Anorectal malformations (ARM) are rare forms of congenital uro-rectal anomalies with largely unknown causes. Besides genetic factors, prenatal exposures of the parents to nicotine, alcohol, caffeine, illicit drugs, occupational hazards, overweight/obesity and diabetes mellitus are suspected as environmental risk factors.Relevant studies published until August 2010 were identified through systematic search in PubMed, EMBASE, ISI Web of Knowledge and the Cochrane Library databases. Furthermore, related and cross-referencing publications were reviewed. Pooled odds ratios  were determined to quantify associations of maternal and paternal smoking, maternal alcohol consumption, underweight (body mass index [BMI] < 18.5), overweight (BMI 25-29.9), obesity (BMI ≥30) and maternal diabetes mellitus with ARM using meta-analyses.22 studies that reported on the association between prenatal environmental risk factors and infants born with ARM were included in this review. These were conducted in the United States of America (n = 12), Spain (n = 2), Sweden (n = 2), the Netherlands (n = 2), Japan (n = 1), France (n = 1), Germany (n = 1) and Hungary (n = 1). However, only few of these studies reported on the same risk factors. Studies were heterogeneous with respect to case numbers, control types and adjustment for covariates. Consistently increased risks were observed for paternal smoking and maternal overweight, obesity and diabetes, but not for maternal smoking and alcohol consumption. In meta-analyses, pooled odds ratios  for paternal smoking, maternal overweight, obesity, pre-gestational and gestational diabetes were 1.53 (1.04-2.26), 1.25 (1.07-1.47), 1.64 (1.35-2.00), 4.51 (2.55-7.97) and 1.81 (1.23-2.65), respectively.Evidence on risk factors for ARM from epidemiological studies is still very limited. Nevertheless, the few available studies indicate paternal smoking and maternal overweight, obesity and diabetes to be associated with increased risks. Further, ideally large-scale multicentre and register-based studies are needed to clarify the role of key risk factors for the development of ARM. In recent years, a number of studies have shown that prenatal exposures of the parents are associated with an increased risk for having a malformed child. However, only few studies exist regarding the association with anorectal malformations (ARM).ARM are rare birth defects concerning anus and rectum. Approximately 1 in 2,500 to 1 in 5,000 new born babies are affected . DiffereWe conducted a systematic review and meta-analysis of epidemiological studies to summarize current evidence on the relationship between parental risk factors and anorectal malformations and to identify knowledge deficits that need to be addressed in future research.A literature search was carried out to identify epidemiological studies assessing the association between seven prenatal exposures of parents that have been suggested to be environmental risk factors for anorectal malformations: smoking, alcohol, caffeine, illicit drugs, overweight/obesity, diabetes and occupational hazards. Relevant studies published in English were systematically searched in PubMed, EMBASE, ISI Web of Knowledge and the Cochrane Library databases by using various combinations of the following terms: , congenital abnormality, congenital abnormalities, birth defect(s), anorectal malformation(s), anorectal atresia, anal atresia, imperforate anus) AND , drug(s), overweight, obesity, adiposity, diabetes (mellitus), diabetes type 2, diabetes type 1, type 2 diabetes, type 1 diabetes, gestational diabetes, pre-gestational diabetes, pre-existing diabetes, occupational hazard(s), occupational risk(s), professional risk(s), job hazard(s), parental occupation, maternal occupation, paternal occupation). Duplicate articles were deleted. Each title and abstract was checked for relevance. The full text was reviewed if the abstract indicated that the article reported an association between ARM and one of the previously mentioned risk factors. Furthermore, the identified articles were reviewed for related articles and cross-referring publications.Articles were included if they reported on associations of anorectal malformations with at least one of the previously mentioned environmental risk factors. When available, data of ARM infants with isolated anomalies  were preferred to data of ARM infants with multiple defects. Articles were excluded if the reported number of ARM cases was less than two. ARM infants analysed only in a group with other anomalies like intestinal or tracheo-esophageal atresias were also excluded because of concern that associations of risk factors with these anomalies might be different from associations with ARM. Searches were restricted to English-language articles.Two reviewers independently assessed the articles and extracted the following key information in a standardized manner: first author, year, country, study design, characteristics of the study population, period of data acquisition, assessed risk factor(s) for ARM and the respective measures of odds ratio or prevalence ratio (see below), as well as covariates adjusted for in the analysis. Initial disagreements on classifications of study characteristics were resolved by discussion within the team of authors.Associations between parental exposures and ARM are presented by odds ratios (OR) and their 95% confidence intervals (CI). Alternatively, reported prevalence ratios (PR) are shown. Unadjusted values were recalculated by the Review Manager Software, version 5.0.24  to validate the results. When measures of associations were not explicitly reported, they were derived from data provided in the articles.© software, version 2.11.1  using standard meta-analysis methods. The fixed effects model was used to estimate the variance of the summary odds ratio when study heterogeneity was low (I²≤ 25) and the random effects model when study heterogeneity was moderate to high (I²> 25) [Meta-analyses were performed for risk factors for which results were available from at least two studies. Heterogeneity was assessed by the χ² and I² statistics. When the number of studies is low or when sample sizes are small, the power of the χ² test is low. The I² measure describes the proportion of total variation in effect estimates across studies that is due to heterogeneity rather than sampling error . Fixed a(I²> 25) ,21. Indi(I²> 25)  and Egge(I²> 25)   and ARM table . Risks wThe result of the meta-analysis on the association of maternal underweight with ARM is shown in figure The result of the meta-analysis on the association of maternal overweight with ARM is shown in figure The result of the meta-analysis on the association of maternal obesity with ARM is shown in figure Among eight studies assessing maternal diabetes, six differentiated between pre-existing and gestational diabetes table . The cloThe result of the meta-analysis on the association of any maternal diabetes mellitus with ARM is shown in figure The result of the meta-analysis on the association of maternal pre-gestational diabetes with ARM is shown in figure The result of the meta-analysis on the association of maternal gestational diabetes with ARM is shown in figure Five studies reported on a potential role of maternal and paternal occupational hazards table . Herdt-LThis systematic review and meta-analysis summarized the results of 22 studies on the association between prenatal environmental risk factors and infants born with an anorectal malformation reported between 1981 and June 2010. The majority of the studies were conducted in the United States. Case numbers ranged from 14 ARM cases in the study by Shiono et al.  to 564 AThere is a great discrepancy in the reported results on the associations between maternal illicit drug use and ARM which impede comparability. Closer examination of the studies suggests that different data collection could lead to these different results. In the study by van Gelder et al. , mothersWhen available, data on ARM infants with isolated anomalies  were preferred in this review to data on ARM infants with multiple defects. Only six of the 22 reviewed studies looked at both groups ,37,38,40Looking at some other gastro-intestinal malformations, maternal diabetes also seems to be a risk factor for esophageal atresia ,32,34. HThe significant associations with ARM and some other gastro-intestinal malformations show that the rise in maternal overweight and obesity, as well as diabetes during the last decades are of relevance for these birth defects. For example, the prevalence of overweight (obesity) in adult females from the Netherlands increased from 30% (6%) in 1981 to 42% (12%) in 2004 . In girlOur review has a number of limitations mostly resulting from the overall scarcity of published evidence. First, our meta-analysis was limited by the data provided in the individual studies. Not all studies provided risk estimates adjusted for potentially influential confounders, such as maternal age, ethnicity, education, parity, periconceptional smoking and folic acid intake  or materTo our knowledge, our article is the first systematic review and meta-analysis that provides an overview of the few available studies that reported on the association between prenatal environmental risk factors of the parents and ARM. Adequate evidence is still very limited. Therefore, further multicenter or register-based studies are needed to clarify the role of key risk factors for the development of ARM. One example is the recent establishment of the German Network for Congenital Uro-REctal Malformations (CURE-Net). The aim of this consortium is to collect data of affected newborns as well as of older patients with an anorectal malformation (ARM) or an exstrophy-epispadias complex (EEC) that allow to investigate molecular causes, clinical implications and psychosocial outcomes. For a standardized description of diagnostic subgroups, international classifications are used (Krickenbeck for ARM  and GearThe authors declare that they have no competing interests.Conception and design was done by HB. Literature review, data extraction and statistical analysis were carried out by NZ and EJ. Drafting of the article was done by NZ. Revision of the article was done by NZ, EJ and HB. All authors read and approved the final manuscript.


HHEX) gene is identified as a promising candidate for type 2 diabetes by genome-wide association studies, triggering plenty of subsequent replications; however, the results are conflicting. We therefore conducted a meta-analysis of three widely-evaluated polymorphisms in HHEX gene and diabetes risk.The hematopoietically-expressed homeobox  for rs1111875, 18 studies (18227/30366) for rs5015480 and 26 studies (25725/30579) for rs7923837, respectively. Overall analyses indicated that rs1111875-C allele , rs5015480-C allele  and rs7923837-G allele  conferred significantly increased risk for type 2 diabetes, yet accompanying moderate to strong evidence of heterogeneity. Despite vast divergence in allele distributions, subgroup analyses by ethnicity showed comparable risk estimates between Asians and Caucasians for three examined polymorphisms. Moreover, results of studies with hospital-based controls deviated greatly from that of all qualified studies, especially for rs7923837-G allele carrying a doubled risk (OR = 1.37 versus 1.18). Furthermore, when only large studies (≥500 case-patients) were considered, risk effects were identical to the overall estimates for three examined polymorphisms. The Begg's funnel plot and Egger's test indicated low probability of publication bias.HHEX gene with type 2 diabetes.Our results provide clarification to the significant association of rs1111875, rs5015480 and rs7923837 in  HHEX) has been repeatedly identified as a promising candidate in susceptibility to type 2 diabetes by genome-wide association studies across ethnicities HHEX gene encodes a transcription factor involved in a fundamental pathway  for cell growth and development HHEX gene is located on chromosome 10q24, contains 4 exons, and spans about 5.7 kb of genomic sequence HHEX attributable to the development of hyperglycemia has triggered hundreds of association studies lately. Several polymorphisms in HHEX gene have been identified, with rs1111875 T>C, rs5015480 T>C and rs7923837 A>G being extensively evaluated. However, results are controversial and firm association has not yet been established, possibly due to some methodological drawbacks, including the insufficient sample sizes, inappropriate selection of patients and controls, population stratification/admixture, ethnicity-specific genetic backgrounds, and lack of adjustment for confounders The gene encoding hematopoietically-expressed homeobox  statement HHEX, diabetes, gene and polymorphism. Articles written in English and performed on humans were identified. We browsed the title and abstract of all retrieved articles to determine whether data on the topic of interest were included. If article could not be rejected with certainty, we resorted to the full text of article for evaluation. The search was also supplemented by checking the bibliographies from the main reports and relevant reviews for additional eligible articles unidentified by PubMed. We abstracted the most complete data from articles with duplicate or overlapping samples. We treated articles that had more than one subgroup with homogenous characteristics separately.We conducted a comprehensive search of PubMed database from its inception through March 2012 using the following subject terms: hematopoietically-expressed homeobox, HHEX gene with diabetes risk; (2) involving unrelated subjects and non-overlapping data; (3) having a retrospective or nested case-control design; (4) genotyping with validated methods; (5) supplying genotype/allele counts between cases and controls or the odds ratio (OR) and its 95% confidence interval (95% CI) of examined polymorphisms. Articles investigating phenotype modification, response to treatment, birth weight, insulin secretion, β-cell function, survival or family-based studies were excluded. Moreover, case reports/series, editorials, review articles, and non-English articles were also excluded.The quantified articles must meet the following criteria: (1) evaluating the relationship of either rs1111875 or rs5015480 or rs7923837 in All data were reviewed and extracted independently by two investigators (X.L. and Y.L.) using a standardized data-extraction form. The following data were collected from each article: the first author's name, publication year, ethnicity of study population, types of diabetes and/or complications, diagnostic criteria, study design, source of controls, genotyping method, genotypes or alleles of examined polymorphisms, and other traditional risk factors, if available, including age, percentage of males and body mass index (BMI). Any discrepancies were resolved by discussion and, when necessary, adjudicated by a third investigator (W.N.).HHEX gene rs1111875-C, rs5015480-C and rs7923837-G alleles compared with the alternative alleles were calculated, respectively. The goodness-of-fit of the observed allele frequencies with the expected frequencies by Hardy-Weinberg equilibrium was assessed using the χ2 test or Fisher's exact test. Between-group differences of demographic data were calculated by the Student's paired t test.Due to a considerable number of articles providing data only on allele counts and to enhance study power to detect an association, we exclusively took account of allelic model in this meta-analysis. Pooled OR (95% CI) for diabetes risk associated with I2) statistic (ranging from 0 to 100%). The I2 statistic is defined as the percentage of the observed between-study variability that is due to heterogeneity rather than chance, with high values suggesting more possible existence of heterogeneity. Potential heterogeneity between results of individual studies or in subgroups respectively by disease subtype, ethnicity, study design, source of controls, genotyping method, diagnostic criterion, and sample size was explored using χ2 test.We employed a random-effects model to bring the individual effect size estimates together, and quantified between-study heterogeneity by inconsistency index  encompassing 57931/74658 cases/controls for rs1111875, 18 studies  encompassing 18227/30366 cases/controls for rs5015480, and 26 studies  encompassing 25725/30579 cases/controls for rs7923837. The frequency of rs1111875-C allele in type 2 diabetic patients (45.78%) was lower than that in subjects with IGT/IFG (51.96%) and gestational diabetic patients (48.99%), whereas the frequency of rs5015480-C allele in type 2 diabetic patients (33.53%) was significantly higher than that in subjects with IGT/IFG (17.69%) and gestational diabetic patients (21.85%). In contrast, frequency of rs7923837-G allele in type 2 diabetic patients (41.61%) was intermediate between that of subjects with IGT/IFG (52.66%) and gestational diabetic patients (24.94%). Across ethnicities in type 2 diabetic patients, frequency of rs1111875-C allele in Asians (34.52%) was exceedingly lower than that in Caucasians (61.97%), Mexicans (62.75%), Arabs (74.92%) and Africans (77.6%). Similar tendency was noted for the frequencies of rs5015480-C and rs7923837-G alleles in Asians (26.49% and 25.1%), Caucasians (61.52% and 65.91%) and Africans (92.87%), respectively. There was no detectable deviation from the Hardy-Weinberg equilibrium in all studies but one by van Hoek M et al Egger = 0.275), rs5015480 (PEgger = 0.449) and rs7923837 (PEgger = 0.645) , rs5015480-C  and rs7923837-G  alleles was significantly associated with an increased risk of developing diabetes . Restric= 0.645) .Considering the fact that few studies relied on IGT/IFG and gestational diabetes and therefrom to eliminate their interference, we merely centered on type 2 diabetes in following analyses. To explore the potential sources of heterogeneity, a set of subgroup analyses were undertaken according to descent of study populations (mainly Asian and Caucasian), study design (prospective and retrospective), source of controls , genotyping method (mainly TaqMan and Array), diagnostic criterion (mainly WHO) and sample size in cases (≥500 subjects and <500 subjects), respectively .Grouping studies by ethnicity showed that there was slight difference for three examined polymorphisms between Asians and Caucasians in association with type 2 diabetes, despite the vast divergence in allele frequencies. For instance, the odds associated with rs1111875-C allele was 1.18  in Asians and 1.14  in Caucasians. Likewise, studies in either prospective or retrospective design exhibited comparative association for rs1111875 and rs7923837, and the risk estimate was dramatically reduced to non-significant for rs5015480 in prospective studies .Upon stratification by source of controls, association was greatly potentiated in studies recruiting controls from hospitals relative to those from populations for rs1111875 and rs7923837, whereas was reduced for rs5015480. Take rs7923837 for example, contrast of G allele versus A allele more than doubled the OR, from 1.37  in studies with hospital-based controls to 1.16  in studies with population-based controls. With regard to genotyping methods, studies adopting Array technique had relatively weak association compared with those adopting TaqMan technique for three examined polymorphisms. Concerning the diagnostic criteria for type 2 diabetes, close half of studies did not offer such details, and nearly all remaining studies abided by the WHO criteria with the risk estimates in parallel with that of overall estimates.When the analyses were restricted to the large studies (≥500 case-patients), summary risk effect was identical to the overall result, whereas analyses of small studies (<500 case-patients) detected an overestimation of the true association, significantly yielding an OR of 1.22  for rs1111875, 1.26  for rs5015480 and 1.27  for rs7923837.HHEX genetic polymorphisms with type 2 diabetes fluctuated around the overall estimates according to the ascending year of publication, and for studies published over the past two years, the risk magnitude tended to be weakened or have wide 95% CIs.As shown in HHEX gene with type 2 diabetes in a subset of studies that had data these factors.In order to further illuminate potential sources of heterogeneity, we undertook a multivariable meta-regression model by incorporating several study-level covariates that were unlikely influenced by drugs, such as age, gender and BMI. However, unfortunately none of these covariates contributed significantly to the association of three examined polymorphisms in HHEX gene three widely-evaluated polymorphisms and risk of diabetes among 162663 subjects in 43 articles. Importantly, we observed significant association of rs1111875, rs5015480 and rs7923837 in HHEX gene with type 2 diabetes. However, the gene effect size suffered from moderate to strong interference of heterogeneity in the results of different studies, reflecting the variation observed between ethnic populations and/or differences in sources of controls. Moreover, when only large studies (≥500 case-patients) were considered, the association remained stable, indicating the robustness of our results.The present meta-analysis provides the most comprehensive assessment of HHEX gene with type 2 diabetes were compatible with that of the present meta-analysis. However, given the largest sample sizes, our results provided a relatively precise assessment  of the average risk estimates. For example, in the Cai et al study The pooled results from the Wang et al Another interesting finding of this meta-analysis was that despite the vast differences in allele distributions of examined polymorphisms, subgroup analyses by ethnicity produced comparable results between Asians and Caucasians, which is worthy of our careful thinking. Broadly speaking, distributions of rs1111875-C allele, for example, followed a ladder-like trend of falls from Africans (77.6%) to Caucasians (61.97%) and Mexicans (62.75%), and to Asians (34.52%), in line with a significant degree of gene flow between Africa, Europe and Asia in the famous “Out of Africa” theory. Moreover, the similar effect of rs1111875-C allele on diabetes across ethnicities might be explained by the phenomenon of ‘canalization’, a developmental compensation that can atone for disruptive environmental or genetic forces HHEX gene with type 2 diabetes reached significance, there was moderate to strong evidence of heterogeneity attributable to genuine changes in gene effect size. In this meta-analysis, source of controls was identified as a potential source of between-study heterogeneity by subgroup analyses for three examined polymorphisms. Notably, the results from studies with hospital-based controls deviated greatly from that of our main analysis. For example, the summary estimate of rs7923837-G allele was at 1.37-fold increased risk for type 2 diabetes in studies with hospital-based controls, a doubling of risk in studies with population-based controls (OR = 1.16) and in all included studies (OR = 1.18). It is widely believed that controls drawn from the general population might be representative of the true population of those without the disease, albeit running the risk of misclassification of study participants. However, studies drawing controls from hospitals had bigger problems in terms of population admixture and stratification, as well as the poor comparability between cases and controls due to their differential hospitalization rates. Another major threat to studies with hospital-based controls was a latent narrow socioeconomic profile, especially drawing controls from only one hospital. Once again, the consistency of our findings between main analysis and analysis of only studies with population-based controls was strong support for the robustness of our observations.It is not uncommon to encounter genetic heterogeneity in pooled association studies. Although the overall association of HHEX gene, and did not cover other diabetes-susceptibility genes or polymorphisms. It is possible that the potential role of examined polymorphisms is diluted or masked by other gene-gene or gene-environment interactions. Thus, we cannot jump to a conclusion until further verification of our findings in vitro, in vivo and in large prospective studies of multiple gene-gene and gene-environment interactions.Finally, cautions are urged regarding the interpretation of this meta-analysis. First, most included studies were prospective in design, precluding comments on causality. Second, as with all meta-analyses, publication bias might have occurred because our analyses were based entirely on published studies from English-language journals other than the “grey” literature. Usually, studies with “negative results” either take longer to be published compared with that with enthusiastic results (known as “time lag bias”) or are never published (known as “publication bias”). These biases may have led to an overestimation of the effects in this meta-analysis. Third, although a set of subgroup analyses had been undertaken, significant heterogeneity still persisted in some subgroups, limiting the interpretation of pooled risk estimates. Moreover, considering the relatively small sample sizes for some polymorphisms, especially in subgroups, more studies are warranted to quantify the effect reliably. Fourth, we failed to obtain all of the study-level covariates, preventing a straightforward evaluation of their effects on risk prediction and precluding a more robust assessment of other sources of heterogeneity. Fifth, we only focused on three widely-evaluated polymorphisms in HHEX gene with type 2 diabetes. Moreover, our findings not only confirm and extend the previous meta-analyses, but also indicate obvious robustness in view of stable observations within studies with large sample size and population-based controls. Also our findings leave open the question about the counterintuitive phenomenon for differences strikingly in allele distributions, but negligibly in their risk estimations across ethnicities. Future large, well-designed studies are warranted to provide conclusive evidence on the effects of HHEX gene and other relevant genes on risk of diabetes.Despites these cautions, our meta-analysis of 162663 subjects provides clarification to the significant association of rs1111875, rs5015480 and rs7923837 in the Figure S1Pooled random-effects odds ratios of developing diabetes for rs1111875 (A), rs5015480 (B) and rs7923837 (C) polymorphisms in the HHEX gene under allelic model.(PDF)Click here for additional data file.


CETP gene and myocardial infarction (MI) risk.This meta-analysis aims to evaluate the relationships between seven functional polymorphisms in the The PubMed, CISCOM, CINAHL, Web of Science, Google Scholar, EBSCO, Cochrane Library, and CBM databases were searched for relevant articles published before March 1st, 2013 without any language restrictions. Meta-analysis was conducted using the STATA 12.0 software.CETP rs708272 (C>T) polymorphism might be correlated with an increased risk of MI, especially among Caucasians. Furthermore, we observed that CETP rs1800775 (C>A) polymorphism might increase the risk of MI. Nevertheless, no similar findings were found for CETP rs5882 (A>G), rs2303790 (A>G), rs1800776 (C>A), rs12149545 (G>A), and rs4783961 (G>A) polymorphisms.Nine case-control studies with a total 8,623 MI cases and 8,564 healthy subjects met the inclusion criteria. The results of our meta-analysis suggested that CETP rs708272 (C>T) and rs1800775 (C>A) polymorphisms may contribute to MI susceptibility, especially among Caucasians. Thus, CETP rs708272 and rs1800775 polymorphisms may be promising and potential biomarkers for early diagnosis of MI.The current meta-analysis suggests that  Myocardial infarction (MI) remains the leading cause of death and disability worldwide, accounting for up to 40% of all deaths CETP gene may enhance plasma cholesteryl ester formation and lead to low HDL-C levels and thereby possibly explain the inter-individual differences in MI risk Cholesteryl ester transfer protein (CETP) is a plasma protein that mediates the exchange of neutral lipids, including cholesteryl esters and triglycerides between plasma lipoproteins CETP gene is located on chromosome 6q21 and consists of 16 exons and 15 introns, spanning approximately 25 kb CETP gene have been found in the CETP gene, such as rs708272 (C>T), rs1800775 (C>A), rs5882 (A>G), rs2303790 (A>G), rs1800776 (C>A), rs12149545 (G>A), and rs4783961 (G>A); among these, rs708272 (C>T) and rs1800775 (C>A) are the most common variants that have been widely investigated CETP genetic polymorphisms might be a reliable predictor for the incidence of MI CETP gene and the risk of MI.Human The PubMed, CISCOM, CINAHL, Web of Science, Google Scholar, EBSCO, Cochrane Library, and CBM databases were searched for relevant articles published before March 1st, 2013 without any language restrictions. The following keywords and MeSH terms were used: (“SNP” or “mutation” or “genetic polymorphism” or “variation” or “polymorphism” or “single nucleotide polymorphism” or “variant”) and  and (“cholesterol ester transfer protein” or “CETP” or “cholesteryl ester exchange protein” or “CE transport protein”). We also performed a manual search of the reference lists from the relevant articles to find other potential articles.CETP genetic polymorphisms with the risk of MI; (2) all patients met the diagnostic criteria for MI; (3) the genotype frequencies of healthy controls should follow the Hardy-Weinberg equilibrium (HWE); (4) the study must provide sufficient information about the genotype frequencies. If the study could not meet the inclusion criteria, it would be excluded. The most recent or the largest sample size publication was included when the authors published several studies using the same subjects. The PRISMA checklist is available in The included studies must meet all four of the following criteria: (1) the study design must be clinical cohort or case-control study that focused on the relationships of Relevant data were systematically extracted from all included studies by two observers by using a standardized form. The researchers collected the following data: language of publication, publication year of article, the first author's surname, geographical location, design of study, sample size, the source of the subjects, genotype frequencies, source of samples, genotyping method, evidence of HWE, etc.Methodological quality was evaluated separately by two observers using the Newcastle-Ottawa Scale (NOS) criteria 2χ test. The statistical significance of pooled ORs was assessed by the Z test. The Cochran's Q-statistic and 2I test were used to evaluate potential heterogeneity between studies Q-test shows a P<0.05 or 2I test exhibits >50% which indicates significant heterogeneity, the random-effect model was conducted, or else the fixed-effects model was used. We also performed subgroup and meta-regression analyses to investigate potential sources of heterogeneity. We conducted a sensitivity analysis to assess the influence of single studies on the overall ORs. Begger's funnel plots and Egger's linear regression test were used to investigate publication bias The STATA version 12.0  software was used for meta-analysis. We calculated crude odds ratio (OR) with their 95% confidence interval (95%CI) to evaluate their relationships under 5 genetic models. Genotype frequencies of healthy controls were tested for the HWE using the CETP gene CETP gene were assessed, including rs708272 (C>T), rs1800775 (C>A), rs5882 (A>G), rs2303790 (A>G), rs1800776 (C>A), rs12149545 (G>A), and rs4783961 (G>A); and among these, rs708272 (C>T) and rs1800775 (C>A) were the most common SNPs. None of the studies deviated from the HWE . NOS scores of all included studies were ≥5. We summarized the study characteristics and methodological quality in CETP genetic polymorphisms are shown in Initially, the searched keywords identified 90 articles. We reviewed the titles and abstracts of all articles and excluded 44 articles; full texts were also reviewed and 34 articles were further excluded. Three other studies were excluded due to no sufficient data about seven common SNPs in the CETP rs708272 (C>T) polymorphism with the risk of MI were reported in 5 studies. The heterogeneity obviously existed (P<0.05), so the random effects model was conducted. Our meta-analysis results revealed that CETP rs708272 polymorphism may increase the risk of MI  (CETP rs708272 (C>T) polymorphism and an increased risk of MI among Caucasians (P>0.05). The results of subgroup analyses also suggested that CETP rs708272 (C>T) polymorphism was associated with increased risk of MI in the UK, population-based, hospital-based, PCR-RFLP and direct sequencing subgroups (as shown in CETP rs708272 (C>T) polymorphism showed no association with MI susceptibility in studies conducted in China, Iceland and USA.The relationships of P<0.001) . Among ducasians , but notCETP rs1800775 (C>A) polymorphism with MI risk. Since heterogeneity was significantly observed (P<0.05), the random effects model was used. Meta-analysis of these studies indicated positive correlations of CETP rs1800775 (C>A) polymorphism with an increased risk of MI  (CETP rs1800775 (C>A) polymorphism might increase susceptibility to MI in most subgroups (as shown in There were 4 studies that referred to the relationships of = 0.004) . We alsoCETP rs5882 (A>G), rs2303790 (A>G), rs1800776 (C>A), rs12149545 (G>A), and rs4783961 (G>A) polymorphisms  (as shown in The relationships of rs5882 (A>G), rs2303790 (A>G), rs1800776 (C>A), rs12149545 (G>A), and rs4783961 (G>A) polymorphisms with MI risk were also evaluated. Nevertheless, no similar associations were found for t = −1.92, P = 0.151; rs1800775: t = −0.07, P = 0.951).Meta-regression analyses were conducted for rs708272 (C>T) and rs1800775 (C>A) polymorphisms. The results confirmed that ethnicity might be a main source of heterogeneity  polymorphism might increase the risk of MI, especially among Caucasians, while similar results were not observed among Asians. There also existed positive correlations of CETP rs1800775 (C>A) polymorphism with an increased risk of MI among Caucasians. Although ethnic differences in to the risk of MI are well known, potential molecular mechanism is not fully understood. One possible reason for ethnic difference might be that CETP gene mutations might affect cholesteryl ester synthesis and result in low HDL-C levels, thereby possibly explaining interindividual differences in the incidence of MI CETP rs708272 (C>T) polymorphism with an increased risk of MI in the UK, population-based, hospital-based, PCR-RFLP and direct sequencing subgroups, indicating that country, source of controls and genotype method may be the potential sources of heterogeneity. However, our meta-regression analyses indicated that only ethnicity was the major source of heterogeneity. These disparate results may be due to small sample size resulting in substantial errors from estimation. Nevertheless, we observed no associations between the other 5 common polymorphisms in the CETP gene and MI risk. In short, the results of our meta-analysis were consistent with previous studies that CETP genetic polymorphisms may be closely linked to the risk of MI, suggesting that CETP genetic polymorphism could be useful and promising biomarkers for early diagnosis of MI.In the present meta-analysis, our findings revealed that CETP genetic polymorphisms and MI risk. Secondly, meta-analysis is a retrospective study that may lead to subject selection bias, and thereby affecting the reliability of our results CETP genetic polymorphisms in the development of MI. Although our study has many limitations, this is the first meta-analysis focusing on the relationships between CETP genetic polymorphisms and the risk of MI. Furthermore, we performed a highly sensitive literature search strategy for electronic databases. A manual search of the reference lists from the relevant articles was also conducted to find other potential articles. The selection process of eligible articles was based on strict inclusion and exclusion criteria. Importantly, rigorous statistical analysis of SNP data provided a basis for pooling of information from individual studies.The current meta-analysis also had many limitations that should be acknowledged. First, our results had lacked sufficient statistical power to assess the correlations between CETP rs708272 (C>T) and rs1800775 (C>A) polymorphisms may contribute to MI susceptibility, especially among Caucasians. Thus, CETP rs708272 and rs1800775 polymorphisms may be promising and potential biomarkers for early diagnosis of MI. However, due to the limitations mentioned above, more researches with larger sample size are needed to provide a more representative statistical analysis precisely.In conclusion, our findings provide empirical evidence that Checklist S1The PRISMA Checklist.(DOC)Click here for additional data file.File S1The Newcastle-Ottawa quality assessment scale.(DOC)Click here for additional data file.File S2CETP genetic polymorphisms in the case and control groups.The genotypic distributions of (XLS)Click here for additional data file.


The healthcare burden related to congenital heart disease (CHD) is increasing with improving survival. We assessed changing trends in prenatal risk factors for CHD in the current era in a Canadian cohort.P<0.001). Despite an increase in genetic testing in the recent era, only 9.5% of cases with CHD had a confirmed genetic diagnosis. Yield of genetic testing  was higher in familial and syndromic cases. There was an increase in parental age at conception, maternal prepregnancy body mass index, maternal urinary tract infections, type 1 diabetes, and exposure to nonfertility medications during pregnancy from 1990–2011. Later year of birth, family history of CHD, presence of major ECAs, maternal smoking during pregnancy, and maternal medication exposure were associated with increased odds of CHD . Advanced parental age was associated with increased odds of CHD caused by genetic abnormalities.CHD patients <18 years old (n=2339) and controls without structural heart disease (n=199) were prospectively enrolled in an Ontario province‐wide biobank registry from 2008–2011. Family history, frequency of extra‐cardiac anomalies (ECAs), and antenatal risk factors were assessed. Temporal trends were analyzed and associations with CHD were measured using linear and logistic regression. Family history of CHD and frequency of major ECAs was higher in cases versus controls (The increase in prenatal risk factors for CHD highlights the need for more rigorous ascertainment of genetic and environmental factors including gene‐environment interactions that contribute to CHD. Extrapolation of these findings estimates currently over 200 000 CHD cases in Canada and over 70 000 in Ontario alone.9 The changing population demographics highlight the need to reassess the contribution of genetic and environmental risk factors in the current era.10 An exploration of the contribution of noninherited risk factors that are potentially modifiable is particularly important in the context of the growing health burden of CHD.11Congenital heart disease (CHD) is the leading cause of infant deaths due to birth defects.17 The Baltimore‐Washington Infant Study previously associated maternal diabetes, influenza, ibuprofen therapy, parental smoking, and nutritional deficiencies with specific CHD subtypes.18 More recent studies have identified other associations including the National Birth Defects Prevention Study that evaluated the potential risk of medication use during pregnancy and birth defects.23 Changes in population demographics  and cultural diversity with time may also influence both genetic and environmental risk. We therefore performed a comprehensive analysis of genetic and environmental risk factors in CHD patients enrolled in an Ontario province‐wide biorepository and registry to assess trends in risk factors and their contribution to CHD subtypes in the current era.Reports linking environmental exposures to birth defects have steadily increased during the past decade with reported association of maternal  illnesses, nutritional deficiencies, drugs, and chemical exposures during embryonic and early fetal development with CHD. However, a failure to routinely ascertain environmental exposures during pregnancy, difficulty in quantifying these exposures, and maternal recall bias limit the ability to determine causality.24We established an Ontario province‐wide hospital‐based biobank registry of patients with congenital and other forms of childhood onset heart disease representing the first large‐scale study of CHD in an ethnically diverse population of Southern Ontario. Patients were prospectively enrolled from 6 pediatric and 4 adult cardiac programs across 7 hospitals in the province of Ontario between February 2008 and July 2011 with the goal of studying the genetic and environmental basis of CHD. Inclusion criteria were pediatric patients under the age of 18 years with structural heart disease. Controls without CHD were enrolled concurrently and included patients presenting to the hospital with innocent cardiac murmurs or chest pain with normal echocardiograms, dental lesions, infections, or obesity. The study was approved by the Research Ethics Board of each participating site. Written informed consent was obtained from the patient and/or parent or legal guardian. Consent was obtained for donation of biological samples including DNA, tissue, ongoing review of the patient's medical and surgical records, and completion of an intake questionnaire by the patient/parent. Details of the cohort design and recruitment processes have been previously published.25 The following information was captured from a review of the patients' medical records: detailed echocardiographic diagnosis , results of genetics evaluation, chromosomal, genetic and cytogenetic testing, the presence and type of extra‐cardiac anomalies (ECA) and concurrent medical illnesses. Cases were classified using the International Nomenclature for Congenital Heart Surgery into the following categories: septal defects (SD), endocardial cushion defects (ECD), right heart lesions (RHL), left heart lesions (LHL), transposition of the great arteries (TGA), thoracic vessel anomalies (TVA), patent ductus arteriosus (PDA), laterality disorders (LATDIS), and single ventricles (SV).26 ECAs were coded using the World Health Organization's International Classification of Diseases and Related Health Problems 10th Revision (ICD‐10) into major or minor congenital anomaly, non‐congenital anomaly, and chromosomal abnormality. Changes in the frequency from 1990−2011 of genetic screening and of prenatal exposure to noninherited or environmental risk factors were ascertained.The following clinical information was captured through questionnaires—maternal and paternal age at conception, parental consanguinity, maternal medical, gestational and obstetric history, smoking, alcohol and drug exposure during first trimester of pregnancy, and a multi‐generational family history of CHD and other birth defects. Exposure was defined by positive maternal history during the first trimester of pregnancy to the various exposures listed in Table 3. First‐, second‐, and third‐degree relatives were defined as previously reported by Oyen et al.P<0.05 to enter). All statistical analyses were performed using SAS statistical software v9.3 (The SAS Institute).Data are presented as means with standard deviation and frequencies as appropriate. Associations between year of birth and risk factors were evaluated in linear regression models. The differences between annualized frequencies were reported as estimated effect size (EST) with 95% confidence intervals (CI). Factors associated with all CHD and with different lesion subtypes were assessed in logistic regression models using patients without CHD as controls. Associations between exposure and risk were expressed as unadjusted odds ratios (OR) using univariable analysis unless otherwise specified. CHD and its subtypes were compared with controls in univariable and multivariable models using a stepwise algorithm for multivariable model selection (27 Distribution of primary and secondary CHD diagnoses are listed in Tables P<0.05 versus cases). Racial distribution differed between cases and controls but was comparable to Ontario population census data from 2006 .28 Gender distribution was similar between controls and cases . However, there was a preponderance of males to females in the following CHD subtypes relative to controls: ECD , PDA , SD  and TVA . Of the 2339 CHD index cases, 9.5% had a confirmed genetic diagnosis or recognizable syndrome, 21.8% had a positive family history of CHD or associated major ECAs of unknown etiology, and the remaining 68.7% had isolated, sporadic CHD of unknown etiology  ; 2339 index cases with CHD <18 years old were eligible for this study. An additional 199 children without CHD were recruited as controls (consent rate 89%). A total of 1581 (68%) patients had a single primary lesion, 758 (32%) had diagnoses encompassing multiple cardiac lesions. This is consistent with findings in the National Birth Defect Prevention Study.ed ECAs) . The freP=0.005) and higher frequency of affected first‐degree relatives in cases compared to controls  (P=0.001), PDA , RHL , and SD   . The les P=0.02) a. TwentyP<0.001) (P<0.001) and LATDIS  compared with other CHD subtypes (18%)   and stroes (18%) b. Major es (18%) . Forty‐oP<0.001). During the same period, frequency of genetic testing increased from 9% to 25%  including increased karyotype testing, fluorescent in situ hybridization (FISH) for 22q11deletion, microarray testing, and multiplex ligation‐dependent probe amplification (MLPA) for detecting deletions/duplications  (P<0.001). However, the increase in frequency of genetic testing was not paralleled by an increase in the yield from genetic tests . Thus, the proportion of patients with a clinically diagnosed syndrome and/or abnormal genetic test in the overall cohort only increased from 8% to 11%  representing a minor fraction of all CHD despite a 3‐fold increase in testing indicating that the increase in confirmed genetic diagnoses was due to increased testing rather than improved sensitivity of the genetic tests. Overall, the yield on genetic testing was highest in syndromic patients (43%) followed by familial cases (32%) and lowest in isolated, sporadic CHD (8%) using conventional testing methods.During 1990 to 2011, frequency of fetal echocardiographic screening increased from 21% (1990–99) to 36% (2000–11)  . This waP<0.001), paternal age at conception , increase in pre‐pregnancy maternal body mass index (BMI) , frequency of maternal urinary tract infections during pregnancy , type 1 diabetes , and exposure to nonfertility medications during the first trimester . Frequency of maternal smoking  and alcohol ingestion during early pregnancy  declined with time. There was no change over time in the frequency of rubella, hypertension, in vitro fertilization, gestational diabetes, and recreational drug use.We assessed prenatal risk factors through data from questionnaires . PrenataWe compared the frequency of prenatal risk factors including medication exposures between CHD cases and controls . Medicat2=70.2, P<0.0001; c‐statistic=0.74), the following factors were associated with CHD: later year of birth , family history of CHD , presence of major ECAs , maternal smoking during pregnancy , and maternal exposure to nonfertility medications  (P=0.002) and older paternal age  was limited to CHD patients with genetic abnormalities.In multivariable regression models (χP<0.001) . These aIn a study of genetic and environmental risk factors in a prospectively enrolled cohort of children with CHD from a multiethnic population in Ontario, we identified a high proportion of inherited CHD but low sensitivity of current genetic testing methods in identifying genetic loci for CHD particularly in isolated or sporadic CHD. Our findings also demonstrated a rising trend in prenatal environmental exposures in the recent era and a strong association of these factors with CHD.25 who reported a 3.1% prevalence of CHD in first‐degree relatives. Previous cohort studies have revealed CHD recurrence rates between 2.7% and 4.1% with higher recurrence rates in some subtypes .29 While the higher recurrence rate identified in our cohort may reflect differences in heritability associated with different ethnicities, it may also represent better ascertainment of family history which was done prospectively as opposed to through a retrospective review of registry data. Our findings emphasize the importance of routine ascertainment of 3‐generation family history as was emphasized in the American Heart Association guidelines.3 However, family history alone may miss “silent” cardiac lesions like bicuspid aortic valve, small SDs, or minor TVAs and thereby underestimate familial incidence. Routine echocardiographic screening of family members particularly for lesions with a high recurrence risk may better help identify familial cases and help prioritize these cases for genetic testing given the higher yield of genetic testing in familial CHD. Importantly, since yield on genetic testing is higher in familial compared to sporadic cases, ascertainment of family history will help prioritize these cases for genetic evaluation.The first important finding was the high prevalence of CHD in first‐degree relatives (9%) compared to that reported in a recent Danish cohort study by Oyen et al30 The utility of classifying CHDs by cardiac and extra‐cardiac phenotypes was shown to be a useful approach for deciphering disease etiology in a report by Botto et al27 using data from the National Birth Defect Prevention Study. Relatively high prevalence of ECAs, particularly major ECAs (22%), not only in cases with ECDs and LD as would be expected, but also in other CHD subtypes reinforces the importance of detailed physical examination and screening of CHD cases for ECAs. Knowledge of extra‐cardiac phenotype is useful in prenatal and postnatal counseling due to the potentially adverse impact of major ECAs on overall outcomes. More importantly, early screening and identification of ECAs can facilitate preemptive and perioperative management strategies that reduce the adverse impact of unrecognized anomalies.32 Also, given the higher yield on genetic testing of syndromic cases, this approach may also help identify a subset of patients who should be offered genetic testing.The relatively high burden of ECAs in our cohort was comparable to findings in Danish and Norwegian cohorts.35 These technologies are rapidly becoming available in the clinical arena and are likely to improve the yield of genetic tests as well as improve our ability to identify gene‐gene interactions and a “polygenic” etiology, while permitting better discrimination between benign and pathogenic variants.Disappointingly, despite a high proportion of inherited and/or syndromic CHD and overall increase in genetic testing in patients with CHD in the current era, genetic diagnoses were confirmed in only 9.5% of patients. Overall yield of genetic testing even in the current era was low at 20%. While the yield can be increased by targeting genetic testing to patients with familial or syndromic CHD that comprise nearly 40% of the CHD cohort, current testing methods remain relatively insensitive in their ability to identify small structural variations and/or rare sequence variations in coding and noncoding regions that likely contribute to a large proportion of CHD. High‐resolution genomic arrays and next‐generation sequencing‐based diagnostics are likely to become important tools in identifying these single or compound rare and de novo variants particularly in patients with sporadic isolated CHD who comprise the vast majority of CHD.37 This may reflect the decrease in maternal alcohol consumption and lower prevalence of obesity in our cohort compared to other cohorts and/or the cosegregation of these risk factors with other risk factors identified in our study.17 A particularly important finding was the association of advanced parental age with CHD with genetic abnormalities consistent with previously reported associations of advanced maternal age with aneuploidy and advanced paternal age with germline mutations, and more recently with de novo mutations in disorders like childhood autism.38 This finding raises concerns about the mutational burden associated with rising parental age on CHD and emphasizes the need for routine prenatal or postnatal screening with genetic testing and echocardiography in pregnancies with advanced parental age.The search for the genomic basis of complex disorders is incomplete without an assessment of environmental factors that, either independently or through gene‐environment interactions, can influence disease causation. We found a significant increase in the frequency of prenatal exposure to environmental risk factors in the current era. These included advanced maternal and paternal age at conception, higher maternal BMI, higher frequency of maternal medical conditions during pregnancy like urinary tract infections and type 1 diabetes, and higher prenatal exposure to medications. Although maternal smoking and alcohol consumption rates decreased over time, maternal smoking remained highly associated with all types of CHD. On multivariable analysis, later year of birth, positive family history of CHD, presence of major ECAs, maternal smoking, and maternal intake of medications remained associated with the risk of CHD . Unlike 39 Our findings are also consistent with other studies which reported a significant association between fertility medication use and CHD in a recent National Birth Defects Prevention Study report that demonstrated an association of septal heart defects and coarctation of aorta with prenatal clomiphene citrate intake.41 The association with nonfertility medications is equally concerning and highlights the gaps in our knowledge of the safety of commonly used drugs during pregnancy. We recognize that these associations do not necessarily indicate causality and, therefore, caution is advised when making generalized inferences of causation. Also it is not clear whether the association with CHD is related to the use of medication or to the underlying medical condition for which medications were used. Nonetheless, our findings raise concerns about the presumed safety of prescribed or over‐the‐counter medications and highlight the need for more rigorous assessment of the safety of common medications used during pregnancy. They also suggest that consideration should be given to early screening of pregnancies involving assisted conception for CHD. Finally, an improved knowledge of pharmacogenomics may enable us in the future to identify which pregnancies are susceptible to the teratogenic effects of specific medications and help individualize prenatal counseling towards reducing risk factor exposure in at‐risk pregnancies.42 The importance of population biorepositories such as ours that capture both genetic and environmental data to address these gaps in knowledge cannot be overemphasized.24A factor that emerged significantly associated with all forms of CHD independent of the presence of genetic abnormalities was maternal intake of fertility and nonfertility medications. This was concerning particularly in light of the increase in medication use during pregnancy in our cohort. Our findings are concordant with a recent study from Australia which reported a higher frequency of birth defects in pregnancies with assisted conception (8.3%) versus 5.8% birth defects in pregnancies not involving assisted conception (OR 1.47).43 Another limitation was the lack of ascertainment of socio‐economic and educational status, and the reliance on questionnaires rather than blood sampling of pregnant mothers to assay environmental exposures that can result in recall bias. Nonetheless, coupling detailed assessment of both prenatal and environmental risk factors with sample collection for genomics research has enabled us to identify a cohort of high‐risk women with prenatal exposures that will be explored further to define the gene‐environment interactions that contribute to complex multifactorial disorders like CHD.Our study was limited by the lack of routine echocardiographic, extra‐cardiac, and genetic screening of all CHD families which may have resulted in underestimation of recurrence rates and of ECAs. Since patients were recruited after birth, the study excluded prenatally diagnosed cases that died or underwent termination antenatally or those that died early postnatally which may have resulted in underrepresentation of the most severe phenotypes. However, as a case cohort study to analyze risk factors for CHD, the study cohort is still considered representative of postnatal CHD survivors. The relatively small size of the control cohort may have reduced our power to detect some significant associations and resulted in some OR being calculated from rare events in controls. Where possible, factors were grouped into categories  to increase event rate and improve the precision of OR calculations. Prevalence of consanguinity in cases and controls was relatively high compared to a previous Canadian study which utilized data from 1959 and therefore did not account for the ethnic diversity of Ontario, immigration of ethnic populations, nor increased consanguinity in Asian and South Asian populations.In summary, our study highlights the growing burden of genetic and environmental prenatal risk factors for CHD in the current era, in particular the rising prevalence of maternal obesity and diabetes, advanced maternal and paternal age at conception, and increased use of medications. It highlights a pressing need for better surveillance for CHD both antenatally and postnatally, routine ascertainment and counselling regarding environmental exposures during pregnancy, routine family history in all affected pregnancies, and better genetic screening technology. Public health advocacy measures to reduce environmental risk especially for modifiable risk factors like smoking, alcohol, obesity, diabetes, and medication use are important. Consideration should be given to routine antenatal screening for CHD in women with multiple risk factors including advanced parental age, preexisting maternal conditions and maternal exposure to known teratogens and fertility drugs. Ultimately, this knowledge can be used for early prevention, early risk stratification, and the development of targeted diagnostics and therapies to reduce the health and economic burden of CHD.


GSTT1) polymorphism and risk of prostate cancer showed inconclusive results. To clarify this possible association, we conducted a meta-analysis of published studies.Recent studies on the association between Glutathione S-transferase T1 . The odds ratio (OR) and its 95% confidence interval (95%CI) was used to assess the strength of the association. We summarized the data on the association between GSTT1 null genotype and increased risk of prostate cancer . Meta-analysis of adjusted ORs also showed a significant association between GSTT1 null genotype and increased risk of prostate cancer . Similar results were found in the subgroup analyses by ethnicity and types of controls.Ultimately, a total of 43 studies with a total of 26,393 subjects  were eligible for meta-analysis. Overall, there was a significant association between GSTT1 null genotype is associated with prostate cancer susceptibility, and GSTT1 null genotype contributes to increased risk of prostate cancer.This meta-analysis demonstrates that  GSTT1) gene located on the long arm of chromosome 22 (22q11.23), and the homozygous deletion (null genotype) of GSTT1 gene causes complete absence of GST enzymes activity GSTT1 null genotype and prostate risk was reported. This meta-analysis including 22 studies  concluded that there was no association between GSTT1 null genotype and prostate risk GSTT1 null genotype and prostate risk GSTT1 null genotype and prostate risk.Prostate cancer is a common cause of cancer mortality and one of the most frequently diagnosed malignancies in men GSTT1” or “GSTT”) and (“prostate cancer” or “prostate carcinoma”). Additional literature was collected from cross-references within both original and review articles. No language restrictions were applied. A study was included in the current meta-analysis if: (1) it was published up to May 2012; (2) it was a case-control study; (3) the control subjects are prostate cancer-free regardless of whether they had benign prostate hyperplasia (BPH) or not. We excluded family-based studies of pedigrees with several affected cases per family because the analysis was based on linkage considerations. When a study reported the results on different ethnicities, we treated them as separate studies.Data were collected from the following electronic databases: Pubmed, Embase, and and Chinese Biomedical Database (CBM). Relevant publications were identified through a literature search using the following search strategy:  and its 95% confidence interval (95%CI). Different descents were categorized as Caucasians, East Asians, Africans, Indians, and Others. If original genotype frequency data were unavailable in relevant articles, a request was sent to the corresponding author for additional data. In deed, only two requests were sent, but no replies were obtained.Information was carefully extracted from all the eligible publications independently by two of the authors according to the inclusion criteria listed above. Disagreement was resolved by discussion among all authors. Data extracted from the selected studies included author, year of publication, country, ethnicity, definition of cases, characteristics of controls, total numbers of cases and controls, the genotype frequency of GSTT1 null genotype and prostate cancer risk was assessed by calculating the pooled OR with its 95%CI. The pooled ORs were obtained using either the fixed-effects (Mantel-Haenszel's method) 2 statistic 2 statistic (I2>50%) indicated obvious heterogeneity across studies, and the random effect model was selected to pool the ORs. Otherwise, the fixed effect model was selected to pool the ORs. Subgroup analyses were performed by ethnicity, adjusted ORs, and types of controls. Subgroup analyses were firstly performed by adjusted ORs including subgroup analysis of adjusted ORs and subgroup analysis of unadjusted ORs. Subgroup analyses were then performed ethnicity, and ethnicities were categorized as Caucasians, East Asians, Africans, Indians, and Others. Finally, Subgroup analyses were performed by the types of controls. Publication bias was investigated with the funnel plot. The funnel plot should be asymmetric when there is a publication bias, and the funnel plot asymmetry was further assessed by the method of Egger's linear regression test The strength of the association between GSTT1 polymorphism; 2 were meta-analysis; 2 were reviews), leaving 47 studies for full publication review There were 97 papers relevant to the searching words, and 50 papers were excluded    . Meta-an= 0.006) .GSTT1 null genotype and increased risk of prostate cancer in Caucasians , East Asians , and Indians , but not in Africans .In the subgroup analyses were firstly performed by ethnicity . There was an obvious association between GSTT1 null genotype and increased risk of prostate cancer . In the subgroup analysis of controls without BPH, there was an obvious association between GSTT1 null genotype and increased risk of prostate cancer .In the subgroup analysis of BPH controls, there was no obvious association between Egger's test = 0.117). Thus, there was no obvious risk of bias in this meta-analysis.Both funnel plot and Egger's test were performed to assess the publication bias of the studies. The shape of the funnel plots did not reveal any evidence of obvious asymmetry for any genetic model in the overall and subgroup meta-analysis . Next, EGSTT1 null genotype and prostate cancer risk reported inconclusive and inconsistent findings. Therefore, to get a reliable conclusion for the association of GSTT1 null genotype and prostate risk, we conducted the present meta-analysis of 43 independent studies including a total of 26, 393 subjects . Overall, there was a significant association between GSTT1 null genotype and increased risk of prostate cancer Click here for additional data file.Checklist S1PRISMA Checklist.(DOC)Click here for additional data file.


ICAM-1) K469E  gene polymorphism with diabetic microvascular complications (DMI) including diabetic nephropathy (DN) and diabetic retinopathy (DR) in different populations. However, the results of individual studies remain conflicting.A number of studies evaluated the association of intracellular adhesion molecule-1  and 95% confidence intervals (CIs) were assessed using the fixed or random effect model.P = 0.02). In the subgroup analysis stratified by ethnicity, significant association was found in Asians but not in Caucasians . Moreover, it showed a significant association between the A allele and risk of DN in a recessive model .Seven studies involving 3411 subjects were included. Overall, the meta-analysis showed a significant association of the A allele with increased risk of DMI susceptibility in a recessive model (OR = 1.37, 95% CI 1.04–1.80, ICAM-1 gene might affect individual susceptibility to DMI and showed a discrepancy in different ethnicities. Further investigations are needed to validate the association.This meta-analysis suggested that the K469E polymorphism in  There has been a rising epidemic of diabetes mellitus throughout the world in recent years and an alarming increase in the rate of mortality and morbidity due to coexisting dyslipidemia, atherosclerosis and cardiovascular disease ICAM-1), a cell surface glycoprotein, is a member of the immunoglobulin superfamily of adhesion molecules ICAM-1 in animal models of diabetic nephropathy and diabetic retinopathy ICAM-1 gene  results in an amino acid substitution from glutamic acid (E) to lysine (K) in immunoglobulin-like domain 5 of the ICAM-1 protein. It has been shown to inﬂuence the binding of ICAM-1 on endothelial cells and lymphocyte function-associated antigen-1 (LFA-1) and Mac-1 on leucocytes, mediating leukocytosis and its migration in an inﬂammatory environment Intercellular adhesion molecule-1 ” or “variant”. Both type 1 and type 2 diabetic patients were enrolled in the study. Additional studies not captured by our database searches were identified through reviewing the reference lists of retrieved articles. The included studies were published ranging from 2002 to 2012 .The electronic databases PubMed, Embase and Web of Science (ISI) were searched using the following terms: “ICAM-1 gene and risk of DN and/or DR; (2) available genotype distribution of cases and controls that can provide sufficient data for calculation; (3) published in English.Two investigators reviewed all identified articles independently to determine whether an individual study was eligible for inclusion in our meta-analysis. The inclusion criteria were as follows: (1) case-control study published as an original study to evaluate the association between K469E polymorphism in All data were collected according to a standard technological process. Studies that were repeated, did not satisfy the inclusion criteria, and provided little information or insufficient data were excluded. P<0.05. Dominant, recessive and additive genetic models were all used in our meta-analysis. The 2I of Higgins and Thompson was used to test the heterogeneity between the studies 2I>50%) The relationship between K469E (A/G) polymorphism and DMI including DR and DN was compared using odds ratios (ORs) and their corresponding 95% confidence intervals (95% CIs). The Z test was used to determine the pooled OR with the significance level set at P<0.05. The potential publication bias was evaluated by Egger’s test and visual inspection of funnel plots. All statistical analyses were performed using the STATA version 11.0 software .An exact Chi-square test was used to assess the Hardy–Weinberg equilibrium (HWE) with the significance level set at ICAM-1 K469E gene polymorphism and DMI was found in a recessive genetic model . However, no significant association was found either using a dominant model  or an additive model  in all study populations . Therefore, the random-effects model was used for synthesis of the data.As shown in ulations . In the P = 0.05). The dominant model and the additive model were remains non-significant .After exclusion of the article deviating from HWE in cases and in controls, the A allele was still found to be significant associated with an increase risk of DMI in a recessive model  and an additive  model, but not in a dominant model . However, the significant association between the ICAM-1 K469E gene polymorphism and DMI was not found among Caucasians . Moreover, the heterogeneity of the subgroup disappeared (I2 = 0.0%). However, in the subgroup of DR, no significant association with the A allele was found in all genetic models .With regard to the specific type of DMI, we also conducted the subgroup analyses stratified by DN or DR. The results showed that the A allele was found to be significantly associated with an increase risk of DN in a recessive model .The publication bias of the included studies was assessed by the Begg’s funnel plot and Egger’s test. The funnel plot for additive model in all studies showed no evidence for asymmetry . And EggICAM-1 gene, encoding intercellular adhesion molecule 1, might play a crucial role in the pathogenesis of DMI including DN and DR ICAM-1 gene K469E (rs5498) polymorphism and DMI risk was first reported in an East Asian population ICAM-1 gene K469E polymorphism in DMI susceptibility have been reported ICAM-1 gene K469E polymorphism and DMI risk.The incidence of microvascular complications is increasing among the growing number of patients suffering from diabetes mellitus ICAM-1 gene K469E polymorphism and DMI risk. With the use of results provided in previous studies, we compared the minor allele to major allele in additive model, recessive model and dominant model. A significant relationship was found between ICAM-1 gene K469E polymorphism and increased DMI risk under a recessive model . However, no significant association between ICAM-1 gene K469E polymorphism and DMI risk was found in dominant and additive models . Furthermore, ethnic-specific meta-analysis showed that no significant association existed between ICAM-1 gene K469E polymorphism and DMI in Europeans . In contrast, DMI risk was increased in Asians in recessive and additive models , suggesting a possible influence among environmental exposures and different genetic backgrounds. In the stratified analysis by the specific type of microvascular complication, the significant association was observed in DN subgroup in recessive model . Nevertheless, no significant association of ICAM-1 gene K469E polymorphism with DR subgroup was found . Since this meta-analysis included only two studies using DN population, the false positive association between ICAM-1 gene K469E polymorphism and DN could not be ruled out because studies with small sample size may have random error to detect a slight effect. Additional future studies should be performed to focus on DN population. More studies are warranted to further validate microvascular complication type difference in the effect of this polymorphism on DMI susceptibility.This current meta-analysis of 7 studies including 1810 DMI cases and 1601 diabetic controls systematically evaluated the association between ICAM-1 that is essential for dimerization, surface presentation and solubilisation of the protein ICAM-1 mRNA splicing pattern and TPA-induced apoptosis ICAM-1 gene may play an important role in inﬂammation and atherosclerosis.The polymorphism K469E (rs5498) is a non-synonymous single nucleotide polymorphism and resides in the fifth immunoglobulin-like domain of As the publication of findings often depends on the expectation of researchers, false-negative results may be suppressed or false positive results magnified The present meta-analysis had several limitations that must be taken into account. Firstly, only published data which were included by the published studies and unpublished studies which had null results were missed, which might bias the results, while our statistical tests may not have totally shown it. Secondly, the overall outcomes were based on individual unadjusted genotype data, while a more precise evaluation should be made by adjusting other potentially suspected factors including age, sex, and environmental factors. Thirdly, data were not stratified by other factors such as gender status and the clear diagnosis methods of DMI, because sufficient information could not be extracted from the original studies. Fourthly, because of the complex nature of DMI, it is unlikely that a SNP in one single gene would be obviously associated with an increase in DMI risk, without consideration of any other polymorphic susceptible genes. Fifthly, although there are many similarities in the coexistence of DR and DN being both as microvascular disease and microscopically both have capillary basement membrane thickening, they still have somewhat different pathogenesis. DR is characterized by a spectrum of lesions within the retina. These include changes in vascular permeability, capillary microaneurysms, capillary degeneration, and excessive formation of new blood vessels. However, the development and progression of DN is highly complex given the diversity of cell populations present within the kidney and the various physiological roles of this organ. High glucose concentrations induce specific cellular effects, which affect various resident kidney cells including endothelial cells, smooth muscle cells, mesangial cells, podocytes, cells of the tubular and collecting duct system, and inﬂammatory cells and myofibroblasts. Sixthly, both types of diabetes were enrolled in our study, and differences in pathogenesis between type 1 and type 2 diabetes are existed. Finally, since the number of studies included in the subgroup analyses was small, the results lacked sufficient reliability to confirm or refute an association in a definitive manner.ICAM-1 gene K469E polymorphism and DMI susceptibility. It provided evidences of the association between ICAM-1 gene K469E polymorphism and DMI risk, and supported the hypothesis that the ICAM-1 gene K469E polymorphism might be a susceptibility marker for DMI. Since potential biases and confounders could not be ruled out completely in this meta-analysis, additional large case-control studies are required to validate our findings. Meanwhile, further studies regarding other SNPs (or haplotypes) in the ICAM-1 gene and DMI susceptibility are also encouraged to help better understand the role of ICAM-1 gene in DMI. Moreover, gene-gene and gene-environment interactions should also be considered in future studies.To our knowledge, this study was the first comprehensive meta-analysis to assess the relationship between


CYP2C19 and ABCB1 polymorphisms in an individualized approach to clopidogrel treatment. The aims of this study were to evaluate the frequencies of CYP2C19 and ABCB1 polymorphisms and to identify the clopidogrel-predicted metabolic phenotypes according to ethnic groups in a sample of individuals representative of a highly admixtured population.Recent studies have reported the clinical importance of ABCB1c.C3435T (rs1045642), CYP2C19*2 (rs4244285), CYP2C19*3 (rs4986893), CYP2C19*4 (rs28399504), CYP2C19*5 (rs56337013), and CYP2C19*17 (rs12248560) polymorphisms were detected by polymerase chain reaction followed by high resolution melting analysis. The CYP2C19*3, CYP2C19*4 and CYP2C19*5 variants were genotyped in a subsample of subjects (300 samples randomly selected).One hundred and eighty-three Amerindians and 1,029 subjects of the general population of 4 regions of the country were included. Genotypes for the CYP2C19*3 and CYP2C19*5 variant alleles were not detected and the CYP2C19*4 variant allele presented a frequency of 0.3%. The allelic frequencies for the ABCB1c.C3435T, CYP2C19*2 and CYP2C19*17 polymorphisms were differently distributed according to ethnicity: Amerindian ; Caucasian descent ; Mulatto ; and African descent  individuals, respectively. As a result, self-referred ethnicity was able to predict significantly different clopidogrel-predicted metabolic phenotypes prevalence even for a highly admixtured population.The ABCB1 and CYP2C19 variant allele frequencies in the Brazilian general population plus Amerindians. This information could help in stratifying individuals from this population regarding clopidogrel-predicted metabolic phenotypes and design more cost-effective programs towards individualization of clopidogrel therapy.Our findings indicate the existence of inter-ethnic differences in the  Clopidogrel, a prodrug, is a thienopyridine that inhibits adenosine diphosphate-induced (ADP) platelet aggregation. It has been prescribed mainly in patients with acute coronary syndromes (with or without ST-segment elevation) and patients submitted to percutaneous coronary intervention. It is a pro-drug that requires hepatic metabolization and activation by the cytochrome P450 (CYP) in order to produce its active metabolite. Metabolization of the drug is achieved by a number of different CYP isoenzymes. Two oxidative steps are essential, which culminates in the active metabolite. In particular, the isoenzyme CYP2C19 is involved in the two steps contributing to an estimated 45% of first step and 21% of its change to the active metabolite .CYP2C19 gene polymorphisms and the enzyme activity [CYP2C19*2 (c.G681A), leads to a splicing defect that functionally affects the enzyme. Other alterations have also been reported as loss-of-function: CYP2C19*3 , CYP2C19*4 , and CYP2C19*5  [Several studies have demonstrated an association between activity -9. The mCYP2C19*2 allelic variant has been associated with higher levels of ADP-induced platelet aggregation values in clopidogrel-treated patients and, consequently, a higher risk of adverse cardiovascular events, such as the occurrence of stent thrombosis [CYP2C19*17 , has been associated with increased enzyme function [rombosis -8. In cofunction . Thus, ifunction .MDR1 or ABCB1) encodes a drug-efflux transporter called P-glycoprotein, which functions as a physiologic intestinal barrier against drug absorption [ABCB1 gene [On the other hand, it is known that the bioavailability of clopidogrel and of other drugs is also limited by absorption. The multidrug resistance gene  . The uniIn addition, one hundred and eighty-three Amerindians derived from two different groups  were also analyzed.The study protocol was approved by the involved Institutional Ethics Committees and National Ethic Committee for Human Research (CONEP Register Number 4599), and written informed consent was obtained from all participants prior to entering the study.ABCB1c.C3435T (rs1045642), CYP2C19*2 , CYP2C19*3 , CYP2C19*4 , CYP2C19*5 , and CYP2C19*17  polymorphisms were detected by polymerase chain reaction (PCR) followed by high resolution melting analysis [®, Qiagen, Courtaboeuf, France) using the primer sequences listed in Table Genomic DNA was extracted from peripheral blood leukocytes following a standard salting-out method . Genotypanalysis  . In the HRM phase, the Rotor Gene 6000® measured the fluorescence in each 0.1°C temperature increase in the range of 70-94°C. Melting curve was generated by the decrease in fluorescence with the increase in the temperature; and in analysis, nucleotide changes results in different curve patterns. Samples of the three observed curves were sequenced  to confirm the genotypes indicated by HRM.The PCR was performed with addition of fluorescent DNA-intercalating SYTO9CYP2C19 polymorphisms, individuals were grouped into distinct phenotypes: extensive metabolizer (EM: wild-type for the CYP2C19 polymorphisms), intermediate metabolizer (IM: heterozygous genotype for the loss-of-function CYP2C19 polymorphisms and wild-type for the CYP2C19*17), poor metabolizer (PM: homozygous or compound heterozygous genotypes for the loss-of-function CYP2C19 polymorphisms) and ultra-rapid metabolizer (UM: heterozygous or homozygous genotypes for the CYP2C19*17 and wild-type for the CYP2C19*2). The predicted metabolic phenotype of individual carrying homozygous or heterozygous genotypes for the CYP2C19*17 polymorphism plus heterozygous genotype for the CYP2C19*2 polymorphism are unknown. The individuals carrying homozygous genotype for the *2 (*2/*2) plus heterozygous or homozygous genotype for the *17 were classified as PM, because the first alteration leads to a loss-function enzyme, while a second causes an increased transcription . Chi-square test was also performed for the determination of differences of allelic frequency for the ABCB1 and CYP2C19 polymorphisms, of ethnicity according to Brazilian regions, and for the comparative analysis between our data and previous reports. Hardy-Weinberg equilibrium and linkage disequilibrium analyses were conducted with Haploview 4.0. All other statistical analyses were carried out using the SPSS software (v. 16.0), with the level of significance set at p < 0.05.Chi-square test was performed for comparative analysis of the allelic and genotypic frequencies for the Of the 1,212 subjects (mean age 43.2 ± 14.2), 651 (53.7%) were female and 561 (46.3%) male. Ethnic group distribution was: Amerindians 15.1% (n = 183), Caucasian descent 50.7% (n = 615), Mulatto 26.0% (n = 315) and African descent 8.2% (n = 99).Of the 1,029 subjects from the general population, 615 (59.8%) individuals belonged to the Southeast region, 198 (19.2%) to the Northeast region, 114 (11.1%) to the South region, 98 (9.5%) to the Midwest region, and only 4 (0.4%) to the North region of the country. The South region presented the highest frequency of Caucasian descent subjects (86.0%) as opposed to the Northeast region (52.0%), while the Northeast and Midwest regions presented higher frequencies of African descent subjects (11.1% and 9.2%) as opposed to the South region (4.4%) (p < 0.001). These results are in accordance to the described by the IBGE (Brazilian Institute of Geography and Statistic) on the last Brazilian census report.ABCB1c.C3435T polymorphism were higher in Amerindians compared with Caucasian descent , Mulatto , and African descent , respectively (p < 0.001)  and of the homozygous genotype 27.3%) for the 7.3% for CYP2C19*2 variant allele and of the homozygous genotype were higher in African descent individuals (20.2% and 6.0%) and were lower in Amerindians (10.4% and 3.8%) compared with other ethnic groups  . However, the CYP2C19*4 variant allele was observed in two samples in the heterozygous form .The CYP2C19*17 variant allele was higher in African descent subjects (26.3%) and was lower in Amerindians (15.8%) compared with other ethnic groups (p = 0.048) .Linkage disequilibrium analysis show that the ABCB1c.C3435T variant allele frequency was observed in the South region (44.0%), while a lower prevalence was presented in the Midwest region (32.0%) (p = 0.017). The Midwest region presented higher frequency of subjects carrying CYP2C19*2 variant allele (26.0%) compared with other regions (p = 0.003). For the CYP2C19*17 variant allele no difference in the frequency between regions was observed  than in Caucasian descent (47.0%), Mulatto (40.6%) and African descent (33.3%) p < 0.001). The frequency of IM individuals was higher in African descent subjects (19.2%) than in other groups (p = 0.010). African descent subjects (32.3%) presented a higher frequency of the UM predicted phenotype, while the Amerindians presented lower frequency (20.8%) (p = 0.048). However, no differences were observed in the frequency of PM individuals according to ethnicity (Table % than in. The freCYP2C19*17 polymorphism plus a heterozygous genotype for the CYP2C19*2 polymorphism (*2/*17) are unknown. The frequencies of these genotype combinations were similar in Amerindians (4.4%), Caucasian descent (5.5%), Mulatto (6.0%), and African descent (9.1%) groups (p = 0.429)  Table .CYP2C19 polymorphisms in Brazilian Amerindians plus a sample representative of the Brazilian general population. These results could be very useful in the strategic planning of the implementation of pharmacogenetic testing for these variants, aiming at an individual therapeutic approach and adverse drug effect profile prediction both, at the individual and regional country level. To our knowledge, there is no implemented genetic-based prescription program in Brazil; however, the study by Gladding et al concluded that genotyping for the relevant gene polymorphisms may help to individualize and optimize clopidogrel treatment [Probably the main contribution of the present study was the demonstration, in the Brazilian population of significant differences between the allelic and genotypic frequencies of polymorphisms associated to clopidogrel, according to ethnicity. To our knowledge this is the first study evaluating One potential limitation relates to the self-referred ethnicity. However, this type of classification is the one most probable to be encountered in real-life situations. In addition, even self-referred ethnicity was able to clearly differentiate groups of individuals with rather different allele and genotype frequencies. Finally, different allele and genotype frequencies were also observed when individuals were separated by the country's geographic region. Although a great amount of this effect was probably due to different ethnic distribution according to regions, both variables were independently predictive of genotype distribution in multivariate models adjusted by both ethnic group and country region (data not shown). Probably interaction effects, as well as other confounders, could explain these findings. In fact, one should not dissociate ethnic group self-referral from country region, since cultural aspects may modulate the way people describe themselves regarding ethnicity and this certainly may differ in different parts of the country. This effect should be studied in future works.VKORC1 polymorphism in 4,886 individuals of 11 countries , and the contribution of VKORC1 toward dose requirements is higher in whites than in nonwhites [Similarly, interethnic differences were observed in the onwhites . Other sonwhites .ABCB1 gene encodes a P-glycoprotein that exports drugs, including clopidogrel. Simon et al (2009) studied 2,208 patients presenting with an acute myocardial infarction and receiving clopidogrel therapy. They reported that patients carrying one or two variant alleles for the ABCB1 c.C3435T polymorphism presented more than five times the rate of adverse events of patients with the wild-type genotype [The ABCB1 c.C3435T variant allele frequencies reported in studies using samples from African individuals (Ghanian and Kenyan [The d Kenyan ) was of d Kenyan ; Spanishd Kenyan ; German,d Kenyan ; Polish,d Kenyan ), the vaCYP2C19*3 and CYP2C19*5 variant alleles and the rare frequency of CYP2C19*4 variant allele (0.3%) in our study does not exclude the existence of individuals with PM or IM predicted metabolic phenotypes by presence of these loss-of-function alleles in the Brazilian population. Nevertheless, it clearly shows that these variants are less powerful for the cost-effectiveness design of programs aiming at the identification of individuals harboring predicted metabolic phenotypes compared to the CYP2C19*2 and *17 alleles.The absence of CYP2C19*2 variant allele frequency found in our study was higher (p < 0.05) in African descent subjects (20.2%) compared with other ethnic groups and with Italian [The  Italian  (11.1%); Italian  13.0%); Italian  (15.9%) .0%; Ital Italian  (22.0%).In the general population, the PM predicted metabolic phenotype frequency  was lower (p < 0.050) than in Japanese  (15.0%).CYP2C19*2 polymorphism have been established in recent studies using clopidogrel. Mega et al (2009) observed that carriers of a reduced-function CYP2C19*2 allele have significantly lower levels of the active metabolite of clopidogrel, diminished platelet inhibition, and a higher rate of major adverse cardiovascular events, including stent thrombosis [The phenotypic implications of the rombosis . Simon erombosis .CYP2C19*17 variant allele, and the UM predicted phenotype, prevalence found was higher in African descent subjects  and lower in Amerindians  compared with other ethnic groups (p = 0.048). Some studies have reported lower frequencies of this variant allele in Chinese (4.0%) [CYP2C19*17 is a recently reported variant causing ultra-rapid metabolism of CYP2C19 substrates. Regarding clopidogrel, Sibbing et al. (2010) observed that patients carrying heterozygous or homozygous genotypes (UM predicted phenotype) had lower ADP-induced platelet aggregation values compared with wild-type. In addition, CYP2C19*17 allele carriage was significantly associated with an increased risk of bleeding [The e (4.0%) , Japanese (4.0%)  and Kores 26.3%; .3% and ls 26.3%; .3% and le (4.0%) . CYP2C19It is interesting that the genetic and functional knowledge of a CYP2C19 enzyme provide enough information to identify patients who will fall outside the therapeutic window of clopidogrel. Thus, it would be possible to justify increases in dosage or a change in therapy. However, it is important to consider that this metabolism has many influences , all of which culminate in variations in the drug action and in the effectiveness of the therapeutic regimen .ABCB1 and CYP2C19 variant allele and predicted metabolic phenotype frequencies in the Brazilian general population plus Amerindians. Recent studies, have reported the clinical importance of these polymorphisms. The results of the present study will be very useful in the development of effective programs in stratifying individuals regarding clopidogrel-predicted metabolic phenotypes.Our findings indicate the existence of interethnic differences in the The authors declare that they have no potential conflicts of interest regarding the present publicationPCJLS carried out the molecular genetic studies, statistical analysis and drafted the manuscript. RAGS and DGBS carried out the molecular genetic studies. ACP participated in the design of the study, statistical analysis and coordinated experiments and manuscript preparation. RMN, GLLMC, JCN, JGM, JEK participated in the design of the study and were responsible for individual selection and characterization. All authors contributed critically to the manuscript, whose present version was read and approved by all.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2350/12/13/prepubCYP2C19*2 and CYP2C19*17 polymorphismsTable S1. Classification of predict metabolic phenotype according to genotype combinations for the . Classification in EM, IM, PM, UM. CYP2C19*2 and CYP2C19*17 polymorphisms according to ethnic groupsTable S2. Distribution of genotype combinations for the . CYP2C19*2 genotypes versus CYP2C19*17 genotypes. Figure S1. Map of Brazil according geographic regions. Studied cities.Figure S2. Map of Brazil according geographic regions showing distribution of variant allele frequencies. Distribution of CYP2C19*2, CYP2C19*17 and ABCB1 polymorphisms.Click here for file