Aug 2026· Frontiers in Medicine· Vol 13· 0 citations· 34 references
Medicine
TL;DR
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.
Abstract
Objective To analyze differences in serum metabolic profiles between patients with interstitial lung disease (ILD) and healthy controls in northern China using untargeted metabolomics techniques, to identify differentially expressed metabolites and key dysregulated pathways, and to identify potential metabolic biomarkers. Methods Thirty patients with interstitial lung disease (ILD) and 30 healthy controls were enrolled. Untargeted metabolomics analysis was performed using LC-MS/MS in both positive and negative ion modes. Differentially expressed metabolites were identified using the criteria VIP > 1.0, FC > 1.2 or FC < 0.833 and P-value < 0.05. Pathway enrichment analysis was conducted using the KEGG database, and diagnostic performance was evaluated using ROC curves. Results The global metabolic profile showed significant separation between the ILD group and the control group. Pathway enrichment analysis revealed significant dysregulation in lipid metabolism (particularly linoleic acid metabolism), amino acid biosynthesis, and steroid hormone metabolism. GSEA analysis further confirmed the suppression of overall metabolic activity and the specific enrichment of tryptophan metabolism. Among the differentially expressed metabolites, DG(15:0/18:2(9Z,12Z)/0:0) (AUC = 0.914), Medroxalol (AUC = 0.912), estriol 3-sulfate (AUC = 0.890) and DHEA-S (AUC = 0.877) demonstrated high diagnostic value. Conclusion Untargeted metabolomics has revealed significant systemic metabolic dysregulation in ILD. The biomarkers and “metabolic-immune-endocrine” interaction patterns identified offer potential leads for early diagnosis and targeted treatment, which require validation in larger cohorts.
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
Kawasaki disease (KD) is one of the most common rheumatic diseases in children and manifests with multisystem clinical features. Using untargeted metabolomics, our study investigated alterations in small-molecule metabolites in plasma of children with acute KD. Our study aimed to identify differential metabolic pathways and potential biomarkers.
Plasma samples were collected from 30 children diagnosed with KD and 30 age-matched healthy controls (HC) at Jinhua Maternal and Child Health Hospital between January 2025 and December 2025. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was applied to analyse plasma samples. Enriched pathways were identified using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and differential metabolic pathways were determined using MetaboAnalyst 5.0. Differential metabolites were screened using the nonparametric Mann–Whitney
U
-test and receiver operating characteristic curve area (AUC). The conservative average AUC from nested cross-validation was reported as the primary performance metric. Pearson correlation analysis was conducted to evaluate correlations between metabolites and clinical parameters.
In total, 261 differential metabolites were identified between the KD and HC groups, including 87 lipids and lipid-like molecules, 69 organic heterocyclic compounds, 38 benzenoids, 34 organic acids, 14 phenylpropanoids, and 19 other compounds. Pathway analysis of these differential metabolites revealed 30 putatively enriched metabolic pathways for exploratory analysis. Of these pathways, primary bile acid biosynthesis, arginine biosynthesis, histidine metabolism, and phenylalanine-tyrosine-tryptophan biosynthesis were nominally associated with KD. Six metabolites with exploratory discriminatory performance (AUC > 0.8) were further identified: L-tyrosine, L-tryptophan, glutamine, histidine, histamine, and taurocholic acid. A combined model incorporating these metabolites achieved an apparent AUC of 0.984 in the full dataset; nested cross-validation yielded a more conservative AUC of 0.889 (95% CI 0.798–0.968), indicating promising exploratory discriminatory performance.
Untargeted metabolomics enables identification of metabolically perturbed pathways during the acute phase of KD. L-tyrosine, L-tryptophan, glutamine, histidine, histamine, and taurocholic acid may serve as candidate biomarkers for acute phase of KD.
Hanqi Dai, Qianwen Wang, Yi Zhan· Frontiers in Medicine· 0 citations
Findings highlight coordinated dysregulation of amino acid and lipoprotein metabolism as hallmarks of established MS and identify a novel association of the omega-6/omega-3 ratio with inflammatory disease activity.
R. Rodin, B. Healy, Mariann Polgár-Turcsányi et al.· bioRxiv· 0 citations
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.
Hangming Xiong, Yingying Xue, Xiaojing Zhang et al.· Journal of Proteomics· 0 citations
Three candidate biomarkers co-dysregulated across T2DM and MCI transcriptomes and associated with uric acid metabolism are identified and considered hypothesis-generating and require validation in larger independent cohorts.
Yan Liu, Dongmei Kang, Yuan Lei· Experimental biology and med...· 0 citations
These findings bridge the gap between metabolic lipotoxicity and epigenetic regulation, suggesting that lactylation acts as a critical driver in NAFLD pathogenesis.
Qing-Xuan He, Xu Wang, Peng-Fei Wang et al.· Endocrine, Metabolic & Immun...· 0 citations
