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Review Article

Phenotypic Variance in COPD: Recent Developments in Clinical, Radiographic and Molecular Aspects, and Relevance to Management Strategies

Khadir Kakal1, Santhi Kumar1, Ahmet Baydur*1

1The Division of Pulmonary and Critical Care Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California

*Corresponding author:  Dr. Baydur, Division of Pulmonary and Critical Care Medicine, Keck School of Medicine, University of Southern California, 2020 Zonal Avenue, IRD 725, Los Angeles, CA 90033, Tel : 323-226-7923; Email: baydur@usc.edu

Submitted: 09-15-2015 Accepted: 09 -26-2015 Published: 10-13-2015

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COPD is a heterogeneous disease. Subcategories of COPD used currently are nonspecific and future subgrouping increasingly needs novel approaches. Understanding COPD susceptibility depends on pursuing genome-wide studies that elucidate phenotyping and genotyping. Genes that are identified should be localized within molecular pathways to assess the role of these networks in disease pathogenesis. Once critical pathways are identified, means to inhibit those pathways should lead to disease-modifying therapy. The diversity in symptoms, clinical responsiveness and quality of life in these patients, separating patients into subgroups may lead to more meaningful assessment to response to therapy. It is hoped that understanding the genetics of COPD will play a major role in the development of personalized medicine: genetic information will define an individual’s disease characteristics, potential complications, co-morbidities and treatment. Coupled with the elimination of cigarette smoking, this approach will ultimately lower the burden of COPD.

Keywords: Chronic Obstructive Pulmonary Disease; Phenotypes; Genetic Factors; Pharmacologic Associations


Chronic obstructive pulmonary disease (COPD) is a complex disease which has been simplified by current definition as a disease state characterized by poorly reversible airflow obstruction associated with persistent chronic inflammatory state of the lungs secondary to noxious stimuli. The problem with this definition is that it isn’t justified by the complexity of the disease, nor does it isolate a uniform group of patients for optimal diagnosis, assessment and management. COPD comprises a range of respiratory and systemic manifestations. Its severity is graded by forced expiratory volume in 1 second (FEV1) [1], yet if this approach is meant to reflect quality of life and severity of symptoms, FEV1 only weakly correlates with dyspnea [2] and does not recognize differences in pathophysiological abnormalities that may be present in this heterogeneous condition. Furthermore, inconsistencies  amongst symptoms and spirometric findings can lead to inappropriate medical management. For example, consider two patients who are both smokers and with FEV1/ FVC <70% and FEV1 of 50%, one of whom has never been hospitalized and the other has been battling exacerbations 3-4 times per year. Should both of these patients be lumped within the same group, should they get the same treatment, and are they likely to have similar clinical outcomes? We know the answers are no, so the question that arises is that is there a better way to define and characterize COPD? The recent GOLD guidelines have tried to incorporate both physiologic and symptom- and exacerbation-related aspects in attempting to classify COPD in a more clinically relevant manner and one that more logically guides towards rational treatment options [3].

To begin with, COPD remains underdiagnosed because of infrequent use of spirometry in the medical community [4]. Among patients who do undergo spirometry, up to 14% exhibit decreased lung function [5] that cannot be classified under the Global Initiative for Chronic Obstructive Lung Disease (GOLD) diagnostic and staging criteria [6]. These GOLD-Unclassified (GOLD-U) individuals, who exhibit reduced FEV1 but maintain an FEV1/FVC ratio greater than or equal to 0.7, are excluded from COPD studies because of poor characterization. Even though such patients are characterized as having “restrictive” lung disease, this pattern on spirometry has poor predictive value for true restriction as defined by a decreased total lung capacity [7-9]. GOLD-unclassified smokers comprise 9% of smokers in the COPDGene study and exhibit increased body mass index (BMI), TLC reduction more than expected from obesity, a higher proportion of African-American subjects and patients with diabetes and congestive heart failure [10].

Lung function alone cannot account for the multiple factors that contribute to the pathogenesis of emphysema. Chest CT scans provide a sensitive and noninvasive method to identify emphysema in patients with COPD. Because variations in phenotypic presentation are important in identifying genetic association results in COPD, objective classification of patients with COPD based on emphysema measurements using CT are helping to reduce this heterogeneity [11, 12]. By providing surrogate measurements of structural and functional abnormalities, thoracic imaging has improved our understanding of COPD and its response to therapy. Quantitative assessment of emphysema by CT scanning done by measuring the percentage of lung volume occupied by low attenuation areas correlates well with histopathologic findings [13] and degree of expiratory airflow limitation [14]. In a retrospective study of 274 patients with CT scan-defined emphysema and COPD defined by GOLD criteria, 10.4% exhibited normal spirometry [15]. Thus imaging may be useful in characterizing patients with respiratory symptoms and normal spirometry. This approach goes beyond what information FEV1 can provide with respect to exacerbations and mortality.

Definition and Clinical Correlations

Phenotype refers to any observable characteristic of an organism, and until recently,several disease characteristics have been termed COPD phenotypes. Han and colleagues [15] have proposed a modification on this definition: ‘‘a single or combination of disease attributes that describe differences between individuals with COPD as they relate to clinically meaningful outcomes (symptoms, exacerbations, response to therapy, rate of disease progression, or death).’’ This more focused definition allows for classification of patients into distinct prognostic and therapeutic subgroups for both clinical and research purposes. Han et al [16] listed 6 phenotypic criteria based on clinical manifestation, physiologic findings, radiographic presentation, frequency of COPD exacerbations, markers for systemic inflammation, and comorbidities (figure 1).


pulm fig 11.1
Figure 1. Validation of candidate phenotypes upon establishing their relevance to clinical outcomes. Entry points into this scheme can be multiple: For example subpopulations may be identified by similar clinical outcomes or by a biologic marker that focus attention on a particular therapy based on the clinical outcome or biologic marker [16].

Phenotyping of COPD is not a novel idea. Dornhorst [17] offered a landmark description of two extreme clinical phenotypes in the mid-1950s. The “blue bloater” was described as a younger patient with chronic bronchitis, who often presented with congestive right heart failure. The classic “pink puffer” was an older and skeletal muscle-wasting patient who experienced unrelenting, disabling dyspnea and clinical and radiographic features of emphysema. Today these extremes of clinical presentation are not commonly observed in practice, but they serve as crude models for the multiple and mixed presentations of COPD encountered today [18]. For example, patients with COPD develop emphysema to differing extents, as defined by intensity, location and distribution. Castaldi and colleagues [19] characterized emphysema by using a local histogram- based emphysema (LHE) assessment of lung density. This approach was able to establish associations between imaging patterns of emphysema and a number of physiologic and functional outcomes, providing an improved predictive COPD-related measure than threshold-based quantification methods. However, the LHE method has limitations, including the absence of information regarding the distribution pattern within the lung and its lack of correlation with pathologic emphysema [20]. In a later study, members of the COPDGene Investigators [21] demonstrated genetic associations with distinct CT emphysema patterns based on pathologic categories of centrilobular and panlobular emphysema in non-Hispanic white and African-American smokers.

The study of phenotyping has facilitated characterization of COPD in different ethnic and racial groups. For example, the Spanish guidelines for COPD [22] propose four COPD phenotypes: (i) frequent exacerbation phenotype with chronic bronchitis, (ii) frequent exacerbation phenotype with emphysema, (iii) asthma-COPD overlap syndrome (ACOS), and (iv)no exacerbation phenotype, and treatment plan per actual phenotypes as shown in fig. 2. Description of some of these phenotypes are summarized below:

pulm fig 11.2

Figure 2. Four COPD phenotypes relevant for the management of COPD: (i) non-exacerbator phenotype, (ii) mixed COPD-asthma phenotype; (iii) exacerbator phenotype with emphysema; and (iv) exacerbator phenotype with chronic bronchitis (rom ref. 22).

Asthma-COPD Overlap Syndrome (ACOS)

Patients with COPD/asthma overlap phenotype are a heterogeneous group with features of partially reversible airway obstruction and variable air flow as documented by bronchial hyper responsiveness. Lacking a clear definition, this subtype has been described as “a syndrome characterized by persistent airflow limitation with several features usually associated with asthma and several features usually associated with COPD. ACOS is therefore identified by features that are shared with both asthma and COPD”[23].

Patients in the United States and the United Kingdom exhibit an increasing proportion of ACOS with increasing age [24]. Explanations differ as to the pathogenesis of this phenotype. Underlying asthma may be compounded by the effects of smoking leading to a mixed picture. ACOS patients exhibit elevated sputum markers in comparison to patients with COPD [25]. Asthmatic
patients who smoke are at high risk for accelerated loss of lung function compared to non-smoking asthmatics [26].

Clinical features of patients with this mixed phenotype include increased likelihood of airway neutrophilia and less eosinophilic inflammation [27]. Imaging in patients with severe, persistent airflow limitation exhibits bronchial wall thickening and dilation in comparison to patients with normal lung function [28].

Studying this COPD phenotype has been challenging as patients with asthma are often excluded from clinical studies. In the largest study of this particular phenotype, the COPDGene trial [29], over 10,000 subjects between the ages of 45 and 80 years with at least a 10-pack year smoking history were assessed for evidence of ACOS. Patients with ACOS met criteria for GOLD stage 2 or greater disease and reported a history of asthma diagnosed by a physician before the age of 40. Patients with overlap syndrome were older, had a higher BMI, and fewer pack years of smoking than subjects with COPD alone. More were women and of African-American origin. Despite similar  lung function and fewer pack-years of smoking, patients with ACOS had worse measures of disease severity than patients with COPD alone, as evidenced by a higher BODE index and higher scores on the St George’s Respiratory Questionnaire. They also experienced more exacerbations per year and more exacerbations resulting in emergency room visits or hospital stay. Radio graphically, when adjusted for age, sex, race, BMI and CT scanner type, ACOS patients have more airway disease as demonstrated by increased wall thickness and less emphysema [29, 30] (figure 4). In light of a refined definition for ACOS with the GINA/GOLD, a recent study of the CHAIN cohort in Spain followed 125 patients with ACOS over one year [31]. In contrast to the previous study, these patients were likely to be male, and had a better one-year prognosis than those that did not have ACOS.

pulm fig 11.4

Figure 4. Relationship of COPD exacerbations to emphysema and bronchial wall thickness as detected by chest CT scanning. From ref. 30, Han et al. Radiology 2011;261(1):274.

Asthmatics that smoke are less responsive to the effects of inhaled or oral corticosteroids in preserving lung function and diminishing respiratory symptoms and experience more exacerbations in compared to nonsmokers. Patients with ACOS have significantly higher peripheral and sputum eosinophil counts as compared to those with asthma [32]. Asthma-derived gene expression signatures of T helper type 2 (Th2) inflammation are associated with increased disease severity, eosinophil counts, and increased response to inhaled corticosteroids (ICS) [32, 33]. As sputum eosinophilia is not regularly tested in patients with COPD, clinicians require alternative methods of measuring airway inflammation in these patients. One study evaluated airway inflammation using exhaled nitric oxide (eNO) in patients with diagnosed COPD and showed high correlation with sputum eosinophilia [34].

Management of patients with ACOS

The first step in diagnosing and managing these patients is to confirm the patient has symptoms of both asthma and COPD. The Global Initiative for Chronic Obstructive Lung Disease [3] and Global Initiative for Asthma (GINA) [23] have recently published guidelines to help clinicians differentiate between COPD and asthma. After ensuring the patient has clinical features of COPD and asthma, initial therapy consists of a low- or moderate- dose inhaled ICS. Long-acting bronchodilators (LABA) should be continued or added but should not be used alone in patients with asthma (figure 3). Although ACOS is associated with increased responsiveness to ICS, these drugs should not be used alone if clinical features suggest COPD as they are more effective when combined with a LABA. As with any patient with COPD, patients with ACOS should be counseled on smoking cessation, pulmonary rehabilitation, treatment of comorbidities and age-appropriate vaccinations. Currently there are no clear guidelines for the use of long-acting anticholinergics (LAMAs) in this subset of patients [23].

Frequent exacerbation of emphysema and chronic bronchitis phenotypes 

Acute exacerbations of COPD (AECOPD) are associated with acceleration of disease, decreased quality of life, and increased health care costs. Patients that fall in the category of frequent exacerbator are hospitalized more frequently and utilize more health care dollars than other phenotypes.

Exacerbations are defined as “an acute event characterized by a worsening of the patient’s respiratory symptoms that is beyond normal day-to-day variation and leads to a change in medication [3].” Symptoms include increase in cough, mucus hypersecretion and dyspnea. Exacerbators have been defined as patients who have 2 or more exacerbations per year separated by a minimum 4 weeks of treated exacerbations 6 weeks after the onset of symptoms in patients who have not have had symptoms [35].

The pathophysiology of this subtype is multifactorial. Patients with this phenotype have airway and systemic inflammation evidenced by elevated CRP in the blood and increased neutrophil predominance in the sputum [36]. Bacterial or viral infections are implicated in 50-70% of exacerbations [37].

pulm fig 11.3

Figure 3. Proposed pharmacological treatment of COPD phenotypes according to revised Spanish guidelines (table 3 from [22]).

The Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) study found that the strongest predictor of having 2 or more exacerbations per year was a history of previous exacerbations [38]. The risk of exacerbation, while not associated with a lower FEV1 and can often occur in any GOLD stage, increases with decreasing FEV1. Furthermore, symptoms of gastroesophogeal reflux disease double the risk of reported exacerbations.

Frequent exacerbations have a myriad of effects on the health and quality of life of patients. Multiple studies have confirmed an accelerated decline in FEV1 in patients with frequent exacerbations [39, 40]. Frequent exacerbations also appear to be associated with increased cardiovascular risk, especially in the 6 months following an exacerbation [41]. These patients also experience higher prevalence of depression, decreased quality of life and increased mortality [43].

Management of the Frequent Exacerbator Phenotypes

Initial management of the frequent exacerbator phenotype is done in accordance with GOLD grouping with a long acting bronchodilator with LAMAs or a LABA with ICS with the combination being applied if one treatment alone does not improve symptoms (figure 3). Roflumilast, an oral once daily selective phosphodiesterase 4 inhibitor has been shown to significantly reduce exacerbations and improve FEV1 as compared to placebo by inhibiting the activation of inflammatory cells [44].Recent subset analysis from the roflumilast study showed that only patients with FEV1<50% predicted and features of chronic bronchitis demonstrated greatest clinical response [45]. The role of roflumilast in patients that are not maintained on ICS and bronchodilators is unclear and therefore should only be used as second or third line therapy.

Antibiotic therapy in the treatment of this subtype has also been explored. Pulsed moxifloxicin given for five days every eight weeks for 6 treatment cycles reduced the odds of an exacerbation in those with mucopurulent sputum by 45% [46]. The use of azithromycin 500 mg three times a week has also been shown to reduce exacerbations when compared to placebo [47].

Two recent large clinical trials in China assessing the effects of 600 mg N-acetylcysteine (NAC) twice daily showed a reduction in number of exacerbations regardless if the patient was receiving inhaled corticosteroids. The effects were more pronounced in those with moderate COPD as compared to those with severe COPD [48, 49]. However, the HIACE study comprised a heterogeneous group of patients with COPD of varying severity and risks for exacerbation [48].

Non-Exacerbator Phenotypes with Emphysema or Chronic Bronchitis

The emphysema-hyperinflation phenotype patients generally present with dyspnea and exercise intolerance with symptoms of hyperinflation. The classic pink puffer, these patients are characterized by emphysema and hyperinflation seen on imaging and pulmonary function testing consistent with increased air trapping and lower diffusion capacity. Emphysema severity has been suggested as an independent risk factor for loss of lung function [50]. Chronic bronchitis is associated with bronchial hypersecretion, airway inflammation and increased risk of respiratory infections. The presence microorganisms residing in the airways, especially in chronic pseudomonas infection, leads to further deterioration, and more exacerbations and increased mortality, regardless of severity and comorbidities [51].

It is important to differentiate between the emphysema and chronic bronchitis phenotypes as the COPDGene study cohort has shown that the emphysema phenotype is associated with increased mortality, although this phenotype is characterized by fewer exacerbations than the chronic bronchitis phenotype, except in the most severe forms, with involvement of more than 30% patients [52].

Management of Non-Exacerbator Phenotype

The mainstayof treatment for the non-exacerbator phenotype are long-acting bronchodilators, initially as monotherapy and in combination in severe cases. Multiple trials in Europe have shown that the combination of LABA and LAMA vs LAMA alone or combination of LABA/ICS is superior in patients with moderate to severe COPD without exacerbation [53, 54] (Figure 3).

Cellular, molecular, physiologic and radiographic relationships

Phenotypic description of COPD by the use of biomarkers allows distinct subgroups of patients with different prognosis or response to therapy to be identified. Since the discovery of alpha-1 antitrypsin in the early 1960s [55], several new genes have been implicated in the pathogenesis of COPD. Genome- wide association studies (GWAS) have been used to identify genes and their variants and pathways [56]. Thus far,  most of current understanding about COPD candidate genesoriginates from GWAS. Cross-study replications and advanced meta-analyses continue to reveal details about the pathogenesis of this syndrome.

Animal models have shown that exposure to molecular, chemical and environmental agents produces airspace enlargement [55, 57, 58]. Upon exposure to cigarette smoke, mice exhibit changes similar to humans such as inflammation with neutrophils, macrophages and T cells followed by airspace enlargement [59]. Tobacco smoke exposure leads to cilia loss in mice airways, goblet cell hypertrophy, and submucosal fibrosis. The mouse strain often determines the pattern of changes observed. Phenotypes measured in multiple mouse strains can be used in GWA scans (genetic mapping studies similar to GWA studies in humans) to identify disease-causing genetic variants. Exposure to tobacco smoke results in down-regulation of mRNA expression of junctional proteins in airway epithelium, increase in epithelial to mesenchymal transition in patients with COPD [60, 61] and increase in mucosal permeability [62].

Cultured bronchial epithelial cells from former smokers with COPD exhibit structural changes with decreased capacity to form epithelial junctions during air-liquid interface differentiation related to reduced expression of tight junction proteins [63]. Myeloid dendritic cells (mDCs) of current smokers with COPD possess increased expression of surface receptors for antigen recognition as compared with never-smoking controls or former smokers [64]. The changes of these mDC surface receptors are related to smoking rather than to the airway obstruction itself.

In this connection, Milic-Emili and others [65] have proposed progression of lung injury associated with cigarette smoking characterized by three sequential stages in which (i) closing capacity exceeds functional residual capacity, followed by (ii) tidal expiratory flow limitation (first during supine then in seated posture) leading to (iii) dynamic hyperinflation [with resultant decrease in the inspiratory capacity (IC)] producing exertional dyspnea and exercise limitation [2, 66]. This sequence of events generates peripheral airway damage, but patients may not be uniformly susceptible to these effects of tobacco smoke. It is possible that regulation of certain genes are influenced by repetitive expansion and contraction of airways. In some ways, airway injury is akin to ventilator-induced alveolar injury occurring during acute respiratory distress syndrome [67, 68]. Analysis of genetic variants may determine which patients are likely to develop such changes based on molecular and cellular studies of airway and alveolar structure and function, leading to selection of agents that prevent or reverse such changes.

Because COPD is progressive over time, lung damage is present long before the patient becomes symptomatic. The development of small airway changes and centriacinar emphysema have been observed in resected lung tissue [69]. Tests of small airway function such as forced oscillatory technique (exhibiting  increased respiratory impedance) and gas washout techniques (revealing increased closing volume) can be abnormal in the presence of normal spirometry [70]. When such patients with very mild COPD are exercised under carefully controlled conditions, they exhibit higher ventilatory demand related to increased dead space physiology, reduced exercise tolerance, and, late in exercise, an increase in end-expiratory volume with reciprocal reduction in the IC [71]. Unlike patients with established COPD, they maintain or increase their oxygenation, with no change in an already increased resting alveolar-arterial oxygen difference. In another study, the same authors compared physiologic measurements during rest and incremental exercise in patients with minor spirometric changes, with and without chronic bronchitis (mucus hypersecretion) (CB), and healthy controls [72]. Patients with CB reported more respiratory symptoms related to physical activity and reduced health-related quality of life than patients without CB despite similar spirometric abnormalities, and patients with CB exhibited greater exertional dyspnea and dynamic respiratory limitations than patients without CB [as shown by smaller IC, smaller tidal volume, and higher respiratory rate at a given work rate in the patients with CB]. The findings of this study provide a physiologic explanation for the chronic dyspnea and poor health status of patients with the CB phenotype, and a potential for further evaluation of drugs such as antimuscarinics, phsophodiesterase inhibitors and long-acting bronchodilators.

An intriguing concept has been the role that airway basal cells play in the pathogenesis of COPD [73]. When exposed to the constant stress of smoking, basal cells lose capacity to regenerate normal epithelium by as much as one half in cell cultures [74]. In addition to its anti-protease activity, alpha-1-antitrypsin (AAT) also has a major anti-inflammatory role [75]. Furthermore, the lungs of patients with AAT deficiency have been shown to exhibit an adaptive immune inflammation response regulated by CD4+ and CD8+ T cells, B cells and lymphoid follicles with oligoclonal or monoclonal B cells [76]. These findings in AAT deficient patients are similar to those in usual COPD, suggesting that similar inflammatory mechanisms are at play in both diseases; they may also explain, in part, why some patients with AAT deficiency do not develop emphysema or develop a milder form of it. Thus, even in a specific form of emphysema such as that due to AAT deficiency, modifying genetic factors can result in phenotypic variation.

Even after cessation of smoking, some patients exhibit a progressive decline in lung function [77], implying the contribution of age-related factors to tobacco exposure in lung injury. In this connection, short telomeres are a potent inducer of cell aging and apoptosis [78-80]. Telomerase is a polymerase that synthesizes telomere repeats [81]. Its mutations cause telomere shortening and are reflected in age-related lung disease such as idiopathic pulmonary fibrosis and emphysema. Mice with short telomeres exposed to cigarette smoke develop alveolar enlargement by causing additive DNA damage to telomere dysfunction, inhibiting proliferative recovery, and failure to down-regulate cellular senescence [82].

Not everyone with COPD has smoked tobacco. In a Danish population study, Thomsen and colleagues [83] tested the hypothesis that individuals who have never smoked have different characteristics and less severe outcomes than smokers. They assessed characteristics, symptoms, disease severity, and serum concentrations of inflammatory biomarkers at baseline, and the risk of respiratory-related hospitalizations, cardiovascular comorbidities and all-cause mortality in nearly 7,000 patients with COPD and no asthma, and compared them to a cohort of over 24,000 never smokers without COPD during a median follow up of 4 years. Never-smokers with COPD exhibited a family history of asthma and milder disease limited to the lungs compared with current and former smokers with COPD. Despite respiratory-related morbidity being significant in never smokers with COPD, overall prognosis was better in never smokers with COPD than in smokers with COPD.

The largest GWAS of radiographic characterization in lung disease [84] has been a combined analysis of 3 separate cohorts: (1) the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) Study [85-87] (figures 5 and 6), (2) a cohort from Bergen, Norway [88-91], and (3) the National Emphysema Treatment Trial (NETT) [92]. The most significant finding was at the B1CD1 locus with the presence of emphysema as a radiologist-assessed qualitative trait. B1CD1 is one of two human homologues of BicD protein which forms a complex with dynein-dynactin playing an important role in dynein cellular functions, including mitosis, nuclear migration, and transport of axonal and dendritic vesicles. The effect of B1CD1 in emphysema could be related to shortened telomeres (see above). Impeding telomere shortening through this pathway may be a means to prevent or retard the development of emphysema.

pulm fig 11.5

Figure 5. Network layout of the systemic inflammatory response (inflammome) in non-smokers (n = 202), smokers with normal lung function (n = 297) and COPD patients (n = 1755) at recruitment. Each node of the network corresponds to one of the six inflammatory biomarkers determined in this study (see color code at top), and its size is proportional to the prevalence of abnormal values (0.95th percentile of nonsmokers)of that particular biomarker in that particular group of subjects (precise figure shown inside of each node). Two nodes are linked if more than 1% of subjects in the network share abnormal values of these two biomarkers, its width being proportional to that proportion [87].

In a GWAS meta-analysis of quantitative imaging, combining data from the COPDGene, ECLIPSE, NETT and GenKols studies (comprising more than 12,000 subjects), genome-wide significant associations with loci previously known to be associated with COPD or with spirometric evidence for airflow limitation were identified [93]. In addition, new GWAS with emphysema and variants near SERPINA10 and DLC1 were described. Of note, the study also showed increased risk for emphysema in individuals with PI MZ (a heterozygous form of alpha-1 antitrypsin deficiency). This large study of quantitative imaging further advances efforts to identify risk factors for COPD phenotypes and imaging aspects associated with previously identified genetic loci.

pulm fig 11.6

Figure 6. Proportion of patients with none, one, or two (or more) biomarkers (WBC count, CRP, IL-6 and fibrinogen) in the upper quartile of the COPD distribution, at baseline (left bars) and after one year follow up (right bars) [87].

Along the same lines, not all smokers develop airway wall thickening with consequent expiratory flow limitation, as shown in studies of familial aggregation [94] and COPD candidate genes associated with airway wall thickening [95]. More recently, Dijkstra et al [96] found that 3 significant loci on chromosomes 2q and 10q were associated with airway wall thickening as assessed by low-dose CT scanning, as well as being associated with bronchial inflammation, emphysema, and expiratory flow limitation.

Specific clinical associations: Exacerbations, ethnicity and gender

Exacerbations become more frequent (and more severe) as the severity of COPD increases. Exacerbation rates in the first year of follow-up increase with severity of COPD as defined by GOLD [38]. The single best predictor of exacerbations, across all GOLD stages, was a history of exacerbations. The frequent-exacerbation phenotype appeared to be relatively stable over a period of 3 years and could be predicted on the basis of the patients’ recall of previous treated events. In addition to its association with more severe disease and prior exacerbations, the phenotype was independentlyassociated with a history of gastroesophageal reflux or heartburn, poorer quality of life, and elevated white-cell count. The risk of exacerbation, while not associated with a lower FEV1 and can often occur in any GOLD stage, does increase with decreasing FEV1.The rate at which AECOPD occurred appears to reflect an independent susceptibility phenotype, regardless of the GOLD stage. This has implications for the targeting of exacerbation-prevention strategies across the spectrum of disease severity.

Findings from the first 2,500 individuals enrolled in the COPDGene study confirmed that female gender is important in the development of severe, early-onset COPD [97-99]. These patients smoke less, suggesting that additional influences, such as genetic and maternal factors and their interaction may play more important roles. Subjects in the COPDGene study were also significantly younger than older patients with severe COPD and had less time to accumulate pack-years of smoking. Cluster analysis attempts to organize information so that heterogeneous groups of variables can be classified into relatively homogeneous groups, and has been used to assess phenotypic heterogeneity in airway diseases [100]. Recent application of a cluster method in 10,000 smokers in the COPDGene study has identified four clusters of smokers with distinct patterns of airway wall thickness, emphysema distribution and severity showing strong association with relevant clinical measures and known COPD associated genetic variants [101].

Racial ancestry constitutes increasing interest in the area of human health as a result of projects like the HGDP [102] and the 1000 Genomes Project [103]. Genome-wide genotyping has shown that Native American ancestry is inversely associated with COPD but positively associated with FEV1 or FVC in racially admixed Costa Ricans, even after accounting for age, sex, height, educational level, and current smoking but this relationship becomes less significant with increase in pack-years of smoking [104]. Yet the estimated effect of Native American ancestry on FEV1 or FVC remains significant after excluding subjects with COPD or adjusting for intensity of smoking, suggesting additional effects exerted by genetic factors such as body habitus (trunk-to-limb ratio).

The Proyecto Latinoamericano de Investigacion en Obstruccion Pulmonar (PLATINO)

study assessed different aspects of the chronic bronchitis (CB) phenotype in a large cohort from five Latin American cities [105]. Specifically, it evaluated the frequency of the CB phenotype in subjects with and without COPD in the PLATINO population, and the association of symptoms of CB with airway obstruction, general health status, physical activity and frequency of exacerbations. Using the definition of CB as productive cough for at least 3 months of the year for at least 2 years, the prevalence of this phenotype in COPD and non-COPD subjects was 14% and 6%, respectively. Those with CB exhibited more respiratory symptoms and exacerbations, worse general health status, more physical activity limitation, lower age, and worse lung function.

While there has been increasing interest in health related- quality of life (HR-QOL) amongst Latinos with various chronic conditions [106], less is known about the influence of COPD in this population [107]. A recent analysis of the National Health and Nutrition Examination Survey (NHANES) using HR-QOL data from surveys conducted in 2007-2008 and 2009- 2010 compared adult Mexican-Americans with a non-Hispanic white cohort, all of whom had undergone spirometry [108]. Mexican-Americans reported a more severe impact of COPD on health status than non-Hispanic whites, the most important factor being socioeconomic disparities (education and access to health care). Additional comorbidities, physical impairment, and current smoking status contributed to a lesser extent to fair or poor health status. This study extended previous findings concerning Hispanics with metabolic syndrome [106] and Mexican-Americans living in colonias on the Texas-Mexico border [109]. Han et al [110] found similar worsening of HR-QOL in African-Americans experiencing exacerbations of COPD. Factors influencing quality of life should be considered by the clinician when planning for and counseling in the management of individuals with differing ethnic backgrounds.

Management Implications: General Principles and Recent Gene and Phenotype Associations

Management of currently recognized phenotypes of COPD has been discussed in previous sections of this chapter. Medical management of COPD has followed guidelines as recommended by the GOLD consensus statement [3], and is based on the severity of the condition as assessed by FEV1. Maintenance therapy consists of an ascending scale of short- and long-acting bronchodilators with the addition of inhaled corticosteroids (figure 3). Recently phosphodiesterase inhibitors have made a comeback to supplement regimens (theophylline being commonly used half a century ago). How patients respond to this approach is variable, and some individuals show poor response despite combination therapy in maximum acceptable doses. In addition to phenotypic characterization of COPD subtypes, response to specific therapy likely depends on age, gender, and disease severity by lung function.

Recent studies on the beta-2 adrenergic receptor gene, ADRB2, have yielded variable responses to combinations of long-acting beta-2 agonists and inhaled corticosteroids [111-114]. In a clinical trial of over 5,000 COPD patients, patients homozygous for the Arg16 variant of the ADRB2 gene and using salmeterol exhibited decreased risk for exacerbations in contrast to placebo or tiotropium [115].

Daily azithromycin administration decreases the frequency of AECOPD [116] but its efficacy varies with age, smoking status, GOLD stage, oxygen supplementation and inhalation therapy. A recent comprehensive analysis showed that the drug was most effective in reducing AECOPD (by 17% to 24%) in patients receiving antibiotics and steroids combined, suggesting more prevention of more severe exacerbations [117]. Individuals aged 65 years or older and in milder GOLD stages seemed to benefit more from the azithromycin. Based on adjusted, multivariate  group analyses, sex, history of chronic bronchitis, use of oxygen and bronchodilator therapy had no significant influence response to the compound. Azithromycin inhibits mucin production at the transcriptional level [118], and is possibly counteracted by smoking. At the same time, because smoking also impairs host immunity, azithromycin may exhibit benefit through its antimicrobial effects.

The National Emphysema Treatment Trial identified a subgroup of patients with upper lobe predominant emphysema and low exercise capacity that would benefit from LVRS [92].

Conclusions and Future Directions

COPD is a heterogeneous disease. Understanding its pathogenesis as well as management is unlikely if the disease is viewed as a single entity. Subcategories of COPD used currently are nonspecific and future subgrouping increasingly needs novel approaches. Understanding COPD susceptibility depends on pursuing genome-wide studies that elucidate phenotyping and genotyping. Genes that are identified should be localized within molecular pathways to assess the role of these networks in disease pathogenesis. Once critical pathways are identified, means to inhibit those pathways should lead to disease-modifying therapy. It is hoped that understanding the genetics of COPD will play a major role in the development of personalized medicine: genetic information will define an individual’s disease characteristics, potential complications, co-morbidities and treatment. Coupled with the elimination of cigarette smoking, this approach will ultimately lower the burden of COPD.

Conflict of Interest Statement

The authors have no conflicts to declare.



1.Berndt A, Leme AS, Shapiro D. Emerging genetics of COPD. EMBO Mol Med. 2012, 4(11): 1144–1155.

2.Eltayara L, Becklake MR, Volta CA, Milic-Emili J. Relationship between chronic dyspnea and expiratory flow-limitation in patients with chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 1996, 154: 1726-1734.

3.Global strategy for the diagnosis, management and prevention of COPD. GOLD website, January 2014.

4.Mannino DM, Gagnon RC, Petty TL, Lydick E. Obstructive lung disease and low lung function in adults in the United States: data from the National Health and Nutrition Examination Survey, 1988-1994. Arch Intern Med. 2000, 160(11): 1683-1689.

5.Han MK, Kim MG, Mardon R, Renner P, Sullivan S et al. Spirometry utilization for COPD: how do we measure up? Chest. 2007, 132(2): 403-409.

6.Pauwels RA, Buist AS, Calverley PM, Jenkins CR, Hurd SS. Global strategy for the diagnosis , management, and prevention of chronic obstructive pulmonary disease. NHLBI/ WHO global initiative for chronic obstructive lung disease (GOLD) workshop summary. Am J Respir Crit Care Med. 2001, 163(5): 1256-1276.

7.Aaron SD, Dales RE, Cardinal P. How accurate is spirometry at predicting restrictive pulmonary impairment? Chest. 1999, 115(3): 869-873.

8.Swanney MP, Beckert LE, Frampton CM, Wallace LA, Jensen RL et al. Validity of the American Society and other spirometric algorithms using FVC and forced expiratory volume in 6 s for predicting a reduced total lung capacity. Chest. 2004, 126(6): 1861-1866.

9.Vandewoorde J, Verbanck S, Schuermans D, Broekaert L, Devroey D et al. Forced vital capacity and forced expiratory volume in six seconds as predictors of reduced total lung capacity. Eur Respir J. 2008, 31(2): 391-395.

10.Wan ES, Hokanson JE, Murphy JR, Regan EA, Make BJ et al. Clinical and radiographic predictors of GOLD-unclassified smokers in the COPDGene study. Am J Respir Crit Care Med. 2011, 184(1): 57-63.

11.Mair G, Maclay J, Miller JJ, McAllister D, Connell M et al. Airway dimensions in COPD: relationships with clinical variables. Respir Med. 2010, 104(11): 1683-1690.

12.Coxson HA, Leipsic J, Parraga G, Sin DD. Using pulmonary imaging to move COPD beyond FEV1. Am J Respir Crit Care Med. 2014, 190(2): 135-144.

13.Bergin C, Müller N, Nichols DM, Lillington G, Hogg JC et al. A computed tomographic-pathologic correlation. A Rev Respir Dis. 1986, 133(4): 541-546.

14.Schroeder JD, McKenzie AS, Zach JA, Wilson CG, Curran-Everett D et al. Relationships between airflow obstruction and quantitative CT measurements of emphysema, air trapping, and airways in subjects with and without chron-ic obstructive pulmonary disease. AJR Am J Roentgenol. 2013,W460-W470.

15.Lutchmedial SM, Creed WG, Moore AJ, Walsh RR, Gentchos GE et al. How common is airflow limitation in patients with emphysema on CT scan of the chest? Chest. 2015, 148(1): 176-184

16.Han MK, Agusti A, Calverley PM, Celli BR, Criner G et al. Chronic obstructive pulmonary disease phenotypes. The future of COPD. Am J Respir Crit Care Med. 2010, 182(5): 598-604.

17.Dornhorst AC. Respiratory insufficiency (Frederick Price Memorial Lecture). Lancet. 1955, 268(6876): 1185-1187

18.Petty T. COPD: Clinical Phenotypes. Pulm Pharmacol Ther. 2002, 15(4): 341-351.

19.Castaldi PJ, San José Estépar R, Mendoza CS, Hersh CP, Laird N et al. Distinct quantitative computed tomography emphysema patterns are associated with physiology and function in smokers. Am J Respir Crit Care Med. 2013, 188(9): 1083-1090.

20.Dirksen A, MacNee W. The search for distinct and useful phenotypes in chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2013, 188(9): 1056-1046

21.Castaldi PJ, Cho MJ, San José Estépar R, McDonald ML, Laird N et al. Genome-wide association identifies regulatory loci associated with distinct local histogram emphysema patterns. Am J Respir Crit Care Med. 2014, 190(4): 399-409.

22.Miravitlles M, Soler-Cataluña JS, Calle M, Molina J, Almagro P et al. Spanish Guidelines for COPD (GesEPOC). Update 2014. Arch Bronconeumol. 2014, 50(Suppl 1): 1-16.

23.From the Global Strategy for Asthma Management and Prevention, Global Initiative for Asthma (GINA) 2015.

24.Soriano JB, Davis KJ, Coleman B, Visick G, Mannino D et al. The proportional Venn diagram of obstructive lung disease: two approximations form the United States and the United Kingdom. Chest. 2003, 124(12): 474-481.

25.Iwamoto H, Gao J, Koskela J, Kinnula V, Kobayashi H et al. Differences in plasma and sputum biomarkers between COPD and COPD-asthma overlap. Eur Respir J. 2014, 43(2): 421-429.

26.Polosa R, Thomson NC. Smoking and asthma: dangerous liaisons. Eur Respir J. 2013, 41(3): 716-726.

27.Boulet LP, Lemiere C, Archambault F, Carrier G, Descary MC et al. Smoking and asthma: clinical and radiologic features, lung function and airway inflammation. Chest. 2006, 129(3): 661-668.

28.Bumbacea D, Campbell D, Nguyen L, Carr D, Barnes PJ, et al. Parameters associated with persistent airflow obstruction in chronic severe asthma. Eur Respir J. 2004, 24(1): 122-128.

29.Hardin M, Cho M, McDonald ML, Beaty T, Ramsdell J et al. The clinical and genetic features of COPD-asthma overlap syndrome. Eur Respir J. 2014, 44(2): 341-350.

30.Han MK, Curran-Everett D, Dransfield MT, Liu LX, Murray S et al. Chronic obstructive pulmonary disease exacerbations in the COPDGene study: associated radiologic phenotypes. Radiology. 2011, 261(1): 274-282.

31.Cosio BG, Soriano JB, López-Campos JL, Calle-Rubio M, Soler-Cataluna JJ et al. Defining the Asthma-COPD overlap syndrome in a COPD cohort. Chest. 2015.

32.Kitaguchi Y, Komatsu Y, Fujimoto K, Hanaoka M, Kubo K et al. Sputum eosinophilia can predict responsiveness to inhaled corticosteroid treatment in patients with overlap syndrome of COPD and asthma. Int J Chron Obstruct Pulmon Dis. 2012, 7: 238-239.

33.Christenson SA, Steiling K, van den Berghe M, Hijazi K, Hiemstra PS et al. Clinical relevance of genomic signatures of type 2 inflammation in chronic obstructive pulmonary disease. Am J Respir Crit Care. 2015, 191(7): 758-766.

34.Chou KT, Su KC, Huang SF, Hsiao YH, Tseng CM et al. Exhaled nitric oxide predicts eosinophilic airway inflammation in COPD. Lung. 2014, 192(4): 499–504.

35.Soler-Cataluna JJ, Rodriguez-Roisin R. Frequent chronic obstructive pulmonary disease exacerbators: how much real, how much fictitious? COPD. 2010, 7(4): 276-284.

36.Bhowmik A, Seemungal TA, Sapsford RJ, Wedzicha JA. Relation of sputum inflammatory markers to symptoms and lung function changes in COPD exacerbations. Thorax. 2000, 55(2): 114-120.

37.Sapey E, Stockley RA. COPD exacerbations. 2: aetiology. Thorax. 2006, 61(3): 250-258.

38.Hurst JR, Vestbo J, Anzueto A, Locantore N, Müllerova H et al. and the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) Investigators. Susceptibility to exacerbation in chronic obstructive pulmonary disease. N Engl J Med. 2010, 363(12): 1128-1138

39.Donaldson GC, Seemungal TA, Bhowmik A, Wedzicha JA et al. Relationship between exacerbation frequency and lungfunction decline in chronic obstructive pulmonary disease. Thorax. 2002, 57(10): 759-764.

40.Halpin DM, Decramer M, Celli B, Kesten S, Liu D et al. Exacerbation frequency and course of COPD. Int J Chron Obstruct Pulmon Dis. 2012, 7: 653-661.

41.Halpin DM, Decramer M, Celli B, Kesten S, Leimer I et al. Risk of nonlower respiratory serious adverse events following COPD exacerbations in the 4-year UPLIFT trial. Lung. 2011, 189(4): 261-268.

42.Donaldson GC, Hurst JR, Smith CJ, Hubbard RB, Wedzicha JA. Increased risk of myocardial infarction and stroke following exacerbation of COPD. Chest. 2010, 137(5): 1091- 1097.

43.Wedzicha JA, Brill SE, Allinson JP, Donaldson GC. Mechanisms and impact of the frequent exacerbator phenotype in chronic obstructive pulmonary disease. BMC Med. 2013, 11: 181.

44.Martinez FJ, Calverley PMA, Goehring U-M, Brose M, Fabbri LM et al. Effect of roflumilast on exacerbations in patients with severe chronic obstructive pulmonary disease uncontrolled by combination therapy (REACT): a multicentre randomised controlled trial. Lancet. 2015, 385(9971): 857-866.

45.Fabbri LM, Calverley PM, Izquierdo-Alonso JL, Bundschuh DS, Brose M et al. Roflulimast in moderate to severe chronic obstructive pulmonary disease treated with longacting bronchodilators: two randomized clinical trials. Lancet. 2009, 374(9691): 695-703.

46.Sethi S, Jones PW, Theron MS, Miravitlles M, Rubinstein E et al. Pulsed moxifloxacin for the prevention of exacerbations of chronic obstructive pulmonary disease: a randomized controlled trial. Respir Res. 2010, 11:88.

47.Uzun S, Djamin RS, Kluytmans JA, Mulder PG, van’t Veer NE et al. Azithromycin maintenance treatment in patients with frequent exacerbations of chronic obstructive pulmonary disease (COLUMBUS): a randomized, double-blind, placebo-controlled trial. Lancet Respir Med. 2014, 2(5): 361-368.

48.Zheng JP, Wen FQ, Bai CX, Wan HY, Kang J. Twice daily N-acetylcysteine 600mg for exacerbations of chronic obstructive pulmonary disease (PANTHEON): a randomized, double-blind placebo-controlled trial. Lancet Respir Med. 2014, 2(3): 187-194.

49.Tse HN, Raiteri L, Wong KY, Yee KS, Ng LY et al. High-dose N-acetylcysteine in stable COPD: the 1-year, double-blind, randomized, placebo-controlled HIACE study. Chest. 2013, 144(1): 106-118

50.Nishimura M, Makita H, Nagai K, Konno S, Nasuhara Y et al. Annual change in pulmonary function and clinical phenotype in chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2012, 185(1): 44-52.

51.Almagro P, Salvadó M, García-Vidal C, Rodríguez-Carballeira M, Cuchi E et al. Pseudomonas aeruginosa and mortality after hospital admission for chronic obstructive pulmonary disease. Respiration. 2012, 84(1): 36-43.

52.Martinez CH, Chen Y-H, Westgate PM, Liu LX, Murray S et al. Relationship between quantitative CT metrics and health status and BODE in COPD. Thorax. 2012, 67(5): 399-406

53.Vogelmeier CF, Bateman ED, Pallante J, Vijay KT Alagappan, , Peter D’Andrea et al. Efficacy and safety of once-daily QVA149 compared with twice-daily salmeterol–fluticasone in patients with chronic obstructive pulmonary disease (ILLUMINATE): a randomised, double-blind, parallel group study. The Lancet Respiratory Medicine. 2013, 1(1): 51–60.

54.Mahler D, Decramer M, D’Urzo A, Worth H, White Tet al. Dual bronchodilation with QVA149 reduces patient-reported dyspnoea in COPD: the BLAZE study. ERJ. 2014, 43(6): 1599-1609.

55.Eriksson S. Pulmonary emphysema and alpha-1 antitrypsin deficiency. Acta Medica Scandinavica. 1964, 175: 197- 205.

56.Hancock DB, Eijgelsheim M, Wilk JB, Gharib SA, Loehr LR et al. Meta-analyses of genome-wide association studies identify multiple loci associated with pulmonary function. Nat Genet. 2010, 42(1): 45-52.

57.Gross P, Pfitzer EA, Tolker E, Babyak MA, Kaschak M. Experimental emphysema: its product papain in normal and silicotic rats. Arch Environ Health. 1965,11: 50-58.

58.Shapiro SD. Animal models for COPD. Chest. 2000, 17: 223S-227S

59.Hautamaki RD, Kobayashi DK, Senior RM, Shapiro SD. Requirement for macrophage elastase for cigarette smoke-induced emphysema in mice. Science .1997, 277(5334): 2002-2004.

60.Shaykiev R, Otaki F, Bonsu P, Dang DT, Teater M. Cigarette smoking reprograms apical junctional complex molecular in the human airway epithelium in vivo. Cell Mol Life Sci. 2011, 68(5): 877-892.

61.Milara J, Peiró T, Serrano, Cortijo J. Epithelial to mesenchy-mal transition is increased in patients with COPD and induced by cigarette smoke. Thorax. 2013, 68(5): 410-420.

62.Hogg JC. Bronchial mucosal permeability and its relationship to airways hyperreactivity. Eur J Respir Dis Suppl. 1982, 122: 17-22.

63.Heijink IH, Noordhoek JA, Times W, van Oosterhout AJ, Postma DS. Letter to the editor. Abnormalities in airway epithelial junction formation in chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2014, 189(11): 1439-1442.

64.Stoll P, Heinz A-S, Bratke K, Bier A, Garbe K et al. Impact of smoking on dendritic cell phenotypes in the airway lumen of patients with COPD. Respir Res. 2014, 15: 48-57.

65.Milic-Emili J, Pecchiari M, D’Angelo E. Pathophysiology of chronic obstructive lung pulmonary disease. Curr Respir Med Rev. 2008, 4: 250-257.

66.Milic-Emili J, Koulouris N, Tantucci C. Spirometric predictions of exercise limitation in patients with chronic obstructive pulmonary disease. In Physiologic Basis of Respiratory Disease, eds. Hamid Q, Shannon J, Martin J. BC Dekker Inc, Hamilton, Canada, 2005, ch. 58, pp. 671-679.

67.D’Angelo E, Pecchiari M, Della Valle P, Koutsoukou A, Milic- Emili J. Effects of mechanical ventilation at low lung volume on respiratory mechanics and nitric oxide exhalation in normal rabbits. J Appl Physiol 2005, 99(2): 433-444.

68.Taskar V, John J, Evander E, Robertson B, Jonson B. Surfactant dysfunction makes lungs vulnerable to repetitive collapse and reexpansion. Am J Respir Crit Care Med. 1997, 155(1): 313-320.

69.Hogg JC, McDonough JE, Suzuki M. Small airway obstruction in COPD: New insights based on micro-CT imaging and MRI imaging. Chest. 2013, 143(5):1436-1443.

70.Usmani OS, Barnes PJ. Assessing and treating small airways disease in asthma and chronic obstructive pulmonary disease. Ann Med. 2012, 44(2): 146-156.

71.Elbehairy AF, Ciavonaglia CE, Webb KA, Guenette JA, Jensen D et al. Pulmonary gas exchange abnormalities in mild chronic obstructive pulmonary disease: implications for dyspnea and exercise intolerance. Am J Respir Crit Care Med. 2015, 191(12): 1384-1394

72.Elbehairy AF, Raghavan N, Cheng S, Yang L, Webb KA et al. Physiologic characterization of the chronic bronchitis phenotype in GOLD grade IB COPD. Chest. 2015, 147(5): 1235-1245..

73.Crystal RG. Airway basal cells. The “smoking gun” of chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2014, 190(12): 1355-1362.

74.Staudt MR, Burto-Auriemma L, Walter MS, Salit J, Vincent T et al. Airway basal stem/progenitor cells have diminished capacity to regenerate airway epithelium in COPD. Am J Respir Crit Care Med. 2014, 190(8): 955-8.

75.Bergin DA, Hurley K, McElvaney NG, Reeves EP. Alpha-1antitrypsin: a potent anti-inflammatory and potential novel therapeutic agent. Arch Immunol Ther Exp (Warzs). 2012, 60(2): 81-97.

76.Baraldo S, Turatto G, Lunardi F, Bazzan E, Schiavon M et al. Immune activation in α 1-antitrypsin-deficiency emphysema. Beyond the protease-antiprotease paradigm. Am J Respir Crit Care Med. 2015, 191(4): 402-409.

77.Tuder RM, Yoshida T, Arap W, Pasqualini R, Petrache I. State of the Art. Cellular and molecular mechanisms of alveolar destruction in emphysema: an evolutionary perspective. Proc Am Thorac Soc. 2006, 3(6): 503-510.

78.Harley CB, Futcher AB, Greider CW. Telomeres shorten during ageing of human fubroblasts. Nature. 1990, 345(6274): 458-460.

79.Lee HW, Blasco MA, Gottlieb GJ, Horner JW II, Greider CW et al. Essential role of mouse telomerase in highly proliferative organs. Nature. 1998, 392(6676): 569-574.

80.D’Adda di Fagagna F, Reaper PM, Clay-Farrace L, Fiegler H et al. A DNA damage checkpoint response in telomere-initiated senescence. Nature. 2003, 426(6963): 194-198.

81.Greider CW, Blackburn EH. The telomere terminal transferase of tetrahymena is a ribonucleoprotein enzyme with two kinds of prier specificity. Cell. 1987, 51(6): 887-898.

82.Alder JK, Guo N, Kembou F, Parry EM, Anderson CJ et al. Telomere length is a determinant of emphysema susceptibility. Am J Respir Crit Care Med. 2011, 184(8): 904-912.

83.Thomsen M, Nordestgaard BG, Vestbo J, Lange P. Characteristics and outcomes of chronic obstructive pulmonary disease in never smokers in Denmark: a prospective population study. Lancet Respir Med. 2013, 1(7): 543-550.

84.Kang X, Cho MH, Anderson W, Coxson HO, Muller N et al. Genome-wide association study identifies B1CD1 as a susceptibility gene for emphysema. Am J Respir Crit Care Med. 2011, 183(1): 43-49.

85.Vestbø J, Anderson W, Coxson HO, Crim C, Dawber Fet al. Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-Points (ECLIPSE). Eur Respir J. 2008, 31(4): 869-873.

86.Lomas DA, Silverman EK, Edwards LD, Locantore NW, Miller BE et al. Serum surfactant protein D is steroid sensitive and associated with exacerbations of COPD. Eur Respir J. 2009, 34(1): 95-102.

87.Agusti A, Edwards LD, Rennard SI, MacNee W, Tal-Singer R et al. Persistent systemic inflammation is associated with poor clinical outcomes in COPD: A novel phenotype. PLoS ONE. 2012, 7(5): 1-10.

88.Zhu G, Warren L, Aponte J, Gulsvik A, Bakke P et al. The SERPINE2 gene is associated with chronic obstructive pulmonary disease in two large populations. Am J Respir Crit Care Med. 2007, 176(2): 167-173.

89.Pillai SG, Zhu G, Gulsvik A, David A. Lomas, Edwin K. Silverman. SERPINE2 and COPD. Am J Respir Crit Care Med. 2007, 176(7): 726.

90.Eagan TML, Gulsvik A, Eide GE, Bakke PS. Remission of respiratory symptoms by smoking and occupational exposure in a cohort study. Eur Respir J. 2004, 23(4): 589-594

91.Brogger J, Eagan T, Eide G, Bakke P, Gulsvik A. Bias in retrospective studies of trends in asthma incidence. Eur Respir J. 2004, 23(2): 281-286.

92.Fishman A, Martinez F, Naunheim K, Piantadosi S, Wise R et al. A randomized trial comparing lung-volume-reduction surgery with medical therapy for severe emphysema. N Engl J Med. 2003, 348(21): 2059-2073.

93.Cho MH, Castaldi PJ, Hersch CP, Hobbs BD, Barr RG et al. A genome-wide association study of emphysema and airway quantitative imaging phenotypes. Am J Respir Crit Care Med. 2015, 192(5): 559-69.

94.Patel BD, Coxson HO, Pillai SG, Agustí AG, Calverley PM et al. International COPDGenetics Network. Airway wall thickening and emphysema show independent familial aggregation in chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2008, 178(5): 500-505.

95.Kim WJ, Hoffman E, Reilly J, Hersh C, Demeo D et al. Association of COPD candidate genes with computed tomography emphysema and airway phenotypes in severe COPD. Eur Respir J. 2011, 37(1): 39-43.

96.Dijkstra AE, Postma DS, van Ginneken, Wielpütz MO, Schmidt M et al. Novel genes for airway wall thickness identified with combined genome-wide association and expression analyses. Am J Respir Crit Care Med. 2015, 191(5): 547-556.

97.Foreman MG, Zhang L, Murphy J, Hansel NN, Make B et al. Early-onset chronic obstructive Pulmonary disease is associated with female sex, maternal factors, and African American race in the COPDGene study. Am J Respir Crit Care Med. 2011, 184(4): 414-420

98.Silverman EK, Weiss ST, Drazen JM, Chapman HA, Carey V et al. Gender-related differences in severe, early-onset chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2000, 162(6): 2152-2158.

99.Sorheim IC, Johannessen A, Gulsvik A, Bakke PS, Silverman EK et al. Gender differences in COPD: Are women more susceptible to smoking effects than men? Thorax. 2010, 65(6): 480-485.

100.Burgel P-R, Paillasseur J-L, Caillaud D, Tillie-Leblond I, Chanez P et al. Clinical COPD phenotypes: a novel approach using principal component and cluster analyses. Eur Respir J. 2010, 36(3): 531-539.

101.Castaldi PJ, Dy J, Ross J, Chang Y, Washko GR et al. Cluster analysis in the COPDGene study identifies subtypes of smokers with distinct patterns of airway disease and emphysema. Thorax. 2014, 69(5): 416-423.

102.Li JZ, Absher DM, Tang H, Southwick AM, Casto AM et al. Worldwide human relationships inferred from genome-wide patterns of variation. Science. 2008, 319(5866): 1100-1104.

103.1000 Genomes Project Consortium, Abecasis GR, Altshuler D, Auton A, Brooks LD et al. A map of human genome variation from population-scale [published correction appears in Nature. 2011, 473(7319): 1061-1073.

104.Chen W, Brehm JM, Boutaoui N, Soto-Quiros M, Avila L et al. Native American ancestry, lung function, and COPD in Costa Ricans. Chest. 2014, 145(4): 704-710.

105.de Oca MM, Halbert RJ, Lopez MV, Perez-Padilla R, Tálamo C et al. The chronic bronchitis phenotype in subjects with and without COPD: the PLATINO study. Eur Respir J. 2012, 40(1): 28-36.

106.Okosun IS, Annor F, Esuneh F, Okoegwale EE. Metabolic syndrome and impaired health-related quality of life in non-Hispanic white, non-Hispanic blacks and Mexican- American adults. Diabetes Metab Syndr. 2013, 7(3): 154-160.

107.Brehm JM, Celedon JC. Chronic obstructive pulmonary disease in Hispanics. Am J Respir Crit Care Med. 2008, 177(5): 473-478.

108.Martinez CH, Manino DM, Curtis JL, Han MK, Diaz AAet al. Socioeconomic characteristics are major contributors to ethnic differences in health status in obstructive lung disease. An analysis of the National Health and Nutrition Examination Survey 2007-2010. Chest. 2015, 148(1): 151-158.

109.Mier N, Ory MG, Zhan D, Conkling M, Sharkey JR et al. Health-related quality of life among Mexican Americans living in colonias at the Texas-Mexico border. Soc Sci Med. 2008, 66(8): 1760-1771.

110.Han MK, Curran-Everett D, Dransfield MT, Criner GJ, Zhang L et al. COPDGene Investigators. Racial differences in quality of life in patients with COPD. Chest. 2011, 140(5): 1169-1176.

111.Hizawa N. Pharmacogenetics of chronic obstructive pulmonary disease. Pharmacogenomics. 2013, 14(10): 1215-1225.

112.Hersh CP. Pharmacogenetics of chronic obstructive pulmonary disease: challenges and opportunities. Pharmacogenomics. 2010, 11(2): 237-247.

113.Bleecker ER, Meyers DA, Bailey WC, Sims AM, Bujac SR et al. ADRB2 polymorphisms and budesonide/formoterol responses in COPD. Chest. 2012, 142(2): 320-328.

114.Yelensky R, Li Y, Lewitzky S, Leroy E, Hurwitz C et al. A pharmacogenetic study of ADRB2 polymorphisms and indacaterol response in COPD patients. Pharmacogenomics. 2012, 12(16): 484-488.

115.Rabe KF, Fabbri LM, Israel E, Kögler H, Riemann K et al. Effect of of ADRB2 polymorphisms on the efficacy of salmeterol and tiotropium in preventing COPD exacerbations: a prespecified substudy of the POET-COPD trial. Lancet Respir Med. 2013, 2(1): 44-53.

116.Albert RK, Connett J, Bailey WC, William C. Bailey, Richard Casaburi et al. Azithromycin for prevention of exacerbations of COPD. N Engl J Med. 2011, 365: 689-698.

117.Han MK, Tayob N, Murray S, Dransfield MT, Washko G et al. Predictors of chronic obstructive pulmonary disease exacerbation in response to daily azithromycin therapy. Am J Respir Crit Care Med. 2014, 189(12): 1503-1508.

118.Kanoh S, Rubin BK. Mechanisms of action and clinical application of macrolides as immunomodularity medications. Clin Microbiol Rev. 2010, 23(3): 590-615.

Cite this article: Baydur A. Phenotypic Variance in COPD: Recent Developments in Clinical, Radiographic and Molecular Aspects, and Relevance to Management Strategies. J J Pulmonol. 2015, 1(2): 011.

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