Jul 2026· Journal of Proteomics· Vol 331, pp.
105706
· 0 citations
Medicine
TL;DR
The findings reveal coordinated dysregulation of mitochondrial energy metabolism, redox homeostasis, and lipid remodeling in COPD, highlighting the interconnected roles of metabolic reprogramming, oxidative stress, and inflammation in disease pathophysiology.
Abstract
Chronic obstructive pulmonary disease (COPD) is a respiratory disorder characterized by chronic inflammation, oxidative stress, and metabolic dysregulation. The lack of convenient and easily-accessible non-invasive diagnostic approaches remains a major clinical challenge. This study applied an integrated saliva-based proteomic and untargeted metabolomic strategy to identify potential biomarkers for COPD classification. Comprehensive multi-omics analyses identified 225 differentially abundant proteins and 60 differentially abundant metabolites between patients with COPD and healthy controls, including 24 biologically relevant endogenous metabolites. Functional enrichment analyses revealed pronounced dysregulation of mitochondrial energy metabolism, redox homeostasis, lipid remodeling, and inflammatory-related pathways in COPD. By integrating salivary proteomic and metabolomic biomarkers, a stepwise feature selection combined with LASSO logistic regression was used to construct diagnostic models, yielding an optimized biomarker panel consisting of 11 proteins and 2 endogenous metabolites. This integrated model achieved excellent diagnostic performance, with an area under the ROC curve of 0.96. Collectively, these findings demonstrate that integrated salivary proteomic and metabolomic profiling provides a robust, non-invasive approach for COPD classification and offers a promising foundation for the development of biosensor-based diagnostic platforms and early disease detection. SIGNIFICANCE: Chronic obstructive pulmonary disease (COPD) remains a major global health burden. Current diagnostic approaches rely largely on spirometry and clinical assessment, which are limited in sensitivity for early-stage disease and unsuitable for large-scale screening. This study employs an integrated saliva-based proteomic and metabolomic strategy to identify non-invasive biomarkers for COPD classification. Our findings reveal coordinated dysregulation of mitochondrial energy metabolism, redox homeostasis, and lipid remodeling in COPD, highlighting the interconnected roles of metabolic reprogramming, oxidative stress, and inflammation in disease pathophysiology. Notably, a robust diagnostic panel comprising 11 proteins and 2 endogenous metabolites was established, achieving excellent classification performance (AUC of 0.96). To our knowledge, the integrated application of salivary proteomics and metabolomics for COPD diagnosis remains largely unexplored, underscoring the significance and translational potential of our findings.
Background Early diagnosis of chronic obstructive pulmonary disease (COPD) remains challenging due to the limited sensitivity of spirometry and imaging in early-stage disease and the lack of reliable blood-based biomarkers. COPD is increasingly recognized as a heterogeneous disorder driven by coordinated immune dysregulation and airway structural remodeling; however, clinically applicable molecular signatures that capture these processes are still lacking. Objectives To identify and validate a blood-based diagnostic signature for COPD and to explore the underlying immune and structural remodeling mechanisms. Design A multi-stage integrative study combining retrospective bioinformatics analysis with prospective experimental validation. Methods Public lung transcriptomic datasets were used to identify COPD-associated candidate genes through differential expression, co-expression network, and machine-learning analyses. Candidate genes were validated by RT-qPCR in peripheral blood samples from stable COPD patients and healthy controls. Exploratory immune, single-cell, virtual perturbation, and molecular simulation analyses were performed to assess potential biological relevance. Results Four lung-derived candidate genes, AC079767.4, CEP55, EMR3, and ATP6V0D2, were identified. In peripheral blood validation, CEP55 and ATP6V0D2 showed the strongest diagnostic performance, whereas AC079767.4 showed limited blood-based discriminatory ability. Functional and immune analyses suggested that these genes may be associated with intracellular pH regulation, vesicular acidification, cytokinesis, immune imbalance, and inflammatory pathways. Single-cell analysis indicated that CEP55 was mainly enriched in epithelial, endothelial, and smooth muscle cells, whereas ATP6V0D2 was enriched in macrophages and monocytes. Virtual perturbation and molecular simulation analyses provided hypothesis-generating evidence for possible involvement in antigen presentation, T-helper-cell-related pathways, and ligand–target interactions. Conclusion This study identified four lung-derived COPD-associated candidate genes through integrative transcriptomic, network, and machine-learning analyses. Among them, CEP55 and ATP6V0D2 showed the strongest peripheral-blood diagnostic performance and biological plausibility, supporting their prioritization as candidate circulating biomarkers for further validation. Exploratory docking and MD simulations suggested possible ligand–target interactions involving CEP55 and ATP6V0D2, but these computational findings require experimental pharmacological validation before any therapeutic relevance can be inferred.
Wenbo Du, Yukun Wang, Xiang Li et al.· Therapeutic Advances in Resp...· 0 citations
Untargeted metabolomics has revealed significant systemic metabolic dysregulation in ILD and the biomarkers and “metabolic-immune-endocrine” interaction patterns identified offer potential leads for early diagnosis and targeted treatment, which require validation in larger cohorts.
Lu Liu, Xinyi Wang, Jinling Xiao et al.· Frontiers in Medicine· 0 citations
Chronic Obstructive Pulmonary disease (COPD) and Idiopathic Pulmonary Fibrosis (IPF) are chronic pulmonary disorders with distinct pathologies but shared risk factors. Metabolomics may provide insights into mechanisms. To identify metabolites associated with COPD and IPF, and to characterize shared and disease-specific signatures. Plasma metabolomic profiling was conducted in the Lung Tissue Research Consortium (LTRC). Logistic regression identified metabolites associated with COPD and IPF, and results were replicated in an external cohort, COPDGene. We applied Weighted Gene Co-expression Network Analysis (WGCNA) to explore disease-associated metabolite modules. We further evaluated relationships between significant metabolites and risk genes of interest. Of 1131 metabolites in LTRC, 246 (21.8%) differed between COPD and controls, and 136 (12.0%) between IPF and controls (FDR < 0.05). Among 80 shared significant metabolites in COPD and IPF, 77 showed concordant directions of effect. Shared metabolomic changes included reduced levels of steroids, triglycerides, diglycerides, phosphatidylcholines, and increased levels of carnitines. In contrast, polyunsaturated fatty acids, nicotine, and thyroxine metabolites differed between COPD and IPF; these findings were further explored by the WGCNA. External replication was performed for 120 metabolites measured in both cohorts, of which 49 (40.8%) replicated in COPD vs. control. In exploratory analyses leveraging quantitative imaging abnormalities (QIA) as a surrogate for IPF; only 4 (3.3%) metabolites replicated in the QIA vs. control model, and only 9 (7.5%) for COPD vs. QIA. Alterations in metabolomic profiles of COPD and IPF suggested shared dysregulation of several lipids. However, some metabolites pointed to disease-specific differences.
Aldric Rosario, N. Prince, S. Madha-Krause et al.· Metabolomics· 0 citations
Psoriasis (PS) is a chronic inflammatory skin disease associated with cardiometabolic comorbidity. While systemic inflammation is recognized as a major driver of this risk, metabolomic signatures linking PS to cardiometabolic dysfunction remain incompletely defined. The aim of this study was to characterize the serum metabolomic profile of PS and identify metabolic alterations that may contribute to cardiometabolic risk. Fasting serum samples from 455 individuals with PS and 591 matched controls were measured using proton NMR spectroscopy. A total of 325 biomarkers including lipoproteins, fatty acids, amino acids, apolipoproteins, inflammation-related metabolites and their ratios were quantified. PS demonstrated an atherogenic metabolic signature characterized by increased LDL, ApoB, triglyceride-rich VLDL, and small HDL/LDL subclasses. Elevations in saturated, monounsaturated, and omega-6 fatty acids–including linoleic acid were observed, alongside increases in histidine and valine and decreases in glycine and phenylalanine. Differential correlation and interaction analyzes revealed extensive remodeling of the metabolic network architecture in psoriasis. It can be concluded that PS is associated with coordinated disturbances across lipid, fatty-acid, and amino-acid pathways, reflecting a systemic pro-atherogenic and pro-inflammatory environment. These metabolomic alterations provide mechanistic insight into heightened cardiometabolic risk and highlight potential biomarkers for disease stratification and future interventional studies.
A. Ottas, M. Karu, L. Ilves et al.· Scientific Reports· 0 citations
Purpose: We compared salivary metabolomic signatures from patients with stable COPD across a range of severity of airflow obstruction with healthy controls. Patients and Methods: In this exploratory study, 47 people with COPD and 48 age-matched, healthy controls, provided saliva that was assessed by flow infusion electrospray mass spectrometry (FIE-MS). Spectra were interrogated using an open-source library DIMEpy package. Results: Four potential biomarkers identified the presence of COPD with a sensitivity of 73% and specificity of 72%. Six metabolites predicted the level of airflow obstruction, FEV1% in the COPD cohort ( P < 0.001, R 2 > 0.3, AUC > 0.7), whilst a range of multivariate approaches targeted six metabolites linked to COPD stage of severity ( P < 0.001, AUC > 0.7). Identification of the metabolites suggested changes in pterin biosynthesis, lipid processing, nucleotide metabolism and melatonin in COPD patients. Conclusion: This proof-of-concept study shows metabolic fingerprinting of saliva samples is feasible and can differentiate patients with COPD from people (including smokers) without COPD and correlates with COPD severity as defined by level of airflow obstruction. Metabolic fingerprinting also offers insights into the metabolic pathways involved in COPD aetiology.
Denisa Asandei, Keiron O'Shea, Rachel Paes de Araujo et al.· International Journal of COP...· 0 citations
Summary Kidney fibrosis, the final pathological outcome of chronic kidney disease, lacks reliable biomarkers, and the role of lactylation in its pathogenesis remains poorly defined. We integrated multi-omics, machine learning, and experimental validation to identify lactylation-associated biomarkers using two public transcriptomic datasets. After batch correction and differential expression analysis, 13 overlapping lactylation-modified genes were obtained, and eight hub genes were identified via 113 model combinations. Downregulated hub genes regulate core renal metabolic pathways including TCA cycle and oxidative phosphorylation, while upregulated genes mediate immune-inflammatory activation and cytokine signaling. Immune infiltration analysis showed significant immune cell enrichment in fibrotic tissues, with hub genes correlated with T cell subsets. Six hub genes were validated in UUO mouse models and human fibrotic kidney tissues. A five-gene diagnostic panel exhibited robust diagnostic performance with AUCs of 0.89–0.90. This study establishes a lactylation-related diagnostic signature, reveals metabolic-immune crosstalk, and supports early clinical diagnosis of kidney fibrosis.
Ye Kuang, Xiuhong Xiang, Chuan-Mei Peng et al.· iScience· 0 citations