MTHFR 677C>T polymorphism on susceptibility to ovarian and cervical cancers in women, but the conclusions are still controversial. To get a more precise evaluation of the association between MTHFR 677C>T polymorphism and risk of ovarian and cervical cancers, we performed a meta-analysis of the association of all eligible studies. Previous studies have evaluated the impact of A comprehensive search performed in PubMed, Google Scholar, CNKI, and Web of Science databases to identify the relevant studies up to October 15, 2018. The strength of the association was estimated by odds ratios (OR) with 95% confidence interval (CI). MTHFR 677C>T polymorphism not significantly associated with an increased risk of ovarian and cervical cancers under all five genetic models. However, stratified analysis by ethnicity showed that the MTHFR 677C>T polymorphism was significantly associated with risk of ovarian cancer in Asians. No publication bias was found in the current meta-analysis. A total of 27 case-control studies including eleven studies with 4990 cases 7730 controls on ovarian cancer and 16 studies with 4990 cases and 7730 controls on cervical cancer were selected. Pooled data revealed that the MTHFR 677C>T polymorphism may not play a role in development of ovarian and cervical cancers in overall population. Further well-designed studies are necessary to clarify the precise role of the MTHFR 677C>T polymorphism on ovarian and cervical cancers risk.The results of this meta-analysis proposes that the  Gynecological cancers are among the most common cancers in women and hence a major health problem worldwide . Ovarian and cervical cancers are the most common gynecological cancers affecting women worldwide . Ovarian cancer is the second most common cancer and main cause of death with gynecological tumors worldwide . Moreover, cervical cancer is the third most frequent neoplasm among women worldwide . In 2017, a study showed that ovarian cancer (47%) followed by cervical cancer (29%) are the most common gynecological malignancy among Pakistan women . Despite continuous advances in cancer biology research, the etiology of ovarian and cervical cancer are not known exactly, partly because of the inconsistency of findings among epidemiological studies . A reappraisal of Genome-wide association studies (GWAS) and genetic association studies suggested a strong genetic component to susceptibility to ovarian and cervical cancers .MTHFR 677C>T (in exon 4) polymorphism has been heavily studied in different disease. The MTHFR 677C>T is associated with reduced enzyme activity and arise an elevated plasma homocysteine level. Moreover, the MTHFR 677C>T polymorphism leads to increased heat liability and reduced enzymatic capability for methylation of Homocysteine . The mutant homozygous genotype (TT) of MTHFR 677C>T polymorphism was particularly common in northern China (20%), southern Italy (26%), and Mexico (32%) .Epidemiological studies had identified that Methylene tetrahydrofolate reductase (MTHFR) was a potential genetic marker of different malignancies . The human MTHFR gene is located on chromosome 1p36.3, consist of 11 exons and spans 2.2 kb of genomic DNA . It is encodes the vital enzyme which plays a key role in the folate/homocysteine metabolic pathway and regulates the intracellular folate level for the synthesis and methylation of DNA . In humans, the MTHFR 677C>T polymorphism and susceptibility to ovarian and cervical cancer . However, the results were conflicting and inconclusive, presumably due to small sample size in each published study, various genetic backgrounds and possible selection bias . Subsequently, a few novel studies have recently been performed to estimate the associations of MTHFR 677C>T polymorphism with risk of ovarian and cervical cancer and provide new evidences that were not included in the previous meta-analyses. Thus, this meta-analysis covering all potentially eligible studies was performed to get a more precise evaluation of the association between MTHFR 677C>T polymorphism and risk of ovarian and cervical cancers.Over the past decades, a large number of epidemiological studies and meta-analyses have evaluated the association between the Literature Search StrategyMTHFR 677C>T polymorphism with risk of ovarian and cervical cancers up to October 15, 2018. The following keywords and terms were used:  AND (‘’Methylene tetrahydrofolate reductase’’ OR ‘’MTHFR’’ OR ‘’677C>T’’ OR ‘’rs1801133’’) AND (“Polymorphism” OR ‘’SNP’’ OR ‘’Mutation’’ OR “Variant” OR “Variation”). Moreover, the references of the retrieved articles manually checked for other potential studies that possibly have been missed in the initial search.A comprehensive searched in PubMed, Google scholar, Web of Science, EMBASE, Chinese Biomedical database, and China National Knowledge Infrastructure (CNKI) databases was performed to obtain the all relevant studies investigated association of Inclusion Criteria and Data ExtractionMTHFR 677C>T polymorphism with ovarian cancer and cervical cancer; and d) the number of MTHFR 677C>T polymorphism genotypes in the cases and healthy control was reported to estimates odds ratio (OR) and 95% confidence interval (CI). The exclusion criteria were: a) abstracts, case reports, reviews, previous meta-analyses, posters, letters to editor and commentaries; b) animal studies; c) case only studies; d) linkage or sibling studies; e) studies did not calculated MTHFR polymorphisms genotype frequencies or which the number of genotypes and alleles could not be ascertained; f) studies on other polymorphisms of MTHFR gene; and g) overlapping studies and studies duplicate or containing previously published data. Moreover, if studies had overlapping data, only the study with the largest population or more recently published data was finally selected.Studies were included in the current meta-analysis only if they met all of the following criteria: a) studies with case-control or cohort design; b) only published studies; c) evaluated the association of Data ExtractionTwo authors (H.A and A.H) independently assessed the articles for their eligibility for inclusion and the needed data were carefully extracted based on the inclusion criteria above using a standard form. Any disagreements were solved by discussion with a third author (E.S). The following data were extracted for each study: first author’s name, publication year, country, ethnicity, source of control , genotyping methods, and the number of alleles and genotypes in the cases and controls, minor allele frequency (MAF) among controls, and P-value for Hardy-Weinberg equilibrium (HWE).Statistical AnalysisMTHFR 677C>T polymorphism and ovarian and cervical cancers was assessed by using odds ratios (ORs) and 95% confidence intervals (CIs). The P-value of the pooled ORs was considered significant if less than 0.05, which was examined by Z-test. The pooled ORs were calculated under all five genetic models, i.e., allele (T vs. C), homozygote (TT vs. CC), heterozygote (TC vs. CC), dominant (TT+TC vs. CC), and recessive (TT vs. TC+CC), in which the ‘’C’’ represents the major allele and the ‘’T’’ represents the minor allele. The Cochran’s Q-test was used to access the between-study heterogeneity. Moreover, the effects of heterogeneity was we quantified using I2 statistic (ranges from 0 to 100%), in which detected variations among studies due to heterogeneity rather than chance  . A chi-square test was used to determine Hardy-Weinberg equilibrium (HWE) in controls, which p-value less than 0.05 was representative of statistical significance. Subgroup analyses were performed to explore possible sources of heterogeneity by ethnicity, source of controls, genotyping method and HWE status. Sensitivity analyses were performed by sequential removal of each study and by excluding those studies deviation from HWE to test the stability and reliability of the results. Visual inspection of asymmetry in funnel plots and Begg’s rank correlation statistically were used to test whether publication bias existed or not, in which P<0.05 was considered to be represented of statistically significant. All statistical analyses were performed using the Comprehensive Meta-Analysis (CMA) software version 2.0 . Two-sided P<0.05 was considered statistically significant.The strength of association between Characteristics of StudiesMTHFR 677C>T polymorphism , homozygote ; heterozygote , homozygote ; heterozygote , dominant , and recessive , but not in Caucasians , homozygote ; heterozygote , dominant  for cervical cancer. However, excluding the study did not significantly affect the pooled ORs for cervical cancer, indicating the robustness and reliability of this meta-analysis.Publication BiasMTHFR 677C>T polymorphism with ovarian and cervical cancer risk in all genetic models. No asymmetry was observed in the Begg’s rank correlation among the studies on ovarian and cervical cancer. MTHFR 677C>T polymorphism and risk of cervical cancer in recessive model (TT vs. TC+CC). Moreover, the Egger’s linear regression test did not show any statistical evidence of publication bias among the studies on ovarian and cervical cancer . Thus, the current meta-analysis was performed to evaluate the association of MTHFR 677C>T polymorphism with susceptibility to ovarian and cervical cancers in women. Finally, 27 case-control studies including eleven studies on ovarian cancer and 16 studies on cervical cancer were selected. Therefore, the current meta-analysis was the largest scale study so far on MTHFR 677C>T polymorphism association with ovarian and cervical cancers. This meta-analysis pooled data revealed that the MTHFR 677C>T polymorphism was not associated with an increased risk of ovarian and cervical cancers in overall population. The negative results in this pooled analysis agrees with the previous meta-analysis on cervical cancer . However, He and Shen (2017) in meta-analysis of eight studies found that the MTHFR 677C>T polymorphism was associated with ovarian cancer risk. The main strength of this meta-analysis in comparison with the previous meta-analyses was the total number of cases and healthy controls selected. Therefore, this meta-analysis more power to detect the small effects of the polymorphism than previous studies. However, we recommend increasing the sample size in future studies in order to increase the power to detect small effects of the MTHFR 677C>T polymorphism on risk of ovarian and cervical cancers.MTHFR is an important enzyme which has an important role in the regulation of methionine and homocysteine levels in folate metabolism. The MTHFR 677C>T polymorphism was significantly associated with ovarian cancer in Asians, but not in Caucasians. Similarly, He and Shen (2017) showed that the MTHFR 677C>T polymorphism is a risk factor for ovarian cancer and also breast cancer in Asians. It seems that due to the some genetic and environmental differences between Asian and Caucasian populations, the MTHFR 677C>T polymorphism might play a different role in the development of ovarian cancer in the two populations. However, the subgroup analysis did not show a significant association between MTHFR 677C>T polymorphism and cervical cancer by ethnicity. However, the previous meta-analysis revealed that MTHFR 677C>T polymorphism was significantly associated with cervical cancer in Asians .When stratified analysis by ethnicity was performed the results showed that the Between-study heterogeneity refers to the variation in study results between different studies, which could affects pooled results of a meta-analysis  and a significant problem when interpreting of a meta-analysis . Several factors such as sample size, ethnicity, source of controls, genotyping methods, participants demographic and lifestyle might lead to the heterogeneity among studies . Thus, to explore the potential sources of heterogeneity among studies, we conducted subgroup analyses by ethnicity, cancer, source of control, HWE and genotyping methods. However, the subgroup analysis results showed that only ethnicity was the main source of heterogeneity in this meta-analysis.MTHFR 677C>T polymorphism with susceptibility to ovarian and cervical cancer. However, there were some limitations in our meta-analysis which must be described. First, we have only focused those published studies in English and Chinese in the current meta-analysis. Second, in the current meta-analysis the number of studies and the sample size in the studies by other ethnicities such as Africans, Latinos and mixed populations were small. Therefore, the lack of power due to the small number of studies leaves it an open field by ethnicity. Third, our meta-analysis was not adjusted by the potential confounders, such as age, gender and lifestyle, because not all of the studies reported adjusted ORs potential confounders. Finally, the potential effect of MTHFR 677C>T polymorphism might be affected by gene-gene and gene-environment interactions. However, due to the lack of original data limited further evaluation of potential gene-gene and gene-environment interactions and also interactions of other polymorphisms of MTHFR gene.To the best knowledge, this meta-analysis was the most comprehensive and convicting on the association of the MTHFR 677C>T polymorphism was not associated with an increased risk to ovarian and cervical cancer in overall population. However, MTHFR 677C>T polymorphism was significantly associated with ovarian cancer in Asians, but not in Caucasians. Moreover, considering the limitations of the study, large well-designed studies from different ethnicities should be conducted to provide a better understanding of the association of MTHFR 677C>T polymorphism with risk of ovarian and cervical cancer.In summary, this meta-analysis demonstrated that the


The relationship between dietary protein consumption and the risk of type 2 diabetes (T2D) has been inconsistent. The aim of this meta-analysis was to explore the relations between dietary protein consumption and the risk of T2D. We conducted systematic retrieval of prospective studies in PubMed, Embase, and Web of Science. Summary relative risks were compiled with a fixed effects model or a random effects model, and a restricted cubic spline regression model and generalized least squares analysis were used to evaluate the diet–T2D incidence relationship. T2D risk increased with increasing consumption of total protein and animal protein, red meat, processed meat, milk, and eggs, respectively, while plant protein and yogurt had an inverse relationship. A non-linear association with the risk for T2D was found for the consumption of plant protein, processed meat, milk, yogurt, and soy. This meta-analysis suggests that substitution of plant protein and yogurt for animal protein, especially red meat and processed meat, can reduce the risk for T2D. Diabetes mellitus is considered a serious public health issue worldwide with the vast majority of patients having type 2 diabetes (T2D). According to the International Diabetes Federation, T2D is expected to grow by 54.5 percent from 2013 levels by 2035 [Dietary factors are major behavioral factors that can influence the risk for T2D to a great extent . One stuThere are a growing number of studies investigating the potential link between protein intake and diabetes, and the conclusions are not consistent. The relationship between protein consumption and high-protein food intake with T2D risk has not been systematically evaluated. To address this question, we performed a meta-analysis of prospective studies to quantify this relationship and identify optimal food types for a low T2D risk.We identified cohort studies that looked at the relationship between dietary protein intake and T2D by searching the databases of PubMed, Embase, and Web of Science as of 5 March 2019. The full search strategy is presented in All included studies matched the following criteria: the study must have a cohort design; the study outcomes include type 2 diabetes; the study had to report relative ratio (RR), odds ratio (OR), or hazard ratio (HR); the independent variables for the study included protein intake; and all studies had a quality score as assessed by the Newcastle Ottawa Scale (NOS) of cohort studies of at least 6.Two authors independently extracted the following information from each publication: the first author, publication year, geographic location, study name, cohort size, the years of follow-up, gender, baseline age of study subjects, diagnosis and assessment of T2D, dietary assessment methods, type of dietary protein, number of participants and T2D cases, dietary protein consumption per category and the RR/OR/HR and 95% CI of T2D incidence related to those categories, number of T2D cases and total subjects per category, and covariates of a fully adjusted model included in the analyses. The dispute was resolved by discussion between the two authors.Two reviewers independently performed the quality assessment by using the NOS (for cohort and case-control studies) with a full score of 9 stars .If the category of dietary protein intake had an open interval, we assumed that the width of the interval is the same as the adjacent category . For cohp value for non-linearity was calculated by testing whether the coefficient of the second spline was equal to zero [We initially pooled RRs and the corresponding 95% CIs from the highest compared with the lowest category of dietary protein intake in each study by the fixed-effect or random-effect model . To capt to zero . Subgrou2 statistic  [p value was used with a level of 0.05. All data analyses were performed by using Stata 12.1 .Heterogeneity among studies was assessed using the Q test and Iy exist) . We assey exist) . A two-sA flowchart  shows th2 = 0.0%)  and there was no heterogeneity in stratified analyses (p = 0.084)  . The posanalyses .There wa= 0.084) .2 = 42.7%)  and we detected evidence of heterogeneity in analysis of gender, countries, and number of cases  . The resof cases . There wof cases .2 = 41.7%)  and there was no evidence of heterogeneity between subgroups  . A consiubgroups . In non-ubgroups .2 = 76.0%, n = 16 studies)  . The pos studies ,31,32,332 = 85.6%)  . The sim studies ,36,37,382 = 61.9%)  . A borde studies ,45,46,472 = 0.0%)  . A sligh studies ,32,33,482 = 5.3%)  . Compari studies ,55,56,572 = 48.9%)  . A signi studies ,56,58,592 = 85.2%, n = 19 studies)  . A simil studies ,63,64,652 = 70.8%)  . A signi studies ,72,73,742 = 1.9%, n = 15 studies [Twelve studies were included in the dose-response meta-analysis and no association was observed for each daily 30g of cheese consumption  . A borde studies ,56,58,59The results varied little by methodological assumption, including only those with a low risk of bias .In this meta-analysis, no publication bias was found by Begg-Mazumdar’s test and Egger’s test , except A comprehensive meta-analysis of 72 studies demonstrated that consumption of total and animal protein was positively associated with the risk for T2D and intake of plant protein was inversely related to the risk of T2D. In the linear dose-response meta-analysis of nine food groups and their relationship to T2D incidence, the intake of red meat, processed meat, milk, and eggs, the relationship was positive with T2D incidence; only the association between yogurt consumption and T2D yielded an inverse relationship. Some evidence of non-linearity between the consumption of plant protein, processed meat, milk, yogurt, and soy with the risk of T2D was found.There is consistent evidence that total and animal protein increases the risk of T2D, and a beneficial effects of plant protein consumption on diabetes is in line with a previous meta-analysis ,75,76. AAlthough excessive consumption of total animal protein is likely to augment the risk of T2D, not all foods containing high animal protein are equal. A positive association was found for meat intake  and egg consumption. On the contrary, white meat and dairy products may be beneficial for T2D prevention. Thus, the complex effect of animal protein on diabetes is remains to be established.The results for red and processed meat were aligned with an updated meta-analysis which showed a 19% and 51% higher risk of T2D for 100 g red meat/day and 50 g processed meat/day, respectively . A studyAlthough no association was detected in the meta-analysis of fish consumption and risk of T2D, stratification analysis showed that fish consumption was associated with a lower risk of T2D in Asian studies but not in Europe. It has been reported that fish consumption is negatively associated with the risk of T2D in China , while aIn this study, intake of yogurt was inversely with the risk of T2D at any daily intake. The risk of T2D was reduced by 17% when the consumption of yogurt was up to 60 g/day. The study was reinforced by a previous review that suggested dairy products, especially fermented yogurt, may reduce the risk of T2D by reducing the risk of obesity, one of the main causes of T2D . The favN-oxide from egg yolks which might be a driver for the positive association between eggs and T2D [This study suggests a slight detrimental effect of egg consumption for the risk of T2D, which was supported by the American Heart Association (AHA) dietary guidelines that egg intake should be limited to prevent cardiovascular disease . Some ev and T2D . Contrad and T2D . Moreove and T2D .ThereforFor high protein plant-based foods, no association was detected for soy consumption and the risk of T2D in all subjects. However, it was found that soy consumption could reduce the risk of T2D in Asians but not in Europeans and Americans. And, a study from Thailand, an Asian country, and a cross-sectional study from China both observed that traditional fermented soy intake had a slight protective effect on glucose ,96. SuchA comprehensive comparison of dietary guidelines around the world shows that different countries have similar dietary recommendations for some daily food, such as strict limits on the consumption of processed meat, whether among healthy people or patients with chronic diseases. Our meta-analysis provides further scientific evidence to support the inclusion of some food groups in the food-based dietary guidelines and to understand their potential role in the risk for T2D. Based on our study, the optimal consumption of yogurt and milk is associated with 24% lower risk, whereas avoidance of foods associated with a higher risk is associated with 69% lower incidence of T2D. Establishing a proper amount of total protein intake, strictly limiting the intake of animal protein, especially for processed meat and red meat, and maintaining adequate intake of yogurt and plant protein, can produce a host of beneficial effects to reduce the risk of T2D in a convenient and cost-effective way.Foremost in the strengths of this meta-analysis is the large number and high quality of included prospective studies and a complete and detailed description of dietary protein consumption. Another strength is the variety of types of analyses including a high vs. low meta-analysis, linear dose–response analysis, and non-linear dose-response analysis. Third, we effectively avoided recall bias because the studies we included were cohort studies.Some limitations also exist in this meta-analysis. First, some studies did not adjust for important factors that influence T2D such as family history of diabetes and physical activities, which could compromise results. Second, among the included studies, the follow-up time span was large, so a temporal bias may affect the relationship between dietary protein consumption and T2D risk. Third, some food groups showed heterogeneity with respect to the analyzed age, sex, follow-up length, geographic location, and number of cases.Among the investigated protein and high-protein foods, selecting specific optimal intakes  can lead to a significant decrease in risk for T2D.


Cytomegalovirus (CMV) infection is one of the most common infectious diseases in pregnant women in terms of global impact and is related with many adverse health consequences during pregnancy. For the first time, we performed a systematic review and meta-analysis study to evaluate the possible association between CMV infection and preeclampsia (PE).to identify the relevant papers published earlier than February 2018 was performed in PubMed, ISI (Web of Science), Google Scholar and SCOPUS databases. We followed the PRISMA  guidelines for design, analysis and interpretation of results. Pooled odds ratio (OR) and 95% confidence intervals (CI) were estimated using a random-effects meta-analysis model. Heterogeneity was assessed with Q-test and I2 statistics.A comprehensive literature search 2=57.3%), IgG-ELISA  and IgM-ELISA  demonstrated that CMV infection could not be a potential risk factor for PE. A total of 13 studies including 6158 pregnant women  met the eligibility criteria. The results of meta-analyses based on PCR (OR: 3.09; 95% CI:0.72–13.24; I In conclusion, results of the present study demonstrated that CMV infection could not be a potential risk for developing PE. More epidemiological and experimental studies are needed to investigate the impact of CMV infection on the development of PE. It gener (PlGF) , 5. Furtr (PlGF) , 7. In tr (PlGF) . CytomegCMV is responsible for a broad range of disabilities in newborns, such as visual impairment, sensorineural hearing loss, and motor and cognitive deficits. In pregnant women, clinical symptoms of CMV infection is generally nonspecific and resemble a mononucleosis- or flu-like syndrome, with fever, sore throat, cervical lymphadenopathy, myalgia, and fatigue , 11. Moreover, it is demonstrated that CMV infection is a potential risk factor for the development of hypertension and cardiovascular disease . In the Study design: For this meta-analysis study, we followed the PRISMA  guidelines for design, analysis and interpretation of results. The exposure for our study was serological or molecular evidence of CMV infection and the main outcome of interest was developing PE in infected women and compared with healthy controls. To prevent common biases during the literature research, language, geographical area or date restrictions were not applied. All observational  studies that evaluated the CMV infection status among women with PE and healthy controls were included in the present meta- analysis. PE is defined as a systolic blood pressure ≥ 140 mm by the American College of Obstetricians and Gynecologists (ACOG) criteria  and CMV Search strategy and study selection: A comprehensive literature search for identifying the relevant papers published earlier than February 2018 was performed in PubMed, ISI (Web of Science), Google Scholar and SCOPUS databases. Our search was done by using the combination of the following keywords: “Cytomegalovirus”, “Cytomegalovirus infection”, “CMV”, “preeclampsia”, “eclampsia”, “gestosis”, “pregnancy hypertension” and “gestational hypertension”, with the Boolean operators “OR” and/or “AND”. Finally, our search was complemented by reviewing the reference lists of the electronically retrieved full-text papers and related reviews. Our search strategy is schematically presented in the PRISMA flow diagram  independently assessed the full text of eligible studies and information was extracted using Microsoft Excel software. The following information was extracted for each study: first author, publication year, country, study design, sample size, diagnostic method. In case-control studies, matching criteria, number of cases and controls and of infected subjects in each group were extracted. Any uncertainties were resolved by joint review of the manuscript and consultation with third researcher (M.N.S) to reach consensus. Newcastle-Ottawa scale was used for quality assessment of the included studies, as it was used in our previously meta-analysis studies , 8. ThisData synthesis and statistical analysis: In this study, meta-analysis was performed using Stata Version 12 . The association between CMV infection and PE was assessed through generating the pooled odds ratio (OR) and 95% confidence intervals (CI) using a random effects model. I2 methods were utilized. Stratified analysis was subsequently performed regarding the type of antibodies and methods . Publication bias was assessed through Egger’s publication bias method for asymmetry. In studies where adjusted ORs were presented, they were used in preference to crude odds ratio. To assess heterogeneity amongst the studies, Q-test and -value of less than 0.1 was considered statistically significant. Results are presented as forest plots and the association between CMV infection and PE is illustrated by an OR and 95% CI.A pStudy characteristics: As shown in PRISMA flowchart , 58.8 (1123/1909), and 3.5% (89/2490), respectively. While, the prevalence of CMV infection in healthy controls based on PCR, IgG and IgM were 21.5% (14/65), 62.1% (1595/2566), and 3.5% (74/2099), respectively.Results of meta-analysis: At first, we performed meta-analysis regarding the three different methods  used in the included studies for the detection of CMV infection between cases and controls. The results of meta-analysis based on PCR , IgG-ELISA  and IgM-ELISA  demonstrated that CMV infection could not be the potential risk factor for PE (r for PE . 2=54.7%), whereas this relationship was not significant in nested case-control studies   . Egger’sI2=0.0%) .The results of this study demonstrated that women with PE have higher rate of CMV infection compared to healthy controls, although the statistically significant relationship was not observed. Specially we have found higher odds in studies that used PCR to detect CMV infection (OR=3.09), although the number of studies was very low (two studies). We guess if more molecular studies were available, it was possible that significant correlation would be found. Higher odds found in PCR studies could be due to higher sensitivity and specificity of PCR-based methods compared to serological methods.Although it should be more investigated, since several potential mechanisms could be involved in the association between CMV infection and the development of PE. Endothelial-platelet dysfunction and acute atherosis in arterial wall resulting from CMV infection can lead to uteroplacental ischemia, a key pathogenic condition to the development of PE , 29. FurSeveral studies have demonstrated that the shift of immunological cytokine profile of Th2 toward Th1 and high levels of pro-inflammatory cytokines have important role in the onset of PE , 34. MorIn addition, it is demonstrated that CMV infection can modify adhesion molecules such as VCAM-1 (vascular cell adhesion molecule-1) and ICAM-1 (intercellular adhesion molecule-1) and E-selectin which is related with the increase of matrix metalloproteinase (MMP-2) activity and fms-like tyrosine kinase-1 (sFlt-1), that can cause alteration in vessel remodeling, infiltration of inflammatory cells and the development of PE , 26.Helicobacter pylori and the developing of PE  are needed to investigate the impact of CMV infection or its eradication on the risk of developing PE. Besides, more experimental studies should be done to identify the exact involved pathways. The GRADE for this study is this fact that further researches are very likely to have an important impact on our estimated effect and is likely to change the estimate.


Epidemiological studies have found that high whole grain intake may be associated with a reduced risk of breast cancer. However, the evidence has not been consistent. We conducted a meta-analysis to quantitatively assess the association between whole grain intake and breast cancer risk.Relevant observational studies were identified by searching PubMed, Embase, Cochrane library databases, and Google Scholar through April 2017. Summary relative risk (RR) estimates were calculated using random-effects meta-analysis.p = 0.009; I2 = 63.8%, pfor heterogeneity = 0.002). Subgroup analysis by study design found a significant inverse association in the case-control studies , but not in the cohort studies . In addition, stratified analysis suggested that sample size could be a potential source of heterogeneity.A total of 11 studies, including 4 cohort and 7 case-control studies and involving 131,151 participants and 11,589 breast cancer cases, were included in the current meta-analysis. The pooled RR of breast cancer for those with high versus low whole grain intake was 0.84  contains supplementary material, which is available to authorized users. Breast cancer is the most commonly diagnosed cancer among women worldwide. The incidence rate has been rising increasing over the past several decades . On aggrGrains are one of the major staple foods consumed globally and provide 56% of the energy and 50% of the protein intake . They maThe association between whole grain consumption and breast cancer risk has been investigated in previous epidemiological studies. Some have found a possible inverse association –21, wherWe followed the guidelines of the Meta-analysis of Observation Studies in Epidemiology group (MOOSE) , and theStudies were eligible if they met the following inclusion criteria: 1) a case-control or cohort study; 2) assessed the association between whole grain intake and the risk of breast cancer; 3) breast cancer cases were diagnosed and verified by pathological biopsies or other standard methods, with controls being females without breast cancer; 4) reported relative risks (RRs) or odds ratios (ORs) and the corresponding 95% confidence intervals (CIs) for the highest versus the lowest levels of whole grain intake.Two reviewers independently screened the titles and abstracts of the searched papers and excluded the articles which did not meet the above-described inclusion criteria. For those which were difficult to determine the eligibility based on title and abstract review, the full-texts were obtained and reviewed. All disagreements were resolved by discussion to reach a consensus.n = 3); [n = 14); [n = 4) [The search strategy identified 479 potentially relevant articles from the various databases, and 94 records were excluded because they were duplicates Fig. . After tn = 3); , 12, 28 n = 14); –42 or 3) [n = 4) –45. ElevTwo reviewers independently extracted data on study characteristics and results by using a standard data collection form. Data extracted included: first author’s last name; year of publication; country of origin; study design; sample size; mean age of study population; dietary assessment methods; types of whole grain; RRs, including hazard ratios (HRs), ORs or incidence density ratios (IDRs), with the corresponding 95% CIs; and adjusted variables.We also systematically assessed the study quality. Briefly, a 9-score system on the basis of the Newcastle Ottawa Scale (NOS) was used to assess the quality of included studies. Each study was evaluated on three broad criteria: 1) the proper selection of study population, 2) the comparability of the study groups, and 3) the ascertainment of the exposure or outcome of interest. Two reviewers independently assessed the quality of each study. Studies scored greater or equal to7 (out of a maximum 9 points) were considered to be high quality studies. Any discrepancies in data extraction and quality assessment between the reviewers were resolved by consensus.p value < 0.10 considered as statistically significant. We also calculated the I2 statistic, which describes the proportion of total variation across studies which was attributable to heterogeneity rather than chance alone; an I2 value greater than 50% indicated at least moderate heterogeneity [RR was used as a common measure of the association between whole grain intake and the risk of breast cancer. HRs, ORs, or IDRs were considered as estimates of RR. To calculate summary RR and its 95% CI, we pooled the results by using the random-effects meta-analysis . The ranogeneity . Dose rep < 0.10 level of significance [p value < 0.05 was considered statistically significant, except those specified otherwise.Potential publication bias was evaluated by visual inspection of the Begg funnel plots in which the log RRs were plotted against their standard errors (SEs). We also performed the Begg rank correlation test and Egger linear regression test at the ificance , 50. AllThe 11 included studies were published between 1987 and 2016, among which four were cohort studies , 23 and According to the NOS criteria, the quality scores of the included studies ranged from 6 to 9 Tables  and 4. Np = 0.009), with significant heterogeneity .The RRs of breast cancer risk comparing the highest versus the lowest levels of whole grain intake varied from 0.42 to 1.21 across the studies  and the high intake level of whole grains . No significant heterogeneity was observed for the intermediate intake level , whereas significant heterogeneity was found for the high intake level    Fig. . Six stup = 0.001; I2 = 58.2%, pfor heterogeneity = 0.026), but no association in the four cohort studies .In addition, a significant association was observed in studies with sample size ≤2300 , those with the number of adjusted variables ≤7 , studies published before 2008 , or studies with quality score ≤ 7 . To explore whether these associations were statistically different between the subgroups, we further performed meta-regression analyses and found the association was statistically different between the subgroups of sample size (p < 0.05) but was not significant between other subgroups .Although the funnel plot was slightly asymmetric, after using the trim-and-fill method, visual inspection of the Begg funnel plot did not identify substantial asymmetry . However, the stratified analyses by sample size found that heterogeneity was no longer significant in the two subgroups , suggesting that sample size might be a potential source of heterogeneity. In addition, the association was only significant in case-control studies, in studies with sample size≤2300, published before 2008, or studies with the number of adjusted covariates ≤7 or quality score ≤ 7, but not significant in cohort studies, in studies with sample size> 2300, published after 2008, or studies with the number of adjusted covariates > 7 or with quality score > 7. Approximately two thirds of the studies were case-control studies with inadequate adjustment of potential confounders and comparatively low quality. Given that the possible recall bias and selection bias in case-control studies, and the limited number of only four cohort studies, more large-scale prospective cohort studies with full adjustment for potential confounding factors are urgently needed to confirm the inverse association observed in the current meta-analysis.Heterogeneity poses an important challenge in conducting and interpreting the results of meta-analyses . Variousn = 6) in the subgroup analysis by quality score. Third, the intake levels of whole grain were reported in six included studies. However, a dose-response meta-analysis could not be conducted due to incomplete data and the inconsistencies in the measurement units of whole grain intake and different assessment methods. We did perform a meta-regression analysis to explore the association between dose of whole grain intake and breast cancer risk and found an inverse association. In addition, differences in the definitions of whole grain and in the categories of whole grain foods among studies might also be another possible source of heterogeneity. Fourth, the 95%CI was not reported in one study [Our meta-analysis has several limitations. First, it included seven case-control studies and four cohort studies. As indicated above, case-control studies are likely susceptible to recall and selection bias. Second, the quality of the included studies was moderate and the inverse association was only observed in low quality studies Additional file 2:Figure S1. Meta regression analysis of the association between the publication year , the sample size , the number of adjustment covariates , and the study quality score  and the risk of breast cancer. (TIF 62 kb)Additional file 3:Figure S2. Sensitivity analyses of the association between whole grain intake and the risk of breast cancer with one study omitted at a time. (TIF 7 kb)Additional file 4:Figure S3. Publication bias assessed by funnel plot of the association between whole grain intake and the risk of breast cancer in the meta-analysis. (TIF 10 kb)


I2 = 75.3%), with stronger association and less heterogeneity among women  than among men . Our dose-response analysis revealed that for each 300 mg/day increase in calcium intake, the risk of MetS decreased by 7% . In conclusion, our findings suggest that dietary calcium intake may be inversely associated with the risk of MetS. These findings may have important public health implications with respect to preventing the disease. Further studies, in particular longitudinal cohort studies and randomized clinical trials, will be necessary to determine whether calcium supplementation is effective to prevent MetS.Growing evidence has suggested a possible relationship between dietary calcium intake and metabolic syndrome (MetS) risk. However, the findings of these observational studies are inconclusive, and the dose-response association between calcium intake and risk of MetS remains to be determined. Here, we identified relevant studies by searching PubMed and Web of Science databases up to December 2018, and selected observational studies reporting relative risk (RR) with 95% confidence interval (CI) for MetS based on calcium intake and estimated the summary RRs using random-effects models. Eight cross-sectional and two prospective cohort studies totaling 63,017 participants with 14,906 MetS cases were identified. A significantly reduced risk of MetS was associated with the highest levels of dietary calcium intake (RR: 0.89; 95% CI: 0.80–0.99;  The global incidence of MetS is continuing to rise over the past decades. The age-adjusted prevalence of MetS in the United States increased from 29.2% to 34.2% from 1999 to 20063. Asian populations also showed the similar trend4. Given its strong link to several chronic diseases, preventing MetS has been an important public health problem.Metabolic syndrome (MetS) is characterized by a constellation of interacting risk factors including impaired glucose tolerance (IGT), atherogenic dyslipidemia, elevated blood pressure, and visceral adiposity. These factors contribute to type 2 diabetes mellitus(T2D), cardiovascular disease (CVD), and other interrelated diseases5. Serving as a ubiquitous signaling molecule with diverse role, calcium is also involved in a wide variety of physiological processes outside of the skeleton, including neuronal transmission, muscle contraction, organelle communication, hormone secretion, fertilization, and cell growth6. Previous evidence from meta-analysis indicated that calcium may reduce the risk of CVD and some types of cancer8. In the recent dozen years, a growing body of epidemiological studies evaluated the association between dietary calcium intake and the risk of MetS. However, the results of these studies were not consistent, and the overall conclusion still remains controversial.Calcium, an essential element, is the most abundant ion in human body. It is mainly stored in bones in the form of hydroxyapatiteTo our knowledge, there is no meta-analysis has been performed before to study the putative association between dietary calcium intake and the risk of MetS. Hence, we conducted the current systematic review and meta-analysis in order to quantify the dose-response relationship between dietary calcium intake and MetS risk.16 and 2 prospective cohort studies18.Figure 16, two studies were conducted in United States18, and the others were performed in Saudi Arab9, France17, and Australia14, respectively. The definition of metabolic syndrome in all these studies either used the International Diabetes Federation (IDF) criteria or the National Cholesterol Education Program (NCEP) ATP III criteria. Quality assessment for the studies yielded an average score of 7.7 (0.9) (Tables Table ) Tables –3, and tvs. lowest dietary calcium intake are shown in Fig. I2 = 75.3%). Neither Egger’s test (P = 0.46) nor the funnel plot  of MetS for highest I2 = 0). Moreover, association was more robust in the analysis based on cohort studies  than that based on cross-sectional studies . The associations were similar in other subgroups, including study location and the definition of MetS.To identify the potential sources of heterogeneity, we performed subgroup analyses among all of the selected studies in order Table . NotablyI2 = 77.7%; see Fig. For dose-response analysis, one cross-sectional study and one cohort study were excluded for lacking detailed data of dietary calcium intake level. We extracted data from the remaining 8 studies. The result showed that a 300 mg/day increase in dietary calcium intake was associated with a 7% lower risk of MetS . In addition, Cho et al. indicated menopause status may influence the protective effect of calcium intake on MetS10. They found that only in postmenopausal women, higher level of calcium intake was related to decreased MetS risk. However, these findings weren’t repeated successfully in subsequent research11. Notably, heterogeneous methods to measure calcium intake, such as food frequency questionnaire (FFQ), 24-hour or 3-day food recall, were used among these studies, which may lead to misclassification of exposure and inconsistencies in findings.In view of the current study, the controversy among different epidemiological studies may be attributed to gender difference. According to the data extracted from the Insulin Resistance Syndrome (DESIR) cohort, Drouillet 30. Accumulating evidence has suggested that imbalance of intercellular calcium homeostasis may play an important role in adipocyte function6. Increased cytosolic calcium promoted triglyceride accumulation as well as lipid storage through controlling de novo lipogenesis31. Additionally, unabsorbed calcium in the gastrointestinal tract isn’t without metabolic effects32. For example, calcium may form insoluble calcium soaps with fatty acids in gastrointestinal tract to influence fat and energy metabolism33.Although the exact mechanisms remain unclear, the protective effect of calcium consumption on MetS may be due to its ability in regulating energy metabolism and insulin-stimulated glucose uptake and storageThis meta-analysis has several advantages. Above all, the primary advantage is that it is the first dose-response meta-analysis that quantitatively examined the relationship between dietary calcium intake and the risk of MetS. We also generated linear associations in addition to comparing the highest and lowest categories of calcium intake to increase the power of meta-analysis. Moreover, a common source of concern in meta-analysis is publication bias, but There was no evidence of publication bias in our study. Last but not least, relatively large number of study population enhanced the statistical power and made the subgroup analysis feasible.On the other hand, the primary limitation of our analysis is that most of the selected studies were retrospective epidemiological studies. We also cannot exclude the possibility of confounding because of the observational nature of the included studies, although most of the original studies were adjusted for major potential confounders. Second, we also found significant heterogeneity in the result of the present study, and the sources of high heterogeneity cannot be totally explained by most of our subgroup analyses. However, significant differences in dietary calcium intake and MetS risk remained in several subgroups with lower heterogeneity, suggesting that the pooled results are likely reliable. Third, the number of included studies is relatively small. Besides, we might have neglected the missed unpublished reports, although every effort was made to estimate the unpublished risk. Finally, measurement and recall bias of dietary consumption assessment using food recall or FFQ would likely cause information bias.In summary, this meta-analysis suggested that dietary calcium intake was inversely related to MetS risk, and such weak but significant association was supported by linear dose-response analysis. Subgroup analysis provided evidence that the beneficial effect may be significant among women, but less robust among men. In consideration of developing guidelines to prevent MetS by increasing the calcium-rich foods consumption, these findings may have important public health implications. However, the putative inverse association of dietary calcium intake with MetS risk still needs to be confirmed by larger prospective cohort studies and randomized clinical trials.A comprehensive bibliographic research was performed on two databases - PubMed and Web of Science - for population-based studies published up to December 31th, 2018. Observational studies that examined the relationship between dietary intake of calcium and the risk of developing MetS were considered as potential suitable studies. The following terms were adopted as search strategy: calcium AND (“metabolic syndrome” OR “insulin resistance syndrome” OR “syndrome X”). To identify potential publications, we also examined the references of relevant reviews and meta-analysis. Bibliographic search was restricted to human studies without language limitation.Each included studies in this meta-analysis should fulfill the following four criteria: (1) population-based epidemiological studies, including cohort studies, case-control studies, and cross-sectional studies; (2) the exposure of interest is intake of dietary calcium; (3) the outcome is MetS; (4) either adjusted risk ratios, including relative risks (RRs) and odds ratios (ORs) with 95% confidence intervals (95% CIs), or necessary data to calculate these values should be reported.During the screening process, we excluded non-observational studies, studies that were not original , or not conducted in human subjects.Two investigators (authors DH and XF) extracted the relevant data independently from the identified articles using a standard extraction form. From each identified study, we extracted the following information: study characteristics ; the participants’ characteristics ; the method used to assess nutrient intakes; and the definition of metabolic syndrome measurements.34, while cross-sectional studies were evaluated using a modified version of NOS with a highest score of ten35. Scores of 0–3, 4–6, and 7–9 were interpreted as low, moderate, or high quality, respectively.Quality assessment of included studies was conducted according to the Newcastle-Ottawa Scale (NOS) that gives a maximum of nine points for each studyIn the present study, we used RR with 95% CI to estimate risk; in addition, ORs  were used to directly determine the relative risk. Before inclusion in the overall analysis, we pooled the results that were stratified by sex by conducting a fixed effects meta-analysis.36. Prospective and retrospective studies were analyzed separately in the main meta-analysis. To determine the sources causing between-study heterogeneity, we also performed subgroup analyses based on sex, location, study design, and the definition of MetS.We first pooled these RRs sequentially using the DerSimonian and Laird random effects method, taking both within-study and between-study variability into account37 and using the publicly available Stata command written by Orsini et al.38. In accordance with this method, studies with three or more exposure categories were included. If the number of cases or participants was not available, we used variance-weighted least-squares regression to estimate risk39. If neither the median nor the mean was given in the original study, we used the categorical midpoint instead. If the lowest and/or highest category was open-ended, the midpoint of the category was determined by assuming that the width of the category is the same as the next adjacent category.Dose-response analysis for calcium intake and MetS were conducted according to the method described by Greenland and LongneckerI² tests for across studies comparison. The values of 25%, 50%, and 75% were interpreted as low, moderate, and high degrees of heterogeneity, respectively40. Publication bias was evaluated by visually inspecting a contour-enhanced funnel plot and by performing Egger’s linear regression test (with significance defined as P < 0.10)41. Stata 12  was used to perform all statistical analyses. All statistical tests were two-sided and differences with a P-value < 0.05 were considered significant except where noted otherwise.We used Supplementary data


Several meta-analyses have been published summarizing the associations of the Mediterranean diet (MedDiet) with chronic diseases. We evaluated the quality and credibility of evidence from these meta-analyses as well as characterized the different indices used to define MedDiet and re-calculated the associations with the different indices identified. We conducted an umbrella review of meta-analyses on cohort studies evaluating the association of the MedDiet with type 2 diabetes, cardiovascular disease, cancer and cognitive-related diseases. We used the AMSTAR (A MeaSurement Tool to Assess systematic Reviews) checklist to evaluate the methodological quality of the meta-analyses, and the NutriGrade scoring system to evaluate the credibility of evidence. We also identified different indices used to define MedDiet; tests for subgroup differences were performed to compare the associations with the different indices when at least 2 studies were available for different definitions. Fourteen publications were identified and within them 27 meta-analyses which were based on 70 primary studies. Almost all meta-analyses reported inverse associations between MedDiet and risk of chronic disease, but the credibility of evidence was rated low to moderate. Moreover, substantial heterogeneity was observed on the use of the indices assessing adherence to the MedDiet, but two indices were the most used ones [Trichopoulou MedDiet (tMedDiet) and alternative MedDiet (aMedDiet)]. Overall, we observed little difference in risk associations comparing different MedDiet indices in the subgroup meta-analyses. Future prospective cohort studies are advised to use more homogenous definitions of the MedDiet to improve the comparability across meta-analyses. The Seven Countries Study observed in the 1960s a lower cardiovascular mortality in the participating countries around the Mediterranean area . Apart fThe interest in the MedDiet as a whole was not restricted to those countries and thus, the MedDiet has been investigated in many countries that are geographically far from being Mediterranean, e.g. Australia and Japan –15. The The creation of nutritional indices is a common tool largely used in the nutritional epidemiology research with the purpose of reflecting the adherence to a dietary pattern, e.g. the MedDiet, in a certain population. These are created by ranking the population according to the intake of foods considered to be in line with, or against, the dietary pattern under study.Sofi et al. as well as Davis et al. discussed the derived difficulties from the use of different scores measuring MedDiet adherence , 19. TheThis manuscript was drafted in adherence to the recommendations of the ‘Preferred Reporting Items for Systematic reviews and Meta-Analyses’ (PRISMA) checklist .The methodological approach of this umbrella review is based on previous published umbrella reviews, which focused on nut and garlic intake and risk of CVD , 22, andPubMed (from inception until 27th March 2018) and Embase (from inception until 27th March 2018) was searched for meta-analyses published in English language using following search terms: (Mediterranean[tiab]) AND  AND . Additionally, reference lists of the included meta-analyses were verified for further relevant studies as well.Studies were included in this umbrella review if they met all of the following criteria: (1) meta-analysis of cohort studies, (2) evaluating the association of scores used for assessing adherence to a MedDiet or considered by the authors as reflecting a MedDiet type diet, (3) study population: ≥ 18 years, (4) study endpoints include overall cancer mortality and/or incidence, CVD or coronary heart disease (CHD) mortality and/or incidence, stroke, myocardial infarction (MI), acute myocardial infarction (AMI) type 2 diabetes, Alzheimer’s disease (AD), mild cognitive impairment (MCI), or dementia.The methodological quality was evaluated using a modified version of the AMSTAR (A MeaSurement Tool to Assess systematic Reviews)  checklisTo evaluate credibility of evidence for the association between adherence to MedDiet and risk of the included outcomes we applied the NutriGrade scoring system (max 10 points) which comprises the following items for cohort studies : (1) risWithin the meta-analyses included in this study the different scores used in the primary studies were carefully evaluated. The nine food groups referred to by Trichopoulou et al. , and usuIf at least two cohort studies were included in a meta-analysis for at least two specific MedDiet adherence scores identified  a new meta-analysis was carried out to estimate and compare the associations between these scores for the included outcomes. These new meta-analyses were performed by combining the multivariable adjusted RRs, HR of the highest compared with the lowest MedDiet adherence category, or 2-point increase in MedDiet adherence score based on a random effects model using the DerSimonian–Laird method, which incorporated both within and between study variability . To evalTo detect discrepancies between the different types of MedDiet adherence scores for an outcome a test for subgroup differences was performed based on a random effects model .For the summary random effects, we estimated for each meta-analysis the 95% prediction interval (PI), which further accounts for the degree of between-study heterogeneity and gives a range for which we are 95% confident that the effect in a new study examining the same association lies within .All analyses were conducted using the Review Manager by the Cochrane Collaboration (version 5.3) and Stata 14.2 .The study characteristics of the meta-analyses are summarized in Table Almost all included meta-analyses showed a significant inverse association between higher adherence to a MedDiet and risk of chronic diseases. Estimating 95% prediction intervals, however, the null value was excluded only in some of the associations . This implies that most meta-analyses indicated high degrees of statistical heterogeneity and/or were based on a limited number of studies.In total, the overall methodological quality of the included meta-analyses was rated as moderate Table . On averThe NutriGrade credibility of evidence judgement varied between low (low confidence for the effect estimate: further research provides important information on the confidence and likely change the effect estimate) and moderate (moderate confidence for the effect estimate: further research could add information on the confidence and may change the effect estimate).A total of 70 primary studies were included within the 27 meta-analyses, where 34 different scores meant to reflect the MedDiet were applied –106. A dThe second main definition observed referred to the one created by Fung et al. , the altMediterranean-like cluster.Apart from these two main groups of definitions we identified 16 other scores used to assess MedDiet adherence in 24 reports , 83–105.Several of the included meta-analyses reported moderate to high statistical heterogeneity, which could be related to the different indices applied. Once we identified the different scores used in the primary studies and considered these as similar enough, if at least two cohort studies were included in a meta-analysis for at least two different MedDiet scores, we combined the studies applying similar scores in a new meta-analysis and tested for possible subgroup differences in between the different scores.p > 0.10) for T2D as outcome in the random effects model (Table p = 0.06) was observed when reanalysing the meta-analysis by Sofi et al.  have been identified as the most used and we encourage researchers to use one of these two definitions when assessing adherence to the MedDiet if possible in order to not compromise further comparability among studies. The use of other scores would be justified in case these would better reflect the MedDiet for the purpose of the research. For most of the outcomes here evaluated we did not observe major differences in the use of one or the other of these two scores, nevertheless, some differences were observed for cancer mortality, fact that could be due to the betterment of the aMedDiet with regard to the tMedDiet according to the literature evidence.


Background: The Leu72Met polymorphism of ghrelin gene has been associated with genetic predisposition to type 2 diabetes mellitus (T2DM), while conclusions remain conflicting. Hence, we performed this updated meta-analysis to clarify the association between Leu72Met polymorphism and T2DM susceptibility.Methods: Six electronic databases were consulted for articles published before 1 January, 2018. Pooled odds ratios (OR) and 95% confidence intervals (CI) were calculated under five genetic models to assess this association. We used I2-test and Q statistics to measure heterogeneity across the included studies. Subgroup analyses and publication bias were also performed.Results: Thirteen case-control studies involving 4720 T2DM patients and 4206 controls were included in this meta-analysis. The overall results using fixed-effects models showed that Leu72Met polymorphism was significantly associated with an increased risk of T2DM under homozygous model . Further subgroup analyses stratified by ethnicity revealed that the risk for T2DM was only increased in Asians , while decreased in Caucasians . Funnel plots were basically symmetrical, and all p-values of Egger's test under five genetic models were >0.050, which indicated no evidence of publication bias.Conclusions: Our results demonstrate that the Leu72Met polymorphism of ghrelin gene may be protective against T2DM in Caucasians, while predisposing to T2DM in Asians. Type 2 diabetes mellitus (T2DM), the most common metabolic disease, is characterized by a progressive decline in pancreatic β-cell function and increase in insulin resistance. It is estimated that ~415 million adults across the world were diagnosed with diabetes in 2015, and this number is predicted to rise to 642 million by 2040 , a unique 28-amino acid gastrointestinal peptide hormone, was first discovered by Kojima and Kangawa in 1999 as the endogenous ligand for the growth hormone secretagogue receptor  guideline  and three Chinese  electronic databases were consulted for English and Chinese peer-reviewed articles published before 1 January 2018 regarding the association between ghrelin Leu72Met polymorphism and T2DM susceptibility. For the English databases, search strategy (“diabetes” or “T2DM”) and (“ghrelin” or “GHRL” or “Leu72Met” or “+408 C > A” or “rs696217”) and (“polymorphism” or “mutation” or “variant”) were applied. For the Chinese databases, search terms included “T2DM,” “ghrelin,” and “polymorphism.” Additional publications from the reference lists of original research articles and review articles were also searched. The papers were limited to humans and published in English or Chinese.Studies which meet the following inclusion criteria were considered eligible: (1) studies reporting the association between the Leu72Met polymorphism of ghrelin gene and T2DM risk; (2) case–control study design; and (3) providing sufficient genotype data that could calculate odds ratios (ORs) and 95% confidence intervals (CIs). The exclusion criteria were: (1) family or sibling pairs based studies; (2) editorials, case reports, reviews or meta-analyses, and (3) studies without detailed genotyping data. In addition, if there were duplicate publications from the same population, only the study with larger sample size and comprehensive data was included in our meta-analysis.For the included studies, data were independently extracted by two authors (Huang R and Tian S) as follows: the first author's name, year of publication, country, ethnicity, sample size of cases and controls, diagnostic criteria for T2DM, genotyping method, genotype and allele distributions of cases and controls, and controls with Hardy–Weinberg equilibrium (HWE) or not. The controversy about one article was discussed and resolved by a third reviewer (Cai RR).The Newcastle-Ottawa quality assessment scale (NOS) was used to evaluate the methodological quality of the included case-control studies, which consists of the following three aspects: (1) selection of study subjects: 0–4 star, (2) comparability of study subjects: 0–2 star, and (3) exposure or outcomes: 0–3 star , fixed-effects models were used; otherwise, random-effects models were applied. Sensitivity analysis was carried out by removing each study in sequence to assess the stability of the results. Additionally, Begg's funnel plots and Egger's regression test were used for investigating the potential publication bias. The results were considered statistically significant if the 2-tailed p-value was below 0.050. All the above-mentioned statistical analyses were performed with STATA software (Version 11.0) .The pooled OR with a 95% CI was used to estimate the strength of the association between ghrelin Leu72Met polymorphism and T2DM risk under different comparison models, including dominant model (Leu72Met + Met72Met vs. Leu72Leu), recessive model (Met72Met vs. Leu72Met + Leu72Leu), homozygous model (Met72Met vs. Leu72Leu), heterozygous model (Leu72Met vs. Leu72Leu), and allelic model (Met72 + vs. Leu72+). Subsequently, we performed subgroup analyses to evaluate the effect of Leu72Met polymorphism on T2DM susceptibility under above-mentioned five genetic models according to the ethnicity of included populations. Heterogeneity across the included studies was assessed via A total of 208 studies were identified in the literature search using the above-mentioned search strategies Figure . Of thesp = 0.049) , while decreased in Caucasians   Figure . Furtherp = 0.065; OR = 1.300, 95%CI 0.994–1.700, p = 0.056; OR = 1.290, 95%CI 0.986–1.686, p = 0.063; OR = 1.308, 95%CI 1.000–1.711, p = 0.050; OR = 1.250, 95%CI 0.955–1.636, p = 0.104; OR = 1.298, 95%CI 0.989–1.702, p = 0.060; OR = 1.297, 95%CI 0.989–1.700, p = 0.060; OR = 1.336, 95%CI 0.926–1.928, p = 0.122; OR = 1.267, 95%CI 0.959–1.674, p = 0.096, respectively) .Funnel plot, Begg's test and Egger's test were performed to evaluate whether there exist possible publication biases. The funnel plots appeared to be basically symmetrical, and all T2DM is a multifactorial disorder attributing to the coexistence of a variety of genetic and environmental factors        as 0.05, the total sample size of 2,950 subjects with 1,548 cases and 1,402 controls and 6.46 and 7.70% of Met72 allele in cases and controls only provides 25.90% power to detect the OR of 0.79 in the dominant model in Caucasians. Moreover, sensitivity analysis of this meta-analysis also indicated that the overall results were somewhat unstable. Second, we only included the studies performed in Caucasians, Asians, and Arabians, which limited the application to a certain degree. Third, the overall results of our study were based on individual unadjusted OR because we had no access to the original data, such as BMI and IR. Additionally, gene-gene interaction and T2DM-related phenotypes were not taken into account because of limited date addressing these issues.In conclusion, our results demonstrated that the Leu72Met polymorphism of ghrelin gene is protective against T2DM in Caucasians, while predisposing to T2DM in Asians. Since the low power of detecting effects and other potential biases and confounders can't be ruled out completely in this meta-analysis, further studies based on a large sample size are needed to verify the current findings.SW and RH designed the study. RH, ST, and RC collected the data. RH, JS, and YS performed the analyses. RH wrote the first draft. SW and ST checked the manuscript and revised it. All authors approved the final submission.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


IL-6) -174 G/C single nucleotide polymorphism (SNP) and the risk and mortality of sepsis by conducting this updated meta-analysis with trial sequential analysis.This article intends to explore the association between interleukin-6 gene  and allelic model, while trial sequential analysis revealed it could be a false positive result nevertheless.Twenty studies (including 3282 cases and 4926 controls) and eight studies (including 610 cases and 1856 controls) were respectively enrolled in the analysis on the association between IL-6-174 G/C polymorphism is not associated with the risk and mortality of sepsis. Trial sequential analysis showed that a large sample size was needed to get a more reliable result of the association between IL-6-174 G/C polymorphism and sepsis in non-adults.The online version of this article (10.1186/s12881-019-0766-2) contains supplementary material, which is available to authorized users. Sepsis is a systemic multiorgan dysfunction secondary to the dysregulated host response to infection as suggested in the latest definition for sepsis (Sepsis-3.0) and has a strong correlation with intensive care unit (ICU) admission and in-hospital mortality , 2. The The alteration of immune function has been considered a key factor in the pathogenesis of sepsis . The hosIL-6 gene, located at 7p15.3 is responsible for the regulation of the transcriptional activity during inflammation reaction. The possible association between its − 174 G/C polymorphism (rs1800795) at promoter region and the risk and mortality of sepsis has been widely studied. However, the findings are varied among different studies. IL-6-174 C allele is thought to block the norepinephrine-induced transcription factor binding to IL-6 gene promotor and thus to lower the gene expression, which is favorable for inflammation-related diseases [IL-6-174 G/C polymorphism did not have a link with the risk and mortality of sepsis at any age and ethnicity groups [IL-6-174 G allele was associated with early-onset sepsis in Saudi infants [IL-6-174 C allele rather than G allele that contributed to the risk of sepsis induced by pneumonia [IL-6-174 CC genotype and a higher septic shock-related mortality in patients who underwent major surgery [phism rs100795 at neumonia , 12. Wheneumonia . Jimenez surgery . These sWe searched PubMed, Web of Science and China National Knowledge Infrastructure (CNKI) for available studies published before September 2018. The keywords for searching were a combination of “IL-6, interleukin-6, rs1800795, -174G/C, polymorphism, sepsis, septicemia, septic shock”. Meanwhile, references of the relevant literature reviews were screened to identify potentially relevant publications.IL-6-174 G/C polymorphism and the risk and/or mortality of sepsis; objects in each study were from same epoch; including a case group of sepsis; including a control group; including precise sample size of IL-6-174 G/C polymorphism of case and control groups which could be directly extracted or calculated according to the information available. Excluded were: repetition of the published studies; a meta-analysis or a review; study with insufficient or incorrect data; study with only G or C allele carriers. The screening process is illustrated in a flow chart  by two researchers . Availab2-test for evaluating Hardy-Weinberg equilibrium (HWE). When P > 0.05, the objects were under Hardy-Weinberg equilibrium and within a same Mendelian population. Homogeneity of the studies was tested. When P < 0.1 or I2 > 50%, a high level of heterogeneity between studies was envisaged and random-effect model was adopted; when P > 0.1 and I2 < 50%, there was no significant heterogeneity between studies, and fixed-effect model was used. The effect of IL-6-174 G/C on the risk or mortality of sepsis was measured by P value, odd ratio (OR) and 95% confidence interval (CI). P < 0.05 was reviewed as statistical significance. In the analysis on sepsis risk, subgroup analyses based on age group, ethnicity, restricted healthy controls were conducted. Subgroup analysis on age and ethnicity in the mortality analysis was also made. If no information of age group was given in a study, we considered it would be as a study on adult. The majority of the nation of study was taken as the ethnicity of the study population in case that it was not specifically mentioned. The objects in three studies were mainly Caucasians, so they were included in the subgroup analysis of the Caucasians as the number of non-Caucasians were very small [P > 0.05 in regression test, no obvious publication bias would exist.The role of minor allele C in the risk and mortality of sepsis was targeted. Thus an analysis was made using dominant model (GC + CC versus GG), recessive model (CC versus GC + GG), co-dominant model (GC versus GG and CC versus GG) and allelic model (C versus G). While some studies only yielded a sum of number of genotypes, they were enrolled in analyses just under certain genetic models –19. Statry small , 20, 21.IL-6-174G/C polymorphism have or did not have a correlation with sepsis, respectively. TSA was conducted in the genetic model with the most included studies. If each genetic model had the same number of included studies, TSA would be conducted in allelic model. Meta-analysis which presented a significant result in the pool analysis was also tested under TSA. TSA was conducted on TSA software 0.9.5.10 Beta.Meta-analysis might be affected by type I error due to the increased risk of random error and repeated significance testing. Trial sequential analysis (TSA) was a useful tool to verify the reliability of the results from meta-analysis by estimating the required information size (RIS) (sample size of included studies) and calculating the threshold for statistical significance . A type IL-6-174 G/C polymorphism were shown in Table 354 studies were initially acquired from databases and 4 studies were from references of publications. After exclusion of irrelevant studies, review and meta-analysis as well as repetitions, 29 studies were identified for full-text review. 5 studies were further excluded after full-text review because of inadequate data for analysis –27. EvenIL-6-174 G/C polymorphism and the risk of sepsis concerning the overall population under dominant model, recessive model, codominant model and allelic model  , recessive model , codominant model  and allelic model . Subgroup analysis on adults and Caucasians did not show any association between IL-6-174 G/C polymorphism and mortality. Nevertheless, subgroup analysis on non-adults manifested that IL-6-174 G/C polymorphism was associated with worse survival of septic patients in recessive model , co-dominant model  and allelic model .The results were shown in Table IL-6-174 G/C polymorphism and the mortality of non-adult  were changed after omitting certain studies. Additionally, some relevant studies might influence the results of study were also tested in our analyses. An analysis after omitting two studies including elder children from non-adults group was also made, the results being unchanged [No obvious publication bias was found in every section of this meta-analysis in Egger’s test. The results and graphs of Egger’s tests were shown in Table nchanged , 33 , non-adults (dominant model), adults (recessive model), Caucasians (recessive) and analysis involving healthy controls  and Mendelian population . Z-curves crossed the futility boundary and reached the required sample size in those analysis. The exception was the analysis on non-adult group, where Z-curve crossed neither conventional test boundary nor the futility boundary Fig. . In the IL-6-174 G/C polymorphism and the risk or mortality of sepsis has been widely studied, and previous meta-analyses have been conducted in 2008 and 2013. Five more studies have been published in recent years. Because of the controversial findings, an updated meta-analysis is necessary to bring some new insights into this topic. This study has the largest sample so far to address this issue. What’s more, trial sequential analysis was carried out in order to quantify the statistical reliability of the results. No association between IL-6-174 G/C polymorphism and the risk or mortality of sepsis in the overall population was found. This is similar to the finding by Gao et al. [The association between o et al. . HeterogIL-6 gene, − 174 G/C was found to be associated with the lower serum IL-6 level and lower inflammatory response subsequently [IL-6-174G/C polymorphism and the risk and mortality of sepsis [IL-6-174 G/C polymorphism might influence the transcriptional activity and lower the inflammatory reaction, it did not get the point that it could influence the development of sepsis nevertheless. Secondly, IL-6-174 G/C polymorphism might have an impact on the certain groups of people and pathological states, which were not within the subgroups of this study. Thirdly, IL-6 had many promotor SNPs such as -597G/A, −572G/C, −373AnTn and -174G/C, these polymorphic sites did not regulate the gene function independently [Located at promotor region of equently , 27, 41.f sepsis , 39, 40.endently . And theIL-6 expression, a study on neonates showed serum IL-6 level was higher in C carriers [IL-6-174 G/C polymorphism on the inflammatory process of non-adults might be promising in further studies.It’s noteworthy that C allele was associated with poor outcomes of sepsis in non-adults in recessive model, codominant model (CC vs. GG) and allelic model. However, TSA revealed that this result was not reliable as Z-curve crossed neither the conventional test boundary nor the futility boundary. Although many studies demonstrated C allele led to a lower carriers . It was carriers . We hypocarriers . Thus thIL-6 -174G/C polymorphism were rare in Asian population that resided in Korea, Japan and Shandong province and Guangxi province of China [IL-6 -174G/C polymorphism and the risk of sepsis in the Chinese Han population in Henan province [IL-6 -174G/C polymorphism was distributed in Asians that resided in certain areas and might have an influence on the pathogenesis of sepsis.Most included studies in our analysis were concerned with the Caucasians, rather than the Asians. Previous analysis also present that the frequency of of China , 46, 47.province , 14. ThiAs the types of controls were varied, it was considered that the status of controls could influence the results. In some studies, the case group was not comprised of septic patients only. Being compared to healthy controls and to mendelian population, the association with the risk of sepsis was not found, nevertheless. The case group of one study included a part of patients diagnosed as systemic inflammatory response syndrome (SIRS) or multiple organ disorder syndrome (MODS) . And conOur study has two strengths. Firstly, to avoid our analysis to be biased from publication, database, inclusion criteria and language, strict criteria were laid out for enrolling studies and publications in the Chinese language were also searched. Publication bias was tested in Egger’s tests. Secondly, TSA was adopted to test the reliability of results and provide the research field which required more studies.There were several limitations in this study. First, as the definition for sepsis changed, it was unlikely that the enrolled studies would have same definition because our analysis included studies within a large time range. Second, the majority of the objects studied were Caucasians, more studies were needed to further the study on other ethnicity groups. Third, three studies were not under Hardy-Weinberg equilibrium, although the results were not changed after omitting those studies. In addition, we could not get some details of the objects such as treatment and lifestyle, which prevented us from seeking more factors influencing the results.IL-6-174 G/C polymorphism and the risk or mortality of sepsis. Trial sequential analysis indicated that large sample size was needed to get a more reliable result for the association between IL-6-174 G/C polymorphism and the risk and mortality of sepsis in non-adults. More studies on the molecular mechanism and interactions between SNPs were needed.In conclusion, we did not find the evidence of the association between Additional file 1:Table S1. Results of quality assessment of included studies using Newcastle-Ottawa Scale. Table S2. Summary of the studies with changed results after sensitivity analysis. Table S3. Results of meta-analysis on non-adults after excluding two studies discussing elder children. Table S4. Results of meta-analysis after including the study by Reiman. (DOCX 22 kb)Supplementary tables. Additional file 2:Supplementary figures. The figures of pool analysis, egger’s test, sensitivity analysis and trial sequential analysis of each study were summarized. (DOCX 9463 kb)


Meta-analytic structural equation modeling (MASEM) is a statistical technique to pool correlation matrices and test structural equation models on the pooled correlation matrix. In Stage 1 of MASEM, correlation matrices from independent studies are combined to obtain a pooled correlation matrix, using fixed- or random-effects analysis. In Stage 2, a structural model is fitted to the pooled correlation matrix. Researchers applying MASEM may have hypotheses about how certain model parameters will differ across subgroups of studies. These moderator hypotheses are often addressed using suboptimal methods. The aim of the current article is to provide guidance and examples on how to test hypotheses about group differences in specific model parameters in MASEM. We illustrate the procedure using both fixed- and random-effects subgroup analysis with two real datasets. In addition, we present a small simulation study to evaluate the effect of the number of studies per subgroup on convergence problems. All data and the R-scripts for the examples are provided online. The combination of meta-analysis and structural equation modeling (SEM) for the purpose of testing hypothesized models is called meta-analytic structural equation modeling (MASEM). Using MASEM, correlation matrices from independent studies can be used to test a hypothesized model that explains the relationships between a set of variables or to compare several alternative models that may be supported by different studies or theories . HoweveSpecifically, we propose a follow-up analysis in which the equality of structural parameters across studies can be tested. Assuming that there are hypotheses on categorical study-level variables, the equality of specific parameters can be tested across subgroups of studies. In this way, it is possible to find a model in which some parameters are equal across subgroups of studies and others are not. More importantly, it helps researchers to identify how study-level characteristics can be used to explain differences in parameter estimates.With regard to how to handle heterogeneity in a meta-analysis, two dimensions (or approaches) can be distinguished . The fiThe fixed-effects model (without moderators) usually assumes that all studies share the same population effect size, while the fixed-effects model with moderators assumes that the effects are homogeneous after taking into account the influence of moderators. The random-effects model assumes that the differences across studies are random. The random-effects model with moderators, known as a mixed-effects model, assumes that there will still be random effects after the moderators are taken into account.The above framework from general meta-analysis is also applicable to MASEM. Table One way to account for heterogeneity is by estimating between-study heterogeneity across all studies in the random-effects approach  with data from Norton, Cosco, Doyle, Done, and Sacker  as well In the next two sections we briefly describe fixed-effects TSSEM and random-effects TSSEM. For a more elaborate explanation see Cheung and Chan , Cheung The fixed-effects TSSEM approach was proposed by Cheung and Chan . They peIn fixed-effects TSSEM, the correlation matrices in the individual studies are assumed to be homogenous across studies, all being estimates of one common population correlation matrix. Differences between the correlation matrices in different studies are assumed to be solely the result of sampling error. The model that is fitted at Stage 1 is a multigroup model in which all correlation coefficients are assumed to be equal across studies. Fitting this model to the observed correlation matrices in the studies leads to an estimate of the population correlation matrix In Stage 2 of the analysis, weighted least squares (WLS) estimation Browne,  is used In random-effects TSSEM, the population effects sizes are allowed to differ across studies. The between-study variability is taken into account in the Stage 1 analysis. Estimates of the means and the covariance matrices in random-effects TSSEM are obtained by fixing the sampling covariance matrices to the known values variances in group g. The covariance structure is identified by setting diag(Φg) = I. Since the input is a correlation matrix, the constraint diag(Pg) = I, is required to ensure that the diagonals of For ease of discussion, we suppose that there are two subgroups. Given the two Stage 1 pooled correlation matrices in the subgroups In order to test the equality of factor loadings across groups, a model can be fitted in which The approach of creating subgroups with similar study characteristics and equating parameters across groups is suitable for any structural equation model. For example, in a path model, it may be hypothesized that some or all direct effects are different across subgroups of studies, but variances and residual variances are not. One could then compare a model with equal regression coefficients with a model with freely estimated regression coefficients to test the hypothesis. Also, the subgroups approach can be applied using fixed-effects or random-effects analyses.Structural equation models are ideally fitted on covariance matrices. In MASEM, and meta-analysis in general, it is very common to synthesize correlation coefficients. One reason for the synthesis of standardized effect sizes is that different studies may use different instruments with different scales to operationalize the variables of interest. The analysis of correlation matrices does not pose problems when the necessary constraints are included  variances of the indicators and common factors. Moreover, if all standardized factor loadings are set to be equal across groups, this implies that all standardized residual variances are equal across groups. Note that although one may be inclined to denote a test of the equality of factor loadings a test of weak factorial invariance .In this section, we present two examples of the testing of moderator hypotheses in MASEM using subgroup analysis. Example 1 illustrates the testing of the equality of factor loadings using factor analysis under the fixed-effects model  = 2,101.48, RMSEA = .039, 95% CI RMSEA: , CFI = .953, SRMR = .033). The parameter estimates from this model can be found in Table Norton et al.,  concludeχ26 = 2,101.χ2 = 5,756.84, p <.05). Homogeneity could be considered to hold approximately, based on the RMSEA , but not based on the CFI (.923) and SRMR (.111). In the non-patient group, homogeneity was also rejected by the chi-square test, In the patient group, homogeneity was rejected by the chi-square test  = 11.16, p <.05). However, the RMSEA of .013  indicated close approximate fit, as well as the CFI (.966) and SRMR (.045). Table We fitted a path model to the pooled Stage 1 correlation matrix, in which positive and negative relations predicted achievement indirectly, through engagement. Exact fit of this model was rejected (I2) within the subgroups are smaller than they were in the total sample, indicating that SES explains part of the between-study heterogeneity.Different pooled correlation matrices were estimated in the group of studies with low SES and the group of studies with high SES .The data-generating model was based on the results from Example 2. The population values for the direct effects in Subgroup 1 were: In each condition we fitted the correct model to the two subgroups separately, as well as to the subgroups combined. We restricted the between-studies covariance matrices to be diagonal, in order to reduce the number of parameters to be estimated. In practice, this restriction is often applied Becker, . We evalFigure We evaluated the parameter bias in mentclass2pt{minimThe relative bias in standard errors was around 10% in all conditions for the overall analysis. With the subgroup analysis, the standard error estimates were more accurate, with a bias of between roughly -5% and 5% in all conditions. The results are presented in Fig. if the model converges, the subgroup analysis will lead to better parameter estimates and standard error estimates in cases where a difference in the population coefficient is present, even if the population difference is small. In order to increase the likelihood of obtaining a converged solution, it is recommended that as many studies as possible be included.The simulation study showed that convergence is a serious potential problem when applying random-effects MASEM. Moreover, the likelihood of non-convergence occurring increases with smaller numbers of studies, such as with a subgroup analysis. However, We proposed subgroup analysis to test moderation hypotheses on specific parameters in MASEM. We illustrated the approach using TSSEM. The subgroup analysis method that was presented is not restricted to TSSEM. One could just as easily apply the subgroups analysis on pooled correlation matrices obtained with univariate approaches (Hunter & Schmidt, Creating subgroups of studies to test the equality of parameters across groups is a useful approach, but may also lead to relatively small numbers of studies within each subgroup. Given the large number of parameters involved in random-effects modeling, the number of studies may become too small for a converged solution to be obtained, as was the case in our Example 1. One way to reduce the number of parameters is to estimate the between-study heterogeneity variances but not the covariances among the random effects, i.e., restricting  Becker, . We applIn the simulation study, we found that even with a diagonal heterogeneity matrix, random-effects subgroup modeling is often not feasible due to convergence problems. In practice, researchers may therefore have no other option than to apply fixed-effects modeling instead of random-effects modeling. However, ignoring between-study heterogeneity is known to lead to inflated false positive rates for significance tests Hafdahl, . ResearcA limitation of the subgroup analysis to test moderation is that the moderator variables have to be categorical. In the second example, we split the studies into two groups based on the percentage of respondents with high SES in the study. By dichotomizing this variable we throw away information and lose statistical power. Indeed, contrary to our findings, the univariate meta-regression analyses reported by Roorda et al. showed significant moderation by SES. However, these analyses did not take into account the multivariate nature of the data, and tested the moderation of the correlation coefficients and not of the regression coefficients. Future research is needed to develop methods to include study-level variables as continuous covariates in TSSEM.In the current paper we presented a framework to test hypotheses about subgroup differences in meta-analytic structural equation modeling. The metaSEM and OpenMx-code and R-functions used in the illustrations are provided online, so that researchers may easily adopt the proposed procedures to test moderator hypotheses in their MASEM analyses. The simulation study showed that increasing the number of studies in a random-effects subgroup analysis increases the likelihood of obtaining a converged solution.


The association between estrogen receptor-β (ESR2) rs4986938 polymorphism and the risk of various types of cancer have been investigated in previous studies. However, the results remained disputable. Here, we conducted a meta-analysis to investigate the association between ESR2 rs4986938 polymorphism and the risk of cancer.We searched for relevant articles collected by the PubMed, EMBASE, and Cochrane library up to March 30, 2018. The association was assessed using Odds ratios (ORs) and 95% confidence intervals (CIs).P=0.20), dominant model , recessive model , heterozygous model , and homozygous model . Results of subgroup analysis stratified by ethnicity and cancer types further validated the results.The meta-analysis involved a total of 23 studies in 20 papers, including 24,334 cases and 31,707 controls. No significant association was detected between the rs4986938 polymorphism and cancer risk in the additive model (A compared with G: OR=0.97, 95% CI=0.92–1.02, We found no evidence of an association between rs4986938 and the risk of overall cancer. Estrogen receptors (ER), one of the family of nuclear transcription factors, are responsible for mediating the effects of steroids on many necessary functions such as cellular homeostasis, proliferation, development, reproduction, and gene expression , 2. ER gGenetic variation of the ESR genes could potentially lead to ESRs with altered binding kinetics that can adversely affect cellular metabolism . RNA staAn earlier meta-analysis reported that ESR2 rs4986938 was associated with the risk of breast cancer (BC) . ESR2 rsOwing to the inconsistent and inconclusive results found in the literature, the aim of the present meta-analysis was to provide exhaustive evidence to evaluate the effect of ESR2 rs4986938 on cancer risk. The subgroup analysis regarding ethnicity and cancer type were conducted to further analyze.We searched the PubMed, EMBASE, Cochrane library databases for relevant articles up to March 30, 2018, with the following terms: (“variants” or “polymorphisms” or “genetic polymorphism” or “single nucleotide polymorphism” or “SNP”) and (“estrogen receptors beta” or “estrogen receptor 2” or “ERbetacx” or “ESR2”) and (“tumors” or “neoplasm” or “cancer” or “carcinoma”). We had no limitations in language. Articles derived from these searches and related references cited in these articles were also reviewed.The inclusion criteria of eligible studies were as follows: (a) prospective cohort study or case-control study; (b) the studies assessed the association between ESR2 rs4986938 and cancer risk; (c) detailed genotyping data were provided; (d) cancer cases were histologically diagnosed and confirmed.The exclusion criteria of eligible studies were as follows: (a) duplicate studies; (b) studies with insufficient genotyping data; (c) studies include case-only; (d) not related to ESR2 rs4986938 polymorphisms and cancer risk.P value for HWE and genotype distributions in cases and controls.Two reviewers (Zhaofang Li and Xiaoli Yang) independently extracted data and reached consensus regarding all the items. If controversy appeared, the third researcher (Rongqiang Zhang) participated in the discussion to resolve the issue. The extracted data included the first author, publication year, country, ethnicity, cancer type, genotyping method, source of controls, sample size, The quality of the selected studies was accessed independently according to the Newcastle-Ottawa Scale (NOS). The quality score of the assessment scale was calculated by group selection, comparability and evaluation of exposure or outcome. The scores ranged from 0 to 10 and those with scores ≥6 were considered “high-quality” studies. Any discrepancies in the evaluation were settled by the third researcher (Rongqiang Zhang).P<0.10 was considered with significant heterogeneity. A random-effects model was applied when the heterogeneity was significant; otherwise, fixed-effect model was selected. Sensitivity analysis was conducted to evaluate the reliability and stability of the results by omitting one study at a time and calculating the effect size. Publication bias was accessed by the funnel plots and further performed by Egger’s test and Begg’s test. All tests carried out in the present report were two-tailed and P ≤ 0.05 was considered to be statistically significant. Data were performed using the Stata software  and RevMan software .The strength of associations between SNPs rs4986938 in ESR2 and cancer risk was analyzed by odds ratios (ORs) with 95% confidence intervals (CIs) in additive (A vs. G), dominant (AA+AG vs. GG), recessive (AA vs. AG+GG), heterozygous (AG vs GG) and homozygous (AA vs GG) models. Heterogeneity analysis was conducted using the Cochran’s Q test and I2 statistics. In any case A total of 210 publications were identified through the literature search. After removing the duplicate articles, 178 articles are still available for subsequent evaluation.Another 111 articles containing 32 reviews and/or meta-analysis and 79 irrelevant articles were excluded after screening the titles and abstracts. Finally, 20 articles were included in the present study after reading in greater detail . A totalThe cancer types analyzed in these studies were breast cancer (BC); prostate cancer (PCA); lung cancer (LC); colorectal adenoma (CRA); biliary tract cancers (BTC); and endometrial cancer (EC). The characteristics of the eligible studies are summarized in P=0.20), dominant model , recessive model , heterozygous model , and homozygous model  have been completely observed by the authors.