APEX1) may be involved in the carcinogenesis by affecting DNA repair. We aimed to summarize available data on the association of the APEX1 Asp148Glu (rs1130409) polymorphism with risk of multiple types of cancer via a meta-analysis.Polymorphisms in the APEX nuclease  1 gene =1.05; 95% confidence interval (95% CI): 0.99-1.11; P=0.071), dominant , and heterozygous genotypic  models, with significant heterogeneity and publication bias. In subgroup analyses by cancer type, with a Bonferroni corrected alpha of 0.05/6, significant association was observed for gastric cancer under both dominant  and heterozygous genotypic  models. In subgroup analysis by ethnicity, risk estimates were augmented in Caucasians, especially under dominant  and heterozygous genotypic  models. By study design, there were no significant differences between population-based and hospital-based studies. In subgroup analysis by sample size, risk estimates were remarkably overestimated in small studies, and no significance was reached in large studies except under the heterozygous genotypic model . By quality score, the risk estimates, albeit nonsignificant, were higher in low-quality studies than in high-quality studies. Further meta-regression analyses failed to identify any contributory confounders for the associated risk estimates.In total, 58 qualified articles including 22,398 cancer patients and 26,505 controls were analyzed, and the data were extracted independently by two investigators. Analyses of the full data set indicated a marginally significant association of the APEX1 Asp148Glu polymorphism might be a genetic risk factor for the development of gastric cancer. Further investigations on large populations are warranted.Our findings suggest that  APEX1) may be involved in the carcinogenesis by correcting DNA damage [1]. The APEX1 encodes the major apurinic/apyrimidinic endonuclease in human cells, and the loss of bases in apurinic/apyrimidinic sites can usually block the progress of the DNA replication apparatus and cause mutations. Therefore, the genetic defects responsible for the repair capacity of the APEX1 are often regarded as the logical candidates for its functional investigations. It is worth noting that a single transition of the 1349th base pair T allele to G allele, inducing the substitution of the 148th amino acid aspartate (Asp) to glutamate (Glu) , in the 5th exon of the APEX1, has been extensively investigated in association with a wide range of cancers, such as lung cancer, breast cancer, and bladder cancer [2-4]. The results of individual association studies in the literature, however, are often controversial and inconclusive. Taking lung cancer as an example, the APEX1 148Glu allele was a risk-conferring factor in Caucasians [5], but a risk-reducing factor in Asians [6]. As a caveat, this lack of consistency might be attributable to the presence of genetic heterogeneity across ethnic populations, the insufficient sample sizes involved, and the possibly uncontrolled confounding effects. To shed some light on these issues and to generate more information, we sought to summarize available data on the association of the APEX1 Asp148Glu polymorphism with all types of cancers from both English and Chinese literature via a meta-analysis, and further to explore the potential sources of between-study heterogeneity and the possible existence of publication bias.Polymorphisms in the APEX nuclease  1 gene  statement [7] (Please see the http://www.wanfangdata.com.cn), and CNKI  were searched on May 1, 2013 for observational studies investigating the association between the APEX1 Asp148Glu polymorphism and all types of cancers. Subject terms used for the search were: ‘apurinic/apyrimidinic’, ‘APE1’, ‘APEX1’, ‘cancer’, ‘tumor’, ‘neoplasm’, combined with ‘gene’, ‘polymorphism’, ‘variant’, ‘mutation’, ‘allele’, or ‘genotype’. The reference lists of all the retrieved articles as well as those of reviews on the same topic were also searched to identify the additional missing articles. Searching results were limited to studies with a case-control design and articles published in the English or Chinese language.Four databases including the PubMed, EMBASE (Excerpta Medica database), Wanfang (Two investigators (Dan Hu and Wenquan Niu) independently obtained the full texts of potentially eligible articles on the basis of their titles and abstracts. To avoid the double counting of the participants recruited in more than one publication, article authors were emailed for inquiry when necessary. In case of more than one publication from the same study population, the data from the most recent or the most complete publication were extracted.APEX1 Asp148Glu polymorphism. Studies were excluded (one point was sufficient for exclusion) if they investigated the progression, severity, phenotype modification, and the response to treatment or survival, as well as if they were conference abstracts, case reports or series, editorials, narrative reviews, and the non-English and non-Chinese articles.Our analyses were limited to the studies that strictly fulfilled the following inclusion criteria : (1) clinical endpoint (dependent variable): all types of cancers; (2) study design: either retrospective or nested case-control design; (3) independent variables: the genotype and/or allele counts of the The data were extracted from all the qualified articles independently by two investigators (Dan Hu and Wenquan Niu) according to a standardized Excel template . The discrepancies were resolved by the discussion and review of original articles, and a consensus was reached finally.APEX1 Asp148Glu polymorphism between patients and controls, and the demographic data, if available, including age, gender, smoking, and drinking.The data were collected on the first author, year of publication, ethnicity of the study population, cancer type, study design, case-control status, the genotypes/alleles of the APEX1 Asp148Glu polymorphism and cancer are described in the The study quality was evaluated by using a quality assessment score developed for genetic association studies by Thakkinstian and colleagues [8]. Total scores range from 0 (the worst) to 12 (the best). The criteria for quality assessment of genetic associations between the APEX1 Asp148Glu polymorphism including allelic model , dominant model (the 148Glu/148Glu genotype plus the 148Glu/Asp genotype versus the 148Asp/Asp genotype), homozygous (the 148Glu/148Glu genotype versus the 148Asp/Asp genotype) and heterozygous (the 148Glu/Asp genotype versus the 148Asp/Asp genotype) genotypic models.In this meta-analysis, four genetic models of inheritance were performed for 2 test, and was quantified by the inconsistency index (I2) statistic, which ranges from 0% to 100% and is defined as the percentage of the observed between-study variability that is due to heterogeneity rather than chance.The random-effects model using the DerSimonian & Laird method was employed to compute the weighted odds ratios (ORs) and the corresponding 95% confidence intervals (95% CIs). Heterogeneity between studies was evaluated by the χPredefined subgroup analyses were performed a priori according to the cancer type, ethnicity of the study populations , study design , the total sample size (<300 subjects or ≥300 subjects), and the quality score (score <7 or score ≥7). For a certain cancer, the data were presented and summarized if there were three or more independent studies that provided the genotype or allele counts of the Asp148Glu polymorphism between patients and controls.APEX1 Asp148Glu polymorphism on cancer risk.Meta-regression analyses were performed to estimate the extent to which different study-level variables, including age, smoking, drinking, and quality score, explained the potential heterogeneity of pooled effect estimates of the I2 and Egger’s statistics, for which significance was defined as P<0.10 [9]. All statistical analyses were conducted by the STATA software .Besides the Egger’s test, publication bias was evaluated by the trim-and-fill method, which can estimate the number and outcomes of theoretically missing studies due to publication bias. P<0.05 was considered statistical significance, except for the A flow diagram schematizing the process of article selection with specific reasons is presented in APEX1 Asp148Glu polymorphism between cancer patients and controls of all qualified populations are presented in the The baseline characteristics of all qualified populations are shown in APEX1 Asp148Glu polymorphism with cancer risk under allelic , dominant , and heterozygous genotypic  models, with high probabilities of heterogeneity   . Moreoveχ2 test) . We estiTo account for the potential sources of between-study heterogeneity, a set of predefined subgroup analyses were conducted .By cancer type, after the Bonferroni correction for the multiple testing (Bonferroni significance threshold P=0.05 divided by the number of cancers (n=6): P=0.0083), significant association was observed for gastric cancer under both dominant  and heterozygous genotypic  models, whereas no significance was reached for the other cancers under investigation. The heterogeneity between studies was relatively low for bladder and prostate cancers.By ethnicity, the magnitude of risk estimates was marginally significant in Caucasians under both dominant  and heterozygous genotypic  models, whereas this significance failed to survive the stringent Bonferroni correction (Bonferroni significance threshold P=0.05 divided by the number of ethnicities (n=4): P=0.0125). In Asians and African-Americans, there was no significant association observed in this meta-analysis.By study design, there were no significant differences in the pooled risk estimates between the population-based and hospital-based studies, with high probabilities of between-study heterogeneity and publication bias.By sample size, the risk estimates were significantly overestimated in small studies , and no significance was reached in large studies  under all but heterozygous genotypic model , even after the Bonferroni correction (Bonferroni significance threshold P=0.05 divided by the number of 2 groups: P=0.025). There was moderate evidence of heterogeneity.By quality score, the risk estimates were relatively higher in low-quality studies  than in high-quality studies , and there was no significance observed under all four genetic models. The presence of heterogeneity was more evident in low-quality studies than in high-quality studies. Significant publication bias was found under both dominant and heterozygous genotypic models.APEX1 Asp148Glu polymorphism and cancer susceptibility.To further explore additional sources of between-study heterogeneity, we constructed a multivariable meta-regression model that included age, smoking, drinking, and quality score as independent variables. However, none of these variables were observed to significantly affect the relationship between the APEX1 with cancer risk. The principle finding of this study was that the APEX1 148Glu allele was associated with the significant risk of developing gastric cancer under both dominant and heterozygous genotypic models, even after the Bonferroni correction. Moreover, our subgroup analyses indicated that ethnicity might be an underlying cause of heterogeneity between studies. Although other sources of heterogeneity cannot be easily ruled out, this study, to the best of our knowledge, is so far the largest meta-analysis examining the association of the APEX1 Asp148Glu polymorphism with cancer risk.Via a meta-analysis of the data from 58 articles and on 48903 participants, we investigated the association of the non-synonymous polymorphism Asp148Glu in APEX1, and they failed to find any relationship between cancer risk and the Asp148Glu polymorphism [64]. By contrast, the findings of this meta-analysis supported the significant roles of the 148Glu allele in susceptibility to gastric cancer. However, a note of caution should be added because the risk estimates for gastric cancer were based on 803 patients and 1311 controls from 4 independent populations in this meta-analysis, the sample size might not be sufficient enough to derive a firm conclusion. It is recommended that to generate robust data, a much larger sample set encompassing more than 1000 participants in each group might be required [65]. A large, well-designed study is therefore warranted to confirm or refute the significance of our findings.Recently, Zhou and colleagues have synthesized data from 32 case-control articles on the two polymorphisms of APEX1 Asp148Glu polymorphism with cancer risk in Caucasians under both dominant and heterozygous genotypic models, but not in Asians and African-Americans. One possible explanation for this divergence is the genetic heterogeneity across ethnicities. For example in this meta-analysis, the average frequency of the APEX1 148Glu allele was 34.82% in Asian controls, but was as exceedingly high as 45.21% in Caucasian controls. In general, genetic heterogeneity is an inevitable problem in any disease identification strategy. This ethnicity-specific effect suggests that different genetic backgrounds may account for this discrepancy or that different populations may have different linkage disequilibrium patterns due to the evolutionary history. As such, it is necessary to construct a database of susceptible genes and polymorphisms implicated in carcinogenesis in each ethnic group.Moreover, extending the findings of the meta-analysis by Zhou and colleagues [64], we, in subgroup analyses, observed a marginally significant association of the To seek additional sources of heterogeneity, an alternative method is to perform a meta-regression analysis; however, none of the confounders under study contributed remarkably to the presence of heterogeneity in this meta-analysis. It is important to bear in mind that meta-regression analysis, albeit enabling quantitative covariates to be considered, does not have the methodological rigor of a properly designed study that is intended to test the effect of these covariates formally. Admittedly, one limitation facing this method was the number of available studies with detailed information such as smoking and drinking. In fact, most studies did not report the study-level covariates of interest, precluding a more robust assessment of additional sources of heterogeneity.APEX1 Asp148Glu polymorphism, and did not cover the other polymorphisms of APEX1. It is possible that the potential role of the examined polymorphism is diluted or masked by other gene-gene or gene-environment interactions. Thus, we cannot just to a conclusion until further confirmation of our findings has been undertaken.Some limitations need to be acknowledged for this meta-analysis. First, all qualified studies were conducted on case-control design, which precludes further comments on a cause-effect relationship. Second, in both overall and subgroup analyses, most resultant associations might be biased by the moderate to high degree of between-study heterogeneity, which enhances the difficulty in drawing firm conclusions and encourages the exploration of other possible reasons for heterogeneity. Third, the overall findings of this study were skewed by publication bias, although publication bias was improved in most subgroups, possibly due to the lack of power for small number of studies involved. Factually as suggested by Hannah and colleagues, the study power is low if the number of studies included in a meta-analysis is 10 or fewer [66]. Moreover, potential selection bias cannot be completely ruled out, because we only retrieved studies from English and Chinese journals and published articles. Fourth, due to the relatively small sample sizes involved in subgroup analyses, we must hold some reservations about the interpretation of our subgroup results. Last but not the least, we only focused on the APEX1 Asp148Glu polymorphism might be a genetic risk factor for the development of gastric cancer. Nevertheless, despite the small sample sizes involved in subgroup analyses, this meta-analysis provides an anchoring point for better understanding of the pathogenesis of cancers. For practical reasons, we hope that this study will not remain just another endpoint of research instead of a beginning to establish the background data to understand the roles of the APEX1 in carcinogenesis.In conclusion, via a meta-analysis of the data from 58 articles and on 48903 participants, we provide evidence that the Table S1APEX1 Asp148Glu polymorphism with cancer risk.Criteria for quality assessment of genetic associations of the (DOC)Click here for additional data file.Table S2APEX1 Asp148Glu polymorphism between cancer patients and controls of all examined populations in this meta-analysis.The genotype distributions and allele frequencies of the (DOC)Click here for additional data file.Figure S1APEX1 Asp148Glu polymorphism under the allelic model.Forest plots of the lung, bladder, colorectal cancer (the upper panel), and prostate, breast, gastric cancers (the lower panel) in subgroup analyses by cancer type for the (PDF)Click here for additional data file.Figure S2APEX1 Asp148Glu polymorphism under the allelic model.Forest plots of the Caucasians (the upper panel), Asians (the middle panel), African-Americans and mixed populations (the lower panel) in subgroup analyses by ethnicity for the (PDF)Click here for additional data file.Figure S3APEX1 Asp148Glu polymorphism under the allelic model.Forest plots of the hospital-based studies (the upper panel), and population-based studies (the lower panel) in subgroup analyses by study design for the (PDF)Click here for additional data file.Figure S4APEX1 Asp148Glu polymorphism under the allelic model.Forest plots of the small studies (the upper panel), and large studies (the lower panel) in subgroup analyses by sample size for the (PDF)Click here for additional data file.Figure S5APEX1 Asp148Glu polymorphism under the allelic model.Forest plots of the high-quality studies (the upper panel), and low-quality studies (the lower panel) in subgroup analyses by sample size for the (PDF)Click here for additional data file.Checklist S1MOOSE checklist.(DOC)Click here for additional data file.


MnSOD, ECSOD, CAT, GSTT1, GSTM1, GSTP1, and iNOS polymorphisms. Data on cumulative asbestos and smoking were available for all subjects. To assess gene-gene and gene-environmental interactions, logistic regression was used. The associations between MnSOD Ala −9Val polymorphism and the risk of asbestosis and between iNOS genotypes and asbestosis were modified by CAT –262 C > T polymorphism . A strong interaction was found between GSTM1-null polymorphism and smoking (P = 0.007), iNOS (CCTTT)n polymorphism and smoking (P = 0.054), and between iNOS (CCTTT)n polymorphism and cumulative asbestos exposure (P = 0.037). The findings of this study suggest that the interactions between different genotypes, genotypes and smoking, and between genotypes and asbestos exposure have an important influence on the development of asbestosis and should be seriously considered in future research on occupational/environmental asbestos-related diseases.This study investigated the influence of gene-gene and gene-environment interactions on the risk of developing asbestosis. The study comprised 262 cases with asbestosis and 265 controls with no asbestos-related disease previously studied for  The findings of the studies indicate that, in addition to asbestos exposure, the genetic factors may influence the development of asbestosis –8. 2∙−), hydrogen peroxide (H2O2), hydroxyl radical (OH∙), and nitric oxide (NO) are suggested to be involved in the pathogenesis of this disease [2∙− to H2O2 and oxygen (O2), whereas CAT subsequently catalyses the conversion of H2O2 to water (H2O) and O2 [The reactive oxygen and nitric species (ROS and RNS) such as superoxide anion (O disease –11. Seve) and O2 , 12, 13.) and O2 –16. The ) and O2 , 18.MnSOD gene results in alanine (Ala) to valine  substitution ; of the ECSOD gene results in arginine (Arg) to glycine (Gly) change (Arg213Gly); and of the CAT gene results in cytosine (C) to thymine (T) substitution (−262C > T) [GSTM1 and GSTT1 genes exhibit null polymorphism due to gene deletion [GSTP1 gene, two functional SNPs cause isoleucine (Ile) to Val substitution  and Ala to Val change  [GSTP1 genotypes may be combined into groups with a presumed high, intermediate, or low conjugation capacity of the enzyme, as described previously [iNOS, one of the most frequently investigated polymorphisms is the CCTTT pentanucleotide repeat ((CCTTT)n) in the promotor region [The genes coding for all these enzymes are polymorphic , 19–21. 62C > T) , 13, 22.deletion . In the a114Val) , 20. Basion Ile10Val and Ar region .MnSOD Ala −9Val, ECSOD Arg213Gly, CAT −262C > T, GSTT1-null, GSTM1-null, GSTP1 Ile105Val, and Ala114Val and iNOS (CCTTT)n), between genotypes and smoking, and between genotypes and cumulative asbestos exposure on the risk of developing asbestosis.The associations between asbestosis and different genetic polymorphisms have been investigated in several studies –8, 14. HThe participants in the nested case-control study were selected from a cohort of 2,080 workers occupationally exposed to asbestos who were presented at the State Board for the Recognition of Occupational Asbestos Diseases at the Clinical Institute of Occupational Medicine in Ljubljana in the period from January 1, 1998 to December 31, 2003. In this cohort, a total of 356 subjects were diagnosed with asbestosis. All these subjects were included in the present study and represented the cases. A group of 356 controls matched by gender and age with no asbestos-related disease was selected from the same cohort of workers occupationally exposed to asbestos. However, among the selected cases, 40 (11.2%) died in the period from the recognition of the occupational disease to the time of the beginning of the study, 2 (0.6%) developed a malignant disease and 52 (14.6%) refused to participate, so the final number of cases included in the study was 262 (73.6%). Among the controls, 29 (8.1%) died, 9 (2.5%) developed a cancer, and 53 (14.9%) rejected taking part in the study, so the final number of controls was 265 (74.5%). 3-years, were available for all the subjects from the previous study [3, a gravimetric method measuring milligrams/m3, and membrane filter measuring fibers/cm3. The exposure estimation included the following main steps: (1) for all production workers, work histories were obtained from the company personnel files; (2) all air measurements, information about product (asbestos or asbestos-cement) for a particular task, the process type (wet or dry), percent of time per task, units used for the air sampling measurements , and department were entered into an ACCESS table for each production job for every year in the study period; (3) operation-specific conversion factors from particle/cm3 to fibres/cm3 and mg/m3 to fibres/cm3 were calculated; (4) applying the appropriate conversion factor to the measured and estimated exposure intensities, exposure intensities by job and year were calculated for asbestos for all production workers; (5) the exposure intensity table for production jobs (The Job Exposure Matrix) and the work histories for each production worker were combined using the SAS program to obtain the cumulative exposure for each worker [The information on smoking history was collected for all subjects during an interview using a standardized questionnaire , 25. TheThe diagnosis of asbestosis or “no asbestos-related disease” was verified by two groups of experts of the State Board for Recognition of Occupational Asbestos Diseases, following the Helsinki Criteria for Diagnosis and Attribution of Asbestos Diseases  and the MnSOD Ala −9Val, ECSOD Arg213Gly, CAT −262C > T, GSTT1-null, GSTM1-null, GSTP1 Ile105Val and Ala114Val, and iNOS (CCTTT)n genotyping as previously described [PCR-based methods were used for escribed .t-test, χ2 test, and univariate logistic regression analysis. Next, multivariate logistic regression modelling, including genotypes, cumulative asbestos exposure, possible confounders, or effect modifiers, was employed. To test the effect modification (interactions), simple categorical models based on stratification were constructed first, followed by logistic regression models using dummy variables. The statistical analysis followed the standard procedure calculating first the descriptive statistics, The baseline characteristics  of cases and controls are presented in MnSOD, ECSOD, CAT, GSTT1, GSTM1, GSTP1, and iNOS genotypes in this cohort were described previously [P > 0.05; data not shown). The frequencies of eviously –8. In thMnSOD, ECSOD, CAT, GSTT1, GSTM1, GSTP1, and iNOS genotypes  were reported in detail in previous studies [Logistic regression analysis revealed no association between asbestosis and smoking (ever/never) , while a significant association was observed between asbestosis and log-transformed cumulative asbestos exposure . The results of univariate logistic regression analysis for In a subsequent statistical analysis, no significant change in the risk of asbestosis was observed in numerous multivariate models involving different genotypes, cumulative asbestos exposure and possible confounders, or effect modifiers compared to univariate models (data not shown).MnSOD Ala –9Val polymorphism and the risk of asbestosis was modified strongly by CAT –262 C > T polymorphism  (iNOS (CCTTT)n polymorphism and asbestosis was modified by CAT –262 C > T polymorphism   . Similarm Tables  and 4, w= 0.000) . No inteGSTM1-null polymorphism was shown to modify the association between smoking and asbestosis  (iNOS (CCTTT)n polymorphism   . Similarm Tables  and 4. I= 0.050) . Other i3-years and >11.23 fibres/cm3-years (11.23 fibres/cm3-years is the mean cumulative asbestos exposure for the controls) were constructed first. The analysis showed that the association between dichotomized cumulative asbestos exposure and the risk of asbestosis was modified by iNOS (CCTTT)n polymorphism n polymorphism .In all presented models, the likelihood ratio test showed that the interaction model is better if compared to the models including only the main effects  in models testing the genotype-genotype and genotype-environmental interactions, but there was no important difference in asbestosis risk compared to the models presented (data not shown).MnSOD –9Ala/Ala and GSTP1105Ile/Ile genotypes significantly increase the risk of developing asbestosis, while a protective effect was observed for GSTT1-null genotype [ECSOD 213Arg/Gly genotype, CAT −262 TT genotype and iNOS LL genotype, but the results were not significant or borderline significant [The already published findings of our study show that genotype , 5, 7. Anificant . In thisCAT –262 C > T polymorphism strongly modifies the association between MnSOD Ala –9Val polymorphism and the risk of asbestosis. As both MnSOD and CAT constitute part of the primary defence system against ROS and catalyse the sequence of reactions in the detoxification of ROS [CAT –262 C > T polymorphism has been shown to also modify the association between iNOS (CCTTT)n polymorphism and asbestosis. Considering that ROS and NO have been proposed to cooperate in causing the cytotoxic and mutagenic effects of asbestos fibres [2O2 [2O2 decreases the cytotoxicity of NO [A crucial finding of the current study shows that n of ROS , 12, 13,s fibres , 11 and res [2O2 , which ires [2O2 , 12, 13,ty of NO , this inGSTM1-null polymorphism and smoking, despite the fact that there was no independent association between either GSTM1-null polymorphism or smoking and asbestosis risk. The explanation could be that both asbestos and smoking increase the production of ROS [∙ by 2-3 times [GSTM1 in the defence against ROS [iNOS (CCTTT)n polymorphism. This interaction may be explained by the observation that cigarette smoke is the largest source of NO and can also increase the expression and activity of iNOS [According to present knowledge, asbestosis has not been associated with smoking with certainty , 31. Nevn of ROS , 32, 33,n of ROS , 34, 35.inst ROS , 36, 37, of iNOS , 39 and  of iNOS , 17.iNOS (CCTTT)n polymorphism on the association between asbestosis and cumulative asbestos exposure. This has been proved in the simple categorical model and in logistic regression analysis with logarithmically transformed cumulative asbestos exposure as a continuous variable. Additional studies including more subjects are needed to elucidate whether other genetic polymorphisms modify or confound cumulative asbestos exposure—asbestosis associations. This study also suggested a modifying effect of In the present study, no bias was introduced by genetic heterogeneity because all the subjects were recruited in a small geographical area with an ethnically homogeneous population . In conclusion, the findings of this study suggest that the interactions between different genotypes, genotypes and smoking, and between genotypes and asbestos exposure have an important influence on the development of asbestosis and should be seriously considered in future research on occupational/environmental asbestos-related diseases.


It has become increasingly clear that ATM (ataxia-telangiectasia-mutated) safeguards genome stability, which is a cornerstone of cellular homeostasis, and ATM IVS 22-77 T>C affects the normal activity of ATM proteins. However, the association between the ATM IVS 22-77 T>C genetic variant and cancer risk is controversial. Therefore, we conducted a systematic meta-analysis to estimate the overall cancer risk associated with the polymorphism and to quantify any potential between-study heterogeneity.A total of nine studies including 4,470 cases and 4,862 controls were analyzed for ATM IVS 22-77 T>C association with cancer risk in this meta-analysis. Heterogeneity among articles and their publication bias were also tested.Our results showed that no association reached the level of statistical significance in the overall risk. Interestingly, in the stratified analyses, we observed an inverse relationship in lung and breast cancer.Further functional research on the ATM mechanism should be performed to explain the inconsistent results in different cancer types. Cancer is a multi-factorial disease that results from complex interactions between environmental and genetic factors Ataxia-telangiectasia (A–T) is a rare autosomal recessive disorder that affects many parts of the body and has an exceptionally high incidence of cancer, including breast cancer, leukemia, and lymphoma DNA damage jeopardizes cellular homeostasis and initiates a response that activates various repair mechanisms that recognize specific DNA lesions Polymorphisms in ATM, which affect normal protein activity, may alter the efficiency of cell cycle checkpoint activation, DNA repair and induction of apoptosis and lead to genetic instability and increased cancer risk. A single-nucleotide polymorphism (SNP) IVS 22–77 T>C (rs664677) is located within intron 22 of the ATM gene and has a minor allele frequency higher than 10%. In addition, IVS 22–77 T>C is in tight linkage disequilibrium with IVS48 _ 238 G, another ATM variant allele that was shown to be an association with breast-cancer risk For the literature review, we searched the PubMed and Embase databases  using the following search terms: “ATM” and “cancer” or “tumor” and “polymorphism” or “variant”. In addition, we screened the reference lists for all included studies, reviews and meta-analyses.Previous studies were included if they contained sufficient published data regarding the following information: 1) The ATM rs664677 polymorphism and cancer risk; 2) A human case-control study of a polymorphism associated with cancer risk; and 3) The genotype frequencies for both cancer cases and controls. Primary reasons for the exclusion of studies are listed as follows: 1) the literature did not contain information regarding cancer research; 2) the study duplicated a previous publication; 3) the study reported no usable data; and 4) the study only involved a case population.The data extracted from each eligible publication included the following information: the first author's name, the year published, the year the data were collected, the country in which the study was conducted, the ethnicities of the individuals involved, the cancer type, the source of the controls used, the matching criteria, the genotyping method, the specimen type, the sample size, the genotypic frequencies for experimental cases and controls, and the Hardy-Weinberg equilibrium (HWE) among the controls. Specifically, each selected case was classified as population-based, hospital-based, or mixed. The ethnicity was classified as Asian or European. If the ethnicity was not reported, we considered the ethnicity of the source population of the country where the study was performed.The data from nine cancer case-control publications was used in these analyses. A summary of the individual studies is given in All statistical tests performed in this study were two-tailed and p values less than 0.05 were considered significant, unless otherwise stated. Statistical analyses were performed using Stata, version 11.0.For the control groups of each study, the allelic frequency was calculated, and the observed genotype frequencies of the rs664677 polymorphism were assessed for Hardy-Weinberg equilibrium using the test. The publication by Natallia M Akulevich et al. The strength of the association between the rs664677 polymorphism and cancer risk was evaluated by the odds ratios (ORs) with 95% confidence intervals (CIs). Pooled estimates of the ORs and 95% CIs were calculated by logistic regression. The pooled ORs were calculated for the heterozygote comparison (CT versus TT), homozygote comparison (CC versus TT), dominant model (CT/CC versus TT) and recessive model (CC versus CT/TT), respectively. The values for the ORs and CIs for each individual were considered twice. The meta-analyses were stratified by cancer type, ethnicity and source of the controls if the data permitted; a minimum of three data sources were required. Of the individual studies included in this pooled analysis, only one source of controls per study was found in all but two cases; these studies were combined into the “mixed” group.The evaluation of the meta-analysis results included an examination of the heterogeneity, an analysis of the sensitivity, and an examination for bias. The chi-squared-based Q-statistic test was used to assess the between-study heterogeneity, and it was considered significant if P<0.10. The fixed and random effects models were performed, respectively, to combine values from each of the studies based on the Mantel-Haenszel The inverted funnel plots and Egger's regression test were used to investigate the publication bias. The potential publication bias was assessed with funnel plots of the effect sizes versus the standard errors; the Begg's test was used to identify the significant asymmetry. An asymmetric plot suggests possible publication bias. The bias due to results from small studies was evaluated by the modified Egger's test, which corrected for potential type I errors A total of 110 publications were relevant to the search words. Seven studies were obviously irrelevant. Forty studies were excluded because they were duplicates of previous publications (27 studies) or on different genes (13 articles). Four of the articles were meta-analyses, and six of the publications were reviews. Among the remaining 53 publications, six of the articles were not human studies, five of the publications were not for cancer research and six articles had no control population. Another twenty-eight studies were also excluded because they did not present detailed genotyping information (19 articles) or did not report usable data (9 articles). Finally, the references from all included studies reviews and meta-analyses were screened. One additional eligible article was retrieved. Overall, nine studies, involving 4,470 cases and 4,862 controls, concerning ATM rs664677 polymorphism and cancer susceptibility were available for this meta-analysis .The studies investigating different cancers, multiple ethnicity or different sources of controls were separated into multiple studies in a subgroup analysis. In addition, one study It is known that the frequency of the ATM rs664677 polymorphism varies between ethnic groups. For the European populations (n = 1542), the cc allele frequency was 40.9% (95% CI = 33.4–48.4), which was significantly lower than that of the Asian population , heterozygote (CT versus TT: P heterogeneity<0.001), and dominant model (AA/GA versus GG: P heterogeneity<0.001) comparisons. However, in the recessive model comparison (CC versus CT/TT: P heterogeneity = 0.539), heterogeneity was not found. We evaluated the source of heterogeneity by tumor type, ethnicity, publication year, control source, and sample size. We did not observe any contribution to the substantial heterogeneity.Sensitivity analyses were conducted to ascertain the primary origin of the heterogeneity. Four independent studies by Sang-Ah Lee Begger's funnel plot and Egger's test were used to identify the potential publication biases of the literature, the shapes of the funnel plots appeared to be symmetrical , suggestIn response to DNA damage, the dormant kinase and sensors of ATM are rapidly activated, and various downstream substrates of ATM, which compose an ever-expanding network, are phosphorylated. Some of the downstream substrates are key factors in the regulation of cell-cycle arrest, DNA repair, and apoptosis. Given the important roles of ATM in response to DNA damage, inherited variability in this gene could directly or indirectly contribute to susceptibility to cancer Several studies have reported the associations between several genetic variants of ATM and risk of cancer, for instance, rs1800057 (P1054R), rs1801516 (D1853N) and rs1800054 (S49C) The present meta-analysis of 9 studies, including 4470 cases and 4862 controls, provided evidence that there is no association between cancer and the ATM rs664677 polymorphism. The results from a recent meta-analysis investigation of the association between the ATM D1853N polymorphism and breast cancer risk presented evidence consistent with our results In the subgroup analysis according to cancer type, the odds ratio for CC homozygosity versus heterozygosity plus TT homozygosity was decreased for lung cancer, but this was not statistically significant . In other models, however, the OR was significantly decreased. In contrast to lung cancer, where the ATM rs664677 C allele is protective, in breast cancer, it seems to be associated with an elevated risk. Such differences have been previously reported; for example, the CHEK2 I157T variant with the rare allele conferred an elevated breast cancer risk but a protective effect on lung cancer Recent genome-wide association studies (GWAS) have reported several SNP to be associated with breast or lung cancer, including rs1219648, rs1092913, rs2736100, rs16969968, rs8034191, and rs402710 et al A literature reviewed that eight hallmarks constitute an organizing principle for rationalizing the complexities of neoplastic disease. They include sustaining proliferative signaling, evading growth suppressors, resisting cell death, enabling replicative immortality, inducing angiogenesis, activating invasion and metastasis, reprogramming energy metabolism and evading immune destruction Heterogeneity is a potential problem that might affect the interpretation of the results. Significance between the meta-analysis heterogeneity existed in almost all comparisons, except the recessive model. We detected the source of heterogeneity by tumor type, ethnicity, publication year, control source, and sample size. However, there was no evidence to determine which of them contributed to the substantial heterogeneity. One possibility involves differences in the matching status. However, we cannot confirm this possibility because no detailed information was provided. Heterogeneity could also have resulted from the fact that each study used a different approach to select participants. However, it seems unlikely that the selection procedure would affect the genotype at the locus. Thus, we do not have a clear explanation for the statistical heterogeneity that was present for the SNP. The leave-one-out sensitivity analysis would not have materially altered the results of this pooled analysis, indicating that our results were robust. The publication bias for the association between this polymorphism and cancer risk was not observed.Several potential limitations of the present meta-analysis should be taken into consideration. First, although the funnel plot and Egger's test showed no publication bias and although an exhaustive literature search was done, it is likely that some publications and unpublished data were overlooked. Selection bias for the meta-analysis might have occurred. Secondly, in the subgroup analysis by cancer type, the number of studies and subjects analyzed for rs664677 was small, and the statistical power was so low that caution should be taken in interpreting these results. A further investigation with much larger sample sizes is needed. Thirdly, our results were based on unadjusted estimates due to the absence of available information. A more precise analysis would be detected if more detailed individual data were available, such as age, sex, and exposure. Despite its limitations, our meta-analysis also had some advantages. There was no evidence for heterogeneity in a recessive model among the studies of this SNP. We found a paradoxical role for the ATM rs664677 polymorphism contributing to both cancer suppressing and promoting effects.In summary, this meta-analysis convincingly demonstrated that the ATM rs664677 polymorphism is not associated with cancer risk. A moderately protective effect was observed with the lung cancer risk. In contrast, we observed an elevated risk of breast cancer susceptibility. In conclusion, well-designed, unbiased studies should be done to gain a more comprehensive understanding of the association between the ATM gene and cancer risk.


CYP1A1 MspI T6235C, GSTM1 present/null, GSTT1 present/null and GSTP1 Ile105Val polymorphisms are related to the risk of developing lung cancer in relation to tobacco consumption and occupation in Asturias, Northern Spain.Metabolic genes have been associated with the function of metabolizing and detoxifying environmental carcinogens. Polymorphisms present in these genes could lead to changes in their metabolizing and detoxifying ability and thus may contribute to individual susceptibility to different types of cancer. We investigated if the individual and/or combined modifying effects of the A hospital-based case–control study (CAPUA Study) was designed including 789 lung cancer patients and 789 control subjects matched in ethnicity, age, sex, and hospital. Genotypes were determined by PCR or PCR-RFLP. Individual and combination effects were analysed using an unconditional logistic regression adjusting for age, pack-years, family history of any cancer and occupation.No statistically significant main effects were observed for the carcinogen metabolism genes in relation to lung cancer risk. In addition, the analysis did not reveal any significant gene-gene, gene-tobacco smoking or gene-occupational exposure interactions relative to lung cancer susceptibility. Lastly, no significant gene-gene combination effects were observed.CYP1A1, GSTM1, GSTT1 and GSTP1 metabolic genes were not significantly associated with lung cancer risk in the current study. The results of the analysis of gene-gene interactions of CYP1A1 MspI T6235C, GSTM1 present/null, GSTT1 present/null and GSTP1 Ile105Val polymorphisms in lung cancer risk indicate that these genes do not interact in lung cancer development.These results suggest that genetic polymorphisms in the  Established risk factors for lung cancer include exposure to cigarette- and environmental-derived pro-carcinogens. Cigarette smoking accounts for 80% to 90% of cases among men and 55% to 80% of cases among women. OccupatCYP1A1 is responsible for the metabolic activation of polycyclic aromatic hydrocarbons , a leading pro-carcinogen found in cigarette smoke and environmental pollution). There were no statistically significant differences among the cases and controls regarding gender. There were statistically significant differences comparing the cases to controls regarding median age (67 vs. 66), tobacco smoking pack-years (PY) (54 vs. 30.1), family history of lung cancer (11.4% vs. 6.5%) and list A occupation status (List A include occupations known to be associated with lung cancer) (8.8% vs. 13.2%). There were more current smokers (63.7% vs. 34.3%) and more heavy smokers (62.29 vs. 36.89 PY) among the cases than among the controls. Histologically, squamous cell carcinoma (39.8%) and adenocarcinoma (31.3%) were the main types of lung cancer  on the risk of developing lung cancer. Within our study set, in heritance of at least one GST  deletion or GSTP1 105Val alleles were fairly common among controls with frequencies ranging from 21.3-58.1%, as detailed in TableWe evaluated the impact of polymorphisms detected in 4 in Phase I and Phase II metabolism genes  in relation to lung cancer susceptibility using univariate as well as multivariate statistics. No significant individual gene effects were observed among carriers of one or more CYP1A1 MspI 6235C ; GSTM1 null ; GSTT1 null ; GSTP1 Val , as summarized in TableCYP1A1 MspI T6235C polymorphism and lung cancer risk .No association was found between GSTM1 present/null polymorphism, the frequency of the GSTM1 null genotype was lower in the cases (51.7%) than in the controls (53.9%), although not statistically significant. When we analyzed the association between the GSTM1 genotypes and lung cancer risk, we found that the ≥1 null allele was no associated with the risk of developing lung cancer .For the GSTT1 present/null polymorphism the frequency of the GSTT1 null genotype was lower in the cases (20.4%) than in the controls (21.3%), although not statistically significant. We did not find any evidence of an association between the GSTM1 genotypes and lung cancer risk.In the case of the GSTP1 Val allele was 0.338 in the cases and 0.349 in the controls. The frequency of the Val/Val genotype was slightly higher in the cases (12.3%) than in the controls (11.7%). When we analysed the association between the GSTP1 genotypes and lung cancer risk, we found no association between individuals with the variant genotype Val/Val or the carriers of variant allele Val  and the risk of developing lung cancer  . However, the case of the C-allele variant in the CYP1A1 gene could represent a possible interaction with occupation (adjusted OR [95%CI]: 2.20 [1.11-4.35] for workers in occupations included in list A), as shown in TableAn analysis of the interaction of each variant carcinogen metabolism gene alone and tobacco consumption in lung cancer risk showed that there is no gene-environment interaction Table. In addiCYP1A1, GSTM1, GSTT1, and GSTP1 polymorphisms showed a gene-gene interaction . Inevitably, the use of hospital-based controls is a potential limitation. The hospitals from which the cases were recruited were reference centers for all patients requiring hospitalization. Our controls were referred to these hospitals due to the presence of acute health conditions that were unrelated to lung cancer risk factors. There is always a chance of recall bias consisting of a systematic error due to differences in memories of cigarette smoking habits or occupational exposures between cases and controls. Structured interviews, like those used in this study, help to minimize this type of risk. Moreover, the prevalence of tobacco smoking and occupational exposure was in agreement with the literature. Our sample size is not large enough to find conclusive results in interaction analysis. Other genes that could participate in xenobiotic metabolism were not considered on the current study, which is another possible limitation. Therefore, our future objective is to validate these results with more individuals and powerful genotyping techniques.CYP1A1 MspI T6235C polymorphism is associated with an increased lung cancer risk in Asian populations, especially in relation to tobacco smoking[Several studies have shown that the  smoking,32. Howe smoking and two  smoking, in addiGST genes, including GSTM1, GSTT1 and GSTP1, resulting in reduced enzymatic activity in the cell, epidemiological studies do not support these findings. Many studies, including several meta-analyses and pooled analyses, support our finding that these three polymorphisms are not associated with lung cancer risk[Although biological studies have shown evidence of variant genotypes in the cer risk-19,24-27GSTM1 present/null polymorphism. However, when only studies with more than 500 case/control pairs were considered, no association was observed. Similarly, pooled analyses with either non-smokers from 23 studies[A large meta-analysis conducted in 2006, including 19,729 cases and 25,931 controls from 117 studies[ studies on cases studies were notGSTT1 present/null polymorphism, two meta-analyses and three pooled analyses have been performed to date. Similarly to the GSTM1 present/null polymorphism, the meta-analysis carried out by Ye et al.[GSTT1. However, when only studies with more than 500 case/control pairs were considered, no association was observed. In addition, a meta-analysis of 34 studies found no association between this polymorphism and lung cancer risk in a Caucasian population[In relation to the e et al., includipulation. The thrpulation, the secpulation, and theGSTP1 Ile105Val polymorphism and lung cancer risk[Finally, a recent meta-analysis including 8,322 cases and 8,844 controls from 27 studies found no association between the cer risk among alcer risk and withAnalyses of gene-gene interactions are especially important in the glutathione metabolic pathway where multiple enzymes with overlapping functions and shared substrates have been associated with susceptibility to carcinogens and toxic agents. In this study, no association was found probably due to the failure to consider an exhaustive chart of carcinogen metabolism related genes. However, other studies have found positive results in the gene-gene interaction analysis,27,54, wGSTM1 present/null, GSTT1 present/null, and GSTP1 Ile105Val polymorphisms but found no association. Jourenkova-Mironova et al.[Although it is well established that occupational exposure is an important risk factor for lung cancer and the a et al., Reszka a et al. used occa et al. used occCYP1A1, GSTM1, GSTT1 and GSTP1 metabolic genes are not associated with lung cancer risk in our total population of Caucasians from Northern Spain. Furthermore, the negative results in the gene-gene interactions analysis seem to indicate that these interactions do not have an association with lung cancer development. Well-designed and powerful epidemiological studies are necessary to determinate the true role of genetic susceptibility in lung cancer.In summary, our results suggest that the four genetic polymorphisms studied in the The authors declare that they have no competing interests.MFLC carried out the molecular genetic studies and drafted the manuscript. SMAA revised the manuscript. TP participated in the patient enrolment. AFS performed the statistical analysis and revised the manuscript. AT conceived the study, participated in its design and coordination, and revised the manuscript. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2407/12/433/prepub


ARMS2) has a different hereditary contribution in neovascular age-related macular degeneration (AMD) and polypoidal choroidal vasculopathy (PCV).To investigate whether the A69S variant of the age-related maculopathy susceptibility 2 gene  and 95% confidence intervals (CIs) were estimated using a fixed effects model.We initially conducted a comparative genetic analysis of neovascular AMD and PCV, genotyping the The genetic effect of the A69S variant was stronger in neovascular AMD  than in PCV . The pooled risk allele frequency was significantly higher in neovascular AMD (64.7%) than in PCV (55.6%). The population attributable risks for the variant allele were estimated to be 43.9%  and 29.7%  for neovascular AMD and PCV, respectively. No significant between-study heterogeneity was observed in any statistical analysis in this meta-analysis.ARMS2 A69S variant confers a significantly higher risk of neovascular AMD than PCV. Furthermore, there is compelling evidence that the risk attributable to the A69S variant differs between geographic atrophy and neovascular AMD. Together with defining the molecular basis of susceptibility, understanding the relationships between this genomic region and disease subtypes will yield important insights, elucidating the biologic architecture of this phenotypically heterogeneous disorder.Our meta-analysis provides substantial evidence that the  Age-related macular degeneration (AMD), a leading cause of irreversible blindness among older individuals in developed countries, is a common multifactorial disease with heterogeneous clinical manifestations . An earlARMS2] [HTRA1])   and high[HTRA1]) ,11, the [HTRA1]) , two nei[HTRA1]) , the com[HTRA1]) , the hep[HTRA1]) ,16, the [HTRA1]) ,16, and [HTRA1]) ,16. Rece[HTRA1]) . The metg others .Polypoidal choroidal vasculopathy (PCV), characterized by inner choroidal vascular networks ending in polypoidal lesions , is now ARMS2 A69S variant is strongly associated with neovascular AMD and PCV, with a stronger association in neovascular AMD than in PCV [We have previously shown that the n in PCV ; howevern in PCV -31. Inten in PCV ,32. Sub-n in PCV , rheumatn in PCV , and varn in PCV -37. GenoARMS2/HTRA1 region [ARMS2 A69S variant in 181 subjects with neovascular AMD, 198 subjects with PCV, and 203 controls. Results were then integrated into a meta-analysis of previous studies representing an assessment of the association between the ARMS2 A69S variant and neovascular AMD and/or PCV, comprising a total of 3,828 subjects of Asian descent, to more reliably compare the genetic effect of ARMS2 A69S between neovascular AMD and PCV.To date, some meta-analyses have been published regarding the association between AMD and the 1 region -40, but ARMS2 A69S variant [The study protocol was approved by the Institutional Review Board at Kobe University Graduate School of Medicine and performed in accordance with the Declaration of Helsinki. Written informed consent was obtained from all subjects before participation in this study. All cases and controls included in our original sample set were Japanese individuals recruited from the Department of Ophthalmology at Kobe University Hospital in Kobe, Japan. This cohort is an extension of one previously published for an association with the  variant . A porti variant ,41,42. I variant . The demGenomic DNA was extracted from peripheral blood using a standard methodology. Genotyping was performed using a pre-developed TaqMan SNP Genotyping Assay  on a StepOnePlus™ Real-Time PCR System (Applied Biosystems) in accordance with the manufacturer’s recommendations.ARMS2 A69S variant with chi-square tests on 2 × 2 contingency tables using the software package PLINK v1.07. Deviations from the Hardy–Weinberg equilibrium (HWE) were tested using the exact test [R project, where the subtypes were used as the outcome and the A69S genotype as the explanatory variable [Allelic associations were evaluated for the act test  implemenvariable .HTRA1,” “age-related maculopathy susceptibility 2,” “ARMS2,” or “LOC387715,” and “age-related macular degeneration” or “polypoidal choroidal vasculopathy.” The literature search was performed in duplicate by two authors (S.Y. and N.K.).We performed a systematic PubMed literature search (up to May 2011) using the following search terms in different combinations: “HtrA serine peptidase 1” or “ARMS2 A69S variant and neovascular AMD and/or PCV in East Asian populations. (2) The study must distinguish PCV from the neovascular form of AMD based on findings of indocyanine green angiography, and must look at PCV and/or neovascular AMD (CNV) as specific outcomes. (3) The study must present available data on allele and genotype distributions for cases and controls. (4) The study must be written in English and published in peer-reviewed journals. For duplicate publications, the largest data set was chosen for meta-analysis.Studies included in the meta-analysis had to fulfill the following criteria: (1) The study must be unrelated case-control or population-based representing an assessment of the association between the The following variables were extracted from each study: the name of the first author, the year of publication, ethnicity, and allele and genotype distributions in cases and controls.For each study, deviations from the HWE in controls were tested using the exact test . Pooled I2 statistic [I2 ranges between 0% and 100% , and larger values represent increasing heterogeneity.Between-study heterogeneity was assessed using the Q-statistic test and tatistic ,50. A p All meta-analyses were conducted using the Stata software . All tests were two tailed. A p value of <0.05 was considered statistically significant except for the test of between-study heterogeneity.ARMS2 A69S variant (rs10490924) in our original sample set. Genotype distributions for this variant are given in ARMS2 A69S variant showed strong evidence of association with neovascular AMD and PCV. ORs for the risk allele T were 2.82  and 2.39  for neovascular AMD and PCV, respectively. For heterozygous and homozygous carriers of the risk allele, the genotype-specific OR was 2.62  and 7.49  for neovascular AMD and 1.56  and 5.02  for PCV, respectively. Similar to previous findings of ARMS2 A69S association studies [We initially conducted a comparative genetic analysis of neovascular AMD and PCV, genotyping the  studies -31, the Our search identified five studies that met our inclusion criteria -31,51,52I2=41.2%; frequency of GT/TT genotypes, Q=9.0, 5 d.f., p=0.11, I2=44.5%).None of the five previously published studies demonstrated significant deviation from the HWE among controls . To estiI2=44.3%). This result, coupled with the finding that the 95% CIs for allelic summary ORs for neovascular AMD did not overlap with those for PCV, indicates that the genetic effect of the ARMS2 A69S variant is significantly stronger in neovascular AMD than in PCV.We conducted a meta-analysis based on an allele contrast model. The A69S variant showed a significant summary OR of 3.09  compared with PCV (55.6%). The meta-analysis estimated the attributable risks for the variant allele were 43.9% and 29.7% for neovascular AMD and PCV, respectively. In the control populations, the pooled frequency for the risk allele T of the A69S variant was estimated to be 37.4%, and individuals carrying at least one copy of the risk allele accounted for 60.8%, indicating its population-wide epidemiological consequence in Asian populations owing to the high frequency of the risk allele. No significant between-study heterogeneity was observed in any statistical analysis in this meta-analysis of Asian populations.Several studies have reported that the n in PCV -31. HoweThere is increasing evidence that ethnicity influences disease via genetic background . Risk alARMS2/HTRA1 region on 10q26 is a source of genetic risk for AMD is unclear. Much effort has been made to localize variant(s) causally related to AMD in this region and to understand the molecular basis of the susceptibility [ARMS2/HTRA1 region, adding to the difficulty in identifying true causal variant(s) by association mapping alone [ARMS2 and HTRA1 [ARMS2 A69S variant has been reported to show the strongest evidence for association [HTRA1 [ARMS2 [Currently, how the tibility ,54-58. Hng alone . The assnd HTRA1 . This LDn [HTRA1  and the 1 [ARMS2 —have rec1 [ARMS2 ,54-58. TARMS2 A69S variant between neovascular AMD and PCV. In addition, a significant difference has been reported between geographic atrophy and neovascular AMD with respect to genetic susceptibility at this locus [ARMS2/HTRA1 region on 10q26 in AMD susceptibility, defining molecular mechanisms through which the genomic variants influence disease risk and understanding the relationships between this region and disease subtypes will yield important insights, elucidating the biologic architecture of this phenotypically heterogeneous disorder.In conclusion, our meta-analysis has identified a difference in the hereditary contribution of the is locus ,32. This


Evidence suggests that MDM2 T309G polymorphism may be a risk factor for several cancers. Increasing investigations have been conducted on the association of MDM2 T309G polymorphisms with lung cancer risk and have yielded conflicting results. Previous meta-analyses on this issue have reported inconclusive data. The aim of the present study was to derive a more precise estimation of the relationship.Updated meta-analyses examining the association between MDM2 T309G polymorphism and lung cancer risk were performed. Separate analyses on ethnicity, smoking status, histological types and gender as well as source of controls were also implemented. Eligible studies were identified for the period up to Feb 2012. Lastly, ten publications including eleven case-control studies were selected for analysis. The overall data failed to indicate a significant association between MDM2 T309G polymorphism and lung cancer risk . In a subgroup analysis by smoking status, increased lung cancer risk was shown among never-smokers . In subgroup analysis by gender, elevated risk was presented among women under a recessive model . In the subgroup analysis by ethnicity, histological types and source of controls, no marked associations were observed.Compared to the previous meta-analyses, the results of this study confirmed that MDM2 T309G polymorphism might be a risk factor for lung cancer among never-smokers. However, the data failed to suggest a marked association between the G allele of MDM2 T309G and lung cancer risk among Asians. More interestingly, subgroup analysis by gender indicated that homozygous GG alleles might raise lung cancer risk among females. Lung cancer is the most commonly diagnosed cancer as well as the leading cause of cancer death worldwide Genetic factors involved in lung cancers have been extensively studied and to date several genetic polymorphisms have been identified as candidates by meta-analyses. Previous studies indicated that variations of some genes such as CYP1A1 Murine double minute-2 (MDM2) is a key negative regulator of the P53 tumor suppressor pathway that has been suggested to be mutated in a variety of cancers th nucleotide in the first intron (rs2279744), with a T to G change, could increase the affinity for stimulatory protein (Sp) 1 binding and result in increased MDM2 expression and subsequent attenuation of the P53 pathway A MDM2 single nucleotide polymorphism at the 309Previously, Gui et al. and Bai et al. conducted meta-analyses concerning the relationship between MDM2 T309G polymorphism and lung cancer risk In the present study, we carefully conducted a search and retrieved the possible publications up to Feb 2012. Then, we performed an updated meta-analysis that increases statistical power to derive a more precise estimation of the relationship.Murine double minute-2, MDM2, lung, neoplasm, tumor, cancer, variation and polymorphism. All searched studies were retrieved and the bibliographies were checked for other relevant publications. Review articles and bibliographies of other relevant studies identified were hand searched to find additional eligible studies.We carried out a search in the Medline, EMBASE, OVID, Sciencedirect, and Chinese National Knowledge Infrastructure (CNKI) without a language limitation, covering all papers published up to Feb 2012, with a combination of the following keywords: The following criteria were used for the literature selection: first, studies should concern association of MDM2 T309G polymorphism with lung cancer risk; second, studies must be observational studies (Case–control or cohort); and third, papers must offer the size of the sample, odds ratios (ORs) and their 95% confidence intervals (CIs), the genetic distribution or the information that can help infer the results. After rigorous searching, we reviewed all papers in accordance with the criteria defined above for further analysis.(Zhuo and Zhang) according to the inclusion criteria mentioned above. For conflicting evaluations, an agreement was reached following a discussion. If a consensus could not be reached, another author was consulted to resolve the dispute and then a final decision was made by the majority of the votes. Extracted information was entered into a database.Data were carefully extracted from all eligible publications independently by two of the authors 2I metric was applied to quantify heterogeneity between the included studies  P>0.1 for a given Q-test indicated a lack of heterogeneity among the studies, then ORs were pooled according to the fixed-effect model (Mantel-Haenszel) The odds ratio (OR) of MDM2 T309G polymorphisms and lung cancer risk was estimated for each study. The pooled ORs were performed for additive model (GG versus TT), dominant model (GG+GT versus TT) and recessive model (GG versus GT+TT). For detection of any possible sample size bias, the OR and its 95% confidence interval (CI) for each study was plotted against the number of participants. Publication bias was assessed by visual inspection of funnel plots Possible relevant publications were retrieved and screened. As shown in Of the selected publications, all were written in English. We established a database according to the extracted information from each study. The relevant information was listed in In the included studies, there were five groups of Caucasians Information about histological category could be extracted from six studies The distributions of MDM2 T309G genotype as well as the genotyping methods of the included studies are presented in P = 0.001 for Q-test; 2I = 67.5%), dominant model  and recessive model .As shown in However, when subgroup analyses regarding ethnicity, smoking status and histological types, gender as well as source of controls were further conducted, we found a reduced or loss of heterogeneity in some of the subgroups., when data were stratified according to ethnicity, no increased lung cancer risk was observed among Asians, Caucasians and Africans . Likewise, when data were stratified by histological types and source of controls, no significant increased lung cancer risk were observed. Nevertheless, in subgroup analysis regarding smoking status, increased lung carcinoma susceptibility was shown among the never-smoking subgroup , suggesting that G allele of MDM2 might increase lung cancer risk among individuals who have no smoking history. No significant association of MDM2 polymorphism with lung cancer risk was shown in the smoking group . In subgroup analysis by sex, the data indicated no associations regarding lung cancer risk among male subgroup. However, as for the female group, increased lung cancer risk was shown under the recessive model  .In subgroup analyses , when da, when da, when daWhen the effect-models were changed, the significance of the overall data for the three models was not statistically altered (data not shown). Additionally, we also conducted one-way sensitivity analysis . Additionally, results of the Egger’s tests also support the notion that the funnel plots were symmetrical  .Funnel plots were created for assessment of possible publication biases. Then, Egger’s linear regression tests were used to assess the symmetries of the plots. The funnel plots appeared to be symmetrical for the three models of the overall data . AdditioFor the overall data, the results showed that MDM2 T309G might not have a correlation with increased lung cancer risk. However, the subgroup analyses revealed an increased lung cancer risk among never-smokers who carry the G allele. Moreover, homozygous GG may increase lung cancer susceptibility among women.Several genome-wide association studies (GWASs) on SNPs have identified three genomic loci at 15q25, 5p15 and 6p21, which associate with the risk of lung cancer in Caucasians Previous meta-analyses have been conducted on the association of MDM2 T309G polymorphisms with several other cancer risks. Reports suggest that MDM2 T309G variation could increase risk of sarcoma, endometrial, hepatocellular and breast cancers For lung carcinoma, in the studies by Bai et al. and Gui et al. only seven reports with eight groups containing 6063 cases and 6678 controls were involved Smoking is an established risk factor for lung cancer and our data suggest that G allele carriers may have an approximately 48 percent higher lung cancer risk than the homozygous TT carriers who have no smoking history. However, the G allele seems to exert little effect on smokers. In the previous meta-analyses by Bai et al. and Gui et al., only the study by Bai et al. When the data were stratified according to ethnicity, no marked increased lung cancer risk was observed among Asians, Caucasians or Africans, inconsistent with the two previous meta-analyses In subgroup analysis according to gender, no increased lung cancer risk was presented in the male group. However, the recessive model showed increased lung cancer susceptibility among female individuals carrying GG alleles. The underlying mechanisms are still unclear. Evidence suggests that estrogen receptors have been widely detected in lung cancer cells, indicating that sex steroid may play a critical role in the pathogenesis of lung neoplastic diseases In the subgroups concerning histological type, no significant associations were observed in either the adenocarcinoma or the squamous cell carcinoma group. The results were in line with the overall data. We tried to extract information about other types of lung cancer. However, only sufficient data regarding adenocarcinoma and squamous cell carcinoma are available in the primary literature. Considering that possible differences may exist between these two most common subtypes of lung carcinoma due to the differences in genetic changes during tumorigenesis In the present study, between-study heterogeneities for overall data were observed in the three genetic models, and thus a random-effect model was used. However, we found that the heterogeneities were removed or reduced in the subgroup analyses, suggesting that the heterogeneities may be multifactorial such as selection of controls, race variation, gender, and prevalence of lifestyle factors.Publication biases were assessed via funnel plots and their symmetries were further evaluated by Egger’s linear regression tests. The data suggest that no evident biases were observed in the three genetic models, indicating the credibility and robustness of the results.Whether MDM2 SNP309 polymorphism has a correlation with the prognosis of cancers remains controversial. Evidence indicates that MDM2 SNP309 genetic variation might confer poor outcomes in colorectal cancer and chronic lymphocytic leukemia Several limitations might be included in this study. First, in this meta-analysis, the subgroup analysis concerned only Caucasians, Asians and African. Data regarding African could be extracted from only one study. Thus, data regarding other ethnicity are desired. Second, subgroup analyses regarding age have not been conducted in the present study because the criteria for age division were different in the primary literature. Third, hospital-based controls were used in some included studies and hence, non-differential misclassification bias might exist. Nevertheless, subgroup analysis regarding source of controls was carried out and no evident influence on the results was found. Additionally, gene-gene and gene-environment interactions should also be considered in future studies. However, the sensitivity analysis and publication biases analysis suggest the stability and credibility of the present meta-analysis.In summary, previous meta-analyses indicated a possible association of MDM2 T309G polymorphism with lung cancer risk among Asians and never-smokers. In the present updated meta-analysis, the data confirmed the relationship between MDM2 T309G genetic variation and lung cancer risk among individuals who have no smoking history. However, the data failed to show a significant increased lung carcinoma risk among Asians. More interestingly, subgroup analysis regarding histological types, source of controls and sex were performed and the data suggest that homozygous GG alleles might elevate lung cancer risk among females. Further investigations are needed to confirm the conclusions.


Candidate gene association studies and genome-wide association studies (GWAs) have identified a large number of single nucleotide polymorphisms (SNPs) loci affecting susceptibility to rheumatoid arthritis (RA). However, for the same locus, some studies have yielded inconsistent results. To assess all the available evidence for association, we performed a meta-analysis on previously published case-control studies investigating the association between SNPs and RA.OR) and 95% CIs were calculated. Cochran’s Q-statistics were used to assess heterogeneity. If the heterogeneity was high, a random effects model was used for meta-analysis, otherwise a fixed effects model was used.Two hundred and sixteen studies, involving 125 SNPs, were reviewed. For each SNP, three genetic models were considered: the allele, dominant and recessive effects models. For each model, the effect summary odds ratio (P<0.01) for the allele, dominant, and recessive models, respectively. (2) rs2476601 (PTPN22) showed the strongest association for all the three models: OR = 1.605, 95% CI: 1.540–1.672, P<1.00E−15 for the T-allele; OR = 1.638, 95% CI: 1.565–1.714, P<1.00E−15 for the T/T+T/C genotype and OR = 2.544, 95% CI: 2.173–2.978, P<1.00E−15 for the T/T genotype. (3) Only 23 (18.4%), 13 (10.4%) and 15 (12.0%) SNPs had high heterogeneity (P<0.01) for the three models, respectively. (4) For some of the SNPs, there was no publication bias according to Funnel plots and Egger’s regression tests (P<0.01). For the other SNPs, the associations were tested in only a few studies, and may have been subject to publication bias. More studies on these loci are required.The meta-analysis results showed that: (1) 30, 28 and 26 SNPs were significantly associated with RA (http://210.46.85.180/DRAP/index.php/Metaanalysis/index.Our meta-analysis provides a comprehensive evaluation of the RA association studies from the past two decades. The detailed meta-analysis results are available at:  Rheumatoid Arthritis (RA) is an autoimmune disease that causes inflammation of the joints and surrounding tissues. Its main symptoms are pain, swelling, stiffness and loss of function in the joints As a common, complex disease, RA is usually caused by the interaction of multiple genetic variants and environmental factors DRB1, especially affecting a shared common string of amino acid residues . These DRB1 alleles have consistently been shown to have strong association with RA Many studies have successfully identified RA disease loci. The most significant genetic locus for RA is the human leukocyte antigen (HLA) within the major histocompatibility complex (MHC) on chr 6p21. There are many alleles of the HLA class II gene, Although association studies of RA have achieved great success, certain problems remain. For the same locus, some studies have yielded conflicting results. For example, Munoz-Valle et al. described that the SNP rs231775 at position 49 (A/G) of the CTLA-4 gene is associated with RA Meta-analysis is a powerful tool that can improve the statistical performance by combining the results of multiple studies. Using meta-analysis methods, certain SNP loci, such as STAT4 rs7574865 The PubMed literature database was used to search for appropriate studies. The following key words were used: ‘polymorphism’, ‘single nucleotide polymorphisms’, ‘genome-wide association study’, ‘GWAs’, ‘rheumatoid arthritis’ and ‘RA’. All the studies were selected in accordance with following criteria: (1) all the articles were published between January 1992 and December 2011; (2) all the studies must be a case-control design, and examine the association between SNPs and RA; (3) the data of SNP genotypes in patients and in controls was available; and (4) the study was published as a full paper, not as an meeting abstract or review. Ultimately, 216 studies involving 125 SNPs were included in the meta-analysis. For each study, the following information was extracted: the polymorphism studied, the first author, year of publication, demographics, the numbers of cases and controls for the study.A and a . A is the high-risk candidate allele and a is the lower-risk allele. Three models are described as follows:To comprehensively analyze the relationships between SNPs and RA, three genetic models were selected: the allele model, the dominant model, and the recessive model. To illustrate the models, we assumed that a SNP marker locus has two alleles, labeled A allele vs. the a allele.Allele model: The effect of the A allele, that is, the A/A+A/a vs. the a/a genotypesDominant model: If it produces an RA phenotype when present in either one or two copies of A allele, that is, the A/A vs. the A/a+a/a genotypesRecessive model: If it produces a RA phenotype only when present in two copies of OR and its 95% CI for the individual study.For each model, we calculated the Q-statistics were used to test the heterogeneity of between- and within-study variation Cochran’s 2I, was used to measure the degree of inconsistency across studies. 2I is given by the formula: 2I takes values between 0% and 100%. 2 = I0–25% indicates low heterogeneity; 2 = I25–50% indicates moderate heterogeneity, 2 = I50–75% indicates large heterogeneity and 2 = I75–100% indicates extreme heterogeneity Another indicator, Q-statistics were used to test heterogeneity. If the Q-statistic was not significant, all differences between studies were considered to be caused by sampling error. Then, a fixed effects model was selected for the meta-analysis. The fixed effects model assumes that all studies in the meta-analysis share a common effect size. In contrast, if the Q-statistic was significant (P<0.01), heterogeneity existed between the studies. In this case, a random effects model was selected for the meta-analysis. The random effects model assumes that each study has a specific effect size, and allows heterogeneity exists between studies For each of the 125 loci, Cochran’s Funnel plots were used to assess publication bias. The estimated effects were plotted against their standard error. Usually, larger sample studies have smaller standard errors, and smaller sample studies have larger standard errors. Therefore, the estimated effects of small studies are more widely scattered than those of larger studies. If there is no bias, the plot will be a symmetrical inverted funnel. Egger’s test was used to test the asymmetry of the funnel plot http://cran.r-project.org/web/packages/meta/index.html).All statistical analyzes were performed using ‘Meta’ packages in the R language (PTPN22 gene locus was reported most frequently (34 times). For each study, the number of SNP genotypes in cases and controls was extracted for subsequent analysis.The PubMed database was searched and about 1,500 studies were reviewed. Ultimately, 216 published articles involving 125 SNPs were included in the meta-analysis. Each SNP was reported in at least two studies. The number of studies for each locus was also counted. Twenty SNPs were reported more than five times, 41 SNPs were reported three to four times, and 64 SNPs were reported twice. SNP rs2476601 at the OR and its 95% CI of the A allele (A vs. a) were calculated for the individual study, and the heterogeneity between studies was tested.For each SNP, the Q-statistic P<0.01. For the meta-analysis of these SNPs, a random effects model was used. For the remaining 102 SNPs, a fixed effects model was used. The meta-analysis showed that 30 SNPs were significantly associated with RA  for rs7528684 and 1.223 (95% CI 1.066–1.404) for rs1748033. The other 28 SNPs showed an association with RA under the fixed effects model. The most significant locus is rs2476601 . The pooled summary OR based on the fixed effects model was 1.605 (95% CI: 1.540–1.672), suggesting that the rs2476601 T-allele does confer susceptibility to RA. The publication bias was tested using Egger’s test. No significant publication biases were observed for any of the 30 significant SNPs.After heterogeneity testing, 23 SNPs had a P<0.01), and were analyzed using the random effects model. One hundred and twelve SNPs were analyzed using the fixed effects model. Q = 20.260, P = 0.009). For SNP rs7528684, although heterogeneity was observed under the allele model, it did not show heterogeneity under the dominant model . Therefore, the random effects model was used for the meta-analysis of rs1748033, and fixed effects model for rs7528684. All the meta-analysis results were compared under the allele model and the dominant model. Twenty-two SNPs displayed associations with RA under both models. Six SNP  were associated with RA only under the dominant model rather than the allele model. SNP rs2476601  still had the strongest association with RA under the dominant model . For all 28 significant SNPs, no significant publication biases were observed.Based on the dominant model (AA+Aa vs. aa genotype), the heterogeneity between the studies was tested. Thirteen SNPs had high heterogeneity . Compared with the allele model, 20 SNPs were significantly associated with RA under both the recessive model and the allele model, and six SNPs were specificity associated with RA under the recessive model. Compared with the dominant model, 12 SNPs were significantly associated with RA under both the recessive model and the dominant model, and 14 SNPs were specificity associated with RA under recessive model. Twelve SNPs  were significantly associated with RA under all the three genetic models. The most significant locus was still rs2476601 . For all 26 significant SNPs, no significant publication biases were observed.For the recessive model (AA vs. Aa+aa), 15 SNPs were analyzed using the random effects model, and 110 SNPs were analyzed using the fixed effects model. Ultimately, 26 SNPs displayed significant associations with RA , 2I and its 95% CI, results of meta-analysis (under the fixed effects model and the random effects model), forest plots and funnel plot for publication biases. These results are all available at: http://210.46.85.180/DRAP/index.php/Metaanalysis/index.More detailed meta-analysis results were gathered for each of the 125 loci, including: detailed list of articles , individual and combed PTPN22 gene), the T allele was significantly associated with RA in RF-positive, RF-negative and anti-CCP-positive RA patients versus controls. In addition, the T allele also showed a significant difference between RF-positive and -negative subjects. For rs7021206 (TRAF1 gene), the G allele was significantly associated with RA in RF-positive, anti-CCP-positive and anti-CCP-negative RA patients versus controls. For rs7574865 (STAT4 gene), the T allele was significantly associated with RA in RF-positive, RF-negative, anti-CCP-positive, and anti-CCP- negative RA patients versus controls. No heterogeneity was found for any of the 16 SNPs, and the meta-analysis was performed using fixed effects model. For more detailed results for each SNP see: http://210.46.85.180/DRAP/index.php/Metaanalysis/index.In the process of data collection, we noticed that some articles also provided additional testing for samples, such as rheumatoid factor  and anti-cyclic citrullinated peptide antibody . A meta-analysis of the SNPs that included the above information (16 SNPs) was also carried out. The meta-analysis results are shown in OR = 1.17, 95% CI: 1.09–1.24, P<1.00E−4). No evidence of association was observed in European and American subgroups. This indicated that the heterogeneity of rs7528684 may be caused by regional differences, and the C allele is a risk allele in the Asian population, but not in Europeans and Americans. For SNP rs1800629, 14 studies were divided into three subgroups: European (six studies), Asian (four studies) and American (three studies). One study was excluded because the study population was African. For each of the three subgroups, no heterogeneity was observed. The meta-analysis results showed that rs1800629 was associated with RA in both Asian  and American  subgroups. However, there was different risk allele in the two subgroups . No evidence of association was observed in the European subgroup. This also indicated that regional difference is an important reason for the heterogeneity of rs7528684. The risk allele in Asian is G, while in American is A. For rs1800896, only the European subgroup was analyzed . There was a high heterogeneity in the European subgroup (P = 0.001) and rs1800896 is not associated with RA in the European subgroup. Further studies are required to identify the reasons behind the heterogeneity of the SNP rs1800896.In this paragraph, some of the SNPs that showed heterogeneity were subjected to subgroup analysis to explain the causes of the heterogeneity. Some SNPs were reported by a few individual studies, and not suitable for the classification by subgroups. Thus, SNPs were selected that were reported by more than 10 individual studies for the subgroup analysis. Three SNPs, rs7528684 (15 studies), rs1800629 (14 studies) and rs1800896 (11 studies) were selected. Only the allele model was considered. The meta-analysis results of the subgroups are shown in In the past two decades, many SNP loci have been identified as associated with RA by candidate gene association studies and GWAs. However, RA is a complex disease, and many genetic loci contribute to susceptibility to RA. Some association studies are underpowered for detecting the modest contributions of these genetic loci. This will lead to inconsistent results because of false-positives, false-negatives, or population differences OR = 1.605 for allele model, OR = 1.638 for dominant model, and OR = 2.544 for recessive model). The SNP is a common SNP, and is located in the PTPN22 gene, which encodes a lymphoid-specific phosphatase (Lyp). rs2476601 is a nonsynonymous SNP, and changes the amino acid at position 620 from an arginine (R) to a tryptophan (W). This change affects the physical association with tyrosine kinase Csk during T cell activation PTPN22 gene showed significant association with RA: five SNPs in the allele model .In this study, a comprehensive and systematic meta-analysis was carried out to assess the associations between 125 SNPs and RA susceptibility. Three genetic models were considered: the allele, recessive and dominant models. The meta-analysis results showed that 30, 28 and 26 SNPs were significantly associated with RA under each model, respectively. SNP rs2476601 had the strongest association with RA under all three models , rs2280714 , TAP2 379A/G , and TNFRII 676T/G . For all four sites, the results of the meta-analysis were not significant under all three genetic models. In other words, the significant association results in the meta-analysis were not affected by publication bias. This indicated that our meta-analysis is reliable. Nevertheless, some of the SNPs were tested for association only in a few studies, and there may be a publication bias for such SNPs. More studies on these loci are required.In summary, a meta-analysis of 125 SNPs was carried out with the aim improving the statistical performance by increasing the sample size. After the meta-analysis, associations between certain SNPs and RA susceptibility were confirmed. However, certain SNP loci were reported by only a few articles, and further more studies are needed to clarify the associations between these SNPs and RA susceptibility.


The association of functional polymorphisms in the promoter of the apoptosis gene FAS with systemic lupus erythematosus (SLE) susceptibility has been a controversial subject. We conducted a case-control study to investigate this association in a Chinese population and performed a meta-analysis in different populations. The single nucleotide polymorphisms (SNPs) rs2234767 (−1377G>A) and rs1800682 (−670A>G) were genotyped by TaqMan allelic discrimination assays in 552 Chinese SLE patients and 718 healthy controls. In our case-control study, we observed allelic association between the promoter SNP rs2234767  and SLE but not the SNP rs1800682. Haplotype analysis revealed that one haplotype of GA was significantly associated with the disease . In the meta-analysis available studies, including our data, were combined using the STATA software package v.7.0. The meta-analysis revealed a significant association between FAS polymorphisms and SLE . In conclusion, FAS gene polymorphisms may contribute to SLE susceptibility in the Chinese population, and the meta-analysis shows that FAS polymorphisms may be associated with SLE susceptibility in different populations. Systemic lupus erythematosus (SLE) is a prototypic auto-immune disease, characterized by autoantibody production, immune complex formation and multiple organ damage . AlthougFAS (CD95/APO-1/TNFSF6), as a transmembrane receptor among cell surface death receptors, belongs to the tumor necrosis factor receptor (TNFR) superfamily. It is expressed on numerous types of immune cells  and playThe human FAS gene, which is mapped to chromosome 10q24.1, consists of nine exons and eight introns –16. ThesA total of 552 patients with SLE were recruited from Anhui Provincial Hospital and The First Affiliated Hospital of Anhui Medical University. All patients fulfilled the 1997 revised criteria of the American College of Rheumatology for the classification of SLE . Their mEDTA anti-coagulated venous blood samples were obtained from all the participants. Genomic DNA was extracted from peripheral blood lymphocytes by standard procedures using Flexi Gene DNA kits . All samples were stored at −80°C prior to testing. A total of two SNPs were genotyped by the TaqMan SNP Genotyping Assay kit . Real-time polymerase chain reaction (PCR) was performed on the ABI PRISM 7300 . The reaction conditions were initially denatured at 95°C for 10 min followed by 45 cycles of denaturing at 95°C for 15 sec and annealing/extension at 60°C for 1 min.*Power (http://www.psycho.uniduesseldorf.de/aap/projects/gpower).Data analysis was performed using SPSS 10.0 software . The Chi-square test or Fisher's exact test was used to estimate the Hardy-Weinberg equilibrium (HWE) in both SLE patients and healthy controls, as well as to compare the genotype and allele frequencies between the two groups. Odds ratios (ORs) and 95% confidence intervals (CIs) were also calculated. The multiple-locus haplotypes comprising the two SNPs were estimated by comparing the difference in the haplotype frequencies for the overall subjects with the SHEsis software . In the All studies examining the association between FAS polymorphism and SLE were fully considered and carefully selected. Three electronic databases  were searched using the search terms ‘FAS’, ‘TNFSF6’, ‘CD95’, ‘APO-1’, ‘systemic lupus erythematosus’ and ‘SLE’. The most recent search was updated in March 2012. We only recruited data from fully published papers, not meeting or conference abstracts. The inclusion criteria were as follows; i) independent case-control design, ii) available allele frequency or genotype distribution data and iii) sufficient published data for estimating OR with 95% CI.2) values were presented to assess the heterogeneity (2>50%) indicated heterogeneity across studies, the random effects model was used, and when heterogeneity was not indicated across studies, the fixed effects model was used. The Z test was used to determine the significance of overall effect . Cochran's Q-statistic and inconsistency . We estimated that our study has a statistical power of 94.6% by the statistical program G*Power.The association between the frequencies of haplotypes and SLE was also estimated. A total of four  possibleIn the meta-analysis, four studies ,13,16 weA summary of the meta-analysis findings on the association between the FAS polymorphisms and SLE is provided in *Power. Heterogeneity was demonstrated in the meta-analysis for the rs1800682 but not for the rs2234767 polymorphism. Egger's regression test showed no evidence of publication bias in this meta-analysis of FAS polymorphisms in any of the studies included (Egger's regression test P>0.1; The distribution of rs2234767 and rs1800682 genotypes in control groups was consistent with the HWE in all studies . We evalEvidence has accumulated that FAS-mediated apoptosis may be involved in the pathogenesis of SLE. The expression of FAS on peripheral blood lymphocytes has been reported to be upregulated in patients with SLE . The varet al (In our case-control study, we analyzed the frequencies of alleles and genotypes at the two SNPs in 552 SLE patients and 718 healthy controls of the Chinese population. We showed that the A allele frequency of rs2234767 is associated with SLE susceptibility. Significant differences in the genotype frequencies of AG vs. GG, AG+AA vs. GG at rs2234767 were observed. However, on evaluation of allele and genotype distributions at rs1800682, no significant differences were observed between patients and controls. Analysis of the haplotypes revealed that individuals carrying the haplotype GA had an increased risk of SLE. The results of the haplotype analysis were concordant with the suggestion that the rs2234767 G allele was mainly associated with the rs1800682 A allele in SLE patients by Kanemitsu et al . They obet al . This coet al (et al (et al (The repeated investigation of the association of FAS polymorphisms with SLE in different populations supports the involvement of this gene in SLE susceptibility. However, certain conclusions are inconsistent. For example, studies by Molin et al  and Kanel (et al  demonstrl (et al , Korean l (et al , Australl (et al  populatil (et al , the SNPl (et al  and Austl (et al . Due to The positive result of rs2234767 was presented by our replication study and confirmed by meta-analysis. Although our study did not find an association between rs1800682 and SLE in the Chinese population, the association was identified in overall and Asian populations in the meta-analysis. Heterogeneity was observed in the meta-analysis for rs1800682 and SLE. One of the reasons for this disparity may be due to population differences in genotype distributions. In addition, we observed a strong LD between the two SNPs in our study population, but a weaker LD was suggested in the Japanese population . TherefoThere are certain limitations of this meta-analysis that should be discussed. First, the number of studies and the number of subjects in the studies included in the meta-analysis by the disease were small. Second, when we explored the association between rs1800682 and SLE, heterogeneity was observed. Third, our ethnicity-specific meta-analysis included data from individuals with Asian and European origin, and thus the results are applicable to only these groups. In the subgroup analysis, the majority of the studies were performed in populations of Asian descent. Further studies are therefore required in other ethnic populations. Despite these limitations, our meta-analysis confirmed an association between SLE and FAS gene polymorphisms.Our investigation provided evidence that FAS gene polymorphisms contributed to SLE susceptibility in the Chinese population. The combined results of independent association studies by meta-analysis showed significant association between FAS polymorphisms and SLE. The investigation of the genetic basis of SLE in other populations may advance the overall understanding of the pathogenesis of this disease. Further studies are still required in larger numbers of samples and other ethnic populations.