Front. Med. 2013, 7(4): 425–432 DOI 10.1007/s11684-013-0295-x

REVIEW

Heterogeneity of chronic obstructive pulmonary disease: from phenotype to genotype Xu Chen1, Xiaomao Xu2, Fei Xiao (

✉)1,a

1

Key Laboratory of Geriatrics, Beijing Institute of Geriatrics; 2Department of Respiratory Medicine, Beijing Hospital, Ministry of Health, Beijing 100730, China

© Higher Education Press and Springer-Verlag Berlin Heidelberg 2013

Abstract Chronic obstructive pulmonary disease (COPD) is one of the leading causes of morbidity and mortality throughout the world and is mainly characterized by persistent airflow limitation. Given that multiple systems other than the lung can be impaired in COPD patients, the traditional FEV1/FVC ratio shows many limitations in COPD diagnosis and assessment. Certain heterogeneities are found in terms of clinical manifestations, physiology, imaging findings, and inflammatory reactions in COPD patients; thus, phenotyping can provide effective information for the prognosis and treatment. However, phenotypes are often based on symptoms or pathophysiological impairments in late-stage COPD, and the role of phenotypes in COPD prevention and early diagnosis remains unclear. This shortcoming may be overcome by the potential genotypes defined by the heterogeneities in certain genes. This review briefly describes the heterogeneity of COPD, with focus on recent advances in the correlations between genotypes and phenotypes. The potential roles of these genotypes and phenotypes in the molecular mechanisms and management of COPD are also elucidated. Keywords

chronic obstructive pulmonary disease; heterogeneity; phenotype; genotype; prediction

Introduction Chronic obstructive pulmonary disease (COPD) is a common, preventable, and treatable disease mainly characterized by persistent and progressive airflow limitation. COPD is usually associated with enhanced chronic inflammatory response in the airways and lung to noxious particles or gases [1]. The incidence of COPD is about 3% to 11% in the general population but may be increased in smokers, males, and people older than 40 years [2,3]. In 1990, COPD ranked as the sixth leading cause of death worldwide but is estimated to become the fourth leading cause no later than 2030 [4]. As a complex disease, COPD can be influenced by various environmental and genetic factors, such as exposure to cigarette smoke and other noxious particles, asthma/bronchial hyper-reactivity, chronic bronchitis, infections, age, and gender. Heterogeneities in susceptibility genes can also lead to distinct responses of each person [5].

Received April 19, 2013; accepted August 22, 2013 Correspondence: [email protected]

Bottlenecks in COPD diagnosis and therapy The diagnosis, assessment, and treatment of COPD are mainly based on spirometry, clinical symptoms (including dyspnea, chronic cough, and sputum production), history of exposure to risk factors, and related comorbidities. Lung function tested by spirometry has been previously considered as the gold standard for COPD diagnosis, i.e., a postbronchodilator forced expiratory volume in one second (FEV1)/forced vital capacity (FVC) ratio < 0.70, indicating persistent airflow limitation [6]. However, the role of spirometry in COPD diagnosis and assessment has been questioned in recent years [7–9]. The arguments were as follows. First, no sufficient evidence has demonstrated that the fixed FEV1/FVC ratio is associated with improved COPD outcomes. Second, the FEV1/FVC ratio may result in misdiagnosis in adults younger than 45 years [10]. Third, patients with similar FEV1 can exhibit completely different clinical symptoms and therapeutic responses, as well as certain non-consistencies between spirometry tests and changes in chest CT scanning. Therefore, spirometry can be regarded as one parameter rather than an independent criterion for COPD diagnosis and treatment. A better

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combined assessment approach instead of the unidimensional FEV1/FVC ratio has been recommended to indicate airflow limitation [11]. Such an approach can comprehensively assess COPD according to symptoms (mMRC or CAT score is recommended for assessment), GOLD spirometric classification, and future risk of exacerbation. As a result, patients can be grouped into four as follows: (1) low risk, less symptoms; (2) low risk, more symptoms; (3) high risk, less symptoms; and (4) high risk, more symptoms.

COPD phenotypes The latest phenotypes based on different COPD elements may provide new insights. The phenotypes are based on the heterogeneities of COPD with some other obstructive lung diseases, particularly asthma, which shares some overlapped features with COPD in clinical symptoms, physiology, and airflow limitation [12]. The definition of COPD phenotype was first proposed in 2010 and refers to a single or combination of disease attributes that describe the diverse symptoms and outcomes (exacerbations, response to therapy, rate of disease progression, or death) of COPD patients [13]. Han et al. [14] also discussed the potential COPD phenotypes based on clinical and physiological manifestations, radiological characterization, COPD exacerbations, systemic inflammation, comorbidities, and other multidimensional indicators (Table 1). Clinical phenotypes have been assessed by obvious properties or presentations (e.g., age, gender, smoking history, and ethnicity) that can distinguish individuals with COPD and influence the outcomes [14–18]. Most studies have revealed that phenotypes grouped by the above properties significantly differ in terms of drug response, prognosis, as well as mortality and morbidity risks [19]. Although the FEV1/FVC ratio is not adequate to reflect the COPD complexity, the rapid physiological decline in FEV1 can be regarded as a distinct COPD phenotype. The decline in FEV1 is associated with age, gender, chronic productive cough, and some plasma biomarkers; the rate may decrease after smoking cessation [20,21]. FEV1 is a good indicator for COPD assessment and prognosis and is also a valuable predictor of morbidity, mortality, and hospitalization rate

Heterogeneity of COPD: from phenotype to genotype

[22,23]. Imaging phenotypes are identified by lung structural abnormalities [24] including emphysema, airway wall thickening and bronchiectasis, which can be measured by computed tomography (CT). The distribution and severities of these abnormalities are closely correlated with the clinical features and prognosis of COPD [25]. In fact, these three major clinical phenotypes of COPD have been identified by imaging tests, and certain overlaps are found to exist between these two phenotypes. Quantitative CT can also effectively identify the exacerbation phenotype and indicate the racial difference of COPD [26,27]. Acute exacerbation of COPD (AECOPD) is another phenotype defined as sustained worsening of a patient’s condition from a stable state to beyond normal day-to-day variation, which is acute at the onset and necessitates a change in regular medication in a patient with underlying COPD [28]. The frequency of AECOPD increases along with disease progression. Patients with AECOPD often have more severe functional impairments and higher risks of hospitalization and death. The immune pathogenesis of COPD can be interpreted as an inflammatory response to noxious stimuli [29]. COPD is a systemic inflammatory response syndrome mediated by complex interactions between innate/adaptive immune systems and numerous environmental factors. Therefore, systemic inflammation is also considered as a COPD phenotype [30]. Currently, a lymphatic vessel phenotype has been introduced, which can reflect the severe stages of COPD based on changes in distal lung immune cell traffic [31]. Systemic inflammation may also incur comorbidities, including cardiovascular diseases, asthma, lung cancer, diabetes and its precursors (obesity and metabolic syndrome), depression, cognitive impairment, and/or osteoporosis [32], thereby increasing the risk of death. Therefore, tailored management is required to improve COPD prognosis [33,34]. Kim et al. [35] analyzed COPDGene and revealed that the novel chronic bronchitis phenotype of COPD indicates the worse respiratory symptoms and higher risk of AECOPD. Thus, patients in this phenotype require more treatments to reduce risks. Many indices have been proposed to better describe COPD

Table 1 Phenotypes of COPD Phenotypes

Descriptions

Clinical phenotype

Including age, gender, smoking history, ethnicity, etc.

Rapid decline in FEV1

A distinct phenotype; the rate may decrease after smoking cessation

Imaging phenotype

Lung structural abnormalities measured by CT or quantitative CT

AECOPD

More severe impairments and higher risks of hospitalization and death

Systemic inflammation

COPD is also an inflammatory response to noxious stimuli

Lymphatic vessels phenotype

Reflects the stages by the changes of distal lung immune cell traffic

Comorbidities

Chronic bronchitis, cardiovascular diseases, asthma, diabetes, etc.

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prognosis. The most common is the BODE index, which refers to body mass index, obstruction of airflow, dyspnea, and exercise capacity. Other multidimensional indices such as E-BODE (BODE plus exacerbations), ADO (dyspnea, FEV1, and age), and SAFE (SGRQ score, air-flow limitation, and exercise tolerance) are also useful for predicting COPD prognosis [36–38]. Although phenotype classification can facilitate clinical trials and patient management [39], this method still has several limitations. Most importantly, phenotypes are identified by clinical symptoms and physiopathological changes in late-stage COPD [40,41], during which the symptoms are often too unspecific to be distinguished from other respiratory diseases and the pathophysiological measurements are not strongly suggestive [42]. Apart from phenotypes, the genetic susceptibility of COPD may be more informative.

COPD genotypes COPD is a multi-factorial disorder that displays familial aggregation. Genetic factors play significant roles in COPD in an environmental background. With the rapid development of sequencing technologies and bioinformatics, remarkable advances have been made in candidate genes and genome studies, indicating that certain genotypes involved in proteases and anti-proteases system, inflammation, oxidative stress, and many other processes are associated with current

phenotypes [43], some of which can even be regarded as an independent marker to guide the clinical practices and predict COPD prognosis (Table 2). Since 1964, SERPINA1 (or PI) gene located in 14q32.1 and coding for α1-antitrypsin (protease inhibitor 1) has been the only accepted COPD-associated gene. Variations decrease the inhibition activity of α1-antitrypsin (AAT) and disturb the microenvironment of pulmonary fibrous connective tissue. As a result, excessive protease damages the lung tissue and may even precipitate the development of emphysema. Thus far, the PI Z/Z genotype still predicts the highest risk of lung structure abnormalities, and its variation can boost the incidence of COPD by 6 to 50 times [44]. An increasing number of susceptibility genes or polymorphisms have been suggested to be associated with COPD, but their values still need further studies. In smokers, the 198 G/G genotype in ET-1 gene (coding for Endothelin-1) possesses higher risk to COPD than the TT genotype [45]. Most studies in different countries and races have congruously indicated that the cholinergic receptor-nicotinic-α 5/3 gene (CHRNA3/5) is strongly associated with COPD, whereas the rs6495309 CT or TT genotype in CHRNA3 gene is associated with a significantly decreased risk of COPD compared with the CC genotype [46–51]. In addition, in a multistage genome-wide association study (GWAS) carried out by Pillai et al. in 2009, the rs8034191 and rs1051730 genotypes in CHRNA3/5 have been associated

Table 2 Correlations between the phenotypes and genotypes of COPD Phenotype

Gene

Genotype

Function

Clinical Smoking

ET-1[44]

198G/G

Higher incidence of COPD in smokers ( – )

CHRNA3/5[45–50]

rs6495309 C/T& T/T rs8034191 C/C

Significantly decreased risk of COPD (+) Population attributable risk of 12.2% ( – )

EPHX1[61]

H139R

Weakly protective, significant in Asian(+)

Physiological FEV1

MMP12[53]

rs2276109 G/G

Reduced risk of the onset of COPD (+)

SOD3[54]

rs8192287 G/T rs8192288 G/T

Higher risk, reduced FEV1% predicted and FVC% predicted ( – )

HHIP[55]

rs11938704 rs10013495

Significantly associated with FEV1 in subjects with COPD

Imaging Emphysema

SERPINA1[43]

PI Z/Z

Incidence:1% to 2%; highest risk of COPD( – )

MMP-9[54]

– 1562C/T

Alter promoter activity, increased risk ( – )

IL6/IL6R[56]

rs4129267 C/T

Smoking induced inflammation ( – )

IL1RN[58]

*2 Alleles

Strong risk of COPD in Asian females ( – )

TNFA[56,57]

– 308A allele

Risk for the development of COPD ( – )

rs2241712 A/G

Protective (+)

Inflammation

TNFB1[57]

rs1982073 T/C rs1800469 C/T rs6957 A/G Note: (+) means protective predictor; ( – ) means negative predictor.

Increased risk of COPD ( – )

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with COPD phenotypes (based on FEV1/FVC). Moreover, these two single nucleotide polymorphisms (SNPs) reach genome-wide significance and can be replicated in an independent cohort study. The C allele in the rs8034191 is estimated to have a population-attributable risk for COPD of 12.2% [52]. Matrix metalloproteinases play a critical role in tissue remodeling and repair [53]. The minor allele (G) of rs2276109 in MMP12 is associated with the FEV1 phenotype and thus with a reduced risk of COPD onset [54]. The – 1562C/T in the MMP9 gene promoter is also associated with COPD in many countries, such as Japan, China, and Russia. Recently, rs8192287 and rs8192288 in superoxide dismutase 3 (SOD3) gene have been associated with increased risk for COPD in Copenhagen City Heart Study and also found with reduced predicted FEV1% and FVC% [55]. Other candidate genes including HOX1,FAM13A, GSTCD, TNS1, AGER, HTR4, THSD4, SOX5, MFAP2, TGFB2, HDAC4, RARB, MECOM, SPATA9, ARMC2, NCR3, ZKSCAN3, CDC123, C10orf11, LRP1, CCDC38, MMP15, CFDP1, KCNE2, RAB4B, EGLN2, MIA, CYP2A6, and HHIP are also associated with FEV1 in COPD patients, but their relationship with COPD risk is unclear [56]. COPD is a chronic inflammatory reaction during which tumor necrosis factor (TNF), transforming growth factor (TGF), and interleukin (IL) are the major inflammatory mediators. The 308A allele in the TNFA gene is a risk factor affecting COPD development, and four SNPs in TGFB1 (coding for TGF-β1) gene have been discovered to be related to COPD risk, i.e., the minor alleles of rs2241712, rs1982073, and rs1800469 are protective, but rs6957 provides significant increased risk of COPD [57,58]. IL6/IL6R has been widely studied, and rs4129267 C/T has been associated with smoking-induced inflammation. IL1RN VNTR (variable number of tandem repeats) polymorphisms (especially IL1RN*2 allele) are strong risks for COPD in Asians, especially among females [59]. In addition to these inflammatory factors, airway microorganisms (respiratory viruses and bacterial species) may release antigens, including endotoxin, peptidoglycan fragments, lipoproteins, and other molecules that may induce potent inflammatory effects and exacerbations [60,61]. Some genes coding xenobiotic metabolism enzymes that act as antioxidants to deleterious elements in smoke and gas are also regarded as genetic risk factors for COPD. In 2008, a meta-analysis reported that Y113H and H139R polymorphisms in microsomal epoxide hydrolase (EPHX1) gene predict a significant increase and slight reduction in COPD risk in Asian populations, respectively [62]. However, a larger metaanalysis in 2009 indicated that Y113H is not associated with COPD, and H139R only plays a weak protective role. Nevertheless, stratification for ethnicity implies that H139R is significantly associated with COPD only in Asians and not in Caucasians. Another enzyme in the antioxidant pathway is glutathione S-transferase subunit M1 (GSTM1), whose

Heterogeneity of COPD: from phenotype to genotype

homozygotes for the GSTM1 null allele have an increased risk of COPD [63]. Some polymorphisms in other candidate genes are also associated with lung structural abnormalities (phenotypes), although their potential predictive roles need to be further studied. Three SNPs in EPHX1 gene (rs2854450, rs3738043, and rs1009668) and five SNPs in SERPINE2 gene (rs6734100, rs729631, rs975278, rs6436449, and rs7608941) are significantly associated with emphysema. Two SNPs in CCL5 gene ( – 403G/A and – 28C/G) are associated with mild emphysema. Meanwhile, two SNPs (rs2854450, rs3753658) in the EPHX1 gene, two SNPs (rs1042717 and rs1042718) in the ADRB2 gene, and one SNP (rs6436459) in SERPINE2 gene are also correlated with airflow thickness in COPD patients.

Summary COPD is a complex disease caused by an imbalance between environmental and genetic factor (Fig. 1), although interactions are not yet well understood. Smoking is considered to be the major risk factor of COPD [64], while only 10% of smokers develop COPD. Pedigree and twin studies have shown that lung function is heritable, and COPD clusters within families. Genetic factors still play determining roles in COPD development, thus, COPDGene, one of the largest worldwide COPD study has been carried out to elucidate the latent inherited genetic factors of COPD. Its results might interpret the individual heterogeneities in susceptibilities, treatment responses, and other differences, and meanwhile provide some novel insights into COPD classification [65]. Meanwhile, the genotyping of COPD can elucidate particular polymorphisms shared with other pulmonary diseases, thereby reducing the delayed diagnosis and underestimation of COPD. However, in the past 50 years, only SERPINA1 gene has been well accepted as a strong genetic factor predicting the AAT deficiency trait in COPD. Unfortunately, only 1% to 2% of COPD patients are accounted for in this category. In summary, COPD is a multi-facet disorder with remarkable hereditary susceptibility. COPD may be feasibly predicted based on certain polymorphisms in a single gene because COPD is determined by a range of candidate genes in different pathways. A genome-wide joint meta-analysis has concluded that the joint testing of SNP and SNP-byenvironment interaction identifies novel loci associated with complex traits that are missed when considering only the genetic main effects [66,67]. Thus, multi-dimensional index models consisting of different genotypes may improve the assessment and prognosis of COPD. Moreover, combined detection of phenotypes and genotypes may dramatically increase the accuracy and efficiency of COPD diagnosis and monitoring. At present, a nationwide epidemiologic study is being

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Fig. 1

Interactions among different COPD factors.

conducted in China under the support of the National High Technology Research and Development Program. This research aims to create a large standard biobank and information system and to establish a key resource-sharing platform. Many significant loci for COPD may be identified, and a more comprehensive clinical scheme of early diagnosis and tailored treatment for COPD may be implemented. Afterwards, a more accurate and practical classification of COPD genotype can be expected.

Acknowledgements This work was supported by the National High Technology Research and Development Program (Grant No. 2012AA02A511) and the National Key Technology Research and Development Program (Grant No. 2012BAI05B02).

Compliance with ethics guidelines Xu Chen, Xiaomao Xu, and Fei Xiao hereby declare that no potential conflict of interest exist with any company/organization whose products or services may have been discussed in this article. This manuscript is a review article and does not involve a research protocol that requires the approval of a relevant institutional review board or ethics committee.

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