Identification of factors directly linked to incident chronic obstructive pulmonary disease: A causal graph modeling study.

BACKGROUND: Beyond exposure to cigarette smoking and aging, the factors that influence lung function decline to incident chronic obstructive pulmonary disease (COPD) remain unclear. Advancements have been made in categorizing COPD into emphysema and airway predominant disease subtypes; however, predicting which healthy individuals will progress to COPD is difficult because they can exhibit profoundly different disease trajectories despite similar initial risk factors. This study aimed to identify clinical, genetic, and radiological features that are directly linked-and subsequently predict-abnormal lung function. METHODS AND FINDINGS: We employed graph modeling on 2,643 COPDGene participants (aged 45 to 80 years, 51.25% female, 35.1% African Americans; enrollment 11/2007-4/2011) with smoking history but normal spirometry at study enrollment to identify variables that are directly linked to future lung function abnormalities. We developed logistic regression and random forest predictive models for distinguishing individuals who maintain lung function from those who decline. Of the 131 variables analyzed, 6 were identified as informative to future lung function abnormalities, namely forced expiratory flow in the middle range (FEF25-75%), average lung wall thickness in a 10 mm radius (Pi10), severe emphysema, age, sex, and height. We investigated whether these features predict individuals leaving GOLD 0 status (normal spirometry according to Global Initiative for Obstructive Lung Disease (GOLD) criteria). Linear models, trained with these features, were quite predictive (area under receiver operator characteristic curve or AUROC = 0.75). Random forest predictors performed similarly to logistic regression (AUROC = 0.7), indicating that no significant nonlinear effects were present. The results were externally validated on 150 participants from Specialized Center for Clinically Oriented Research (SCCOR) cohort (aged 45 to 80 years, 52.7% female, 4.7% African Americans; enrollment: 7/2007-12/2012) (AUROC = 0.89). The main limitation of longitudinal studies with 5- and 10-year follow-up is the introduction of mortality bias that disproportionately affects the more severe cases. However, our study focused on spirometrically normal individuals, who have a lower mortality rate. Another limitation is the use of strict criteria to define spirometrically normal individuals, which was unavoidable when studying factors associated with changes in normalized forced expiratory volume in 1 s (FEV1%predicted) or the ratio of FEV1/FVC (forced vital capacity). CONCLUSIONS: This study took an agnostic approach to identify which baseline measurements differentiate and predict the early stages of lung function decline in individuals with previous smoking history. Our analysis suggests that emphysema affects obstruction onset, while airway predominant pathology may play a more important role in future FEV1 (%predicted) decline without obstruction, and FEF25-75% may affect both.

Incident low muscle mass is associated with greater lung disease and lower circulating leptin in a tobacco-exposed longitudinal cohort.

BACKGROUND: Muscle loss is prevalent in chronic obstructive pulmonary disease (COPD). Prior studies evaluating musculoskeletal dysfunction in COPD have focused on individuals with baseline low muscle mass. Currently, there is limited data evaluating clinical characteristics and outcomes associated with progression to incident low muscle mass in a tobacco-exposed cohort of individuals with baseline normal muscle mass. METHODS: We evaluated 246 participants from a single-center longitudinal tobacco-exposed cohort with serial spirometry, thoracic imaging, dual energy x-ray absorptiometry (DXA) measurements, walk testing, and plasma adipokine measurements. DXA-derived fat free mass index (FFMI) and appendicular skeletal mass index (ASMI) were used as surrogates for muscle mass. Participants with incident low muscle mass (LM) at follow-up were characterized by FFMI < 18.4 kg/m2 in males and < 15.4 kg/m2 in females and/or ASMI < 7.25 kg/m2 in males and < 5.67 kg/m2 in females. RESULTS: Twenty-five (10%) participants progressed to incident low muscle mass at follow-up. At baseline, the LM subgroup had greater active smoking prevalence (60% v. 38%, p = 0.04), lower FFMI (17.8 ± 1.7 kg/m2 v. 19.7 ± 2.9 kg/m2, p = 0.002), lower ASMI (7.3 ± 0.9 kg/m2 v. 8.2 ± 1.2 kg/m2, p = 0.0003), and lower plasma leptin (14.9 ± 10.1 ng/mL v. 24.0 ± 20.9 ng/mL, p = 0.04). At follow-up, the LM subgroup had higher COPD prevalence (68% v. 43%, p = 0.02), lower FEV1/FVC (0.63 ± 0.12 v. 0.69 ± 0.12, p = 0.02), lower %DLco (66.5 ± 15.9% v. 73.9 ± 16.8%, p = 0.03), and higher annual rate of FFMI decline (-0.17 kg/m2/year v. -0.04 kg/m2/year, p = 0.006). There were no differences in age, gender distribution, pack years smoking history, or walk distance. CONCLUSIONS: We identified a subgroup of tobacco-exposed individuals with normal baseline muscle mass who progressed to incident DXA-derived low muscle mass. This subgroup demonstrated synchronous lung disease and persistently low circulating leptin levels. Our study suggests the importance of assessing for muscle loss in conjunction with lung function decline when evaluating individuals with tobacco exposure.

Mixed graphical models for integrative causal analysis with application to chronic lung disease diagnosis and prognosis.

MOTIVATION: Integration of data from different modalities is a necessary step for multi-scale data analysis in many fields, including biomedical research and systems biology. Directed graphical models offer an attractive tool for this problem because they can represent both the complex, multivariate probability distributions and the causal pathways influencing the system. Graphical models learned from biomedical data can be used for classification, biomarker selection and functional analysis, while revealing the underlying network structure and thus allowing for arbitrary likelihood queries over the data. RESULTS: In this paper, we present and test new methods for finding directed graphs over mixed data types (continuous and discrete variables). We used this new algorithm, CausalMGM, to identify variables directly linked to disease diagnosis and progression in various multi-modal datasets, including clinical datasets from chronic obstructive pulmonary disease (COPD). COPD is the third leading cause of death and a major cause of disability and thus determining the factors that cause longitudinal lung function decline is very important. Applied on a COPD dataset, mixed graphical models were able to confirm and extend previously described causal effects and provide new insights on the factors that potentially affect the longitudinal lung function decline of COPD patients. AVAILABILITY AND IMPLEMENTATION: The CausalMGM package is available on http://www.causalmgm.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Loss of skin elasticity is associated with pulmonary emphysema, biomarkers of inflammation, and matrix metalloproteinase activity in smokers.

BACKGROUND: Elastin breakdown and the resultant loss of lung elastic recoil is a hallmark of pulmonary emphysema in susceptible individuals as a consequence of tobacco smoke exposure. Systemic alterations to the synthesis and degradation of elastin may be important to our understanding of disease phenotypes in chronic obstructive pulmonary disease. We investigated the association of skin elasticity with pulmonary emphysema, obstructive lung disease, and blood biomarkers of inflammation and tissue protease activity in tobacco-exposed individuals. METHODS: Two hundred and thirty-six Caucasian individuals were recruited into a sub-study of the University of Pittsburgh Specialized Center for Clinically Orientated Research in chronic obstructive pulmonary disease, a prospective cohort study of current and former smokers. The skin viscoelastic modulus (VE), a determinant of skin elasticity, was recorded from the volar forearm and facial wrinkling severity was determined using the Daniell scoring system. RESULTS: In a multiple regression analysis, reduced VE was significantly associated with cross-sectional measurement of airflow obstruction (FEV1/FVC) and emphysema quantified from computed tomography (CT) images, ß = 0.26, p = 0.001 and ß = 0.24, p = 0.001 respectively. In emphysema-susceptible individuals, elasticity-determined skin age was increased (median 4.6 years) compared to the chronological age of subjects without emphysema. Plasma biomarkers of inflammation (TNFR1, TNFR2, CRP, PTX3, and SAA) and matrix metalloproteinase activity (MMP1, TIMP1, TIMP2, and TIMP4) were inversely associated with skin elasticity. CONCLUSIONS: We report that an objective non-invasive determinant of skin elasticity is independently associated with measures of lung function, pulmonary emphysema, and biomarkers of inflammation and tissue proteolysis in tobacco-exposed individuals. Loss of skin elasticity is a novel observation that may link the common pathological processes that drive tissue elastolysis in the extracellular matrix of the skin and lung in emphysema-susceptible individuals.

Association of Systemic Inflammation with Depressive Symptoms in Individuals with COPD.

RATIONALE: Depression is a prevalent comorbidity of chronic obstructive pulmonary disease (COPD) that, along with COPD, has been associated with inflammation. An association between inflammation and depression in COPD has not been validated in a large COPD cohort. METHODS: Individuals from the University of Pittsburgh SCCOR cohort and the COPDGene cohort with tobacco use history and airway obstruction (FEV1/FVC <0.7) were evaluated using the Beck Depression Inventory II (BDI-II) and the Hospital Anxiety and Depression Scale (HADS), respectively. Participants completed symptom-related questionnaires and plasma IL-6 measurements. T-test, Fisher's Exact tests and logistic regression were used for statistical analysis. RESULTS: The SCCOR cohort included 220 obstructed participants: 44% female and 21.4% with elevated depressive symptoms. GOLD staging distribution was predominantly stage I and II. The COPDGene cohort included 745 obstructed participants: 44% female and 13.0% with elevated depressive symptoms. GOLD distribution was predominantly stage II and III. In the SCCOR cohort, correlation between IL-6 and depressive symptoms trended toward significance (p= 0.08). Multivariable modeling adjusted for FEV1, age, gender and medical comorbidities showed a significant association (OR = 1.70, 95% CI = 1.08-2.69). IL-6 was significantly associated with elevated depressive symptoms in COPDGene in both univariate (p=0.001) and multivariable modeling (OR = 1.52, 95% CI =1.13-2.04). CONCLUSION: Elevated plasma IL-6 levels are associated with depressive symptoms in individuals with COPD independent of airflow limitation and comorbid risk factors for depression. Our results suggest that systemic inflammation may play a significant and possibly bidirectional role in depression associated with COPD.