Molecular Determinants of Lung Function Decline: A Multi- Level Analysis of Gene Expression.

Background: Chronic obstructive pulmonary disease (COPD) is characterized by progressive lung function decline, commonly measured by forced expiratory volume in one second (FEV). Uncovering the genetic basis of FEV decline is essential for understanding COPD pathophysiology and for developing therapies. We hypothesized that gene expression patterns in inflammatory pathways are associated with FEV decline.

Overlap between COPD genetic association results and transcriptional quantitative trait loci.

Genome-wide association studies (GWAS) have identified multiple genetic loci associated with chronic obstructive pulmonary disease (COPD). Here, we identify SNPs that are associated with alternative splicing (sQTL) and gene expression (eQTLs) to identify functions for COPD associated genetic variants. RNA sequencing on whole blood from 3743 subjects in the COPDGene Study and from lung tissue of 1241 subjects from the Lung Tissue Research Consortium (LTRC) was analyzed.

miRNA-mRNA network analysis identifies PAX5 as a potential regulator of adaptive immune response in COPD.

Micro-ribonucleic acids (miRNAs) are key post-transcriptional regulators of the immune system and may play a role in Chronic Obstructive Pulmonary Disease (COPD). In this paper, we constructed subject-specific miRNA-mRNA regulatory networks using bulk and deconvoluted whole blood RNA-sequencing, whole blood miRNA-sequencing, and B-cell receptor-sequencing data from up to 570 miRNAs, 11,859 mRNAs, and 3,190 participants in the COPDGene study. Analysis of whole blood networks revealed two subnetworks of miRNA-mRNA interactions significantly (FDR<0.

Proteomic biomarkers of emphysema-predominant and non-emphysema-predominant chronic obstructive pulmonary disease.

Background: Chronic Obstructive Pulmonary Disease (COPD) is a complex and heterogeneous disease. Emphysema-predominant and non-emphysema predominant COPD are two major disease subtypes capturing important aspects of COPD heterogeneity. Molecular differences between these COPD subtypes are unknown.

Omic Risk Scores are Associated with COPD-related Traits Across Three Cohorts.

Background: Chronic obstructive pulmonary disease (COPD) exhibits marked heterogeneity in lung function decline, mortality, exacerbations, and other disease-related outcomes. Omic risk scores (ORS) estimate the cumulative contribution of omics, such as the transcriptome, proteome, and metabolome, to a particular trait. This study evaluates the predictive value of ORS for COPD-related traits in both smoking-enriched and general population cohorts.

Respiratory Exacerbations Increase with Chronic PM Exposure in Current and Former Smokers.

Rationale: Short-term exposure to fine particulates (PM) transiently increases the risk of respiratory exacerbations, but the contribution of chronic, long-term particulate exposure to respiratory exacerbations is poorly defined.

Objectives: To assess long-term effects of PM exposure on risk of severe respiratory exacerbations.

Methods: A longitudinal cohort of current and former smokers with and without COPD were surveyed every six months for severe exacerbation events.

B-cell immune repertoire sequencing in tobacco cigarette smoking, vaping, and chronic obstructive pulmonary disease in the COPDGene cohort.

Rationale: Cigarette smoking (CS) impairs B-cell function and antibody production, increasing infection risk. The impact of e-cigarette use ('vaping') and combined CS and vaping ('dual-use') on B-cell activity is unclear.

Objective: To examine B-cell receptor sequencing (BCR-seq) profiles associated with CS, vaping, and dual-use.

Extensions of Heterogeneity in Integration and Prediction (HIP) With R Shiny Application.

Multiple data views measured on the same set of participants are becoming more common and have the potential to deepen our understanding of many complex diseases by analyzing these different views simultaneously. Equally important, many of these complex diseases show evidence of subgroup heterogeneity (e.g.

Airway Spatial Transcriptomics in Smoking.

Background: Cigarette smoking has a significant impact on global health. Although cessation has positive health benefits, some molecular changes to intercellular communications may persist in the lung. In this study we created a framework to generate hypotheses by predicting altered cell-cell communication in smoker lungs using single-cell and spatial transcriptomic data.

A generalized higher-order correlation analysis framework for multi-omics network inference.

Multiple -omics (genomics, proteomics, etc.) profiles are commonly generated to gain insight into a disease or physiological system. Constructing multi-omics networks with respect to the trait(s) of interest provides an opportunity to understand relationships between molecular features but integration is challenging due to multiple data sets with high dimensionality.

LungGENIE: the lung gene-expression and network imputation engine.

Background: Few cohorts have study populations large enough to conduct molecular analysis of ex vivo lung tissue for genomic analyses. Transcriptome imputation is a non-invasive alternative with many potential applications. We present a novel transcriptome-imputation method called the Lung Gene Expression and Network Imputation Engine (LungGENIE) that uses principal components from blood gene-expression levels in a linear regression model to predict lung tissue-specific gene-expression.

Cross-cohort analysis of expression and splicing quantitative trait loci in TOPMed.

Most genetic variants associated with complex traits and diseases occur in non-coding genomic regions and are hypothesized to regulate gene expression. To understand the genetics underlying gene expression variability, we characterize 14,324 ancestrally diverse RNA-sequencing samples from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and integrate whole genome sequencing data to perform and expression and splicing quantitative trait locus (-/trans-e/sQTL) analyses in six tissues and cell types, most notably whole blood (N=6,454) and lung (N=1,291). We show this dataset enables greater detection of secondary cis-e/sQTL signals than was achieved in previous studies, and that secondary cis-eQTL and primary trans-eQTL signal discovery is not saturated even though eGene discovery is.

Characterisation of a COPD-associated nephronectin () functional splicing genetic variant in human lung tissue long-read sequencing.

Background: Identification of COPD disease-causing genes is an important tool for understanding why COPD develops, who is at highest COPD risk and how new COPD treatments can be developed. Previous COPD genetic studies have identified a highly significant genetic association near (nephronectin), a gene involved in tissue repair, but the biological mechanisms underlying this association are unknown.

Methods: Splicing quantitative trait locus (sQTL) analysis was performed to identify common genetic variants that alter RNA splicing in lung tissues.

Vitamin D Supplementation, Chronic Obstructive Lung Disease and Asthma Exacerbations, and Lung Function Decline.

Background: It remains unclear whether supplementation with vitamin D reduces risk of acute exacerbations of chronic obstructive lung disease (COPD) or asthma, major contributors to the world-wide burden of disease.

Objectives: To compare effects of vitamin D with placebo supplementation for the prespecified primary endpoints 1) acute exacerbations of COPD and 2) decline in pulmonary function measures of airflow obstruction. Prespecified secondary endpoints included asthma exacerbations and control.

Peripheral blood miRNAs are associated with airflow below threshold in children with asthma.

Background: MicroRNAs (miRNAs) are crucial post-transcriptional regulators involved in inflammatory diseases, such as asthma. Poor lung function and airflow issues in childhood are linked to the development of chronic obstructive pulmonary disease (COPD) in adulthood.

Methods: We analyzed small RNA-Seq data from 365 peripheral whole blood samples from the Genetics of Asthma in Costa Rica Study (GACRS) for association with airflow levels measured by FEV1/FVC.

Computational deconvolution of cell type-specific gene expression in COPD and IPF lungs reveals disease severity associations.

Background: Chronic obstructive pulmonary disease (COPD) and idiopathic pulmonary fibrosis (IPF) are debilitating diseases associated with divergent histopathological changes in the lungs. At present, due to cost and technical limitations, profiling cell types is not practical in large epidemiology cohorts (n > 1000). Here, we used computational deconvolution to identify cell types in COPD and IPF lungs whose abundances and cell type-specific gene expression are associated with disease diagnosis and severity.

Distinct physiological, transcriptomic, and imaging characteristics of asthma-COPD overlap compared to asthma and COPD in smokers.

Background: The clinical and pathological features of asthma and chronic obstructive pulmonary disease (COPD) can converge in smokers and elderly individuals as asthma-COPD overlap (ACO). This overlap challenges the diagnosis and treatment of the distinct aetiologies underlying these conditions.

Methods: We analysed 2453 smokers (≥10 pack-years), aged 45-80 years, from the Genetic Epidemiology of COPD (COPDGene) Study, stratified as Control, Asthma, COPD, and ACO based on Global Initiative for Chronic Obstructive Lung Disease (GOLD) criteria.

Polygenic and transcriptional risk scores identify chronic obstructive pulmonary disease subtypes in the COPDGene and ECLIPSE cohort studies.

Background: Genetic variants and gene expression predict risk of chronic obstructive pulmonary disease (COPD), but their effect on COPD heterogeneity is unclear. We aimed to define high-risk COPD subtypes using genetics (polygenic risk score, PRS) and blood gene expression (transcriptional risk score, TRS) and assess differences in clinical and molecular characteristics.

Methods: We defined high-risk groups based on PRS and TRS quantiles by maximising differences in protein biomarkers in a COPDGene training set and identified these groups in COPDGene and ECLIPSE test sets.

Partial correlation network analysis identifies coordinated gene expression within a regional cluster of COPD genome-wide association signals.

Chronic obstructive pulmonary disease (COPD) is a complex disease influenced by well-established environmental exposures (most notably, cigarette smoking) and incompletely defined genetic factors. The chromosome 4q region harbors multiple genetic risk loci for COPD, including signals near HHIP, FAM13A, GSTCD, TET2, and BTC. Leveraging RNA-Seq data from lung tissue in COPD cases and controls, we estimated the co-expression network for genes in the 4q region bounded by HHIP and BTC (~70MB), through partial correlations informed by protein-protein interactions.

B cell immune repertoire sequencing in tobacco cigarette smoking, vaping, and chronic obstructive pulmonary disease in the COPDGene cohort.

Rationale: Cigarette smoking (CS) impairs B cell function and antibody production, increasing infection risk. The impact of e-cigarette use ('vaping') and combined CS and vaping ('dual-use') on B cell activity is unclear.

Objective: To examine B cell receptor sequencing (BCR-seq) profiles associated with CS, vaping, dual-use, COPD-related outcomes, and demographic factors.

Development and validation of a mortality risk prediction model for chronic obstructive pulmonary disease: a cross-sectional study using probabilistic graphical modelling.

Background: Chronic Obstructive Pulmonary Disease (COPD) is a leading cause of mortality. Predicting mortality risk in patients with COPD can be important for disease management strategies. Although all-cause mortality predictors have been developed previously, limited research exists on factors directly affecting COPD-specific mortality.