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Genetic studies have identified numerous regions associated with plasma fibrinogen levels in Europeans, yet missing heritability and limited inclusion of non-Europeans necessitates further studies with improved power and sensitivity. Compared with array-based genotyping, whole genome sequencing (WGS) data provides better coverage of the genome and better representation of non-European variants. To better understand the genetic landscape regulating plasma fibrinogen levels, we meta-analyzed WGS data from the NHLBI’s Trans-Omics for Precision Medicine (TOPMed) program (n=32,572), with array-based genotype data from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium (n=131,340) imputed to the TOPMed or Haplotype Reference Consortium panel. We identified 18 loci that have not been identified in prior genetic studies of fibrinogen. Of these, four are driven by common variants of small effect with reported MAF at least 10% higher in African populations. Three ( SERPINA1, ZFP36L2 , and TLR10) signals contain predicted deleterious missense variants. Two loci, SOCS3 and HPN , each harbor two conditionally distinct, non-coding variants. The gene region encoding the protein chain subunits ( FGG;FGB;FGA ), contains 7 distinct signals, including one novel signal driven by rs28577061, a variant common (MAF=0.180) in African reference panels but extremely rare (MAF=0.008) in Europeans. Through phenome-wide association studies in the VA Million Veteran Program, we found associations between fibrinogen polygenic risk scores and thrombotic and inflammatory disease phenotypes, including an association with gout. Our findings demonstrate the utility of WGS to augment genetic discovery in diverse populations and offer new insights for putative mechanisms of fibrinogen regulation. KEY POINTS: Largest and most diverse genetic study of plasma fibrinogen identifies 54 regions (18 novel), housing 69 conditionally distinct variants (20 novel). Sufficient power achieved to identify signal driven by African population variant. Links to (1) liver enzyme, blood cell and lipid genetic signals, (2) liver regulatory elements, and (3) thrombotic and inflammatory disease.

Additional file 1: Text and Figures S1–S5. Supplementary text for the methods (study phenotype, quality control, imputation, significance and suggestive thresholds, annotation), results (power to detect associations, annotation of rs142755000), and discussion (suggestive associations) as well as related references. Figure S1. a: COPDGene XWAS in Stratified Populations All Subjects. b: COPDGene XWAS in Stratified Populations Males. c: COPDGene XWAS in Stratified Populations Females. Figure S2. Meta-analysis XWAS in Stratified Population. Figure S3. Meta-analysis Locus Plots of Top Suggested Associations in COPD Related Phenotypes. Figure S4. Meta-analysis Quantile–Quantile and Manhattan Plots. Figure S5. Sex differential edge weights connecting the transcription factor POU3F4 in GTEx Lung Tissue.

Additional file 1: Table S1. Multivariate association of optimism with lung function and functional outcomes with 2 tier model. Table S2. HADS adjustment instead of previous history of depression diagnosis. Table S3. Sensitivity analysis excluding subjects with history of depression. Table S4. Sensitivity analysis excluding collection of subjects with previous history of depression and present depression by HADS. Table S5. Association of disease-related characteristics at previous visits as predictor of optimism score in next visit. Fig. S1. Flow chart of enrollment of COPDGene study population.

COPD is a heterogeneous syndrome. Many COPD subtypes have been proposed, but there is not yet consensus on how many COPD subtypes there are and how they should be defined. The COPD Genetic Epidemiology Study (COPDGene), which has generated 10-year longitudinal chest imaging, spirometry, and molecular data, is a rich resource for relating COPD phenotypes to underlying genetic and molecular mechanisms. In this article, we place COPDGene clustering studies in context with other highly cited COPD clustering studies, and summarize the main COPD subtype findings from COPDGene. First, most manifestations of COPD occur along a continuum, which explains why continuous aspects of COPD or disease axes may be more accurate and reproducible than subtypes identified through clustering methods. Second, continuous COPD-related measures can be used to create subgroups through the use of predictive models to define cut-points, and we review COPDGene research on blood eosinophil count thresholds as a specific example. Third, COPD phenotypes identified or prioritized through machine learning methods have led to novel biological discoveries, including novel emphysema genetic risk variants and systemic inflammatory subtypes of COPD. Fourth, trajectory-based COPD subtyping captures differences in the longitudinal evolution of COPD, addressing a major limitation of clustering analyses that are confounded by disease severity. Ongoing longitudinal characterization of subjects in COPDGene will provide useful insights about the relationship between lung imaging parameters, molecular markers, and COPD progression that will enable the identification of subtypes based on underlying disease processes and distinct patterns of disease progression, with the potential to improve the clinical relevance and reproducibility of COPD subtypes.

BackgroundChronic bronchitis (CB) increases risk of COPD exacerbations. We have shown that the St. George's Respiratory Questionnaire (SGRQ) CB definition identifies patients with a similar clinical phenotype as classically defined CB. Whether the SGRQ CB definition is a predictor of future COPD exacerbations is unknown.MethodsWe analyzed 7,557 smokers with normal spirometry and Global Initiative for Chronic Obstructive Lung Disease stage 1-4 COPD in the Genetic Epidemiology of COPD study with longitudinal follow-up data on exacerbations. Subjects were divided into classic CB+ or classic CB-, using the classic definition. In addition, subjects were divided into SGRQ CB+ or SGRQ CB-. Exacerbation frequency and severe exacerbation frequency were determined in each group. Multivariable linear regressions were performed for exacerbation frequency with either classic CB or SGRQ CB and relevant covariates.ResultsThere were 1,434 classic CB+ subjects and 2,290 SGRQ CB+ subjects. The classic CB+ group had a greater exacerbation frequency compared with the classic CB- group (0.69 ± 1.26 vs0.36 ± 0.90 exacerbations per patient per year; P< .0001) and a greater severe exacerbation frequency (0.26 ± 0.74 vs0.13 ± 0.46 severe exacerbations per patient per year; P< .0001). There were similar differences between the SGRQ CB+ and SGRQ CB- groups. In multivariable analysis, both SGRQ CB and classic CB were independent predictors of exacerbation frequency, but SGRQ CB had a higher regression coefficient. In addition, SGRQ CB was an independent predictor of severe exacerbation frequency whereas classic CB was not.ConclusionsThe SGRQ CB definition identified more subjects at risk for future exacerbations than the classic CB definition. SGRQ CB was at least a similar if not better predictor of future exacerbations than classic CB.

Rationale: Several common and rare genetic variants have been associated with idiopathic pulmonary fibrosis, a progressive fibrotic condition that is localized to the lung. Objectives: To develop an integrated understanding of the rare and common variants located in multiple loci that have been reported to contribute to the risk of disease. Methods: We performed deep targeted resequencing (3.69 Mb of DNA) in cases (n = 3,624) and control subjects (n = 4,442) across genes and regions previously associated with disease. We tested for associations between disease and 1) individual common variants via logistic regression and 2) groups of rare variants via sequence kernel association tests. Measurements and Main Results: Statistically significant common variant association signals occurred in all 10 of the regions chosen based on genome-wide association studies. The strongest risk variant is the MUC5B promoter variant rs35705950, with an odds ratio of 5.45 (95% confidence interval, 4.91-6.06) for one copy of the risk allele and 18.68 (95% confidence interval, 13.34-26.17) for two copies of the risk allele (P = 9.60 × 10-295). In addition to identifying for the first time that rare variation in FAM13A is associated with disease, we confirmed the role of rare variation in the TERT and RTEL1 gene regions in the risk of IPF, and found that the FAM13A and TERT regions have independent common and rare variant signals. Conclusions: A limited number of common and rare variants contribute to the risk of idiopathic pulmonary fibrosis in each of the resequencing regions, and these genetic variants focus on biological mechanisms of host defense and cell senescence.

Chronic obstructive pulmonary disease (COPD) is the leading cause of respiratory mortality worldwide. Genetic risk loci provide novel insights into disease pathogenesis. We performed a genome-wide association study in 35,735 cases and 222,076 controls from the UK Biobank and additional studies from the International COPD Genetics Consortium. We identified 82 loci with P-value [less than] 5 × 10-8; 47 were previously described in association with either COPD or population-based lung function. Of the remaining 35 novel loci, 13 were associated with lung function in 79,055 individuals from the SpiroMeta consortium. Using gene expression and regulation data, we identified enrichment for loci in lung tissue, smooth muscle and several lung cell types. We found 14 COPD loci shared with either asthma or pulmonary fibrosis. COPD genetic risk loci clustered into groups of quantitative imaging features and comorbidity associations. Our analyses provide further support to the genetic susceptibility and heterogeneity of COPD.

Chronic obstructive pulmonary disease (COPD) is the leading cause of respiratory mortality worldwide. Genetic risk loci provide new insights into disease pathogenesis. We performed a genome-wide association study in 35,735 cases and 222,076 controls from the UK Biobank and additional studies from the International COPD Genetics Consortium. We identified 82 loci associated with P < 5 × 10-8; 47 of these were previously described in association with either COPD or population-based measures of lung function. Of the remaining 35 new loci, 13 were associated with lung function in 79,055 individuals from the SpiroMeta consortium. Using gene expression and regulation data, we identified functional enrichment of COPD risk loci in lung tissue, smooth muscle, and several lung cell types. We found 14 COPD loci shared with either asthma or pulmonary fibrosis. COPD genetic risk loci clustered into groups based on associations with quantitative imaging features and comorbidities. Our analyses provide further support for the genetic susceptibility and heterogeneity of COPD.

Chronic obstructive pulmonary disease (COPD) is the leading cause of respiratory mortality worldwide. Genetic risk loci provide novel insights into disease pathogenesis. We performed a genome-wide association study in 35,735 cases and 222,076 controls from the UK Biobank and additional studies from the International COPD Genetics Consortium. We identified 82 loci with P-value < 5 × 10−8; 47 were previously described in association with either COPD or population-based lung function. Of the remaining 35 novel loci, 13 were associated with lung function in 79,055 individuals from the SpiroMeta consortium. Using gene expression and regulation data, we identified enrichment for loci in lung tissue, smooth muscle and several lung cell types. We found 14 COPD loci shared with either asthma or pulmonary fibrosis. COPD genetic risk loci clustered into groups of quantitative imaging features and comorbidity associations. Our analyses provide further support to the genetic susceptibility and heterogeneity of COPD., Editorial summary Genome-wide analysis of chronic obstructive pulmonary disease identifies 82 loci, 35 of which are new. Integration of gene expression and genomic annotation data shows enrichment of signals in lung tissue, smooth muscle and several lung cell types.

RationaleIncreasing awareness of the prevalence and significance of Preserved Ratio Impaired Spirometry (PRISm), alternatively known as restrictive or Global Initiative for Chronic Obstructive Lung Disease (GOLD)-unclassified spirometry, has expanded the body of knowledge on cross-sectional risk factors. However, longitudinal studies of PRISm remain limited.ObjectivesTo examine longitudinal patterns of change in lung function, radiographic characteristics, and mortality of current and former smokers with PRISm.MethodsCurrent and former smokers, aged 45 to 80 years, were enrolled in COPDGene (phase 1, 2008-2011) and returned for a 5-year follow-up (phase 2, 2012-2016). Subjects completed questionnaires, spirometry, chest computed tomography scans, and 6-minute-walk tests at both study visits. Baseline characteristics, longitudinal change in lung function, and mortality were assessed by post-bronchodilator lung function categories: PRISm (FEV1/FVC 0.7 and FEV1 > 80%), and GOLD1-4 (FEV1/FVC

BACKGROUND: Previous investigations in adult smokers from the COPDGene Study have shown that early-life respiratory disease is associated with reduced lung function, COPD, and airway thickening. Using 5-year follow-up data, we assessed disease progression in subjects who had experienced early-life respiratory disease. We hypothesized that there are alternative pathways to reaching reduced FEV1 and that subjects who had childhood pneumonia, childhood asthma, or asthma-COPD overlap (ACO) would have less lung function decline than subjects without these conditions.METHODS: Subjects returning for 5-year follow-up were assessed. Childhood pneumonia was defined by self-reported pneumonia at < 16 years. Childhood asthma was defined as self-reported asthma diagnosed by a health professional at < 16 years. ACO was defined as subjects with COPD who self-reported asthma diagnosed by a health-professional at ≤ 40 years. Smokers with and those without these early-life respiratory diseases were compared on measures of disease progression.RESULTS: Follow-up data from 4,915 subjects were examined, including 407 subjects who had childhood pneumonia, 323 subjects who had childhood asthma, and 242 subjects with ACO. History of childhood asthma or ACO was associated with an increased exacerbation frequency (childhood asthma, P < .001; ACO, P = .006) and odds of severe exacerbations (childhood asthma, OR, 1.41; ACO, OR, 1.42). A history of childhood pneumonia was associated with increased exacerbations of COPD (absolute difference [β], 0.17; P = .04). None of these early-life respiratory diseases were associated with an increased rate of lung function decline or progression on CT scans.CONCLUSIONS: Subjects who had early-life asthma are at increased risk of COPD developing and of having more active disease with more frequent and severe respiratory exacerbations without an increased rate of lung function decline over a 5-year period.TRIAL REGISTRY: ClinicalTrials.gov; No. NCT00608764; https://clinicaltrials.gov.

BackgroundEmphysema has considerable variability in its regional distribution. Craniocaudal emphysema distribution is an important predictor of the response to lung volume reduction. However, there is little consensus regarding how to define upper lobe-predominant and lower lobe-predominant emphysema subtypes. Consequently, the clinical and genetic associations with these subtypes are poorly characterized.MethodsWe sought to identify subgroups characterized by upper-lobe or lower-lobe emphysema predominance and comparable amounts of total emphysema by analyzing data from 9,210 smokers without alpha-1-antitrypsin deficiency in the Genetic Epidemiology of COPD (COPDGene) cohort. CT densitometric emphysema was measured in each lung lobe. Random forest clustering was applied to lobar emphysema variables after regressing out the effects of total emphysema. Clusters were tested for association with clinical and imaging outcomes at baseline and at 5-year follow-up. Their associations with genetic variants were also compared.ResultsThree clusters were identified: minimal emphysema (n= 1,312), upper lobe-predominant emphysema (n= 905), and lower lobe-predominant emphysema (n= 796). Despite a similar amount of total emphysema, the lower-lobe group had more severe airflow obstruction at baseline and higher rates of metabolic syndrome compared with subjects with upper-lobe predominance. The group with upper-lobe predominance had greater 5-year progression of emphysema, gas trapping, and dyspnea. Differential associations with known COPD genetic risk variants were noted.ConclusionsSubgroups of smokers defined by upper-lobe or lower-lobe emphysema predominance exhibit different functional and radiological disease progression rates, and the upper-lobe predominant subtype shows evidence of association with known COPD genetic risk variants. These subgroups may be useful in the development of personalized treatments for COPD.

Figure S1. Plot of the pectoralis muscle area (PMA) to paravertebral muscle area (PVMA). The relationship between the muscle groups was significant (R2 = 0.44, P

Implementing precision medicine for complex diseases such as chronic obstructive lung disease (COPD) will require extensive use of biomarkers and an in-depth understanding of how genetic, epigenetic, and environmental variations contribute to phenotypic diversity and disease progression. A meta-analysis from two large cohorts of current and former smokers with and without COPD [SPIROMICS (N = 750); COPDGene (N = 590)] was used to identify single nucleotide polymorphisms (SNPs) associated with measurement of 88 blood proteins (protein quantitative trait loci; pQTLs). PQTLs consistently replicated between the two cohorts. Features of pQTLs were compared to previously reported expression QTLs (eQTLs). Inference of causal relations of pQTL genotypes, biomarker measurements, and four clinical COPD phenotypes (airflow obstruction, emphysema, exacerbation history, and chronic bronchitis) were explored using conditional independence tests. We identified 527 highly significant (p < 8 X 10−10) pQTLs in 38 (43%) of blood proteins tested. Most pQTL SNPs were novel with low overlap to eQTL SNPs. The pQTL SNPs explained >10% of measured variation in 13 protein biomarkers, with a single SNP (rs7041; p = 10−392) explaining 71%-75% of the measured variation in vitamin D binding protein (gene = GC). Some of these pQTLs [e.g., pQTLs for VDBP, sRAGE (gene = AGER), surfactant protein D (gene = SFTPD), and TNFRSF10C] have been previously associated with COPD phenotypes. Most pQTLs were local (cis), but distant (trans) pQTL SNPs in the ABO blood group locus were the top pQTL SNPs for five proteins. The inclusion of pQTL SNPs improved the clinical predictive value for the established association of sRAGE and emphysema, and the explanation of variance (R2) for emphysema improved from 0.3 to 0.4 when the pQTL SNP was included in the model along with clinical covariates. Causal modeling provided insight into specific pQTL-disease relationships for airflow obstruction and emphysema. In conclusion, given the frequency of highly significant local pQTLs, the large amount of variance potentially explained by pQTL, and the differences observed between pQTLs and eQTLs SNPs, we recommend that protein biomarker-disease association studies take into account the potential effect of common local SNPs and that pQTLs be integrated along with eQTLs to uncover disease mechanisms. Large-scale blood biomarker studies would also benefit from close attention to the ABO blood group.

The heritability of chronic obstructive pulmonary disease (COPD) cannot be fully explained by recognized genetic risk factors identified as achieving genome-wide significance. In addition, the combined contribution of genetic variation to COPD risk has not been fully explored. We sought to determine: (1) whether studies of variants from previous studies of COPD or lung function in a larger sample could identify additional associated variants, particularly for severe COPD; and (2) the impact of genetic risk scores on COPD. We genotyped 3,346 single-nucleotide polymorphisms (SNPs) in 2,588 cases (1,803 severe COPD) and 1,782 control subjects from four cohorts, and performed association testing with COPD, combining these results with existing genotyping data from 6,633 cases (3,497 severe COPD) and 5,704 control subjects. In addition, we developed genetic risk scores from SNPs associated with lung function and COPD and tested their discriminatory power for COPD-related measures. We identified significant associations between SNPs near PPIC (P = 1.28 × 10-8) and PPP4R4/SERPINA1 (P = 1.01 × 10-8) and severe COPD; the latter association may be driven by recognized variants in SERPINA1. Genetic risk scores based on SNPs previously associated with COPD and lung function had a modest ability to discriminate COPD (area under the curve, ∼0.6), and accounted for a mean 0.9-1.9% lower forced expiratory volume in 1 second percent predicted for each additional risk allele. In a large genetic association analysis, we identified associations with severe COPD near PPIC and SERPINA1. A risk score based on combining genetic variants had modest, but significant, effects on risk of COPD and lung function.

Chronic obstructive pulmonary disease (COPD) is a leading cause of mortality worldwide. We performed a genetic association study in 15,256 cases and 47,936 controls, with replication of select top results (P < 5 × 10(-6)) in 9,498 cases and 9,748 controls. In the combined meta-analysis, we identified 22 loci associated at genome-wide significance, including 13 new associations with COPD. Nine of these 13 loci have been associated with lung function in general population samples, while 4 (EEFSEC, DSP, MTCL1, and SFTPD) are new. We noted two loci shared with pulmonary fibrosis (FAM13A and DSP) but that had opposite risk alleles for COPD. None of our loci overlapped with genome-wide associations for asthma, although one locus has been implicated in joint susceptibility to asthma and obesity. We also identified genetic correlation between COPD and asthma. Our findings highlight new loci associated with COPD, demonstrate the importance of specific loci associated with lung function to COPD, and identify potential regions of genetic overlap between COPD and other respiratory diseases.

Range of Cytokines and Chemokines for MSD assay. Table S2. Regression Models and Covariates for each Phenotype. Table S3. Biomarkers associated with age. Table S4. Biomarkers associated with female gender. Table S5. Biomarkers associated with BMI. Table S6. Biomarkers associated with current smoking. Table S7. Biomarkers associated with FEV1/FVC. Table S8. Amount of variance explained by biomarker and clinical covariate alone and in combination. Table S9. Biomarkers associated with decline in FEV1 (ml/yr) for all subjects. Table S10. Biomarkers associated with decline in FEV1 (ml/yr) by COPD or no COPD in COPDGene subjects. Figure S1. Subtyping of subjects based on airflow obstruction (FEV1/FVC) and emphysema severity (LAA% 5%). Subjects with chronic bronchitis are shown by red cross and those without a blue circle. The upper panel shows those included in analysis and the lower panels show the whole cohort for COPDGene (left) and SPIROMICS (right). Figure S2. Histograms of chemokines and cytokines in COPDGene and SPIROMICS (log10 transformed). Units are pg/ml. Figure S3. Pearson correlations between cytokines/chemokines and cell counts in COPDGene and SPIROMICS. Red squares are positive correlation coefficients and blue negative correlation coefficients with P

Cross Sectional Associations by Subgroup Heat Map. (PDF 156Â kb)

Associations with Disease Progression by Subgroup Heatmap. (PDF 7Â kb)

SummaryBackgroundChronic obstructive pulmonary disease (COPD) is characterized by marked phenotypic heterogeneity. Most previous studies have focused on COPD subjects with FEV1

RationaleThe small conducting airways are the major site of airflow obstruction in chronic obstructive pulmonary disease and may precede emphysema development.ObjectivesWe hypothesized a novel computed tomography (CT) biomarker of small airway disease predicts FEV1 decline.MethodsWe analyzed 1,508 current and former smokers from COPDGene with linear regression to assess predictors of change in FEV1 (ml/yr) over 5 years. Separate models for subjects without and with airflow obstruction were generated using baseline clinical and physiologic predictors in addition to two novel CT metrics created by parametric response mapping (PRM), a technique pairing inspiratory and expiratory CT images to define emphysema (PRM(emph)) and functional small airways disease (PRM(fSAD)), a measure of nonemphysematous air trapping.Measurements and main resultsMean (SD) rate of FEV1 decline in ml/yr for GOLD (Global Initiative for Chronic Obstructive Lung Disease) 0-4 was as follows: 41.8 (47.7), 53.8 (57.1), 45.6 (61.1), 31.6 (43.6), and 5.1 (35.8), respectively (trend test for grades 1-4; P

Chronic obstructive pulmonary disease (COPD) is a progressive disease with both environmental and genetic risk factors. Genome-wide association studies (GWAS) have identified multiple genomic regions influencing risk of COPD. To thoroughly investigate the genetic etiology of COPD, however, it is also important to explore the role of copy number variants (CNVs) because the presence of structural variants can alter gene expression and can be causal for some diseases. Here, we investigated effects of polymorphic CNVs on quantitative measures of pulmonary function and chest computed tomography (CT) phenotypes among subjects enrolled in COPDGene, a multisite study. COPDGene subjects consist of roughly one-third African American (AA) and two-thirds non-Hispanic white adult smokers (with or without COPD). We estimated CNVs using PennCNV on 9,076 COPDGene subjects using Illumina's Omni-Express genome-wide marker array. We tested for association between polymorphic CNV components (defined as disjoint intervals of copy number regions) for several quantitative phenotypes associated with COPD within each racial group. Among the AAs, we identified a polymorphic CNV on chromosome 5q35.2 located between two genes (FAM153B and SIMK1, but also harboring several pseudo-genes) giving genome-wide significance in tests of association with total lung capacity (TLCCT ) as measured by chest CT scans. This is the first study of genome-wide association tests of polymorphic CNVs and TLCCT . Although the ARIC cohort did not have the phenotype of TLCCT , we found similar counts of CNV deletions and amplifications among AA and European subjects in this second cohort.

BackgroundPulmonary function decline is a major contributor to morbidity and mortality among smokers. Post bronchodilator FEV1 and FEV1/FVC ratio are considered the standard assessment of airflow obstruction. We performed a genome-wide association study (GWAS) in 9919 current and former smokers in the COPDGene study (6659 non-Hispanic Whites [NHW] and 3260 African Americans [AA]) to identify associations with spirometric measures (post-bronchodilator FEV1 and FEV1/FVC). We also conducted meta-analysis of FEV1 and FEV1/FVC GWAS in the COPDGene, ECLIPSE, and GenKOLS cohorts (total n = 13,532).ResultsAmong NHW in the COPDGene cohort, both measures of pulmonary function were significantly associated with SNPs at the 15q25 locus [containing CHRNA3/5, AGPHD1, IREB2, CHRNB4] (lowest p-value = 2.17 × 10(-11)), and FEV1/FVC was associated with a genomic region on chromosome 4 [upstream of HHIP] (lowest p-value = 5.94 × 10(-10)); both regions have been previously associated with COPD. For the meta-analysis, in addition to confirming associations to the regions near CHRNA3/5 and HHIP, genome-wide significant associations were identified for FEV1 on chromosome 1 [TGFB2] (p-value = 8.99 × 10(-9)), 9 [DBH] (p-value = 9.69 × 10(-9)) and 19 [CYP2A6/7] (p-value = 3.49 × 10(-8)) and for FEV1/FVC on chromosome 1 [TGFB2] (p-value = 8.99 × 10(-9)), 4 [FAM13A] (p-value = 3.88 × 10(-12)), 11 [MMP3/12] (p-value = 3.29 × 10(-10)) and 14 [RIN3] (p-value = 5.64 × 10(-9)).ConclusionsIn a large genome-wide association study of lung function in smokers, we found genome-wide significant associations at several previously described loci with lung function or COPD. We additionally identified a novel genome-wide significant locus with FEV1 on chromosome 9 [DBH] in a meta-analysis of three study populations.

RationaleFormer smoking history and chronic obstructive pulmonary disease (COPD) are potential risk factors for osteoporosis and fractures. Under existing guidelines for osteoporosis screening, women are included but men are not, and only current smoking is considered.ObjectivesTo demonstrate the impact of COPD and smoking history on the risk of osteoporosis and vertebral fracture in men and women.MethodsCharacteristics of participants with low volumetric bone mineral density (vBMD) were identified and related to COPD and other risk factors. We tested associations of sex and COPD with both vBMD and fractures adjusting for age, race, body mass index (BMI), smoking, and glucocorticoid use.Measurements and main resultsvBMD by calibrated quantitative computed tomography (QCT), visually scored vertebral fractures, and severity of lung disease were determined from chest CT scans of 3,321 current and ex-smokers in the COPDGene study. Low vBMD as a surrogate for osteoporosis was calculated from young adult normal values. Male smokers had a small but significantly greater risk of low vBMD (2.5 SD below young adult mean by calibrated QCT) and more fractures than female smokers. Low vBMD was present in 58% of all subjects, was more frequent in those with worse COPD, and rose to 84% among subjects with very severe COPD. Vertebral fractures were present in 37% of all subjects and were associated with lower vBMD at each Global Initiative for Chronic Obstructive Lung Disease stage of severity. Vertebral fractures were most common in the midthoracic region. COPD and especially emphysema were associated with both low vBMD and vertebral fractures after adjustment for steroid use, age, pack-years of smoking, current smoking, and exacerbations. Airway disease was associated with higher bone density after adjustment for other variables. Calibrated QCT identified more subjects with abnormal values than the standard dual-energy X-ray absorptiometry in a subset of subjects and correlated well with prevalent fractures.ConclusionsMale smokers, with or without COPD, have a significant risk of low vBMD and vertebral fractures. COPD was associated with low vBMD after adjusting for race, sex, BMI, smoking, steroid use, exacerbations, and age. Screening for low vBMD by using QCT in men and women who are smokers will increase opportunities to identify and treat osteoporosis in this at-risk population.

Smoking is a notorious risk factor for chronic mucus hypersecretion (CMH). CMH frequently occurs in chronic obstructive pulmonary disease (COPD). The question arises whether the same single-nucleotide polymorphisms (SNPs) are related to CMH in smokers with and without COPD.We performed two genome-wide association studies of CMH under an additive genetic model in male heavy smokers (≥20 pack-years) with COPD (n=849, 39.9% CMH) and without COPD (n=1348, 25.4% CMH), followed by replication and meta-analysis in comparable populations, and assessment of the functional relevance of significantly associated SNPs.Genome-wide association analysis of CMH in COPD and non-COPD subjects yielded no genome-wide significance after replication. In COPD, our top SNP (rs10461985, p=5.43×10−5) was located in the GDNF-AS1 gene that is functionally associated with the GDNF gene. Expression of GDNF in bronchial biopsies of COPD patients was significantly associated with CMH (p=0.007). In non-COPD subjects, four SNPs had a p-value −5 in the meta-analysis, including a SNP (rs4863687) in the MAML3 gene, the T-allele showing modest association with CMH (p=7.57×10−6, OR 1.48) and with significantly increased MAML3 expression in lung tissue (p=2.59×10−12).Our data suggest the potential for differential genetic backgrounds of CMH in individuals with and without COPD.

The supplement for this manuscript contains the following information, tables, and figures. The COPD Foundation funding and a list of the COPDGene and ECLIPSE investigators are given in the supplement. Tables S1â S12 list the top SNPs with a p-value

[This corrects the article DOI: 10.1371/journal.pone.0091621.]

Smoking is a notorious risk factor for chronic mucus hypersecretion (CMH). CMH frequently occurs in chronic obstructive pulmonary disease (COPD). The question arises whether the same single-nucleotide polymorphisms (SNPs) are related to CMH in smokers with and without COPD. We performed two genome-wide association studies of CMH under an additive genetic model in male heavy smokers (≥20 pack-years) with COPD (n=849, 39.9% CMH) and without COPD (n=1348, 25.4% CMH), followed by replication and meta-analysis in comparable populations, and assessment of the functional relevance of significantly associated SNPs. Genome-wide association analysis of CMH in COPD and non-COPD subjects yielded no genome-wide significance after replication. In COPD, our top SNP (rs10461985, p=5.43×10(-5)) was located in the GDNF-AS1 gene that is functionally associated with the GDNF gene. Expression of GDNF in bronchial biopsies of COPD patients was significantly associated with CMH (p=0.007). In non-COPD subjects, four SNPs had a p-value10(-5) in the meta-analysis, including a SNP (rs4863687) in the MAML3 gene, the T-allele showing modest association with CMH (p=7.57×10(-6), OR 1.48) and with significantly increased MAML3 expression in lung tissue (p=2.59×10(-12)). Our data suggest the potential for differential genetic backgrounds of CMH in individuals with and without COPD.

Background Preserved Ratio Impaired Spirometry (PRISm), defined as a reduced FEV1 in the setting of a preserved FEV1/FVC ratio, is highly prevalent and is associated with increased respiratory symptoms, systemic inflammation, and mortality. Studies investigating quantitative chest tomographic features, genetic associations, and subtypes in PRISm subjects have not been reported. Methods Data from current and former smokers enrolled in COPDGene (n = 10,192), an observational, cross-sectional study which recruited subjects aged 45–80 with ≥10 pack years of smoking, were analyzed. To identify epidemiological and radiographic predictors of PRISm, we performed univariate and multivariate analyses comparing PRISm subjects both to control subjects with normal spirometry and to subjects with COPD. To investigate common genetic predictors of PRISm, we performed a genome-wide association study (GWAS). To explore potential subgroups within PRISm, we performed unsupervised k-means clustering. Results The prevalence of PRISm in COPDGene is 12.3%. Increased dyspnea, reduced 6-minute walk distance, increased percent emphysema and decreased total lung capacity, as well as increased segmental bronchial wall area percentage were significant predictors (p-value

ObjectiveDiabetes damages major organ systems through disrupted glycemic control and increased inflammation. The effects of diabetes on the lung have been of interest for decades, but the modest reduction in pulmonary function and its nonprogressive nature have limited its investigation. A recent systematic review found that diabetes was associated with reductions in forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), and diffusing capacity for carbon monoxide of the lung and increased FEV1/FVC. They reported pooled results including few smokers. This study will examine measures of pulmonary function in participants with extensive smoking exposure.Research design and methodsWe examined pulmonary function in participants with a >10-pack-year history of smoking with and without diabetes with and without chronic obstructive pulmonary disease (COPD). We measured pulmonary function, exercise capacity, and pulmonary-related quality of life in 10,129 participants in the Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene) Study.ResultsParticipants with diabetes were observed to have reduced pulmonary function after controlling for known risk factors and also significant reductions in exercise capacity and quality of life across functional stages of COPD.ConclusionsPulmonary function in patients with ≥10 pack-years of smoking and diabetes is reduced, and this decrease is associated with significant reductions in activity-related quality of life and exercise capacity.

Background: Chronic obstructive pulmonary disease (COPD) has been classically divided into blue bloaters and pink puffers. The utility of these clinical subtypes is unclear. However, the broader distinction between airway-predominant and emphysema-predominant COPD may be clinically relevant. The objective was to define clinical features of emphysema-predominant and non-emphysematous COPD patients. Methods: Current and former smokers from the Genetic Epidemiology of COPD Study (COPDGene) had chest computed tomography (CT) scans with quantitative image analysis. Emphysema-predominant COPD was defined by low attenuation area at -950 Hounsfield Units (LAA(-950)) >= 10%. Non-emphysematous COPD was defined by airflow obstruction with minimal to no emphysema (LAA(-950) < 5%). Results: Out of 4197 COPD subjects, 1687 were classified as emphysema-predominant and 1817 as non-emphysematous; 693 had LAA(-950) between 5-10% and were not categorized. Subjects with emphysema-predominant COPD were older (65.6 vs 60.6 years, p < 0.0001) with more severe COPD based on airflow obstruction (FEV1 44.5 vs 68.4%, p < 0.0001), greater exercise limitation (6-minute walk distance 1138 vs 1331 ft, p < 0.0001) and reduced quality of life (St. George's Respiratory Questionnaire score 43 vs 31, p < 0.0001). Self-reported diabetes was more frequent in non-emphysematous COPD (OR 2.13, p < 0.001), which was also confirmed using a strict definition of diabetes based on medication use. The association between diabetes and non-emphysematous COPD was replicated in the ECLIPSE study. Conclusions: Non-emphysematous COPD, defined by airflow obstruction with a paucity of emphysema on chest CT scan, is associated with an increased risk of diabetes. COPD patients without emphysema may warrant closer monitoring for diabetes, hypertension, and hyperlipidemia and vice versa., Supported by U.S. National Institutes of Health grants R01HL094635 (CPH), R01NR013377 (CPH), R01HL089856 (EKS), R01HL089897 (JDC), P01HL105339 (EKS). COPDGene is also supported by the COPD Foundation through contributions made to an Industry Advisory Board comprised of AstraZeneca, Pfizer, Novartis, Boehringer-Ingelheim, Siemens, Sunovion, and GlaxoSmithKline. ECLIPSE is supported by GlaxoSmithKline. The sponsors had no role in study design; collection, analysis, and interpretation of the data; preparation of the manuscript; and decision to submit the manuscript for publication.

BackgroundCOPD patients have a great burden of comorbidity. However, it is not well established whether this is due to shared risk factors such as smoking, if they impact patients exercise capacity and quality of life, or whether there are racial disparities in their impact on COPD.MethodsWe analyzed data from 10,192 current and ex-smokers with (cases) and without COPD (controls) from the COPDGene® cohort to establish risk for COPD comorbidities adjusted for pertinent covariates. In adjusted models, we examined comorbidities prevalence and impact in African-Americans (AA) and Non-Hispanic Whites (NHW).ResultsComorbidities are more common in COPD compared to those with normal spirometry (controls), and the risk persists after adjustments for covariates including pack-years smoked. After adjustment for confounders, eight conditions were independently associated with worse exercise capacity, quality of life and dyspnea. There were racial disparities in the impact of comorbidities on exercise capacity, dyspnea and quality of life, presence of osteoarthritis and gastroesophageal reflux disease having a greater negative impact on all three outcomes in AAs than NHWs (p

Rationale Bronchodilator responsiveness (BDR) is a common but variable phenomenon in COPD. The CT characteristics of airway dimensions that differentiate COPD subjects with BDR from those without BDR have not been well described. We aimed to assess airway dimensions in COPD subjects with and without BDR. Methods We analyzed subjects with GOLD 1–4 disease in the COPDGene® study who had CT airway analysis. We divided patients into two groups: BDR + (post bronchodilator ΔFEV1 ≥ 10%) and BDR-(post bronchodilator ΔFEV1

We performed a genome-wide association study of non-Hispanic, white individuals with fibrotic idiopathic interstitial pneumonias (IIPs; n = 1,616) and controls (n = 4,683), with follow-up replication analyses in 876 cases and 1,890 controls. We confirmed association with TERT at 5p15, MUC5B at 11p15 and the 3q26 region near TERC, and we identified seven newly associated loci (Pmeta = 2.4 × 10(-8) to 1.1 × 10(-19)), including FAM13A (4q22), DSP (6p24), OBFC1 (10q24), ATP11A (13q34), DPP9 (19p13) and chromosomal regions 7q22 and 15q14-15. Our results suggest that genes involved in host defense, cell-cell adhesion and DNA repair contribute to risk of fibrotic IIPs.

We performed a genome-wide association study of non-Hispanic, white individuals with fibrotic idiopathic interstitial pneumonias (IIPs; n = 1,616) and controls (n = 4,683), with follow-up replication analyses in 876 cases and 1,890 controls. We confirmed association with TERT at 5p15, MUC5B at 11p15 and the 3q26 region near TERC, and we identified seven newly associated loci (Pmeta = 2.4 × 10(-8) to 1.1 × 10(-19)), including FAM13A (4q22), DSP (6p24), OBFC1 (10q24), ATP11A (13q34), DPP9 (19p13) and chromosomal regions 7q22 and 15q14-15. Our results suggest that genes involved in host defense, cell-cell adhesion and DNA repair contribute to risk of fibrotic IIPs.

Implementing precision medicine for complex diseases such as chronic obstructive lung disease (COPD) will require extensive use of biomarkers and an in-depth understanding of how genetic, epigenetic, and environmental variations contribute to phenotypic diversity and disease progression. A meta-analysis from two large cohorts of current and former smokers with and without COPD [SPIROMICS (N = 750); COPDGene (N = 590)] was used to identify single nucleotide polymorphisms (SNPs) associated with measurement of 88 blood proteins (protein quantitative trait loci; pQTLs). PQTLs consistently replicated between the two cohorts. Features of pQTLs were compared to previously reported expression QTLs (eQTLs). Inference of causal relations of pQTL genotypes, biomarker measurements, and four clinical COPD phenotypes (airflow obstruction, emphysema, exacerbation history, and chronic bronchitis) were explored using conditional independence tests. We identified 527 highly significant (p < 8 X 10−10) pQTLs in 38 (43%) of blood proteins tested. Most pQTL SNPs were novel with low overlap to eQTL SNPs. The pQTL SNPs explained >10% of measured variation in 13 protein biomarkers, with a single SNP (rs7041; p = 10−392) explaining 71%-75% of the measured variation in vitamin D binding protein (gene = GC). Some of these pQTLs [e.g., pQTLs for VDBP, sRAGE (gene = AGER), surfactant protein D (gene = SFTPD), and TNFRSF10C] have been previously associated with COPD phenotypes. Most pQTLs were local (cis), but distant (trans) pQTL SNPs in the ABO blood group locus were the top pQTL SNPs for five proteins. The inclusion of pQTL SNPs improved the clinical predictive value for the established association of sRAGE and emphysema, and the explanation of variance (R2) for emphysema improved from 0.3 to 0.4 when the pQTL SNP was included in the model along with clinical covariates. Causal modeling provided insight into specific pQTL-disease relationships for airflow obstruction and emphysema. In conclusion, given the frequency of highly significant local pQTLs, the large amount of variance potentially explained by pQTL, and the differences observed between pQTLs and eQTLs SNPs, we recommend that protein biomarker-disease association studies take into account the potential effect of common local SNPs and that pQTLs be integrated along with eQTLs to uncover disease mechanisms. Large-scale blood biomarker studies would also benefit from close attention to the ABO blood group., Author Summary Precision medicine is an emerging approach that takes into account variability in genes, gene and protein expression, environment and lifestyle. Recent advances in high-throughput genome-wide genotyping, genomics, and proteomics coupled with the creation of large, highly-phenotyped clinical cohorts now allows for integration of these molecular data sets at the individual level. Here we use genome-wide genotyping and blood measurements of 88 biomarkers in 1,340 subjects from two large NIH-supported clinical cohorts of smokers (SPIROMICS and COPDGene) to identify more than 300 novel DNA variants that influence measurement of blood protein levels (pQTLs). We find that many DNA variants explain a large portion of the variability of measured protein expression in blood. Furthermore, we show that integration of DNA variants with blood biomarker levels can improve the ability of predictive models to reflect the relationship between biomarker and disease features (e.g., emphysema) within chronic obstructive pulmonary disease (COPD).

Rationale: Genome-wide association studies (GWAS) have identified loci influencing lung function, but fewer genes influencing chronic obstructive pulmonary disease (COPD) are known.

BackgroundThe coexistence of COPD and asthma is widely recognized but has not been well described. This study characterizes clinical features, spirometry, and chest CT scans of smoking subjects with both COPD and asthma.MethodsWe performed a cross-sectional study comparing subjects with COPD and asthma to subjects with COPD alone in the COPDGene Study.Results119 (13%) of 915 subjects with COPD reported a history of physician-diagnosed asthma. These subjects were younger (61.3 vs 64.7 years old, p=0.0001) with lower lifetime smoking intensity (43.7 vs 55.1 pack years, p=0.0001). More African-Americans reported a history of asthma (33.6% vs 15.6%, p

Reduced lung function predicts mortality and is key to the diagnosis of chronic obstructive pulmonary disease (COPD). In a genome-wide association study in 400,102 individuals of European ancestry, we define 279 lung function signals, 139 of which are new. In combination, these variants strongly predict COPD in independent populations. Furthermore, the combined effect of these variants showed generalizability across smokers and never smokers, and across ancestral groups. We highlight biological pathways, known and potential drug targets for COPD and, in phenome-wide association studies, autoimmune-related and other pleiotropic effects of lung function-associated variants. This new genetic evidence has potential to improve future preventive and therapeutic strategies for COPD.

Chest CT Parameters for Subjects With and Without History of Childhood Pneumonia. Table S2. Effect of Childhood Pneumonia with Childhood Asthmatics Removed. Table S3. Effect of Childhood Pneumonia in Childhood Asthmatics Only. Table S4. Recall Assessment in Subjects Who Did Not Report Known COPD or Emphysema Diagnosis. Figure S1. Classification of subjects in cohort based on childhood pneumonia status. Figure S2. Distribution of age of first pneumonia in entire cohort (a) in subjects with a history of childhood pneumonia (b) and in subjects without a history of childhood pneumonia (c). Includes all subjects who reported an age of first pneumonia. (PDF 943 kb)

205 SNPs Associated with IIP at 5 × 10−8 in Imputation Analysis. Table S2: SNPs with 5×10−8 0.5 Included. Figure S5: Comparison of SNPTest p-values after genomic control (see manuscript statistical methods) and GEMMA dosage-values. GEMMA dosage p-values computed after initial study complete. (DOCX 8917 kb)

205 SNPs Associated with IIP at 5 × 10−8 in Imputation Analysis. Table S2: SNPs with 5×10−8 0.5 Included. Figure S5: Comparison of SNPTest p-values after genomic control (see manuscript statistical methods) and GEMMA dosage-values. GEMMA dosage p-values computed after initial study complete. (DOCX 8917 kb)

Chronic obstructive pulmonary disease (COPD) is a leading cause of mortality worldwide. We performed a genetic association study in 15,256 cases and 47,936 controls, with replication of select top results (P < 5 × 10(-6)) in 9,498 cases and 9,748 controls. In the combined meta-analysis, we identified 22 loci associated at genome-wide significance, including 13 new associations with COPD. Nine of these 13 loci have been associated with lung function in general population samples, while 4 (EEFSEC, DSP, MTCL1, and SFTPD) are new. We noted two loci shared with pulmonary fibrosis (FAM13A and DSP) but that had opposite risk alleles for COPD. None of our loci overlapped with genome-wide associations for asthma, although one locus has been implicated in joint susceptibility to asthma and obesity. We also identified genetic correlation between COPD and asthma. Our findings highlight new loci associated with COPD, demonstrate the importance of specific loci associated with lung function to COPD, and identify potential regions of genetic overlap between COPD and other respiratory diseases.

Chest CT Parameters for Subjects With and Without History of Childhood Pneumonia. Table S2. Effect of Childhood Pneumonia with Childhood Asthmatics Removed. Table S3. Effect of Childhood Pneumonia in Childhood Asthmatics Only. Table S4. Recall Assessment in Subjects Who Did Not Report Known COPD or Emphysema Diagnosis. Figure S1. Classification of subjects in cohort based on childhood pneumonia status. Figure S2. Distribution of age of first pneumonia in entire cohort (a) in subjects with a history of childhood pneumonia (b) and in subjects without a history of childhood pneumonia (c). Includes all subjects who reported an age of first pneumonia. (PDF 943 kb)

IRB Approval and Protocol Numbers for COPDGene. (DOCX 26 kb)

Chronic obstructive pulmonary disease (COPD) has been classically divided into blue bloaters and pink puffers. The utility of these clinical subtypes is unclear. However, the broader distinction between airway-predominant and emphysema-predominant COPD may be clinically relevant. The objective was to define clinical features of emphysema-predominant and non-emphysematous COPD patients. Current and former smokers from the Genetic Epidemiology of COPD Study (COPDGene) had chest computed tomography (CT) scans with quantitative image analysis. Emphysema-predominant COPD was defined by low attenuation area at -950 Hounsfield Units (LAA-950) ≥10%. Non-emphysematous COPD was defined by airflow obstruction with minimal to no emphysema (LAA-950

Implementing precision medicine for complex diseases such as chronic obstructive lung disease (COPD) will require extensive use of biomarkers and an in-depth understanding of how genetic, epigenetic, and environmental variations contribute to phenotypic diversity and disease progression. A meta-analysis from two large cohorts of current and former smokers with and without COPD [SPIROMICS (N = 750); COPDGene (N = 590)] was used to identify single nucleotide polymorphisms (SNPs) associated with measurement of 88 blood proteins (protein quantitative trait loci; pQTLs). PQTLs consistently replicated between the two cohorts. Features of pQTLs were compared to previously reported expression QTLs (eQTLs). Inference of causal relations of pQTL genotypes, biomarker measurements, and four clinical COPD phenotypes (airflow obstruction, emphysema, exacerbation history, and chronic bronchitis) were explored using conditional independence tests. We identified 527 highly significant (p < 8 X 10^−10) pQTLs in 38 (43%) of blood proteins tested. Most pQTL SNPs were novel with low overlap to eQTL SNPs. The pQTL SNPs explained >10% of measured variation in 13 protein biomarkers, with a single SNP (rs7041; p = 10^−392) explaining 71%-75% of the measured variation in vitamin D binding protein (gene = GC). Some of these pQTLs [e.g., pQTLs for VDBP, sRAGE (gene = AGER), surfactant protein D (gene = SFTPD), and TNFRSF10C] have been previously associated with COPD phenotypes. Most pQTLs were local (cis), but distant (trans) pQTL SNPs in the ABO blood group locus were the top pQTL SNPs for five proteins. The inclusion of pQTL SNPs improved the clinical predictive value for the established association of sRAGE and emphysema, and the explanation of variance (R2) for emphysema improved from 0.3 to 0.4 when the pQTL SNP was included in the model along with clinical covariates. Causal modeling provided insight into specific pQTL-disease relationships for airflow obstruction and emphysema. In conclusion, given the frequency of highly significant local pQTLs, the large amount of variance potentially explained by pQTL, and the differences observed between pQTLs and eQTLs SNPs, we recommend that protein biomarker-disease association studies take into account the potential effect of common local SNPs and that pQTLs be integrated along with eQTLs to uncover disease mechanisms. Large-scale blood biomarker studies would also benefit from close attention to the ABO blood group.

IRB Approval and Protocol Numbers for COPDGene. (DOCX 26 kb)