P = 0.005; I2 = 80.70 %, Pheterogeneity < 0.001). Subgroup analysis by statin type showed that the ADRs risk was significantly elevated among simvastatin users , but not among atorvastatin users. No significant relationship was found between the −388A>G polymorphism and ADRs caused by various statins . The meta-analysis suggests that SLCO1B1 −521T>C polymorphism may be a risk factor for statin-induced ADRs, especially in simvastatin therapy. Conversely, there may be no significant association for −388A>G polymorphism.An increasing number of studies have investigated the association between SLCO1B1 −521T>C and −388A>G polymorphisms and the risk of statin-induced adverse drug reactions (ADRs), but the results have been inconsistent. This meta-analysis was performed to gain more insight into the relationship. PubMed, Embase, Cochrane Library and Web of Science were searched for relevant articles published before March 5th, 2015. The quality of included studies was evaluated by the Newcastle-Ottawa Quality scale. Pooled effect estimates (odds ratios [ORs] or hazard ratios [HRs) and corresponding 95 % confidence intervals (CIs) were calculated to assess the association in overall and subgroup analyses for various genetic models. Begg’s rank correlation test and Egger’s linear regression test were used to examine the publication bias. A total of nine cohort and four case–control studies involving 11, 246 statin users, of whom 2, 355 developing ADRs were included in the analysis. Combined analysis revealed a significant association between the SLCO1B1−521T>C polymorphism and increased risk for ADRs caused by various statins, but the synthesis heterogeneity was generally large (dominant model: pooled effect estimate = 1.85, 95 % CI 1.20–2.85,  Statins or the 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitors have become the most important pharmaceutical intervention for the primary and secondary prevention of cardiovascular diseases by lowering blood concentrations of low density lipoprotein cholesterol (LDL-C)   independently. Any discordance was subsequently resolved through discussion or a third party (Zhang). Studies were considered eligible if they met all of the following criteria: (1) It investigated the association between −521T>C or −388A>G polymorphisms in the SLCO1B1 gene and the risk of statin-induced ADRs; (2) It provided effect estimates  and their corresponding 95 % confidence intervals (95 % CIs) or allele or genotype frequencies for calculating the effect estimates; (3) The publication language was English. Studies consistent with any of the following conditions were excluded: (1) Reviews, case reports, comments, letters, news, editorials; (2) In vitro or animal trials; (3) Studies lacking information necessary or usable data for the analysis; (4) For overlapping and republished studies, only the most recent or the largest population was included.Data were extracted independently by two reviewers (Jiang and Tang). Disagreements were solved by discussion, and a third party (Zhang) was involved when necessary. The collected information included: first author, year of publication, country where study was conducted, ethnicity, study design, definition of ADRs, characteristics of participants, statin type, dose and regimen, sample size, polymorphism region, allele or genotype frequencies in patients with or without ADRs during the treatment of statins, crude and adjusted effect estimates  and their corresponding 95 % CIs as reported, any multivariate analyses adjustment factors, genotyping method, and information about Hardy–Weinberg Equilibrium (HWE).Newcastle-Ottawa Quality scale (NOS) , the Mantel–Haenszel fixed effect model was used (Mantel and Haenszel www.stata.com) software. A P value of 0.05 for any test or model was considered to be statistically significant.The effect estimates that were extracted, if available, or de novo calculated from available data, were crude and adjusted ORs and HRs. We pooled OR estimates and HR estimates for each study together. If both the crude and the adjusted effect estimates were available for the same outcome, we incorporated the adjusted one into the analysis. Pooled effect estimates were calculated for all of the following genetic models: the allele contrast, the homozygote comparison, the heterozygote comparison, the dominant model, the recessive model, and the additive model respectively. Heterogeneity among included studies was assessed by Chi square-based A total of 676 records were yielded by the search strategy from four electronic databases. Among these, 35 publications met the inclusion criteria after title and abstract screening. Based on full-text inspection, we excluded another 25 publications because 11 of them lacked information necessary or usable data for the analysis ; the homozygote comparison ; the dominant model ; the recessive model  and the additive model , but not for the heterozygote comparison . Figure All of the 13 included studies explored the association between −521T>C polymorphism of the SLCO1B1 gene and statin-induced ADRs. The results of meta-analysis are presented in Table P = 0.005), the homozygote comparison , the dominant model   and the additive model . Whereas in contrast, the combined effect estimates for atorvastatin-induced ADRs were far from being statistically significant in any of the six genetic models. The association between the −521T>C polymorphism and atorvastatin-induced ADRs in the dominant model is shown in Fig. In the stratified analysis by statin type Table , the synP = 0.526; the additive model: pooled effect estimate = 0.91, 95 % CI 0.81–1.02, P = 0.114)  and 1.34  respectively. In addition, the result changed and became insignificant when we excluded the study by Carr et al. (P = 0.059). The results were not materially altered for other analysis except for the above situations.For −521T>C polymorphism and risk of ADRs induced by any statin, the conclusion of insignificant association for the heterozygote comparison was materially altered by removing the study by de Keyser et al.  with ther et al.  in the hP > 0.05 for all of the genetic models) except in the analysis of −521T>C polymorphism and ADRs induced by any statin in the heterozygote comparison  and the additive model      per copy of the C allele in patients taking 80 mg of simvastatin daily in the SEARCH study was approximately 2 times of that in those taking 40 mg daily within the Heart Protection Study . Besides, Carr et al. (P = 0.004), however, we extracted the HR for whole population, which showed no significance, other than the outcome of stratification analysis. Therefore, we could anticipate that a significant higher risk would appear if patients are prescribed to high dose atorvastatin. Puccetti et al. (P < 0.001). Since the genetic model under which the reported OR had been calculated was not available, we did not incorporate this study into our meta-analysis, which may influence our results.There remains uncertainty about the biological mechanisms underlying the statin-associated myopathy but statin concentrations in the blood was one possible reason Stewart . A non-sr et al.  discoverr et al.  recommenr et al. , an assoi et al.  conducteThe −388A>G is another common variant in the SLCO1B1 gene, which is in strong linkage disequilibrium with the −521T>C SNP , asthma (P = 0.080), and hypertension (P = 0.087) were determined, which might be confounders making the calculated OR biased consequently influencing the pooled result.When we performed the meta-analyses on association between SLCO1B1 −521T>C and ADRs caused by various statins, high heterogeneity was present in all genetic models except for the recessive model. The disparate definitions of ADRs, study design, characteristics of participants , statin type, dose and duration of treatment, and some other factors maybe the potential explanation. Unfortunately, we could only conduct the subgroup analysis for statin type but not other factors owing to the limited available data and small number of original studies. After stratification analyses, the r et al.  respectir et al.  for the Several limitations in our study may affect the results. Firstly, it is noteworthy that the definitions of statin-induced ADRs varied among individual studies, which contributed to the presence of heterogeneity to a large extent. Further studies using uniform definitions are required to reach more definitive conclusions. Secondly, the crude and adjusted effect estimates were combined together due to the limited available data from the original studies. Moreover, the adjusting factors for each effect estimate were not completely consistent. As such, some potential confounding risk factors may be introduced to influence our pooled results, such as the differences in statin therapy including dose and duration of treatment. It is indicated that methodological improvement in the individual studies should be focused. Thirdly, the data from original studies were insufficient. We could not perform further stratification analyses to explore dose-, gender-, age-, BMI- and comedication-gene interactions. Additionally, the limited number of studies on −388A>G polymorphism lowered our power and the results of meta-analyses should be interpreted with caution. Fourthly, we only included articles published in English in four databases, relevant articles published in other databases and in other languages and unpublished studies may have been missed. What’s more, as the number of included studies was small, the power of detecting the publication bias in Begg’s and Egger’s test was low. Finally, the original studies were entirely or predominantly based on Caucasians, thus additional researches in other ethnicities are needed to generalize the findings.In conclusion, our meta-analysis suggests that SLCO1B1 −521T>C polymorphism may be significantly associated with increased risk of statin-induced adverse reactions, especially in the simvastatin therapy. Conversely, the −521C minor allele might not modify the risk of atorvastatin-associated adverse effects. Besides, there may be no significant association between −388A>G polymorphism and statin-related adverse reactions. However, the finding should be interpreted with caution because of the small number of studies and small sample sizes. Well-designed epidemiological studies with large sample size in the treatment of various statins among different ethnicities should be carried out to confirm these associations and interaction between dose-, sex-, BMI-, extensive physical exercise-, comedication-gene should also be further investigated.


IL-10 gene with the risk for colorectal cancer and hepatocellular carcinoma. Qualification assessment and data collection were completed by two authors independently. The random-effects model using the DerSimonian and Laird method was fitted by the STATA software. Twenty-five articles involving 5933 cases and 9724 controls were meta-analyzed. Overall comparisons of the mutant alleles  of three promoter polymorphisms with alternative wild alleles failed to reveal any statistical significance for both colorectal cancer and hepatocellular carcinoma (P > 0.05), and the likelihood of heterogeneity was low (I2 < 50%). For −592C > A polymorphism, a significant risk for colorectal cancer was identified when analysis was restricted to East Asians  and retrospective studies . As weighed by the Egger’s test and the fill-and-trim method, there was a low probability of publication bias for all studied polymorphisms. Our findings collectively suggest that the −592C > A polymorphism in IL-10 gene might be a susceptibility locus for colorectal cancer in East Asians.Mounting evidence supports a potent inhibitory role of interleukin-10 (IL-10) in tumor carcinogenesis, angiogenesis and metastasis. This meta-analysis was designed to examine the association of three promoter polymorphisms  in  IL-10 gene on chromosome 1q31-q32 (gene ID: 3586), which comprises 5 exons and 4 introns. So far, there are 354 validated single nucleotide polymorphisms identified in IL-10 gene (http://www.ncbi.nlm.nih.gov/gene/3586). Human IL-10 in vivo is produced mainly by T-cells, B-cells, monocytes and macrophages, and its changes are under strong genetic control, with an estimated heritability of as high as 75%IL-10 genetic alterations may contribute not only to circulating IL-10 variation but also to cancer susceptibility.Interleukin-10 (IL-10) is an anti-inflammatory and immune-suppressive cytokine1IL-10 gene, three promoter polymorphisms including −592C > A (rs1800872), −819C > T (rs1800871) and −1082G > A (rs1800896) are well-defined and have been widely evaluated in predisposition to cancer at some sites89IL-10 gene are associated with hepatocellular carcinoma or colorectal cancer have shown controversial and inconclusive results8111214IL-10 gene with the risk of having colorectal cancer and hepatocellular carcinoma among 5933 cases and 9724 controls from 25 articles published in English.Of validated polymorphisms in  rs180089 are wellA rs180082, −819C To improve the quality of a systematic review, this meta-analysis was conducted according to the statement put forward by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)www.endnote.com, Thomson Reuters).Potentially relevant articles were retrieved by searching Medline (PubMed), EMBASE (Excerpta Medica Database) and Web of Science using the following subject words: (interleukin-10 OR IL-10 OR IL 10) AND  AND  as of January 1, 2016. All retrieved articles were managed by the EndNote X5 software  genetic data: the genotype or allele distributions of studied polymorphism(s) between cases and controls or the associated odds ratio (OR) and 95% confidence interval (CI). In case of duplicated publications from the same study group, article with a larger sample size was retained. Qualification assessment was completed independently by two investigators (Yan-Hui Shi and Chang-Zhu Lu), and if necessary a discussion was made over any uncertainties encountered.As a prerequisite, all potential articles must be published in English. In addition, articles were qualified if they simultaneously satisfied the following criteria: (1) clinical endpoint: colorectal cancer or hepatocellular carcinoma; (2) study design: retrospective or nested case-control design; (3) studied polymorphisms: at least one of the three promoter polymorphisms, −592C > A, −819C > T and −1082G > A, in From each qualified article, the same two investigators (Yan-Hui Shi and Chang-Zhu Lu) collected and typed relevant information into a standardized Excel template, including the first author’s surname, publication year, the country where study subjects resided, race, cancer type, matched condition, source of controls, study design, sample size, age, gender, smoking, drinking and family history of cancer, hepatitis B virus (HBV) and hepatitis C virus (HCV), as well as the genotype or allele distributions of studied polymorphisms between cases and controls. Two independently-completed templates were cross-checked with inconsistencies solved by consensus. The detailed characteristics of all qualified articles are summarized in All statistical analyses are carried out with the STATA software for the Windows version 12.0 . For all studied polymorphisms, deviation from the Hardy-Weinberg equilibrium for each polymorphism was assessed by the Chi-squared test or the Fisher’s exact test where appropriate in control groups at a significance level of 5%.I2) is calculated, and it denotes the percent of observed diversity that is explained by heterogeneity rather than by chance. If the I2 is over 50% - a generally accepted cutoff value, it is indicative of significant heterogeneity. Individual effect-size estimates, ORs and its 95% CIs, were calculated under the fixed-effects model adopting the Mantel-Haenszel methodTo statistically quantify the between-study heterogeneity, the inconsistency index . There were 17 studies with total sample size of 300 or more, and 8 studies of less than 300.For both colorectal cancer and hepatocellular carcinoma, cases tended to be older , male gender  and smokers (P = 0.035 and 0.059) relative to controls. Moreover for hepatocellular carcinoma, the percentage of cases with HVB was exceedingly higher than that of controls .I2 (<50%), except for the association of −592C > A polymorphism with colorectal cancer under the allelic model (I2 = 52.3%) and with hepatocellular carcinoma under the dominant model (I2 = 59.3%), as well as for the association of −891C > T polymorphism with colorectal cancer under both allelic (I2 = 72.0%) and dominant (I2 = 56.1%) models.Given the small number of mutant homozygous genotypes of three studied polymorphisms, individual effect-size estimates were pooled only on the basis of both allelic and dominant models. Overall comparisons of the mutant alleles  with the alternative wild alleles failed to reveal any statistical significance (P > 0.05) for both colorectal cancer and hepatocellular carcinoma under both allelic and dominant models , 3, 4, aConsidering the limited number of qualified studies for −819C > T polymorphism, the exploration of clinical heterogeneity by stratified analyses was only presented for −592C > A and −1082G > A polymorphisms under both allelic and dominant models  and 3. FIL-10 gene associated with colorectal cancer and hepatocellular carcinoma, influential analyses confirmed the overall changes in direction and magnitude under both allelic and dominant models.For three studied polymorphisms in By modeling age, gender, smoking, drinking and family history of cancer, HBV and HCV (HBV and HCV for hepatocellular carcinoma only), the meta-regression analyses failed to detect any positive signals for three studied polymorphisms in association with both colorectal cancer and hepatocellular carcinoma under both allelic and dominant models .As weighed by the Egger’s test, there was a low probability of publication bias for three studied polymorphisms, except for −1082G > A polymorphism in association with hepatocellular carcinoma under the allelic model (Egger’s test: P = 0.042). As estimated by the trim-and-fill method, no missing studies were required to make the filled funnel plots symmetrical for three studied polymorphisms under both allelic  and domiIL-10 gene with colorectal cancer and hepatocellular carcinoma, we found that the −592C > A polymorphism might be a susceptibility locus for colorectal cancer in East Asians. Besides ethnic heterogeneity, study design might be another potential source of clinical heterogeneity for the association between −592C > A polymorphism and colorectal cancer. To our knowledge, this is so far the largest meta-analysis that has evaluated IL-10 gene multiple promoter polymorphisms with colorectal cancer and hepatocellular carcinoma risk.Through a comprehensive meta-analysis of three promoter polymorphisms in et al. who enrolled subjects of only Caucasian descentet al.et al.11Differing from the findings of previous meta-analysis by Zhang IL-10 gene with hepatocellular carcinoma in this meta-analysis, inconsistent with the findings of the previous meta-analysis by Wei et al.12212224252838I2 = 37.2% in contrast to 0.0% in Wei et al’s meta-analysisIL-10 gene are not biologically functional, and it is possible that the relative risk attributable to a single allele is smallThrough exhaustive data explorations, there is no hint of significance for the association of three studied polymorphisms in IL-10 gene, and the other polymorphisms were not considered due to insufficient available data. Third, the only significant finding in this meta-analysis was based only on two eligible studies, leaving some room for further criticism. Fourth, all enrolled studies are case-control in design, which precluded the causality exploration. Fifth, only the risk of having colorectal cancer or hepatocellular carcinoma was treated as the clinical endpoint, and it is of interest to investigate whether the studied polymorphisms are associated with the recurrence and survival during subsequent medical therapies.Finally, some possible limitations need to be acknowledged when interpreting and extrapolating our meta-analytical findings. First, our literature retrieval was only limited to articles published in English, and doing so might introduce a selection biasIL-10 gene found that the -592C > A polymorphism might be a susceptibility locus for colorectal cancer in East Asians. Considering the ubiquity of genetic heterogeneity and in view of small sample sizes involved, our findings should be considered to be preliminary until being replicated or confirmed in other larger, well-designed studies in future investigations.Taken together, we in an updated meta-analysis of three promoter polymorphisms in How to cite this article: Shi, Y.-H. et al. The association of three promoter polymorphisms in interleukin-10 genewith the risk for colorectal cancer and hepatocellular carcinoma: A meta-analysis. Sci. Rep.6, 30809; doi: 10.1038/srep30809 (2016).


Maternal gestational smoking, diabetes, alcohol drinking, and pre-pregnancy obesity are thought to increase the risk of cryptorchidism in newborn males, but the evidence is inconsistent.We conducted a systematic review and meta-analysis of studies on the association between maternal gestational smoking, diabetes, alcohol drinking, and pre-pregnancy obesity and the risk of cryptorchidism. Articles were retrieved by searching PubMed and ScienceDirect, and the meta-analysis was conducted using Stata/SE 12.0 software. Sensitivity analysis was used to evaluate the influence of confounding variables.We selected 32 articles, including 12 case—control, five nested case—control, and 15 cohort studies. The meta-analysis showed that maternal smoking  or diabetes  during pregnancy were associated with increased risk of cryptorchidism. Overall, the association between maternal alcohol drinking , pre-pregnancy body mass index  and risk of cryptorchidism were not statistically significant. Additional analysis showed reduced risk  of cryptorchidism with moderate alcohol drinking during pregnancy. No dose—response relationship was observed for increments in body mass index in the risk of cryptorchidism. Sensitivity analysis revealed an unstable result for the association between maternal diabetes, alcohol drinking and cryptorchidism. Moderate heterogeneity was detected in studies of the effect of maternal alcohol drinking and diabetes. No publication bias was detected.Maternal gestational smoking, but not maternal pre-pregnancy overweight or obesity, was associated with increased cryptorchidism risk in the offspring. Moderate alcohol drinking may reduce the risk of cryptorchidism while gestational diabetes may be a risk factor, but further studies are needed to verify this. Cryptorchidism is a genital malformation of newborn males, in which one or both testes are absent from the scrotum at birth. It has a prevalence of 1.63 to 2.90% . Nearly The causes of cryptorchidism are not well understood. In addition to genetic alterations  and expoWe conducted a systematic review and meta-analysis of current observational studies following the PRISMA statement  S1 PRIS. Our priThe studies selected for analysis satisfied the following criteria. (1) The studies included newborn males diagnosed with cryptorchidism in case group. (2) The effects of maternal gestational smoking, diabetes, alcohol drinking or maternal pre-pregnancy body mass index (BMI) were investigated. (3) The control or non-case group comprised boys without cryptorchidism. (4) The study was of a cohort, case—control, or nested case—control design. (5) Complete data were reported; or missing data could be obtained from the study investigators. Response letters or meeting papers were also considered if additional information was provided.We searched PubMed and ScienceDirect for relevant, English-language studies published to February 10, 2014. The PubMed search terms were: [ OR  OR  OR (pre-pregnancy obesity OR pre-pregnancy overweight OR pre-pregnancy body mass index) OR (risk factors)] AND (cryptorchidism OR undescended testes OR cryptorchism) AND (human). We also manually searched the reference lists of retrieved articles and reviews.Two reviewers (L. Zhang and X.-H. Wang) independently extracted the author names, publication year, country, study type, the number of cryptorchidism cases, controls or non-cases or person years, exposure categories, adjusted or crude relative risk (RR), odds ratio (OR), hazard ratio (HR), or prevalence ratio (PR) with 95% confidence intervals (CIs), and adjusted variables. A standardized data collection form was used. When more than one OR  was shown, the one from multivariate-adjusted was extracted to account for the influence of potential confounders. If a study included two or more control groups, the one that matched more of the study variables or was population-based was analyzed. A third author (T.Z. Liu) independently reviewed the articles for the extracted information, which were then discussed by all authors to decide on inclusion.0) in the control group. It should be noted that, this conversion may overestimate the variance of OR [0 could not be obtained since the incidence of cryptorchidism is low (< 10%) that RR is similar to OR, as described by Zhang et al. [2 statistics to detect statistical heterogeneity, which varied from 0 to 100% and was described as low (0–40%), moderate (30–60%), substantial (50–90%), and considerable (75–100%) [2 < 30%) was detected; otherwise, a random-effect model was used. Studies that reported results separately by area, sex, or race, the ORs were pooled using a fixed-effects model before combining it to overall meta-analysis. Subgroup analysis  was used to address heterogeneity. The ORs and 95%CI were log-transformed and the weight was calculated by the inverse variance method.In the first part of the analysis, we pooled the ORs and 95% CIs of cryptorchidism for the mother who smoking, drinking, with gestational diabetes or pre-pregnancy obesity. For studies that did not provide valid evaluations, we used the reported tabular data to calculate crude ORs with their 95% confidence intervals (CIs). If the raw data included a zero cell, 0.5 was added to every cell in the 2 x 2 table. Studies with two or more zero cells in 2 x 2 tables were excluded. In the meta-analysis, hazard ratios (HRs) and prevalence ratio (PRs) were considered as RRs; and then relative risk (RRs) and relevant standard error (SE) were converted into ORs using the method described by Zhang et al , which rce of OR . We poolg et al. . We used75–100%) . A fixedTo determine whether high and low exposure resulted in differences in the risk of cryptorchism , we pooled the ORs of high or moderate separately, and compared them to ORs of low exposure groups. We also evaluated potential dose-response relationships as previously described by Orsini et al.  when a sEgger’s test and Begg’s test were used to detect potential publication bias, and a sensitivity analysis was performed to evaluate the robustness of the results. All the analyses were conducted using Stata/SE 12.0 software .Thirty-two studies were selected , 27–50. 2 = 28.30%, P = 0.10) among studies.  was seen among the studies. A Forest plot for maternal gestational diabetes and risk of cryptorchidism is shown in Thirteen studies including 15,373 cases investigated the relationship between maternal gestational diabetes and risk of cryptorchidism , 45, 48.2 = 35.80%, P = 0.08) was detected  compared with those who had a BMI < 25 kg /m2. No obvious heterogeneity  was detected. Subgroup analyses showed that neither maternal obesity (BMI ≥ 30 kg /m2) nor pre-pregnancy overweight (25 kg /m2 ≤ BMI < 30 kg/m2) associated with the risk of cryptorchidism , see Eight studies investigated the association between maternal pre-pregnancy BMI and the risk of cryptorchidism , 40, 41.2 = 78.00%) while moderate-level exposure associated decreased risk , see Several studies , 34, 37 2 increment of BMI was not associated with the risk of cryptorchidism . No obvious heterogeneity was detected .Five studies , 40, 41 2 = 54.60%, P = 0.02), cohort studies , studies adjusted for variables , and studies reporting positive results . For maternal diabetes, high heterogeneity was found in European studies , studies adjusted for variables , and studies reporting positive results .Because moderate heterogeneity was detected among the studies of alcohol drinking and diabetes, subgroup analyses on geographical region , study design , adjusted/crude ORs, and positive/negative results were done . For alcSensitivity analysis was conducted to evaluate the robustness of the results because some studies reported only RRs or HRs, and others had not adjusted for confounding variables. We found three articles , 33, 45,1) and Begg’s test (P2), which yielded no significant results for maternal gestational diabetes , smoking , drinking ,or pre-pregnancy obesity . The results suggested no obvious publication bias in present meta-analysis. Publication bias was evaluated by Egger’s test  allowed for investigation of possible relationships between the extent of exposure and the degree of risk.This meta-analysis also has several limitations. Moderate heterogeneity was detected in studies of alcohol drinking and diabetes and sensitivity analysis revealed the result of alcohol drinking and diabetes was unstable. Although some variability is inevitable, this may influence the reliability of our results. In addition, at least half the studies did not adjust for confounding variables. Although we conducted subgroup meta-analyses to avoid bias, this may still affect our results. In addition, one  article Smoking may be a risk factor for cryptorchidism; both parents should avoid fetal exposure to cigarette smoke. Maternal gestational diabetes may be (a) risk factor, but needs further research for confirmation. Drinking alcohol during pregnancy is not associated with increased risk of cryptorchidism, but five or more drinks a week may increase risk while one to five drinks a week may reduce the risk. No significant associations were found between maternal pre-pregnancy obesity or overweight and the risk of cryptorchidism.S1 Dataset(XLSX)Click here for additional data file.S1 PRISMA Checklist(DOC)Click here for additional data file.


A large number of single nucleotide polymorphisms (SNPs) associated with cervical cancer have been identified through candidate gene association studies and genome-wide association studies (GWAs). However, some studies have yielded different results for the same SNP. To obtain a more comprehensive understanding, we performed a meta-analysis on previously published case–control studies involving the SNPs associated with cervical cancer.Electronic searches of PubMed and Embase were conducted for all publications about the association between gene polymorphisms and cervical cancer. One-hundred and sixty-seven association studies were included in our research. For each SNP, three models  were adopted in the meta-analysis. For each model, the effect summary odds ratio (OR) and 95% CI were calculated. Heterogeneity between studies was evaluated by Cochran’s Q test. If the p value of Q test was less than 0.01, a random effect model was used; otherwise, a fixed effect model was used.The results of our meta-analysis showed that: (1) There were 8, 2 and 8 SNPs that were significantly associated with cervical cancer (P < 0.01) in the allele, dominant and recessive effect models, respectively. (2) rs1048943 (CYP1A1 A4889G) showed the strongest association with cervical cancer in the allele effect model ; in addition, rs1048943 (CYP1A1 A4889G) had a very strong association in the dominant and recessive effect model. (3) 15, 11 and 10 SNPs had high heterogeneity (P < 0.01) in the three models, respectively. (4) There was no published bias for most of the SNPs according to Egger’s test (P < 0.01) and Funnel plot analysis. For some SNPs, their association with cervical cancer was only tested in a few studies and, therefore, might have been subjected to published bias. More studies on these loci are required.Our meta-analysis provides a comprehensive evaluation of cervical cancer association studies.The online version of this article (doi:10.1186/s12881-015-0168-z) contains supplementary material, which is available to authorized users. Cervical cancer is a serious disease which affects women’s health. It is the third most common malignancy in women worldwide ,2. HowevThe PubMed and Embase were searched for the appropriate studies using the following keywords: (polymorphism OR mutation OR single nucleotide polymorphisms OR genome-wide association study OR SNP OR GWAS) AND . The studies to be included in the meta-analysis were selected in accordance with the following criteria: 1) the articles must have been published between January of 1990 and June of 2014; (2) the studies must employ a case–control design and must examine the association between SNPs and cervical cancer; (3) data on the SNP genotypes of patients and controls must be available; (4) the studies must be published as a full paper, not as a meeting abstract or review; and (5) NOT-HLA. For each study, we extracted the following information: the gene polymorphisms, first author, date of publication, title, population and number of cases and controls. Then, we choose those SNPs which published at least 2 times. Using these criteria, 152 papers involving 42 SNPs were selected for the meta-analysis . A is the high-risk candidate allele, and a is the low-risk allele. The three models are described as follows:A allele vs. the effect of the a allele;Allele model: the effect of the AA + Aa vs. aa genotypes.Dominant model: If the SNP produces a cervical cancer phenotype when present in either one or two copies of the A allele, i.e., the aa genotype exists, the SNP produces a cervical cancer phenotype.Recessive model: If only the To comprehensively analyze the association between SNPs and cervical cancer, we adopted three genetic models: the allele effect model, the dominant effect model, and the recessive effect model. In these models, we assumed that each SNP marker locus has two alleles )/Q*100% (where k is the number of studies). When the value of I2 is more than 25%, 50% or 75%, low-, mid- or high-grade heterogeneity is present, respectively [Cochran’s Q test was used to evaluate the heterogeneity of between- and within-study variation. In fact, Cochran’s Q test is simply a chi-square test . The nulI , which mectively -16.In this meta-analysis, Cochran’s Q test was used to evaluate the heterogeneity between studies. If the Q-statistic was not significant, we considered that all of the differences between studies were caused by sampling error. Then, we selected the fixed effects model in the meta-analysis. In contrast, if the p value was significant (P < 0.01), meaning that heterogeneity exists between studies, we chose the random effects model.Funnel plots were used to intuitively assess publication bias. The horizontal ordinate of the Funnel plots corresponded to the study effects. If the variable was continuous, the effects are just shown as the original value; otherwise, the effects are shown as a log value. The vertical ordinate corresponds to the sample size, standard error or accuracy. The smaller the sample, the more scattered the distribution; and the larger the sample size, the more concentrated the distribution. If there is no bias, the Funnel plot is symmetrical. In contrast, if the diagram is asymmetrical, it means that publication bias exists. In addition, Egger’s test was used to quantitatively assess the symmetry of the Funnel plots ,18. EggeIn our search for eligible studies and loci, we input the aforementioned keywords into the PubMed and Embase and then obtained 2552 studies. Screened by the criteria mentioned in the data collection, 152 of these 2552 studies involving 42 SNPs were included in our meta-analysis  were calculated for each study, and the heterogeneity between studies was tested. In our analysis of heterogeneity, we identified 15 SNPs with a Q test P value of <0.01. Thus, for the meta-analysis of these SNPs, we used the random effects model. For the remaining SNPs that did not show heterogeneity, we used the fixed effects model. The meta-analysis showed that 8 SNPs were significantly associated with cervical cancer , we tested the heterogeneity between studies. Heterogeneity was found for eleven SNPs (P < 0.01). For these SNPs, the random effects model was used in the meta-analysis. For the others that did not show heterogeneity, the fixed effects model was used. Table Based on the dominant model (Based on the recessive model (AA vs. Aa + aa), there were ten SNPs that showed heterogeneity, with a Q test P value of <0.01. The random effects model was used for these ten SNPs. The fixed effects model was used for the remaining SNPs. Table During the data collection process, we noticed that some publications provided additional testing, such as genotyping for GSTM1 (positive or negative) and CYP2E1 (c1 or c2). These SNPs also were included in the meta-analysis. The results are shown in Table We performed a sensitivity analysis by sequentially removing each article at a time for the SNPs which number of studies was larger than or equal to 4 for the three models. Then we found that only CTLA-318 rs5742909, XRCC1 codon 194 in dominant genetic model and IFN-r rs62559044 4 in allele model can affect the overall pooled OR. The data can be seen in Additional file In our meta-analysis, some SNPs showed heterogeneity and then were subjected to subgroup analysis to explain the causes of their heterogeneity. Most SNPs were reported by only a few individual studies and were not suitable for classification into subgroups; thus, we only selected 5 SNPs for the subgroup analysis. These SNPs were P53 codon 72 Arg/Pro (44 studies), TNF-α-308 (G/A) (11 studies), GSTM1 (positive/null) (15 studies), GSTT1 (positive/null) (15 studies) and XRCC1 Condon399 (G/A) (12 studies). The results are listed in Table In recent years, many SNPs have been demonstrated to be associated with cervical cancer by candidate gene association studies and GWAS. For an individual SNP, many studies show inconsistent results, which are sometimes even contradictory, perhaps due to false positives, false negatives, or race or population differences. Meta-analysis is a powerful tool that can increase statistical power by pooling the results of independent studies. In this paper, we carried out a comprehensive and systematic meta-analysis to assess the relationship between 42 SNPs and the risk of cervical cancer. We used three genetic models: the allele model, dominant model and recessive model. Our meta-analysis results showed that 8, 2 and 8 SNPs showed significant associations with cervical cancer in each model, respectively. In the three effect model, SNP rs1048943 (CYP1A1 G/A) all demonstrated the highly significant association with cervical cancer . In the recessive model, the SNPs rs16944 (IL-1βC/T) and rs4646903 (CYPA1 T/C) also showed highly significant association with cervical cancer . The finding of positive SNPs is very important for the prevention, treatment and prognosis of cervical cancer. For example, the CYP1A1 (cytochrome P450) gene, which is present in 15q22-24, is a key metabolic enzyme that activates polycyclic aromatic hydrocarbon, catalyzes the oxidation of foreign compounds in the body, transforms inactive carcinogens into electrophilic compounds and promotes the formation of DNA adducts, thus generating immunotoxicity and, finally, cancer. It has been discovered that the polymorphism of CYP1A1 is associated with many cancers, such as lung cancer , esophagIn conclusion, our meta-analysis, which identified 42 SNPs, showed the pooling effects. Through this meta-analysis, SNP loci that are associated with cervical cancer were discovered. However, some of these SNPs were reported so few times that it was difficult to assess the significance of their association with cervical cancer. We plan to continue our search for articles on SNPs and cervical cancer and will update our database accordingly.


MTHFR) polymorphisms with multiple myeloma (MM) risk has been explored, but the results remain controversial. Thus, a meta-analysis was performed to provide a comprehensively estimate. The case-control studies about MTHFR C677T and A1298C polymorphisms with MM risk were collected by searching PubMed, Elsevier, China National Knowledge Infrastructure and Wanfang Databases. Odds ratios (ORs) with 95% confidence intervals (CIs) were applied to assess the strength of association. Overall, no significant association was found between MTHFR A1298C polymorphism and MM risk under all four genetic models . The risk was also not significantly altered for C677T polymorphism and MM in overall comparisons . In subgroup analyses by ethnicity, no significant association was observed in both Caucasians and Asians. This meta-analysis suggested that MTHFR polymorphisms were not associated with MM risk.The association of methylenetetrahydrofolate reductase ( Multiple myeloma (MM), the second most common hematological cancer, is a kind of plasma cells cancer characterized by bone marrow plasmacytosis and presence of monoclonal immunoglobulin1333791012MTHFR gene locates in chromosome 1p36.3MTHFR gene, C677T (rs1801133) and A1298C (rs1801131), have been identified, and the variants are associated with low levels of plasma folate and significantly reduced activity of the MTHFR enzyme1921MTHFR gene through the alteration of DNA synthesis and methylation. There have been several studies investigating the relationship between MTHFR C677T and A1298C genetic polymorphisms and MM susceptibility, but the published results are inconsistent, which may be attributed to the relatively small sample size and different ethnic background in each study24MTHFR C677T or A1298C polymorphisms with MM risk.Methylenetetrahydrofolate reductase (MTHFR), the most critical enzyme in folate-metabolizing pathway, catalyzes the irreversible reduction of 5.10-methylenetetrahydrofolate to 5-methyltetrahydrofolate, which acts as a methyl donor for the remethylation of homocysteine into methionine15 C677T rs01133 andet al. were selected among the general population and hospitalized subjects with diagnoses excluding canceret al.MTHFR C677T and A1298C polymorphisms in cases and controls was listed in The process of study selection was showed in 2425262728293031242627282930322425262930312728242628293032MTHFR A1298C polymorphism and MM risk under all four genetic models . The similar results were obtained in the stratified analyses by ethnicity, source of controls (population-based), and quality score of studies . In the subgroup analyses according to ethnicity, no significant association was observed in both Caucasians and Asians  . The search terms and keywords used were as follows: “methylenetetrahydrofolate reductase” or “MTHFR”, “polymorphism” or “variation” or “variant” or “mutant”, and “multiple myeloma” or “MM” or “plasma cell myeloma” or “myeloma” or “myelomatosis”, without any restriction on the language. A manual search for references cited in the eligible articles was also performed to look for additional studies.Two authors independently conducted a systematic literature search in the PubMed, Elsevier, China National Knowledge Infrastructure platform and Wanfang databases to identify studies about the relationship between MTHFR C677T or A1298C polymorphisms with MM risk; (b) the case group had confirmed diagnosis; (c) genotype frequencies for both cases and controls were available; (d) the distribution of genotypes in the control group was in consistent with Hardy-Weinberg equilibrium (HWE). If there were multiple articles from the same study, the most relevant was included. The case reports, letters, meta-analysis, and reviews were excluded.Studies included in this meta-analysis had to meet the following criteria: (a) case-control studies about the association of MTHFR C677T and A1298C polymorphisms in cases and controls, and HWE of control group. Two authors independently extracted information and disagreement was addressed by discussion between them.The following information were extracted from each included study: first author’s name, publication year, country, ethnicity of the study population, source of controls, genotyping methods, sample size of cases and controls, genotypes distribution of the The Newcastle-Ottawa Scale (NOS) was applied to assess the quality of the included studies independently by two reviewersMTHFR C677T and A1298C polymorphisms with MM risk was assessed by odds ratios (ORs) with 95% confidence intervals (CIs) under the heterozygote model , homozygote model , recessive model  and dominant model . The Z-test was used to determine the significance of combined ORs. The heterogeneity between included studies was evaluated by the Q-test. If P > 0.05, indicating that there exists no significant heterogeneity, the fixed-effects model (Mantel-Haenszel) was selected to combine the data, otherwise, the random-effects model (DerSimonian-Laird) was applied. Subgroup analyses were performed according to ethnicity (Asians and Caucasians), source of controls , and quality score of studies (high and intermediate). The publication bias was detected using funnel plot and sensitivity analysis was performed by sequential omission of individual studies to assess the stability of results. HWE of genotypes distribution in the control group was checked by the χ2-test. All the tests were two-sided and P < 0.05 was considered as statistically significant. The data analyses were performed using the software STATA v12.0  and Review Manager v5.2 .The strength of association of How to cite this article: Ma, L.-M. et al. Meta-analysis of the association of MTHFR polymorphisms with multiple myeloma risk. Sci. Rep.5, 10735; doi: 10.1038/srep10735 (2015).


GLUT9) locus are clearly related to uric acid concentrations previously identified as a major cause of gout. Due to the important function of various SNPs, we hypothesized that the common GLUT9 polymorphisms  are associated with gout risk. The purpose of this investigation was to test the hypothesis.Single nucleotide polymorphisms (SNPs) at the glucose transporter 9 . Either the fixed- or the random-effect model was used for OR calculations. Subgroup analyses were carried out by ethnicity for rs16890979 and by gender for all SNPs.We analyzed a total of 8 studies involving 2525 subjects for rs16890979, 2654 for rs6855911, and 2637 for rs7442295. A significantly declined risk was suggested in the meta-analyses of rs16890979 under dominant model  and heterozygote model . The OR was 0.41 under allele frequency model . Significantly declined risk in relation to rs16890979 was also found among Asians. Similarly decreased risk was revealed for rs7442295, both in total samples and in males. However, the meta-analysis of rs6855911 revealed no significant associations.GLUT9 rs16890979 and rs7442295.These data seem to support the hypothesis that the risk of gout may be associated with  According to the results of genome-wide association studies and candidate gene analyses, serum uric acid levels are markedly linked with single nucleotide polymorphisms (SNP) within the region of the glucose transporter 9 (GLUT9) gene.9A major type of arthritis that has caught worldwide attention is gout, a most frequently diagnosed inflammatory joint disease characterized by inflammation, joint pain, chronic hyperuricemia, and painful tophi.GLUT9 (corresponds to SLC2A9) codes a protein of the GLUT9 facilitative glucose transporter family. The members of this family have a central role in maintaining glucose homeostasis. The encoded protein acts as a mediator of chondrocytes in cartilage matrices and thereby affects their survival. The human GLUT9 could transport uric acid. Its SNPs have been identified as susceptibility factors for several diseases such as Alzheimer's disease, hyperuricemia, and gout.12 These data suggest that studies looking at sequence variations in the GLUT9 gene may shed light on the molecular mechanisms underlying the prevalent inflammatory arthritis. However, previous conclusions on the correlation between the polymorphisms and gout risk have been called into question as a result of the inconsistency. For example, Hollis-Moffatt et al demonstrated evidence that GLUT9 polymorphisms play a significant role in modifying the risk of gout, including rs16890979, rs11942223, rs11942223, and rs5028843.13 Disappointedly, this finding was not replicated among samples of Chinese ancestry.14 The genetic effects of GLUT9 polymorphisms may be underestimated due to the limited sample size of published studies.The purpose of our investigation was to clarify whether the most frequently studied SNPs  are correlated with the genetic risk of gout by means of meta-analysis.GLUT9 polymorphisms and gout as possible, we undertook literature searches in ISI Web of Science, Wiley Online Library, Embase, Science Direct, PubMed (Medline), and CNKI web databases, using the following combination: (glucose transporter 9 OR GLUT9 OR SLC2A9) AND (polymorphism OR polymorphisms) AND (gout). We did not impose any language restrictions on the literature search. All possibly relevant studies were retrieved and their reference lists were scanned for additional articles. If the same patient population was investigated in more than 1 study, the most informative study with a larger sample was considered in further analyses.To cover as many research articles reporting on correlation between GLUT9 polymorphism of interest with gout risk; genetic data presented in the research article were sufficient to estimate the risk of gout . Studies were excluded if: included overlapped data with less subjects; gout risk was studied among patients only; and insufficient genetic data.Selection of eligible studies was based on the predefined inclusion criteria: a case–control or cohort study addressing correlation of at least 1 Data on first author's name, study design, country of origin, ethnicity/race, total cases and controls, count of genotypes, genotyping assays, gender distribution, source of controls, and year of publication were separately extracted by 2 of the investigators. In cases of disputes, discussion with a senior investigator was carried out to make a final decision.GLUT9 polymorphisms. Dominant model, allele frequency model, and heterozygote model  were tested in the meta-analysis. In order to decide if the fixed-effect model (FEM) or the random-effect model (REM) was used to estimate the pooled ORs, we detected inter-heterogeneity across the studies by using the Chi-squared-based Q-test and the I2 statistics.16 A P value < 0.05 or/and I2 > 50% indicated presence of heterogeneity. Under this condition, we chose the REM or calculate the pooled ORs 17 otherwise the FEM was selected.18 Subgroup analyses were carried out by ethnicity for rs16890979 and by gender for all 3 polymorphisms.Summary ORs and 95% CIs were estimated with an aim to examine the correlation between gout risk and 19 The 1-way sensitivity analysis was performed to check the robustness of meta-analysis results. Consistency with Hardy–Weinberg equilibrium (HWE) was examined among controls via the Chi-squared test.Publication bias was estimated using the funnel plots supplemented by the Egger's test, a linear regression approach to examine the funnel plot asymmetry on the natural logarithm scale of the OR.P < 0.05 was taken as the significance threshold for all tests.Stata software  was utilized to analyze all statistical data. 25 24 was in agreement with HWE. Four different ethnic groups were included in the meta-analysis: Caucasian, Asian, Maori, and Pacific Islander. The studies published between 2008 and 2012 used population-based controls. In terms of the choice of genotyping assays, TaqMan was used in 4 studies (50%), PCR in 2 studies (25%), and high-resolution melting (HRM) in 2 studies (25%). In addition, most studies were carried out among male subjects  and recessive model (22 vs 12 + 11) was not conducted.Results of meta-analysis examining the association between There was a significant association observed between rs16890979 and the risk of gout. In general, the rare homozygote and heterozygote genotypes combined , without substantial heterogeneity .P = 0.853, 0.360, and 0.194 for rs16890979, rs6855911, and rs7442295, respectively; dominant model). These data indicated that our meta-analysis estimates were robust and reliable.The 1-way sensitivity analyses suggested that the pooled ORs were not qualitatively altered by any single study (data not shown). In the funnel plots for rs16890979 see Fig. , rs6855926The meta-analysis was carried out following the guidelines of PRISMA .GLUT9 polymorphisms being investigated are associated with gout risk. On the basis of genetic and allelic data drawn from the epidemiological studies, we found a significantly declined risk of gout (OR = 0.44) associated with the rare homozygote and heterozygote genotypes combined or the heterozygote genotype alone in the meta-analysis of rs16890979, and a similar decline in relation to the minor allele (OR = 0.41). Significantly declined risk ranging from 53% to 60% was also found among Asians. Likewise, a significant decrease was revealed for rs7442295, both in total samples and in males. However, the meta-analysis of rs6855911 showed no evidence supporting a significant association. Taken together, our meta-analysis seems to support the hypothesis that rs16890979 and rs7442295, but not rs6855911 at the GLUT9 locus, may protect against the risk to develop gout.The purpose of this analysis was to investigate the hypothesis that the 3 27 Based on these observations, we presumed that not only uric acid itself, but the mediators of its concentrations, such as genetic variations in candidate genes, may also play a role in these common diseases, including gout. This assumption is supported by several groups interested in family-based gout. The researchers concluded that gout arises possibly from genetic inheritance due to the high prevalence of asymptomatic hyperuricemia (range: 25–70%), a well-established predisposing factor for gout.29 The genetic base of gout is further evidenced in several epidemiological studies, where the investigators demonstrated strong evidence that serum levels and low renal fractional excretion of uric acid, a primary cause of hyperuricemia, are markedly linked to the polymorphisms in GLUT9 gene.30 Since identifying the correlation between the nonsynonymous polymorphisms of GLUT9 and uric acid or gout may better elucidate the mechanisms underlying gout,31 we decided to perform a meta-analysis to provide reliable estimates for the associations. As expected, 2 of GLUT9 polymorphisms were significantly associated with gout risk, a finding in agreement with the data documented in previous research concerning GLUT9 and uric acid or gout.Aberrant expression of uric acid is a known risk factor for human diseases. Elevation in serum uric acid levels has been associated with metabolic syndrome, hypertension, cardiovascular disease, and renal disease in the domain of epidemiology.32 found that gout is especially prevalent among men. Lawrence et al4 lend further support to the fact that the inflammatory joint disease generally occurs more often among men than among women. Nevertheless, the prevalence rises with age for both, particularly among postmenopause women.4 Moreover, Doring et al10 reported that serum uric acid concentrations are differentially affected by the GLUT9 genotypes among men and women: lower in men and higher in women. Therefore, GLUT9 polymorphisms may predispose to gout in both genders. But it is still unclear whether the SNPs confer equal effects or the effects are more pronounced in 1 gender. Notably, gender as well as age is important component in the development of gout. It is worthwhile carrying out additional studies to determine their roles in the pathogenesis of the disease.We additionally identified a decreased risk among males for rs7442295. This finding appears epidemiologically plausible. In a recent study, Luk and SimkinGLUT9 locus are functionally important and play a role in the regulation of serum uric acid levels, a direct cause of gout. It remains to be clarified whether the null result is due to the limited sample size or the significant heterogeneity across the studies. The last but not the least, a more precise estimate could be derived if common confounding factors are taken into account, such as ethnicity, age, and gender.Due to the lack of original data for various ethnic groups, such as African and those included in the present analysis, we were unable to detect the possible associations for these ethnic populations. Even if there were some data for the Asian populations, the current number may be insufficient to provide strong evidence. This constitutes 1 limitation of our study. Second, we did not find any associations for rs6855911, which contradicts earlier observations that the polymorphisms at GLUT9 polymorphisms with gout risk to date. We have demonstrated some evidence that rs16890979 and rs7442295, rather than rs6855911, may decrease the risk of developing gout. Despite the relatively reliable results, additional studies with a larger number of participants and ethnically diverse populations are recommended to determine the role of GLUT9 gene SNPs in the pathogenesis of human gout.In summary, to the best of our knowledge, this is the first meta-analysis examining the association of


Purpose. To investigate the potential relationship between open-angle glaucoma (OAG) and peripapillary choroidal thickness (PPCT). Materials and Methods. Relevant publications were searched systematically through various databases from inception to January 2016. Studies comparing PPCT in OAG patients and healthy controls were retrieved. All qualified articles were analyzed using Stata 14.0 and Revman 5.3 software. Results. A total of 13 studies were identified for inclusion. There was a significant reduction of average PPCT in OAG patients compared to control participants . Reduction of PPCT was significant in the superior  and nasal  sectors, but there was no significant reduction of PPCT in the inferior  and temporal  sectors. No obvious publication bias was detected. Conclusions. This meta-analysis suggests that open-angle glaucoma patients have significantly decreased peripapillary choroidal thickness compared to healthy individuals. Peripapillary choroidal thickness measured by optical coherence tomography may be an important parameter to consider in open-angle glaucoma. Glaucoma is becoming more common than expected, which is characterized by loss of retinal nerve fiber layers and an associated change in visual field, resulting in irreversible blindness worldwide. The total number of people aged 40–80 years diagnosed as having primary open-angle glaucoma (POAG) is predicted to increase to 79.76 million in 2040, approximately 85% of the glaucomatous population . The patA precise clinical assessment of choroidal changes might be particularly important for an accurate interpretation of glaucoma. Prior to the improvements of optical coherence tomography (OCT), the choroid could only be evaluated by indocyanine green angiography (ICGA) , laser DWith renewed interest in the potential role of the choroid in the pathophysiology of OAG, some recent studies have explored PPCT measured by OCT in OAG patients, only to find conflicting results. If PPCT changes correlate with OAG, evaluation of PPCT would be particularly important, because earlier detection and better monitoring of glaucoma would minimize the risk of blindness. To determine whether PPCT changes in OAG patients or not, we therefore reviewed the current literature and performed a meta-analysis.http://dx.doi.org/10.1155/2016/5484568) [This updated meta-analysis was conducted under the guidance of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement  was employed in the quality assessment in our meta-analysis . This quI2 test. P < 0.05 for Chi-square test or I2 > 50% represented the presence of obvious heterogeneity; then a random-effect analysis model was used and subgroup analysis would be conducted. Otherwise, the fix-effect analysis model was applied. P < 0.05 represented a statistically significant difference for overall effect.Statistical analysis was performed using Revman software . As the PPCT was continuous outcomes, the effect sizes were measured using the weighted mean difference (WMD) and 95% confidence interval (CI). We examined heterogeneity among the studies using the Chi-square test and To explore the stability and reliability of our results, we performed sensitivity analysis using Stata . This was conducted by deleting one study successively and recalculating the effect sizes of the remaining studies.In order to detect potential publication bias, funnel plots were performed using Revman 5.3. Meanwhile, Begg's and Egger's tests were also calculated for the primary outcome using Stata .We initially identified 122 articles from the databases and no additional studies were identified. The majority of these were excluded after the application of inclusion and exclusion criteria, mainly because most of them were not relevant to our analysis. The remaining 19 articles were subsequently reviewed in detail. Six studies were finally excluded for various reasons: three due to unqualified control groups  and random-effects model was applied. The result showed that the average PPCT in OAG patients was reduced significantly compared to the healthy individuals   .I2 = 82%), inferior (I2 = 95%), nasal (I2 = 92%), and temporal (I2 = 95%). However, meta-analysis of each sector showed that a significant reduction of PPCT between the two groups in the superior  and nasal  parts was identified, but PPCT in the inferior  and temporal  sectors was not significantly different in OAG patients compared to the control group ; similar result was observed in NTG patients  but with significant heterogeneity (I2 = 92%)  with no heterogeneity (2 = 92%) . The datFigures P = 0.499) and Egger's test (P = 0.859), and no obvious evidence of publication bias was found. Similar results were revealed in the analysis of each sector  and Zhang et al. actually included 10 studies when analyzing the relationship between OAG and PPCT. Three studies in the synthesis conducted by Zhang et al. [In contrast with the earlier meta-analyses conducted by Wang and Zhang  and Zhang et al.  were notg et al.  only meag et al.  examinedg et al.  reviewedg et al.  was not Although there are important discoveries revealed by these studies, there were several limitations in this meta-analysis. First, studies included in our meta-analysis examined patients with variable types of OCT instruments and different OCT provided different scan methods. Also, the segmentations of the choroid were performed manually and the measurements were conducted at different locations. The measurements may not display the whole dimensions of the choroid. Although we had made a significant effort to select the most consistent data for analysis, we still could not completely exclude the measurement bias. Second, there was substantial heterogeneity among studies in the primary analysis. Different OCT instruments, different measurement points, and patient characteristics, such as race, sex, age, and axial length, may contribute to the heterogeneities in our meta-analysis. We only conducted a subgroup analysis according to the type of glaucoma, which indicated that the type of glaucoma might be a risk factor influencing peripapillary choroidal thickness. The remaining factors were too various to perform subgroup analysis or meta-regression which might explain the heterogeneities to a certain extent. Third, only published studies were included and no apparent evidence of publication bias was presented in our analysis; however, unpublished studies and original data may be neglected; thus a potential publication bias may exist. Additionally, not all potentially confounding factors such as diurnal fluctuation of PPCT, medication treatments, and systematic vascular related diseases were reported among the included studies, which would increase the risk of bias. The results based on the quantitative research synthesis suggest that further researches are required to better describe the relationship between different glaucoma patients and peripapillary choroidal thickness in detail.In a word, recent innovations in optical coherence tomography have helped to better visualize and quantitatively analyze the choroid effectively. But the association between the choroidal thickness measured by optical coherence tomography and the choroid circulation has not been completely understood. As the technology continues to evolve, the combination of OCT and angiography shows the potential to assess ocular hemodynamics and reveals that glaucomatous eyes have reduced peripapillary flow . Though Our meta-analysis indicated that average peripapillary choroidal thickness decreased in open-angle glaucoma. The results also highlight that peripapillary choroidal thickness measured by optical coherence tomography may be an important parameter to consider in open-angle glaucoma.This meta-analysis was performed in accordance with the generally accepted methodology recommendations below and the PRISMA  statement was followed in the whole process.


K-ras gene mutations are common in patients with pancreatic cancer (PC); however, their prognostic value for PC remains inconclusive. This meta-analysis was performed to quantitatively evaluate the association between K-ras mutations and survival in patients with pancreatic cancer.We performed a comprehensive search of electronic sources including MEDLINE (via PubMed), Web of Science, and the Cochrane Library. The search covered a publication period from inception to November 2015.P < 0.001). Moreover, further subgroup analyses by ethnicity, publication year, therapy method, cancer resectability, and gene detection method all revealed that pancreatic cancer patients with the K-ras mutation had significantly poorer OS (P < 0.05). And results from four studies with 225 patients focused on plasma K-ras mutations enhanced such association .Seventeen studies with a total of 2249 patients with pancreatic cancer were included in the tissue detection of this study. The meta-analysis indicated a significant association between mutant K-ras genes and overall survival (OS) (HR = 1.51, 95 % CI 1.32–1.72, As a prediction of poor prognosis, the detection of K-ras mutations may be a useful prognostic factor for pancreatic cancer patients. To our knowledge, this is the first meta-analysis of all eligible studies on the prognostic role of the K-ras mutation in patients with pancreatic cancer. In populations of both Caucasian and Asian descent, patients with pancreatic cancer harboring K-ras mutations tend to get a worse survival. K-ras mutations may represent a useful prognostic factor to stratify patients with high risk and develop specific treatments for these patients in clinical applications.Pancreatic cancer (PC) has a 5-year survival rate of less than 5 %, is one of the most aggressive malignancies, and represents a leading cause of cancer-related mortality , 2. MostAs a member of the Ras gene family, K-ras plays a key role in Ras/mitogen-activated protein kinase signaling. Somatic mutation in K-ras mutations have been shown to be early events in the carcinogenesis of human pancreatic cancer , 4. ApprRecent meta-analyses have suggested that K-ras mutations can be used as useful biomarkers for the early detection of pancreatic cancer , 10. It A systematic literature search was carried out in MEDLINE (via PubMed), Web of Science, and the Cochrane Library to screen for cohort/case-control studies characterizing the association between K-ras mutation and prognosis in PC patient. The search terms were pancreatic or pancreas neoplasms, ras or K-ras gene, survival, and prognosis, which covered the publication period from inception to November 2015. The meta-analysis was performed using the STATA statistical software. Review articles were also screened to search for relevant original studies. Only articles published in English were included in our meta-analysis.Studies deal with the comparison between PC patient with and without K-ras mutation fulfilling the following criteria were considered to satisfy the inclusion criteria of present study: (1) cohort studies, nested case-control studies, or case-control studies focusing on the prognostic value of K-ras mutant type in patients with pancreatic cancer; (2) gene amplification status of K-ras was detected in surgical or plasma specimens; (3) all patient diagnoses of pancreatic cancer were confirmed through histopathologic detection; (4) sufficient data were provided to calculate hazard ratios (HR) for OS comparing mutant K-ras with wild-type K-ras patients; and (5) more than ten patient samples with K-ras mutation were included in the original studies because small sample size may be vulnerable to selection bias. If more than one study by the same authors (using the same case series) was published, the study with the largest sample size was included. The data collected from surgical tissues and plasma specimens were divided in two different groups and analyzed, respectively.Two reviewers (LY Tao and LF Zhang) firstly screened the titles and/or abstracts of all articles independently; we resolved cases with any disagreements through discussion and careful reexaminations. The following variables from studies were extracted with a pre-designed spreadsheet: first author, year of publication, source of publication, country, patients’ ethnicity, study design, total number of cases, detection method of K-ras expression, mutated sites, treatment method, and OS. Quality assessment of the included studies was conducted based on the Newcastle-Ottawa Scale (NOS) criteria  . The NOShttp://sourceforge.net) when the HR was not provided, and the minimum and maximum follow-up periods were obtained from the articles. Heterogeneity between studies was estimated using both the Cochran’s Q statistic (which considered significant at P < 0.10 [Q test with P > 0.10). Otherwise, the random effects model (the DerSimonian Laird method) was conducted. The significance of the pooled estimate was determined using the Z test.The effects of K-ras gene mutations on OS were assessed using the overall HR and 95 % confidence interval (95 % CI). Data from Kaplan-Meier survival curves were collected through Engauge Digitizer version 4.1 (free software downloaded from P < 0.10 ). A fixeP < 0.05 as statistically significant.Subgroup analyses were performed based on ethnicity, publication years, detection methods, tumor resectability, and treatment methods. Besides, a sensitivity analysis was performed using the sequential omission of individual studies to assess the quality and consistency of the results. Begg’s funnel plots were also constructed to evaluate the effect of publication bias on this study, and Egger’s linear regression test was further performed to evaluate the symmetry of these funnel plots . All metA total of 1147 studies meeting the search strategy were initially identified, and 699 duplicates were excluded, leaving 448 articles. After a review of their titles and abstracts, 387 articles were excluded. Another 61 articles were excluded after full text identification, leaving 17 studies for tissues detection and 4 studies for plasma detection that met our criteria for this meta-analysis  . Because the publication number of K-ras-related articles focus on pancreatic cancer was elevated significantly after 2010, we chose the year of 2010 as a cutoff point. The further stratified analyses by publication year suggested that, despite no significant association between K-ras mutation and OS prior to 2010, which included the year of 2010 , the K-ras mutant patients had worse OS than the patients without K-ras mutations after 2010 . With the exception of the study by Kinugasa H [P < 0.001 and HR = 1.57, 95 % CI 1.30–1.91, P < 0.001, respectively; both P for heterogeneity >0.1, fixed effects models). Additionally, the subgroup analysis according to treatment methods revealed a statistically significant difference in OS between the K-ras gene mutant group and the wild-type group . Finally, a subgroup analysis according to gene detection methods also showed that the K-ras gene mutation was significantly associated with poorer OS  , , Table .P = 0.356) did not reveal evidence of obvious publication bias , which indicated that K-ras mutations have negative prognostic value in pancreatic cancer. In our subgroup analyses, the HR for both Caucasian and Asian populations implied that pancreatic cancer patients harboring K-ras mutations also tend to get a worse survival. Furthermore, subgroup analyses according to tumor resectability and the treatment and detection methods of K-ras still revealed that K-ras gene mutations were strongly correlated with poorer prognoses in patients with pancreatic cancer. Notably, the K-ras mutation was only significantly correlated with poorer OS after 2010 (not included 2010). However, the combined HR of K-ras mutation before is 1.27, which still supports our conclusion. The reason why the insignificant association may be the small sample sizes of the studies.In our work, the combined HR for 17 studies evaluating the correlation between K-ras mutations and overall survival of patients with pancreatic cancer was 1.51  and the treatment after operation like chemotherapy may be different between the studies. Such limitation is hard to control for the treatment of pancreatic cancer is still under controversy. Lastly, data about tumor stage or sample size were not provided in most included articles, and the divide of stage for analysis was also not unified, which prevent a further subgroup analysis. Despite those shortcomings, the effect of K-ras on survival was consistent in nearly all of the included studies, and no studies reported a favorable outcome in patients with K-ras mutations.In conclusion, K-ras gene mutations are associated with a poorer prognosis in patients with pancreatic cancer. It may represent a useful prognostic factor to stratify patients with high risk and in developing specific treatments for these patients in clinical applications.This study was approved by the Clinical Ethics Committee of Peking University Third Hospital.


Recent studies have shown that the single-nucleotide polymorphism (SNP) rs1801157 in the stromal cell-derived factor (SDF)-1 gene is associated with susceptibility to coronary heart disease (CHD). However, published studies have shown inconsistent results. Therefore, a meta-analysis was carried out to evaluate the association between rs1801157 and CHD in the literature. A systematic literature search was performed using the PubMed, Web of Science, Cochrane Library, Chinese National Knowledge Infrastructure and Chinese Wan Fang databases. Heterogeneity and publication bias were also evaluated. Seven eligible studies that involved 4656 cases and 2654 controls were finally included in this meta-analysis. Overall, the results showed that the rs1801157 polymorphism was not statistically associated with the risk of CHD under all genetic models but that rs1801157 was associated with decreased susceptibility to myocardial infarction (MI) in subgroup analyses. Moreover, no association was found between rs1801157 and the susceptibility to CHD in either Caucasians or Asians. In conclusion, our meta-analysis demonstrated that the rs1801157 polymorphism is not associated with the susceptibility to CHD but may be associated with a decreased risk of MI. However, further large-scale, case-control studies with rigorous designs should be conducted to confirm these conclusions. Coronary heart disease (CHD) is becoming one of the major causes of morbidity and mortality worldwide35Stromal cell-derived factor (SDF)-1  is a small chemokine that usually acts as a chemoattractant to recruit lymphocytes and monocytes891013The gene encoding SDF-1 is located on the human chromosome 10q11.1, which has been previously identified as a susceptibility locus for CHD by genome-wide association studies (GWASs)16162021A systematic search was conducted using the PubMed, Web of Science, Cochrane Library, Chinese National Knowledge Infrastructure (CNKI) and Chinese Wan Fang databases until January 1, 2015, to identify all potentially relevant studies. The following search terms were used: (“genetic polymorphism” or “single nucleotide polymorphism” or “SNP” or “gene mutation” or “genetic variants”) and  and . Manual searching was carried out to determine other potentially eligible studies by scanning the references cited in the retrieved articles. The full-text articles were further reviewed to determine whether they could be included in the final analysis strictly based on the eligibility criteria. If two reviewers disagreed, all of the authors critically evaluated the studies to determine whether a certain study should be included or excluded.All of the eligible articles had to meet the major inclusion criteria: (i) assessment of the association between the SDF-1 gene polymorphism and CHD; (ii) case-control or cohort studies; and (iii) the data provided concerning allele frequency should be sufficient to calculate genotypic odds ratio (ORs) with the corresponding 95% confidence intervals (95% CIs) in both cases and controls. Studies were excluded when they (i) included duplicated data or (ii) were case reports, letters, review articles or editorial comments. The diagnosis of a CHD case was based on the WHO criteria for CHD, as previously described (stenosis ≥50% of the diameter in at least one major coronary artery based on computer-assisted assessments)23Data extraction was performed independently by two authors using a standardized data extraction form including the following elements: 1) author’s name, year of publication; 2) patient characteristics of each group; 3) number of participants in the case and control groups; 4) study type; 5) genotyping method; 6) P value of the Hardy–Weinberg equilibrium (HWE) test in the control; and 7) OR and 95% CI for the association with CHD. The study quality was assessed using the Newcastle-Ottawa Scale (NOS), as previously described2) metric. Heterogeneity was considered significant with P < 0.10 or I2 > 50%. When heterogeneity existed, the random-effects model was performed to calculate the pooled OR of each eligible study; otherwise, the fixed-effect model was used. Generally, we assessed the association between the rs1801157 polymorphism and CHD using five genetic models: allele model (A vs. G), homozygote (co-dominant) model (AA vs. GG), heterozygote (co-dominant) model (AG vs. GG), dominant model (AA/AG vs. GG) and recessive model (AA vs. AG/GG). Subgroup analyses were further performed according to ethnicity (Asian and Caucasian) and primary outcome . Publication bias was analyzed using the Egger’s linear regression test and funnel plots. Publication bias was considered present with P < 0.05. Sensitivity analysis was also performed to evaluate the stability of the meta-analysis. Briefly, a new analysis was performed by omitting one study at a time to test its influence on the overall estimate. All of the statistical analyses were performed using the STATA 11.0 program . All of the P values were two-tailed.First, the genotype frequencies of the rs1801157 polymorphism among the controls of all of the included studies were assessed under HWE using the chi-squared goodness-of-fit test. ORs with their corresponding 95% CIs were used to estimate the strength of the association between the rs1801157 polymorphism and CHD. The between-study heterogeneity across all eligible comparisons was tested using the Cochran’s Q statistic and I-squared (IAs shown in 202122262728The characteristics of the included studies are summarized in P < 0.001) (P = 0.002) (P < 0.001) (P < 0.001) (P = 0.019)  , homozyg= 0.002) , heteroz< 0.001) , dominan< 0.001)  and rece= 0.019) . However= 0.019) .The aim of sensitivity analysis was to evaluate the influence of each study on the pooled ORs and thereby ensure that no single study was completely responsible for the combined results. The results of sensitivity analysis showed that the pooled ORs were not considerably affected by omitting any individual study using the five genetic models, which confirmed that our results were robust .P = 0.243, 95% CI: −14.03181, 4.487158 for the allele model; P = 0.086, CI: −11.33623, 1.042932 for the homozygote model; P = 0.183, 95% CI: −8.048598, 2.003117 for the heterozygote model; P = 0.234, 95% CI: −10.6939, 3.317689 for the dominant model; P = 0.093, 95% CI: −10.0156, 1.077358 for the recessive model), which suggested that no publication bias existed.Visual inspection of the funnel plot did not reveal any evidence of obvious asymmetry for the five genetic models . In addiet al. reported that SDF-1 recruited circulating neutrophils to atherosclerotic lesions, whereas the depletion of neutrophils reduced plaque formation and prevented its exacerbationet al. found that reduced SDF-1 plasma levels were associated with unstable coronary artery disease in a clinical study and suggested that plasma SDF-1 might mediate anti-inflammatory and matrix-stabilizing effects in unstable angina3233SDF-1 was demonstrated to be a chemokine that exerts protective effects on the pathogenesis of CHD30et al., Apostolakis et al., and Simeoni et al. suggested that there was no correction between rs1801157 and the risk of CHD2228202126et al. suggested that rs1801157 was associated with increased susceptibility to coronary artery disease2026The SDF-1 rs1801157G/A polymorphism resides in a hot SNP locus that has been reported in diverse research fields and is associated with cancer, dermatosis and infectious disease353637162026To our knowledge, our study was the first report to pool published case-control studies to estimate the association between the rs1801157 polymorphism and susceptibility to CHD. The result of the meta-analysis showed that the rs1801157 polymorphism was not associated with the risk of CHD, but the result also yielded significant heterogeneity across studies. To explore the source of heterogeneity, we further performed subgroup and sensitivity analyses. The results of subgroup analysis not only suggested that rs1801157 was significantly associated with a decreased risk of MI but also significantly diminished the heterogeneity across studies, which indicated that the difference in CHD subtype was a source of heterogeneity. However, sensitivity analysis did not identify any sources of heterogeneity.Several limitations existed in our meta-analysis. First, only seven published studies involving a total of 7310 subjects were included in the final meta-analysis. Similarly, only two studies with a small sample size were involved in our analysis of the association between this polymorphism and susceptibility to MI. The sample size remained relatively small and may not exactly estimate the correlation between the rs1801157 polymorphism and susceptibility to CHD or MI. Therefore, more studies with a larger sample size should be included to enhance the reliability and stability of the meta-analysis.Second, strong heterogeneity exists in the meta-analysis of the association between the rs1801157 polymorphism and the risk of CHD. However, we did not perform meta-regression analysis to explore the source of heterogeneity because meta-regression analysis is not suitable for assessing heterogeneity with a sample size <10Finally, although MI was considered a subtype of CHD for subgroup analysis, more subtypes of CHD, such as stable angina and acute coronary syndrome, should be further analyzed. However, we could not analyze the difference among more subtypes of CHD because of the lack of sufficient statistical data in the literature.In conclusion, our meta-analysis suggested that the SDF-1 rs1801157 polymorphism is not associated with the susceptibility to CHD but may be associated with a decreased risk of MI. Further large-scale, case-control studies with rigorous designs should be conducted to confirm the above conclusions. Despite some limitations, this meta-analysis still provides new insights into the role of the SDF-1 gene in the occurrence and progression of CHD.How to cite this article: Wu, N. et al. Lack of an Association between the SDF-1 rs1801157 Polymorphism and Coronary Heart Disease: A Meta-Analysis. Sci. Rep.5, 11803; doi: 10.1038/srep11803 (2015).