COPD is Associated with Epigenome-wide Differential Methylation in BAL Lung Cells

Lung Function Trajectories and Associated Mortality among Adults with and without Airway Obstruction

Rationale: Spirometry is essential for diagnosis and assessment of prognosis in patients with chronic obstructive pulmonary disease (COPD). Objectives: To identify FEV1 trajectories and their determinants on the basis of annual spirometry measurements among individuals with and without airway obstruction (AO) and to assess mortality in relation to trajectories. Methods: From 2002 through 2004, individuals with AO (FEV1/VC < 0.70, n = 993) and age- and sex-matched nonobstructive (NO) referents were recruited from population-based cohorts. Annual spirometry until 2014 was used in joint-survival latent-class mixed models to identify lung function trajectories. Mortality data were collected during 15 years of follow-up. Measurements and Main Results: Three trajectories were identified among the subjects with AO and two among the NO referents. Trajectory membership was driven by baseline FEV1% predicted (FEV1%pred) in both groups and also by pack-years in subjects with AO and current smoking in NO referents. Longitudinal FEV1%pred depended on baseline FEV1%pred, pack-years, and obesity. The trajectories were distributed as follows: among individuals with AO, 79.6% in AO trajectory 1 (FEV1 high with normal decline), 12.8% in AO trajectory 2 (FEV1 high with rapid decline), and 7.7% in AO trajectory 3 (FEV1 low with normal decline) (mean, 27, 72, and 26 ml/yr, respectively) and, among NO referents, 96.7% in NO trajectory 1 (FEV1 high with normal decline) and 3.3% in NO trajectory 2 (FEV1 high with rapid decline) (mean, 34 and 173 ml/yr, respectively). Hazard for death was increased for AO trajectories 2 (hazard ratio [HR], 1.56) and 3 (HR, 3.45) versus AO trajectory 1 and for NO trajectory 2 (HR, 2.99) versus NO trajectory 1. Conclusions: Three different FEV1 trajectories were identified among subjects with AO and two among NO referents, with different outcomes in terms of FEV1 decline and mortality. The FEV1 trajectories among subjects with AO and the relationship between low FVC and trajectory outcome are of particular clinical interest.

Precision medicine in complex diseases-Molecular subgrouping for improved prediction and treatment stratification

Complex diseases are caused by a combination of genetic, lifestyle, and environmental factors and comprise common noncommunicable diseases, including allergies, cardiovascular disease, and psychiatric and metabolic disorders. More than 25% of Europeans suffer from a complex disease, and together these diseases account for 70% of all deaths. The use of genomic, molecular, or imaging data to develop accurate diagnostic tools for treatment recommendations and preventive strategies, and for disease prognosis and prediction, is an important step toward precision medicine. However, for complex diseases, precision medicine is associated with several challenges. There is a significant heterogeneity between patients of a specific disease-both with regards to symptoms and underlying causal mechanisms-and the number of underlying genetic and nongenetic risk factors is often high. Here, we summarize precision medicine approaches for complex diseases and highlight the current breakthroughs as well as the challenges. We conclude that genomic-based precision medicine has been used mainly for patients with highly penetrant monogenic disease forms, such as cardiomyopathies. However, for most complex diseases-including psychiatric disorders and allergies-available polygenic risk scores are more probabilistic than deterministic and have not yet been validated for clinical utility. However, subclassifying patients of a specific disease into discrete homogenous subtypes based on molecular or phenotypic data is a promising strategy for improving diagnosis, prediction, treatment, prevention, and prognosis. The availability of high-throughput molecular technologies, together with large collections of health data and novel data-driven approaches, offers promise toward improved individual health through precision medicine.

Modulation of innate immunity in airway epithelium for host-directed therapy

Innate immunity of the mucosal surfaces provides the first-line defense from invading pathogens and pollutants conferring protection from the external environment. Innate immune system of the airway epithelium consists of several components including the mucus layer, mucociliary clearance of beating cilia, production of host defense peptides, epithelial barrier integrity provided by tight and adherens junctions, pathogen recognition receptors, receptors for chemokines and cytokines, production of reactive oxygen species, and autophagy. Therefore, multiple components interplay with each other for efficient protection from pathogens that still can subvert host innate immune defenses. Hence, the modulation of innate immune responses with different inducers to boost host endogenous front-line defenses in the lung epithelium to fend off pathogens and to enhance epithelial innate immune responses in the immunocompromised individuals is of interest for host-directed therapy. Herein, we reviewed possibilities of modulation innate immune responses in the airway epithelium for host-directed therapy presenting an alternative approach to standard antibiotics.

Short-term exposure to fine particulate matter and genome-wide DNA methylation in chronic obstructive pulmonary disease: A panel study conducted in Beijing, China

Background

Fine particulate matter (PM2.5) is a crucial risk factor for chronic obstructive pulmonary disease (COPD). However, the mechanisms whereby PM2.5 contribute to COPD risk have not been fully elucidated. Accumulating evidence suggests that epigenetics, including DNA methylation, play an important role in this process; however, the association between PM2.5 exposure and genome-wide DNA methylation in patients with COPD has not been studied.

Objective

To evaluate the association of personal exposure to PM2.5 and genome-wide DNA methylation changes in the peripheral blood of patients with COPD.

Methods

A panel study was conducted in Beijing, China. We repeatedly measured and collected personal PM2.5 data for 72 h. Genome-wide DNA-methylation of peripheral blood was analyzed using the Illumina Infinium Human Methylation BeadChip (850 k). A linear-mixed effect model was used to identify the differentially methylated probe (DMP) associated with PM2.5. Finally, we performed a functional enrichment analysis of the DMPs that were significantly associated with PM2.5.

Results

A total of 24 COPD patients were enrolled and 48 repeated DNA methylation measurements were associated in this study. When the false discovery rate was < 0.05, 19 DMPs were significantly associated with PM2.5 and were annotated to corresponding genes. Functional enrichment analysis of these genes showed that they were related to the response to toxic substances, regulation of tumor necrosis factor superfamily cytokine production, regulation of photosensitivity 3-kinase signaling, and other pathways.

Conclusion

This study provided evidence for a significant relationship between personal PM2.5 exposure and DNA methylation in patients with COPD. Our research also revealed a new biological pathway explaining the adverse effects of PM2.5 exposure on COPD risk.