Sean Jacobson

Dissecting childhood asthma with nasal transcriptomics distinguishes subphenotypes of disease

BACKGROUND Bronchial airway expression profiling has identified inflammatory subphenotypes of asthma, but the invasiveness of this technique has limited its application to childhood asthma. OBJECTIVES We sought to determine whether the nasal transcriptome can proxy expression changes in the lung airway transcriptome in asthmatic patients. We also sought to determine whether the nasal transcriptome can distinguish subphenotypes of asthma. METHODS Whole-transcriptome RNA sequencing was performed on nasal airway brushings from 10 control subjects and 10 asthmatic subjects, which were compared with established bronchial and small-airway transcriptomes. Targeted RNA sequencing nasal expression analysis was used to profile 105 genes in 50 asthmatic subjects and 50 control subjects for differential expression and clustering analyses. RESULTS We found 90.2% overlap in expressed genes and strong correlation in gene expression (ρ = .87) between the nasal and bronchial transcriptomes. Previously observed asthmatic bronchial differential expression was strongly correlated with asthmatic nasal differential expression (ρ = 0.77, P = 5.6 × 10(-9)). Clustering analysis identified TH2-high and TH2-low subjects differentiated by expression of 70 genes, including IL13, IL5, periostin (POSTN), calcium-activated chloride channel regulator 1 (CLCA1), and serpin peptidase inhibitor, clade B (SERPINB2). TH2-high subjects were more likely to have atopy (odds ratio, 10.3; P = 3.5 × 10(-6)), atopic asthma (odds ratio, 32.6; P = 6.9 × 10(-7)), high blood eosinophil counts (odds ratio, 9.1; P = 2.6 × 10(-6)), and rhinitis (odds ratio, 8.3; P = 4.1 × 10(-6)) compared with TH2-low subjects. Nasal IL13 expression levels were 3.9-fold higher in asthmatic participants who experienced an asthma exacerbation in the past year (P = .01). Several differentially expressed nasal genes were specific to asthma and independent of atopic status. CONCLUSION Nasal airway gene expression profiles largely recapitulate expression profiles in the lung airways. Nasal expression profiling can be used to identify subjects with IL13-driven asthma and a TH2-skewed systemic immune response.

Plasma sphingolipids associated with chronic obstructive pulmonary disease phenotypes

RATIONALE Chronic obstructive pulmonary disease (COPD) occurs in a minority of smokers and is characterized by intermittent exacerbations and clinical subphenotypes such as emphysema and chronic bronchitis. Although sphingolipids as a class are implicated in the pathogenesis of COPD, the particular sphingolipid species associated with COPD subphenotypes remain unknown. OBJECTIVES To use mass spectrometry to determine which plasma sphingolipids are associated with subphenotypes of COPD. METHODS One hundred twenty-nine current and former smokers from the COPDGene cohort had 69 distinct sphingolipid species detected in plasma by targeted mass spectrometry. Of these, 23 were also measured in 131 plasma samples (117 independent subjects) using an untargeted platform in an independent laboratory. Regression analysis with adjustment for clinical covariates, correction for false discovery rate, and metaanalysis were used to test associations between COPD subphenotypes and sphingolipids. Peripheral blood mononuclear cells were used to test associations between sphingolipid gene expression and plasma sphingolipids. MEASUREMENTS AND MAIN RESULTS Of the measured plasma sphingolipids, five sphingomyelins were associated with emphysema; four trihexosylceramides and three dihexosylceramides were associated with COPD exacerbations. Three sphingolipids were strongly associated with sphingolipid gene expression, and 15 sphingolipid gene/metabolite pairs were differentially regulated between COPD cases and control subjects. CONCLUSIONS There is evidence of systemic dysregulation of sphingolipid metabolism in patients with COPD. Subphenotyping suggests that sphingomyelins are strongly associated with emphysema and glycosphingolipids are associated with COPD exacerbations.

Biomarkers Predictive of Exacerbations in the SPIROMICS and COPDGene Cohorts.

Rationale: Chronic obstructive pulmonary disease exacerbations are associated with disease progression, higher healthcare cost, and increased mortality. Published predictors of future exacerbations include previous exacerbation, airflow obstruction, poor overall health, home oxygen use, and gastroesophageal reflux. Objectives: To determine the value of adding blood biomarkers to clinical variables to predict exacerbations. Methods: Subjects from the SPIROMICS (Subpopulations and Intermediate Outcomes Measures in COPD Study) (n = 1,544) and COPDGene (Genetic Epidemiology of COPD) (n = 602) cohorts had 90 plasma or serum candidate proteins measured on study entry using Myriad‐RBM multiplex panels. We defined total exacerbations as subject‐reported worsening in respiratory health requiring therapy with corticosteroids and/or antibiotics, and severe exacerbations as those leading to hospitalizations or emergency room visits. We assessed retrospective exacerbations during the 12 months before enrollment and then documented prospective exacerbations in each cohort. Exacerbations were modeled for biomarker associations with negative binomial regression including clinical covariates (age, sex, percent predicted FEV1, self‐reported gastroesophageal reflux, St. Georges Respiratory Questionnaire score, smoking status). We used the Stouffer‐Liptak test to combine P values for metaanalysis. Measurements and Main Results: Between the two cohorts, 3,471 total exacerbations (1,044 severe) were reported. We identified biomarkers within each cohort that were significantly associated with a history of exacerbation and with a future exacerbation, but there was minimal replication between the cohorts. Although established clinical features were predictive of exacerbations, of the blood biomarkers only decorin and &agr;2‐macroglobulin increased predictive value for future severe exacerbations. Conclusions: Blood biomarkers were significantly associated with the occurrence of exacerbations but were not robust between cohorts and added little to the predictive value of clinical covariates for exacerbations.

Gene and metabolite time-course response to cigarette smoking in mouse lung and plasma

Prolonged cigarette smoking (CS) causes chronic obstructive pulmonary disease (COPD), a prevalent serious condition that may persist or progress after smoking cessation. To provide insight into how CS triggers COPD, we investigated temporal patterns of lung transcriptome expression and systemic metabolome changes induced by chronic CS exposure and smoking cessation. Whole lung RNA-seq data was analyzed at transcript and exon levels from C57Bl/6 mice exposed to CS for 1- or 7 days, for 3-, 6-, or 9 months, or for 6 months followed by 3 months of cessation using age-matched littermate controls. We identified previously unreported dysregulation of pyrimidine metabolism and phosphatidylinositol signaling pathways and confirmed alterations in glutathione metabolism and circadian gene pathways. Almost all dysregulated pathways demonstrated reversibility upon smoking cessation, except the lysosome pathway. Chronic CS exposure was significantly linked with alterations in pathways encoding for energy, phagocytosis, and DNA repair and triggered differential expression of genes or exons previously unreported to associate with CS or COPD, including Lox, involved in matrix remodeling, Gp2, linked to goblet cells, and Slc22a12 and Agpat3, involved in purine and glycerolipid metabolism, respectively. CS-induced lung metabolic pathways changes were validated using metabolomic profiles of matched plasma samples, indicating that dynamic metabolic gene regulation caused by CS is reflected in the plasma metabolome. Using advanced technologies, our study uncovered novel pathways and genes altered by chronic CS exposure, including those involved in pyrimidine metabolism, phosphatidylinositol signaling and lysosome function, highlighting their potential importance in the pathogenesis or diagnosis of CS-associated conditions.

Multiple biomarkers predict disease severity, progression and mortality in COPD

BackgroundChronic obstructive pulmonary disease (COPD) is a heterogeneous disease characterized by multiple subtypes and variable disease progression. Blood biomarkers have been variably associated with subtype, severity, and disease progression. Just as combined clinical variables are more highly predictive of outcomes than individual clinical variables, we hypothesized that multiple biomarkers may be more informative than individual biomarkers to predict subtypes, disease severity, disease progression, and mortality.MethodsFibrinogen, C-Reactive Protein (CRP), surfactant protein D (SP-D), soluble Receptor for Advanced Glycation Endproducts (sRAGE), and Club Cell Secretory Protein (CC16) were measured in the plasma of 1465 subjects from the COPDGene cohort and 2746 subjects from the ECLIPSE cohort. Regression analysis was performed to determine whether these biomarkers, individually or in combination, were predictive of subtypes, disease severity, disease progression, or mortality, after adjustment for clinical covariates.ResultsIn COPDGene, the best combinations of biomarkers were: CC16, sRAGE, fibrinogen, CRP, and SP-D for airflow limitation (p < 10−4), SP-D, CRP, sRAGE and fibrinogen for emphysema (p < 10−3), CC16, fibrinogen, and sRAGE for decline in FEV1 (p < 0.05) and progression of emphysema (p < 10−3), and all five biomarkers together for mortality (p < 0.05). All associations except mortality were validated in ECLIPSE. The combination of SP-D, CRP, and fibrinogen was the best model for mortality in ECLIPSE (p < 0.05), and this combination was also significant in COPDGene.ConclusionThis comprehensive analysis of two large cohorts revealed that combinations of biomarkers improve predictive value compared with clinical variables and individual biomarkers for relevant cross-sectional and longitudinal COPD outcomes.

The R213G polymorphism in SOD3 protects against allergic airway inflammation

Oxidative stress is important in the pathogenesis of allergic asthma. Extracellular superoxide dismutase (EC-SOD; SOD3) is the major antioxidant in lungs, but its role in allergic asthma is unknown. Here we report that asthmatics have increased SOD3 transcript levels in sputum and that a single nucleotide polymorphism (SNP) in SOD3 (R213G; rs1799895) changes lung distribution of EC-SOD, and decreases likelihood of asthma-related symptoms. Knockin mice analogous to the human R213G SNP had lower airway hyperresponsiveness, inflammation, and mucus hypersecretion with decreased interleukin-33 (IL-33) in bronchoalveolar lavage fluid and reduced type II innate lymphoid cells (ILC2s) in lungs. SOD mimetic (Mn (III) tetrakis (N-ethylpyridinium-2-yl) porphyrin) attenuated Alternaria-induced expression of IL-33 and IL-8 release in BEAS-2B cells. These results suggest that R213G SNP potentially benefits its carriers by resulting in high EC-SOD in airway-lining fluid, which ameliorates allergic airway inflammation by dampening the innate immune response, including IL-33/ST2-mediated changes in ILC2s.

Features of COPD as Predictors of Lung Cancer

Background: Lung cancer is a leading cause of death and hospitalization for patients with COPD. A detailed understanding of which clinical features of COPD increase risk is needed. Methods: We performed a nested case‐control study of Genetic Epidemiology of COPD (COPDGene) Study subjects with and without lung cancer, age 45 to 80 years, who smoked at least 10‐pack years to identify clinical and imaging features of smokers, with and without COPD, that are associated with an increased risk of lung cancer. The baseline evaluation included spirometry, high‐resolution chest CT scanning, and respiratory questionnaires. New lung cancer diagnoses were identified over 8 years of longitudinal follow‐up. Cases of lung cancer were matched 1:4 with control subjects for age, race, sex, and smoking history. Multiple logistic regression analyses were used to determine features predictive of lung cancer. Results: Features associated with a future risk of lung cancer included decreased FEV1/FVC (OR, 1.28 per 10% decrease [95% CI, 1.12–1.46]), visual severity of emphysema (OR, 2.31, none‐trace vs mild‐advanced [95% CI, 1.41–3.86]), and respiratory exacerbations prior to study entry (OR, 1.39 per increased events [0, 1, and ≥ 2] [95% CI, 1.04–1.85]). Respiratory exacerbations were also associated with small‐cell lung cancer histology (OR, 3.57 [95% CI, 1.47–10]). Conclusions: The degree of COPD severity, including airflow obstruction, visual emphysema, and respiratory exacerbations, was independently predictive of lung cancer. These risk factors should be further studied as inclusion and exclusion criteria for the survival benefit of lung cancer screening. Studies are needed to determine if reduction in respiratory exacerbations among smokers can reduce the risk of lung cancer.

Metabolomic similarities between bronchoalveolar lavage fluid and plasma in humans and mice

This observational study catalogues the overlap in metabolites between matched bronchoalveolar lavage fluid (BALF) and plasma, identifies the degree of congruence between these metabolomes in human and mouse, and determines how molecules may change in response to cigarette smoke (CS) exposure. Matched BALF and plasma was collected from mice (ambient air or CS-exposed) and humans (current or former smokers), and analyzed using mass spectrometry. There were 1155 compounds in common in all 4 sample types; fatty acyls and glycerophospholipids strongly overlapped between groups. In humans and mice, more than half of the metabolites present in BALF were also present in plasma. Mouse BALF and human BALF had a strong positive correlation with 2040 metabolites in common, suggesting that mouse models can be used to interrogate human lung metabolome changes. While power was affected by small sample size in the mouse study, the BALF metabolome appeared to be more affected by CS than plasma. CS-exposed mice showed increased plasma and BALF glycerolipids and glycerophospholipids. This is the first report cataloguing the metabolites present across mouse and human, BALF and plasma. Findings are relevant to translational studies where mouse models are used to examine human disease, and where plasma may be interrogated in lieu of BALF or lung tissue.

Original Research Marijuana Use Associations with Pulmonary Symptoms and Function in Tobacco Smokers Enrolled in The Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS)

Background: Marijuana is often smoked via a filterless cigarette and contains similar chemical makeup as smoked tobacco. There are few publications describing usage patterns and respiratory risks in older adults or in those with chronic obstructive pulmonary disease (COPD). Methods: A cross-sectional analysis of current and former tobacco smokers from the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS) study assessed associations between marijuana use and pulmonary outcomes. Marijuana use was defined as never, former (use over 30 days ago), or current (use within 30 days). Respiratory health was assessed using quantitative high-resolution computed tomography (HRCT) scans, pulmonary function tests and questionnaire responses about respiratory symptoms. Results: Of the total 2304 participants, 1130 (49%) never, 982 (43%) former, and 192 (8%) current marijuana users were included. Neither current nor former marijuana use was associated with increased odds of wheeze (odds ratio [OR] 0.87, OR 0.97), cough (OR 1.22; OR 0.93) or chronic bronchitis (OR 0.87; OR 1.00) when compared to never users. Current and former marijuana users had lower quantitative emphysema (P=0.004, P=0.03), higher percent predicted forced expiratory volume in 1 second (FEV1%) (P<0.001, P<0.001), and percent predicted forced vital capacity (FVC%) (p<0.001, P<0.001). Current marijuana users exhibited higher total tissue volume (P=0.003) while former users had higher air trapping (P<0.001) when compared to never marijuana users. Conclusions: Marijuana use was found to have little to no association with poor pulmonary health in older current and former tobacco smokers after adjusting for covariates. Higher forced expiratory volume in 1 second (FEV1) and forced vital capacity (FVC) was observed among current marijuana users. However, higher joint years was associated with more chronic bronchitis symptoms (e.g., wheeze), and this study cannot determine if long-term heavy marijuana smoking in the absence of tobacco smoking is associated with lung symptoms, airflow obstruction, or emphysema, particularly in those who have never smoked tobacco cigarettes.

Meta-analysis of peripheral blood gene expression modules for COPD phenotypes

Chronic obstructive pulmonary disease (COPD) occurs typically in current or former smokers, but only a minority of people with smoking history develops the disease. Besides environmental factors, genetics is an important risk factor for COPD. However, the relationship between genetics, environment and phenotypes is not well understood. Sample sizes for genome-wide expression studies based on lung tissue have been small due to the invasive nature of sample collection. Increasing evidence for the systemic nature of the disease makes blood a good alternative source to study the disease, but there have also been few large-scale blood genomic studies in COPD. Due to the complexity and heterogeneity of COPD, examining groups of interacting genes may have more relevance than identifying individual genes. Therefore, we used Weighted Gene Co-expression Network Analysis to find groups of genes (modules) that are highly connected. However, module definitions may vary between individual data sets. To alleviate this problem, we used a consensus module definition based on two cohorts, COPDGene and ECLIPSE. We studied the relationship between the consensus modules and COPD phenotypes airflow obstruction and emphysema. We also used these consensus module definitions on an independent cohort (TESRA) and performed a meta analysis involving all data sets. We found several modules that are associated with COPD phenotypes, are enriched in functional categories and are overrepresented for cell-type specific genes. Of the 14 consensus modules, three were strongly associated with airflow obstruction (meta p ≤ 0.0002), and two had some association with emphysema (meta p ≤ 0.06); some associations were stronger in the case-control cohorts, and others in the cases-only subcohorts. Gene Ontology terms that were overrepresented included “immune response” and “defense response.” The cell types whose type-specific genes were overrepresented in modules (p < 0.05) included natural killer cells, dendritic cells, and neutrophils. Together, this is the largest investigation of gene blood expression in COPD with 469 cases in COPDGene, ECLIPSE and TESRA combined, with 6267 genes common to all data sets. Additional, we have 42 and 83 controls in COPDGene and ECLIPSE, respectively.