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IntroductionDespite the identification of multiple susceptibility loci by genome-wide association studies (GWAS), considerable chronic obstructive pulmonary disease (COPD) heritability remains unexplained.AimTo identify interaction networks of airway epithelial cell DNA methylation in COPD and further explore potential correlations with airway bacterial composition, as potentially collective regulators of biological pathways influencing COPD severity.MethodsUsing DNA isolated from bronchial airway brushings of 67 ever-smokers (>20 pack-years) from the SubPopulations and InteRmediate Outcomes Measures in COPD Study (SPIROMICS), we assessed proportion of DNA methylation (β) by epigenome-wide association study (EWAS) and examined associations of differentially methylated CpG probes (DMPs) with risk for moderate-to-severe COPD (N=34) versus absent or mild COPD (N=33). We tested co-methylation modules generated by Weighted Correlation Network Analyses (WGCNA) for associations with moderate-to-severe COPD and with bacterial genus-level relative abundances (16S rRNA sequencing).ResultsEWAS-identified nominally significant DMPs enriched for lung function GWAS loci. Eigengenes in six WGCNA modules were associated with moderate-to-severe COPD (false discovery rate <0.05). Four of those modules were enriched for forced expiratory volume in 1 s/forced vital capacity GWAS loci, and five overlapped with DMPs from EWAS. Overlapping CpG loci in three COPD-associated modules were adjacent to mucin genes; one had 10 genes highly ranked by connectivity with MUC5B, including important pathway genes: B3GNT6, DGKI and ITGA8. CpGs in an independent COPD-associated module showed the most correlations with Rothia, with directionality suggestive of negative associations with moderate-severe COPD.ConclusionsBronchial epithelial DNA methylation modules enriched for lung function GWAS loci associate with COPD severity in SPIROMICS. Potential module relationships to bronchial bacterial composition require further validation.

Chronic bronchitis is currently diagnosed by asking patients if they expectorate sputum on a regular basis. In this study, the concentration of mucin was higher in the induced sputum of patients with chronic bronchitis than in those who did not meet the case definition of the disorder.

Chronic obstructive pulmonary disease diagnosis rests on chronic pulmonary symptoms and airflow obstruction. This study showed that people may have chronic COPD symptoms but no airflow obstruction. Such patients have more COPD exacerbations than those without chronic symptoms. Among the criteria that are needed to make a diagnosis of chronic obstructive pulmonary disease (COPD) are deficits in the rate at which one can forcefully exhale. Most experts consider a low ratio (<0.70) of the forced expiratory volume in 1 second (FEV 1 ) to the forced vital capacity (FVC) after bronchodilator use to be a key diagnostic criterion. 1 Once the diagnosis of COPD has been established, the Global Initiative for Chronic Obstructive Lung Disease (GOLD) nomenclature grades severity according to the degree to which the measured FEV 1 is lower than the patient’s predicted value. GOLD stage 1, . . .

More recent studies demonstrate that symptoms are associated with excess exacerbations and radiographic abnormalities (10, 11, 14). [...]features inadequately captured by spirometric airflow limitation are now recognized as independent clinical manifestations of COPD-related disease (15). An 8- to 10-pack-year smoking history has been linked to lung function decline in subjects aged 35 to 53 years (29). [...]contemporary studies confirm that \"chronic bronchitis\" or \"chronic mucus hypersecretion\" predict future COPD incidence (30), especially among younger adults (4). [...]matrix destruction might also cause airway dropout via anoikis, leading to the epithelial apoptosis observed by multiple groups in established disease but unstudied in early COPD. [...]rather than globally suppressing inflammatory cell function, future therapies to arrest early COPD might focus on containing the microbial invasion that drives inflammation.

BackgroundElectronic cigarettes (e-cigarettes) are battery-operated nicotine-delivery devices used by some smokers as a cessation tool as well as by never smokers.ObjectiveTo determine the usage of e-cigarettes in older adults at risk for or with chronic obstructive pulmonary disease (COPD).DesignProspective cohorts.ParticipantsCOPDGene (N = 3536) and SPIROMICS (N = 1060) subjects who were current or former smokers aged 45–80.Main MeasuresParticipants were surveyed to determine whether e-cigarette use was associated with longitudinal changes in COPD progression or smoking habits.Key ResultsFrom 2010 to 2016, participants who had ever used e-cigarettes steadily increased to 12–16%, but from 2014 to 2016 current use was stable at ~5%. E-cigarette use in African-Americans (AA) and whites was similar; however, AA were 1.8–2.9 times as likely to use menthol-flavored e-cigarettes. Current e-cigarette and conventional cigarette users had higher nicotine dependence and consumed more nicotine than those who smoked only conventional cigarettes. E-cigarette users had a heavier conventional cigarette smoking history and worse respiratory health, were less likely to reduce or quit conventional cigarette smoking, had higher nicotine dependence, and were more likely to report chronic bronchitis and exacerbations. Ever e-cigarette users had more rapid decline in lung function, but this trend did not persist after adjustment for persistent conventional cigarette smoking.ConclusionsE-cigarette use, which is common in adults with or at risk for COPD, was associated with worse pulmonary-related health outcomes, but not with cessation of smoking conventional cigarettes. Although this was an observational study, we find no evidence supporting the use of e-cigarettes as a harm reduction strategy among current smokers with or at risk for COPD.

Background The 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. Methods We performed a cross-sectional study comparing subjects with COPD and asthma to subjects with COPD alone in the COPDGene Study. Results 119 (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 < 0.0001). Subjects with COPD and asthma demonstrated worse disease-related quality of life, were more likely to have had a severe COPD exacerbation in the past year, and were more likely to experience frequent exacerbations (OR 3.55 [2.19, 5.75], p < 0.0001). Subjects with COPD and asthma demonstrated greater gas-trapping on chest CT. There were no differences in spirometry or CT measurements of emphysema or airway wall thickness. Conclusion Subjects with COPD and asthma represent a relevant clinical population, with worse health-related quality of life. They experience more frequent and severe respiratory exacerbations despite younger age and reduced lifetime smoking history. Trial registration ClinicalTrials.gov: NCT00608764

Abstract Rationale Chronic obstructive pulmonary disease (COPD) has been associated with numerous genetic variants, yet the extent to which its genetic risk is mediated by variation in lung structure remains unknown. Objectives To characterize associations between a genetic risk score (GRS) associated with COPD susceptibility and lung structure on computed tomography (CT). Methods We analyzed data from MESA Lung (Multi-Ethnic Study of Atherosclerosis Lung Study), a U.S. general population–based cohort, and SPIROMICS (Subpopulations and Intermediate Outcome Measures in COPD Study). A weighted GRS was calculated from 83 SNPs that were previously associated with lung function. Lung density, spatially matched airway dimensions, and airway counts were assessed on full-lung CT. Generalized linear models were adjusted for age, age squared, sex, height, principal components of genetic ancestry, smoking status, pack-years, CT model, milliamperes, and total lung volume. Measurements and Main Results MESA Lung and SPIROMICS contributed 2,517 and 2,339 participants, respectively. Higher GRS was associated with lower lung function and increased COPD risk, as well as lower lung density, smaller airway lumens, and fewer small airways, without effect modification by smoking. Adjustment for CT lung structure, particularly small airway measures, attenuated associations between the GRS and FEV1/FVC by 100% and 60% in MESA and SPIROMICS, respectively. Lung structure (P < 0.0001), but not the GRS (P > 0.10), improved discrimination of moderate-to-severe COPD cases relative to clinical factors alone. Conclusions A GRS associated with COPD susceptibility was associated with CT lung structure. Lung structure may be an important mediator of heritability and determinant of personalized COPD risk.

Chronic obstructive pulmonary disease (COPD) is a heterogeneous smoking-related disease characterized by airway obstruction and inflammation. This inflammation may persist even after smoking cessation and responds variably to corticosteroids. Personalizing treatment to biologically similar \"molecular phenotypes\" may improve therapeutic efficacy in COPD. IL-17A is involved in neutrophilic inflammation and corticosteroid resistance, and thus may be particularly important in a COPD molecular phenotype. We generated a gene expression signature of IL-17A response in bronchial airway epithelial brushings from smokers with and without COPD (n = 238), and validated it using data from 2 randomized trials of IL-17 blockade in psoriasis. This IL-17 signature was related to clinical and pathologic characteristics in 2 additional human studies of COPD: (a) SPIROMICS (n = 47), which included former and current smokers with COPD, and (b) GLUCOLD (n = 79), in which COPD participants were randomized to placebo or corticosteroids. The IL-17 signature was associated with an inflammatory profile characteristic of an IL-17 response, including increased airway neutrophils and macrophages. In SPIROMICS the signature was associated with increased airway obstruction and functional small airways disease on quantitative chest CT. In GLUCOLD the signature was associated with decreased response to corticosteroids, irrespective of airway eosinophilic or type 2 inflammation. These data suggest that a gene signature of IL-17 airway epithelial response distinguishes a biologically, radiographically, and clinically distinct COPD subgroup that may benefit from personalized therapy. ClinicalTrials.gov NCT01969344. Primary support from the NIH, grants K23HL123778, K12HL11999, U19AI077439, DK072517, U01HL137880, K24HL137013 and R01HL121774 and contracts HHSN268200900013C, HHSN268200900014C, HHSN268200900015C, HHSN268200900016C, HHSN268200900017C, HHSN268200900018C, HHSN268200900019C and HHSN268200900020C.

BackgroundTreatment and preventative advances for chronic obstructive pulmonary disease (COPD) have been slow due, in part, to limited subphenotypes. We tested if unsupervised machine learning on CT images would discover CT emphysema subtypes with distinct characteristics, prognoses and genetic associations.MethodsNew CT emphysema subtypes were identified by unsupervised machine learning on only the texture and location of emphysematous regions on CT scans from 2853 participants in the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS), a COPD case–control study, followed by data reduction. Subtypes were compared with symptoms and physiology among 2949 participants in the population-based Multi-Ethnic Study of Atherosclerosis (MESA) Lung Study and with prognosis among 6658 MESA participants. Associations with genome-wide single-nucleotide-polymorphisms were examined.ResultsThe algorithm discovered six reproducible (interlearner intraclass correlation coefficient, 0.91–1.00) CT emphysema subtypes. The most common subtype in SPIROMICS, the combined bronchitis-apical subtype, was associated with chronic bronchitis, accelerated lung function decline, hospitalisations, deaths, incident airflow limitation and a gene variant near DRD1, which is implicated in mucin hypersecretion (p=1.1 ×10−8). The second, the diffuse subtype was associated with lower weight, respiratory hospitalisations and deaths, and incident airflow limitation. The third was associated with age only. The fourth and fifth visually resembled combined pulmonary fibrosis emphysema and had distinct symptoms, physiology, prognosis and genetic associations. The sixth visually resembled vanishing lung syndrome.ConclusionLarge-scale unsupervised machine learning on CT scans defined six reproducible, familiar CT emphysema subtypes that suggest paths to specific diagnosis and personalised therapies in COPD and pre-COPD.

Background Transcriptomic analysis is common in large cohort studies but is generally restricted to cells in blood, which limits inferences about organs of interest, and direct organ sampling is mostly infeasible in large cohorts. New techniques for RNA-seq from noninvasive biosamples may provide the opportunity to profile transcriptomes of additional tissues for more organ-relevant insights at scale. We investigated the feasibility and utility of hair follicle gene expression profiling in a multi-center study of chronic obstructive pulmonary disease (COPD). Methods Bulk RNA-seq was performed on hair follicles collected in the SubPopulations and InteRmediate Outcome Measures in COPD Study (SPIROMICS), a multi-center longitudinal study of COPD ( n  = 97). The resulting hair follicle gene expression data were characterized and compared both to gene expression in whole blood and bronchial epithelium previously measured in SPIROMICS and to Genotype-Tissue Expression (GTEx) project tissue gene expression by principal component analysis and single-sample gene enrichment analysis, used to estimate hair follicle cell type proportions, and tested for association with disease-relevant lung phenotypes. eQTL discovery was also performed and colocalization with a genome-wide association study for lung function was tested. Results Hair follicles reliably produced transcriptomic data of sufficient quality and number for cell type composition, which revealed mostly epithelial and fibroblast cells. Comparison to other tissues previously profiled in SPIROMICS and GTEx project demonstrated transcriptomes from hair follicles were much more similar to those from lung parenchyma than blood. Combining these data with rich clinical, imaging, and genomic profiling in SPIROMICS, we found that they provided an attractive approach for discovery of associations with complex lung phenotypes, particularly of the airways. Finally, we investigated hair follicle genetic architecture through expression quantitative trait locus (eQTL) discovery and demonstrated better colocalization with lung-related genetic associations than blood. Conclusion Here, we demonstrated that RNA-seq applied to hair follicle transcriptomic profiling can be scaled up successfully in a multi-center study to yield inferences not available from blood transcriptomics.