This study was conducted to assess the association between the risks of spina bifida (SB) in relation to cigarette, alcohol, and caffeine consumption by women during the first month of pregnancy. Between 1988–2012, this multi-center case-control study interviewed mothers of 776 SB cases and 8,756 controls about pregnancy events and exposures. We evaluated cigarette smoking, frequency of alcohol drinking, and caffeine intake during the first lunar month of pregnancy in relation to SB risk. Logistic regression models were used to calculate adjusted odds ratios and 95% confidence intervals. Levels of cigarette smoking (1–9 and ≥10/day), alcohol intake (average ≥4 drinks/day) and caffeine intake  were not likely to be associated with increased risk of SB. Further, results were similar among women who ingested less than the recommended amount of folic acid (400 μg/day). Spina bifida (SB), a neural tube defect (NTD), is a serious birth defect affecting approximately 35 per 100,000 live births . MaternaBecause SB continues to occur among mothers who have ingested at least 400 μg per day of FA, other factors have been considered to explain the etiology of this birth defect. Among these, and based on their established or hypothesized teratogenic properties in humans, are cigarette smoking, alcohol drinking, and caffeine consumption ,12,13,14FA metabolism is believed to be altered by exposure to cigarette smoke, alcohol, and caffeine. Smokers have lower plasma folate levels after adjustment for folate intake ,20. AlcoUtilizing data collected in the Boston University Slone Epidemiology Center Birth Defects Study, we tested the hypotheses that the risk of SB is associated with smoking, alcohol drinking, and coffee consumption during the first 28 days after the last menstrual period (LMP). Additionally, we investigated whether the risk would be greater in women who failed to ingest the recommended amount of folic acid.The Slone Epidemiology Center Birth Defects Study is an on-going case-control study in North America, which began in 1976 and has been described in detail elsewhere ,25,26,27The present study was restricted to subjects interviewed between 1988 and 2012 when questions on changes in behaviors were asked. Cases of SB were excluded if they had a conjoined twin, chromosomal anomaly, Mendelian-inherited disorder, a known syndrome, amniotic bands, or a body wall defect. Cases were then reviewed by a clinical geneticist to ensure that they met the case definition. For 1988–1992, controls were infants with minor malformations or non-structural defects; for 1993–2012, control subjects were non-malformed infants.Maternal interviews were conducted within six months of delivery by trained study nurses; interviews were conducted in person until 1998 and, thereafter by telephone. The interview consisted of questions pertaining to socio-demographic factors, reproductive history, illness during pregnancy, details on prescription and over-the-counter medication use (including vitamins), and behavioral risk factors . Cases and controls whose maternal exposure information was missing were excluded from the specific analysis. To assess dietary intake, the long version Willett Food Frequency Questionnaire (FFQ) was administered from 1988–1997; it was replaced with a modified, shortened, version in 1998.For the period beginning two months before and throughout pregnancy, mothers were asked the average number of cigarettes smoked per day before and after any changes in amount and the dates of those changes. Using the maternal-reported average and accounting for changes, we calculated an estimated average number of cigarettes smoked by determining the total number of cigarettes smoked during the 28 days after the LMP and then averaging the total number over the 28 days. Mothers were categorized according to the calculated average amount of cigarettes smoked per day  during the first lunar month after the LMP.Mothers were asked about the average number of drinking days per week (frequency) and the average number of drinks per drinking day (intensity) of alcohol consumption two months prior to and during pregnancy, including changes in patterns of intake and the date of any such change. Maternal-reported averages and the change dates were used to estimate the total number of drinks per day and drinking days for the 28 days. A calculated average of the 28-day period was then determined. Mothers were categorized as a heavy drinker if they reported ≥4 drinks per day at any time during the first lunar month of pregnancy. Mothers were also classified, using the calculated average, according to their frequency of consumption in days per week  and the intensity of consumption as the number of drinks per drinking day  during the first lunar month after the LMP. From 1998 through 2012, mothers were asked about the average number of cups of caffeinated coffee, tea, and soda consumed two months before and during their pregnancy; changes in frequency and the timing of any changes were also recorded. Before 1998, data on changes in frequency use were not collected. Changes in the interview occurring in 2005 led to different categorizations for tea and soda that were incompatible with previous years and therefore the main analysis was restricted to coffee intake from 1998 through 2012. To assess the influence of other sources of caffeine, a sensitivity analysis was performed using coffee, soda, and tea data from 1998 through 2005. For both analyses, mothers were categorized by the average number of caffeinated beverages/coffee consumed per day  during the first lunar month of pregnancy based on the total number over the 28 day period divided by 28 days, taking any changes into account.We then assessed potential interactions among the exposure variables. The interactions were examined by pairs  and all together (smoking/heavy drinking/coffee). Women who were in the highest exposure category for each variable were then compared to women who were in the reference category.FA intake during the first lunar month of pregnancy was calculated by summing the average daily folic acid intake from supplements and fortified foods. Natural folate was also included, but discounted by 30% due to its lower bioavailability compared to synthetic folic acid . The resMultiple logistic regression models were used to calculate crude (cORs) and adjusted odds ratios (aORs) and 95% confidence intervals (CIs) for each level of cigarette, alcohol and coffee exposure, with the non-use of each as the reference category. Sociodemographic factors that were considered as potential confounders included: maternal race/ethnicity , maternal age , maternal education , study center , body mass index , non-steroidal anti-inflammatory (NSAID) drug use , use of medication that is to known be a folic acid antagonist , and amount of FA intake . Variables that changed estimates by more than 10% were kept in the final model. A sub-analysis was performed for each exposure, in which we excluded women who had been diagnosed with diabetes prior to the index pregnancy. Data were stratified by study year (1988–1997 and 1998–2012) due to interview differences and by FA intake to assess for potential effect measure modification. All analyses were performed using SAS 9.2 software [A total of 511 cases of SB and 868 controls  were included for the years 1988 through 1997, while 265 cases of SB and 7,888 non-malformed controls were included for the years after 1998. Distributions of sociodemographic factors are presented in i.e., addition of the variable caused more than a 10% change in the estimate) for the years 1988 through 1997 only maternal race/ethnicity and education met the criterion for confounding in the later years.Due to missing smoking information, six cases and five controls were excluded from the 1988–1997 smoking analysis and three controls were excluded from the 1998–2012 smoking analysis. For all years, cigarette smoking was more common among younger mothers and those with fewer years of education . In the For the years 1988 through 1997, no increased risk was observed for moderate smoking but there was a suggestion of an increased risk for heavier smokers  . No incrHeavy drinking was examined by comparing mothers who drank ≥4 drinks per drinking day any time during the first month to mothers who drank less or none . MaternaOne case from the early period and seven controls from the later period were excluded from the alcohol analysis on frequency and intensity due to missing data on alcohol intake. Sociodemographic factors meeting the criterion for confounding were study center, maternal education, and FA intake. For frequency and intensity of alcohol intake, the reference groups were defined as mothers reporting <1 drinking day per week and <1 drink per drinking day, respectively. When both frequency and intensity were considered together, women in both of these lower levels of intake constituted the reference group. Considered separately, neither frequency nor intensity measures was associated with increased SB risk, but women who were both frequent (≥3 days/week) and intense (≥3 drinks/day) drinkers were twice as prevalent among SB cases as controls . HoweverCaffeine intake from coffee consumption was analyzed for data between 1998 through 2012; no subjects were excluded from the coffee analysis due to missing data. Only study center met the criterion for confounding. Compared to mothers who reported consuming no coffee, no increase in risk was observed for daily coffee drinkers . Furthermore, there was no observed change in risk among mothers who had low intake levels of folic acid . When otBecause there was only one case in both the highest exposure group of caffeine and smoking, and none in the highest caffeine and heavy drinking, we did not assess these interactions in relation to SB risk. Women who reported both smoking 10+ cigarettes per day and heavy alcohol drinking were compared to women who did not smoke and were not heavy drinkers. Confounders identified in the early years were study center, maternal education, NSAID use, and folate antagonist medication use. In the later years confounders that met the criterion were maternal education, race/ethnicity, NSAID use, and folate antagonist medication use. Prior to 1998, there was no observed association for SB risk and the combination of 10+ cigarettes and heavy drinking . However, in the later years, a modest association was observed but the confidence interval included the null . After stratifying women according to folic acid intake, there was little change in risk among mothers in both periods; however the elevated risk among mothers in the later years was more apparent  .In this case-control study the risk for SB does not appear to be associated with cigarette smoking, alcohol consumption, and coffee consumption at the levels of intake observed in the study. These null results, with narrow CIs, are consistent with many previous reports ,40,41,42Our results for the earlier years of the study showed a small increase in risk for SB at each level of cigarette smoking, with a slight dose effect. In the later years, however, both levels of smoking exposure resulted in a null association with SB risk. The discontinuity between findings in the two time periods could be due to several factors. First, beginning in 1998, interviews were conducted over the phone as opposed to in-person. If in-person interviews elicit more accurate responses, then our findings from the more recent years would be more vulnerable to bias. A second possible explanation is the use of different controls prior to and following 1993; controls with minor malformations and certain medical conditions were used prior to 1993. However, a post hoc analysis of data collected before and after that change in the composition of control subjects revealed similar results (data not shown). Another possibility is uncontrolled confounding by factors that vary in distribution between the two time periods. For example, if FA is a true confounder and we tended to underestimate intakes, a larger proportion of women in the early years would be affected by such misclassification when intakes in general were lower, as observed in other population-based studies of intakes and blood folate levels ,45,46. IIn the present study, neither frequent nor intense alcohol consumption was associated with SB risk, which is consistent with previous studies ,17,34. WWe found that maternal exposure to caffeine from coffee was not associated with an increased risk of SB. Rather, ORs for varying levels of intake were all below 1.0, but the 95% confidence intervals included 1.0. Furthermore, we observed very little confounding of our risk estimates for caffeine. Consistent with our findings, two previous studies found no association between NTDs and coffee or caffeine ,35 and oThe combination of smoking 10+ cigarettes per day and heavy drinking was not associated with SB risk in the earlier years of the study, but a doubling in risk in the later years. As described above in our discussion of cigarette smoking results, the discontinuity in our findings between the two time periods could be due to different interviewing formats or uncontrolled confounding. Previous studies of smoking and alcohol exposures in relation to NTDs did not examine the interaction of these two variables ,17,42,43There were limitations to our study. First, reported exposures suggest that only a small percentage of women are in the highest exposure group, which limits our ability to study the effects of these exposures and decreases the precision of our estimates. The problem was exacerbated when the data were stratified by FA intake. Additionally, data on exposure were collected by maternal self-report which likely has high sensitivity but low specificity in that some women may under-report. Such misclassification may be greater for exposures with the most stigma  in pregnPower was maximized and bias minimized through systematic approaches in the study design. This study included a large number of cases and controls to maximize the number of subjects within each stratum of exposure. During maternal interviews, information was gathered on frequency, quantity, and timing through the use of a standardized questionnaire and detailed support material  to help participants give complete and accurate responses. To minimize any potential bias stemming from maternal recall, reporting accuracy was maximized for both cases and controls through highly structured interviews conducted within six months of birth or termination by skilled and experienced nurse interviewers who were unaware of the study hypotheses.We have investigated the association between the risk of SB and periconceptional cigarette, alcohol, and coffee consumption, using a large geographically diverse case-control study. Our findings suggest that there is no increased risk for SB among women who consumed cigarettes, alcohol, and caffeine. This observation held true among women who did not consume the recommended amount of folic acid. Despite the fact that our findings are similar to those of previous studies, the results should still be interpreted cautiously due to limitations, including low precision for the highest levels of intake.


However, the results remain conflicting rather than conclusive.Emerging evidence suggests that microRNAs play a critical role in the pathogenesis of breast cancer. Several molecular epidemiological studies were conducted in recent years to evaluate the association between vs GG: OR = 1.00, 95% CI = 0.90−1.09, Pheterpgeneity = 0.364; for CC vs GG: OR = 1.16, 95% CI = 0.98−1.36, Pheterpgeneity = 0.757; for GC+CC vs GG: OR = 1.02, 95% CI = 0.93−1.12, Pheterpgeneity = 0.562; for CC vs GC+GG: OR = 1.10, 95% CI = 0.96−1.26, Pheterpgeneity = 0.441). However, in the stratified analysis by ethnicity, we found the rs2910164 polymorphism was associated with increased breast cancer risk among Europeans in homozygote comparison  and recessive model . No publication bias was found in the present study.We performed a meta-analysis of 6 case-control studies that included 4238 breast-cancer cases and 4469 case-free controls. We assessed the strength of the association, using odds ratios (ORs) with 95% confidence intervals (CIs). Overall, this meta-analysis showed that the rs2910164 polymorphism was not associated with a significantly increased risk of breast cancer in all genetic models (for GC This meta-analysis suggests, for the first time, that the CC homozygote of rs2910164 may contribute to breast cancer susceptibility in Europeans. Breast cancer (BC) is the most frequently diagnosed cancer and the leading cause of cancer death among women globally. About 1.3 million women are diagnosed with BC annually worldwide and about 465,000 die from the disease microRNA-146a has been shown to bind to the 3′UTR of the BC susceptibility gene BRCA1 and negatively regulate its expression miR-146a precursor, results in a change from G:U to C:U in its stem region miR-146a rs2910164 polymorphism and BC risk miR-146a G>C polymorphisms contribute to BC susceptibility.Emerging evidence supports a role for microRNAs (miRNAs) in BC development and progression has-miR146a rs2910164 polymorphism and BC risk up to September 2011. The following key words were used: “miR-146a/rs2910164,” “breast cancer/carcinoma,” and “polymorphism/variant”. The electronic searching was supplemented by checking reference lists from the identified articles and reviews for additional original reports. All the studies must meet the following criteria: (1) case-control study; (2) the outcome had to be breast cancer; and (3) at least two comparison groups (cancer group vs. control group). The major exclusion criteria were: (1) duplicate data, (2) abstract, comment, review and editorial, and (3) no sufficient data were reported.We searched the PubMed and Embase databases for all articles on the association between Two of the authors (H.L. and L.W.) extracted all data independently, complied with the selection criteria, and reached a consensus on all items. In case of disagreement, a third author (JM.Z.) assessed the articles. The following items were collected: first author's name, year of publication, country of origin, ethnicity, definition of study patients (cases), genotyping method, total number of cases and controls, and genotype distributions in cases and controls. PRISMA Checklist for the studies was shown as Checklist S1.hsa-miR-146a polymorphism from expectation under Hardy-Weinberg equilibrium (HWE) was assessed by the chi-square test in controls and a P<0.05 was considered as significant disequilibrium. The strength of the association between the hsa-miR-146a polymorphism and BC risk was measured by odds ratios (ORs) with 95% confidence intervals (CIs). The significance of the pooled OR was determined by the Z-test, and P<0.05 was considered statistically significant. For miR-146a G/C, the meta-analysis examined the association between C allele and BC risk compared with that for G allele in the co-dominant model , dominant model (GC/CC versus GG) and recessive model (CC versus GC/GG). The heterogeneity among the studies was checked by using the chi-square based Q statistic and considered statistically significant at P<0.10 P>0.10, the pooled OR of each study was calculated by using the fixed-effects model  P<0.05 was considered representative of statistically significant publication bias) The departure of frequencies of A total of 41 articles were achieved by literature search from the PubMed and EMBASE, using different combinations of key terms. As shown in vs GG: OR = 1.00, 95% CI = 0.90−1.09, Pheterpgeneity = 0.364; for CC vs GG: OR = 1.16, 95% CI = 0.98−1.36, Pheterpgeneity = 0.757; for GC+CC vs GG: OR = 1.02, 95% CI = 0.93−1.12, Pheterpgeneity = 0.562; for CC vs GC+GG: OR = 1.10, 95% CI = 0.96−1.26, Pheterpgeneity = 0.441)  . When st= 0.032)  and rece= 0.019) . HoweverP = 0.707, Egger's test P = 0.955; CC vs.GG: Begg's test P = 0.452, Egger's test P = 0.130; GC+CC vs.GG: Begg's test P = 0.707, Egger's test P = 0.976; CC vs.GC+GG: Begg's test P = 0.707, Egger's test P = 0.078) (Begg's rank correlation method and Egger's weighted regression method were used to assess publication bias. No evidence of publication bias was observed in any comparison model (GC vs.GG: Begg's test = 0.078) .miR-146a, a microRNA that binds to the 3′ UTR of BRCA1 pre-miR-146a, which is the miR-146a precursor. et al. first reported a correlation between rs2910164 polymorphism in miR-146a and early cancer onset in familial BRCA1/BRCA2-negative breast/ovarian cancer patients et al. failed to confirm the association of rs2910164 with BC risk in Chinese women et al. showed that the rs2910164 SNP in the miR-146a gene was not associated with BC risk in BRCA1 and BRCA2 mutation carriers miR-146a rs2910164 polymorphism and BC risk. We found that hsa-miR-146a rs2910164 G>C polymorphism was associated with a significantly increased risk of BC in the CC homozygote as opposed to the GG homozygote or GC/GG genotype among Europeans. These findings suggest, for the first time, that the CC homozygote of rs2910164 polymorphism may contribute to BC susceptibility.The identification of single-nucleotide polymorphisms (SNPs) that affect gene function or expression and contribute to BC susceptibility is important to help predict individual and population risk and understand the pathogenesis of BC. A G>C polymorphism (rs2910164) has been identified in the gene for miR-146a was significantly upregulated in breast carcinoma tissues compared with normal breast tissues miR-146a has been reported as a signature in breast, pancreatic and prostate cancers mir-146a. This polymorphism involves a mispairing in the hairpin of the precursor, which leads to altered processing, lower expression of the mature sequence and predisposition to papillary thyroid carcinoma et al. found that the rs2910164 CC genotype was associated with a significantly higher risk of gastric cancer when compared to non-cancer subjects et al. reported that rs2910164 genotype GG was associated with increased risk of esophageal squamous cell carcinoma compared with variant genotype CC in a Chinese Han population MicroRNAs could function as tumor suppressors or oncogenes and are down-regulated or up-regulated in human tumors, including BC. Based on array data, it was previously reported that et al. found significant differences in the prevalence of the rs11614913 T allele and rs2910164 C allele among controls of Asian  and Caucasian  One important property of the gene polymorphism is that their incidence can vary substantially between different racial or ethnic populations. Xu Although many previous studies have been carried out to reveal the potential associations between mir-SNPs and cancer risk, most of these studies use a candidate gene approach as most mir-SNPs have not been included in current genome-wide association studies (GWAS) designs In interpreting the current results, some limitations should be considered. First, lack of the original data of the reviewed studies limited our further evaluation of potential interactions, because the interactions between genes and between genes and environment may modulate breast cancer risk. Second, only published studies were included in this meta-analysis, unpublished data and ongoing studies were not sought, which may have biased our results. Third, all case-control studies were from Asia, Europe, and the United States. Thus our results may be applicable only to these ethnic groups. In spite of these, our meta-analysis has some advantages. First, in the present study, no obvious heterogeneity between studies was observed in overall comparisons by the Q-test. Second, according our selection criteria, the quality of studies included in our meta-analysis was satisfactory. Third, no publication bias was detected, indicating that the whole pooled results may be unbiased.has-miR-146a rs2910164 polymorphism is associated with an increased breast cancer risk in Europeans. Caution must be made about the interpretation of the results because of the limited sample size. Additional large case-control studies are necessary to validate our findings, especially in non-Europeans.In conclusion, this meta-analysis suggests that CC genotype of Checklist S1(DOC)Click here for additional data file.


Polycystic ovarian syndrome (PCOS) refers to an inheritable androgen excess disorder characterized by multiple small follicles located at the ovarian periphery. Hyperandrogenism in PCOS, and inverse correlation between androgen receptor (AR) CAG numbers and AR function, led us to hypothesize that CAG length variations may affect PCOS risk.CAG repeat region of 169 patients recruited following strictly defined Rotterdam (2003) inclusion criteria and that of 175 ethnically similar control samples, were analyzed. We also conducted a meta-analysis on the data taken from published studies, to generate a pooled estimate on 2194 cases and 2242 controls.2 = 4.41; P = 0.036), which turned insignificant upon applying Bonferroni correction for multiple comparisons. X-chromosome inactivation analysis showed no significant difference in the inactivation pattern of CAG alleles or in the comparison of weighed bi-allelic mean between cases and controls. Meta-analysis also showed no significant correlation between CAG length and PCOS risk, except a minor over-representation of short CAG alleles in the cases.CAG bi-allelic mean length was between 8.5 and 24.5  repeats in the controls and between 11 and 24  repeats in the cases, without any significant difference between the two groups. Further, comparison of bi-allelic mean and its frequency distribution in three categories  did not show any significant difference between controls and various case subgroups. Frequency distribution of bi-allelic mean in two categories  showed over-representation of extreme sized alleles in the cases with marginally significant value (50.3% vs. 61.5%, χCAG bi-allelic mean length did not differ between controls and cases/case sub-groups nor did the allele distribution. Over-representation of short/extreme-sized alleles in the cases may be a chance finding without any true association with PCOS risk. Polycystic ovarian syndrome (PCOS) refers to an inheritable endocrine disorder characterized by multiple small follicles located under the surface of one or both of the ovaries of a woman. These follicles are all small and immature and do not grow to maturity and ovulate. A consensus workshop in Rotterdam in May 2003 suggested that a woman has PCOS if she has two of the following three features (after the exclusion of related disorders): (1) Oligo- or an-ovulation, (2) Clinical and/or biochemical signs of hyperandrogenism, and (3) Polycystic ovaries in vitro study showed inverse relationship between the number of CAG repeats and the AR activity. AR alleles with lesser number of CAG repeats showed higher activity while increase in the number of CAG repeats progressively decreased the activity PCOS is now considered to be a disorder of androgen excess, commonly termed as hyper-androgenism Variations in the length of the CAG tract have been shown to affect the risk of various disease conditions The study was approved by the Institutional Ethics Committee of the Centre for Cellular and Molecular Biology, Hyderabad, India. The analysis was undertaken between May, 2012 and December, 2012 at the CSIR-Centre for Cellular and Molecular Biology (CCMB), Hyderabad, and the CSIR-Central Drug Research Institute, Lucknow, India. In total, 344 subjects with or without PCOS were recruited from the Genesis Fertility Research Centre of the Maaruthi Medical Center and Hospitals at Erode, Tamil Nadu, India. Informed written consent was obtained from all the participants and all available details about the cases such as age, height, weight, and age at marriage, were noted. The inclusion of the patients was done on the basis of the Rotterdam Revised 2003 (2 out of 3) diagnosis criteria 2 . Out of all cases (N = 169), patients having acne, alopecia aereata and hirsutism were 75, 41, and 117, respectively  criteria. The patients were aged between 20 and 46 years  with BMI between 22 and 47 kg/mectively .A total of 175 control samples from the same age group as the patients were collected from ethnically similar proven fertile women who volunteered for participation in the study. Hospital staff and women visiting the clinic along with the patients but having no genetic relationship with the patients, and women attending the clinic for purposes other than fertility issues , were considered as potential controls. The controls were recruited according to the inclusion criteria of having proven fertility, normal menstrual cycle and ovarian morphology, and no history of sub-fertility treatment. Normal ovarian morphology and no evidence of polycystic ovaries in the controls were confirmed by transvaginal ultrasonography in 100% of the subjects. Peripheral blood samples (3–5 ml) from the participants were collected for genetic analysis. 98.8% of the cases and all controls belonged to Tamil Nadu and had Dravidian ethnicity, except two cases having mixed ethnicity.DNA was isolated from the peripheral blood samples according to the protocol described in our earlier study The CAG repeat region of the AR gene was amplified using primers and the protocol published in our previous study www.vassarstats.net). The bi-allelic CAG mean of all controls and all cases were compared by Student’s independent ‘t’ test. The bi-allelic CAG mean of the three groups were compared by one factor analysis of variance (ANOVA), and the significance of mean difference between the groups was checked by Bonferroni post hoc test after adjusting the significance for multiple contrasts.All the comparisons were done using statistical software package “STATISTICA”, and the results were confirmed by online available statistical tools  and in two allele size categories  was compared. The bi-allelic CAG mean between groups and lengths were compared by two factors ANOVA, and the significance of mean difference within and between the groups was done by Bonferroni post hoc test after adjusting the significance for multiple contrasts. The frequency distribution between cases and controls was compared using chi square test. Two-sided P values of less than 0.05 (95% level of confidence) were considered significant for inference for individual tests; however, for multiple comparisons, the significance was checked against P value corrected for multiple contrasts. The power of all statistical tests was 80.0% with 5.0% margin of error.HPaII in one set  and without the enzyme in another set . Next day, the enzyme was inactivated by heating the mixture at 95°C for 5 minutes. 1 ul of digested and undigested DNA samples were amplified using primers mentioned above, followed by calculation of area under each CAG allele using GeneMapper software . Total area under each CAG peak was taken into account for comparison between digested and undigested samples. The number of individuals showing inactivation of the longer allele to different degrees was plotted for cases and controls. Less than 60% inactivation of any allele was called random inactivation, 60–80% inactivation of either allele was called non-random inactivation, and more than 80% inactivation of either allele was called skewed X-inactivation. X-inactivation weighted bi-allelic mean was calculated by multiplying the allele length by its percent inactivation value, followed by addition of the two corrected allele values.For X-chromosome inactivation assay, PCR was standardized using minimum amount of DNA (10 ng per reaction). In case of heterozygous cases (N = 158) and controls (N = 150), 10 µl of the diluted samples was incubated overnight at 37°C with As stated above, published studies have reported contrasting findings across populations. There could be several plausible reasons behind this, including ethnic variations as one of the strongest reasons. Therefore, we have also conducted a meta-analysis to have a quantitative estimate of the correlation between CAG repeat length variation and PCOS.A systematic literature search in the public databases; ‘Pubmed’, ‘Google Scholar’ and ‘Science Direct’, was conducted using the keywords; ‘CAG repeats’, ‘Androgen receptor gene’, ‘AR gene’, ‘Polycystic ovary syndrome’ and ‘PCOS’, in different combinations. Irrelevant studies were excluded by reading abstracts of the articles. Full texts of all relevant articles were collected from respective journals or from the authors by contacting them via e-mail. Citations in these papers were looked carefully to identify maximum number of relevant studies. The studies thus selected were further subjected to inclusion and exclusion criteria, followed by data extraction from the shortlisted articles.Inclusion criteria: The following inclusion criteria were adopted for meta-analysis:Each trial should be an independent case-control study.The purpose of all the studies should be similar.The study had supplied enough information for calculation of odds ratio.Standard methods were used to analyze CAG repeat polymorphism at high resolution level.Inclusion of the patients was done according to standard diagnosis parameters.Exclusion criteria: Studies not providing detailed description of subjects, raw data, and other required information to fully understand the study design and the data generated were considered for exclusion.2 value was used to quantify the degree of heterogeneity between studies. Values for I2 statistics suggested by Higgins and Thompson were used to infer about the magnitude of heterogeneity; viz. 25%, 50% and 75%, which correspond to low, medium and high heterogeneity, respectively Meta-analysis was conducted using Comprehensive Meta-Analysis software (version-2). Continuous data in the form of mean CAG values (with standard deviation) and size of case/control groups were fed into the software. Weighted mean differences (WMD) and 95% confidence interval were chosen as effect sizes. In two studies We found CAG repeat number to lie between 7 and 29 for both cases and controls. Allele distribution pattern looked similar between the two groups . The bi-While considering CAG bi-allelic mean a continuous variable, the bi-allelic mean was categorized in three groups  on the basis of median cut off value of 18.0. Two way ANOVA was employed for comparing bi-allelic CAG mean between the three groups, showing no significant difference between controls and cases , and between controls and case subgroups based on obesity  and hirsutism  . A signi2 = 5.11, p = 0.078). Similarly, no significant difference between controls and various case subgroups based on obesity , androgenism , and hirsutism , was observed , and from controls to case-subgroups ; however, the differences did not reach statistical significance in any of these comparisons.Further, the numbers of subjects (frequency distribution) falling in the three categories of bi-allelic mean were compared between controls and cases, and between controls and various case subgroups . It was observed . NeverthIn another method of analysis, the bi-allelic mean was categorized into two groups . Two way ANOVA was employed for comparison of the bi-allelic CAG mean between the cases and the controls. However, no significant difference between cases and controls  and between controls and case sub-groups based on obesity , androgenism , and hirsutism , was observed .2 = 4.49, p = 0.106), androgenism , and hirsutism  .Further, the numbers of subjects falling in the two CAG categories were compared between controls and cases, and between controls and various case subgroups . It was = 0.104) . MoreoveX-chromosome inactivation analysis showed that random X-inactivation was most common (76% of the cases and 74% of the controls) . Non-ranLiterature search retrieved twenty-two studies, of which only fifteen studies fulfilled the inclusion criteria. Among the remaining seven studies, two Out of seventeen studies, seven reported short CAG alleles in the cases in comparison to the controls Looking at the expected heterogeneity across the studies, we had a priori preference to use random effects model for overall inference. Comparison of data showed true significant heterogeneity  = 16.000, P-value = 0.00, I-squared = 63.538) between studies, favoring the use of random effects model. Pooled estimate of the weighted mean difference across the studies showed no statistically significant difference  ; howeverSensitivity analysis removing one study at a time failed to identify any study sensitive enough to severely affect the pooled estimate. After removal of seven studies using small sample size , data became more homogeneous  = 9.000, P-value = 0.013, I-squared = 57.125). However, the overall inference that the cases had short CAG alleles in comparison to the controls, but without statistical significance , remained unaffected.In vitro demonstration of the effect of CAG length on AR function has infused further interest in deciphering the impact of repeat length on ovarian function. Our analysis on a large sample size from South India found that the mean CAG length does not significantly differ between cases and controls; nevertheless a trend of higher frequency of extreme sized alleles in the cases in comparison to the controls was seen. Increased PCOS risk with short CAG is supported by an almost equal number of studies Hyperandrogenism in a large fraction of the PCOS cases suggests involvement of androgens and the AR gene in the etiology of this disorder. Variations in the number of CAG repeats in the coding region of the AR gene make it an interesting polymorphism for investigation. Obesity is thought to promote the development of PCOS Contrast in the results across the studies could be due to the ethnic/racial and study-to-study variations in the recruitment of cases and controls. For example, before 2003 Rotterdam criteria, there was a wide variation in diagnostic criteria of PCOS, and 1990 NIH criteria, which does not include the appearance of polycystic ovaries, were most often used for diagnosis of PCOS condition. Wide variation in the outcome of published studies prompted us to undertake meta-analysis to generate a pooled estimate of correlation between CAG length and the PCOS risk. Seventeen studies adding to a total of 2194 cases and 2242 controls were included in the meta-analysis. Pooled estimate found significant heterogeneity in the data and suggested that the mean length between cases and controls does not differ significantly, though a minor over-representation of shorter alleles in the cases was evident. Sensitivity analysis failed to identify any study sensitive enough to significantly modify the results of meta-analysis. Two other recent meta-analyses have also stated no association of the CAG repeat with PCOS risk The results of this meta-analysis could be affected by some variables such as clinical and phenotypic features of subjects; which could have affected the recruitment of cases across studies. We could not adjust the pooled estimate for these limitations because of different reporting approaches used in the studies. However, such an adjustment could provide more comprehensible estimate of the relationship between CAG length and PCOS risk, particularly in the subgroup analysis. Since the studies using small sample size are more likely to show odd outcomes, inclusion of small studies could have affected the pooled estimate. Seven studies had used a sample size <100 in either of the groups. Interestingly, after excluding such studies, only two were found to have reported significant association in vitro studies have shown that AR activity is maximum in moderate sized alleles compared with short and long alleles In summary, our study on a South Indian population and meta-analysis on seventeen studies constituting a large cohort found no significant difference between cases and controls. A little higher frequency of short/extreme-sized alleles in the cases may be a chance finding, without any real implication in PCOS pathogenesis. Most of the earlier studies have compared mean CAG length between cases and controls. This was due to a general belief that AR activity is inversely proportional to the CAG length. This assumption is based on a few studies comparing AR alleles with great differences in CAG lengths. Recent Checklist S1(DOC)Click here for additional data file.


Runt-related transcription factor 3 (RUNX3) is a member of the runt-domain family of transcription factors and has been reported to be a candidate tumor suppressor in gastric cancer. However, the association between RUNX3 promoter methylation and gastric cancer remains unclear.We systematically reviewed studies of RUNX3 promoter methylation and gastric cancer published in English or Chinese from January 2000 to January 2011, and quantified the association between RUNX3 promoter methylation and gastric cancer using meta-analysis methods.vs undifferentiated gastric cancers, and in intestinal-type vs diffuse-type carcinomas were 0.59  and 2.62 , respectively. There were no significant differences in RUNX3 methylation in cancer tissues in relation to age, gender, TNM stage, invasion of tumors into blood vessel or lymphatic ducts, or tumor stage.A total of 1740 samples in 974 participants from seventeen studies were included in the meta-analysis. A significant association was observed between RUNX3 promoter methylation and gastric cancer, with an aggregated odds ratio (OR) of 5.63 . There was obvious heterogeneity among studies. Subgroup analyses , meta-regression were performed to determine the source of the heterogeneity. Meta-regression showed that the trend in ORs was inversely correlated with age. No publication bias was detected. The ORs for RUNX3 methylation in well-differentiated This meta-analysis identified a strong association between methylation of the RUNX3 promoter and gastric cancer, confirming the role of RUNX3 as a tumor suppressor gene. Gastric cancer is the second most common gastrointestinal tumor worldwide. Although its incidence continues to decline year by year, it remains the second most common causes of cancer-related deaths ,2.Runt-related transcription factor 3 (RUNX3) is a member of the runt domain family of transcription factors, also known as polyomavirus enhancer-binding protein 2 (PEBP2)/core binding factors (CBF) . RUNX3 iMeta-analysis is a well-established method for quantifying gene-disease associations more precisely, by using all the available published data to increase the statistical power . We therThis pooled study involved searching a range of computerized databases, including Medline, Blackwell, Cochrane Central, Web of Science, and Ovid, for articles published in English or Chinese from January 2000 to January 2011. The study used a subject and text word strategy with (RUNX3 OR AML2 OR CBFA3 OR PEBP) AND ((gastric OR stomach) AND (cancer OR neoplasm)) as the primary search terms. The search strategy was tailored to each database to ensure that the search was comprehensive and not limited to randomized controlled trials.Three independent reviewers  screened the titles and abstracts identified by the electronic search to identify relevant studies. Relevant articles were further examined to see if they met the inclusion criteria. The reference sections of all retrieved articles were searched to identify further relevant articles. A citation search was carried out on all included articles using the Science Citation Index. Potentially relevant papers were obtained and the full text articles were screened for inclusion by two independent reviewers . Disagreements were resolved by discussion. Included studies were summarized in data extraction forms. Authors were contacted when relevant data were missing.The name of the first author, year of publication, origin of the study patients, sample size, and methylation status of the RUNX3 promoter in human gastric cancer and normal or control tissues were extracted. The inclusion criteria were as follows: the patients had to be diagnosed with gastric cancer and the studies had to have RUNX3 gene promoter methylation data from tissue samples. The following types of studies were excluded: animal experiments, case reports, review articles or meta-analyses, and studies with insufficient data.P ≤ 0.05 was considered significant. Heterogeneity was tested using the I2 statistic with values >50% and χ2 test with P ≤ 0.05 indicating strong heterogeneity between the studies. τ2 was used to determine how much heterogeneity was explained by subgroup differences [Data were analyzed mainly using STATA Software . The strength of association was expressed as pooled odds ratio (OR) with corresponding 95% confidence intervals (CI). Data were extracted from the original studies and recalculated if necessary. The data were pooled using the DerSimonian and Laird random effects model , which tferences . If the The electronic search strategy identified 132 potentially relevant articles, which were further screened for inclusion on the basis of their titles, abstracts, full texts, or a combination of these. The electronic search was supplemented from reference lists of relevant articles including reviews, and by discussion with experts.A total of 55 full-text articles were retrieved, of which 38 were excluded. The remaining 17 studies included data on the relationship between RUNX3 gene promoter methylation and gastric cancer, and these studies were pooled for analysis (Table P < 0.0001), indicating an increased likelihood of methylation in gastric cancer tissue, compared with normal tissue  and normal tissues (n = 812), with a total sample size of 1740 cases. The total number of participants is 974 from 17 articles including 890 patients from 17 articles and 84 controls from 3 articles which provided heterogeneous control groups. The pooled OR for RUNX3 methylation in cancer tissues compared with normal tissues was 5.63  and that in the heterogeneous tissue subgroup was 4.44   (Table P = 0.001), for the European-American subgroup was 5.15 , for the Chinese subgroup was 26.19 , and for the Korean subgroup was 4.96  , which changed the OR from significant (fixed) to non-significant (random) (Table P < 0.0001), that for the 60-65 subgroup was 6.31 , and that for the ≥65 subgroup was 3.75    indicating a positive association between RUNX3 methylation and gastric cancer.A funnel plot of methylation status of gastric cancer tissue versus normal tissue showed that four studies exceeded the 95% confidence limits Figure . We alsoThere were no significant differences in RUNX3 methylation status in cancer tissue in relation to age, gender, TNM stage, invasion of tumors into blood vessels or lymphatic ducts, or tumor stage, or tumor metastases (Data not shown).The overall results demonstrated that RUNX3 methylation was more frequent in intestinal-type, compared with diffuse-type gastric carcinomas . Undifferentiated gastric cancer also had a higher methylation OR than well-differentiated cancer tissue  (Data not shown).The role of the RUNX3 gene in gastric cancer is controversial ,22,42,432and I2 tests and meta-regression was therefore used to determine the sources of the heterogeneity. This showed that the trend in ORs was inversely correlated with age, which accounted for at least some of the heterogeneity . These results were consistent with the results of subgroup analysis according to age. The incidence of age-related methylation in most organs was in accordance with the reported incidences of methylation in their malignant counterparts [The overall OR for methylation status in gastric cancer versus normal gastric tissue was 5.63 , using a random effects model on pooled data from 16 observations in 15 studies. Subgroup analysis showed an OR in the heterogeneous tissue-origin subgroup of 4.44 , which was significant in the fixed, but not in the random effects model. This discrepancy may be a result of the smaller number of studies analyzed. The ORs also differed in subgroups with different ethnic origins: the OR in the Chinese subgroup was 26.19 , followed by the European-American subgroup , the Korean subgroup , and the Japanese subgroup . The ORs for the different age subgroups were 15.00  for age <60, 6.31  for age 60-65, and 3.75  for age ≥ 65. Heterogeneity within the studies was demonstrated by χterparts . RUNX3 mterparts . We founterparts . The negOther factors including sample size, year of publication, proportion of males, and the origins of the patients were not identified as sources of heterogeneity by meta-regression analysis.Meta-analysis of small studies may result in biased results. The funnel plot showed that the standard errors in four of the studies exceeded the 95% confidence limits; furthermore, the asymmetry test of the funnel plot by Egger's regression method showed that the smaller studies reported more positive results, raising the suspicion of bias among the studies. To produce a more robust estimation, we performed sensitivity analysis using the random effects model and were unable to identify any individual sensitive study with a strong influence on the pooled results. Trim and fill tests were performed using the random effects model, and two virtual studies were filled. The overall OR of the trim and fill method was 4.67, which was slightly smaller than that of the crude meta-analysis, but it was still significant, indicating a strong association between RUNX3 promoter methylation and gastric cancer.There were no significant differences in RUNX3 methylation in cancer tissues in relation to gender, TNM stage, invasion of tumors into vessels or lymphatic ducts, or tumor stage. Although some studies have reported significant differences in methylation status and protein expression of RUNX3 in relation to tumor invasion depth , the oveThe aggregated results found that RUNX3 methylation was more frequent in intestinal-type compared with diffuse-type gastric carcinomas, suggesting that inactivation of RUNX3 might play a more significant role in the development of intestinal-type gastric carcinomas.Analysis of the pooled data also showed that undifferentiated gastric cancers had a higher methylation OR than well-differentiated cancer tissues. This suggests that RUNX3 promoter methylation or down-regulation of the RUNX3 gene may be related to poor prognosis, as suggested in previous studies ,48.In conclusion, this meta-analysis of pooled data provides additional evidence to support a strong association between methylation of the RUNX3 promoter and gastric cancer. This association depended on patient origin and the controls used, and further studies are needed to explore these aspects. Younger individuals had higher RUNX3 methylation rates than older individuals. RUNX3 methylation was also associated with histological type and differentiation state of the gastric cancer. However, gender, TNM stage, invasion of tumors into blood vessels or lymphatic ducts, and tumor stage showed no significant associations with RUNX3 methylation in gastric cancer tissues.RUNX3: Runt-related transcription factor 3; PEBP2: polyomavirus enhancer binding protein 2; CBF: core binding factors; TGF-β: transforming growth factor-β; LOH: loss of heterozygosity; OR: odds ratio; CI: confidence interval; TNM: tumor: node: metastasis.The authors declare that they have no competing interests.All authors have made substantial contributions to this article: WP, XX, ZY and CH contributed to the conception, design and final approval of the submitted version. XF and XH contributed to the analysis and interpretation of data, and drafting of the article. TH, NW and YZ contributed to the acquisition of data and revision of the article. WH, ZM and CZ contributed to the acquisition of data and discussion of the article design. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-230X/11/92/prepub


We performed a meta-analysis to systematically summarize the possible association.MicroRNAs regulate gene expression at the post-transcriptional level and involved in diverse biological and pathological processes, including tumorigenesis. Rs11614913 in miR-196a2 and from ten studies with 15,126 subjects for miR-146a. As for rs11614913, the contrast of homozygote , allele  and recessive model  produced statistically association. Subgroup analysis by ethnicity, statistically significantly decreased cancer risks were found among Asians for allele contrast  and the recessive genetic model . According to subgroup analysis by tumor types, the protective effect of C/T polymorphism was only found in breast cancer under allele contrast . For rs2910164, no significant associations were found among overall analysis model with relatively large heterogeneity. Through the stratified analysis, heterogeneity decreased significantly. In the subgroup analyses by cancer types, the C allele of rs2910164 was associated with protection from digestive cancer in allele contrast .We assessed published studies of the association between these microRNA polymorphisms and cancer risk from eleven studies with 16,771 subjects for Our meta-analysis suggests that the rs11614913 most likely contributes to decreased susceptibility to cancer, especially in Asians and breast cancer. Besides, the C allele of the rs2910164 might be associated with a protection from digestive cancer. MicroRNAs (miRNAs) are a class of naturally occurring, small non-coding, single-stranded RNA molecules that form base-pairs with target mRNAs and negatively regulate their translational efficiency and stability miRNA gene region may affect the property of miRNAs through altering miRNA expression and/or maturation miR-196a2  and miR-146a  as possible biomarkers, which were associated with multiple kind of malignant tumors, such as those that occur in the central nervous system mir-196a2 C/T and mir-146a G/C SNP with cancer risks.Single nucleotide polymorphisms (SNPs) or mutations occurring in the We carried out a search in Medline, Embase and Chinese National Knowledge Infrastructure (CNKI) databases, covering all papers published between 1991 and 2011, with a combination of the following keywords: “microRNA/miR-196a2/miR-146a”, “gene”, “polymorphism” and “cancer” (last search was updated on 15 Jan 2011). We evaluated potentially relevant publications by examining their titles and abstracts and all studies matching the eligible criteria were retrieved.Studies included in the current meta-analysis had to meet all the following criteria: (a) evaluation of the rs11614913 and/or rs2910164 and cancer risks, (b) use a case-control design, (c) sufficient published data for estimating an odds ratio (OR) with 95% confidence interval (CI).miR-196a2 C/T and/or miR-146a G/C genotypes, respectively. Different ethnicity descents were categorised as Caucasian and Asian.Data were independently abstracted in duplicate by two investigators (Xu and Chen) using a standard protocol and data-collection form according to the inclusion criteria listed above. Characteristics abstracted from the studies included the name of first author, publication date, country origin, ethnicity, cancer type, control characteristics, genotyping methods, total number of cases and controls, and numbers of cases and controls with microRNA polymorphism and cancer. The significance of the pooled OR was determined by the Z-test, and P<0.05 was considered as statistically significant. For miR-196a2 C/T, the meta-analysis examined the association between T allele and cancer risk compared with that for C allele (T vs C); homozygote TT was contrasted with CC (TT vs CC) and recessive (TT vs CC+CT) and dominant (TT+CT vs CC) models for allele T were also used, so was miR-146a. Subgroup analyses were done by racial descent and tumor type.OR corresponding to 95% CI was used to assess the strength of association between Q-test P-value>0.10 for the Q-test indicates a lack of heterogeneity among the studies, then the pooled OR estimate of each study was calculated by the fixed-effects model (the Mantel-Haenszel method) P-value<0.05 was considered significant. One-way sensitivity analyses were performed to determine whether the assumptions or decisions we have made do in fact have a major effect on the results of the review, namely, a single study in the meta-analysis was deleted each time to reflect the influence of the individual data-set to the pooled OR. Publication bias was assessed by visual inspection of funnel plots in which the standard error of log (OR) of each study was plotted against its log (OR). An asymmetric plot suggests a possible publication bias. Funnel plot asymmetry was assessed by the method of Egger's linear regression test, a linear regression approach to measure funnel plot asymmetry on the natural logarithm scale of the OR. The significance of the intercept was determined by the t-test  P-values.Heterogeneity in meta-analysis refers to the variation in study outcomes between different studies. Heterogeneity assumption was checked by the chi-square-based microRNAs, therefore, each group in these studies was considered separately for pooling analyses. The characteristics of selected studies are summarized in A total of 101 articles were achieved by literature search, from the PubMed, EMBASE and CNKI database, using different combination of key terms. As shown in The allele frequencies were calculated for controls from the corresponding genotype distributions. The two variant alleles had the higher representations among controls of Asian descent  than in controls of Caucasian descent  respectively.vs CC: OR = 0.92, 95% CI = 0.85–0.99, Pheterogeneity = 0.45; T vs C: OR = 0.96, 95% CI = 0.92–0.99, Pheterogeneity = 0.61 and the recessive model: OR = 0.90, 95% CI = 0.84–0.97, Pheterogeneity = 0.50). In the subgroup analysis by ethnicity, statistically significantly decreased cancer risks were found among Asians for allele contrast . In the tumor type subgroup analysis, T allele had an effect of decreasing the risk of breast . Through stratified analyses, the heterogeneity of the subgroup significantly reduced. In the stratified analysis by racial descent, no significant risks were found among Asians and Caucasians. Carriage of the C variant of rs2910164 was found to be associated with protection from digestive cancer  in the subgroup analyses by cancer types. No significant associations were found in breast cancer and other subgroups. The data are shown in For rs2910164, five kinds of genetic models did not produce significant association among all studies with relatively large heterogeneity  and up-regulation of oncogenes  by introduction of pre-miR196a-C would be consistent with overall oncogenic activity, and the diminished regulatory activity of pre-miR196a-T is consistent with a protective role for the T allele of the SNP in breast cancer cells.Some studies have shown that the cleavage of mRNAs of miR-146a gene is located in the stem region opposite to the mature miR-146 sequence and results in a change from G:U pair to C:U mismatch in the stem structure of miR-146a precursor. In two separate studies, Xu et al. miR-146a could affect target mRNA binding. In this meta-analysis, significant association was found about this polymorphism with cancer risk only in the digestive cancer subgroup, and further evaluations were warranted to confirm these results.Rs2910164 in the One important property of the gene polymorphisms is that their incidence can vary substantially between different racial or ethnic populations. In this meta-analysis, we found highly significant differences in the prevalence of the rs11614913 T allele and rs2910164 C allele among controls of Asian  and Caucasian . In the subgroup analysis by ethnicity, the association between T variant genotypes of rs11614913 and reduced risks of cancer was significant only in Asians but not in Caucasians, suggesting genetic diversity among different ethnicities.Caution must be made about the interpretation of the results because of the relatively large heterogeneity in rs2910164 studies. In the subgroup analyses stratified by tumor site and racial descent respectively, it can be found that the heterogeneity of the subgroup reduced significantly. Therefore, it can be presumed that the relatively large heterogeneity mainly results from differences of ethnicity and tumor types. Simultaneously, the heterogeneity may also have been caused by the differences in the selection of subjects, such as familial breast cancer cases negative for disease-causing mutation in Catucci's research miR-196a2 most likely contributes to decreased susceptibility to cancer, especially in the subgroup of Asians and breast cancer. Besides, the C allele of rs2910164 in miR-146a might be associated with protection from digestive cancer. Larger well-designed studies with subjects of the same ethnic background and tissue-specific biochemical and biological characterization are warranted to validate these findings.In summary, this meta-analysis supports that the rs11614913 in Figure S1Funnel plot of publication bias in rs11614913 studies. Log OR is plotted versus standard error for each of studies in this meta-analysis. Each point represents a separate study for the indicated association by T over C allele.(DOCX)Click here for additional data file.Figure S2Funnel plot of publication bias in rs2910164 studies. Each point represents a separate study for the indicated association by C over G allele.(DOCX)Click here for additional data file.Table S1ORs (95% CI) of sensitivity analysis for rs11614913 and rs2910164.(DOCX)Click here for additional data file.


Ovarian cancer is the deadliest gynecologic cancer in the US. The consumption of refined sugars has increased dramatically over the past few decades, accounting for almost 15% of total energy intake. Yet, there is limited evidence on how sugar consumption affects ovarian cancer risk.We evaluated ovarian cancer risk in relation to sugary foods and beverages, and total and added sugar intakes in a population-based case–control study. Cases were women with newly diagnosed epithelial ovarian cancer, older than 21 years, able to speak English or Spanish, and residents of six counties in New Jersey. Controls met same criteria as cases, but were ineligible if they had both ovaries removed. A total of 205 cases and 390 controls completed a phone interview, food frequency questionnaire, and self-recorded waist and hip measurements. Based on dietary data, we computed the number of servings of dessert foods, non-dessert foods, sugary drinks and total sugary foods and drinks for each participant. Total and added sugar intakes (grams/day) were also calculated. Multiple logistic regression models were used to estimate odds ratios and 95% confidence intervals for food and drink groups and total and added sugar intakes, while adjusting for major risk factors.We did not find evidence of an association between consumption of sugary foods and beverages and risk, although there was a suggestion of increased risk associated with sugary drink intake .Overall, we found little indication that sugar intake played a major role on ovarian cancer development. Ovarian cancer is the ninth most common cancer among women and ranks fifth in overall cancer deaths in women in the United States. OvarianThe World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) Second Expert Report recommendations for cancer prevention include limiting consumption of refined sugars. NeverthThe New Jersey Ovarian Cancer Study is a population-based case–control study and has been described elsewhere-19. In bSame study procedures and materials were used for cases and controls. Informed consent was obtained before the phone interview. Cases and controls completed a phone interview during which a questionnaire was administered ascertaining demographic characteristics and major risk factors for the disease such as hormone use, family history of cancer, reproductive history, medical history, and lifestyle factors up to a year prior to diagnosis (or date of interview for controls). A food frequency questionnaire (FFQ), the Block 98.2 FFQ (110 food items), was self-administered and returned by mail, along with waist and hip measurements (a tape measure and instructions were provided), and a mouthwash sample for DNA extraction.We initially identified 682 eligible cases, of whom some were excluded as they were either deceased (n=61) or physicians advised us not to contact them (n=9). Additional cases were excluded if they could not be reached or no longer met eligibility requirements, such as a communication barrier or medical conditions that precluded participation (n=119). In total, 233 of the remaining 493 cases (47%) and 467 controls (40%) completed the phone interview. Participants were excluded from the analysis if their menopausal status was unknown or if they were missing other major covariates. Those who were postmenopausal but did not know their age at menopause were included in the analysis. Of the remaining cases and controls, 205 cases (88%) and 398 controls (85%) completed both the interview and FFQ. Eight of these controls were excluded from these analyses because both of their ovaries had been removed. There were no significant differences in major characteristics between those who did and did not complete the food frequency questionnaire.Participants’ responses were converted to number of servings per day based on their reported frequency and portion sizes for sugary foods and beverages. Frequency was measured as ‘never’, ‘a few times per year’, ‘once per month’, ‘2-3 times per month’, ‘once per week’, ‘2 time per week’, ‘3-4 times per week’, ‘5-6 times per week’, and ‘everyday’ for most food items. For a few foods, ‘never’ and ‘a few times per year’ were combined into one choice: ‘never or a few times per year’ and the choice of ‘2+ times per day’ was added. Portion size for food items was measured in teaspoons, tablespoons, ounces, pounds, cups, pieces, patties, bowls or slices. Portion size for beverages was measured as number of cups, glasses, cans or bottles consumed.Serving sizes were based on the guidelines listed in Reference Amounts Customarily Consumed (RACC) Per Eating Occasion: General Food Supply by the Food and Drug Administration (FDA). This doNext, we computed the number of servings of dessert foods with added sugars, non-dessert foods with added sugars, sugary drinks and total sugary foods and drinks for each participant. Total and added sugar intakes (g/day) were calculated for each relevant food item by multiplying the frequency of intake by the total/added sugar content per 100 grams of food.Total sugars are the sum of both natural and added sugars in the diet. NaturalCalculation of percent of calories from sweets and desserts  included the following FFQ items: regular and low-fat ice cream, ice milk or ice cream bars, doughnuts or Danish pastry, regular or low-fat cake, sweet rolls or coffee cake, regular and low-fat cookies, pumpkin pie or sweet potato pie, other pie or cobbler, chocolate candy or candy bars, candy (not chocolate), soft drinks or sweetened bottled drinks like Snapple (not diet), sugar or honey added to coffee/tea, breakfast bars, granola bars or power bars, sweetened cereals, and jelly, jam or syrup. Information about the respondent’s consumption of diet drinks or use of non-caloric sweeteners (within foods or added at the table) was not collected.Descriptive statistics were computed for total and added sugars and food and drink groups. For all analyses, statistical significance was considered a p-value less than 0.05. To describe our study population, the distribution of major characteristics for cases and controls was tabulated. Two sample t-tests were used to compare cases and controls across continuous variables and chi-square tests were used for categorical variables. Age-adjusted logistic regression models were used to calculate odds ratios (ORs) and 95% confidence intervals (CIs) to compare ovarian cancer risk across major risk factors (except for age).ANCOVA was used to calculate age-adjusted means to compare mean intake between cases and controls for each food and drink group: dessert foods, non-dessert foods, sugary drinks, total sugary foods and drinks, as well as total and added sugar intakes. Based on the distribution in controls, tertiles for the food and drink groups and total and added sugars intake were created and frequencies calculated across the tertiles. Age-adjusted and multiple unconditional logistic regression models were used to estimate ORs and 95% CIs for the food and drink groups and total and added sugar intakes.2; continuous), smoking status  and pack-years (continuous) for ever smokers, physical activity measured in continuous metabolic equivalents (METs), tubal ligation (yes vs. no), dietary intakes of fiber, total fat and saturated fat, and diabetes (yes vs. no). We adjusted for total energy intake using the multivariate nutrient density method.Only a few studies have reported on the impact of various sugary foods on ovarian cancer risk, with inconclusive results. Similar to our results, Pan et al. using daptrend=0.08). They also found no heterogeneity of effects among pre- or postmenopausal women by smoking status, parity, age at menarche, HRT use, or alcohol intake[ptrend=0.02].Overall, studies have produced inconsistent findings on the relationship between dietary sugars  and ovarian cancer risk. Only two prospective studies,34 have l intake,17,34-41l intake independl intake detectedWe also considered a potential effect modification by physical activity, central adiposity, and general obesity, and did not observe any significant heterogeneity of effects estimates. Abdominal obesity and highRecent studies have reported significant differences across histologic subtypes in the associations of epithelial ovarian cancer with reproductive and non-reproductive risk factors, perhaps due to variations in etiology, morphology, and genetic expression of ovarian tumors,47. UsinSome limitations of our study must be noted. First, portion sizes were based on national food surveys performed over twenty years ago. Using nationally representative data collected between 1977 and 1996, Nielsen and Popkin observedTo our knowledge this is the first study to evaluate ovarian cancer risk in relation to total and individual consumption of sugary foods and beverages, total and added sugar intake, as well as a potential effect modification by several insulin-related risk factors. Although in our study there was a suggestion of a moderately increased cancer risk associated with sugary beverage consumption, overall, we did not detect significant relationships with any of the sugar variables evaluated. The overall evidence for sugary foods and drinks and added sugars remains inconclusive. These apparent gaps in the literature emphasize the need for future research, preferably large prospective studies, to evaluate the role of added sugars in the etiology of ovarian cancer, while taking into consideration various factors capable of influencing the body’s insulin response such as anthropometric measures and physical activity.WCRF: World Cancer Research Fund International;AICR: American Institute for Cancer Research;SE: Standard error;OR: Odds ratio;CI: Confidence interval;FFQ: Food frequency questionnaire;BMI: Body mass index;WHR: Waist-to-hip ratio;HRT: Hormone replacement therapy;OC: Oral contraceptives;METs: Metabolic equivalentsThe authors declare that they have no competing interests.MGK wrote the first draft of the manuscript. EVB conceptualized the study design and supervised the implementation of the study. MGK, EVB, and UC performed all the data analyses. SHO recruited members of the control group in conjunction with the EDGE Study. Additional expertise was provided by KD and SHO (cancer epidemiology), S-EL (biostatistics), NP , and LRR (gynecologic oncology). All authors provided substantive comments and editorial review and approved the final version of the manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2407/13/94/prepub


GST) polymorphisms were associated with a susceptibility to age-related cortical cataract  in the Han Chinese population.The aim of this study was to examine whether glutathione S-transferase (GSTM1) and glutathione S-transferase T1 (GSTT1) gene polymorphisms were genotyped in 422 Han Chinese patients with age-related cortical cataract, and in 312 age, sex, and ethnically matched healthy controls, using a multiplex polymerase chain reaction.Glutathione S-transferase M1 . There was a statistically significant association between the GSTM1 positive genotype and the risk of cataract development in both female and male groups . A combination of GSTM1 positive and GSTT1 null genotypes was associated with the risk of developing age-related cortical cataract . The results revealed that the GSTM1 positive genotype was significantly higher in the smoker patients group as compared to the non-smoker patients group . Logistic regression analysis revealed that smoking may be a risk factor for the development of ARC .The results showed that the GSTM1 positive genotype and a combination of GSTM1 positive and GSTT1 null genotypes may be associated with a susceptibility to age-related cortical cataract in the Han Chinese population. The current study indicates that smoking may be an important factor in the development of cortical ARC.Our study suggests that the  HSF4), gap junction protein alpha 8 (GJA8), eph-receptor tyrosinekinase-type A2 (EPHA2), and glutathione S-transferase (GST). However, these genes account only partially for the genetic predisposition to ARC. Studies need to be performed to search for other genes, related to oxidative stress, which may be responsible for the development of ARC.Cataract is one of the leading causes of visual impairment and blindness in the world today . It is eGSTs) are a group of dimeric detoxification enzymes that play an important role in detoxifying exogenous and endogenous toxic compounds under conditions of oxidative stress [GSTM1) and glutathione S-transferase T1 (GSTT1) have been found to have functional polymorphisms and have been studied extensively in relation to disease [GST polymorphisms with susceptibility to cortical ARC in the Han Chinese population.Glutathione S-transferases . All the patients and healthy controls underwent a full ophthalmic examination, including visual acuity, slit lamp examination of the anterior chamber, gonioscopy, central corneal thickness, measurement of intraocular pressure, fundus examination with special attention paid to optic disc parameters, and visual field. The degree of cataract in all patient eyes was either CII or CIII, according to the Lens Opacities Classification System, version II (LOCS II) . SubjectGSTM1 and GSTT1 polymorphisms were genotyped using the multiplex polymerase chain reaction (PCR). The PCR primers used in present study were as described [GSTM1 were 5′-GAA CTC CCT GAA AAG CTA AAG C-3′ and 5′-GTT GGG CTC AAA TAT ACG GTG G-3′. Primers for GSTT1 were 5′-TTC CTT ACT GGT CCT CAC ATC TC-3′ and 5′-TCA CCG GAT CAT GGC CAG CA-3′. To avoid false- negative results, the β-globin gene was used as an internal control. Primers for β-globin were 5′-CAA CTT CAT CCA CGT TCA CC-3′ and 5′-GAA GAG CCA AGG ACA GGT AC-3′. Each PCR reaction was performed in a 10-μl reaction mixture containing 5 μl Premix Taq , 15 pmol primers, and 0.1 μg of genomic DNA for ampliﬁcation of the DNA. The conditions of PCR were as follows: Amplification was performed by initial denaturation at 94 °C for 5 min, followed by 33 cycles at 94 °C for 40 s, at 64 °C for 40 s, and at 72 °C for 40 s, with a final extension at 72 °C for 5 min.The escribed . PrimersGSTM1, GSTT1, and β-globin were 219 bp, 459 bp, and 268 bp, respectively. In the presence of the β-globin band condition, an absence of PCR product for GSTM1 or GSTT1 was described as GSTM1 null or GSTT1 null genotype.Digestion products were visualized on a 2.0% agarose gel, and were stained with GoldView . The product lengths for t-test was used to compare the ages of the patient and control groups. The GSTM1 and GSTT1 genotypes were compared between patients and controls by the χ2 test, using SPSS . Logistic regression analysis was used to estimate the actual risk conferred by the genetic variants . The p-values were corrected (Pc) with the Bonferroni correction by multiple comparison with the number of analyses performed. Statistical significance was set at a p value <0.05.Student’s Four hundred and twenty-two patients with age-related cortical cataracts and three hundred and twelve healthy controls were recruited for the present study. The average age of the cortical ARC patients was 59.61±9.52 years. The average age of the healthy controls was 57.34±10.27 years. There was no significant difference between patients and controls as regards age.GSTM1 and GSTT1 genotypes in patients and healthy controls are shown in GSTM1 positive genotype is significantly higher in the patients relative to the healthy controls. The frequency of the GSTT1 null/positive genotype was not significantly different between the patients and the healthy controls. We also investigated the association between a combination of GST genotypes and cortical ARC. The results are shown in GSTM1 positive and GSTT1 null genotypes.Distribution of the GST genotype, so tested the association between GST genotype and cataract risk, stratified by sex. There was a statistically significant association between the GSTM1 positive genotype and ARC in both female and male groups. The result revealed that in this study gender was not a risk factor for the development of ARC.We questioned whether the sex of the subjects can affect the GSTM1 positive genotype was significantly higher in the smoker patients’ group. The results were shown in the To search for risk factors in the development of ARC, we divided the patients’ samples into two groups according to smoking status. The results showed that the GST polymorphic variants and disease susceptibility. The GSTM1 and GSTT1 polymorphisms were reported to be associated with many diseases, including glaucoma [GSTM1 and GSTT1 could contribute to the development of cortical ARC in the Han Chinese population.Age-related cataract is one of the most common causes of useful vision loss in the world . Althougglaucoma ,22, acutglaucoma , senile glaucoma , and catglaucoma . These rGSTM1 positive genotype is associated with cortical ARC and may be a genetic risk factor for the development of this disease. These results agree with previous findings reporting on senile cortical cataract in the Estonian and Turkish populations [GSTM1 null genotype has been reported to be associated with an increased risk of cataract in Asian populations [GSTT1 null genotype was not associated with cortical ARC. Similarly, no association was found between the GSTT1 null genotype and cataract in Iranian [GSTT1 null genotype was reported to be associated with an increased risk for senile cataract in Asian populations, and with primary open-angle glaucoma (POAG) in a Turkish population [GSTM1 positive and GSTT1 null genotypes was significantly associated with cortical ARC development. Similarly, a combination of GSTM1 positive and GSTT1 null genotypes was associated with the incidence of POAG in a Turkish population [The present study suggests that the ulations ,26. Howeulations ,25. The  Iranian , Turkish Iranian . In contpulation ,15. The pulation . Many faGSTM1 positive genotype and cortical ARC. On the one hand, GST enzymes are very useful for detoxification and defense against oxidative stress, but they are also involved in reactions that result in toxic products. The toxic products may lead to structural damage of the proteins in the lens that then cause lens opacification [GSTM1 positive genotype may have lost its ability to detoxify the harmful substances under oxidative stress.There are several reasons to account for the association between the fication ,26. On tGSTM1 positive genotype was significantly higher in the smoker patients group. It may be assumed that smoking leads to an increase of toxic compounds in the lens tissue. The increased toxicity would then lead to damage of the lens protein [GST polymorphisms and senile cataract, this study did not find any association between them. It was consistent with the result of Meta-analysis between GST polymorphisms and senile cortical cataract [There are many clinical and life-style factors may influence the results of association study. In current study, the patients were divided into two groups according to smoking status. The  protein ,26. As acataract .GST genotypes influence susceptibility to cataract. Third, many recent publications have analyzed the single copy deletions in GSTM1 and GSTT1, but this study has only tested the complete deletions in them, and not the single copy deletions. In addition, the patients in this study were only cortical cataract cases, other types of ARC should be tested in subsequent studies.As with other candidate gene studies, there are several limitations inherent to our study. First, the subjects were recruited from a Han Chinese population only. The results need to be confirmed in other ethnic populations. Second, extensive research is needed to clarify how the GSTM1 positive genotype and a combination of GSTM1 positive and GSTT1 null genotypes were associated with susceptibility to cortical ARC. The predisposing effect of the GSTM1 positive genotype to cortical ARC was stronger in the smoker patients group, and smoking may therefore be a risk factor for this disease. This study may give some information for diagnosis and preventing the ARC.In summary, our study showed that the


However, the results were contradictory. We performed a meta-analysis to examine the association between CTLA-4 polymorphisms and asthma susceptibility.A number of studies assessed the association of Pubmed, EMBASE, HuGE Navigator, and Wanfang Database were searched. Data were extracted independently by two reviewers. Odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the strength of associations.P = 0.04). There were no significant associations between −318 C/T, −1147 C/T, CT60 A/G, −1722 C/T, or rs926169 polymorphisms and asthma risk.Seventeen studies involving 6378 cases and 8674 controls were included. Significant association between +49 A/G polymorphism and asthma was observed for AA vs. AG+GG (OR = 1.18, 95% CI 1.01–1.37, CTLA-4 was a risk factor for asthma.This meta-analysis suggested that the +49 A/G polymorphism in  CTLA-4) gene has been extensively studied.Asthma is a major public health problem worldwide. The disease affects over 300 million people CTLA-4, a B7-binding protein, was initially described as a classical type I glycoprotein on the surface of activated T cells CTLA-4 gene is located on chromosome 2q33.2 CTLA-4 gene have been identified. Some of these studies have demonstrated a significant association of CTLA-4 polymorphisms with atopy or asthma The human CTLA-4 gene variants and asthma. To our knowledge, this is the first meta-analysis of the association between CTLA-4 polymorphisms and asthma susceptibility.Considering a single study may lack the power of providing a reliable conclusion, we performed a meta-analysis to investigate the relationship between CTLA-4 polymorphism and asthma risk to identify studies not included in the computerized databases.Pubmed, EMBASE, HuGE Navigator, and Wanfang Database were searched . The following MeSH terms were used in Pubmed: “asthma” and “polymorphism, genetic” and “CTLA 4 antigen”. The search terms used in EMBASE and Wanfang Database were as follows: (asthma or asthmatic) and (cytotoxic T-lymphocyte associated antigen 4 or CTLA4 or CTLA-4 or CD152) and (polymorphism or mutation or variant). We also searched the reference list of original reports and review articles related to CTLA-4 gene and asthma risk performed, (3) using a case-control design, (4) genotype distributions in both asthma cases and controls should be available for estimating an odds ratio (OR) with 95% confidence interval (CI). Studies were excluded if one of the following existed: (1) not clinical studies, and (2) reviews and abstracts. For overlapping studies, only the one with the largest sample size was included. There was no language restriction.Studies fulfilled the following criteria were included in this meta-analysis: (1) asthma diagnosed by a physician or according to asthma guidelines, (2) evaluation of the polymorphisms in Two authors independently assessed the quality of each study. Any disagreement was resolved by consensus. Quality assessment scores of molecular association studies of asthma were used to assess the quality of selected articles CTLA-4 gene, and genotype number in cases and controls. Authors of the included studies were contacted via E-mail when additional study data were needed.Two investigators (Nie and Chen) independently reviewed full manuscripts of eligible studies, and the relevant data were extracted into predesigned data collection forms. We verified accuracy of data by comparing collection forms from each investigator. Any discrepancy was resolved by discussion or a third author (Xiu) would assess these articles. The following data were collected from each study: first author's name, year of publication, original country, ethnicity, age, atopic status,sample size, asthma and atopy definition, genotyping method, the polymorphisms in Z test.When the data from at least 2 similar studies were available, meta-analysis was performed. ORs and 95% CIs were employed to assess the strength of association between SNPs in +49 A/G, −318 C/T, −1147 C/T, CT60 A/G, −1722 C/T, rs926169 and asthma risk. OR1, OR2, and OR3 were calculated for the genotypes 1) AA vs. GG (OR1), AG vs. GG (OR2), and AA vs. AG (OR3) for the +49 A/G and CT60 A/G polymorphisms, 2) CC vs. TT (OR1), CT vs. TT (OR2), and CC vs. CT (OR3) for the −318 C/T, −1147 C/T, and −1722 C/T polymorphisms, and 3) AA vs. CC (OR1), AC vs. CC (OR2), and AA vs. AC (OR3) for the rs926169, respectively. These pairwise differences were used to indicate the most appropriate genetic model as following: if OR1 = OR3≠1 and OR2 = 1, then a recessive model was suggested; if OR1 = OR2≠1 and OR3 = 1, then a dominant model was suggested; if OR2 = 1/OR3≠1 and OR1 = 1, then a complete overdominant model was suggested; if OR1>OR2>1 and OR1>OR3>1 (or OR1<OR2<1 and OR1<OR3<1), then a codominant model was suggested I2 statistic were used to test for heterogeneity among the studies included in the meta-analysis. Sensitivity analyses were performed by including studies not in HWE. In addition, sensitivity analyses were also done by ethnicity and atopic status. Graphic exploration with funnel plots was used to evaluate the publication bias visually. The Begg's test and the Egger's test were used to assess publication bias statistically Departure from Hardy-Weinberg equilibrium (HWE) in controls was tested by the chi-square test. The Q statistic and the P value<0.05 was considered statistically significant, except for tests of heterogeneity where a level of 0.10 was used.All statistical tests were performed by using the Revman 5.1 software , STATA 11.0 software , and SPSS 18.0 software . A P = 0.04) (P = 0.41). However, the exclusion of studies with Caucasians did not change the result . Sensitivity analyses were also performed by atopic status. Borderline yet significant increase of asthma risk was found among the AA carriers of atopic asthma patients . The funnel plot was slightly asymmetrical .Eleven studies determined the association between +49 A/G polymorphism and asthma  = 0.04) Figure 2CTLA-4 −318 C/T polymorphism and asthma risk P = 0.86) (P = 0.98). Furthermore, no statistically significant results were found in sensitivity analyses conducted by ethnicity and atopic status .Twelve case-control studies identified an association between  = 0.86) Figure 4P = 0.21) and 1.16 . Only 5 studies and 3 studies were eligible for meta-analysis on CT60 A/G, −1722 C/T, and rs926169 polymorphisms. Dominant genetic models were chosen based on the estimated OR1, OR2 and OR3 of these three polymorphisms. Results from our meta-analysis demonstrated that CT60 A/G, −1722 C/T, and rs926169 polymorphisms were not risk factors for asthma. Summary of comparisons are listed in Six studies studied the association between −1147 C/T polymorphism and asthma risk CTLA-4 gene and asthma risk. We found that +49 A/G polymorphism was a modest risk factor for developing asthma in the overall study population. The results revealed that carriers of the AA homozygote had 18% increased asthma risk compared to those individuals with the G allele carriers (AG+GG). In the sensitivity analysis, we found that individuals carrying AA homozygote had increased asthma risk in Asians, but not in Caucasians. These results suggested that interactions between different ethnicities and genetic variants may contribute to asthma risk. However, there were only 4 studies on Caucasians for this polymorphism I2 = 56%) but not in the Asians subgroup (I2 = 7%). Furthermore, asthma is a complex disease. Both genetic and environmental factors affect the risk of asthma in different populations. It is possible that different asthma risks in Asians and Caucasians were due to exposure to various environmental factors. However, no reported article was performed to assess the effect of environment-CTLA-4 interactions in different ethnicities. In the future, more studies should be designed to analyze these associations. We also carried out sensitivity analysis for atopic status. We found that atopic patients had increased asthma risk, suggesting a possibility of atopic status differences in asthma pathogenesis.This meta-analysis of 17 case-control studies including 6378 cases and 8674 controls systematically evaluated the association between +49 A/G, −318 C/T, −1147 C/T, CT60 A/G, −1722 C/T, and rs926169 polymorphisms in the 17Ala>17Thr substitution in the leading peptide of CTLA-4 17Thr substitution increased binding of CTLA-4 to B7.1, causing stronger inhibition on T cell activation then CTLA-4 17Ala CTLA-4 polymorphisms in determining the Th1/Th2 balance Ligers and co-workers showed that CTLA-4 cell-surface expression was significantly increased in individuals carrying the AA genotype, compared to levels in carriers of the AG and GG genotypes Results from our meta-analysis showed the lack of associations between the −318 C/T, −1147 C/T, CT60 A/G, −1722 C/T, or rs926169 polymorphisms and asthma risk. However, these results should be interpreted with caution. Because −318 C/T was shown to be associated with asthma severity and may serve as a clinically useful marker of severe asthma Publication bias and heterogeneity may influence the results of meta-analyses. In our meta-analysis, only studies indexed by the selected databases were included. Negative studies were less likely to be published in journals and be available in computerized database Some limitations of this meta-analysis should be considered. First, the number of available studies that could be included was moderate. Therefore, the results could be influenced by factors like random error. Second, only 7 of the 17 studies were conducted in non-Asian population. Third, the overall outcomes were based on individual unadjusted ORs, while a more precise evaluation should be adjusted by other potentially suspected factors including age, sex and lifestyle. Finally, this study could not address gene-gene and gene-environment interactions, due to insufficient information from the primary publication.CTLA-4, but not the −318 C/T, −1147 C/T, CT60 A/G, −1722 C/T, or rs926169 polymorphisms, represented a risk factor for asthma. Future large-scale studies are still needed to validate our findings. Moreover, gene-gene and gene-environment interactions should also be considered in future studies.In conclusion, our meta-analysis suggested that the +49 A/G polymorphism in