Identifying chronic obstructive pulmonary disease from integrative omics and clustering in lung tissue
Year: 2023
Type: article
Study design: Observational Study
Abstract: Background Chronic obstructive pulmonary disease (COPD) is a highly morbid and heterogenous disease. While COPD is defined by spirometry, many COPD characteristics are seen in cigarette smokers with normal spirometry. The extent to which COPD and COPD heterogeneity is captured in omics of lung tissue is not known. Methods We clustered gene expression and methylation data in 78 lung tissue samples from former smokers with normal lung function or severe COPD. We applied two integrative omics clustering methods: (1) Similarity Network Fusion (SNF) and (2) Entropy-Based Consensus Clustering (ECC). Results SNF clusters were not significantly different by the percentage of COPD cases (48.8% vs. 68.6%, p = 0.13), though were different according to median forced expiratory volume in one second (FEV 1 ) % predicted (82 vs. 31, p = 0.017). In contrast, the ECC clusters showed stronger evidence of separation by COPD case status (48.2% vs. 81.8%, p = 0.013) and similar stratification by median FEV 1 % predicted (82 vs. 30.5, p = 0.0059). ECC clusters using both gene expression and methylation were identical to the ECC clustering solution generated using methylation data alone. Both methods selected clusters with differentially expressed transcripts enriched for interleukin signaling and immunoregulatory interactions between lymphoid and non-lymphoid cells. Conclusions Unsupervised clustering analysis from integrated gene expression and methylation data in lung tissue resulted in clusters with modest concordance with COPD, though were enriched in pathways potentially contributing to COPD-related pathology and heterogeneity.
Source: BMC Pulmonary Medicine
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,790
Funders: Alpha-1 Foundation, AstraZeneca, Chiesi Farmaceutici, Regeneron Pharmaceuticals, Intuitive Surgical, Myriad Genetics, National Institutes of Health, Genentech, National Heart, Lung, and Blood Institute, National Human Genome Research Institute, National Cancer Institute, National Institute of Allergy and Infectious Diseases, National Institute of Biomedical Imaging and Bioengineering
Awards: Networks Tools to Understand Sex- and Gender-Specific Drivers of Disease, Epitranscriptomics of the aging lung, Identifying functional variants in COPD GWAS loci, Systems Biology of Airway Disease, Genetic and Functional Dissection of a Cluster of COPD GWAS Signals on Chromosome 4q, Lung Navigation System for Localizing and Resecting Nodules, G4844096456, Functional Redundancy of Human Microbiome and its Implication in Fecal Microbiota Transplantation, G5520316217, (2 of 2) Genetic Epidemiology of COPD, Multi-omic Subtyping of Chronic Obstructive Pulmonary Disease, G6127908160, Identifying Protein-Protein Network Interactions between COPD Susceptibility Genes, COPD SUBTYPES AND EARLY PREDICTION USING INTEGRATIVE PROBABILISTIC GRAPHICAL MODELS R01HL157879, Clinical Implications, Genomics, and Transcriptions of Mucus Plugging in Smokers, Integrative omics pipeline to identify novel COPD genes and pathways, G9000228787, COPD Susceptibility, Heterogeneity, and Progression: Proteomics and Genetics, Distinct and Overlapping Pathways of Fibrosis and Emphysema in Cigarette Smokers, Prospective Validation of Prognostic and Predictive Molecular tests in Mesothelioma
OpenAlex ID: W4364361705