CYP1A1) is a phase I enzyme that regulates the metabolism of environmental carcinogens and alter the susceptibility to various cancers. Many studies have investigated the association between the CYP1A1 MspI and Ile462Val polymorphisms and digestive tract cancer (DTC) risk in different groups of populations, but their results were inconsistent. The PubMed and Embase Database were searched for case–control studies published up to 30th September, 2015. Data were extracted and pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to assess the relationship. Totally, 39 case–control studies  were included. The G allele in Ile/Val polymorphism was significantly associated with elevated DTC risk with per‐allele OR of 1.24 . Similar results were also detected under the other genetic models. Evidence was only found to support an association between MspI polymorphism and DTC in the subgroups of caucasian and mixed individuals, but not in the whole population . In conclusion, our results suggest that the CYP1A1 polymorphisms are potential risk factors for DTC. And large sample size and well‐designed studies with detailed clinical information are needed to more precisely evaluate our founding.Cytochrome P450 1A1 ( Global Cancer Statistics, 2012 CYP1A1, as its protein‐coding gene, is located on Chr15q22~q14, encoding aryl hydrocarbon hydroxylase. Aryl hydrocarbon hydroxylase is active in metabolizing some pro‐carcinogens, particularly the polycyclic aromatic hydrocarbons (PAHs), into intermediates. The intermediate substitutes may contribute to carcinogenesis eventually if bind to DNA and form adducts Digestive tract cancers (DTCs), well known as the most common malignant tumours globally, include oesophageal, gastric and colorectal cancers CYP1A1 gene consists of many single nucleotide polymorphisms (SNPs). These diverse variants could break the initial physiological equilibrium between activation and detoxification of metabolic carcinogens by adjusting the quantity and function of such enzyme. The two functional polymorphisms in CYP1A1gene, MspI  and Ile462Val , may associate with the risk of DTC by the mechanism above CYP1A1 and risk of many cancers et al. Many studies have been carried out to examine the association between the two polymorphisms of CYP1A1 polymorphisms and DTC were searched manually on PubMed and Embase Database up to 30th September, 2015. The search was limited to English language papers, using the key words ‘’ and ‘polymorphism’ and ‘’. And the following criteria were established: (i) case–control studies, (ii) exploring the association between MspI or Ile/Val polymorphism and DTC, (iii) DTC confirmed histologically or pathologically, (iv) providing sufficient data to calculate the odds ratio (OR) with its 95% confidence interval (CI) and P‐value. The exclusion criteria were as follows: (i) a case report or a review, (ii) no sufficient genotype frequency, (iii) a duplicated publication The published case–control studies about the associations between the Based on the inclusion criteria listed above, two authors independently extracted data from all qualified publications. Controversies were eliminated through discussion with another investigator. Following data were collected: first author’ s name, year of publication, cancer type, country and ethnicity of population, genotyping method, source of controls, number of cases and controls with different genotypes, adjusted OR and 95% CI and adjustment of variables if available and Hardy–Weinberg equilibrium (HWE) P < 0.05 was considered as significant disequilibrium. OR and 95% CI were calculated for CYP1A1 MspI/Ile462Val polymorphisms and DTC risk in each study. The pooled OR was also determined by the Z‐test . Stratified analyses by cancer type, source of controls, ethnicity, sample size and genotyping method were performed The HWE in control group was assessed by Pearson's goodness‐of‐fit chi‐square test and I2. A fixed‐effects model (the Mantel–Haenszel method) was applied if P > 0.05, which indicated no or little heterogeneity among eligible studies. Otherwise, the random‐effects model (Der Simonian and Laird method) was used. Galbraith graph was performed to explore the source of heterogeneity. Sensitivity analysis was tested to assess the stability of our results. The funnel plot was performed for potential publication bias. Funnel plot asymmetry was statistically assessed by Egger's linear regression test (publication bias exists if P < 0.05). All statistical analyses were carried out by Stata software  Heterogeneity in our meta‐analysis was assessed by the chi‐square‐based Q‐test and CYP1A1  polymorphisms and DTC risk, were included in the present meta‐analysis. The literature selection process was illustrated in Figure MspI polymorphism, including a total of 1717 cases and 2046 controls. And for the Ile/Val polymorphism, 26 studies  were retrieved, covering a total of 7377 cases and 10,441 controls. More detailed charismatics about population source, ethnicity distribution, sample size, genotyping method and adjusted OR and 95% CI and adjustment of variables if available can be seen in Tables Totally 37 publications MspI (rs4646903) polymorphism in all genetic models when all the eligible case–control studies were pooled together. Moreover, the adjusted pooled result was consistent with the crude one . However, because of unavailable adjusted data on colorectal cancer, this positive result could not be validated . Stratifying for ethnicity, an increased susceptibility was found in individuals with CC genotype among Caucasians and mixed population . However, no evidence was observed to prove that among Asians. In the stratified analysis by the source of controls, sample size or genotyping method, some statistical correlations were observed in the group of ‘population with sources unreported (NR)’, ‘size <300’ and ‘PCR‐RFLP method’ respectively (data shown in Table S1).Overall, no sufficient evidence was found to support an association between increased susceptibility of DTC and  rs464690 polymorpP = 0.001). Similar results were also detected under other genetic models and in our adjusted pooled result . But the positive result was only observed in oesophagus cancer from the adjusted result partially together . A significant association was also observed in Asians , but not in caucasians or mixed individuals. Stratified by the source of controls, significant association was observed both in HB and NR group. Stratified by sample size and genotyping method, associations were found in most groups. Detailed analyses of the genetic variant are provided in Table S2.The G allele was significantly associated with elevated DTCs risk with per‐allele OR of 1.24 . As shown in Tables S3 and S4, subgroup analyses stratified by cancer type, ethnicity, source of controls, sample size and genotyping method could not explain the source of heterogeneity at length. Hence, to further explore the heterogeneity source, we performed Galbraith graph. The study conducted by Saeed et al. e.g. the dominant mode: OR = 1.10, 95% CI = 0.90–1.35, P = 0.336), but its heterogeneity decreased significantly  . Similar results were observed in other genetic models. In the same way, we found the source of heterogeneity in Figure Ile/Val polymorphism. When we removed the study conducted by Pereira Serafim et al. P = 0.016; I2 = 34.8%, Ph = 0.046) .For The corresponding pooled ORs were not qualitatively influenced when any particular study had been removed from the meta‐analysis (including the studies not conforming to HWE) for the two polymorphisms respectively . Regarding Ile/Val, no publication bias was detected as well in the dominant model  , which verified the reliability of our results again. As the number of studies with adjusted data for MspI polymorphism is only 4, and moreover, only one study provided adjusted data for smoking, we did not carry out the analyses for MspI polymorphism.Stratified by cancer type, the MspI and Ile/Val respectively. Through Galbraith graph, we found the study conducted by Saeed et al. MspI. For Ile/Val, the heterogeneity mainly came from study conducted by Pereira Serafim et al. Some limitations and potential bias cannot be ignored in our meta‐analysis. First, we centre on the heterogeneity. Moderate and high heterogeneity were detected among the studies for CYP1A1 Ile462Val polymorphism and increased digest tract cancers risk. While no sufficient evidence was found to support the association between the CYP1A1 MspI polymorphism and DTC. In the subgroup analyses, the positive results were found in CC group, caucasians and mixed individuals for MspI polymorphism. Our results suggest that the CYP1A1 polymorphisms are potential risk factors for DTC. Large sample size and well‐designed studies with more clinical information like age, gender, smoking and drinking are needed to clarify our finding.In summary, our meta‐analysis revealed the significant association between the The authors declare no competing financial interest.LJZ and YBH conceived and designed the study. HND and AJR performed the experiments. AJR, TTQ, QQW and DHZ analysed the data. AJR, TTQ, QQW and DHZ contributed to the reagents/materials/analysis tools. AJR wrote the manuscript. All authors reviewed the manuscript.Figure S1 Forest plot of digestive cancer risk associated with MspI polymorphism with adjusted OR and 95% CI (the codominant model CC versus TT).Figure S2 Forest plot of digestive cancer risk associated with Ile/Val polymorphism with adjusted OR and 95% CI (the codominant model GG versus AA).Figure S3 Forest plot of digestive cancer risk associated with MspI polymorphism after dropping the data from Saeed et al. 2013versus TT).Figure S4 Forest plot of digestive cancer risk associated with Ile/Val polymorphism after dropping the data from Pereira Serafim et al. 2008 versus AA).Table S1 Pooled ORs and 95% CIs of stratified meta‐analysis for MspI polymorphism.Table S2 Pooled ORs and 95% CIs of stratified meta‐analysis for Ile/Val polymorphism.Table S3 Heterogeneity test for MspI polymorphism.Table S4 Heterogeneity test for Ile/Val polymorphism.Table S5 Subgroup analyses for adjusted status (Yes or no) and adjusted status especially for smoking history (Yes or no) for Ile/Val polymorphism (GG/AA model).Click here for additional data file.


XRCC3 polymorphisms are associated with ovarian cancer risk. Eligible case-control studies were identified through search in PubMed. Pooled odds ratios (ORs) were appropriately derived from fixed effects models. We therefore performed a meta-analysis of 5,302 ovarian cancer cases and 8,075 controls from 4 published articles and 8 case-control studies for 3 SNPs of XRCC3. No statistically significant associations between XRCC3 rs861539 polymorphisms and ovarian cancer risk were observed in any genetic models. For XRCC3 rs1799794 polymorphisms, we observed a statistically significant correlation with ovarian cancer risk using the homozygote comparison , heterozygote comparison , and the recessive genetic model . For XRCC3 rs1799796 polymorphisms, we also observed a statistically significant correlation with ovarian cancer risk using the heterozygote comparison . In conclusion, this meta-analysis shows that the XRCC3 were associated with ovarian cancer risk overall for Caucasians. Asian and African populations should be further studied.This meta-analysis aims to examine whether the  BRCA1, BRCA2, MLH1, MSH2, SMAD6, RAD51C, RAD51D, RB1, LIN28B, CASP8, and MTDH have all been implicated [Ovarian cancer is the leading cause of the female reproductive system, with over 220,000 new cases and over 140,000 deaths worldwide in 2008 [plicated –11. Receplicated –14. Examplicated .XRCC3 (X-ray repair cross-complementing group 3) belongs to a family of genes responsible for repairing DNA double strand breaks caused by normal metabolic processes or exposure to ionizing radiation [ XRCC3 interacts and stabilizes Rad51 and involves in HRR  for DBSs (double strand breaks of DNA) and cross-link repair in mammalian cells [ A > G) is located in 5′UTR and the SNP rs1799796 (17893 A > G) is located in intron 5 [ XRCC3. XRCC3 polymorphism was associated with the risks of many cancers, such as lung cancer, breast cancer, and head and neck cancer [ XRCC3 polymorphism and ovarian cancer has been studied [ XRCC3 polymorphism on the risk for ovarian cancer, we performed a meta-analysis.adiation . XRCC3 ian cells , 18. Thean cells , 19. Theintron 5 . So the k cancer –24. The  studied , 25–29; XRCC3,” “rs861539,” “T241M,” “rs1799794,” “a4541g,” “rs1799796,” “a17893g,” “polymorphism,” “ovarian cancer,” and their combination. Two authors (Yuan and Wang) independently checked all the references retrieved to assess their appropriateness for the inclusion in this meta-analysis. In addition, we checked all the references cited in the articles and relevant reviews. For overlapping and republished studies, only the study with the largest samples was included. If an article reported results including different studies, each study was treated as a separate comparison in our meta-analysis.The search of the PubMed database was performed using the following keywords: “X-ray repair cross-complementing group 3,” “ XRCC3 polymorphisms and ovarian cancer risk;evaluating the association betweenusing sufficient published data to enable estimation of an odds ratio (OR) with its 95% confidence interval (CI);using respective or prospective cohort case-control studies.Included studies met 3 criteria:Two authors (Yuan and Wang) independently extracted data from selected articles according to the inclusion criteria and reached a consensus on all items. XRCC3 in both cases and controls.The following information was extracted from each study if available: the first author, year of publication, countries, area of the cases, the ethnicity of the population, the cases source, the sample type of cases, the numbers of cases and controls, and the genotype distributions ofTwo authors independently evaluated the quality of the 8 studies according to the scale for quality assessment , which h XRCC3 polymorphism and ovarian cancer susceptibility, according to the genotype frequencies of cases and controls groups [P < 0.05 was considered statistically significant; all tests and CIs were two sided. If the heterogeneity was significant, the pooled ORs were initially measured by the random effects model. Else, the fixed-effects model was chosen [Pooled ORs with 95% CIs were calculated to access the strength of association betweens groups . P < 0.0s chosen . XRCC3 polymorphism and ovarian cancer risk were performed for a homozygote comparison (T2T2 versus T1T1), heterozygote comparison (T1T2 versus T1T1), dominant genetic model (T1T2+T2T2 versus T1T1), and the recessive genetic model (T2T2 versus T1T1+T1T2). In addition, sensitivity analysis was performed by omitting each study. Publication bias was estimated using a funnel plot. The degree of asymmetry was examined by t Egger's test (P < 0.05 was considered significant publication bias) [http://ihg.gsf.de/cgi-bin/hw/hwa1.pl).Theon bias) . The anaThrough the literature search, 13 articles were found. Eight articles –42 were Hardy-Weinberg disequilibrium of genotype frequencies among the controls was calculated in three studies.The heterogeneity analysis has been carried out. As it was shown in Tables  XRCC3 rs861539 polymorphisms are shown in  XRCC3 rs861539 polymorphisms and ovarian cancer risk were observed in any genetic models .The meta-analysis results of XRCC3 rs1799794 polymorphisms, two studies [P = 0.005), heterozygote comparison , and the recessive genetic model . However, no statistically significant associations were observed in dominant genetic model .For studies , 23, 24  XRCC3 rs1799796 polymorphisms, the meta-analysis results were shown in P = 0.04). However no statistically significant associations were observed in homozygote comparison , dominant genetic model , and the recessive genetic model .ForThe publication bias was tested by Begg's funnel plot and Egger's test for three SNPs. Egger's test results did not show any evidence of publication bias for any of the genetic models of the three SNPs (data not shown). The shape of the four Begg's funnel plots showed no evidence of obvious asymmetry of the three SNPs (data not shown).In the sensitivity analysis, the corresponding pooled ORs were not altered, when the fixed-effects model was changed to random-effects model. So it revealed that the results of this meta-analysis were stable. XRCC3 gene is required for genomic stability [ XRCC3 polymorphism increased the risk of many cancers, including ovarian cancer [ XRCC3.Thetability . It was n cancer . However XRCC3 rs1799794 and rs1799796 polymorphisms, we observed a statistically significant correlation with ovarian cancer risk. It was shown that the difference between different SNP sites was considerable for XRCC3.For rs861539 polymorphisms, no correlation with ovarian cancer risk was observed in any genetic models. However, For XRCC3 polymorphisms and ovarian cancer risk in other ethnicities.All of the literature was of high quality. All study subjects were Caucasian. The global multicenter studies can provide more valuable conclusions. So further studies should be done to explore the possible relationships between XRCC3 were associated with ovarian cancer risk overall for Caucasians. Asian and African populations should be further studied.In conclusion, this meta-analysis shows that the


I2=0%). Besides, no significant association was found in case-control studies  or cohort studies . A linear dose–response relationship was attested that an increase in dietary selenium intake of 10 μg/day is marginally associated with 1% increase in the risk of developing OAC , but not statistically significant. No publication bias was found. In conclusion, our analysis indicated that a higher selenium level was not significantly associated with the risk of OAC. The relevant further studies are warranted.Quantification of the association between selenium and risk of oesophageal adenocarcinoma (OAC) is still conflicting. The purpose of this meta-analysis is to explore the relationship between selenium levels and OAC risk. PubMed and Web of Knowledge were searched for the related articles. Pooled relative risks (RRs) with 95% confidence intervals (CIs) from random effects models were calculated. Sensitivity analysis and publication bias were conducted. Dose–response relationship was assessed by restricted cubic spline and variance-weighted least squares regression analysis. Five articles involving 748 OAC cases were included in this meta-analysis. Pooled results suggest that higher selenium level was not significantly associated with the risk of OAC (summary RRs=1.08, 95% CIs=0.84–1.39,  Over the past several decades, the incidence of oesophageal adenocarcinoma (OAC) has risen more rapidly in many high-income countries for reasons that are not well understood –3. BesidSelenium is one of the dietary factors, which has been investigated for its possible role in cancer aetiology . EvidencStudies were identified by using a literature search of PubMed and Web of Knowledge through June, 2015 and by handsearching the reference lists of the retrieved articles. The following search terms were used: ‘diet’ or ‘lifestyle’ or ‘selenium’ combined with ‘oesophageal adenocarcinoma’ or ‘OAC’ or ‘oesophageal carcinoma’. Two investigators (Bin Hong and Lihong Huang) searched the related articles and reviewed all the retrieved studies independently.For inclusion, studies had to fulfil the following criteria: (1) prospective or case-control study design; (2) reported the relationship between selenium and OAC; (3) relative risks (RRs) or odds ratios (ORs) with 95% confidence intervals (CIs) were provided; (4) for dose–response analysis, the each category of selenium was provided ; and (5) written in English.The exclusion criteria for this meta-analysis were as follows: (1) reviews; (2) the above-mentioned interests were not reported; (3) impossible to extract the appropriate data from the published results.When the same institution reported more than once, the most recent publication was included. Two investigators carefully reviewed all identified studies independently to determine whether an individual study was eligible for inclusion criteria in this meta-analysis.Two researchers (Bin Hong and Lihong Huang) independently extracted the following data from the included studies: the first author's last name, the age for participants, publication year, geographic locations, study design, duration of follow-up, the number of cases and participants (person-years), adjustment for covariates and RRs (95% CIs) for each category of selenium. From each study, we extracted the RRs that reflected the greatest degree of control for potential confounders. Otherwise, the crude RRs with 95% CIs were extracted. Any disagreements with the two authors were resolved by discussion between the third reviewers (Liangbo Hu).RRs estimates across categories of selenium levels. The non-linear relationships by modelling selenium levels were also explored by using restricted cubic splines with three knots at fixed percentiles  of selenium levels distribution [P-value for non-linearity was calculated by testing against the null hypothesis that the coefficient of the second spline transformation was equal to zero [RRs estimate. We used the midpoint between the upper and lower boundary if the median intake was not reported in the article. If the upper boundary of the highest category was not provided, we assumed that the boundary had the same amplitude as the adjacent category. Statistical heterogeneity across studies was assessed using the I2 statistics [I2 values of 0, 25, 50 and 75% represent no, low, moderate and high heterogeneity respectively [P ≤ 0.05 was accepted as statistically significant. The P value <0.1 was considered as significant for between-study heterogeneity and publication bias.A random-effect dose–response meta-analysis was conducted with the method proposed by Greenland and Longnecker  and Orsiribution . The P-v to zero . The req to zero ,19. The atistics , and I2 ectively . Sensitiectively  was perfectively  and Eggeectively . All staIn total, the electronic database searches 140 articles from PubMed and Web of Knowledge. After screening the title or abstract, 119 studies were excluded and 21 were retrieved and evaluated in detail. Finally, five articles –29 involTable 1.P=0.722, I2=0%, P=0.869, I2=0%) or cohort studies .Two of the included studies reported an inverse but non-significant association between selenium levels and OAC risk, whereas three studies reported that selenium levels could increase but not significant for the OAC risk. Our pooled results suggested that the high selenium levels compared with low levels were not significantly associated with the risk of OAC  was found. Our dose–response analysis indicates that an increase in selenium intake of 10 μg/day is marginally associated with 1% increase in the risk of developing OAC , but not statistically significant  were found in the pooled results and subgroup analysis. Thus, the univariate meta-regression was not performed.As shown in P=0.738) and Begg's funnel plot (Influence analysis shows that no individual study exerted excessive influence on the association of selenium levels and OAC risk. Egger's test (nel plot  showed nThe findings from this meta-analysis indicated that selenium were not significantly associated with the risk of OAC. The associations were also not significant both in case-control studies and cohort studies. An increased in selenium intake of 10 μg/day is marginally associated with 1% increase in the risk of developing OAC, but not statistically significant.The incidence of OAC has risen dramatically in the current social. Selenium has been studied in related to the cancer risk. The reason for selenium in prevention to cancer aetiology is the antioxidant capacity of the selenium-dependent glutathione peroxidase enzymes ,30. SomeTo the best of our knowledge, this is the first comprehensive meta-analysis to explore the relationship between selenium levels and OAC risk. The dose–response analysis between selenium levels and OAC risk was also conducted. The highlights of this meta-analysis were that no between-study heterogeneity was found in the pooled analysis and subgroup analyses and large number of cases and participants were included, allowing a much greater possibility of reaching reasonable conclusions between selenium levels and OAC risk. Third, Egger's test and Begg's funnel plot showed no significant publication bias was found. However, there were some limitations in this meta-analysis should be concerned. First, our meta-analysis included three case-control studies and two cohort studies. For the case-control studies, some recall or selection bias may be inherent in the original studies. The result of the meta-regression showed that no evidence of significant between subgroup of study design, and the summary RRs were consistent in the case-control studies and cohort studies. In our results, the association was not significant either in case-control studies or in prospective studies. Therefore, more original studies especially with prospective design are wanted in the future studies. Second, other unpublished literatures on relevant pharmaceutical websites were not searched and only studies in English were included, which may lead to a potential publication bias, although no significant publication bias was found by Egger's test and Begg's funnel plot. Third, between-study heterogeneity is common in the meta-analysis, and our study found no evidence of between-study heterogeneity in the pooled analysis.In summary, results from this meta-analysis suggested that a higher selenium level was not significantly associated with the risk of OAC. The dose–response analysis indicated that an increased in selenium intake of 10 μg/day is marginally associated with 1% increase in the risk of developing OAC, but not statistically significant. The relevant further studies are warranted.


NOS3) gene polymorphisms with respect to coronary artery disease (CAD) have been published in the past two decades. However, their association with the disease, especially among different ethnic subgroups, still remains controversial. This prompted us to conduct a systematic review and an updated structured meta-analysis, which is the largest so far , examining association of three polymorphic forms of the NOS3 gene  with CAD. In a subgroup analysis, we tested their association separately among published studies originating predominantly from European, Middle Eastern, Asian, Asian-Indian and African ancestries. The pooled analysis confirmed the association of all the three selected SNP with CAD in three different genetic models transcending all ancestries worldwide. The Glu298Asp polymorphism showed strongest association , followed by T786-C  and 4b/a,  in our pooled analysis. Subgroup analysis revealed that Glu298Asp  and 4b/a  have highest degree of association amongst the Middle Easterners. On the other hand, T786-C and its minor allele seem to carry a highest risk for CAD among subjects of Asian ancestry .Several association studies of endothelial nitric oxide synthase ( NOS3 gene. The NOS3 gene is located on chromosome 7q35-36, consists of 26 exons with a total size of 21 kb and it encodes for intracellular NO production Endothelial-derived nitric oxide (NO) has been known to be a major contributor in vascular regulation and has been amply implicated with coronary artery disease (CAD). NO is an important relaxing factor in the human body and is involved in a variety of different important physiological functions. It is synthesized in the human body from L-arginine by at least three isoforms of NO synthase (NOS), viz. inducible NOS, constitutive neuronal NOS and constitutive endothelial NOS (eNOS). NOS3 gene, resulting in the replacement of glutamic acid by aspartic acid at codon 298 . This variant has been shown to be associated with coronary spasm, Hingorani et al., NOS3 gene. NOS3 promoter activity approximately by 50% and has been associated with an increased risk for coronary artery spasm among subjects of Japanese ethnicity. NOS3 promoter region (T786-C) is associated with reduction in the promoter efficiency and the level of expressed enzyme, leading to increased CAD risk. Another common variant of this gene results by a cytosine replacing a thymine at nucleotide −786  at the 5′-flanking region of the NOS3 gene. Among them polymorphic repeats close to the 5′ end of the gene, the 27-base pair (bp) repeat in intron 4 is one of the most studied. The resulting rare 4-repeat allele has been shown to be associated with CAD among subjects belonging to European ancestry. NOS3 gene was found to be associated with MI, among subjects of Turkish descent. There are also several variable number of tandem repeats (VNTRs) with functional significance within NOS3 SNPs with respect to CAD reported association only in recessive genetic model of Glu298Asp, while dominant and allelic comparisons came out to be non-associated in the pooled analysis . NOS3 polymorphisms, which would aid to improve the existing understanding of these polymorphic forms of this gene in relation to CAD was warranted. Taking this as an objective, we conducted a systematic review and updated meta-analysis to ascertain the role of the three most common NOS3 gene polymorphisms in CAD. We also tested their association separately among published studies originating predominantly from European, Middle Eastern, Asian, Asian-Indian and African ancestries.The only meta-analysis to assess the role of all three The databases of the US National Institutes of Health (PubMed), EMBASE and a MEDLINE Scopus and Web of Knowledge were systematically searched for relevant articles published online by March 2014. Both medical search headings and open text fields were used to identify articles. We systematically searched various databases and the reference lists of the relevant publications using the combination of terms like ‘NOS3’ OR ‘eNOS’ OR ‘constitutive endothelial NOS’ OR ‘ecNOS’ OR ‘endothelial nitric oxide synthase’ OR ‘endothelial NO synthase’ paired with ‘atherosclerotic heart disease’ OR ‘coronary artery disease’ OR ‘CAD’ OR ‘MI’ OR ‘Myocardial Infarction’ OR ‘AMI’ OR Acute Myocardial Infarction OR ‘ACS’ OR ‘Acute Coronary Syndrome’ AND ‘polymorphism’ OR ‘mutation’ OR ‘gene polymorphism’ Or ‘SNP’ OR ‘Single Nucleotide Polymorphism’. The search in these databases was restricted to articles relating to humans, covering all relevant English language publications published up to March 2014. All references cited in the resulting studies and in previously published reviews on this topic were examined to identify additional work not indexed in internet databases. Papers without sufficient information were identified and their corresponding authors were contacted via at least three emails (spaced one week apart) requesting needed information. Publications whose corresponding authors did not respond were thenceforth not included. Since data from unpublished studies is unlikely to be trustworthy, we chose not to include it into this present meta-analysis. The decision to include studies was hierarchical; initially study titles, then abstracts and finally the full body of the text were assessed. The following information was recorded from the retrieved studies: author's names, publication year, country where the study was conducted, study design, inclusion criteria for CAD patients and normal controls, methods used for genotyping and the distribution of polymorphic genotypes and alleles in each group.To be included in the meta-analysis, articles had to assess the association between CAD or MI patients and CAD free controls. Our selection criteria included studies that met all of the following criteria: (1) published in a peer-reviewed journal and independent studies using original data; (2) unrelated case-control or cohort studies; (3) providing complete data with genotype and allele frequencies to calculate the odds ratio (OR) with confidence interval (CI) and p values; (4) CAD patient diagnosis based on coronary angiography/clinical assessment and controls not being CAD patients; (5) all studies included had to be published in English language; and (6) all included studies had to have their genotype distribution among controls consistent with Hardy Weinberg approximations. We excluded the case reports, case studies and the studies not providing adequate information on selection criteria and the actual distribution of genotypes in each group. We also purposefully excluded studies with a surrogate endpoint such as “coronary artery spasm” or “heart failure”. Strict adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses-PRISMA statement http://www.tufts.edu/~mcourt01/Documents/Court%20lab%20-%20HW%20calculator.xls). Studies with genotype frequency among controls yielding a p value of <0.05, did not conform to HWE approximations and were thus excluded.All required data along with genotypic distribution among cases and controls were recorded from publications (in duplicate) on a paper proforma. Later allele frequency was calculated manually and all the data was then transcribed on to a Microsoft Excel program on a computer. We checked departure from Hardy-Weinberg equilibrium (HWE) among control population for each included study using Michael H. Court's (2005–2008) online calculator (RevMan) [Computer program]. Version 5.3. Copenhagen: The Nordic Cochrane Centre, The Cochrane Collaboration, 2012. The extracted data from all publications were tested using previously described three genetic models i.e. dominant, recessive, and allelic model. Z test . Summary P value and Z value was also calculated (as listed) for each study group, for each genetic model to express the significance and degree of association. Existence of heterogeneity was tested using a Q test. It was performed using Higgins 2I statistics (2I) and Cochran's Q statistics (PQ) for each group of studies. Those resulting with 2I>50% and PQ<0.01 were identified as a heterogeneous group. Low, moderate and high heterogeneity was defined according to previously published estimates 2I values as 25%, 50% and 75%. Using this calculation, 2I value of <50% and PQ>0.01 was considered the criterion for selecting fixed effects for analysis. On the other hand, random effects were used for analyses for groups having 2I values of >50%. In order to define the sources of heterogeneity, subgroup analysis was performed. The subgroups were classified according to predominant ancestry among which the study was conducted. Publication bias was identified by examining Begg's funnel plots All calculations in this meta-analysis were carried out using Review Manager . A total of 60 case control studies  and 2I range = 18–23% and PQ range = 0.26–0.28). All other ancestral groups (apart from African which had only 1 study) showed moderate to high heterogeneity (2I range = 33–78% and PQ range = 0.16 to <0.00001). Among subgroups for Glu298Asp, 17 studies belonged to the European,  and 2I range = 35–69%, PQ range = 0.03 to <0.00001). Twenty nine case-control studies  and 2I range = 50–72%, PQ range = 0.16 to <0.00001). ( and S4)Among the ancestral subgroups, 15 studies constituted the European group, 2I = 17–61%, PQ = 0.17 to <0.00001). Forty three case-control studies, .00001). Table 2 2 rangeI = 0–33%; PQ range = 0.18–0.83), while European and Asian-Indian groups showed very low to very high heterogeneity . A total of 20 studies from European, –0.005). Table 2 Higher degree of heterogeneity was seen amongst almost all ancestral groups (except Asian-Indians) in all comparisons for Glu298Asp polymorphism. All groups were fairly heterogeneous in all comparisons for T786-C polymorphism. Fairly low heterogeneity was seen amongst Middle Eastern and Asian groups in all comparisons for 4b/a polymorphism. Table 2 Potential publication bias among groups of studies for each SNP was assessed by two different statistical tests, viz. Egger's plots S9-A, B). Each point in the figure represents OR of a study plotted against standard error (SE) of OR of that particular study. Different indicators of the studies belonging to each ancestry are used in these plots where they are seen to be generally contained within the inverted cone, indicating no significant publication bias, at least in the pooled analyses.Begg's funnel plots, Sensitivity analysis was performed in each study group in every genetic model, where we excluded studies one after another and conducted the analysis after each omission. The results in none of the groups and studied genetic models altered substantially to change the results from no association to significant association or the other way around (in groups of ≥5 studies). This indicates that the present meta-analysis is robust in nature.NOS3 gene polymorphisms,  with CAD.The present meta-analysis and structured systematic review is the most comprehensive till date and comprises of published studies which investigated the association of three most common  and  and S2) Consistent to the seen pattern, the T allele also showed a significant association with CAD in almost all ancestral groups, barring the Africans which had only 1 study. All comparisons in the pooled analysis for all three SNPs indicated significant association with CAD. The pooled results of Glu298Asp suggested that the presence of even a single T allele in a genotype effects in an increased risk of CAD. The risk of CAD is even higher if the genotype contains more than 1, T allele. This association is evident by the obtained pooled OR in allelic comparison .  and  and S2 CNOS3 SNPs are also now into public domain. NOS3 gene and CAD, Our pooled analysis showed significant associations of all three selected SNPs with CAD in every employed genetic model. Our results are in contrast to the previously published meta-analysis , NOS3 SNPs. Secondly, our study had strict inclusion/exclusion criteria, and we excluded studies with surrogate endpoints, and omitted studies in which controls did not conform to HWE proportions . This methodology ensured that we eliminated studies with potentially biased/inaccurate results, thus possibly presenting a real picture.There are basically two major merits of the present study which makes it superior to all previously published meta-analyses on this subject. NOS3 gene polymorphisms has been studied in detail by several researchers. Most schools of thought suggest that all these SNPs of NOS3 gene viz. Glu298Asp, T786-C and 4b/a 27bp VNTR via various mechanisms affect the serum nitrite/nitrate (NOx) concentrations in the human body. Over a period of time this imbalance in NOx concentrations results in “endothelial dysfunction” which finally blooms into an overt form of CAD. It is plausible that this degree of association with CAD and the resulting NOx concentrations are affected by gene-gene, gene-environment interactions. Compensatory mechanism of the human body against CAD may also increase NO secretion from the vascular endothelium during sudden reperfusion after acute coronary syndromes. x concentrations.The biochemical basis of the association of CAD with various  and , S2) The reason of this differential risk of CAD seen among different ancestral groups carrying this polymorphism is unknown and should be investigated upon. We presume that this difference could had been brought about by the variance in Asp allele frequency (range = 0.04-0.39), as well as several known and unknown gene-gene and gene-environment interactions. The biochemical basis of the association of CAD with Asp allele carriers has although been extensively studied upon however a clear consensus is still lacking. Some studies have reported an association of this SNP with intracellular NO concentration. x concentrations with any of the genotypes or alleles for this SNP. Also, since these associations are often masked, as it is affected by several physiological and pathological conditions, the real effect of NOS3 gene on plasma NOx levels is hard to determine. NOS3 gene.Positive association of Glu298Asp with CAD/MI has been reported over the years in several published studies. We found that along with a significant association for all three genetic models in our pooled analysis, this SNP seen to be associated with CAD separately among all ancestral groups, with the highest degree of association seen amongst the Middle Easterners. The reason behind this dissimilar degree of association among these ancestral groups is unknown. More in depth studies are warranted to answer this pertinent question. In vitro reporter gene assays performed by Nakayama et al., NOS3 mRNA and serum NOx levels in genotypes with ≥1, 786C alleles, NOS3 Glu298Asp and T786-C polymorphism has also been reported to be the cause of increased CAD risk among carriers of this SNP. The T786-C gene variant of NOS3 4b/a VNTR polymorphism with CAD. In contrast to the previous studies,  and , S6) The precise reason of this heightened risk amongst subjects of Middle Eastern ancestry is unknown and can only be speculated upon. Here again the influence of environmental factors such as diet and exercise may well be associated with the increased risk. Conflicting reports between the intron-4 variant and NO pathway activity are there in the public domain. Genotypes carrying ≥1 mutant alleles have been shown to have lower plasma NO levels and reduced protein expression, NOS3 gene. Clear scientific evidence is lacking which can explain the seen association of We believe that the present study has successfully answered the research question that it aimed at the outset and is statistically powered enough to the stand by the results it obtained. Although, there is a scope for limitations in every meta-analysis of genetic association studies and ours was no exception either. Firstly, we believe that there was under representation of the South-Asian region, and we found no published data on the subject from several South-Asian countries like Bangladesh, Sri Lanka and Pakistan etc., which have a sizable population inflicted with CAD. Secondly possibility of errors in genotyping, presence of selection bias and risk of inadequate sample size among different studies cannot be ruled out. It is also noteworthy that in case of polygenic diseases like CAD, an association study cannot test causality, it can merely measure statistical associations. Also, during meta-analysis of association studies we cannot ensure interference of linkage disequilibrium of the selected SNP with another closely linked site and its extent of effect on the overall association. Even after using two statistical tools, we could not detect any hint of publication bias amongst our study groups, at least for Glu298Asp and 4b/a polymorphisms. However, Egger's plot asymmetry was observed, with significant p values for pooled and European subgroup of T786-C polymorphism. Since the accuracy of Egger's test is debatable, and this asymmetry in the aforementioned plots could have possibly been due to factors like inter-study variations or small study effects among European subgroup for T786-C. Even then, the role of existing publication bias cannot be completely ruled out. This also qualifies to be listed as another small limitation in the present study.NOS3 gene polymorphisms i.e. Glu298Asp, T786-C and 4a/b VNTR with CAD transcending all ancestries worldwide. Results amongst different ancestral subgroups were rather illuminating. Amongst the studied NOS3 SNPs, both Glu298Asp and 4b/a showed strongest association among the Middle Eastern subgroup. On the other hand, T786-C and its minor allele seem to carry the highest risk for CAD among subjects of Asian ancestry. Our study significantly improves the understanding of the relation between this gene and CAD and its association amongst subjects of all major ancestries. These findings should thenceforth be assessed clinically for its implications in prevention and treatment strategies of CAD.In conclusion, since the criteria for inclusion and exclusion of studies are critical parts of a meta-analysis and can substantially affect results, we find that the present study is the most comprehensive till date and is systematically planned to funnel out erroneous studies. We thus feel that our study projects the real picture, and confirms the association of the three common Figure S1Forest plot depicting results of meta-analysis of studies reporting NOS3 Glu298Asp polymorphism assessed under dominant (TT+GT vs. GG) genetic model. Effect size estimates for all ancestral groups in this plot were obtained using random effects for analysis. Effect sizes using fixed effects were recalculated for Asian-Indian group which showed homogenous distribution among its included studies. Recalculated effect size estimate for Asian-Indians was, OR, 95%CI = 1.21, 1.01–1.45; Z = 2.07; P = 0.04.(TIF)Click here for additional data file.Figure S2Forest plot depicting results of meta-analysis of studies reporting NOS3 Glu298Asp polymorphism assessed under recessive (TT vs. GG+GT) genetic model. Effect size estimates for all ancestral groups in this plot were obtained using random effects for analysis. Effect sizes using fixed effects were recalculated for Asian and Asian-Indian groups which showed homogenous distribution among its included studies. Recalculated effect size estimates were, OR, 95%CI = 2.22, 1.21–4.08; Z = 2.57; P = 0.01 and OR, 95%CI = 1.85, 1.12–3.04; Z = 2.42; P = 0.02 for Asians and Asian-Indians respectively.(TIF)Click here for additional data file.Figure S3Forest plot depicting results of meta-analysis of studies reporting NOS3 T786-C polymorphism assessed under dominant (CC+CT vs. TT) genetic model. Effect size estimates for all ancestral groups in this plot were obtained using random effects for analysis.(TIF)Click here for additional data file.Figure S4Forest plot depicting results of meta-analysis of studies reporting NOS3 T786-C polymorphism assessed under recessive (CC vs. TT+CT) genetic model. Effect size estimates for all ancestral groups in this plot were obtained using fixed effects for analysis. Effect sizes using random effects were recalculated for three ancestral subgroups viz. Middle Eastern, Asian-Indian and African, which showed homogenous distribution among its included studies. Recalculated effect size estimates were, OR, 95%CI = 1.35, 0.69-2.65; Z = 0.87; P = 0.38 for Middle Easterners; OR, 95%CI = 1.73, 0.38–7.95; Z = 0.71; P = 0.48 for Asian-Indians and OR, 95%CI = 1.85, 0.77–4.44; Z = 1.37; P = 0.17 for Africans.(TIF)Click here for additional data file.Figure S5Forest plot depicting results of meta-analysis of studies reporting NOS3 4b/a VNTR polymorphism assessed under dominant (4a4a+4a4b vs. 4b4b) genetic model. Effect size estimates for all ancestral groups in this plot were obtained using random effects for analysis. Effect sizes using fixed effects were recalculated for Middle Eastern and Asian groups which showed homogenous distribution among its included studies. Recalculated effect size estimates were, OR, 95%CI = 1.73, 1.46–2.05; Z = 6.28; P = <0.00001 and OR, 95%CI = 1.22, 1.04–1.42; Z = 2.45; P = 0.01 for Middle Easterners and Asians respectively.(TIF)Click here for additional data file.Figure S6Forest plots depicting results of meta-analysis of studies reporting NOS3 4b/a VNTR polymorphism assessed under recessive (4a4a vs. 4a4b+4b4b) genetic model. Since all the ancestral groups showed homogenous distribution among its included studies, effect size estimates for all groups in this plot were obtained using fixed effects for analysis.(TIF)Click here for additional data file.Figure S7Begg's funnel plots for testing publication bias in comparisons under different genetic models for NOS3 Glu298Asp polymorphism. Each point in each figure represents OR of a study plotted against the standard error (SE) its OR. Different indicators of the studies belonging to each ancestral group are used in these plots. Figure S7A: Begg's Plot for comparisons under dominant genetic model (TT+GT vs. GG); Figure S7B: Begg's Plot for comparisons under recessive genetic model (TT vs. GG+GT).(TIF)Click here for additional data file.Figure S8Begg's funnel plots for testing publication bias in comparisons under different genetic models for NOS3 T786-C polymorphism. Each point in each figure represents OR of a study plotted against the standard error (SE) its OR. Different indicators of the studies belonging to each ancestral group are used in these plots. Figure S8A: Begg's Plot for comparisons under dominant genetic model (CC+CT vs. TT); Figure S8B: Begg's Plot for comparisons under recessive genetic model (CC vs. TT+CT).(TIF)Click here for additional data file.Figure S9Begg's funnel plots for testing publication bias in comparisons under different genetic models for NOS3 4b/a VNTR gene polymorphism. Each point in each figure represents OR of a study plotted against the standard error (SE) its OR. Different indicators of the studies belonging to each ancestral group are used in these plots. Figure S9A: Begg's Plot for comparisons under dominant genetic model (4a4a+4a4b vs. 4b4b); Figure S9B: Begg's Plot for comparisons under recessive genetic model (4a4a vs. 4a4b+4b4b).(TIF)Click here for additional data file.Data S1The raw data collected from all the published association studies included in the present meta-analysis.(ZIP)Click here for additional data file.Checklist S1PRISMA Checklist.(DOC)Click here for additional data file.


Radiotherapy for breast cancer often involves some incidental exposure of the heart to ionizing radiation. The effect of this exposure on the subsequent risk of heart disease is uncertain. We performed a meta‐analysis to investigate the link between radiotherapy and long‐term cardiovascular morbidity and mortality in patients with breast cancer.MEDLINE (January 1966 to January 2015) and EMBASE (January 1980 to January 2015) with no restrictions. Studies that reported relative risk (RR) estimates with 95%CIs for the associations of interest were included. Pooled effect estimates were obtained by using random‐effects meta‐analysis. Thirty‐nine studies involving 1 191 371 participants were identified. Patients who received left‐sided radiotherapy, as compared with those receiving right‐sided radiotherapy, experienced increased risks of developing coronary heart disease , cardiac death  and death from any cause . In a comparison of patients with radiotherapy and without radiotherapy, the RRs were 1.30 (95%CI 1.13‐1.49) for coronary heart disease and 1.38 (95%CI 1.18‐1.62) for cardiac mortality. Radiotherapy for breast cancer was associated with an absolute risk increase of 76.4 (95%CI 36.8‐130.5) cases of coronary heart disease and 125.5 (95%CI 98.8‐157.9) cases of cardiac death per 100 000 person‐years. The risk started to increase within the first decade for coronary heart disease and from the second decade for cardiac mortality.We performed a literature search using Exposure of the heart to ionizing radiation during radiotherapy for breast cancer increases the subsequent risk of coronary heart disease and cardiac mortality. The association between radiotherapy for breast cancer and long‐term cardiovascular risk remains unclear.The meta‐analysis found that, in women diagnosed with breast cancer, risks of coronary heart disease and cardiac mortality were increased in patients with left‐sided radiotherapy compared with those with right‐sided radiotherapy, as well as in the comparison of patients with radiotherapy and those without radiotherapy.The meta‐analysis found that, in women diagnosed with breast cancer, radiotherapy increased the risks of coronary heart disease and cardiac mortality.Contemporary radiotherapy techniques have likely reduced the risk, but they may not have eliminated cardiotoxicity, and therefore the long‐term hazards in the general population still need to be monitored directly.The association between radiotherapy and cardiovascular risk has clinical relevance with respect to individual screening, risk factor modification, and the primary and secondary prevention of heart disease.Breast cancer is the most common cancer in women, with over a million new cases diagnosed each year worldwide. During the past 30 years, prognosis of breast cancer patients has improved substantially, with 5‐year survival now around 90% in many countries, due partly to earlier diagnosis and greater use of adjuvant therapies.The US SEER (Surveillance Epidemiology and End Results) cancer registries have reported increased risk of cardiovascular death after radiotherapy for breast cancer during the first 2 decades.If the relationship between cardiac radiation exposure and the long‐term risk of heart disease were known, then physicians should weigh the likely long‐term benefit of radiotherapy on the breast cancer and the likely long‐term risk of radiation‐induced heart disease and tailor the treatment accordingly. Therefore, we conducted a meta‐analysis with the following aims: (1) to investigate cardiovascular risk in breast cancer patients with left‐sided irradiation or with right‐sided irradiation; (2) to investigate cardiovascular risk in breast cancer patients with or without radiotherapy; (3) to measure the relationship between breast cancer radiotherapy and cardiovascular risk according to different characteristics of the study populations, study designs, follow‐up duration, and treatment eras; and (4) to estimate absolute risk of cardiovascular disease associated with breast cancer radiotherapy in the studies included in the meta‐analysis.We followed the PRISMA  guidelines for systematic reviews and meta‐analyses.The primary study end points were coronary heart disease  and cardiac mortality identified using the death registry or validated with medical records. In addition, we included an analysis of death from any cause to examine whether the risk for cardiac death would offset the survival benefit by radiotherapy. We also analyzed the end point of heart failure, arrhythmia, and valvular heart disease that may be associated with cardiovascular toxicity by radiotherapy.P value of the significance of the estimate). (2) We included cohort studies, case‐control studies, and randomized controlled trials published as original articles; case reports, ecological, and prevalence studies were excluded. (3) We considered studies that were independent. Once full articles were retrieved, studies were further excluded if there was an overlap in patients with another study within the same analysis . If some patients had been included in another study with different analysis , they would be included once in 1 given analysis. Consequently, there was no overlap in patients included in our meta‐analyses.To minimize differences between studies, we imposed the following methodological restrictions for the inclusion criteria. (1) We used studies that contained the minimum information necessary to estimate the relative risk (RR) associated with radiotherapy and a corresponding measure of uncertainty  extracted the data, and 1 author (C.‐C.J.) independently double‐checked the available data. The following data were extracted from each study: first author's name, publication year, geographical location, mean age, sample size, study design, sampling framework, study population, study end points, number of events, duration of follow‐up, treatment era, and the relative risks and associated measure of variance for all categories of outcomes. When available, we used the most comprehensively adjusted risk estimates. Percentage agreement between the 2 authors on the quality review ranged from 90% to 100%. Any disagreements were resolved by consensus.To determine the quality of the included studies, we used the Modified Jadad Score for the randomized control trials and the Newcastle‐Ottawa scale for the observational studies. Y.‐J.C. and X.‐Y.N. developed the evaluation criteria Tables . The scoThe RR was used as a measure of the association between breast cancer radiotherapy and cardiovascular risk. For case‐control studies, the odds ratio was used as an estimate of the RR because cardiovascular events are sufficiently rare.2 statistic , applying the following interpretation for I2: <50%=low heterogeneity; 50% to 75%=moderate heterogeneity; >75%=high heterogeneity.0}, where RR indicates pooled RRs and I0 was the cumulative event rate per 100 000 patient‐years of follow‐up for the reference population. On the basis of population‐based cohort studies, I0 was estimated by weighting by the sample size of each study.We assessed the heterogeneity across studies by the Cochran test and by calculating the IP values are 2‐sided. Results were considered to be statistically significant at a P value of less than 0.05. Statistical analysis was performed with the use of Stata software, version 12.0 .Small study bias, consistent with publication bias, was assessed with funnel plot, by the Begg adjusted rank correlation test and by the Egger regression asymmetry test.Our literature search identified 2523 potentially relevant studies as shown in the flow diagram. Of these, 281 articles were considered of interest, and full text was retrieved for detailed evaluation. An additional 242 studies were excluded due to overlap of patients or no relevant outcomes, and finally, 39 studies were included in the meta‐analysis Figure .A total of 1 191 371 individuals were enrolled in 39 eligible studies, including 11 randomized controlled trials,P<0.001), with low between‐study heterogeneity   . With the trim‐and‐fill approach, the imputed estimate  was similar to that in the main analysis, indicating that results are unlikely to be explained by publication bias. In a sensitivity analysis that included only the 11 studies that used myocardial infarction or death due to coronary heart disease as the outcome of interest, the pooled RR was 1.34 (95%CI 1.20‐1.50), with no evidence of significant heterogeneity   Figure . However) Figure .P=0.65), breast cancer staging (P=0.69), follow‐up duration (P=1.00), age at breast cancer diagnosis (P=0.11), number of patients (P=0.47), source of patients (P=0.83), whether risk profiles were adjusted (P=0.83), or whether adjuvant chemotherapy was administered (P=0.38). Significant heterogeneity between pooled analyses was noted for studies published before 2010 compared with those published after 2010 , studies in which cases were validated with medical record compared with studies in which they were not , and breast cancer diagnosed before 1980 compared with breast cancer diagnosed after 1980 . The RRs for coronary heart disease in women with left‐sided versus right‐sided radiotherapy, according to the number of years since diagnosis of breast cancer, were as follows: 0 to 4 years, 1.14 (95%CI 0.95‐1.36); 5 to 9 years, 1.17 (95%CI 1.04‐1.32); 10 to 14 years, 1.93 (95%CI 1.13‐3.30); 15 to 20 years, 1.39 (95%CI 1.08‐1.79)   Figure . Using tP=0.002). There was evidence of moderate heterogeneity of RRs across these studies    Figure .P=0.01). In addition, breast cancer diagnosis period also seemed to be associated with the results . The RRs for cardiac mortality, left versus right tumor laterality, increased steeply with time since diagnosis of breast cancer: 0 to 4 years, 1.02 (95%CI 0.96‐1.08); 5 to 9 years, 1.05 (95%CI 0.97‐1.14); 10 to 14 years, 1.26 (95%CI 1.11‐1.44); 15 to 20 years, 1.44 (95%CI 1.14‐1.82)   Figure . CompareP=0.02) , death from myocardial infarction , and myocardial infarction   Figure . We alsoP<0.001), with moderate heterogeneity  . This raises the possibility of publication bias, although neither the Begg nor the Egger test was statistically significant  . Further analysis of 9 studies that used myocardial infarction or death from coronary heart disease as the end point yielded similar results   Figure . Because) Figure .P=0.004). Notably, although treatment era seemed to be associated with the results, patients diagnosed after 1980 with modern radiotherapy techniques still experienced increased risk of coronary heart disease compared with those without radiotherapy . The risk increase started within the first 5 years and continued into the third decade after radiotherapy: the RRs were 1.40 (95%CI 1.12‐1.74) for 0 to 4 years, 1.70 (95%CI 1.18‐2.45) for 5 to 9 years, 1.79 (95%CI 1.08‐2.97) for 10 to 14 years, 1.23 (95%CI 1.02‐1.48) for 15 to 19 years, and 1.88 (95%CI 1.08‐3.27) for 20 years or more  higher risk of cardiac mortality , the Begg and Egger tests indicated no evidence of publication bias   Figure .P=0.02), studies with case validation than those without case validation , and breast cancer diagnosed before 1980 than that diagnosed after 1980 . The RRs of cardiac mortality were 1.04 (95%CI 0.51‐2.12) during 0 to 4 years after primary diagnosis, 1.17 (95%CI 0.55‐2.48) during 5 to 9 years, 1.41 (95%CI 1.04‐1.92) during 10 to 14 years, 1.63 (95%CI 1.21‐2.21) during 15 to 19 years, and 1.59 (95%CI 1.33‐1.91) after 20 years  and myocardial infarction . Analysis of 4 studies involving 5628 patients and 53 events showed a statistically nonsignificant 1.84‐fold increased risk for death from myocardial infarction. In addition, we found no significant association between radiotherapy and risk of death from any cause, heart failure, arrhythmia, and valvular heart disease , Guangdong Province Science and Technology Program (No. 2012B031800091), and Guangzhou City Science and Technology Program (No. 201508020057) to Dr Wu; and National Natural Science Foundation of China for Young Scholar (No. 81600260) and Natural Science Foundation of Guangdong Province (No. 2016A030313210) to Dr Cheng.None.Table S1. Studies Included in the Meta‐Analysis That Assessed Cardiac Morbidity and Mortality Associated With Breast Cancer RadiotherapyTable S2. The Quality Assessment of Included Cohort Studies Using the Newcastle‐Ottawa ScaleTable S3. The Quality Assessment of Included Case‐Control Studies Using the Newcastle‐Ottawa ScaleTable S4. The Quality Assessment of Included Randomized Controlled Studies Using the Modified Jadad ScoresFigure S1. Flowchart of the selection of studies included in meta‐analysis.Figure S2. Funnel plots showing association of coronary heart disease and cardiac death with radiotherapy.Figure S3. Forest plot for risk of myocardial infarction and death from coronary heart disease in patients with left‐sided radiotherapy versus right‐sided radiotherapy.Figure S4. Forest plot for risk of coronary heart disease in unirradiated patients with left‐sided versus right‐sided breast cancer.Figure S5. Forest plot for risk of cardiac death in unirradiated patients with left‐sided versus right‐sided breast cancer.Figure S6. Forest plot for risk of death from any cause in patients with left‐sided radiotherapy versus right‐sided radiotherapy.Figure S7. Forest plot for risk of myocardial infarction and death from coronary heart disease in patients with radiotherapy versus those without radiotherapy.Click here for additional data file.


Q Test and I2 statistics. A random‐effect model or a fixed‐effect model was applied depending on the heterogeneity. Subgroup analysis and meta‐regression were used to evaluate the source of heterogeneity. Among the 11 eligible studies, three reported both CVE and mortality outcome, one reported only CVEs and the other seven provided mortality data only. Higher circulating TMAO was associated with a 23% higher risk of CVEs  and a 55% higher risk of all‐cause mortality . Notably, the latter association may be blunted by potential publication bias, although sensitivity analysis by omitting one study at a time did not significantly change the results. Further subgroup analysis and meta‐regression did not support that the location of the study, follow‐up duration, publication year, population characteristics or the samples of TMAO affect the results significantly. Higher circulating TMAO may independently predict the risk of subsequent cardiovascular events and mortality.Circulating trimethylamine N‐oxide (TMAO), a canonical metabolite from gut flora, has been related to the risk of cardiovascular disorders. However, the association between circulating TMAO and the risk of cardiovascular events has not been quantitatively evaluated. We performed a systematic review and meta‐analysis of all available cohort studies regarding the association between baseline circulating TMAO and subsequent cardiovascular events. Embase and PubMed databases were searched for relevant cohort studies. The overall hazard ratios for the developing of cardiovascular events (CVEs) and mortality were extracted. Heterogeneity among the included studies was evaluated with Cochran's  Firmicutes, Proteobacteria, Anaerococcus hydrogenalis, Clostridium asparagiforme, C. hathewayi, C. sporogenes, Escherichia fergusonii, Proteus penneri, Providencia rettgeri, Edwardsiella tarda and Desulfovibrio desulfuricans, have been identified as potential producers of TMAO in vivoRecent findings from studies in animal models and patients suggest that microbiota from human body may contribute to the development of various disorders, including diabetes, atherosclerosis and related cardiovascular disorders. Interestingly, trimethylamine N‐oxide (TMAO), an organic compound that was first found in marine organisms Cardiovascular diseases (CVD), including coronary artery disease, peripheral artery disease and cerebral vascular disease, are the leading cause of mortality worldwide, which contribute to over 30% of global mortality annually We searched the PubMed and Embase databases from the inception up to 15 January 2017 for relevant studies without language restriction. Methods used are in compliance with the PRISMA statement for reporting systematic reviews and the Meta‐analysis of Observational Studies in Epidemiology (MOOSE) guidelines via two independent reviewers. Consultation with a senior investigator was carried out with consensus to resolve any remaining discrepancies.The inclusion criteria of the current systematic review and meta‐analysis were as follows: (1) studies conducted in human; (2) designed as a prospective cohort study; (3) plasma or serum trimethylamine N‐oxide level was evaluated at baseline; (4) major cardiovascular events  or all‐cause mortality were reported as the end‐points; (5) hazard ratios (HR) with confidence intervals (CI) were reported or could be estimated as for the association between baseline TMAO and CVEs. We excluded studies that are narrative reviews, animal experiments, case reports or present insufficient data for pooling. Studies without adjustments for confounding factor, including age, gender, eGFR, N‐proBNP or traditional CVD risk factors, were also excluded. The database searching and subsequent review of the literatures were performed Surname of the first author, country of origin, year of publication, sample size, research design, gender, age, follow‐up period, serum TMAO, disease outcome, adjustment variables, HRs  with their corresponding 95% CIs were extracted for each potentially included study. Outcome assessed in the meta‐analysis included risk of CVD, all‐cause mortality and major adverse cardiac and cerebrovascular event (MACCE) including congestive heart failure (CHF), MI, death due to cardiac causes, stroke and cardiac transplantation. Two independent investigators extracted the data using a pre‐designed data extraction form. Divergences were resolved by consensus or consulting a senior investigator.Newcastle–Ottawa Scale Q test and quantified using the I2 static. Random‐effects model was applied for all meta‐analyses in spite of those with fewer than five studies, for which both fixed‐effect and random‐effects models were used to calculate pooled HRs. Fixed‐effect model was also used when heterogeneity was absent (I2 = 0%). We explored potential sources of heterogeneity via subgroup analysis by study population, sample type, country of origin, follow‐up duration and year of publication. A meta‐regression model fitted with co‐variables including study population, sample type, country of origin, follow‐up duration and year of publication was analysed to explore potential sources of heterogeneity. In sensitivity analysis, the influence of each single study on overall estimates was evaluated. To assess the influence of new studies on overall effects, we performed cumulative meta‐analysis according to the year of publication for individual studies. Publication bias and selective reporting were examined by visual inspection of the asymmetry of funnel plot, in which the standard error of log HR was plotted against HR. Egger's and Begg's linear regression tests were conducted to determine statistical significance P value <0.05 was considered with statistical significance.HRs and their corresponding Cis were used to evaluate the risk of cardiovascular outcome for patients with the highest quartile as compared with the lowest quartile of TMAO levels. The definitions of quartiles of baseline TMAO were in consistent with the original definition of the literatures. Heterogeneity among studies was evaluated using the Cochran's Totally, 400 records from Embase and PubMed databases were retrieved. After removing 160 duplicates, the remaining 240 records were further examination for the titles and abstracts. Among these papers, 207 are not associated with the theme and six are not prospective studies. Full‐text review further excluded 16 articles, yielding a sum of 11 studies for the meta‐analysis.Of these studies, five presented odds ratio (OR) The detailed characteristics of the 11 prospective studies published from 2013 to 2017 are shown in Table I2 = 31.4%, P = 0.212; Fig. P = 0.497) and Begg's tests (P = 0.806).Five prospective cohorts with a total of 8139 participants reported HRs for the association between baseline TMAO and CVEs risk I2 = 80.8%, P < 0.001)  increase of overall mortality in CAD patients, but not in patients with CKD or HF . In addition, elevated TMAO was associated with increased mortality risk in studies with plasma samples , but not in studies with serum samples . Additional subgroup analyses showed similar increases of mortality risk in studies with different follow‐up periods . As all included studies in this meta‐analysis have been published within 5 years, we checked whether the year of publication affected the pooled HR by cumulative analysis . Fitting other variables, including country of origin, follow‐up years, sample types and population, into the meta‐regression model did not indicate additional sources of heterogeneity  and Begg's (P = 0217) regression tests did not show significant bias in publication  for the association between TMAO (lowest vs. highest category) and CVD risk in different populations.Fig. S3 Cumulative analysis for baseline TMAO level and death (a) and CVEs (b).Fig. S4 Sensitivity analysis for TMAO level and death (a) and CVEs (b).Fig. S5 Egger linear regression test and Begg's test plot with 95% CIs for the relationship between baseline TMAO level and death risk.Fig. S6a Risk of bias graph: review authors’ judgements about each risk of bias item presented as percentages across all included studies.Fig. S6b Risk of bias summary: review authors’ judgements about each risk of bias item for each included study.Click here for additional data file.


TGF-β1) gene on chromosome 19 modify the risk for chronic obstructive pulmonary disease (COPD). However, results from previous studies are contradictory. We therefore conducted a meta-analysis of published case–control studies on the association between five common TGF-β1 polymorphisms  and COPD risk. Data sources were Pubmed, Scopus, ISI Web of Science, China National Knowledge Infrastructure (CNKI), and Wanfang databases. Twelve studies including 6749 participants were reviewed and analyzed. For the TGF-β1 polymorphism rs1982073, the results indicted that the C allele was associated with decreased risk of COPD in Caucasians (odds ratio (OR) =0.79, 95% confidence interval (CI): 0.64–0.99, P=0.038) but not in Asians . No associations with COPD were identified for other polymorphisms evaluated in the present study including rs1800469 , rs2241712 , rs6957 , and rs2241718 . In conclusion, this meta-analysis showed that the C allele of rs1982073 was protective against COPD in Caucasians but not in Asians, whereas there was no association of rs1800469, rs2241712, rs6957, and rs2241718 with COPD.It has been hypothesized that polymorphisms in the transforming growth factor-β1 ( TGF-β1 gene located in chromosome 19q13.1-q13.3. A number of studies have assessed the relation of single nucleotide polymorphisms (SNPs) in the TGF-β1 gene with COPD; however, results have been controversial and the contribution of these SNPs to COPD risk remains unclear [Chronic obstructive pulmonary disease (COPD) is characterized by persistent progressive airflow limitation, chronic inflammation of the airways, and systemic effects or comorbidities. Genetic factors play a role in COPD susceptibility but are poorly understood . Transfo unclear –17. To cWe adopted the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines for our meta-analysis. Literature searches were conducted to identify relevant studies in the following sources: PubMed, Scopus, ISI Web of Science, China National Knowledge Infrastructure (CNKI), and Wanfang databases until 25 April 2017. The following terms were used in the search string: ‘chronic obstructive pulmonary disease’, ‘COPD’, ‘transforming growth factor-β1’, ‘TGF-β1’, ‘polymorphism’, ‘genetics’, and ‘association study’. The literature was screened and selected for eligibility and inclusion on the basis of title, abstract and keywords by two independent reviewers. Disagreements were resolved by consensus. When a title/abstract could not provide us with enough information for study selection, the full text of the publication was evaluated. To further identify potentially relevant studies missed by the electronic database search, the bibliographies of relevant meta-analyses and reviews were hand searched. When two similar studies were reported from the same institution or author, the study with the largest dataset was included in the meta-analysis. We did not apply for ethics approval in that we only utilized previously published data.TGF-β1 polymorphisms with COPD, (iii) providing information on genotypic or allelic frequency for the TGF-β1 polymorphisms in both COPD patients and control subjects, and (iv) genotype distribution in the control group was in agreement with Hardy–Weinberg equilibrium (HWE) expectations. Criteria for exclusion were as follows: case reports, editorials, review articles, meeting abstracts, familial-based studies, and animal studies.Our meta-analysis included genetic association studies fulfilling the following inclusion criteria: (i) study design: case–control studies, (ii) investigating the association of the TGF-β1 polymorphisms in cases and controls. Disagreement between the reviewers was resolved by discussion. The Newcastle–Ottawa Scale (NOS) was used to assess the quality of each study [Two reviewers were involved in data extraction in a predetermined database. The following data were extracted from each study: first author, year of publication, country, ethnicity, and genotypic or allelic distribution of the ch study . Includech study .Z-test was used to calculate the P-value of the overall effect for the meta-analysis and P<0.05 was considered statistically significant. Included studies were tested for between-study heterogeneity using the chi-square test, with significance set at P<0.10 [Quantitative meta-analysis was performed using STATA version 11.0. The odds ratio (OR) was used as a summary statistic. We calculated four crude unadjusted ORs and their corresponding 95% confidence intervals (CIs) for each study: (i) dominant OR, (ii) recessive OR, (iii) homozygote OR, and (iv) allele contrast OR. A DerSimonian and Laird random effects meta-analysis model was used to estimate the pooled effect sizes in case of substantial between-study heterogeneity . In thist P<0.10 . We exclt P<0.10 .TGF-β1 gene with COPD. Three hundred and sixty-nine (n =369) unique papers were retrieved from searching five major databases . Study characteristics and methodological quality of included studies are presented in In the present meta-analysis, we aimed to evaluate the relation of five common SNPs  in the atabases . After sTGF-β1 rs1982073 polymorphism. By pooling these nine studies, meta-analysis showed no association between this polymorphism and COPD risk in all the subjects (Caucasians and Asians) in dominant , recessive , homozygote , and allelic comparison  models (P=0.038)  models . HoweverP=0.038) . We did P=0.038) .P=0.398), recessive , homozygote , and allelic comparison  models  models . Similar) models .Between-study heterogeneity was identified in the pooled analyses of rs1982073, rs2241712, rs1800469, and rs6957, but not in those for rs2241718 . The DerTGF-β1 SNPs rs1982073, rs1800469, rs2241712, rs6957, and rs2241718 with COPD in populations of different origins. The main findings of our study are the following: (i) the C allele of rs1982073 is associated with decreased risk of COPD in Caucasians, whereas there is no association between rs1982073 and COPD risk in Asians; (ii) the TGF-β1 polymorphisms rs1800469, rs2241712, rs6957, and rs2241718 are not associated with COPD risk.We carried out a meta-analysis of published data on the relation of the TGF-β1 polymorphisms and found that there was an association of rs2241712 and rs6957 with COPD risk using a small number of subjects. However, these results were not confirmed by our meta-analysis including more eligible studies. For evaluating rs1982073, Smolonska et al. [TGF-β1 polymorphisms with COPD; the number of SNPs was the largest amongst all meta-analyses on this topic.The results of rs1982073 in the present study were not consistent with two prior meta-analyses which showed that the C allele of rs1982073 was associated with decreased risk of COPD in both Caucasians and Asians . Our meta et al.  combinedLTBP-4 gene developed severe pulmonary emphysema owing to a reduced deposition of TGF-β1 in the extracellular space [TGF-β1 polymorphism rs1982073 is a C→T substitution, resulting in a proline to leucine substitution at codon 10 [TGF-β1 mRNA and protein levels [TGF-β1 is a multifunctional cytokine which regulates cell proliferation and differentiation, immune responses, and production of collagen and other extracellular matrix proteins. Animal studies have shown that mice with abnormalities in the activation and signaling of TGF-β1 develop pulmonary emphysema through increased expression of the extracellular macrophage metalloproteinase Mmp12 in the lung . The latar space . Moreovear space . These scodon 10 . It was n levels ,35. ThusTGF-β1 polymorphisms with lung function in COPD patients and disease severity, because there were not enough published studies in this field. The study by van Diemen et al. [TGF-β1 polymorphisms were associated with forced expiratory volume in 1 s (FEV1)/inspiratory vital capacity (IVC) in patients with COPD, suggesting that the severity of airway obstruction was genetically influenced by the TGF-β1 polymorphisms. Future studies are needed to validate their findings in different populations. Second, gene–gene interaction was not investigated in this meta-analysis because most included studies did not address this issue. Third, we only included common TGF-β1 SNPs assessed in more or equal than three studies. Other TGF-β1 SNPs, such as rs1800471 and rs1800468, were not evaluated in this meta-analysis due to the limited availability of published results. Fourth, we did not conduct stratified analysis to adjust for smoking due to limited availability of published data.The present study has potential limitations. First, we did not assess the relation of the n et al. , found tIn summary, we found that the C allele of rs1982073 was associated with decreased risk of COPD in Caucasians, but not in Asians. There was no association of rs1800469, rs2241712, rs6957, and rs2241718 with COPD risk.


Several studies addressed the association of autoimmune regulator (AIRE) gene polymorphism with the risk of rheumatoid arthritis (RA); however, their conclusions were inconsistent. For better investigating the effects of this polymorphism on the risk of RA, we conducted this study to evaluate the role of AIRE rs2075786 polymorphism in the risk of RA. Four eligible studies involving 6,755 cases and 7,970 controls were identified by searching the databases of PubMed, CNKI and EMBASE up to February 2017. Our study revealed that AIRE rs2075786 polymorphism was associated with an increased risk of RA under all genetic models. In the subgroup analysis, AIRE rs2075786 polymorphism contributed to RA susceptibility among Asians, but not among Caucasians. To summarize,, this meta-analysis confirms that AIRE rs2075786 polymorphism may play a significant role in increasing the risk of RA. Stratification analysis by ethnicity reveals that AIRE rs2075786 polymorphism is associated with an increased risk of RA among Asians, but not among Caucasians. These findings need further validation in the large multicenter case-control studies. Rheumatoid arthritis (RA), is a chronic inflammatory autoimmune disease in which hyperplasia, hypertrophy and angiogenesis of synovial tissue contribute to inflammatory joint destruction . In induet al. found significantly lower levels of AIRE expression were associated with the development of thymoma-related autoimmune diseases [et al. found that downregulation of AIRE by genetic polymorphisms may trigger auto-inflammation in RA [The autoimmune regulator (AIRE) gene is located in the 21q22.3 region, and is 12.5 kb in length, and contains 14 exons that encode a 545 amino acid protein of 58 kD , 7. AIREon in RA .Over 100 mutations in the AIRE gene have been reported in the Human Gene Mutation Database, varying from single nucleotide substitutions to large deletions spread out across the coding sequence. AIRE gene polymorphism has been studied in various autoimmune disease, such as Graves’ disease , type 1 70 articles were retrieved after initial search. The selection process of eligible articles is shown in Figure P < 0.001, Figure P = 0.002, Figure In the overall analysis, AIRE rs2075786 polymorphism showed positive correlation with RA risk and could be viewed as a risk factor of RA under five models  and heterozygous models , which may have effects on our results. Subgroup analyses and sensitivity analysis were conducted to uncover the source of heterogeneity. Due to limited studies in this meta-analysis, we cannot undertake the meta-regression. Unfortunately, we did not detect ethnicity and HWE status were account for high heterogeneity. However, sensitivity analysis indicated our data were stable and robust.High heterogeneities were observed in the dominant  have been identified by hand screening.Eligible studies conformed to the following criteria: (1) investigating the relationship between AIRE rs2075786 polymorphism and risk of RA; (2) sufficient data for calculating the pooled odds ratio (ORs) with 95% confidence interval (CI); (3) case-control studies; (4) studied on human beings. Exclusion criteria were as follows: (1) duplicate studies; (2) lack of enough genotype data or data for calculating genotype distribution; (3) not case-control studies; (4) case only studies.Two investigators reviewed and extracted data independently in accordance with the inclusion criteria. From each study, the following information was extracted: name of first author, publication year, country of origin, ethnicity, numbers of cases and controls, and cancer type. When studies included subjects of more than one ethnicity, genotype data were extracted separately. The Newcastle-Ottawa Scales (NOS) were used to assess the quality of the selected studies . The disP < 0.05 was considered statistically significant. Taking possible between-study heterogeneity into consideration, we considered the presence of significant heterogeneity at the 10% level of significance and values of I2 exceeding 50% as an indicator of significant heterogeneity. When no heterogeneity was found with P > 0.10 or I2 < 50%, a fixed-effect model was used. Otherwise, a random-effects model was applied [2 test. Publication bias was evaluated by visual inspection of symmetry of Begg's funnel plot and assessment of Egger's test [P < 0.05 was regarded as representative of statistical significance.All statistical analyses were performed using the Stata 11.0 software . Pooled ORs with corresponding 95% CIs were calculated to evaluate the strength of relationship between AIRE rs2075786 polymorphism and risk of RA. Stratification analyses were carried out by ethnicity and HWE.  applied . Sensitir's test ; P < 0.0


DAZL) gene and male infertility risk, but with inconsistent results. We aimed to derive a more precise estimation of the relationship, therefore a meta-analysis was performed. A total of 13 case-control studies, including 2556 cases and 1997 controls, were selected. Two polymorphisms in DAZL were investigated, namely T12A (Thr12 → Ala) and T54A (Thr54 → Ala). Our meta-analysis showed that A > G is a risk factor for male infertility . However, when using trial sequential analysis (TSA) to confirm, we found that A > G risk effect turned out to be false positive. In addition, significant association was found between the T54A polymorphism and male infertility under co-dominant model  and dominant model . Stratified analysis showed that significantly strong association between T54A polymorphism and male infertility was present only in Asians, but not in Caucasians. Further studies of T12A and T54A with their biological functions are needed to understand the role of these polymorphisms in the development of male infertility.Several studies have investigated the association between polymorphisms in the Deleted in AZoospermia-Like ( Globally, around 15% of heterosexual couples suffer from inability to conceive their own child without any assistanceDAZL (deleted in azoospermia-like) is an autosomal homologue of the DAZ (deleted in azoospermia), a gene cluster which gets deletions in at least 10% of males with azoospermia or oligozoospermia567DAZL has always been seen as a promising candidate for male infertility. Although varies in detail, studies aiming at DAZL expression share the same point: DAZL plays an important role in the human spermatogenic processes and might function as a translational activator through regulating mRNA expression91011Dazl null background, either carrying human DAZL or human DAZ shows a partial rescue of the Dazl knockout mice. Although the mice remain infertile, both transgenes enable prophase spermatocytes to be producedDAZL polymorphisms and male infertility in diverse populations. Among them, two non-synonymous single nucleotide polymorphisms (SNPs) at nucleotide position 260 (exon 2) and 386 (exon 3), resulted by the amino acid exchange T12A (Thr12 → Ala) and T54A (Thr54 → Ala) respectively, are most frequently studied151617181920212223242526Recently, a number of molecular epidemiological studies have been conducted to examine the association between Through the literature search and selection based on inclusion criteria, 13 articles were identified by reviewing potentially relevant articles . The chaT12A polymorphism: A total of 10 studies were included in the meta-analysis with 2174 cases and 1594 controls. The number of cases included in the studies varied from 92 to 660, with a mean (± SD) of 217.40 (±163.16), and the number of controls varied from 40 to 350, with a mean (± SD) of 159.40 (±89.67).T54A polymorphism: In total, twelve studies met the inclusion criteria and were selected for the meta-analysis including 2456 cases and 1897 controls. The number of cases included in the studies varied from 71 to 660, with a mean (± SD) of 204.67 (±151.70), and the number of controls varied from 40 to 350, with a mean (± SD) of 158.08 (±85.35).T12A polymorphism and male infertility risk is summarized in T12A polymorphism and male infertility under dominant model and recessive model . However, we found that when companied with AA genotype, AG is significantly associated with male infertility . Furthermore, in the subgroup analyses based on ethnicity and case types, no significant association was found between the T12A polymorphism and male infertility in the Caucasian group , Asian group , azoospermia group  and OAT group .The evaluation of the association between T54A polymorphism and male infertility risk is summarized in T54A polymorphism and male infertility under co-dominant model  and dominant model . To clarify the potential ethnic difference, subgroup analysis by ethnicity of study population was also conducted. Significant association was found between T54A polymorphism and the risk of male infertility in the subgroups of Asians under co-dominant model  and dominant model . While no such conclusion can be found in Caucasian group under co-dominant model  and dominant model .The evaluation of the association between T12A, the shape of the funnel plot did not reveal any evidence of obvious asymmetry . For T54A, Egger's test revealed the existence of significant publication bias and small-study effects .Begg's funnel plot and Egger's test were performed to assess the publication bias of literatures. For symmetry . MoreoveT12A under co-dominant model by omitting one study at a time in the calculation of the summary outcome. The results showed that no study fundamentally changed the relationship between T12A and risk of male infertility. As for T54A, although the sample size for cases and controls in all eligible studies varies, the corresponding pooled ORs were not qualitatively altered with or without any study , but failed to cross the trial sequential monitoring boundaries for harm (inward sloping red lines). Neither did the cumulative Z-curve reach the trial sequential monitoring boundaries for futility. Within the set assumptions for confidence and effect size, we found that in T12A the A > G risk effect turned out to be false positive. As for T54A, the positive result was confirmed . However, when using trial sequential analysis (TSA) to confirm, we found that A > G risk effect turned out to be false positive. Our analysis suggests that further exploration of the true association between DAZL polymorphism and male infertility is demanded.Spermatogenesis is a complex process of mitotic and meiotic divisions of germ cells finally resulting in the formation of haploid spermatozoaT54A polymorphism and male infertility risk is replete with small studies that report controversial findings. No clear consensus has been reached and there is no meta-analysis. Only in Taiwanese population T54A polymorphism do pose a significant difference between case and control group. We have the following assumptions: firstly, the studies from mainland China with a relatively small sample size (average of 171 cases and 89 controls) might lack of adequate power to draw a fair conclusion. Inconsistent associations in Caucasian data indicate that there may be differences in the magnitude of the contribution to male infertility susceptibility by ethnicity. Secondly, the progress of male infertility has long been seen as the outcome of the interaction between gene and environmentDazl-knockout mice. The findings suggest DAZL's interactions with environment is essential in protecting male germ cells from heat stressDAZL can be explained when taking interaction into account. Thirdly, apart from interactions, SNPs' joint effects and DAZL haplotypes should also be considered. An individual with a clinical disorder is not the product of the single gene that is disrupted, but that the genetic disruption is embedded within the context of that individual's entire genomeDAZL haplotypes and human spermatogenic failure2334DAZL and DAZL's role of epigenetic mechanisms in male infertility should be taken into future studieset al.DAZL promoter is found to be closely associated with oligozoospermiaThe literature on the relationship between DAZL has a relationship with male infertility, but the exact molecular mechanisms of how the variant T54A (located on exon 3) affects male infertility is unknown. In order to explore the probable mechanisms, a secondary structure of the DAZL mRNA sequence prediction was performed, using RNAfold (http://rna.tbi.univie.ac.at/cgi-bin/.RNAfold.cgi)T54A polymorphism might affect the stability of the RNA or the interaction of the RNA with other macromolecules.Our meta-analysis suggests that However, some limitations need to be addressed in our meta-analysis. Firstly, some studies with small sample size may not have enough statistical power to explore the real association and are thought to be more likely to report larger beneficial effects than large trialsT12A polymorphism and male infertility is demanded. At the same time, significant associations were found between the T54A polymorphism and male infertility under co-dominant model and dominant model. Concerning male infertility with multifactorial etiology, more studies with a large sample size and stratified by different ethnic background, environmental exposure or other risk factors are needed to be performed to clarify the possible roles of DAZL polymorphism in the pathogenesis of male infertility in the future.In conclusion, our meta-analysis suggested that further exploration of the true association between http://www.cnki.net), VIP (http://www.cqvip.com), and WanFang (http://www.wanfangdata.com.cn)]. The following searching phrases were used: (DAZL or deleted-in-azoospermia-like) and (polymorphism or polymorphisms) and male infertility. Data from single reports were extracted and summarized in We systematically collected published studies from 2002 to 2014 by searching both the common English database (PubMed) and the Chinese literature databases . Taking consideration of possible between-study heterogeneity, a statistical test for heterogeneity was performed. If the P value for heterogeneity was >0.10 and I2 < 50%, indicating an absence of heterogeneity between studies, and we used the fixed-effect model to evaluate the summary OR. In contrast, if the P value for heterogeneity was ≤0.10 or I2 ≥ 50%, indicating a high extent of heterogeneity between studies, and we used the random-effect model to evaluate the summary OR. A fixed-effect model using the Mantel-Haenszel method and a random-effects model using the DerSimonian and Laird method were used to combine values from studies. Begg's and Egger's test and funnel plots were utilized to provide a diagnosis of publication bias and small-study effects (linear regression asymmetry test). Due to the lack of polymorphism, several trials report zero events in both infertility and control groups. Exclusion of these trials could inflate the size of pooled treatment. To compensate for this we applied a continuity correction of 0.5 in zero-event trialsAll statistical analyses were carried out using STATA 12.0  and A novel statistical analysis software, TSA , can adjust the threshold for statistical significance according to the quantified strength of evidence and the impact of multiplicity. A meta-analysis may result in type I errors and type II errors if data are sparse or if there is repeated testing for significance when new trials are added45To minimize the risk of type-I errors, TSA program was used. TSA combines conventional meta-analysis methodology with meta-analytic sample size considerations  and methods for repeated significance testing on accumulating data in trials. Recent studies show that TSA has the potential to make conclusions more reliable than those traditional meta-analyses45supplementary information