ArticleFrontiers in genetics2025
Transcriptomic profiling reveals macrophage gene signatures associated with lactylation-related pathways in chronic obstructive pulmonary disease.
Article in Frontiers in genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Molecular Mechanisms and Therapeutic Targeting of the Macrophage Metabolic-Epigenetic Interaction Network in Chronic Obstructive Pulmonary Disease.Cell biochemistry and biophysics · 2026Review
- ASGR2 and CLEC12A as Prognostically Relevant C-Type Lectin Hubs in Glioblastoma.International journal of molecular sciences · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Macrophages contribute to the immune dysregulation observed in chronic obstructive pulmonary disease (COPD). Additionally, lactylation exerts an indirect influence on COPD pathogenesis. However, the specific biomarkers linked to macrophage activation in COPD and the underlying molecular mechanisms remain poorly understood. This study aimed to identify these biomarkers and elucidate the associated molecular pathways. Methods: Data were retrieved from public databases. A comprehensive analysis was conducted using weighted gene co-expression network analysis (WGCNA), immune infiltration analysis, differential expression analysis, correlation studies, machine learning, receiver operating characteristic (ROC) analysis, and expression level validation to identify macrophage lactylation-related biomarkers in COPD. The nomogram model, Gene Set Enrichment Analysis (GSEA), molecular regulatory networks, compound predictions, and molecular docking were employed to further explore the roles of these biomarkers in COPD. Clinical samples were used to validate the expression levels of the identified biomarkers. Results: Three key biomarkers-ALDH2, ASGR2, and CYP1B1-were identified. The nomogram model based on these biomarkers accurately predicted the mortality of patients with COPD. GSEA suggested that the biomarkers are likely involved in metabolic pathways and B-cell receptor signaling. Five transcription factors (TFs), including STAT3, were associated with all identified biomarkers. Eight compounds, including bisphenol A, were linked to multiple biomarkers, with CYP1B1 exhibiting the strongest binding affinity to benzo(a)pyrene. Conclusion: This study identified three biomarkers, offering new perspectives on potential therapeutic targets for COPD.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.