The results of meta-analyses conducted by previous association studies between total homocysteine and schizophrenia suggest that an elevated total homocysteine level is a risk factor for schizophrenia. However, observational studies have potential limitations, such as confounding and reverse causation. In the present study, we evaluated a causal relationship between plasma total homocysteine and schizophrenia by conducting a Mendelian randomization analysis.MTHFR C677T polymorphism as an instrumental variable, which affects the plasma total homocysteine levels. To calculate the risk estimate for the association of this single nucleotide polymorphism (SNP) with schizophrenia, we conducted a meta-analysis of case–control studies that comprise a total of 11,042 patients with schizophrenia and 14,557 control subjects. We obtained an estimate for the association of this SNP with the plasma total homocysteine levels from a meta-analysis of genome-wide association studies comprising 44,147 individuals.We used the −4) for schizophrenia per 1-SD increase in the natural log-transformed plasma total homocysteine levels.By combining these two estimates, we demonstrated a significant effect of the plasma total homocysteine on schizophrenia risk, representing an OR of 2.15  contains supplementary material, which is available to authorized users. MTHFR) C677T (rs1801133) polymorphism is a well-characterized genetic variant. C677T of the MTHFR gene results in amino-acid substitution , and causes a reduction of enzyme activity and higher plasma total homocysteine levels [Homocysteine is a key substance in the methionine cycle, which is involved in one-carbon methyl group-transfer metabolism. The methylenetetrahydrofolate reductase  and the genotype-outcome association  in an unconfounded manner . By combMTHFR C677T polymorphism as an instrumental variable.In this study, we evaluated a causal relationship between plasma total homocysteine and schizophrenia by conducting a Mendelian randomization analysis based on the MTHFR C677T polymorphism  was evaluated by conducting a meta-analysis of case–control studies with the random-effect model by ‘metafor’, an R package. Eligible studies were identified using SZGene [MTHFR” or “schizophrenia”. We also conducted an additional manual search of reference lists and review articles. Studies meeting the following criteria were included for meta-analysis: (1) performed a case–control study , (2) provided data on genotype frequencies, and (3) was published in the English language. The two reviewers (Kinoshita M and Nishi A) selected the articles independently according to the above inclusion criteria, and then discussed the articles until they reached a consensus on every study used for the meta-analysis. Heterogeneity was assessed using the I2 statistic, and publication bias was assessed using funnel plots and a regression test [The risk estimate for the gene-schizophrenia association of the T allele of the g SZGene  and the ion test . OR and ion test , 29–59 bion test   from a recent meta-analysis of genome-wide association studies comprising 44,147 individuals [We used a pooled estimate of per-T allele standardized β coefficient (0.158) of the effect of the ividuals .scz/hcy) as log OR scz/hcy = / beta hcy/per T-allele, as in previous studies [scz/hcy is the (log) increase of schizophrenia risk by 1-standard deviation (SD) increase in the natural log-transformed plasma total homocysteine . Log OR scz/per T-allele is the (log) increase in schizophrenia risk per T allele of the MTHFR C677T polymorphism (gene-schizophrenia association). Beta hcy/per T-allele is the number of SD differences in the natural log-transformed plasma total homocysteine levels per the T allele  .We calculated a Mendelian randomization estimate of the effect of the plasma total homocysteine levels on the risk of schizophrenia  with significant heterogeneity . By combining two pooled estimates, OR scz/per T-allele from a meta-analysis of 36 case–control studies and beta hcy/per T-allele from a meta-analysis of genome-wide association studies by van Meurs and colleagues [scz/hcy of 2.15  for schizophrenia per 1-SD increase in the natural log-transformed plasma total homocysteine levels , SENSHIN Medical Research Foundation, and the Research Group for Schizophrenia.


S-transferase (GST) mu 1 and theta 1 were confirmed to exert independent effects on cancer. We concluded that the application of ETMA to real meta-analysis data was successful. Finally, we developed an R package, etma, for the detection of epistasis in meta-analysis [etma is available via the Comprehensive R Archive Network (CRAN) at https://cran.r-project.org/web/packages/etma/index.html].Conventional genome-wide association studies (GWAS) have been proven to be a successful strategy for identifying genetic variants associated with complex human traits. However, there is still a large heritability gap between GWAS and transitional family studies. The “missing heritability” has been suggested to be due to lack of studies focused on epistasis, also called gene–gene interactions, because individual trials have often had insufficient sample size. Meta-analysis is a common method for increasing statistical power. However, sufficient detailed information is difficult to obtain. A previous study employed a meta-regression-based method to detect epistasis, but it faced the challenge of inconsistent estimates. Here, we describe a Markov chain Monte Carlo-based method, called “Epistasis Test in Meta-Analysis” (ETMA), which uses genotype summary data to obtain consistent estimates of epistasis effects in meta-analysis. We defined a series of conditions to generate simulation data and tested the power and type I error rates in ETMA, individual data analysis and conventional meta-regression-based method. ETMA not only successfully facilitated consistency of evidence but also yielded acceptable type I error and higher power than conventional meta-regression. We applied ETMA to three real meta-analysis data sets. We found significant gene–gene interactions in the renin–angiotensin system and the polycyclic aromatic hydrocarbon metabolism pathway, with strong supporting evidence. In addition, glutathione  Many complex human traits are considered to be associated with genetic factors, and previous genetic studies have identified a large number of causal variants . HoweverMeta-analysis has become a popular method for discovering genetic risk variants, because it can increase detection power ,8. HowevMeta-regression is a common approach to assessing interaction effects in meta-analysis of randomised controlled trials ,15, and In summary, a single trial often has insufficient sample size, but meta-analysis lacks sufficient detailed individual information. The current method using averaged summary data for detecting interaction effects faces the challenge of inconsistent estimates. We propose a Markov chain Monte Carlo (MCMC)-based method, called ‘Epistasis Test in Meta-Analysis (ETMA)’, using genotype summary data for obtaining consistent estimates of epistasis in meta-analyses.x1) and SNP2 (x2) are binary variables encoded as 0 and 1 , and that the dependent variable (y) is an outcome event encoded as 0 and 1 . Under the above assumptions, we defined p1, p2, p3, p4, p5 and p6 as follows:We assume that SNP1 (p1):Disease risk in subjects with wild-type alleles of SNP1 and SNP2 (p2):Disease risk in subjects with wild-type alleles of SNP1 and mutation of SNP2 (p3):Disease risk in subjects with mutations of SNP1 and wild type of SNP2 (p4):Disease risk in subjects with mutations of SNP1 and SNP2 (p5):Mutation frequency of SNP1 (p6):Mutation frequency of SNP2 :Main effect of SNP1 on y :Main effect of SNP2 on y (ORinteraction):Gene–gene interaction effect between SNP1 and SNP2 on p2, p3 and p4 can be calculated by the following equations:Thus, x1 mutation inthe case group , (2) of thex1 mutation in the control group, (3) of the x2 mutation in the case group  and (4) of the x2 mutation in the control group . These four exposure rates can be represented as combinations of p1, p2, p3, p4, p5 and p6. Their relationships are shown as follows  of the According to the above relationship, we can calculate the likelihood of the sample using binomial distribution and execute the MCMC algorithm as follows:X is an n × 8 matrix including the numbers of variants of SNP1 and SNP2 in case and control in each study (n is the number of studies). P is an n × 3 matrix describing p1, p5 and p6 in each included study, and OR is a 1 × 3 vector containing ORy,SNP1, ORy,SNP2 and ORinteraction. X is a known matrix, and P and OR are unknown matrices. P and OR can be expressed as follows:P, OR| X) as follows:We can use the approach outlined in the following iteration process to construct a Markov chain stationary distribution Pr((0) for OR (OR(0) = [1 1 1]), we iterate the following steps for m = 1, 2, …Starting with initial values ORP(m) from Pr(P(m) |X, OR(m−1))Step 1: Sample (m) from Pr(OR(m) |X, P(m))Step 2: Sample ORStep 1 is to assume that ORy,SNP1, ORy,SNP2 and ORinteraction are known parameters and to estimate p1, p5 and p6 in each included study using the Metropolis–Hastings algorithm. This algorithm will find the p1, p5 and p6 that maximise the likelihood of a given sample. Finally in this step, we can obtain the p1, p5 and p6 of each included study. Step 2 is to assume that p1, p5 and p6 are known parameters and to estimate ORy,SNP1, ORy,SNP2 and ORinteraction. We assume that each cell of P or OR is described by a random walk in the logistic or logarithmic normal distribution, respectively. The above two steps are repeated until convergence of the log likelihood.In simple terms, https://cran.r-project.org/web/packages/etma/index.html]. The main function of etma package is ‘ETMA’, and ETMA use an n × 8 matrix including the numbers of variants of SNP1 and SNP2 in case and control in each study (n is the number of studies) to analyse gene-gene interaction. Thus, the inputs of ETMA function include: (1) the number of wild type of SNP1 in case group, (2) the number of mutation type of SNP1 in case group, (3) the number of wild type of SNP1 in control group, (4) the number of mutation type of SNP1 in control group, (5) the number of wild type of SNP2 in case group, (6) the number of mutation type of SNP2 in case group, (7) the number of wild type of SNP2 in control group, and (8) the number of mutation type of SNP1 in control group.An R package, etma, is developed for carrying out the epistasis detection in meta-analysis . However, the interaction term of GSTM1 and GSTT1 is not significant (p = 0.2525). Although these genes belong to the same family, we also considered this to be a reasonable result. The GST family has many overlapping functions, and GSTM2 can perform more functions in subjects with a GSTM1 null genotype . Moreovep = 0.0201), and the main effect of each SNP is not significant . CYP1A1 and GSTM1 are two important members in the PAH metabolism pathway [The analysis of the metabolism pathway of PAHs and oral cancer shows a significant gene–gene interaction effect (OR: 2.220 (95% CI: 1.166–4.225),  pathway , and PAH pathway . Moreove pathway .The analysis of the RAS and chronic kidney disease also shows a significant gene–gene interaction (OR: 1.305 (95% CI: 1.048–1.624), p = 0.0188). This result indicates an interaction effect between AGT M235T (rs699) and ACE I/D rs4340) on chronic kidney disease, but that neither alone increases the risk of chronic kidney disease, because its main effect is not significant . The detailed mechanisms and possible reasons are described in the Discussion. We judged these results to be consistent with expectations. The AGT M235T polymorphism has been confirmed to affect blood AGT concentration , and exc0 on chroBecause the technological limitation of multi-loci analysis, previous meta-analysis often focus on the association between a specific disease and a SNP but not on the epistasis. Thus, the existing meta-analysis including more than 1 SNP are rare. However, epistasis is important in genetic association study. Previous studies considered that ‘missing heritability’ is often attributed to the technical limitations of epistasis estimation –5. The sx1 mutation in the case group, of the x1 mutation in the control group, of the x2 mutation in the case group and of the x2 mutation in the control group) in each included study. Some studies matched the environmental factors to reduce the confounding bias, sacrificing 1 degree of freedom. Thus, fitting of gene–environment interactions using ETMA will constitute overfitting. However, although this defect causes a problem in ETMA, it solves the problem of inconsistent estimates in meta-regression analysis [ETMA may lack the ability to detect gene–environment interactions because of issues related to degrees of freedom. ETMA is based on four exposure rates  was developed in the R language and may be extensively applied to detect epistasis in meta-analyses.In conclusion, ETMA has acceptable type I error rates under all simulation condition. Moreover, it not only successfully facilitates consistency of evidence but also increases power. Although our results also show that individual data analysis is the most powerful analysis, sufficient detailed information is difficult to obtain, so that the practical value of ETMA for meta-analysis is higher. Because ETMA assumes independence between two loci, analysis of loci on different chromosomes is a better option (at least on different genes). For gene–environment interactions, we suggest that the researcher use conventional meta-regression unless it is verified that the distribution of environmental factors has not been artificially changed (such as by matching). Finally, a package Click here for additional data file.S2 FigPage 1 shows the MCMC plot for the first iteration, page 2 the second and so on. The final page shows the final iteration result, and the analysis results are based on this chain value.(PDF)Click here for additional data file.S3 FigPage 1 shows the MCMC plot for the first iteration, page 2 the second and so on. The final page shows the final iteration result, and the analysis results are based on this chain value.(PDF)Click here for additional data file.S1 TableVariable definitions:Study: the first author and published year in each included studyEthnicity: the ethnicity of included population.Country: the country of study.Cancer: the cancer type.case.GSTM1.0: the number of functional GSTM1 carriers in cases (including heterozygous).ctrl.GSTM1.0: the number of functional GSTM1 carriers in controls (including heterozygous).case.GSTM1.1: the number of null/null GSTM1 carriers in cases (risk type).ctrl.GSTM1.1: the number of null/null GSTM1 carriers in controls (risk type).case.GSTT1.0: the number of functional GSTT1 carriers in cases (including heterozygous).ctrl.GSTT1.0: the number of functional GSTT1 carriers in controls (including heterozygous).case.GSTT1.1: the number of null/null GSTT1 carriers in cases (risk type).ctrl.GSTT1.1: the number of null/null GSTT1 carriers in controls (risk type).(XLSX)Click here for additional data file.S2 TableVariable definitions:Author: the first author in each included article.Year: the year of publication.Country: the country of study location.case.CYP1A1.0: the number of subjects with AA genotype in rs4646903 in cases.case.CYP1A1.1: the number of subjects with AC/CC genotype in rs4646903 in cases (risk type).ctrl.CYP1A1.0: the number of subjects with AA genotype in rs4646903 in controls.ctrl.CYP1A1.1: the number of subjects with AC/CC genotype in rs4646903 in controls (risk type).case.GSTM1.0: the number of functional GSTM1 carriers in cases (including heterozygous).case.GSTM1.1: the number of null/null GSTM1 carriers in cases (risk type).ctrl.GSTM1.0: the number of functional GSTM1 carriers in controls (including heterozygous).ctrl.GSTM1.1: the number of null/null GSTM1 carriers in controls (risk type).(XLSX)Click here for additional data file.S3 TableVariable definitions:Author: the first author in each included article.Year: the year of publication.Race: the race of the study population.Type: the subtype of chronic kidney disease in each study.case.ACE.0: the number I allele in rs4340 in cases.case.ACE.1: the number D allele in rs4340 in cases (risk type).ctrl.ACE.0: the number I allele in rs4340 in controls.ctrl.ACE.1: the number D allele in rs4340 in controls (risk type).case.AGT.0: the number M allele in rs699 in cases.case.AGT.1: the number T allele in rs699 in cases .ctrl.AGT.0: the number M allele in rs699 in controls.ctrl.AGT.1: the number T allele in rs699 in controls .(XLSX)Click here for additional data file.S1 Text(DOCX)Click here for additional data file.S2 Text(DOCX)Click here for additional data file.


ACP1 gene was closely related to the risk of CAD in Han Chinese . This significant association of rs3828329 with CAD was only found in the females . Moreover, rs3828329 was likely to exert its effect in females aged 65 years and older . Further meta-analyses showed that the rs12526453 of PHACTR11 gene  and the rs11066301 of PTPN11 gene  were associated with CAD risk in multiple populations. Our results showed that the polymorphisms rs12526453 and rs11066301 are significantly associated with the CAD risk in multiple populations. The rs3828329 of ACP1 gene is also a risk factor of CAD in Han Chinese females aged 65 years and older.Recent studies showed that the serum alkaline phosphatase is an independent predictor of the coronary artery disease (CAD). In this work, we aimed to summarize the association between three phosphatase related single nucleotide polymorphisms  and the risk of CAD in Han Chinese. Our results showed that the rs3828329 of the  Coronary artery disease (CAD) is one of the leading causes of death in the developing and developed countries . CAD is PHACTR1, rs3828329 of ACP1 and rs11066301 of PTPN11. The PHACTR1 gene encodes the protein phosphatase 1 and actin regulator 1 (PHACTR1), an enzyme regulating endothelial nitricoxide in humans [PTPN11 gene and is known to modulate multiple signaling involved in inflammatory responses [PTPN11 mutations have also been detected in acute myeloid leukemia [Three genetic variants connected with phosphatase are shown to be associated with the risk of CAD ,7, inclun humans , immunoln humans  and cancn humans . ACP1 con humans . ACP1 man humans . Previoun humans . As a meesponses ,18. PTPNesponses , and incesponses . PTPN11 esponses , glioma esponses , myelopresponses  and gastesponses ,25. Actileukemia , breast leukemia , colorecPHACTR1, ACP1 and PTPN11) to the CAD risk in Eastern China by meta-analyses and case-control study. This study aimed to summarize the contribution of the polymorphisms of three genes (ACP1 gene.As shown in PHACTR11) with CAD. Since substantial heterogeneity was observed among the overall studies , a random-effect model was applied for the meta-analysis. As shown in PHACTR11 gene was a risk factor for CAD . The analysis was carried out in multiple populations including European, North American, and Asian. Strong association of rs12526453 with CAD was observed in the European studies  < 0.0001), the North American studies  = 0.002) and the Asian studies  < 0.0001). Subgroup analysis indicated that the population was likely to be the main source of heterogeneity  and the Asian studies . In contrast, no heterogeneity was observed in the North American studies .A total of 10 reports including 19 studies  were selected in the meta-analysis for the association of rs12526453 . The pooled data showed a significant association between rs11066301 and CAD risk . No visual publication bias in the meta-analysis was detected by the funnel plot . Among the studied SNPs, only rs3828329 of the ACP1 gene was significantly correlated with CAD risk . Moreover, rs3828329 showed a strong association with CAD risk under the dominant and recessive model . No significant differences between case and control groups were found for rs12526453 and rs11066301  and over 65 years older . A significant association was observed between rs3828329 and CAD risk in females older than 65 years .A case-control cohort was recruited to investigate the relationships between three SNPs and CAD risk in Han Chinese. The distribution of genotypes and alleles were listed in 11066301 . AdditioPHACTR1, ACP1 and PTPN11) in CAD was explored through meta-analysis and case-control study. Our results showed that rs12526453 of the PHACTR11 gene and rs11066301 of PTPN11 gene were associated with CAD risk in multiple populations. The rs3828329 of the ACP1 gene is closely related to CAD risk in Han Chinese. In addition, through gender-stratified comparison, rs3828329 of the ACP1 gene was associated with CAD risk in females. In this work, the significance of the polymorphisms of the three phosphatase association genes  gene are significantly associated with atherosclerotic cerebral infarction (ACI) in the Chinese population [Phosphatase is implicated in many human diseases, such as cancer, diabetes and cardiovascular disease ,40. Recepulation . Geneticpulation ,44. The pulation , and thepulation .ACP1 were shown to be associated with the risk of multiple diseases, such as favism [ACP1 polymorphism may play an important role in CAD through inducing enzymatic activity and affecting biochemical and functional properties of p53 [ACP1 gene is has been shown to be significantly associated with fasting insulin and insulin sensitivity in type 2 diabetes in Mexican-Americans [ACP1 rs3828329 and CAD risk. In this work, our case-control study showed that rs3828329 was significantly associated with CAD in Han Chinese. A statistical calculation showed that the rs3828329 of the ACP1 gene had 93.9% power to detect the relative risk at the nominal Type I error rate <0.05. The sample size may not be optimal, although it should be sufficient to describe a tendency that may guide clinical practice.Common variants of s favism , cancer s favism , type 1 s favism  and cards favism . The ACPs of p53 . SNP rs3mericans . HoweverPHACTR1 variants that influence the risk of myocardial infarction (MI) in genome-wide association studies (GWAS) were identified [PHACTR1 showed directionally consistent associations with CAD risk in type 2 diabetes [PHACTR1 was shown to be the same background haplotype as rs12526453  [PTPN11 locus are considered to be a cause of Noonan syndrome and LEOPARD syndrome [PTPN11 mutations are correlated with congenital heart defects in Noonan and LEOPARD syndromes [PTPN11 polymorphism rs11066301 located on 12q24 was shown to be associated with platelet count in humans [PTPN11 polymorphisms could influence serum lipid levels in a sex-specific pattern in Northeast Chinese [p < 0.0001). The rs11066301 showed a significant association with CAD risks in European and Asian populations through meta-analysis of 27,097 individuals. Strong heterogeneity in the meta-analysis for rs12526453 was mostly due to the different populations in the European studies and the Asian studies (entified . SNP rs1diabetes . The oth = 0.37) . Both th = 0.37) . Epidemi = 0.37) . In the  = 0.37) . Throughsyndrome ,57. Evidyndromes . The PTPn humans . The PTP Chinese . In this studies .There are several limitations of this work. Firstly, the sample size of the case-control study was moderate and might not be sufficient to perceive genes involved with moderate or minor effect. Secondly, only three SNPs were checked for the association with CAD. Other genetic polymorphisms in the selected genes might be involved as the real functional markers of CAD. Further large sample studies are necessary for verifying the association between other polymorphisms of phosphatase and CAD risk in various populations.PHACTR1”, “PTPN11”, “ACP1”, “polymorphism”, “variation”, “rs11066301”, “rs12526453”, “rs3828329” paired with “coronary artery disease”, respectively. Full text articles were read to select the related information. References listed on the retrieved articles and previous meta-analyses on this topic were searched to appraise other studies of potential relevance. Meanwhile, the papers published in Chinese or English till 2013 were included. Studies were selected based on the following inclusion criteria: (1) the study must be case-control or a prospective design; (2) the study must evaluate the relationship between ACP1 rs3828329, PHACTR1 rs12526453 or PTPN11 rs11066301and CAD; (3) the study contains complete data with genotype and allele frequencies or odds ratio (OR) with 95% confidence interval (95% CI); (4) the genotype distribution of controls is in Hardy-Weinberg equilibrium (HWE). Information was collected from each study, including first author, publication year, study design, total number of cases and controls, OR and 95% CI.The meta-analyses were performed to examine the association of the three SNPs with CAD. We systematically searched in multiple literature databases including EMBASE, PubMed, Web of Science and China National Knowledge Infrastructure (CNKI), Wanfang Chinese Periodical Database. The search strategy was to use the following keywords in different combinations: “A total of 1086 unrelated individual inpatients were recruited from LaiWu TaiShan Medical College Hospital in Laiwu city of Shandong province, China. Among them, 666 CAD patients were confirmed by the angiographic evidence that the stenosis was greater than 50% in at least the major coronary artery  or there® double strand (dsDNA) DNA Quantification Kit . Amplification was performed on the ABI Geneamp® PCR System 9700 Dual 384-Well Sample Block Module  for the Polymerase Chain Reaction (PCR). PCR conditions included an initial denaturation stage at 94 °C for 15 s, followed by 45 amplification cycles of 94 °C for 20 s, 56 °C for 30 s, and primer extension at 72 °C for 1 min, and then a final extension for 3 min at 72 °C. Primer extension for genotyping was performed on the SEQUENOM® Mass-ARRAY iPLEX® platform according to the manufacturer's instructions [Human genomic DNA was isolated from peripheral blood samples using a conventional phenol/chloroform method, and was quantified using the PicoGreenructions . 2 statistic) [2 value >50% indicated a significant heterogeneity among the studies included in the meta-analysis [The meta-analyses were performed by the RevMan software  and the Stata software . Statistical heterogeneity between studies was estimated using the Q-test  and incoatistic) . An I2 vanalysis . Random-analysis . Publicaanalysis . p-value 0.05 was considered as significant.For the case-control study, HWE was analyzed using Arlequin program (version 3.5) . DiffereACP1 gene is strongly associated with the CAD risk in Han Chinese females aged 65 years and older. Meta-analyses supported that the rs12526453 of PHACTR11 gene and the rs11066301 of PTPN11 gene are associated with CAD risk in multiple populations.Our case-control study showed that the rs3828329 of the


APOC3) rs5128 polymorphism and plasma levels of apolipoprotein C3 (APOC3) and lipids have reported apparently conflicting findings. This meta-analysis aimed to investigate the associations of the rs5128 polymorphism with fasting APOC3 and lipid levels.Studies of the association between the apolipoprotein C3 gene  , total cholesterol (TC) , and low-density lipoprotein cholesterol (LDL-C)  than the non-carriers. No significant association between the APOC3 rs5128 polymorphism and lower levels of high-density lipoprotein cholesterol (HDL-C) was detected under the dominant model .The results showed that the carriers of the variant allele G had higher levels of APOC3 [standardized mean difference (SMD): 0.22, 95% confidence interval (CI): 0.12-0.31, APOC3 rs5128 polymorphism and higher levels of APOC3, TG, TC and LDL-C, but further studies are needed to elucidate the underlying mechanisms.The results from the present meta-analysis demonstrate a significant association between the The online version of this article (doi:10.1186/s12944-015-0027-0) contains supplementary material, which is available to authorized users. Cardiovascular disease (CVD) is now the leading cause of death worldwide, both in developed countries and in many developing countries . After dAPOC3) is a member of the APOA1/C3/A4/A5 gene cluster and located on chromosome 11q23, an area in strong linkage with lipid metabolism  was employed to ensure adequate statistical power. When data was presented for more than one subpopulation  in one article, each subpopulation was treated as a separate comparison in this meta-analysis. In addition, subgroup analyses were conducted by age, gender, ethnicity and health condition. Age subgroups were defined as adults and children (under 18 years old). Ethnic subgroups were defined as Caucasian, Asian, and the populations of other ethnic origins. The meta-analyses on the subgroup were only performed with at least four comparisons to ensure adequate statistical power.2-based Q-statistic at a significance level of P < 0.05. Galbraith plot was used to detect the potential sources of heterogeneity, and the pooled SMD was recalculated after removal of the outlier studies identified in the plot. The populations in the studies were tested for Hardy-Weinberg equilibrium (HWE) by χ2 test; the significance level is defined as α < 0.05. Publication bias was assayed by Egger's linear regression test [The pooled standardized mean difference (SMD) and its 95% confidence interval (CI) were used to assess the differences of the variables between the genotypes. A random effects model was used for all analyses because both between-study and within-study heterogeneity is considered in this model; it provides a more conservative evaluation of the significance of the association than the fixed effects model . Heterogion test , and a sInitial search of the literature yielded 646 publications. Five hundred and eighteen studies were excluded according to title and abstract. Then full text articles were retrieved and assessed on the basis of the inclusion criteria. Eighty-six papers were ineligible for the following reasons: 57 papers did not provide complete data for this meta-analysis, 24 papers presented data on other polymorphisms, 2 papers had subjects overlap with other publications, and 3 studies were based on pedigree data. In the end, 42 studies were selected for this meta-analysis.The characteristics of the 42 included studies were summarized in Table 28Sixty-seven comparisons were distinguished according to the categories such as age, gender, smoking status, and health condition. Of these, 18, 64, 49, 42 and 54 comparisons were included for comparing the differences in APOC3, TG, TC, LDL-C and HDL-C, respectively (Table P < 0.00001), TG , TC , and LDL-C  than the non-carriers (Table P = 0.156) was detected between the G carriers and the non-carriers , TG , TC  and LDL-C  were also significant  and children for TG   and other ethnic origins . The significant associations between the APOC3 rs5128 polymorphism and higher LDL-C levels were detected in females , children , Asians , and marginally in Caucasians . The associations between the APOC3 rs5128 polymorphism and higher levels of LDL-C were also significant in healthy subjects  and diabetic patients  .Then the subgroup analyses stratified by the characteristics of the subjects were performed. The associations between the P = 0.018, Pheterogeneity = 0.158; TG: SMD: 0.17, 95% CI: 0.14-0.21, P < 0.00001, Pheterogeneity = 0.311; TC: SMD: 0.12, 95% CI: 0.08-0.17, P < 0.00001, Pheterogeneity = 0.152; LDL-C: SMD: 0.07, 95% CI: 0.03-0.12, P = 0.002, Pheterogeneity = 0.270). No significant heterogeneity was found among the total comparisons and the subgroup analyses for HDL-C.There was significant heterogeneity among the total comparisons for APOC3, TG, TC, and LDL-C. Seven comparisons , 12 comparisons , 3 comparisons  and 4 comparisons  were respectively identified as the main contributors of the heterogeneity for APOC3, TG, TC, and LDL-C by using Galbraith plot. The heterogeneity was effectively removed or decreased after exclusion of these outlier studies, but the SMD values andtheir 95% CI did not change significantly , TG , TC , LDL-C , and HDL-C . Figures A-E of the Additional file The Egger’s test revealed that no publication bias was present in the analyses for APOC3 , and did not provide data separately for heterozygote CG and homozygote GG. Therefore, a dominant model (CC vs. CG + GG) was employed for this meta-analysis to ensure adequate statistical power. The results suggested that the analysis  demonstrAPOC3 rs5128 polymorphism with plasma HDL-C levels was not detected in this meta-analysis.Subgroup analyses by age, gender, ethnicity and health condition were performed since they might be important variables in determining associative risk with dyslipidemia. For example, the present analyses indicated that age might modulate the association between the rs5128 polymorphism and TG levels since the significant association especially exists in males and females, but not in children . Firstly, the results from this meta-analysis were based on the random effects model. Comparing with fixed effects model, the random effects model is a more conservative method and less likely to produce false-positive results. Secondly, 42 studies with 23846 subjects were included in this meta-analysis. Among the subjects, 26% of them were the carriers of the rs5128 G allele. Since the incidence of the G allele carriers was sufficiently high, type I error may have been prevented.The associations of the APOC3 and leads to a higher plasma APOC3 level since the rs5128 polymorphism is located in the 3'UTR of exon 4 of this gene. In the present analyses, a significant higher level of APOC3 was found in G carriers comparing with the CC genotype subjects. Previous studies have shown that APOC3 can increase plasma TG levels. Three mechanisms are involved in the elevation of TG levels by APOC3. Firstly, APOC3 promotes the assembly and secretion of VLDL in liver [APOC3 in McA-RH7777 cells by recombinant adenovirus expression vector resulted in significantly increased VLDL assembly and secretion with a dose-dependent effect [The possible mechanism under which the rs5128 polymorphism modulates plasma APOC3 has not been clarified yet. One explanation could be that the G allele enhances the transcriptional activity of in liver -58. Overt effect . APOC3 gt effect . Functiot effect ,58. Secot effect . ThirdlyAPOC3 is a member of the APOA1/C3/A4/A5 gene cluster which is the key component in modulating lipid metabolism [APOA1/C3/A4/A5 gene cluster have been found to significantly affect plasma LDL-C levels [The present meta-analysis also suggested the significant associations of the rs5128 polymorphism with higher levels of LDL-C and TC. There is interrelationship between TG metabolism and cholesterol metabolism in the body, so the elevation of VLDL-TG by APOC3 might have disturbed the cholesterol metabolism and increased plasma LDL-C and TC levels. For example, LDL particles are formed in the bloodstream as VLDL particles lose TG through the action of LPL. Hence, the increase of VLDL Levels can cause the elevation of LDL levels, and accordingly the LDL-C levels. Since approximately 70% of plasma cholesterol molecules are resided in LDL particles, the elevation of LDL-C can lead to higher levels of TC. In addition, it is likely that the rs5128 polymorphism is in linkage disequilibrium with other causative mutations involved in the metabolism of LDL. tabolism . SeveralC levels .APOC3 rs5128 polymorphism and lower levels of HDL-C by meta-analysis. One reason could be that HDL is metabolized independently of APOC3 [APOC3 rs5128 polymorphism was found to be associated with the plasma levels of APOC3, TG, LDL-C and TC, but not HDL-C.In the current study, we did not find significant association between the of APOC3 ,5. Unlikof APOC3 . TherefoThe limitations of the present meta-analysis should be noted. Firstly, dyslipidemia is involved in a number of genes as well as some environmental factors. However, the interactions of the rs5128 polymorphism with other polymorphic loci or environmental factors on plasma APOC3 and lipid levels have not been investigated in this analysis due to the lack of the original data of the included studies. In other words, the more precise results could have been gained if more detailed individual data were available or the stratification analyses based on the environmental factors such as diet, exercise, and smoking status were performed. Secondly, a relatively small number of subjects were included for the association analysis between the rs5128 polymorphism and plasma APOC3 levels due to the limited available studies, which may reduce the statistic power and even cause the type II errors . More studies with larger sample size are required to further investigate the association. Thirdly, this meta-analysis only included the studies published in English because it was very difficult to get the full papers published in various languages.APOC3 rs5128 polymorphism and higher levels of APOC3, TG, TC, and LDL-C were found in the present meta-analysis.In conclusion, the significant associations between the


Most Parkinson’s disease (PD) patients present without known family history and without a diagnosed prodromal phase, underscoring the difficulty of employing primary (neuroprevention) and secondary (neuroprotection) preventions. In cases of monogenic forms, however, potential gene-carrying family members of a proband could engage in neuroprevention, such as exercise or diet modifications, to attenuate the risk of, or delay, disease development. However, a historical lack of recognized disease-modifying interventions has limited clinicians’ ability to recommend reliable preventive measures in caring for at-risk populations. We briefly analyze the first retrospective study to examine caffeine consumption and PD risk in a LRRK2 R1628P cohort. Meta-analyses , 2 suggetagonism ), a symptagonism ), reverstagonism ), or contagonism ).n = 11) OR of PD; by contrast, gene-carrier caffeine-consumers had a lower increased OR of 3.07 . On the basis of these data, the study authors suggest that caffeine intake may be associated with reduced risk of PD development especially in those who are gene-carriers.Most recently, a new case–control study  examinedn = 28; 18 caffeine-consumers and 10 caffeine-abstainers) and controls , yielding an imprecise OR (1.94 to 122.3) that clearly overlapped with the OR for gene-carrier caffeine-consumers. Second, recall bias or other sources of measurement error may have influenced the interpretation of the PD environmental risk factor questionnaire. Third, it is unclear what number of multiple hypotheses were tested in this cohort; if dozens of potential gene-environment interactions were queried, the chances of a spurious result are high. It should be cautioned that many gene-environment findings based upon single cohort studies are not reproduced. Finally, the physiologic mechanism(s) governing the putative impact of caffeine in the PD neurodegenerative cascade remains unclear. Recognizing the excitement that the prima-facie favorable findings of this study may generate among patients and clinicians, these key caveats should be considered in the course of crafting an evidence-based and patient-centered approach to neuropreventive counseling and care.Some caveats should be considered when interpreting these results. First, the sample size was insufficient to provide an estimate of a true effect, as within the R1628P sample, there were too few PD cases  and dementia . A recenIf such a study is replicated in a larger series—which is critical for ascertainment of such gene-environmental interactions—it may have implications for other well-known LRRK2 variants, such as G2019S, which has a calculated disease penetrance of 26 % by age 80 . Might cNot applicable.Not applicable.Not applicable.


IL2RA) gene have been suggested to be associated with type 1 diabetes (T1D) susceptibility. However, the results from individual studies are inconsistent. To explore the association of IL2RA polymorphisms with T1D, including rs11594656, rs2104286, rs3118470, rs41295061 and rs706778, a meta-analysis involving 10 independent studies with 19 outcomes was conducted: five studies with a total of 10,572 cases and 12,956 controls were analysed for rs11594656 with T1D risk, three studies with 7300 cases and 8331 controls for rs2104286, three studies with 3880 cases and 5409 controls for rs3118470, five studies with 11,253 cases and 13,834 controls for rs41295061 and three studies with 1896 cases and 1709 controls for rs706778 respectively. Using minor allelic comparison, the five investigated SNPs were all observed to have a significant association with T1D: For rs11594656, fixed effect model (FEM) odds ratio (OR) 0.87, 95% confidence interval (CI) 0.83, 0.91; rs2104286, FEM OR 0.81, 95% CI 0.77, 0.85; rs3118470, FEM OR 1.23, 95% CI 1.16, 1.31; rs41295061, random effect model (REM) OR 0.67, 95% CI 0.60, 0.76 and rs706778 FEM OR 1.20, 95% CI 1.08, 1.33. Similar results were obtained when all the included studies were calculated by a REM. Our meta-analysis suggests that all five SNPs in the IL2RA gene are risk factors for T1D risk, and rs11594656, rs2104286 and rs41295061 are the most associated SNPs in the populations investigated. This conclusion warrants confirmation by further studies.Single nucleotide polymorphisms (SNPs) in the interleukin 2 receptor alpha ( IL2RA, also known as CD25) encodes the α-chain of the IL-2 receptor complex and binds to IL-2 with high-affinity. Studies have indicated that IL-2/IL-2RA-mediated regulatory mechanisms play a central role in preventing T1D IL-2/IL-2RA-dependent proliferation of CD4+ FOXP3+ Tregs could be strongly linked to their efficiency in the immune homoeostasis, as impairment of CD4+ FOXP3+ Treg in T1D occurs primarily because of the inefficient induction and maintenance of Tregs, with deficiencies in IL-2/IL2RA signalling Type 1 diabetes (T1D) is a complex, multigenetic autoimmune disease featured by destruction of the insulin producing beta-cells of the pancreas by autoreactive T lymphocytes. The interleukin 2 receptor alpha  and rs11594656; and one SNP in the intron 1, rs2104286. Furthermore, it has been demonstrated that rs41295061 was associated with glutamate decarboxylase antibody positivity in T1D patients et al. The association of the Despite strong functional evidence for the correlation of these SNPs with the immune status in T1D, the results of the genetic association studies of T1D remain inconsistent. To evaluate the potential role of these five SNPs in influencing T1D susceptibility, we performed a meta-analysis on eligible studies to confirm the association.IL2RA gene polymorphisms in T1D. Search strategies were investigated using combinations of the following search terms: (IL2RA or CD25) and (T1D) and . The publication language was restricted to English, but no restriction was set on the source of control participants . To identify additional relevant studies, we also searched the reference lists and the Medline option ‘Related Articles’ of the selected articles.Electronic databases (Medline and EMBASE) were searched up to March 2015 for all genetic association studies evaluating the i) study evaluated the association of IL2RA polymorphisms (rs11594656 and/or rs2104286 and/or rs3118470 and/or rs41295061 and/or rs706778) with T1D; (ii) study had sufficient published data to estimate an odds ratio (OR) with 95% confidence interval (CI) or provided raw data that allowed us to calculate them; (iii) if the data were duplicated or had been published more than once, the most recent and complete study was chosen; (iv) studies were excluded if the genotype distribution of the controls deviated from Hardy-Weinberg equilibrium (HWE) and (v) review articles, abstracts, editorials, reports with incomplete data and studies based on pedigree data were also excluded.Any human genetic association study, regardless of sample size, was included in the meta-analysis if it met the following criteria: . Not all articles reported the necessary statistics directly, so in some instances we transformed and estimated an OR from the reported data P < 0.05 for case-control studies and P < 10−5 for GWAS Z-test, and P < 0.05 was considered statistically significant. The heterogeneity between the studies was evaluated with chi-squared based Q statistic and I2 metric. Heterogeneity was considered significant at P < 0.05 for the Q statistic and I2 > 50% for the I2 metric. The pooled OR was calculated by a fixed effect model  or a random effect model  according to the heterogeneity among studies et al. P < 0.05 was considered statistically significant). All statistical analyses were conducted using STATA version 11.0 .The distribution was considered to be deviated from HWE at A total of 10 studies Results of pooled analyses are summarized in detail . Our metet al. et al. Significant heterogeneity was only observed in the studies investigating rs41295061 polymorphism , and senAs expected, the funnel plots for the associations of the investigated SNPs with T1D were symmetrical and the results for modified Begg’s and Egger’s tests were not significant, confirming that our results were statistically robust and not affected by publication bias .et al. i.e. 0.00001–0.0001; data not shown), which implicated that the results may be statistically robust.Several GWASs and a number of case-control studies have examined the association between the investigated five SNPs and T1D risk, but the results showed significant between-study variation. So we conducted a meta-analysis to obtain a more definitive conclusion. Our meta-analysis results suggested all the investigated SNPs had a significant association with T1D risk in overall. Although the influence analysis indicated that the study from Maier et al. et al. et al. IL2RA locus, rs11594656, rs2104286 and rs41295061, as a general autoimmunity gene contributing to the pathogenesis of autoimmune diseases, such as T1D. And the other two SNPs need to be further verified by a greater number of participants.The five investigated SNPs were independently tagged polymorphisms of IL2RA gene. Studies have indicated that the rs41295061 protective haplotype that is only associated with T1D, the rs2104286 protective haplotype that is associated with MS, T1D and RA and the rs11594656 haplotype that is associated with protection from T1D but risk for MS etc. Initial inspection of the data did not immediately identify any likely candidate variable or study that was significantly impacting on the result. The reason for this is unclear, but it may be that populations also have environmental differences that affect their sensitivity to particular genomic variants, such as viral infections, toxins and diet.Heterogeneity is potentially a significant problem when interpreting the results of any meta-analysis of genetic association studies IL2RA polymorphisms. However, we could not assess the haplotype effects, which would require individual patient data or compound genotype summary data. In addition, other SNPs in the IL2RA gene were also reported to be associated with T1D, such as rs4147359 The current meta-analysis should also be interpreted within the context of a number of limitations. Only two studies from Asian descendents were included in the meta-analysis IL2RA gene are significantly associated with T1D independently. We suggest that additional larger studies allowing stratification for other gene × environment interactions should be performed to further clarify the possible roles of these genetic variants in the aetiology of T1D.In conclusion, our results suggest that the five investigated SNPs in the


CYP1B1) is a key P450 enzyme involved in the metabolism of exogenous and endogenous substrates. Previous studies have reported the existence of CYP1B1 L432V missense polymorphism in prostate, bladder and renal cancers. However, the effects of this polymorphism on the risk of these cancers remain conflicting. Therefore, we performed a meta-analysis to assess the association between L432V polymorphism and the susceptibility of urinary cancers.The Cytochrome P450 1B1  and 95% confidence intervals (95% CI) were calculated to evaluate the strength of these associations. Simultaneously, publication bias was estimated by funnel plot and Begg’s test with Stata 11 software.We searched the PubMed database without limits on language for studies exploring the relationship of CYP1B1 L432V polymorphism and urinary cancers. The overall OR (95% CI) of CC versus CG was 0.937 (0.881-0.996), the overall OR (95% CI) of CC versus CG + GG was 0.942 (0.890-0.997). Furthermore, we identified reduced risk for CC versus other phenotypes in both prostate and overall urinary cancers, when studies were limited to Caucasian or Asian patients.We observed a significant association between CYP1B1 L432V polymorphism is associated with urinary cancer risk.This meta-analysis suggests that the http://www.diagnosticpathology.diagnomx.eu/vs/3108829721231527The virtual slide(s) for this article can be found here:  Prostate cancer, urothelial carcinoma and renal cancer are common cancer types and major cause of cancer-related death worldwide,2. SmokiCYP1B1) is a member of the CYP1 gene family and one of the major enzymes involved in the hydroxylation of estrogens, involved in the oxidative activation and deactivation of xenobiotics[CYP1B1 gene have been reported, including 4326C/G  in exon 3, which encodes the heme-binding domain, have been associated with enhanced catalytic activity when compared to the wild-type allele[Cytochrome P450 1B1 . References of the retrieved articles on this topic were also manually screened for additional relevant eligible studies.Medline, PubMed, Embase and Web of Science were searched for all relevant articles with the following terms: “Cytochrome P450 1B1” or “We defined inclusion criteria as follows: written in English; case–control design; sufficient information for estimating odds ratio (OR) and their 95% confidence interval (CI); observed genotype frequencies in the controls in agreement with Hardy-Weinberg equilibrium (HWE). Abstracts and unpublished reports were not considered. Investigations in subjects with family history or cancer-prone disposition were also excluded. Meanwhile, if studies had overlapping subjects, we selected the most recent study that included the largest number of individuals in the publications. This study was approved by the ethics committee of the Second Affiliated Hospital of Nanchang University.CYP1B1 polymorphisms in cases and controls, and main findings.Two investigators independently extracted the following information from each study: the first author, year of publication, country of origin, ethnicity, source of controls , genotyping method, number of genotyped cases and controls, number of genotypes for three P < 0.05 was considered representative of departure from HWE. Crude OR with 95% CI was used to assess the strength of association between the three CYP1B1 L432V polymorphism and urinary cancer risk. Then, we calculated the pooled ORs and 95% CIs. Heterogeneity assumption was checked by the chi-square-based Q-test. A P value greater than 0.10 for the Q-test indicates a lack of heterogeneity among studies, so the pooled OR estimate of the each study was calculated by the fixed-effects model (the Mantel–Haenszel method), the random-effects model (the Der-Simonian and Laird method) was used otherwise[P < 0.05 was considered representative of statistically significant publication bias)[Hardy–Weinberg equilibrium (HWE) was evaluated for each study, using the goodness-of-fit chi-square test. therwise,31. To aWe identified a total of 71 relevant publications after initial screening. Among these, 26 publications had met the inclusion criteria and were subjected to further examination. We excluded 4 publications because they did not present detailed genotyping information. We also excluded 5 publications because they did not include L432V polymorphism. Our final data consisted of 10 publications with a total of 5949 cases and 5388 controls for prostate cancer, 5 publications with 1658 cases and 1593 controls for bladder cancer, 2 publications with 337 cases and 408 controls for renal cancer  . Therefore, we used the random-effects model that generated wider CIs. For the other groups of comparisons, no heterogeneity was found among studies and the fixed-effects model was performed (Table Heterogeneities were observed among studies for the association between the The shapes of the funnel plots seemed symmetrical, and Egger’s test suggested that publication bias was only found in the CC vs GG group of bladder cancer (Table CYP1B1 gene and urinary cancer risk by comparing the allele frequencies from 17 published studies. We observed a significant association of L432V polymorphism with overall urinary cancer risk, as well as in the subgroups defined as Caucasian or Asian populations. Urinary system tumorigenesis is a complex event, in which different carcinogenic chemicals are involved. Prostate is a hormone-responsive organ in which androgens are believed to stimulate growth and secretory functions. Evidences have been shown that CYP1B1 protein is highly expressed in prostate cancer tissues, while not in normal prostate tissues[CYP1B1 have different catalytic activities and specificities to procarcinogens, thus partly explains molecular mechanism of CYP1B1 in carcinogenesis[CYP1B1 L432V polymorphism and bladder cancer and renal cancer risk[CYP1B1 polymorphism contributes to urinary cancer susceptibility requires further illustration.In this meta-analysis, we tested the association between L432V polymorphism in the  tissues. It has ogenesis. Except cer risk,28,29. HSome limitations of this meta-analysis should be discussed. First, the total number of included studies of bladder cancer and renal cancer was relatively small. Second, our results were based on unadjusted estimates, while a more precise analysis is needed if individual data were available, which would allow for the adjustment by other factors such as age, smoking status, drinking status. Finally, unpublished data may have not been included in the current analysis, potentially causing a bias in the results.CYP1B1 L432V polymorphism is associated with urinary cancer development, especially in specified Caucasian and Asian populations. However, studies with larger number of samples from homogeneous urinary cancer patients are needed. Further biological investigations may eventually lead to better understanding of the association between the CYP1B1 polymorphism and urinary cancer risk.In conclusion, this meta-analysis suggests that the The authors declare that they have no competing interests.WF J, G S and JH X conceived and performed statistics, WF J, XQ X and ZM S extracted data and wrote the manuscript, G S and ZM S revised the manuscript. All authors read and approved the final manuscript.CYP1B1 L432V polymorphism and urinary cancer risk.Subgroup analysis of association between Click here for file


MTHFR) polymorphism may be a risk factor for male infertility. However, the epidemiologic studies showed inconsistent results regarding MTHFR polymorphism and the risk of male infertility. Therefore, we performed a meta-analysis of published case-control studies to re-examine the controversy.Methylenetetrahydrofolate reductase  with 95% confidence interval (CI) was used to assess the strength of association between the MTHFR polymorphism and male infertility risk.Electronic searches of PubMed, EMBASE, Google Scholar and China National Knowledge Infrastructure (CNKI) were conducted to select eligible literatures for this meta-analysis . According to our inclusion criteria and the Newcastle-Ottawa Scale (NOS), only high quality studies that observed the association between MTHFR 677C>T polymorphism showed significant associations with male infertility risk in both fixed effects  and random effects models . Further, when stratified by ethnicity, sperm concentration and control sources, the similar results were observed in Asians, Caucasians, Azoo or OAT subgroup and both in population-based and hospital-based controls. Nevertheless, no significant association was only observed in oligo subgroup.Twenty-six studies involving 5,575 cases and 5,447 controls were recruited. Overall, MTHFR polymorphism is associated with an increased risk of male infertility. Further well-designed analytical studies are necessary to confirm our conclusions and evaluate gene-environment interactions with male infertility risk.Our results indicated that the  Infertility has been acknowledged as a very common health problem that affects approximately 15%-20% of couples who want to conceive –6. In maMTHFR) is one of the key regulatory enzymes in folate metabolism which can catalyze the reduction of 5,10-methylenetetrahydrofolate to 5-methyltetrahydrofolate, the methyl donor for homocysteine in the synthesis of methionine. Subsequently, methionine in its activated form S-adenosylmethionine is the methyl donor for DNA methylation [MTHFR or by the action of carcinogenic elements, for example, alcohol or tobacco [Folate is very important for the maintenance of genome integrity due to its role in DNA synthesis, repair and methylation , 8. It ihylation . Methyla tobacco .MTHFR gene, located on the short arm of chromosome1 (1p36.3), which is composed of 11 exons [MTHFR gene causes the substitution of valine for alanine in the MTHFR protein and a consequent reduction in enzyme activity. The MTHFR 677C>T variant decreases the activity of the enzyme by 35% in the presence of heterozygosis and by 70% in homozygosis [MTHFR polymorphisms is considered as a risk factor for many diseases, including infertility [The 11 exons , 13. Theozygosis . Reducedertility .MTHFR 677C>T polymorphism and male infertility risk in diverse populations, but the results of these studies remain conflicting rather than conclusive. Some studies exhibited significantly increased risk of male infertility with MTHFR 677C>T, while some other studies showed nonsignificantly enhanced risk. As a result, there were five meta-analyses [MTHFR 677C>T polymorphism and the risk of male infertility, however, the results still inconsistent. Moreover, many new researches studied the association between male infertility risk and MTHFR 677C>T after the last meta-analysis researching, so an updated and high quality meta-analysis is needed.Recent years, a number of epidemiological studies have been conducted to examine the association between analyses –19 perfoMTHFR 677C>T polymorphism and male infertility risk, we carried out a meta-analysis with subgroup analysis using all the eligible published data until June 19, 2014.In order to evaluate the association between the MTHFR”, ‘‘polymorphism” or ‘‘variant”, “infertility” or ‘‘azoospermia” or “oligoasthenoteratozoospermia” or ‘‘oligozoospermia” or “subinfertility”. In addition, we checked the references of all eligible articles which our research retrieved. For the meta-analysis, the following inclusion criteria were considered: (1) studied on human beings; (2) studies which evaluated the association between MTHFR 677C>T polymorphism and male infertility risk; (3) studies with case-control design; (4) sufficient published data about the size of the sample, odds ratio (OR), and their 95% confidence interval (CI). For the exclusion criteria, we provided as follows: (1) without raw data for the calculation of odds ratios (ORs) with corresponding 95% confidence intervals (95% CIs); (2) when studies with overlapping cases or controls, we included only the most recent or the largest report.According to the Meta-analysis on Genetic Association Studies Checklist , we condP value of Hardy Weinberg Equilibrium (HWE). Different ethnic groups were mainly categorized as Caucasian, Asian and African. According to the sperm concentration, we divided the subgroup as azoospermia (Azoo), oligoasthenoteratozoospermia (OAT) and oligozoospermia (oligo) groups. Study designs were stratified to population-based studies and hospital-based studies.According to the inclusion and exclusion criteria, the two investigators (Tingyu He and Zhirong Shi) extracted raw data independently in order to ensure the accuracy of extracted information. For conflicting evaluations, an agreement was reached following a discussion. The following information was collected from all eligible studies showing in Three authors  assessed the study quality independently based on the Newcastle-Ottawa Scale , which uMTHFR 677C>T polymorphism and the male infertility risk were estimated by pooled ORs with 95% CI. The statistical significance of the pooled ORs was examined by Z test and P (two-tailed) <0.05 was considered statistically significant. A chi-square test was used to examine the deviation from HWE for controls and P value<0.05 signified a departure from HWE. In this meta-analysis, heterogeneity between studies was assessed by the I2 test and which was considered statistically significant with I2>50% [I2≤50%) or presence (I2>50%) of heterogeneity, respectively. When heterogeneity between studies is absent, these two models provide similar results, if not, the random effects model is more appropriate. Subgroup analysis was performed by ethnicity, sperm concentration and the control sources. In addition, to assess the stability of results, sensitivity analysis was performed by omitting one study at a time and calculating the overall homogeneity and effect size. As publication bias was always concerned in meta-analysis, an evaluation of which was carried out with funnel plot and Egger’s test (P<0.05 was significant publication bias) [The association between  I2>50% . A fixed I2>50%  or rando I2>50%  was usedon bias) . The staMTHFR 677C>T polymorphism and male infertility risk. After data extraction, we excluded 4 articles from the meta-analysis. One of them had no controls [MTHFR 677C>T and male infertility risk. Among of them, five studies were excluded because of the poor quality, which was evaluated by Newcastle-Ottawa Scale [MTHFR 677C>T polymorphism. All the researches contained in this meta-analysis are case-control studies. Of the 26 studies included in the meta-analysis, there were 10 studies of Asians, 11 studies of Caucasians, 1 study of African and 4 studies did not mention. According to the control sources, general populations were used as controls in 12 studies whereas hospital patients were used in 8 studies and 6 studies did not mention. The genotype distributions among the controls of all studies followed HWE except for two studies [Through a literature searching, initially a total of 46 potentially relevant publications were indentified. Out of these, eleven studies were eliminated because they did not investigate the association between the controls  while oncontrols , besidescontrols  while thcontrols . Hence, wa Scale –34. Therwa Scale , 35–57  and random effects models .MTHFR 677C>T polymorphism and male infertility were found in Asians  and Caucasians  and OAT  subgroups. Whereas, no significant association was observed in oligo subgroup .Subgroup analyses were also performed for azoospermia (Azoo), oligoasthenoteratozoospermia (OAT) and oligozoospermia (oligo) groups . StudiesP = 0.001, I2 = 72.5%) and hospital-based controls   .To assess the effect of individual study on all subjects and subgroups, the sensitivity analyses were performed by excluding one study each time. If the exclusion of any single study did not alter the significance of the final decision, it suggested that the outcomes were robust. However, our corresponding pooled ORs were not materially altered in all subjects and all subgroups. In addition, when excluding the two studies , 49 whicP value of Egger’s test also suggested that there was no evidence of publication bias  These two GWASs both conducted by Aston KI only included Caucasians of European decent, while we included men of other ethnicities. SNP frequencies vary widely between ethnic groups, for example, the frequency of the MTHFR 677C>T allele varies significantly among populations, ranging from 30% to 40% in Europe and America to 5% to 10% in Africa and Sri Lanka [In recent years, the application of the genome-wide association study (GWAS) in many types of diseases has exploded. Until now, there are twelve GWASs about male infertility, and two of them , 69 mentri Lanka , 71; (2)ri Lanka . About mri Lanka . Anotherri Lanka .MTHFR 677C>T polymorphism, our study was more rigorous and comprehensive. First, more up-to-date studies (26 studies) that contained a substantial number of cases and controls were pooled from published studies, which dramatically increased the statistical power of the analysis. Second, the quality of studies included in this meta-analysis was satisfactory, as we first used the Newcastle-Ottawa Scale to assess the quality of the articles. When the study met our strict criteria, it could be enrolled in. Third, we are the first that showed the significantly increased risk between MTHFR 677C>T polymorphism and male infertility in Caucasians and OAT subgroup. Also, for the first time we performed in detail to check into the association between male infertility risk and MTHFR 677C>T polymorphism according to the control sources. Our results showed obvious higher male infertility risk in both population-based and hospital-based controls.Although several previous meta-analyses have researched the association between male infertility risk and MTHFR 677C>T polymorphism among all the studies was dramatic. Even though we conducted subgroup analyses and the heterogeneity was efficiently decreased or removed in some subgroups, it still existed in the population-based controls and oligo subgroup. Several reasons could explain the significant heterogeneity. First, lifestyle factors especially intake of folate and B-vitamins may play a role. For instance, deficient intake of folate and vitamin B12 is prevalent in India [Nonetheless, there are some limitations should be addressed in this meta-analysis. First of all, the heterogeneities for in India –77; in cin India , Korea [in India  and Italin India . Second,in India , 81. AltMTHFR 677C>T polymorphism is associated with an enhanced risk of male infertility, supporting the hypothesis that the MTHFR 677C>T may be a potential cause of male infertility. Specifically, increased infertility risks with MTHFR 677C>T were observed in overall analysis and most subgroups, except oligo subgroup. However, large scale, well-designed and high quality epidemiological studies will be required to confirm our findings in the future.In summary, our meta-analysis suggested that the S1 Checklist(DOCX)Click here for additional data file.


MTHFD1) gene, as one of the key genes involved in the folate pathway, has been reported to play a critical role in the pathogenesis of neural tube defects (NTDs). However, the results of published studies are contradictory and inconclusive. Thus, this meta-analysis aimed to evaluate the effect of the common polymorphism in the MTHFD1 gene, the G1958A  variant, on the risk of NTDs in all eligible studies.The methylenetetrahydrofolate dehydrogenase  and their corresponding 95% confidence intervals (CIs) were calculated to evaluate the association between the MTHFD1 G1958A polymorphism and NTDs in an overall meta-analysis. For family-based studies, the study subjects were classified as NTD cases, mothers with NTDs offspring, and fathers with NTDs offspring. We found no association between any of the fathers’ genotypes and NTDs, whereas there was a clear excess of the 1958A allele in the mothers of children with NTDs compared with controls individuals.We performed a meta-analysis of nine studies with a total of 4,302 NTDs patients and 4,238 healthy controls. Our results demonstrated a significant correlation between the MTHFD1 G1958A polymorphism might be associated with maternal risk for NTDs in Caucasian populations. However, the evidence of this association should be interpreted with caution due to the selective nature of publication of genetic association studies.In summary, our meta-analysis strongly suggests that the  Neural tube defects (NTDs) are among the most common congenital malformations at birth and present as a wide range of phenotypes, primarily including anencephaly, spina bifida and encephalocele MTHFR) gene, that may be associated with an approximately doubled risk of NTDs MTHFR 677TT genotype arrived at a pooled OR of 2.02 (95% CI 1.51–2.71) MTHFR variant does not appear to account for a large proportion of the etiologic factors for NTDs MTHFR, additional folate-related genes are likely to also be involved.Numerous investigations of genes that are specifically involved in folate metabolism have identified at least one polymorphism, C677T  in the 5, 10-methylenetetrahydrofolate reductase (MTHFD1), given its central role in folate metabolism, is an attractive candidate gene in NTDs aetiology. MTHFD1 is a nicotinamide adenine dinucleotide phosphate (NADP)-dependent trifunctional cytoplasmic enzyme (often referred to as “C1-THF synthase”), acting as 10-formyl, 5, 10-methenyl, and 5, 10-methylene derivatives MTHFD1 plays a critical role as a structural component in methionine synthesis and de novo purine and pyrimidine synthesis MTHFD1 gene were identified from public databases. Among them, a SNP at nucleotide 1958 of the MTHFD1 gene, which causes a G to A transition  that results in replacement of the arginine residue at position 653 by glutamine (R653Q), is one of the most attractive and frequently studied polymorphisms.Another folate-dependent enzyme, 5, 10-methylenetetrahydrofolate dehydrogenase  .MTHFD1 G1958A polymorphism with susceptibility to NTDs was conducted in the MEDLINE, EMBASE, Cochrane Library, CBM  and CNKI  databases. The following combinations of MeSH terms and keywords were used:  and  and (‘methylenetetrahydrofolate dehydrogenase’ or ‘MTHFD1’ or ‘G1958A’ or ‘rs2236225’ or ‘R653Q’). A manual search was also carried out to find additional potential studies in the references lists of reviews. The latest search was performed on January 3, 2014 without any limitation on language.A comprehensive literature search for studies reporting on the association of the MTHFD1 G1958A polymorphism and susceptibility to NTDs; (2) all patients in the candidate studies met the diagnostic criteria for NTDs and controls were without NTDs; and (3) sufficient available genotype data for estimating ORs with their corresponding 95%CIs. The major reasons for the exclusion of studies are as follows: (1) not related to the G1958A polymorphism and NTDs; (2) repeated or duplicate studies; (3) studies only examining case populations; and (4) no usable data reported. When there were multiple studies with the same or overlapping data, only the most recent one with the most subjects was selected for this meta-analysis.The following inclusion criteria were used to select potential studies for this meta-analysis: (1) evaluated the relationship between the Following the PRISMA guide, two investigators independently reviewed and checked all full-text reports and extracted relevant information, including trial features , participants’ general features , genotyping methods, data needed for meta-analysis , evidence of Hardy-Weinberg equilibrium (HWE) in controls, etc. Discrepancies were solved through discussion until consensus was reached. When crucial data was not reported in the original publication, required information was obtained by contacting the authors when possible.The methodological quality of all included studies was assessed by the Newcastle-Ottawa Scale (NOS) criteria  [20]. ThP<0.05 was considered statistically significant. Genotype frequencies of the MTHFD1 G1958A polymorphism in the control groups were tested for conformation to HWE using the chi-square test. The strength of the association between the MTHFD1 G1958A polymorphism and susceptibility to NTDs was assessed by the pooled ORs, whereas a sense of the precision of the estimate was provided by their corresponding 95% CIs. We examined MTHFD1 G1958A genotypes using five genetic models, including allele , dominant (AA+AG vs. GG), recessive (AA vs. AG+GG), homozygous (AA vs. GG), and heterozygous (AA vs. AG) comparisons. The significance of the pooled ORs was determined by the Z-test with a P-value less than 0.05 indicating statistical significance.All statistical analyses were performed using the STATA software . And two-tailed 2I metric were conducted P less than 0.10 and 2I exceeding 50% were considered to indicate the presence of significant heterogeneity. Either a random-effects (DerSimonian-Laird method) or fixed-effects model (Mantel-Haenszel method) was applied to calculate pooled effect estimates in the presence or absence of heterogeneity, respectively. In addition, to assess possible publication bias, the Begg’s funnel plot and Egger’s liner regression test were conducted Taking into consideration possible heterogeneity between-studies, Cochran’s Q statistic and the MTHFD1 G1958A polymorphism. Thus, 16 articles were retained for a full text evaluation. Among them, 4 articles were excluded for including irrelevant genotypic and allelic frequency data  When the data from all eligible studies, with a total of 4,302 NTDs cases and 4,238 controls, were pooled together, a borderline significant overall association was found under four genetic models , indicating that there might be a differential magnitude of effect between large and small studies.Our main results on the association between the MTHFD1 G1958A polymorphism played different roles in different populations. The sample sizes were 1,257/2,939 in NTDs children and controls, 1,356/2,893 in mothers with NTDs offspring and controls, and 962/2,736 in fathers with NTDs offspring and controls. For mothers with NTDs offspring, subjects harboring the 1958A variant are approximately 15–30% more likely to have NTDs when compared to subjects with the 1958G allele . However, there emerged no evidence of a significant association between the MTHFD1 G1958A polymorphism and NTDs risk in children and fathers with NTDs offspring under either genetic model   . Since tMTHFR (methylenetetrahydrofolate reductase) gene MTRR (methionine synthase reductase) gene MTR (methionine synthase) gene RFC-1 (reduced folate carrier) gene MTHFD1 genetic polymorphism on susceptibility to NTDs.Neural tube defects (NTDs) are one of the most prevalent and most severe congenital malformations with a high mortality rate. It is widely known and accepted that the pathogenesis of NTDs is unlikely to be ascribed to any single factor, either genetic or environmental. Previous research has revealed that folic acid or folic acid containing multivitamin supplementation in early pregnancy can prevent not only NTDs MTHFD1 G1958A polymorphism for predicting NTDs risk was conducted by Hol et al. and proved no evidence for involvement of the G1958A alteration in NTDs etiology MTHFD1 G1958A polymorphism and susceptibility to NTDs, which may be helpful in identifying which part of the complex folate metabolism is related to NTDs. To the best of our knowledge, this study is the first meta-analysis to comprehensively assess the association of the G1958A polymorphism with susceptibility to NTDs.The first report evaluating the use of the MTHFD1 G1958A polymorphism and NTDs in an overall meta-analysis of seven studies. The rationale for the possible association is based on the enzyme activities of MTHFD1 that play a central role in folate pool maintenance. It is also possible that this mutation may be in linkage disequilibrium with another, as yet undescribed, variant that alters function. In this meta-analysis, we also performed a stratified analysis for the five family-based studies by classifying study subjects as NTD cases, mothers with NTDs offspring, and fathers with NTDs offspring. As for the NTDs cases subgroup, no significant allelic or genotypic association between this polymorphism and NTDs could be observed. However, for the parents with NTDs offspring subgroups, a comparison between groups yielded significant evidence for the overrepresentation of the 1958A allele and AA homozygote among the case mothers, compared with control individuals, suggesting that the AA genotype may have a different effect in the embryo and may have a maternal effect only. It is noteworthy that women who harbor the AA homozygote for the MTHFD1 G1958A polymorphism are almost three times more likely to develop severe abruptio placentae during their pregnancy than women who are ‘GA’ or ‘GG’ MTHFD1 1958AA homozygote have a 1.64-fold increased risk of having an unexplained second trimester loss, which suggests that the MTHFD1 1958AA genotype may be an important maternal risk factor to consider during pregnancy Our results demonstrated a significant correlation between the MTHFD1 G1958A polymorphism with susceptibility to NTDs should be interpreted in caution, and more large-scale studies on other ethnicities are warranted to support our findings. Third, NTD defects cover a continuum of differing severity and the outcome of an NTD patient varies from livebirth to stillbirth, and thus the effects of genetic variants on risk of NTDs may be underestimated if studies only collect livebirths and less severity cases. Last, given that the significant publication bias was found in this meta-analysis and the nature of publication of genetic association studies, our results should be interpreted with caution. However, notwithstanding the preceding limitations, our meta-analysis also had some strengths: (1) we analyzed the association between the MTHFD1 G1958A polymorphism and the NTDs risk in three groups , which minimized the influence of confounding factors; (2) sensitivity analysis did not show any single study strongly affecting the combined results, suggesting sufficient reliability and stability of the pooled results; (3) this is the first meta-analysis to combine data from previous studies on relationship between the MTHFD1 G1958A polymorphism and NTDs pathogenesis.Meta-analysis is a useful method in synthesizing data from all the eligible studies to obtain greater statistical power. However, several specific issues in this meta-analysis should be considered. First, our study was based on single-factor estimates without adjustment for other risk factors since no information on potential confounders was obtained, a fact that might have caused bias. Second, all the study populations included in our meta-analysis were Caucasian and thus we couldn’t perform stratified analyses based on ethnicity. Hence, for Asian and African populations, the association of the MTHFD1 G1958A and an increased risk of NTDs, especially in mothers of children with NTDs. However, due to the limitations of this study and the low edge of 95%CI, which nearly touched the null value, these results should be viewed with caution. Further large-scale studies will be needed to provide more conclusive and accurate evidence regarding relationships between SNPs in the folate pathway genes and NTDs and how these relationships impact women during the crucial period of pregnancy.In summary, the current meta-analysis demonstrated a significant correlation between the Supplement S1PRISMA 2009 Checklist.(DOC)Click here for additional data file.Supplement S2Newcastle-Ottawa Quality Assessment Scale.(DOC)Click here for additional data file.Supplement S3Full-text articles excluded (a); Studies only included in qualitative synthesis (b).(DOC)Click here for additional data file.


FokI polymorphism and tuberculosis (TB) risk remains a matter of debate. Potential selection bias exists in most studies using HIV-positive TB patients.The association between vitamin D receptor (VDR) FokI polymorphisms and TB risk, especially in HIV-negative TB patients. All major databases from inception to June 2015 were searched for all publications that studied the association between FokI polymorphism and TB risk. The odds ratios (ORs) and the corresponding 95% confidence intervals (CIs) were calculated according to the frequencies of genotypes.An update meta-analysis was carried out to derive a more reliable assessment of the association between P = 0.005) in the best genetic model  with moderate heterogeneity . In the subgroup analysis stratified by HIV status, significant associations were found only in the HIV-negative TB group . In the subgroup analysis stratified by ethnicity, significant associations were found in the Asian group , but not in the Caucasian group  and African group .In total, 32 studies with 4894 cases and 5319 controls were included in this meta-analysis. In the overall analysis, the estimated OR was 1.34 (95% CI=1.091–1.646, FokI polymorphism contributes to the risk of TB, especially in HIV-negative TB patients and in the Asian group. Further studies are required to clarify the role of the FokI polymorphism in HIV-positive TB and in other ethnic groups.This meta-analysis confirms that VDR  Other factors, such as environmental and genetic factors, HIV infection, and diabetes, also play important roles in the process.5 Likewise, genetic factors are important in determining susceptibility and resistance to MTB and are considered related to the susceptibility to TB.6Tuberculosis (TB) is a global public health problem and remains a great burden throughout the world.8 The VDR gene is located in the chromosomal 12q13 region, and there are 4 classically typed single-nucleotide polymorphisms (SNPs), FokI, BsmI, ApaI and TaqI, which were studied intensively for association with various human traits and were reported to affect risk of variousdiseases.9 The FokI restriction site defines an SNP  in the first of 2 potential translations—initiation start sites for VDR mRNA. The VDR protein synthesizes full-length (427 amino acids) in the alternate allele form (ATG) (designated f) and has 3 more amino acids than the VDR encoded by the common allele form (ACG) (designated F). The FokI restriction site is a functional polymorphism of the VDR gene.10 The polymorphisms of FokI can alter the amount of VDR produced 11 and are related to plasma vitamin D levels in TB patients.12Vitamin D is now considered to be a key factor in the body's defense against TB, mediated by binding to the vitamin D receptor (VDR) in monocytes, macrophages, and lymphocytes.FokI have been studied in relation to the risk of TB in many populations; however, the results remained contradictory.15 Recently, Chen et al16 and Sun and Cai17 carried out meta-analyses focusing on the associations between FokI polymorphisms and TB risk; these 2 meta-analyses missed many studies.23 Moreover, HIV infection status should be adjusted in studies focused on genetic susceptibility to TB since TB is the frequent major opportunistic infection in HIV-infected patients.24 Thus, we carried out an update meta-analysis to derive a more reliable assessment on the association between FokI polymorphisms and TB risk, especially in HIV-negative TB patients.To date, the polymorphisms of 25The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement was used in the process of the meta-analysis (Table S1).vitamin D receptor or VDR in combination with polymorphism, polymorphisms, and mutation or variant in combination with tuberculosis or TB. Two investigators (LH and XY) conducted an extensive literature search independently for all publications. Articles in reference lists were also hand-searched and authors of trial reports published only as abstracts were contacted and asked to contribute full datasets or completed papers. There were no language restrictions and only human studies were searched.A search of the medical literature was conducted using the Embase, PubMed, and Cochrane Library databases through June 30, 2015. The search terms were used as follows: Case-control studies with enough data to calculate odds ratio (OR) were included in our study. We excluded duplicate studies or studies containing overlapping data. Family-based studies were also excluded.All data were extracted independently by 2 investigators (LH and XY). The following clinical data were extracted from eligible studies: the baseline characteristics, such as the first author's name, publication year, country, ethnicity, total sample size, genotyping method, and source of control group, and details of TB types and genotype frequencies of cases and controls. Hardy-Weinberg equilibrium (HWE) was calculated from genotype frequencies of controls. Investigators would try to contact the author to get the original data if the literature could not provide sufficient data. A third reviewer (JC) resolved any discrepancies when the abovementioned reviewers disagreed.26In this study, we considered f is the increasing or risk allele; therefore, an allelic model (f vs F), a codominant model , a dominant model (ff+fF vs FF), and a recessive model (ff vs fF+FF) are accessed by calculating the unadjusted odds ratios (ORs) and the corresponding 95% confidence intervals (CIs) according to the frequencies of genotypes. To avoid the problem of multiple comparisons, we applied the method for meta-analysis of molecular association studies to dictate the best genetic model.χ2Q test and I2 statistics. The heterogeneity was significant if PQ < 0.1 or I2 > 50%, and a random-effects model was conducted using the DerSimonian and Laird method. Otherwise, the fixed-effects model (the Mantel-Haenszel method) was performed.28 A subgroup analysis of ethnicity was carried out considering that the same gene polymorphism plays different roles in the risk of diseases among different ethnic subpopulations. HIV-negative TB patients who were studied were also considered a subgroup and pooled in this meta-analysis. Galbraith plots analysis was performed for further exploration of the heterogeneity.Heterogeneity was assessed with a χ2 test for goodness of fit, and a P value <0.05 was considered out of HWE. Sensitivity analysis was conducted to examine such influence by removing studies one by one and by recalculating the pooled OR and 95% CI. The Begg rank correlation method and the Egger weighted regression method were used to statistically assess publication bias.HWE in the controls was tested with the Ethical approval was not necessary, as this study is a meta-analysis, which is based on the published data.P <0.05 indicated that the result was statistically significant.All the tests in this meta-analysis were conducted with STATA software ; 30 Four studies were excluded for not focusing on FokI polymorphism.34 In addition, a meeting abstract 35 and a study about nontuberculous mycobacterial lung disease 36 were also excluded. The study by Alagarasu et al13 was separated into 3 studies for different TB types and HIV status. Finally, 32 studies with 4894 cases and 5319 controls met inclusion criteria. Details of the study flow are documented in Figure Thirty-eight articles were initially evaluated for the meta-analysis, of which 8 studies were excluded. Two studies were excluded because, even though an attempt was made to contact the study authors, no sufficient data were obtained.45 8 studies involving Caucasians,50 and 6 studies involving Africans.55 Fourteen studies included HIV-negative TB patients,56 but only the study by Alagarasu et al13 included HIV-positive TB patients, and the other 16 studies did not offer detailed information. The genotype distributions among the controls of all studies were consistent with HWE, with the exception of 3 studies.49 TB types, genotyping methods, and genotype numbers are shown in Table Table FokI polymorphisms and TB risk are shown in Table 26 the estimated OR1(ff vs FF), OR2(fF vs FF), and OR3(ff vs fF) were 1.34 (95% CI = 1.036–1.730), 0.96 (95% CI = 0.827–1.110), and 1.34 (95% CI = 1.122–1.599). These indicated that OR1 and OR3 were significant (P < 0.05) and OR2 was not significant (P = 0.566); the genetic model was most likely recessive.The evaluations of the association of P = 0.005). There was moderate heterogeneity in the pooled results . Therefore, we performed subgroup analysis according to ethnicity and HIV status. In the subgroup analysis by ethnicity , but not in the Caucasian group , and the African group . The HIV status was stratified as the HIV-negative TB group and the other group (HIV-positive or no information). As shown in Figure P = 0.002; I2 = 29.5%, and P = 0.141 for heterogeneity). To further explore the sources of heterogeneity, we carried out a Galbraith plot analysis to confirm the outliers that might cause the heterogeneity .Using a recessive model, data for the fF and FF group were collapsed and compared to the ff group (ff vs fF+FF). The estimated OR was 1.34 .First, sensitivity analysis was performed by omitting 1 study at a time, and there were no statistically significant changes in all ORs. We then omitted the 3 studies, which were out of HWE, and the statistical significance of the pooled result did not change .As shown in Figure FokI polymorphism contributes to the risk of TB. The results suggest that people who had genotype ff had a 34% higher risk of developing TB than people who had genotypes fF/FF, and the risk effect was confirmed in HIV-negative TB patients (OR = 1.60). In addition, results from subgroup analysis stratified by ethnicity indicate that TB risk was increased in Asians with ff genotype (OR = 1.65), but not in Caucasians and Africans.This meta-analysis with 32 case-control studies indicates that VDR 16 in 2013. Compared with the previous study, our meta-analysis included 7 additional studies on the FokI polymorphism.23 Recently, a meta-analysis was performed by Sun et al. However, this meta-analysis missed 11 studies47 according to the specific combinations of search terms and their inclusion and exclusion criteria. In addition, some comparison genetic models in this study were incorrect . Therefore, this update meta-analysis has more statistical power than the 2 previous studies. Likewise, considering TB is the frequent major opportunistic infection in HIV-infected patients, we carried out a subgroup analysis stratified by HIV status. Interestingly, the risk effect was found only in HIV-negative TB patients. As expected, the heterogeneity decreased significantly, which not only strongly confirms the conclusion that FokI polymorphism contributes to the risk of TB, but also indicates that HIV status was the main source of heterogeneity in the previous meta-analysis. This may be a reason for controversial results from previous studies. Indeed, HIV infection is associated with a greater risk for disease than HIV-negative individuals.57 Of note, a study by Xu et al58 also focused on this topic; nevertheless, our study is more comprehensive than this study and we found the risk effect only in HIV-negative TB patients but not observed in HIV-positive or not clearly identified group. Therefore, our results suggest it is crucial to avoid selection bias in such genotype association studies.The results of the present meta-analysis are consistent with a similar meta-analysis performed by Chen et al59; the active form of vitamin D 2D3) is an important immunoregulatory hormone and moves into the nucleus by binding to the VDR complex.60 Low vitamin D levels have been found to contribute to the risk of TB infection.61 VDR gene polymorphisms are related to vitamin D-related disease,11 and significant interaction between vitamin D status and VDR gene polymorphisms has also been observed.10 Indeed, VDR polymorphism may influence susceptibility to infectious diseases, such as hepatitis B virus infection62 and leprosy.63 With respect to FokI polymorphisms, the short 424 amino acid VDR protein variant  has been found to be more active than the long 427 ff variant.59 Hence, the f allele of FokI might decrease the activity of the VDR protein, and then block the binding of active vitamin D and VDR. In summary, VDR polymorphism may influence the function of vitamin D and, therefore, contribute to the susceptibility to TB infection.Our results are also consistent with the functional studies on the VDR genepolymorphismsFokI polymorphism and TB. Likewise, our results were relatively reliable for no significant heterogeneity, and some results were given in the sensitivity analysis. However, having some limitations is a required consideration in this study. We should note the potential publication biases when explaining the results, although no significant publication biases were found in this study; positive results mainly come from the Asian region, especially China. In addition, we did not stratify or analyze the other factors, such as sex or clinical and environmental variables, because of a lack of original data from authors. Also, our HIV status-specific analysis included only 2 studies from HIV-positive TB patients, and HIV positive or no information were together as a subgroup in meta-analysis would represent a bias in the analysis and conclusions; additional studies are warranted to explore the relationship between HIV-positive TB and FokI polymorphisms.The present study has some advantages compared with previous studies. First, this update meta-analysis has more statistical power than the 2 previous studies. We also selected the best genetic model to avoid multiple comparisons. Second, we confirmed the conclusion in the HIV-negative TB group, which would further reveal the association between FokI polymorphism contributes to the risk of TB, especially in HIV-negative TB patients and the Asian group. Further studies are required to clarify the role of the FokI polymorphism in HIV-positive TB and in other ethnic groups.In conclusion, this meta-analysis confirms that VDR