Exposure to cigarette smoking can increase the risk of cancers and cardiovascular and pulmonary diseases. However, the underlying mechanisms of how smoking contributes to disease risks are not completely understood. Epigenome-wide association studies (EWASs), mostly in non-Asian populations, have been conducted to identify smoking-associated methylation alterations at individual probes. There are few data on regional methylation changes in relation to smoking. Few data link differential methylation in blood to differential gene expression in lung tissue. We identified 108 significant (false discovery rate (FDR) < 0.05) differentially methylated probes (DMPs) and 87 significant differentially methylated regions (DMRs) (multiple-testing corrected p < 0.01) in current compared to never smokers from our EWAS of cotinine-validated smoking in blood DNA from a Korean chronic obstructive pulmonary disease cohort (n = 100 including 31 current, 30 former, and 39 never smokers) using Illumina HumanMethylation450 BeadChip. Of the 108 DMPs (FDR < 0.05), nine CpGs were statistically significant based on Bonferroni correction and 93 were novel including five that mapped to loci previously associated with smoking. Of the 87 DMRs, 66 were mapped to novel loci. Methylation correlated with urine cotinine levels in current smokers at six DMPs, with pack-years in current smokers at six DMPs, and with duration of smoking cessation in former smokers at eight DMPs. Of the 143 genes to which our significant DMPs or DMRs annotated, gene expression levels at 20 genes were associated with pack-years in lung tissue transcriptome data of smokers (Asan Biobank, n = 188). Our study of differential methylation in Koreans confirmed previous findings from non-Asian populations and revealed novel loci in relation to smoking. Smoking-related differential methylation in blood is associated with gene expression in lung tissue, an important target of adverse health effects of smoking, supporting the potential functional importance of methylation in smoking-related disease.

Background: High blood eosinophil count is a predictive biomarker for response to inhaled corticosteroids in prevention of acute exacerbation of COPD, and low blood eosinophil count is associated with pneumonia risk in COPD patients taking inhaled corticosteroids. However, the prognostic role of blood eosinophil count remains underexplored. Therefore, we investigated the associated factors and mortality based on blood eosinophil count in COPD. Methods: Patients with COPD were recruited from 16 hospitals of the Korean Obstructive Lung Disease cohort (n=395) and COPD in Dusty Area cohort (n=234) of Kangwon University Hospital. The two merged cohorts were divided based on blood eosinophil count into three groups: high (≥5%), middle (2%–5%), and low (<2%). Results: The high group had longer six-minute walk distance (high =445.8±81.4, middle =428.5±88.0, and low =414.7±86.3 m), higher body mass index (23.3±3.1, 23.1±3.1, and 22.5±3.2 kg/m²), lower emphysema index (18.5±14.1, 22.2±15.3, and 23.7±16.3), and higher inspiratory capacity/total lung capacity ratio (32.6±7.4, 32.4±9.2, and 29.9% ± 8.9%) (P<0.05). The survival period increased with increasing blood eosinophil count (high =9.52±0.23, middle =8.47±1.94, and low =7.42±0.27 years, P<0.05). Multivariate linear regression analysis revealed that the emphysema index was independently and negatively correlated with blood eosinophil count (P<0.05). Conclusion: In COPD, the severity of emphysema was independently linked with low blood eosinophil count and the longer survival period was associated with increased blood eosinophil count, though it was not proven in the multivariate analysis.

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease with variable clinical manifestations, structural changes, and treatment responses. In a cohort study, we performed a baseline cluster analysis to identify the subgroups of COPD and to assess the clinical outcomes of each subgroup during a 1-year follow-up. We analyzed dusty areas cohort comprising 272 patients with COPD. The main factors with the highest loading in 15 variables were selected using principal component analysis (PCA) at baseline. The COPD patients were classified by hierarchical cluster analysis using clinical, physiological, and imaging data based on PCA-transformed data. The clinical parameters and outcomes during the 1-year follow-up were evaluated among the subgroups. PCA revealed that six independent components accounted for 77.3% of variance. Three distinct subgroups were identified through the cluster analysis. Subgroup 1 included younger subjects with fewer symptoms and mild airflow obstruction, and they had fewer exacerbations during the 1-year follow-up. Subgroup 2 comprised subjects with additional symptoms and moderate airflow obstruction, and they most frequently experienced exacerbations requiring hospitalization during the 1-year follow-up. Subgroup 3 included subjects with additional symptoms and mild airflow obstruction; this group had more female patients and a modest frequency of exacerbations requiring hospitalization. Cluster analysis using the baseline data of a COPD cohort identified three distinct subgroups with different clinical parameters and outcomes. These findings suggest that the identified subgroups represent clinically meaningful subtypes of COPD.

Human pluripotent stem cell (hPSC)-derived alveolar epithelial cells (AECs) provide new opportunities for understanding lung development and the treatment of pulmonary diseases. However, toxicity assessments using hPSC-AECs have not been undertaken. In this study, we generated functional AECs from hPSCs and evaluated their inflammatory and apoptotic responses to cadmium (Cd) exposure (1, 5, and 10 μM) for 24 h compared with the human bronchial epithelial cell line (BEAS-2B) and primary AECs as controls. Our data showed that Cd (10 μM) treatment induced substantial inflammatory responses and apoptosis in BEAS-2B cells, but not in both hPSC-AECs and primary AECs. Interestingly, conditioned medium from AEC cultures significantly alleviated apoptotic and inflammatory responses to Cd exposure in BEAS-2B cells. Using cytokine arrays, several potential factors secreted from hPSC-AECs and primary AECs were detected and may be involved in reducing Cd-induced cytotoxicity. We also observed higher expression of surfactant proteins B and C in both hPSC-AECs and primary AECs, which may contribute to protection against Cd-induced cytotoxicity. These results suggested that hPSC-AECs phenotypically and functionally resemble primary AECs and could be more biologically relevant alternatives for evaluating the pathological contribution of confirmed or potential pulmotoxic materials included in smoking and microdust.

Background: Recent advances in critical care and infection control have led to improved intensive care unit (ICU) survival rates. However, controversy exists regarding the benefits of ICU treatment for patients with lung cancer. In this study, we evaluated the clinical outcomes of patients from the Korean national database, who had been diagnosed with lung cancer and had received ICU treatment. Methods: We investigated patients in Korea who had been newly diagnosed with lung cancer between January 1, 2008 and December 31, 2010. We classified these critically ill patients with lung cancer according to their lung cancer treatment pathways, with a specific focus on those who had undergone ICU treatment. Results: We found that 31.3% of patients newly diagnosed with lung cancer had been admitted to the ICU for any reason, and 18.5% of patients with lung cancer were admitted to the ICU for reasons other than postoperative surgical lung cancer resection. The ICU mortality rate was 2.9% in patients admitted to the ICU for postoperative care and 47.5% in patients admitted for other reasons. Clinical cancer staging (HR, 7.02; 95% CI, 5.82–8.48; P<0.01) and the need for mechanical ventilator (HR, 1.34; 95% CI, 1.27–1.41; P<0.01) were independently associated with ICU mortality. The importance of mechanical ventilator intervention as a predictor for survival was significantly greater in the earlier stages of lung cancer (HR, 1.97; 95% CI, 1.15–3.38; P<0.01). Conclusions: This study suggests that goals and treatment plans for critically ill patients with lung cancer should be determined by the individual patient’s clinical cancer stage, regardless of the reason for admission to the ICU.