Genome-wide association studies and meta-analyses indicate that the polymorphism of rs266729 in adiponectin gene increases the risk of type 2 diabetes mellitus (T2DM); however, these study methods have not been able to identify the underlying genetic effect on the development of T2DM. A genetic model-free approach was conducted to determine the underlying genetic model of inheritance of T2DM because of rs266729 in adiponectin gene.λ was calculated to estimate the genetic model, which was defined as the quotient of natural logarithm odds ratio of GC to CC divided by the natural logarithm odds ratio of GG to CC. Finally, binary logistic regression analysis was used to calculate the genetic effect of rs266729 on T2DM.We searched available studies on the association between the rs266729 in adiponectin gene and T2DM in accordance with the inclusion and exclusion criteria. Based on the information extracted from the studies, generalized odds ratio value (GOR) was used to evaluate whether the rs266729 polymorphism was a risk factor for T2DM. The parameter λ was 0.47 . The result of logistic regression indicated that the G allele influenced the development of T2DM in the additive model, whereas the genetic effect was 1.13 . Sources of control populations were the cause of between-study heterogeneity; nonetheless, there was no publication bias among studies.Data from 7 studies were included in this meta-analysis. The total number of subjects was 12,323, comprising 5,948 cases and 6,395 controls. Mean (standard deviation) age of cases was 59.50 (11.53), and that of the controls was 53.80 (11.65), whereas the proportion of male was 40.9 and 50.0%, respectively. GOR was 1.13  and The G allele of rs266729 in adiponectin gene increases the risk of T2DM through an additive genetic model with an effect of 1.13 . However, there are still limitations with the use of these tools for the diagnostic screening of T2DM, and as such additional diagnostic biomarkers of T2DM are still being of explored.Diabetes mellitus  is the most prevalent metabolic disorder that is characterized by chronic sustained hyperglycemia due to defects in insulin secretion from beta cells of the pancreas or resistance against insulin action. Its incidence has been increasing globally at an extremely rapid rate. In 2015, there were 415 million adults living with DM, and the number is expected to rise to 642 million by 2040. Type 2 diabetes mellitus  is the most prevalent form of DM and the health consequences and economic burden caused by this disorder are enormous. is negatively correlated with fasting glucose, insulin-resistance (IR), and T2DM.–6 Epigenetic modifications, such as DNA methylation, of the adiponectin gene affecting gene transcription and health status, may be involved in T2DM. The methylation in the promoter region of this gene may result in repressed transcriptional activity of the adiponectin gene and low plasma adiponectin levels, leading to pathogenesis and progression of T2DM. Similarly, single-nucleotide polymorphisms (SNPs) and methylation in the promoter region of the gene could together affect adiponectin gene transcription. Genome-wide association studies (GWAS) have been used to evaluate the associations between the adiponectin gene promoter polymorphism, especially the rs266729, and T2DM.,9 However, limitations of these studies have included: first, the reduction of the problem to a single comparison, either by performing 2 separate pairwise comparisons or by assuming a specific underlying genetic model. This method of multicomparisons declines statistical power, increases type I error rate, and false-positive rate. Second, the lack of insights into the association between the SNPs and genetic risks of developing DM, when such risks are controversial. For resolving the problem above, generalized odds ratio (GOR) was used in this study to evaluate the association between adiponectin rs266729 polymorphisms and disease status (T2DM vs. control) under complete genotype distribution, providing a summary risk effect and heterogeneity metric. Then a genetic model-free approach was conducted to estimate the rs266729 genetic effect on the development of T2DM and the underlying genetic model of inheritance, which may provide potential biomarkers and important evidence to establish prevention and treatment strategies for T2DM.The human adiponectin gene encoding the adiponectin protein,22.12.1.1Potential eligible studies were identified by systematically searching the ISI Web of Science, Pubmed, MEDLINE, Elsevier, Springer, EBSCO, and Chinese Biological Medicine, China National Knowledge Infrastructure (CNKI), and Wanfang databases up to October 2016 using the terms: “adiponectin” “type 2 diabetes” “gene promoter region” and various synonyms. Search strategy: (“Adiponectin”) AND (“rs266729” OR “SNP-11377C/G” OR “SNP-11377” OR “C-11377G” OR “-11377C>G”) AND (“diabetes” OR “type 2 diabetes mellitus” OR “glycuresis” OR “fasting plasma glucose” OR “fasting blood glucose” OR “fasting blood sugar” OR “blood glucose level” OR “serum glucose”).2.2Studies that fulfilled the following criteria were included: studies showing the association between polymorphisms of adiponectin gene and T2DM; original articles of prospective cohort, case–control, or whole-genome association studies with raw data; studies with detailed criteria for T2DM diagnosis; studies showing the sample size of the 3 genotypes  in both groups.Studies were excluded if: they were not related to adiponectin rs266729 polymorphism; data were incomplete; when multiple published reports from the same population spanning the same time period are found, the one with the most useful information was included; they were series of studies, in which case the latest was included while the old ones excluded; sample size of any group was <500; family studies; genotype distribution of the control group deviated from Hardy-Weinberg equilibrium (HWE).2.3 A study was judged on 3 broad perspectives in the NOS scale: the selection of study groups (0–4 stars); comparability of groups (0–2 stars); ascertainment of the exposure of interest (0–3 stars). A higher score represented the better methodological quality; studies that received a rating of at least 7 stars were judged as “high quality.”Data were independently extracted by 2 investigators (PS and LL) and checked by a third investigator (JC). Both investigators independently completed primary screening by reading the title and abstract of the studies, and subsequently screening the full article. The studies were included or excluded according to the criteria. The following information was extracted from all included studies: author, year of publication, continent, country, nationality, population, standards of T2DM diagnosis, average age and standard deviation, and frequencies of genotypes in both groups. If the 2 investigators had different opinions, consensus was reached through discussion. Emails were sent to corresponding authors for full texts where they were not available online. The quality of included studies in this meta-analysis was assessed by the Newcastle Ottawa Scale (NOS).2.42.4.1χ2 test in Excel 2007 (Microsoft Corporation). The significance level was set at 0.05, and all P values were 2-sided. This study was a meta-analysis, and ethical approval and informed consent were not sought.HWE analysis for genotype distribution was checked with 2.5 which could obtain fixed-effect result and random-effect result. If I2 ≤ 25%, this was indicative of lack of significant heterogeneity among studies, and a fixed-effect result was adopted. If I2 ≥ 25%, it meant that significant heterogeneity existed among studies, and a random effect result was adopted. If GOR and its 95% confidence interval (CI) were >1, the G allele of rs266729 was likely a risk factor for T2DM; if the range of 95% CI contained 1, this indicated the likely absence of relationship between the G allele of rs266729 and T2DM; if GOR and its 95% CI were <1, this indicated that the G allele was probably a protective factor against T2DM.GOR methodology can be implemented by ORGGASMA software,Analysis for dominant () and additive  models was performed by STATA 12.0 , and the results were compared with those of GOR estimation.2.5.1OR for GC to CC was estimated as OR1, whereas that of GG to CC as OR2; the quotient of natural logarithm OR1 divided by natural logarithm OR2 was defined as parameter λ (Formula 1), wherein LogOR2 was the independent variable and LogOR1 was the dependent variable. The scatter plot was drawn in excel and the simple linear regression analysis was performed with Stata. Then λ and its 95% CI were used to determine the genetic model of the dominant G allele. If λ was 0, 1, or between 0 and 1, the corresponding genetic model of the G allele was recessive, dominant, or incompletely dominant, respectively; If λ >1 or <0, this indicated overdominance or underdominance. When λ = 0.5, it was called additive . The C allele of the rs266729 is a wild allele, whereas the G allele is a mutant. The 2.5.2λ = 0, the genetic model was recessive, and the effect of GG would be 1, whereas those of GC and CC would be zero. With frequencies weighted, the genotypes, GG = 1, GC = 0, and CC = 0, were defined as categorical variables, whereas the groups (T2DM patients = 1 and control group = 0) were defined as binary dependent variables in the logistic regression, and the result was statistically significant. If λ = 1, the genetic model would be dominant, and the effects of GG and GC would be 1 and that of CC would be zero. If the genotypes, GG = 1, GC = 1, and CC = 0, were defined as categorical variables, and data were analyzed as the steps above, and the result was statistically significant. If λ was between 0 and 1, genetic model would be incompletely dominant, and genotypes were defined as categorical variables, and data were analyzed as the steps above. During the regression analysis, the CC genotype was taken as the reference category. Thus, if there were multiple relations between the GG and CC genotype coefficients, the genotypes were defined as ordinal variables and the data were analyzed as the steps above, and the result would be statistically significant . If 2.5.3χ2-based Q test. If there was heterogeneity, meta regression was used to find out sources of heterogeneity. Additionally, the Begg funnel plot and Egger test were performed to determine whether the literature showed a publication bias. An asymmetric plot or P < .05 suggested possible publication bias. Sensitivity analysis was performed to assess the influence of each individual study by omitting one study at a time and calculating pooled ORs for the remaining studies. All statistical analyses above were performed by Stata.The between-study heterogeneity was assessed by performing the Cochrane 33.1A total of 380 potentially relevant studies were retrieved and screened. Of these, 159 studies were not related to the association between the adiponectin rs266729 polymorphism and T2DM, and were excluded on the basis of title and abstract. Next, 206 studies were excluded because they did not meet the inclusion criteria, leaving 15 studies, from which an additional 2 literatures were excluded because they had incomplete information on the numbers of genotypes. Six studies were further excluded because they deviated from the HWE. Finally, 7 studies were included in this meta-analysis, including 1reported in Chinese and 6 reported in English  age of cases and controls was 59.50 (11.53) and 53.80 (11.65) years, respectively, whereas the proportion of males was 40.9% and 50.0%, respectively. The frequency of CC genotype in the case and control groups was 53.23% and 56.40%, respectively, whereas that of GC was 39.64% and 37.75%, respectively, and that of GG was 7.13% and 5.85%, respectively. The frequency of the G allele in the case and control groups was 26.95% and 24.73%, respectively. Among the 7 studies, 3 were on Asians, 2 were on Europeans, 1 was on Africans, and another was on Americans. The subjects in the remaining studies were Italian, French, Arabs, Indian, Chinese Han, whites. The characteristics of the study groups and individuals’ overall demographics are shown in Table Study quality scores are summarized in Table 3.3P < .001. Because I2 = 55.32%, there was significant statistical heterogeneity among studies, and the random-effect result was adopted. Both GOR and 95% CI were >1, P < .001, indicating that adiponectin rs266729 G allele was a risk factor for T2DM. GOR forest plots are shown in Figure GOR was used to efficiently estimate the association between the adiponectin rs266729 G allele and T2DM under unknown genetic model. The fixed-effect model result was: GOR = 1.14 and 95% CI , whereas the random-effect result was: GOR = 1.13 and 95% CI , , P = .001) and there was significant heterogeneity among studies (P = .047). (GC + CC) increased the risk for T2DM compared with GG , whereas GC increased the risk compared with CC , without significant heterogeneity among studies (P > .05). The risk of T2DM did not increase for GG compared with GC .Summary ORs are shown in Table 3.4OR1 and logOR2 was defined as λ, which was found to be 0.47 . The genetic effect was estimated by binary logistic regression. The disease status was regarded as binary-dependent variable and the genotypes as categorical variables; the coefficient of the GC genotype was 0.11, whereas that of the GG genotype was 0.26 (P < .01). The GG coefficient was nearly twice as much as that of GC and the genotypes were GG = 2, GC = 1, and CC = 0, λ was 0.5, and the genetic model for the effect of the G allele on T2DM was additive. During the logistic regression analysis based on ordinal variable, the result showed that the genetic effect was 1.13   of 1.07  for G versus C allele. However, the study did not provide the rs266729 genetic effect on the development of T2DM in different populations. Therefore, a more precise association between the adiponectin gene rs266729 polymorphism and T2DM risk reported in this meta-analysis for the first time is that the rs266729 G allele may increase the risk of T2DM in an additive genetic model.The mechanisms underlying the development of T2DM are complex. Nonetheless, adiponectin gene polymorphisms and abnormalities in plasma adiponectin levels have been associated with the disease. Accordingly, plasma adiponectin level closely correlates with IR and is decreased in T2DM patients. Studies also demonstrate a decline in adiponectin levels in clinical subjects and experimental animals with prediabetes. In line with plasma levels of adiponectin, the rs266729 polymorphism has been identified as a susceptibility locus for DM.ORs , GC vs. CC) were consistent with the result of GOR estimation, except for the OR of GG to GC. Then, the result of the genetic model assessment showed that the rs266729 G allele was incompletely dominant for inheritance of T2DM (P < .001), with λ of 0.47 . Finally, the genetic effect was quantitatively evaluated by binary logistic regression, and the result further demonstrated that the genetic model of the rs266729 polymorphism was that of incomplete dominance: additive inheritance, λ = 0.5. Thus, the risk of developing DM increased by 13.0% (OR = 1.13) when the G allele was present at rs266729. Therefore, the rs266729 G allele was a risk factor for DM and the genetic model was that of additive inheritance.In our study, the association between the rs266729 polymorphism and T2DM was evaluated objectively by analyzing GOR and its 95% CI under complete genotype distribution without a genetic model. The result showed that the rs266729 G allele was a risk factor for T2DM and people with the rs266729 G allele had 1.13-fold higher risk of developing T2DM compared to those without the G allele. Summery  The rs266729 G allele alters the DNA sequence of the SP1-binding site of the transcriptional elements, resulting in a reduction in the transcriptional activity of the adiponectin gene promoter. Additionally, based on the location of DNA methylation in a genomic sequence, the consequence can produce varied genetic effects. For example, gene promoters and intergenic regions can become methylated and result in gene silencing, ultimately affecting the expression of genes during development.–32 DNA methylation in the promoter region of rs266729 interacting with polymorphism may lead to the inhibited gene expression and low plasma adiponectin levels. These mechanisms can result in downregulation of the adiponectin gene resulting in decreased plasma adiponectin concentration. The deficiency or inactivity of adiponectin influences insulin sensitivity and accelerates the occurrence of T2DM.,34 The pathophysiologic mechanisms of T2DM can be explained by IR and pancreatic β-cells failure, which closely relates to the adiponectin protein. Moreover, adiponectin plays a significant role in regulating glucose metabolism and IR.,37 In addition, numerous studies report the association of the rs266729 G allele with low plasma adiponectin concentrations. Thus, having an appropriate level of adiponectin is essential to maintaining normal body metabolism.The question, however, still remained regarding the molecular mechanisms of rs266729 polymorphism additively affecting T2DM. Sp1 is associated with the adiponectin gene promoter and its overexpression enhances the gene promoter activity.P > .05) among Asian, European, American, and African control populations; hence, there were no discrepancies in the genotype frequencies distribution of the rs266729 among control populations, and the genetic background of the rs266729 polymorphism for study populations was similar. The ethnicity could not influence the reliability of the results.Furthermore, between-study heterogeneity present in this study must be interpreted with caution; obviously, heterogeneity existed in healthy volunteers and passively selected populations. Other contributing factors may be the variable definition of T2DM patients and controls, genotype errors, and environmental history. There were no significant statistical differences (,39 wherein OR values are collectively calculated by performing 2 separate pairwise comparisons or by assuming a specific underlying genetic model. Multicomparisons decline statistical power, increase type I error rate and false-positive rate. The effect of the rs266729 G allele on T2DM development could not be accurately estimated because of uncertain genetic model in previous studies. However, this study provides a genetic model-free approach to quantitatively analyze the association between the rs266729 polymorphism and T2DM. The genetic model was estimated on the basis of the genotype frequency available rather than assumed, whereas the genetic effects could be evaluated by binary logistic regression on the basis of genetic model. Furthermore, to guarantee the quality of this study, investigators used explicit criteria for inclusion and a strict procedure for data extraction. Similarly, the sample size of each included study was >500 in case and control, making the result more robust than previous meta-analysis that included studies with smaller sample sizes. In general, this method avoids the confounding of possible genetic models, making the results better powered and more informative than previous studies for the association between rs266729 polymorphism and T2DM. The result indicated that the rs266729 is a potential functional variant, which influences the adiponectin gene mRNA stability or adiponectin gene expression. It also indicates the importance of the rs266729 during the development of T2DM, which may provide important evidence to establish prevention and treatment strategies for T2DM. However, the limitation of this study was that original data could not be obtained, thereby limiting further evaluation of potential gene–gene interaction and gene–environment interaction.GWAS and meta-analyses have been used to evaluate the association between adiponectin gene polymorphism and T2DM,In conclusion, the results of the present study reveal that the rs266729 in adiponectin gene is a susceptibility site for T2DM, and the genetic model of the G allele at this site contributing to the development of T2DM was that of incomplete dominance during inheritance. Individuals carrying the G allele can easily develop T2DM more than those without the G allele. However, these results highlight the challenge of polygene effect on T2DM. In the future, comprehensive interactions at the gene–gene and gene–environment level should be explored to further reveal the effect of multiple susceptibility genes on the development of T2DM.


P=0.044, OR=0.72) and rs2293303  polymorphisms were associated with overall cancer risk. In stratified analysis, rs4135385 polymorphism was found to elevate the risk in Caucasian or in gastrointestinal cancer subgroup. Additionally, rs2293303 conferred to an increased cancer risk when the source of control groups was hospital-based (HB). In conclusion, the three CTNNB1 SNPs were suggested to have the potential to be novel biomarkers for risk prediction of cancer in overall population or some specific subgroups. Our study could provide research clues for further related investigations.CTNNB1, encoding β-catenin, is a well-known tumor-related gene in the wnt signaling pathway. It has been reported that CTNNB1 polymorphisms are associated with cancer risk. However, the data were inconsistent. In this article, we conducted a systematic review for the researches related to the association of single nucleotide polymorphisms (SNPs) in CTNNB1 with overall cancer risk. Meanwhile, a series of inclusion and exclusion criteria were set to select articles for quantitative analysis. Consequently, eight case-control studies containing 4388 cases and 4477 controls were included in a meta-analysis of four highly studied CTNNB1 SNPs . The association between each SNP and cancer risk was estimated by calculating odds ratios (ORs) and their 95% confidence intervals (95%CIs). The results showed rs1798802 (AA compared with GG:  CTNNB1 gene, has two roles in the cells. It forms a functional cadherin–catenin adhesive complex involved in cell–cell adhesion in the membrane, while its nuclear pool participates in signaling pathways and regulates a remarkable variety of cellular process such as cell proliferation, cell survival, and migration [The Wnt signaling pathway was primarily identified for its role in cancer development, which induced the expression of tumor-related genes and contributed to cancer progression by promoting the stabilization of cytoplasmic β-catenin ,2. β-catigration . Dereguligration –6.As the most common form of genetic variation, the single nucleotide polymorphisms (SNPs) are universally present in CTNNB1, which have been extensively investigated. It has been found that mutations in CTNNB1 exons could lead to impaired degradation of β-catenin protein and thus constitutive activation of the Wnt pathway ,8. MountIn the present study, we systematically reviewed the relationship between CTNNB1 SNPs and overall cancer risk. Based on that, available data were used to perform a meta-analysis, aiming to explore the association of CTNNB1 polymorphisms with cancer and to provide research clues for screening novel biomarkers for cancer risk prediction.A literature search of PubMed and Web of Science was performed by two independent investigators (Yanke Li and Fuqiang Zhang) up to June 12, 2017, with the following keywords: ‘CTNNB1/beta-catenin/β-catenin’; ‘polymorphism/SNP/variant/variation’; and ‘cancer/carcinoma/tumor/neoplasm’. All the studies we selected met these criteria: (i) case–control study; and (ii) based on the association between CTNNB1 SNPs and cancer risk. The exclusion criteria consisted of: (i) duplicate studies; (ii) not related to carcinoma or CTNNB1 SNPs; (iii) no available data and failing to contact with the authors.Two investigators (Yanke Li and Fuqiang Zhang) independently extracted data and reached consensus regarding all the items. The following information was obtained from each article: the first author, publication year, country origin, cancer type, genotyping method, source of control groups , sample size of cases and controls, genotype distributions in case and control groups, and adjusted factors. Meanwhile, we classified ethnicity into Asian and Caucasian. And both gastric cancer (GC) and colorectal cancer were categorized as ‘gastrointestinal cancer’ for stratified analysis.Two reviewers (Yanke Li and Fuqiang Zhang) evaluated the quality of the selected studies by scoring them independently according to recent meta-analyses ,14. Six 2>50%). We pooled the results using the fix-effect model when inter-study heterogeneity was absent; otherwise, the random-effect model was selected. Begg’s rank correlation and Egger’s linear regression methods were used to assess the publication bias. Sensitivity analysis was conducted to examine whether the overall findings were robust to one or two outlying studies. The analyses mentioned above were all performed using STATA software, version 11.0 . All the tests were two-sided and P<0.05 was considered to be statistically significant. Additionally, the dominant and recessive genetic models were defined as heterozygote + homozygote variant compared with homozygote wild and homozygote variant compared with heterozygote + homozygote wild, respectively.The HWE for the genotype frequencies of CTNNB1 polymorphisms in control groups was evaluated using the chi-square test. The association between each SNP and cancer risk was estimated by calculating odds ratios (ORs) and their 95% confidence intervals (95%CIs). Inter-study heterogeneity was examined with a chi-square based Q statistic test (significance at IPHWE<0.05). Polymorphisms based on one single study were also excluded. Consequently, four CTNNB1 SNPs were involved in our final calculation, including rs1798802 A/G, rs4135385 A/G, rs11564475 A/G, and rs2293303 C/T.After removal of duplicate studies, a total of 715 records were retrieved through database searching. We excluded 704 records by reading titles and abstracts for the following reasons: 574 were functional studies; 61 were reviews or meta-analyses; 58 were not about CTNNB1 SNPs; 6 were not related to carcinoma; and 5 were not associated with the risk of cancer. Then, 11 case–control studies that met our inclusion criteria were involved in the quantitative synthesis. However, two of them had no available original data and one failed in assessment of methodology quality. Therefore, eight studies containing 4388 cases and 4477 controls were included in our meta-analysis . Their cP=0.044, OR=0.72, 95%CI=0.52–0.99). For rs2293303, its variant genotype, recessive and allelic models were all associated with an increased cancer risk . Its variant G allele was also observed to increase the gastrointestinal cancer risk when compared with the wild A allele . For rs2293303, the variant type TT, recessive and allelic models conferred an elevated risk when the control groups were HB .Begg’s test and Egger’s test were used to evaluate the potential publication bias of the included studies. No significant publication bias was indicated in any genetic model of the studied CTNNB1 SNPs .Aberrant activation of the Wnt signaling pathway has been found in many tumors, caused by the accumulation of CTNNB1 expression product in cell . It is wRegarding rs1798802, our findings differed from other related studies to some extent. We observed that the variant type of rs1798802 could reduce the risk of overall cancer, suggesting a potential predictive ability of this polymorphism for cancer risk. The SNP is located in the intron region of CTNNB1, thus it might affect gene transcription and shearing, alter CTNNB1 expression level, and exert effects on the downstream caner-related molecules . The orihttps://www.ncbi.nlm.nih.gov/projects/SNP/snp_ref.cgi?rs=4135385) to obtain the genotype frequency distributions of rs4135385 among different ethnic populations: A/A 48.3%, A/G 46.7%, and G/G 5.0% for European; A/A 17.8%, A/G 57.8%, and G/G 24.4% for Asian. Obviously, the risk genotypes frequency of the SNP is higher in Asian than in Caucasian. Therefore, it is reasonable that the effects of the polymorphism on cancer susceptibility might be masked by the higher frequency of risk genotypes in healthy subjects. Additionally, it has been reported that the association of rs4135385 with GC risk is more prominent among patients with cardia GC than non-cardia GC [Currently, rs4135385 is the most intensively investigated polymorphism among all the CTNNB1 SNPs, recording the largest number of reports in this field. Several researches have demonstrated that rs4135385 is associated with multiple cancers ,16. As tardia GC . Similarardia GC , althougRs2293303 was the only one found to be associated with cancer risk both in overall and stratified analysis among the studied SNPs. Importantly, it is a synonymous SNP (sSNP), located in gene-coding regions of CTNNB1 . AlthougPHWE<0.05 were all excluded from final calculation. These conditions may have led to the limited number of records included in our meta-analysis.Several limitations in our study should be acknowledged. First of all, only English documents were searched while reports in other languages were not involved, which may lead to publication bias. In addition, the study about the association of CTNNB1 polymorphisms with cancer risk remains a relatively emerging field; consequently, the relevant researches are lacking. Besides, the records for which In summary, we systematically reviewed the relationship between CTNNB1 polymorphisms and overall cancer risk. Meanwhile, available data was used to perform a meta-analysis for four highly studied SNPs. The results suggested three of them were associated with cancer risk in overall population or some specific subgroups, including rs1798802, rs4135385, and rs2293303. Our study could provide research clues for further investigations focused on the identification of novel biomarkers with cancer forewarning function.


INPP5D) was reported to be associated with Alzheimer's disease (AD) through modulating the inflammatory process and immune response. A recent genome-wide association study discovered a new locus single nucleotide polymorphism  of INPP5D which was significantly associated with susceptibility to late-onset Alzheimer's disease (LOAD) in Caucasians. In this study, we investigated the relations between the INPP5D polymorphism rs35349669 and LOAD in Han Chinese population comprising 984 LOAD cases and 1352 healthy controls being matched for age and gender. Our results showed no obvious differences in the genotypic or allelic distributions of rs35349669 polymorphism between LOAD cases and healthy controls . Additionally, when these data were stratified by APOEε4 status, there are still no evident differences in the genotypic or allelic distributions in APOEε4 carriers (p > 0.05). Furthermore, meta-analysis of 81964 individuals confirmed that rs35349669 was significantly associated with the risk for LOAD , but the results remained negative in Chinese subgroup . Overall, the current evidence did not indicate that INPP5D rs35349669 polymorphism play a role in the genetic predisposition to LOAD in Chinese population.Inositol polyphosphate-5-phosphatase ( APP, PSEN1 and PSEN2 are associated with early-onset familial AD, which is responsible for part of AD [APOE) gene has been consistently related to the risk of this disease [APOE, recent genome-wide association studies (GWAS) have identified other 20 genes/loci that affected the susceptibility of LOAD [Alzheimer's disease (AD), the most common form of dementia in the elderly , is a nert of AD . The gen disease . In addi of LOAD .INPP5D) are increasingly investigated in AD genetic association studies. INPP5D, mainly expressed in hematopoietic cells, plays an important role in a series of inflammatory responses [INPP5D was implicated in the pathogenesis of LOAD through the regulation of microglial cell function [INPP5D rs35349669 polymorphism was recognized to be strongly associated with the development of LOAD in 74,046 Caucasians [INPP5D in diverse ethnic groups might be different, replication is necessary to validate the potential effects of INPP5D in non-Caucasian population including Asians. To address this question, the present study was conducted to evaluate the association of rs35349669 SNP with LOAD in Northern Han Chinese population.Given the significant part of inflammation in AD pathogenesis, inflammation-relevant genes including Inositol polyphosphate-5-phosphatase . As expected, MMSE scores were obviously less in LOAD patients than that in control subjects (P < 0.001). The APOE4 allele frequency was also obviously different between patients and control subjects (P < 0.001). Distributions of the APOE and rs35349669 genotypes in cases and controls were all in the Hardy–Weinberg equilibrium (P > 0.05).The demographic and clinical characteristics of the subjects are detailed in Table P = 0.167, allele P = 0.094). To rule out blending effects in our initial association analyses, we reassessed rs35349669 effects under various genetic models in logistic regression adjusting for age at onset in LOAD patients (age at examination in control group), gender, and APOE ε4 status. Disappointedly, the result also failed to reveal any significant difference between LOAD and controls. Thus, our study observed no significant differences in the genotypic or allelic distributions of rs35349669 polymorphism between LOAD cases and healthy controls in a Northern Han Chinese population. Meanwhile, we carried out a meta-analysis about the association of rs35349669 with LOAD and found rs35349669 was strongly associated with LOAD  . In subgroup analysis, the rs35349669 polymorphism was also significantly associated with the risk for LOAD in Caucasian, however, the results showed that there was no association of rs35349669 with AD risk in Chinese population .The allele and genotype distributions of rs35349669 in two groups are presented in Table APOE genotype on the risk for LOAD in logistic regression models . In order to further investigate whether the presence of the APOE ε4 allele modified the association of rs35349669 with LOAD, the total group was stratified in by APOE ε4 carriers and APOE ε4 noncarriers. We observed no significant differences between AD and controls in genotype and allele distributions (P > 0.05) (Table P > 0.05)  family, is located on chromosome 2q37.1 [INPP5D and LOAD risk in Northern Han Chinese. Finally, we failed to find significant differences in the genotypic or allelic distributions of rs35349669 polymorphism between LOAD cases and healthy controls in a Han Chinese population, even after adjustment for age, gender, and APOE ε4 status, these findings might have resulted from the relatively small sample size of our experimental study, in order to reduce the possibility, we explored the association of rs35349669 with LOAD risk in the meta-analysis in 81 964 individuals including Caucasian and Chinese, rs35349669 polymorphism was strongly associated with AD risk in the entire population and in Caucasian , while rs35349669 polymorphism did not relate to LOAD in Chinese. Therefore, the current evidence did not support the correlation between rs35349669 and LOAD in Chinese.e 2q37.1 , 11, it e 2q37.1 , 12, 13.INPP5D rs35349669 polymorphism was identified to be strongly associated with the development of LOAD (P < 0.05) in two-stage meta-analysis of GWAS in 74,046 Caucasians [http://www.ncbi.nlm.nih.gov/projects/SNP). Alternatively, the effects of rs35349669 may be population-specific, possibly due to specific interactions between gene and environment. The differentiated effects of INPP5D rs35349669 polymorphism on AD probably attribute to a brain structural mechanism for such population specific genetic effects. In addition to the population specification and special genetic backgrounds, environments, educational background, sample size, etc. may be the source of different results between Caucasian and Chinese. On the other hand, although our study failed to replicate any association of the examined SNP with LOAD in Chinese, we could not rule out the possibility that other SNPs of INPP5D associated with LOAD.Recently, ucasians . SubsequINPP5D in immune response and inflammation in the central nervous system(CNS) is still poorly understood. Recent studies showed that the human SHIP protein, encoded by the INPP5D gene, was supposed to restrain the release of diverse inflammatory cytokines from microglia,astrocytes or even neurons, such as IL-6, IL-8,TNF-α [INPP5D with the product of CD2AP, another LOAD risk gene, could control degradation of IgE receptor FceRIc, some IgE receptors are members of the MS4A gene superfamily that has been correlated with LOAD risk [INPP5D gene was associated with other neuropathologies coexist with AD pathology, such as microinfarcts and LB disease [INPP5D in the near future, it may be helpful to find new loci that related to LOAD.The function of -8,TNF-α . In addiOAD risk . Besides disease . With reINPP5D rs35349669 polymorphism with LOAD in Chinese. It is likely that the implication of INPP5D variation in AD risk may be specific to particular ethnic groups, besides, the implication is too small to be detected responsibly by a cohort of our size. It warranted investigators to clarify the role of INPP5D polymorphisms in LOAD in larger cohorts and in other ethnic populations.In conclusion, we were not able to detect the significant association of We investigated 984 sporadic LOAD patients  and 1352 healthy control subjects  matched for sex and age. All the subjects were unrelated Northern Han Chinese originated from Shandong Province. The patients were recruited from the Department of Neurology at Qingdao Municipal Hospital and some other hospitals in Shandong province. The diagnose of probable AD met with the criteria of the National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's disease and Related Disorders Association . No famiINPP5D (rs35349669) and APOE polymorphisms was performed by a custom-by-design 48-PlexSNP scan TM Kit , as previously described [APOE were carried out by Shanghai Genesky Bio-Tech Co., Ltd. (http://biotech.geneskies.com/index.html) using the improved multiplex ligase detection reaction (iMLDR) method [Genomic DNA was extracted from peripheral blood leukocytes of AD patients and healthy individuals using the Wizard genomic DNA purification kit .Genotyping of escribed . This wa) method . Data anAPOE4 status were also examined by the chi-square test. The association of rs35349669 with LOAD risk was further analyzed using logistic regression adjusting for age, gender, and APOE 4 status under various genetic models that were defined as 1 (TT + TC) versus 0 (CC) for dominant, 1 (TT) versus 0 (TC + CC) for recessive, and 0 (CC) versus 1 (TC) versus 2 (TT) for additive. The P value, odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Estimation of the statistical power was performed with the STPLAN 4.3 software. Values of P < 0.05 were considered statistically significant.Statistical analysis was performed using SPSS16.0 software. Genotype and allele frequencies were calculated by counting. The Hardy–Weinberg equilibrium (HWE) was tested for each SNP with genotype data from both AD patients and controls. Differences in the characteristics between the two groups were tested using Student's t-test or the chi-square test. Genotypes and alleles frequencies between LOAD and healthy control group were compared using Pearson χ2 test or Fisher's exact test. Differences between cases and controls after stratification for 2 estimates with evaluate the possible effect of study heterogeneity on the results. Stata V.12.0 was used to perform all these analyses.Additionally, we also combined our data with the results from other studies about rs35349669 and LOAD risk , 19, 20


The renin-angiotensin system (RAS) represents an important target of antihypertensive medications. Angiotensin-converting enzyme inhibitors (ACEI) and angiotensin II receptor blockers (ARB), which are widely-used RAS inhibiting drugs, have been suggested to have beneficial effects on bone tissue. We aimed to assess the associations of use of ACEIs and/or ARBs with the risk of fractures using a population-based prospective cohort and a meta-analysis of published prospective cohort studies. Information on antihypertensive medication use (including both ACEIs and ARBs) were assessed in 1743 men and women of the Kuopio Ischemic Heart Disease prospective cohort study. Hazard ratios (HRs) [95% confidence intervals (CI)] of ACEIs or ARBs use with incident fractures were calculated. A total of 203 composite  fractures occurred during a median follow-up of 14.8 years. In multivariate adjusted analysis, the HR for composite fractures comparing users of ACEIs or ARBs with non-users was 1.00 (0.59–1.69). The corresponding adjusted HR for hip fractures comparing users versus non-users of ACEIs or ARBs was 0.89 (0.32–2.47). Including the current study, a total of 11 observational cohort studies involving 3526,319 participants and >323,355 fractures were included in a meta-analysis. Comparing ACEI users with non-users and ARB users with non-users, the HRs for composite fractures were 1.09 (0.89–1.33) and 0.87 (0.76–1.01) respectively. The corresponding HRs for hip fractures were 0.91 (0.86–0.95) and 0.80 (0.75–0.85) respectively. Use of RAS inhibitors was not associated with long-term risk of composite fractures in both primary and pooled analyses. Pooled evidence however suggests a beneficial effect of RAS blockers on hip fracture risk.The online version of this article (doi:10.1007/s10654-017-0285-4) contains supplementary material, which is available to authorized users. Aging of the population is associated with an increase in age-related chronic conditions such as fractures (particularly osteoporotic fractures). These are one of the most common causes of disability worldwide and associated with high health care costs , 2. CompThe majority of older people with osteoporosis have co-morbidities such as hypertension and cardiovascular disease. Two major risk factors for osteoporotic fractures are reduced bone mass and falls, and these have a close relationship with hypertension . ElevateWe conducted the primary cohort analyses according to STROBE  guidelines for reporting observational studies in epidemiology  .The study population formed part of the ongoing Kuopio Ischaemic Heart Disease (KIHD) population-based prospective cohort study, which was set up primarily to investigate established and emerging risk factors for cardiovascular disease and other additional health outcomes in eastern Finland . ParticiAntihypertensive medications were classified based on antihypertensive medication classes; all antihypertensives, ACEIs or ARBs, β-blockers, calcium channel blockers, and diuretics. Data on diagnosis of chronic diseases including hypertension and the use of antihypertensive drugs were assessed by self-administered questionnaires. These were then cross-checked by a physician.We included all incident fractures, representing all hip, humeral, and wrist fractures, that occurred from study entry to 2014. The endpoints assessed were incident composite, hip, and wrist fractures. Composite fractures were defined as hip, humeral, and wrist fractures. In the KIHD study, participants are under annual continuous surveillance for the development of new outcome events, including fractures . No lossAll baseline characteristics as well as risk markers were assessed during the same visit at study entry. Methods for collection of blood specimens and the measurement of lipids and biochemical analytes have been previously described in detail . BrieflyBaseline characteristics were presented as means (SD) or median (interquartile range) for continuous variables and percentages for categorical variables. Cox proportional hazard regression models were used to conduct time-to-event analyses after confirmation of the proportional hazards assumptions . Antihypχ2 statistic and the I2 statistic [We conducted a systematic review and meta-analysis of observational cohort studies using a predefined protocol and which was reported in accordance with PRISMA and MOOSE guidelines , 38 , which remained non-significant following further adjustment for several risk factors  1.00 . There was similarly no association after additional adjustment for SES and physical activity 1.00  , 0.89 , and 0.89  respectively. There was also no evidence of any associations with risk of wrist fractures (Table During a median (interquartile range) follow-up of 14.8 12.8–15.8) years, 203 incident composite fractures  were recorded. Of the total number of incident fractures, 70 and 42 were hip and wrist fractures respectively. Comparing ACEIs or ARBs users with non-users, the age and sex adjusted HR for composite fractures was 1.00  in pooled analysis of two studies  that compared ACEI users with non-users. In pooled analysis of these two studies, the corresponding risk was 0.80 (95% CI 0.75–0.85) when ARB use was compared with no use. Comparing ACEI or ARB users with non-users, the RR for hip fractures in pooled analysis of four studies was 0.95 (95% CI 0.72–1.26)  and 0.81 (95% CI 0.69–0.95) for wrist fractures . The RR for wrist fractures was 0.68 (95% CI 0.53–0.87) and 0.76 (95% CI 0.61–0.94) for pelvic fractures, when ARB use was compared with non-use .In this population-based prospective study of middle-aged to elderly men and women, there was no evidence of an association of ACEI or ARB use with the risk of fractures and this was consistent across several clinically relevant subgroups. No evidence of significant associations with risk of fractures was also observed for diuretic use or β-blocker use. In pooled analysis of relevant published cohort studies, use of ACEI or ARB was not associated with the risk of composite fractures. However, pooled analysis of two large studies showed that ACEI use was associated with reduced risk of hip fractures , 47. TheFindings of our primary cohort analysis are consistent with a number of cohort studies , 44, 48 Given the close relationship between hypertension and its detrimental effects on bone physiology –10, it hTaken together, the evidence suggests ACEIs and ARBs, which inhibit the RAS, may help reduce fracture risk by improving bone composition and structure. The inconsistent associations between the use of RAS inhibitors and risk of site-specific fractures as demonstrated in our findings, may reflect the beneficial effects of angiotensin II on bone and the differential effects of ACEIs and ARBs on bone tissue. For example, Izu and colleagues showed in mice that a type 2 ARB significantly enhanced bone mass, whilst a type 1 ARB did not improve bone mass . In the Our study had the advantage of utilizing a large-scale population-based prospective cohort design with a pooled analysis of all published observational cohort studies on the topic in one comprehensive investigation. The primary cohort study employed a sample of men and women who were representative of the general middle-aged to elderly population; there was complete follow-up for all participants; follow-up period was long with annually updated incident outcomes; and the analysis was comprehensive with adjustment for several confounders as well as assessment for evidence of effect modification. Pooled analysis of previous studies, including the current study, enhanced power to assess the nature and magnitude of the association. Limitations of the current study include lack of separate data on ACEIs and ARBs and the duration of blood pressure treatment in the primary cohort; absence of data on relevant confounders such as markers of renal function , which influence bone health; the relatively young age of study cohort at baseline precluded the ability to potentially assess all fracture cases during the follow-up period of the current study, as majority of fracture cases tend to occur in the very elderly; the limited number of studies for the pooled analysis; inconsistent definition of composite fracture outcomes that did not enhance comparison across studies; substantial heterogeneity across studies; and inability to explore for publication bias because of the small number of studies. In addition, due to the variable adjustment by the eligible studies in the review, there was the possibility of residual confounding. However, the majority of studies reported estimates based on adjustment for a comprehensive panel of confounders. Finally, a number of these studies did not account for other antihypertensive medication use such as thiazides and β-blockers in their analysis.In a middle-aged to elderly population of Caucasian men and women, use of RAS inhibitors was not associated with risk of composite fractures and this was confirmed by our pooled analysis of previously published observational cohort studies. A beneficial effect of use of RAS inhibitors was observed for hip fractures, though the evidence was limited; however, it was based on pooled analysis of two large-scale cohort studies. Our study findings highlight the fact there are still inconsistencies in the associations of use of RAS inhibitors with risk of fractures. Further research is needed to confirm or refute these findings and assess the biological pathways underpinning any associations.Supplementary material 1 (DOCX 158 kb)Below is the link to the electronic supplementary material.


Glutathione-S-Transferase T1 (GSTT1) null genotype has been shown to be associated with the risk of esophageal cancer. However, the results remain inconsistent. Thus a comprehensive meta-analysis was conducted to assess the strength of association between GSTT1 null genotype and the risk of esophageal cancer.A literature search of PubMed, Embase, China National Knowledge Infrastructure (CNKI) and Wanfang databases up to March 31, 2017 was conducted and 30 eligible articles with 4482 cases and 6681 controls were finally recruited. The strength of correlation between GSTT1 polymorphism and the susceptibility of esophageal cancer was assessed by the crude odds ratios (ORs) with 95% confidence intervals (CIs). Subgroup analyses and sensitivity analyses were performed to further identify the association.P < 0.05). In a subgroup analysis by ethnicity, GSTT1 null genotype was correlated with a significantly increased risk of esophageal cancer among Asians , instead of Caucasians or Africans . In the analysis by histological type, GSTT1 null genotype was correlated with a significantly increased risk of esophageal squamous cell carcinoma , particularly among Asians , but not among Caucasians or Africans . In addition, there is no significant correlation between GSTT1 null genotype and the risk of esophageal adenocarcinoma .GSTT1 null genotype significantly increased the risk of esophageal cancer (OR = 1.20; 95% CI 1.04–1.40; Our findings demonstrate that GSTT1 null genotype significantly increases esophageal cancer risk, particularly in Asians. Esophageal cancer is the sixth leading cause of cancer-related mortality and the eighth most common cancer worldwide . An estiet al. [Glutathione-S-transferases (GSTs) are important phase II biotransformation enzymes that catalyzing the nucleophilic addition of glutathione to several hazardous xenobiotics, including phase I electrophilic and carcinogenic metabolites . Howeveret al. –8. Previet al. –11.To date, several meta-analysis studies have reported the association between null GSTT1 genotype and the risk of esophageal cancer. However, the results of these studies remain outdated and incomprehensive –14. In tIn total, 100 articles were retrieved. Figure P < 0.05; Table P < 0.05; Table P > 0.05 for Caucasians and OR = 1.32; 95% CI 0.98–1.77; P > 0.05 for Africans; Table Table P < 0.05; Table P < 0.05; Table P > 0.05 for Caucasians and OR = 1.32; 95% CI 0.98–1.77; P > 0.05 for Africans; Table P > 0.05; Table In the analysis by histological type, GSTT1 null genotype were correlated with a significantly increased risk of ESCC . Thus, there was no obvious publication bias in this meta-analysis.Publication bias was assessed by both the Begg’s funnel plot and the Egger’s test. The shape of the Begg’s funnel plot did not reveal any evidence of obvious asymmetry Figure . Egger’sThe sensitivity analysis was conducted to test the influence of an individual data on the pooled ORs and CIs by eliding a study in turn. Our findings suggested that the present meta-analysis results were relatively robust and stable Figure .As showed in Figure et al. study, 11 studies included in the meta-analysis were in Chinese Han population. Although the results showed a significant association between GSTT1 null genotype and esophageal cancer risk, the single Chinese Han population limited the power of the statistical analysis [et al. study, 15 studies included in the meta-analysis were in Asian population. Although the results showed a significant association between GSTT1 null genotype and esophageal cancer risk, the single Asian population limited the power of the statistical analysis [et al. study, a total of 24 studies were used. Adjusted ORs with corresponding 95% CIs were reported in 9 studies. In the overall analysis there was no significant association between GSTT1 null genotype and esophageal cancer risk. However, meta-analysis of adjusted ORs showed a significant association between GSTT1 null genotype and esophageal cancer risk [Many studies suggest genetic variants play important roles in individual susceptibility to esophageal cancer , 42. In analysis . Also Inanalysis . In Cai cer risk . Becausecer risk –14. ThusThis meta-analysis, including 30 case-control studies with 4482 cases and 6681 controls, identified the association between GSTT1 null genotype and esophageal cancer risk. GSTT1 null genotype significantly increased overall esophageal cancer risk. In a subgroup analysis by ethnicity, GSTT1 null genotype was correlated with a significantly increased risk of esophageal cancer among Asians. In the analysis by histological type, GSTT1 null genotype was correlated with a significantly increased risk of ESCC, particularly in Asians. However, there was no significant correlation of GSTT1 null genotype with the risk of EADC. To date, this is the first meta-analysis concerning the association of GSTT1 null genotype with the risk of different histological types.GSTT1, encodes an enzyme that plays a crucial role in the detoxification of a variety of endogenous or exogenous carcinogens. It is located on 22q11.23 with 8146 base pairs, 5 exons and 4 introns in all . Our resSince the results from meta-analysis can be affected by histological types, a subgroup analysis was carried out regarding different histological type for the GSTT1 null genotype. GSTT1 null genotype was correlated with a significantly increased risk of ESCC among Asians, but not among Caucasians and Africans. However, there was no significant correlation of GSTT1 null genotype with the risk of EADC. All results should be interpreted with caution. Only two African studies were recruited in the current meta-analysis, which may restrict statistical power to detect a real assessment in Africans. More large scale studies are needed to verify the results. Subgroup analyses were also performed regarding ethnicity for the GSTT1 null genotype. GSTT1 null genotype was correlated with a significantly increased risk of esophageal cancer among Asians, but not among Caucasians and Africans. The results were more robust on histological type of ESCC. This meta-analysis confirmed the mutual effect of GSTT1 null genotype in different populations to the risk of esophageal cancer. Possible explanations include: (1) significance of these enzymes may vary with the ethnicity genetic backgrounds, environmental exposures and histological types. The regional difference in the frequency of esophageal cancer is probably due to genetic polymorphism and variable exposure to environmental factors; (2) GSTs metabolize a variety of overlapping substrates and individuals lacking GSTT1 can also metabolize the carcinogens by other alternative GST enzymes. Furthermore, there was only one study concerning the association between GSTT1 null genotype and EADC on Asians. Thus, we failed to evaluate the potential role of GSTT1 null genotype in EADC risk in Asians due to the lack of available data to date. More case-control studies on the GSTT1 null genotype are encouraged, especially in Asians, for a better understanding the role of GSTT1 null genotype in the EADC development.Some limitations must be acknowledged in the current meta-analysis. First, significant heterogeneity was observed between publications for GSTT1 null genotype. Potential sources of heterogeneity include the study design, publication year, ethnicity, country, histological type, sample size, and so on. When subgroup analyses were carried out according to ethnicity and histological type, this heterogeneity was reduced or removed in some subgroups, implying different effects on histological types and ethnic populations. These findings should be interpreted with very cautions. Second, our findings were based on unadjusted ORs and CIs, whereas a more precisely investigation could be performed if the sufficient individual data were available. Third, only two African studies were recruited in the current meta-analysis, the results in African population should be interpreted with caution. More large scale studies are needed to verify the results in Africans. Finally, due to lack of uniform individual-level data, further stratified analysis to measure any interactions between gene–gene variation and gene-metabolic traits was not performed.In conclusion, our meta-analysis findings demonstrated that GSTT1 null genotype significantly increased esophageal cancer risk, particularly in Asians. In addition, GSTT1 null genotype was correlated with a significantly increased risk of ESCC, particularly among Asians. However, more studies are warranted to confirm or refute these correlations, particularly with respect to gene-gene and gene-environment interactions.Pubmed, Embase, China National Knowledge Infrastructure (CNKI) and Wanfang databases  were searched using the following terms: ‘glutathione S-transferase T1’ or ‘GSTT1’, ‘polymorphism’ or ‘variant’, and ‘esophageal’ or ‘esophagus’, and ‘cancer’ or ‘carcinoma’ or ‘tumor’ or ‘malignancy’. The literature search was limited to English or Chinese articles. Additional publications were identified by a manual search based on references of retrieved studied or reviews.The selection criteria were: (1) in a case-control study design, (2) studies that evaluated the relationship between the GSTT1 null genotype polymorphism and esophageal cancer, (3) usable data on genotype frequency. Thus, reports without usable data, reviews, comments and duplicated publications were excluded.The data were collected by two independent reviewers. The extracted information contained: first author, year of publication, country of origin, ethnicity, number of cases and controls, genotyping method and characteristics of cases and controls. When come to conflicting assessment, disagreements were settled through a discussion among all authors.P < 0.05 (two-tailed) was considered as statistical significance. A Chi-square-based I2 test was used to detect heterogeneity [I2 < 25% indicates low heterogeneity, 25% ≤ I2 ≤ 50% indicates moderate heterogeneity, and I2 > 50% indicates large heterogeneity [I2 > 50% or P < 0.10 (two-sided), the random-effects model (the DerSimonian-Laird method) was utilized to pool the data [The strength of correlation between GSTT1 null genotype and the susceptibility of esophageal cancer was assessed by the crude odds ratios (ORs) with 95% confidence intervals (CIs). A ogeneity  and an Iogeneity . When I2the data , otherwithe data . Subgourthe data . Sensiti


BRCA1) gene makes great contributions to the repair of DNA. The association between BRCA1 P871L polymorphism and cancer risk has been investigated in a growing number of studies, but the conclusions are not conclusive. To obtain a comprehensive conclusion, we performed a meta-analysis of 24 studies with 13762 cases and 22388 controls. The pooled results indicated that BRCA1 gene P871L variant decreased risk of overall cancer (homozygous model: odds ratio (OR) = 0.89, 95%confidence interval (CI) = 0.79-1.00; recessive model: OR = 0.89, 95% CI = 0.80-0.99). The stratified analysis observed decreased risk associated with BRCA1 P871L in subgroups among Asians and high score studies, but not Caucasians or low score studies. In conclusion, despite several limitations, this meta-analysis suggested that BRCA1 P871L genetic variation may be associated with decreased susceptibility to cancer.Breast cancer 1 ( Cancer is one of serious diseases severely endangering the human health and lives. In 2012, the world had 14.1 million new cases of cancer and 8.2 million patients died from cancer  and recessive models [TT vs. (CC/CT)] as the models. The stratified analysis was performed by cancer type, ethnicity, control source and quality score of studies.P>0.10 for the Q-test), the fixed effect model was performed to estimate the combined OR [I2 statistics and a larger I2 value indicating a greater heterogeneity [P values were two-sided test and P< 0.05 was considered statistically significant.Z-test was used to determine the statistical significance of pooled ORs. Hardy-Weinberg equilibrium (HWE) was examined by Chi-square test based on the genotype distribution among controls. Heterogeneity was analyzed using the Chi-square based Q-test. When no heterogeneity exist (bined OR . Otherwibined OR . In addiogeneity . Sensitiogeneity . STATA 1


P = 0.010). Moderate heterogeneity of RRs was observed across these studies . Dose-response meta-analysis indicated that the risk of prostate cancer reduced by 3.7% (95% CI 1.5%−5.8%) for each 20 grams per day increment of legume intake. In conclusion, the results from this meta-analysis suggest that a high intake of legumes is associated with a low incidence of prostate cancer.Previous studies regarding the relationship between legume intake and risk of prostate cancer have reported inconsistent results. We conducted a meta-analysis of prospective cohort studies to summarize evidence on this association. A systematic literature search of articles published through June 2016 was performed using PubMed and Web of Science databases. The combined relative risk (RR) with its 95% confidence interval (CI) for the highest versus the lowest intake of legumes was calculated with a random-effects model. Dose-response meta-analysis was also performed for the studies that provided at least three levels of legume consumption. Ten articles (eight cohorts) reporting 281,034 individuals and 10,234 incident cases were identified. The individuals with high consumption of legumes compared with the reference group experienced a significantly reduced risk for developing prostate cancer (RR: 0.85 [95% CI 0.75−0.96],  Prostate cancer is the second most common cancer in men worldwide, with 1,111,700 newly diagnosed cases and 307,500 deaths estimated to have occurred in 2012  and crucLegumes contain a broad class of bioactive compounds for which anti-carcinogenic roles have been indicated by experimental studies, either directly or through further metabolizing by gut microbiota . In epidWith the aim of exploring the risk of prostate cancer at different levels of legume consumption, we performed a meta-analysis of prospective cohort studies published up to June 2016.With the search strategy, 840 unique publications were initially retrieved. After reading the titles and abstracts, 47 articles were considered of interest and full text was retrieved for further evaluation. Thirty-seven of these 47 articles were subsequently excluded and finally 10 articles –18 were Two included articles published by Park et al. . All studies had described independent, consecutive sampling of their cohort. Mean or median follow-up duration ranged from 4.2 to 19.4 years. Participants were followed up for an average of over 7 years in the most of articles (70.0%). The sample sizes of the cohorts ranged from 3,313 to 82,483, with the four largest studies recruiting individuals over 40 thousand , histologically examination (two studies), or medical and pathology records (one studies) Table .Adjusted RRs could be determined for all cohort studies. Each risk estimate was adjusted for age. Five studies (50.0%) reported an estimate adjusted for at least one of the other two established risk factors for prostate cancer: race (3 cohorts) and family history of prostate cancer (5 cohorts). Four articles provided estimates adjusted for total energy intake. Detailed information on adjustments is present in Table P = 0.010). Moderate heterogeneity of RRs was observed across these studies . Therefore, we explored the potential sources  of heterogeneity by using meta-regression. As a result, only the sample size (P = 0.033) was identified as a possible source of heterogeneity in the overall meta-analysis. In addition, we also used Galbraith plot to detect studies that might contribute to heterogeneity. As a result, we found that the Diallo et al.’ study [P = 0.232, 2I = 24.7%), and the combined RR (95% CI) was 0.90 (0.81–0.99).Figure .’ study  was the P = 0.041). Funnel plot .Considering three studies only reported risk estimates for total soy food or one type of soy food, in order to allow an unbiased comparison, we also computed the RR for whole legume foods from the remaining five studies. Compared with subject with low intake of legumes, the individuals with high consumption of whole legumes experienced a significant reduced risk for developing prostate cancer , but not in other geographical populations. When stratified by type of legumes, the analysis limited to soy products yielded an RR of 0.89 . In the subgroup analysis by follow-up time, the RRs (95% CI) were 0.80 (0.64–1.02) and 0.86 (0.71–1.03) for follow-up > 10 years and ≤ 10 years, respectively. Finally, in the stratified analyses by sample size and publication year, statistically significant association was observed in those small studies  and studies published before 2005 .Next, we performed stratified analyses based on a number of key study characteristics Table . We firsThe influence of each included study on the pooled risk estimate was assessed by repeating the meta-analysis after omitting each study in turn. The results suggested that the combined RR was not dominated by any single study. The RRs ranged from a low of 0.81 (95% CI 0.69–0.95) to a high of 0.90 (95% CI 0.81–0.99) via omission of the study by Park et al.  and the Cumulative meta-analysis is the process of repeated meta-analysis of individual studies each time adding a new study. In this study, we performed the cumulative meta-analysis according to publication year. As shown in P = 0.41 for non-linearity). The risk reduced by 3.7% (95% CI 1.5%–5.8%) for every additional 20 grams per day   for each 20 grams per day increment of legume intake.n = 5) and, hence, insufficient statistical power. However, these results also implied that other types of legumes except soybeans might contribute the protective effects of whole legumes on incidence of prostate cancer, which is worthy of further investigation in future studies.Two meta-analysis published in 2009 , 20 inveHeterogeneity is often a concern in a meta-analysis. Moderate heterogeneity was observed among included studies, which could distort the pooled risk estimates. Heterogeneity is caused by variation in definitions and ranges of legume intake, methods of exposure and outcome assessment, and sources of study population. According to the results of meta-regression analysis, we think the difference in sample size is the major source of between-study heterogeneity. In addition, we removed the studies that obviously contributed to the heterogeneity through the Galbraith plot and then repeated the meta-analysis. The relationship still persisted without any significant heterogeneity. These results indicated our findings were robust and less likely affected by the heterogeneity.A causal relationship between legume intake and prostate cancer risk may be mediated by several mechanisms because of a great variety of anti-carcinogens in legumes. Flavonoids, especially isoflavones, may be the most important contributor to the anti-cancer activity of legumes. Mukhtar et al. reported that dietary flavonoid fisetin could inhibit proliferation, migration, and invasion by binding to β-tubulin and disrupting microtubule dynamics in prostate cancer cells . It alsoStrengths of our meta-analysis include the strict inclusion criteria, especially restriction to prospective cohort studies, which greatly reduced the likelihood of recall and selection biases. In addition, as individual studies had limited statistical power, our study expanded the sample size and provided more reliable estimates. Finally, the reliability of the findings in sensitivity analyses and Galbraith plot analysis, as well as the significant dose-response relationship, further strengthened our findings.A potential limitation of this study is the inadequate control of all known confounding factors in included studies, which may bias the results in either direction, toward exaggeration or underestimation of the effect size estimates . AnotherIn conclusion, the results from this meta-analysis suggest that a high intake of legumes is associated with a low incidence of prostate cancer. Considering the limited included studies, further large well-designed cohort studies are warranted to confirm the findings from this meta-analysis. In addition, the mechanisms and active compounds in legumes mediated this relationship remain to be elucidated.This meta-analysis follows the standards of quality for reporting meta-analyses . We searTo reduce varieties between studies, we adopted the following methodological restrictions as the inclusion criteria: studies that provided the minimum information essential to calculate the relative risk (RR) associated with intake of legumes, including cohort and nested case-control studies published as original articles. In instances of duplicate publications, the most comprehensive information with the longest follow-up was used.Articles were reviewed and cross-checked independently by two investigators (J.L. and Q.Q.M). Data on the following characteristics were collected: surname of the first author, publication year, study design, study population, sample size, number of patients who developed prostate cancer, mean or median years of follow-up, study location , type of legumes studied, assessment of exposure, ascertainment of prostate cancer, and reported adjustment for potential confounding factors. When available, we used the effect size estimates from the most fully adjusted model. Any disagreements were resolved by consensus.http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp). This scale is an eight-item instrument designed to assess study population and selection, study comparability, follow-up, and assessment of outcome. One or two points were awarded for each criterion and then points were added up to compare study quality in a quantitative manner. We assigned total points of < 7 and ≥ 7 for low and high quality of studies, respectively.The quality of each study was evaluated by the same two investigators using the Newcastle-Ottawa Scale  was calculated by combining the study specific estimates with a random-effects model  that acctatistic  to evaluith plot  was usedP value for nonlinearity was calculated by testing the null hypothesis that the coefficient of the second spline is equal to 0.In the dose-response analysis, we included studies that provided at least three levels of legume consumption and person-years in each exposure category. Because most included studies provided categorical data with a range for exposures, we assigned the mid-point in each category to the corresponding RR for each study. When the highest category was open ended, we assumed the width of the interval to be the same as in the preceding category. We used generalized least squares trend (GLST) regression model , 33 to aTo calculate the person-years in each exposure category, we extracted data from articles that specified one or more of the following: total person-years of follow-up; sample size and mean (or median) follow-up time; or sample size and cumulative incidence rate. Event rates were expressed as per 100,000 patient-years at risk. Weighted meta-analytic prevalence estimates for outcome were calculated with an inverse-variance random-effects model. The variance was stabilized using the Freeman-Tukey type arcsine square-root transformation .P < 0.05.Small study bias  was assessed with funnel plot, Begg's test (rank correlation method)  and Egge


Many people are exposed to perfluoroalkyl substances (PFASs) because these substances are widely used as industrial products. Although epidemiological studies suggest that PFASs can disrupt thyroid hormones, the association between PFAS exposure and thyroid function remains inconclusive. Therefore, we performed a comprehensive meta-analysis to investigate the association between PFASs exposure and thyroid hormones.We searched medical literature databases for articles on the association between PFASs–perfluorooctanesulfonic acid (PFOS), perfluorooctanoic acid (PFOA), and perfluorohexane sulfonic acid (PFHxS)–and thyroid hormone levels in adults. Twelve articles were included in the meta-analysis, and the pooled z values were calculated with correlation or regression coefficients.The blood PFOS concentration was positively correlated with free T4. The pooled z value was 0.05 : 0.03, 0.08). PFOS was negatively correlated with total T4 and total T3 when excluding outlier studies. In a subgroup analysis stratified by mean PFOS concentration, PFOS was observed to be positively associated with free T4 and TSH and negatively associated with total T3 in the intermediate concentration group (8–16 ng/mL). PFOA concentration was negatively correlated with total T4  after omitting one outlier study. PFHxS also showed a negative correlation with total T4 . A subgroup analysis of pregnant women showed that there was no association between PFASs and thyroid hormones.Our meta-analysis suggests that PFASs are negatively associated with total T4, and their effect can be different depending on the PFAS concentration. Perfluoroalkyl substances  have been widely used as various industrial products such as surfactants, lubricants, photographic emulsifiers, paints, fire-fighting foams and food packaging. Humans are exposed to PFASs mainly through contaminated food, water, and household dust . Thus, PThyroid hormones play a critical role in the regulation of metabolism, and thyroid function is related to cardiovascular disease, fertility, and fetal neurodevelopment , 19. In A meta-analysis was performed in accordance with the general principles recommended in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)  35]..35].In the databases PubMed, Embase, and Web of Science, articles, published from inception (1985 in PubMed and Web of Science and 1987 in Embase) to April 30, 2017 were searched by two investigators (S.M. and M.J.K.) using a combination of the following terms: “perfluorinated”, “perfluorooctanoic”, “perfluorooctane”, “perfluorohexane”, “PFOS”, “PFOA”, and “PFHxS” and “thyroid”. The language used in the literature was limited to English. The detailed search strategy is presented in the To select studies to be included in this meta-analysis, the PCOS  framework was used . The parin vitro models (n = 105); 3), the study was not related to PFAS and thyroid (n = 32). Second, the full texts of the selected, potentially relevant articles (n = 35) were electronically downloaded and reviewed independently by the two investigators (S.M. and M.J.K.) based on the criteria listed above. Articles were excluded for the following reasons: 1) the participants were not adults (n = 8) or part of the general population (n = 2); 2) PFAS and/or thyroid concentrations were presented as quartiles or quintiles, not as a continuous variable (n = 9); 3) there was no information on the Pearson correlation coefficient, Spearman correlation coefficient, or regression coefficient between PFASs and thyroid hormones (n = 2); 4) multiple studies used the National Health and Nutrition Examination Survey database (n = 2). Any disagreements were resolved by a third investigator (Y.J.P.). Finally, 12 articles were selected for the meta-analysis.Literature search yielded 449 potentially relevant articles . DuplicaThe following data were collected: first author, publication year, country, number of subjects, the mean or median blood concentration of PFASs, TSH, total/free T4 and/or total T3, and Pearson correlation coefficient, Spearman correlation coefficient, or regression coefficient. In addition, the method for measuring free T4 in each study was checked. Blood concentration of free T4 was measured in nine studies and all of them used the analog method: chemiluminescent immunoassay (n = 5), radioimmunoassay (n = 3), or enzyme-linked immunosorbent assay (n = 1).Three researchers independently assessed the methodological quality of the included articles using a modified cross-sectional assessment provided by the Agency for Healthcare Research and Quality . Here, eTo investigate the association between PFASs and thyroid hormone levels, we calculated the pooled z values using a Pearson correlation coefficient transformed by the Fisher z-transformation. Among the 12 studies, the Pearson correlation coefficient was reported only in two studies , 38. In (1) Estimated Pearson correlation coefficient = 2 × sin (Spearman correlation coefficient ×π/6)2 = t2/(t2+n-2)(2) (Estimated Pearson correlation coefficient)t = regression coefficient /the standard error of regression coefficient.2 statistic was used to test for heterogeneity. Subgroup and sensitivity analyses were performed to determine the cause of heterogeneity. In the sensitivity analysis, we checked the changes in the results by excluding one specific study to examine the stability or strength of the results. The potential for publication bias was assessed using a funnel plot analysis. All statistical analyses were conducted using the statistical program R .The Higgins’ IFour hundred and forty-nine studies were screened and assessed for eligibility, and 12 studies were finally selected for this meta-analysis . The stu2 = 0%). No publication bias was found. To evaluate the concentration-dependent difference in the association, studies were divided into three groups according to their mean PFOS concentration: < 8 ng/mL (low), 8–16 ng/mL (intermediate), and > 16 ng/mL (high). The correlation became more pronounced in the intermediate concentration group; the pooled z values of the studies were 0.07 . Because pregnancy itself can affect thyroid hormone levels and the thyroid function plays an important role in fetal neurodevelopment [2 = 18%).Nine studies provided data suitable for a meta-analysis of correlations between PFOS exposure and free T4 . PFOS waelopment , 44, the2 = 70%; p < 0.01) (2 = 5%)  and showed significant heterogeneity (I < 0.01) . One out(2 = 5%) . Subgrou(2 = 5%) .2 = 63%) (2 = 46%). A subgroup analysis based on pregnancy status showed no correlation  and showed significant heterogeneity (I2 = 63%) . One out2 = 63%) . In the relation .2 = 71%)  with considerable heterogeneity (I2 = 71%) . Even af2 = 71%) . PFOS wa2 = 71%) .2 = 66%). One outlier study was found using sensitivity analysis [2 = 47%)  . PFOA sh2 = 47%) . There w2 = 47%) .The studies were divided into three groups according to the mean PFOA concentration: < 2 ng/mL (low), 2–3 ng/mL (intermediate), and > 3 ng/mL (high). The subgroup analysis stratified by either the PFOA levels or pregnancy revealed no significant correlation .2 = 30%) (2 = 30%) while there was no significant correlation in pregnant women  . Subgrount women .Whether exposure to PFASs can disrupt thyroid function remains uncertain because previous epidemiological studies have reported conflicting results regarding the relationship. This is the first meta-analysis that provides evidence on the health effects of PFASs as a thyroid disrupting chemical; although a systematic review on the association between PFASs and thyroid function was reported previously , the subOur results suggest that PFOS exposure could increase free T4 levels and decrease total T4 levels. In all the studies included in our analysis, free T4 was measured by the analog method, which is subject to a methodological issue. PFOS can bind to thyroid hormone binding proteins, such as albumin and transthyretin (TTR) competing with thyroid hormone , 48, andAll three studied PFASs were negatively correlated with total T4 in the meta-analysis. There is sufficient evidence showing that PFASs lower total T4. Experimental studies performed in rats and monkeys have reported that PFOS or PFOA treatment lowered the total and/or free T4 concentrations , 54, 55.The effect of PFASs can be different according to the concentration. Therefore, we performed a subgroup analysis. Interestingly, PFOS showed a significant correlation with thyroid hormones in the intermediate concentration group (8–16 ng/mL). It was not a typical linear dose-response relationship. Such nonmonotonic or U-shaped dose response is considered to be one of the characteristics of endocrine-disrupting chemicals , 34.Pregnancy can affect the influence of PFASs on thyroid function. Maternal PFASs can be transferred to fetuses, and the PFAS concentration in cord sera is positively correlated with PFASs in maternal serum . TherefoOur study has limitations. Although we performed subgroup analyses based on the mean PFAS concentration and pregnancy status, there are potential confounding factors such as age and gender. Both PFAS and thyroid hormone levels vary with age and gender , 31. HowBecause people are simultaneously exposed to multiple PFAS chemicals and other endocrine-disrupting chemicals, chemical co-exposures can be a potential confounding factor or have mixture effects. Although there was a study that reported results based on the sum of total PFAS concentrations, most studies evaluated the relationship between single PFAS and thyroid hormones . The effIn conclusion, this meta-analysis suggests a negative correlation between certain PFASs and total T4 levels. Among PFASs, PFOS had the greatest effect on thyroid hormones, especially at intermediate concentrations (8–16 ng/mL).S1 Appendix(DOC)Click here for additional data file.S2 Appendix(DOC)Click here for additional data file.S1 Table(DOC)Click here for additional data file.S2 Table(DOC)Click here for additional data file.


AIRE gene. SNPs thereby provide a less efficient negative selection, propagate higher survival of autoimmune T-cells, and elevate susceptibility to autoimmune diseases. To date, only rheumatoid arthritis (RA) has been analysed by epidemiological investigations in relation to SNPs in AIRE. In our meta-analysis, we sought to encompass case-control studies and confirm that the association between SNP occurrence and RA. After robust searches of Embase, PubMed, Cochrane Library, and Web of Science databases, we found 19 articles that included five independent studies. Out of 11 polymorphisms, two  were common in the five case-control studies. Thus, we performed a meta-analysis for rs2075876 (7145 cases and 8579 controls) and rs760426 (6696 cases and 8164 controls). Our results prove that rs2075876 and rs760426 are significantly associated with an increased risk of RA in allelic, dominant, recessive, codominant heterozygous, and codominant homozygous genetic models. These findings are primarily based on data from Asian populations.Autoimmune regulator (AIRE) is a transcription factor that functions as a novel player in immunological investigations. In the thymus, it has a pivotal role in the negative selection of naive T-cells during central tolerance. Experimental studies have shown that single nucleotide polymorphism (SNP) alters transcription of the  Although the aetiology of RA has not been completely elucidated, numerous publications agree that autoimmune T-cells may escape from the adaptive immune system and, by migrating to the synovium, initiate disease development5. RA susceptibility is determined by multiple environmental and genetic factors, including several risk alleles. The latest trans-ethnic genome wide association study (GWAS), which involved 29,980 RA cases and 73,578 controls, completely screened novel polymorphisms in genes contributing to the disease6. One of the associated genes that seems to play a pivotal role in controlling autoimmunity is autoimmune regulator (AIRE). The gene is located in the 21q22.3 region, is ∼12.5 kb long, and encodes a 545 amino acid protein of 58 kDa by 14 exonial sequences9. The AIRE protein is a transcription factor that is indispensable with regards to the negative selection of immature T-cells (thymocytes). Cooperating with DNA-binding proteins, AIRE controls the promiscuous expression of peripheral tissue antigens (PTA). Mutations in the protein coding gene sequence of AIRE results in the development of autoimmune polyendocrinopathy candidiasis-ectodermal dystrophy, an autoimmune deterioration of numerous organs12.Rheumatoid arthritis (RA) is a common autoimmune disease associated with chronic synovial inflammation. The resultant symmetrical polyarticular arthritis, combined with extra-articular complications, leads to functional impairment. In developed countries, disease prevalence is 0.5–1% of the adult population, and the annual incidence has been reported to be 5–50 per 100,000AIRE transcription. The SNPs thereby alter the functional activity of AIRE and potentially elevate disease susceptibility7. A recent experimental study described two distinct SNPs of AIRE. AIRE−230Y, and AIRE−655G. AIRE−230T haplotype transcriptionally modifies AIRE expression and influence negative selection, elevating the risk of autoimmunity13. Various SNPs in the AIRE genetic sequence have garnered attention; however, to date, only a minority of case-control studies have observed an association between gene polymorphism and susceptibility to diseases, including vitiligo14, alopecia areata15, melanoma16, systemic sclerosis17 and RA22. Among the latter diseases, only RA has been analysed by multiple case-control studies and, therefore, seems to be optimal to analyse positive or negative associations7. Xu et al. have published that AIRE polymorphism was associated with the increased risk of RA23. Here, we present a systematic review and first meta-analysis that includes case-control studies to verify the association of SNPs rs2075876 and rs760426 in the AIRE gene with RA.To date, increasing numbers of publications have suggested that SNPs in the gene sequence affect 24. The overall mean age of RA patients was 54.1 ± 2.4 years, and the percentage of female cases was 73.34%. Genotyping was conducted by microarrays, single base extension methods (SNaPshot), and Taqman SNP Genotyping Assays. By further reviewing the five eligible publications, we identified 11 SNPs of the AIRE gene . Only rs2075876 and rs760426 were involved in four or more studies; therefore, we performed meta-analysis for rs2075876 (7145 cases and 8579 controls) and rs760426 (6696 cases and 8164 controls). All genotype frequencies of the controls were in Hardy-Weinberg Equilibrium (HWE). Characteristics of the included studies on rs2075876 and rs760426 are summarized in Table We identified 19 publications after a thorough search of Embase, PubMed, Cochrane Library, and Web of Science databases. After removing duplicates, we reviewed the remaining 11 studies for eligibility and selected five publications for inclusion in our meta-analysis. Our PRISMA flow chart of the searching process is shown in Fig. 22. Most of the publications doubled the individual number to account for alleles; thus, to normalize the data, we also calculated with duplicated values . With the exception of García-Lozano et al.19, all of the studies described the genotype distribution for GG, AG, AA. Therefore, we calculated odds ratios (ORs) for genetic models where there was no available or feasible data in the given study  and RA susceptibility.Only four out of 31 ORs were statistically insignificant, and the ORs revealed that SNP rs2075876 (G > A) is associated with an elevated risk of RA. These results therefore suggest a link between 22. Most of the publications doubled the individual number; thus, to normalize the data, we also calculated with duplicated values, as was conducted with rs2075876 SNP . With the exception of Feng et al.21, all studies described the genotype distribution for AA, GA, GG. We therefore calculated ORs for all the genetic models that were not published in the original articles , 1.19 , and OR 1.32 . For the recessive model  and RA susceptibility.Only four out of 26 ORs were statistically insignificant, and the ORs showed that rs760426 (A > G) SNP is associated an elevated risk. These results therefore suggest a link between To detect the influence of each case-control study on the whole meta-analysis, we performed sensitivity analysis by omitting one individual study. Heterogeneity was not found in SNP rs2075876 or rs760426 by investigating allelic Fig.  and S4.FBias analysis was performed by generating funnel plots for each polymorphism of the allelic Fig. , dominanWe performed a TSA for the allelic models Fig.  of SNPs 25. The latest GWAS meta-analysis discovered and screened 42 novel RA risk SNPs at a genome level from 98 candidate biological RA risk genes6. The detected risk genes, including AIRE, are mainly in the category of primary immunodeficiency (PID), HIV, and immune dysregulation. With the exception of AIRE, none of the other associated proteins have been directly related to central tolerance6.RA is a multifactorial disorder where genetic and environmental events equally contribute to disease commencementAIRE, decrease the presentation of self-antigens, reduce negative selection, and contribute to the escape and survival of autoimmune T-cells. Reaching the periphery, matured, autoimmune T-cells are a source of autoantibodies and serve as a medium for numerous immune disorders, including RA. In support of this belief, Lovewell et al.13 have concluded, through a gene reporter assay, that specific haplotypes (AIRE−655G AIRE-230T) can dramatically reduce AIRE transcription. However, with in vitro and in vivo experiments, Kont et al.26 have demonstrated that the presentation of PTAs from mTECs is quantitatively affected by these reductions in AIRE expression.Self-tolerance involving negative selection, the machinery of which is directed by AIRE, is a central immuno-physiological process required to create a normal adaptive immune system. We believe that polymorphisms in this indispensable gene lower the protein expression of in silico investigation by Terao et al.18, which analysed the expression profile of 210 lymphoblastoid cells in the Gene Expression Omnibus (GEO) database, has demonstrated a statistically significant (p < 0.001) correlation between the rs2075876 risk allele (A) and decreased AIRE transcription27. No association was found in GEO between rs760426 (G) and AIRE expression. Additionally, García-Lozano et al.19 found statistically significant decreases in the expression levels of rs878081 C allele by analysing GEO database. This SNP is located in the Exon 5 region of AIRE; however, rs2075876 (G > A) is located in Intron 5 and rs760426 (A > G) in Intron 127. The latter SNPs may affect the transcription of AIRE by modifying alternative splicing or intron-mediated enhancement28. The reduction in transcription, in turn, provides lower amounts of PTAs ectopically on the major histocompatibility complex/human leukocyte antigen of mTECs, which thereby contributes to the failure of negative selection in the thymus and increases the survival of autoimmune T-cells. In individuals who carry these SNPs, this sequence increases RA susceptibility. By analysing allelic, dominant, recessive, codominant heterozygous, and codominant homozygous models, we demonstrated that the SNPs rs2075876 (G > A) and rs760426 (A > G) occur more frequently in RA patients than in controls.An et al.19, the results are not statistically significant; however, rs878081 C allele seemed to occur more frequently in RA patients. Furthermore, considering GWAS of Terao et al.18, the association of AIRE with RA among Caucasians was not supported. The number of the included studies also limited our meta-analysis; however, Terao et al.18 provided three case-control studies in one publication, which elevated the number of the included epidemiological studies. In the future, further European case-control, GWAS, and stratified subgroup analyses  are needed in order to better elucidate the association between RA and AIRE polymorphism.There are some limitations in our meta-analysis. We cannot extrapolate the findings of rs2075876 (G > A) and rs760426 (A > G) to Caucasians due to the limited study number. Based on García-Lozano To our knowledge, this is the first time that the association between SNP rs2075876 (G > A), rs760426 (A > G), and RA susceptibility was statistically estimated in one meta-analysis. We used multiple haplotype investigations for each polymorphism, sensitivity analyses, and TSA to confirm the robustness of association. In conclusion, our meta-analysis clearly confirmed with each genetic model that the presence of SNPs rs2075876 (G > A) and rs760426 (A > G) is significantly associated with an increased risk for RA.29. On 16th May 2017 we completed the search. Keywords  were thoroughly used by two independent investigators. All studies were published from April 2011 to June 2016.We searched for related literature in the PubMed, Embase, Cochrane Library, and Web of Science databases in accordance with the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statementAIRE gene and RA susceptibility, (2) the study was case-control-designed, (3) all RA patients met the American College of Rheumatology classification and diagnostic criteria, and (4) detailed genotype data and feasible ORs, 95% CIs, and p-values were available. Publications were excluded if (1) a previous study was duplicated or (2) the given polymorphism was not found in at least four studies. Review articles were also excluded. Inclusion and exclusion criteria were independently screened by two investigators.In order for studies to be included, publications had to demonstrate that (1) the study focused on the association between SNPs or haplotypes within the 30 because of the different ethnicities of those included. Heterogeneity between trials was tested with two methods. First, we employed the Cochrane’s Q homogeneity test, which exceeds the upper-tail critical value of chi-square on k–1 degrees of freedom, with a p-value of less than 0.10 considered suggestive of significant heterogeneity. Second, we used the inconsistency (I2) index. I2 is the proportion of total variation contributed by between-study variability. I2 values of 25, 50 and 75% correspond to low, moderate, and high degrees of heterogeneity, respectively, based on Cochran’s handbook31. Sensitivity analyses were performed to identify the influence of each study on the pooled ORs and 95% CIs. Publication bias was examined by visual inspection of funnel plots where the standard error was plotted against the log odds ratio. Meta-analytic calculations were performed with Comprehensive MetaAnalysis software Version 3 .HWE was calculated by the chi-squared test for each study in the control groups. Pooled ORs and 95% CIs were calculated to examine the strength of the association between rs2075876 and rs760426 polymorphisms and RA. We used the random effect model by DerSimonian and Laird34. TSA combines an estimation of the required sample size with an adjusted threshold for statistical significance. The relationship between the cumulative z-curve and the trial sequential monitoring boundary shows the expressiveness of the meta-analysis. If the cumulative z-curve crosses the trial sequential monitoring boundary, and the cumulative sample size of the meta-analysis reaches the required sample size, firm evidence can be observed. When the cumulative z-curve crosses the boundaries, but the sample size does not reach the required information size, a sufficient level of evidence for the anticipated intervention effect may have been reached and no further trials are needed. If the z-curve does not cross any of the boundaries and the required sample size has not been reached, evidence to reach a conclusion is insufficient35. For calculation of the information size, we used a heterogeneity adjusted assumption with 10% of relative risk reduction, 5% of overall Type-I-Error, and 10% of Type-II-Error for the case of both gene alleles. The adjusted CIs for rs2075876 and rs760426 are 1.13–1.31 and 1.11–1.26, respectively. For calculations we used the Trial Sequential Analysis software tool from Copenhagen Trial Unit, Center for Clinical Intervention Research, Denmark .Meta-analyses may be biased in type I errors owing to an increased risk of random error when sparse data are analysed, combined with reduplicative testing on accumulating data. To avoid this problem and to increase the robustness of conclusions, we used trial sequential analysis (TSA)All data generated or analysed during this study are included in this published article and its Supplementary information file.Dataset 1