The Bcl-2-associated X protein (Bax) is a proapoptotic member of the Bcl-2 family known to be activated and upregulated during apoptosis. Single nucleotide polymorphisms (SNPs) in Bax promoter may participate in the process of carcinogenesis by altering its own expression and the cancer related genes. Bax-248G>A polymorphism has been implicated to alter the risk of cancer, but the listed results are inconsistent and inconclusive. In the present study, we performed a meta-analysis to systematically summarize the possible association of this polymorphism with the risk of cancer.We conducted a search of case-control studies on the associations of Bax-248G>A polymorphism with susceptibility to cancer in Pub Med, Science Direct, Wiley Online Library and hand search. Data from all eligible studies based on some key search terms, inclusion and exclusion criteria were extracted for this meta-analysis. Hardy-Weinberg equilibrium (HWE) in controls, power calculation, heterogeneity analysis, Begg’s funnel plot, Egger’s linear regression test, forest plot and sensitivity analysis were performed in the present study.Cancer risk associated with Bax-248G>A polymorphism was estimated by pooled odds ratios (ORs) and 95% confidence intervals (95% CIs). The pooled ORs were calculated in allele contrast, homozygous comparison, heterozygous comparison, dominant and recessive model. Statistical significance was checked through Z and p-value in forest plot. A total of seven independent studies including 1772 cases and 1708 controls were included in our meta-analysis. Our results showed that neither allele frequency nor genotype distributions of this polymorphism were associated with risk for cancer in any of the genetic model. Furthermore, Egger’s test did not show any substantial evidence of publication bias.This meta-analysis suggests that the Bax-248G>A polymorphism is not an important cancer risk factor. Nevertheless, additional well-designed studies with larger sample size focusing on different ethnicities and cancer types are required to further validate the results. The specific causes of cancer are not yet known. However, epidemiological studies contribute to suggest the relationship of genetic polymorphism to cancer susceptibility. Genetic association studies with single nucleotide polymorphisms (SNPs) targeting cancer are emerging area of research. SNP can be defined as a genomic locus where two or more alternative bases occur with substantial frequency of greater than 1% . PreviouAn extensive search was performed on Pub Med, Science Direct, Wiley Online Library and hand search with a combination of following search terms: Bax, polymorphism, SNP, mutation and/or cancer up to March, 2013. We evaluated all associated publications to identify the most eligible literature. The selection procedure of this study has been shown in The following criteria were used to select studies for this meta-analysis (a) published in peer reviewed journals, (b) articles about Bax-248GA polymorphism and risk of cancers and (c) articles containing useful allele and genotype frequency. The exclusion criteria were (a) not case-control studies, (b) control population including with cases of cancers, and (c) duplication of a previous publication.Two investigators (SKS and TC) reviewed and extracted the information from all eligible publications independently from each other according to the inclusion and exclusion criteria listed above. The following characteristics were collected from each study: first author’s name, year of publication, country of origin, cancer type, genotyping method for the assessment of Bax-248GA polymorphism, total number of controls and cases with G/G, G/A and A/A genotypes.http://biostat.mc.vanderbilt.edu/twiki/bin/view/Main/PowerSampleSize) which showed that a sample size of nearly 200 controls and cases would provide a power of more than 50%. Genotype and allele frequency were calculated by manual counting. All statistical analysis for the current meta-analysis was performed by comprehensive meta-analysis version 2 software. The association of Bax-248GA polymorphism with cancer was assessed by calculation of odds ratios (ORs) and 95% confidence intervals (CIs) in various models: (i) the allele contrast (A versus G), (ii) homozygous comparison (AA versus GG), (iii) heterozygous comparison (GA versus GG), (iv) dominant model (AA+GA versus GG) and (v) recessive model (AA versus GG+GA) in study I, II, III, IV and V respectively. Also, the Z and p-values were calculated in forest plot . In addition, I2 statistics was used to quantify inter study variability that can be attributed to heterogeneity rather than chance. It ranges between 0% and 100%, where a value of 0% indicates no observed heterogeneity and larger values indicate an increasing degree of heterogeneity . Moderate heterogeneity was observed in most of the models which were included for the analysis . First we assessed Hardy-Weinberg equilibrium (HWE) for each study using SNPalyze software  to identify systematic genotyping errors. A power calculation was carried out a priori using PS: Power and Sample Size Calculation Software .Begg’s funnel plot and Egger’s linear regression tests  were con-248G allele (88.33%) and -248GG genotype (72.04%) in lung cancer patients which were 65.65% and 48.26% respectively for healthy controls. Thus, they have shown the protective role of this polymorphism. Apoptosis is an event that leads to the death of cell without releasing harmful substances into the tissue. In mitochondria mediated apoptotic cell death process Bax acts as an essential gatekeeper as its activation irreversibly commits the most of the cells to die ,41. It hHowever, the results from other groups reported lack of association of this polymorphism and risk of cancer. Starczynski et al. in their study found 23% of CLL and 15% of control with no significant allele frequency between the two groups . SkosberOdds ratios were used to determine the relative odds of the occurrence of the cancer risk with Bax-248GA polymorphism and 95% CI to estimate the precision of the OR. A large CI indicates a low-level of precision of the OR, whereas a small CI indicates a higher precision of the OR. In our results as shown in 2 value. The heterogeneity may be due to various factors, such as diversity in population characteristic, study design, differences in the number of cases and controls, genotype method, etc. Some eligible unpublished publications were not available to include in the present meta-analysis, which might affect the results. Selection bias could have played a role to influence the result because the genotype distribution of this polymorphism deviated from HWE in one study [Heterogeneity was observed among these studies through Ine study . The resTo the best of our knowledge this is the first meta-analysis regarding the comprehensive assessment of the relationship between Bax-248GA polymorphism and the risk of cancer. Our results did not support a genetic association between this polymorphism and susceptibility to cancer corroborates with some of the previous case-control studies –37. NeitFollowing practical recommendations which constitute action points may be consider in future association studies:The lack association in this study of Bax-248GA polymorphism and cancer risk should be replicated with biological functions to better motivate the study and to enable interpretation of results. Histopathological and clinical data can sub classify the type and stage of many cancer cases to get more homogeneous population for analysis.Try to decrease false positive and negative results by conducting the studies in a large sample with stratification by age, sex, food habit, lifestyle and ethnicity.Studies examining the combined effects of different Bax polymorphism or different polymorphisms of Bax related genes (e.g. Bcl2) should be investigated.The role of environmental factors and epistatic interaction are not considered in this study due to lack of information in original published articles which need to explore further to draw more reliable conclusions.This study reveals no significant association of Bax-248GA SNP to cancer risk as evidenced from all genetic models. Moreover, it would be enlightening to extend the investigation to a wider range of human populations including different cancer types which may lead to a better, comprehensive understanding of the association between this polymorphism and susceptibility to cancer. The ability to implement the involvement of this SNP towards cancer etiology and an individual’s chance for developing cancer by considering the proposed recommendation will help in the future. This may further translate into basic research or clinical practice to save the human lives.Checklist S1PRISMA checklist.(DOC)Click here for additional data file.Figure S1A) and funnel plot (B) of Bax-248G>A polymorphism in association with cancers after omission of A.Forest plot  study. In forest plot (A), the squares and horizontal lines correspond to the study specific odds ratios (ORs) and 95% confidence intervals (CI) respectively. The area of the squares reflects the study specific weight (inverse of the variance). The diamond represents the pooled ORs and 95%CI. In funnel plot (B), each point represents a separate study. The OR was plotted on a logarithmic scale against the precision  of each study.(TIF)Click here for additional data file.Figure S2A) and funnel plot (B) of Bax-248G>A polymorphism in association with cancers after omission of J.Forest plot  study. In forest plot (A), the squares and horizontal lines correspond to the study specific odds ratios (ORs) and 95% confidence intervals (CI) respectively. The area of the squares reflects the study specific weight (inverse of the variance). The diamond represents the pooled ORs and 95%CI. In funnel plot (B), each point represents a separate study. The OR was plotted on a logarithmic scale against the precision  of each study.(TIF)Click here for additional data file.Figure S3A) and funnel plot (B) of Bax-248G>A polymorphism in association with cancers after omission of A.Forest plot  study. In forest plot (A), the squares and horizontal lines correspond to the study specific odds ratios (ORs) and 95% confidence intervals (CI) respectively. The area of the squares reflects the study specific weight (inverse of the variance). The diamond represents the pooled ORs and 95%CI. In funnel plot (B), each point represents a separate study. The OR was plotted on a logarithmic scale against the precision  of each study.(TIF)Click here for additional data file.Figure S4A) and funnel plot (B) of Bax-248G>A polymorphism in association with cancers after omission of H.Forest plot  study. In forest plot (A), the squares and horizontal lines correspond to the study specific odds ratios (ORs) and 95% confidence intervals (CI) respectively. The area of the squares reflects the study specific weight (inverse of the variance). The diamond represents the pooled ORs and 95%CI. In funnel plot (B), each point represents a separate study. The OR was plotted on a logarithmic scale against the precision  of each study.(TIF)Click here for additional data file.Figure S5A) and funnel plot (B) of Bax-248G>A polymorphism in association with cancers after omission of K.Forest plot  study. In forest plot (A), the squares and horizontal lines correspond to the study specific odds ratios (ORs) and 95% confidence intervals (CI) respectively. The area of the squares reflects the study specific weight (inverse of the variance). The diamond represents the pooled ORs and 95%CI. In funnel plot (B), each point represents a separate study. The OR was plotted on a logarithmic scale against the precision  of each study.(TIF)Click here for additional data file.Figure S6A) and funnel plot (B) of Bax-248G>A polymorphism in association with cancers after omission of Irina A.Forest plot  study. In forest plot (A), the squares and horizontal lines correspond to the study specific odds ratios (ORs) and 95% confidence intervals (CI) respectively. The area of the squares reflects the study specific weight (inverse of the variance). The diamond represents the pooled ORs and 95%CI. In funnel plot (B), each point represents a separate study. The OR was plotted on a logarithmic scale against the precision  of each study.(TIF)Click here for additional data file.Figure S7A) and funnel plot (B) of Bax-248G>A polymorphism in association with cancers after omission of Yemilha Yildiz et al.Forest plot ((2013) study. In forest plot (A), the squares and horizontal lines correspond to the study specific odds ratios (ORs) and 95% confidence intervals (CI) respectively. The area of the squares reflects the study specific weight (inverse of the variance). The diamond represents the pooled ORs and 95%CI. In funnel plot (B), each point represents a separate study. The OR was plotted on a logarithmic scale against the precision  of each study.(TIF)Click here for additional data file.


MTRR) and methylenetetrahydrofolate reductase (MTHFR) are two of the key regulatory enzymes involved in the metabolic pathway of homocysteine. Genes involved in homocysteine/folate metabolism may play an important role in CHDs. In this study; we determined the association of A66G and C524T polymorphisms of the MTRR gene and C677T polymorphism of the MTHFR gene in Iranian VSD subjects. A total of 123 children with VSDs and 125 healthy children were included in this study. Genomic DNA was extracted from the buccal cells of all the subjects. The restriction fragment length polymorphism polymerase chain reaction (PCR-RFLP) method was carried out to amplify the A66G and C524T polymorphism of MTRR and C677T polymorphism of MTHFR genes digested with Hinf1, Xho1 and Nde1 enzymes, respectively. The genotype frequencies of CC, CT and TT of MTRR gene among the studied cases were 43.1%, 40.7% and 16.3%, respectively, compared to 52.8%, 43.2% and 4.0%, respectively among the controls. For the MTRR A66G gene polymorphism, the genotypes frequencies of AA, AG and GG among the cases were 33.3%, 43.9% and 22.8%, respectively, while the frequencies were 49.6%, 42.4% and 8.0%, respectively, among control subjects. The frequencies for CC and CT genotypes of the MTHFR gene were 51.2% and 48.8%, respectively, in VSD patients compared to 56.8% and 43.2% respectively, in control subjects. Apart from MTHFR C677T polymorphism, significant differences were noticed (p < 0.05) in C524T and A66G polymorphisms of the MTRR gene between cases and control subjects.Ventricular septal defect (VSD) is one of the most common types of congenital heart defects (CHD). There are vivid multifactorial causes for VSD in which both genetic and environmental risk factors are consequential in the development of CHD. Methionine synthase reductase ( Congenital heart disease (CHD) is one of the most commonly occurring noninfectious diseases and birth defects among children. CHD is a condition whereby there is a malformation in the cardiovascular system whilst the child is still at an embryo stage . The freC677T polymorphism of methylene tetrahydrofolate reductase (MTHFR), a thermolabile variant with reduced activity, and has been associated with elevated plasma homocysteine concentrations, especially when there is insufficient folate [Ventricular septal defect (VSD) is the most common form of CHD occurring in children at a range of 1.56 to 53.2 per 1000 live births . In spitt folate ,9.MTRR) is one of the main regulatory enzymes in the homocysteine metabolic pathway. This flavoprotein has an important role in maintaining sufficient levels of activated cobalamin, which acts as a carrier for methyl during the remethylation of homocysteine to methionine. Therefore, a lack of this enzyme may cause hyperhomocysteinemia. Wilson et al. found an MTRR gene polymorphism that is a “missense” mutation (A66G), which leads to an isoleucine being substituted by a methionine residue at codon 22 [MTRR polymorphism is one of the causes of alterations in either plasma Hcy levels and/or vascular disease [Methionine synthase reductase  subjects in many populations [MTHFR and MTRR gene polymorphisms, and CAD has been reported in Asian population. In this study we examined the association of three SNPs; a common MTHFR gene polymorphisms C677T (rs1801133), and two MTRR gene polymorphisms A66G (rs1801394) and C524T (rs1532268) in Iranian VSD subjects. Homozygosity (TT) for this MTHFR single nuclear polymorphism is associated with higher homocysteine levels and lower serum folate concentrations [MTHFR and CHD, several studies with conflicting outcomes have been published [MTHFR acting as a risk factor for the development of CHD.Methionine synthase is critical for homocysteine metabolism, and methionine synthase reductase is required to maintain methionine synthase in an active state. Both enzymes are associated with frequent polymorphisms that alter the primary structure of the proteins, and both have been subject to extensive analysis of metabolite and disease associations. Studies have suggested that the ulations ,12,27. Ttrations ,29, thantrations ,31, alth524T rs15268 in IrT rs18011, and twoublished –39, lateC677T polymorphism of the MTHFR gene and A66G and C524T polymorphisms of the MTRR gene among Iranian VSD subjects. This study was designed to compare the genotypes and allele frequencies of polymorphisms between cases and controls. Case control studies are the most common method used for testing associations of genetic polymorphisms with traits [To the best of our knowledge, this is the first study to examine the association of h traits . In addip < 0.05).The percentage of males and females among the VSD cases was 46.3% and 53.7% respectively, whereas the percentage of males and females among the control subjects was 44.8% and 55.2%, respectively, in this study. The mean age of case subjects was 4.51 ± 2.39 whereas the mean age of controls was 5.43 ± 0.51. There was a significant difference of mean group of age between cases and controls  and (p > 0.05), respectively. The percentage of CC and CT genotypes among cases was 51.2% and 48.8%, respectively, compared to 56.8% and 43.2%, respectively among control subjects. The derived allele frequencies of C and T alleles were 75.6% and 24.4%, respectively, among cases and 78.4% and 21.6%, respectively, among controls.Genotypes of Lane M illustrates the 100bp DNA ladder. Lanes 1 and 2 show the PCR products (198bp), Lanes 3 and 4 show the heterozygote fragments (198 and 1475 bp), Lanes 5 and 6 shows the wild type fragment (198 bp) and Lane N represents the negative test control.C677T polymorphism of MTHFR were compared between cases and controls. There were no significant differences between genotype and allele frequencies of C677T polymorphism among cases and controls (p > 0.05). The percentage of CC and CT genotypes among cases was 51.2% and 48.8%, respectively, compared to 56.8% and 43.2%, respectively, among control subjects. The derived allele frequencies of C and T alleles were 75.6% and 24.4%, respectively, among cases and 78.4% and 21.6%, respectively, among controls. As there was no TT genotype in cases and controls, we failed to show an association between MTHFR C677T gene polymorphism and the occurrence of VSD. The results obtained from a study done by Zhu et al. on a Chinese population suggested that the MTHFR C677T locus variation is associated with the occurrence of atrial septal defect (ASD) and patent ductus arteriosus (PDA), and carriers of mutant homozygote TT and allele T had a high risk of these two types of CHDs [et al. studied the relationship of MTHFR C677T gene polymorphism with CHDs, and the results showed that TT homozygoty was significantly related to congenital heart structure teratogenesis, especially with pulmonary artery stenosis, left heart dysplasia syndrome and coarctation of aorta [MTHFR gene polymorphism, which is in consistence to our study but in contrast to the findings of Bennouar et al. in a Moroccan population [Genotype and allele frequencies of  of CHDs . Junker of aorta . Subsequof aorta –39 failepulation .C524T polymorphism of MTRR, the amplified PCR product . Derived allele frequencies of C allele and T allele were 63.4% and 36.6% among cases and 74.4% and 25.6% among controls. There was a significant difference between the allele frequency among cases and controls (p < 0.05). For the A66G polymorphism of MTRR, the genotype and frequencies differed significantly between cases and controls (p < 0.05). The genotypes of A66A, A66G and G66G were 33.3%, 43.9%, and 22.8%, respectively, in cases compared to 49.6%, 42.4% and 8%, respectively, among control subjects. The allele frequencies as shown in p < 0.05). C677T genotype frequencies were in agreement with those predicted by the Hardy Weinberg distribution, whereas, MTRR gene polymorphisms did not meet the Hardy Weinberg assumption in neither cases nor controls.For ectively . There wMTRR is a central regulatory enzyme in the metabolic pathway of homocysteine/folate. The malfunction of this enzyme has been considered as a modifiable risk factor for heart and vascular disease [A66G and C524T polymorphisms of MTRR gene between cases and controls (p < 0.05), which is in accordance with some studies [A66G and C524T alleles of the MTRR gene and CHDs in the Iranian subjects. In contrast, a difference in homocysteine concentration between the 66 MTRR genotypes in CAD and ischemic cerebrovascular disease was not detected in some studies [MTHFR and MTRR genes in Iranian subjects. It is important to consider the need for future studies of folate-pathway genes other than those found in the current study, and it is also potentially complex to study the gene-gene and gene-environment interactions and VSD in the Iranian population. disease . In this studies –47. We f studies ,16. The For further confirmation, random samples were selected and repeated with the same PCR conditions to confirm the genotyping results. Those samples were purified and DNA sequencing was performed with the Applied Biosystems 3730xl DNA Sequencer provided by Medigene Sdn. Bhd, Selangor, Malaysia.MTHFR and MTRR gene polymorphisms among Iranian VSD patients as compared to control subjects. However, we failed to analyze the MTHFR and MTRR mRNA levels in both VSD patients and control subjects. Apart from the MTHFR and MTRR gene polymorphisms other polymorphisms such as TBX5, NKX2.5 and GATA4 need to be analyzed to determine the association of the other candidate genes with VSD and other defects. Replication studies with a larger number of samples and assessing the genotypic and allelic frequencies of mothers are also needed in order to understand the etiological factors.In this study, a number of limitations have to be considered. The present study has provided only a genetic association for Ethical approval was obtained from the Shaheed Beheshti University of Medical Sciences and also from the Faculty of Medicine and Health Sciences, Universiti Putra Malaysia. A written informed consent was obtained from the parents of the children with CHD. Similarly, consent forms were obtained from all of the control subjects enrolled in this study.A total of 150 pediatric patients were approached, and 123 pediatric patients were recruited as the other subjects were excluded due to the inconsistent results and extreme values. All the patients were recruited from the pediatric infectious research center (PIRC), Mofid children hospital, Tehran, Iran. All the subjects were visited during July 2010 to Jun 2011 in the hospital from the different parts of the districts. The diagnosis of non-syndromic CHD and classification of the type of the cardiac defect had been done by a pediatric cardiologist based on the clinical and echocardiography findings with or without the diagnostic cardiac catheterization findings and surgical notes. Whereas for the control subjects, a total of 125 healthy control subjects with no history of congenital heart disease were recruited in for this study.Buccal cell samples were collected on a sterile cytobrush  Genomic DNA extraction was carried out using the DNA isolation kit . The purity of extracted DNA was quantified using Eppendorf UVette® in Biophotometer .MTHFR and MTRR genes, genomic DNA was amplified first by the respective primers using the polymerase chain reaction (PCR) technique. The PCR amplification for all the respective polymorphisms was performed in a total volume of a 25 μL reaction mixture consisting of 10 pmol of each primer and the Mastermix (i-DNA Biotechnology (M) Sdn Bhd, Kuchai lama, Kuala Lumpur, Malaysia) and the template DNA. A negative control containing no genomic DNA and a positive control of known genotype were always included in the set of reactions. All the PCR cycling conditions were carried out on an iCycler machine . The amplified PCR products for all the three gene polymorphisms were separated at 2%–4% agarose gel . The agarose gel was stained in ethidium bromide and visualized using Alpha Imager . The PCR products of the respective genes were digested with 2–4 units of the respective restriction enzymes  with 10× Fast Digest Green Buffer in a final volume of 30 μL reaction mixture. To determine the genotypes of Purified PCR products were sent to Research Biolabs Malaysia to confirm the nucleotide sequence. The sequencing results were aligned with the respective reference gene sequence from the NCBI-GeneBank sequences using the sequence alignment MEGA4 software .p < 0.05 considered in all tests to be statistically significant.Data analysis was done by SPSS version 18.00 . Alleles and genotype distribution were tested for deviation from the Hardy-Weinberg by a Chi Square test. The odds ratio (OR) and its 95% confidence intervals (CI) were used to illustrate the association, with MTHFR gene and VSD subjects. However, the MTRR gene polymorphisms (C524T and A66G) can be considered as risk factors for the development for VSD in Iranian subjects.This study failed to show an association between the


Mounting evidence has suggested that α-adducin and G-protein β3 (GNB3) genes are logical candidates for salt-sensitive hypertension. Some, but not all, studies have reported that α-adducin G460T and GNB3 C825T polymorphisms may influence the risk of the disease. To comprehensively address this issue, we performed a meta-analysis to evaluate the influence of these two polymorphisms on hypertension and potential biases in Chinese.Data were analyzed using Stata (v11.0) and random-effects model was applied irrespective of between-studies heterogeneity, which was evaluated via subgroup and meta-regression analyses. Study quality was assessed in duplicate. Publication bias was weighed using Egger's test and funnel plot.I2>25%). Subgroup analyses by study design indicated that the magnitude of association in population-based studies was marginally significantly strengthened for α-adducin G460T allelic model . Moreover, subgroup analyses by geographic distribution indicated comparison of 825T with 825C yielded a marginally significant increased risk in southern Chinese only . Further meta-regression analyses showed that geographic regions were a significant source of between-study heterogeneity for both polymorphisms. There was a possibility of publication bias for G460T, but not for C825T.36 study populations totaling 9042 hypertensive patients and 8399 controls were finally identified. Overall, in allelic/genotypic/dominant/recessive models, no significant association was identified for both G460T and C825T polymorphisms (P>0.05) and there was possible heterogeneity (Our overall results suggest null association of α-adducin G460T and GNB3 C825T polymorphisms with hypertension in Chinese but indicate local marginal significance of C825T, as a putative salt-sensitive switch, in southern Chinese. A strong genetic underpinning presents in hypertension: premature onset of hypertension among first-degree relatives yielded a remarkable high risk of 3.8 times to develop hypertension Adducin exerts modulatory effects on the actin cytoskeleton dynamics and clathrin-dependent endocytosis G-protein β3 (GNB3) subunit plays a vital role in intracellular signal transduction As the genomic sequences of α-adducin and GNB3 genes are highly polymorphic, it is of added interest to identify which polymorphism(s) in these genes might have functional potentials of affecting their bioavailability. Two exonic polymorphisms G460T in α-adducin gene and C825T in GNB3 gene have become a focus of researches and are suggestively associated with hypertension, although this claim is controversial. Generally, inadequate inclusion of hypertensive patients and controls as well as genetic background noise might account for this controversy.To generate more information, we restricted our research to Chinese populations and conducted a comprehensive meta-analysis to ascertain whether there was indeed an association of G460T and C825T polymorphisms with hypertension and whether study design and geographic distribution of study populations were potential biases and sources of heterogeneity between studies.viz. PubMed and Excerpta Medica Database (EMBASE), as well as two Chinese searching engines, viz. Wanfang database (http://www.wanfangdata.com.cn) and China Biological Medicine (CBM) (http://cbm.imicams.ac.cn) with the last update as of September 20, 2010. As a prerequisite, only those published in English and Chinese languages and performed in Chinese populations were identified. In addition, reference lists of all retrieved publications were checked for the missing information. If two or more studies shared the same patients or control subjects, the one with large sample size was selected. If more than one geographical or ethnic populations were included in one report, each population was considered separately.We collected information via two international searching engines, Studies that we identified satisfied the following criteria: (i) evaluation of the α-adducin gene G460T or GNB3 gene C825T polymorphisms in association with hypertension; (ii) case-control study using either a hospital-based or a population-based design; (iii) sufficient information on G460T and C825T genotype counts between hypertensive patients and controls for estimating odds ratio (OR) and its corresponding 95% confidence interval (CI). Hypertension was defined as systolic BP equal to or above 140 mmHg or diastolic BP equal to or above 90 mmHg or treatment with antihypertensive medication. Studies evaluating secondary hypertension or other types of monogenic hypertension were excluded.Two authors (W. Niu and Y. Qi) independently drew the following information from all qualified studies: first author's last name, publication date, population ethnicity, study design, baseline characteristics of the study population, and the genotype distribution in patients and controls. Any encountered discrepancies were adjudicated by a discussion until a consensus was reached. For consistency, continuous variables e.g. age expressed as mean ± standard error (SE) were converted to mean ± standard deviation (SD).2-based probability is less than 0.05.Pooled allelic/genotypic association of α-adducin gene G460T and GNB3 gene C825T polymorphisms with hypertension was performed using the Stata/SE 11.0 for Windows. In this meta-analysis, we implemented the random-effects model using the method of DerSimonian & Laird, instead of fixed-effects model, to bring the individual effect-size estimates together, and the estimate of heterogeneity was taken from the Mantel-Haenszel model I2 statistic, which was documented for the percentage of the observed between-study variability due to heterogeneity rather than chance with the ranges of 0 to 100%  Heterogeneity was assessed by the In addition, to look at more narrowly drawn subsets of the studies such as different study designs and areas, separate analyses were undertaken in a sensitivity way. Furthermore, to estimate the extent to which one or more covariates explain heterogeneity, meta-regression, as an extension to random-effects meta-analysis, was employed. The meta-regression model relates the treatment effect to the study-level covariates, assuming a normal distribution for the residual errors with both a within-study and an additive between-studies component of variance.Finally, publication bias was assessed using the Egger regression asymmetry test. The Egger's test detects funnel plot asymmetry by determining whether the intercept deviates significantly from zero in a regression of the standardized effect estimates against their precision.As for α-adducin gene G460T, we identified 23 eligible reports published both in Chinese (n = 20) and English (n = 4), which met our inclusion/exclusion criteria, whereas due to the shared study groups, we removed five of them with the fewer sample sizes. Finally, there were 18 qualified studies (18 populations) totaling 4676 hypertension patients and 4482 controls. Basic characteristics of the study populations are presented in Regarding GNB3 gene C825T, a total of 29 reports were identified, and 11 of them were excluded for the following reasons: five papers with shared study subjects, four review articles, one with only hypertensive patients, and one conducted in Japanese subjects. Of the remaining 18 qualified reports (20 populations), 3 were published in English and 15 in Chinese. Basic characteristics of the study populations are presented in Distribution of the population sources for all studies was shown in I2 statistic indicated the large between-study heterogeneity for all comparisons except for that of 460GT with 460GG (I2 = 2.7%).As for α-adducin gene G460T, in allelic model, comparison of 460T with 460G allele generated a nonsignificant 5% increased hypertension risk (P = 0.34) . No signI2 statistic except for the dominant model (I2 = 31.6%).With regard to GNB3 gene C825T, in allelic model, comparison of 825T with 825C allele yielded a nonsignificant 2% increased risk (P = 0.56) . SimilarMoreover, since most of studies were conducted in Han Chinese, after restricting analyses to Han populations, there was no material changes in ORs for both polymorphisms under study (data not shown).Considering the fact that study design and the geographic difference might bias the overall association, we conducted separate analyses according to these factors. In view of study design, the magnitude of association in population-based studies was marginally significantly strengthened for α-adducin gene G460T allelic model  , but weaChina has a vast territory, and geographic differences cause various characters as a result of historical and cultural impact. We thus demarcate China into north and south by the Qinling Mountains of China's Huaihe River. In allelic model, as for G460T, there was no material difference between northern and southern Chinese , whereasIn case of genotypic, dominant and recessive models, there were no material changes in prediction of these two polymorphisms for hypertension according to study design and the geographic difference (data not shown).viz. model 1 regressing study design, geographic region, and the differences of age, gender and body mass index (BMI) between cases and controls; model 2 regressing study design, geographic region, and the average of age, gender and BMI of both groups  and BMI  were a marginally significant source of between-study heterogeneity in model 1 and no heterogeneity was identified in model 2. In contrast, for C825T, meta-regression suggested that geographic region could increase the risk of hypertension in southern Chinese compared with northern ones in both model 1  and model 2 .As reflected by the Egger's test and funnel plot , there wVia a comprehensive meta-analysis with 36 study populations totaling 17441 subjects, we assessed association of α-adducin gene G460T and GNB3 gene C825T polymorphisms with hypertension in Chinese and we failed to detect the overall positive signals for these two polymorphisms. Compared with the large volumes of evidence implicating their biological involvement in BP regulation, some, but not all, studies have positively ascertained the relationship between these polymorphisms and human hypertension More recently, a larger meta-analysis involving 22 worldwide studies by Liu et al failed to observe any signs of significance for association of α-adducin gene G460T polymorphism with hypertension It is generally believed that except a climatically different environment between northern and southern China, dietary habits especially salt consumption make a great difference In addition, a recent report by Kelly et al in Han Chinese suggested a role for the α-adducin gene and GNB3 gene in blood pressure salt sensitivity Despite the clear strength of our study including large sample sizes, some limitations merit serious consideration. First, all included studies had the cross-sectional design, which precludes further comments on cause-effect relationship Taken together, our overall associations suggested null association of α-adducin G460T and GNB3 C825T polymorphisms with hypertension in Chinese, whereas we locally indentified marginal significance for C825T, as a putative salt-sensitive switch, in southern Chinese. Although further analyses are warranted to investigate α-adducin gene and GNB3 gene adjacent markers in a wider context, future studies on GNB3 and hypertension should concentrate on gene-environment interactions, particularly on the influence of 825T variant on hypertension or blood pressure in populations with different salt intake habits.Table S1The baseline characteristics of all qualified studies for α-adducin gene G460T polymorphism in this meta-analysis.(DOC)Click here for additional data file.Table S2The baseline characteristics of all qualified studies for GNB3 gene C825T polymorphism in this meta-analysis.(DOC)Click here for additional data file.


Prestige accident  the most recent. Taking into account the consistent large number of individuals exposed to oil that exists all over the world, it seems surprising the absence in the literature of studies focused on the chronic effects of this exposure on human health. In this work we evaluated the level of DNA damage by means of comet assay, and the potential endocrine alterations (prolactin and cortisol) caused by Prestige oil exposure in a population of 180 individuals, classified in 3 groups according to the tasks performed, and 60 controls. Heavy metals in blood were determined as exposure biomarkers, obtaining significant increases of aluminum, nickel and lead in the exposed groups as compared to controls. Higher levels of genetic damage and endocrine alterations were also observed in the exposed population. DNA damage levels were influenced by age, sex, and the use of protective clothes, and prolactin concentrations by the last two factors. Surprisingly, the use of mask did not seem to protect individuals from genetic or endocrine alterations. Moreover, polymorphisms in genes encoding for the main enzymes involved in the metabolism of oil components were analyzed as susceptibility biomarkers. CYP1A1-3′UTR and EPHX1 codons 113 and 139 variant alleles were related to higher damage levels, while lower DNA damage was observed in GSTM1 and GSTT1 null individuals.Since 1960, about 400 tankers spilled more than 377765 tons of oil, with the  Taking into account the large number of oil spills occurred all around the world, it seems surprising the absence in the international literature of consistent studies dealing with the possible long term effects that oil exposure can cause in humans. Since 1960, 410 tankers spilled more than 377765 tons of oil , with thPrestige oil spill in order to try to alleviate the catastrophic consequences caused in the environment. This fact positioned these people as integrants of an exposed population probably affected by the oil. The Spanish National Research Council determined the composition of Prestige oil as 50% aromatic hydrocarbons, 22% saturated hydrocarbons and 28% resins and asphalthene  exposed only for 5 days, and hired staff who worked either manually for 4 months (MW) or using high-pressure cleaning machines for 3 months (HPW). Comet assay was employed as an indicator of the genotoxic effects, and plasmatic levels of prolactin and cortisol were determined to evaluate the potential alterations in the endocrine status. Complementarily, several genetic polymorphisms in the enzymes involved in the metabolism of VOC and PAH contained in the oil  were analyzed in order to evaluate their influence on DNA damage levels and endocrine toxicity.Three different groups of exposed individuals were examined, 61 volunteers (V) involved in the manual collection of oil in March 2003 during 5 days for 4 h/day, 59 hired workers (MW) that collected oil from December 2002 to April 2003 for 6.5 h/day, and 60 hired workers who employed high-pressure machines (HPW) to clean rocks from February to May 2003 for 6.5 h/day. In the exposed population 38.3% were males, 37.8% smokers (8.81 ± 10.99 packs-year), and the mean age was 32.26 ±11.68 years. Protective devices used included clothes  and cellulose mask, although some individuals did not wear them (18.3% for clothes and 6.7% for mask). Sixty non-exposed individuals were included as control group; 51.1% were males, 31.7% were smokers (3.92 ±4.64 packs-year), and the mean age was 23.31 ± 4.89 years. An informed consent was signed and a detailed questionnaire on lifestyle and consumption habits was filled in by each individual included in the study. This study was performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki.™ CPT™ for leukocyte isolation for the comet assay. All samples were codified and refrigerated until arrival to the laboratory, where they were processed according to each established protocol.Samples were collected between March and May 2003. Peripheral blood was drawn early in the morning before the working shift by venipuncture in three types of tubes, one containing lithium heparine for determining blood concentrations of heavy metals, EDTA containers for DNA extraction and genotyping, and special BD VacutainerIn order to determine heavy metal intake, blood concentrations of aluminum, cadmium, nickel, lead and zinc were analyzed by graphite furnace atomic absorption spectrophotometry (GFAAS) after microwave digestion . AccuracMononuclear leukocyte isolation was made using BD Vacutainer™ CPT™ Cell Preparation Tubes (Becton Dickinson) following manufacturer’s instructions. Cells were resuspended in freezing medium  and stored at −80 ºC in a Nalgene® Cryo 1 ºC Freezing Container  until their use.Leukocytes were thawed at 37 ºC and their viability was checked with trypan blue, being always ≥85%. Alkaline comet assay was performed basically as described by Specific radioimmunoassays (RIA) were used to determine plasmatic prolactin and cortisol levels using two commercial kits, previously tested: Prolactin IRMA DSL-4500 and Cortisol RIA DSL-2000  following manufacturer’s recommendations. The intraassay coefficients of variation were 7.4% and 4.3% for prolactin and cortisol, respectively. All samples were measured in the same assay to avoid interassay variations. Sensitivities of the assays were 0.1 ng/ml for prolactin and 0.11 μg/dl for cortisol.DNA was extracted from 300 μl of whole peripheral blood using Puregene™ DNA isolation kit . Genetic polymorphisms consisting in single nucleotide changes were evaluated by means of PCR-RFLP techniques following Analysis of Variance (ANOVA) and Tukey’s test were used to evaluate the existence of differences among groups. The contribution of exposure and potential confounding factors  to the genotoxic and endocrine response variables considered was assessed by means of multifactorial ANOVA analysis. The associations between two variables were analyzed by Pearson’s correlation. The level of statistical significance was set at 0.05, and all analyses were performed using the SPSS for Windows statistical package, version 14.0 .P < 0.01) was obtained.Exposure levels were measured by determining blood concentrations of aluminum, cadmium, nickel, lead and zinc. Results obtained adjusted by sex, age and smoking habits are gathered in The contribution of exposure and potential confounding factors to the genotoxic and endocrine response variables considered was assessed by means of multifactorial ANOVA analysis.P values); both of them remained significant when they were mutually adjusted, i.e. introduced together in the same model . Furthermore, there was a significant correlation between %TDNA and age . Significant effect of sex on prolactin concentrations (P = 0.017) was also obtained, but no effect was observed on cortisol levels. Although smoking did not influence any response variable evaluated, smokers presented DNA damage levels significantly higher than non-smokers in V group  but significantly lower in MW group . With regard to the effect of wearing protective devices during cleaning labors, significantly increased DNA damage and prolactin levels  were associated with the absence of using clothes, while no influence of wearing mask on any parameter was observed.The analysis of the influence of sex, age and smoking habits on DNA damage and endocrine parameters is summarized in We analyzed the possible influence of some important polymorphisms in genes involved in the biotransformation pathways of oil components on the DNA damage and hormone levels. After confirming that CYP1A1, EPHX1 and GSTP1 studied polymorphisms were in Hardy-Weinberg equilibrium, individuals were grouped depending on the most suitable heredity model for each gene according to the results , since no data were available in the literature, excepting for EPHX1 .*2A variant allele were obtained. With respect to the effect of EPHX1 polymorphisms, results displayed a statistically significant increase in DNA damage related to the presence of the codon 113 variant allele in individuals from control, MW and HPW groups; nevertheless for V the effect was the opposite. Data from the analysis of EPHX1 codon 139 polymorphism showed a decrease of %TDNA in control individuals carrying the variant allele, while in V and MW this value was increased. Presence of GSTP1 codon 105 variant allele was associated with a decrease of the strand breaks level in V group, exerting the inverse effect in total exposed population and HPW. GSTM1 null individuals generally showed decreased levels of DNA damage with regard to the positive ones, reaching statistical significance in total exposed and MW groups. Similarly, GSTT1 null MW and HPW individuals presented significantly lower rates of DNA strand breaks than positive subjects.*2A allele, and increases in cortisol levels in control individuals carrying the variant GSTP1-105Val allele and in GSTT1 null V subjects.Genetic polymorphisms analyzed seemed not to significantly influence plasmatic hormone levels, excepting for decreases in prolactin concentrations both in controls and exposed carrying the CYP1A1Prestige oil spill was almost exclusively related to the environmental effects on the flora and fauna, the scarce works dealing with human health were just set in the framework of acute effects of the exposure  than in the controls (10.96 ± 0.96 vs. 11.86 ± 1.02), pointing to a sex influence related to the exposure that could determine a higher susceptibility of females to the effects of oil exposure on prolactin secretion. On the other hand, no effect of sex on cortisol concentrations was observed.Sex is a very influential factor on cytogenetic genotoxicity tests , but itsOur results showed a direct relationship between age and %TDNA, agreeing with the fact that age has been widely related to increases in the background damage levels, losses in the efficacy of the repair mechanisms and the subsequent damage accumulation. The decrease of the defense mechanisms against toxicity related to age was found to be associated with the generation of reactive oxygen species and the decrease of agents participating in the detoxification processes as glutathione . StudiesTobacco smoke is especially associated with the exposure evaluated in this work due to the great number of highly toxic component substances that share with oil . Tobacco consumption did not influence comet assay results; however smoking was related to increase in genetic damage in V group but decrease in MW chronically exposed group. Protective devices used by the exposed individuals included waterproof clothes and cellulose mask, aimed at avoiding dermal and respiratory exposure, respectively. Clothes seemed to protect against increase in DNA damage and plasmatic prolactin levels, but surprisingly wearing mask did not influence genetic or endocrine parameters. Thus, it seems that inhalant exposure risk would seem to have been minimal compared to dermal. In contrast, use of mask determined a significant decrease in DNA damage levels (comet assay) in individuals engaged in the cleaning and autopsies of Prestige oil contaminated birds . The inaNowadays, the existence of polymorphisms in several genes involved in metabolic pathways are widely described and considered key in epidemiological studies due to their repercussions on the activation/detoxification processes and consequently on damage induction. Therefore an important part of this work dealt with the analysis of the influence of the main metabolic polymorphic variants on the effect biomarkers evaluated.Cytochrome P450 (CYP) enzymes are considered the first defense against lipophilic compounds. Specifically, CYP1A1 catalyzes the formation of mutagenic intermediaries of many PAH . One of Two EPHX1 polymorphisms affecting the activity of the resulting microsomal epoxide-hydrolase enzyme and established as risk factors against several exposures were studied. Codon 113 polymorphism was reported to decrease enzyme activity  and resuEPHX1 codon 139 polymorphism increases epoxide-hydrolase activity . This poS-transferases (GST) is not a priority pathway in liver, it acquires greater importance in other tissues where epoxide-hydrolase activity is low  were also observed in the exposed population. DNA damage levels were influenced by age, sex, and the use of protective clothes, and prolactin concentrations by the last two factors. Surprisingly, the use of mask did not seem to protect individuals from genetic or endocrine alterations. Regarding to susceptibility biomarkers, CYP1A1-3′URT and EPHX1 codons 113 and 139 variant alleles were related to higher damage levels, while absence of GSTM1 and GSTT1 activities gave rise to lower DNA damage. In view of all the results obtained, it ought to be highlighted the need for developing this kind of studies after oil spills, on one hand to increase the knowledge on the effect of the exposure on human health, as they are more frequent than expected, and on the other hand to define the factors to be taken into account when designing an action protocol before such catastrophes, in order to try to minimize the risk for the individuals.


We describe the areas of application that multivariate meta-analysis has found, the methods available, the difficulties typically encountered and the arguments for and against the multivariate methods, using four representative but contrasting examples. We conclude that the multivariate methods can be useful, and in particular can provide estimates with better statistical properties, but also that these benefits come at the price of making more assumptions which do not result in better inference in every case. Although there is evidence that multivariate meta-analysis has considerable potential, it must be even more carefully applied than its univariate counterpart in practice. Copyright © 2011 John Wiley & Sons, Ltd.The multivariate random effects model is a generalization of the standard univariate model. Multivariate meta-analysis is becoming more commonly used and the techniques and related computer software, although continually under development, are now in place. In order to raise awareness of the multivariate methods, and discuss their advantages and disadvantages, we organized a one day ‘Multivariate meta-analysis’ event at the Royal Statistical Society. In addition to disseminating the most recent developments, we also received an abundance of comments, concerns, insights, critiques and encouragement. This article provides a balanced account of the day's discourse. By giving others the opportunity to respond to our assessment, we hope to ensure that the various view points and opinions are aired before multivariate meta-analysis simply becomes another widely used  British Medical Journal in 1994 Now that meta-analysis is well established in medical statistics, it is perhaps easy to forget that, until relatively recently, its use has been considered controversial by the medical community The general problem is therefore to make inferences about correlated study effects, where each study estimates one or more of them and ideally provides the corresponding within-study covariance matrix. Not all studies may provide estimates of all effects of interest, so it is vitally important to handle missing data in a suitable way. We will describe the precise form of the multivariate random effects model in Section 3, and methods for fitting it in Section 4, but until then it is essential that the reader keeps the general problem firmly in mind. For a detailed account of the univariate methods that are extended here, see Normand's tutorial The variation in the studies' effects is separated into two components by the random effects model. The within-study variation refers to the variation in the repeated sampling of the studies' results if they were replicated, and the between-study variation refers to any variation in the studies' true underlying effects. Hence, we have both within- and between-study correlations in the multivariate random effects model. Within-study correlation occurs because different effects are calculated using the same set of patients. For example, if the effects of interest relate to desirable outcomes such as overall and disease-free survival status, then they will almost necessarily be positively correlated.The between-study correlation allows the true underlying outcome effects to be correlated and hence the studies' effects to be more or less correlated than we would expect from the within-study variation alone. An obvious situation where the between-study correlation is important is the meta-analysis of diagnostic test accuracy. Here, within studies, the sensitivities and specificities are assumed to be independent because they are calculated using data from different individuals. Despite this, a negative correlation between these quantities across studies is likely We assume that a ‘two-stage’ approach to analysis is adopted. At the first stage,  analyses of each trial are performed, and estimates of parameters of interest are obtained; for example, in a survival study, the estimated hazard ratios of overall and disease-free survival. The within-study covariance matrices are also obtained at this stage, containing the variance of each effect and their covariances. These estimates are then combined at the second phase. If the estimates are obtained from published papers, as is typically the case, then a two-stage approach is necessary but if individual patient data (IPD) are available a one-stage approach is possible and may be preferable. One-stage methods for IPD random effects meta-analyses have been suggested for continuous Statistics in Medicine less than a decade later than Eysenck's article. This tutorial mainly focussed on the bivariate case where the outcome pairs are arm-specific measures. Hence, conditional on the study-specific true underlying measures, all effects are assumed to be independent. Although this special case is useful in some settings, applications have been found where this assumption is clearly implausible. More recently, investigations have examined the effect of misspecifying the within-study correlations Considerable progress has recently been made in the development of multivariate meta-analysis and a tutorial paper per se should have been as recently as 1997.In order to raise awareness of the recent methodological developments, and the applications that motivated them, the authors of this article organized a one day ‘Multivariate Meta-Analysis’ event on 26th January 2010 at the Royal Statistical Society (RSS). The authors initially presented the theory, and the applications followed.  This meeting resulted in considerable enthusiasm and encouragement but concerns and issues were also raised and we felt it timely to provide a balanced account of the discourse of the meeting. Riley In this article we proceed as follows. In Section 2 we describe the areas of application that motivated multivariate methods. In Section 3 we discuss the multivariate random effects model and its assumptions. In Section 4 we describe the estimation methods that have been developed. In Section 5 we apply the methods to our example data sets and discuss the advantages and limitations of the multivariate methods in relation to these. In Section 6 we tackle perhaps the greatest practical difficulty: handling the (frequently unknown) within-study correlations. We conclude our article with a discussion, which is followed with invited commentaries from some of those present at the RSS meeting and others with an interest in meta-analysis.The need for multivariate meta-analysis methodology has been driven by a variety of applications and in this section we describe some of these. In addition to the areas of medicine represented by our examples, applications have included education Perhaps the most common medical application of multivariate meta-analysis is the bivariate meta-analysis of studies of diagnostic test accuracy et al.This use of the bivariate random effects model for meta-analysis is perhaps especially appealing due to the pioneering work of Harbord et al.Our first example data set is a meta-analysis of prognostic test studies and is taken from Kertai In any context where clinical trials or observational studies report more than a single outcome of interest, multivariate meta-analysis may be used. This presents an additional challenge not present in diagnostic testing because the within-study correlations must also be available. Despite this, multivariate meta-analysis has been successfully applied in this setting Our second and third examples are of this kind. A representative selection of the studies' results from the second example are shown in Y1 denotes the log hazard ratio for disease-free survival and Y2 denotes the log hazard ratio for overall survival. Only 3 studies provide estimates for disease-free survival. The within-study correlations are again unknown to the authors but are expected to be highly positively correlated.Our third example The multivariate methods lend themselves to the meta-analysis of observational IPD. Here, we wish to pool information across studies for exposure parameters that represent effects of particular interest. Typically, we include more covariates in our within-study models that we wish to adjust inferences for.Our fourth example is of this kind The multivariate methods also lend themselves to ‘network meta-analysis’ ith study as Yi. The entries of Yi may be correlated and it is assumed that within each studyWe denote the vector of effects (or estimates) for the multivariate normal distribution, µi is the true underlying effect for the ith study and Si is the covariance matrix of Yi. The matrices Si are referred to as the within-study covariance matrices; their entries are estimated in practice using the IPD for each study separately but regarded fixed and known when pooling the results to make inferences. The within-study variances  treatment effect vector and Σ is the between-study covariance matrix. We interpret µ as the average effect from a normal distribution of study effects. We regard Σ as being unstructured but simplifications are possible: for example, all between-study correlations, or all between-study variances, could be assumed to be the same.et al.In the presence of missing study effects, there must be enough estimated effects, and combinations of these within studies, to make Σ identifiable. We assume throughout that this is so. If all entries of Σ are determined to be zero, then the model reduces to a fixed effects  model. For those who prefer to fit fixed effects models, or reduced random effects models with fewer heterogeneity parameters , when these appear to describe the data reasonably well, Ritz The model for the random effects  is hardeA multivariate linear between-studies regression.A further consequence of the assumed normality is a constant between-studies covariance matrix, where the conditional variances of all components of the random effect are also constant.A normal distribution for the random effect implies that this is symmetrical and does not allow for a distribution with heavy or light tails.When all, or the majority of, studies provide all effects then these assumptions are not so worrying. When a relatively large number of studies do not provide all effects, assumptions 1–3 become more of a concern, as the borrowing of strength discussed below depends on the distributional relationships between the observed and unobserved effects. For example, an outlying trial result on one outcome could be very influential for the inferences for both this and other effects, because of the assumed distributional form of the random effect and the linear regressions. If separate univariate meta-analyses are conducted such an outlying result could still be influential Marginally, this provides the conventional multivariate random effects meta-analysis modelYi are further assumed to be independent because they come from separate studies. For any studies that provide only some effects, the model for the studies' results are taken as their submodel from  per cent confidence interval can be obtained for µIf some studies have missing effects then, assuming that these are missing at random and for computational convenience, such studies can be incorporated into the matrix solutions  and 5)  5) by alet al.The main statistical difficulty lies in estimating the between-study covariance matrix Σ. As the estimation of this is typically fairly imprecise for examples with small numbers of studies, the resulting statistical procedures may not perform well as can be seen in some simulation studies of Jackson LLT, and back transform to obtain As the likelihood is the product of normal densities it can be maximized numerically to simultaneously give estimates of the entries of Σ, subject to the constraint that this matrix is positive semi-definite, and REML given by Jennrich and Schluchter It is more usual to estimate the entries of the between-study covariance matrix using REML. The restricted likelihood is a function of the variance components only (i.e. not µ) and REML helps to correct for the downward bias of maximum likelihood estimates of variance components. Estimation is performed by maximizing a special case of the expression λri denote the residuals and where the ned from .The main difficulty presented by these likelihood-based methods for estimating the between-study covariance matrix is their computational intensity as the dimension of the meta-analyses increases.et al.The univariate method of DerSimonian and Laird sumption . Howeversumption  is stillIn addition to these procedures, more computationally intensive alternatives are possible that allow for the uncertainty in the between-study covariance matrix and hence may perform better. For example, Kenward and Roger The use of profile likelihood in meta-analysis was established by Hardy and Thompson et al.Complex Bayesian analyses are now computationally feasible due to the advent of MCMC methods which WinBUGS de facto method for the analysis of network meta-analyses where ‘incoherence’ or ‘inconsistency’ is modelled. A Bayesian approach also facilitates incorporating external evidence via informative priors if desired, and may be particularly useful to help estimate the between-study correlation.The multivariate setting provides the additional challenge of placing vague priors that ensure that the between-study correlation matrix is positive semi-definite; at our RSS meeting it was suggested that a uniform prior be placed on log(ρ/(1−ρ)) in the bivariate case, rather than on the correlation ρ directly. In high dimensions perhaps the easiest way to attempt to use a vague prior for the between-study covariance matrix is to use a Wishart prior mvmeta1 is used throughout the following section to obtain the results for our example data sets. mvmeta1 is an updated version of mvmetamvmeta version 2. All the three estimation methods described in Section 4.1 have been implemented in both mvmeta and mvmeta1. The Stata program metandiPROC NLMIXED and METADAS are however fully viable alternatives for performing multivariate analyses.The Stata program In this section we describe the advantages and potential limitations of multivariate meta-analysis, and use the four examples introduced in Section 2 to illustrate the key concepts. For each of example data sets 2–4  and III,The results of the meta-analyses of examples 1–4 are shown in It is more elegant to perform a single multivariate meta-analysis than many univariate ones. This advantage is demonstrated well by our fourth example . The mulThis advantage is nicely demonstrated by our first example  and V. FThe utilization of between-study correlation here allows the appropriate calculation of a joint confidence region around the pooled sensitivity and specificity pair, as shown in et al.et al.In some situations one may wish to use multivariate meta-analysis to fit a line through the multiple effects of interest. For example, in our first example the summary ROC curve is derived by assuming a linear trend between logit-sensitivity and logit-specificity between studies , an ideaet al.Parameter estimation is often superior in a multivariate meta-analysis than in a univariate meta-analysis, again as it utilizes the correlation between the endpoints of interest and thus each endpoint ‘borrows strength’ from the other related endpoints. Assuming that the between-study variance estimates are the same in multivariate and univariate analyses, Riley 2 and µ4 compared with the univariate analyses.The gain in efficiency of parameter estimates is most clearly demonstrated by our second example  and VI. The multivariate approach also improves estimation of the between-study variances, and thus borrowing of strength occurs for both the pooled estimates and the between-study variance estimates. For example, it has been shown that the multivariate model of Equations  and 2)  2) givesConclusions from a multivariate meta-analysis may sometimes differ from those from univariate meta-analysis. For example, consider the comparison of group A to the baseline group in example 4  and VIIIIn our third example  and VII,A multivariate meta-analysis can utilize the correlation between overall survival and disease-free survival to borrow strength and reduce this problem. The univariate approach gives a pooled log hazard ratio for disease-free survival of −0.80 , indicating there is large statistically significant evidence that patients with mutant p53 have a decreased event risk . HoweverSeparate univariate meta-analyses are more transparent and easier to understand than a multivariate method. A related argument is that we do not usually model effects from individual trials multivariately, so why should we attempt this in the context of meta-analysis?Sophisticated modelling is extremely difficult in meta-analysis without IPD. All we usually have are a handful of estimates and, if we are lucky, their standard errors. Multivariate meta-analysis often also requires within-study correlation estimates, but these are rarely available as in examples 2 and 3. In such situations sensitivity analyses, or some other approaches (see Section 6), are needed to limit this problem, which is not ideal.Even when the within-study correlations are available, it is often difficult to estimate the between-study correlation and it is often estimated as 1 or −1, at the boundary of its parameter space, causing a slight upward bias in the between-study variance estimates Some discrepancies between the method of moments and REML are also evident in the parameter estimates for Chromosome 1p in example 2, where REML provides smaller pooled estimates. The method of moments is a semi-parametric method for estimating the random effects, and it seems the stronger multivariate normality assumption of REML when estimating the between-study covariance matrix is leading to different conclusions and perhaps additional borrowing of strength.In a univariate meta-analysis the assumption that the random effects are normally distributed is hard to verify. In a multivariate meta-analysis, the multivariate normality assumption is even stronger and harder to verify. Furthermore, in the multivariate case, an implicit assumption is that the effects have a linear relationship between studies. It is hard to estimate nonlinear relationships with the few studies meta-analysis usually has available, but clearly the borrowing of strength will be influenced by this assumption. This may be particularly crucial when borrowing strength beyond the range of data for which an effect is available. For example, in example 3 the relationship between overall and disease-free survival p53 hazard ratio estimates is observable across those 3 studies that report both outcomes ; howeveret al.We were expecting our audience at our RSS meeting to be more impressed with the borrowing of strength within multivariate meta-analysis, and the more precise estimates it often brings. However, the enthusiasm level was rather underwhelming, even when the standard errors of pooled estimates dropped by around 10 to 30 per cent, as they do for many of the estimates in example 2 . The vieWhile we agree gains in statistical properties are often only small, particularly for complete data, it is important to note here that even small changes in estimates and their precision can change statistical significance and clinical conclusions, as discussed earlier for group A in example 4 .et al.A further potential difficulty is publication and related biases Perhaps the greatest difficulty applying the multivariate meta-analysis model in practice is that the within-study correlations are required by the model and are typically unknown as in our second and third examples.et al.Recall from Section 3 that all entries of the within-study covariance matrices are regarded as fixed and known. The diagonal entries are obtained in the same way as in the univariate case and are typically given, or can be ascertained, from the published reports of the studies included in the analysis. The within-study correlations are not generally available in this way. It is perhaps partly because of this difficulty that multivariate meta-analysis has primarily found applications in diagnostic testing and IPD meta-analysis so far; in the former the within-study correlations can safely be assumed to be zero, and given IPD one can usually fit the desired model or models and extract the within-study covariance matrix in a routine way. Jackson For the special case of mutually exclusive binary outcomes, formulae for the correlations have been derived IPD allows us to obtain the entire within-study covariance matrix in each study as noted above, alleviating the reliance on reported information. In more complex modelling situations, bootstrapping methods may be required IPD may be available for some studies. In this situation one solution is to use the within-study correlations derived from IPD studies to inform the likely value of the within-study correlation in aggregate data studies. For example, the average available within-study correlation could be imputed, or sensitivity analyses could be performed by imputing over the range of observed values.et al.Even without IPD studies, it may be possible to narrow the range of possible values for the unknown within-study correlations. For example, Raudenbush et al.Where little or no information about the within-study correlations exists, a further option is to perform sensitivity analyses by imputing correlations over the entire range of values (i.e. from −1 to 1), to assess whether and how conclusions depend on the correlation that is imputed. In a Bayesian framework, Nam mvmeta1.An alternative multivariate random effects model for meta-analysis has been proposed which does not require the within-study correlations et al.Hedges To summarize, a variety of approaches are available for handling the common situation where the within-study correlations are unknown. The absence of information about the within-study correlation structure does not entirely prohibit a multivariate approach but this does present very real statistical issues and a consensus about the best approach or approaches has yet to be reached.We hope that this article will serve to summarize the current multivariate meta-analysis climate, in both theoretical and computational terms, and raise awareness of the type of applications it has found. One vision for the future is that every meta-analysis will eventually be multivariate (unless only a single effect is considered). The concern now is whether or not this is sensible, and is this really what we want? We have found that the multivariate methods have the potential to make a real contribution to meta-analysis, but also that they bring additional complications and issues with them. Our examples are representative of our experiences that multivariate meta-analysis can be helpful in some instances, but are not necessarily so every time. Our third example makes a strong case for those contemplating the use of the multivariate techniques to take even greater care when using them, compared with the ‘old and (perhaps) more reliable’ univariate methods.We have described the advantages of the multivariate methods but some might reasonably argue that the univariate scenario is still not understood well enough to proceed with the multivariate setting. Conventional univariate meta-analysis requires normal approximations, and replaces variance parameters with estimates, and it is not really understood how many and large the studies must be to make these approximations accurate enough to be appropriate. It is unclear whether the multivariate setting will exacerbate these kind of issues, and if so by how much. There is also the argument that statisticians' energy should go into getting good estimates and standard errors, and avoiding publication biases, rather than developing complex models which may be unnecessary for such simple data structures.Visual plots are important in any statistical analysis and forest and funnel plots have an established place in univariate meta-analysis. The ‘bubbleplot’, as shown for our first example in mvmeta1. The additional problem of having to estimate the effect of covariates in a conventional univariate meta-regression has been found to require larger sample sizes to perform well It should be noted that multivariate meta-regression I2I2 and related statistics should be extended to more than a single dimension could be reached, then we would recommend that these also be provided and interpreted when using multivariate methods. Currently the authors simply calculate I2-type statistics as the ratio of diagonal entries of the estimated between-study covariance matrix and the sum of this and the usual ‘typical’ within-study variance, obtained from the corresponding univariate within-study variances, but it may be that something more sophisticated than this is both possible and desirable.Alternative multivariate methods are also possible. Multivariate generalizations of descriptive statistics as Now that we have provided our version of events, we await the testimony of our expert witnesses with considerable interest.


KCNE3 as a potential candidate for tinnitus susceptibility. 288 Caucasian outpatients with a diagnosis of chronic tinnitus were systematically screened for mutations in the KCNE3 open reading frame and in the adjacent region by direct sequencing. Allele frequencies were determined for 11 known variants of which two (F66F and R83H) were polymorphic but were not associated with the disorder. No novel variants were identified and only three carriers of R83H were noted. However, owing to a lack of power, our study can neither rule out effects of KCNE3 on the risk for developing chronic tinnitus, nor can it exclude a role in predicting the severity of tinnitus. More extensive investigations are invited, including tests for possible effects of variation in this ion channel protein on the response to treatment.Membrane-stabilizing drugs have long been used for the treatment of chronic tinnitus, suggesting an underlying disturbance of sensory excitability due to changes in ion conductance. The present study addresses the potassium channel subunit gene  Epidemi 1 and 2 ,6, in DN 1 and 2 , and in  1 and 2 , among o 1 and 2 , in nois 1 and 2 ,11, in a 1 and 2 , and in  1 and 2 .KCNE3 is expressed in the mammalian inner ear [KCNE3 which maps to chromosome 11q13-14, a linkage hot-spot for autosomal recessive, non-syndromal hearing impairment [KCNE3 variants.A further candidate gene, encoding the potassium channel ß subunit KCNE3/MIRP2, has been adressed in Menière's disease . Like KCnner ear  and brainner ear ,16. Bothnner ear . So far,pairment . In viewpairment , and of pairment , we hypoKCNE3 variants with tinnitus susceptibility  consulting for chronic tinnitus (minimum duration of 6 months), the diagnosis was confirmed by a detailed neurootological examination including otoscopy, stapedius reflexes, middle ear pressure measurements, pure tone audiometry, tinnitus pitch and loudness matches. For the present study, those patients with a history of vestibular schwannoma, Menière's disease, or pathological middle ear conditions were excluded. The remaining subjects suffered from primary tinnitus and family histories were available in 139 subjects. Of these, 38% reported at least one first-degree relative affected by tinnitus. Tinnitus severity was assessed by the Tinnitus Questionnnaire (TQ)  in 283 pibility  and 5'-CCA GAG CAT CTT CCT GTC TC-3' (reverse). PCR products were purified for Sanger sequencing and for the identification of variants against the human genome reference . Multiple sequence alignments were conducted with DNA Dynamo 1.0 . STATA 8.0  was used for statistical analyses. KCNE3 allele frequencies from reference populations were compared to the present data using Fisher's exact test. All p values are uncorrected for multiple testing.Genomic DNA was extracted from lymphocytes using standard pocedures prior to amplification of the For assessing the functionality of coding variants observed in our sample, evolutionary conservation was assessed with a phylogenetic hidden Markov model-based method, PhastCons, that describes the process of DNA substitution at each site in a genome and the way this process changes from one site to the next . GenomicKCNE3 variants listed in dbSNP were absent from our sample . Four previously reported KCNE3 mutations were also absent: T4A [We confirmed two known coding variants with observed heterozygosities of 0.215 (F66F) and 0.01 (R83H), and featuring genotype distributions that conformed to the Hardy-Weinberg equilibrium  out of 84 points (N = 283). By this measure, tinnitus was rated mild (0 to 30 points) in 94 subjects (33.2%), moderate (31 to 46 points) in 84 subjects (29.7%), severe (47 to 59 points) in 55 subjects (19.4%), and extreme (60 to 84 points) in 50 subjects (17.7%). There was no significant difference in mean TQ scores between carriers and non-carriers of the minor alleles at either of the two confirmed polymorphic KCNE3 nucleotides . As we encountered only three carriers of the rare missense variant R83H (fHIS83 = 0.005), the impact of this substitution on tinnitus severity could not be fully judged. However, neither of the two variants is expected to be inert by comparative genomic analysis  the biophysical properties of the channel complex are significantly altered.In view of the limited power of our pilot study and the need to assesss promotor variation, more research is invited to address The authors declare that they have no competing interests.Authors PGS, BL and TK acquired, analysed and interpreted the data. PGS designed the study and drafted the original manuscript. All authors revised the manuscript for important intellectual content and provided final approval of the version to be published.


The survivin polymorphisms have been shown to confer genetic susceptibility to various tumors, but the results are inconsistent. In order to accomplish a more precise estimation of the relationship, a meta-analysis was performed.For rs9904341, a significantly increased tumor risk was found in overall meta-analysis under C/C vs. G/G , dominant  and recessive  genetic models and Asians group. In subgroup analyses of tumor types, we found a significant association between this SNP and an increased risk of gastric, colorectal, bladder and other tumors as well as a decreased risk of hepatocellular cancer. For rs17878467, a significantly decreased tumor risk was identified in overall meta-analysis for allele contrast , C/T vs. C/C  and dominant  genetic models and Asians group. For rs2071214, we found a significant association between this SNP and an increased tumor risk in overall meta-analysis under G/G vs. A/A  and recessive  genetic models and Asians group. Besides, there was a significant association of rs8073069 with an increased tumor risk under recessive genetic model , while no significant association between rs1042489 and tumor risk was detected.The survivin rs9904341 most likely contributed to increased susceptibility to tumor in Asians as well as to gastric, colorectal and bladder cancers. As for rs17878467, the T allele might be a protective factor for tumor, especially in Asians. Moreover, the survivin rs8073069 and rs2071214 seemed to be associated with an increased tumor risk in Asians, while there was no association between the survivin rs1042489 and tumor risk. Apoptosis, also known as programmed cell death, plays an important role in the development and maintenance of tissue homeostasis in multicellular organisms Survivin is a member of the inhibitor of apoptosis protein family, which is involved in the inhibition of apoptosis Survivin is expressed in a cell-cycle-regulated manner, with a peak in the G2/M phase of the cell cycle, which is largely controlled at the genetic level Many studies have recently explored the potential association of several SNPs in survivin gene with the susceptibility to various tumors The present meta-analysis and systematic review follows the Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA) statements . And thePubMed, EMBASE, and Chinese National Knowledge Infrastructure (CNKI) were searched till the end of January 2013 to identify relevant studies. Literature searching was performed by applying combinations of the following terms:  and (“genetic variant” or “genetic variation” or “polymorphism”) and (“tumor” or “cancer” or “carcinoma” or “neoplasia” or “neoplasms”). These keywords were used as MESH headings and free text words. Besides, the manual searching of reference lists from potentially relevant papers was also performed, based on the computer-assisted strategy, to identify any additional studies that may have been missed.The inclusive criteria were: (1) studies used validated genotyping methods  to measure the association of survivin polymorphisms with tumor risk; (2) studies were in an appropriate analytical design ; (3) studies were published in English or Chinese; (4) studies with the full-text availability; (5) data were not duplicated in another manuscript. Studies were excluded if they did not report the relevant data to calculate the odds ratios and its variance. In addition, studies were also excluded if control subjects in these studies departed from Hardy-Weinberg equilibrium (HWE).Two reviewers (ZY and ZSS) independently performed the data extraction, with the disagreements resolved through consensus decision. For each trial, the following items were collected: the surname of first author, year of publication, country, ethnicity ), sample size, types of tumors, matching criteria of cases and controls, control source, genotyping methods, genes and variants genotyped.http://ihg2.helmholtz-muenchen.de/cgi-bin/hw/hwa1.pl). And a p–value less than 0.05 of HWE was considered significant.The evidence of HWE in controls was recalculated in the present meta-analysis through the application of the online software  when data were available from more than three studies. The strength of association between survivin polymorphisms and tumor risk was measured by odds ratios (ORs) with their 95% confidence intervals (CIs). The significance of pooled ORs was determined by the Z–test, and statistical significance was defined as a 2-sided P-value <0.05. As for survivin rs9904341, allele frequency comparison model (C versus G) was initially used to examine the potential association of the assumed risk allele C with tumor susceptibility, then different comparison models, including additive (C/C versus G/G and G/C versus G/G), dominant (C/C+G/C versus G/G), and recessive (C/C versus G/C+G/G) genetic models, were also used to estimate tumor risk, as well as other SNPs of survivin gene. Besides, subgroup analyses were stratified by ethnicity and types of tumors, respectively.h<0.1 and 2>I50%). A sensitivity analysis was performed to explore the potential source of heterogeneity. In addition, publication bias was assessed by visual inspection of funnel plots in which the standard error of log (OR) of each study was plotted against its log (OR). Funnel plot asymmetry was assessed by Egger's linear regression test.A fixed-effects model (the Mantel–Haenszel method) was firstly used to estimate the pooled ORs, while the random-effects model (the DerSimonian and Laird method) was planned to be used if there was evidence of significant heterogeneity across trials , dominant  and recessive  genetic models, while there was no significant association of this SNP with tumor risk under allele frequency comparison model and C/C vs. G/G genetic model . In the For the survivin rs2071214 , we founFor the survivin rs8073069 and rs1042489 , there wIn order to assess the robustness of our results, we performed the sensitivity analysis with each study removed for every meta-analysis. The results of sensitivity analyses indicated that pooled ORs before and after exclusion of the study which majorly contributed to heterogeneity were generally similar, suggesting that most evidences from our meta-analysis should be considered to be stable and convincing .Publication bias of the included trials was assessed by Begg's funnel plot and Egger's test. As for survivin rs9904341, symmetrical funnel plots were obtained under all genetic models , and theIt is generally considered that tumor is a multifactorial disease involving both environmental and genetic factors; however, the precise molecular mechanism of which still remains unclear Growing evidences have suggested that several factors including genetic variation of suvivin gene can modulate the expression of survivin, especially the functional SNPs The survivin rs9904341 is identified in the survivin promoter, which is located at the cell cycle-dependent elements (CDEs) and cell cycle homology regions (CHRs) repressor binding site. In-vitro analyses have shown that this mutation can derepress the cell cycle-dependent transcription of survivin gene through the functional disruption of binding at the CDE/CHR repressor motifs and result in over-expression of survivin at both mRNA and protein levels Consistent with the functional studies Although the survivin rs17878467 and rs8073069 are also positioned in the survivin promoter, they are not cis-acting element or located in putative transcription factor binding site. However, like survivin rs9904341, there was a significant association of these two SNPs with tumor risk. Consistent with the previous studies The survivin rs2071214 leads to amino acid change from Lys to Glu at codon 129 in exon 4, which is located at the C-terminal end of the protein (142 amino acids). Pooled ORs showed that individuals with the +9194GG genotype had an increased risk of tumor when compared to AA or AA/AG genotypes. Our results were consistent with the previous studies Although a substantial heterogeneity was detected in many pooled analyses, it did not have a significant impact on the results of these analyses, indicating that most evidences from our study should be considered to be stable and convincing. However, our study still had several potential limitations, and some cautions should be applied when interpreting these results. First, previous studies have shown that the presence of survivin rs9904341 was correlated in many cancer cell lines with increased survivin expression at both mRNA and protein levels when compared to normal cell line controls, indicating that transcriptional deregulation caused by this mutation in the promoter region of survivin gene might be an important mechanism involved in the aberrant expression of survivin in some cancers In conclusion, our study revealed that the survivin rs9904341 most likely contributed to increased susceptibility to tumor in Asians as well as to gastric, colorectal and bladder cancers. As for rs17878467, the T allele might be a protective factor for tumor, especially in Asians. Moreover, the survivin rs8073069 and rs2071214 seemed to be associated with an increased tumor risk in Asians, while there was no association between the survivin rs1042489 and tumor risk. However, further studies of high quality with larger sample sizes are still needed to confirm these findings.Checklist S1PRISMA Checklist.(DOC)Click here for additional data file.Table S1Sensitivity analysis for heterogeneity.(DOCX)Click here for additional data file.