angle glaucoma to the 10p15-p14 region. Am J Hum Genet . 1998;62:641–652. [CrossRef] [PubMed]
Matlashewski G Lamb P Pim D Peacock J Crawford L Benchimol S . Isolation and characterization of a human p53 cDNA clone: expression of the human p53 gene. EMBO J . 1984;3:3257–3262. [PubMed]
Isobe M Emanuel BS Givol D Oren M Croce CM . Localization of gene for human p53 tumour antigen to band 17p13. Nature . 1986;320:84–85. [CrossRef] [PubMed]
Sager R . Tumor suppressor genes: the puzzle and the promise. Science . 1989;246:1406–1412. [CrossRef] [PubMed]
Morrison RS Kinoshita Y Johnson MD Guo W Garden GA . p53-dependent cell death signaling in neurons. Neurochem Res . 2003;28:15–27. [CrossRef] [PubMed]
Lane DP . Cancer. p53, guardian of the genome. Nature . 1992;358:15–16. [CrossRef] [PubMed]
Xu H el-Gewely MR . P53-responsive genes and the potential for cancer diagnostics and therapeutics development. Biotechnol Annu Rev . 2001;7:131–164. [PubMed]
Izzotti A Di Marco B De Flora S Sacca S . Open angle glaucoma: epidemiology, pathogenesis and prevention [in Italian]. Recenti Prog Med . 2006;97:37–45. [PubMed]
Quigley HA Nickells RW Kerrigan LA Pease ME Thibault DJ Zack DJ . Retinal ganglion cell death in experimental glaucoma and after axotomy occurs by apoptosis. Invest Ophthalmol Vis Sci . 1995;36:774–786. [PubMed]
Lin HJ Chen WC Tsai FJ Tsai SW . Distributions of p53 codon 72 polymorphism in primary open angle glaucoma. Br J Ophthalmol . 2002;86:767–770. [CrossRef] [PubMed]
Acharya M Mitra S Mukhopadhyay A Khan M Roychoudhury S Ray K . Distribution of p53 codon 72 polymorphism in Indian primary open angle glaucoma patients. Mol Vis . 2002;8:367–371. [PubMed]
Blanco-Marchite C Sanchez-Sanchez F Lopez-Garrido MP WDR36 and P53 gene variants and susceptibility to primary open-angle glaucoma: analysis of gene–gene interactions. Invest Ophthalmol Vis Sci . 2011;52:8467–8478. [CrossRef] [PubMed]
Daugherty CL Curtis H Realini T Charlton JF Zareparsi S . Primary open angle glaucoma in a Caucasian population is associated with the p53 codon 72 polymorphism. Mol Vis . 2009;15:1939–1944. [PubMed]
Dimasi DP Hewitt AW Green CM Mackey DA Craig JE . Lack of association of p53 polymorphisms and haplotypes in high and normal tension open angle glaucoma. J Med Genet . 2005;42:e55 [CrossRef] [PubMed]
Mabuchi F Sakurada Y Kashiwagi K Yamagata Z Iijima H Tsukahara S . Lack of association between p53 gene polymorphisms and primary open angle glaucoma in the Japanese population. Mol Vis . 2009;15:1045–1049. [PubMed]
Saglar E Yucel D Bozkurt B Ozgul RK Irkec M Ogus A . Association of polymorphisms in APOE, p53, and p21 with primary open-angle glaucoma in Turkish patients. Mol Vis . 2009;15:1270–1276. [PubMed]
Silva RE Arruda JT Rodrigues FW Moura KK . Primary open angle glaucoma was not found to be associated with p53 codon 72 polymorphism in a Brazilian cohort. Genet Mol Res . 2009;8:268–272. [CrossRef] [PubMed]
Fan BJ Liu K Wang DY Association of polymorphisms of tumor necrosis factor and tumor protein p53 with primary open-angle glaucoma. Invest Ophthalmol Vis Sci . 2010;51:4110–4116. [CrossRef] [PubMed]
Worley A Grimmer-Somers K . Risk factors for glaucoma: what do they really mean? Aust J Prim Health . 2011;17:233–239. [CrossRef] [PubMed]
Khan AO . Genetics of primary glaucoma. Curr Opin Ophthalmol . 2011;22:347–355. [CrossRef] [PubMed]
Levine AJ . p53, the cellular gatekeeper for growth and division. Cell . 1997;88:323–331. [CrossRef] [PubMed]
Ioannidis JP Ntzani EE Trikalinos TA Contopoulos-Ioannidis DG . Replication validity of genetic association studies. Nat Genet . 2001;29:306–309. [CrossRef] [PubMed]
Munafo M . Replication validity of genetic association studies of smoking behavior: what can meta-analytic techniques offer? Nicotine Tob Res . 2004;6:381–382. [CrossRef] [PubMed]
Attia J Thakkinstian A D'Este C . Meta-analyses of molecular association studies: methodologic lessons for genetic epidemiology. J Clin Epidemiol . 2003;56:297–303. [CrossRef] [PubMed]
Footnotes
 Supported in part by Major and Key Programs of Chinese National Natural Science Foundation Grant 30730099, and “Project 211,” The Innovation Fund for Graduate Students of Tianjin Medical University.
Footnotes
4  These authors contributed equally to the work presented here and should therefore be regarded as equivalent authors.
Footnotes
 Disclosure: Y. Guo, None; H. Zhang, None; X. Chen, None; X. Yang, None; W. Cheng, None; K. Zhao, None
Figure 1. 
 
Flow chart of literature search and study selection.
Figure 1. 
 
Flow chart of literature search and study selection.
Figure 2. 
 
Forest plot of the association between TP53 codon 72 polymorphism (CC versus CG+GG) and risk for POAG in order of publication year. The size of the square indicates the relative weight of each study. Bars, 95% CI.
Figure 2. 
 
Forest plot of the association between TP53 codon 72 polymorphism (CC versus CG+GG) and risk for POAG in order of publication year. The size of the square indicates the relative weight of each study. Bars, 95% CI.
Figure 3. 
 
Forest plot of the association between TP53 16-bp insertion polymorphism (Ins versus Del) and risk for POAG in order of publication year. The size of the square indicates the relative weight of each study. Bars, 95% CI.
Figure 3. 
 
Forest plot of the association between TP53 16-bp insertion polymorphism (Ins versus Del) and risk for POAG in order of publication year. The size of the square indicates the relative weight of each study. Bars, 95% CI.
Figure 4. 
 
Subgroup analyses of the association between TP53 codon 72 and risk for POAG in order of publication year. The size of the square indicate the relative weight of each study. Bars, 95% CI (A) Subgroup analysis stratified by ethnicity. (B) Subgroup analysis stratified by glaucoma subtype.
Figure 4. 
 
Subgroup analyses of the association between TP53 codon 72 and risk for POAG in order of publication year. The size of the square indicate the relative weight of each study. Bars, 95% CI (A) Subgroup analysis stratified by ethnicity. (B) Subgroup analysis stratified by glaucoma subtype.
Figure 5. 
 
Begg's funnel plot of TP53 codon 72 polymorphism and POAG for overall CC versus CG+GG. Each circle represents a separate study for the indicated association, and its size is proportional to the sample size of each study. The study by Silva et al. was excluded because of no homozygous subjects (CC) in the control group.
Figure 5. 
 
Begg's funnel plot of TP53 codon 72 polymorphism and POAG for overall CC versus CG+GG. Each circle represents a separate study for the indicated association, and its size is proportional to the sample size of each study. The study by Silva et al. was excluded because of no homozygous subjects (CC) in the control group.
Table 1.  
 
Main Characteristics of Studies Included in This Meta-Analysis
Table 1.  
 
Main Characteristics of Studies Included in This Meta-Analysis
P53 Codon72
Author Year Ethnicity HWE Cases Control
GG GC CC GG GC CC
 Lin et al. 2002 Asian 0.96 12 26 20 25 26 8
 Acharva et al. 2002 Asian 0.98 23 30 14 30 57 25
 Dimasi et al. 2005 Caucasian 0.49 296 186 41 109 57 12
 Mabuchi et al. 2009 Asian 0.95 177 197 51 83 83 23
 Daugherty et al. 2009 Caucasian 0.87 124 55 12 82 72 13
 Saglar et al. 2009 Caucasian 0.02 19 44 12 41 69 9
 Silva et al. 2009 Brazilian 0.0003 24 78 2 18 40 0
 Fan et al. 2010 Asian 0.51 100 176 121 55 108 38
 Blanco-Marchite et al. 2011 Caucasian 0.57 148 106 14 252 111 17
HTG
 Dimasi et al. 2005 Caucasian 0.49 158 101 24 109 57 12
 Mabuchi et al. 2009 Asian 0.95 85 102 25 83 83 23
 Daugherty et al. 2009 Caucasian 0.88 89 40 10 82 72 13
 Fan et al. 2010 Asian 0.51 64 114 74 55 108 38
NTG
 Dimasi et al. 2005 Caucasian 0.49 29 28 5 109 57 12
 Mabuchi et al. 2009 Asian 0.95 92 95 26 83 83 23
 Daugherty et al. 2009 Caucasian 0.88 36 15 1 82 72 13
 Fan et al. 2010 Asian 0.51 22 43 34 55 108 38
P53 Intron 3 16-bp Insertion
Del/Del Del/Ins Ins/Ins Del/Del Del/Ins Ins/Ins
 Acharva et al. 2002 Asian 0.14 56 11 0 67 33 0
 Mabuchi et al. 2009 Asian 425 0 0 189 0 0
 Daugherty et al. 2009 Caucasian 0.51 145 42 4 117 43 7
 Blanco-Marchite et al. 2011 Caucasian 0.98 135 38 2 167 55 5
HTG
 Mabuchi et al. 2009 Asian 212 0 0 189 0 0
 Daugherty et al. 2009 Caucasian 0.51 107 29 3 117 43 7
NTG
 Mabuchi et al. 2009 Asian 213 0 0 189 0 0
 Daugherty et al. 2009 Caucasian 0.51 38 14 0 117 43 7
Table 2.  
 
Results of Meta-Analysis for TP Polymorphisms and Risk of Primary Open-Angle Glaucoma
Table 2.  
 
Results of Meta-Analysis for TP Polymorphisms and Risk of Primary Open-Angle Glaucoma
Comparisons Number of Studies OR 95% CI P Value Heterogeneity Effects Model Egger's Test
I 2 P Value P > | t |
P53 Codon72
C vs. G 9 1.1 1.00–1.22 0.054 0.1264 0.125 Fixed 0.979
 Caucasian 4 1.07 0.82–1.40 0.609 9.11% 0.028 Random 0.609
 Asian 4 1.11 0.96–1.27 0.154 3.92% 0.27 Fixed 0.73
 HTG 4 1.05 0.91–1.20 0.535 4.63% 0.201 Fixed 0.225
 NTG 4 1.03 0.78–1.38 0.817 7.30% 0.063 Random 0.5
CC vs. GG 9 1.23 0.98–1.56 0.079 7.97% 0.437 Fixed 0.7
 Caucasian 4 1.2 0.81–1.77 0.36 3.67% 0.299 Fixed 0.768
 Asian 4 1.24 0.93–1.66 0.156 3.84% 0.279 Fixed 0.763
 HTG 4 1.16 0.85–1.58 0.361 1.53% 0.675 Fixed 0.278
 NTG 4 1.13 0.78–1.65 0.519 3.96% 0.266 Fixed 0.5
CC vs. CG+GG 9 1.31 1.05–1.63 0.017 7.99% 0.434 Fixed 0.96
 Caucasian 4 1.19 0.82–1.74 0.365 2.42% 0.49 Fixed 0.56
 Asian 4 1.37 1.03–1.80 0.026 5.06% 0.168 Fixed 0.964
 HTG 4 1.26 0.94–1.69 0.125 2.14% 0.544 Fixed 0.22
 NTG 4 1.25 0.88–1.78 0.22 4.89% 0.18 Fixed 0.252
CC+CG vs. GG 9 1.06 0.94–1.19 0.317 8.75% 0.364 Fixed 0.906
 Caucasian 4 1.05 0.80–1.39 0.716 7.34% 0.062 Random 0.5
 Asian 4 1.04 0.88–1.24 0.636 1.30% 0.73 Fixed 0.653
 HTG 4 1 0.85–1.18 0.999 3.41% 0.332 Fixed 0.32
 NTG 4 1.02 0.83–1.25 0.17 4.15% 0.246 Fixed 0.63
P53 Intron 3 16-bp Insertion
 Ins vs. Del 4 0.75 0.57–0.97 0.031 1.55% 0.46 Fixed 0.169
 Ins/Ins vs. Del/Del 4 0.49 0.18–1.32 0.156 0 0.96 Fixed
 Ins/Ins vs. Del/Del+Del/Ins 4 0.51 0.19–1.37 0.181 0 0.97 Fixed
 Ins/Ins+Del/Ins vs. Del/Del 4 1.01 0.87–1.17 0.91 0 1 Fixed 0.579
×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×