CHRNA coding subunits of nicotinic acetylcholine receptor. Herein, we performed a meta-analysis to clarify the impact of CHRNA variants on COPD.Only 10-15% of smokers develop chronic obstructive pulmonary disease (COPD) which indicates genetic susceptibility to the disease. Recent studies suggested an association between COPD and polymorphisms in CHRNA. Pooled odds ratios (ORs) were calculated using the major allele or genotype as reference group.We searched Web of Knowledge and Medline from 1990 through June 2011 for COPD gene studies reporting variants on CHRNA, rs1051730 was finally analyzed with sufficient studies. Totally 3460 COPD and 11437 controls from 7 individual studies were pooled-analyzed. A-allele of rs1051730 was associated with an increased risk of COPD regardless of smoking exposure . At the genotypic level, the ORs gradually increased per A-allele . Besides, AA genotype exhibited an association with reduced FEV1% predicted  and increased risk of emphysema .Among seven reported variants in CHRNA is a susceptibility variant for COPD, in terms of both airway obstruction and parenchyma destruction.Our findings suggest that rs1051730 in  Chronic obstructive pulmonary disease (COPD) is one of the leading causes of morbidity and mortality worldwide and results in an economic and social burden which is both substantial and still increasing . It is cCHRNA3-CHRNB4-CHRNA5 on chromosome 15q25 have been identified to be associated with nicotine dependence [CHRNA3-CHRNB4-CHRNA5 region encodes the subunits of alpha-nicotinic acetylcholine receptor (nAChR), which are expressed not only in neurons but also in other tissues [CHRNA have been reported to be related to functional consequences, such as altered receptor response to nicotine agonist [CHRNA5 in brain and lung tissue [Several single nucleotide polymorphisms (SNPs) in the gene cluster pendence -14. Thes tissues ; and inf tissues . Experim tissues ,20. More tissues . The varg tissue . Therefog tissue ,23-29.CHRNA. We also performed a meta-analysis on published case-control studies aiming to confirm the effect of nAChR variants on susceptibility to COPD.In order to confirm a conclusive relationship between genetic locus and susceptibility to COPD, it is important to determine its impact on the development of COPD and COPD-related phenotypes. Individual studies on the association between nAChR polymorphisms and COPD were of limited sample size and there has been a lack of replication between various studies. From the most recent studies focusing on the association between genetic polymorphisms in 15q25 locus and different subtypes of COPD (airway obstruction and emphysema) ,25, we sLiterature search was carried out using electronic databases Web of Knowledge (1990 to June 2011) via library of Fudan University and Medline (1990 to June 2011) by PubMed search engines, with the databases being last assessed on 10 July 2011. The search histories were as follows:  AND  AND (chronic bronchitis OR emphysema OR chronic obstructive pulmonary disease OR COPD). The reference lists of relevant publications were manually searched for additional studies.Ethical approval was not required for this meta-analysis.Studies were included if they reported the genotype count or allele frequency. The included studies should be a case-control design, with at least two comparison groups, i.e. COPD and controls. Population-based studies were included, but studies base on family or sibling pairs were excluded. Self-reported COPD were not acceptable as a reliable diagnosis, and therefore studies using such diagnostic criteria were excluded. In case of studies containing the same data sets as studies that had been published before, only the study with the largest sample size was included. Data published only in abstract form or from web-site materials were excluded due to the fact that these studies had not undergone peer-review and the inclusion of these studies might introduce bias into the meta-analysis. Case reports, review articles, and textbook chapters were also excluded from the analysis. Two authors independently reviewed the abstracts of all the studies generated by the literature search. The variants, which were reported by more than 5 independent studies, were further meta-analyzed. The full text articles of all eligible abstracts were reviewed and data were extracted by the two authors. Any discrepancies were resolved by discussion with a third author to reach a final consensus.The extracted data included: (1) publication details including year of publication, title, name of the first author, and country in which the study was conducted; (2) type of study design; (3) sample size; (4) age range, gender and ethnicity of the study population; (5) COPD definition; (6) smoking history of the studied subjects; (7) allele frequency; (8) genotype counts; (9) phenotypes ; (10) methods which were used to investigate polymorphisms. The authors of the included studies were contacted for additional information if there was no sufficient data for analysis.CHRNA and COPD. Data from each case-control study were extracted to construct a two-by-two table in which subjects were classified by diagnostic category (COPD versus control) and different genotype or alleles. The odds ratios (ORs) were estimated using the major allele or genotype as the reference group. All the statistical analysis was performed by Review Manager Software 5.1.2 . The Chi-square test was used to evaluate the presence of statistically significant heterogeneity across the studies and the inconsistency index (I2) was used to quantify the amount of heterogeneity [A methodological meta-analysis was conducted to determine the overall association between the candidate variant in ogeneity . If therThe initial literature search revealed 29 articles, of which 20 were excluded because their title and abstract were irrelevant to our study question. For all the known variants on 15q25, only rs1051730 was reported by more than 5 independent studies. In the subsequent literature analysis, eleven potentially eligible studies on rs1051730 were identified from the remaining 7 articles -29. The 2 = 4%), a fix-effect model was used for the analysis. The A-allele was significantly more common in COPD subjects compared with control subjects. As shown in Figure -5). Therefore, the A-allele carriers were more susceptible to having COPD.Data from seven independent studies were analyzed for the OR of A-allele using the G-allele as the reference group -27. As tAccording to the comparability of smoking exposure (pack-years) between COPD group and control group, we performed a subgroup analysis. As shown in Table Six studies reported the genotype counts. There was no heterogeneity between studies , and analysis was performed under a fix-effect model. At the genotypic level, homozygous AA and heterozygous GA carriers exhibited an increased risk of having COPD compared to homozygous GG carriers Table .The funnel plot for the OR analysis of the frequencies of A-allele and G-allele between COPD and control Figure  suggests1) values against different genotypes. FEV1% predicted values in GA and AA genotype were significantly reduced compared to that in GG genotype, with the mean difference being 3.51% and 6.86% respectively . In addition, AA genotype, compared to GG genotype, showed statistically significant evidence of association with lower FEV1% predicted  and higher incidence of emphysema .Genetic findings suggest that COPD is associated with the chromosome 15q25 region, which includes the it genes ,15,23-29it genes ). Of 7 rCHRNA. In the COPD GWA study, rs16969968 (which is in strong linkage disequilibrium with rs1051730) showed a weaker association than rs1051730 [There was limited data about the association between the susceptibility to COPD and other variants in s1051730 . In the s1051730 ,26. In as1051730 .CHRNA have a direct effect on COPD or merely mediate smoking habits [et al [et al [The overlap of nAChR polymorphisms for nicotine dependence and COPD has led to the debate whether polymorphisms in g habits ,15,27. Ss [et al  reportedl [et al  includedCHRNA3 gene. The genetic variant was correlated to the mRNA expression of nAChRs subunits [CHRNA3/5 gene cluster might work together and alter the function of nicotinic receptor in lung tissue and further increase the risk for COPD. Our findings showed that SNP rs1051730 was associated with a reduced FEV1  polymorphism, the GSTM1 null variant, Ile105Val (rs1695) in GSTP1, rs2241712/rs1982073/rs6957/rs1800470 in TGFB1, 308GA (rs1800629) in TNF and rs1799896 in SOD3. Furthermore, another gene IREB2 was also identified as a potential gene for COPD susceptibility [IREB2 and CHRNA are both on chromosome 15q25. It was found that IREB2 protein and mRNA were increased in lung-tissue samples from COPD subjects in comparison to controls. However, further investigations are essentially required in order to understand more about the interaction between rs1051730 and other genes (such as IREB2) for the pathogenesis of COPD in the future.COPD is a multi-factorial disease, and therefore, a variety of genes in the biological pathway of COPD might act together in the development and progression of the disease, and single polymorphism might have interactions with other genetic factors. Apart from  protein ,34, a se protein ,7,35-38.tibility ,40. IREBOur study has the following limitations. First, our study did not consider gene-by-smoking interactions. In all included studies except the Copenhagen City Heart Study, inclusion criteria on smoking history was similar in case and control group Table ; howeverCHRNA as a susceptibility variant for the development of COPD, in terms of both airway obstruction and parenchyma destruction. A-allele carriers have a higher risk for COPD, and have a lower FEV1%predicted and higher incidence of emphysema. However, many questions are still to be answered before establishing nAChRs as an interventional target for COPD. Epidemiologic analysis in different ethnic populations, the mediating effect of smoking exposure, and functional studies should be prioritized for further research.In summary, quantitative meta-analysis identified rs1051730 in The authors declare that they have no competing interests.JZ participated in the design of the study, carried out the database search, performed article revaluation and data retraction, and drafted the manuscript. HS carried out article revaluation and the data retraction. YGZ performed the statistical analysis. JMQ conceived of the study, participated in the design and coordination of the study and. All authors read and approved the final manuscript.


CYP2D6 genotype and tamoxifen response through.To evaluate evidence on the association between Systematic review and meta-analysis of prospective, cross-sectional and case-control studies published to 2012. For each study, relative risks and 95% confidence intervals were extracted and pooled with a fixed and random effects model. Heterogeneity, publication bias, subgroup, and meta-regression analyses were performed.PubMed (inception-2012) and EMBASE (inception-2012).CYP2D6 gene.Criteria for inclusion were studies reporting breast cancer outcomes in patients treated with tamoxifen and genotyped for polymorphisms in the CYP2D6 genotype with outcomes in breast cancer women all receiving tamoxifen treatment (“treatment-only” design). Three randomized trials evaluated the effect of CYP2D6 genotype on tamoxifen response (“effect modification” design). In analysis of treatment-only studies, the relative risk (RR) of all-cause mortality  for carriers of a CYP2D6 reduced function allele was 1.11 : 0.94 to 1.31) compared to individuals with normal/increased function CYP2D6 alleles. When we investigated a composite outcome including all-cause mortality and surrogate endpoints for overall survival , carriers of a CYP2D6 reduced function allele had a RR of 1.27 (95% CI: 1.11 to 1.45). From two randomized trials that permitted effect-modification analysis, one had only 154 patients and showed evidence of effect modification of tamoxifen by CYP2D6 genotype for distant recurrence but was directionally opposite to that predicted, whereas a larger trial of 2,537 patients failed to show evidence of effect modification for breast cancer-free interval .Twenty-five studies of 13,629 individuals were identified, of which 22 investigated the association of CYP2D6 genotyping to guide tamoxifen treatment.Based on these findings, there is insufficient evidence to recommend  Tamoxin situ .A meta-analysis of 20 randomized clinical trials (RCTs) including 10,645 women with estrogen receptor positive breast cancer demonstrated that, compared to no tamoxifen, adjuvant tamoxifen reduced breast cancer recurrence (relative risk (RR) 0.53, 95% CI: 0.47 to 0.59) and breast cancer mortality  at 5 years [CYP2D6 that alter the level or activity of the encoded enzyme might alter the response to tamoxifen [Tamoxifen itself is only a weak modulator of the estrogen receptor while its metabolites (including endoxifen) are thought to be many times more potent . Severalamoxifen . A U.S. amoxifen .CYP2D6 genotype and response to tamoxifen treatment in individuals with breast cancer by conducting a systematic review and meta-analysis.We investigated the evidence of the association between CYP2D6 genotype in humans of any ethnic group.To be eligible for inclusion, studies reported breast cancer outcomes in relation to th January 2012. The search terms included the generic and proprietary drug names  and the gene name . Full details of the search string are provided in the Supplementary Methods reported in CYP2D6 genotype and tamoxifen response in humans. Eligible studies had an abstract containing the keywords “tamoxifen” and “CYP2D6” and reported original data. Editorials and reviews were omitted. The search was complemented by hand-searches of the bibliographies of included articles and of narrative reviews.Following PRISMA guidance , we searThe search was conducted by DWKL and a random subset of studies was double-checked by MVH and ADH. Uncertainties were resolved by consensus. When questions remained, corresponding authors were contacted. The literature search was not restricted by ethnicity or language.CYP2D6 genotypes. For the main analysis, we compared individuals with any reduced/non-functional CYP2D6 allele to individuals with normal/increased function alleles. In studies that reported individual CYP2D6 genotype comparisons (e.g. *4 vs. *1), individuals carrying one or more reduced functional alleles  and/or non-functional alleles  were grouped together and compared with individuals carrying normal/increased function CYP2D6 alleles . For studies that grouped CYP2D6 alleles into so-called “predicted phenotypes”, the poor metabolizers and intermediate metabolizers were grouped  and were compared with extensive metabolizers and ultra metabolizers  compared to individuals that did not harbour these alleles.We used information from The Human Cytochrome P450 (CYP450) Allele Nomenclature Database  and the Pharmacogenetics Knowledgebase  to classify CYP2D6 allele compared to the normal/increased function alleles , we synthesized a hierarchy to reflect clinical importance of the reported study outcomes based on recent narrative reviews of clinical trials in cancer –15. We hIn addition to the main outcomes, we conducted separate meta-analyses for the following individual outcomes for the treatment-only analysis: (i) breast cancer-specific mortality; (ii) overall survival/all-cause mortality; (iii) surrogate endpoints for overall survival ; (iv) non-fatal events (breast cancer recurrence), and; (v) the adverse drug reaction, hot flushes.For the effect modification studies, we used outcomes reported in the clinical trials.CYP2D6 genotype (e.g. *4 vs. *1) and grouped CYP2D6 genotypes comparisons (e.g. poor metabolizers vs. extensive metabolizers), the latter was used as it incorporated more genetic variation in CYP2D6.We extracted counts of events by genotype and used these to generate odds ratios for each study. When event counts were not available, we used the reported univariate effect estimates. When neither event counts nor univariate estimates were reported, we used the reported multivariate effect estimates. When a study reported both single The analysis was split into two main types depending on the design : the treI2 statistic and tested using Cochrane’s Q test [For the treatment-only analysis, we used fixed and random effects meta-analysis models to pool estimates from individual studies. Unless otherwise stated, meta-analyses used the fixed effects model . The sums Q test .CYP2D6 genotype.For the effect-modification analysis, we used the Bland and Altman method  to test We used several techniques to investigate potential sources of bias. Publication bias was investigated by visual inspection of the funnel plot and quantified by the intercept from linear regression . The staCYP2D6 reduced function alleles and the risk of each composite outcome.We investigated the potential for a dose-response relationship on the treatment-only analysis by conducting meta-regression analyses, testing a linear relationship between the number of All statistical analyses were performed using Stata v11.2  and reported P-values are two-sided. For the treatment-only analysis, a P-value <0.05 was used to indicate evidence against the null hypothesis of no association. In the subgroup analysis of treatment-only studies see S1, we aWe identified 25 studies including 13,629 participants that fulfilled our selection criteria S3. The CYP2D6 genotype (All identified studies were conducted in women. The median age was 58 years (range 41 to 76) and median sample size per study was 462 participants (range 84 to 3155). In the 17 of 25 (68%) studies that reported duration of follow-up, the median duration was 6.3 years (range 4.5 to 11.4). Most studies (16 of 22 that reported ethnicity) reported data principally on Caucasian individuals. The breast cancer stage of study participants ranged from 0 to IV  alleles were genotyped across the studies, with only four alleles  genotyped in half or more of the 13,629 individuals across the 25 studies. The most commonly genotyped CYP2D6 alleles were *4 in 23 studies (genotyped in 96% of participants), followed by *41 in 13 studies (genotyped in 77% of participants). There were several * alleles that were genotyped but not reported  in the fixed effects analysis and 1.12 (95% CI: 0.90 to 1.41) in random effects meta-analysis  reported data that could be incorporated into the all-cause mortality analysis. Compared to those with normal or increased function alleles, individuals with any copy of a reduced function analysis S6.CYP2D6 allele had a RR of achieving the composite of 1.27  for fixed effects and 1.34 (95% CI: 1.06 to 1.69) for random effects meta-analysis compared to individuals with normal/increased function CYP2D6 alleles  could be incorporated into the analysis. Individuals with any copy of a reduced function  alleles S7.CYP2D6 allele had a RR of achieving this end point of 1.19  for fixed effects and 1.22 (95% CI: 1.01 to 1.46) for random effects meta-analysis compared to those with normal or increased function CYP2D6 alleles , individuals with any copy of a reduced function  alleles S8.CYP2D6 allele was associated with meeting a surrogate endpoint for overall survival  as well as non-fatal recurrence   was RR 1.12; 95% CI: 0.89 to 1.40 and for overall survival/all-cause mortality  it was RR 1.11; 95% CI: 0.95 to 1.29) S6. Carrto 1.54) S6.CYP2D6 genotype according to patient ethnicity, concomitant therapy, breast cancer stage/grade and menopause status, none of the subgroup analyses surpassed our a priori Bonferroni-adjusted P-value threshold of <0.002 . Although there was a suggestion of a differential association of f <0.002 .The funnel plots for the three composite outcomes appeared symmetrical S10, supCYP2D6 alleles and composites outcomes in patients treated with tamoxifen, the point estimate for two reduced function CYP2D6 alleles was consistently of greater magnitude than for one copy in each of the three composite outcomes, however the 95% CI were wide and there was no evidence for a trend on formal statistical testing   1.Of 25 potentially eligible studies, three were trials with participants randomized to tamoxifen or a comparator group 1. One oCYP2D6*4 reduced function allele was 0.18 (95% CI: 0.05 to 0.61) for tamoxifen compared to no tamoxifen, whereas for individuals with the normal CYP2D6 allele (*1/*1), the corresponding OR was 0.96 (95% CI: 0.45 to 2.04). A test for interaction yielded evidence for effect modification (P=0.02)  2. HowevCYP2D6 allele was 1.05 (95% CI: 0.72 to 1.52), and for individuals with normal function CYP2D6 allele, it was 1.26 (95% CI: 0.94 to 1.69), with no evidence for effect modification (P=0.44) (CYP2D6 genotype and tamoxifen therapy for the adverse outcome of hot flush (P=0.52)  2. There(P=0.52) 2.CYP2D6 genotype, as the comparator groups used and the outcomes reported were different in the two trials.It was not possible to provide a pooled summary estimate for the effect of tamoxifen versus comparator group stratified by CYP2D6 genotype and clinical outcomes following tamoxifen treatment for breast cancer. A total of 25 studies were identified comprising 13,629 patients with breast cancer adding to prior meta-analyses [CYP2D6 genotype status.We investigated the evidence base on the association between analyses ,24 by inCYP2D6 allele had a higher risk of an adverse outcome than individuals with normal/increased function CYP2D6 alleles. In the analysis of the individual outcomes, we did not identify an association between CYP2D6 genotype and mortality, but did find an association between CYP2D6 genotype and surrogate endpoints for overall survival . Although it was not possible to pool information from the treatment trials in the effect-modification analysis, because of the different comparator arms, neither trial individually provided support for the hypothesis that carriage of reduced function CYP2D6 alleles modified the treatment response to tamoxifen, regardless of whether the comparator was a placebo or letrozole (a drug that is not considered to be metabolized by CYP2D6) [In the treatment-only analysis for all-cause mortality, the point estimate was consistent in direction with that expected from the hypothesis that reduced tamoxifen metabolism is associated with a poorer outcome but the confidence limits were wide and included the null value (of RR=1). When we used a less stringent composite outcome encompassing all-cause mortality and surrogate endpoints for overall survival , individuals carrying any copy of a reduced function  CYP2D6) . However CYP2D6) . Taken tCYP2D6 genotype with surrogate endpoints for overall survival  on the treatment-only analysis is worthy of discussion. Controversy exists on the validity of using surrogates when evaluating cancer treatments [The association of eatments . For deceatments . Howevereatments –32. Impoeatments . Criticieatments  and thateatments .CYP2D6 allele versus none) that aimed to simplify the genetic comparison, which allowed us to include all studies in the analysis. Although the outcomes reported did differ considerably between studies, our approach was to generate composite outcomes to pool the individual outcomes reported across studies to maximize power. Because use of composites may obscure associations with individual constituents, we also investigated the association of CYP2D6 genotype with individual outcomes.This systematic review and meta-analysis has several limitations that are worthy of comment. First, the lack of trials available for the effect modification analysis and differences in the treatment regimens and outcomes reported in the trials meant that we could not conduct a meta-analysis of effect modification analyses. However, the largest trial provided no evidence for effect modification. Second, we used aggregate rather than participant data, which meant we were limited in the precision with which we could conduct subgroup analyses and our ability to homogenize the genotype comparisons or outcomes reported. In an attempt to address this, we used a genetic analysis model , the associations between CYP2D6 genotype and surrogate endpoints for overall survival that we identified should be interpreted with caution.Our systematic review is timely and an important addition to recent findings from two large clinical trials ,22 that t ensued ,35,36. FCYP2D6 genotype and surrogate endpoints for overall survival, we did not identify an association between CYP2D6 genotype and tamoxifen response for all-cause mortality or overall survival. The current evidence does not support the use of CYP2D6 genotyping to guide tamoxifen prescribing for the treatment of breast cancer.Despite a weak association between Text S1Supplementary Methods.(PDF)Click here for additional data file.Table S1CYP2D6 alleles.Nomenclature for the CYP2D6 phenotype predicted from (PDF)Click here for additional data file.Table S2Contribution of included studies from the systematic review to each of the composite outcomes.(PDF)Click here for additional data file.Table S3Clinical and genotype characteristics of the 25 studies included in the systematic review.(PDF)Click here for additional data file.Table S4Participant, genotype and treatment characteristics of the 25 studies included in the systematic review.(PDF)Click here for additional data file.Table S5Breast cancer characteristics of the 25 studies included in the systematic review.(PDF)Click here for additional data file.Table S6Meta-analysis pooled estimates for the composite and individual outcomes comparing fixed and random effects models.(PDF)Click here for additional data file.Table S7Risk of bias in the two randomized trials that conducted an effect modification analysis.(PDF)Click here for additional data file.Figure S1Metabolism of tamoxifen by the hepatic cytochrome P450 (CYP) enzymes and the mechanism of the endoxifen (4-hydroxy-N-desmethyl-tamoxifen) metabolite in breast cell growth inhibition.(PDF)Click here for additional data file.Figure S2Generation of the composite outcomes from outcomes reported in the studies identified from the systematic review.(PDF)Click here for additional data file.Figure S3PRISMA flow diagram for systematic review of the association of CYP2D6 genotype and tamoxifen response in breast cancer patients.(PDF)Click here for additional data file.Figure S4Unique outcomes reported by studies and the grouping into main outcomes for analyses.(PDF)Click here for additional data file.Figure S5CYP2D6 * alleles.Proportions of 13,629 individuals in the 25 studies that were genotyped for the 36 (PDF)Click here for additional data file.Figure S6CYP2D6 allele versus none for the risk of all-cause mortality.Meta-analysis (fixed and random effects models) of the association of any reduced function (PDF)Click here for additional data file.Figure S7CYP2D6 allele versus none with the composite outcome of all-cause mortality and surrogate endpoints for overall survival .Meta-analysis (fixed and random effects models) of the association of any reduced function (PDF)Click here for additional data file.Figure S8CYP2D6 allele versus none with the composite outcome of all-cause mortality, surrogate endpoints for overall survival  and non-fatal events.Meta-analysis (fixed and random effects models) of the association of any reduced function (PDF)Click here for additional data file.Figure S9CYP2D6 allele versus none for the composite outcome of all-cause mortality and surrogate endpoints for overall survival .Subgroup analysis of the association of any reduced function (PDF)Click here for additional data file.Figure S10CYP2D6 allele versus none for the composite outcomes.Funnel plot of any reduced function (PDF)Click here for additional data file.Figure S11CYP2D6 allele versus none for the composite outcomes.Influence analysis of any reduced function (PDF)Click here for additional data file.Checklist S1PRISMA checklist.(DOC)Click here for additional data file.


Alvar Agusti, MD, PhDWayne Anderson, PhDPer S. Bakke, PhD, MDKathleen C. Barnes, PhDR. Graham Barr, MD, DrPHEugene R. Bleecker, MDKristin M. Burkart, MD, MScBartolome R. Celli, MDMichael H. Cho, MDWilliam O.C. Cookson, MD, DPhilJames D. Crapo, MDThomas Croxton, MD, PhDDenise Daley, PhDDawn L. DeMeo, MD, MPHWeiniu Gan, PhDJudith Garcia-Aymerich, MDNadia N. Hansel, MD, MDPHCraig Hersh, MD, MPHNoor Kalsheker, MDJames P. Kiley, PhDWoo Jin Kim, MD, PhDDiether Lambrechts, MDSang-Do Lee, MDStephanie J. London, M.D., Dr.P.H.William MacNee, MB, ChB, MDMasaharu Nishimura, MDBorge G. Nørdestgaard, MD, DMScChristopher O'Donnell, M.D.Edwin K. Silverman, MD, PhDYohannes Tesfaigzi, PhDMartin D. Tobin, MDJørgen Vestbo, MD, DMScClaus Vogelmeier, MDJohn W WalshJemma B. Wilk, DScEmiel Wouters, MD, PhDRobert P. Young, MD, PhDLoems Ziegler-Heitbrock, MDREPORT AND RECOMMENDATIONS FROM CONFERENCE HELD JULY 13-14,2010, BOSTON, MASSACHUSETTS1 among smokers with similar smoking exposures (Chronic obstructive pulmonary disease (COPD) is defined by the Global Initiative for Chronic Obstructive Lung Disease (GOLD) as a disease state characterized by airflow limitation that is not fully reversible . Cigaretxposures , 3. The xposures , 5. In axposures . A smallWith the substantial impact of AAT deficiency on our understanding of COPD pathogenesis, it was natural to hope that the identification of other COPD susceptibility genes would lead to similar novel insights into COPD. Until recently, however, progress in the identification of additional genetic risk factors for COPD has been slow.To facilitate the development of such research, a meeting of COPD genetics investigators was held on July 13-14,2010 in Boston. The goals of the meeting were:To review the current state of COPD genetics research;To discuss existing study populations for COPD genetics research throughout the world;To consider opportunities for collaborations between different COPD research groups through an International COPD Genetics Consortium;To recognize challenges in building COPD genetics collaborations and to discuss them openly; and,To develop a framework for future collaborative studies.Many candidate gene association studies have been performed over the past 40 years, but the results have been largely inconsistent. These inconsistencies likely relate to a variety of methodological issues, including small sample sizes, variable definitions of case and control groups, failure to adjust for multiple statistical testing, and inadequate adjustments for population stratification and smoking exposure. Most of the studies describing COPD-associated polymorphisms were performed in White populations . A meta-Another factor likely impeding the progress of identifying COPD susceptibility genes is the lack of accurate phenotypic characterization of this complex and heterogeneous disease. Airflow limitation determined by spirometry has been the most common approach to classify and monitor the disease. Structural changes of the lung including emphysema and small airway obstruction are the primary processes that affect lung function , but theHHIP gene, on chromosome 4 in the FAM13A gene, and on chromosome 15 in a block of genes which contains several components of the nicotinic acetyl-choline receptor as well as the IREB2 gene.Perhaps the greatest problem in the candidate gene era of COPD genetic studies was improper candidate gene selection, which reflects our limited understanding of COPD pathogenesis. However, the application of genome-wide association studies (GWAS), which provide an unbiased and comprehensive search throughout the genome for common susceptibility loci, has changed the landscape of COPD genetics. Based on GWAS, three genetic loci have been unequivocally associated with COPD susceptibility, located on chromosome 4 near the CHRNA3/CHRNA5/IREB2 region to COPD  ((HHIP) ((FAM13 A)  , 19, chr ((HHIP) , 21, andFAM13 A) . Thus, t and a nicotine-metabolizing enzyme , with studies of smoking behavior and addiction, and studies of diseases characterized by compromised lung function .Fine mapping of selected loci to identify functional variants will be necessary. This will include statistical approaches such as multiple regression as well as additional genotyp-ing. The particular importance of including ancestral groups of non-European origin in these analyses is noted, in order to use their differences in linkage disequilibrium patterns to break up linkage disequilibrium blocks, and to demonstrate generalizability of variants associated with COPD to the population at large.Next-generation DNA sequencing approaches have the capacity to discover highly penetrant rare variants in common diseases such as COPD. Limiting sequencing to the ex-ome greatly reduces costs compared to whole genome sequencing approaches, while retaining much of the information that is likely to lead to the identification of disease-related rare variants. Although the value of exome sequencing has not yet been established in complex genetic diseases, it is desirable to explore the use of exome sequencing to search for rare mutations in patients with severe spectrum disease, including non-smokers with COPD as a separate group.Genomic studies allow systematic investigation of pathways and networks of gene functions underlying disease . InvestiLastly, it is now possible to quantify bacterial colonization of airways using DNA and RNA sequencing techniques that address the hyper-variable bacterial 16S gene as well as metagenomic approaches that examine the global gene content and gene expression of human bacteria . It is tPrecise definition and validation of clinical phenotypes are key prerequisites to identify the genetic basis of complex diseases, since a principal goal of genetic research is to identify specific genotypes that link to specific phenotypes , 31. FroThe degree of airflow limitation remains the defining characteristic of COPD and thus its most important pheno-typic expression. However, there is sufficient evidence to support the need to consider additional phenotypic expressions in the characterization of patients with COPD. These include: 1) the degree, type and distribution of emphysema (discussed below); 2) the extent of airway wall thickening caused by inflammation; 3) the degree of hyperinflation expressed by the IC and the IC/TLC; 4) the presence of abnormal gas exchange (hypoxia and hypercapnia); 5) the presence of systemic involvement as measured by the BMI; 6) the exercise capacity whether measured in the laboratory (peak oxygen uptake) or in the field ; and 7) the degree of functional dyspnea. These characteristics can practically be integrated into multidimensional tools such as the BODE index capable of providing a more comprehensive evaluation of COPD subjects . The detThe study of COPD phenotypes is relevant to disease etiology, pathophysiology, and treatment. The identification of clinically relevant phenotypes would change the present view of COPD as a unique multicomponent disease , 36 to aThe use of chest CT scans for determination of lung density was first described in the 1980s as a measure of the degree of emphysema in COPD . An impoA more recent approach is the assessment of the thickness of the airwaywalls in order to determine the degree of airway remodelling. This was initially applied to asthma and more recently also to COPD . This apAn important issue for multicenter trials is standardization of CT measurements across different clinical centers. Here the different brands and models of CT scanners, which use different scanning technologies, scanning protocols, and different algorithms for data processing, can affect the lung density and the airway wall results. Careful standardization including the use of phantoms for all scanners is required in order to be able to compare results. In spite of these problems, it maybe possible to obtain data on CT-assessed emphysema which could be compared in a multicenter study.At the Boston meeting, 38 study populations which included spirometric assessment of COPD and DNA sample collection were reviewed . These sUsing the reported definitions of COPD and non-COPD from each study, there are approximately 39,600 COPD cases and 131,600 control subjects in the combined set of case-control and population cohort studies . In thesAt the Boston meeting, the participants identified multiple advantages of creating a COPD genetics research consortium, and strongly endorsed this approach. Larger sample sizes of cases and controls will definitely increase power to detect COPD susceptibility loci. The potential to assemble large numbers of severe COPD subjects that are clearly affected is a major advantage, since relatively small numbers of severely affected subjects have been included in most individual studies. Similarly, the opportunity to perform pooled analyses of chest CT phenotypes was seen as a major strength, as long as the technical challenges of different CT scanning and analytical protocols can be overcome. Opportunities to study other COPD-related phenotypes, including COPD exacerbation frequency, lung function decline, and lung cancer, were also recognized. Although many of the participating studies do not yet have genome-wide SNP genotyping, these studies provide opportunities to replicate initial GWAS findings in large numbers of additional subjects. In addition to studies of main genetic effects, a large COPD genetics consortium would improve the statistical power to study gene-by-environment interactions.Although the studies listed above could be performed in a fairly short time-frame, potential future advantages of a COPD genetics consortium were also appreciated. Such a consortium could provide a framework for future genetic collaborations in exome sequencing and whole genome sequencing, as well as in other genetic/genomic areas . There would likely be increased standardization of study protocols and procedures for future studies  and the potential for collaborative studies of non-genetic issues . Limiting duplication of research effort could likely be accomplished as well. Overall, there was general consensus that a COPD genetics consortium would have a high likelihood of significantly advancing knowledge in the field.In addition to these advantages of forming a collaborative consortium, a variety of challenges were identified. It was recognized that there are academic realities including the need for individual research groups to demonstrate academic productivity to renew funding and promote research personnel. Some COPD genetics collaborations already exist, and a goal was not to interfere with those existing relationships. Although studies that include reasonable numbers of COPD cases and control subjects could be analyzed individually and combined using meta-analytical approaches, the optimal approach for utilizing studies of COPD cases only or controls only was not as clear.A variety of challenges related to phenotypic characterization were also identified. Substantial variation exists in the definitions of cases and controls between studies , as well as in spirometry protocol . Some pheno-types  maybe difficult to combine across studies due to technical issues. There are important variations in study populations  and genetic analysis approaches .Despite these challenges, there was general agreement that the advantages of collaboration far outweighed the limitations, and that a transparent and open collaboration could overcome most of the challenges. To be successful, the needs and rights of each contributing study will need to be respected. Based on the enthusiastic support for an international COPD genetics consortium from the Boston meeting participants, the research projects amenable to this consortium approach and an organizational structure for the consortium were discussed.Although the development of large consortia of thousands of subjects may obviate some of the issues that have contributed to non-replication of previous COPD genetic studies , the inclusion of data from a large number of studies presents unique challenges and opportunities.Despite the challenges of disease gene discovery in complex disease, there are some striking advantages to studying the genetics of COPD (COPD strictly being a syndrome not a specific disease). First, one of the most important features of studying the genetics of COPD is that the key environmental exposure of cigarette smoking is known and quantifiable in the setting of a gene-by-environment interaction. In contrast to most other complex diseases, the majority of COPD can be attributed to a single exposure (cigarette smoking) which can be crudely quantified, by intensity (cigarettes/day) and/or total exposure (pack-years), across both cases and controls in geographically diverse populations. The central role of smoking exposure in genetic susceptibility is illustrated by the divergent outcomes in people with alpha-1 antitrypsin deficiency based on their smoking history .1 and FEV1/FVC ratio), which can be measured by simple spirometry in population studies. From an epidemiological perspective, FEV1  provides a good starting place from which to define COPD, as it is a highly heritable trait , and the importance of defining disease subtypes. In addition, not all studies have performed pre- and post-bronchodilator spirometry, and many studies have not been sufficiently resourced to undertake chest CT scanning to phenotype COPD pathologically. Even in the presence of post-bronchodilator spirometry, issues of spirometric diagnosis of COPD based on using GOLD criteria versus lower limit of normal may contribute to phenotypic heterogeneity. This is likely to be minimized in those case-control studies comparing more extreme (susceptible vs resistant) phenotypes where misclassi-fication of cases or controls based on variation in spirometry-based definition is likely to be minor. However, severity of COPD is an issue that needs careful consideration given the strong association between aging and loss of lung function. Moreover, it is noted that a spirometric diagnosis of a resistant smoker does not obviate some misclassification as smoking-related emphysema may be present despite normal spirometric measures.A major strength of this consortium will be the availability of data from both spirometry and CT scans of the lungs for parsing subjects by emphysema status . Although CT scanning presents challenges , computerized approaches to process and analyze chest CT scans may be useful in harmonizing CT scan data, and will likely assist in refinement of COPD subtypes.Although the inclusion of data from Caucasian, African, Native American, and Asian subjects may lead to false positive and/or false negative association findings due to population substructure, contribution of all subjects’ data to the power of the overall analysis, and to the race-specific genetic association analyses of COPD, are major strengths of performing a multi-ethnic consortium. There are many existing examples of disease associations confined to specific ethnic groups. Primary analyses would be conducted within each ethnic group, followed by comparison of association results between groups.Although the inclusion of many studies of COPD may increase the power due to an increase in total subject number, presently a minority of COPD studies have GWA data. Given the large burden of disease accounted for by COPD, this void of GWA data in and of itself supports the importance of efforts to accrue more GWA data. The consortium will include GWA data on both population-based cohorts and case-control studies. In the population-based cohorts, the contribution of genetic variants on lung function can be explored in settings other than chronic smoking.There is a need for more GWA data in case-control studies, where smoking has been accounted for and other important exposures have been examined. Case-control studies can also allow investigation of the role in disease of variants shown to be associated with lung function in population-based studies. The case-only studies can be added to the case-control studies in a mega-analysis of individual genotype and phenotype data, or in circumstances where data can be combined or compared with the controls derived from other studies. The consortium is also fortunate enough to have large prospective studies in which the genetic determinants of rate of decline in lung function (or other aspects of disease progression) can be studied; this could be insightful, for example, for those variants shown to be associated with COPD or cross-sectional lung function measures.Other study-specific issues include variations in enrollment criteria, age ranges of subjects, and rates of co-morbid conditions including obesity which may affect lung function. Of these, variations in smoking history (described above) and current smoking status are potentially the most essential, as some of the COPD studies had minimum amounts of smoking exposure required for eligibility, and include a mix of current and former smokers. Given that gene-by-smoking interactions are crucial to include in genetic analyses , 51-53 tFor genetic studies there is likely enrichment in genetic effects in those subjects who develop COPD at a very young age as well as those smokers who remain resistant to both COPD and emphysema at very old ages. Associations will need to be re-examined with stratification by age of disease onset, total pack-year exposure and current smoking status where the data are known.Variable rates of comorbidities in the different COPD studies may impact genetic associations with lung function (such as the association of diabetes with lower lung function) but the inclusion in genetic analysis of the most diverse group with COPD may increase the likelihood that positive associations are true positive findings.in silico tools allow for the development of a larger study population less constrained by choice of genotyping technology. In addition to the genotyping platform, approaches to data cleaning may vary between bioinformatics groups. However, a harmonized approach to data cleaning is mandatory.As has been the challenge in other complex diseases such as diabetes, the platforms used for genome-wide genotyping have varied. There is variable inclusion of SNPs leading to differential coverage of genes on a given platform. However, this reality has led to the availability of imputation methods to overcome the differences between GWA arrays; these novel The protection of human data and subject privacy is paramount and the ability to share individual level genotype results maybe limited. Thus, the performance of “mega-analysis” in which individual-level genotype and phenotype data would be shared, though remaining a worthwhile eventual goal, was judged not to be essential to progress at this time. However, meta-analytic approaches that use study-wide association data  weighted by study size or by inverse variance have been shown to be as powerful as mega-analysis approaches that utilize subject level data . Thus foA preliminary design for the initial collaborative genetic association meta-analysis for the consortium was created at the Boston meeting. Two key genome-wide association analyses were proposed: 1) All COPD vs. Controls, and 2) Severe COPD vs. Controls. The precise definitions of All COPD and Severe COPD remain to be determined. Within each study population that has existing genome-wide SNP geno-typing data, standard quality control approaches will be used to clean the data, including criteria for exclusion of SNPs with low call rates, low minor allele frequency, departures from Hardy-Weinberg equilibrium, and differential rates of missing data between cases and controls, and exclusion of individuals with low call rates or exhibiting cryptic relatedness among unrelated samples.Standard approaches to genotype imputation will be applied in each study, followed by a similar approach to population stratification adjustment within each study using adjustment with principal components for genetic ancestry. Genome-wide association analysis for the two COPD affection status phenotypes  will be performed within each study, with separate analyses in subjects of Caucasian, Asian, and African ancestry. Meta-analysis of GWAS will be performed within each major racial group using inverse variance weighted meta-analysis methods to account for differences in sample size and imputation quality across genotyping platforms, followed by comparison of association evidence between major racial groups. Finally, replication genotyping and association analysis of the most interesting SNPs will be performed in the remaining study populations without genome-wide SNP data.The mandate of the International COPD Genetics Consortium is to find common and rare genetic determinants of COPD; to identify COPD subtypes and their genetic basis; and to use this information to develop new disease classifications and therapeutic interventions. Based on the discussions at the Boston meeting, it was recommended that research studies including COPD and control subjects would be invited to participate if they collected high quality spirom-etry data and DNA samples, and if the study met a minimum sample size. The expectation is that the studies will include at least 200 COPD cases and 200 controls, but review of specific studies is possible if those criteria are not met. For studies that include case-only collections, they would be encouraged to find appropriate sets of control subjects for genetic association analysis; if not available, those COPD study populations could be included in studies of COPD progression or CT subtypes. Study populations meeting these criteria that were not represented at the Boston meeting will be welcome to join this international collaborative effort.Several committees will be created to perform the consortium research and administration, including a Steering Committee (in charge of major decisions); Planning/Executive Committee (routine operations); Phenotype Harmonization; Imaging Committee; Genotyping and Genomics Core; and Analysis Core.The International COPD Genetics Consortium has the potential to provide short-term results by providing highly powered genome-wide association studies of COPD susceptibility, and long-term results by facilitating the study of other COPD-related phenotypes and other genomic outcomes. Organization, resources, and communication will be essential to realize this potential.Create the International COPD Genetics Consortium (ICGC) - to be open worldwide to include all study populations meeting minimum criteria for size, spirometric data, and DNA availability.Mandate of the ICGC is to:Use pooled resources to define rare and common genetic determinants of COPDIdentify COPD subtypes and their genetic basisDevelop new disease classifications for COPDFoster development of new therapeutic interventions that are subtype or disease classification specificRecommended committee structure:Steering Committee (with oversight of major decisions)Planning/Executive CommitteeImaging CommitteePhenotype Harmonization CommitteeGenotyping and Genomics CoreAnalysis CoreGenerating new GWAS/genotyping/sequencing/gene expression dataExpand and extend existing and ongoing genetic analysis projectsPlans for genetic analysisInitial meta-analysis focused on common definitions of case status and on extreme phenotypesCommon standardized quality control approaches to clean dataStandard approach for data analysisSeparate meta-analysis for each racial and ethnic groupReplication in study populations not having genome-wide SNP dataData sharingOptimize data sharing while protecting privacy and personal health information


It is well established that drinking alcohol raises the risk of liver cancer (hepatocellular carcinoma). However, it has not been sufficiently established as to whether or not drinking cessation subsequently reduces the risk of liver cancer and if it does reduce the risk how long it takes for this heightened risk to fall to that of never drinkers. This question is important for effective policy design and evaluation, to establish causality and for motivational treatments.A systematic review and meta-analysis using the current available evidence and a specific form of Generalised Least Squares is performed to assess how the risk of liver cancer changes with time for former drinkers.Four studies are found to have quantified the effect of drinking cessation on the risk of liver cancer. The meta-analysis suggests that the risk of liver cancer does indeed fall after cessation by 6-7% a year, but there remains a large uncertainty around this estimate both statistically and in its interpretation. As an illustration it is estimated that a time period of 23 years is required after drinking cessation, with a correspondingly large 95% confidence interval of 14 to 70 years, for the risk of liver cancer to be equal to that of never drinkers.This is a relatively under researched area and this is reflected in the uncertainty of the findings. It is our view that it is not possible to extrapolate the results found here to the general population. Too few studies have addressed this question and of the studies that have, all have significant limitations. The key issue amongst the relevant studies is that it appears that current drinkers, abstainers and former drinkers are not composed of, or effectively adjusted to be, similar populations making inferences about risk changes impossible. This is a very difficult area to study effectively, but it is an important topic. More work is required to reduce both statistical uncertainty and tackle the various study limitations this paper highlights and until this is done, the current result should be considered preliminary. Liver cancer was again replaced with ICD 10 code C22 in another search. The search was initially performed in PUBMED and MEDLINE.The following exclusion criteria were applied; (1) the study was not published in English; (2) the study was not performed on humans; (3) the study was not designed to capture data on alcohol cessation (ex-drinkers) or did not distinguish between lifetime abstainers and former drinkers ; and (4) the study did not investigate cancer of the liver.The search initially yielded 44 articles in PUBMED and MEDLINE. Inspection of abstracts narrowed it down to 15 articles potentially relevant to the current study area. These articles were read in full and the reference lists were searched manually. Complementary search was done in ERIC, CINAHL, Google scholar and Google. In all, eleven relevant articles were obtained that met the set criteria (above) to be included in the review and are summarised and compared in Additional file et al.)[Five relevant studies were identified by the systematic review that quantified the risk impact on liver cancer of drinking cessation and the duration of drinking cessation. In two studies ,8 the saInformation extracted from selected articles includes but is not limited to; country and study years, study type, sample size, age, gender specific calculations, statistical methods, whether incidence of liver cancer was confirmed by histology, definition of a former drinker and risk estimates with confidence intervals  of liver cancer as this is the most appropriate for the cost of alcohol literature. However, some studies report odds ratios (ORs) and others present hazard ratios (HRs). At low prevalence levels it can be assumed that RR, OR and HR are approximately equal. Due to the nature of liver cancer and its low prevalence amongst the population all measures will be treated as ORs. This allows for greater mathematical ease whilst still allowing the interpretation in terms of relative risks.et al.[The problem of bias amongst published studies, in particular the issue of publication bias, is considered through the utilisation of funnel plots of the data, with current drinkers as the reference group. This is a helpful tool although other interpretations other than publication bias are not excluded. See Egger, M. et al. for a coet al.[In traditional meta-analysis the risks are weighted by the inverse of their variance (Weighted Least Squares) with the assumption that the variances are independent. However, it cannot be realistically assumed that the variance of the odds ratios by duration are independent when they are all estimated using a common reference group within each study. Ignoring this underestimates the variance of the slope and consequently will lead to spurious accuracy of reported standard errors. A proposed strategy to deal with this is suggested by Greenland et al. whereby In estimating the trend of years since cessation of alcohol (dose) and the log risk of liver cancer, additional explanatory variables will be utilised including a squared term to test whether a nonlinear association between log odds ratio of liver cancer and duration of alcohol cessation exists as well as controls for heterogeneity between and within studies. This approach is called the "fixed effects meta-regression" model, which assumes that each study is estimating the same underlying trend. After controlling for study specific differences, the errors are assumed to have a zero mean distributed with normal variance:it is a t × k matrix of k covariates for study i, dose period t. When applying the fixed effects meta-regression model using GLS on dose-response data a test for heterogeneity is the Q test:Where β is a k × 1 vector of coefficients and Xet al. in the GLS estimate[where Σ is the estimated variance covariance matrix estimated using the method proposed by Greenland  estimate. This is estimate.This section focuses on the results of the meta-analysis. The results should be considered preliminary due to the limited available evidence in this area. The results of the systematic literature review are presented in Additional file Figure Table Models 4-6 are applied to the data where former drinkers who have just quit (shortest recorded cessation period) are used as the reference group and all other former drinker categories of longer duration are compared to this group. Structural heterogeneity and/or influences on the trend estimate of risk decline of liver cancer after drinking cessation are explored. Model 4 is a simple regression of dose and log risk and finds a reversible effect of drinking cessation on the risk of liver cancer. It is not clear that there is a non-linear relationship between the log odds ratio of liver cancer and duration of alcohol cessation because including a second polynomial makes the linear dose term non-significant (results not shown). The second polynomial is therefore dropped. Gender no longer has a structural impact on the estimates which is not surprising given the very small samples of the female estimates (again results not shown). Only the dummy "Radiation" is significant. The "study characteristics" dummy is tested to see if it influences the trend. There is no evidence that the trend estimates are different between study types. The results from models 4-6 all show consistent trend estimates and indicate no measureable between study heterogeneity as per the Q statistic suggesting this is a robust relationship and a common trend exists between the studies.Table Across all of the studies two types of study design were used, either case-control or prospective cohort. All of the eleven studies found in the systematic review show that the risk of liver cancer just after alcohol cessation is either the same or higher compared to current drinkers. Given the detrimental effect of alcohol, an a priori expectation was that the risk would be lower after cessation, all else equal.Due to the nature of case-control and prospective cohort studies, matching of treatment and control groups and/or controlling for confounding factors such as smoking, diabetes and past drinking habits (and other factors known to have an influence on risk of liver cancer) are important to ensure the effect of alcohol cessation is being isolated. Indeed some of the studies presented in the systematic review show that smoking matters and that there is an interaction effect between smoking and alcohol consumption, but no However, beyond showing that various factors increase the risk, none of the studies presented here control for all of them when considering the time effect of alcohol cessation on liver cancer. It is therefore not clear that these studies are able to isolate the average treatment effect of alcohol cessation on the risk of liver cancer. The design of the studies and the lack of effective controls for confounding factors (possibly as a consequence of lack of focus on the question at hand) are likely to bias the end results. It means that the reader cannot be sure whether there is a real relationship between the observed risk of treatment and control groups or whether this is due to some other unobserved or uncontrolled for factors.before cessation would be higher than for the general group of current drinkers, and the increase in risk after cessation is an artefact of poorly matched groups. This is something that could have been controlled for but none of the studies presented any information on this. There are also reasons to doubt that for some of the studies the choice of control group is a reasonable representation of the population. Some of the studies removed certain individuals from the control groups who had past history of liver disease or certain illnesses making the risk of liver cancer in the control groups artificially low (see appendix 1 for details). There is not enough information about the control and treatment groups to test whether there are any important systematic differences between them that may explain why an increase in risk is observed for just quitters compared to current drinkers but serious doubts remain about how well they have been matched. There is also not enough information to assess how well either the control or treatment groups represent the wider population to be able to make an assessment of the external validity of the results. This implies that the results of the included studies and thus also this meta-analysis have a limited interpretation to that of the studied samples. The wider implications for the general population are debatable.The problem is particularly acute here where the medical assumption of reversibility would predict a lower risk of cancer post cessation of alcohol compared to current drinkers if both groups being compared are representative of the population, yet what is observed is that just quitters have a higher risk of liver cancer than current drinkers. Prior studies have found that "former drinker" categories are often over-represented by former heavy drinkers and alcoholics. If thisIn order to account for this uncertainty and summarise the current position of the literature, a preliminary meta-analysis has been performed on two different forms of the same data to assess if there was any correspondence between the studies on the shape of the dose-response relationship of alcohol cessation and liver cancer. The first uses current drinkers as the reference category and calculates the dose-response relationship assuming current drinkers are the relevant reference group. The second deals with the potential overrepresentation of former heavy drinkers in the cessation group and uses just quit drinking as the reference category. Although this has the downside of reducing the sample size, it was expected to allow for a more accurate calculation of how risk declines after cessation of alcohol consumption.The results where current drinkers were used as the reference group found only that recent quitters have much higher risk of liver cancer than current drinkers. Using former drinkers who had just quit as the reference group found a statistically significant downward trend in risk of liver cancer over time post cessation. This is the preferred estimate as it appears that it is based on a much better match between treatment and control groups. To answer the question at hand it is paramount that both treatment and control groups are representative of each other. If they differ in a significant way that biases the results it is impossible to draw robust conclusions about how risk changes after cessation of alcohol consumption. It seems that former drinkers in these studies have worse health than current drinkers and given that all of the former drinkers in these studies were at one time "just quitters" it then appears more sensible to use just quitters as the preferred control group. The rate of risk decline using just quitters as the reference group is quite robust to specification and common across the studies.By way of illustration, the findings from the meta-analysis tentatively suggest that for each year of cessation the risk of liver cancer declines by about 6-7% i.e. there is exponential decay. In order to calculate the length of time until increased risk of liver cancer has fallen to that of never drinkers, the relative risk of former drinkers compared to never drinkers is required. To ensure internal consistency of the estimates , supplementary meta-analysis, not shown here, finds that the average odds ratio between just quit drinking and never drinkers is 0.19, significantly different from 1. Using the results from model 6 to illustrate what the current evidence suggests, it is estimated that it would take about 23 years  for the risk of liver cancer of quitters of alcohol to fall to that of never drinkers. This illustrative example based on the meta-analysis is shown diagrammatically in Figure The rate of risk decline estimated here has great statistical uncertainty. It is also difficult to interpret, as the interpretation depends on whether the trend is the same for all groups or varies by key factors e.g. smoking, past alcohol consumption patterns, gender and age. The current extent of the literature means it is not known if this trend does vary by these key factors. It appears that the trend estimate found here is for a subgroup of the population but it is not possible to say what this sub-population looks like. There is indicative evidence that the treatment groups appear to be dissimilar to current drinkers and exhibit the patterns observed in heavy drinkers. Due to these issues, the results presented here should be interpreted with caution.Many questions remain and more research is needed in this important area. Future research looking into the cessation effect of alcohol consumption on liver cancer will need to consider more seriously how well matched their treatment and control groups are, especially with regard to behaviours and factors associated with liver cancer outcomes. Care also needs to be taken in allowing interpretation of the external validity of the findings, either by controlling for characteristics so that broader conclusions can be drawn or by using sampling in a way that more accurately represents the wider population. The question at hand here also requires a long follow up as it is indicated in this study that the rate of decay in risk occurs over a substantial time period.Given the difficult nature of studying alcohol intake's effect on human outcomes and the difficulty of separating the choice from the chooser, an effective study may need to make use of a policy experiment rather than just observe people's behaviour. The policy would have to be aimed at reducing intake of alcohol. An experiment large enough with a well matched and representative control group, ideally chosen at random would present both the ability to effectively assess the effectiveness of the policy and the effect of reduced alcohol intake on various outcomes (if the policy was effective of course).The authors report no conflicts of interest with people or organisations that could inappropriately influence the work. The authors did not receive any outside assistance writing this manuscript.BA carried out the initial systematic literature review and drafted this particular section of the manuscript. GH independently verified the findings of the literature review, performed the statistical analysis and drafted the manuscript. JJ and UG participated in the conception and design of the study and participated in the write-up of the manuscript. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2407/11/446/prepubDetailed findings from the systematic review. A descriptive overview of the current literature examining the effect of alcohol cessation on liver cancer, including the raw data used in the meta-analysis.Click here for file


Compared with TT homozygotes, the restenosis risk was significantly increased in the carriers of the C allele . Subsequent stratified analysis revealed that the frequency of the C allele was significantly higher in the male ISR group than in the male NISR group . The restenosis risk was ∼four-fold higher in the C carriers (CC+TC) than in the TT homozygotes . However in the female population, there was no difference in the ISR risk between the carriers of the C allele (CC+TC) and the TT homozygotes (P=0.70). In summary, the C allele of the connexin37 gene is not only is associated with the susceptibility to CAD, but also associated with restenosis following coronary stenting in the population studied herein, particularly the male population.Studies have shown that a C1019T polymorphism of the gene encoding the gap junction protein connexin37 is associated with coronary artery disease (CAD). The aim of the present study was to explore the association between the C1019T polymorphism in the connexin37 gene and CAD patients with in-stent restenosis (ISR). A total of 532 patients who had undergone coronary stenting and coronary angiography at least three months after the procedure were divided according to a clinical diagnosis standard into two groups which were ISR (n=67) and no in-stent restenosis  groups. A further 501 healthy individuals were controls. The subjects were genotyped by DNA sequencing. The results demonstrated the following: i) connexin37 gene 1019 sites in the population were distributed by polymorphism into three genetic types . The distribution frequency of the healthy control, ISR and NISR groups conformed to the Hardy-Weinberg genetic balance rule; ii) in comparison with the healthy controls, the frequency of the connexin37 C allele was higher in the CAD patients . The frequency of the C carriers (CC+TC) was 65.47% in the healthy controls, vs. 79.32% in CAD patients (P<0.01). The CAD risk was significantly increased in the carriers of the C allele (CC+TC) compared with TT homozygotes . Stratified analysis demonstrated that a significant difference existed in the frequency of C carriers between the male CAD patients and healthy controls , as well as in the female CAD patients . In the female and male CAD patients, the frequency of the connexin37 C allele was higher than in the healthy controls (male: χ Percutaneous coronary intervention (PCI) is well-established treatment strategy for coronary artery disease (CAD), particularly following the introduction of drug-eluting stents ,2. DespiConnexins are members of a family of proteins encoded by at least 20 different mammalian genes expressed in a wide variety of tissues –9. They et al identified a link between a single nucleotide polymorphism (SNP) in the human connexin37 gene and the thickening of the carotid in a Swedish male population  in various populations. However, whether such a polymorphism may be used as a prognostic marker of ISR following percutaneous coronary intervention, is not known. The present study was designed to investigate whether the connexin37 C1019T polymorphism is associated with restenosis following coronary stenting in the Han population of Wuxi City in China.This was a single-center, prospective observational study. A total of 532 Han Chinese patients who had undergone successful coronary stenting at the Cardiac Unit of Nanjing Medical University Hospital in Wuxi between 2009 and 2011 and returned for follow-up coronary angiography at least three months later  were selected. In particular, if clinical symptoms appeared , coronary angiography was performed at any time. All patients regularly received anti-platelet drugs , statins (types and doses determined by doctors) and other necessary drugs, such as angiotensin-converting enzyme inhibitor, β-blockers and nitrates, after the procedure. A further 501 healthy individuals from the medical examination center of the same hospital were the controls. No patients or controls were blood relatives. All participants gave written consent and the ethics committee of People’s Hospital of Wuxi City approved the study.Questionnaires were filled out to record basic information for each case , risk factors for restenosis  and family history of cerebrocardiac vessel disease. Information concerning disease onset, date of patient examinations during hospitalization and procedure-associated information were also collected.QCA was performed as described previously on images obtained before and immediately after stent placement and at follow-up using a computerized quantitative analysis system. The angiography was performed with at least two projections following an intracoronary injection of isosorbide dinitrate (0.2 mg). The tip of a 6F or 7F catheter filled with contrast medium was used for calibration. Restenosis was defined as a ≥50% diameter reduction in the dilated segment.μl reaction volume was used for PCR containing 10 μl 2X mix , 1.0 μl upstream primer (10 pmol), 1.0 μl downstream primer (10 pmol), 2 μl genomic DNA template  and 6 μl ddH2O. The reaction began with denaturation at 94°C for 5 min, followed by 35 cycles of denaturation at 95°C (30 sec), annealing at 60°C (30 sec), extension at 72°C (30 sec) and a final extension at 72°C (7 min). Genotype analysis was performed using DNA sequencing, which was completed by Ying-Jun Biological Company.DNA was purified from samples of whole white blood cells, which had been stored frozen at −20°C. Purification was performed using a DNA Purification kit  according to the manufacturer’s instructions. The polymerase chain reaction (PCR) was conducted with the upstream primer, 5′-CCTCCTCAGACCCTTACACGG-3′ and downstream primer, 5′-CATCCCAGGCAGCCAGACT-3′ . A 20-2 test. Data are presented as the mean ± SD or number . Continuous variables with a Gaussian distribution, as determined by the Shapiro-Wilk test, were compared by one-way analysis of variance (ANOVA) or t-tests. Categorical values were compared by the χ2 test. Continuous variables with a non-Gaussian distribution were compared by the Mann-Whitney U test. Analyses were performed using the SPSS statistical software . P<0.05 was considered to indicate a statistically significant difference.Allele frequencies were calculated by allele counting. Analyses for possible deviations of the genotype distribution from that expected for a population in Hardy-Weinberg equilibrium were performed with the χA total of 501 healthy individuals formed the control group and 532 patients were enrolled, 67 of whom developed ISR. The distribution of clinical and procedure-associated factors, including age, gender, body mass index (BMI) and hypertension, were not observed to be significantly different between the ISR and no in-stent restenosis (NISR) groups. Stent length, stent diameter and release pressure exhibited no differences between the ISR and NISR groups .The C1019T polymorphism of the connexin37 gene was detected in the whole population . The gen2=12.67, P < 0.01; female: χ2=50.20, P<0.01; . The frequency of C carriers (CC+TC) was 79.32% in the CAD patients and 65.47% in the healthy controls (P<0.01). The CAD risk was significantly increased in the carriers of the C allele (CC+TC) compared with TT homozygotes . Subsequent stratified analysis demonstrated that a significant difference existed in the frequency of C carriers between the male CAD patients and healthy controls , as well as in the female CAD patients . In female and male CAD patients, the frequency of the connexin37 C allele was higher than in the healthy controls  were significantly higher in the ISR group . Compared with TT homozygotes, the restenosis risk was significantly increased in the C carriers . Subsequent stratified analysis revealed that the frequency of the C allele was significantly higher in the male ISR group than in the male NISR group . The restenosis risk was ∼four-fold higher in the C carriers (CC+TC) than in the TT homozygotes . However, in the female population, no difference was identified in the ISR risk between the C carriers (CC+TC) and the TT homozygotes P=0.70;  and VII.et al of a northern Han population in China  or stent placement during PCI . Subsequ−/−ApoE−/− mice developed more aortic lesions than connexin37+/+ApoE−/− control mice, indicating that connexin37 was atheroprotective , this causes a nonconservative amino acid change in the regulatory C-terminus of the connexin37 protein, a proline-to-serine substitution (P319S) . This shIn conclusion, the present study indicates that the C allele in the connexin37 gene may not only be associated with susceptibility to CAD, but also with restenosis following coronary stenting, particularly in the male population.


IL-10) in SZ has been explored in a number of studies by investigating association of single nucleotide polymorphisms (SNPs) and susceptibility of SZ. However, the results are inconsistent since its power is limited by the individual sample size. To evaluate the overall effect between them, we conducted a meta-analysis by combining all available studies.The involvement of cytokines in schizophrenia (SZ) has been proposed in recent years and various studies have accumulated convergent lines of evidence. Among which, the role of interleukin-10 .P-value  = 2.06E-04). Meanwhile, among six haplotypes of rs1800896 - rs1800871 - rs1800872, significant associations were observed in haplotype A-C-A  and G-C-C  for Asians. These results were still significant after adjusting for multiple comparisons.Eleven studies including 6399 subjects (3129 cases and 3270 controls) were available for the meta-analysis. Among three investigated SNPs, rs1800872 was observed to be significantly associated with risk of SZ (AA vs. AC+CC, Pooled OR = 1.351, IL-10 significantly associated with SZ, suggesting that IL-10 might be a risk factor of SZ.This meta-analysis demonstrated an SNP and two haplotypes of  Schizophrenia (SZ) is a complex psychiatric disorder which affects approximately 1% of the population worldwide During these decades, researches from different areas have provided convergent lines of evidence for the involvement of cytokines in SZ. Comprehensive meta-analyses of clinical studies showed that compared with healthy controls, patients with SZ had significant inflammatory cytokine alterations IL-10) in SZ has been supported by a variety of evidence. IL-10 was an anti-inflammatory cytokine that regulates the inflammatory response, by inhibiting pro-inflammatory cytokine production IL-10 by macrophages attenuates behavioral abnormalities in a mouse model IL-10 levels were significantly decreased in acutely relapsed inpatients of SZ IL-10 levels were associated with severity of symptoms in SZ patients IL-10 level Among those investigated cytokines, the involvement of interleukin-10 (IL-10) in SZ has been explored in a number of studies by investigating association of single nucleotide polymorphisms (SNPs) and susceptibility of SZ IL-10 polymorphisms on SZ, a meta-analysis was conducted in the present study by pooling all available data together.Both clinical and epidemiological evidence has supported the cytokine imbalance hypothesis. With the emergence of the evidence, abundant genetic researches have been conducted to explore the genetic basis of this hypothesis. Among these cytokines, the role of interleukin-10  The database of PubMed, PsycINFO and ISI web of Knowledge were searched up to November 2013 using the following search terms: (“interleukin 10” OR “interleukin-10” OR “IL10” OR “IL 10” OR “IL-10”) AND “Schizophrenia”. Publication date and publication language were not restricted in our search. Reference lists and supplemental materials were also examined manually to further identify potentially relevant studies. Meanwhile, published genome-wide association studies (GWASs) about schizophrenia were also examined. Furthermore, we also contacted the authors to ask for original genotype data and related information if insufficient data were provided. If overlapped samples were used in different studies, we excluded overlapping samples or keep the study with the largest sample size.IL-10 polymorphisms and susceptibility of SZ were included. Moreover, studies had to fulfill all of the following criteria: 1) a case-control design comparing patients with SZ to controls without mental disorders; 2) patients were diagnosed with well-validated diagnostic criteria ; 3) controls were free of autoimmune or inflammatory diseases; 4) original data of genotype frequencies were published or provided by the authors. Studies were excluded if one of the following existed: 1) studies used family-based or cohort design; 2) samples were cases only; 3) genotype frequencies were neither published nor provided; 4) information is still insufficient for the meta-analysis even after requesting from authors.Studies aiming to examine the association between All data were extracted independently by two authors according to the inclusion criteria listed above. Disagreements were resolved by discussion between the two authors. The following characteristics were collected from each study: the first author, publication year, geographic region, ethnicity, diagnostic criteria, gender component, sample size, age of cases, age of controls, SNPs/haplotypes investigated, and distribution of genotypes among cases and controls for each involved SNP/haplotype.P-value <0.1), a random-effects model (the DerSimonian and Laird method) was selected to pool the data. Otherwise, a fixed-effects model (the Mantel-Haenszel method) was selected to pool the data.The statistical analysis was conducted using STATA 11.0 . The strength of association was expressed as pooled odds ratio (OR) along with the corresponding 95% confidence interval (CI), which were estimated for each study in a random-effects model or in a fixed-effects model. If there was a significant heterogeneity  on odds ratios derived from each study if significant heterogeneity was observed in the meta-analysis. Moreover, corrections for multiple comparisons were conducted by the Bonferroni method As suggested in previous studies P-value <0.01 was considered as significant deviation from HWE. As deviations from HWE in control subjects may bias the estimates of genetic effects in a meta-analysis Hardy-Weinberg Equilibrium (HWE) in the controls was tested by the chi-square test for goodness of fit, using a previous meta-analysis as reference 2 -based Q testing and I2 statistics P-value <0.1 was considered significant for the χ2-based Q testing and I2 was interpreted as the proportion of total variation contributed by between-study variation Heterogeneity among studies was examined with the χIL-10 were obtained IL-10 SNPs  and six haplotypes of rs1800896-rs1800871-rs1800872 were meta-analyzed . The result of recessive model (A/A vs. C/A+C/C) still remained significant even after correcting for multiple comparison with a P-value of 1.86E-03. No significant associations were observed in other SNPs  and SZ have been conducted, and significant associations were observed only in rs1800872  and G-C-C  for Asians and the results were still significant after correcting for multiple comparison with a P-value of 0.012 , significant association was observed in haplotype A-C-A , subgroup analysis was conducted. After stratifying for ethnicity, significant association was still observed under recessive model in both Caucasians  and Asians , indicating that the significance does not vary across different ethnic groups. Similarly, for rs1800896, no significant results were observed under any genetic model when all samples were included. Considering the difference in allele frequencies among different ethnic groups , subgroup analysis was also conducted. After stratifying for ethnicity, significant results were observed in neither Caucasians nor Asians, suggesting these results did not vary across ethnic groups either. For rs1800871, no significant results were observed, as all included studies were Asian samples , the association in other enthic groups were worthy of being investigated further.Results from the meta-analysis showed a significant association between rs1800872 of Besides, among six haplotypes of rs1800896-rs1800871-rs1800872, two haplotypes, A-C-A and G-C-C, were both observed to be significantly associated with SZ in Asians, with an OR of 1.762 and 0.649 respectively. For haplotype A-C-A (frequency in cases/controls: 0.013∼0.063/0.009∼0.048), A-T-A (frequency in cases/controls: 0.120∼0.688/0.113∼0.685) and A-T-C (frequency in cases/controls: 0.015∼0.145/0.016∼0.165), all included studies were Asian samples. The lack of Caucasian samples was due to the the absence of these haplotypes in Caucasians IL-10, it was reported that the C allele of this polymorphism correlates with higher IL-10 production. Furthermore, it was also reported that carriers of haplotype G-C-C had higher IL-10 production IL-10 production genotypes might have a higher risk of SZ, compared with those with higher IL-10 production genotypes. This was supported by a previous study demonstrating that excessive prenatal levels of IL10 could decrease the risk of behavioral dysfunctions in the grown offspring IL-10 was a cytokine with anti-inflammatory effect IL-10 production genotypes.For rs1800872 (-592A/C), an SNP locating within a putative STAT-3 binding site and negative regulatory region of There are still some limitations for this study: 1) as limited statistical power is a common problem in genetic association studies, in our meta-analysis, negative results should be interpreted cautiously and still need to be further investigated in larger scale of samples. 2) In some cases, heterogeneity was not resolved after subgroup analyses, suggesting that other factors such as the differences in assays or clinical characteristics might have caused heterogeneity. 3). The lack of clinical information such as age onset of patients made us unable to further investigate the association of diseases with more detailed factors.IL-10 polymorphisms and risk of SZ. In this study, rs1800872 of three investigated SNPs of IL-10 was observed to be significantly associated with SZ. Meanwhile, significant associations were also presented in haplotypes A-C-A and G-C-C among six haplotypes of rs1800896 - rs1800871 - rs1800872 for Asians, even after adjusting for multiple comparisons. The overall effect of this meta-analysis suggested that IL-10 might be a risk factor of SZ. Larger and well-designed studies based on different ethnic groups are needed to confirm our results.As far as we know, this is the first meta-analysis to investigate the association between Figure S1Funnel plot of rs1800896.(DOC)Click here for additional data file.Figure S2Funnel plot of rs1800871.(DOC)Click here for additional data file.Figure S3Funnel plot of rs1800872.(DOC)Click here for additional data file.Figure S4Funnel plot of six haplotypes of rs1800896- rs1800871-rs1800872.(DOC)Click here for additional data file.Table S1Results of sensitivity analysis.(DOC)Click here for additional data file.Checklist S1PRISMA Checklist.(DOC)Click here for additional data file.Diagram S1PRISMA Flow Diagram.(DOC)Click here for additional data file.