ADIPOQ gene polymorphisms have been indicated to be associated with hypertension; however, published studies have reported inconsistent results. Eligible studies were retrieved by searching the PubMed, Embase and China National Knowledge Infrastructure databases. The case group consisted of patients with hypertension, and the control group consisted of subjects with normal blood pressure. Based on eleven published articles, involving 4837 cases and 5618 controls, the pooled results from rs2241766 polymorphism showed increased risk in the allelic model , recessive model , dominant model  and homozygote model . In addition, rs266729 polymorphism showed increased risk for hypertension in the recessive model . In the Caucasian subgroup, rs1501299 polymorphism showed decreased risk of hypertension in the allelic model , dominant model  and heterozygote model . The rs2241766 polymorphism was associated with a significant increase in hypertension risk based on our analysis. Moreover, an increased risk of rs266729 in hypertension patients was also detected. Our meta-analysis suggests that the rs1501299 polymorphism may play a protective role in hypertension in Caucasian subgroup; however, this finding requires further study. Hypertension is a major risk factor for vascular disease and the leading source of global health burden345Adiponectin is an adipocyte-derived hormone and plays an important role in energy homeostasis by regulating glucose and lipid metabolism891213et al.et al.et al.Most of the published studies have investigated the associations of rs2241766, rs1501299 and rs266729 polymorphisms in the ADIPOQ gene with risk factors of hypertension151617A total of 233 articles were obtained by online and manual search. After removing duplicates and screening the title and abstract, eighteen articles were selected. Seven articles were excluded due to lack of detailed genotype distribution. Finally, a total of eleven published articles10171820212223242526The characteristics of all the included articles are summarized in Sensitivity analysis was performed by sequentially omitting 1 individual study; in order to detect the influence of each study on the overall meta-analysis. No heterogeneity was observed in the polymorphisms , 5 and 6No publication bias was detected among studies regarding the association between the rs2241766 polymorphism and hypertension risk . Howeverin vitro, and its concentration is decreased in patients with coronary artery disease and hypertension3436Endothelial dysfunction plays an important role in the pathogenesis of hypertension303132et al.et al.et al.Our results show that the rs2241766 polymorphism in the ADIPOQ gene is significantly associated with hypertension. Increased risk is observed in the allele, recessive, dominant and homozygote genetic model. The minor G allele of ADIPOQ rs2241766 may increase the risk of hypertension by 16% , and GG genotype may increase the risk of hypertension by 34% compared to the GT and TT genotype . When compared with the TT genotype alone, a 38% increase in risk was detected in GG genotype group . In the ethnicity subgroup analysis, increased risk is not only observed in the allele, recessive, dominant and homozygote genetic models in the Caucasian group but also in allele, recessive and homozygote genetic model in Mongolian population. In the eleven included studies, four studies from the Chinese population are consistent with our results182123et al.et al.et al.Significant association between rs266729 and hypertension is found in the recessive genetic model in our study. The GG genotype may increase the risk of hypertension by 43% compared to GC and CC genotype . In the ethnicity subgroup analysis, increased risk was only detected in the recessive and homozygote genetic model. Four of five included studies addressing the association between rs266729 and hypertension risk were consistent with our result. Haplotype is also an important risk factor in hypertension and the −11426G −11377C haplotype was found to be associated with low plasma adiponectin level in the hypertension group, as reported by Zhang 2)et al.In the Caucasian subgroup, the rs1501299 polymorphism in the ADIPOQ gene was significantly associated with hypertension. The minor T allele of ADIPOQ rs266729 may decrease the risk of hypertension by 25% , and the TG genotype may decrease the risk of hypertension by 18% compared to GG genotype . The same decreased risk of hypertension was also observed in the dominant genetic model. For the rs1501299 polymorphism, a protective role of rs1501299 polymorphism in hypertension group is found in the Caucasian subgroup, which is contrary to the results of nine included studies. An association between the rs1501299 polymorphism and adiponectin concentration was found in obese subjects  requires additional study. In addition, the potential influence on genotype-hypertension associations by environment factors is worthy of consideration.In conclusion, the rs2241766 polymorphism was found to be associated with a significant increase in hypertension risk based on our analysis. Moreover, an increased risk in rs266729 in hypertension patients was also detected. Our meta-analysis suggests that rs1501299 polymorphism may play a protective role in hypertension in the Caucasian subgroup; however, additional studies are required to support this finding.The systematic review was written in adherence to the PRISMA  checklistPubMed, Embase, VIP, Wanfang and China National Knowledge Infrastructure databases were thoroughly searched in March 2016 by the first two investigators to identify potential studies addressing the associations between the ADPIOQ gene polymorphisms and hypertension. The terms “hypertension,” “high blood pressure,” “adiponectin,” “ADIPOQ,” “APM1,” “polymorphism,” and “polymorphisms” were used. The missing data (the data that we failed to identify during the electronic search) were obtained by reviewing the citations of review articles and all eligible studies.To be included in this meta-analysis, studies met the following inclusion criteria: (1) evaluation of the association between the ADIPOQ gene polymorphisms and hypertension; (2) case-control study or cohort design; (3) detailed genotype data could be acquired to calculate odds ratios (ORs) and 95% confidence intervals (CIs); Exclusion criteria: (1) duplication of previous publications; (2) comment, review and editorial; (3) study without detailed genotype data. The selection of the studies was achieved by two investigators independently, according to the inclusion and exclusion criteria by screening the title, abstract and full-text. Any dispute was solved by discussion.From each study, the following data were independently extracted by the first two investigators using a standardized form: first author’s last name, year of publication, study country, ethnicity, genotyping methods, age, body mass index, sample size, source of controls, Hardy-Weinberg equilibrium, number of cases and controls, and genotype frequency in cases and controls for ADIPOQ gene. Different ethnicity descents were classified as Caucasian and Mongolian. Disagreements were resolved through discussion.Two reviewers independently assessed the quality of the included studies, according to a set of criteria  modified2 statistic (greater than 50% as evidence of significant inconsistency). Heterogeneity between studies was evaluated with the I2 test, and a higher I2 values means higher levels of heterogeneity (Hardy–Weinberg equilibrium (HWE) was evaluated for each study by Chi-square test in control groups, and P < 0.05 was considered as a significant departure from HWE. Odds ratio (OR) and 95% confidence intervals (CIs) were calculated to evaluate the strength of the association between ADIPOQ gene polymorphisms and hypertension risk. Pooled ORs were performed for the allelic model , recessive model , dominant model , heterozygote model , and homozygote model , respectively. Heterogeneity was evaluated by Q statistic (significance level of P < 0.1) and IHow to cite this article: Fan, W. et al. Associations between polymorphisms of the ADIPOQ gene and hypertension risk: a systematic and meta-analysis. Sci. Rep.7, 41683; doi: 10.1038/srep41683 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Non-alcoholic fatty liver disease (NAFLD) has been recently identified as a risk factor of gastrointestinal tract cancers, especially hepatocellular carcinoma, and colorectal cancer. Whether NAFLD is a risk factor for cholangiocarcinoma (CCA) remains inconclusive. The aim of this study is to determine a potential association between NAFLD and CCA, stratifying by its subtypes; intrahepatic CCA (iCCA), and extrahepatic CCA (eCCA).A search was conducted for relevant studies published up to April 2017 using MEDLINE, EMBASE, Scopus and Cochrane databases. Odds ratio (OR) and adjusted OR with 95% confidence interval (CI) were estimated using a random-effects model. Subgroup analyses were conducted with study characteristics.I2=76%). When classified by subtypes, NAFLD was associated with both iCCA and eCCA, with ORs of 2.22  and 1.55 , respectively. The overall pooled adjusted ORs were 1.97 , 2.09  and 2.05  for all CCAs, iCCA, and eCCA, respectively.Seven case-control studies were included in the analysis, with a total of 9,102 CCA patients  and 129,111 controls. Overall, NAFLD was associated with an increased risk for CCA, with pooled OR of 1.95 .The online version of this article (10.1186/s12876-017-0696-4) contains supplementary material, which is available to authorized users. Cholangiocarcinoma (CCA) is a cancer arising from bile duct epithelium. The incidence of CCA varies by geographic regions, ranging from 0.4–3.4 per 100,000 persons-year in North America and Europe to 1–85 per 100,000 persons-year in East Asia [CCA is broadly categorized into 2 subtypes by anatomic locations as intrahepatic (iCCA) and extrahepatic (eCCA) subtypes. The two subtypes hold different genetics, presentations, management, and outcomes [Non-alcoholic fatty liver disease (NAFLD) is a spectrum of liver disease, ranging from fatty liver to non-alcoholic steatohepatitis (NASH) and cirrhosis. It is estimated that one-third of the general population has NAFLD –5. AccumTo determine an association between NAFLD and CCA including its subtypes, we conducted a meta-analysis of case-control and cohort studies.The protocol for this study was registered with PROSPERO . We performed a systematic review in accordance with the PRISMA  guidelines  independently screened titles and abstracts of all studies that determined any risk factors for CCA and reached for the full text. From full text, studies were included if they that met all of the following criteria: (i) case-control, cohort or trial study, (ii) NAFLD or NASH, defined by either histopathological examination, imaging study or International Classification of Diseases, Ninth Revision (ICD-9) or ICD-10 codes, as one of the exposure of interests, (iii) CCA either iCCA, eCCA, or both as outcome of interest, (iv) study that provided adequate information for calculation of odds ratio (OR) or relative risk for case-control study and cohort study, respectively. Studies of patient cohorts with recurrent CCA or combined hepatocellular-cholangiocarcinoma were excluded. If the same patient cohort was included in more than one study, the study with a larger sample size and a higher quality score assessed by Newcastle-Ottawa scale (NOS) scale was included.Data were independently extracted from full-text articles by two authors (NW and BA). Disagreements were identified and discussed with the third author (RC). The information extracted included diagnostic criteria of NAFLD/NASH, a crude number of individuals with and without NAFLD/NASH in the case and control groups, the source of controls , number of participants, country where a study was conducted, and publication year. Adjusted odds ratio (AOR) and covariates in the adjusted analysis model were also extracted.The quality of studies was evaluated using Newcastle-Ottawa scale (NOS) , which cI2 statistics and P value. An I2 value of >50% indicates substantial heterogeneity. Univariate random-effects model meta-regressions of the adjusted OR (AOR) from the included studies were performed. Publication bias was assessed by the Egger test. All analyses were performed using Comprehensive Meta-Analysis Software version 2.0, and the Metan and Metareg Commands of Stata 11 .Pooled OR along with 95% confidence interval (CI) of CCA, iCCA, and eCCA were estimated from the crude number of study patients using a random-effects model. Heterogeneity among studies was assessed using both the n = 149); the case group was not diagnosed with CCA (n = 25); no control group in the study (n = 13); and irrelevant study (n = 16). There were ten potential relevant studies, of which studies from Chaiteerakij et al. [After excluding duplicates, 1843 articles that met the search criteria were identified. After title and abstract screening, 213 studies that met the selective criteria were further assessed Fig. n = 9; the caj et al.  were exctudy n = . There wj et al. , respectGiven the difference in study design, 7 case-control studies were included in this meta-analysis Table  9, 10, –20. The In the 7 case-control studies, the period of participant enrollment ranged from 1992 to 2014. There was a total of 9102 CCA patients (5067 iCCA and 4035 eCCA) and 129,111 controls. Overall, 426 (4.7%) CCA cases and 1018 (0.8%) controls had underlying NAFLD or NASH , and 2.13  for studies conducted in Western and Asian countries, respectively. The good quality studies had pooled OR of 1.33  and the fair quality studies had pooled OR of 2.48   for iCCA risk.Of the six studies presenting results of NAFLD and iCCA risk , 19, 20,I2 = 69%; P = 0.02).There were four studies presenting results of NAFLD and risk of eCCA , 16–18. I2 = 71%; P < 0.001) [I2 = 47%; P = 0.11) [I2 = 0%; P = 0.90) [All but two studies provided AOR of NAFLD for CCA risk  , 17, 20. = 0.11) , 17, 20  = 0.90) , 16, 17,P = 0.82 and 0.86 for unadjusted and adjusted OR of NAFLD, respectively. However, due to the limited number of the included studies, the interpretation of Egger’s test should be done cautiously.No publication bias was detected by the Egger’s regression asymmetry test, with The present meta-analysis of seven case-control studies found that NAFLD was significantly associated with an increased risk of CCA for both iCCA and eCCA subtypes. This finding might in part explain the recent trend of rising incidence of CCA.Although the mechanism by which NAFLD causes CCA development has not yet been well studied, it is biologically plausible that NAFLD promotes cholangiocarcinogenesis directly through an induction of hepatic inflammation, or indirectly via cirrhosis. Cirrhosis, regardless of etiology, has recently been recognized as a risk factor for CCA , 16, 17.It is important to note that the prevalence of NAFLD in this meta-analysis varied from 0.8 to 44.1% and 0.3 to 18.8% in CCA cases and controls, respectively. These numbers were relatively low as compared to previous studies reporting prevalence of NAFLD in the general population of 11–45% and 8–42% in North America and Asia, respectively  which usOur finding showed the effect of NAFLD was more pronounced for the development of iCCA than eCCA (pooled OR of 2.22 vs. 1.55). This finding is consistent with the previous study showing that iCCA was more associated with chronic liver diseases than eCCA . On the As expected, the estimated pooled OR of NAFLD obtained from community-based studies was greater than that obtained from hospital-based studies (2.46 vs. 1.47) (Data not shown). This can be explained by a relatively lesser proportion of controls diagnosed with NAFLD in community-based studies compared to hospital-based studies. Because individuals with NAFLD are mostly asymptomatic, thus controls in community-based studies might have less likelihood to undergo radiologic images, which could potentially increase the possibility of under-detection of NAFLD in controls in community-based studies. This is suggested by the finding that the proportion of NAFLD in controls in community-based studies were lower than the previous reports –5. To miThe present meta-analysis has some limitations. Diagnostic methods for NAFLD were different among studies. This bias was accounted by the aforementioned analysis of subgroup by the same diagnostic methods for both case and control groups. The results of the two analyses were consistent, implying that our finding was not influenced by NAFLD diagnosis method. In addition, subgroup analyses of some underlying diseases predisposing to CCA, e.g. primary sclerosing cholangitis, cholelithiasis, biliary tract infection, and other chronic liver diseases, cannot be performed due to the limited number of participants with these conditions. Because CCA is considered to be a relatively rare cancer, the number of publications in this field is quite small compared to other cancers. Consequently, the number of studies qualified for this meta-analysis was limited. Accordingly, the probability of type I errors in the process of hypothesis testing existed, particularly with multiple subgroup analyses. However, the subgroup analyses are necessary to explore the finding of the main analysis. We limited the subgroup analyses to the three most important subgroups, including CCA subtypes, study region, and study quality. Another limitation was that NAFLD is a spectrum of disease, ranging from simple steatosis to cirrhosis; in this study, we were not able to estimate the magnitude of impact of steatosis, steatohepatitis or NASH-related cirrhosis on CCA risk individually because they used different diagnostic methods and most papers grouped steatosis and steatohepatitis together. Lastly, cirrhosis itself has recently been recognized as a risk factor for CCA, the possibility that the observed association between NAFLD and CCA in this study was confounded by cirrhosis cannot be excluded. A study to determine whether the increased risk of CCA in patients with NAFLD is independent to cirrhosis status is needed.This meta-analysis suggests that NAFLD may potentially increase the risk of CCA development. The magnitude of NAFLD on CCA risk is greater for iCCA than eCCA subtype, suggestive of a common pathogenesis of iCCA and hepatocellular carcinoma. Further studies to elucidate both the strength of the association between NAFLD and CCA, as well as the mechanisms that underlie this relationship are warranted.Additional file 1: Data S1.PRISMA 2009 checklist for systematic review. (DOC 66 kb)Additional file 2: Data S2.Data S2 B. Search strategy for EMBASE. Data S2 C. Search strategy for Scopus. Data S3 Exclusion of studies that had the same patient cohort. Data S4 Data of the included cohort study. Data S5 Quality assessment of included paper by Newcastle-Ottawa scale (NOS). Data S6 Adjusted odds ratios shown in the included studies. (DOCX 41 kb)A. Search strategy for Ovid MEDLINE Epub Ahead of Print, In-Process & Other Non-Indexed Citations, Ovid MEDLINE Daily and Ovid MEDLINE.


It was reported that Fas  and FasL  gene polymorphism might be related to the risk of musculoskeletal degenerative diseases (MSDD), such as osteoarthritis (OA), intervertebral disc degeneration (IVDD) and rheumatoid arthritis (RA). However, data from different studies was inconsistent. Here we aim to elaborately summarize and explore the association between the Fas  and FasL  and MSDD.Literatures were selected from PubMed, Web of Science, Embase, Scopus and Medline in English and VIP, SinoMed, Wanfang and the China National Knowledge Infrastructure (CNKI) in Chinese up to August 21, 2017. All the researches included are case-control studies about human. We calculated the pooled odds ratios (ORs) with 95% confidence intervals (95% CI) to evaluate the strengths of the associations of Fas  and FasL  polymorphisms with MSDD risk.Eleven eligible studies for rs1800682 with 1930 cases and 1720 controls, 6 eligible studies for rs2234767 with 1794 cases and 1909 controls, 3 eligible studies for rs5030772 with 367 cases and 313 controls and 8 eligible studies for rs763110 with 2010 cases and 2105 controls were included in this analysis. The results showed that the G allele of Fas (rs1800682) is associated with an increased risk of IVDD in homozygote and recessive models. The G allele of Fas (rs2234767) is linked to a decreased risk of RA but an enhanced risk of OA in allele and recessive models. In addition, the T allele of FasL (rs763110) is correlated with a reduced risk of IVDD in all of models. However, no relationship was found between FasL (rs5030772) and these three types of MSDD in any models.Fas (rs1800682) and FasL (rs763110) polymorphism were associated with the risk of IVDD and Fas (rs2234767) was correlated to the susceptibility of OA and RA. Fas (rs1800682) and Fas (rs2234767) are more likely to be associated with MSDD for Chinese people. FasL (rs763110) is related to the progression of MSDD for both Caucasoid and Chinese race groups. But FasL (rs5030772) might not be associated with any types of MSDD or any race groups statistically.The online version of this article (10.1186/s12891-018-2057-z) contains supplementary material, which is available to authorized users. Degenerative disease is the consequence of a successive process resulted from degenerative cell changes, influencing tissues or organs, which will gradually deteriorate over time. The most common degenerative diseases in musculoskeletal systems include intervertebral disc degeneration (IVDD), osteoarthritis (OA) and rheumatoid arthritis (RA). IVDD, which results from ageing, small injuries and natural daily compression on intervertebral disc (IVD), has been regarded as one of the main causes to low back pain and motor deficiency. OA, a common type of joint disease, is owing to the destruction of joint cartilage and subchondral bone and is traditionally considered to be associated with articular cartilage degeneration . RA, a lApoptosis represents a physiological procedure in order to remove harmful, damaged, or unwanted cells . Fas is Although the exact etiology of OA is still unclear, current researches have explored an association between chondrocyte apoptosis and the progression of OA , 16. RA,So we performed a comprehensive meta-analysis containing three MSDD  and enrolling all races of populations besides Chinese. Also we corrected the mistakes of the previous meta-analysis, Lee et al.  and addeTo identify all literatures that studied the association of Fas and FasL genes polymorphisms with MSDD, we searched nine electronic databases including PubMed, Web of Science (WOS), Embase, Scopus and Medline in English and VIP, SinoMed, Wanfang and the China National Knowledge Infrastructure (CNKI) in Chinese. The search period for all these nine databases was up to August 21, 2017. The search strategy to explore all potential studies involved the use of the following terms: “Intervertebral Disk Degeneration” or “IDD” or “Disc Degeneration” or “disc herniation” or “low back pain” or “IVDD”, “Osteoarthritides” or “Osteoarthrosis” or “Arthritis, Degenerative” or “Degenerative Arthritis” or “Osteoarthrosis Deformans”, “Rheumatoid Arthritis”, “CD95 antigen, human” or “Fas” or “tumor necrosis factor receptor superfamily, member 6 protein, human” or “CD95L” or “Fas Ligand” or “FasL Protein” or “tumor necrosis factor ligand superfamily member 6” or “CD178 Antigens” or “CD95 Antigen Ligand” or “TNFRSF6 protein, human” or “Fas1 protein, human” or “rs1800682” or “rs2234767” or “rs5030772” or “rs763110”, “polymorphism” and “SNP”.To be included in this meta-analysis, studies should satisfy the following inclusion criteria: (1) evaluated the association of Fas and FasL genes polymorphisms with IVDD, OA and RA; (2) case-control studies; (3) offered sufficient data to calculate an odds ratio (OR) with 95% confidence interval (CI). What’s more, the following exclusion disciplines were also applied: (1) non–case-control studies; (2) repeated publications; (3) the study only concerned with a case group; (4) comment or review; and (5) not relevant to MSDD. Two investigators (Xiao and Huang) independently evaluated the articles in accord with the inclusion and exclusion criteria. Any inconsistency was solved by discussion. If these 2 authors could still not reach the uniformity, senior authors (Ma and Deng) were asked to resolve the disputes.For each study, the following characteristics were collected: (1) name of the first author; (2) year of publication; (3) country of enrollment; (4) ethnicity, age range and gender of the study population; (5) diagnosis and diagnostic criteria for MSDD cases; (6) genotyping methods; (7) source of controls; (8) matching criteria. (9) number of subjects under MSDD cases and controls; and (10) the HWE among the controls. Data were extracted cautiously from all eligible articles independently by 2 authors (Xiao and Huang). For conflict resolution, the accordance was realized by discussion.The qualities of all the included studies were assessed by two investigators (Xiao and Huang) separately using the Clark scores system, which includes 10 items . Scores 2 test before statistical analysis and P <  0.05 was thought to indicate significant disequilibrium. We examined Fas  and FasL  genotypes using the allele  model, homozygote  model, heterozygote  model, dominant  model, recessive  model. The strength of the association between Fas  and FasL  polymorphism and MSDD was assessed by the pooled ORs and 95% CI. Subgroup analyses were conducted to find whether diagnosis of MSDD or race groups was also related to the value of the pooled ORs and 95% CI. The statistical heterogeneity was verified by I2 statistics. Fixed-effects model was applied to estimate the ORs and 95% CI when heterogeneity was low (I2 < 50%); instead, the random-effects was used when heterogeneity was high (I2 > 50%) [P <  0.05 was considered to be statistically significant). All statistical analyses were managed using STATA 14 . All P-values were two-sided.The PRISMA checklists and their guidelines were carefully followed in the whole process of this study . The HWE2 > 50%) . Sensiti2 > 50%)  and the 2 > 50%)   and FasL  polymorphism by deleting one study each turn in every genetic model.P = 0.025) and in recessive model  for Fas (rs1800682) site. We also noted that the overall ORs significantly changed when we deleted Zhu et al. (published in 2011) [P = 0.204) and Zhu et al. (published in 2016) [P = 0.082) for Fas (rs2234767) site. We found that the pooled ORs significantly differed when we deleted Sun et al. 19] in dominant model  and Seyfi et al. [P = 0.053) for FasL (rs763110) site as well. However, there was no change in the significance of results in any models for FasL (rs5030772) site.We observed that the pooled ORs significantly differed when we deleted Huang et al.  in homozin 2016)  in homozi et al.  in dominP = 0.436, Egger’s test: P = 0.576 for allele model; Begg’s test P = 0.640, Egger’s test P = 0.609 for homozygote model; Begg’s test P = 0.876, Egger’s test P = 0.694 for heterozygote model; Begg’s test: P = 0.640, Egger’s test: P = 0.965 for dominant model; Begg’s test: P = 1.000, Egger’s test: P = 0.508 for recessive model). was linked to a decreased risk of MSDD only in homozygote model and the T allele of FasL rs763110) was associated with a reduced risk of MSDD in all of the comparison models. Besides that, subgroup analyses leveled by diagnosis suggested that the G allele of Fas (rs1800682) was associated with an increased risk of IVDD in homozygote and recessive models. The G allele of Fas (rs2234767) was linked to a decreased risk of RA but an enhanced risk of OA in allele and recessive models. In addition, the T allele of FasL (rs763110) was correlated with a reduced risk of IVDD in all of models. However, no relationship was found between FasL rs5030772) and these three types of MSDD in any models. In addition, subgroup analyses leveled by race groups showed that the G allele of Fas (rs1800682) was associated with an increased risk of MSDD in homozygote and recessive models only in Chinese people. The G allele of Fas (rs2234767) was linked to a decreased risk of MSDD in homozygote model for Chinese people. What’s more, the T allele of FasL (rs763110) was correlated with a reduced risk of MSDD in allele and recessive models for both Caucasoid and Chinese race groups. However, no relationship was found between FasL (rs5030772) and these two race groups of MSDD in any models. Our results have several differences with the previous meta-analyses of RA recently published 10 was as. Compare772 and tWhat’s more, the genotype distributions of controls in all of models were in accordance with HWE, except Sezgin et al.  in Fas (I2 > 50%) in some models for overall analyses, leading to a cautious acceptance of the results. So we performed subgroup analyses stratified by diagnosis to make the result more credible. What’s more, some of the included articles did not match the confounding factors such as age, sex and ethnicity between case group and control group. And different factors for matching might also increase the probability of residual confounding. Such confounding factors might influence the final results. However, this meta-analysis has some strength. For example, to our best knowledge, this is the most comprehensive meta-analysis focused on the association of Fas/FasL gene polymorphism with the susceptibility of MSDD, including OA, IVDD and RA. Several strategies and rigid criteria were set to assess the methodological quality of each study; all of the included studies possessed high or moderate qualities.There are some limitations in the present study. Firstly, only three studies for FasL rs5030772 site were included in analysis and only one article was screened out for OA subgroup analysis due to shortage of original studies. Secondly, the heterogeneity was a little bit high  and FasL (rs763110) polymorphism were associated with the susceptibility of IVDD. Fas (rs2234767) was correlated to the risk of OA and RA. Fas (rs1800682) and Fas (rs2234767) are more likely to be associated with MSDD for Chinese people. FasL (rs763110) is related to the progression of MSDD for both Caucasoid and Chinese race groups. However, FasL (rs5030772) might not be associated with MSDD. Because of the above-mentioned limitations, large-scale studies, including larger populations and considering more confounding factors, are required to verify the outcomes of this meta-analysis.Additional file1:Table S1. Summary of meta-analysis for the association of Fas rs1800682 and rs2234767 polymorphisms with musculoskeletal degenerative diseases leveled by diagnosis. (DOCX 25 kb)Additional file 2:Table S2. Summary of meta-analysis for the association of FAS rs1800682 and rs2234767 polymorphisms with musculoskeletal degenerative diseases leveled by race groups. (DOCX 23 kb)Additional file 3:Table S3. Summary of meta-analysis for the association of FasL rs5030772 and rs763110 polymorphisms with musculoskeletal degenerative diseases leveled by diagnosis. (DOCX 24 kb)Additional file 4:Table S4. Summary of meta-analysis for the association of FASL rs5030772 and rs763110 polymorphisms with musculoskeletal degenerative diseases leveled by race groups. (DOCX 22 kb)


The aim of this systematic review and meta-analysis was to synthesize the knowledge about the relation between intake of 12 major food groups and risk of type 2 diabetes (T2D). We conducted a systematic search in PubMed, Embase, Medline (Ovid), Cochrane Central, and Google Scholar for prospective studies investigating the association between whole grains, refined grains, vegetables, fruits, nuts, legumes, eggs, dairy, fish, red meat, processed meat, and sugar-sweetened beverages (SSB) on risk of T2D. Summary relative risks were estimated using a random effects model by contrasting categories, and for linear and non-linear dose–response relationships. Six out of the 12 food-groups showed a significant relation with risk of T2D, three of them a decrease of risk with increasing consumption , and three an increase of risk with increasing consumption  in the linear dose–response meta-analysis. There was evidence of a non-linear relationship between fruits, vegetables, processed meat, whole grains, and SSB and T2D risk. Optimal consumption of risk-decreasing foods resulted in a 42% reduction, and consumption of risk-increasing foods was associated with a threefold T2D risk, compared to non-consumption. The meta-evidence was graded “low” for legumes and nuts; “moderate” for refined grains, vegetables, fruit, eggs, dairy, and fish; and “high” for processed meat, red meat, whole grains, and SSB. Among the investigated food groups, selecting specific optimal intakes can lead to a considerable change in risk of T2D.The online version of this article (doi:10.1007/s10654-017-0246-y) contains supplementary material, which is available to authorized users. The global prevalence of type 2 diabetes (T2D) is increasing rapidly, running parallel to the increase in obesity, the reduction in physical activity/adoption of a sedentary lifestyle, and changes in diet towards unhealthy eating behaviors. It has been estimated that 415 million persons had T2D in 2015, and the number has been projected to increase to 642 million by 2040 [Therefore, implementation of effective T2D prevention strategies, as well as early detection programs is of major importance to reduce the health burden of the disease –5.Moreover, healthy eating patterns assessed by hypothesis-driven approaches such as the Mediterranean diet score, the Healthy Eating Index, the Alternate Healthy Eating Index and the DASH dietary score have been associated with reduced risk of T2D , 7. The In this context, the following 12 food groups might be of interest when analyzing diet and risk of T2D because they are the basis for most diet quality indices/scores , 7, 10, Furthermore, the quality of evidence provided by meta-analyses of cohort studies is rarely assessed. Consequently, one of the most important questions that remain to be answered is which food groups show high quality meta-evidence of protective or detrimental effects in relation to risk of T2D using an integrative approach.Thus, we synthesized all available data from prospective studies for investigating the associations of the 12 a priori defined food groups, including whole grains, refined grains, vegetables, fruits, nuts, legumes, eggs, dairy, fish, red meat, processed meat, and SSB with risk of T2D. We specifically aimed to clarify the strength and shape of the dose–response relationship and to find optimal food intakes for a low disease risk.www.crd.york.ac.uk/prospero/index.asp, identifier CRD42016037069). This systematic review was planned and conducted according to the standards of the Meta-analysis of Observational Studies in Epidemiology [The review was registered in PROSPERO , Cochrane Central, and Google Scholar until February 2017 with no restriction to calendar date and language using the following search terms (Supplementary Appendix S1).Moreover, the reference lists from the retrieved articles, systematic reviews, and meta-analyses were checked to search for further relevant studies. The literature search was conducted by two authors , with disagreement resolved by consensus of another reviewer.Studies were included in the meta-analysis if they met all of the following criteria: (1) prospective design studies  that were peer-reviewed and available in full-text; (2) information about the association for ≥1 of the following twelve food groups: whole grains/cereals, refined grains/cereals, vegetables, fruits, nuts, legumes, eggs, dairy products, fish, red meat, processed meat, and SSB on risk of T2D; (3) Participants ≥18 years; and (4) considering T2D as outcome (study population had to be free of T2D at the onset of the study).After determination of the study selection, two reviewers extracted the following characteristics: the first author’s last name, year of publication, study origin, cohort name, sample size, number of cases, age at entry, sex, study length, outcome, outcome assessment, assessment of food group, quantity of food, risk estimate (most adjusted measures) (hazard ratios (HR), risk ratios (RR) with their corresponding 95% confidence intervals (CIs)), and adjustment.When a study provided several risk estimates, the multivariable adjusted model was chosen. When only separate risk estimates for male and female participants were available in a study, we combined the RRs using a fixed effects model before inclusion in the meta-analysis.ascertainment of exposure );assessment of outcome (low risk of bias: record linkage (ICD codes), accepted clinical criteria, self-reported and validated);adequacy of follow-up length (low risk of bias: >5 years);and adjusted basic model  and outcome-relevant adjustments .In a previous analysis of 50 randomly selected meta-analyses of cohort studies exploring the field of nutritional sciences we could show that 20 meta-analyses (40%) applied no quality assessment score, and 19 (38%) used the Newcastle Ottawa Scale . HoweverStudies were classified as being at low risk of bias (2 points) only if none of the domains established a high/unclear risk of bias, high risk of bias (if at least one sub-item was rated as high risk), and moderate/unclear risk (if at least one sub-item was rated as moderate/unclear risk).A random effects model was used to calculate summary RRs and 95% CIs for the associations between T2D and the highest versus the lowest intake category for each of the 12 pre-defined food groups and for the dose–response analysis , which iThe method described by Greenland and Longnecker , 17 was When studies reported only the total number of cases or total person-years and the exposure was defined in quantiles, the distribution of cases or person-years was calculated dividing the total number by the number of quantiles. Whenever reported, the mean or median intake by category was assigned to the corresponding RR. The midpoint was calculated for studies that only reported a range of intake by category. When the intake range was open-ended, we assumed that its width was the same as the adjacent category.The dose–response was expressed in the following servings: whole grains/cereals (30 g/day), refined grains/cereals (30 g/day), vegetables (100 g/day), fruits (100 g/day), nuts (28 g/day), legumes (50 g/day), eggs (50 g/day), dairy products (200 g/day), fish (100 g/day), red meat (100 g/day), processed meat (50 g/day), and SSB (250 ml/day). For studies that reported intake only as serving size, we used recommended conversions (Supplementary Table S1).To examine possible nonlinear associations, we calculated restricted cubic splines for each study with more than three categories of exposure, using three fixed knots at 10, 50, and 90% through the total distribution of the reported intake, and combined them using multivariable meta-analysis .Moreover, the T2D risk reduction potential of foods was calculated by multiplying the RR by selecting an optimal consumption (serving category with the strongest association) of risk-decreasing foods, and risk-increasing foods, respectively.2 statistic . In addPotential small-study effects, such as publication bias, were explored using Egger´s test and funnel plots  when at To evaluate the meta-evidence for the association between 12 pre-defined food groups and T2D  we applied the NutriGrade scoring system (max 10 points), which comprises the following items: (1) risk of bias/study quality/study limitations, (2) precision, (3) heterogeneity, (4) directness, (5) publication bias, (6) funding bias, (7) study design , (8) effect size . Based oOut of 14,167 records identified by the literature search, 439 full text articles were assessed in detail as they reported on one or more of the twelve foods groups and T2D in the title/abstract , 15 for refined grains , 13 for vegetables , 15 for fruits , 8 for nuts , 12 for legumes , 13 for eggs , 21 for dairy products , 16 for fish , 15 for red meat , 14 for processed meat , and 10 for consumption of SSB .2 = 86%) . Each additional daily 30 g of whole grains was inversely associated with T2D risk  . The inverse associations and heterogeneity persisted in additional analyses stratified by sex, age, follow-up length, geographic location, number of cases, dietary assessment, and outcome assessment (Supplementary Table S14). Evidence of heterogeneity between subgroups in stratified analyses was observed for geographic location, dietary assessment method, and outcome assessment. There was significant evidence for small study effects in the high versus low meta-analysis, but not in the dose–response meta-analysis. Visual inspection of the funnel plot suggests that small studies showing positive association may be missing . There was evidence of a non-linear dose–response association; the risk of T2D decreased by 25% with increasing intake of whole grains up to ~50 g/day. Small benefits for increasing intake above this value were observed . Comparing extreme categories, a strong inverse association between T2D and whole grain intake was observed  , and for each additional daily 30 g  . No significant association or heterogeneity were observed within and between subgroups of the stratified analyses, except for a positive association among participants <50 years of age (Supplementary Table S15). There was no evidence for small study effects in the high vs. low and in the dose–response meta-analysis . There was no evidence of a non-linear dose–response association. However, 200–400 g/day of refined grains were associated with a 6–14% increased risk of T2D . No association was observed for the highest versus lowest refined grain intake category   and dose–response analysis  . The inverse association was observed only in Asian and Australian studies, but not for American and European studies, and in studies with a lower number of cases (Supplementary Table S16). There was no evidence of heterogeneity between subgroups in stratified analyses. No evidence for small study effects was observed, and visual inspection of the funnel plot suggests symmetry . There was evidence of a non-linear dose–response association; the risk of T2D decreased by 9% with increasing intake up to 300 g/day. No benefit for increasing intake is apparent above this value . A borderline inverse association was observed for the high versus low  . Each additional daily 100 g of fruits was inversely associated with T2D risk  . The inverse association was observed only in studies with a longer-term follow-up (≥10 years), and including participants younger than 50 years of age (Supplementary Table S17). There was no evidence of heterogeneity between subgroups in stratified analyses. No evidence for small study effects was observed, and visual inspection of the funnel plot suggests symmetry . There was evidence of a non-linear dose–response association; the risk of T2D decreased by 10% with increasing intakes of fruits up to 200–300 g/day. No benefit for increasing intake is apparent above this value . A borderline inverse association was observed  , and for each additional daily 28 g  . We observed a significant inverse association for studies conducted in Asian countries and for studies with a shorter-term follow-up, confirmed by significant heterogeneity between subgroups (Supplementary Table S18). There was no evidence of a non-linear dose–response association . No significant association was observed for the highest versus lowest nut intake category  , and for each additional daily 50 g  . There was no evidence of heterogeneity between subgroups in stratified analyses, except for an inverse association among participants <50 years of age (Supplementary Table S19). No evidence for small study effects was observed, but visual inspection of the funnel plot suggests asymmetry . There was no evidence of a non-linear dose–response association . No significant association was observed for the highest versus lowest legume intake category  , and for each additional daily 30 g  . We observed a strong positive association for studies conducted in America in the dose–response analysis, but not for Asian and European studies (Supplementary Table S20). Moreover, significant positive associations were observed for studies with ≥1000 diabetes cases, using FFQ, and self-reported T2D diagnosis. There was some evidence of heterogeneity between subgroups in stratified analyses . No evidence for small study effects was observed, and visual inspection of the funnel plot suggests symmetry . There was little evidence of a non-linear dose–response association (p = 0.09) . No significant association was observed for the highest versus lowest egg intake category  . Each additional daily 200 g of dairy products was inversely associated with diabetes risk  . The inverse association was observed only in Asian and Australian studies, but not for American and European studies. Moreover, significant associations were observed for studies with <1000 T2D cases, participants ≥50 years of age, and a shorter follow-up (<10 years). In subgroup analyses low-fat dairy products showed a borderline inverse association, whereas no association could be observed for high-fat dairy products (Supplementary Table S21). Some evidence of heterogeneity between subgroups in stratified analyses was observed . There was significant evidence for small study effects in the dose–response meta-analysis, but not in the high versus low meta-analysis . Visual inspection of the funnel plot suggests that small studies showing positive or null association may be missing. There was no evidence of a non-linear dose–response association between dairy products and T2D; the risk decreased by 6% with increasing intake up to 400–600 g/day. No benefit for increasing intake was apparent above this value . A significant inverse association was observed  , and for each additional daily 100 g  . We observed a strong positive association for studies conducted in America between fish intake and risk of T2D, with stronger associations in the dose–response analysis (Supplementary Table S22), and an inverse association in Asian studies. We found statistically significant heterogeneity between subgroups of geographic location and length of follow-up. No evidence for small study effects was observed, and visual inspection of the funnel plot suggests symmetry . There was no evidence of a non-linear dose–response association . No significant association was observed for the highest versus lowest fish intake category  . Each additional daily 100 g of red meat was positively associated with T2D risk  . The observed positive associations and heterogeneity persisted in additional analyses stratified by age, sex, follow-up length, geographic location, number of cases, and dietary assessment method. We observed a positive association for studies conducted in America and Europe in both the high versus low and the dose–response analysis, but not in Asian studies (Supplementary Table S23). There was some evidence of heterogeneity between subgroups in stratified analyses (≥1000 vs. <1000 cases). There was no significant evidence for small study effects in the both high versus low and dose–response meta-analysis. Visual inspection of the funnel plot suggests symmetry . There was no evidence of a non-linear dose–response association . A significant positive association was observed  . Each additional daily 50 g of processed meat was strongly associated with diabetes risk  . The observed positive associations and heterogeneity persisted in additional stratified analyses (Supplementary Table S24). We detected evidence of heterogeneity between subgroups in stratified analyses for geographic location, dietary assessment, and outcome assessment. There was significant evidence for small study effects in the dose–response meta-analysis, but not in the high versus low meta-analysis. Visual inspection of the funnel plot suggests that small studies showing inverse or null association may be missing . There was evidence of a non-linear dose–response association; the risk of T2D increased by 30% with increasing intakes up to 50 g/day. Moderate additional detrimental effects for increasing intake above this value were observed . A significant positive association was observed  . Each additional daily 250 ml of SSB was associated with T2D risk  . The observed positive associations persisted in additional stratified analyses (Supplementary Table S25). Some evidence of heterogeneity between subgroups in stratified analyses (follow-up length) was observed. There was significant evidence for small study effects in the dose–response meta-analysis, but not in the high versus low meta-analysis . Visual inspection of the funnel plot suggests that small studies showing inverse or null association may be missing. There was evidence of a non-linear dose–response association but the curve shows an increase of risk of T2D throughout all the range of SSB investigated . A significant positive association between T2D and SSB was observed . Findings including studies with low risk of bias suggest stronger inverse associations for fruit and whole grain consumption, and stronger positive associations for red meat and SSB intake in the dose–response analyses.We rated the quality of meta-evidence for the 12 food groups . The NutIn this meta-analysis we systematically assessed whether associations exist between 12 a priori defined food groups and T2D risk by applying high versus low, linear and non-linear dose–response analyses. In high versus low and linear dose–response meta-analysis, a link with T2D risk was identified for 6 out of the 12 food groups; for the consumption of whole grains, dairy, and fruits this association was inverse; for processed meat, red meat, and SSB consumption, the association was positive. However, we observed that 5 from the 12 food groups showed also a significant nonlinear association. A high confidence in the effect estimate according to the NutriGrade scoring was seen for whole grains, for red and processed meat, and for SSB. This observation is concordant with the overall importance of these food groups for T2D occurrence and prevention.Our findings are in line with previous meta-analyses conducted mostly on single food groups and not synoptically for 12 food groups as it was done in the present systematic review.Taken together, an inverse association between dairy products, fruits, whole grains and T2D as well as a positive association between red and processed meat, SSB and risk of T2D was reported –26, whilA protective effect of whole grain consumption against T2D is biologically plausible and several mechanisms may operate to reduce the risk. Thus, reduced adiposity may partly explain the beneficial effects of whole grains in the prevention of T2D . In addiThere is strong evidence that SSB consumption is associated with weight gain and obesity in adults . Sugars There is consistent evidence that red and processed meat is associated with T2D risk. The positive association for red meat could not be confirmed pooling two Asian studies. Whereas one of these studies showed a clear positive association between red meat and T2D risk , the ShaA recent meta-analysis showed that processed meat was associated with higher fasting glucose, and unprocessed red meat was associated with both higher fasting glucose and fasting insulin concentrations . WhereasSimilar to a previous meta-analysis we observed an inverse association of fruit and vegetable consumption and T2D . PotentiSeveral potential mechanisms are known for dairy products and T2D risk. There is some evidence that dairy products, especially those that are fermented, are associated with reduced risk of adiposity . MoreoveIn contrast to a non-significant linear association between eggs and T2D, we observed a 13% increased risk for approximately one serving/day in the non-linear meta-analysis. Moreover, there was a strong positive association between egg intake and risk of T2D among US- studies, whereas no association was observed for European and Asian studies. A possible explanation for this finding could be that in the US, eggs are frequently consumed with processed meat like bacon and sausages, which have been strongly associated with T2D risk.Although two , 46 out A positive association between dietary cholesterol intake and risk of gestational diabetes was shown also in the Omega study . There iThe results of the present meta-analysis add further scientific evidence supporting the inclusion of some food groups into food-based dietary guidelines for their potential role in preventing T2D. Optimal consumption of whole grains, vegetables, fruits, and dairy, and non-consumption of red meat, processed meat, SSB, and eggs was associated with an 81% reduced risk of T2D. Previous studies could show that diet plays an important role in T2D risk. A study from the EPIC-Potsdam cohort found occurrence of T2D to be particularly sensitive to lifestyle factors including diet compared to diseases such as coronary heart disease, stroke, or cancer . One of Reduction of SSB offers one of the most important strategies to reduce the global burden of T2D. SSB can easily be replaced by water. In line with this approach are public health strategies to increase the cost for this food by levying tax or introducing sugar duty on SSB, which has been implemented in several countries including European countries, several states of the US, and Mexico . AnotherSpecific dietary guidelines for the primary prevention of T2D by the American Diabetes Association include only one food-based recommendation: whole grains should constitute one-half of the total grain intake , whereasThe present systematic review has several limitations. For some included studies, only baseline food intake was used (assuming a stable consumption over time). The included studies showed substantial heterogeneity with respect to the analyzed population size, follow-up length, baseline age, and food consumption. Moreover, only a few prospective studies reported nut intake, therefore the results should be interpreted with caution.The strengths of the present meta-analysis include the a priori published systematic review protocol, the comprehensive literature search, the large number of included prospective studies and food groups, the different types of analyses , the calculated servings and its associated risk for T2D, and the application of the NutriGrade scoring system to assess the quality of meta-evidence for each food group. Because we based our analyses on prospective studies, we effectively avoided recall bias and reduced the potential for selection bias.Among the investigated food groups, selecting specific optimal intakes  can lead to a considerable change in risk of T2D.Supplementary material 1 (PDF 914 kb)Below is the link to the electronic supplementary material.


The relationship between intake of fish and n-3 fatty acids and endometrial cancer risk has not been consistent across epidemiological studies. We quantitatively assessed the aforementioned association through a systematic review and meta-analysis. PubMed and Embase were searched through March 2017 for eligible epidemiological studies. Fixed or random-effects models were used to pool relative risks (RRs) and 95% confidence intervals (CIs). The dose-response relationship was also evaluated. Based on the literature search, five prospective studies and 11 case-control studies were identified. All 16 studies were categorized as high-quality studies. After pooling available risk estimates, no significant association was detected between overall fish intake and endometrial cancer risk. In subgroup analyses, every one additional serving/week of fish intake was significantly associated with inversed endometrial cancer risk in studies adjusted for smoking (RR (95% CI): 0.95 (0.91–1.00)), or studies performed in Europe (RR (95% CI): 0.90 (0.84–0.97)), but not in other tested subgroups. In studies conducted in Asia, there was significant positive association (RR (95% CI): 1.15 (1.10–1.21)). Regarding n-3 PUFA intake, marginally inverse associations of high EPA or DHA intake were detected (EPA: RR (95% CI) = 0.79 (0.61–1.04); DHA: RR (95% CI) = 0.85 (0.64–1.11)). Dose-response analyses suggested a significant nonlinear relationship between DHA intake and endometrial cancer risk (p: 0.04). Overall, this meta-analysis suggests that intake of n-3 PUFA may be inversely associated with endometrial cancer risk at some level of evidence, although the exact relationship, especially for fish intake, needs further characterization. Further well-designed studies are warranted. As one of the most common female pelvic malignancies, endometrial cancer represents the sixth leading cause of cancer incidence in women worldwide in 2012 –12. ReseBandera et al. conducted a meta-analysis summarizing studies up to 2006 and identified no association between overall fish intake and endometrial cancer risk . In thisn = 4), did not report usable data of risk estimates (n = 18), or contained duplicate subjects with other larger studies (n = 4). We further identified 3 additional eligible studies by screening the reference lists of the included studies and relevant review and meta-analysis publications. Overall, a total of 16 studies met our inclusion criteria and were included in the meta-analysis [The detailed literature search and article screening processes are shown in Figure analysis , 28–31. vs. lowest category of fish consumption and endometrial cancer risk , with relatively high heterogeneity  or Begg’s test (p for bias: 0.631). According to the subgroup analyses . The test for nonlinearity suggested that a linear relationship might be more appropriate (p for nonlinearity: 0.77). Assuming a linear relationship, we also incorporated two additional studies with available data [P for heterogeneity < 0.001)  Table . Subgrou1) Table , and a s1) Table . Further1) Table .I2 = 57.7%). Based on dose-response analyses of two studies [p: 0.24), nor a significant linear relationship (p: 0.66) of EPA intake.After pooling relevant association estimates from four studies –18, 24,  studies , 24, theI2 = 59.6%). The dose-response analysis suggested a significant non-linear relationship between DHA intake and endometrial cancer risk .Based on four studies –18, 24 rWe performed a comprehensive systematic review and meta-analysis of epidemiological studies to assess the association between intake of fish/n-3 PUFA and endometrial cancer risk. After summarizing all available evidence, no significant association was detected for intake of overall fish, which is consistent with findings from an earlier meta-analysis . HoweverThe identified inverse association between DHA intake and endometrial cancer risk is plausible from biological perspectives. DHA is associated with reduced inflammation –35, whicOur finding of a null association of overall fish intake may be explained by several reasons. One possible explanation is that only fatty fish is associated with reduced endometrial cancer risk due to its enrichment of n-3 PUFA, and thus many studies assessing the overall fish intake could not identify the association due to the mixture of fish types evaluated. In a nation-wide case-control study in Sweden, it was indeed that only consumption of fatty fish, but not other types of fish, was significantly associated with reduced endometrial cancer risk. Another reason is that different methods of cooking/preparing fish may induce the heterogeneities across studies. For example, in China, people often tend to cook fish using deep frying methods, which could lead to formation of mutagens and carcinogens, such as heterocyclic amines , 29. ManOur study has several strengths. To our knowledge, this is the most comprehensive meta-analysis evaluating the association between fish consumption and endometrial cancer risk. The synthetization of evidence focusing on n-3 PUFA with endometrial cancer risk, based on our knowledge, is for the first time. In addition to conducting multiple subgroup analyses to further evaluate the association, we performed dose-response analyses to further clarify the relationship. Findings of our analyses suggested a potential beneficial role of DHA/EPA in reducing endometrial cancer development, which warrants further investigation.Several potential limitations of the present study need to be acknowledged. First, as mentioned above, the fact that we do not have access to the individual level data from the included studies raises a possibility that the association estimates used in our study may not be fully adjusted for. Reproductive factors and smoking are known risk factors for endometrial cancer , 47, 48.In conclusion, after summarizing all available evidence from epidemiological studies, intake of fish is significantly associated with reduced endometrial cancer risk in studies adjusted for smoking and those conducted in Europe. DHA tends to be inversely associated with risk of endometrial cancer in a nonlinear relationship. Further well-designed studies are warranted to better characterize the relationship between fish, n-3 PUFA and endometrial cancer development.We conducted a literature search of PubMed (MEDLINE) and Embase through March 2017 to identify eligible epidemiological studies. The following search keywords were used:  AND  AND . There was no language restriction. We also reviewed the reference lists of the identified articles and related review and meta-analysis articles to identify additional potential studies.i) were prospective studies or case-control studies, (ii) evaluated the association between fish intake or n-3 PUFA intake (EPA or DHA) and endometrial cancer risk, and (iii) presented odds ratio (OR), relative risk (RR), or hazard ratio (HR) estimates with 95% confidence intervals (CI) or necessary data for calculation. Studies were included regardless of sample size. If multiple publications regarding the same study were identified, we retained the study with the largest number of cases in our analyses.Studies were eligible if they . If there were multiple estimates of the association, we used the estimate with adjustments for the most appropriate covariates.To assess the quality of included studies, we used the Newcastle-Ottawa Quality Assessment Scale . This scI2 were used to assess heterogeneity across studies, with a I2 > 50% suggesting high heterogeneity [p value of less than 0.05 was considered to indicate significant publication bias.We synthesized association estimates for intake of fish, EPA, and DHA. For each one, pooled estimates comparing the highest category and the lowest category of dietary intake were synthesized. Due to the rarity of endometrial cancer in the general population, ORs and HRs were deemed equivalent to RRs and RRs were used to represent association estimates. The ogeneity , 52. Theogeneity , and theogeneity . We alsoogeneity  and Beggogeneity  were perFor the dose-response analyses, we explored both non-linear and linear relationships between intake of fish/n-3 PUFA (EPA or DHA) and endometrial cancer risk . The met


Introduction: There is no global consensus on the relationship of dairy products withcardiovascular diseases. This study was conducted to evaluate the effect of the consumption ofdairy products on cardiovascular diseases, including stroke and coronary heart disease (CHD).Methods: Important electronic databases such as the Scopus, Science Direct, and PubMed wereevaluated up to September 2014. All prospective cohort studies that evaluated the relationshipbetween dairy products consumption and cardiovascular diseases were included regardless oftheir publication date and language. The study participants were evaluated regardless of age, sex,and ethnicity. The STROBE checklist was used to assess quality of the study. Two investigatorsseparately selected the studies and extracted the data. The designated effects were risk ratio (RR)and hazard ratio (HR). The random effect model was used to combine the results.Results: Meta-analysis was performed on 27 studies. There were 8648 cases of cardiovasculardiseases (CVD), 11806 cases of CHD, and 29300 cases of stroke. An inverse association wasfound between total dairy intake and CVD  and stroke  while no association was observed between total dairy intake and CHD. Thetotal diary intake was associated with decreased mortality of stroke although it had no association with its incidence .Conclusion: This is the first meta-analysis of the relationship of total dairy intake with CVD. Thisstudy showed an inverse relationship between total dairy intake and CVD while no relationshipwas found for CHD. Considering the limited number of studies in this regard, more studies arerequired to investigate the effect of different factors on the association of dairy intake and CVD. According to the World Health Organization (WHO) statistics, an estimated 17.5 million people died from CVDs in 2012, representing 31% of all global deaths. Of these deaths, an estimated 7.4 million were due to coronary heart disease (CHD) and 6.7 million were due to stroke.7 Dairy products are a major source of energy, protein, and calcium. The pattern of the dairy consumption is different in different parts of the world depending on cultural patterns and income. The highest consumption of dairy products is reported in North American and European countries. The consumption of milk is markedly high in the northernmost and Central European and North American countries while the consumption of cheese is high in Mediterranean countries like France, Italy, and Spain.11Different factors have been suggested as the causes of CVD, including behavioral risk factors related to unhealthy diet and obesity, lack of physical activity, excess alcohol consumption, and smoking, among which inappropriate diet is the most important.15 while some other researchers believe that dairy products have a protective effect.19 The results of some studies have shown no relationship between the consumption of dairy products and the mortality of cardiovascular diseases.22Previous studies have published different reports regarding the effect of dairy consumption on CVD like stroke and CHD. Some researchers believe that increased intake of dairy products increases the risk of CVD25 It seems that a meta-analysis is essential to summarize the previous studies. Therefore, this study was conducted to summarize the results of the previous studies in order to reach a single conclusion.There is no global consensus on the relationship of dairy consumption with CVD. Since no meta-analysis has evaluated the effect of total dairy intake on CVD and the available studies have either addressed dairy consumption and stroke, or the number of the studies or their exposures are limited,Our search strategy was to use a combination of the following keywords: “dairy” OR “milk” OR “cheese” OR “butter” OR “cream” OR “yogurt” OR “yoghurt” AND “cerebrovascular disease” OR “cardiovascular diseases” OR “stroke” OR “cerebral infarction” AND “coronary heart disease” OR “myocardial infarction” OR “MI” OR “ischemic heart disease” OR “IHD” AND “mortality” OR “incidence” OR “survival”.We searched three databases: PubMed (1945 to September 2014), Science Direct (1823 to September 2014), and Scopus (1973 to September 2014). We used the references of the studies, especially systematic review studies.http://www.who.int/classifications/icd/en). In addition, it included cardiac arrest (I46), heart failure (I50), and sudden death (R69). CHD was considered as acute myocardial infarction, angina pectoris, and other ischemic heart disease (as in ICD- 10 I20-I25).All cohort studies that evaluated the relationship between dairy intake and CVD were included in the study regardless of their language and publication year. Our population was all healthy individuals regardless of age, gender, and ethnicity; therefore, studies whose baseline population had diseases like diabetes or CVD were excluded from our study. We defined exposure as all dairy products and the outcome of the study was the incidence or mortality of CVD (stroke or CHD). CVD included stroke and CHD  were responsible for selecting the studies independently. These researchers were not blind to the name of the authors and the journal and their results. When there was an opinion disagreement, decision was made after consulting with the third researcher (NS). The two researchers extracted the data from the selected studies. The extracted variables for data analysis included the name of the first author, study title, publication year, study location, age of the participants in the beginning of the study, sample volume, number of cases, follow-up duration, sex, type of dairy product, study outcome , RR (95% CI) or HR (95% CI) for the highest vs. lowest categories of dairy foods and variables adjusted in the analysis. RR was considered with greatest degree of control for potential confounders. If data were duplicated in more than one study, we included the study with the largest number of cases.26 Two researchers (GF and MK) evaluated the quality of the studies separately. The evaluated items included (a) mentioning the study design accurately (here prospective), (b) explaining how the exposure was measured accurately (here dairy products), (c) explaining how the outcome was measured accurately , (d) explaining the duration of data collection and follow-up, (e) explaining the inclusion and exclusion criteria, and (f) explaining how loss to follow-up was addressed.The STROBE checklist was used to evaluate the risk of bias and the quality of the studies.Pooled measures were calculated as the inverse variance-weighted mean of the logarithm of RR and HR with 95% CI to assess the strength of association. As for the relationship of dairy products with CVD, if more than two products were evaluated in a study, they were first merged and one overall effect was reported for each study. The results were reported separately for men and women. Butter, cream, ice cream, high fat milk, cream cheese, and chocolate milk were considered high fat or whole dairy products. Stata version 12 was used for data analysis. The effect was reported using the random effect model. P value less than 0.05 was considered significant.2 according to the Higgins classification in which I2 values of 25%, 50%, and 75% indicate low, moderate, and high heterogeneity, respectively.27 We used a funnel plot28 and the Egger test29 to evaluate publication bias.Heterogeneity was evaluated quantitatively using I30 and a study is excessively influential if the significance of its “omitted” meta-analytic estimate differed relative to the overall estimate. Meta-regression was used to evaluate heterogeneity between studies.31Sensitivity analysis was performed with one study removed at a time,37 were excluded due to reporting the results of the populations of other studies37 and 30 studies were excluded because they did not report the data required for evaluating the relationship between dairy intake and CVD. Finally, 27 studies entered the meta-analysis. Ten studies with 12 separate results were entered into the CVD meta-analysis, covering a total of 140851 individuals and 8648 CVD cases. Seventeen studies with 21 separate results were entered into the CHD meta-analysis, including 47190 individuals and 11 806 CHD cases. Sixteen studies with 19 separate results were entered into the stroke meta-analysis, including 765 026 individuals and 29300 stroke cases. The FFQ questionnaire was used to estimate the consumption of dairy products in the 25 studies. One study used the 7-day household inventory method12 and another used to 3-day diet records38 to estimate the consumption of dairy products. The duration of follow-up was at least 10 years except for 3 studies.41 The results were presented according to sex in 5 studies.43 Twenty out of 27 studies were adjusted for important variables like age, sex, cigarette smoking, alcohol consumption, total energy intake, and BMI while adjustment for the above-mentioned variables was not performed in 7 studies.46 Twenty-one, four, and two studies were of high, moderate, and low quality, respectively   while no2=55.8% for CVD (P=0.04). Asymmetry was observed in the funnel plot  of the study after it was excluded. The results of sensitivity analysis for CVD showed that excluding each study did not change the overall estimate of the study significantly; this relationship was 0.90, ranging from 0.78 to 1.01.Heterogeneity was I for CVD . Considenel plot  due to s2=51.6% for CHD (P<0.001) (P=0.44), location  )P=0.96 (P=0.54) and low quality: (RR=0.68 [95% CI: 0.40-1.14]) (P=0.26), adjustment for 4 or more of the following covariates  yes: RR=0.96 (95% CI: 0.88-1.04); no: RR=1.11 (95% CI: 0.94-1.30) (P=0.15), sex/male: RR=1.01 (95% CI: 0.89-1.15); female: RR=0.99 (95% CI: 0.85-1.16) (P=0.95), and also fat content of dairy products   . Meta-re P=0.74; .P=0.71), mean age (P=0.91), and number of cases (P=0.52) were not among the sources of heterogeneity. There was no publication bias according to the Egger test (P=0.84). Its funnel plot is shown in Duration of follow-up (year) (2=63.1% for stroke (P<0.001)  while there was no association with its incidence (RR=0.96 [95% CI: 0.88-1.04]) (P<0.001). Total dairy intake may lower the risk of stroke in Asian studies (RR=0.79 [95% CI: 0.75-0.82]) compared to European studies (RR=0.96 [95% CI: 0.89-1.04]) (P<0.001). The estimated effect had no relationship with the following: moderate quality (RR=1.01 [95% CI: 0.84-1.04]) compared to high quality (RR=0.89 [95% CI: 0.85-0.94]) (P=0.05) and low quality (RR=0.79 [95% CI: 0.75-0.83]) compared to high quality (P=0.26), adjustment for 4 or more of the following covariates  yes: RR=0.91 (95% CI: 0.85-0.98); no: RR=0.79 (95%CI: 0.75-0.83) (P=0.1), sex/female: RR=0.78 (95% CI: 0.66-0.91), male: RR=0.92 (95% CI: 0.79-1.07) (P=0.90), and also fat content of dairy products  (P=0.62) (P=0.42), mean age (P=0.17), and number of cases (P=0.76) were not among the sources of heterogeneity. Although there was no publication bias according to the Egger test (P = 0.70), asymmetry was observed in the funnel plot  . Heterog(P=0.62) . Durationel plot  due to tThe findings of our meta-analysis showed that total dairy intake can lower the risk of CVD by 10% while it has no relationship with CHD. Total dairy intake has an inverse association with stroke and lowers its risk by up to 12%; this protective relationship can be attributed to low-fat dairy products while high-fat dairy products play no role in this regard. It should be noted that according to the results of our study, the consumption of dairy products only postpone stroke and lower its risk by 20% while it has no effect on its incidence.54 investigated the relationship between dairy intake and the risk of stroke and IHD  and concluded that the dairy intake lowered the risk of IHD and stroke; the results of this study regarding stroke are in line with our findings while the results of IHD are slightly different due to the smaller number of IHD cases and exposure to other item like calcium intake in addition to dairy products in the study by Elwood et al.A meta-analysis by Elwood et al in 201023 Moreover, in 2012, Larsson et al conducted a cohort study on a population of 74961 participants and reported that the consumption of low-fat dairy products decreased the relative risk of stroke .55 As for the mechanisms of this protective relationship, it can be stated that the intake of dairy products can lower the blood pressure which is an important risk factor of cardiovascular diseases.58 A study in 2009 confirmed this finding and reported that the HR of the participants who consumed low-fat dairy products was in the highest quantile .59Another meta-analysis study by Hu et al showed that the relationship between total dairy intake and stroke was protective . This relationship was attributed to low-fat dairy products. The results of this study are in line with our findings.60 It seems that this phenomenon is due to calcium in dairy products because calcium can decrease platelet aggregation and total cholesterol through creating insoluble complexes with fatty acids and decreasing their absorbance.61 Similarly, Hiroyasu reported that the risk of stroke was 31% less in women in the highest quintile of calcium intake versus those in the lowest quintile.62 However, it should also be noted that people who consume dairy products often pay more attention to other aspects of health which can affect their health status. For example, in 2008, a preventive medicine specialist reported that people who consumed low-fat dairy products were less likely to smoke or drink alcohol and had more physical activity and more vitamin use; moreover, they consumed more fruits, vegetables, and cereal and less red meat.63The results of a randomized controlled trial study showed that the systolic blood pressure of the individuals who used milk protein supplements was 2.3 mm Hg lower than the systolic blood pressure of those who used carbohydrates.25A meta-analysis performed by Qin et al on the relationship of dairy foods with CVD, stroke, and CHD showed that dairy products lowered the risk of CVD by 12% which is in line with our results. However, few studies were included in this study, and combining of all dairy products was not done to investigate the relationship and limited exposures were considered. Nonetheless, this study showed the protective role of dairy intake against stroke which is similar to our findings. No relationship was found between dairy intake and CHD in this study, which is again in line with our results.51 while in the study by Elwood et al, the risk of IHD was RR=0.79 (0.95% CI: 0.68–0.91) in individuals who had the highest consumption of dairy products.54 It seems that the contradictory results are due to different designs, different characteristics of the participants, adjustment for different confounders, different sample sizes, and the residual confounding effects of unknown variables.A prospective study on 4000 adults in London did not show any relationship between CHD and dairy products8 Another reason could be different classifications in different continents; the highest quintile was 132.6 g/d for men and 168.3 g/d for women in a study by Kondo et al in Japan in 201338 while the highest quintile was 1296 g/d in the study by Larsson et al in Sweden in 2009.14The relationship between total dairy intake and stroke was significant in Asia and not in Europe, may be due to different patterns of dairy consumption in different parts of the world. The mean dairy intake was more than 200 g/d in the United States in 2000-2005 but less than 27 g in a country like China.14 Therefore, more studies are required to shed light on the relationship of dairy intake in male smokers and stroke. Considering these limitations, more studies should be performed in this regard. However, our study showed the protective role of dairy consumption on stroke and CVD which is of clinical significance.This study had some potential limitations and biases. It should be noted that although cohort studies are valuable ones, they are weaker than RCT studies for detecting causality; therefore, causal interpretations should be made with caution. Moreover, the limited number of studies and non-availability of the full text of some articles despite a great deal of efforts were other limitations of the study, which might have led to selection bias. On the other hand, it was not possible to calculate the crude effect because the required data were not available and analysis was performed on adjusted effects. Therefore, there is the possibility of residual confounding. However, considering the relatively good data of the studies, analysis was performed in different subgroups separately. Since few studies have evaluated the relationship between dairy consumption and different types of stroke and CHD, more studies are required in this regard. Despite the heterogeneity and lack of publication bias in our meta-analysis due to the limited number of included studies, caution should be exercised when interpreting the results. The results of sensitivity meta-analysis in stroke showed that the study by Larsson et al in 2009 was a source of heterogeneity because male smokers were investigated in this study and smoking is a risk factor of stroke.This is the first meta-analysis addressing the relationship between total dairy intake and CVD. The results showed a possible inverse association between total dairy intake and CVD and stroke while no association was observed between total dairy intake and CHD. Due to the limited number of studies in this regard, more studies investigating all factors associated with cardiovascular diseases are required to make a definite conclusion.The local ethical committee reviewed and approved the study.None.We would like to thank all those researchers who helped us to conduct this study.


TNF-α -308 G > A (rs1800629) polymorphism and CD susceptibility have yielded inconsistent results. In this study, PubMed, EMBASE, and Google Scholar web-databases were searched for pertinent reports showing association of TNF-α -308 G > A gene with CD risk. A total of eleven reports involving 1774 controls and 1147 CD cases were included. Significant associations in four genetic models, viz. variant allele , variant homozygous , recessive  and dominant  were found in comparison with wild type homozygous GG genotype. However, heterozygous genetic model did not show any association. Sensitivity analysis revealed stable and statistically robust results. Our results suggest that TNF-α -308 G > A gene polymorphism significantly contributes to CD susceptibility.Celiac disease (CD) remains one of the most significant autoimmune diseases worldwide. The pathogenesis of CD is not clearly understood and is probably attributed to genomic variations and host genetic make-up. Case-control and cohort studies of the association between the  Celiac disease  is a chronic inflammatory autoimmune disorder characterized by abnormalities in the small intestine caused by permanent intolerance to dietary gluten or related proteins from wheat and rye3TNF-α gene has close linkage between HLA class I and class IITNF-α gene has been correlated with various autoimmune diseasesTNF-α geneTNF-α -308G allele, A allele has higher transcriptional activity and often connected to autoimmune diseases12TNF-α gene has raised the possibility that this polymorphism may influence immunologic homeostasis and contribute to the pathogenesis of CD.Tumor necrosis factor-alpha (TNF-α) is a potentpro-inflammatory and immunoregulatory cytokine mapped on chromosome 6 (6p21.31) spanning about 3 kb and contains 4 exons. TNF-α stimulates many other cytokines and mediates the cytokine cascade that causes inflammationTNF-α -308 G > A gene polymorphism and CD susceptibility14151617181920212223TNF-α -308 G > A gene polymorphism and CD susceptibility. The schematic representation of the entire pooled study is presented as Graphical Abstract , EMBASE and Google Scholar search database were one hundred and sixty. All the retrieved hits (articles) were checked by reading their titles and abstracts, and the full texts for the possibly relevant publications. In addition, the articles were further scrutinized for their appropriateness for this meta-analysis . A PRISMTNF-α gene and CD susceptibility , homozygous variant , recessive  and dominant  genetic models in comparison with wild type GG genotype. However heterozygous  genetic model did not show any association. The Forest plots for all the genetic models are shown in After cautious appraisal, all the data from the selected eleven studies were pooled together that lead to 1774 controls and 1147 CD cases were included to evaluate the overall association between the TNF-α -308 G > A gene polymorphism and CD susceptibility were stable and statistically robust  is one of the best understood autoimmune disorders and genetic factors are considered to be strong determinants of this diseaseThe genetics involved in the development of CD is very complex, with evidence for the participation of multiple intrinsic (genetic) and extrinsic  factorsNevertheless, our current meta-analysis has some advantages, which could be summarizes as follows. First, we tried our best to find as many published studies by means of various searching approaches. Second, publication bias was not detected by funnel plot and Egger’slinear regression test, thus the all results were statistically robust. Third, sensitivity analysis also demonstrated that the results were not influenced by any single study. Fourth, we used strict data extraction and analysis to make satisfactory and reliable conclusion.TNF-α -308 G > A polymorphism with increased CD susceptibility. Hence, determining TNF-α -308A genotype is a probable determinant for the development of CD. Further, well designed large-scale studies with the considerations of gene-gene and gene-environment interactions are warranted to investigate this association. Future studies are encouraged to validate our current findings and to prove the clinical relevance of TNF-α -308 G > A polymorphism in the development of CD. Here, we analyzed the -308 G > A variant of TNF-α gene for the risk of CD without considering the interaction between several other SNPs. In future, we intend to explore other pertinent interactions to facilitate the discovery of CD development.In conclusion, we can say that meta-analysis is an extremely valuable and powerful tool for numerical data-analysis that takes in to account both statistically significant and non-significant data from the individual studies and results into a cumulative precise conclusion. To the best of our knowledge, this is the very first meta-analysis showing association of TNF-α gene OR TNF gene AND polymorphism OR mutation OR variant AND -308 rs1800629 AND Celiac OR Coeliac disease’ (last updated on May 2016). All the references present in the retrieved studies were also checked by hand search to identify the studies that possibly have not been included in these databases. All the published studies matching with the above mentioned eligibility criteria were selected and included in the present meta-analysis.Pertinent studies were cautiously identified by multiple comprehensive search of PubMed (Medline), EMBASE and Google Scholar online web databases covering all research articles published with a combination of the following key words: ‘Tumor necrosis factor-alpha gene OR TNF-α -308 G > A polymorphism and CD risk, (ii) reported original data from the case-control and cohort study, (iii) enrolled pathologically confirmed CD cases and CD-free controls, (iv) presented useful genotype frequency in all the cases as well as in the controls, and (v) must be published in the English language. The leading reasons for the exclusion of the studies were, overlapping of the data, review articles, abstract only, and case-only studies. The studies of TNF polymorphism to predict survival and expression level considering it as an indicator for the response to therapy were also excluded.In order to minimize heterogeneity and facilitate the accuracy of the findings, studies included in the present meta-analysis had to follow the preset criteria: (i) must evaluated For all the selected publications, the methodological quality assessment and the data extraction were independently abstracted in duplicate by two independent investigators using a standard protocol. The data accuracy was determined by using a data-collection form according to the pre-set inclusion criteria as stated in the above section. The quality assessment of the case-control studies for this meta-analysis was done by two independent investigators (AJ & SAD) based on the pre-set eligibility criteria of the present study, and sequential exclusion of the inappropriate studies. In case of disagreements between the two investigators on any item regarding the data collected from the retrieved studies, the issue was openly discussed in detail and an agreement was reached following a discussion with the adjudicator (RKM). The abstracted characteristics from the selected studies included the name of first author, the year of publication, the country of origin, sources of study, the number of cases/controls, genotyping methods and frequencies and association with CD.Methodological quality assessment of the included studies was done separately by two independent researchers using the Newcastle-Ottawa Scale (NOS) criteriaTNF-α -308 G > A gene polymorphism and CD risk. Heterogeneity belief associated with the selected studies was investigated by the chi-square based Q-test and I2 test2 value was less than 70%; otherwise, random-effects models were adopted39The pooled odds ratios (ORs) and their respective 95% confidence intervals (CIs) were calculated to evaluate the relation between How to cite this article: Khan, S. et al. TNF-α -308 G > A (rs1800629) Polymorphism is Associated with Celiac Disease: A Meta-analysis of 11 Case-Control Studies. Sci. Rep.6, 32677; doi: 10.1038/srep32677 (2016).