Serum Proteomic Profiling in Patients with Chronic Obstructive Pulmonary Disease

This study using data-independent acquisition analyses with PRM confirmation of findings identified 11 DEPs in the serum of patients with COPD. These DEPs are potential diagnostic or prognostic biomarkers or may be future targets for the treatment of COPD.

Serum samples were collected from 56 participants (COPD group n = 28; Healthy Control group n = 28). A data-independent acquisition quantitative proteomics approach was used to identify differentially expressed proteins (DEPs) between the two groups. Gene Ontology (GO) functional annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway functional enrichment, and protein-protein interaction analyses of DEPs were conducted to identify their relevant biological processes, cellular components, and related pathways. We used a parallel reaction monitoring (PRM)-based targeted quantitative proteomics approach to validate those findings.

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease with high morbidity and mortality rates. This study used proteomic profiling of serum to identify the differentially expressed proteins in COPD patients compared with healthy controls, to expand the knowledge of COPD pathogenesis and to ascertain potential new targets for diagnosis and treatment of COPD.

Of 8484 peptides identified by searching the UniProtKB/Swiss-Prot knowledgebase, 867 proteins were quantifiable, of which 20 were upregulated and 35 were downregulated in the COPD group. GO functional annotation indicated that the subcellular localization of most DEPs was extracellular. The top three molecular functions of the DEPs were signaling receptor binding, antigen binding, and immunoglobulin receptor binding. The most relevant biological process was immune response. The transforming growth factor-β signaling pathway, Staphylococcus aureus infection, and hematopoietic cell lineage were the top three pathways identified in the KEGG pathway functional enrichment. Our PRM analyses confirmed the identification of 11 DEPs identified in our data-independent acquisition analyses, 8 DEPs were upregulated and 3 DEPs were downregulated.