PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of ajrcmbIssue Featuring ArticlePublisher's Version of ArticleSubmissionsAmerican Thoracic SocietyAmerican Thoracic SocietyAmerican Journal of Respiratory Cell and Molecular Biology
 
Am J Respir Cell Mol Biol. 2011 March; 44(3): 316–322.
Published online 2010 May 6. doi:  10.1165/rcmb.2009-0360OC
PMCID: PMC3095932

Polymorphisms in Surfactant Protein–D Are Associated with Chronic Obstructive Pulmonary Disease

Abstract

Chronic obstructive pulmonary disease (COPD) is characterized by alveolar destruction and abnormal inflammatory responses to noxious stimuli. Surfactant protein–D (SFTPD) is immunomodulatory and essential to host defense. We hypothesized that polymorphisms in SFTPD could influence the susceptibility to COPD. We genotyped six single-nucleotide polymorphisms (SNPs) in surfactant protein D in 389 patients with COPD in the National Emphysema Treatment Trial (NETT) and 472 smoking control subjects from the Normative Aging Study (NAS). Case-control association analysis was performed using Cochran–Armitage trend tests and multivariate logistic regression. The replication of significant associations was attempted in the Boston Early-Onset COPD Study, the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) Study, and the Bergen Cohort. We also correlated SFTPD genotypes with serum concentrations of surfactant protein–D (SP-D) in the ECLIPSE Study. In the NETT–NAS case-control analysis, four SFTPD SNPs were associated with susceptibility to COPD: rs2245121 (P = 0.01), rs911887 (P = 0.006), rs6413520 (P = 0.004), and rs721917 (P = 0.006). In the family-based analysis of the Boston Early-Onset COPD Study, rs911887 was associated with prebronchodilator and postbronchodilator FEV1 (P = 0.003 and P = 0.02, respectively). An intronic SNP in SFTPD, rs7078012, was associated with COPD in the ECLIPSE Study and the Bergen Cohort. Multiple SFTPD SNPs were associated with serum SP-D concentrations in the ECLIPSE Study. We demonstrated an association of polymorphisms in SFTPD with COPD in multiple populations. We demonstrated a correlation between SFTPD SNPs and SP-D protein concentrations. The SNPs associated with COPD and SP-D concentrations differed, suggesting distinct genetic influences on susceptibility to COPD and SP-D concentrations.

Keywords: COPD, surfactant protein–D, single-nucleotide polymorphisms, genetics

CLINICAL RELEVANCE

Genetic variants in surfactant protein–D (SFTPD), a gene essential to host defense, exert a dual impact. Polymorphisms in SFTPD are associated with susceptibility to chronic obstructive pulmonary disease and influence serum concentrations of SP-D, a pulmonary biomarker.

The alveolar lining is the principal mucosal surface in contact with the external environment (1). As a result, the lungs are constantly exposed to microbes and particulate material. The ability to detect and distinguish dangerous substances precedes the resistance to pathogenic invasion. Innate immunity, an essential facet of host defense, is the first line of contact, through the recognition of microbe-induced molecular patterns or pathogen-induced alterations in host receptors that trigger a cascade of inflammatory events. Pulmonary surfactant, which lines the alveolar epithelium, is highly active in host defense through bacterial agglutination, opsonization, and viral neutralization (2, 3). Surfactant protein–D bridges the innate and adaptive immune systems, with the ability to bind several classes of immunoglobulins, in addition to recognizing carbohydrate arrays on microbial cell surfaces (4). Surfactant protein–D also enhances the clearance of apoptotic cells (5), a potentially important mechanism in the pathogenesis of chronic obstructive pulmonary disease (COPD) (6, 7). Surfactant protein–D has proinflammatory and anti-inflammatory signaling functions (8).

Increasing evidence implicates surfactant protein–D in the pathogenesis of COPD. Elevated serum concentrations of surfactant protein–D are a biomarker for COPD (9), and may ultimately have clinical relevance in the evaluation and design of novel drug therapies. Although the genetic association of three surfactant protein–D single-nucleotide polymorphisms (SNPs) with surfactant protein–D serum concentrations was analyzed, and demonstrated that the Met11Thr variant (rs721917) was associated with the assembly, function, and concentration of surfactant protein–D (10), the effects of SFTPD SNPs on the susceptibility to COPD are unknown. We hypothesized that SNPs in SFTPD, a mediator of primordial immune responses, could influence the susceptibility to COPD.

MATERIALS AND METHODS

Study Populations

Genetics Ancillary Study of the National Emphysema Treatment Trial.

In this case–control association analysis, participants with COPD were derived from the Genetics Ancillary Study in the National Emphysema Treatment Trial (NETT), previously described in detail (11, 12). For randomization into the NETT, eligible participants met a variety of inclusion criteria, such as severe obstructive airflow limitation (FEV1 ≤ 45% predicted), bilateral emphysema according to high-resolution computed tomography scanning, and hyperinflation according to pulmonary function testing. For this study, 389 non-Hispanic white NETT subjects out of the population of 1,218 NETT participants were analyzed.

Normative Aging Study.

The Normative Aging Study (NAS) is a population-based, prospective, longitudinal study of aging in men. This multidisciplinary cohort was initiated in Boston by the Veterans Administration in 1963 (13). At the onset of the study, participants were free of chronic medical conditions, were predominantly of Northern European descent, and underwent extensive evaluations every 3–5 years. The 472 male, non-Hispanic white NAS control subjects in this analysis had normal lung function during their last study visit and a 10 pack-year minimum smoking history. The largest pack-year value reported at any follow-up visit was used for this analysis.

Boston Early-Onset COPD Study.

The Boston Early-Onset COPD Study (EOCOPD) is a family-based study of the heritable determinants of COPD. Eligibility criteria for probands include: (1) age equal to or less than 52 years, (2) FEV1 at less than 40% predicted, (3) no evidence of severe α-1 antitrypsin deficiency, and (4) physician-diagnosed COPD. Detailed descriptions concerning the inception of the cohort, enrollment criteria, and physiologic evaluations are available elsewhere (14, 15). For this study, we analyzed data from 949 individuals in 127 pedigrees.

Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints Study.

The Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) Study (16) is a multinational, 3-year, noninterventional investigation of patients with COPD (GOLD Stages II–IV) and control subjects, designed to identify factors predictive of the progression of COPD in various COPD subtypes and to identify clinically relevant biomarkers for the prediction of disease progression (17). Only white subjects from the ECLIPSE cohort were included in this analysis, comprising 1,719 patients with COPD and 172 smoking (> 10 pack-year) control subjects.

Bergen cohort.

Eight hundred and twenty-three patients with COPD and 810 control subjects were analyzed in a cohort from Bergen, Norway. Postbronchodilator spirometric criteria for patients with COPD included the ratio of forced expiratory volume in one second/forced vital capacity (FEV1/FVC) of less than 0.7, and FEV1 at less than 80% predicted. Eligible control subjects exhibited FEV1/FVC of greater than 0.7, and FEV1 greater than 80% predicted. Both patients and control subjects reported at least 2.5 pack-years of smoking. Additional details concerning this cohort were described previously (18, 19).

SNP Selection and Genotyping

NETT–NAS/EOCOPD.

Genotypic data for individuals of European ancestry (CEU) from the International HapMap Project (20) and the Seattle SNPs Program for Genomic Applications (http://www.pga.mbt.washington.edu/) were used to select linkage disequilibrium (LD) tagging SNPs in SFTPD. Pairwise LD tagging was achieved with Tagger (http://www/broad.mit.edu/mpg/tagger/) for SNPs with a minimum minor allele frequency of 0.1 and an r2 of at least 0.8. LD between the SNPs in SFTPD was calculated using Haploview (21). Hardy–Weinberg equilibrium (HWE) was tested in control subjects, using the χ2 goodness-of-fit test. Two genotyping platforms were used: the 5′ to 3′ exonuclease assay (TaqMan; Applied Biosystems, Foster City, CA), and unlabeled minisequencing reactions and mass spectrometry (Sequenom, San Diego, CA) (22). Duplicate genotyping was performed on approximately 5% of the population for quality control. One discordant genotype occurred among the 525 duplicates (0.2%). Genotype call rates were greater than 95%. Whole-genome amplification was performed for 11 NAS participants, to avoid depletion of the source specimens (23).

ECLIPSE Study/Bergen Cohort.

The Illumina 550Kversion 3 SNP array was used for SNP genotyping. Details on the genotyping and quality-control evaluation are described elsewhere (24). Samples with a call rate of less than 98% were deleted. SNPs in SFTPD were selected from this genome-wide association study (GWAS) dataset, including the flanking regions 100 kb upstream and downstream from SFTPD. The 28 haplotype-tagging SNPs and their genotype frequencies are listed in Tables E1 and E2, respectively, in the online supplement.

Serum Surfactant Protein D Concentrations

Serum surfactant protein D (SP-D) concentrations were determined in the ECLIPSE Study with an ELISA (2527) (Biovendor, Inc, Heidelberg, Germany). Briefly, this sandwich enzyme immunoassay used two monoclonal antibodies specific to human SP-D for the quantitative measurement of SP-D in biologic specimens. Additional details concerning the measurement of serum surfactant protein D were reported by Lomas and colleagues (9).

Statistical Analysis

Quantitative data with a normal distribution are presented as means ± standard deviations. Variables with a non-normal distribution are presented as medians ± interquartile ranges. Discrete data were analyzed in 2 × 2 tables with χ2 test statistics. The case–control association analysis was performed using SAS/Genetics (SAS, Inc., Cary, NC). Polymorphisms with significant results for trend (P ≤ 0.05) in the Cochran–Armitage test (a genotype-based test for association) (28) were entered into logistic regression models. Logistic regression models were constructed for the probability of COPD. The logistic models, adjusted for age and pack-years, analyzed linear trends with additive genetic coding. Haplotype analysis was performed on haplotypes with at least 5% frequency, using the haplo.stats package in the R Project for Statistical Computing (http://www.r-project.org) (version 2.6.0). The sliding-window haplotype analysis involved the sequential testing of overlapping, adjacent two-loci, three-loci, or four-loci allelic combinations. Empiric values for significant global haplotypes and sliding-window analyses were obtained through the permutation of P values with 1,000 simulations.

Family-based association analyses for the EOCOPD Study were performed using the Pedigree-Based Association Test implemented in SVS Golden Helix (SVS 7.2.2, 2009-11-24, build 6685) (Golden Helix, Inc., Bozeman, MT). PedCheck (http://www.genomeutwin.org/member/cores/stat/linkage/pedcheck.html) was used as a quality-control measure of the genotyping used in the family-based association analysis (29). The additive genetic models were adjusted for age, age2, height, height2, pack-years of smoking, pack-years of smoking2, current smoking, and sex.

Multivariate models were constructed in a subset of the ECLIPSE subjects with COPD to determine the independent effects of genotype and lung function (FEV1 percent predicted) on surfactant protein D concentrations. These models were constructed with PLINK (30) (http://pngu.mgh.harvard.edu/purcell/plink), controlling for several additional covariates: age, sex, pack-years of smoking, smoking status, and principal components derived from a population stratification analysis using EIGENSTRAT (http://genepath.med.harvard.edu/~reich/EIGENSTRAT.htm) (31).

We performed logistic regression analysis in the Bergen Cohort with COPD as the outcome variable, adjusting for sex, age, pack-years of smoking, smoking status (former/current), and principal components for genetic ancestry.

RESULTS

NETT–NAS/EOCOPD Study

The demographic characteristics of participants in the NETT–NAS case–control analysis and the EOCOPD family-based replication population are presented in Table 1. The healthy smoking control subjects in NAS were slightly older and had less exposure to tobacco smoke. The NETT and NAS subjects were predominantly male. Of 389 NETT subjects, fewer than 40% were female and all NAS subjects were male. Individuals who actively smoked cigarettes were excluded from NETT. Approximately 7% of NAS control subjects were current smokers. Participants in the EOCOPD Study consisted of 127 probands: 98% had a history of smoking, and 13% were current smokers. In the relatives of probands, 63% had a history of smoking, and approximately one third were current smokers.

TABLE 1.
DEMOGRAPHIC CHARACTERISTICS

The characteristics of the six SFTPD SNPS in the NETT–NAS case–control association analysis and the EOCOPD family-based replication analysis are listed in Table 2. Five SNPs were in Hardy–Weinberg equilibrium (P > 0.05). For SNP rs6415320, the HWE P value was 0.04, but this SNP was not excluded because of the marginal P value for the deviation from HWE. In NETT–NAS, pairwise LD was determined for the six SFTPD SNPs using r2 (shown in the LD map in Figure 1). To maximize efficiency, we selected these six SNPs for genotyping that were not in strong LD. The highest r2 between genotyped SNPs was 0.6, between rs2245121 and rs911887. For individuals of European–American ancestry, the six LD-tagging SNPs genotyped in SFTPD captured 100% of the HapMap SNPs, with a minor allele frequency of at least 10% and an r2 greater than 0.8. The genotype frequencies for the ECLIPSE subjects with COPD are listed in Table E2.

TABLE 2.
MINOR ALLELE FREQUENCIES IN SURFACTANT PROTEIN–D
Figure 1.
Linkage disequilibrium map for six surfactant protein–D (SFTPD) single-nucleotide polymorphisms (SNPs) in subjects from the National Emphysema Treatment Trial and Normative Aging Study. Values of r2 (×100) are shown. Solid squares, an ...

Of the six SFTPD SNPs analyzed in the NETT–NAS case–control association analysis (Table 3), two intronic SNPs were significantly associated with susceptibility to COPD in the multivariate logistic regression models: rs2245121 (odds ratio [OR], 1.3; 95% confidence interval [CI], 1.1–1.7; P = 0.01) and rs911887 (OR, 1.4; 95% CI, 1.1–1.7; P = 0.006). In addition, significant associations were found for two nonsynonymous SNPs in SFTPD and susceptibility to COPD: rs6413520 (OR, 0.5; 95% CI, 0.3–0.8; P = 0.004) and rs721917 (OR, 1.4; 95% CI, 1.1–1.7; P = 0.006). In the family-based EOCOPD Study, rs911887 was associated with prebronchodilator FEV1 (P = 0.003) and postbronchodilator FEV1 (P = 0.02). In the EOCOPD Study, an exonic SNP, rs721917, revealed evidence suggestive of an association with prebronchodilator FEV1, but this finding did not reach statistical significance (P = 0.058). An additional SNP, rs1051246, revealed evidence suggestive of an association with moderate or greater COPD as defined by GOLD stage, but this finding did not reach statistical significance (P = 0.059). In all these models, as the number of minor alleles increased, increased airflow limitation was manifested as a reduction in prebronchodilator FEV1 and FEV1/FVC.

TABLE 3.
ASSOCIATION OF SURFACTANT PROTEIN D AND COPD PHENOTYPES IN FOUR STUDIES

Haplotype analysis was performed in NETT–NAS on SFTPD haplotypes of a least 5% frequency to extract additional information from the SNP data. The permuted and unadjusted global haplotype score P value for all six SNPs, based on 1,000 simulations, was P = 0.02. The A–G–T–A–G–A haplotype (rs1051246–rs2245121–rs911887–rs225601–rs6413520–rs721917) had the strongest statistical significance (P = 0.002) and a frequency of 7%. The empiric P value, as determined by simulation with sliding windows, was also significant (P = 0.008) for two SNP sliding windows (rs6413520–rs721917), three SNP sliding windows (P = 0.02) (rs911887–rs225601–rs6413520), and four SNP sliding windows (P = 0.02) (rs911887–rs225601–rs6413520–rs721917). Performing sliding-window simulations can be useful in prioritizing loci. Our strongest signal in the sliding-windows analysis involved the two-SNP sliding window that included rs6413520 and rs721917. After adjustment for age and pack-years of smoking, the global haplotype P value, based on 1,000 simulations, was 0.03.

ECLIPSE Study–Bergen Cohort

The ECLIPSE and Bergen participants in this study were slightly younger than the subjects in NETT–NAS. Demographic characteristics of the ECLIPSE and Bergen Cohort subjects are described in Table 1.

An intronic SNP, rs7078012, was associated with COPD susceptibility in the Bergen Cohort (P = 0.049; OR, 0.79; 95% CI, 0.62–0.999) and replicated in the ECLIPSE Study (P = 0.004; OR, 0.63; 95% CI, 0.4595–0.8622). This polymorphism was not genotyped in the NETT–NAS case–control study, and it was not in strong LD with SNPs in the NETT–NAS panel. Only two SNPs from NETT–NAS, rs911887 and rs721917, were among the 28 SNPs genotyped in the Illumina genome-wide panel in the ECLIPSE Study.

Serum SP-D Concentrations

Serum SP-D concentrations in ECLIPSE subjects were log-transformed, using the natural logarithm to approximate a normal distribution. In additive genetic models adjusting for age, sex, pack-years, and current smoking, several SNPs in SFTPD demonstrated strong associations with SP-D concentrations in current or former smokers (Table 4). Similar to the findings of Leth-Larsen and colleagues (10), we found an association between rs721917 and SP-D concentration. However, our strongest effect occurred with rs1885551, a promoter polymorphism (Figure 2). This finding suggests that the previously reported nonsynonymous SNP (rs721917) is not the most significant determinant of SFTPD gene regulation. Instead, rs1885551 or an SNP in LD with that polymorphism appears to exert the strongest impact on serum SP-D concentrations. In our multivariate genetic models, FEV1 percent predicted and SNP genotypes for multiple SFTPD variants were significant and independent predictors of SP-D concentrations (Table 5), demonstrating that lung function and SFTPD SNP genotype significantly and independently influence serum SP-D concentrations.

TABLE 4.
EFFECTS OF SFTPD ON SERUM SURFACTANT PROTEIN–D CONCENTRATIONS IN THE ECLIPSE STUDY
Figure 2.
Boxplots of SFTPD genotypes versus SP-D concentration (unadjusted) in rs721917: CC = Thr/Thr CT = Met/Thr TT = Met/Met.
TABLE 5.
PREDICTION OF SERUM SURFACTANT PROTEIN–D LEVEL BY SFTPD SNPS AND FEV1 IN ECLIPSE CURRENT OR FORMER SMOKERS

DISCUSSION

We demonstrated a significant association of several SNPs in SFTPD with susceptibility to COPD and COPD-related phenotypes. The strength of these associations was enhanced by the replication across multiple study designs and independent populations, although the same SFTPD SNP was not associated with COPD in all four study populations. We demonstrated that genetic variants in SFTPD correlate with quantifiable differences in serum protein concentrations, measured as serum SP-D.

A potential role for SFTPD in the pathogenesis of COPD is supported by murine models, where genetically altered mice lacking the production of SP-D spontaneously develop emphysema-like lesions, and have increased metalloproteinase activity and increased oxidant production (3235). The attenuation of these effects was shown after treatment with truncated recombinant human SP-D (36). These murine models provide support for the concept that SP-D is necessary for the regulation of oxidant production, inflammatory responses in alveolar macrophages, and apoptotic cell clearance.

SP-D is predominantly produced by alveolar Type II cells, and is systemically released as a consequence of lung injury (37). SP-D production is constitutive and under genetic (3840) and environmental control. In animal models, increased concentrations were demonstrated with exposure to tobacco smoke (40, 41), and decreased concentrations coincided with the resolution of ozone exposure (42). Serum SP-D was analyzed as a biomarker for COPD, a proxy for COPD pathology, or an unbiased measure of a pharmacologic response, in a study where inhaled corticosteroid therapy in conjunction with a long-acting β-agonist reduced circulating SP-D (43, 44). In multivariate analyses, COPD was an independent predictor of the presence of SP-D. The reduction in SP-D after treatment with corticosteroids was confirmed in a larger study, where SP-D was also demonstrated to be predictive of risk for a COPD exacerbation (9).

The Met11Thr variant (rs721917) of SFTPD was previously associated with lower serum concentrations of SP-D, and was found to inhibit the oligomerized state, with a reduction in binding of bacterial ligands (40). High SP-D concentrations were associated with an increased risk of COPD exacerbations (9). SP-D concentrations are reduced in the bronchoalveolar lavage fluid of patients with COPD (45), in contradistinction to the high concentrations measured in the peripheral blood of patients with COPD. According to a mechanism postulated to explain this discordance, inflammation in the lungs of patients with COPD results in the endothelial leakage of SP-D systemically, although other mechanisms may exist (46). In addition to its potential as a lung-specific biomarker, SP-D was correlated with body mass index (BMI) (47, 48). In a murine model, the overexpression of SFTPD was associated with atherosclerosis. Whether SP-D is related to systemic manifestations of COPD, such as low BMI or cardiovascular comorbidity (9), remains to be proven.

Few previous studies investigated the association between SFTPD and susceptibility to COPD or declines in lung function (49, 50). Although we demonstrated gene-level replication for an association of SFTPD SNPs with susceptibility to COPD in multiple populations, our study contains some limitations. In a previous candidate gene case–control association study by our research group, we found no association in NETT–NAS and EOCOPD participants with two SNPs in SFTPD (rs2243639 and rs721917) (51). However, in the present analysis of new genotyping data in these same populations, a significant association with rs721917 was evident in the NETT–NAS case–control analysis, with a trend toward the association of rs721917 with prebronchodilator FEV1. The present and previous investigations contained substantial differences that likely account for the disparate results. The present study used an LD-tagging approach in an attempt to assess the entire SFTPD gene. This NETT–NAS analysis was larger, with a net accrual of 115 additional subjects (85 NETT and 30 NAS subjects). Slight differences were also evident in the results of the previous and present genotyping. In the family-based association analysis, advances were implemented in the more recent version of Pedigree Based Association Testing (PBAT), used in the present analysis, which incorporates an algorithm with greater efficiency in detecting associations in extended pedigrees (C. Lange, personal communication). In addition, the spirometric phenotypes differed between the two analyses of the EOCOPD Study. Although the present analysis from the EOCOPD Study used prebronchodilator FEV1 and FEV1/FVC, resulting in a larger sample size and allowing the inclusion of 35 additional participants, the result for rs721917 is concordant with the previous report of postbronchodilator spirometry.

In regard to a further limitation, we do not replicate the association of the same SNP across all study populations. For instance, although rs721917 was associated with susceptibility to COPD in NETT–NAS, with lung function in the EOCOPD Study, and with SP-D concentrations in the ECLIPSE Study, this SNP was not associated with COPD in the ECLIPSE Study and Bergen Cohort. Moreover, although we demonstrated significant and independent effects of SFTPD SNPs and FEV1 percent predicted in surfactant protein D concentrations, our strongest association with SP-D concentrations occurred for a promoter polymorphism (rs1885551) rather than the nonsynonymous SNP, rs721917, previously suggested to be functional (10).

Our data suggest the possibility that different SFTPD SNPs influence susceptibility to COPD versus SP-D concentrations. Although we did not perform functional studies to determine the effects of these polymorphisms in the lungs, Leth-Larsen and colleagues demonstrated that polymorphic variations in the N-terminal domain of SFTPD affect surfactant serum concentrations, polymerization, and function (10). Surfactant reduces sputum adherence to the epithelium and airway inflammation, and improves mucociliary clearance (52). In a cohort of patients with chronic bronchitis, the administration of exogenous surfactant (palmitoylphisphadidylcholine) resulted in improvements in lung function and an increased in vitro ciliary transport of sputum (52).

In recognition of another potential limitation, we appreciate that corrections for multiple statistical testing are controversial. Our primary approach to the confirmation of genetic association was through replication. Lastly, spurious allelic associations attributable to population stratification are ameliorated in family-based designs. Previous genotyping for population stratification in the NETT–NAS cohort did not demonstrate significant population stratification (53).

We provide evidence that SFTPD is involved in the pathogenesis of COPD. In independent populations and across multiple study designs, we demonstrate that genetic variations in SFTPD influence serum concentrations and lung function, and are associated with susceptibility to COPD. Further work is required to understand the role of shared versus independent genetic influences on SP-D concentrations and susceptibility to COPD.

Supplementary Material

[Online Supplement]

Acknowledgments

The authors acknowledge the contributions of Barbara Klanderman, Ph.D. (Channing Laboratory, Brigham and Women's Hospital, Boston, MA).

Notes

This work was supported by National Institutes of Health grants HL092601, HL007427, HL075478, HL082541, and HL083069. The Normative Aging Study is supported by the Cooperative Studies Program/Epidemiologic Research and Information Center of the United States Department of Veterans Affairs, and is a component of the Massachusetts Veterans Epidemiology Research and Information Center. The Evaluation of Chronic Obstructive Pulmonary Disorder Longitudinally to Identify Predictive Surrogate Endpoints Study is funded by GlaxoSmithKline. The National Emphysema Treatment Trial was supported by National Heart, Lung, and Blood Institute contracts N01HR7601, N01HR76102, N01HR76103, N01HR76104, N01HR76105, N01HR76107, N01HR76108, N01HR76109, N01HR76110, N01HR76111, N01HR76112, N01HR76113, N01HR76114, N01HR76115, N01HR76116, N01HR76118, and N01HR76119, by the Centers for Medicare and Medicaid Services, and by the Agency for Healthcare Research and Quality.

This article has an online supplement, which is accessible from this issue's table of content at www.atsjournals.org

Originally Published in Press as DOI: 10.1165/rcmb.2009-0360OC on May 6, 2010

Author Disclosure: P.B. received lecture fees from GlaxoSmithKline and AstraZeneca for $1,001–$5,000 each, and an industry-sponsored grant from GlaxoSmithKline for $10,001–$50,000. D.L.D. received a sponsored research grant from the National Institutes of Health and a Career Development Award from the Doris Duke Charitable Foundation for more than $100,001 each. M.G.F. received a sponsored grant from the Alpha-1 Foundation and a K Grant from the National Heart, Lung, and Blood Institute for more than $100,001 each. C.P.H. received a sponsored grant from the National Institutes of Health and the Alpha-1 Foundation for more than $100,001 each. X.K. is a full-time employee of GlaxoSmithKline. A.A.L. received author royalties from UpToDate, Inc., for $1,001–$5,000, and a sponsored research grant from the National Institutes of Health for more than $100,001. D.A.L. received consultancy fees from GlaxoSmithKline for $10,001–$50,000, Novartis for $1,001–$5,000, and Genzyme and Amicus for less than $1,000 each. D.A.L. serves on the advisory board of GlaxoSmithKline for $10,001–$50,000, of Talecris for $5,001–$10,000, and of Thorax for $1,001–$5,000. D.A.L. received lecture fees from GlaxoSmithKline for $1,001–$5,000, from AstraZeneca for less than $1,000, and from Boehringer Ingelheim for $1,001–$5,000. D.A.L. received industry-sponsored grants from GlaxoSmithKline and Merck Sharp & Dohme for more than $100,001 each. D.A.L. received sponsored grants from the Wellcome Trust, the British Lung Foundation, and the Medical Research Council for more than $100,001, and serves on the advisory board of the Medical Research Council, receiving $1,001–$5,000. S.G.P. was a full-time employee of GlaxoSmithKline until September 2009, and is a full-time employee of Roche Pharmaceuticals. S.G.P. owns stock in GlaxoSmithKline. S.D.S. serves on the advisory boards of Bohringer Ingelheim and GlaxoSmithKline for $1,001–$5,000 each. E.K.S. received consultancy fees from GlaxoSmithKline and AstraZeneca for $10,001–$50,000 each. E.K.S. received lecture fees from GlaxoSmithKline and Bayer for $1,001–$5,000, and from AstraZeneca for $5,001–$10,000. E.K.S. received a sponsored grant from GlaxoSmithKline and the National Institutes of Health for more than $100,001. R.T.S. is a full-time employee of GlaxoSmithKline, and has patents pending from SmithKline Beecham and Wistar for (1) compounds and methods for treating viral reactivation, (2) a method of treating viral diseases with IL-18, and (3) a method for detecting, analyzing, and mapping viral transcripts. R.T.S. owns stock in GlaxoSmithKline as an employee benefit of more than $100,001. A.G. does not have a financial relationship with a commercial entity that has an interest in the subject of this manuscript.

References

1. Martin TR, Frevert CW. Innate immunity in the lungs. Proc Am Thorac Soc 2005;2:403–411. [PMC free article] [PubMed]
2. Alcorn JF, Wright JR. Degradation of pulmonary surfactant protein D by Pseudomonas aeruginosa elastase abrogates innate immune function. J Biol Chem 2004;279:30871–30879. [PubMed]
3. Sano H, Kuroki Y. The lung collectins, SP-A and SP-D, modulate pulmonary innate immunity. Mol Immunol 2005;42:279–287. [PubMed]
4. Nadesalingam J, Reid KB, Palaniyar N. Collectin surfactant protein D binds antibodies and interlinks innate and adaptive immune systems. FEBS Lett 2005;579:4449–4453. [PubMed]
5. Vandivier RW, Ogden CA, Fadok VA, Hoffmann PR, Brown KK, Botto M, Walport MJ, Fisher JH, Henson PM, Greene KE. Role of surfactant proteins A, D, and C1q in the clearance of apoptotic cells in vivo and in vitro: calreticulin and CD91 as a common collectin receptor complex. J Immunol 2002;169:3978–3986. [PubMed]
6. Tsuji T, Aoshiba K, Nagai A. Alveolar cell senescence in patients with pulmonary emphysema. Am J Respir Crit Care Med 2006;174:886–893. [PubMed]
7. Park JW, Ryter SW, Choi AM. Functional significance of apoptosis in chronic obstructive pulmonary disease. COPD 2007;4:347–353. [PubMed]
8. Guo CJ, Atochina-Vasserman EN, Abramova E, Foley JP, Zaman AM, Crouch E, Beers MF, Savani RC, Gow AJ. S-nitrosylation of surfactant protein–D controls inflammatory function. PLoS Biol 2008;6:e266. [PMC free article] [PubMed]
9. Lomas DA, Silverman EK, Edwards LD, Locantore NW, Miller BE, Horstman DH, Tal-Singer R. Serum surfactant protein D is steroid sensitive and associated with exacerbations of COPD. Eur Respir J 2009;34:95–102. [PubMed]
10. Leth-Larsen R, Garred P, Jensenius H, Meschi J, Hartshorn K, Madsen J, Tornoe I, Madsen HO, Sørensen G, Crouch E, Holmskov U. A common polymorphism in the SFTPD gene influences assembly, function, and concentration of surfactant protein D. J Immunol 2005;174:1532–1538. [PubMed]
11. National Emphysema Treatment Trial Research Group. Rationale and design of the National Emphysema Treatment Trial (NETT): a prospective randomized trial of lung volume reduction surgery. J Thorac Cardiovasc Surg 1999;118:518–528. [PubMed]
12. National Emphysema Treatment Trial Research Group. Patients at high risk of death after lung-volume–reduction surgery. N Engl J Med 2001;345:1075–1083. [PubMed]
13. Litonjua AA, Lazarus R, Sparrow D, Demolles D, Weiss ST. Lung function in Type 2 diabetes: the Normative Aging Study. Respir Med 2005;99:1583–1590. [PubMed]
14. Silverman EK, Chapman HA, Drazen JM, Weiss ST, Rosner B, Campbell EJ, O'Donnell WJ, Reilly JJ, Ginns L, Mentzer S, et al. Genetic epidemiology of severe, early-onset chronic obstructive pulmonary disease: risk to relatives for airflow obstruction and chronic bronchitis. Am J Respir Crit Care Med 1998;157:1770–1778. [PubMed]
15. Hersh CP, DeMeo DL, Al-Ansari E, Carey VJ, Reilly JJ, Ginns LC, Silverman EK. Predictors of survival in severe, early onset COPD. Chest 2004;126:1443–1451. [PubMed]
16. Vestbo J, Anderson W, Coxson HO, Crim C, Dawber F, Edwards L, Hagan G, Knobil K, Lomas DA, MacNee W, et al. Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE). Eur Respir J 2008;4:869–873. [PubMed]
17. Rabe KF, Hurd S, Anzueto A, Barnes PJ, Buist SA, Calverley P, Fukuchi Y, Jenkins C, Rodriguez-Roisin R, van Weel C, Zielinski J; Global Initiative for Chronic Obstructive Lung Disease. Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary. Am J Respir Crit Care Med 2007;176:532–555. [PubMed]
18. Zhu G, Warren L, Aponte J, Gulsvik A, Bakke P, Anderson WH, Lomas DA, Silverman EK, Pillai SG; International COPD Genetics Network (ICGN) Investigators. The SERPINE2 gene is associated with chronic obstructive pulmonary disease in two large populations. Am J Respir Crit Care Med 2007;176:167–173. [PubMed]
19. Pillai SG, Gulsvik A, Lomas DA, Silverman EK. SERPINE2 and COPD. Am J Respir Crit Care Med 2007;176:726. [PubMed]
20. International HapMap Consortium. A haplotype map of the human genome. Nature 2005;437:1299–1320. [PMC free article] [PubMed]
21. Barrett JC, Fry B, Maller J, Daly MJ. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 2005;21:263–265. [PubMed]
22. Shi MM. Enabling large-scale pharmacogenetic studies by high-throughput mutation detection and genotyping technologies. Clin Chem 2001;47:164–172. [PubMed]
23. Paez JG, Lin M, Beroukhim R, Lee JC, Zhao X, Richter DJ, Gabriel S, Herman P, Sasaki H, Altshuler D, et al. Genome coverage and sequence fidelity of phi29 polymerase-based multiple strand displacement whole genome amplification. Nucleic Acids Res 2004;32:e71. [PMC free article] [PubMed]
24. Pillai SG, Ge D, Zhu G, Kong X, Shianna KV, Need AC, Feng S, Hersh CP, Bakke P, Gulsvik A, et al. A genome-wide association study in chronic obstructive pulmonary disease (COPD): identification of two major susceptibility loci. PLoS Genet 2009;5:e1000421. [PMC free article] [PubMed]
25. Honda Y, Kuroki Y, Matsuura E, Nagae H, Takahashi H, Akino T, Abe S. Pulmonary surfactant protein D in sera and bronchoalveolar lavage fluids. Am J Respir Crit Care Med 1995;152:1860–1866. [PubMed]
26. Inoue T, Matsuura E, Nagata A, Ogasawara Y, Hattori A, Kuroki Y, Fujimoto S, Akino T. Enzyme-linked immunosorbent assay for human pulmonary surfactant protein D. J Immunol Methods 1994;173:157–164. [PubMed]
27. Nagae H, Takahashi H, Kuroki Y, Honda Y, Nagata A, Ogasawara Y, Abe S, Akino T. Enzyme-linked immunosorbent assay using F(ab′)2 fragment for the detection of human pulmonary surfactant protein D in sera. Clin Chim Acta 1997;266:157–171. [PubMed]
28. Freidlin B, Zheng G, Li Z, Gastwirth JL. Trend tests for case–control studies of genetic markers: power, sample size and robustness. Hum Hered 2002;53:146–152. [PubMed]
29. O'Connell JR, Weeks DE. PedCheck: a program for identification of genotype incompatibilities in linkage analysis. Am J Hum Genet 1998;63:259–266. [PubMed]
30. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, Maller J, Sklar P, de Bakker PI, Daly MJ, Sham PC. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 2007;81:559–575. [PubMed]
31. Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D. Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet 2006;38:904–909. [PubMed]
32. Wert SE, Yoshida M, LeVine AM, Ikegami M, Jones T, Ross GF, Fisher JH, Korfhagen TR, Whitsett JA. Increased metalloproteinase activity, oxidant production, and emphysema in surfactant protein D gene-inactivated mice. Proc Natl Acad Sci USA 2000;97:5972–5977. [PubMed]
33. Yoshida M, Korfhagen TR, Whitsett JA. Surfactant protein D regulates NF-kappa B and matrix metalloproteinase production in alveolar macrophages via oxidant-sensitive pathways. J Immunol 2001;166:7514–7519. [PubMed]
34. Senft AP, Korfhagen TR, Whitsett JA, Shapiro SD, LeVine AM. Surfactant protein–D regulates soluble CD14 through matrix metalloproteinase–12. J Immunol 2005;174:4953–4959. [PubMed]
35. Yoshida M, Whitsett JA. Alveolar macrophages and emphysema in surfactant protein–D–deficient mice. Respirology 2006;11:S37–S40. [PubMed]
36. Knudsen L, Ochs M, Mackay R, Knudsen L, Ochs M, Mackay R, Townsend P, Deb R, Mühlfeld C, Richter J, et al. Truncated recombinant human SP-D attenuates emphysema and Type II cell changes in SP-D deficient mice. Respir Res 2007;8:70. [PMC free article] [PubMed]
37. Pastva AM, Wright JR, Williams KL. Immunomodulatory roles of surfactant proteins A and D: implications in lung disease. Proc Am Thorac Soc 2007;4:252–257. [PMC free article] [PubMed]
38. Husby S, Herskind AM, Jensenius JC, Holmskov U. Heritability estimates for the constitutional levels of the collectins mannan-binding lectin and lung surfactant protein D: a study of unselected like-sexed mono- and dizygotic twins at the age of 6–9 years. Immunology 2002;106:389–394. [PubMed]
39. Heidinger K, Konig IR, Bohnert A, Kleinsteiber A, Hilgendorff A, Gortner L, Ziegler A, Chakraborty T, Bein G. Polymorphisms in the human surfactant protein–D (SFTPD) gene: strong evidence that serum levels of surfactant protein-D (SP–D) are genetically influenced. Immunogenetics 2005;57:1–7. [PubMed]
40. Sorensen GL, Hjelmborg JB, Kyvik KO, Fenger M, Høj A, Bendixen C, Sørensen TI, Holmskov U. Genetic and environmental influences of surfactant protein D serum levels. Am J Physiol Lung Cell Mol Physiol 2006;290:L1010–L1017. [PubMed]
41. Cao Y, Grous M, Scanlon S, Beers MF, Panettieri RA, Salmon M, Haczku A. The innate molecule surfactant protein (SP-D) is upregulated in the lung following cigarette smoke (CS) exposure in a murine model. Am J Respir Crit Care Med 2004;169:A832.
42. Kierstein S, Poulain FR, Cao Y, Grous M, Mathias R, Kierstein G, Beers MF, Salmon M, Panettieri RA Jr., Haczku A. Susceptibility to ozone-induced airway inflammation is associated with decreased levels of surfactant protein D. Respir Res 2006;7:85. [PMC free article] [PubMed]
43. Sin DD, Leung R, Gan WQ, Man SP. Circulating surfactant protein D as a potential lung-specific biomarker of health outcomes in COPD: a pilot study. BMC Pulm Med 2007;7:13. [PMC free article] [PubMed]
44. Sin DD, Man SF, Marciniuk DD, Ford G, FitzGerald M, Wong E, York E, Mainra RR, Ramesh W, Melenka LS, et al. The effects of fluticasone with or without salmeterol on systemic biomarkers of inflammation in chronic obstructive pulmonary disease. Am J Respir Crit Care Med 2008;177:1207–1214. [PubMed]
45. Sims MW, Tal-Singer RM, Kierstein S, Musani AI, Beers MF, Panettieri RA, Haczku A. Chronic obstructive pulmonary disease and inhaled steroids alter surfactant protein D (SP-D) levels: a cross-sectional study. Respir Res 2008;9:13. [PMC free article] [PubMed]
46. Dahl M. Biomarkers for chronic obstructive pulmonary disease: surfactant protein D and C-reactive protein. Am J Respir Crit Care Med 2008;177:1177–1178. [PubMed]
47. Sorensen GL, Hjelmborg JV, Leth-Larsen R, Schmidt V, Fenger M, Poulain F, Hawgood S, Sørensen TI, Kyvik KO, Holmskov U. Surfactant protein D of the innate immune defence is inversely associated with human obesity and SP-D deficiency infers increased body weight in mice. Scand J Immunol 2006;64:633–638. [PubMed]
48. Zhao XM, Wu YP, Wei R, Cai HX, Tornoe I, Han JJ, Wang Y, de Groot PG, Holmskov U, Xia ZL, Sorensen GL. Plasma surfactant protein D levels and the relation to body mass index in a Chinese population. Scand J Immunol 2007;66:71–76. [PubMed]
49. Guo X, Lin HM, Lin Z, Montaño M, Sansores R, Wang G, DiAngelo S, Pardo A, Selman M, Floros J. Surfactant protein gene A, B, and D marker alleles in chronic obstructive pulmonary disease of a Mexican population. Eur Respir J 2001;18:482–490. [PubMed]
50. van Diemen CC, Postma DS, Aulchenko YS, Snijders PJ, Oostra BA, van Duijn CM, Boezen HM. Novel strategy to identify genetic risk factors for COPD severity: a genetic isolate. Eur Respir J 2010;35:768–775. [PubMed]
51. Hersh CP, Demeo DL, Lange C, Litonjua AA, Reilly JJ, Kwiatkowski D, Laird N, Sylvia JS, Sparrow D, Speizer FE, et al. Attempted replication of reported chronic obstructive pulmonary disease candidate gene associations. Am J Respir Cell Mol Biol 2005;33:71–78. [PMC free article] [PubMed]
52. Anzueto A, Jubran A, Ohar JA, Piquette CA, Rennard SI, Colice G, Pattishall EN, Barrett J, Engle M, Perret KA, Rubin BK. Effects of aerosolized surfactant in patients with stable chronic bronchitis: a prospective randomized controlled trial. JAMA 1997;278:1426–1431. [PubMed]
53. Hersh CP, Hansel NN, Barnes KC, Lomas DA, Pillai SG, Coxson HO, Mathias RA, Rafaels NM, Wise RA, Connett JE, et al. Transforming growth factor–beta receptor–3 is associated with pulmonary emphysema. Am J Respir Cell Mol Biol 2009;41:324–331. [PMC free article] [PubMed]
54. Crapo RO, Morris AH, Gardner RM. Reference spirometric values using techniques and equipment that meet ATS recommendations. Am Rev Respir Dis 1981;123:659–664. [PubMed]

Articles from American Journal of Respiratory Cell and Molecular Biology are provided here courtesy of American Thoracic Society