Genome-wide association identifies regulatory Loci associated with distinct local histogram emphysema patterns

Breathing new life into the study of COPD with genes identified from genome-wide association studies

COPD is a major cause of morbidity and mortality globally. While the significance of environmental exposures in disease pathogenesis is well established, the functional contribution of genetic factors has only in recent years drawn attention. Notably, many genes associated with COPD risk are also linked with lung function. Because reduced lung function precedes COPD onset, this association is consistent with the possibility that derangements leading to COPD could arise during lung development. In this review, we summarise the role of leading genes (HHIP, FAM13A, DSP, AGER and TGFB2) identified by genome-wide association studies in lung development and COPD. Because many COPD genome-wide association study genes are enriched in lung epithelial cells, we focus on the role of these genes in the lung epithelium in development, homeostasis and injury.

Blood-based Transcriptomic and Proteomic Biomarkers of Emphysema

Rationale: Emphysema is a chronic obstructive pulmonary disease phenotype with important prognostic implications. Identifying blood-based biomarkers of emphysema will facilitate early diagnosis and development of targeted therapies. Objectives: To discover blood omics biomarkers for chest computed tomography-quantified emphysema and develop predictive biomarker panels. Methods: Emphysema blood biomarker discovery was performed using differential gene expression, alternative splicing, and protein association analyses in a training sample of 2,370 COPDGene participants with available blood RNA sequencing, plasma proteomics, and clinical data. Internal validation was conducted in a COPDGene testing sample (n = 1,016), and external validation was done in the ECLIPSE study (n = 526). Because low body mass index (BMI) and emphysema often co-occur, we performed a mediation analysis to quantify the effect of BMI on gene and protein associations with emphysema. Elastic net models with bootstrapping were also developed in the training sample sequentially using clinical, blood cell proportions, RNA-sequencing, and proteomic biomarkers to predict quantitative emphysema. Model accuracy was assessed by the area under the receiver operating characteristic curves for subjects stratified into tertiles of emphysema severity. Measurements and Main Results: Totals of 3,829 genes, 942 isoforms, 260 exons, and 714 proteins were significantly associated with emphysema (false discovery rate, 5%) and yielded 11 biological pathways. Seventy-four percent of these genes and 62% of these proteins showed mediation by BMI. Our prediction models demonstrated reasonable predictive performance in both COPDGene and ECLIPSE. The highest-performing model used clinical, blood cell, and protein data (area under the receiver operating characteristic curve in COPDGene testing, 0.90; 95% confidence interval, 0.85-0.90). Conclusions: Blood transcriptome and proteome-wide analyses revealed key biological pathways of emphysema and enhanced the prediction of emphysema.

Spatial Transcriptomics Resolve an Emphysema-Specific Lymphoid Follicle B Cell Signature in Chronic Obstructive Pulmonary Disease

Rationale: Within chronic obstructive pulmonary disease (COPD), emphysema is characterized by a significant yet partially understood B cell immune component. Objectives: To characterize the transcriptomic signatures from lymphoid follicles (LFs) in ever-smokers without COPD and patients with COPD with varying degrees of emphysema. Methods: Lung sections from 40 patients with COPD and ever-smokers were used for LF proteomic and transcriptomic spatial profiling. Formalin- and O.C.T.-fixed lung samples obtained from biopsies or lung explants were assessed for LF presence. Emphysema measurements were obtained from clinical chest computed tomographic scans. High-confidence transcriptional target intersection analyses were conducted to resolve emphysema-induced transcriptional networks. Measurements and Main Results: Overall, 115 LFs from ever-smokers and Global Initiative for Chronic Obstructive Lung Disease (GOLD) 1-2 and GOLD 3-4 patients were analyzed. No LFs were found in never-smokers. Differential gene expression analysis revealed significantly increased expression of LF assembly and B cell marker genes in subjects with severe emphysema. High-confidence transcriptional analysis revealed activation of an abnormal B cell activity signature in LFs (q-value = 2.56E-111). LFs from patients with GOLD 1-2 COPD with emphysema showed significantly increased expression of genes associated with antigen presentation, inflammation, and B cell activation and proliferation. LFs from patients with GOLD 1-2 COPD without emphysema showed an antiinflammatory profile. The extent of centrilobular emphysema was significantly associated with genes involved in B cell maturation and antibody production. Protein-RNA network analysis showed that LFs in emphysema have a unique signature skewed toward chronic B cell activation. Conclusions: An off-targeted B cell activation within LFs is associated with autoimmune-mediated emphysema pathogenesis.

Deep Learning Integration of Chest Computed Tomography Imaging and Gene Expression Identifies Novel Aspects of COPD

Rationale

Chronic obstructive pulmonary disease (COPD) is characterized by pathologic changes in the airways, lung parenchyma, and persistent inflammation, but the links between lung structural changes and blood transcriptome patterns have not been fully described.

Objections

The objective of this study was to identify novel relationships between lung structural changes measured by chest computed tomography (CT) and blood transcriptome patterns measured by blood RNA sequencing (RNA-seq).

Methods

CT scan images and blood RNA-seq gene expression from 1223 participants in the COPD Genetic Epidemiology (COPDGene®) study were jointly analyzed using deep learning to identify shared aspects of inflammation and lung structural changes that we labeled image-expression axes (IEAs). We related IEAs to COPD-related measurements and prospective health outcomes through regression and Cox proportional hazards models and tested them for biological pathway enrichment.

Results

We identified 2 distinct IEAs: IEAemph which captures an emphysema-predominant process with a strong positive correlation to CT emphysema and a negative correlation to forced expiratory volume in 1 second and body mass index (BMI); and IEAairway which captures an airway-predominant process with a positive correlation to BMI and airway wall thickness and a negative correlation to emphysema. Pathway enrichment analysis identified 29 and 13 pathways significantly associated with IEAemph and IEAairway, respectively (adjusted p<0.001).

Conclusions

Integration of CT scans and blood RNA-seq data identified 2 IEAs that capture distinct inflammatory processes associated with emphysema and airway-predominant COPD.

Animal models and mechanisms of tobacco smoke-induced chronic obstructive pulmonary disease (COPD)

Chronic obstructive pulmonary disease (COPD) is the third leading cause of death worldwide, and its global health burden is increasing. COPD is characterized by emphysema, mucus hypersecretion, and persistent lung inflammation, and clinically by chronic airflow obstruction and symptoms of dyspnea, cough, and fatigue in patients. A cluster of pathologies including chronic bronchitis, emphysema, asthma, and cardiovascular disease in the form of hypertension and atherosclerosis variably coexist in COPD patients. Underlying causes for COPD include primarily tobacco use but may also be driven by exposure to air pollutants, biomass burning, and workplace related fumes and chemicals. While no single animal model might mimic all features of human COPD, a wide variety of published models have collectively helped to improve our understanding of disease processes involved in the genesis and persistence of COPD. In this review, the pathogenesis and associated risk factors of COPD are examined in different mammalian models of the disease. Each animal model included in this review is exclusively created by tobacco smoke (TS) exposure. As animal models continue to aid in defining the pathobiological mechanisms of and possible novel therapeutic interventions for COPD, the advantages and disadvantages of each animal model are discussed.

A spatially resolved atlas of the human lung characterizes a gland-associated immune niche

Single-cell transcriptomics has allowed unprecedented resolution of cell types/states in the human lung, but their spatial context is less well defined. To (re)define tissue architecture of lung and airways, we profiled five proximal-to-distal locations of healthy human lungs in depth using multi-omic single cell/nuclei and spatial transcriptomics (queryable at lungcellatlas.org ). Using computational data integration and analysis, we extend beyond the suspension cell paradigm and discover macro and micro-anatomical tissue compartments including previously unannotated cell types in the epithelial, vascular, stromal and nerve bundle micro-environments. We identify and implicate peribronchial fibroblasts in lung disease. Importantly, we discover and validate a survival niche for IgA plasma cells in the airway submucosal glands (SMG). We show that gland epithelial cells recruit B cells and IgA plasma cells, and promote longevity and antibody secretion locally through expression of CCL28, APRIL and IL-6. This new 'gland-associated immune niche' has implications for respiratory health.

Genetics of chronic obstructive pulmonary disease: understanding the pathobiology and heterogeneity of a complex disorder

Chronic obstructive pulmonary disease (COPD) is a deadly and highly morbid disease. Susceptibility to and heterogeneity of COPD are incompletely explained by environmental factors such as cigarette smoking. Family-based and population-based studies have shown that a substantial proportion of COPD risk is related to genetic variation. Genetic association studies have identified hundreds of genetic variants that affect risk for COPD, decreased lung function, and other COPD-related traits. These genetic variants are associated with other pulmonary and non-pulmonary traits, demonstrate a genetic basis for at least part of COPD heterogeneity, have a substantial effect on COPD risk in aggregate, implicate early-life events in COPD pathogenesis, and often involve genes not previously suspected to have a role in COPD. Additional progress will require larger genetic studies with more ancestral diversity, improved profiling of rare variants, and better statistical methods. Through integration of genetic data with other omics data and comprehensive COPD phenotypes, as well as functional description of causal mechanisms for genetic risk variants, COPD genetics will continue to inform novel approaches to understanding the pathobiology of COPD and developing new strategies for management and treatment.

Incorporating Biomarkers in COPD Management: The Research Keeps Going

Globally, chronic obstructive pulmonary disease (COPD) remains a major cause of morbidity and mortality, having a significant socioeconomic effect. Several molecular mechanisms have been related to COPD including chronic inflammation, telomere shortening, and epigenetic modifications. Nowadays, there is an increasing need for novel therapeutic approaches for the management of COPD. These treatment strategies should be based on finding the source of acute exacerbation of COPD episodes and estimating the patient’s own risk. The use of biomarkers and the measurement of their levels in conjunction with COPD exacerbation risk and disease prognosis is considered an encouraging approach. Many types of COPD biomarkers have been identified which include blood protein biomarkers, cellular biomarkers, and protease enzymes. They have been isolated from different sources including peripheral blood, sputum, bronchoalveolar fluid, exhaled air, and genetic material. However, there is still not an exclusive biomarker that is used for the evaluation of COPD but rather a combination of them, and this is attributed to disease complexity. In this review, we summarize the clinical significance of COPD-related biomarkers, their association with disease outcomes, and COPD patients’ management. Finally, we depict the various samples that are used for identifying and measuring these biomarkers.

Genome-wide association study of hospitalized COVID-19 patients in the United Arab Emirates

BACKGROUND

The heterogeneity in symptomatology and phenotypic profile attributable to COVID-19 is widely unknown. The objective of this manuscript is to conduct a trans-ancestry genome wide association study (GWAS) meta-analysis of COVID-19 severity to improve the understanding of potentially causal targets for SARS-CoV-2.

METHODS

This cross-sectional study recruited 646 participants in the UAE that were divided into two phenotypic groups based on the severity of COVID-19 phenotypes, hospitalized (n=482) and non-hospitalized (n=164) participants. Hospitalized participants were COVID-19 patients that developed acute respiratory distress syndrome (ARDS), pneumonia or progression to respiratory failure that required supplemental oxygen therapy or mechanical ventilation support or had severe complications such as septic shock or multi-organ failure. We conducted a trans-ancestry meta-analysis GWAS of European (n=302), American (n=102), South Asian (n=99), and East Asian (n=107) ancestry populations. We also carried out comprehensive post-GWAS analysis, including enrichment of SNP associations in tissues and cell-types, expression quantitative trait loci and differential expression analysis.

FINDINGS

Eight genes demonstrated a strong association signal: VWA8 gene in locus 13p14·11 (SNP rs10507497; p=9·54 x10-7), PDE8B gene in locus 5q13·3 (SNP rs7715119; p=2·19 x10-6), CTSC gene in locus 11q14·2 (rs72953026; p=2·38 x10-6), THSD7B gene in locus 2q22·1 (rs7605851; p=3·07x10-6), STK39 gene in locus 2q24·3 (rs7595310; p=4·55 x10-6), FBXO34 gene in locus 14q22·3 (rs10140801; p=8·26 x10-6), RPL6P27 gene in locus 18p11·31 (rs11659676; p=8·88 x10-6), and METTL21C gene in locus 13q33·1 (rs599976; p=8·95 x10-6). The genes are expressed in the lung, associated to tumour progression, emphysema, airway obstruction, and surface tension within the lung, as well as an association to T-cell-mediated inflammation and the production of inflammatory cytokines.

INTERPRETATION

We have discovered eight highly plausible genetic association with hospitalized cases in COVID-19. Further studies must be conducted on worldwide population genetics to facilitate the development of population specific therapeutics to mitigate this worldwide challenge.

FUNDING

This review was commissioned as part of a project to study the host cell receptors of coronaviruses funded by Khalifa University's CPRA grant (Reference number 2020-004).

A genome-wide association study of quantitative computed tomographic emphysema in Korean populations

Emphysema is an important feature of chronic obstructive pulmonary disease (COPD). Genetic factors likely affect emphysema pathogenesis, but this question has predominantly been studied in those of European ancestry. In this study, we sought to determine genetic components of emphysema severity and characterize the potential function of the associated loci in Korean population. We performed a genome-wide association study (GWAS) on quantitative emphysema in subjects with or without COPD from two Korean COPD cohorts. We investigated the functional consequences of the loci using epigenetic annotation and gene expression data. We also compared our GWAS results with an epigenome-wide association study and previous differential gene expression analysis. In total, 548 subjects (476 [86.9%] male) including 514 COPD patients were evaluated. We identified one genome-wide significant SNP (P < 5.0 × 10^-8), rs117084279, near PIBF1. We identified an additional 57 SNPs (P < 5.0 × 10^-6) associated with emphysema in all subjects, and 106 SNPs (P < 5.0 × 10^-6) in COPD patients. Of these candidate SNPs, 2 (rs12459249, rs11667314) near CYP2A6 were expression quantitative trait loci in lung tissue and a SNP (rs11214944) near NNMT was an expression quantitative trait locus in whole blood. Of note, rs11214944 was in linkage disequilibrium with variants in enhancer histone marks in lung tissue. Several genes near additional SNPs were identified in our previous EWAS study with nominal level of significance. We identified a novel SNP associated with quantitative emphysema on CT. Including the novel SNP, several candidate SNPs in our study may provide clues to the genetic etiology of emphysema in Asian populations. Further research and validation of the loci will help determine the genetic factors for the development of emphysema.

Progress and Research Priorities in Imaging Genomics for Heart and Lung Disease: Summary of an NHLBI Workshop

Imaging genomics is a rapidly evolving field that combines state-of-the-art bioimaging with genomic information to resolve phenotypic heterogeneity associated with genomic variation, improve risk prediction, discover prevention approaches, and enable precision diagnosis and treatment. Contemporary bioimaging methods provide exceptional resolution generating discrete and quantitative high-dimensional phenotypes for genomics investigation. Despite substantial progress in combining high-dimensional bioimaging and genomic data, methods for imaging genomics are evolving. Recognizing the potential impact of imaging genomics on the study of heart and lung disease, the National Heart, Lung, and Blood Institute convened a workshop to review cutting-edge approaches and methodologies in imaging genomics studies, and to establish research priorities for future investigation. This report summarizes the presentations and discussions at the workshop. In particular, we highlight the need for increased availability of imaging genomics data in diverse populations, dedicated focus on less common conditions, and centralization of efforts around specific disease areas.

Filtering Spatial Point Patterns Using Kernel Densities

Understanding spatial inhomogeneity and clustering in point patterns arises in many contexts, ranging from disease outbreak monitoring to analyzing radiologically-based emphysema in biomedical images. This can often involve classifying individual points as being part of a feature/cluster or as being part of a background noise process. Existing methods for this task can struggle when there are differences in the size and/or density of individual clusters. In this work, we propose employing kernel density estimates of the underlying point process intensity function, using an existing data-driven approach to bandwidth selection, to separate feature points from noise. This is achieved by constructing a null distribution, either through asymptotic properties or Monte Carlo simulation, and comparing kernel density estimates to a given quantile of this distribution. We demonstrate that our method, termed Kernel Density and Simulation based Filtering (KDS-Filt), showed superior performance to existing alternative approaches, especially when there is inhomogeneity in cluster sizes and density. We also show the utility of KDS-Filt for identifying clinically relevant information about the spatial distribution of emphysema in lung computed tomography scans. The KDS-Filt methodology is available as part of the sncp R package, which can be downloaded at https://github.com/stop-pre16/sncp.

Chronic obstructive pulmonary disease and related phenotypes: polygenic risk scores in population-based and case-control cohorts

BACKGROUND

Genetic factors influence chronic obstructive pulmonary disease (COPD) risk, but the individual variants that have been identified have small effects. We hypothesised that a polygenic risk score using additional variants would predict COPD and associated phenotypes.

METHODS

We constructed a polygenic risk score using a genome-wide association study of lung function (FEV1 and FEV1/forced vital capacity [FVC]) from the UK Biobank and SpiroMeta. We tested this polygenic risk score in nine cohorts of multiple ethnicities for an association with moderate-to-severe COPD (defined as FEV1/FVC <0·7 and FEV1 <80% of predicted). Associations were tested using logistic regression models, adjusting for age, sex, height, smoking pack-years, and principal components of genetic ancestry. We assessed predictive performance of models by area under the curve. In a subset of studies, we also studied quantitative and qualitative CT imaging phenotypes that reflect parenchymal and airway pathology, and patterns of reduced lung growth.

FINDINGS

The polygenic risk score was associated with COPD in European (odds ratio [OR] per SD 1·81 [95% CI 1·74-1·88] and non-European (1·42 [1·34-1·51]) populations. Compared with the first decile, the tenth decile of the polygenic risk score was associated with COPD, with an OR of 7·99 (6·56-9·72) in European ancestry and 4·83 (3·45-6·77) in non-European ancestry cohorts. The polygenic risk score was superior to previously described genetic risk scores and, when combined with clinical risk factors (ie, age, sex, and smoking pack-years), showed improved prediction for COPD compared with a model comprising clinical risk factors alone (AUC 0·80 [0·79-0·81] vs 0·76 [0·75-0·76]). The polygenic risk score was associated with CT imaging phenotypes, including wall area percent, quantitative and qualitative measures of emphysema, local histogram emphysema patterns, and destructive emphysema subtypes. The polygenic risk score was associated with a reduced lung growth pattern.

INTERPRETATION

A risk score comprised of genetic variants can identify a small subset of individuals at markedly increased risk for moderate-to-severe COPD, emphysema subtypes associated with cigarette smoking, and patterns of reduced lung growth.

FUNDING

US National Institutes of Health, Wellcome Trust.

Smaller Left Ventricle Size at Noncontrast CT Is Associated with Lower Mortality in COPDGene Participants

Background Smokers with chronic obstructive pulmonary disease (COPD) have smaller left ventricles (LVs) due to reduced preload. Skeletal muscle wasting is also common in COPD, but less is known about its contribution to LV size. Purpose To explore the relationships between CT metrics of emphysema, venous vascular volume, and sarcopenia with the LV epicardial volume (LV_EV) (myocardium and chamber) estimated from chest CT images in participants with COPD and then to determine the clinical relevance of the LV_EV in multivariable models, including sex and anthropomorphic metrics. Materials and Methods The COPDGene study (ClinicalTrials.gov identifier: NCT00608764) is an ongoing prospective longitudinal observational investigation that began in 2006. LV_EV, distal pulmonary venous blood volume for vessels smaller than 5 mm² in cross section (BV5), CT emphysema, and pectoralis muscle area were retrospectively extracted from 3318 nongated, unenhanced COPDGene CT scans. Multivariable linear and Cox regression models were used to explore the association between emphysema, venous BV5, pectoralis muscle area, and LV_EV as well as the association of LV_EV with health status using the St George's Respiratory Questionnaire, 6-minute walk distance, and all-cause mortality. Results The median age of the cohort was 64 years (interquartile range, 57-70 years). Of the 2423 participants, 1806 were men and 617 were African American. The median LV_EV between Global Initiative for Chronic Obstructive Lung Disease (GOLD) 1 and GOLD 4 COPD was reduced by 13.9% in women and 17.7% in men (P < .001 for both). In fully adjusted models, higher emphysema percentage (β = -4.2; 95% confidence interval [CI]: -5.0, -3.4; P < .001), venous BV5 (β = 7.0; 95% CI: 5.7, 8.2; P < .001), and pectoralis muscle area (β = 2.7; 95% CI: 1.2, 4.1; P < .001) were independently associated with reduced LV_EV. Reductions in LV_EV were associated with improved health status (β = 0.3; 95% CI: 0.1, 0.4) and 6-minute walk distance (β = -12.2; 95% CI: -15.2, -9.3). These effects were greater in women than in men. The effect of reduced LV_EV on mortality (hazard ratio: 1.07; 95% CI: 1.05, 1.09) did not vary by sex. Conclusion In women more than men with chronic obstructive pulmonary disease, a reduction in the estimated left ventricle epicardial volume correlated with a loss of pulmonary venous vasculature, greater pectoralis muscle sarcopenia, and lower all-cause mortality. © RSNA, 2020 Online supplemental material is available for this article.

Artificial Intelligence in COPD: New Venues to Study a Complex Disease

Chronic obstructive pulmonary disease (COPD) is a complex and heterogeneous disease that can benefit from novel approaches to understanding its evolution and divergent trajectories. Artificial intelligence (AI) has revolutionized how we can use clinical, imaging, and molecular data to understand and model complex systems. AI has shown impressive results in areas related to automated clinical decision making, radiological interpretation and prognostication. The unique nature of COPD and the accessibility to well-phenotyped populations result in an ideal scenario for AI development. This review provides an introduction to AI and deep learning and presents some recent successes in applying AI in COPD. Finally, we will discuss some of the opportunities, challenges, and limitations for AI applications in the context of COPD.

Genetic Advances in Chronic Obstructive Pulmonary Disease. Insights from COPDGene

Chronic obstructive pulmonary disease (COPD) is a common and progressive disease that is influenced by both genetic and environmental factors. For many years, knowledge of the genetic basis of COPD was limited to Mendelian syndromes, such as alpha-1 antitrypsin deficiency and cutis laxa, caused by rare genetic variants. Over the past decade, the proliferation of genome-wide association studies, the accessibility of whole-genome sequencing, and the development of novel methods for analyzing genetic variation data have led to a substantial increase in the understanding of genetic variants that play a role in COPD susceptibility and COPD-related phenotypes. COPDGene (Genetic Epidemiology of COPD), a multicenter, longitudinal study of over 10,000 current and former cigarette smokers, has been pivotal to these breakthroughs in understanding the genetic basis of COPD. To date, over 20 genetic loci have been convincingly associated with COPD affection status, with additional loci demonstrating association with COPD-related phenotypes such as emphysema, chronic bronchitis, and hypoxemia. In this review, we discuss the contributions of the COPDGene study to the discovery of these genetic associations as well as the ongoing genetic investigations of COPD subtypes, protein biomarkers, and post-genome-wide association study analysis.

Lung epithelium damage in COPD - An unstoppable pathological event?

Chronic obstructive pulmonary disease (COPD) is a common term for alveolar septal wall destruction resulting in emphysema, and chronic bronchitis accompanied by conductive airway remodelling. In general, this disease is characterized by a disbalance of proteolytic/anti-proteolytic activity, augmented inflammatory response, increased oxidative/nitrosative stress, rise in number of apoptotic cells and decreased proliferation. As the first responder to the various environmental stimuli, epithelium occupies an important position in different lung pathologies, including COPD. Epithelium sequentially transitions from the upper airways in the direction of the gas exchange surface in the alveoli, and every cell type possesses a distinct role in the maintenance of the homeostasis. Basically, a thick ciliated structure of the airway epithelium has a major function in mucus secretion, whereas, alveolar epithelium which forms a thin barrier covered by surfactant has a function in gas exchange. Following this line, we will try to reveal whether or not the chronic bronchitis and emphysema, being two pathological phenotypes in COPD, could originate in two different types of epithelium. In addition, this review focuses on the role of lung epithelium in COPD pathology, and summarises underlying mechanisms and potential therapeutics.

Machine Learning Characterization of COPD Subtypes: Insights From the COPDGene Study

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.

Imaging Advances in Chronic Obstructive Pulmonary Disease. Insights from the Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene) Study

The Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene) study, which began in 2007, is an ongoing multicenter observational cohort study of more than 10,000 current and former smokers. The study is aimed at understanding the etiology, progression, and heterogeneity of chronic obstructive pulmonary disease (COPD). In addition to genetic analysis, the participants have been extensively characterized by clinical questionnaires, spirometry, volumetric inspiratory and expiratory computed tomography, and longitudinal follow-up, including follow-up computed tomography at 5 years after enrollment. The purpose of this state-of-the-art review is to summarize the major advances in our understanding of COPD resulting from the imaging findings in the COPDGene study. Imaging features that are associated with adverse clinical outcomes include early interstitial lung abnormalities, visual presence and pattern of emphysema, the ratio of pulmonary artery to ascending aortic diameter, quantitative evaluation of emphysema, airway wall thickness, and expiratory gas trapping. COPD is characterized by the early involvement of the small conducting airways, and the addition of expiratory scans has enabled measurement of small airway disease. Computational advances have enabled indirect measurement of nonemphysematous gas trapping. These metrics have provided insights into the pathogenesis and prognosis of COPD and have aided early identification of disease. Important quantifiable extrapulmonary findings include coronary artery calcification, cardiac morphology, intrathoracic and extrathoracic fat, and osteoporosis. Current active research includes identification of novel quantitative measures for emphysema and airway disease, evaluation of dose reduction techniques, and use of deep learning for phenotyping COPD.

Combined Pulmonary Fibrosis and Emphysema: Pulmonary Function Testing and a Pathophysiology Perspective

Combined pulmonary fibrosis and emphysema (CPFE) has been increasingly recognized over the past 10–15 years as a clinical entity characterized by rather severe imaging and gas exchange abnormalities, but often only mild impairment in spirometric and lung volume indices. In this review, we explore the gas exchange and mechanical pathophysiologic abnormalities of pulmonary emphysema, pulmonary fibrosis, and combined emphysema and fibrosis with the goal of understanding how individual pathophysiologic observations in emphysema and fibrosis alone may impact clinical observations on pulmonary function testing (PFT) patterns in patients with CPFE. Lung elastance and lung compliance in patients with CPFE are likely intermediate between those of patients with emphysema and fibrosis alone, suggesting a counter-balancing effect of each individual process. The outcome of combined emphysema and fibrosis results in higher lung volumes overall on PFTs compared to patients with pulmonary fibrosis alone, and the forced expiratory volume in one second (FEV₁)/forced vital capacity (FVC) ratio in CPFE patients is generally preserved despite the presence of emphysema on chest computed tomography (CT) imaging. Conversely, there appears to be an additive deleterious effect on gas exchange properties of the lungs, reflecting a loss of normally functioning alveolar capillary units and effective surface area available for gas exchange, and manifested by a uniformly observed severe reduction in the diffusing capacity for carbon monoxide (D_LCO). Despite normal or only mildly impaired spirometric and lung volume indices, patients with CPFE are often severely functionally impaired with an overall rather poor prognosis. As chest CT imaging continues to be a frequent imaging modality in patients with cardiopulmonary disease, we expect that patients with a combination of pulmonary emphysema and pulmonary fibrosis will continue to be observed. Understanding the pathophysiology of this combined process and the abnormalities that manifest on PFT testing will likely be helpful to clinicians involved with the care of patients with CPFE.

Arterial Vascular Pruning, Right Ventricular Size, and Clinical Outcomes in Chronic Obstructive Pulmonary Disease. A Longitudinal Observational Study

Rationale: Cor pulmonale (right ventricular [RV] dilation) and cor pulmonale parvus (RV shrinkage) are both described in chronic obstructive pulmonary disease (COPD). The identification of emphysema as a shared risk factor suggests that additional disease characterization is needed to understand these widely divergent cardiac processes.Objectives: To explore the relationship between computed tomography measures of emphysema and distal pulmonary arterial morphology with RV volume, and their association with exercise capacity and mortality in ever-smokers with COPD enrolled in the COPDGene Study.Methods: Epicardial (myocardium and chamber) RV volume (RVEV), distal pulmonary arterial blood vessel volume (arterial BV5: vessels <5 mm2 in cross-section), and objective measures of emphysema were extracted from 3,506 COPDGene computed tomography scans. Multivariable linear and Cox regression models and the log-rank test were used to explore the association between emphysema, arterial BV5, and RVEV with exercise capacity (6-min-walk distance) and all-cause mortality.Measurements and Main Results: The RVEV was approximately 10% smaller in Global Initiative for Chronic Obstructive Lung Disease stage 4 versus stage 1 COPD (P < 0.0001). In multivariable modeling, a 10-ml decrease in arterial BV5 (pruning) was associated with a 1-ml increase in RVEV. For a given amount of emphysema, relative preservation of the arterial BV5 was associated with a smaller RVEV. An increased RVEV was associated with reduced 6-minute-walk distance and in those with arterial pruning an increased mortality.Conclusions: Pulmonary arterial pruning is associated with clinically significant increases in RV volume in smokers with COPD and is related to exercise capacity and mortality in COPD.Clinical trial registered with www.clinicaltrials.gov (NCT00608764).

Identification of an emphysema-associated genetic variant near TGFB2 with regulatory effects in lung fibroblasts

Murine studies have linked TGF-β signaling to emphysema, and human genome-wide association studies (GWAS) studies of lung function and COPD have identified associated regions near genes in the TGF-β superfamily. However, the functional regulatory mechanisms at these loci have not been identified. We performed the largest GWAS of emphysema patterns to date, identifying 10 GWAS loci including an association peak spanning a 200 kb region downstream from TGFB2. Integrative analysis of publicly available eQTL, DNaseI, and chromatin conformation data identified a putative functional variant, rs1690789, that may regulate TGFB2 expression in human fibroblasts. Using chromatin conformation capture, we confirmed that the region containing rs1690789 contacts the TGFB2 promoter in fibroblasts, and CRISPR/Cas-9 targeted deletion of a ~ 100 bp region containing rs1690789 resulted in decreased TGFB2 expression in primary human lung fibroblasts. These data provide novel mechanistic evidence linking genetic variation affecting the TGF-β pathway to emphysema in humans.

DSP variants may be associated with longitudinal change in quantitative emphysema

Background

Emphysema, characterized by lung destruction, is a key component of Chronic Obstructive Pulmonary Disease (COPD) and is associated with increased morbidity and mortality. Genome-wide association studies (GWAS) have identified multiple genetic factors associated with cross-sectional measures of quantitative emphysema, but the genetic determinants of longitudinal change in quantitative measures of emphysema remain largely unknown. Our study aims to identify genetic variants associated with longitudinal change in quantitative emphysema measured by computed tomography (CT) imaging.

Methods

We included current and ex-smokers from two longitudinal cohorts: COPDGene, a study of Non-Hispanic Whites (NHW) and African Americans (AA), and the Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-points (ECLIPSE). We calculated annual change in two quantitative measures of emphysema based on chest CT imaging: percent low attenuation area (≤ − 950HU) (%LAA-950) and adjusted lung density (ALD). We conducted GWAS, separately in 3030 NHW and 1158 AA from COPDGene and 1397 Whites from ECLIPSE. We further explored effects of 360 previously reported variants and a lung function based polygenic risk score on annual change in quantitative emphysema.

Results

In the genome-wide association analysis, no variants achieved genome-wide significance (P < 5e-08). However, in the candidate region analysis, rs2076295 in the DSP gene, previously associated with COPD, lung function and idiopathic pulmonary fibrosis, was associated with change in %LAA-950 (β (SE) = 0.09 (0.02), P = 3.79e-05) and in ALD (β (SE) = − 0.06 (0.02), P = 2.88e-03). A lung function based polygenic risk score was associated with annual change in %LAA-950 (P = 4.03e-02) and with baseline measures of quantitative emphysema (P < 1e-03) and showed a trend toward association with annual change in ALD (P = 7.31e-02).

Conclusions

DSP variants may be associated with longitudinal change in quantitative emphysema. Additional investigation of the DSP gene are likely to provide further insights into the disease progression in emphysema and COPD.

Trial registration

Clinicaltrials.gov Identifier: NCT00608764, NCT00292552.

Electronic supplementary material

The online version of this article (10.1186/s12931-019-1097-8) contains supplementary material, which is available to authorized users.

Pharmacological Management of Chronic Obstructive Lung Disease (COPD). Focus on Mutations - Part 1

BACKGROUND

We report a comprehensive overview of current Chronic Obstructive Lung Disease (COPD) therapies and discuss the development of possible new pharmacological approaches based on "new" knowledge. Specifically, sensitivity/resistance to corticosteroids is evaluated with a special focus on the role of gene mutations in drug response.

OBJECTIVE

Critically review the opportunities and the challenges occurring in the treatment of COPD.

CONCLUSION

Findings from "omics" trials should be used to learn more about biological targeted drugs, and to select more specific drugs matching patient's distinctive molecular profile. Specific markers of inflammation such as the percentage of eosinophils are important in determining sensitivity/resistance to corticosteroids. Specific gene variations (Single nucleotide polymorphisms: SNPs) may influence drug sensitivity or resistance. Clinicians working in a real-world need to have a suitable interpretation of molecular results together with a guideline for the treatment and recommendations. Far more translational research is required before new results from omics techniques can be applied in personalized medicine in realworld settings.

The Role of Hedgehog Signaling in Adult Lung Regeneration and Maintenance

As a secreted morphogen, Sonic Hedgehog (SHH) determines differential cell fates, behaviors, and functions by forming a gradient of Hedgehog (Hh) activation along an axis of Hh-receptive cells during development. Despite clearly delineated roles for Hh during organ morphogenesis, whether Hh continues to regulate cell fate and behavior in the same fashion in adult organs is less understood. Adult organs, particularly barrier organs interfacing with the ambient environment, are exposed to insults that require renewal of cellular populations to maintain structural integrity. Understanding key aspects of Hh’s ability to generate an organ could translate into conceptual understanding of Hh’s ability to maintain organ homeostasis and stimulate regeneration. In this review, we will summarize the current knowledge about Hh signaling in regulating adult lung regeneration and maintenance, and discuss how alteration of Hh signaling contributes to adult lung diseases.

Pharmacogenomics of chronic obstructive pulmonary disease

INTRODUCTION

Chronic obstructive pulmonary disease (COPD) is a heterogeneous condition, which presents the opportunity for precision therapy based on genetics or other biomarkers. Areas covered: Alpha-1 antitrypsin deficiency, a genetic form of emphysema, provides an example of this precision approach to diagnosis and therapy. To date, research in COPD pharmacogenomics has been limited by small sample sizes, lack of accessible target tissue, failure to consider COPD subtypes, and different outcomes relevant for various medications. There have been several published genome-wide association studies and other omics studies in COPD pharmacogenomics; however, clinical implementation remains far away. There is a growing evidence base for precision prescription of inhaled corticosteroids in COPD, based on clinical phenotypes and blood biomarkers, but not yet based on pharmacogenomics. Expert opinion: At this time, there is insufficient evidence for clinical implementation of COPD pharmacogenomics. Additional genome-wide studies will be required to discover predictors of drug response and to identify genomic biomarkers of COPD subtypes, which could be targeted with subtype-directed therapies.

Allele-specific enhancers mediate associations between LCAT and ABCA1 polymorphisms and HDL metabolism

For most complex traits, the majority of SNPs identified through genome-wide association studies (GWAS) reside within noncoding regions that have no known function. However, these regions are enriched for the regulatory enhancers specific to the cells relevant to the specific trait. Indeed, many of the GWAS loci that have been functionally characterized lie within enhancers that regulate expression levels of key genes. In order to identify polymorphisms with potential allele-specific regulatory effects, we developed a bioinformatics pipeline that harnesses epigenetic signatures as well as transcription factor (TF) binding motifs to identify putative enhancers containing a SNP with potential allele-specific TF binding in linkage disequilibrium (LD) with a GWAS-identified SNP. We applied the approach to GWAS findings for blood lipids, revealing 7 putative enhancers harboring associated SNPs, 3 of which lie within the introns of LCAT and ABCA1, genes that play crucial roles in cholesterol biogenesis and lipoprotein metabolism. All 3 enhancers demonstrated allele-specific in vitro regulatory activity in liver-derived cell lines. We demonstrated that these putative enhancers are in close physical proximity to the promoters of their respective genes, in situ, likely through chromatin looping. In addition, the associated alleles altered the likelihood of transcription activator STAT3 binding. Our results demonstrate that through our approach, the LD blocks that contain GWAS signals, often hundreds of kilobases in size with multiple SNPs serving as statistical proxies to the true functional site, can provide an experimentally testable hypothesis for the underlying regulatory mechanism linking genetic variants to complex traits.

Limited overlap in significant hits between genome-wide association studies on two airflow obstruction definitions in the same population

BACKGROUND

Airflow obstruction is a hallmark of chronic obstructive pulmonary disease (COPD), and is defined as either the ratio between forced expiratory volume in one second and forced vital capacity (FEV1/FVC) < 70% or < lower limit of normal (LLN). This study aimed to assess the overlap between genome-wide association studies (GWAS) on airflow obstruction using these two definitions in the same population stratified by smoking.

METHODS

GWASes were performed in the LifeLines Cohort Study for both airflow obstruction definitions in never-smokers (NS = 5071) and ever-smokers (ES = 4855). The FEV1/FVC < 70% models were adjusted for sex, age, and height; FEV1/FVC < LLN models were not adjusted. Ever-smokers models were additionally adjusted for pack-years and current-smoking. The overlap in significantly associated SNPs between the two definitions and never/ever-smokers was assessed using several p-value thresholds. To quantify the agreement, the Pearson correlation coefficient was calculated between the p-values and ORs. Replication was performed in the Vlagtwedde-Vlaardingen study (NS = 432, ES = 823). The overlapping SNPs with p < 10- 4 were validated in the Vlagtwedde-Vlaardingen and Rotterdam Study cohorts (NS = 1966, ES = 3134) and analysed for expression quantitative trait loci (eQTL) in lung tissue (n = 1087).

RESULTS

In the LifeLines cohort, 96% and 93% of the never- and ever-smokers were classified concordantly based on the two definitions. 26 and 29% of the investigated SNPs were overlapping at p < 0.05 in never- and ever-smokers, respectively. At p < 10- 4 the overlap was 4% and 6% respectively, which could be change findings as shown by simulation studies. The effect estimates of the SNPs of the two definitions correlated strongly, but the p-values showed more variation and correlated only moderately. Similar observations were made in the Vlagtwedde-Vlaardingen study. Two overlapping SNPs in never-smokers (NFYC and FABP7) had the same direction of effect in the validation cohorts and the NFYC SNP was an eQTL for NFYC-AS1. NFYC is a transcription factor that binds to several known COPD genes, and FABP7 may be involved in abnormal pulmonary development.

CONCLUSIONS

The definition of airflow obstruction and the population under study may be important determinants of which SNPs are associated with airflow obstruction. The genes FABP7 and NFYC(-AS1) could play a role in airflow obstruction in never-smokers specifically.

A decade in psychiatric GWAS research

After more than 10 years of accumulated efforts, genome-wide association studies (GWAS) have led to many findings, most of which have been deposited into the GWAS Catalog. Between GWAS's inception and March 2017, the GWAS Catalog has collected 2429 studies, 1818 phenotypes, and 28,462 associated SNPs. We reclassified the psychology-related phenotypes into 217 reclassified phenotypes, which accounted for 514 studies and 7052 SNPs. In total, 1223 of the SNPs reached genome-wide significance. Of these, 147 were replicated for the same psychological trait in different studies. Another 305 SNPs were replicated within one original study. The SNPs rs2075650 and rs4420638 were linked to the most replications within a single reclassified phenotype or very similar reclassified phenotypes; both were associated with Alzheimer's disease (AD). Schizophrenia was associated with 74 within-phenotype SNPs reported in independents studies. Alzheimer's disease and schizophrenia were both linked to some physical phenotypes, including cholesterol and body mass index, through common GWAS signals. Alzheimer's disease also shared risk SNPs with age-related phenotypes such as age-related macular degeneration and longevity. Smoking-related SNPs were linked to lung cancer and respiratory function. Alcohol-related SNPs were associated with cardiovascular and digestive system phenotypes and disorders. Two separate studies also identified a shared risk SNP for bipolar disorder and educational attainment. This review revealed a list of reproducible SNPs worthy of future functional investigation. Additionally, by identifying SNPs associated with multiple phenotypes, we illustrated the importance of studying the relationships among phenotypes to resolve the nature of their causal links. The insights within this review will hopefully pave the way for future evidence-based genetic studies.

Using a spatial point process framework to characterize lung computed tomography scans

Pulmonary emphysema is a destructive disease of the lungs that is currently diagnosed via visual assessment of lung Computed Tomography (CT) scans by a radiologist. Visual assessment can have poor inter-rater reliability, is time consuming, and requires access to trained assessors. Quantitative methods that reliably summarize the biologically relevant characteristics of an image are needed to improve the way lung diseases are characterized. The goal of this work was to show how spatial point process models can be used to create a set of radiologically derived quantitative lung biomarkers of emphysema. We formalized a general framework for applying spatial point processes to lung CT scans, and developed a Shot Noise Cox Process to quantify how radiologically based emphysematous tissue clusters into larger structures. Bayesian estimation of model parameters was done using spatial Birth-Death MCMC (BD-MCMC). In simulations, we showed the BD-MCMC estimation algorithm is able to accurately recover model parameters. In an application to real lung CT scans from the COPDGene cohort, we showed variability in the clustering characteristics of emphysematous tissue across disease subtypes that were based on visual assessments of the CT scans.

Pharmacological Management of Chronic Obstructive Lung Disease (COPD). Evidence from a Real-World Perspective - Part 2

BACKGROUND

We report a comprehensive overview of current COPD therapies from a real-world experience.

OBJECTIVE

Critically review the opportunities and the challenges occurring in the real-world treatment of COPD.

METHODS

This is a review that also report results from COPD patients treated with standardized therapy including pulmonary rehabilitation (Real World Data - RWD).

CONCLUSION

Comprehensive assessment of COPD management requires strategies able to evaluate efficacy and usefulness in a real-world population, that take into account the interaction between experience and academic training, research, adherence to guidelines and judgments in order to plan the appropriate and optimum use of available strategies.

The usefulness of soluble receptor for advanced glycation end-products in the identification of COPD frequent exacerbator phenotype

Introduction

Exacerbations of COPD (ECOPDs) are important events in the course of COPD, accelerating the rate of decline in lung function and increasing the mortality risk. A growing body of evidence suggests the significance of the “frequent exacerbator” phenotype. This phenotype seems to be associated with a more severe airflow limitation, symptoms, health-related quality of life impairment, and higher mortality. However, there is no described biomarker that would help to identify this group of patients.

Patients and methods

Patients with COPD in “D” GOLD category were monitored for 3 years according to events of ECOPD. Serum samples were collected from the patients. Circulating level of plasma soluble receptor for advanced glycation end-products (sRAGE) was measured using commercially available high sensitivity kits. The receiver operating characteristic (ROC) curve analysis was used to assess the usefulness of sRAGE to identify frequent exacerbator phenotype. Log-rank test was used in the analysis of time to the subsequent exacerbation. Pearson (R) or Spearman’s rank (R_S) correlation coefficients were used for correlation analysis.

Results

Nineteen patients were enrolled. The area under the ROC curve (AUROC) for sRAGE for the identification of frequent exacerbator phenotype was 0.81. Analysis identified the cutoff point as 850.407 pg/mL, characterized by a sensitivity of 0.80 (95% CI: 0.28–1.0) and specificity of 0.93 (95% CI: 0.66–1.0). Additionally, in the group with sRAGE ≤850.407 pg/mL, we observed significantly shorter time to the subsequent exacerbation: median of 32 vs 105.5 days (P=0.03). Correlation analysis revealed significant negative correlation between sRAGE and the number of exacerbations requiring hospitalization during the whole time of follow-up (R_S=−0.53; P=0.02) and significant positive correlation with FEV₁ expressed as the percentage of reference value (R=0.6; P=0.006).

Conclusion

sRAGE seems to be useful in the identification of frequent exacerbator phenotype. This parameter may also be used in the prediction of time to ECOPD. Our findings should be confirmed in a sufficiently powered larger sample.

Dissecting the Genetics of Osteoporosis using Systems Approaches

Osteoporosis is a condition characterized by low bone mineral density (BMD) and an increased risk of fracture. Traits contributing to osteoporotic fracture are highly heritable, indicating that a comprehensive understanding of bone requires a thorough understanding of the genetic basis of bone traits. Towards this goal, genome-wide association studies (GWASs) have identified over 500 loci associated with bone traits. However, few of the responsible genes have been identified, and little is known of how these genes work together to influence systems-level bone function. In this review, we describe how systems genetics approaches can be used to fill these knowledge gaps.

Myh10 deficiency leads to defective extracellular matrix remodeling and pulmonary disease

Impaired alveolar formation and maintenance are features of many pulmonary diseases that are associated with significant morbidity and mortality. In a forward genetic screen for modulators of mouse lung development, we identified the non-muscle myosin II heavy chain gene, Myh10. Myh10 mutant pups exhibit cyanosis and respiratory distress, and die shortly after birth from differentiation defects in alveolar epithelium and mesenchyme. From omics analyses and follow up studies, we find decreased Thrombospondin expression accompanied with increased matrix metalloproteinase activity in both mutant lungs and cultured mutant fibroblasts, as well as disrupted extracellular matrix (ECM) remodeling. Loss of Myh10 specifically in mesenchymal cells results in ECM deposition defects and alveolar simplification. Notably, MYH10 expression is downregulated in the lung of emphysema patients. Altogether, our findings reveal critical roles for Myh10 in alveologenesis at least in part via the regulation of ECM remodeling, which may contribute to the pathogenesis of emphysema.

COPD is accompanied by co-ordinated transcriptional perturbation in the quadriceps affecting the mitochondria and extracellular matrix

Skeletal muscle dysfunction is a frequent extra-pulmonary manifestation of Chronic Obstructive Pulmonary Disease (COPD) with implications for both quality of life and survival. The underlying biology nevertheless remains poorly understood. We measured global gene transcription in the quadriceps using Affymetrix HuGene1.1ST arrays in an unselected cohort of 79 stable COPD patients in secondary care and 16 healthy age- and gender-matched controls. We detected 1,826 transcripts showing COPD-related variation. Eighteen exhibited ≥2fold changes (SLC22A3, FAM184B, CDKN1A, FST, LINC01405, MUSK, PANX1, ANKRD1, C12orf75, MYH1, POSTN, FRZB, TNC, ACTC1, LINC00310, MYH3, MYBPH and AREG). Thirty-one transcripts possessed previous reported evidence of involvement in COPD through genome-wide association, including FAM13A. Network analysis revealed a substructure comprising 6 modules of co-expressed genes. We identified modules with mitochondrial and extracellular matrix features, of which IDH2, a central component of the mitochondrial antioxidant pathway, and ABI3BP, a proposed switch between proliferation and differentiation, represent hubs respectively. COPD is accompanied by coordinated patterns of transcription in the quadriceps involving the mitochondria and extracellular matrix and including genes previously implicated in primary disease processes.

Expansion of hedgehog disrupts mesenchymal identity and induces emphysema phenotype

GWAS have repeatedly mapped susceptibility loci for emphysema to genes that modify hedgehog signaling, but the functional relevance of hedgehog signaling to this morbid disease remains unclear. In the current study, we identified a broad population of mesenchymal cells in the adult murine lung receptive to hedgehog signaling, characterized by higher activation of hedgehog surrounding the proximal airway relative to the distal alveoli. Single-cell RNA-sequencing showed that the hedgehog-receptive mesenchyme is composed of mostly fibroblasts with distinct proximal and distal subsets with discrete identities. Ectopic hedgehog activation in the distal fibroblasts promoted expression of proximal fibroblast markers and loss of distal alveoli and airspace enlargement of over 20% compared with controls. We found that hedgehog suppressed mesenchymal-derived mitogens enriched in distal fibroblasts that regulate alveolar stem cell regeneration and airspace size. Finally, single-cell analysis of the human lung mesenchyme showed that segregated proximal-distal identity with preferential hedgehog activation in the proximal fibroblasts was conserved between mice and humans. In conclusion, we showed that differential hedgehog activation segregates mesenchymal identities of distinct fibroblast subsets and that disruption of fibroblast identity can alter the alveolar stem cell niche, leading to emphysematous changes in the murine lung.

Genome-wide assessment of gene-by-smoking interactions in COPD

Cigarette smoke exposure is a major risk factor in chronic obstructive pulmonary disease (COPD) and its interactions with genetic variants could affect lung function. However, few gene-smoking interactions have been reported. In this report, we evaluated the effects of gene-smoking interactions on lung function using Korea Associated Resource (KARE) data with the spirometric variables—forced expiratory volume in 1 s (FEV₁). We found that variations in FEV₁ were different among smoking status. Thus, we considered a linear mixed model for association analysis under heteroscedasticity according to smoking status. We found a previously identified locus near SOX9 on chromosome 17 to be the most significant based on a joint test of the main and interaction effects of smoking. Smoking interactions were replicated with Gene-Environment of Interaction and phenotype (GENIE), Multi-Ethnic Study of Atherosclerosis-Lung (MESA-Lung), and COPDGene studies. We found that individuals with minor alleles, rs17765644, rs17178251, rs11870732, and rs4793541, tended to have lower FEV₁ values, and lung function decreased much faster with age for smokers. There have been very few reports to replicate a common variant gene-smoking interaction, and our results revealed that statistical models for gene-smoking interaction analyses should be carefully selected.

Extracellular matrix in lung development, homeostasis and disease

The lung's unique extracellular matrix (ECM), while providing structural support for cells, is critical in the regulation of developmental organogenesis, homeostasis and injury-repair responses. The ECM, via biochemical or biomechanical cues, regulates diverse cell functions, fate and phenotype. The composition and function of lung ECM become markedly deranged in pathological tissue remodeling. ECM-based therapeutics and bioengineering approaches represent promising novel strategies for regeneration/repair of the lung and treatment of chronic lung diseases. In this review, we assess the current state of lung ECM biology, including fundamental advances in ECM composition, dynamics, topography, and biomechanics; the role of the ECM in normal and aberrant lung development, adult lung diseases and autoimmunity; and ECM in the regulation of the stem cell niche. We identify opportunities to advance the field of lung ECM biology and provide a set recommendations for research priorities to advance knowledge that would inform novel approaches to the pathogenesis, diagnosis, and treatment of chronic lung diseases.

Human Genetics of Addiction: New Insights and Future Directions

PURPOSE OF REVIEW

With the advent of the genome-wide association study (GWAS), our understanding of the genetics of addiction has made significant strides forward. Here, we summarize genetic loci containing variants identified at genome-wide statistical significance (P < 5 × 10-8) and independently replicated, review evidence of functional or regulatory effects for GWAS-identified variants, and outline multi-omics approaches to enhance discovery and characterize addiction loci.

RECENT FINDINGS

Replicable GWAS findings span 11 genetic loci for smoking, eight loci for alcohol, and two loci for illicit drugs combined and include missense functional variants and noncoding variants with regulatory effects in human brain tissues traditionally viewed as addiction-relevant (e.g., prefrontal cortex [PFC]) and, more recently, tissues often overlooked (e.g., cerebellum). GWAS analyses have discovered several novel, replicable variants contributing to addiction. Using larger sample sizes from harmonized datasets and new approaches to integrate GWAS with multiple 'omics data across human brain tissues holds great promise to significantly advance our understanding of the biology underlying addiction.

COPD GWAS variant at 19q13.2 in relation with DNA methylation and gene expression

Chronic obstructive pulmonary disease (COPD) is among the major health burdens in adults. While cigarette smoking is the leading risk factor, a growing number of genetic variations have been discovered to influence disease susceptibility. Epigenetic modifications may mediate the response of the genome to smoking and regulate gene expression. Chromosome 19q13.2 region is associated with both smoking and COPD, yet its functional role is unclear. Our study aimed to determine whether rs7937 (RAB4B, EGLN2), a top genetic variant in 19q13.2 region identified in genome-wide association studies of COPD, is associated with differential DNA methylation in blood (N = 1490) and gene expression in blood (N = 721) and lungs (N = 1087). We combined genetic and epigenetic data from the Rotterdam Study (RS) to perform the epigenome-wide association analysis of rs7937. Further, we used genetic and transcriptomic data from blood (RS) and from lung tissue (Lung expression quantitative trait loci mapping study), to perform the transcriptome-wide association study of rs7937. Rs7937 was significantly (FDR < 0.05) and consistently associated with differential DNA methylation in blood at 4 CpG sites in cis, independent of smoking. One methylation site (cg11298343-EGLN2) was also associated with COPD (P = 0.001). Additionally, rs7937 was associated with gene expression levels in blood in cis (EGLN2), 42% mediated through cg11298343, and in lung tissue, in cis and trans (NUMBL, EGLN2, DNMT3A, LOC101929709 and PAK2). Our results suggest that changes of DNA methylation and gene expression may be intermediate steps between genetic variants and COPD, but further causal studies in lung tissue should confirm this hypothesis.

Visual Assessment of Chest Computed Tomographic Images Is Independently Useful for Genetic Association Analysis in Studies of Chronic Obstructive Pulmonary Disease

RATIONALE

Automated analysis of computed tomographic (CT) lung images for epidemiologic and genetic association studies is increasingly common, but little is known about the utility of visual versus semiautomated emphysema and airway assessments for genetic association studies.

OBJECTIVES

Assess the relative utility of visual versus semiautomated emphysema and airway assessments for genetic association studies.

METHODS

A standardized inspection protocol was used to visually assess chest CT images for 1,540 non-Hispanic white subjects within the COPDGene Study for the presence and severity of radiographic features representing airway wall thickness and emphysema. A genome-wide association study (GWAS) was performed, and two sets of candidate single-nucleotide polymorphisms with a higher prior likelihood of association were specified a priori for separate analysis. For each visual CT examination feature, a corresponding semiautomated CT feature(s) was identified for comparison in the same subjects.

MEASUREMENTS AND MAIN RESULTS

GWAS for visual features of chest CT scans identified a genome-wide significant association with visual emphysema at the 15q25 locus (P = 6.3e^-9). In the a priori-specified set of 19 previously identified GWAS loci, 7 and 8 loci were associated with airway measures or emphysema measures, respectively. In the a priori-specified candidate gene set, 13 of 196 candidate genes harbored a nearby single-nucleotide polymorphism significantly associated with an emphysema phenotype. Visual CT examination associations were robust to adjustment for semiautomated correlates in many cases.

CONCLUSIONS

Standardized visual assessments of emphysema and airway disease are significantly associated with genetic loci previously associated with chronic obstructive pulmonary disease susceptibility or semiautomated CT examination phenotypes in GWAS. Visual CT measures of emphysema and airways disease offer independent information for genetic association studies in relation to standard semiautomated measures.

Disease Severity Dependence of the Longitudinal Association Between CT Lung Density and Lung Function in Smokers

BACKGROUND

In smokers, the lung parenchyma is characterized by inflammation and emphysema, processes that can result in local gain and loss of lung tissue. CT measures of lung density might reflect lung tissue changes; however, longitudinal data regarding the effects of CT lung tissue on FEV₁ in smokers with and without COPD are scarce.

METHODS

The 15th percentile of CT lung density was obtained from the scans of 3,390 smokers who completed baseline and 5-year follow-up of the Genetic Epidemiology of COPD (COPDGene) study visits. The longitudinal relationship between total lung capacity-adjusted lung density (TLC-PD15) and FEV₁ was assessed by using multivariable mixed models. Separate models were performed in smokers at risk, smokers with preserved ratio and impaired spirometry (PRISm), and smokers with COPD according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) staging system.

RESULTS

The direction of the relationship between lung density and lung function was GOLD stage dependent. In smokers with PRISm, a 1-g/L decrease in TLC-PD15 was associated with an increase of 2.8 mL FEV₁ (P = .02). In contrast, among smokers with GOLD III to IV COPD, a 1-g/L decrease in TLC-PD15 was associated with a decrease of 4.1 mL FEV₁ (P = .002).

CONCLUSIONS

A decline in TLC-PD15 was associated with an increase or decrease in FEV₁ depending on disease severity. The associations are GOLD stage specific, and their presence might influence the interpretation of future studies that use CT lung density as an intermediate study end point for a decline in lung function.

TRIAL REGISTRY

ClinicalTrials.gov; No.: NCT00608764; URL: www.clinicaltrials.gov.

Lobar Emphysema Distribution Is Associated With 5-Year Radiological Disease Progression

BACKGROUND

Emphysema 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.

METHODS

We 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.

RESULTS

Three 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.

CONCLUSIONS

Subgroups 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.

Variable Susceptibility to Cigarette Smoke-Induced Emphysema in 34 Inbred Strains of Mice Implicates Abi3bp in Emphysema Susceptibility

Chronic obstructive pulmonary disease (COPD) is caused by a complex interaction of environmental exposures, most commonly cigarette smoke, and genetic factors. Chronic cigarette smoke exposure in the mouse is a commonly used animal model of COPD. We aimed to expand our knowledge about the variable susceptibility of inbred strains to this model and test for genetic variants associated with this trait. To that end, we sought to measure differential susceptibility to cigarette smoke-induced emphysema in the mouse, identify genetic loci associated with this quantitative trait, and find homologous human genes associated with COPD. Alveolar chord length (CL) in 34 inbred strains of mice was measured after 6 months of exposure to cigarette smoke. After testing for association, we connected a murine candidate locus to a published meta-analysis of moderate-to-severe COPD. We identified deleterious mutations in a candidate gene in silico and measured gene expression in extreme strains. A/J was the most susceptible strain in our survey (Δ CL 7.0 ± 2.2 μm) and CBA/J was the least susceptible (Δ CL -0.3 ± 1.2 μm). By integrating mouse and human genome-wide scans, we identified the candidate gene Abi3bp. CBA/J mice harbor predicted deleterious variants in Abi3bp, and expression of the gene differs significantly between CBA/J and A/J mice. This is the first report of susceptibility to cigarette smoke-induced emphysema in 34 inbred strains of mice, and Abi3bp is identified as a potential contributor to this phenotype.

Extreme Trait Whole-Genome Sequencing Identifies PTPRO as a Novel Candidate Gene in Emphysema with Severe Airflow Obstruction

RATIONALE

Genetic association studies in chronic obstructive pulmonary disease have primarily tested for association with common variants, the results of which explain only a portion of disease heritability. Because rare variation is also likely to contribute to susceptibility, we used whole-genome sequencing of subjects with clinically extreme phenotypes to identify genomic regions enriched for rare variation contributing to chronic obstructive pulmonary disease susceptibility.

OBJECTIVES

To identify regions of rare genetic variation contributing to emphysema with severe airflow obstruction.

METHODS

We identified heavy smokers that were resistant (n = 65) or susceptible (n = 64) to emphysema with severe airflow obstruction in the Pittsburgh Specialized Center of Clinically Oriented Research cohort. We filtered whole-genome sequencing results to include only rare variants and conducted single variant tests, region-based tests across the genome, gene-based tests, and exome-wide tests.

MEASUREMENTS AND MAIN RESULTS

We identified several suggestive associations with emphysema with severe airflow obstruction, including a suggestive association of all rare variation in a region within the gene ZNF816 (19q13.41; P = 4.5 × 10^-6), and a suggestive association of nonsynonymous coding rare variation in the gene PTPRO (P = 4.0 × 10^-5). Association of rs61754411, a rare nonsynonymous variant in PTPRO, with emphysema and obstruction was demonstrated in all non-Hispanic white individuals in the Pittsburgh Specialized Center of Clinically Oriented Research cohort. We found that cells containing this variant have decreased signaling in cellular pathways necessary for survival and proliferation.

CONCLUSIONS

PTPRO is a novel candidate gene in emphysema with severe airflow obstruction, and rs61754411 is a previously unreported rare variant contributing to emphysema susceptibility. Other suggestive candidate genes, such as ZNF816, are of interest for future studies.

Imaging approaches to understand disease complexity: chronic obstructive pulmonary disease as a clinical model

The clinical manifestations of chronic obstructive pulmonary disease (COPD) reflect an aggregate of multiple pulmonary and extrapulmonary processes. It is increasingly clear that full assessment of these processes is essential to characterize disease burden and to tailor therapy. Medical imaging has advanced such that it is now possible to obtain in vivo insight in the presence and severity of lung disease-associated features. In this review, we have assembled data from multiple disciplines of medical imaging research to review the role of imaging in characterization of COPD. Topics include imaging of the lungs, body composition, and extrapulmonary tissue metabolism. The primary focus is on imaging modalities that are widely available in clinical care settings and that potentially contribute to describing COPD heterogeneity and enhance our insight in underlying pathophysiological processes and their structural and functional effects.