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• W2138730078 abstract "Review23 October 2012Open Access Emerging genetics of COPD Annerose Berndt Corresponding Author Annerose Berndt [email protected] Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh Medical Center, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA Search for more papers by this author Adriana S. Leme Adriana S. Leme Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh Medical Center, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA Search for more papers by this author Steven D. Shapiro Steven D. Shapiro Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh Medical Center, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA Search for more papers by this author Annerose Berndt Corresponding Author Annerose Berndt [email protected] Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh Medical Center, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA Search for more papers by this author Adriana S. Leme Adriana S. Leme Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh Medical Center, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA Search for more papers by this author Steven D. Shapiro Steven D. Shapiro Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh Medical Center, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA Search for more papers by this author Author Information Annerose Berndt *,1, Adriana S. Leme1 and Steven D. Shapiro1 1Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh Medical Center, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA *Tel: +1 412 624 8534; Fax: +1 412 648 2117 EMBO Mol Med (2012)4:1144-1155https://doi.org/10.1002/emmm.201100627 PDFDownload PDF of article text and main figures. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions Figures & Info Abstract Since the discovery of alpha-1 antitrypsin in the early 1960s, several new genes have been suggested to play a role in chronic obstructive pulmonary disease (COPD) pathogenesis. Yet, in spite of those advances, much about the genetic basis of COPD still remains to be discovered. Unbiased approaches, such as genome-wide association (GWA) studies, are critical to identify genes and pathways and to verify suggested genetic variants. Indeed, most of our current understanding about COPD candidate genes originates from GWA studies. Experiments in form of cross-study replications and advanced meta-analyses have propelled the field towards unravelling details about COPD's pathogenesis. Here, we review the discovery of genetic variants in association with COPD phenotypes by discussing the available approaches and current findings. Limitations of current studies are considered and future directions provided. Introduction The Global Initiative for Chronic Obstructive Lung Disease (GOLD) defines chronic obstructive pulmonary disease (COPD) as a disease state associated with airflow obstruction that is not fully reversible (http://www.goldcopd.org/). COPD is currently the fourth leading cause of death and the World Health Organization reports a likely increase in importance to the third leading cause by 2030. According to the World Health Organization, COPD is the most common serious chronic disease worldwide affecting about 64 million people (The global burden of disease: 2004 update, published in 2008). Hence, COPD represents a large and increasing burden to the health care system. Unfortunately, we have limited disease-modifying therapy for COPD and hence, an improved understanding of pathogenetic mechanisms leading to novel therapeutic interventions and preventive strategies is greatly needed. Understanding the genetic predisposition to COPD is essential to develop personalized treatment regimens (Shapiro, 2011). This Review aims to highlight the advances in the discovery of genetic variants in association with COPD by discussing the available approaches and current findings. Chronic obstructive pulmonary disease is a multi-factorial disorder caused by environmental determinants – most commonly cigarette smoking – and genetic risk factors (Decramer et al, 2012). In addition to cigarette smoking, COPD can also be caused by other environmental factors, particularly indoor biomass smoke exposure in developing countries (Kennedy & Chambers, 2007). COPD is diagnosed by spirometry showing an irreversible decrease in forced expiratory volume in 1 s (FEV1) and the ratio of FEV1 to forced vital capacity (FEV1/FVC). Although there is a dose–response relationship between FEV1 and the amount of smoke exposure, the FEV1 decline for smokers with similar exposure varies considerably (Burrows et al, 1977; Fletcher, 1976). This suggests that, in addition to cigarette smoking (and potentially other environmental factors), COPD is also influenced by genetic risk factors (Fig 1). For over 45 years, we have known that genetic variants in the alpha-1 antitrypsin (AAT) gene serpin peptidase inhibitor, clade A, member 1 (SERPINA1) lead to COPD. However, AAT deficiency accounts for only 1–2% of all COPD cases. Thus, other variants in the genome are likely to be associated with COPD traits. Finally, it will be important to unravel how environment and genes interact as part of COPD's pathogenesis. As with other chronic inflammatory diseases, it has been shown that epigenetic changes (Yao & Rahman, 2012) and somatic mutations (Tzortzaki et al, 2012) are involved in the pathogenesis of COPD. Figure 1. COPD is caused by chronic environmental insults (in particular cigarette smoking) in individuals with predispositions due to variations in one or multiple genes. The combination of environment and genes lead to distinct aberrant pathophysiological processes/pathways, the combination of which causes COPD. Download figure Download PowerPoint Like many chronic complex diseases, it has been difficult to unravel the genetic predisposition and pathogenetic mechanisms for COPD. This is in part due to the heterogeneous nature of the disease. For example, airflow obstruction that defines COPD can result from destruction and enlargement of alveoli (i.e. emphysema) with loss of elastic recoil or through obstruction of small airways or both (Hogg et al, 2004). Both of these processes occur with smoking but are not mechanistically related. Therefore, identifying the genetic basis for either of the traits does not justify extrapolation of genetic determinants for other phenotypes. Rather different phenotypic traits may be determined by complex genetic networks, which may or may not overlap. Improved phenotypic measurement of discrete disease traits, such as computerized tomography (CT) for emphysema and spirometry primarily for small airway disease, will allow investigators to more precisely identify genotype–phenotype correlations (Kim et al, 2009). Genetic approaches Family, twin and segregation studies Basic genetic approaches included family, twin and segregation studies. Early epidemiological studies found that COPD aggregates in families (Larson et al, 1970; Higgins et al, 1984; Tager and Speizer, 1976) by showing stronger correlations between parents and children or siblings than between spouses. Twin (Redline et al, 1987; Redline, 1990) and segregation studies (Givelber et al, 1998) suggested that the genetic susceptibility for COPD is due to many genes with small effects (Chen et al, 1996; Givelber et al, 1998). These early discoveries initiated the search for novel gene variants with gene-association and linkages studies. Candidate gene-association studies Candidate gene-association studies examine genes that were postulated to play a central role in COPD pathogenesis and investigate the strength of association between disease traits and candidate gene variants. Genetic studies for COPD were performed as gene-association studies by focusing primarily on genes from the protease–antiprotease and oxidant–antioxidant pathways. However, given the diverse pathways (such as inflammation, innate immunity, cell death, matrix repair mechanisms and lung development) involved in COPD pathogenesis it is likely that other genes contribute as well. Also, inconsistencies among those studies restrained our advancement towards clarifying the genetic basics of COPD. The contradictory findings were mostly driven by limited population cohorts, non-standardized disease definitions and varying statistical methods (including differences in adjusting for race, ethnicity, gender, environment and genetic background). A recent meta-analysis of assumed genes showed that many of the gene variants tested in gene-association studies are indeed not successfully associated with COPD (Smolonska et al, 2009). Nevertheless, in spite of the overall disappointing results, a few studies appear promising – namely for MMP12 – and will be discussed in detail below (Hersh et al, 2011; Hunninghake et al, 2009). Linkage studies As opposed to candidate gene-association studies where genes are chosen, linkage studies represents an unbiased approach and are not limited by an incomplete understanding of disease pathogenesis. Polymorphic markers that are spread across the entire genome are examined for their association with the phenotype of interest. Yet, due to the low marker density, the identified loci are often large in size and can contain several hundreds of genes that need to be sorted through to find those that are associated with the disease. Fine-mapping procedures can eventually narrow the regions to more defined locations and potentially identify novel genes (DeMeo et al, 2006; Wilk et al, 2003). However, linkage studies lack the statistical power needed to identify genetic loci with small genetic effects that are commonly associated with complex diseases, such as COPD (Risch & Merikangas, 1996). Since the recent availability of high-density single nucleotide polymorphism (SNP) panels for whole-genome association studies, linkage studies have largely been abandoned. Genome-wide association studies Genome-wide association (GWA) studies provide an unbiased and hypothesis-free approach to identify genome variations associated with disease phenotypes (Soler Artigas, 2012). We have come a long way since the first COPD GWA study and have not only identified novel candidate genes but also improved the methods along the way to ensure the most accurate results. Due to the use of dense SNP maps (generally hundreds of thousands of SNPs), the search for novel genes can be pinpointed more accurately than with linkage analysis. However, GWAS studies also have limitations due to the small sample sizes (the genome variation underlying lung function are believed to have modest effects; therefore, very large populations are required to identify them) and lack of large-scale follow up studies, which increases the risk for identification of false-positive associations. Also, SNP panels often do not represent disease-associated genetic variants per se but may rather be in linkage disequilibrium (LD) with them. A potential strategy to resolve these issues has been proposed recently at an international COPD genetics conference, where it was suggested that a COPD Genetics Consortium be formed to promote collaborations between investigators of existing COPD populations (Silverman et al, 2011). A similar approach has been initiated with the SpiraMeta Consortium combining multiple GWA studies on subjects with European ancestry in large-scale meta-analysis (Obeidat et al, 2011). These Consortia provide an approach for empowering GWA studies and accelerating the identification of common genome variations associated with COPD. In the very near future, we are going to be able to utilize whole-genome information obtained by next-generation sequencing that will not only improve our abilities to identify common variants but also help teasing out the role of rare and structural genomic variations. However, there are many challenges that must be overcome before whole-genome sequencing becomes routine. For Freeman–Sheldon syndrome 2 and Miller syndrome, it has already been demonstrated successfully that whole-exome sequencing can identify the underlying disease gene (Biesecker, 2010; Ng et al, 2010). Whole-exome sequencing was also applied successfully for the identification of DNMT3A mutations in acute myeloid leukaemia (Ley et al, 2010). While whole-exome sequencing has the advantage of cost and coverage, rapid cost reductions of whole-genome sequencing will likely render whole-exome sequencing less useful since it only covers 1–2% of the genome – albeit an important 1–2%. In summary, although progress in resolving the genetic basis of COPD has been slow since the discovery of AAT in the early 1960's, recent techniques have greatly improved and advances in defining COPD genes have accelerated and will continue to do so. To date, there are currently accepted and recently suggested COPD genes that will be discussed in this review below (Table 1 and Fig 1). Table 1. Overview of COPD genes and details of their study of origin Year Gene Chr Band Approach Phenotype #SNPs Population Primary population(s) Replication population Potential Function of Variants Reference 1964 AAT 14 q32.13 Pi system (electrophoresis) Respiratory insufficiency NA 2 patients NA Protease inhibition Eriksson (1964) 2007 IL6R 1 q21.3 GWA study FEF25–75 70,987 1220 (fb) FHS NA Immune mechanisms Wilk et al (2007) 2007 GSTO2 10 q25.1 FEV1, FVC NA Arsenic biotransformation 2009 HHIP 4 q31.21 GWA study FEV1/FVC 550,000 7691 (fb) FHS Family Heart Study, CHARGE Consortium, SpiroMeta Consortium Lung development by hedgehog signaing Wilk et al (2009) 2009 IREB2 15 q25.1 GWA study FEV1/FVC 561,466 823 (810) Bergen cohort ICGN, NETT/NAS, BEOCOPD Pulmonary iron homeostasis Pillai et al (2009) 2009 MMP12 11 q22.3 Gene-association study FEV1 SNPs in linkage with MMP12 8300 Genetics of Asthma in Costa Rica Study, CAMP, Children, Allergy, Milieu, Stockholm, Epidemiological Survey, BEOCOPD, NETT, Lovelace Smokers Cohort, NAS Elastase activity Hunninghake et al (2009) 2010 FAM13A 4 q22.1 GWA study FEV1/FVC 550,000 2940 (1380) Bergen cohort, NETT/NAS, ECLIPSE COPDGene, ICGN, BEOCOPD, CHARGE Consortium Oxidative stress and impaired apoptosis Cho et al (2010) 2010 GSTCD 4 q24 GWA study FEV1 2,705,257 20,288 12 GWA studies (european origin) CHARGE Consortium Developmental and remodeling pathways Repapi et al (2010) TNS1 2 q35 FEV1 AGER 6 p21.3 FEV1/FVC CHARGE Consortium HTR4 5 q32 FEV1 CHARGE Consortium THSD4 15 q23 FEV1/FVC 2011 BICD1 12 p11.21 GWA study CT scan 550,000 2380 ECLIPSE, NETT/NAS, Bergen cohort Telomere shortening Kong et al (2011) 2011 SOX5 12 p12.1 GWA study/Gene-association study FEV1, FEV1/FVC 1387 386 (424) NETT/NAS BEOCOPD Development lung morphogenesis Hersh et al (2011) 2011 MFAP2 1 Meta-analysis GWA FEV1, FEV1/FVC ∼2,500,000 48,201 SpiroMeta Consortium, CHARGE Consortium CARDIA, CROATIA-Split, LifeLines, LBC1936, MESA-Lung, RS-III, TwinsUK-II antigen of elastin-associated microfibrils Soler Artigas et al (2011) TGFB2 1 Epithelial repair process, extracellular collagen accumulation HDAC4 2 regulation of gene expression RARB 3 premature alveolar septation MECOM 3 SPATA9 5 ARMC2 6 NCR3 6 ZKSCAN3 6 CDC123 10 Response to cell stress C10orf11 10 LRP1 12 CCDC38 12 MMP15 16 CFDP1 16 KCNE2 21 Ion transport in airway epithelial cells 2011 RAB4B 19 19q13 Meta-analysis GWA COPD, FEV1 ∼6,100,000 3499 (1922) ECLIPSE, NETT/NAS, Bergen cohort, COPDGene ICGN Cho et al (2012) EGLN2 MIA CYP2A6 Nicotine dependence Accepted COPD genes Alpha-1 antitrypsin, encoded by the SERPINA1 gene, is a member of the serpine protease inhibitor superfamily (SERPIN). AAT is mainly produced in the liver and is the major physiologic inhibitor of the serine protease neutrophil elastase (NE; Stoller & Aboussouan, 2011). In addition to NE, AAT inhibits other serine proteinases including proteinase 3 (PR3) (Esnault et al, 1993) and cathepsin G (Topic et al, 2009). AAT also inhibits kallikreins (Felber et al, 2006), matriptase (Janciauskiene et al, 2008), caspase-3 (Miller et al, 2007) and ADAM-17 (Bergin et al, 2010). Alpha-1 antitrypsin deficiency was first described in 1964 in two patients with severe respiratory insufficiency due to emphysema (Eriksson, 1964). The identification of the AAT variant was possible due to the development of the Pi system, in which AAT mutants migrate distinctly in an electric field from the normal M form. The most common variant, the Z isoform, is due to the single amino acid substitution from glutamic acid to lysine (i.e. Glu342Lys), which causes a perturbation in the protein structure resulting in its defective secretion from hepatocytes (Kass et al, 2012). This remarkable story not only shows how a clinical diagnosis can successfully be linked to the genetic basis for a COPD phenotype, it also highlights the long time span required in the past to go from clinical observation (1963) to identification of the amino acid substitution (1978) with limited tools. Fortunately, technical advances in unravelling the pathogenetic basis of diseases greatly accelerate the processes involved in gene finding today. However, at present, the Z variant of AAT remains the only truly accepted genome variant associated with COPD. Suggested COPD genes Early COPD GWA studies: interleukin 6 receptor (IL6R) and glutathione S-transferase (GSTO2) Wilk and colleagues reported a GWA study for lung function measures in 2007 (Wilk et al, 2007). The authors collected several spirometry parameters from 1220 related individuals that participated in the Framingham Heart Study (FHS) and performed association studies using 70,987 SNPs from the Affymetrix 100K SNP GeneChip. The location of the strongest associations differed depending on the physiological phenotype. Percent predicted forced expiratory flow from the 25th to 75th percentile (FEF25–75) was slightly associated with a SNP in the IL6R region on 1q21 (rs4129267; p-value = 0.07), whereas FEV1 and FVC were most significantly associated with the GSTO2 region on 10q25.1 (rs156697; p-value = 9.42 × 10−5). Although the findings of this study were groundbreaking at the time, there were shortcomings. In particular, it is important to notice that both associations did not reach genome-wide significance. While the non-synonymous SNP of GSTO2 reached a p-value of 10−5, the SNP at the IL6R locus only reached a p-value of 0.07. Most likely, these shortcomings were at least partially due to the low-density genome coverage with <100,000 SNPs, which may have given rise to potentially ill-defined associations. IL6R, the receptor of interleukin 6 (IL6), is involved in both pro- and anti-inflammatory processes. IL6R exists as soluble form and forms a complex with IL6. The IL6/IL6R complex appears to play a role in cigarette smoke-induced inflammation, recruiting inflammatory cells to the lung to eliminate foreign particles such as cigarette smoke components, only to have a myriad of other effects on lung tissue. Finally, IL6 (the IL6R ligand) has been shown to be associated with lung function in the Framingham offspring population (Walter et al, 2008). GSTO2, a family member of the glutathione S-transferases, which are proteins involved in metabolizing xenobiotics and carcinogens, has been postulated to play role in COPD related to its involvement in arsenic biotransformation as arsenic is a chemical element of cigarette smoke (Mukherjee et al, 2006). Hedgehog-interacting protein (HHIP) Two years after the first COPD GWA publication, the investigators published again on findings from the FHS population addressing some of the issues discussed in their initial study (Wilk et al, 2009). Foremost, the SNP panel was more than five-times larger with 550,000 SNPs. Also, the number of subjects was increased from 1220 to 7691. Another advantage of this investigation was that significant SNPs were also tested in a second unrelated population – the Family Heart Study cohort. This time, the investigators examined FEV1/FVC to characterize patients. Four linked SNPs on chromosome (Chr) 4 at about 145 Mb (i.e. 4q31) were identified to be significant on a genome-wide level. One of those four SNPs (rs13147758) was genotyped in the Family Heart Study, but in this replication study, it did not reach genome-wide significance. However, other studies found SNP associations on 4q31 (Hancock et al, 2010; Repapi et al, 2010; Zhou et al, 2012), thus strengthening evidence that this locus harbours a novel COPD gene. The SNPs on Chr 4 were found to be located in an intergenic region just downstream of the 5′ start site of HHIP, hence representing a potential role in the regulation of HHIP expression. Alternatively, these SNPs could also be in linkage with the disease-causing variant. Together, these findings suggest compelling evidence that this candidate locus may truly influence airflow obstruction in COPD patients. HHIP, a hedgehog-interacting protein, is involved in hedgehog signalling and has been shown to be involved in lung development (Shi et al, 2009). The process of lung development is relevant to COPD because abnormal lung development could lead to impaired reserve predisposing to COPD in smokers. Also, it has been shown that other lung growth and remodelling genes such as WNT are re-activated (Tzortzaki et al, 2012), which indicates that abnormal remodelling and repair mechanisms are important molecular processes involved in COPD. α-Nicotinic acetylcholine receptor (CHRNA 3/5) locus and iron-responsive element binding protein (IREB2) At the same time the HHIP candidate locus was published, Pillai et al published a GWA study on the identification of the CHRNA 3/5 locus at 15q25.1 (Pillai et al, 2009). Here, the primary study population was a case-control cohort from Bergen, Norway, with 823 COPD patients and 810 control subjects. The top 100 associations were further investigated in three other cohorts: the International COPD Genetics Network (ICGN; cases and controls), the US National Emphysema Treatment Trail (NETT; COPD cases) and the Normative Aging Study (NAS; controls), as well as the Boston Early-Onset COPD (BEOCOPD) cohort. Similar to the HHIP publication, the phenotypes investigated here were FEV1/FVC and post-bronchodilator FEV1 (only in the BEOCOPD). Two SNPs on Chr 15 at the CHRNA 3/5 locus (rs8034191 and rs1051730) reached genome-wide significance and were replicated successfully in the independent study cohorts. This Chr 15 locus was previously studied in association with nicotine dependence and, thus represented a promising candidate region (Berrettini, 2008; Saccone et al, 2007; Siedlinski et al, 2011). Interestingly, the SNP associations were significant with and without adjustment for smoking exposure in the original Norway cohort and a significant SNP by pack-years interaction was observed in the ICGN replication population. These observations inferred that the differences between COPD patients and controls were more likely due to genetic determinants of smoking behaviour (i.e. nicotine addiction) rather than genetic determinants of COPD per se. The latter is supported in light of the observations of significant associations between the CHRNA 3/5 locus and smoking behaviour in lung cancer (Spitz et al, 2008; Thorgeirsson et al, 2008). However, another study on lung cancer did not show that this locus is associated with smoking behaviour (Cantrell et al, 2008). Therefore, further investigation is required to characterize the effects of the Chr 15 locus in regards to smoking behaviour, lung cancer or both. An integrative genomics approach (i.e. combined gene expression and genetic association studies) independently identified variants in IREB2 that are in tight LD with the CHRNA 3/5 variants, suggesting IREB2 as a likely COPD candidate gene at the CHRNA 3/5 locus (DeMeo et al, 2009). IREB2 belongs to the iron regulatory protein family (IRPs) that maintains iron homeostasis by regulating iron uptake and distribution. IREB1 and IREB2 maintain the cellular iron metabolism (Rouault, 2006). Regional differences in iron and IRPs exist in smokers (Nelson et al, 1996), which can potentially lead to variation in oxidative stress in the lung – a mechanism of importance in emphysema and lung cancer. Family with sequence similarity 13, member A1 (FAM13A) The independent populations, in which the CHRNA3-CHRNA5-IREB2 and HHIP loci were identified, were combined and resulted in the identification of the FAM13A locus (Cho et al, 2010). Together, the investigators used 2940 COPD cases and 1380 controls (i.e. current and former smokers) from three populations: (i) the case–control population from Norway; (ii) a cohort consisting of NETT cases and NAS controls; and (iii) a case and control population from the multi-centre Evaluation of COPD Longitudinally to Identify Predicted Surrogate Endpoints (ECLIPSE). The two most significantly associated SNPs (rs7671167 and rs1903003; r2 = 0.85) were found at 4q22.1 within a FAM13A intron, which is located just downstream of the Rho-GTPase-activating protein (Rho-GAP) domain. To verify their findings, the investigators genotyped the most significant SNPs using the COPDGene Study population. SNP associations for the top two SNPs were also tested in the ICGN and BEOCOPD populations. Associations of the SNP rs7671167 were significant in COPDGene and ICGN and had a tendency toward significance in the BEOCOPD. Furthermore, an independent GWA investigation of lung function using the populations form the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium reported an association of FAM13A with FEV1/FVC (Hancock et al, 2010). Evidence for a possible role of FAM13A in COPD is its differential expression during hypoxia in cell cultures of epithelial and endothelial cells (Chi et al, 2006) and during epithelial cell differentiation of alveolar type II cells (Wade et al, 2006). FAM13A expression differences have also been observed among mild and severe cystic fibrosis patients (Wright et al, 2006). The significant SNP associations were not associated with pack-years of cigarette smoking and, thus, FAM13A is most likely mediating the genetics of lung function or potentially COPD as opposed to smoking behaviour. A recent report also shows the independent association of the FAM13A locus with lung cancer (Young & Hopkins, 2011). FAM13A – a Rho-GAP domain containing gene (Cohen et al, 2004) – exhibits tumour suppressor activity by inhibiting the signal transduction molecule Rho A (Ridley, 2001). In COPD Rho A activity has been shown to be involved in oxidative stress and impaired clearance of apoptotic cells (Richens et al, 2009). Similar to HMGCoA reductase inhibitors (statins), Rho-GAP seems to modulate the HMGCoA reductase enzyme, and therefore, provides an explanation why statins may have the potential to protect against COPD and lung cancer (Young et al, 2009). Five additional loci associated with FEV1 and FEV1/FVC A meta-analysis of several GWA studies by the SpiraMeta Consortium identified five additional loci associated with FEV1 and FEV1/FVC (Repapi et al, 2010): Tensin 1 (TNS1); glutathione S-transferase, C-terminal domain containing (GSTCD); advanced glycosylation end product-specific receptor (AGER); 5-hydroxytryptamine (serotonin) receptor 4 (HTR4); and thrombospondin, type I, domain containing 4 (THSD4). As a result of combining multiple GWA studies, the investigators were able to include 20,288 individuals with European ancestry and 54,276 individuals in follow-up investigations. The power of the analysis was greatly increased due to increased quantity of genotype and phenotype data, which ultimately led to the identification of highly significant SNP association (p-values ranged from 10−9 to 10−23). Significant loci were detected for FEV1 at 4q24 (GSTCD), 2q35 (TNS1) and 5q33 (HTR4), and for FEV1/FVC at 6p21 (AGER) and 15q23 (THSD4). Another locus at 6p21 within the borders of dishevelled associated activator of morphogenesis 2 (DAAM2) contained a suggestive association with FEV1/FVC. GSTCD, HTR4 and AGER were identified independently in the GWA study by the CHARGE Consortium (Hancock et al, 2010). Both, the SpiroMeta and CHARGE Consortia, also found associations at the HHIP locus (see above). The associations identified in this study did not change when adjusted for qualitative or quantitative smoking exposure and so the underlying genes most likely are not involved in smoking addiction. Nevertheless, a previous report showed a role for TSHD4 in smoking cessation (Uhl et al, 2008). Proposed mechanisms that may underlie these newly identified genes are either developmental pathways or tissue remodelling pathways that are important for airway architecture and lung repair. SRY (sex determining region Y)-box 5 (SOX5) Linkage studies in the family-based BEOCOPD cohort identified a locus on Chr 12 but the gene of interest could not be isolated at this point (Silverman et al, 2002a, b). Thus, a systematic approach to fine-map the region on Chr 12 was applied by genotyping 1387 SNPs in 386 COPD cases from the NETT cohort and 424 healthy s" @default.
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• W2138730078 title "Emerging genetics of COPD" @default.
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