Previous studies have indicated that intake of dietary flavonoids or flavonoid subclasses is associated with the ovarian cancer risk, but presented controversial results. Therefore, we conducted a meta-analysis to derive a more precise estimation of these associations.We performed a search in PubMed, Google Scholar and ISI Web of Science from their inception to April 25, 2015 to select studies on the association among dietary flavonoids, flavonoid subclasses and ovarian cancer risk. The information was extracted by two independent authors. We assessed the heterogeneity, sensitivity, publication bias and quality of the articles. A random-effects model was used to calculate the pooled risk estimates.RR . In a subgroup analysis by flavonoid subtypes, the ovarian cancer risk was also decreased for isoflavones  and flavonols . While there was no compelling evidence that consumption of flavones  could decrease ovarian cancer risk, which revealed part sources of heterogeneity. The sensitivity analysis indicated stable results, and no publication bias was observed based on the results of Funnel plot analysis and Egger’s test (p = 0.26).Five cohort studies and seven case-control studies were included in the final meta-analysis. We observed that intake of dietary flavonoids can decrease ovarian cancer risk, which was demonstrated by pooled This meta-analysis suggested that consumption of dietary flavonoids and subtypes  has a protective effect against ovarian cancer with a reduced risk of ovarian cancer except for flavones consumption. Nevertheless, further investigations on a larger population covering more flavonoid subclasses are warranted. Ovarian cancer remains a highly lethal malignancy in the world, which has been a serious risk factor of health and safety for women, and a majority of patients are diagnosed in late stages of this disease –2. As thFlavonoids with several functions in different physiological and pathological processes of cancer are polyphenolic compounds having a basic benzo-γ-pyrone structure see , which aEpidemiological studies and clinical trials have explored that flavonoids intake has the chemopreventive effects on carcinogenesis –23, and We did our best to conduct a systematic literature search in PubMed, Google Scholar and ISI Web of Science up to April 25, 2015, without language restriction, regarding the association among dietary flavonoids, flavonoid subclasses and ovarian cancer risk. The search terms were as follows: (flavonoids or flavones or isoflavones or flavonols or flavanones or anthocyanidins or flavan-3-ols or polyphenolic compounds) and (Ovarian Neoplasms or Ovary Neoplasms or Ovarian Cancers or Ovary Cancers or Cancer of Ovarian or Cancer of Ovary or Ovarian tumor or Ovary tumor or Ovarian carcinoma or Ovary carcinoma). Furthermore, we performed a manual search by reviewing the related reference articles to identify any studies that were not identified from above literature searches. Only full length original journal articles were considered and articles have only abstracts or unpublished were excluded in this study. Our meta-analysis meta-analysis was conducted following the Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines PRISMA c.ORs) or relative risks (RRs) for ovarian cancer risk in subjects with the highest dietary flavonoids intake compared with those with the lowest dietary flavonoids intake. If multiple articles reported the risk of ovarian cancer from the same data, the most recently published data were selected, the overlapped cases but the latest were excluded. Meanwhile, if articles reported as an abstract, summary, comment letter, review or editorial, were also excluded.Studies were considered eligible if they met all of the following criteria: (1) the original articles described a case-control, cohort or randomized control design; (2) the article had either dietary flavonoids or subclasses of flavonoids intake as the exposure of interest; (3) the article reported the risk of ovarian cancers; and (4) the article reported 95% confidence intervals (CIs) with adjusted odds ratios  quality assessment criteria [On the basis of the inclusion and exclusion criteria listed above, the two independent investigators (LX Yu and XL Hua) extracted the following data: first author, publication year, study region, study design, data acquisition approach, number of cases and controls, types and consumption of flavonoids, controlled confounders adjusted for in multivariate analysis, criteria . The quaRR with 95% CI was assessed for determining the associations between dietary flavonoids, flavonoid subclasses and ovarian cancer risk. The pooled RR were computed by the adjusted RRs or ORs and 95% CIs reported in the studies. The ORs were considered to correspond to RRs. Cochran Q statistic and I2 were used for the assessment of heterogeneity across the studies [Tau2 was also provided. In addition, a random effects model described by DerSimonian-Laird method was preferred to calculate the summarized estimates and corresponding 95% CIs [p < 0.05 suggested statistical significance) [Statistical analyses were performed by using Stata 12.0 software .  studies . Neverth studies , Tau2 wa 95% CIs . Sensiti 95% CIs , just whficance) . To explAs shown in Most individual studies were adjusted for a wide range of potential confounders, including age, education, cumulative updated total energy intake, BMI, physical activity, duration of oral contraceptive use, and history of postmenopausal hormone use.RR = 0.82, 95% CI = 0.68–0.98) in women with highest intakes of total flavonoids, compared with that in those with lowest intakes of total flavonoids. That is, consumption of dietary flavonoids has a protective effect against ovarian cancer. The heterogeneity among the studies was significant (I2 = 62% (95%CI = 28%–80%), Tau2 = 0.059, p = 0.002) from a random effect model    (I2 = 0.0% (95%CI = 0–85%), Tau2 = 0.0, p = 0.68) and flavones (I2 = 29.2% (95%CI = 0–74%), Tau2 = 0.01, p = 0.237) except for isoflavones (I2 = 75.4% (95%CI = 48%–88%), Tau2 = 0.125, p < 0.001).A subgroup meta-analysis was performed according to the subclasses of dietary flavonoids. We identified 4 studies about flavones intake and ovarian cancer risk, 4 studies about flavonols, and 7 studies about isoflavones. Overall, there was no sufficient evidence showing the association between intake of flavones and the ovarian cancer risk (71–1.03) . On the 50–0.92)  and flav58–0.80) . FurtherRR = 0.82, 95% CI = 0.68–0.98) and fixed-effects model  . . .To the best of our knowledge, this is a comprehensive meta-analysis conducted for investigating the relationship among dietary flavonoids, flavonoid subclasses and ovarian cancer risk. The statistical analysis found that intake of dietary flavonoids can decrease ovarian cancer risk by 18%, and flavonoid subclasses: isoflavones by 33%, flavonols by 32%, respectively. That is, intake of total dietary flavonoids and their subclasses  had protective effects against ovarian cancer except for flavones consumption.At present, the influence of dietary flavonoids and flavonoid subclasses on the risk of ovarian cancer remains controversial. Some studies which were consistent with our findings have reported that dietary flavonoids or flavonoid subclasses may decrease the risk of ovarian cancer , 19, 36.Other studies have suggested that intake of total flavonoids may have no clear association on the incidence of ovarian cancer. Maria Hedelin's study  showed tSeveral limitations should be addressed in this meta-analysis. Firstly, despite we searched all studies describing the associations of dietary flavonoids, flavonoid subclasses with ovarian cancer risk without language restricted, the number of eligible studies was still limited, especially in terms of a subgroup analysis. There are only 12 studies about total flavonoids, 4 about flavones, 7 about isoflavones, 4 about flavonols, as shown in In order to explore the source of heterogeneity we conducted a meta-regression analysis in these respects of publication year, study region, cases and the NOS score in . But nonIn contrast, there are also some advantages in our study. Our meta-analysis systematically and comprehensively sheds light on the associations among dietary flavonoids, flavonoid subclasses and ovarian cancer risk. From a public health perspective, the association between consumption of dietary flavonoids and ovarian cancer risk seems highly meaningful, as the protective effects of dietary flavonoids may provide opportunities for prevention regarding ovarian cancer. In addition, due to comprehensive analysis of more case-control and cohort studies data, our analysis increases the power and plausibility of the conclusion when compared with previous individual studies.In summary, the available evidence suggested that intake of dietary flavonoids, flavonoid subclasses  has a protective effect against ovarian cancer with a reduced incidence of ovarian cancer. While the evidence for possible protection of flavones consumption against ovarian cancer was not compelling. The findings likely provide useful insight and evidence which can be used by healthcare professionals when discussing dietary flavonoids and ovarian cancer prevention with patients. While, further investigations on a larger population covering more other different flavonoid subclasses are required to confirm our findings.S1 Table(DOC)Click here for additional data file.S1 File(DOC)Click here for additional data file.S2 File(DOC)Click here for additional data file.


KCNQ1) gene is related to gestational diabetes mellitus (GDM). However, studies for the rs2237892 polymorphism in KCNQ1 and GDM remain conflicting in Asians. Furthermore, associations of this polymorphism with glucose levels during oral glucose tolerance test (OGTT) have not been described in Chinese pregnant women. The present study aimed to provide evidence for the associations of rs2237892 in KCNQ1 with GDM and glucose levels, and to systematically evaluate the effect of rs2237892 on GDM in Asians.Recent genetic studies have shown that potassium voltage-gated channel, KQT-like subfamily, member1  =1.99(1.26-3.15)). Additionally, the polymorphism was associated with levels of 1h and 2h glucose during OGTT. The pre-pregnancy BMI, age and genotypes of KCNQ1 polymorphism were independent risk factors of GDM. Subsequently, we performed a meta-analysis in Asians. In total, C-allele carriers of rs2237892 polymorphism had a 50% higher risk for GDM (OR (95%CI) =1.50(1.15-1.78)).The rs2237892 polymorphism in KCNQ1 rs2237892 polymorphism was associated with GDM and glucose levels in Chinese women. The study provides systematic evidence for the association between this polymorphism and GDM in Asians.The study demonstrated for the first time that the  Gestational diabetes mellitus (GDM) is defined as glucose intolerance that first occurs or is first identified during pregnancy . It is aKCNQ1) [KCNQ1 gene, located on 11p15.5, encodes the pore-forming a-subunit of the voltage-gated K+ channel (KvLQT1) [KCNQ1 is also expressed in pancreatic islets and the cultured insulin-secreting INS-1 cells, and blockade of the channel with KCNQ1 inhibitors 293B stimulated insulin secretion [KCNQ1 channels may play a role in regulation of insulin secretion.The search for candidate genes for GDM has been active, and more and more genes associated with GDM are being discovered. These genetic factors are also likely to contribute to variation in glucose levels in pregnancy. One of these genes is the maternally expressed gene potassium voltage-gated channel, KQT-like subfamily, member1 (KCNQ1) . The KCN(KvLQT1) . In addiecretion , suggestKCNQ1 was first observed to be associated with GDM in a Korean population [KCNQ1 in risk of GDM.The rs2237892 polymorphism in pulation . The asspulation . This stpulation . In thispulation . Recentlpulation . Moreovepulation , 17–22. KCNQ1 rs2237892 polymorphism with GDM and glucose levels in Chinese women. Subsequently, a meta-analysis including the present case-control study and four previously published reports was conducted to systematically evaluate the contribution of rs2237892 to GDM in Asians.Therefore, we conducted a case-control study to assess the association of the The pregnant women aged 20–49 years and at 24–28 gestation weeks were recruited consecutively from the Department of Obstetrics and Gynecology of Peking University First Affiliated Hospital in Beijing from May 2012 to November 2013. The exclusion criteria for subjects were as follows: women who had pre-existing diabetes, or abnormal result in a glucose screening test before the 24th week of gestation, or multiple gestations, or maternal diseases such as hypertension, endocrine disorders, and hepatic diseases; women with incomplete medical information and who had decided to give birth at another hospital; women who were unable or unwilling to get involved in the study. Ultimately, 562 cases and 453 controls were enrolled in this study by providing written informed consent.All pregnant women were screened for GDM at 24–28 gestation weeks with a 75g, 2h OGTT after overnight fast, according to the criteria established by the Ministry of Health of China in 2011, which is consistent with the guidelines of International Association of Diabetic Pregnancy Study Group [The clinical and biochemical data were collected by the trained medical record abstractors from the hospital computer database, which included self-reported pre-pregnancy weight and height measured at the first prenatal visit. The pre-pregnancy BMI was calculated by dividing pre-pregnancy weight in kilograms by height in meters squared. The glucose levels during OGTT were detected by a biochemical automatic analyzer . The glucose levels were measured to the nearest 0.01mmol/L.The study adhered to the principles of the Declaration of Helsinki. The study protocol and written informed consent were approved by the institutional review board, Peking University Biomedical Ethics Committee (IRB00001052-12043). We obtained written informed consent from all the study participants.Genomic DNA was extracted from peripheral blood samples by salting-out procedure. SpectroDESIGNER software  was used to design the primers, including a pair of amplification primers and an extension primer. Sequenom’s MassARRAY platform  was applied for genotyping the rs2237892 polymorphism according to the manufacturer’s instructions . NegativP value of less than 0.05 was considered to be statistically significant. The statistical analyses were performed with SPSS version 18.0 .The quantitative variables with normal distribution was given as mean and standard deviation (SD), and tested by t-test. The chi-square test was used to determine whether the polymorphism was in Hardy-Weinberg equilibrium (HWE). Genotype frequencies in GDM subjects and controls were compared by logistic regression under the dominant model to calculate odds ratios (OR). The ORs were presented with 95% confidence intervals (CIs). The quantitative traits were analyzed by linear regression, and the regression coefficients (b) were presented. A two-sided KCNQ1, rs2237892 and GDM. Reference lists of retrieved articles were also searched to check for additional reports of relevant studies.We searched the databases of PubMed, Wan fang and Chinese National Knowledge Infrastructure (CNKI) for papers published in English or Chinese before November 2014. Wan Fang database comprises over 30 million journal articles from 7,774 full-text journal titles published in China, covering over 90% of the core journals. Wan Fang database in Medicine and Health Sciences can be a valuable tool for Chinese medical research. The key words of our search included Eligible studies met all the following criteria: (1) original papers; (2) case—control studies; (3) genotype frequencies in cases and controls or odds ratio with its 95% CI were provided. The exclusion criteria were: (1) overlapping data; (2) case-only studies; (3) family-based studies; (4) reviews.The following data was extracted from each study independently by two reviewers according to a fixed protocol: name of first author, year of publication, ethnic background of study subjects, criteria followed for diagnosis of GDM, source of control, numbers of cases and controls, method of genotyping, HWE status, genotype frequencies in the GDM subjects and controls. In addition, we tried to contact with the corresponding author to get the detailed data if the genotype distribution was unavailable in the article. The quality scoring scale modified from previous meta-analysis of genetic studies was used to evaluate the quality of included studied by two reviewers , 27. TheI2 value . The data extracted from all publications were tested under the dominant model. The pooled OR with a corresponding 95% CI was calculated to evaluate the association between the rs2237892 polymorphism and GDM. The Z test was performed to determine the significance of the pooled OR. The HWE of the control group was assessed by chi-square test. The heterogeneity was assessed by Q test and ectively ).The pooion bias . Sensitiion bias .P <0.001).The general characteristics of the GDM patients and controls are shown in P = 0.883). Genotype frequencies in the GDM subjects and controls are represented in P = 0.003)  , 17, 18.= 0.003) .P = 0.004 and 0.027). The mean fasting glucose level was 4.89±0.52mmol/L in the combined TC and CC genotypes and 4.83±0.51mmol/L in the TT homozygotes. The 1h glucose level was significantly higher in C-allele carriers than in the TT homozygotes (8.62±1.85 vs. 8.01±1.72mmol/L). And the C-allele carriers also had higher 2h glucose level (7.41±1.59mmol/L) than the TT homozygotes (7.01±1.31mmol/L).We examined associations between the rs2237892 polymorphism and quantitative glucose levels measured during OGTT, including fasting glucose level, 1h and 2h glucose levels . The rs2P<0.001) and age (OR (95%CI) = 1.09 (1.03–1.14); P = 0.001) were independently associated to GDM. Remarkably, the logistic model with age, pre-pregnancy BMI, and genotypes of KCNQ1 polymorphism as independent variables showed a significant association of C-allele carriers with GDM (OR (95%CI) = 2.19 (1.36–3.54); P = 0.001)  = 1.11(1.07–1.16); = 0.001) . And we KCNQ1 and GDM by searching three databases. Relevant titles and summaries were identified and five were chosen from nine articles after removing duplicate, reviews and meta-analysis. Of the five full-text articles, one was further excluded for different SNP  , indicatP = 0.730). The funnel plot for the association between rs2237892 and GDM showed a symmetrical distribution, with P-value of Egger’s test 0.349, suggesting no publication bias  [KCNQ1 genotype and pre-pregnancy BMI. Further studies including more subjects to investigate the role of this SNP will be needed.Our results showed age of GDM subjects was significantly higher than controls, which is supported by the previous study showing age was associated with an elevated GDM . Some st= 0.012) . HoweverKCNQ1 polymorphism (rs2237892) was not associated with GDM [Two published reports in Chinese population showed that with GDM , 17. Howwith GDM , 15. Thewith GDM . With laKCNQ1 variants (rs163184 and rs231362) were not associated with GDM. Considering the two variants were in weak linkage disequilibrium with rs2237892 of the present study , the different regions of KCNQ1 gene might be functionally different. Further fine mapping investigations are needed to clarify which part of KCNQ1 gene is responsible for the potential GDM association.There was a single GDM-GWAS performed in Korean population , in whicKCNQ1 gene, therefore, we cannot rule out the possibility that other polymorphisms or haplotypes in this gene might be also implicated in the development of GDM. Second, lack of individual-level data on lifestyle factors, such as diet and physical activities, prevents us from analyzing any interaction between rs2237892 and other factors on GDM. A study showed that diet with low fiber and high glycemic load was associated with GDM [There were several limitations of the meta-analysis. First, we only assessed rs2237892 polymorphism in with GDM . Physicawith GDM . FurtherKCNQ1 was identified to be associated with risk of GDM and glucose levels by the case-control study and meta-analysis. The rs2237892 polymorphism could provide clues to forecast susceptibility to GDM in Chinese population. Further studies should be conducted to clarify the functional significance of the KCNQ1 rs2237892 polymorphism.In conclusion, the rs2237892 polymorphism in S1 Checklist(DOC)Click here for additional data file.S2 Checklist(DOC)Click here for additional data file.S1 Table(DOC)Click here for additional data file.S2 Table(DOC)Click here for additional data file.


MKK4 gene and risk of cancer, but the results lack of statistical power due to the limited subjects used in these studies. This study was devised to identify the genetic effects of the −1304T > G polymorphism on cancer risk in a large meta-analysis.A number of epidemiological studies have assessed the association of −1304T > G polymorphism in the Eligible studies were identified by searching both Chinese and English databases. General as well as subgroup analyses were performed for 8 independent case–control publications with a total of 4623 cases and 5256 cancer-free controls. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to estimate the association.Overall, this meta-analysis showed that the association between the −1304T > G polymorphism and cancer risk was statistically significant .Our meta-analysis reveals that the presence of the −1304T > G polymorphism is likely to decrease risk of cancer. Future larger studies are necessary to validate the current finding. All references cited in the retrieved articles were also screened to identify the missing data eligible for the meta-analysis. Publications were included in the meta-analysis when satisfying the following criteria: (a) investigating the association between the −1304T > G polymorphism and cancer risk in patients with cancer and control subjects; (b) having genotype data in full detail; (c) published as a full text, rather than a short summary or a comment letter before January 2014. The study was approved by the ethics committee of southwest hospital.We searched both English  and Chinese databases (CNKI) for all publications regarding the association between the −1304T > G polymorphism and cancer risk by using the keywords: Based on the inclusion criteria and a consensus reached on all items, 2 investigators independently extracted data including first author, year of publication, country, ethnicity, control source, sex proportion in cases and controls, cancer type, genotyping method, and genotype distributions in cases and controls. In addition, we merged colon cancer into the colorectal cancer when performing meta-analysis.Q test19 and I2 statistic.20 When no obvious inconsistency existed across the studies (P > 0.10 or I2 < 50%), the fixed-effect model (Mantel–Haenszel) was used to pool the ORs; otherwise, the random effects model (DerSimonian and Laird) was selected.22 Sensitivity analysis was performed by sequentially excluding each study and rechecking whether the corresponding ORs were altered significantly. Funnel plots and Egger's test23 were used to determine the potential publication bias in the meta-analysis. All tests were 2-sided with P < 0.10 being statistically significant.STATA software, version 12.0  was used to analyze the data of the −1304T > G polymorphism. The fixed effects model or the random effects model was performed to calculate the odds ratios (ORs) and 95% confidence intervals (CIs) for each study. Heterogeneity between studies was measured by Chi-square-based 18  and Egger's test suggested no evidence of obvious publication bias among the studies (GG vs TT: P = 0.894) (Figure No significant between-study heterogeneity was suggested in the meta-analysis Table . FurtherBased on 8 independent case–control publications with a total of 4623 cases and 5256 cancer-free controls, we performed a meta-analysis to comprehensively assess the relationship between the −1304T > G polymorphism and risk of different types of cancers. From the analysis results, we found statistically significant evidence for a reduction in cancer risk when combining all data together. Since the insufficient data on each cancer did not allow further stratified analysis, such as by type of cancer, thus we failed to estimate the associations of the studied polymorphism and various cancers.MKK4 belongs to MAPK pathways known to have involvement in the regulation of apoptosis, inflammation, and tumorigenesis.11 An increasing body of evidence has found that the molecular activity of MKK4 is associated with the formation and initiation of cancers.26 Frequent mutations of MKK4 have been reported in lung cancer and colorectal cancer.28 Also, loss-of-function mutations in the MKK4 gene is shown in a portion of numerous human tissues, accounting for approximately 5%.29 Four common polymorphisms in the promotor region of the MKK4 gene have been recorded in Genebank dbSNP database. The genetic variations in the promoter region could affect transcriptional activity and biological function of this gene14 resulting in tumorigeneses.MKK4 was claimed in colorectal cancer,11 a large number of replication studies on various cancers have been successively done in recent years. Most of the studies concluded that the −1304T > G polymorphism have protective effects on the development of cancer.16 Nevertheless, the susceptibility to esophageal cancer was not found to be associated with this polymorphism.15 Although our meta-analysis revealed an decreased risk in overall cancer, we cannot rule the possibility that the functional −1304T > G polymorphism decreases risk of some cancers by increasing the promoter activity, while it has no biological significance in other cancers, such as esophageal cancer.Since the discovery of a decreased risk associated with the −1304T > G polymorphism in the promotor region of 30 However, the estimate of such effects was not considered in the present meta-analysis, because the limited data did not allow us to do so.Several potential factors must be concerned when interpreting the findings in this meta-analysis. First, the connections of various cancer risks associated with the −1304T > G polymorphism are on the basis of small samples, possibly leading to an underestimate of the true association, which should be further confirmed in a much larger study. Second, we only searched studies conducted among Asian subjects, thus the role of the studied polymorphism in cancer should be widely investigated in more ethnic populations. Third, cancer is known to be a multifactorial disease caused by complex interactions between environmental and genetic factors.In summary, this meta-analysis provides evidence that the −1304T > G polymorphism is strongly associated with a decreased risk of cancer. A large well-designed study in diverse ethnic populations is warranted to clarify the true association between the −1304T > G polymorphism and cancer.


This meta-analysis aimed to clarify these correlations.In previous studiesA comprehensive literature search of the MEDLINE and EMBASE databases was conducted for relevant studies published through January 2014. The pooled estimates of odds ratios (OR) and confidence intervals (CI) were computed, and the meta-analysis was performed with the STATA software according to a random effects approach.2 increase in body mass index was associated with a 15%  higher risk of prostate cancer detection and a 37%  higher risk of high-grade prostate cancer detection at biopsy. There were no differences among the results of studies conducted in the USA, Europe or Asia. We also found that studies that had adjusted for prostate-specific antigen levels, digital rectal examination results, and prostate volumes obtained positive significant outcomes , whereas studies that did not adjust for the above-mentioned confounding variables obtained negative results . Moreover, the positive correlation between body mass index and the detection of both prostate cancer and high-grade diseases tended to be stronger as the number of biopsy cores increased.A total of 11 studies that included 29,464 individuals were identified. A 5-kg/mThe present meta-analysis demonstrated that a high body mass index correlated positively with prostate cancer detection, especially high-grade prostate cancer detection. The adoption of a modified and possibly more aggressive biopsy strategy was suggested for obese populations. Obesity, an increasing public health concern worldwide, has been linked to the development of various cancers Might obesity be associated with the risk of PCa or high-grade PCa  diagnosis from a prostate biopsy? The results that might address this question have been inconsistent; different studies have found positive, null, or negative impacts of obesity on the risks of PCa and HGPCa. These contradictory findings have introduced some concern that the current screening practices might be less effective for detecting PCa among men with high body mass indices (BMI), thus suggesting that obese patients would be more likely to receive delayed diagnoses and experience worse pathological outcomes and prognoses.To address this issue, we performed a dose-response meta-analysis of BMI and the risk of PCa and HGPCa at biopsy. The significance of this analysis could be extensive, as an investigation of the mechanisms behind these risk factors might help to optimize the current PCa screening strategies, particularly those for populations of overweight and obese men.th, 2014. Our search criteria included English-language studies that addressed the relationship between obesity and the risk of PCa in a biopsied population. The search query was as follows: (“obese” OR “obesity” OR “overweight” OR “body mass index” OR “weight”) AND (“prostate”) AND (“biopsy”). References from retrieved reviews, meta-analyses and other relevant publications were also sought for inclusion in this study.We searched the MEDLINE and EMBASE databases for studies published up until January 10Two investigators (Hu and Liu) independently assessed the eligibility of each study. The primary goal of our study was to confirm the existence of a positive correlation between obesity and the risk of PCa or HGPCa in a biopsied population. Therefore, only clinical studies conducted in analytical epidemiological settings that offered direct comparisons between the BMI and the risk of PCa or HGPCa were incorporated into the analysis. First, we screened the studies to remove duplicates and then excluded non-English-language articles, non-human studies, studies of other diseases, reviews, editorials, meta-analyses and case reports. Next, we again reviewed the databases and excluded studies that were not related to our topic, that had not been performed in an analytical epidemiology setting or that had not considered the BMI and biopsy results as the primary parameters. Subsequently, we performed a full-text review and excluded studies of all-cancer populations, those that focused on repeat prostate biopsies and those that failed to provide odds ratios (OR), relative risks (RR) or 95% confidence intervals (CI). In cases of overlap among the populations of different studies, only the most recent and most comprehensive data were included.The following data were extracted from each study: title, authors, journal, publication year, study design, study period, study country, study population and setting, biopsy indications, biopsy methods and cores, BMI categories, numbers of subjects and cancer cases, OR estimates with corresponding 95% CIs and confounders that had been adjusted in the multivariate analyses. Two investigators (Hu and Liu) independently retrieved the data, and disagreements between them were resolved by consensus. If multiple multivariate logistic regression models were used in a study, the model with the highest number of variables was selected. To evaluate the study quality, we adopted the Newcastle–Ottawa Scale (NOS) with a nine-star system; this scale assesses the quality of cohort and case-control studies.2 increase in the BMI. We combined the ORs for each 5-kg/m2 increase in BMI according to the random-effect model. We assessed the inter-study heterogeneity using the Q and I2 statistics 2 values of 25%, 50% and 75% corresponded to the cut-off points for low, moderate and high degrees of heterogeneity, respectively. A subgroup meta-analysis was performed and stratified according to the study design, study location, number of biopsy cores and adjustment of the key confounders. A sensitivity analysis was conducted by omitting one study at a time and repeating the analysis to generate an estimate for comparison with the original results. Publication bias was evaluated using both Begg’s and Egger’s tests The dose-response meta-analysis was performed according to the method proposed by Orsini All analyses were performed using the STATA/SE 12.0 software . Statistical significance was defined as a two-tailed alpha value <0.05.According to the search query, 425 and 474 studies were identified from the MEDLINE and EMBASE databases, respectively. After excluding 185 duplicates, our literature search yielded a total of 714 studies that were potentially relevant to our topic. The detailed selection process is presented in a flowchart . We excl2 increase in the BMI was associated with a 15% higher risk of PCa  among biopsied patients (2 = 76.3%). Obesity appeared to have an even greater impact on the risk of HGPCa .Nine and eight studies were included in our meta-analyses when we modeled the relationships between the BMI and the risks of PCa and HGPCa, respectively. The results indicated that a 5-kg/mpatients , and hig2 increase in BMI when correlated with the risks of PCa and HGPCa, respectively. The case-control studies yielded comparatively lower pooled ORs of 0.99  and 1.15 . When stratified by study location, the correlations between the BMI and the risk of PCa were less clear in studies conducted in the USA , Europe  and Asia . In contrast, all studies demonstrated a positive correlation between the BMI and the risk of HGPCa, regardless whether the study was conducted in the USA , Europe  or Asia . We also found that the number of biopsy cores affected the correlations between obesity and the risks of PCa and HGPCa. When the total number of biopsy cores was ≥12, apparent positive correlations were observed between the BMI and the risks of PCa  and HGPCa . In contrast, the same positive correlations were comparatively weak when smaller numbers of biopsy cores were acquired. Meanwhile, we found that studies in which the PSA levels, DRE findings and PV had been adjusted obtained significantly positive outcomes , whereas studies that did not adjust for the above-mentioned key confounders obtained negative outcomes .The subgroup meta-analysis is presented in Studies that provided BMI categories and ORs were pooled in a random-effect dose-response meta-analysis, thus revealing the various associations between the BMI and the risks of PCa and HGPCa. The correlation between the BMI and the risk of PCa appeared to be slightly complex . Specifi2 = 76.3%) observed in the meta-analysis of the relationship between BMI and the risk of PCa, we performed a sensitivity analysis by excluding each study in turn. Upon excluding the study with the highest weight (15.97%) 2 = 50.6) was identified with respect to the correlation between the BMI and the risk of HGPCa; however, a sensitivity analysis indicated that this heterogeneity was not due to the incorporation of a single study. Furthermore, the contradictory outcomes obtained with Begg’s test (p = 0.536) and Egger’s test (p = 0.006) indicated probable publication bias.Given the high level of heterogeneity , and a positive, statistically significant correlation between the BMI and the risk of HGPCa . Our analysis, which included a total of 29,464 patients, featured great power for evaluating these relationships. The introduction of various subgroup analyses and dose-response relationships in our study is also noteworthy.With respect to the locations of the studies that analyzed the relationship between obesity and the risk of PCa, only previous reports from developed countries such as the USA, in which the populations were heavier, consumed higher-fat diets and performed less exercise, were likely to indicate a positive correlation . However, the current subgroup meta-analysis did not find any differences in the pooled results among the studies conducted in different locations. Consequently, we observed only a tendency towards a positive correlation between the BMI and the risk of PCa, regardless whether the studies were conducted in the USA, Europe or Asia; however, we did observe a positive and statistically significant correlation between the BMI and the risk of HGPCa. Masuda Furthermore, we hypothesized that the positive correlation between the BMI and PCa might be attributable to both biological and technical issues. Various biological mechanisms are involved in the PCa initiation and progression. Obese patients produce smaller amounts of total testicular testosterone, a finding that has a complex relationship with PCa and has been associated with a poorer pathological outcome Because the correlation between the BMI and PCa was less evident than the correlation between the BMI and HGPCa, we further hypothesized that this difference might be due to technical issues associated with PCa detection. Early PCa detection depends on prostate biopsy, which is indicated by elevated PSA levels (commonly ≥4 ng/ml) or abnormal DRE findings. However, statistics have demonstrated that obese patients have lower PSA levels and larger prostates; additionally, it is more difficult to observe abnormal DRE findings in obese patients because of the presence of perirectal fat. Under such circumstances, patients with high BMI values who underwent biopsies based on typical indications or for whom the standard numbers of biopsy cores were collected would very likely experience delayed diagnoses and poor prognoses. The current subgroup analysis supported our hypothesis. After adjusting the pooled results of the studies for all key confounders , we observed a strong shift in the OR relative to the studies that omitted one or two of the key confounders ; this finding indicates that these confounders obscured PCa detection to some extent.An inverse relationship between the BMI and PSA levels has been widely recognized Meanwhile, a positive correlation between the BMI and PV has also been reported The current meta-analysis suggested that not only were obese men underdiagnosed but also that this population presented with more aggressive tumors at diagnosis. From our perspective, technical detection bias and biological causes contribute jointly to the elevated risks of PCa and HGPCa in obese patients. Therefore, the maintenance of a healthy weight and the development of novel medications that target obesity-related molecules or signaling pathways should be encouraged. More importantly, we should consider the use of modified biopsy indications and improved biopsy methods for obese patients. Given that patients with higher body weights exhibited lower PSA levels, it could therefore be suggested that for obese men, a lower PSA threshold (≤4 ng/ml) should be used when discriminating between malignant and benign diseases of the prostate. Some studies have proposed formulas for calculating the relationship between obesity and PSA levels The strength of the present meta-analysis was attributed to the strict eligibility criteria, the application of the NOS, the large numbers of subjects and cases, and the assessment of potential nonlinear relationships. Nonetheless, several limitations should be considered when interpreting our data. First, our literature search and data extraction were restricted to studies published in indexed journals, and the number of included studies restricted us from formulating additional conclusions in the subgroup analysis. Second, the present analysis exhibited moderate to severe heterogeneity that might be explained by the various confounding factors present in the original papers, including the different study designs, baseline characteristics, biopsy indications and numbers of biopsy cores. Third, given the lack of data, the current study could not evaluate measures of abdominal obesity such as the waist circumference and waist-to-hip ratio, although these measures are considered to be more strongly associated than BMI with hormonal and metabolic alterations In conclusion, our analysis suggests a positive correlation between BMI and PCa detection, particularly HGPCa detection, at biopsy. Biopsied patients with higher BMI values had a greater risk of receiving diagnoses of PCa and HGPCa. The maintenance of an ideal body weight might help to improve the rate of early detection and the prognoses of individuals with PCa. More importantly, the insight into the biopsy-associated technical issues associated, including the lower PSA levels and larger prostate size associated with a higher BMI, indicated a potential risk for delayed diagnosis and poor pathological outcomes in obese patients following treatment according to standard biopsy strategies. Therefore, we highly suggest the adoption of modified and possibly more aggressive biopsy indications and methods for men with higher BMI values . Additional large population studies across multiple institutions and countries will be needed to obtain a unified picture of the factors responsible for this observed increase. Finally, additional randomized clinical trials should focus on exploring modified prostate biopsy indications and methods based on BMI categories.Checklist S1PRISMA Checklist.(DOC)Click here for additional data file.


High levels of serum uric acid (SUAC) are frequently detected in patients with psoriasis. However, the relationship between psoriasis and hyperuricemia remains unknown. Here we conducted a meta-analysis to identify the SUAC levels in subjects with psoriasis and to determine whether there is an associated risk between psoriasis and hyperuricemia.A comprehensive search of the literature from January 1980 to November 2014 across 7 databases  was conducted to determine whether there is an associated risk between psoriasis and hyperuricemia.P = 0.002) in patients with psoriasis in Western Europe, but no significant differences were found between the East Asia and India subgroup  or the Middle East subgroup . Similar results were obtained from the meta-analysis of SUAC levels in subjects with severe psoriasis.Among the 170 identified reports, 14 observational studies were included in this meta-analysis. We found a significant higher SUAC level (MD 0.68, 95% CI 0.26–1.09; Our meta-analysis showed that the correlation between psoriasis and hyperuricemia was either ethnicity- or region-dependent and that patients with psoriasis in Western Europe were more likely to have hyperuricemia. In addition, patients with psoriasis may present itchy or painful lesions that negatively affect their quality of life. The pathogenesis of psoriasis is not completely understood; however, abnormal differentiation of keratinocytes and infiltration of inflammatory cells have been suggested.2 Inflammatory cytokines that are found in the psoriatic lesions have also been implicated.3 Patients with psoriasis are at greater risk of cardiovascular disease (CVD),4 metabolic syndrome (MetS),6 type 2 diabetes mellitus, dyslipidemia, hypertension, and obesity.8Psoriasis is a chronic immune-mediated skin disease that affects ∼2% to 4% of the population in Western countries.10 In addition, hyperuricemia has been reported to cause adverse cardiovascular outcomes, especially sudden cardiac death.11 In 1958, Walkerin first suggested that psoriasis may be associated with hyperuricemia.12 Since then, several observational studies have reported conflicting results on the correlation between serum UA (SUAC) levels and psoriasis. A previous study observed higher SUAC levels in psoriasis patients, among 76 subjects with psoriasis and 68 persons without psoriasis from the United States in 1961.13 Moreover, the results of a larger prospective study indicated that psoriasis patients with extensive involvement of the skin tended to have a higher incidence of hyperuricemia.14 However, a cohort study conducted in England provided a conflicting result: no significant difference was found between the SUAC levels of a psoriasis group and a group composed of hospital employees (each with 41 subjects).15Hyperuricemia has been detected more frequently in patients with psoriasis and has also been associated with CVD and MetS. Specifically, the prevalence of CVD has been linked with higher levels of uric acid (UA).Herein, we performed a meta-analysis of studies investigating the correlation of SUAC levels with psoriasis and evaluated the influence of potential confounding factors presently under discussion during the past 30 years. We hypothesized that the observed correlation between hyperuricemia and psoriasis might be dependent on the ethnicities of the patients involved or on the geographic locations of the studies.To identify relevant psoriasis studies that measured SUAC levels and having hyperuricemia as an outcome measure, 3 reviewers  systematically searched MEDLINE, Embase, the Cochrane Central Register, the China National Knowledge Infrastructure database (CNKI), the Chinese Scientific Journals Full Text Database (CQVIP), the Wanfang Data Knowledge Service Platform, and the Chinese Biomedical Literature Service System (SinoMed) using the search terms: psoriasis, hyperuricemia, and uric acid. Papers published in English or Chinese and dated from January 1980 to November 2014 were included in this study.28 A flowchart of the search process is shown in Figure To determine eligibility for inclusion in the review, we screened abstracts for the following criteria: case-control, cross-sectional, cohort or nested case-control design; examination of hyperuricemia in relation to psoriasis; or analyses that compared the SUAC profiles of patients with psoriasis with those of control groups. There were no limitations on the participant's age, gender, or nationality. The selection criteria for inclusion were as follows: (i) human-only studies; (ii) availability of original data; (iii) availability of a control group; (iv) odds ratio (OR), risk ratio (RR), hazard ratio estimates with confidence intervals(s) (CI) ; or hyperuricemia considered as a specific outcome event, or the mean with CIs of SUAC provided. In this study, we identified 166 articles from the initial search  the first author; (ii) study characteristics ; (iii) characteristics of participants ; and (iv) outcome characteristics .29 was used to assess the study quality. This scale is categorized into 3 categories including selection, comparability, and exposure for case-control studies; and selection, comparability, and outcome for cohort studies. The selection category contains 4 quality items, the comparability contains 1 item, and the exposure contains 3.The Newcastle–Ottawa Scaleχ2 and I2 tests. P value <0.10 or I2 value >50% is considered as substantial heterogeneity. In this case, DerSimonian and Laird random-effect models were considered in order to compute the global MD and RR. For P values >0.10 or I2 <50%, the between-study heterogeneity was not considered substantial and the fixed-effect models were used. To investigate possible reasons for heterogeneity, we performed subgroup analysis and meta-regression using prespecified variables and random-effects meta-analysis. Prespecified sources of heterogeneity in meta-regression included source population, study design, study quality, severity of psoriasis, presence of psoriatic arthritis, outcome ascertainment, and analysis of outcome. The methods and findings of the present review have been reported following the Meta-analysis of Observational Studies in Epidemiology (MOOSE) group guidelines and checklist.30 Review Manager 5.2 was used for meta-analysis (http://ims.cochrane.org/revman). Meta-regression was performed using STATA version 10.0 .The primary outcomes included the difference in mean SUAC levels between healthy controls and patients with psoriasis, as well as the correlation of psoriasis with the risk of hyperuricemia for each study. The degree of heterogeneity between studies was assessed using Cochrane This study used published data and thus ethical approval was not necessary.26 with dichotomous hyperuricemia as the response variable and a total of 617 participants (265 patients with psoriasis and 352 controls) who met the inclusion criteria for the dichotomous variables of the systematic review. Of these14 studies, 12 were cohort studies, 1 was a case-control study, and 1 was a cross-sectional study . In addition, there was heterogeneity within each separate subgroup . With random-effects modeling, the pooled data for 13 studies showed a significant difference in SUAC levels between psoriasis patients and controls . Although heterogeneity was high, subgroup analyses was able to identify an optimal subgroup in Western Europe . On the contrary, no significant differences were found between the subgroups from East Asia and India  or the Middle East   was conducted. The pooled MD from the random-effects analysis for 3 studies was determined to be 0.53 . There was heterogeneity in the Middle East subgroup , and no significant differences were found  . With fixed effects modeling, we observed significant differences in hyperuricemia occurrences between psoriasis patients and controls in the 2 studies from Italy, with a pooled RR of 2.18   and the United States (3.15%), and the lowest in West Africa (0.08%–0.9%) and East Asia (0.05%–1.23%), and absent in the Andean region of South America. The etiology of psoriasis is dependent on both genetic and environmental factors.34 we found a ethnicity/region-dependent pattern for this correlation. Specifically, the MD value 0 is outside the 95% CI of the SUAC levels in the Western Europe subgroup but within that of the East Asia and India or the Middle East subgroup. Similar results were obtained from the meta-analysis of the SUAC levels in subjects with severe psoriasis.This meta-analysis combined data from 14 studies consisting of about total 29,416 participants. These studies include almost all the available epidemiological evidence worldwide on the topic. Although the correlation between elevated SUAC levels or hyperuricemia and psoriasis had been reported previously,26 included in the second part of the meta-analysis showed that the pooled risk of hyperuricemia was 2 times higher in psoriasis patients. In addition, elevated SUAC levels or hyperuricemia, even within the high-normal range, are positively associated with higher CVD risk of mortality,38 as well as MetS and its components.41 Together, these results suggest that the normal SUAC reference ranges used in the clinic might be inadequate for detecting early metabolic disturbance and CVD risk of mortality.The 2 Italian studies42 Our meta-analysis suggests that UA may be a potential target for preventing the incidence of metabolic disturbances 39 or cardiovascular risk factors.35 On the contrary, it remains to be determined whether the relationship between UA and cardiovascular events is circumstantial or causal in patients with psoriasis from Western Europe.Severe psoriasis has been suggested to be an independent cardiovascular risk factor.25 Furthermore, high degree of heterogeneity is present in the East Asia and India or the Middle East subgroups. Therefore, any interpretation of the results must be done cautiously given these limitations.In any observational study, there is always a potential limitation for unknown confounders influencing the results. Our analysis has some limitations as well. For example, only 2 eligible observation studies from Italy were reviewed in the second part. In addition, the 4 studies from India and the Middle East included patients who were receiving systemic therapy, which may have reduced SUAC levels.To identify potential confronting factors for high heterogeneity, we assessed the effects of multiple variables on the findings among the included studies by meta-regression analysis. These variables include source population, study design, study quality, severity of psoriasis, psoriatic arthritis, outcome ascertainment, and analysis of outcome. We found no statistically significant difference in outcomes resulting from each of these variables.Taken together, our meta-analysis study identified a correlation between psoriasis and hyperuricemia and a difference in SUAC levels between patients with psoriasis and controls in Western Europe. Future investigations are needed to establish a causal relationship between psoriasis and hyperuricemia as well as SUAC levels, and to better understand the mechanisms underlying the correlation between the 2 conditions. Moreover, additional studies should determine the potential efficacy of systemic therapies for controlling SUAC levels in psoriasis. Nevertheless, our results suggest that psoriasis patients in Western Europe should be cautioned about being at higher risk of having higher SUAC levels. Moreover, detection of increased SUAC levels in this patient population may enable earlier implementation of preventive measures for metabolic disturbances and awareness of CVD-associated risk of mortality.


BDNF) is highly expressed in the mammalian brain and is thought to be involved in learning and memory processes. A nonsynonymous polymorphism in the BDNF gene, rs6265 , has been hypothesised to be associated with PTSD. Association studies examining the Val66Met polymorphism and PTSD have been inconclusive, likely due to the variability in type of trauma exposure analysed. Vietnam veterans (n = 257) screened for PTSD and controlled for trauma exposure were genotyped for BDNF Val66Met. The association was not significant so we incorporated our data into a meta-analysis to obtain greater statistical power. A comprehensive search of more than 1237 articles revealed eight additional studies suitable for meta-analysis (n = 3625). A random-effects meta-analysis observed a potential protective factor of the Val/Val genotype. After removing two studies with violation of Hardy-Weinberg equilibrium, findings for the Val/Val genotype reached significance. Subgroup analyses confirmed a trend for this finding. Limitations of some studies that inform this meta-analysis include poorly screened controls and a lack of examination of population stratification. Effectively designed studies should inform this line of research in the future.Posttraumatic stress disorder (PTSD) is a debilitating condition that develops in some people after exposure to a traumatic event. Brain-derived neurotrophic factor ( Posttraumatic stress disorder (PTSD) is a debilitating condition following from the experience of a severe traumatic event . PTSD onMemory processes such as recurring fearful memories and nightmares are central to PTSD symptomatology as they underpin the establishment of exacerbated fear responses . The in BDNF has been hypothesised to be important in fear learning and has shown some promising associations in animal models, reviewed in Andero and Ressler, 2012  and Dretsch et al. 2016 [29].Table S2. Fixed effects model: Results from the subgroup analyses with and without Zhang et al., 2014 [27] and Dretsch et al. 2016 [29].


CXCL12 is a small chemotactic cytokine belonging to the CXC chemokine family expressed in various organs. It contributes to the migration, invasion and angiogenesis of cancer cells. Recently, the CXCL12 G801A polymorphism was shown to be associated with an increased risk of various kinds of cancers, but the results were too inconsistent to be conclusive.To solve the problem of inadequate statistical power and conflicting results, a meta-analysis of published case-control studies was performed, including 4,435 cancer cases and 6,898 controls. Odds ratios (ORs) and their 95% confidence intervals (CIs) were used to determine the strength of association between CXCL12 G801A polymorphism and cancer risk.A significant association between CXCL12 G801A polymorphism and cancer risk was found under all genetic models. Further, subgroup analysis stratified by ethnicity suggested a significant association between CXCL12 G801A polymorphism and cancer risk in the Asian subgroup under all genetic models. However, in the Caucasian subgroup, a significant association was only found under an additive genetic model and a dominant genetic model. The analysis stratified by cancer type found that CXCL12 G801A polymorphism may increase the risk of breast cancer, lung cancer, and “other” cancers. Based on subgroup stratified by source of controls, a significant association was observed in hospital-based studies under all genetic models.The CXCL12 G801A polymorphism is associated with an increased risk of cancer based on current published data. In the future, large-scale well-designed studies with more information are needed to better estimate possible gene-gene or gene-environment interactions. Chemokines are small glycoproteins that contribute to the regulation of various biological processes CXCL12 binds primarily to the CXCR4 receptor, resulting in a CXCL12/CXCR4 receptor-ligand system involving a one-on-one interaction CXCL12 is located on chromosome 10q11.1 and has a G→A mutation at position 801 in the 3′-untranslated region in its β transcriptional splice variant Two investigators independently searched for eligible studies of the associations between CXCL12 G801A polymorphism and cancer risk. Studies published through March 2014 were identified through a computerized search of PubMed without language limitation. The key words used in this search were as follows:  and  and polymorphism. The references of all identified publications were also searched for additional studies. Studies included in this meta-analysis had to meet the following inclusion criteria: (a) used a case-control study design, (b) evaluated CXCL12 G801A polymorphism and cancer risk, (c) reported detailed genotype frequencies of cases and controls or these could be calculated from the text of the manuscript, and (d) the control subjects were in agreement with the Hardy-Weinberg equilibrium (HWE).Two investigators extracted the data independently, and disagreements were settled by discussion. The following data were extracted from the eligible studies: the first author's name, year of publication, country of origin, ethnicity, the source of controls, and numbers of genotyped cases and controls. If the data was not available, study authors were contacted to request missing data.P<0.05 was considered statistically significant. Additive (A vs. G), dominant (GA+AA vs. GG), and recessive (AA vs. GG+GA) genetic models were investigated. Subgroup analysis was performed by ethnicity, cancer type , and source of controls, either hospital or population controls. HWE was tested using the chi-square test among controls, and P<0.05 was considered a significant departure from HWE. If the P value for heterogeneity was >0.05 and I2<50%, indicating an absence of heterogeneity between studies, the fixed-effects model (the Mantel-Haenszel method) was used. In contrast, if either the P value for heterogeneity was ≤0.05 or I2 was ≥50%, indicating heterogeneity among the studies, the more appropriate random-effects model (the DerSimonian and Laird method) was used. Sensitivity analyses were performed to assess the stability of the results. Funnel plots and Egger's linear regression test were used to diagnose potential publication bias, and P<0.05 was used to indicate possible publication bias. All analyses were performed using Stata software. P values were based on two-sided tests.ORs and their 95% CIs were used to determine the strength of association between the CXCL12 G801A polymorphism and cancer risk. The significance of the pooled OR was determined using the Z test, and Our meta-analysis was performed according to guidelines of the “Preferred Reporting Items for Systematic Reviews and Meta-Analyses” (PRISMA) statement  and “MetA significant association between CXCL12 G801A polymorphism and cancer risk was found under an additive genetic model , a dominant genetic model , and a recessive genetic model . Subgroup analysis stratified by ethnicity also suggested a significant association between CXCL12 G801A polymorphism and cancer risk in the Asian subgroup under an additive genetic model , a dominant genetic model  , and a rFurthermore, in the analysis by stratified cancer type, a significantly increased risk was found in breast cancer and lung cancer under all genetic models. In addition, under the additive and dominant genetic models, a significantly increased risk was found in “other” cancers. However, no significant association with this polymorphism was observed in bladder, colorectal and gastric cancers. Base on subgroup analysis by source of controls , a significant association was observed in hospital-based studies under all genetic models .A single study was excluded each time to evaluate the effect of an individual study on the combined ORs and 95% CIs. The omission of any single study did not significantly change the pooled effects of the additive, dominant and recessive genetic models; these findings confirmed that the meta-analysis results were statistically robust and that our results were reliable and stable (data not shown).Begg's funnel plot and Egger's test were performed to assess the publication bias of this set of publications. The shape of the funnel plot did not show obvious publication bias . SimilarCXCL12 is primarily produced by stromal cells and is important for the growth, angiogenesis and metastasis of tumor cells Additionally, our study contributes the results of subgroup analyses stratified by ethnicity, cancer type and source of controls. Our results indicated that the CXCL12 G801A polymorphism was associated with an increased risk of cancers, especially for breast and lung cancer. However, no significant association was observed for bladder, colorectal and gastric cancers. This is maybe because cancers types differ by carcinogenic mechanisms and environmental exposures and have disparate responses to CXCL12 G801A genotypes. In addition, gene-gene and gene-environment interactions may influence the association between CXCL12 G801A polymorphism and susceptibility to specific cancers In the subgroup analysis by ethnicity, the CXCL12 G801A polymorphism was found to confer an increased cancer risk among Asians under all the genetic models, whereas in the Caucasian subgroup, a significant association was only observed under an additive genetic model and a dominant genetic model. The mechanism that explains this ethnic difference is unknown, but differences in genetic backgrounds and life-styles may contribute to different genetic characteristics and susceptibility to specific cancers. In the present meta-analysis, we failed to find significant relationships between CXCL12 G801A polymorphism and cancer risk in ethnic groups besides Asian and Caucasian. Therefore, more studies in other ethnic groups may be necessary for further progress in this area.In the subgroup analysis stratified by the source of controls, significant associations were observed in hospital-based studies but not in population-based studies. However, most of the included studies were hospital-based because hospital controls are more readily available. Therefore, the findings in this subgroup should be interpreted with caution. Additional population-based studies are needed to better evaluate this association.We identified previous genome-wide studies relevant to our research, such as those conducted in breast cancer and lung cancer Two meta-analyses similar to that presented herein were performed by Gong et al. We conducted the largest and most comprehensive quantitative meta-analysis of the relationship between CXCL12 G801A polymorphisms and cancer risk. Nevertheless, we recognize some limitations of this meta-analysis. First, our meta-analysis was based primarily on unadjusted ORs with 95% CIs because potential correlative factors, such as environmental factors and other lifestyle habits, were not available. Second, the meta-analysis was limited by the relatively small number of available studies, which limited our ability to perform subgroup analysis for every type of cancer. Third, our analysis was limited to Asian and Caucasian ethnicities, and it is uncertain whether these results are generalizeable to other populations. In addition, cancer is a multi-factorial disease that results from complex interactions between many genetic and environmental factors. Therefore, a single gene or single environmental factor is unlikely to explain cancer susceptibility.In conclusion, this meta-analysis suggested that CXCL12 G801A polymorphism was associated with an increased risk of cancer based on current published data. In the future, large-scale well-designed studies with more information about potential correlative factors are needed to better estimate possible gene-gene or gene-environment interactions.Checklist S1PRISMA 2009 Checklist.(DOC)Click here for additional data file.Checklist S2Meta-analysis on Genetic Association Studies Checklist.(DOC)Click here for additional data file.


P = 0.20) and the funnel plot. Thus, high caffeine intake during pregnancy is associated with a significant increase in the risk of LBW, and this risk appears to increase linearly as caffeine intake increases.Epidemiologic studies have shown inconsistent conclusions about the effect of caffeine intake during pregnancy on the risk of low birth weight (LBW). We performed a meta-analysis and linear-dose response analysis examining the association between caffeine consumption during pregnancy and risk of LBW. PubMed and EMBASE were searched for relevant articles published up to March 2014. Eight cohort and four case-control studies met all inclusion criteria. Using a random-effects model of the twelve studies, the pooled odds ratio (OR) for the risk of LBW comparing the highest versus lowest level of caffeine intake during pregnancy was 1.38 . Linear dose-response analysis showed that every additional 100 mg of caffeine intake (1 cup of coffee or 2 cups of tea) per day during pregnancy was associated with a 3.0% increase in OR for LBW. There was a moderate level of overall heterogeneity with an I-squared value of 55% , and no evidence of publication bias based on Egger’s test ( A recommendation to limit caffeine intake during pregnancy was issued by the United States Food and Drug Administration in 1980 .Pregnant women have slower caffeine metabolism, with 1.5 to 3.5 times longer half-life needed to eliminate caffeine, compared to non-pregnant woman , 5. The Epidemiologic studies have reported inconsistent conclusions about the effects of caffeine intake during pregnancy on LBW. Larroque et al  and Fortpregnancy, pregnancy outcome, perinatal, maternal, caffeine, coffee, birth weight, infant, and low birth weight  terms or key words h weight . Five blWe included cohort and case-control studies that examined the association between maternal caffeine intake and LBW. All sources of caffeine exposure, such as coffee, tea, cocoa/chocolate and soda drinks, were included. The outcome, LBW, was defined as birth weight smaller than 2,500 grams. We also restricted to studies providing measures of association, relative risk (RR) or odds ratio (OR) estimate and 95% confidence interval (CI), to perform meta-analysis . StudiesFrom each selected study we extracted the following information: authors, publication year, study design (cohort or case-control), study type (retrospective or prospective), source of caffeine (beverage type), exposure timing (trimester), number of cases and non-cases, sample size, most fully adjusted estimates of association and corresponding 95% CIs, study region, percentage of women age > = 35, measurement of caffeine consumption , measurement of outcomes , adjustment for potential confounders Tables . For artFirstly, meta-analysis for highest vs lowest exposure was performed. The summary ORs and 95% CIs were calculated by using random effects model, which allows for between-study variation. If consumption was reported as cups/day, we used a conversion equation of 100mg/day of caffeine for 1 cup of coffee and 50mg/day for 1 cup of tea . The forA linear dose-response meta-analysis was conducted based on the assumption that there is a linear relationship between maternal caffeine consumption and LBW . We usedPotential publication bias was evaluated by the asymmetrical shape of a funnel plot  and by t2 statistic and associated 95% CI [2 statistic of less than 60% represents moderate or no heterogeneity. Sources of heterogeneity were explored by performing meta-regression and subgroup analyses with respect to study design , study region , exposure measurement assessment , sources of caffeine , proportion of women aged 35 , exposure timing , publication year , and the level of confounder adjustment  (Between-study heterogeneity was assessed using Cochran Q-statistic and quantified by Higgins Id 95% CI . Accordihnicity) .The searching scheme resulted in a total of 336 studies. A total of 13 studies, nine cohort , 20–22 aThe pooled estimate of the twelve studies presented that maternal caffeine consumption during pregnancy was associated with increased risk of LBW . The linear dose-response analysis showed that one additional cup of coffee or two additional cups of tea per day during pregnancy was associated with a 3.0% increase in the OR for LBW .P = 0.01, I2 = 55%, 95% CI: 13, 76%). The meta-regression tests showed that none of the study characteristics, including study design, proportion of women aged 35 and older, region, exposure assessment, sources of caffeine, timing of the exposure, publication year, and confounders adjustment status, significantly modified the pooled estimate for the effect of maternal caffeine intake on the risk of LBW. The results of the meta-regression tests for heterogeneity and subgroup meta-analysis are displayed in The test of heterogeneity resulted in a moderate level of heterogeneity .Visual inspection of the funnel plot suggested that the studies were nearly symmetrically distributed around the log of the pooled estimate, and Egger’s tests formally presented that there was no significant evidence of publication bias Click here for additional data file.S2 File(DOCX)Click here for additional data file.S1 Table(TIF)Click here for additional data file.S2 Table(TIF)Click here for additional data file.S3 Table(TIF)Click here for additional data file.


Introduction: Several polymorphisms at the lipoprotein lipase (LPL) locus are associated with variations in LPL activity serum lipid concentrations and the risk of coronary artery disease (CAD). The aim of this study was to investigate the role of the LPL S447X and HindIII polymorphism in a sample of subjects with CAD and compare them with healthy subjects.Methods: The study enrolled 115 patients and 89 healthy subjects who were recruited from Namazi hospital in 2010-2012. The presence of two common polymorphisms of the LPL gene (HindIII and S447X) was determined by polymerase chain reaction restriction fragment length polymorphism (PCR-RFLP) analysis using genomic DNA. SPSS 16.0 was used for statistical analysis.Results: S447X was significantly different between the patients with CAD and the healthy subjects (P < 0.001). But HindIII was not significantly different between the patients with CAD and the healthy subjects (P = 0.741). Risk factors such as smoking, hypertension, hyperlipidemia, triglyceride (TG) and high-density lipoprotein (HDL) levels had a significant association with CAD.Conclusion: In our study, the presence of G allele S447X polymorphism increases the TG level and decrease HDL level, so it increases the susceptibility CAD. Moreover, HindIII polymorphism did not have any significant association with CAD. Several polymorphisms at the LPL locus are associated with variations in LPL activity serum lipid concentrations and the risk of coronary artery disease (CAD).2 In most previous studies Ser447Stop polymorphism has enhanced LPL activity and has been resulted to be related to decreased TG and increased HDL-C.5 Furthermore HindIII polymorphism has been resulted to be associated with elevated TG, lower HDL-C, and an increased risk of CAD in most studies.7 The aim of this study was to investigate the role of the LPL S447X and HindIII polymorphism in a sample of subjects with CAD and compare them with healthy controls.Lipoprotein lipase (LPL) found in 1943. This enzyme plays a central role in lipid metabolism by hydrolyzing triglyceride-rich particles in the muscles. Free fatty acids and glycerol have been produced by adipose tissue and macrophages for energy utilization and storage. The LPL gene is located on chromosome 8p22.The study population comprised 115 patients  and 89 control subjects  who underwent coronary angiography because of either symptoms of suspected CAD or unrelated conditions such as cardiomyopathy or valvular heart disease. Positive angiography was defined as the presence of greater than 50% coronary diameter reduction as described by an experienced cardiologist, while control subjects were those who had <30% stenosis in all major vessels. All participants were apprised on the aims of the study and informed written consent was obtained from them. Study was approved by the ethics committee of Shiraz Medical University. Each participant was interviewed by two trained interviewers about the cardiovascular risk factors such as hypertension (defined as systolic/diastolic blood pressures higher than 140/90 mm Hg or using antihypertensive medications), hyperlipidemia, TG and HDL levels and cigarette smoking habit (cigarette and/or hookah). The subjects who smoked at least one cigarette or hookah per day or were ex-smokers were considered as smokers while non-smokers were defined as those who had never smoked. All subjects in this study were recruited from Namazi hospital between July 2010 and March 2012. Sample size was estimated upon primary study by MedCalc software with α=0.05 and 1-β=%80.8:Genomic DNA for polymerase chain reaction (PCR) was isolated from the whole blood by using salting out methods. Polymerase chain reaction restriction fragment length polymorphism (PCR-RFLP) determined the presence of two common polymorphisms of the LPL gene. The primer sets and procedures were selected from the published information as followsHindIII forward primer: 5’-TGAAGCTCAAATGGAAGAGT-3’, and reverse primer: 5’-TACAAGCAAATGACTAAA-3’;S447X forward primer: 5’-TACACTAGCAATGTCT AGCTGAAGGCAGA -3’, and reverse primer: 5’-TCAG CTTTAGCCCAGAATGCTCACC-3’.+H+, and heterozygote was designated H+H-.9The MnLI restriction endonuclease (Fermentase) was used to detect Ser447Stop polymorphism. Homozygote of the mutation was designated (GG), that of the wild type was designated (CC), and heterozygote was also designated (GC). Also HindIII polymorphism was detected by digestion of PCR products with HindIII restriction endonuclease (Fermentase). Homozygote of the mutation was designated H-H-, that of the wild type was designated HP-value less than 0.05 was considered significant.Gene-Counting was used to calculate the frequencies of genotypes and alleles. SPSS 16.0 was used for statistical analysis. Comparisons of groups were performed using chi-square test. The binary logistic test was also used to further estimate the association between the polymorphism and the developing risk of CAD. P=0.47), with allele frequencies of 77% and 23% for the H+ and H-, respectively (P<0.001), with allele frequencies of 73% and 27% for the C and G, respectively (P<0.001). But HindIII was not significantly different between the patients with CAD and the control subjects (P=0.741).The distribution of the HindIII genotype in the whole population was compatible with Hardy-Weinberg proportion . As shown in P<0.001). The interaction between S447X polymorphism and TG and HDL-C with CAD is shown in Demographic characteristics of the participants are summarized in 11 One of the most desirable candidate genes is LPL gene that may be explain some of the lipid and lipoprotein abnormalities faced in numerous cases of CAD.12 In this study, we presented the results on polymorphisms of the LPL gene, HindIII and S447X and their association with CAD and environmental risk factors including smoking, hypertension, hyperlipidemia, TG and HDL-C levels. To the best of our knowledge, it is the first study on the population of the south of Iran.CAD is a complex disease with genetic and environmental components. The results of most genetic studies of CAD are different, perhaps because the genetic risk of CAD is not based on a single gene but is based on interactions among multiple genes and environmental risk factors. LPL is a potential target for treatment of CAD because LPL gene variants are involved in multiple genes and environmental risk factors associated with CAD.13 reported that the frequency of H- allele HindIII polymorphism was 30%. In a recent study, there was not any significant association between CAD and the control groups (P=0.540). Moreover, the frequency of G allele S447X polymorphism was 12% and there was an association between CAD and the control group (P<0.001). Therefore, we can conclude that S447X polymorphism is associated with CAD . The presence of G allele is due to increased susceptibility of CAD. In this study, we investigated the associations of environmental risk factors with CAD. We could observe that as previous studies, in this study, there were associations between demographic risk factors  and CAD.15 These risk factors were due to the increase in the susceptibility to CAD. Smoking had the most influence on this disease .The frequency of H-allele HindIII polymorphism is 22%. Sayad et al.Another analysis done in this study is the impact of each risk factor with S447X polymorphism. In all analyses, we could observe that the presence of G allele and environmental risk factor is due to the increased susceptibility to CAD.16 Perhaps, S447X polymorphism has affected another function in our population that increases the risk for disease and did not have any protection effect.About TG and HDL-C level, LPL gene has changed the TG and HDL measurement. We could study the influence of both risk factors. The result is G allele, increasing TG level and decreasing HDL level in the case group. Therefore, we conclude that S447X polymorphism influences the plasma lipid levels. In several studies, S447X polymorphism has played a protective role in CAD although in a recent study the result is different.In conclusion, in our study, the presence of G allele S447X polymorphism increases the TG level and decrease HDL level, so it increases the susceptibility CAD. Moreover, HindIII polymorphism doesn’t have any significant association with CAD.The limitation of this study is the number of our groups. It is recommended that in future studies, the number of samples should be more than our study.The authors acknowledge financial support from human genetics research group of ACECR, Fars branch and the hospitals staff for helping us. The authors would like to thank Dr. Nasrin Shokrpour at Center for Development of Clinical Research of Nemazee Hospital for editorial assistance.All patients gave written informed consents and the study was approved by our local ethic committee.There is no conflict of interest on this article.


CD24 gene regarding their associations with MS. To this end, univariate and multivariate meta-analysis were applied along with modifications to include data from family-trios so as to increase the robustness of the meta-analysis. We found that the polymorphism 226 C>T  of the CD24 gene is associated with MS according to the recessive mode of inheritance . Moreover, the 1527–1528 TG>del polymorphism is inversely associated with MS according to the dominant mode of inheritance . Conversely, the 1056 A>G and 1626 A>G polymorphisms were not found to be associated with MS. We conclude that the CD24 226 C>T polymorphism increases the risk of MS, while the 1527–1528 TG>del polymorphism seems to have a protective role against MS, suggesting that these two polymorphisms can be used as predictive biomarkers for MS development.CD24 is a cell-surface protein mainly expressed in cells of the immune and central nervous system (CNS), cells that play a critical role in the development of multiple sclerosis (MS). In the current study, we investigated four polymorphisms of the  Multiple sclerosis (MS) is a chronic and complex demyelinating disease of the central nervous system (CNS) with an occurrence of about 0.1% in Caucasian young adults . It is wCD24, although not detected in GWAS, is a gene that has been investigated thoroughly in regard to its association with autoimmune diseases, including MS, with promising results. The CD24 gene is located in the chromosomal region 6q21. Interestingly, the particular region (6q) has previously been suggested to be in linkage with MS [CD24 is also expressed in cells of the CNS such as neural and gaglion cells, astrocytes and microglia [CD24 expression is required for T-cell homeostatic proliferation [Of particular note,  with MS . The CD2 with MS ,9,10. CDicroglia ,9,10,11,feration ,13.CD24 gene have been found to be implicated in the etiology of MS and various degenerative diseases [CD24 pseudogene, which is located in the chromosomal region Yq11. A number of case-control studies have been performed to investigate the putative association of CD24 gene polymorphisms with MS development and progression, although the results are controversial. In the present study, we performed a complete meta-analysis of the currently available bibliographic data in order to decipher these associations and add statistical support to them.Four polymorphisms of the diseases ; these pdiseases ,15. rs nCD24 226 C>T polymorphism comprising 2085 patients and 2295 healthy controls  produced a significant association with OR 1.26 and 95% CI: 1.02–1.56. Similarly, both recessive and dominant modes resulted in significant association   showed that five out of the eight studies were necessary for achieving statistical significance, a finding that was expected considering the fact that the lower limit of the 95% confidence interval of the pooled estimate was close to unity. Nevertheless, the magnitude of the pooled OR did not change significantly in the sensitivity analysis (data not shown).The results of the eight populations analyzed in the present meta-analysis ,21,22,23 vs. CC) A–C. When vs. CC) . Becauseant mode . Time-trvs. wild-type allele homozygotes (TT vs. CC) yielded a robust and significant association with MS, having OR 2.44 and 95% CI: 1.77–3.38 .To further elucidate the mode of inheritance, multivariate meta-analysis was performed on the combined data available from six studies. The contrast of risk homozygotes .77–3.38 . Lambda vs. TG/TG + TG/del (recessive mode) yielded OR = 1.09 with 95% CI 0.06–18.64. Interestingly, the del/del + TG/del vs. TG/TG (dominant) gave a significant reverse association with OR = 0.57 with 95% CI 0.39–0.83  [vs. A, GG vs. GA + AA and GG + GA vs. AA contrasts, respectively, numbers that might not be very difficult to reach.Finally, meta-analyses were carried out for the 1056 A>G and 1626 A>G polymorphisms using data from two studies ,22. No s. (2003)  method wet al. (2003) method [vs. A, GG vs. GA + AA and GG + GA vs. AA contrasts, respectively, suggesting, as before, that statistical significance can be achieved easily.Likewise, no statistically significant association was attained under any contrast for the 1626 A>G polymorphism with MS . The het) method , statistCD24 polymorphisms with autoimmune diseases such as MS, systemic lupus erythematosus (SLE), rheumatoid arthritis or giant cell arthritis [CD24 was not detected in any GWASs, earlier classical linkage analyses [CD24 is a very promising biomarker for MS development. The fact that CD24 was not identified in GWASs does not necessarily underestimate our study since GWASs often capture only a part of the phenotypic variance, due to intrinsic methodological limitations. The stringent criteria used for statistical significance in GWAS result, in many circumstances, in decreased power to identify a moderate effect. This happens because in the GWAS context, we usually work in an agnostic manner and the primary concern is to reduce the risk of spurious findings and false positive results arising from multiple testing. On the contrary, in the current context, we followed a hypothesis-driven approach. That is, the CD24 gene had been chosen and studied in many independent studies due to some preliminary genetic evidence , as well as due to the presumed biological plausibility that might implicate CD24 antigen in the disease formation. Moreover, the present study includes populations from Iran and Argentina that were not included in previous GWASs. In support of the hypothesis that CD24 plays a pivotal role in the development of autoimmune diseases, Li et al. (2006) [CD24-deficient mice. Thus, the homeostatic proliferation, which should be slow-paced, loses its self-limiting capacity, and this results in the rapid death of the recipient CD24−/− mice.CD24 is a GPI-anchored cell membrane protein, with a molecular mass of 20 to 70 kD, and varying glycosylation. CD24 is a multifaceted protein implicated in inflammation, immunity—both adaptive and autoimmunity—and cancer . Many exrthritis    found thCD24 with MS. Our conclusion is supported by two lines of evidence. First, with univariate meta-analysis, significant association was identified with all modes of inheritance . Second, from multivariate meta-analysis, which can indicate the mode of inheritance, the significant association was strengthened and the recessive mode appeared to be the most prominent. In any case, the association of the CD24 226 C>T polymorphism with MS proved to be quite robust according to the overall estimate of our analysis. The findings of our study are in accordance with previous case-control studies showing that the 226 C>T polymorphism of CD24 is associated with another autoimmune disease, the SLE [The meta-analysis performed in this work, based on all the available data from the biomedical literature, clearly demonstrates a genetic association between the 226 C>T polymorphism of  the SLE ,28.CD24 gene were investigated. Our analysis showed that the 1527–1528 TG>del polymorphism has a protective role against the occurrence of MS. Significant associations were found in the allele and the del/del + TG/del vs. TG/TG genotype contrasts which both had zero heterogeneity. Multivariate meta-analysis further confirmed the above association and reinforced the dominant mode of inheritance. The same TG>del polymorphism has been shown in a case-control study to confer protection against SLE, as well [CD24 transcript [The idea that polymorphisms located in regulatory regions, can account for MS susceptibility has recently gained interest . To this as well  and espeCD24 gene polymorphisms, no association was found under any contrast. Noticeably, all SNPs are in close chromosomal proximity to each other and one would expect Linkage Disequilibrium (LD) between them. The two associated polymorphisms with MS have a distance of about 1400 bp. Nevertheless, no definite LD has been observed between 226 C>T and 1527–1528 TG>del in the literature, neither for MS and SLE nor for other diseases such as Chron’s disease [CD24 gene may have a recombination hotspot between these two polymorphisms [CD24 haplotypes and their associations with MS are greatly needed to clarify the causative polymorphisms.Conversely, based on meta-analyses we performed for the 1056 A>G and 1626 A>G  disease . It is pDespite the robustness of most of our results, the present study has some limitations. First, the number of studies included is relatively small, while the populations’ ethnic diversity is limited to Asians and Caucasians of European, USA, Argentinean and Iranian ancestry. Hence, additional studies with more participants from diverse ethnic backgrounds would be of great value, especially for the meta-analyses concerning the three polymorphisms located in the 3′ UTR. Second, significant heterogeneity was detected in three out of four analyzed polymorphisms. Regarding the 226 C>T polymorphism, heterogeneity was detected in the allele and the recessive mode contrasts. However, when the analyses were restricted to studies with populations in HWE, the heterogeneity was decreased. As far as the analysis of the 1527–1528 TG>del polymorphism is concerned, heterogeneity was present only in the recessive contrast, which yields non-significant results. Importantly, in the other contrasts, and particularly in the dominant mode contrast (the prevailing one) the heterogeneity was almost zero, reinforcing the robustness of the association. It is of particular interest that high heterogeneity appeared in all contrasts for the 1056 A>G polymorphism while zero heterogeneity was present in the contrasts of 1626 A>G polymorphism. Heterogeneity could be due mainly to small sample size, but also to the different criteria used to diagnose MS. Third, meta-analysis is subjected to methodological weaknesses of the original studies.i.e., family-based and population-based ones) and to detect the mode of inheritance. The multivariate method in particular is capable not only of identifying the mode of inheritance but also preserving the nominal type I error rate and protecting from multiple comparisons. Although the method identified the most plausible mode of inheritance, we chose to report all the available contrasts only for completeness. Finally, we took any available precaution in order to minimize different sources of bias, which is the main source of concern in this type of studies. Along these lines, we investigated the sources of heterogeneity, we searched for influential studies, and we performed all the available tests for detecting publication bias and time-trend bias.Overall, our study has several important advantages. First, a thorough and meticulous search was performed, including both a computer-aided and manual search, to identify all possible eligible studies included in published literature. Second, we did not impose any quality restriction and we did not exclude any study based on the design, the language or any other criteria, since most recent guidelines advocate against this. Third, we used modern statistical techniques in order to include all available studies  with the following keywords: “CD24 AND  AND ”. Retrieved abstracts were scrutinized and only the relevant ones were retained. The references from the retrieved articles were also investigated and the relevant ones were included in our study. We included all identified studies that provided data from which an estimate of the relative risk (the odds ratio) and its variance could be calculated. We did not impose any restrictions on the type of studies included with regard to the design, the language in which the study was written or any other quality measure.A comprehensive literature search was performed until September 2014 in PubMed  according to the eligibility criteria. In case problems of poor agreement occurred, they were resolved after discussion with the principle investigator (PGB) and the extracted data were recorded in a spreadsheet. From each article, the PubMed ID, first author’s name, year of publication, the total number of the subjects (cases/controls) as well as the population’s ethnicity and geographical location were recorded in the spreadsheet.Q statistic and the consistency index (I2) [Odds ratio (OR) was used to test the association between the mutant alleles and/or genotypes and MS, along with their 95% CIs . In the case of zero cells, a continuity correction was applied by adding the value 0.5 to all cells of the contingency table. Data were analyzed using the random-effects method with inverse-variance weights . The betdex (I2) . The famdex (I2) .vs. homozygotes and of risk allele homozygotes vs. homozygotes for the wild type allele [The multivariate random-effects method of meta-analysis, which can infer and quantify the genetic mode of inheritance directly, was also applied by estimating the ratio λ of the two log-odds ratios .To estimate possible publication biases, the rank correlation method of Begg and Mazumdar  was usedp-value <0.05 were considered statistically significant.In all analyses, we used STATA 13  and resu