O6-methylguanine-DNA methyltransferase (MGMT) remains controversial for breast and gynecologic cancers. We conducted a meta-analysis to assess the association between hypermethylation of MGMT promoter and the risk of breast and gynecologic cancers. A comprehensive search was conducted in PubMed and Embase electronic databases up to 19th August 2017 for studies about the association between MGMT promoter hypermethylation and breast and gynecologic cancers. A total of 28 articles including 2,171 tumor tissues and 1,191 controls were involved in the meta-analysis. The pooled results showed that MGMT promoter methylation status was significantly associated with an increased risk of breast and gynecologic cancers . The associations were robust in subgroup analysis based on ethnicity, cancer type, methylation detection method, and control source. This meta-analysis indicated that MGMT hypermethylation was significantly associated with the risk of breast and gynecological cancers, and it may be utilized as a valuable biomarker in early diagnostics and prognostication of these cancers. Further efforts are needed to identify and validate this finding in prospective studies, especially in situation with new methylation testing methods and samples from plasma circulating DNA.The role of the promoter methylation of  Breast cancer ranks first with 25.5% (1.7 million cases) of all incident cancers, and the genitals  accounts for 16.5% (1.1 million cases) of them. It has generally been accepted that the late diagnosis of breast and gynecologic cancers is a serious global problem, which makes treatment less likely to succeed and reduces their chances of survival3. As promoter CpG island hypermethylation is considered to be an early alteration in carcinogenesis and is often present in the precursor lesions of a variety of cancers, DNA hypermethylation might be used as a marker for the early diagnosis of cancer4.Malignant diseases of the breast and genitals are the most common cancers in women worldwide, and about 2.8 million new cases and 1.0 million cause-specific death each yearO6-methylguanine-DNA methyltransferase (MGMT), is a widely expressed DNA repair gene that plays a crucial role in repair of DNA damage caused by alkylating agents6. Epigenetic silencing via hypermethylation of specific promoter CpG island is regarded as one of the causes for loss of MGMT activity in tumor tissues7. It has been suggested that loss of MGMT is associated with increased carcinogenic risk and increased sensitivity to therapeutic methylating agents5. Although the exact role of MGMT promoter methylation in malignant transformation and carcinogenesis remains unrevealed completely, it might be a good biomarker candidate for early cancer detection5. The hypermethylation of CpG islands is relatively rare in normal cells, thus the detection of methylated DNA in bodily fluids can be promising8. Several studies have focused on this in other cancers including head and neck squamous cell carcinoma, lung cancer and esophageal cancer11. Nevertheless, for breast and gynecologic cancers, although many studies have explored the association between their risks and MGMT promoter hypermethylation, the results remain inconsistent39. A possible reason to explain the noted discrepancies in results is the inadequate statistical power of the individual studies, especially for relatively rare types . Due to breast cancer and gynecologic cancer generally share several common risk factors, such as reproductive history and BRCA1/2 mutations, it is usually adapted to explore or summarize their associated factors together in a few studies or in clinical resource (such as Physician Data Query)43. Therefore, we conducted this systematic review and meta-analysis to assess the association between hypermethylation of MGMT promoter and the risk of breast and gynecologic cancers.MGMT hypermethylation. According to the inclusion criteria, 28 articles were included in our meta-analysis. One article reported two cancers16 separately and thus was divided to two studies.The selection flow of studies was summarized in Fig. 31 that also included black and other mixed populations. Table All the eligible studies were issued in English. In total of 2,171 cases and 1,191 controls were involved in the pooled analyses. The publication year of selected studies ranged from 2001 to 2015. All studies focused on Caucasians or Asians except for two studies in the USAMGMT promoter hypermethylation with risk of breast and gynecological cancers was shown in Fig. 2 = 54.3%, P < 0.05). The pooled results showed that MGMT promoter methylation status was significantly associated with an increased risk of breast and gynecological cancers in women .The combining result of the association of MGMT promoter methylation, other methods including pyrosequencing, QMSP, MS-MLPA, MS-HRM and MethyLight were classified as non-MSP group. The ORs were 4.56  in the MSP group under random effects model, and 4.60  in the non-MSP group under the fixed-effects model. With regard to the control source, one study20 had both autologous and heterogeneous samples as control and was divided into two studies. Three studies were excluded since they included blood sample as controls. The pooled ORs in heterogeneous and autologous tissue group were overlapped under the fixed effects model, and with the value of 3.33  and 11.37 , respectively. While in heterogeneous exfoliated cells group, the MGMT promoter methylation status was not significantly associated with cancer risk with a pooled OR of 1.83 .We performed subgroup analysis to evaluate the source of the heterogeneity according to ethnicity, cancer type, methylation detection method, and control source Table . No sign38 which got an NOS score < 6. The pooled results were not significant changed for random effects model , indicating that patients with hypermethylated MGMT may have an increased risk in breast and gynecological cancers.Sensitivity analysis performed by excluding the “low quality” study23 with the biggest OR outlier in the random effects model with statistical significant finding. The overall OR was changed from 4.37  to 3.97 , which demonstrated that the pooled OR was reliable and stable.We also took another sensitivity analysis by excluding the studyP < 0.05), suggesting that there might be publication bias due to small-study effects in our study.Visual inspection of funnel plots and the Egger’s test were used to evaluate the publication bias in our meta-analysis. The funnel plot displayed in Fig. MGMT promoter methylation status and risk of breast and gynecological cancers in women. A total of 29 studies including 2,171 tumor tissues and 1,191 controls were involved in the meta-analysis. The proportion of MGMT promoter hypermethylation ranged from 3.0% to 70.1% (median: 24.8%) in tumor tissues and 0.0% to 36.9% (median: 0.3%) in non-cancerous controls, respectively. Our major finding suggested that MGMT promoter hypermethylation had a significantly increased risk in tumor tissues  compared with non-cancerous tissues and exfoliated cells.To the best of our knowledge, this meta-analysis is the first to comprehensively evaluate the association between MGMT promoter and risk of breast and gynecological cancers in women32, whereas all of the remaining suggested no significant relationship39. When all studies were pooled into the meta-analysis, cancer risk associated with MGMT promoter hypermethylation was significant in breast and gynecological cancers. The result of sensitivity analysis revealed that this association was quite reliable and stable after excluding the study with the largest OR outlier23, or excluding four studies with lower quality38. Power analysis was also conducted according to our own data. Assuming OR as 4.0 and proportion of MGMT promoter hypermethylation among controls as 0.3%, the powers before and after excluding above studies were both vigorous with a value always larger than 80% in corresponding sample size.About 8 of 29 included studies presented significant association between hypermethylation of MGMT gene was associated with the risk of breast and gynecological cancers in almost all these subgroups, except for endometrial cancer and vulvar cancer due to limited samples (<50)28. Although MSP has some defects which prompt researchers to develop novel test methods, such as pyrosequencing, QMSP,Since heterogeneity obviously existed among studies, stratified analyses were also performed based on ethnicity, cancer types, methylation detection methods, and control source. The subgroup analysis suggested that hypermethylation of the 45, it is still generally accepted as the best way to evaluate the methylation status of the MGMT promoter46. About 4/5 of included studies have used MSP, and no discrepant results between MSP and non-MSP were showed in our study. We acknowledge that we could not refine the non-MSP in further detail due to the limited related studies, which may need further evaluation in future. In addition, the ORs with autologous tissues as control, were not significantly different from that with heterogeneous tissues, but were significantly larger than that compared with heterogeneous exfoliated cells. It might be explained by the known higher methylation proportion of exfoliated cells in normal or intraepithelial lesions 21. In our pooled result, the MGMT methylation rate was more than 30% in exfoliated cells but only ranged from 0% to 14% for the adjacent tissues, which also further supported our explanation.MS-MLPA, MS-HRM and MethyLightMGMT gene is ubiquitously expressed in different organs and different tumors and MGMT is responsible for removing the alkyl adducts from the DNA molecules48. If repair of the alkylating lesions does not complete entirely, a G → A transition mutation or a strand break can occur, resulting in oncogene mutations in pre-malignant lesions (e.g. KRAS point mutations), or futile cycles of repair that triggers apoptosis (outcome of therapeutic treatment such as Temozolomide in glioblastoma), respectively48. In addition, it has been reported that MGMT gene expression in normal and neoplatic tissues varies and MGMT promoter methylation was associated with better suvivial in some cancer types but not all47. In the present study, we showed that MGMT promoter methylation status was significantly associated with an increased risk of breast and gynecologic cancers, which is consistent with previous studies in head and neck squamous cell carcinoma, lung cancer, glioblastoma, and esophageal cancer11. These works including ours highlighted the possibility of using MGMT promoter methylation status as a biomarker49, based on the facts that MGMT promoter hypermethylation could occur early in the neoplastic process before the clinical manifestation51, or turn up in normal appearing tissues close to tumors53. Currently, it has been indicated that hypermethylation of MGMT in circulating DNA might serve as a surrogate marker for tumor methylation in invasive ductal breast carcinomas26. Therefore, along with the development of different assays for CpGs methylation54, our finding provided supporting evidence for diagnosis and prognosis of breast and gynecological cancers with obtaining blood samples instead of biopsies.The MGMT promoter and the risk of breast and gynecologic cancers. Our results are reliable according to the stability and consistency in all subgroup analysis and sensitivity analyses. Neither specific factor nor single study could significantly affect the summarized OR. However, the presented information still should be interpreted with caution because some limitations existed. Firstly, funnel plots and results of Egger’s test in our study showed significant result. The small-study effect presented clearly base on visual assessment, but it’s hard to attribute this effect entirely to publication bias55. Nevertheless, publication bias may still exist considering that some studies were excluded due to unavailable information and that studies with negative results often have less chance for publication. Secondly, the lack of the original data limited the further subgroup analysis based on patients’ comorbidity, BMI, lifestyle and other environmental factors, thus, it is still not sure whether MGMT promoter hypermethylation is an independent predictive factor. Thirdly, all of the included studies were retrospective, and prospective cohort studies should be required to confirm our conclusion of its predictive value. Fourth, as an association study, it should be noted that although our results indicated the similar positive associations of MGMT promoter hypermethylation with different types of cancer, the exact underlying mechanisms might be still diverse in different types of cancer.We believe that this is the first quantitative study to assess the association between hypermethylation of MGMT hypermethylation was significantly associated with the risk of breast and gynecological cancers. Consequently, detection of MGMT promoter hypermethylation may be utilized as a valuable biomarker in early diagnostics and prognostication of these cancers. However, further efforts are needed to identify and validate this finding in prospective studies, especially in situation with new methylation testing methods and samples from plasma circulating DNA.To sum up, this meta-analysis indicated that 56. We used both the medical subject headings (MeSH) and free-text words. Search terms mainly included methylation, MGMT and different gynecological cancer including endometrial cancer, ovarian cancer, vulvar cancer, uterine cancer, vaginal cancer, cervical cancer, fallopian tube cancer, as well as breast cancer in women. The references of the retrieved articles and related reviews were also carefully checked to find additional eligible studies. No language or other limits were set during the course of literature search.A comprehensive search was conducted to identify all eligible publications in PubMed and Embase electronic databases up to 19th August 2017MGMT and risk of gynecological or breast cancer in women; (3) provided sufficient data  for calculating the odds ratio (OR) and it 95% confidence interval (CI). Letters, comments, conference reports, laboratory studies and articles that didn’t present enough data for ORs calculation were excluded.A study was included if it met the following criteria: (1) case-control or cohort study design; (2) evaluated the association between the methylation of Two reviewers independently read the eligible studies. The following items were extracted from each eligible study: surname of first author, publication year, country of the investigation, ethnicity, diagnosis, method for detecting the methylation status, sample type in case and control groups, and methylation distribution. A discussion was carried out to achieve consensus when discrepancy noted.57. It contains three parts: case and control selection, comparability, and exposure. Each of them respectively comprises four, two, and three items. Each item is given 1 point, 9 points in total. The cut point of 6 points was used to distinguish “low quality” (<6 points) and “high quality” (≥6 points). Disagreements between investigators regarding data extraction were resolved through discussion.The Newcastle-Ottawa Scale1 (NOS), one of the most commonly used tools for assessing the quality of observational studies in a meta-analysis setting, was employed to evaluate the quality of eligible studies by two investigators independentlyMGMT promoter hypermethylation and risk of breast and gynecological cancers. We used I2 statistic and Q test to measure the between-study heterogeneity. If I2 < 50% and P > 0.1, the heterogeneity was considered mild, and the summary ORs were combined under a fixed-effects model, otherwise a random-effects model were used. The Z test was used to assess the statistical significance of pooled ORs, and two-tailed P-values <0.05 were considered significant. Moreover, we performed subgroup analysis based on ethnicity, cancer type, methylation detection method, and control source to explore potential sources of heterogeneity. Sensitivity analysis were also performed by the study with “low quality”, and excluding the study with the OR outlier with statistically significant findings. The Egger’s test and visual inspection of funnel plots were utilized to explore any possible publication bias. All statistical analyses were conducted in STATA 12.0 .Crude ORs together with their corresponding 95% CIs were calculated to evaluate the association between


It is well established that type 2 diabetes mellitus (T2DM) is associated with oxidative stress and glutathione S-transferases (GSTs) protect cells against oxidative stress. The missense substitution Ile105Val (rs1695) of the glutathione S-transferase P1  results from an A/G base substitution at nucleotide 313. Many studies have evaluated the correlation between the rs1695 polymorphism and T2DM, but the results remain inconclusive. The aim of the present meta-analysis was to investigate the association between GSTP1 Ile105Val polymorphism and the susceptibility risk of T2DM. Eligible studies (published before August 2017) were identified in several databases. The heterogeneity between studies was evaluated with the chi-square based Q test and the I2 test. The strengths of the association were assessed by pooled odds ratios (ORs) and the corresponding 95 % confidence interval (95 % CI) using either a fixed or random-effects models. Eighteen studies documenting a total of 2595 T2DM cases and 2888 controls were included in this meta-analysis. In the overall analysis there was no significant association between the rs1695 polymorphism and the risk of T2DM. The subgroup analyses stratified by ethnicity, publication year and sample size did not reveal significant association between the study polymorphism and the risk of T2DM and any sources contributing to the substantial heterogeneity between studies. The present meta-analysis suggested that there was significant heterogeneity between studies. Considering some limi tations of our meta-analysis, further large-scale studies should be done to reach a more comprehensive understanding. Oxidative stress defines as imbalance between reactive oxygen species and anti-oxidant defense systems and it is associated with pathogenesis of diseases. In human, genes involved in antioxidant defenses are highly polymorphic and show association with several multifactorial traits  . The prOne of the most important cellular detoxification systems is glutathione S-transferase  enzymes. The GSTs are involved in catalyzing the conjugation reactions of reactive intermediates of electrophilic compounds with cytosolic glutathione. The glutathione S-transferase P1  encodes the π-class of GSTs, which accounts for about 90 % of the enzymatic activity of the GST family; and expressed in many normal tissues . GSTP1 is polymorphic and its variant alleles occurr at a high frequency. The missense substitution Ile105Val (rs1695) of the GSTP1 results from an A/G base substitution at nucleotide 313. The Val105 form of the GSTP1 enzyme may be 2-3 times less stable than the Ile105 form  and mayal., 1998). Enzymeal., 1998; Hu et aal., 1998; SundberGSTP1 polymorphism and the risk of T2DM has been investigated, but these studies yielded controversial results , other al., 2010; Oniki eal., 2010; Moasseral., 2010; Gönül eal., 2010; Abbasi al., 2010). WhetheLiterature databases, including PubMed, Scopus, DOAJ, Index Copernicus, JSTOR, JournalTOCs, AJOL , Asia Journal Online, Index Scholar, Academic Journals Databases, Google Scholar, Research Bib, High-Wire, J-STAGE, Serbian citation index, KoreaMed, IndMed, PakMediNet and SID (Scientific Information Database) were searched for relevant studies (the last search was updated in August 2017). GSTP1', 'rs1695', polymorphism, Ile105Val. The search was limited to studies published in English or Persian. In addition the bibliographies of the retrieved studies were screened to identify relevant publications.The following search terms were used:  a case-control study to evaluate the association between rs1695 polymorphism and risk of T2DM; (2) raw data including sample size, allele or genotype distribution were given. Accordingly, the exclusion criteria were as follows: reviews, meta-analysis, editorial articles, abstracts, comments.The following information was extracted from each: Name of the first author, year of publication, country of origin, ethnicities of the individuals involved, number of cases and controls, genotyping method, and number of genotypes for the study polymorphism in cases and controls. GSTP1 Ile105Val polymorphism and risk of T2DM were estimated for each study. Hardy-Weinberg equilibrium in controls was tested by a chi-square test. The crude odds ratios (ORs) and 95 % confidence intervals (95 % CIs) of 2 test. An I2 value of less than 25 % indicates low heterogeneity, 25 % to 50 % indicates moderate heterogeneity, and greater than 50 % indicates high heterogeneity. I2> 50 % or P < 0.10 for Q statistics was considered as significant heterogeneity. The heterogeneity between studies was evaluated with the chi-square based Q test and the Ivs Ile/Ile and Val/Val vs Ile/Ile), dominant model  and allele model . We also performed subgroup analysis according to ethnicity (Caucasian), sample size (≤300/>300 subjects), and publication year (prior to or during 2012/after 2012). If no significant heterogeneity was found between the studies, the pooled OR was calculated by using the fixed effects model (the Mantel-Haenszel method) . OtherwMoreover, sensitivity analysis was performed to evaluate the stability of the results following sequential removal of each study. To determine the evidence of publication bias, the funnel plot and Egger's test were both used. An asymmetric plot suggested possible publication bias. For the interpretation of Egger's test, statistical significance was defined as P<0.05 . In total, 18 independent studies including 5483 subjects (2595 T2DM cases and 2888 controls) were included in the study. The studies were published between 2007 and 2017. The characteristics of each study were summarized in Table 1In overall there was no significant association between the study polymorphism and the risk of T2DM under codominant Figure 1. It shouGSTP1 Ile105Val polymorphism and the risk of T2DM in any of the genetic models . The results of sensitivity analyses indicated the stability of the results of this meta-analysis. Funnel plots were created and Egger's test was performed to assess the publication bias of the included studies. The funnel plots did not show obvious asymmetry in the overall population (data not shown). Sensitivity analyses were performed by sequential omission of individual studies for all subjects and subgroups. The corresponding pooled ORs were not altered in all subjects and subgroups of It has been well established that oxidative stress is involved in pathogenesis of T2DM . ConsidSome limitations of the present meta-analysis should be acknowledged. The non-conformity of the geographical distribution of the association studies used in the meta-analysis is the most important limitation of the present study. There was no report from America continent, Western Europe, Australia and East of Asia. Second, the sample size in some subgroup analysis was small (Yalin et al., 2007; Tsai etA more comprehensive analysis should be conducted when more original information is available and interactions among the risk factors are considered. Further well-designed large studies are required to investigate gene-environment interactions.This study was supported by Shiraz University.No competing interests are declared by any of the authors.


PRKAA1) that confers susceptibility to gastric cancer (GC) was identified by genome-wide association in several case-control studies. However, the results remained controversial and ambiguous. Therefore, we performed a larger meta-analysis to confirm this association. We searched the PubMed, Embase, WanFang, and CNKI databases, without any restriction on language, covering all papers published until Feb 22, 2017. Overall, 14 case-control studies with 14,485 cases and 14,792 controls were retrieved based on the search criteria. Odds ratios (ORs) with 95% confidence intervals (CIs) were used to quantify the strength of the association. Publication bias was assessed by Egger’s and Begg’s tests. We found that the PRKAA1 rs13361707 C/T polymorphism had no association with GC risk in any of the pooled genetic models . Furthermore, in analyses stratified by either source of control or geographical origin of subjects, a statistically significant inverse relationship was detected between PRKAA1 rs13361707 C/T polymorphism and GC risk. No obvious evidence of publication bias was detected in the pooled meta-analysis. Furthermore, we observed that individuals carrying T-allele (TT or TC) genotypes had a lower expression of PRKAA1. Our present study indicated that PRKAA1 rs13361707 C/T was not significantly associated with GC risk, despite few positive results in the subgroups.A single nucleotide polymorphism (SNP) of the protein kinase catalytic subunit alpha-1 gene ( Gastric cancer (GC), including both the cardia and non-cardia types, is the second leading cause of cancer mortality in the world, with an estimated 720,000 gastric cancer-related deaths in 2012 . Indeed,Helicobacter pylori (H. pylori), and a history of stomach disorders have been considered potential risk factors [The epidemiology of GC is complex and multifactorial in nature. Several environmental factors, including alcohol consumption, diet, tobacco smoke, exposure to  factors . Additio factors , 6.(PRKAA1) rs13361707 polymorphism was significantly associated with GC risk .In 2011, Shi et al . first pPRKAA1 is also known as AMPKa1. It is the catalytic subunit of 5’-AMP-activated protein kinase (AMPK), which is a cellular energy sensor conserved across all eukaryotic cells. The kinase activity of AMPK is activated by stimuli that increase the cellular AMP/ATP ratio. AMPK regulates the activities of a number of key metabolic enzymes through phosphorylation. It protects cells from stresses that cause ATP depletion by switching off ATP-consuming biosynthetic pathways. Alternatively-spliced transcript variants encoding distinct isoforms of the protein have been observed in several diseases, including cancer –10.rs13361707 SNP is located in the first intron of PRKAA1 at the 5p13.1 site, which is located close to the gene for prostaglandin E receptor 4 (PTGER4). PTGER4 is a prostaglandin (PG) E2 receptor, which is a major product of cyclooxygenase-2 (COX-2) action that plays an important role in immune response and cancer pathogenesis [PRKAA1 rs13361707 C/T polymorphism is associated with gastric, colon, and rectal cancers . However, the direction of this association remains ambiguous and the polymorphism may even be inversely related to GC risk.The PRKAA1 rs13361707 C/T polymorphism and GC risk. However, two limitations affected their study: the samples included were relatively small, and several case-control studies, including two written in Chinese, were not identified for inclusion. Subsequent to that publication, even more case-control studies have been published [PRKAA1 rs13361707 C/T polymorphism and GC risk, especially in the light of new publications, an updated meta-analysis of all eligible case-control studies [In 2015, Qiu et al . conductublished –14. Ther studies –19 was nPRKAA1 polymorphism. Another eight duplicated articles were also excluded. The publication by Shi et al. [A total of 51 articles were retrieved based on our selection strategy from the PubMed, Embase, WanFang, and CNKI databases. Among them, 33 articles were excluded because they did not provide information about the i et al.  includedi et al. , 11–19 (PRKAA1 rs13361707 C/T polymorphism among the five main population groups reported in the 1000 Genomes Browser: East Asian (0.55), European (0.29), African (0.36), American (0.25), and South Asian (0.33). The MAFs in our analysis were found to be 0.49 and 0.51 for the case and control groups, respectively. Our estimates accorded well with the East Asian MAF reported in the 1000 Genomes Browser database. Finally, the distribution of genotypes among controls was consistent with Hardy–Weinberg equilibrium (HWE) in all models.We also checked the MAF  of the PRKAA1 rs13361707 C/T. The different genetic models of polymorphism-associated risk tested for the pooled Asian population were: allelic contrast , heterozygote comparison , the dominant allele model  and the recessive allele model . The lack of association in our models is diametrically opposed to the conclusions reported by Qiu et al. [In the pooled analysis of all Asian populations, no association could be observed between GC risk and the genotypic variants of u et al.  , 64 (32%) and 96 (48%), respectively. Moreover, serum PRKAA1 levels in GC patients with TT/TC genotypes were significantly lower than in those with CC genotypes  polymorphism can decrease GC risk in the HB and Korean populations, which suggests that the role of this polymorphism in increasing GC susceptibility is limited, and the T-allele may even protect against GC susceptibility, although no evidence supporting this possibility had been found until date. A probable explanation for this phenomenon is that the samples included from Korea were much smaller than those included from China; therefore, even if a significant association exists in the Korean population, its influence was offset by a negative association from the Chinese population and thus no association was detected in the pooled analysis. The same explanation might apply to the association observed in the analysis stratified by source of the control group: a significant inverse relationship was observed for the HB population but not for the pooled population. Besides, complex interactions between several genetic and environmental factors may be involved in cancer development.To evaluate the association between analysis  with addanalysis ; therefoPRKAA1 rs13361707 C/T polymorphism in GC risk, we first used an online gene expression mini database to analyze the expression of PRKAA1 in both GC and paracancerous tissues. It indicated that the expression of PRKAA1 was higher in GC tissues. Previously, Varghese et al. [PRKAA1 in glioblastoma was correlated with a poor prognosis. Similarly, Huang et al. [PRKAA1 had a higher expression in a cervical tumor than in the normal epithelium (P < 0.01). Additionally, we found that individuals carrying the TT/TC genotypes of PRKAA1 rs13361707 C/T polymorphism had a lower serum expression level than those carrying CC genotypes. This information suggests that PRKAA1 may be an oncogene. Our analysis, in combination with conclusions reported in the previous meta-analysis [PRKAA1 rs13361707 C/T polymorphism, especially the T-allele or TC/TT genotypes, may reduce the expression of PRKAA1. Thus, individuals carrying the T-allele or TC/TT genotypes have a lower GC risk.In order to better explain the potential function of e et al.  also repg et al.  found thanalysis , suggestPRKAA1 expression levels classified by gender or stage of the tumor; hence, we could not analyze these factors. We advocate future articles including this information.Meta-analyses have been recognized as an effective method to summarize and review previously published quantitative research to answer a wide variety of clinical questions. However, some limitations in our meta-analysis should be acknowledged. First, the number of published studies included in our meta-analysis remains small for a comprehensive analysis. Second, one of the selected studies included five different case-control sub-analyses in the same paper, possibly with overlap or duplication of some data. This could have influenced the power of our analyses too. Third, gene-gene, gene-environment  and within-gene interactions may modulate GC risk, and therefore should be evaluated in future research. Fourth, all the 10 articles included in our meta-analysis lacked information about In spite of these limitations, our meta-analysis has some advantages. First, the power of our analysis is more than 0.9, lending credibility and persuasiveness to our results. Second, the quality of case-control studies included in the current meta-analysis satisfied our more extensive selection criteria. Third, publication bias was not detected in any of the genetic models, suggesting that the results are relatively stable and generalizable.PRKAA1 rs13361707 C/T polymorphism was associated with significantly decreased GC risk in the Korean and HB populations, although no association was found in the pooled populations. Therefore, further well-designed and larger studies, dealing specifically with gene-gene and gene-environment interactions, are warranted.In summary, our meta-analysis showed that PRKAA1’ or ‘protein kinase catalytic subunit alpha-1’ or ‘AMPKa1’, ‘polymorphism’ or ‘variant’ and ‘gastric cancer’ or ‘digestive tract tumor’, without any restriction on language or publication year. Using these terms, a total of 51 articles were retrieved. We also screened references cited in the retrieved articles, and other review articles, by hand.We conducted searches on the PubMed, Embase, WanFang, and CNKI databases  with the keywords ‘PRKAA1 rs13361707 C/T polymorphism; (b) case-control design; (c) sufficient numbers for all genotypes  among cases and controls. Additionally, the following exclusion criteria were also used: (a) no control population; (b) no information on genotype frequency; or (c) duplication of previous publications.Studies that were included in our analysis had to meet all of the following criteria: (a) assessment of correlation between GC and Two authors of this study independently extracted all the data from studies complying with the selection criteria. The following items were collected: first author’s last name, year of publication, country of origin, sample size, total case/control number, subjects of each genotype in cases and controls, source of control (HB or PB), Hardy–Weinberg equilibrium (HWE) of controls, the Newcastle-Ottawa Scale (NOS), GC type, and genotyping methods.The NOS  was usedhttp://gemini.cancer-pku.cn/) to analyze the expression of PRKAA1 in both GC and paracancerous tissues [We used the online gene expression mini database from the Zhang Lab of Peking University ( tissues . This daPRKAA1 rs13361707 C/T polymorphism and GC risk in different strata was expressed as odds ratios (ORs) with 95% confidence intervals (CIs). The statistical significance of the ORs was determined with the Z-test. Heterogeneity assumption was evaluated by a chi-square-based Q-test. When a P-value < 0.10 for the Q-test indicated a lack of heterogeneity among the studies, the random effects model (DerSimonian-Laird method) was used [PRKAA1 rs13361707 C/T genetic variants, we investigated their association with GC risk according to the following models: allelic contrast model , homozygote comparison model (TT vs. CC), heterozygote comparison model (TC vs. CC), dominant genetic model (TT+TC vs. CC) and recessive genetic model (TT vs. TC+CC). Funnel plot asymmetry was assessed using Begg’s test and publication bias was assessed using Egger’s test, P < 0.05 was considered statistically significant [PRKAA1 gene polymorphism from expectation under HWE was assessed in controls by using the Pearson chi-square test; P < 0.05 was considered significant. All statistical tests for this meta-analysis were performed using the Stata software . The power of our meta-analysis was calculated by a program named PS: Power and Sample Size Calculation (http://biostat.mc.vanderbilt.edu/wiki/Main/PowerSampleSize#Windows) [The strength of the association between was used . Otherwiwas used . For difnificant . The depWindows) .PRKAA1 rs13361707 C/T was conducted using different techniques in different studies: polymerase chain reaction matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (PCR-MALDI-TOF-MS), high-resolution melting polymerase chain reaction (HRM-PCR), improved multiplex ligase detection reaction (iMLDR), Affymetrix Genome-Wide Human SNP Array 6.4 chips (AGWHSA 6.0 CHIPS), GoldenGate assay (Illumina), Multiplex SNaPshot SNP, TaqMan and kompetitive allele-specific PCR (KASP).Genotyping of PRKAA1 rs13361707 C/T polymorphism was analyzed by a TaqMan assay as described by Li et al. [Two hundred GC patients were newly diagnosed between November 2014 and May 2016 in the Tongzhou People’s Hospital of Nantong . All GC


In spite of the well-known harmful effects on the fetus, many women continue smoking during pregnancy. Smoking as an important source of toxic chemicals may contribute to the developmental origin of diseases.The aim of this work was to pursue the possible association between maternal smoking and cancer in early life. Specifically, we wanted to identify the associated early life cancer types, and to quantify the associations.In a systematic literature search 825 articles were identified in PubMed and Web of Science, and 55 more through the reference lists. Of these 62 fulfilled the criteria for inclusion in meta-analyses. Using Mantel-Haenszel or DerSimonian and Laird method, depending on heterogeneity of the studies, pooled estimates and 95% confidence intervals for eight cancer types were calculated.Smoking during pregnancy was associated with an increased risk for for brain and central nervous system tumors . Although the risk for lymphoma was also associated , it did not hold up in subgroup analyses. Leukemia was not found to be associated with maternal smoking. Five other cancer types  were also examined, but the number of studies was too limited to exclude the possibility of maternal smoking as a risk factor for cancer in offspring.According to our meta-analyses, maternal smoking is associated with nervous system cancers, but not with leukemia in early life. Confirming or rejecting associations of maternal smoking with lymphoma and the five other cancer types requires further studies. The most common cancer types in childhood are leukemia and brain tumors which constitute over half of the malignant tumors in children . The etiIn utero exposures have potentially devastating effects on the unborn child due to vulnerability during the fetal development leading either to direct health effects or to a higher susceptibility to develop diseases later in life through alterations in both the genome and the epigenome  were included in the same subgroup analysis. Pooled estimates and the corresponding 95% confidence intervals (CI) were calculated using either a fixed effect model or a random effect model. Some studies reported only risk estimates for categories of cigarettes smoked per day. For such studies, we calculated an estimate for the nominal smoking status (smoking vs. no smoking) by pooling all exposed cases (and controls) across the categories of cigarettes smoked per day (CPD). It was not necessary to pool unexposed cases or controls, since all studies compared the smoking categories to the same unexposed children within each study. The pooled number of exposed cases and controls was then subsequently used to calculate the OR for any smoking during pregnancy compared to no smoking during pregnancy.The Generic Inverse Variance Method was used to assign a weight to each study included in the pooled estimate . In caseThe Mantel-Haenszel Method was used to calculate the pooled estimate in the fixed effect model using the above introduced weight and the logarithm of each individual risk estimate . In the 2 statistics were used to assess heterogeneity  and nervous system tumors   nor the negative findings ; 5 studies]. In general, smoking 1–10 CPD was associated with an increased risk, whereas smoking a higher number of cigarettes was not. The association was only significant in smaller studies (less than 50 exposed cases), yet not in bigger studies (50–99 exposed cases). Choice of source for smoking status of the mother seems to alter the risk estimate: pooled OR of studies using interview data was 1.53 , whereas the pooled OR of studies using birth register data was 1.16 , 2 studies) .This meta-analysis included the findings of 22 earlier studies to investigate the association between nervous system tumors and maternal smoking. In general, smoking during pregnancy was positively associated with childhood nervous system tumors   Table E. The assAny smoking during pregnancy was associated with a 30% increase in the risk for Neuroblastoma during early life . The subgroup analyses were conducted with only two to three studies per analysis. Nevertheless, the results suggest associations with 1–10 CPD as well as 20 or more CPD, in European study populations, in studies using questionnaire data and in studies without adjustment of the original risk estimate , astrocytoma and ependymoma (data not shown).th birthday and between the 15th and 19th birthday. Additionally, subgroup analysis of studies using register data for smoking information suggests a negative relationship.The meta-analysis of studies reporting risk estimates for smoking during pregnancy and childhood leukemia included 21 studies. The analysis suggests no association between maternal smoking during pregnancy and leukemia in early life  Table K. MaternaThe Meta-analysis of studies investigating the possible association between maternal smoking and acute lymphoblastic leukemia (ALL) were based on 19 studies  did not suggest an association between maternal smoking and AML. Only subgroup analysis including two studies conducted in South America yielded a significant inverse association  to 641 (germ cells) .No clear association between maternal smoking and cancer in early life was found for the following cancer types: germ cell tumors, hepatic tumors, renal tumors, soft tissue sarcoma, and bone cancer , whereas cases of the five other cancer types were less frequent. The amount of cases in these cancer types ranged from 138 to 641. Thus, the positive association for nervous system tumors is supported with a larger dataset, similarly to the negative findings for leukemia.Meta-analysis is a statistical method to pool results of different observational studies, and is therefore sensitive to uncertainties in the analysis itself, and to consequent uncertainties in the results which are used as input of the analysis. Possible sources of uncertainties are different study designs  of the included studies, as well as the publication bias. It has to be noted, that the included studies used various degrees of adjustment of the risk estimates. Additionally, the main focus of some studies was not maternal smoking, but it instead was only included as a confounding factor in another analysis.Our results suggest that maternal smoking may have a protective effect especially on childhood leukemia. Although there is no clear explanation for these results, it has been hypothesized that benzo[a]pyrene, a constituent of tobacco smoke, causes generalized immunosuppression after birth. This immunosuppression caused by suppressed B-cell lymphopoiesis and induced pre-B-cell apoptosis in bone marrow cultures can lead to a lowered response to the impact of maternal smoking and with that lower risk estimates . Other rThe findings in the subgroup analyses of the risk for lymphomas gives some insight into the problem of epidemiological studies of childhood cancer. Although the overall pooled risk estimate for all identified lymphoma studies was positive , the subgroup analyses show different results based on the study design. In the subgroup analyses of different study designs, only the subgroup with case-control design shows the same clear picture , whereas the subgroup with cohort design does not indicate a clear association between maternal smoking and childhood lymphoma . Both subgroups were of similar size, minimizing the chance that the differences in the pooled risk estimates are due to major differences in the statistical power. It seems likely that the differences are due to inherent differences in the study design, e.g. the risk for recall bias, identification of cases, and adjustment for confounder. This should be kept in mind when interpreting our results, or the results of any other meta-analysis. These differences and limitations are discussed below.All studies included in this analysis were designed to study the association between exposure before birth and cancer in early life, before the age of twenty. Although adult cancers often have a latency time in the order of decades, the latency time for cancer in children is substantially lower with some cancers being observed already as early as at birth or at an age of less than one year. A long latency time and the use of case-control design, which was the most common design in the identified literature, can lead to exposure misclassification due to recall bias in observational studies . Not onlThe conducted subgroup analyses hint on bias due to study design in the results. Case-control design was associated with higher risk estimates compared to a cohort design. Additionally, birth register as a source of information about maternal smoking was consistently associated with lower risk estimates compared to retrospectively collected information via interviews or questionnaires. As discussed earlier in this paper, prospectively collected information on the smoking habits of the mother are considered less biased than information collected retrospectively. It is easier to reach a sufficient number of cancer cases for statistical power in case-control setting, since the cases can be identified directly. In addition, cases and controls can be contacted directly to collect data on smoking and confounders. Cohort studies require large study populations due to the very low incidence rate of childhood cancer and a long follow-up period. It is practically impossible to collect additional data from all study participants, if the study population is too large. Hence, both study designs have their advantages and disadvantages, but it is well recognized that prospective cohort studies are more reliable than retrospective case-control designs . Thus, tin utero, changes in the DNA over years and the development of cancer. A reason for the lack of dose response might be that the exposure assessment of maternal smoking is flawed. As stated earlier, pregnant women frequently underreport the number of cigarettes per day. The resulting exposure misclassification may cover any existing dose response relationship [The subgroup analyses did not suggest any clear dose-response relationship for any cancer type. Smoking 10 or less CPD was associated with a significantly increased risk of lymphoma, whereas the pooled estimate for 11 or more CPD did not reach significance. No dose response pattern emerged for nervous system tumors, either. Smoking 11–20 CPD was significantly associated with the highest risk, whereas smoking more than 20 CPD was associated with the lowest increase in risk, and did not reach statistical significance. As for leukemia, a “U” shaped dose response curve was implicated. Smoking 20 or more CPD was associated with the highest risk, which still remained below 1. The second highest risk was observed for smoking 10 or less CPD. The absence of a dose-response relationship does not support causality. It also might hint, however, at the complex molecular reactions between exposure to tobacco smoke tionship , 95, 96.There was no clear effect by study size on the risk estimates pattern. For lymphoma, non-Hodgkin’s lymphoma and germ cell tumors subgroup analyses for two study sizes (<50 and 50–99 participants) was possible, while for nervous system tumors, leukemia and ALL analysis of all three study size subgroups were possible . There was no consistency whether the pooled OR for the bigger studies was higher than for the smaller studies. Smaller studies usually have lower statistical power than bigger studies, which leads to higher variance in their risk estimates. However, this does not seem to heavily affect the general range of the risk estimates in our study.As was expected, non-adjusted risk estimates were consistently higher compared to adjusted risk estimates. This pattern shows that certain choices in our study design are associated with higher risk estimates. This would in fact argue against the causal nature of the association, and instead in favor of a predominant role of bias. To minimize the effect of possible confounding in the original studies, the available most adjusted risk estimate was included in the meta-analyses. Only when no adjusted risk estimates have been reported in the original study, a non-adjusted risk estimate was used.It has been hypothesized, that the observed increase in cancer cases in the past is partly attributed to improved diagnostics. In spite of that, sensitivity analyses of the time of the diagnosis or the publication year did not show any correlation with reported risk estimates for any cancer type. Additionally, co-exposures during pregnancy as well as exposures between birth and the development of cancer can confound the relationship. A special issue in our analysis is caused by the exposure time we focused on: we aimed at assessing the risk of maternal smoking during pregnancy and not before or after pregnancy. However, it is unlikely that a woman smokes during pregnancy and stops at birth. Hence, the observed risk is most likely confounded by exposure of the child to second hand smoke from the smoking mother, or from other household members. Most studies did not ascertain the smoking status of the mother or other household members after birth. Also, exposure of the pregnant woman to passive smoking due to other household members was not taken into account in the reviewed studies. Exposure to environmental tobacco smoke or via breastfeeding would potentially contribute to the development of cancer.Leave-one-out sensitivity analysis was conducted omitting one study at a time, and this suggested that no specific study influenced the pooled estimate. The pooled estimates did not change significantly, regardless of which study was omitted. This supports the robustness of the pooled risk estimates. Publication bias as evaluated by Egger’s plot did not indicate significant publication bias for neither the positive nor the negative findings.This meta-analysis is an update of previously conducted meta-analyses. By carefully considering all original studies used in previous meta-analyses, we ensure that previous work is included in our analysis. The risk estimates of our analysis are directly comparable between different cancer types, since the same inclusion criteria and methods have been applied. In a first comprehensive meta-analysis Boffetta and colleagues  analysedReaching a sufficient study size can be a challenge, since maternal smoking does not affect the majority of children in combination with a low cancer incidence in early life. Data, which are collected routinely in health registers, enable the use of high numbers of mother-child pairs. Hence, all children born in a specific country should be included in the corresponding birth register that includes information concerning the pregnancy, including the smoking status of the mother. We believe that the use of such routinely collected health data in medical registers is the most promising approach, since the smoking information is collected during the first pregnancy checkup visit (at least in the Nordic countries). Depending on the country and the year, the smoking data are either dichotomous or categorized to smoking per day. By linking the registers, for example birth register or birth certificates with cancer registers, high numbers of data can be easily collected, without the need to contact health care professionals and mothers. This decreases the time and costs of data collection, since no interviews and questionnaires are needed. Furthermore, as the study population is the population of the country, the issue of selecting a cohort or cases and controls representing the target population is omitted. Another remaining open issue is the investigation of genetical susceptibility, especially in terms of genes modifying the effects of smoking and those which predispose to malignancies, potentially modifying the effects of carcinogenic insults. Results might give insights into the mechanisms of initiation of childhood cancers due to prenatal cigarette smoke exposure.After our article was submitted, two prospective, population-based studies have been published. Our work is in good agreement with the results of the study by Heck and colleagues (2016)  for leukin utero exposure to tobacco smoke is associated with an increased risk for childhood cancers, epidemiological studies have so far failed to produce strong and consistent results to establish such a causal relationship. Smoking has long been established as a cause for cancers in adults, such as cancer of the lung, urinary bladder, esophagus, oral cavity, larynx, kidney, pancreas and liver. Passive smoking has been classified as a Class I carcinogen causing lung cancer in humans by the International Agency for Research on Cancer (IARC). Cigarette smoke contains more than 5300 constituents and according to IARC, for 70 of them there is sufficient evidence for carcinogenicity in laboratory animals or humans [Although it seems biologically plausible that r humans , 102.There are several proposed mechanisms to how cigarette smoke contributes to cancer development after prenatal exposure. The generation of reactive oxygen species (ROS) causes oxidative damage and interferes with cell signaling pathways. Animal models using Syrian hamster showed transplacental carcinogenesis caused by 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone exposure. It is one of the IARC Class I carcinogens in cigarette smoke, and it has been detected in urine of newborns of smoking mothers, indicating a direct exposure of the unborn child to the carcinogen . AnotherThe complexity of prenatal exposures and disease onset later in life makes it difficult to study the effects of maternal smoking on the risk of cancer development in early life. The association is modified by co-exposures and polymorphisms in genes coding for enzymes responsible for activation or detoxification of carcinogens and other chemicals. If there is only a slight increase in the risk, an inadequate number of cases or exposure misclassification can already mask the true risk. Thus far, only very few studies, with a relatively small number of cases, have analyzed drug metabolism or transporter polymorphisms in order to investigate if the effect of maternal exposure differs between genetic sub-populations. For example, genetic polymorphisms in the CYPA1 gene  or ABC-tAdditionally, it has to be taken into account that embryonic development is a tightly regulated combination of differentiation, proliferation and apoptosis of cells. This process is very strictly controlled by signaling pathways and transcription factors, which can be easily disturbed. Whichever error occurs during DNA duplication, in that time period such an error will manage to be imprinted in the DNA of a high number of subsequent cells. These errors might not directly lead to cancer, but can increase the susceptibility of cells to later insults of carcinogens .According to our meta-analysis, maternal smoking is associated with brain or CNS cancers and potentially lymphomas, but not with leukemia in early life. For five other cancer types the number of cancer cases in the included studies was limited, and we cannot exclude the possibility of maternal smoking as a risk factor for these cancer types in offspring. Most studies included in this meta-analysis are of case-control design relying on retrospectively collected smoking information. Thus, there is a strong likelihood of recall bias in most studies, and the results have to be interpreted with caution. Dose-response analyses did not reveal a clear relationship. Due to the heterogeneity and uncertainties in broad exposure categories a detailed analysis of specific trimesters in combination with smoking amount was not possible. Further research is needed in order to identify clear sensitive windows of exposure and possible dose-response relationships. Future studies should be included in the meta-analysis to facilitate sufficient statistical power for subgroup analysis. Additionally, effect modifiers, genetic polymorphisms and co-exposures should be similarly taken into account.S1 File(DOCX)Click here for additional data file.S2 File(DOCX)Click here for additional data file.


Studies have investigated the correlation between tumor necrosis factor related apoptosis-inducing ligand (TRAIL) gene polymorphisms and the susceptibility and severity of intervertebral disc degeneration (IDD), but the results were inconsistent. To evaluate the specific relationship, we performed a meta-analysis to clarify the controversies.Four databases were searched, and the pooled results were presented as odds ratios (ORs) with 95% confidence intervals (CIs).P = 0.000). No significant heterogeneity was found in the recessive model . Patients with lower grade IDD had more genotypes or alleles including 1595TT genotype  and 1595 T allele .Three case-control studies from Han Chinese were included (565 cases and 427 controls). All the included studies reported TRAIL 1595C/T gene polymorphisms. The recessive model (CC vs. CT + TT) was the optimal model, which demonstrated a significant relationship between 1595C/T polymorphisms and increased IDD risk  contains supplementary material, which is available to authorized users. Lower back pain is a very common condition. According to the report, 84% of people in the general population suffer from lower back pain in some way, and many people are permanently disabled due to this condition . InterveTumor necrosis factor and apoptotic induction ligands (TRAILs) are transmembrane proteins that belong to tumor necrosis factor ligands. In transformed cells and cancer cells, TRAIL preferentially did apoptosis inductions by TRAIL-R2/DR5 and TRAIL-R1/DR4 receptors . The expAlthough a series of studies –10 have We conducted a computer-based retrieval using the following English and Chinese databases: PubMed, Embase, the China National Knowledge Infrastructure database, and the China Biology Medical Literature database. We did also try to identify additional records through other sources, such as the reference lists in the relevant research reports. The search was conducted from the inception of each database on May 1st, 2016. Our search strategies  the study design was case-control study; (2) the populations of interests were human subjects; (3) the outcome was evaluation of the correlation between TRAIL polymorphisms and IDD risk; (4) sufficient data such that the odds ratios (ORs) and 95% confidence intervals (CIs) could be calculated; (5) and no publication language was restricted.Accordingly, the exclusion criteria were defined as follows: (1) data overlapping with previous publications; (2) comments, reviews, or animal studies; or (3) studies with genotype frequencies that were not detailed. Eligible studies were reviewed independently by two reviewers (QLY and LL) according to the inclusion criteria. Disagreements were resolved by discussion.Two reviewers (QLY and YSC) independently extracted the data from the eligible studies. The data were collected as follows: (1) name of the first author; (2) publication year; (3) country where the study was conducted; (4) ethnicity of the enrolled subjects; (5) gender and age of study participants; (6) numbers of cases and controls; (7) method of genotyping; and (8) genotype frequency in cases and controls. The two reviewers reached a consensus on all the data.We extracted and modified the methodological quality assessment scale based on a previous study . On thisP value of HWE in the control group, and if the P value was greater than 0.05, which satisfied the HWE. The correlation strength between TRAIL polymorphism and IDD risk was calculated by means of odds ratio (OR) and 95% confidence interval (CI). We merged ORs from every trial to reckon up the pooled ORs. Z-test was used to judge if the pooled ORs were statistically significant, and the P value lower than 0.05 indicated a significance. Different genetic models were used.The chi-square test was applied to detect the P value smaller than 0.10 was regarded as significance; similarly, I2 > 50% also indicated a significance [P < 0.05.We used Q statistic to detect the statistical heterogeneity, and a ificance . For a mificance  and Eggeificance  were resShapiro-Wilk W test was applied to estimate whether the models were suitable for the data in our meta-analysis . The metWe estimated the disc degeneration severity of IDD patients with different TRAIL genotypes and alleles, and the variance-stabilizing double arcsine transformation  was usedP-values were two-sided.STATA 14  was used to do all these analyses above. All Our search strategy identified 198 potentially eligible records  = exp. (θ1), OR2 (CC vs. TT) = exp. (θ2), and the null hypothesis (H0) was as follow: θ1 = θ2. As a result, we obtained a P value of <0.001 (<0.05), suggesting that the results support H0, indicating that there was a correlation between the TRAIL gene and IDD. Meanwhile, we also obtained a result as follows: θ1 = 0.073  and θ2 = 0.382 , so θ1 = 0 and θ2 > 0, indicating that the recessive model (CC vs. CT + TT) was the optimal model.The goodness-of-fit test was used to evaluate how the models fit the data in the meta-analysis, in which the Shapiro-Wilk W test for normal distribution was applied in STATA. We found that all P = 0.000) .The recessive model (CC vs. CT + TT) was the optimal model, which showed a significant relationship between 1595C/T polymorphisms and increased IDD risk    Fig.  and 159500) Fig. .Table 3MP values <0.05). In addition, all the point estimates of ORs  were in the range of the 95% CI of the overall meta-analysis (1.45 to 3.27), suggesting that the results of this meta-analysis were robust.Sensitivity analysis confirmed the presence of an association between 1595C/T and IDD risk. We excluded one study at a time, and the omission of any single study resulted in the same significant difference as was detected in the overall meta-analysis .Publication bias in the recessive model was tested. No evidence of publication bias was observed  of the TRAIL gene with IDD risk. Moreover, the demographic data and the IDD disease-related factors were not reported in detail and so few trials were included, which limited further analyses . In addition, although no evidence of publication bias was evident according to Egger’s test and Begg’s test, the possibility of publication bias might still exist because there were only three studies and only studies published in English and Chinese were retrieved. In addition, all the included studies were conducted in China, and all the subjects were Han Chinese, thus the external validity of our study is limited. Finally, IDD is a multifactorial disease, and the association between TRAIL gene polymorphisms and IDD risk or severity might be magnified or diminished by gene-gene, gene-protein and/or gene-environment interactions. However, this issue could not be addressed herein because of the limited availability of individual patient data, such as family history, performance of manual labor and other environmental factors. Overall, these limitations could lead to false-positive findings, thus, additional prospective studies with larger sample sizes including participants of other ethnic populations are warranted.Our findings suggest that there is a significant relationship between 1595C/T polymorphisms and the susceptibility and severity of IDD in the Han Chinese. Patients with lower grade IDD exhibited higher frequency of 1595TT genotypes and 1595 T alleles. These findings should be validated in prospective studies with a larger population including patients of other ethnicities.


Subgroup analyses supported this finding, except for the age-unadjusted group , the ERM classification group (cellophane macular reflex (CMR) OR, 0.93; 95% CI 0.68–1.28; preretinal macular fibrosis (PMF) OR, 0.74; 95% CI 0.41–1.32), the Asian group  and the past smoker group . The pooled effects from the current literature suggested a declining association between smoking and ERM, which requires further studies to confirm.We conducted a meta-analysis of analytic and observational studies to evaluate the association between smoking and epiretinal membrane (ERM). The pertinent studies were identified via a literature search using three databases  and the reference lists of retrieved studies. Cohort, case-control and cross-sectional studies meeting the predefined criteria were included. We extracted the odds ratios (OR) and 95% confidence intervals (CI) from each study. Overall risk estimates were pooled using random-effects models. Subgroup analyses based on several stratified factors were also performed. Two cohort studies and six cross-sectional studies involving 46,837 subjects were included. The pooled effect of all eight studies showed an unexpected significant decreased association between smoking and the occurrence of ERM (OR, 0.72; 95% CI 0.61–0.84; p = 0.29, I Epiretinal membrane (ERM) is a common retinal condition that typically occurs in people aged 50 years and older and is characterized by the proliferation of abnormal tissues on the inner retinal surface15In recent years, studies among different ethnic groups have provided population-based prevalence data on ERM, ranging from 1.0% to 28.9%5891011121314151617511et al.It is know that ERM formation is a fibrotic process that occurs on the surface of the retina42021232426We followed the MOOSE checklist to conduct this meta-analysis. . We conducted a systematic search through three databases, including MEDLINE (1950 to October 2015), the Cochrane Library (up to October 2015), and Embase (1980 to October 2015), using the following MeSH terms and keywords: smoking OR tobacco OR cigarette OR lifestyle OR risk factor OR epidemiology, combined with epiretinal membrane OR cellophane macular reflex OR preretinal macular fibrosis. References in the retrieved publications were reviewed to identify other pertinent studies. No language restrictions were imposed.Studies were considered eligible if they met the following criteria: (1) they were cohort or case–control or cross-sectional studies published as original articles; (2) they estimated the relationship between smoking and the risk of ERM with the odds ratio (OR) and 95% confidence interval (CI) or provided any other calculable information; and (3) they defined OR of smoking as current smoker VS none/never smoker or current smoker VS none/never or past/former/ever smoker. When articles with overlapping participants were available, we selected the most recent study. We contacted the authors of related articles for necessary data such as ORs of association between smoking and ERM and ORs concerning smoking status and other stratified factors to determine whether the article met our inclusion criteria. We excluded the literature sources such as conference abstracts, as they lacked adequate information for evaluation of their validity and reliability.Two of the authors (Q-HT and S-ZW) reviewed the titles and abstracts independently to exclude any obviously irrelevant studies. If uncertainty regarding suitability remained, full manuscripts were subsequently obtained. Any disagreement was resolved by discussion.For each study, the following characteristics were extracted: (1) last name of first author, (2) publication year, (3) country in which the study was conducted, (4) study design, (5) study period, (6) population type and sample size, (7) mean age or age range of study subjects, (8) smoking status, (9) ERM classification, (10) ERM definition and grating, (11) ERM prevalence and (12) adjusted variables. Methodological quality was assessed using the validated Newcastle–Ottawa quality assessment scale (for cohort studies)The association between smoking and ERM was evaluated by calculating pooled ORs and 95% CIs. We used age-adjusted or gender-adjusted ORs whenever possible. However, several articles did not provide adjusted ORs shown in , in whic2 statistics2 was >50%Heterogeneity among the included studies was tested the Cochran Q and IOur search of three databases identified 329 articles. After screening of the titles and abstracts, 311 unrelated articles were excluded as irrelevant. In further evaluation of the remaining 18 articles, 10 were excluded for the following reasons: 6131435363751110912161740The detailed characteristics of the eight selected studies are summarized in 2 = 17.9%) (2 = 0.0%) and cross-sectional group   .2 = 41.4%), a significantly decreased risk between smoking and ERM was found in Caucasians   .2 = 0.0%), while a nonsignificant relationship was found in past smokers   .2 = 68.7%) or in late-stage group (PMF)    .2 = 0.0%) and the group not adjusted for age   .In the overall analysis, we detected that smoking was associated with a significantly decreased risk of ERM  without significant heterogeneity  . We thenBegg’s rank correlation test and Egger’s linear regression test indicated no evidence of significant publication bias among the included studies , and funnel plots showed a symmetric distribution . SensitiOur meta-analysis showed that there was a significant decreasing association between smoking behavior and risk of ERM in cohort and cross-sectional studies. Similar significant relationships were also found in the stratified analyses except for ERM classification, Asian ethnicity, past smoker status and age-unadjusted subgroups.ERM consists of a sheet of fibrotic tissue that varies in thickness from a single layer of collagen with interspersed cells to a thicker, multilayered fibrocellular proliferation4244et al.et al.et al.The unexpected protective association between smoking and ERM was also observed in other studies51516et al. Another intriguing possibility is the higher rates of smoking among Asians. Indeed, it has been reported that smoking rates are higher in China and Japan than in Australia and the United States464748Studies have reported significant discrepancy in the prevalence of ERM among different ethnic groups. Some studies have indicated that the prevalence of ERM in the Caucasian population is much higher than in the Asian population913et al.2 didn’t show statistical significance in most situations, they did exist and could affect the results in some degree. Considering few studies provided both age-adjusted and age-unadjusted ORs, we could neither test the hypothesis nor simply compare the absolute values of ORs among studies and combined effects.We also detected a bit smaller ORs of age-adjusted studies than age-unadjusted studies. Several studies have observed the reverse associations between current smoking and ERM, which they tended to explain by age constitution and survival effect. And the reverse association was attenuated after adjusting age in the research of Kawasaki et al. may also attenuate the difference between none smoker and past smoker. Still, we can not get to a conclusion whether it is a fact or statistical spuriousness. Third, the participants were population-based or volunteer-based. It is a common view that volunteers might be more conscientious about maintaining a healthy lifestyle, which could dilute the observed association. Fourth, we failed to evaluate the dosage– response association owing to insufficient data on smoking consumption and different durations. Furthermore, the study of McCarty et al.Several limitations in our work cannot be ignored. First, there were only eight studies with two different study designs included in our meta-analysis. However, the heterogeneity of total pooled estimates was not significant, which indicated good homogeneity among the included studies. Moreover, sensitivity analysis showed no significant changes after removing one study at a time, indicating the stability of these findings. Still, we should be cautious about generalizing our conclusions to other conditions. Secondly, we defined ORs of smoking as current smoker VS none/never smoker or current smoker VS none/never or past/former/ever smoker, which arbitrarily combined the effects of none smoker and past smoker. Coincidentally, subgroup analysis based on smoking status supported our assumption that differences between the two groups were not significant. Self-reported questionnaires and medical records were widely adopted in these including articles, so unclearly definition of smoking status and recall bias could affect the association. While, obscure smoking status definition of McCarty In conclusion, this meta-analysis of analytic and observational studies revealed an unexpected beneficial effect of smoking related to ERM. We provide additional evidence on the association between smoking and ERM and also discuss the reason for this unusual association. Owing to the limitations of our work, we should be conservative in interpreting the pooled estimates. Further high-quality research that specifically adresses daily cigarette consumption and smoking duration is warranted to confirm our findings and provide a possible explanation for this association.How to cite this article: Wang, S.-Z. et al. The Association Between Smoking and Epiretinal Membrane. Sci. Rep.6, 38038; doi: 10.1038/srep38038 (2016).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


XRCC1) gene and susceptibility to CAD, but findings have been inconclusive. We identified eligible studies through a comprehensive literature search to determine whether an association exists between XRCC1 gene polymorphisms and CAD susceptibility. Findings were assessed using the odds ratio (OR) and corresponding 95% confidence interval (CI), which were calculated using a fixed- or random-effects model, based on the heterogeneity of the studies. Ten eligible studies were finally included in this meta-analysis. Our pooled analysis found that XRCC1 polymorphisms were significantly associated with CAD susceptibility under recessive , homozygous , and allele  genetic models. Following subgroup analysis by ethnicity, in Asian populations, we found evidence of associations between the XRCC1 Arg194Trp polymorphism and CAD under recessive and homozygous genetic models, and between the XRCC1 Arg399Gln polymorphism and CAD under recessive, homozygous, and allele genetic models. Subgroup analysis stratified by control source revealed associations between the Arg194Trp and Arg399Gln polymorphisms and susceptibility to CAD under recessive and homozygous modes of inheritance, respectively. In addition, subgroup analysis stratified by sample size found that findings of the Arg194Trp polymorphism in large sample sizes were comparable to those found using pooled eligible studies. Based on our meta-analysis, we concluded that the XRCC1 gene polymorphisms, Arg194Trp and Arg399Gln, are associated with CAD susceptibility, specifically in Asian populations. However, additional, comprehensive and well-designed studies are warranted to confirm these findings.Genetic variations that influence DNA repair efficiency may contribute to coronary artery disease (CAD) susceptibility. Previous studies have investigated whether there was evidence of an association between polymorphisms at the X-ray repair cross complementing 1 ( XRCC1 gene is located on chromosome 19q13.2–13.3, it consists of 17 exons and encodes a protein of 633 amino acids [Coronary artery disease (CAD), which is recognized as a major public health problem, has high mortality and morbidity worldwide . The maiXRCC1 gene polymorphisms, Arg194Trp (rs1799782) and Arg399Gln (rs25487), which are located at codon 194 of exon 6 and at codon 399 of exon 10 respectively, are reported to affect the expression of XRCC1 and subsequently influence the DNA repair capacity [XRCC1 gene influence DNA repair and are associated with an increased susceptibility to CAD [XRCC1 gene and the likelihood of developing CAD [Two capacity , 15. Furcapacity –18. In ay to CAD . For exay to CAD  demonstrping CAD .XRCC1 and susceptibility to CAD remains controversial and inconclusive. Furthermore, no relevant meta-analysis or genome-wide association studies (GWAS) have been published on this subject. Consequently, to derive a more comprehensive estimation of the role of XRCC1 gene polymorphisms in CAD susceptibility, we identified all eligible studies and performed this meta-analysis.Whether a correlation exists between variants in the DNA repair gene The literature search was performed by two authors (Ma and Zhu). Comprehensive electronic databases including PubMed, EMBASE, Web of Science, ScienceDirect, Cochrane Library, and Ovid were systematically searched for eligible studies up to July 31, 2016. Our search strategy was based on finding keywords or topic-based classifications in the title and abstract of published studies. Keywords and terms used were (“XRCC1” OR “X-ray repair cross-complementing group 1” OR “Arg194Trp” OR “rs1799782” OR “Arg399Gln” OR “rs25487”) and  and . References in eligible studies were also examined as a secondary source to identify eligible studies. Manual searching of relevant journals and screening the reference lists were performed by one author (Liu).XRCC1 Arg194Trp and Arg399Gln polymorphisms and CAD; (2) patients with CAD were documented using angiographic evidence of at least 50% stenosis of one major coronary artery, myocardial infarction, angina, or a history of coronary artery bypass surgery; (3) the total number of cases and controls, distribution of genotypes, or other relevant data could be extracted from the references; and (4) the publication language was in English. Studies were excluded if they met any of the following criteria: (1) publications were abstracts, letters to the editor, animal studies, or reviews; (2) the study presented data that overlapped with a previous publication; and (3) the study presented either uninformative data or did not provide genotype frequencies.Studies included in our meta-analysis were selected according to the following inclusion criteria: (1) the study examined the correlation between the The data from eligible studies were extracted by two independent authors (Ma and Han). Disagreements regarding study selection were resolved by a third author (Liu). Critical data that could not be derived from the references were obtained by directly contacting the authors. We collected the following information: author, year of publication, ethnicity, country, the number of cases and controls, baseline characteristics of the patients, genotyping methods, genotype frequencies in cases and controls, the origin of the controls, and measurements of Hardy-Weinberg equilibrium (HWE) from controls.The quality of eligible studies was assessed by one author (Han), according to the Newcastle–Ottawa scale (NOS) for genetic association studies . NOS quaXRCC1 gene polymorphisms and CAD susceptibility. Tests under dominant , recessive , homozygous , heterozygous , and allele  genetic models were performed and ORs were determined. The Cochrane Q-test and index (I2) were used to examine heterogeneity among studies with a P > 0.10 in the Q-test indicating no heterogeneity. I2 was used to estimate the total variation across studies where an I2 < 25% was considered to have a low level of heterogeneity, an I2 between 25% and 50% indicated moderate heterogeneity, and an I2 > 50% represented a high-level of heterogeneity. A fixed- or random-effects model was performed depending on the observed heterogeneity of the studies. Subgroup analyses were performed to identify potential sources of heterogeneity. Sensitivity analysis was performed to assess the stability of individual studies, and publication bias was determined with funnel plots and Egger’s linear regression test.All statistical analyses were performed using Review Manager v5.2  and Stata 12.0 . Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to evaluate the robustness of the association between Fifty-nine articles were selected following an initial search, of which 44 articles were excluded because of duplicate records. Ten articles remained from the original literature search after screening the titles and abstracts. Of these studies, one article was excluded because it was a review and two other articles were excluded because of insufficient data. Finally, seven articles that contained ten studies were retained –23, 25. P > 0.05).Information of the selected studies is shown in XRCC1 gene polymorphisms and CAD susceptibility are shown in Associations between XRCC1 Arg194Trp polymorphism, we found an increased likelihood of CAD susceptibility in recessive  and homozygous  genetic models when cohorts from all eligible studies were pooled , homozygous , and allele  genetic models, but no evidence of association was identified under dominant and heterozygous models of inheritance , homozygous , and allele  genetic models.For the e pooled ; Fig 2. eritance ; Fig 3. For subgroup analyses based on ethnicity, we found evidence of association between the Arg194Trp polymorphism and CAD susceptibility in Asian populations under recessive and homozygous genetic models, and support for an association for the Arg399Gln polymorphism under recessive, homozygous, and allele models of inheritance. Subgroup analyses stratified by control source found evidence of an association for both the Arg194Trp and Arg399Gln polymorphisms with increased likelihood of CAD in hospital-based studies under recessive and homozygous genetic models and a significant association between the Arg399Gln polymorphism and CAD susceptibility in population-based studies under recessive genetic model. In addition, we found in subgroup analyses stratified by sample size that findings related to the Arg194Trp polymorphism from studies with large sample sizes were similar to those found using pooled eligible studies shown in .The influence of each study on pooled ORs and 95% CIs were evaluated by excluding each study one at a time. As shown in XRCC1 polymorphisms in Arg194Trp  or Arg399Gln .Funnel plots  and EggeXRCC1 gene and an increased likelihood of CAD. Furthermore, subgroup analyses based on ethnicity found that carriers of the Arg194Trp T allele or the Arg399Gln A allele were at increased susceptibility to CAD in Asian populations under several genetic models. However, we found no evidence of an association in non-Asian populations, a finding that may indicate differences in genetic diversity between different ethnic groups. Stratification based on control source found that both the Arg194Trp and Arg399Gln polymorphisms increased the likelihood of CAD in hospital-based studies under recessive and homozygous genetic models, and a significant association was observed between the Arg399Gln polymorphism and CAD susceptibility in population-based studies under recessive genetic model. Possible explanations for these discrepant findings may be the limitation of the small sample sizes, different risk factors among the hospital- and population-based controls, and the possibility of selection bias. In addition, it is worth noting that the hospital-based controls are more 'case-like' than the population-based controls for many variables, which may underestimate the effects and can’t represent the general population. NOS was applied for quality assessment and all the studies included were of moderate or high quality, which improved the reliability of the conclusion. Otherwise, studies of low quality might have increased the heterogeneity and produced misleading results. Furthermore, we performed sensitivity analysis and confirmed the robustness of our findings.We analyzed ten studies in our meta-analysis and found evidence for associations between the Arg194Trp and Arg399Gln polymorphisms at the XRCC1 gene affect DNA repair efficiency and therefore, may influence individual susceptibility to both atherosclerosis and CAD. Consequently, our findings on the joint effects of these polymorphisms in the DNA repair gene XRCC1, on CAD susceptibility supports this rationale and is biologically plausible.Although atherosclerosis is a complex process and its molecular mechanisms are not fully understood, research findings support the hypothesis that DNA damage caused by the production of excessive ROS has an important role in atherogenesis , 27, andXRCC1 gene in patients with CAD when compared with normal people, and Martinet et al. [XRCC1 gene in atherosclerotic plaques. Such upregulation may be in response to elevated DNA damage because of atherosclerotic progression. These findings are consistent with the results of our meta-analysis that found XRCC1 gene polymorphisms may be susceptibility factors and outcome predictors to CAD. However, these findings are in contrast to those of Gokkusu et al. [XRCC1 gene polymorphisms and CAD susceptibility. Possible explanations accounting for these inconsistencies between results may be because of genetic heterogeneity across different ethnicities, different baseline characteristics of study subjects, different sample sizes, or cultural differences in external factors such as nutritional status, diet, or daily exercise. On the other hand, the effect of a single polymorphism in the XRCC1 gene on CAD susceptibility may be very small and is vulnerable to various factors. In recent decades, the dynamic equilibrium between DNA damage and repair in atherosclerosis has been highlighted. However, it remains to be determined whether reducing the rate of DNA damage and improving the capacity of DNA repair, such as overexpression of XRCC1 protein or gene replacement therapy in CAD patients with DNA repair deficiencies, can delay atherosclerotic progression, or open new avenues for therapeutic intervention [Ahmadi et al.  reportedt et al.  found a u et al.  and Guveu et al.  that didrvention , 31.XRCC1 gene and likelihood for different cancers including thyroid cancer [XRCC1 gene in CAD susceptibility. Although our study provides a better understanding of genetic variations in XRCC1 and susceptibility to CAD, it has limitations. First, the limited number of original studies that were examined and the unpublished data that were not available may affect the reliability of our conclusions and potentially limit further analyses. Second, because original individual data could not be extracted from each study and our results were based on unadjusted estimates, the introduction of heterogeneity in our study is unavoidable and may affect our results. Third, because of anticipated interactions between hereditary and environmental factors, genetic variation at a single locus will be insufficient to completely elucidate gene-disease associations. Finally, the publication language of our studies was limited to English and therefore, there is the potential for publication bias, although we found no evidence of such from funnel plots and Egger's test in our meta-analysis.Previous meta-analyses have evaluated genetic polymorphisms in the d cancer , breast d cancer , glioma d cancer , and leud cancer , but to XRCC1, and increased susceptibility to CAD, specifically in Asian populations. Although subgroup analyses to investigate potential sources of heterogeneity did not find evidence for bias, future large-scale well-designed studies to bolster the robustness of our findings and reliability of our conclusions are warranted.The current meta-analysis supports associations between the polymorphisms Arg194Trp and Arg399Gln, in the DNA repair gene S1 File(DOCX)Click here for additional data file.S2 File(DOC)Click here for additional data file.S3 File(DOC)Click here for additional data file.S4 File(DOC)Click here for additional data file.S5 File(ZIP)Click here for additional data file.


There have been inconsistent results about the association between consumption of fruits and vegetables and renal cell carcinoma (RCC) risk. We conducted a meta-analysis of the published observational studies to explore this association.heterogeneity = 0.004, I2 = 53.5%), whereas for fruits it was 0.86 . Linear dose-response analysis also showed similar results, e.g., for per 1 serving/day increment of vegetables, the SRR was 0.90 (95% CI: 0.84–0.96) and for fruits it was 0.97 (95% CI: 0.93–1.01). Nonlinear association was only observed for vegetables (Pnonlinearity = 0.001), but not for fruits (Pnonlinearity = 0.221).Nineteen observational studies , involving 10,215 subjects with RCC were part of this meta-analysis. The SRR for the highest vs. the lowest intake of vegetables was 0.73 . Random-effects model was used to calculate summary relative risk (SRR) and corresponding 95% confidence interval (CI).This meta-analysis indicated a protective effect of consumption of vegetables and fruits on RCC risk. Further studies are warranted with prospective designs that use validated questionnaires and control for important confounders. In case more than one articles on the association between intake of fruits and vegetables and RCC were identified, the most recent report was selected for our analysis.From each study, the following information was independently extracted by two researchers (J.Z.K. and Z.S.J.): first author's last name, study design, publication year, follow-up duration in cohort study, geographic locations where the study was carried out, number of cases, size of cohorts/number of controls, definition of controls, dietary data ascertainment , exposure contrast, the RR estimates with their 95% CI for the highest vs. the lowest level and adjustment variables. When different types of adjusted RRs were presented, we extracted the one that controlled for the most confounders. Differences in data extraction between investigators were unusual and were resolved by consensus.For each publication, the quality score was assessed by using the Newcastle-Ottawa quality assessment Scale (NOS) , which aWe pooled RR estimates and 95% CIs for the comparison between the study-specific highest category of consumption versus the lowest, linear and non-linear dose-responses using the DerSimonian and Laird random-effects model, which incorporates both within- and between-study variability .p < 0.10) and I2 statistics . For the I2 statistic, heterogeneity was interpreted as absent (0%–25%), low (25.1%–50%), moderate (50.1%–75%), or high (75.1%–100%) [Heterogeneity was assessed using the Cochran Q (results were defined heterogeneous for 1%–100%) . SubgrouTo conduct dose-response meta-analyses, published results were transformed into a common scale, which are expressed as increment of 1 serving/day of consumption. For one study which presented the intake per given unit of energy intake, we rescaled it using the mean energy intake provided . For stuTo examine the non-linear dose-response relationship, we carried out the best-fitting second-order fractional polynomial models . The modP value of < 0.05 represents significance.Publication bias was assessed by using funnel plots and the further Begg's adjusted rank correlation and Egger's regression asymmetry test , 58. All