Anti-Inflammatory Function of Fatty Acids and Involvement of Their Metabolites in the Resolution of Inflammation in Chronic Obstructive Pulmonary Disease

Kotlyarov, Stanislav; Kotlyarova, Anna

doi:10.3390/ijms222312803

Cited by 37 publications

(19 citation statements)

References 281 publications

(345 reference statements)

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“…Fig. 5b highlights the ‘Carnitine metabolism’ pathway ( p≤ 0.05), as well as other pathways which may not have reached statistical significance but may be of interest such as ‘Arachidonic acid metabolism, or ‘Mitochondrial fatty acid beta oxidation’ 48,55 . Encouragingly, related pathways in the close neighbourhood of ‘Carnitine metabolism’ have lower p -values than those further from it.…”

Section: Resultsmentioning

confidence: 99%

PathIntegrate: Multivariate modelling approaches for pathway-based multi-omics data integration

Wieder,

Cooke,

Frainay

et al. 2024

Preprint

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As terabytes of multi-omics data are being generated, there is an ever-increasing need for methods facilitating the integration and interpretation of such data. Current multi-omics integration methods typically output lists, clusters, or subnetworks of molecules related to an outcome. Even with expert domain knowledge, discerning the biological processes involved is a time-consuming activity. Here we propose PathIntegrate, a method for integrating multi-omics datasets based on pathways, designed to exploit knowledge of biological systems and thus provide interpretable models for such studies. PathIntegrate employs single-sample pathway analysis to transform multi-omics datasets from the molecular to the pathway-level, and applies a predictive single-view or multi-view model to integrate the data. Model outputs include multi-omics pathways ranked by their contribution to the outcome prediction, the contribution of each omics layer, and the importance of each molecule in a pathway. Using semi-synthetic data we demonstrate the benefit of grouping molecules into pathways to detect signals in low signal-to-noise scenarios, as well as the ability of PathIntegrate to precisely identify important pathways at low effect sizes. Finally, using COPD and COVID-19 data we showcase how PathIntegrate enables convenient integration and interpretation of complex high-dimensional multi-omics datasets. The PathIntegrate Python package is available athttps://github.com/cwieder/PathIntegrate.Author summaryOmics data, which provides a readout of the levels of molecules such as genes, proteins, and metabolites in a sample, is frequently generated to study biological processes and perturbations within an organism. Combining multiple omics data types can provide a more comprehensive understanding of the underlying biology, making it possible to piece together how different molecules interact. There exist many software packages designed to integrate multi-omics data, but interpreting the resulting outputs remains a challenge. Placing molecules into the context of biological pathways enables us to better understand their collective functions and understand how they may contribute to the condition under study. We have developed PathIntegrate, a pathway-based multi-omics integration tool which helps integrate and interpret multi-omics data in a single step using machine learning. By integrating data at the pathway rather than the molecular level, the relationships between molecules in pathways can be strengthened and more readily identified. PathIntegrate is demonstrated on Chronic Obstructive Pulmonary Disease and COVID-19 metabolomics, proteomics, and transcriptomics datasets, showcasing its ability to efficiently extract perturbed multi-omics pathways from large-scale datasets.

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Section: Resultsmentioning

confidence: 99%

PathIntegrate: Multivariate modelling approaches for pathway-based multi-omics data integration

Wieder,

Cooke,

Frainay

et al. 2024

Preprint

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“…This indicates that the development of airway inflammation increases the body's energy requirements (Ho et al, 2013). Glycerol, monoolein, and monostearin are products of altered energy metabolism produced by abnormal pulmonary respiration in patients with COPD, especially in the presence of hypoxia or inflammation (Hallin et al, 2011; Kotlyarov & Kotlyarova, 2021). Chronic hypoxia‐induced HIF activation decreases insulin receptor phosphorylation, which in turn weakens Akt‐mediated downstream signaling.…”

Section: Discussionmentioning

confidence: 99%

Protective effect of Xixin–Ganjiang herb pair for warming the lungs to dissolve phlegm in chronic obstructive pulmonary disease rats based on integrated network pharmacology and metabolomics

Huang,

Xiang,

Wang

et al. 2024

Biomedical Chromatography

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Xixin–Ganjiang herb pair (XGHP) is a classic combination for warming the lungs to dissolve phlegm and is often used to treat a variety of chronic lung diseases; it can treat the syndrome of cold phlegm obstruction of lungs. First, ultra‐performance liquid chromatography–tandem mass spectrometry (UPLC‐MS/MS) was used to examine the composition of XGHP, and network pharmacology was used to predict its potential core targets and signaling pathways in the current study. Second, a rat model of chronic obstructive pulmonary disease (COPD) was established for assessing the anti‐COPD activity of XGHP, and metabolomics was used to explore the biomarkers and metabolic pathways. Finally, the sample was validated using molecular docking and Western blotting. The integration of metabolomics and network pharmacology results identified 11 targets, 3 biomarkers, 3 pathways, and 2 metabolic pathways. Western blotting showed that XGHP effectively regulated the expression of core proteins via multiple signaling pathways (downregulation of toll‐like receptor 4 [TLR4] and upregulation of serine/threonine‐protein kinase 1 [p‐AKT1] and nitric oxide synthase 3 [NOS3]). Molecular docking results showed that the 10 potentially active components of XGHP have good affinity with tumor necrosis factor‐alpha (TNF‐α), interleukin‐6 (IL‐6), matrix metalloproteinase 9 (MMP‐9), TLR4, p‐AKT1, and NOS3. Our findings suggest that XGHP may regulate glucolipid metabolism, improve energy supply, and inhibit inflammatory responses (TNF‐α, IL‐6, and MMP‐9) via the PI3K‐Akt signaling pathway and HIF‐1 signaling pathway in the management of COPD.

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“…Fatty acid degradation is also closely related to mitochondria, and activated fatty acids can only be oxidized inside mitochondria and generate acetyl-coenzyme A. COPD can be accompanied by an imbalance of fatty acid metabolism in the lung, and metabolic reprogramming can also provide a feedback loop and regulate the progress of COPD; for example, by promoting inflammation and airway smooth muscle cell (ASMC) hyperplasia ( 43 , 45 , 78 ). Our proteomics and acetylomics associative analysis found extensive differential acetylation modification in the fatty acid degradation pathway, indicating that protein acetylation modification contributes to the interaction between fatty acid degradation and COPD.…”

Section: Discussionmentioning

confidence: 99%

Associative analysis of multi-omics data indicates that acetylation modification is widely involved in cigarette smoke-induced chronic obstructive pulmonary disease

Gao

Liu²,

Wang³

et al. 2023

Front. Med.

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We aimed to study the molecular mechanisms of chronic obstructive pulmonary disease (COPD) caused by cigarette smoke more comprehensively and systematically through different perspectives and aspects and to explore the role of protein acetylation modification in COPD. We established the COPD model by exposing C57BL/6J mice to cigarette smoke for 24 weeks, then analyzed the transcriptomics, proteomics, and acetylomics data of mouse lung tissue by RNA sequencing (RNA-seq) and liquid chromatography-tandem mass spectrometry (LC-MS/MS), and associated these omics data through unique algorithms. This study demonstrated that the differentially expressed proteins and acetylation modification in the lung tissue of COPD mice were co-enriched in pathways such as oxidative phosphorylation (OXPHOS) and fatty acid degradation. A total of 19 genes, namely, ENO3, PFKM, ALDOA, ACTN2, FGG, MYH1, MYH3, MYH8, MYL1, MYLPF, TTN, ACTA1, ATP2A1, CKM, CORO1A, EEF1A2, AKR1B8, MB, and STAT1, were significantly and differentially expressed at all the three levels of transcription, protein, and acetylation modification simultaneously. Then, we assessed the distribution and expression in different cell subpopulations of these 19 genes in the lung tissues of patients with COPD by analyzing data from single-cell RNA sequencing (scRNA-seq). Finally, we carried out the in vivo experimental verification using mouse lung tissue through quantitative real-time PCR (qRT-PCR), Western blotting (WB), immunofluorescence (IF), and immunoprecipitation (IP). The results showed that the differential acetylation modifications of mouse lung tissue are widely involved in cigarette smoke-induced COPD. ALDOA is significantly downregulated and hyperacetylated in the lung tissues of humans and mice with COPD, which might be a potential biomarker for the diagnosis and/or treatment of COPD.

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Anti-Inflammatory Function of Fatty Acids and Involvement of Their Metabolites in the Resolution of Inflammation in Chronic Obstructive Pulmonary Disease

Cited by 37 publications

References 281 publications

PathIntegrate: Multivariate modelling approaches for pathway-based multi-omics data integration

PathIntegrate: Multivariate modelling approaches for pathway-based multi-omics data integration

Protective effect of Xixin–Ganjiang herb pair for warming the lungs to dissolve phlegm in chronic obstructive pulmonary disease rats based on integrated network pharmacology and metabolomics

Associative analysis of multi-omics data indicates that acetylation modification is widely involved in cigarette smoke-induced chronic obstructive pulmonary disease

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