Nut consumption has been shown to reduce the risk of cardiovascular disease. However, its role in the prevention of metabolic disorders, such as metabolic syndrome (Mets) and overweight/obesity, remains controversial. We therefore conducted a meta-analysis to determine the association of nut consumption with Mets and overweight/obesity.Eligible studies were identified by searching the PubMed and Embase databases and by reviewing the references of relevant literatures. We used random effect models to pool the studies-specific risk ratio (RR) and weighted mean difference (WMD).n = 3) for Mets, 0.97  for overweight/obesity, and 0.95  for obesity. Pooling of randomized trials indicated that nut consumption was related to a significant reduction in body weight , body mass index , and waist circumference . These findings remained stable in the sensitivity analysis, and no publication bias was detected.This meta-analysis included six prospective cohort studies with 420,890 subjects and 62 randomized feeding trials with 7184 participants. Among the cohort studies, the summary RR for every 1-serving/week increase in nut intake was 0.96  contains supplementary material, which is available to authorized users. Metabolic syndrome (MetS) is recognized as a cluster of interrelated metabolic abnormalities, including central adiposity, hypertension, hyperglycemia, and dyslipidemia . It has In recent decades, lifestyle modifications, in particular a healthy diet, have been increasingly considered to play critical roles in the prevention of metabolic diseases. Previous reports have suggested that dietary intake of fruits and vegetables, dairy products, and coffee may reduce the risk of Mets or overweight/obesity –10, whilThis work was implemented in accordance with the Meta-analysis Of Observational Studies in Epidemiology guidelines . We idenTo be included in this meta-analysis, the cohort studies should meet the following conditions: 1) the exposure of interest was nut consumption; 2) the outcomes of interest included incidence of Mets or overweight/obesity; 3) the adjusted risk estimates, such as relative risks (RRs), were provided for at least three quantitative categories of nut consumption. Alternatively, studies that reported the risk estimates for every 1-serving/week increment in nut consumption were also eligible; 5) the median or mean consumption  and number of cases were available for each category of nut intake. We also included randomized feeding trials that examined the effects of a nut-enriched diet on anthropometrical outcomes, including body weight, BMI, and waist circumference. Animal studies, reviews, editorials, and studies of children or adolescents were excluded. When studies pertained to overlapping populations, only the report with the longest follow-up was retained.Two reviewers (H.L. and X.L.) independently abstracted the study details, including study author, publication year, study design, country, baseline age, and sample size. For cohort studies, the number of cases, measurement of nut intake, outcomes evaluated, confounders adjusted in multivariable models, and the maximally-adjusted risk estimates of Mets or overweight/obesity for each category of nut intake were additionally recorded. For clinical trials, we also extracted the type and amount of nuts consumed, details of comparative diet, and intervention duration. If necessary, the corresponding author of the original study was contacted for missing data. The methodological quality was appraised by using the Newcastle-Ottawa Scale  for cohoIn the meta-analysis of cohort studies, RRs and its 95% confidence intervals (CIs) were used to report the summary risk estimates for Mets or overweight/obesity. Because the cut-off points for intake categories were varied among the studies, we calculated an RR for an increase of one serving  per week in nut consumption for each report. The median or mean intake level of nut in each category was defined as the corresponding dose. If the mean or median intake level was not reported, the midpoint of the upper and lower boundaries of each category was used instead. If the highest category was open-ended, we assumed the median level as 1.5-times the lower boundary; and, when the lower boundary of the lowest category was unavailable, we set it to be zero. The method described by Greenland and Longnecker  and OrsiIn the meta-analysis of randomized feeding trials, the summarized estimates of changes in body weight, BMI, or waist circumference were presented as weighted mean differences (WMDs). To enable the pooling of data, standard errors or CIs were converted to standard deviations. All anthropometrical data were evaluated at the longest follow-up time according to the intention-to-treat analysis.p < 0.1). We also quantified the heterogeneity by the I2 statistic, with adoption of the following cut-off values: little or no heterogeneity (< 25%), moderate heterogeneity (25–75%), and substantial heterogeneity (> 75%). The study-specific estimates were aggregated using a random effect model. Subgroup analyses were conducted according to diagnostic criteria of outcomes (for Mets only), with between-subsets difference confirmed by the Altman and Bland test [p values < 0.05 were considered as significant.The heterogeneity between studies were explored by using the Cochrane Q test . The summary RR of Mets for an increase of 1-serving/week in nut intake was 0.96 .Three studies , 20, 22 2 = 0%, p = 0.45; Fig. 2 = 74%, p = 0.05; Fig. Three studies , 19, 21 2, 95% CI: -0.31 to − 0.01; Fig. p = 0.52; BMI: p = 0.37; waist circumference: p = 18). The detailed results from the individual studies were displayed in Additional file The data of body weight, BMI, and waist circumference were provided in 56, 39, and 23 randomized feeding trials, respectively, with substantial heterogeneity across them. Compared with control diet, a nut-enriched diet was associated with a significant decrease in body weight  and improved waist circumference  . SimilarThere are some possible explanations for the observed benefits of nuts. As a nutritious food, high intake of nuts provides abundant bioactive compounds including unsaturated fatty acids, dietary fiber, plant protein, antioxidants, vitamin E, arginine, phytosterols, and minerals like potassium, calcium, and magnesium. These healthy nutrients alone or in combination may improve inflammatory response, oxidative stress, and endothelial function, thus contributing to the improvements in individual Mets component . Recent In this meta-analysis, the inverse association of nut consumption with overweight and/or obesity seems to be counterintuitive, since nuts are a group of foods with high fats and dense calories. However, a previous pooled analysis of controlled feeding trials has shown borderline significant benefits of nut supplementation in the management of body weight, body mass index, and waist circumference . Also, iTo the best of knowledge, this is the first meta-analysis examining the effects of nut intake in risk reduction of Mets and overweight/obesity. Nevertheless, the limitations of our study should not be ignored. First of all, the recall and selection bias cannot be avoided in the analyses of Mets and overweight/obesity due to the observational nature of the original studies. Second, heterogeneity was present among the randomized feeding trials, which may influence the pooled estimates of body weight parameters. Third, owing to the lack of data, we cannot conduct stratified analyses for the risk estimates by some important factors . Fourth, due to the quite limited number of cohort studies, the potential of a non-linear association between nut consumption and risk of Mets or overweight/obesity cannot be evaluated. Last but not the least, this meta-analysis has geographical restrictions, as the majority of the included studies were from North America or Europe. Thus, generalization of our finding needs to be considered with caution.In summary, the results from this meta-analysis suggest that nut intake may be associated with decreased risks of Mets and overweight/obesity and lower body weight measures. The result supports the current recommendation of nut intake for the prevention of chronic diseases. Future prospective studies are still warranted to enhance our findings and to determine the health benefits of specific nuts.Additional file 1:Table S1. Detailed search strategies. Table S2. Excluded articles with reasons at the stage of eligibility. Table S3. Baseline characteristics of feeding trials. Figure S1. Body weight changes from the individual studies in this meta-analysis. Figure S2. Body mass index changes from the individual studies in this meta-analysis. Figure S3. Waist circumference changes from the individual studies in this meta-analysis. (DOCX 1311 kb)


GCKR) that mimic glucokinase-GKRP disruptors.Small-molecules that disrupt the binding between glucokinase and glucokinase regulatory protein (GKRP) in the liver represent a potential new class of glucose-lowering drugs. It will, however, take years before their effects on clinically relevant cardiovascular endpoints are known. The purpose of this study was to estimate the effects of these drugs on cardiorenal outcomes by studying variants in the GKRP gene  and coronary artery disease (CAD), estimated glomerular filtration rate (eGFR), and chronic kidney disease (CKD).The MEDLINE and EMBASE databases were searched for studies reporting on the association between GCKR variants and CAD . Sensitivity analyses showed that replacement of one large, influential CAD study by two other, partly overlapping studies resulted in similar point estimates, albeit less precise . GCKR was associated with an improved eGFR  and a trend towards protection from CKD .In total 5 CAD studies , 7 eGFR studies , and 4 CKD studies  were included. Meta-analysis revealed a significant association between This study suggests that increased glucokinase-GKRP disruption has beneficial effects on eGFR, but these may be offset by a disadvantageous effect on coronary artery disease risk. Further studies are warranted to elucidate the mechanistic link between hepatic glucose metabolism and eGFR. In the current area of precise medicine, there is an ongoing search for new anti-diabetic medication with different modes of action. Drugs that modulate the function of glucokinase have been the scope of diabetes research for more than a decade now –4. GlucoAn alternative way to increase hepatic glucokinase activity is to disrupt the binding between glucokinase and glucokinase regulatory protein (GKRP). GKRP is a liver-specific protein located in the nucleus that binds–and hence inactivates–glucokinase in the fasting state. In the postprandial state, glucokinase dissociates from GKRP and subsequently migrates towards the cytosolic space where it facilitates phosphorylation of glucose , 8. LloyGenetic epidemiology can be helpful to gain more insight into the clinical effects of glucokinase-GKRP disruption in humans. Since individuals are ‘randomized’ at birth to receive a wildtype allele or a variant that encodes GKRP that binds glucokinase less effectively, the effects of this variant on clinical endpoints can be studied as a surrogate for glucokinase-GKRP disruptors. Such a Mendelian randomization approach has been proven to be effective in predicting the (un)intended effects of new drugs .GCKR) ..GCKR andGCKR variant was reported, the functional variant (rs1260326) was chosen. The additive model was the preferred model of inheritance, based on previous GCKR association studies [GCKR per se, we aimed to obtain the crude outcome variables, i.e. without adjustment for potential mediators (e.g. plasma lipids levels).Data extraction was done in a two-step, standardized fashion where one researcher (P.I.H.G.S.) extracted the data, which was subsequently checked by two other researchers (N.S. and M.C.G.J.B.). The following variables were extracted from the included studies: odds ratios or unstandardized beta coefficients, with 95% confidence intervals or standard errors. Authors were contacted in case of missing data (in particular for the GWAS). In case of non-response, a reminder was sent three weeks later. When more than one  studies . FinallyTo avoid inclusion of study cohorts that were reported more than once, in particular in GWAS consortia, special attention was paid to the origin of the individual study populations. In case of overlap, the study that contained the highest number of participants was included. The quality of the study and the risk of bias were assessed by two independent researchers (P.I.H.G.S. and N.S.) according to the Newcastle-Ottawa Scale (NOS) .GCKR alleles was done as described elsewhere [Back-transformation of the log-transformed difference in eGFR between the two lsewhere . Odds raSince most studies (in particular GWAS) only reported the principal summary measures (i.e. odds ratios) instead of individualized data, it was not feasible to adjust for potential environmental effects, nor was it possible to assess Hardy-Weinberg equilibrium or linkage disequilibrium for each study.metaphor package [Sensitivity analyses were performed to assess the impact of studies that included subjects with different ancestries, studies with low quality (defined as a NOS score <5 stars), and studies that did not report crude (or age- and/or sex-adjusted) estimates. All analyses were conducted with the ‘R’ statistical software  using the  package .The electronic search identified 3,051 unique records, which eventually resulted in five studies that were used for the meta-analysis –27 see . The genGCKR effect allele–defined as the allele that predisposes to reduced fasting plasma glucose levels (similar to the effect of a glucokinase-GKRP disruptor)–was the predominant allele. The overall quality of the studies was good  (2 = 0%) [Meta-analysis demonstrated that the  = 0.01) . Heterog(2 = 0%) . Due to (2 = 0%) , 30. Sin(2 = 0%) –we condu(2 = 0%) . The sub(2 = 0%) , 34, whi(2 = 0%) . This alGCKR effect allele was significantly associated with CAD in studies that included subjects of European ancestry only (n = 3) , but not in studies that included subjects of Asian ancestry only  (2 = 88.4%). The only study that reported on cystatin C-based eGFR observed similar effect sizes, which was statistically significant in the discovery cohort (p = 0.006), but not in the replication cohort (p = 0.16) [Meta-analysis, including 195,195 individuals, showed that the  = 0.01) . Heterog = 0.16) .GCKR effect allele on CKD, albeit not statistically significant   . The for= 45.9%) . Repeat = 45.9%) . All CKDGCKR it is possible to gain more insight into the interaction between hepatic glucose metabolism and cardiorenal disease. Moreover, it allows an evaluation of small-molecule disruptors of the glucokinase-GKRP complex as a potential new glucose-lowering treatment. In three meta-analyses using data from at least ~200,000 individuals, we showed that the GCKR effect allele–which encodes a GKRP protein that binds glucokinase less effectively–appeared to be associated with CAD, whereas a protective effect was observed for eGFR.Glucokinase regulatory protein (GKRP) is a liver-specific protein that plays an important role in the regulation of hepatic glucose uptake and, consequently, de novo lipogenesis, one of the principal pathways in the development of NAFLD . By studGCKR effect allele is associated with an atherogenic lipid profile, i.e. higher plasma triglycerides and apolipoprotein B levels, reduced HDL cholesterol levels and the presence of small-dense LDL particles [GCKR on CAD in our primary analysis. If, however, one would take into account the effect of GCKR on only plasma triglycerides, it would be anticipated to already result in an odds ratio of 1.05 to develop CAD [GCKR on CAD risk. GCKR has previously been associated with reduced fasting plasma glucose levels [GCKR on eGFR could be another explanatory factor. Previous epidemiological studies have shown that CKD is an independent cardiovascular risk factor [Previous studies have shown that the articles , 43, 44.elop CAD . The smae levels . The hitk factor .GCKR and (creatinine-based) eGFR was also observed for cystatin C-based eGFR [GCKR, is actually responsible for the association with renal function [increased kidney damage [The current meta-analyses were confined to creatinine-based renal outcome measures (eGFR and CKD), since these were most frequently reported. Köttgen and colleagues showed that the positive relationship between sed eGFR . The samfunction . Howevery damage , which iGCKR effect allele has been associated with increased NAFLD risk, low HDL cholesterol levels, and higher urate levels [GCKR effect allele. Further research is needed to identify these factors as it may have important clinical implications.The mechanism by which enhanced glucokinase-GKRP disruption exerts its renoprotective effects remains to be elucidated. The e levels , 44, 48,e levels –51. ThesGCKR and type 2 diabetes on CAD risk cannot be ruled out. We previously demonstrated that the effects of the GCKR effect allele on plasma lipid levels were more pronounced in patients with type 2 diabetes when compared to healthy individuals [GCKR and type 2 diabetes on CAD risk would seriously decrease the applicability of small molecule disruptors of the glucokinase-GKRP complex as new antidiabetic drug. Unfortunately, there were too few studies that were specifically conducted in type 2 diabetes to formally investigate such an interaction in the current meta-analysis.The present study may provide a glimpse into the future of what the cardiorenal effects of small-molecule disruptors of the glucokinase-GKRP complex will be as a potential new glucose-lowering drug. Although the protective effect on eGFR and CKD appears to be promising at first sight, it may be outbalanced by an increased risk to develop CAD. Furthermore, a synergistic effect between ividuals . A similGCKR with CAD depends to a large extent on the the combined UK Biobank, CARDIoGRAMplusC4D 1000 genomes-based GWAS, and Myocardial Infarction Genetics and CARDIoGRAM Exome dataset, which is actually a meta-analysis by itself [GCKR effect allele and CAD in the primary analysis should therefore be interpreted with some caution.This study has several strengths and limitations. First, the meta-analysis of the association of y itself . In subsy itself –34. AlthGCKR variant that protects from deterioration of renal function is associated with an increased urine albumin-creatinine ratio [Second, the definition of CKD was only based on eGFR–not the presence of albuminuria–in all of the included studies. Both factors are part of the classification of CKD as defined by the Kidney Disease Improving Global Outcomes (KDIGO) . The CKDne ratio . These fGCKR and small molecule disruptors of the glucokinase-GKRP complex are truly comparable. This is one of the general limitations of the Mendelian randomization approach in which genetic variants are used as an instrument to study the effects of a specific drug of interest. However, previous experimental studies have shown that both the product of the GCKR minor allele and glucokinase-GKRP disruptors cause an increased translocation of glucokinase from the nucleus towards the cytosolic space in the liver [GCKR minor allele and treatment with glucokinase-GKRP disruptors [Third, it is not entirely clear whether the effects of genetic variants in he liver , 17.Thissruptors , 54.GCKR-diet interaction on plasma triglycerides levels [GCKR seemed to protect from CKD in one Japanese cohort [GCKR could theoretically be in linkage disequilibrium with a gene that exerts an opposing effect on cardiorenal risk in certain but not all populations. These opposing effects could have important therapeutic implications if they would be inherent to GKRP function and therefore deserve further attention.Another aspect that deserves consideration is the moderate-to-high heterogeneity that was observed in some of the meta-analyses. This could be the result of genotyping errors or difference in methodology, such as discrepancies in outcome measures (particularly for CAD) or study populations . Although ancestry did not account for the moderate-to-high heterogeneity, the number of studies was too small to make strong inferences. Furthermore, differences in diet could contribute to the observed heterogeneity given the previously reported s levels , 56. It e cohort , 41 where cohort . These oGCKR. We correctly assumed that GWAS were likely to include our variants of interest without reporting in the manuscript’s title or abstract.A final limitation was that we were forced to exclude a considerable amount of studies, and hence a substantial number of subjects, from the meta-analyses because of partial overlap of individual study cohorts. Yet, we were still able to include a high number of individuals, ranging from ~200,000 to 400,000 in the three meta-analyses, which can be attributed to our search strategy that was not confined to studies specifically reporting on GCKR effect allele is associated with a better eGFR. A disadvantageous effect on CAD risk can, however, not be ruled out. These findings question the benefits and applicability of small molecule disruptors of the glucokinase-GKRP complex as a potential new class of antidiabetic drugs. Further studies are warranted toidentify the factor that mediates the renoprotective effects of enhanced disruption of the glucokinase-GKRP complex.The present study extends our knowledge on the systemic effects of enhanced disruption of the glucokinase-GKRP complex by demonstrating that the S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.S5 Table(DOCX)Click here for additional data file.S6 Table(DOCX)Click here for additional data file.S1 Fig(DOCX)Click here for additional data file.S2 Fig(DOCX)Click here for additional data file.S3 Fig(DOCX)Click here for additional data file.S4 Fig(DOCX)Click here for additional data file.S5 Fig(DOCX)Click here for additional data file.S1 Checklist(DOCX)Click here for additional data file.


Calmodulin 1 (CALM1) gene and the risk of osteoarthritis  in different populations have yielded conflicting findings. Therefore, we conducted a meta-analysis by systematically searching PubMed, Embase, Medline, Cochrane Library and Google Scholar, and assessing this association by calculating pooled odds ratios with 95% confidence intervals. Subgroup analyses stratified by ethnicity, OA type, and genotype were also conducted. Six studies (2752 cases and 3259 controls) involving six single nucleotide polymorphisms were included. Our data suggested that the T allele and genotype TT of the rs12885713 polymorphism, and the C allele of the rs2300496 polymorphism in the CALM1 gene all increased the risk of OA. The pooled results revealed no significant association between the CALM1 rs3213718 polymorphism and the risk of OA. Stratification analyses by ethnicity and OA type showed that the rs12885713 polymorphism increased the risk of OA among Asians and in knee OA, respectively. In conclusion, the rs12885713 and rs2300496 polymorphisms of the CALM1 gene may both increase the risk of OA. Owing to the limitations of the present study, this finding should be further confirmed in future well-designed studies.The existing studies on the association between polymorphisms of  SMAD3 gene rs12901499 polymorphism increases the risk of OA among both Asians and Caucasians. Lv et al. [ADAM12 gene rs1871054 polymorphism increases knee OA risk in the Asian population, whereas other polymorphisms  in ADAM12 are not associated with knee OA in any population. Pan et al. [GDF5 gene are protective against knee OA susceptibility across different populations. Moreover, single-nucleotide polymorphisms (SNPs) in candidates, such as growth differentiation factor 5 genes, [Osteoarthritis (OA), the most common form of arthritis, can cause progressive loss of joint function . The dis5 genes,  vitamin 5 genes,  have bee2+-dependent cellular events involving an interplay among various proteins [2+-CALM signaling plays a crucial role in cartilage phenotype maintenance and chondrogenesis. CALM probably has pivotal roles in articular cartilage by maintaining the cartilage phenotype in response to mechanical stimuli in mature chondrocytes [Calmodulin (CALM) regulates many Caproteins . Ca2+-CAdrocytes ,16, regudrocytes , and modCALM1 gene, which is located on chromosome 14q32.11, and OA susceptibility. The association between CALM1 gene SNPs and OA susceptibility may provide new research directions for OA studies. However, the findings of previous studies are conflicting and inconclusive because of clinical heterogeneity, different ethnic populations, and small sample sizes. A single case–control study is underpowered and inconclusive, owing to limited sample sizes. Meta-analysis is used to combine findings based on individual research studies to yield robust conclusions, especially when results from single case–control studies are incomprehensive and conflicting. Thus, to precisely elucidate the genetic roles of CALM1 gene polymorphisms in OA development, we performed a comprehensive systematic review and meta-analysis to clarify the association between these SNPs and OA risk.To date, several studies  have expThis meta-analysis was performed in compliance with PRISMA guideline   study with sufficient genetic frequency for extraction. The exclusion criteria were as follows: (1) incomplete data; (2) review or case report; and (3) duplicate or overlapping publication. All questionable publications were discussed and addressed by consensus. Three reviewers independently screened the titles and abstracts. In cases of uncertainty regarding any of the above essential information, the full article was retrieved for further scrutiny, or the authors of the individual trials were contacted directly for further information when necessary.The inclusion criteria were as follows: (1) case–control study on humans; (2) observational study addressing OA patients and controls; (3) study evaluating the association between 2 test (http://ihg.gsf.de/cgi-bin/hw/hwa1.pl). Studies with scores ≥6 were considered high quality.From each eligible study, two reviewers (Y.H.Y and H.Z.Y) independently extracted the following data: first name of the first author, year of publication, country and ethnicity of study population, type of OA, source of controls (SOC), sample size, genotype method, names of gene polymorphisms, and genotype frequencies in cases and controls. The two reviewers (Y.H.Y and H.Z.Y) independently assessed the methodological quality of the included studies according to the Newcastle–Ottawa Scale (NOS) . The NOSCALM1 gene polymorphisms and OA susceptibility. Owing to a lack of original data for sex and age, crude ORs were calculated. Five genetic models were used: (1) allele model; (2) recessive model; (3) homozygous model; (4) heterozygous model; and (5) dominant model. P < 0.05 was considered significant. Heterogeneity across studies was assessed by using the Q statistic with its P-value and I2 statistic [I2<50% and P>0.10, a fixed effects model was used in the calculations [Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to assess the association between tatistic ,26. If Iulations ; otherwiulations . Subgrouulations . Sensitiulations . An FPRPulations ,32.https://www.ncbi.nlm.nih.gov/snp/). We also used bioinformatics databases such as Promo  and the MirSNP database (http://bioinfo.bjmu.edu.cn/mirsnp/search/) to analyze transcription factor binding sites (TFBS).Potential functions of SNPs were extracted from dbSNP  involving six SNPs were included. The year of publication ranged from 2005 to 2017. The numbers of cases and controls ranged from 183 to 920 and from 193 to 1008, respectively. Two included citations  studied itations ,22 studiitations  studied a et al. , Poulou a et al. .CALM1 gene increased OA risk . Neither Egger’s nor Begg’s tests revealed obvious publication bias for the rs12885713 polymorphism .CALM1 gene rs2300496/ rs3213718 polymorphisms and OA risk are shown in The results of pooled analysis on the association between Owing to the incomplete genotype distribution data reported by Valdes et al. , only anCALM1 gene were investigated in only one study [The rs3814843, rs2300500, and rs3179089 polymorphisms of the ne study , which rCALM1.Rs12885713 was located in TFBS. As shown in http://bioinfo.bjmu.edu.cn/mirsnp/search/), the CALM1 gene binds has-miR-497-5p when the nucleotide changes from A to C (for rs3814843). Has-miR-497-5p is a negative regulator of SMAD3 gene expression [Two SNPs (rs3814843 and rs3179089) in the 3′-UTR of CALM1 may affect binding to microRNA. According to the MirSNP database  and varying clinical parameters of different populations may also be potential reasons for the inconclusive findings. As for the conflicting findings according to the OA site, we believe that CALM1 gene rs12885713 polymorphism may be a specific variant for knee OA but not hip OA. Furthermore, the different characteristics of the OA groups (such as age and sex) and disease severity may also be possible reasons for the discrepancies. Finally, the varying environmental factors may also have contributed, because the interaction between genetic factors and environmental factors can eventually lead to the development of OA. Functional predictions indicated that the rs12885713 polymorphism may change the transcriptional efficiency of the CALM1 gene. Thus, we assumed that changes in the transcriptional function by rs12885713 polymorphism may eventually alter CALM1 protein translation, thereby increasing the risk of OA. In addition, we believe that the effect of the rs12885713 polymorphism may be subtle, because this SNPs may be in linkage disequilibrium with other variants affecting the risk of OA . Thus, further studies investigating other SNPs are urgently needed. Our meta-analysis also showed that the CALM1 gene rs2300496 polymorphism, but not the rs3213718 polymorphism, may increase the risk of OA. As for other SNPs of the CALM1 gene, the rs3814843, rs2300500, and rs3179089 polymorphisms were significantly associated with OA risk, although further replication studies are needed to confirm whether these SNPs influence the genetic risk of OA.Owing to their limited sample sizes, previous single studies may have been underpowered and thus have presented conflicting findings, especially given the diverse inheritance of the heterogeneous and complex OA etiology, different ethnicities, clinical heterogeneity, and other causes. Therefore, we conducted this meta-analysis. Our data showed that CALM1 gene rs12885713 polymorphism is a susceptibility locus for other types of OA, thus necessitating further investigation into more types of OA. Finally, five genetic models of inheritance were used; thus, type I error may have arisen through a lack of correction for multiple testing.Some limitations of this meta-analysis should be considered. First, owing to limited data, we were unable to conduct stratification analyses of other potential factors, such as age, sex, and OA onset age. Second, our results were based on unadjusted estimates of confounding factors, which might have affected the final results. Third, although funnel plots and Egger’s tests revealed no publication bias, selection bias could not be fully avoided, because only studies published in English were searched. Fourth, we were unable to assess potential gene–gene or gene–environment interactions because of the lack of relevant data. Fifth, the conclusions of some stratification analyses of the rs12885713 polymorphism should be interpreted with caution, owing to limited sample sizes. Sixth, clinical cases should be investigated in further studies to support these analytical results. Seventh, we can only infer but cannot conclude that the CALM1 gene, but not the rs3213718 polymorphism, may increase the risk of OA. Owing to the study limitations, further well-designed prospective studies with large sample sizes should be performed to confirm these findings.In conclusion, the present meta-analysis demonstrates that the rs12885713 and rs2300496 polymorphisms of the


Background: There is a continued debate and inconsistent findings in previous literature about the relationship of catechol-O-methyltransferase (COMT) and Parkinson’s disease (PD) susceptibility as well as cognitive dysfunction. To substantiate this existing gap, we comprehensively examine COMT genotype effects on the development of PD and test the hypothesis that the Met158 allele of the COMT gene is associated with cognitive dysfunction by conducting a meta-analysis review.Methods: PubMed/MEDLINE, Embase, Cochrane databases search (18/30/08) yielded 49 included studies. Data were extracted by two reviewers and included COMT genotype, publication year, diagnostic status, ancestry, the proportion of male participants, and whether genotype frequencies were consistent with Hardy–Weinberg equilibrium. Unadjusted odds ratios (ORs) were used to derive pooled estimates of PD risk overall and in subgroups defined by ethnicity, gender, and onset of disease. Moreover, the association of certain cognitive domains in PD and COMT gene type was explored. Meta-analyses were performed using random-effect models and p value–based methods. All statistical tests were two-sided. The present study was registered with PROSPERO (CRD42018087323).Results: In the current studies, we found no association between COMT Val158/108Met polymorphism and PD susceptibility. However, the gender-stratified analyses revealed marginally significant effects in heterozygote model analyses in women (P = 0.053). In addition, stratification according to onset of PD also shows significant effects of COMT Val158/108Met polymorphism on late-onset population both in recessive (P = 0.017) and allelic (P = 0.017) genetic models. For the intelligence quotient (IQ) score and Unified Parkinson Disease Rating Scale III (UPDRS III), there was no evidence for genetic association, except in subgroup analyses in Asian populations .Conclusion: The COMT Val158/108Met polymorphism is associated with the risk for PD in female or late-onset PD. Methionine/methionine carriers of Asian population performed significantly worse than the valine allele carriers in IQ score and UPDRS III. Parkinson’s disease (PD) is a common neurodegenerative disorder that leads to a syndrome that is related to neurological control of movement as well as other brain functions including cognition . Due to First and foremost, protein pathological hypothesis displays complex and distinctive pathophysiological profiles: accumulation of aberrantly processed and misfolded proteins, such as amyloid- β (Aβ), tau, α-synuclein, TAR DNA-binding protein 43 (TDP43) , and mutResearch on genetics, however, has always been hampered by inadequate sample size. Meanwhile, gene phenotypes might be better targets for exploring the etiology and pathophysiology of PD. Although the diagnosis of PD relies on the presence of motor deficits and clinical effects of dopamine therapy, this disease is closely related with non-motor symptoms and signs before the onset of the classical motor symptoms. Indeed, some evidence has suggested some of gene phenotypes are dominated by non-motor symptoms, such as cognitive impairment .Catechol-O-methyltransferase (COMT) is involved in catecholamine degradation . The ValTo systematically synthesize these disparate studies, we attempted to synthesize the evidence regarding COMT Val158/108Met polymorphism and occurrence of PD, so much as PD with cognitive disorder through meta-analytic techniques. Therefore, the present study aimed to further our understanding of the effect of the COMT Val158/108Met variant on cognition function of PD. It would also be useful to reveal the mixed findings concerning COMT and PD in GWAS correlational research.Systematic review and meta-analysis were performed using the preferred reporting items for systematic review and meta-analysis statement (PRISMA) . The proWe searched major scientific databases including but not limited to PubMed, EMBASE, the Cochrane Library, Web of Science, the WanFang databases, SinoMed databases, and the CNKI up to November 2018 with different combinations of the following words: “Parkinson Disease,” “Idiopathic Parkinson Disease,” “catechol-O-methyltransferase” or “COMT,” “rs4680,” and “cognitive,” “cognition,” “cognition disorders,” “perception,” “memory,” “executive,” “dementia,” and “attention.” The search was restricted to English and Chinese language publications. We also obtained additional articles using reference lists of articles identified in the initial searches.Qualiﬁed studies in this meta-analysis should satisfy the inclusion criteria:158/108Met polymorphism and PD susceptibility or reported the association between the COMT Val158/108Met and cognition in PD subjects regarding the association between COMT; 2) there were sufficient data of cases and controls to calculate an odd ratio (OR) with 95% conﬁdence interval (CI); 3) the genotypes distribution in the control group was consistent with Hardy–Weinberg equilibrium (HWE); 4) the study was published in the English or the Chinese language; 5) if there were numerous studies from the same population, only the latest one was entered.1) case-control studies that assessed the relationship between COMT ValStudies were excluded for the major following reasons: 1) no PD cognitive data reported; 2) sample comprised patients with 22q11 deletion syndrome (who have only one copy of the COMT gene); 3) studies of a different COMT polymorphism, or overlap of reported data between papers; 4) animal trials, review, and the studies that did not report the genotype frequencies were ruled out.Data were independently extracted by two authors according to the inclusion and exclusion criteria listed above. Disagreements were resolved through discussion with a third author. The following information from included studies was extracted: ﬁrst author, published year, country, ethnicity, sample size, average age of sample, number of male and female participants, allele frequency distribution in case and control, sample size, mean, and standard deviation for each cognitive variable by genotype group. COMT genotypes were grouped according to the presence or absence of the Val allele . The Newcastle-Ottawa Scale (NOS) was used to assess the methodological quality of each study .2 test were used to examine the heterogeneity among the studies. If P > 0.10 or I2 < 50%, the fixed-effect model was adopted. Otherwise, the random-effect model would be used. We made a prior assumption that the meta-analysis can be affected by study level variability determined by different inclusion criteria across RCTs, which is more appropriately addressed by a random-effects model over a fixed-effect model. The pooled OR was assessed by Z test and P < 0.05 level was considered as statistically significant. Sensitivity analysis was carried out by sequentially omitting one study at a time to estimate the stability of the result. Subgroup analysis was performed to assess the influence of potential moderators. Potential publication bias was estimated using Egger’s linear regression test by visual inspection of the funnel plot. All analyses were performed using Stata 12.0.The HWE with an exact test was used to evaluate normal heterogeneity of the population. Six separate analyses as the allelic, recessive, dominant, homozygous, heterozygous, and additive genetic models were conducted in the present meta-analysis. Pooled odds ratios (ORs) with 95% conﬁdence intervals (95% CIs) were used to compare the relationship between COMT polymorphism and PD risk, and standardized mean differences (SMDs) with 95% CIs were calculated for continuous variables. The omnibus (Q) tests and I158/108Met polymorphism and cognitive dysfunction in PD, whereas the other 10 , recessive , dominant , homozygous , heterozygous , and additive genetic models   Table 4.P = 0.053) in the pooled populations (P = 0.017) and allelic genetic models  , recessive , dominant , homozygous , heterozygous , and additive genetic models   Figure 5Sensitivity analysis was carried out for this meta-analysis by omitting one study at a time to assess the influence of any single study and found no significant change in the pooled ORs. The publication bias of the studies was evaluated by Egger’s test. The results of Egger’s test also suggested that the possibility of publication bias was low (data not shown).P = 0.503; I2 = 0%), and random effects analysis indicated no evidence of association  . However, a subgroup analysis comparing the Asians versus Caucasians was significant, indicating that homozygotes for the Met158 allele have higher UPDRS III scores than the Val allele carriers in Asian population . The publication bias of the studies was evaluated by Egger’s test. The results of Egger’s test also suggested that publication bias was low in Asians (P = 0.169) or Caucasians (P = 0.259).The results of Egger’s test also suggested that the possibility of publication bias was high , and random effects analysis indicated no evidence of association . The results of Egger’s test also suggested that the possibility of publication bias was low (P = 0.306). In addition, subgroup analysis by ethnicity indicated that no association was detected in Asian population or Caucasian population , and random effects analysis indicated no evidence of association .Six independent samples with 856 PD patients contributed to the meta-analysis. Combined IQ score included the National Adult Reading Test (NART) and Wechsler Adult Intelligence Scale (WAIS). There was evidence of between-study heterogeneity , although subgroup analysis by ethnicity detected that homozygotes for the Met158 allele have lower IQ scores than the Val allele carriers in Asian population . Considering that the sample size of Asians is limited, one needs to be cautious of the result and large-scale studies need to clarify the significance of the conclusion , no association with COMT Val158/108Met polymorphism was shown. Intriguingly, subgroup analyses focusing on gender and onset time demonstrated that COMT Val158/108Met polymorphism has a major impact on the female in the heterozygous genetic model and the late onset in recessive and allelic genetic models. In addition, there was also a faint association between genotype and abstract thought . We also found no evidence of significant publication bias.For the deep analysis, gender should be considered as a main factor to explore the COMT genotype with cognition in PD. However, not enough data could be obtained for accurate analysis. Sannino et al.  reported that female COMT Met carriers show reduced cortical thickness after puberty and closely correlated with cognitive functions, which indicates that there is a change of brain structure that can increase the risk of PD. These findings suggest that it is important to appreciate the genetic and gender difference in the patient population. In the context of COMT Val158/108Met polymorphism, female PD patients should be assessed for cognitive function alone in future studies.via estrogen receptor function . After further analysis on these two studies, we found that the levodopa dose was lower in subjects with Met/Met genotype than Val/Val group. However, in other studies, almost all PD patients with Met/Met genotype took more LODA. Given the change in the results before and after inclusion, LODA dose was a major factor and concern. It was reported that the relationship between prefrontal function and dopamine levels follows an inverted U-shaped curve Figure 7The Val158/108Met polymorphism remains a plausible candidate that may contribute to cognitive function deficits in PD. Although the results do not meet our expectations, it does not negate the need for scientific rigor in both the analysis and the reporting of results. At the very least, we cannot exclude the possibility that COMT genotype has a small influence on cognitive phenotypes and PD susceptibility in women. These results are partly in agreement with the previous meta-analysis, which reported that there is a significant association between COMT rs4680 and the risk for PD in the total series, as well as homozygosity for the low-activity allele in the Asiatic population . In addiThere are several potential limitations in the present meta-analysis. First, there is marginal significance among female PD patients, which encourages us; further research on the association of gender of PD and COMT Val158/108Met polymorphism should be carried out. Second, sample size limited our ability to investigate the accuracy of association of COMT Val158/108Met polymorphism and cognitive dysfunctions in PD. Additionally, limited data were obtained to explore the COMT genotype and cognition in early or late onset of PD. Due to the uneven nature of population genotype frequencies in different ethnic groups, the association of COMT Val158/108Met polymorphism and cognitive dysfunctions in PD needs further confirmation. The cognition scale indicators were multitudinous, and we were underpowered to test the combined effect in the current sample. Lastly, more studies are desirable in COMT polymorphism studies; also, the type and dose of anti-PD drug should be included specifically.Our findings highlight the impact that COMT genetic factors can have on the susceptibility of PD and cognitive performance, specifically differences in female, late-onset PD patients, and IQ.In summary, the results of our meta-analysis indicated that the COMT Val158/108Met polymorphism may be associated with the risk for PD in female or late-onset PD. Meanwhile, Met/Met carriers of Asian population performed significantly worse than the Val allele carriers in IQ score and UPDRS III. Considering the above potential limitation, these conclusions need to be further confirmed in future research.All authors listed have made substantial, direct, and intellectual contribution to the work and approved it for publication.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.


Randomized controlled trials (RCTs) suggest that supplementation with omega-3 polyunsaturated fatty acids (n-3PUFAs) may favourably modify cardiometabolic biomarkers in type 2 diabetes (T2DM). Previous meta-analyses are limited by insufficient sample sizes and omission of meta-regression techniques, and a large number of RCTs have subsequently been published since the last comprehensive meta-analysis. Updated information regarding the impact of dosage, duration or an interaction between these two factors is therefore warranted. The objective was to comprehensively assess the effect of n-3PUFAs supplementation on cardiometabolic biomarkers including lipid profiles, inflammatory parameters, blood pressure, and indices of glycaemic control, in people with T2DM, and identify whether treatment dosage, duration or an interaction thereof modify these effects.Databases including PubMed and MEDLINE were searched until 13th July 2017 for RCTs investigating the effect of n-3PUFAs supplementation on lipid profiles, inflammatory parameters, blood pressure, and indices of glycaemic control. Data were pooled using random-effects meta-analysis and presented as standardised mean difference (Hedges g) with 95% confidence intervals (95% CI). Meta-regression analysis was performed to investigate the effects of duration of supplementation and total dosage of n-3PUFAs as moderator variables where appropriate.A total of 45 RCTs were identified, involving 2674 people with T2DM. n-3PUFAs supplementation was associated with significant reductions in LDL , VLDL ; p = 0.044], triglycerides ; p = 0.010]. Moreover, n-3PUFAs supplementation was associated with reduction in plasma levels of TNF-α  and IL-6 ; p = 0.026]. All other lipid markers, indices of glycaemic control, inflammatory parameters, and blood pressure remained unchanged (p > 0.05).n-3PUFAs supplementation produces favourable hypolipidemic effects, a reduction in pro-inflammatory cytokine levels and improvement in glycaemia. Neither duration nor dosage appear to explain the observed heterogeneity in response to n-3PUFAs.Trial registration This trial was registered at http://www.crd.york.ac.uk as CRD42016050802The online version of this article (10.1186/s12933-018-0740-x) contains supplementary material, which is available to authorized users. Cardiovascular disease (CVD) is the leading cause of morbidity and mortality in people with type 2 diabetes (T2DM) . While tSuch risk factors are highly amenable to dietary modification , and dieWhilst several meta-analyses have been performed in T2DM, variable degrees of benefit on these biomarkers have been reported –21. SignA primary goal of diabetes management is to establish effective adjunct treatments which act to reduce CVD risk . InformaThis meta-analysis was conducted in accordance with PRISMA  guidelines  and prosTwo reviewers (LLO and JM) independently reviewed all RCTs by title and abstract and subsequently by full text evaluation. Discrepancies which arose during this process were resolved by a third reviewer (KD). RCTs  comparing the effects of n-3PUFAs with placebo control on outcomes of interest amongst adults with T2DM were included in the meta-analysis. All n-3PUFA interventions were in diet or capsule form and included if the dosage and duration could be determined. When RCTs assessed the effects of n-3PUFAs in conjunction with other nutrients or interventions, data were extracted from arms assessing n-3PUFA and placebo only. RCTs conducted in animal models, other forms of diabetes , or in people under 18 years of age were excluded , fasting insulin (pmol L−1), HOMA-IR, C-peptide (nmol L−1), triglycerides (mmol L−1), total cholesterol (mmol L−1), high density lipoprotein (HDL) (mmol L−1), LDL (mmol L−1), very low density lipoprotein cholesterol (VLDL-C) (mmol L−1), very low density lipoprotein triglycerides (VLDL-TG) (mmol L−1), apolipoprotein-A1 (g L−1), apolipoprotein-B (g L−1), non-esterified fatty acids (NEFA) (mmol L−1/ng mL−1), C-reactive protein (CRP) (nmol L−1), tumour necrosis factor alpha (TNF-α) (pg mL−1), interleukin 6 (IL-6) (pg mL−1), systolic blood pressure (SBP) (mmHg), and diastolic blood pressure (DBP) (mmHg). When values were presented in figure form only, the figure was digitized using graph digitizer software  and the means and SD/SEM were measured manually at the pixel level to the scale provided.Data extraction was conducted independently by two authors (LLO and MDC) with discrepancies adjudicated by a third author (KD). Data were extracted into a standardised spreadsheet, which included (i) trial information ; (ii) trial characteristics ; (iii) participant characteristics , and (iv) intervention specifics . Additionally, pre- and post-intervention mean and SD values were extracted, for: HbA1c , fasting plasma glucose (FPG) (mmol LTwo independent reviewers (LLO and MDC) assessed the risk of bias in included trials using The Cochrane Collaboration’s tool for assessing risk of bias . Each RCr = 0.90, fasted plasma glucose r = 0.62, fasted insulin r = 0.41, HOMA-IR r = 0.72, C-peptide r = 0.90, triglycerides r = 0.79, total cholesterol r = 0.90, HDL r = 0.60, LDL r = 0.89, VLDL-C r = 0.72, VLDL-TG r = 0.72, apolipoprotein-A1 r = 0.72, apolipoprotein-B r = 0.18, NEFA r = 0.30, CRP r = 0.81, TNF-α r = 0.94, IL-6 r = 0.90, SBP r = 0.80, DBP r = 0.80.If not reported, standard deviations were calculated from standard errors, confidence intervals (CI), or interquartile ranges . Outcome2 statistic, where 0–20% suggests heterogeneity may be trivial, 20–50% represents low heterogeneity, 50–75% represent moderate heterogeneity, and 75% and above represents high heterogeneity [SMD values of < 0.20 were interpreted as trivial, 0.20–0.39 as small, 0.40–0.80 as moderate and > 0.80 as large . A negatogeneity . This meogeneity . This anIn total 5662 titles were found through database searches, of these 45 RCTs were eligible and included in the quantitative synthesis and meta-analysis Fig. . A totaltrivial decrease in LDL . There was a small significant decrease in triglycerides following n-3PUFA supplementation . n-3PUFAs were associated with a small significant decrease in VLDL-C . Sensitivity analysis, performed to determine the independent effect of each trial on the overall effect size, revealed the independent removal of four single comparisons moderated the statistical interpretation of VLDL-C from significant to non-significant. There was a significant moderate reduction in VLDL-TG following n-3PUFA supplementation . The statistical interpretation of VLDL was changed from significant to non-significant by the independent removal of two RCTs. HDL , total cholesterol , NEFA , apolipoprotein-A1 , and apolipoprotein-B  did not change significantly following n-3PUFA supplementation. Sensitivity analysis revealed that for HDL, the exclusion of three single comparisons in turn moderated the statistical interpretation of the results from non-significant to significant, resulting in a favourable increase in HDL following n-3PUFA supplementation compared to placebo.Supplementation with n-3PUFAs resulted in a moderate reduction in TNF-α following n-3PUFA supplementation . Sensitivity analysis for TNF-α revealed the removal of three single comparisons in turn moderated the statistical interpretation of the results from significant to non-significant. IL-6 was seen to decrease with a large ES . Sensitivity analysis for IL-6 revealed that the independent removal of one RCT moderated the statistical interpretation of the results from significant to non-significant. CRP did not change significantly with n-3PUFAs , sensitivity analysis revealed that the removal of one comparison changed the results from non-significant to significant. n-3PUFAs had no significant effect on SBP  or DBP .There was a significant small yet significant reduction in HbA1c following n-3PUFA supplementation , the degree of heterogeneity was high between included RCTs , fasting insulin , HOMA-IR , C-peptide .There was a Meta-regressions were performed for significant outcomes with more than 10 RCTs; neither duration of supplementation nor dosage of n-3PUFAs statistically explained heterogeneity (i.e. variation in effect sizes) observed in these analyses (Table p = 0.32), LDL , TNF-α , and HbA1c . There was evidence of small study effects for VLDL-C , VLDL-TG , and IL-6 .Inspection of the funnel plots . n-3PUFA intake has long been indicated in the treatment of hypertriglyceridemia , 31, proPrevious research has highlighted, the magnitude of change in LDL is potentially dependent upon baseline triglyceride levels and may also differ between purified eicosapentaenoic acid (EPA)/docosahexaenoic acid (DHA) treatments and combined preparations . We did This is the first meta-analysis to show significant improvements in the inflammatory cytokines TNF-α and IL-6 in people with T2DM in response to n-3PUFA intake. Low grade inflammation is a pathologic mediator of vascular complications in T2DM , and theOverall, we observed a small reduction in HbA1c following n-3PUFA supplementation. Earlier work has indicated that n-3PUFAs may result in adverse effects on HbA1c in patients with T2DM, from which increased basal hepatic glucose output and impaired insulin secretion are postulated to be responsible . Our finThis meta-analysis and meta-regression provides the most comprehensive and contemporary review to date, assessing 19 cardiometabolic biomarkers, and including 45 RCTs—21 more than the largest aggregate data meta-analysis on this topic, and assessed whether treatment dosage, duration or an interaction thereof modify effects. By adopting a random-effects approach over fixed-effects to account for the true variation in effect size from trial to trial , and empOur study reports a major new indication for n-3PUFA intake: improvement in lipid profile and markers of inflammation without adverse effects on LDL or HbA1c. Neither duration of supplementation nor dosage of n-3PUFAs statistically explain the observed heterogeneity meaning that optimal treatment patterns for clinical practice are yet to be determined and further research is warranted. Future precision medicine trials should aim to establish whether interactions between n-3PUFAs and cardiometabolic biomarkers are modified by patient level characteristics to improve response to supplementation in T2DM and whether such improvements are observed in T1DM.Additional file 1: Table S1. Predetermined search terms and strategy. Table S2. The effect of n-3 PUFAs on indices of glycaemic control. Table S3. The effect of n-3 PUFAs on lipid profiles. Table S4. The effect of n-3 PUFAs on Inflammatory parameters, and blood pressure. Table S5. The effect of n-3 PUFAs on apolipoproteins and non-esterified fatty acids. Table S6. Inclusion/exclusion criteria. Table S7. Primary outcome of included studies. Figure S1. Risk of bias across expressed as a percentage across all included studies. Figure S2. Risk of bias figure. Figure S3 A-G. Funnel plot of standard error by standard difference in means for LDL (A), TG (B), VLDL-C (C), VLDL-TG (D), TNF-α (E), IL-6 (F), and HbA1c (G). LDL, low density lipoprotein cholesterol; TG, triglycerides; VLDL-C, very low density lipoprotein cholesterol; VLDL-TG, very low density lipoprotein triglycerides; TNF-α, tumour necrosis factor alpha; IL-6, Interleukin 6; HbA1c, glycated haemoglobin.


Several papers studied dietary protein intake as a potential influence factor for esophageal cancer, but their findings were inconsistent. Thus, this meta-analysis was performed to identify the effect of protein intake on esophageal cancer risk. Potential case–control studies or cohort studies from the databases of Embase, Web of Science and PubMed were searched. The strength of association was quantified by pooling odds ratio (OR) and 95% confidence interval (CI). In total, 11 articles involving 2537 cases and 11432 participants were included in this meta-analysis. As a result, dietary protein intake had non-significant association on esophageal cancer risk overall . Meanwhile, we obtained consistent results in the subgroups analyses by study design, protein type, geographic locations and number of cases. Interestingly, dietary protein intake could significantly increase the risk of esophageal squamous cell carcinoma , instead of other disease type. To sum up, dietary protein intake had no significant association with esophageal cancer risk in the overall analysis; but, protein intake may be associated with the risk of esophageal squamous cell carcinoma. While some limitations existed in the present paper, more studies with large sample size are warranted to further confirm this result. Esophageal cancer is considered as the eighth most common cancer worldwide . It was Two reviewers systematically and independently searched Embase, Web of Science and PubMed to find potential studies without any restriction. The search time was from beginning to 31 July 2019. The keywords included ‘dietary’ AND ‘protein’ AND . The search strategy for computerized literature search conducted in PubMed is listed in Supplementary Table S1. References of identified studies were manually screened to search any omitted articles. The inclusion criteria were (1) case–control studies or cohort studies; (2) having available odd ratios (ORs) and its 95% confidence intervals (CIs) or enough data for calculating them; (3) evaluation of the relationship about protein intake and esophageal cancer risk; (4) human studies. All papers were searched if they met our inclusion criteria no matter full-text available or not.The quality assessment was using the Newcastle–Ottawa Scale (NOS) . Based oP<0.10 or 2I > 50% [P<0.05.Statistical analysis was conducted by Stata 12.0 . Pooled ORs with their 95% CIs was calculated using the independent OR and its 95% CI in each individual study . StratifI2 > 50% . A randoI2 > 50%  and sensI2 > 50%  and asseI2 > 50% . StatistThe initial search returned 1039 articles from the above-mentioned databases. One additional record was identified from the reference of a review. Then 408 duplicated articles from different databases were excluded, and 593 articles were omitted after title and abstract examination. Of the remaining 39 articles, full texts were reviewed. Twenty-eight articles were further excluded due to the reason present in In our included articles, four texts  , Mayne eI2 = 67.0%, for heterogeneityP<0.001)  .Hierarchical analyses by study design, protein type , geographic locations  and number of cases were performed; the association was not significant in all the subgroups. Interestingly, dietary protein intake could significantly increase the risk of esophageal squamous cell carcinoma , instead of other disease types, when we performed the analysis between dietary protein intake and disease type . The detP=0.429) found any significant publication bias.Sensitivity analyses detected that no single study largely affected the overall data, indicating our results are statistically stable (data are shown in Supplementary Table S3). Neither Begg’s funnel plot  nor EggeOur study showed that no significant relationship was found between protein intake and esophageal cancer risk in the overall analysis, as well as in the subgroup analyses by study design, protein type, geographic locations and number of cases. However, stratified analysis of disease type showed that protein intake may be a risk factor on the development of esophageal squamous cell carcinoma, instead of esophageal adenocarcinoma.Protein is involved in the organization of human tissues. Meanwhile, it is vital for our body’s growth and development, as well as the transport of some essential substances and the provision of bioenergy ,38. HoweIn a previous meta-analysis published by Mao et al. , dietaryI2 = 67.0%, for heterogeneityP<0.001) was found in the overall results. As introduced in the ‘Methods’ section, we then used meta-regression to explore the causes of heterogeneity by the covariates of disease type, protein type, study design, geographic locations and assessment of intake. We did not find any covariates which caused this high between-study heterogeneity. Subgroup analyses were performed and the between-study heterogeneity also existed in some subgroup analyses. However, sensitivity analysis showed that no single study largely affected the overall data. Therefore, our results, in whole or in subgroup analyses, were stable.Significant between-study heterogeneity  ) met theIn conclusion, dietary protein intake had no significant association on esophageal cancer risk in the overall analysis; but, protein intake may be associated with the risk of esophageal squamous cell carcinoma. While some limitations exited in the present paper, more studies with large sample size are warranted to further confirm this result.Click here for additional data file.


Chronic kidney disease (CKD) is defined by abnormalities in kidney structure and/or function present for more than 3 months. Worldwide, both the incidence and prevalence rates of CKD are increasing. The renin-angiotensin-aldosterone system (RAAS) regulates fluid and electrolyte balance through the kidney. RAAS activation is associated with hypertension, which is directly implicated in causation and progression of CKD. RAAS blockade, using drugs targeting individual RAAS mediators and receptors, has proven to be renoprotective.ACE, ACE2, AGT, AGTR1, AGTR2 and REN, for association with CKD.To assess genomic variants present within RAAS genes, A systematic review and meta-analysis of observational research was performed to evaluate the RAAS gene polymorphisms in CKD using both PubMed and Web of Science databases with publication date between the inception of each database and 31 December 2018. Eligible articles included case–control studies of a defined kidney disease and included genotype counts.Any paper was removed from the analysis if it was not written in English or Spanish, was a non-human study, was a paediatric study, was not a case–control study, did not have a renal disease phenotype, did not include data for the genes, was a gene expression-based study or had a pharmaceutical drug focus.ACE insertion, AGT rs699-T allele and AGTR1 rs5186-A allele; each variant was associated with a reduced risk of CKD development.A total of 3531 studies were identified, 114 of which met the inclusion criteria. Genetic variants reported in at least three independent publications for populations with the same ethnicity were determined and quantitative analyses performed. Three variants returned significant results in populations with different ethnicities at p<0.05: Further biological pathway and functional analyses of the RAAS gene polymorphisms will help define how variation in components of the RAAS pathway contributes to CKD. Individuals with microalbuminuria were excluded from both the case and control definitions to improve the discrimination between individuals with and without renal disease as microalbuminuria may regress, remain stable or progress to macroalbuminuria.Due to previously reported heterogeneity between different ethnic groups, we included this as a risk factor and performed each analysis per ethnicity.Some studies in our search could not be included in quantitative analysis as they lacked information relating to genotype counts and had an unclear measure and definition of albuminuria for both cases and controls.2, or the presence of persistent urinary abnormalities including albuminuria and/or structural alterations which have been present for at least 3 months.Chronic kidney disease (CKD) is defined as a progressive loss of renal function measured as a reduction in glomerular filtration rate (GFR) to <60 mL/min/1.73 mACE) cleaves angiotensin I to generate angiotensin II, which regulates heart and kidney function by binding to and activating angiotensin II receptors (type I and type II).The renin-angiotensin-aldosterone system (RAAS) is a homeostatic endocrine system which is of critical importance to the regulation of blood pressure and maintenance of fluid and electrolyte balance.ACE, ACE2, AGT, angiotensin II receptor type 1 (AGTR1), angiotensin II receptor type 2 (AGTR2) and renin (REN), as candidate genes for various CKD-related phenotypes. Multiple studies have implicated RAAS gene variants in the progression of CKD.Increased RAAS activation is linked to progression of CKD of different aetiologies, especially diabetic nephropathy (DN),ACE, ACE2, AGT, AGTR1, AGTR2 and REN, for a range of CKD phenotypes and ethnicities, to help define their putative roles as risk factors for CKD.This manuscript describes a systematic review and meta-analysis to examine published data reporting genetic variants present within six of the RAAS candidate genes: A systematic search was undertaken following recognised methods, the Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines,10.1136/bmjopen-2018-026777.supp1Supplementary dataThe general strategy of the searches was to follow the structure:  AND  AND . For each search term, where an appropriate Medical Subject Headings (MeSH) term was available, the query included the quoted search term OR the MeSH term. Additional filters including English OR Spanish languages, human studies, case–control studies, not clinical trials, not review articles, not a case report and not a meta-analysis were applied.Reference lists from included publications were also manually searched. Two authors (LJS and MCG) independently conducted the literature search, screened the articles and extracted the data. In the case of any disagreement, a third author (RCC) considered the articles. A range of CKD phenotypes were included in this analysis, the case and control definitions are included in Inclusion criteria were judged against a standardised list of agreed criteria , where the English or Spanish language publication described an adult, human case–control study of a defined kidney disease. In the rare instances when suspected duplicate data were identified within two or more included articles, only the article either published first, or that with the larger number of participants was included.Articles were excluded if they included paediatric subjects, were a pharmacological-based study reporting clinical trials of medications, did not contain genotypic data for the correct gene or were non-human studies.Where available, the size of each study, case group disease definition and number of individuals, control group definition and number of individuals, ethnicity, genetic variant, genotype in the format of allele 1–heterozygote–allele 2 and allele counts were recorded and calculated in spreadsheets by two authors (LJS and MCG). Articles were reassessed where any disagreement occurred and a third reviewer was employed. Ethnicities were recorded from the articles and recoded following the International Genome Sample Resources’ online guidance.2 statistic.Each genetic variant which had been investigated and reported in at least three independent publications for the same ethnicity and phenotype was included in quantitative statistical analyses. Review Manager (RevMan V.5.3)  was employed to facilitate the analysis of allele frequencies. For each single nucleotide polymorphism (SNP), the total number of alleles was recorded per case and control group. Hardy-Weinberg equilibrium was calculated for all included studies, for cases and controls separately. Statistical analyses were performed using the random-effects model as heterogeneity was expected. For each SNP, this analysis provided the p value, OR and 95% CIs. It also facilitated the assessment of the heterogeneity level using the IThe genotyping quality of the studies was assessed by reported genotype completion rate and Hardy-Weinberg equilibrium. Phenotypes included in this analysis are shown in Neither patients nor the public were directly involved in the design of this study, which analysed previously published data available in the public domain.The database searches returned 3531 results, 144 of which remained following the application of inclusion and exclusion criteria and the removal of any SNP which was not reported on at least three occasions. Several articles included data for more than one gene, signifying that they have emerged multiple times throughout the database searches; the total number of individual articles was therefore 114. The search strategies are included as online 10.1136/bmjopen-2018-026777.supp2Supplementary dataACE2, AGTR2 and REN, there were less than three independent populations studied. A summary table detailing the main results is included as The total number of subjects analysed within these studies (n=114) was 18 231 individuals with renal disease and 21 887 individuals acting as controls. For SNPs in three of the RAAS genes, ACE in eight phenotypes, details of which are included in online 2=55%, showing that the presence of the insertion variant at this ACE locus was significantly associated with this phenotype. The insertion provides a lower risk of developing T2DN in an East Asian population as demonstrated in five studies, which contributed to 51.5% of the weight in this analysis. A total of 15 quantitative analyses were completed for the insertion/deletion (I/D) polymorphism located within ACE insertion variant was similarly significantly associated with a lower risk of T2DN compared with T2DM in a South Asian population, despite the presence of a high level of heterogeneity . This was consistent with the direction of effect in four studies, which contributed to 67.7% of the weight in this analysis . Four studies, supporting 69.7% of the weight in the analysis had shown this effect (figure 2e). Figure 2f shows the associated funnel plot for this analysis.The comparison of East Asian individuals with end-stage renal disease (ESRD) compared to a healthy population with no evidence of renal disease also showed a significant association with moderate levels of heterogeneity , the presence of the 2=0%) and are shown in Seven quantitative analyses were completed for rs699, where the T allele was compared with the C allele. Details of each of these comparisons are included in online AGTR1 rs5186, comparing the A allele with the C. Details of these comparisons are included within online 2=37%). This result resembled the findings of two of the three studies which contributed 87% of the weight in the meta-analysis, as shown in Four quantitative analyses were performed for Studies not complying with Hardy-Weinberg equilibrium are shown in online 10.1136/bmjopen-2018-026777.supp3Supplementary dataInvestigations into RAAS genetic variants previously reported to have been associated with a range of CKD phenotypes were undertaken. A total of 3531 studies were identified, 114 of which met the inclusion criteria. Subsequently, 26 quantitative analyses were completed for three RAAS genes where there were at least three independent population studies of the RAAS gene variants. Five significant results within three genes were obtained at the significance level p<0.05, each revealing an association with CKD.ACE is encoded by DCP1 and is a key component of the RAAS. It catalyses the modification of angiotensin I to II, which is more biologically active.ACE is the most frequently studied gene of the RAAS.ACE and DN has been rigorously investigated,ACE insertion was associated with protection from development of DN in Asians and Caucasians. A second meta-analysis undertaken in 2012 also identified an association between the ACE I/D polymorphism and the development of DN to ESRD, in that the presence of the deletion was associated with ESRD susceptibility.Since 1994, the association of ACE, which comprised 15 265 individuals with CKD and 18 474 individuals as controls from 98 population groups, we identified three significant associations of the ACE I/D polymorphism with CKD. Due to previously reported heterogeneity between different ethnic groups,In our meta-analysis of ACE insertion in the development of DN . This result was mimicked in the comparison of individuals with ESRD, which was not caused by DN, and healthy control individuals in an East Asian population (p=0.008). The ACE I/D polymorphism remains a well-characterised genetic locus associated with the progression of DN.First, comparisons between T2DN and T2DM in East Asian and South Asian populations returned significant results highlighting a protective effect of the AGT encodes the AGT glycoprotein, which is created in the liver and facilitates the creation of angiotensin I.AGT gene variants and their association with risk of CKD.AGT rs699 and its association with ESRD.In European and Middle Eastern populations, the allele distribution of rs699 was very similar to the comparison of T2DN versus T2DM, yet different from the East Asian population. This may have had an impact on the results, potentially limiting the robustness of association analyses across ethnicities.AGTR1 gene has been shown to be involved in the regulation of blood pressure, fluid and electrolyte balance.The AGTR1 and diseases including coronary artery disease,Previous studies have identified associations between rs5186 in AGTR1 variants included 3197 individuals with renal disease and 3720 controls investigating rs5186. One significant result was identified: that the presence of an A allele at this locus provided a lower risk of developing T2DN in a South Asian population (p=0.001).This meta-analysis of One meta-analysis published in 2014ACE2, AGTR2 and REN, have not been researched as extensively as ACE, AGT and AGTR1 for associations with renal disease. Very few articles were identified describing genetic association studies for these genes at the data extraction stage of the analysis, and those that were removed prior to the quantitative analysis stage, mainly due to the inclusion of paediatric individuals or non-human approaches, as outlined in online ACE2, AGTR2 and REN genes and their polymorphisms should be undertaken to elucidate their role in CKD and ESRD.The three remaining RAAS genes included in this meta-analysis, Some studies in our search could not be included in quantitative analysis as they lacked information relating to genotype counts and had an unclear measure and definition of albuminuria for both cases and controls, which could constitute a limitation. Results from genome-wide association studies would have strengthened the analysis, but unfortunately they usually only report significant SNPs. Absolute frequencies are not usually reported at individual SNP level for such large-scale studies. Publication bias was reported in two of our quantitative analyses, but was not found in the analyses which provided our significant results. Lack of clarity in phenotype definitions, along with unclear descriptions of ethnicities, inherently challenge the use of meta-analyses of different populations as a valid instrument to uncover robust associations. CKD itself has a range of causes including glomerular damage and declining estimated GFR without albuminuria. Other confounding factors such as hypertension and cardiovascular disease, and a lack of prospective follow-up of included individuals, which would ensure phenotypes are robust and stable, may also cause conflicting results.ACE I/D polymorphism was a protection factor for the development of DN in individuals with type 2 diabetes mellitus from both East and South Asian origin, and for ESRD in an East Asian population. In Europeans, the T allele of the AGT rs699 conferred a lower risk of ESRD development in healthy population. The A allele in AGTR1 rs5186 acted as a protection factor for renal disease development in South Asian population.This meta-analysis of the RAAS pathway genes and their association with renal disease has provided evidence for five significant associations with individually small effect sizes that may cumulatively contribute to dysfunction of the RAAS pathway leading to kidney disease. The insertion in Further study into the specific ethnicities and investigations into a broader range of RAAS-linked genes, or a deeper analysis of them including investigations of more variants, may pinpoint the molecular basis underlying the role of pathway in kidney disease. Network analysis and functional studies enlightening the mechanisms involved ultimately will be required to complete the picture of RAAS variation in renal traits.


Whether the risk of gastric cancer varies by the types of meat consumption still remains disputable. The purpose of this meta-analysis was to identify the exact associations that red, processed, and white meat have with gastric cancer. We searched relevant studies in Medline, EMBASE, and the Cochrane Library before November 2018, including cohort and case-control studies. We used random-effect models to estimate the adjusted relative risk (RR), and Egger’s tests to evaluate publication bias. Through stepwise screening, 43 studies were included in this analysis . In a meta-analysis for the highest versus lowest categories of meat consumption, both red : 1.21–1.66) and processed  meat consumption were positively associated with gastric cancer risk, while white meat consumption was negatively associated with gastric cancer risk . In a dose–response meta-analysis, the RRs of gastric cancer were 1.26 (95% CI: 1.11–1.42) for every 100 g/day increment in red meat consumption, 1.72 (95% CI: 1.36–2.18) for every 50 g/day increment in processed meat consumption, and 0.86 (95% CI: 0.64–1.15) for every 100 g/day increment in white meat consumption. The increase of white meat consumption may reduce the risk of gastric cancer, while red or processed meat may increase the risk of gastric cancer. Further studies are required to identify these associations, especially between white meat and gastric cancer. For over 50 years, the incidence of gastric cancer has declined worldwide . GastricAs the etiology of gastric cancer is multifaceted, diverse risk factors concerned with gastric cancer were discovered. Among them, dietary habits have long been considered an important factor in the risk of gastric cancer . Among vNevertheless, the precise contributions of red and processed meat on gastric cancer are still in dispute. The Continuous Update Project (CUP) on gastric cancer which was published in 2016 and based on the stomach cancer section of the Second Expert Report by the World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) disclosed that there is strong evidence that high processed meat intake enhances the risk of gastric non-cardia cancer . FurtherHelicobacter pylori (H. pylori) infection, which is one of the strongest risk factors for gastric cancer, as a confounder. Therefore, this systematic review and updated meta-analysis was conducted to identify the exact association that red, processed, and white meat have with gastric cancer.Moreover, although previous meta-analyses were carried out to investigate the associations between red or processed meat and stomach cancer ,9, thereWe followed Preferred Reporting Items for Systematic Reviews and Meta-analyses PRISMA,  10] and and10] aAn online literature search was conducted in MEDLINE (PubMed), EMBASE, and the Cochrane Library until 10 November, 2018, by two independent investigators (SRK and KK). The detailed search terms and words are shown in the Consistent with WCRF/AICR, we defined red meat as beef, pork, lamb, and goat; processed meat as meat preserved by smoking, salting, curing, or meat adding chemical preservatives . Given nTo be included in this meta-analysis, studies had to be case-control or cohort studies that investigated the associations between meat intake  and gastric cancer risk. Additional inclusion criteria are as follows: (1) articles with information on red, processed, and white meat consumption based on WCRF/AICR criteria, (2) outcome of the study of gastric cancer, (3) reporting odds, hazard ratio  or relative risk (RR) for outcome. If population data were duplicated on several studies, the study with larger sample sizes or longer follow-up period was included in this meta-analysis. Articles were excluded if they met the following exclusion criteria: (1) no data on red, processed, or white meat based on WCRF/AICR criteria, (2) no data on incidence of gastric cancer, (3) letter, review, correspondence or commentary, (4) articles which didn’t include OR, HR, or RR for gastric cancer.Two investigators (SRK and KK) independently extracted the following information: last name of the author, study year, country, study design, follow-up duration, number of gastric cancer incidences, sample size, type of meat intake, amount of meat consumption of each category including highest and lowest intake, adjusted ORs or RRs with the corresponding 95% confidence interval (CI), and adjustment variables.Quality evaluation of non-randomized studies, such as cohort studies and case-control studies, is essential for the accurate interpretation of non-randomized studies’ results in a meta-analysis. Low quality studies might distort the results of a meta-analysis. The Newcastle-Ottawa Scale (NOS) is a widely used quality assessment tool, and it assesses the quality of cohort and case-control studies based on their design and contents. The detailed assessment items are suggested in the According to the NOS, we evaluated the study quality on a 9-star system . In addiGiven the generally low incidence of gastric cancer, we assumed that the OR in case-control studies was equal to RR or HR, because OR may approximate the incidence rate ratio (IRR), RR, and HR under the rare disease assumption . We alsoA dose–response meta-analysis was performed to identify the association among estimates for different dose levels using generalized least-squares trend (GLST) estimation analysis which was established by Greenland and Longnecker . This apH. pylori adjustment).Subgroup analysis was also executed by the following various factors: study design , sex, geographic region , anatomical subtype (cardia and non-cardia), histological subtype  and diffuse (undifferentiated)), quality score , and study adjustment , smoking, alcohol drinking, vegetable intake, fruit intake, salt intake, socioeconomic status , and 2 statistics [p value for heterogeneity was <0.1 or I2 was >50%, the studies were considered as heterogeneous. We presented estimates computed by the random effects model for all analyses for consistency regardless of the level of heterogeneity [The heterogeneity across studies was evaluated by Q and Higgin’s Iatistics . If the ogeneity .p value of two tests was <0.1. Statistical analyses were executed using STATA version 13.0 .Publication bias was assessed using Begg’s rank correlation test and Egger’s test ,20. As tp < 0.001; I2, 69.6%). According to the p = 0.022) and Egger’s test (p = 0.076).A total of 5 cohort studies and 19 case-control studies with 9726 cases were included to identify the association between red meat intake and the risk of gastric cancer. H. pylori .A subgroup analysis for red meat was conducted to investigate study heterogeneity, and the results are presented in p < 0.001; I2, 70.3%). According to p = 0.472) and Egger’s test (p = 0.315).A total of 4 cohort studies and 13 case-control studies were included for the dose–response meta-analysis of red meat consumption and gastric cancer risk. As shown in Subgroup analysis for red meat was performed to investigate study heterogeneity, and the results are presented on p < 0.001; I2, 55.5%). As shown in p = 0.556) and Egger’s test (p = 0.448).A total of 8 cohort studies and 20 case-control studies with 10,645 cases were involved to examine the association between processed meat consumption and gastric cancer. According to H. pylori infection model .p < 0.001; I2, 72.1%). According to p = 0.086) and Egger’s test (p = 0.039).A total of 7 cohort studies and 11 case-control studies were included for the dose–response meta-analysis of processed meat consumption and gastric cancer risk. As shown in A subgroup analysis for processed meat was conducted to investigate study heterogeneity, and the results are presented on p = 0.023; I2, 41.9%) and no publication bias both on Begg’s test (p = 0.131) and Egger’s test (p = 0.116), according to A total of 5 cohort studies and 14 case-control studies with 9896 cases were included to investigate the relationship between white meat intake and gastric cancer, and RRs were reported in H. pylori.In the subgroup analysis , a negatp = 0.010; I2, 52.8%). According to p = 0.208), but was detected on Egger’s test (p = 0.096).Four cohort studies and eight case-control studies were included for the dose–response meta-analysis of white meat consumption and gastric cancer risk. As shown in Subgroup analyses for white meat were performed to investigate study heterogeneity, and the results are presented on In a comprehensive and updated meta-analysis, we found that high consumption of red and processed meat was significantly associated with an increased risk of gastric cancer , while that of white meat was significantly associated with a decreased risk of gastric cancer (20% decreased risk). These results and trends were consistent with those of dose–response meta-analyses (26% increased risk for every 100 g/day increase consumption in red meat and 72% increased risk for every 50 g/day increase consumption in processed meat). Generally, significant associations were observed on case-control studies, and these were also detected on cohort studies in processed meat. In all kinds of meats, positive associations were also observed on Asian populations and quality score ≥7 groups.H. pylori, which is a serious leading risk factor for gastric cancer [There have been various studies to identify the underlying biological mechanism for the association between red and processed meat consumption and gastric cancer. Among gastric cancer risk factors, heme iron, which is abundantly contained in red meat promotes endogenous formation of carcinogenic N-nitroso compounds (NOCs) . Since Nc cancer ,69.In addition, for processed meat, the cooking method or processing and storage methods may independently increase the risk of gastric cancer. That is, the cooking method or type of processing and preserving of the meat may also be one of the risk factors for gastric cancer. For example, heterocyclic amines and polycyclic aromatic hydrocarbons are produced when meat is cooked at high temperature . In addiInterestingly, a higher white meat intake was negatively associated with gastric cancer risk. In terms of the fundamental biological mechanism of the association between white meat intake and gastric cancer, lesser heme iron in white meat may hinder an increase in the risk of gastric cancer because it contributes to the suppression of an increase of endogenous formation of NOCs ,72. In aWesterners (Europeans or Americans) consume a larger amount of white meat quantitatively than Asians, and also white meat consumption constitutes a larger proportion of total meat consumption in Westerners than that in Asians . ConsideH. pylori infection). Interestingly, when adjusted for H. pylori, red meat intake was still significantly related to gastric cancer risk. Regarding this result, we considered that a high level of red meat consumption may increase the risk of gastric cancer regardless of the H. pylori infection, which is one of the strongest risk confounders for gastric cancer. We also considered that red or processed meat consumption independently contributes to increasing the risk of gastric cancer, regardless of various important confounders.When stratified by study design, stronger associations between meat consumption and the risk of gastric cancer were observed in case-control studies compared with cohort studies on all kinds of meat. These differences may in part result from the recall bias because case-control studies depend on the patient’s memory of the past. Furthermore, selection bias also may have contributed to the discrepancy between two kinds of studies because the RR was especially higher in hospital-based case-control studies. When classified by geographic region, the relative risks were different depending on geographic regions in all kinds of meats. These different risk values reflect the possibility that regional eating habits may affect the risk of gastric cancer. Especially, regarding only Asian populations with the highest white meat intake had a 30% lower risk of gastric cancer in our study, therefore further investigation is required to identify the associations among ethnicity which is related to geographic region, eating patterns, white meat consumption, and the risk of gastric cancer. When stratified by anatomical type, the increase of risk of gastric cancer was observed on the non-cardia cancer group in processed meat. On the other hand, there were no significant associations between other kinds of meats intake and anatomical subtype (cardia and non-cardia cancer). In addition, no significant associations between all kinds of meat consumption and histological subtype  and diffuse (undifferentiated)) were observed. Thus, more evidential data are required to identify the influence of meat intake to anatomical subtype or histological subtype of gastric cancer. In the subgroup analysis according to adjustments, significantly high RRs were observed on red meat intake regardless of all potential confounding factors (total energy intake, BMI, smoking, alcohol drinking, vegetable intake, fruit intake, salt intake, socioeconomic status, and H. pylori infection, were still not adjusted. We obtained significant results only on red meat after adjusting H. pylori infection. To identify the accurate associations between processed, white meat, and gastric cancer, more studies, which are adjusted for H. pylori infection or other important confounders, should be performed. Second, significantly stronger associations between meat intake and the risk of gastric cancer were detected in case-control studies compared with cohort studies. Generally, cohort studies are more reliable and robust than case-control studies because cohort studies are comparatively free from recall bias or selection bias. In prospective cohort studies, exposure data are collected before the subject’s pathogenesis and are collected from participants who share identical characteristics except for their exposure status of interest. Therefore, further prospective cohort studies are required to identify the exact associations. Third, the results in this study might be slightly influenced by the difference of the definition of meat category because each study had a different criteria of meat categorization. For example, some studies defined processed red meat as ‘red meat’, but it can be also included in ‘processed meat’. Finally, although publication bias was not the problem for processed and white meat, it might have affected the result for red meat. Heterogeneity across studies was also detected in some subgroup analyses, which might have overstated the association between meat consumption and the risk of gastric cancer. However, the publication bias was not detected on the dose–response analysis for red meat, and results were similar with the highest versus lowest consumption analysis.This meta-analysis study has several limitations. First, although various confounding factors were adjusted, some residual confounders may not be excluded because each study had different adjustments. Although many studies were adjusted for total energy, BMI, smoking, alcohol drinking, vegetable intake, fruit intake, and socioeconomic status, some critical confounders, such as H. pylori infection, which is one of the strongest risk factors of gastric cancer. The results in our meta-analysis represented the worldwide large-scale population because 1,764,894 participants and 4314 gastric cancer patients were involved in cohort studies including 76,806 controls and 12,258 cases in case-control studies. These abundant data provided more reliable and robust results, and the analysis in this study was statistically more reliable thanks to the huge scale of population data. Regarding the confined evidences concerning white meat consumption and the risk of gastric cancer [Despite the limitations, our study is highly important because it was the first meta-analysis study to identify the association that white meat intake has with gastric cancer. In addition, this is the first study to identify the dose–response associations between processed or white meat intake and gastric cancer risk. Moreover, our study is more reliable because this is the updated meta-analysis study reflecting recent researches about the association between red or processed meat consumption and gastric cancer after previous meta-analyses. Furthermore, this is the first meta-analysis to investigate the results on studies adjusted for In conclusion, the increased consumption of red and processed meat is positively related to the risk of gastric cancer. On the other hand, white meat intake seems to have a negative association with the risk of gastric cancer. It is a very important issue because red and processed meat consumption still accounts for the largest portion of overall meat intake in developed countries including the United States . Our fin