CCR5) gene polymorphisms have been proposed to play important roles in tumors. Δ32 polymorphism of this gene might correlate with breast cancer (BC) susceptibility. Nevertheless, inconsistent conclusions have been achieved as yet. We carried out this meta-analysis to draw a more comprehensive and convincing conclusion on this issue.Chemokine C-C motif receptor 5  or subgroup analyses by ethnicity and control source.No significant correlation of CCR5 Δ32 polymorphism and BC susceptibility was evaluated using pooled odds ratios (ORs) with their corresponding 95% confidence intervals (95% CIs). To further detect their correlation in specific populations, subgroup analyses were performed based on ethnicity and control source. Sensitivity analysis was conducted in this meta-analysis to test statistical stability of the final results. Publication bias among included studies was inspected with Begg’s funnel plot and Egger’s test.All eligible studies were searched from electronic databases including Chinese National Knowledge Infrastructure (CNKI), PubMed, EMBASE, and Google Scholar Web. Strength of association between CCR5 Δ32 polymorphism may not independently affect the risk of BC. Breast cancer (BC) is the most frequently diagnosed malignancy among women around the world, and its incidence rate has been increasing globally, especially in developed countries compared with developing ones , 2. WithCCR5 gene, some polymorphisms have been identified, and among them, the Δ32 polymorphism has been reported to affect the severity of multiple autoimmune and infectious diseases through mediating inflammatory responses [Chemokines are a class of small cytokines which could be categorized into four subfamilies, namely the CXC, CC, C and CX3C chemokines. Chemokines take part in immune cell trafficking during inflammatory responses through interacting with chemokine receptors on the surface of immune cells , 13. As esponses .CCR5 Δ32 polymorphism on BC susceptibility has been explored in previous studies among different populations, but the number of these researches was relatively small. We therefore performed this meta-analysis to more systematically explore this issue.The influence of CCR5 Δ32 polymorphism (41), being summaries or letters (6) or genome wide association studies (5), without a case-control design (3) or having usable data (6). Ultimately, a total of 6 eligible studies recruiting 1839 participants were incorporated into the present meta-analysis [Literature search strategy initially identified 97 potentially relevant publications from the databases, and 4 of them were firstly removed for being duplicates Figure . During analysis . Among torphism 4, being sCCR5 Δ32 polymorphism showed no correlation with the risk of BC under the genetic models of Δ32 vs. WT and WT/Δ32 vs. WT/WT , so the fixed-effects model was employed for ORs calculation.Q test revealed no significant heterogeneity among included studies , confirming the statistical stability and robustness of our findings.P=0.307), which demonstrated that the publication bias was negligible.In the investigation of potential publication bias, none of the funnel plots was found to be asymmetrical through visual check Figure , and theIn spite the pathogenesis of BC is not definite, documents demonstrate that various factors participate in the onset of BC –26. Besi2+ and activate protein kinases C, thus regulating the migration and proliferation of immune cells [CCR5 mainly distributed in various immune cells and endothelial cells, and is regarded as the specific surface marker for Th1 cells . After cne cells . The Δ32ne cells . A similne cells . Howeverne cells –20. ConsCCR5 Δ32 polymorphism and BC risk, and found no evidence for significant correlation between them in both the overall analysis and subgroup analyses according to ethnicity and control source. As could be known, our conclusions were inconsistent from those of some previous studies. Reasons for the discrepancy may include the following aspects. To begin with, the selection criteria of participants were not the same, so other potential risk factors for BC such as ethnicity and BC family history might statistically differ. Next, the sample size of some studies was relatively smaller, which might weaken the statistical power of final results. Also, in some studies, the Δ32 polymorphism had interactive effects on BC together with other genetic variants, which meant that those variants might interfere with the independent role of Δ32 polymorphism. This conclusion was contrary to that from a previous meta-analysis by Lee et al. [In this meta-analysis, we statistically synthesized findings from several eligible case-control studies involving the association between e et al. , in whicCompared with the above-mentioned studies, our meta-analysis has the advantages of a greater sample size and more comprehensive analyses by dividing the subjects into different subgroups on the basis of ethnicity and source of control. However, some aspects might affect the accuracy of our findings, such as the relatively small number of included studies, the lack of further subgroup analyses based on age, smoking status and other risk factors, as well as the absence of consideration of potential collective effects of our studied polymorphism with other relevant elements on the risk of BC. Therefore, the outcomes from the present study still need to be applied with prudence.CCR5 Δ32 polymorphism has independent influences on individual susceptibility to BC. Nevertheless, these results are required to be further verified by studies with larger sample size in future.In conclusion, our findings do not support the assumption that A systemic search was conducted in the databases of PubMed, EMBASE, Google Scholar Web and CNKI for all relevant papers published in English or Chinese language, using the combination of the following keywords: “chemokine C-C motif receptor 5” or “CCR5” or “CD195”, “breast cancer” or “breast carcinoma” or “mammary cancer”, and “polymorphism” or “mutation” or “variant”. To maximize the number of included studies, the references of relevant articles were all manually checked to supplement the yield of database searching.CCR5 Δ32 polymorphism and BC risk; (3) using validated genotyping method; (4) stating sufficient information on genotype and/or allele distribution both in case and control groups; and (5) focusing on human beings. Papers failing to meet any one of the above standards were eliminated from the present meta-analysis. Besides, excluded publications also contained letters, commentaries, case reports and review articles. If more than one article included the same group of participants, the one with the largest sample size or published most recently was selected.Every included report must conform to the following criteria: (1) with a case-control design; (2) assessing the relationship between P value for Hardy-Weinberg equilibrium (HWE). Cross-check of each item extracted from the eligible studies was completed by these two investigators to guarantee the accuracy of the data. If any discrepancies occurred, they would be settled through discussion between the two investigators until reaching a consensus.Two investigators independently extracted primary information from all eligible studies using the same data table. Information to be recorded contained the following aspects: first author’s name, publication year, original country, ethnic descent, number of cases and controls, control source, genotyping method, frequencies of genotypes and/or alleles in cases and controls, and CCR5 Δ32 polymorphism with BC susceptibility was appraised through calculating odds ratios (ORs) with the corresponding 95% confidence intervals (95% CIs). Between-study heterogeneity was examined with chi-square-based Q test. When P value less than 0.05 represented the existence of significant heterogeneity, the random-effects model was selected to calculate the overall ORs; otherwise, fixed-effects model has been selected. Sensitivity analysis was completed through removing each of included studies in turn and re-calculating pooled ORs to observe the impact on whole results. Additionally, Begg’s funnel plot and Egger’s regression test were both applied to inspect potential publication bias across selected studies. All data syntheses in the present meta-analysis were conducted with STATA 12.0 software .The intensity of the relationship of


However, the estimated hazard ratios of cancer specific postoperative survival are 2.62 (95% CI: 1.67–4.11), 0.72 (95% CI: 0.63–0.83) and 0.66 (95% CI: 0.49–0.89) respectively for underweight, overweight and obesity RCC patients. The risk of hazard ratio decrease 5% for each 1 kg/m2 increment of BMI. In addition, the hazard ratios of postoperative overall survival show a similar tendency. These results indicate an opposite association of BMI with mortality and postoperative survival in renal cell cancer patients.Obesity is one of the major risk factors of cancer. However, how body mass index (BMI) influences the prognosis of renal cell cancer (RCC) patient is unclear. In this work, we have performed a meta-analysis to elucidate the role of abnormal weight in RCC mortality and postoperative survival. Articles related to BMI and RCC mortality as well as postoperative survival has been identified by searching PUBMED and ENBASE. Totally, 19 articles have been selected for this meta-analysis, 5 articles for RCC mortality and 14 for postoperative survival. Compared to normal weight, the estimated relative risks of RCC mortality are 0.71 (95% CI: 0.34–1.49), 1.19 (95% CI: 1.05–1.35) and 1.71 (95% CI: 1.27–2.00) respectively for the underweight, overweight and obesity patients. The risk of RCC mortality increase 5% for each 1 kg/m Cancer is one of the major causes of death in the world and an estimated 12.7 million new cancer cases occur annually, of which approximately 271,000 is new cases of kidney cancer . ObesityWe conducted a literature search of PubMed and Embase database as well as hand-searching to 2017/07/30 for studies evaluating the effect of BMI on the risk of RCC mortality and postoperative survival. The studies were searched using the terms “BMI or body mass index or obesity or overweight” matched “mortality, prognostic or survival” and “renal cell cancer/carcinoma or kidney cancer/carcinoma”. And the publication language was restricted to English. We also searched the reference list of eligible articles. Only the most recent and informative one was included if several articles based on one data.The criteria of studies included in this meta-analysis were set out as: (i) the exposure of interest should be BMI, weight, obesity or underweight; (ii) the outcome of interest should be mortality or postoperative survival; (iii) articles should report BMI categories and risk estimates with responding 95% CIs, or have sufficient information for us to calculate them.All the articles were analyzed independently by two investigators. Data extracted by one and checked by two. And discrepancies were discussed by all investigators until consensus was reached. The following information were extracted from each articles included: the first author’s name, publication year, country, mean age or median age and the range, follow-up year, study size, number of cases Table , BMI catWe assessed the methodological quality of the articles included rely on the Newcastle-Ottawa Scale Star (NOS) system . It asseFor different BMI levels, we conducted separate meta-analysis . For eac2 increment). And a p value for nonlinearity was calculated by testing the null hypothesis that the coefficient of the second spline was equal to zero [For dose-response analysis, a two-staged random-effects dose-response meta-analysis  was perf to zero . And the to zero .p values were 2-sided. p < 0.05 was regarded as statistically significant.All the statistical analysis was performed by using Stata SE 12 for Windows . And all 5244 citations were identified from PUBMED and EMBASE, of which 243 duplicative ones were excluded after reviewed. Figure The main characteristics of the studies are shown in the Table 2 = 40.2%, P = 0.154).The association of BMI and RCC mortality was shown in Figure 2 increment in BMI was associated with a 5% higher risk of mortality in RCC patients (RR: 1.05 (1.03–1.07) P = 0.000).In addition, a dose-response meta-analysis including 5 articles –25 was p2 = 65.0% P = 0.009).The combined hazard ratio (HR) of CSS were 2.62 (95% CI: 1.67–4.11), 0.71 (95% CI: 0.62–0.82), 0.66 (95% CI: 0.49–0.89) respectively for the category of underweight, overweight and obesity based on random-effect models  P = 0.001).For the dose-response meta-analysis, 6 articles were included , 34–36. P = 0.021)  time than normal weight patients (HR: overweight: 0.76 (95% CI: 0.61–0.95); obesity: 0.57 (95% CI: 0.34–0.97))  and 0.43  for CSS and OS in the obesity category.We conducted the meta-regression analysis to investigate whether the association between BMI and RCC postoperative survival is modified by study location, publication year, follow up and sample size. We found that the study location can explain 62.8% and 100% heterogeneity for CSS and OS in the obesity category. For the Asia, the combined HR were 0.44  in RCC population. The mechanism by which obesity may increase RCC mortality is not well studied , althougOn the other hand, it was reported that people without surgery-treatment have a significantly shorter survival time than surgical patients , 46, 47 2 increment of BMI.A clinical-based cohort and meta-analysis by Choi et al  revealedPreviously, a meta-analysis by Bagheri et al , of whicOn the other hand, BMI and the incidence of RCC had been analyzed by wang et al , whose rThere are some limitations in our meta-analysis. Firstly, abnormal weight was associated with unhealthy diet habit, but the studies included were almost not adjusted for it. Secondly, obesity tends to be accompanied with diabetes, which is also associated with RCC , but theIn conclusion, our meta-analysis indicated that obesity may be associated with high risk of mortality in whole RCC patient but a better survival in surgery-treated RCC patients. Individualized weight control might be necessary for RCC patients.


P = 0.028; Meta-analysis: OR = 0.74, 95%CI: 0.62-0.89, P = 0.001). Patients carrying CT or TT genotypes of XRCC1 C580T could be more sensitive to platinum-based chemotherapy compared to patients with CC genotype . CC genotype of XRCC3 C18067T carriers showed more resistance to platinum-based chemotherapy when compared to those with CT or TT genotypes . Our study indicated that XRCC1 G1196A/C580T and XRCC3 C18067T should be paid attention for personalized platinum-based chemotherapy in NSCLC patients.Published data showed inconsistent results about associations of extensively studied polymorphisms with platinum-based chemotherapy response. Our study aimed to provide reliable conclusions of these associations by detecting genotypes of the SNPs in a larger sample size and summarizing a comprehensive pooled analysis. 13 SNPs in 8 genes were genotyped in 1024 NSCLC patients by SequenomMassARRAY. 39 published studies and our study were included in meta-analysis. Patients with GA or GG genotypes of XRCC1 G1196 had better response than AA genotype carriers (Genotyping study: OR = 0.72, 95%CI: 0.53-0.96,  Lung cancer is a serious health problem in the whole world for many decades with its highest mortality . It is hA number of studies suggested single nucleotide polymorphisms (SNPs) may affect chemotherapy response –9. Most In this study, we investigated the relationships between widely studied SNPs and platinum-based chemotherapy response in a larger NSCLC sample size. We also provided a comprehensive meta-analysis on pharmacogenomics of the platinum-based chemotherapy response. Understanding the genetic variants contributed to platinum-based chemotherapy will provide guide for individualized chemotherapy and benefit for NSCLC patients.A total of 1024 NSCLC patients were enrolled in our genotyping study. They were from Shanghai Chest, Shanghai Zhongshan, or Shanghai Changhai Hospitals  from 2005 to 2010, and Affiliated Cancer Hospital or Xiangya Hospital of Central South University  from 2011 to 2015  and stored at −20C until use. Genotyping was conducted by the Sequenom MassARRAY system .th 2015. Keywords for searching the related publications were platinum  and polymorphism  and lung cancer.We did a systematic literature search in PubMed database, ISI Web of Knowledge and Cochrane Library. The identified articles were reviewed carefully to find more relevant articles. The included articles were published before November 23The inclusion criteria of publications were as follows: (1) studies about platinum-based chemotherapy response; (2) Patients with NSCLC; (3) the data of genotypes in responders and nonresponders could be obtained. Studies were excluded by any one of the following conditions: (1) the data of genotypes could not be provided; (2) articles involved in patients received surgery or radiotherapy.All data were extracted independently by two investigators (JC and ZW) using the same data recording form, but they were blind to each other during the whole extracting process. The discrepancies of the extracted data were discussed and resolved with consensus. The following information were collected from each study: first author's name, publication year, ethnicity, country, sample size, polymorphisms, alleles of the investigated polymorphism, genotyping methods, disease stage, chemotherapy regimen, and the numbers of responders and non-responders in different genotypes.P value was 2 sided, and P < 0.05 was considered statistically significant. The aforementioned statistical analyses were performed by PLINK 1.07 [In our genotyping study, the chi-square and Student t tests were used to determine the differences in sex, age, smoking status and histology between responders and nonresponders. Unconditional logistic regression was performed to estimate the association of the polymorphisms with chemotherapy response by calculating odds ratios and their 95% confidence intervals with adjustments. The association study was analyzed in additive, dominant and recessive models. The INK 1.07  and SPSSP < 0.05. We selected the random-effect model to get the results with a wider CIs if P < 0.05. Otherwise, the fixed-effect model was used to calculate the pooled ORs and P values [2 statistic test was also employed, its values of 25%, 50% and 75%were considered as low, moderate and high heterogeneity respectively [P value was 2 sided, and P < 0.05 was considered statistically significant.In the meta-analysis, the pooled odds ratio (OR) and associated 95% confidence interval (95% CI) were calculated by using the Z test. The genetic model was chosen by logistic regression . The hetP values , 31. To ectively . The pubectively and Eggerectively . All cal1024 NSCLC patients were enrolled in our genotyping study and their clinical characteristics were summarized in Table in vitro studies, 9 were about small cell lung cancer, 7 involved in patients with surgery or radiotherapy, and 1 was duplicated publication. Finally, there were 39 publications and our genotyping study included in meta-analysis. The publications included 13 SNPs in 8 genes . Pooled data showed there was significant relationship between XRCC1 C580T and drug response  , thus we chose fixed-effect model. Pooled data contained 1234 NSCLC patients, 408 were responders and 826 were non-responders. The pooled estimated result showed that this polymorphism was significantly correlated with chemotherapy response   Figure . Patient) Figure . XRCC3 C) Figure .P = 0.026)    and publication bias exist among the studies . Moreover, it was hardy to determine about the association of XPD A2251C with chemotherapy response for its 95%CI was 0.99-1.44. Thus, we made quality assessment about the publications by using quality scoring criteria from Wu's study [P = 0.05)   Figure . Patient) Figure . Patient) Figure . Patient) Figure , and XRC) Figure .The reliability of our meta-analysis results were assessed by the criteria described in In this study, we investigated the associations of widely studied SNPs (13 polymorphisms in 8 genes) with platinum-based chemotherapy response in NSCLC patients. We also conducted a comprehensive meta-analysis of these SNPs. Our results showed that XRCC1 G1196A/C580T, and XRCC3 C18067T were significantly correlated with platinum-based chemotherapy. XPD A2251C, MDR1 C3435T and MDR1 G2677T/A, GSTP1 A313G, XPG G3310C, ERCC1 C354T were correlated to platinum-based chemotherapy response in different subgroups.Platinum-based chemotherapy was widely used for treatment of advanced NSCLC, but pharmacogenomic differences between individuals may affect drug response. In the last several decades, gene polymorphisms were revealed to play an important role in chemotherapy response . TherefoDNA repair was one of the classical platinum resistance mechanism . PolymorTransporters involved in drug resistance by decrease uptake or efflux of the drugs by the proteins known as ATP binding cassette transporters . MDR1 alGSPT1 and CDA were metabolism and detoxification pathway genes. GSTP1 was a member of GST family. It mediates formation of platinum-glutathione adduct  which deWe conducted this study to get comprehensive conclusions about SNPs contributed to platinum-based chemotherapy response in NSCLC patients, but there were several possible limitations. It was unfortunately about the genotyping of XRCC1 C580T and XRCC3 C18067T failed in our samples, thus meta-analyses of these two SNPs were calculated without the results from our genotyping study. In meta-analyses of ERCC1 and MDR1, we did not include the data from the studies by Krawczyk et al.  and Du eIt was our first attempt to evaluate the quality of meta-analysis results. Only ERCC1 C3435T/C8092A, XPD A2251C/G934A, XRCC1 G1196A and XRCC3 C18067T showed high reliability. It means the other SNPs may need more investigations, though most of them showed medium reliability. In conclusion, contributions of XRCC1 G1196A/C580T and XRCC3 C18067T to drug response were further confirmed by our large sample size genotyping study and comprehensive meta-analysis. It is meaningful for personalized platinum-based treatment of NSCLC.


A receptor β2 subunit gene (GABRB2) was associated with SCZ. Other studies reported a negative association. Moreover, the results of two previous meta-analyses of GABRB2 with SCZ were inconsistent and the sample sizes were limited. Therefore, an updated meta-analysis combined with genome-wide association study (GWAS) data of the Han Chinese population and Psychiatric Genomics Consortium (PGC) was performed. Available case–control and family-based genetic data were extracted from association studies, and the GWAS data were included. The findings showed no association between six single-nucleotide polymorphisms of GABRB2  and SCZ in a total of 51,491 patients and 74,667 controls. The ethnic subgroup analysis revealed no significant association in Asian populations. Since the PGC data of SCZ  contained 3 studies of Asian populations (1866 patients and 3418 controls), only the data of European samples in SCZ-PGC were used for the meta-analysis of the Caucasian population in the present study. The result still showed no association in the Caucasian population. In conclusion, the present meta-analysis on combined data from GWASs of the Han Chinese population and PGC suggested that GABRB2 polymorphisms might not be associated with SCZ.Schizophrenia (SCZ) is a severe psychiatric disorder with evidence of a strong genetic component in the complex etiologies. Some studies indicated that gamma-aminobutyric acid (GABA) Schizophrenia (SCZ) is a complex psychiatric disorder affecting approximately 1% of the global population and manifesting as positive symptoms , negative symptoms , and cognitive impairment . As SCZ A and GABAB receptors). GABAA receptors are ligand-gated Cl− channels responsible for most of the physiological actions of GABA  and standard errors (SEs). For family-based studies, the Ln (ORs) and SEs of each study were calculated based on the TDT data ,39. For P value of meta-regression less than 0.05 was considered to have a significant effect. A sensitivity analysis was also applied to evaluate the effect of each study on the combined ORs by omitting each study in each turn. Publication bias was assessed using funnel plots and Egger’s test. A P value less than 0.05 in the Egger’s test indicated significance.Meta-regression was used to investigate the effects of the sample size, study design, and year of publication. The et al. 2017, 4383 patients and 5770 controls; Li et al. 2017, 7699 patients and 18,327 controls). The observed genotype distribution in the controls was consistent with Hardy–Weinberg equilibrium. The detailed characteristics of each study are described in The literature search and article screening procedure are shown in GABRB2 included in most of the related association studies and (2) previously reported positive SNPs in GABRB2 related to SCZ. Therefore, six SNPs of GABRB2  were selected to perform the present meta-analysis with SCZ. Before combining with GWAS data, all six SNPs in GABRB2 showed no significant association with SCZ  and Caucasian populations , but not in the overall population (The SNPs were selected according to the following criteria: (1) SNPs in pulation .P = 0.913, rs1816071: OR = 1.03 95% CI = 0.99–1.07 P = 0.1,93, rs1816072: OR = 1.05 95% CI = 0.98–1.12 P = 0.141, rs194072: OR = 1.01 95% CI = 0.97–1.06 P = 0.684, rs252944: OR = 1.01 95% CI = 0.96–1.05 P = 0.746, rs187269: OR = 1.06 95% CI = 0.94–1.20 P = 0.321; GABRB2 and SCZ .The funnel plot and Egger’s test were used to evaluate the publication bias between studies. The funnel plots for all six SNPs were symmetrical . As a stGABRB2  with the occurrence of SCZ. The findings revealed no association. The ethnic subgroup analysis also showed no association in Asian and Caucasian populations.The present meta-analysis study included a large sample size  to investigate the potential association of 6 SNPs of GABRB2 and SCZ. A possible reason might be the larger sample size used in the present study. Sampling error can be decreased by increasing the sample size of the study. The sample size of the previous two meta-analyses studies was limited. In the present meta-analysis, a total of 51,491 patients and 74,667 controls were included. Therefore, the sampling error was greatly reduced, making the assertion of the study more convincing. The weights carried by PGC samples in this meta-analysis were large. Moreover, the large sample size in GWAS might increase the statistical power to detect common SNP with a minor effect on the pathogenesis of SCZ.Meta-analysis is an effective method to reanalyze multiple independent studies revolving around the same issue and obtain a general conclusion. The results of the present meta-analysis were inconsistent with those of two previous meta-analyses on GABRB2 and SCZ.Furthermore, the risk allele of rs1816072 with SCZ was different in Asian  and Caucasian  populations in the present study. These results were also detected in a previously published meta-analysis. Moreover, the minor allele frequency of rs6556547 was 0.178 in the East Asian population and 0.054 in the European population. It is suggested that subjects with different ethnicity exhibit genetic heterogeneity. Considering the ethnic heterogeneity, subgroup analyses were performed in Asian and Caucasian populations separately. In the present study, after combining data from GWASs in the Chinese Han population and PGC, the results of the subgroup analysis by ethnicity showed no association between GABRB2 SNPs implied the possibility of type II error [The present meta-analysis still had a few limitations. First, the limited number of studies investigating the II error . Second,GABRB2 polymorphisms might not be associated with SCZ.In conclusion, the present updated meta-analysis combined with GWAS Data of Han Chinese population and PGC suggested that S1 Fig(A) Meta-analysis of rs6556547. (B) Meta-analysis of rs1816071. (C) Meta-analysis of rs1816072. (D) Meta-analysis of rs194072. (E) Meta-analysis of rs252944. (F) Meta-analysis of rs187269.(DOCX)Click here for additional data file.S2 Fig(A) Funnel plot of rs6556547. (B) Funnel plot of rs1816071. (C) Funnel plot of rs1816072. (D) Funnel plot of rs194072. (E) Funnel plot of rs252944. (F) Funnel plot of rs187269.(DOCX)Click here for additional data file.S3 Fig(A) rs6556547. (B) rs1816071. (C) rs1816072. (D) rs194072. (E) rs252944. (F) rs187269.(DOCX)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S1 File(DOC)Click here for additional data file.S2 File(DOC)Click here for additional data file.S3 File(DOCX)Click here for additional data file.S4 File(DOCX)Click here for additional data file.


Background and Objective: Controversial results of the association between tea  consumption and risk of bladder cancer were reported among epidemiological studies. Thus, we performed a meta-analysis of observational studies to investigate the association.Methods: We searched the PubMed and Embase for studies of tea consumption and bladder cancer that were published in any language up to March, 2016. Cohort or case-control studies were included in the meta-analysis. All statistical analyses were performed in Stata 12.0 software. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to assess the relationship between tea consumption and risk of bladder cancer.Results: Totally, 25 case-control studies (15 643 cases and 30 795 controls) and seven prospective cohort studies (1807 cases and 443 076 participants) were included. The meta-analysis showed that tea consumption was not significantly associated with bladder cancer risk  (in a comparison of highest vs. lowest category). No non-linearity association was observed between tea consumption and bladder cancer risk (P = 0.51 for non-linearity). Specific analysis for black tea, green tea, and mate yielded similar results. The dose-response analysis showed the summary OR for an increment of 1 cup/day of tea consumption was 1.01 (95% CI 0.97–1.05).Conclusion: Results based on current meta-analysis indicated that no significant association was observed between tea consumption and risk of bladder cancer. Bladder cancer is a very common disease worldwide, accounting for ~429 800 new cases and 165 100 deaths occurred in 2012 worldwide  statement , and adjusted variables. Crude ORs or RRs with 95% CIs were only extracted when no adjusted ORs or RRs were presented. In addition, ORs or RRs with 95% CIs in different smoking status were also extracted for assessing the effect of smoking, which is an important confounding factor for bladder cancer.We performed methodological quality assessment of the included studies using the Newcastle-Ottawa Scale Stang, , which iThe statistical analysis for the overall relationship between tea consumption and bladder cancer risk were based on random-effects model and on comparisons of the highest vs. lowest category of tea consumption . For cohort studies, the pooled OR was 0.88 (95% CI 0.67–1.17), with certain between-study heterogeneity  . For population-based case-control studies, the pooled OR was 1.00 (95% CI 0.91–1.10), with no evidence of between-study heterogeneity .The meta-analysis of all 32 studies, no significant association was observed between high tea consumption and risk of bladder cancer  . Thus, a linear regression model was applied. The summary OR of bladder cancer for an increase of one cup of tea per day was 1.01 . For cohort studies, no non-linearity association was observed (Pnon-linearity = 0.11). The summary OR of bladder cancer for an increase of 1 cup/day of tea was 0.97 . For case-control studies, we found no evidence of a non-linearity association between tea consumption and bladder cancer risk (Pnon-linearity = 0.60). We then used the linear model among case-control studies. The pooled OR of bladder cancer for an increase of 1 cup/day was 1.02 .Four cohort studies . For cohort studies, the combined OR was 1.06 (95% CI 0.75–1.50), with low between-study heterogeneity  . For population-based case-control studies, the combined OR was 0.80 (95% CI 0.62–1.02), with no between-study heterogeneity .Black tea consumption was examined in 3 cohort studies . A linear model was used among these studies. The poled OR of bladder cancer for an increase of 1 cup/day of black tea was 0.89 .Four case-control studies . For cohort studies, the combined OR was 1.20 (95% CI 0.90–1.59), with no heterogeneity  . For population-based case-control studies, the combined OR was 1.04 (95% CI 0.59–1.84).Green tea consumption was assessed in 3 cohort studies . A linear model suggested that the summary OR of bladder cancer for an increase of 1 cup/day of green tea was 1.02 .Two cohort studies   (Figure Results of subgroup analyses had been shown in Table P = 0.43 for Egger's test; Figure P = 0.76 for Egger's test; Figure P = 0.06 for Egger's test; Figure No evidence of publication bias was detected in the tea (In present meta-analysis of seven prospective cohort studies that including 443 076 participants and 25 case-control studies that included 15 643 cases and 30 795 controls, we found that high level of tea intake was not significantly associated with bladder cancer risk. Specific analyses for black tea, green tea, and mate yielded similar results except for oolong tea. Dose-response analyses showed that there was no non-linearity or linearity association between tea intake and bladder cancer risk.There are two concerns to the previously published meta-analysis. For instance, dose-response relationship were left unaddressed and only reported data for the highest vs. lowest comparison in two studies (Zeegers et al., Several limitations should be taken into consideration for our study. First, limitations of observational studies contain the problem of residual confounding that may also extend to meta-analysis of observational studies (Threapleton et al., A major strength of this meta-analysis was the inclusion of observational studies from two main online database searches, identifying published studies from over two decades. The quality of the present meta-analysis was strengthened by assessing the quality of included studies and exploring dose-response relation not only reporting the comparisons of highest and lowest tea consumption. Different type of tea may have different influence. Therefore, we have evaluated the relationship between different type of tea and bladder cancer risk, which was an additional strength. Despite certain between-study heterogeneity was examined, the findings were generally consistent and the most of estimations were less than one. Therefore, drinking tea appears to be safe at habitual use.In conclusion, this meta-analysis, consisting of 25 case-control studies and 7 cohort studies, had indicated that there was no significant association between tea consumption and the risk of bladder cancer. However, certain caution is need in interpreting the results from the present meta-analysis because of potential confounders and misclassification of tea consumption. Further studies with high quality and well-designed large scale are needed to provide more precise evidence.XW, HW, and XZ conceived the study. HW and JK searched the databases and extracted the data. HW, SL, and TL analyzed the data. HW and XZ wrote the draft of the paper. XW reviewed the manuscript. All the authors approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer Q.D. and handling Editor declared their shared affiliation, and the handling Editor states that the process nevertheless met the standards of a fair and objective review.


SRD5A2) may affect the susceptibility of PCa, but some researches showed different results. We therefore carried out a meta-analysis to clarify this relationship.The pathogenetic mechanism of prostate cancer (PCa) has not been understood completely, and gene polymorphisms have been demonstrated to play a critical role in the course. It has been reported that rs9282858 polymorphism of steroid 5-α-reductase type 2 (SRD5A2 rs9282858 polymorphism and PCa. Odds ratios (ORs) with their 95% confidence intervals (95% CIs) were calculated to assess the strength of the association. Additionally, stratified analyses were performed based on ethnicity and source of control. Besides, heterogeneity test, sensitivity analysis, and publication bias evaluation were conducted in current meta-analysis as well.Relevant studies were identified through PubMed and Chinese National Knowledge Infrastructure databases concerning the association between SRD5A2 rs9282858 polymorphism was remarkably associated with increased susceptibility of PCa . After subgroup analyses by ethnicity and source of control, we also observed a similar trend in Latinos, other-ethnicity, population-based, and hospital-based groups under corresponding genetic models.Ultimately, 20 publications incorporating 30 case-control studies were included in this meta-analysis, involving a total of 7300 cases and 7952 controls. The overall results demonstrated that SRD5A2 rs9282858 polymorphism may be a susceptible factor to PCa.Our findings indicate that  It is estimated that there are approximately 238,590 newly diagnosed PCa patients and 29,720 deaths caused by it in America in 2013. Although the occurrence rate of PCa has been at a low level for a long time in China, it is rising significantly in recent years as a result of the changes in dietary structure and environment, making PCa become the third malignancy of male urogenital system in the country nowadays. It is well known that age and race are two of the most important risk factors to PCa.–6 Documents reveal that PCa is rare in men younger than 40 years, but its morbidity increases with age more rapidly than any other cancers in men. As a public security issue all over the world, this malignancy still threatens the health, even life, of aged males in spite of notable improvements in the techniques for the diagnosis and treatment.Prostate cancer (PCa) is the most common malignancy in male reproductive system. The occurrence and growth of PCa are induced by the changes of multiple genes and stimulation from environmental factors. At present, researchers have paid close attention to genetic association studies about the relationships of cancer with oncogenes, tumor-suppressor genes, and other genes involved in hormonal environment.Cancer is essentially a genetic disease, and its genesis and development involve a multistep, multistage, and polygenic process. As is well known, there are 2 main types of androgen in humans and other mammals, namely, testosterone and dihydrotestosterone (DHT).,11 Steroid 5α-reductase can restore testosterone into stronger DHT, which has a significant impact on the growth and differentiation of prostate cells. Two types of steroid 5α-reductase have been identified so far, which are steroid 5α-reductase type 1 (SRD5A1) and steroid 5α-reductase type 2 (SRD5A2). Among them, SRD5A2 is highly expressed in androgen-sensitive tissues, such as prostate and testis. In addition, catalyzing SRD5A2 can remarkably enhance the biological activity of DHT and its affinity for androgen receptor (AR), thereby possibly affecting the onset risk of PCa.Androgen reportedly plays a vital role in the canceration of prostate, so relevant genes involved in biosynthesis and metabolic pathway of androgen may influence the pathogenesis of this malignancy.SRD5A2 polymorphisms on PCa susceptibility during the past decade, but the conclusions remained inconsistent.–15 In this study, we searched all eligible publications to carry out a meta-analysis for a clearer perspective on the association of SRD5A2 rs9282858 polymorphism and the susceptibility of PCa.A large number of researches have been performed to explore the effects of 22.1 The PubMed and Chinese National Knowledge Infrastructure databases were searched for all related publications about the association between SRD5A2 rs9282858 polymorphism and PCa. No language restrictions were imposed on literature search strategy. The keywords applied in searches were “steroid 5α-reductase type 2 or SRD5A2” in combination with “prostate cancer” and “polymorphism or mutation or variation.” Moreover, the references of all pertinent articles were manually checked to identify additional relevant studies. All analyses were based on previous published studies; thus, ethical approval was not necessary for this meta-analysis.This meta-analysis was conducted in accordance with the checklist of the Meta-analysis of Observational Studies in Epidemiology guidelines. The proposed checklist contains specifications for reporting of meta-analyses of observational studies in epidemiology, including background, search strategy, methods, results, discussion, and conclusions.2.2SRD5A2 rs9282858 polymorphism and PCa susceptibility; presenting adequate genotype data for calculating pooled odds ratios (ORs) and 95% confidence intervals (95% CIs). Apart from articles not meeting the inclusion criteria, reviews, meta-analysis, and repeated publications were excluded.Studies included in the meta-analysis were required to fulfil the following criteria: they were designed as case-control studies; assessing the correlation between 2.3P values for Hardy-Weinberg equilibrium (HWE) in controls.Data extraction was completed by 2 investigators independently, and all the information was recorded in a standardized form. The results were compared and disagreements were resolved through discussion to reach a consensus. The following data were gathered from each relevant study: the first author's name, year of publication, original country, ethnicity, control source, genotyping method, numbers of cases and controls, genotype frequencies in case and control groups, and 2.4SRD5A2 rs9282858 polymorphism and PCa susceptibility was examined through crude ORs and 95% CIs under TT vs. AA, TT + AT vs. AA, TT vs. AA + AT, allele T vs. allele A, and AT vs. AA contrasts. Subgroup analyses by ethnicity and source of control were performed subsequently. χ2-based Q-statistic test was employed to explore statistical heterogeneity with P < 0.05 for statistical significance. A quantitative measure of between-study heterogeneity was also investigated using the I2 statistic, and the heterogeneity was defined as low, moderate, and high based on I2 values of 25%, 50%, and 75%, respectively. If significant heterogeneity existed (P < .05), the random-effects model was used to pool overall effects; otherwise, a fixed-effect model was selected. Sensitivity analysis was undertook by excluding each single study in turn to investigate the stability of results. Begg funnel plot and Egger test were adopted to detect any underlying publication bias in the meta-analysis. Finally, the distribution of genotypes in controls was tested for a departure from HWE using χ2 test. All statistical analyses in this study were implemented with STATA 12.0 software .The genetic relationship between 33.1–15,18–34 incorporating 30 case-control studies were included in the meta-analysis, involving a total of 7300 cases and 7952 controls. The selection process and characteristics of eligible studies are displayed in Figure P > .05).In accordance with search strategy, 123 articles were searched from electronic databases originally. Apart from 14 duplicates, another 65 records were also deleted because of reviews (n = 6), without controls (n = 12) and irrelevant to the topic (n = 47), and 24 articles were removed because of republished data (n = 2), unusable data (n = 5), meta-analysis (n = 4), and not involving rs9282858 polymorphism (n = 13). Ultimately, 20 articles3.2SRD5A2 rs9282858 polymorphism and increased PCa susceptibility .After subgroup analysis based on ethnicity, the susceptibility of PCa was notably enhanced in Latinos , so we chose the random-effects model to calculate pooled results. Additionally, after stratification analysis by control source, we observed that studies enrolling controls from hospitals might be the source of significant heterogeneity.As shown in Table P = .159), TT + AT versus AA (P = .068), TT versus AA + AT (P = .127), and allele T versus allele A (P = .074) comparisons, a fixed-effect model was therefore applied.Meanwhile, as no substantial heterogeneity was found under TT versus AA , demonstrating that there was no significant publication bias.As for publication bias, the shapes of all funnel plots seemed symmetrical Fig. , and sta4 Up to now, the pathogenesis of PCa has not been identified utterly, but a few risk factors have been recognized, including heredity, high-fat diet, low intake of isoflavone, and excessive intake of pickled meats.–38 Recently, reduce of copy number in AR gene CAG repeat sequences is also proposed to possibly conduce to the occurrence of PCa.PCa is one of the common diseases in older men, frequently occurring in western countries in particular.SRD5A2 coding for the latter is located at chromosome 2p23, containing 5 exons and encoding 254 oxyacids. Investigations have displayed that SRD5A2 SNPs may change the activity of 5α-reductase, so the rs9282858 polymorphism, among others, has attracted increasing attention from scholars for the past few decades. So far, numerous studies have been conducted on the relationship between SRD5A2 rs9282858 polymorphism and PCa susceptibility, but the conclusions are not unanimous. A few meta-analyses–42 were also conducted to figure out the influence of SRD5A2 rs9282858 polymorphism on PCa susceptibility. However, because of different inclusive criteria and uneven sample sizes, these reports presented different conclusions. Among them, the most recent one was conducted in 2012 based on 17 case-control studies, including 13 in whites, 3 in Asians, and 1 in Africans. Thus, it is of great significance to perform a more comprehensive meta-analysis with the updated publications.Steroid 5α-reductase is a membrane protein in microsomal membrane and nuclear membrane principally, consisting of SRD5A1 and SRD5A2. The gene SRD5A2 rs9282858 polymorphism on PCa in specific populations. In this study, our findings revealed that SRD5A2 rs9282858 polymorphism increased PCa susceptibility under all but one comparison in total analysis. Furthermore, after stratified analyses by ethnicity and source of control, a similar association was also found in Latinos, other-ethnicity, population-based, and hospital-based subgroups under corresponding genetic models. Although in terms of Latino groups the data are distinguished between the studies of Pearce et al and Paz-y-Mino et al, no substantial heterogeneity was found between the studies  is a common polymorphism site in the SRD5A2 gene, which results in an alanine residue at codon 49 being replaced with threonine. Furthermore, in vitro experiments uncovered that the presence of rs9282858 missense mutation could increase the activity of steroid 5α-reductase by 5 times,,33 thereby affecting the onset risk of PCa.This meta-analysis, including 30 independent case-control studies with 7300 cases and 7952 controls, was strictly implemented from literature search to information abstract to data syntheses. Compared to the previous studies, this meta-analysis had several strengths. Most importantly, our relatively larger sample size provided the analysis results with strong statistical power, and subgroup analyses by ethnicity and control source also facilitated a more detailed interpretation of the impact of  we could not evaluate the possible impacts of gene-gene and gene-environment interactions on the pathogenesis of PCa in this work because of the lack of original information.Despite certain advantages, some insurmountable limitations in this meta-analysis should be addressed. First, only published studies were included, and publication bias might have been generated, even though it was not detected in relevant tests. Second, although no language restrictions were imposed on literature search strategy, only articles written in English or Chinese language were finally reviewed. This is because of the language ability and the right to use databases of our team, and also might result in some bias. Third, the sample sizes of subgroup analyses were relatively small, which might affect the accuracy of our results and even the subsequent conclusions. Fourth, since meta-analysis is secondary analysis,SRD5A2 and increased PCa susceptibility. It provides an important theoretical basis to reveal the rs9282858 polymorphism and the biological mechanism of developing PCa, which may be helpful to predict the occurrence of PCa. Importantly, more attention should be paid to the roles of polymorphisms in clinical aggressiveness and therapeutic response in future work. Considering the above-mentioned restrictions, more larger-scale and well-designed studies based on multiple ethnic populations are needed to confirm our results in future.Taken together, the present meta-analysis offers additionally strong evidence for the association between the rs9282858 polymorphism in


The inflammatory potential of diet has been inconsistently linked to colorectal cancer (CRC) risk. This meta-analysis aimed to evaluate the association of the inflammatory potential of diet, as estimated by the dietary inflammatory index (DII) score, with CRC risk.The PubMed and Embase databases were searched for relevant studies from inception to February 2017. All cohort and case–control studies investigating the association of the DII score with CRC risk were selected.Four prospective cohorts and four case–control studies, which enrolled a total of 880,380 participants, were included. The pooled adjusted risk ratio (RR) of CRC for the highest DII score versus the lowest category was 1.43 . When stratified by study design, the RRs for the case–control and cohort studies were 1.27 (95% CI: 1.16–1.38) and 1.81 (95% CI: 1.48–2.22), respectively. Subgroup analysis showed that individuals with the highest category of DII score were independently associated with CRC risk in men , women , colon cancer , and rectal cancer . However, the pooled RR was 1.07 (95% CI: 0.87–1.31) for rectal cancer among the prospective cohort studies.As estimated by a high DII score, pro-inflammatory diet is independently associated with increased CRC risk. This finding confirms that low inflammatory potential diet may reduce CRC risk. However, the gender- and cancer site-specific associations of the DII score with CRC risk need to be further investigated. Colorectal cancer (CRC) is the third most common cancer in males and the second in females, with an estimated 1.4 million cases occurring in 2012 . Diet coSeveral dietary indices, such as the Healthy Eating Index , AlternaTo our knowledge, no previous meta-analysis has addressed this issue. The current meta-analysis aimed to investigate the association between the inflammatory potential of diet, as estimated by the DII score, and CRC risk.Figure 2 =77.6%, p < 0.001) was also noted. Sensitivity analysis showed that any study only slightly affected the pooling effect size and revealed the reliability of our pooling summary. No evidence of publication bias was identified on the basis of Egger's test (p = 0.148) and Begg's test (p = 0.108). The trim-and-fill approach suggested three missing studies in the funnel plot . Results stratified by study design showed a stronger risk of higher DII score for CRC among the case–control studies  than among the prospective cohort studies .All the included studies investigated the association of DII score with CRC risk. The pooled RR for the highest versus lowest DII score was 1.43 (95% CI: 1.26–1.62) under a random-effect model  for women and 1.51  for men under a random-effect model.The results stratified by gender are shown in Figure 2 = 71.3%, p = 0.004) for colon cancer and 1.32  for rectal cancer in a random-effect model  showed a 43% increased CRC risk. This finding supports the notion that low inflammatory potential diets reduce CRC risk.In our subgroup analyses, a more significant association of DII score with CRC risk was noted from the case–control studies than from the prospective cohort studies. However, case–control studies are susceptible to recall or selection bias; hence, additional prospective cohort studies are needed to confirm this finding. When the results were stratified by gender, the association between DII score with CRC risk tended to be stronger in men than in women. The mechanisms underlying the weaker association of DII score with CRC risk in women than in men were unclear.CRC is a heterogeneous disease that occurs in the colon and the rectum. When we analyzed the cancer site-specific associations, higher DII score was independently associated with increased risks of colon cancer and rectal cancer in the overall analysis. However, our sensitivity analysis revealed that the association of DII score with rectal cancer risk was not reliable. In particular, rectal cancer showed no significant association with DII score when the analysis was restricted to the prospective cohort studies. This result suggests that the significant association depended on the results of the case–control studies. Given the lower reliability of case–control studies than cohort studies, the positive association of the DII score with rectal cancer risk may not be robust. The difference between the DII scores on colon cancer and rectal cancer risks may be explained by the different etiologies of colon and rectal cancers .The DII score is a new dietary quality index that specifically focuses on the dietary inflammatory potential . A higheThis study holds important implications for clinical practice. Our meta-analysis suggests that consuming pro-inflammatory diet, as estimated by a high DII score, is associated with increased CRC risk. With diet as a modifiable factor, limiting pro-inflammatory diets and/or favoring anti-inflammatory diets may be a strategy to reduce CRC risk. However, the present study results are unclear on the reliability of the cancer site-specific associations with the DII score. Further prospective studies on the cancer site-specific associations are warranted. To create a healthy diet, several anti-inflammatory foods, including fruits, vegetables, fish or fish oil, walnuts, brown rice, and bulgur wheat, should be included in the diet . MoreoveSeveral limitations should be noted in this meta-analysis. First, the DII score was computed by self-report from the FFQs or historical dietary records, which carried an inherent recall bias. Second, the DII score was estimated at baseline, and potential changes in dietary habits during the follow-up duration could not be excluded. However, adult dietary habits tend to be relatively stable over time , 27. ThiIn conclusion, this meta-analysis suggests that pro-inflammatory diet, as estimated by the DII score, is independently associated with increased CRC risk. These findings highlight the need to promote healthy dietary patterns with minimal inflammatory potential to reduce CRC risk. However, gender- and cancer site-specific associations need to be further investigated in future well-designed prospective studies.We performed this meta-analysis in accordance with the guidelines of the Meta-Analysis of Observational Studies in Epidemiology . Two autStudies meeting the following inclusion criteria were included: 1) all cohort and case–control studies that reported on the association of the inflammatory potential of diets, as estimated by DII score, with CRC risk and 2) those that provided the multivariable-adjusted RR, hazard ratio (HR), or odds ratio (OR) with corresponding 95% confidence intervals (CI) of CRC for the highest DII score (highest pro-inflammatory diets) versus the lowest DII score (lowest pro-inflammatory diets).Data extraction and quality assessment were independently performed by two authors (Y Fan and X Jin). Any discrepancy between two authors was resolved through consensus. The following data were collected from each study: last name of the first author, publication year, geographical region, study design, sample sizes, number of cases/controls, source of controls (for case–control studies), proportion of women, age range or mean age, method of diet assessment, comparison of DII score, most fully adjusted risk estimate, duration of follow-up (for cohort studies), and adjustment for confounding factors in the statistical analysis. The methodological quality of the included studies was evaluated using a nine-star NOS . This sc2 statistic. A p-value for Cochrane Q < 0.10 or a I2 statistic > 50% indicated substantial heterogeneity [To assess the association of the DII score with CRC risk, we pooled the most fully adjusted risk estimate for the highest versus the lowest DII score. CRC is relatively rare; thus, OR was an approximate estimation for RR. Heterogeneity among studies was evaluated using the Cochrane Q and Iogeneity . A randoogeneity , and Eggogeneity . In addi


Several genetic association investigations have been performed over the last three decades to identify variants underlying Juvenile Myoclonic Epilepsy (JME). Here, we evaluate the accumulating findings and provide an updated perspective of these studies.A systematic literature search was conducted using the PubMed, Embase, Scopus, Lilacs, epiGAD, Google Scholar and Sigle up to February 12, 2016. The quality of the included studies was assessed by a score and classified as low and high quality. Beyond outcome measures, information was extracted on the setting for each study, characteristics of population samples and polymorphisms.Fifty studies met eligibility criteria and were used for data extraction. With a single exception, all studies used a candidate gene approach, providing data on 229 polymorphisms in or near 55 different genes. Of variants investigating in independent data sets, only rs2029461 SNP in GRM4, rs3743123 in CX36 and rs3918149 in BRD2 showed a significant association with JME in at least two different background populations. The lack of consistent associations might be due to variations in experimental design and/or limitations of the approach.Thus, despite intense research evidence established, specific genetic variants in JME susceptibility remain inconclusive. We discussed several issues that may compromise the quality of the results, including methodological bias, endophenotype and potential involvement of epigenetic factors.CRD42016036063 Juvenile Myoclonic Epilepsy (JME) has been recognized by the International League Against Epilepsy (ILAE) as an epileptic syndrome since 1989 and reprhttp://omim.org and http://www.ncbi.nlm.nih.gov/omim/), including CACNB4 [CASR [GABRA1 [GABRD [EFHC1  containing 1[As demonstrated by family and twin studies, genetic factors play a major role in JME. Differe subunit), CASR (creceptor), GABRA1  alpha 1), GABRD  and EFHCtaining 1–20. Manytaining 1. Howevertaining 1.The main hypothesis to explain genetic susceptibility in non-Mendelian JME is based on the interaction among multiple common and/or rare gene variations with modest or strong effects,24. HoweThe completion of the human genome sequences has allowed significant advance in association studies by using unbiased approaches such as genome-wide association studies (GWAS). In the last decade, this strategy has been used to investigate genetic variants associated with several diseases, including epilepsy. Despitehttp://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD42016036063.The systematic review was conducted and reported in accordance with the PRISMA guidelines and the We did a systematic review to identify genetic association studies with JME. We performed a systematic literature search of PubMed, Embase, Scopus, LILACS, epiGAD (Epilepsy Genetic Association Database), Google Scholar and SIGLE (System for Information on Grey Literature in Europe) up to February 12, 2016 using the following combinations of relevant keywords: “Juvenile Myoclonic Epilepsy” AND “Association Study”, “Juvenile Myoclonic Epilepsy” AND “Polymorphism”, “Idiopathic Generalized Epilepsy” AND “Association Study”, “Generalized Epilepsy” AND “Association Study”, “Juvenile Myoclonic Epilepsy” AND “Variants”, and “Generalized Epilepsy” AND “Variants”.We included population-based genetic association studies investigating any polymorphism with JME. Selected articles had to be original research containing independent data and case-control studies, including those that used candidate gene and GWAS approaches. Articles were filtered in three steps see : i) duplTwo investigators independently (Bruna Santos and Layanne Angelo) performed the literature search and data was cross-checked to ensure consistency. Titles, abstracts, and full texts were screened sequentially for eligibility criteria and any discrepancies were resolved by consensus or by a third reviewer.Data extracted included information on: i) the setting for each study ; ii) characteristics of study participants (phenotypic definitions and ethnic/geographic characteristics); iii) characteristics of polymorphism  and; iv) outcome measure .Methodological quality of the included studies was independently assessed by two reviewers , according to a set of predefined criteria  based onOur search returned 9074 citations, 5570 of which were duplicated. Of the 3504 unique citations, 2652 were excluded because they were not relevant to the current review. Of 852 relevant studies identified, 50 met the predetermined inclusion criteria . Of thes2 test and logistic regression, according to Clarke et al.[The quality of studies ranged from 5 to 13, out of a possible score of 13 . The moske et al.[34–39,41ke et al.–78,80–82In all, 49 published studies provided data regarding 224 polymorphisms in or near 52 different genes, of which 33 were directly related to synapse transmission . The others were involved in different biological processes, such as gene expression regulation, mitochondrial metabolism and immunological response .The studies included in the review were conducted with different ethnic populations from Europe (n = 34), America (n = 5), Asia (n = 10), Africa (n = 2) and Oceania (n = 3). The number of patients ranged from 14 to 732, and their age varied from 2 to 25 years. The most used JME diagnostic criterion was based on the proposal by the Commission on Classification and Terminology of the International League Against Epilepsy. The vast major of polymorphisms failed to show associations with JME .GRM4, rs3743123 in CX36 and rs3918149 in BRD2 showed a significant association with JME in at least two different background populations. For 5 polymorphisms, the positive association was not confirmed in independent studies , reached genome-wide significance with JME , HLA (DRB1), HLA (DQB1), BRD2 (rs3918149 and rs516535), KCNJ10 (rs1130183). As we discussed below, part of the reason for the lack of consistent patterns of association could be the experimental design: sample size, population stratification and phenotype definition.Positive findings using variants from independent data sets could not be replicated in at least one of the studies, including GABRG2 (rs211037) had a significant association with an Indian population but not in a Brazilian population. Interestingly, the allele and genotype frequencies of these polymorphisms show wide variation between the populations investigated, suggesting a role for ethnic differences in the distribution of this variant[Sample size: the recruitment of sufficiently large and homogeneous samples for robust genetic analysis is a long-standing weakness of association studies,85,86. Ts variant. In thess variant,53,56,57s variant–89, espes variant.Phenotype definition: the lack of diagnosis based on rigid standards or objective biomarkers is a critical issue in the genetic analysis of JME and may BRD2, EJM1, a major JME susceptibility locus, was discovered by linkage analysis of three separate family collection[BRD2 is responsible for the EJM1 linkage peak and that the rs3918149 (among others) variant is a risk factor for JME. The positive association of this variant with JME was confirmed by independent familial and populational-based case-control studies[BRD2 (but not rs3918149) was associated with photoparoxysmal response (PPR)[BRD2 and JME has not been replicated across some populations[BRD2 contributions to epileptogenesis. In fact, functional assays with heterozygous BRD2 knockout mice showed an increase in seizure susceptibility to flurothyl and the occurrence of spontaneous seizures in female mice[Thus, because of the difficulty in controlling genetic heterogeneity and all possible confounders across studies, the failure of replication does not prove a false-positive result. Although independent replication of association has been a normative criterion for weighing evidence, Pal et al. suggest ollection,100–103.ollection suggestel studies,83. Furtnse (PPR). Therefopulations,60,77 comale mice. In thisBRD2, only two other polymorphisms showed significant associations with JME (rs2029461 in GRM4 and rs3743123 in CX36) which were replicated in at least one independent study. In fact, these studies showed higher quality scores. For example, to avoid the confounding effect of population admixture in case-control studies, at least, one of these studies applied a genomic control approach[CX36 is an integral membrane protein of neuronal gap junction channels that has a significant role in epileptogenesis[GRM4 encoding the group III metabotropic glutamate receptor 4 (mGluR4) and several studies have indicated a functional importance for this gene in the genesis of epilepsy[CX36 and GRM4 genes are located in two major susceptibility loci (EJM2) for JME: regions 15q14 and 6p21, respectively, and were therefore originally chosen as gene candidate due to positional and functional criteria. However, the mechanisms by which rs3743123 and rs2029461 predispose individuals to developing JME remain obscure.Beyond the rs3918149 in  approach or carri approach,83. CX36togenesis–108. rs3 epilepsy–111. rs2CHRM3)) as having genome-wide significance with JME. However, this positive association was not replicated in a case/control study performed in a Chinese population[Despite intense research over the last decades, there is relatively weak evidence for the involvement of most of the variants investigated in JME susceptibility. Even in a more systematic investigation by using GWAS, the findings are not particularly encouraging. In fact, the single GWAS study only identified rs12059546  have been associated with JME in, at least, two independent gene candidate investigations. The lack of success in replicating the results is related to various aspects, including limitations of experimental design, endophenotypes, channelopathy issues and genetic heterogeneity. Therefore, scientists should go beyond replication criteria and draw on convergent evidence across different study designs. Such an integration of results from different experimental approaches combined with epigenetics and genomic technology could lead us to a more comprehensive evaluation of the current state of JME susceptibility.Considerable effort has been expended over the last 40 years to identify JME causative/susceptibility genes. Here, we provided an updated synthesis of the accumulating findings of genetic association studies and JME. The combined studies provided data on 229 polymorphisms in (or near) 55 different genes. Nevertheless, only three polymorphisms (rs2029461 SNP in S1 Table(DOCX)Click here for additional data file.S2 Table(DOC)Click here for additional data file.S1 Checklist(DOC)Click here for additional data file.S1 File(DOCX)Click here for additional data file.S2 File(XLSX)Click here for additional data file.


GSTM1 null and GSTT1 null polymorphisms have not been reported previously. We, therefore, performed a meta-analysis to investigate the combined effects. 40 publications with 44 case–control studies were selected in the meta-analysis, including 13,706 cases and 13,093 controls. Significant association was observed between the combined effects of GSTM1 and GSTT1 polymorphisms and lung cancer risk when all the eligible studies were pooled into the meta-analysis. When we performed subgroup analysis, significantly increased lung cancer risk was observed in Caucasians , Asians , Indians , hospital-based studies, and population-based studies. In summary, this meta-analysis indicates that the combined effects of the GSTM1 and GSTT1 polymorphisms are associated with increased lung cancer risk in Asians, Caucasians, and Indians.Many studies have reported an association between the glutathione S-transferase M1 null and T1 null polymorphisms and lung cancer risk. However, the combined effects of  Lung cancer has become the most common cancer and the leading cause of cancer death in the world . There wGSTM1 and GSTT1 are two of the most important GST variants. GSTM1 located on chromosome 1p13.3 with 10 exons and GSTT1 is mapped at chromosome 22q11.23 and contains six exons. Individuals with the homozygous deletion of the GSTM1 and GSTT1 locus (GSTM1 null and GSTT1 null) have no enzymatic functional activity [Possible lung cancer susceptibility genes have been sought among tumor suppressor genes, DNA repair genes, and genes encoding phase I and phase II enzymes . GlutathGSTM1 and/or GSTT1 alone gene polymorphisms and risk of lung cancer [GSTM1 and GSTT1 polymorphisms have not been reported previously. In addition, a number of molecular epidemiological studies have been performed to evaluate the association between the combined effects of glutathione S-transferase M1 and T1 polymorphisms and lung cancer risk [GSTM1 and GSTT1 and lung cancer risk.To date, some previous meta-analyses have only studied the association between g cancer , 63, 64.cer risk –56. HoweRelevant publications were retrieved and preliminarily screened. As shown in Figure GSTM1 and GSTT1 polymorphism and lung cancer risk. Significant association was observed between the combined effects of GSTM1 and GSTT1 polymorphism and lung cancer risk  when all the eligible studies were pooled into the meta-analysis. Significant between-study heterogeneity was detected in overall analysis. Hence, then we performed subgroup analysis by ethnicity, significantly increased lung cancer risk was observed in Caucasians . In addition, we also performed subgroup analysis by source of controls, significantly increased lung cancer risk was observed in hospital-based studies  and population-based studies .Table 2 >I 75.0% was observed in Asians (− − vs.+ +), however, when the study of Cao YF et al. [2I = 72.5%). In addition, exclusion of the study of Cao YF et al. [GSTM1 and GSTT1 polymorphisms and lung cancer risk in Asians .Significant heterogeneity was observed in the meta-analysis, as shown in Table F et al.  was exclF et al.  resultedP = 0.007). We used the Duval and Tweedie nonparametric ‘‘trim and fill’’ method to adjust for publication bias. Figure Using Egger's test, significant publication bias was detected in the meta-analysis  of all cancers and 18 % (1.4 million) of all cancer deaths in 2008, has become the most common cancer in the world . GSTM1 acer risk , 63, 64.GSTM1 and GSTT1 polymorphisms and lung cancer risk when all the eligible studies were pooled into the meta-analysis. When we performed subgroup analysis, significant increased lung cancer risk was observed in Caucasians, Asians, and Indians. It is possible that the effect sizes of genetic factors predisposing to human diseases are different in various ethnic populations [GSTM1 and GSTT1 polymorphisms in combination were associated with increased risk factors of lung cancer in Asians. Sharma et al. [GSTM1 and GSTT1 polymorphisms increased lung cancer risk in Indians. The results of the meta-analysis supported the positive association. However, at any case, the association between the combined effects of GSTM1 and GSTT1 polymorphisms and lung cancer risk in Indians essentially remains an open field, as the number of studies (n = 3) is considerably smaller than that needed for the achievement of robust conclusions [Significant association was found between the combined effects of ulations . Dzian eulations , Matakovulations , and Cajulations  suggesteulations , Liang Kulations , Cao YF ulations , Pan et ulations , Piao etulations , and Zhaulations  suggestea et al.  and Sreea et al.  found thclusions . When weGSTM1 and GSTT1 effects and lung cancer risk. Third, a meta-analysis is statistically more powerful than any single study. Fourth, the quality of eligible studies met our inclusion criterion in the meta-analysis.In this meta-analysis, several limitations should be acknowledged. First, due to the limited participant data provided by individual studies, we could not examine the interactions among gene-environment. Second, only published articles were included in this study, which may cause publication bias. Third, the controls were not uniformly defined. However, the current meta-analysis has also particular strengths. First, our meta-analysis explores and analyzes the sources of heterogeneity. Second, This is the first meta-analysis to explore the combined GSTM1 and GSTT1 polymorphisms is associated with increased lung cancer risk in Asians, Caucasians, and Indians. As we only explored the association between two combined genes and lung cancer risk, there is still leaving much to be studied in depth. To further evaluate the effects of gene–gene interaction on lung cancer risk, a population-based study on large size of samples is required.In summary, this meta-analysis indicates that the combined effects of GSTM1”, “Glutathione S-transferase T1 or “GSTT1”, “variant” or “variation” or “polymorphism”, and “lung”. The search was performed without any restrictions on language. In addition to the electronic database search, we reviewed manually the reference lists of retrieved articles to identify additional articles.We searched the electronic databases including PubMed, Embase, Web of Science, and two Chinese databases China National Knowledge Infrastructure (CNKI) and Wanfang Data  with The following key words  used case–control or cohort studies; (4) provided sufficient data of combined genotypes for the GSTM1 and GSTT1 polymorphisms in lung cancer patients and controls; (5) reviews, conference abstracts, letters, and editorials were excluded; (5) duplications of previously published data were excluded . The following data were collected from each study: (1) first author's name; (2) year of publication; (3) country of origin; (4) ethnicity; (5) source of controls ; (6) language; (7) numbers of cases and controls in the combined genotypes for the GSTM1 and GSTT1 polymorphisms whenever possible. Ethnicity was categorized as ‘‘Caucasian’’, ‘‘Asian’’, and “African” (including African Americans). We also considered the samples of studies from India and Pakistan as of “Indian”. Last, When one study did not state which ethnic groups was included, or if it was impossible to separate participants according to phenotype, the sample was termed as ‘‘mixed population’’.The included studies met the following criteria: (1) patients had a diagnosis of lung cancer; (2) evaluated combination effects of the GSTM1 and GSTT1 polymorphisms and lung cancer risk was calculated by the crude odds ratios (ORs) as the combined study effect size and summary statistics with 95 % confidence intervals (CI) in a dominant model (− − vs. (+ −) + (− +) + (+ +)), a recessive model (− − vs. (+ −) + (− +)), and a co-dominant model . − − represented GSTM1 null GSTT1 null genotype. + − represented GSTM1 present GSTT1 null genotype. − + represented GSTM1 null GSTT1 present genotype. + + represented GSTM1 present GSTT1 present genotype. The significance of the pooled OR was determined by the Z-test, and P < 0.05 was considered as statistically significant. Statistical heterogeneity among studies was assessed by the chi-square-based Q test [I2 value [P < 0.1, a random-effects model was used [I2 ≥ 50%, 50% > I2 ≥ 25% or 0 < I2 < 25%, we identified the studies as high, middle or low heterogeneity, respectively. Publication bias was analyzed by Egger's linear regression test [The association between the combined effects of d Q test  and I2 vI2 value . In hetewas used , otherwiwas used . Meanwhiion test . If publion test . Sensiti