Dissecting causal relationships between immune cells, plasma metabolites, and COPD: a mediating Mendelian randomization study

Yangke powder alleviates OVA-induced allergic asthma by inhibiting the PI3K/AKT/NF-κB signaling pathway

BACKGROUND

Asthma is a chronic inflammatory airway disease that remains inadequately controlled by existing conventional treatments. A traditional Chinese medicine (TCM) formula of Yangke powder (yǎng ké sǎn-YKS) has demonstrated potential in alleviating asthma symptoms and reducing its acute exacerbation. Despite clinical evidence supporting its benefit, there is still insufficient understanding of the active compounds in YKS and their underlying mechanisms, which limits its broader clinical application.

OBJECTIVE

This study aims to identify the key active ingredients in YKS and explore their mechanisms, particularly through the PI3K/AKT/NF-κB pathways, to provide a scientific basis for its application in asthma treatment.

METHODS

We employed UPLC-Q-Exactive Orbitrap-MS to analyze YKS constituents, identified key ingredients, and explored asthma treatment mechanisms through bioinformatics, network pharmacology, Mendelian randomization, and molecular docking. The asthma model was evaluated using ovalbumin (OVA) and pulmonary function tests, while pathological examination was conducted using hematoxylin and eosin (HE), periodic acid-Schiff (PAS), and Masson trichrome stains. Concentrations of IgE, IL-4, and IL-5 were measured by ELISA, and protein and mRNA expressions were confirmed via qPCR, immunohistochemistry, and Western blot analysis.

RESULTS

A total of 174 compounds were identified in YKS by UPLC-MS, with 49 detected in the bloodstream, indicating their role as active ingredients. Bioinformatics analysis revealed 353 asthma-related targets and 972 potential targets for YKS. Key targets such as AKT1, TNF, and IL1B were validated by molecular docking. Our studies indicated that YKS modulates asthma primarily through the PI3K/Akt and NF-κB pathways, improving airway resistance, reducing inflammation, mucus production, and airway remodeling, and decreasing Th2 cytokines and IgE levels.

CONCLUSION

This investigation identifies Kaempferol, Norephedrine, Cynaroside, Genistein, and Rutin as critical active ingredients in YKS, impacting key biomarkers such as AKT1, TNF, and IL1B. These substances effectively modulate the PI3K/AKT/NF-κB pathway, enhancing the management of allergic asthma.

Exploring the potential biomarkers and potential causality of Ménière disease based on bioinformatics and machine learning

Meniere disease (MD) is a common inner ear disorder closely related to immune abnormalities, but research on the characteristic genes between MD and immune responses is still insufficient. We employ bioinformatics and machine learning to predict potential biomarkers and characteristic immune cells associated with MD, investigating the Mendelian randomization causation between immune cells and MD, providing new insight for the early diagnosis, prevention, and treatment of MD. We obtained relevant data on MD from the GEO database using R, conducted differential gene analysis, and performed weighted gene co-expression network analysis (WGCNA) to identify genes associated with MD. Moreover, by integrating the selection of core genes from the PPI with machine learning techniques, we predicted potential biomarkers for MD. Simultaneously, conducted immune infiltration analysis of the core genes and identified key immune cell types. Finally, employed Mendelian randomization to comprehensively evaluate the causal relationship between immune cells and MD. Through differential gene analysis and WGCNA, we identified 550 genes associated with MD, with enrichment analysis predominantly focused on pertinent immune responses and related diseases. The protein-protein interaction (PPI) screening and machine learning techniques, we predicted 2 potential biomarkers for MD: CD5 and AJUBA, 3 core immune cell types associated with MD: T cells CD4 memory resting, T cells gamma delta and Dendritic cells activated. Mendelian randomization analysis revealed a causal relationship between 26 types of immune cells and MD. There is a causal relationship between immune cells and MD. CD5 and AJUBA are potential biomarkers of MD, while T cells CD4 memory resting, T cells gamma delta and Dendritic cells activated are core immune cells of MD. These potential biomarkers and core immune cells offer new insights for the early diagnosis, prevention, and treatment of MD.

Effect of the Antibody-mediated Immune Responses on COPD, Asthma, and Lung Function: A Mendelian Randomization Study

INTRODUCTION

The precise cause of antibody-mediated immune responses on chronic obstructive pulmonary disease (COPD), asthma, and lung function remains unclear. We characterized the relationship between antibody-mediated immune responses to COPD, asthma, and lung function, ultimately achieve the prevention or treatment.

METHODS

We obtained summary data from published genome-wide association studies, including antibody-mediated immune responses, COPD, asthma, forced expiratory volume in the first second (FEV1), forced expiratory volume (FVC), and FEV1/FVC. Bidirectional two-sample mendelian randomization (MR) analysis was used to assess causal relationships of antibody-mediated immune responses, COPD, asthma, FEV1, FVC, and FEV1/FVC.

RESULTS

A total of 20 antibody-mediated immune responses were identified have a significant causal effect on COPD, asthma, FEV1, and FVC, with six exhibiting reverse causality. Importantly, the results of the five MR analyses were almost identical with respect to the causal effect of anti-polyomavirus 2 IgG seropositivity and varicella zoster virus glycoprotein E and I antibody levels on the risk of COPD, asthma, FEV1, and FVC.

CONCLUSIONS

This study contributes to existing knowledge by investigating the causal relationship between antibody-mediated immune responses and respiratory conditions, including COPD, asthma, and lung function, using a two-sample MR design. The key findings can aid in identifying individuals at risk of these conditions and facilitate early prevention and diagnosis.

The effects of immune cell phenotypes and plasma metabolomes on diabetic foot ulcer: a Mendelian randomization study and mediation analysis

This study investigates the causal relationships between plasma metabolites, immune cell phenotypes, and diabetic foot ulcer (DFU). A Mendelian randomization (MR) study was conducted, which included 731 immune cell phenotypes, 1400 metabolites, and DFU. The primary analytical approach was the inverse variance-weighted method. Sensitivity analyses were performed to assess heterogeneity and pleiotropy, and MR analyses in the reverse direction were conducted to examine the possibility of reverse causation. In addition, a mediation analysis was performed to reveal how metabolites mediate the impact of immune cells on DFU. Through MR, reverse MR and sensitivity analysis, the casualty was found in 17 immune cell phenotypes and 18 metabolites. A total of 15 mediating relationships were identified through mediation analysis, including 9 metabolites and 10 immune cell phenotypes. Among them, the highest mediation proportion was citrulline levels mediating CD24+ CD27+ AC (absolute count, B cell panel) to DFU, with a proportion of 11.60%. In conclusion, the study identified causal relationships between 10 immune cell phenotypes mediated by 9 metabolites. These discoveries offered fresh perspectives on the processes behind DFU and laid the groundwork for subsequent studies to create specific treatments for DFU.

Genetically Predicted Plasma Metabolome Mediates the Causal Link Between Immune Cells and Risk of Gout

BACKGROUND

Gout is a prevalent metabolic disorder characterized by a multifaceted process of development. Recent research has emphasized a robust correlation between the immune response and gout. Nevertheless, it is still uncertain if this connection is causative. Hence, the objective of this study was to investigate the causal relationship between immune cells and gout, while also analyzing the role of the plasma metabolome as metabolic mediators in this biological process.

METHODS

This study explored the causal link between different subtypes of immune cells and gout using two-sample Mendelian randomization (MR). To confirm the reliability of the findings, reverse MR analysis, steiger test and sensitivity tests were conducted. A two-step mediation analysis was used to gain insight into the role of plasma metabolites as intermediate mediators.

RESULTS

This two-sample, bidirectional, two-step MR analysis found a nominal causal link between 33 immune cells as well as 47 known plasma metabolites and gout. Reverse MR analysis and sensitivity tests demonstrated the reliability of the MR results. In addition, we found that Tetradecadienedioate (C14:2-DC) played a partially mediating role in the CD4 on activated CD4 regulatory T cell and gout pathways, with a mediating proportion of 13.16%, (95% CI = 0.65%-25.67%, p = 0.034).

CONCLUSION

The objective of our research was to investigate the possible causative connection between immune cells and gout. Our findings indicate that certain plasma metabolites may play a role in mediating this association. This study offers novel insights and sources of information that may contribute to the early detection and proactive measures to avoid gout in the future.