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. 2024 Nov 29;103(48):e40541. doi: 10.1097/MD.0000000000040541

Mendelian randomization analysis of two samples to determine the impact of immune cells on bronchitis

Zhiyu Tian a, Zhanliang Jiang a, Li Shi b,*
PMCID: PMC11608709  PMID: 39612414

Abstract

Bronchitis is a common respiratory disease characterized by acute inflammation, edema, and necrosis of the small airways, leading to a significant pathological burden. Immune cells play a crucial role in combating bronchitis. This study aims to explore the causal relationship between immune cells and bronchitis using the Mendelian randomization approach. In this study, we screened 18,183 single nucleotide polymorphisms highly associated with immune cells and employed 5 Mendelian randomization methods to assess the potential causal link between different types of immune cells and bronchitis. Additionally, the study utilized inverse variance weighting and MR-Egger regression analysis to evaluate the heterogeneity and robustness of the causal estimates. The study found a significant causal association between 28 types of immune cells and the risk of bronchitis. These cell types mainly included T cells, monocytes, and B cells. For instance, CD25 on B cells and CD25 on IgD+ were associated with an increased risk of bronchitis, whereas IgD+ CD24‐ B cells and CD33‐ HLA DR‐ AC showed a protective effect against bronchitis. Moreover, the study validated the robustness of these findings through leave-one-out analysis and the MR-Egger method, and quantitatively illustrated the impact of immune cells on the risk of bronchitis through forest plots. This study reveals the dual role of immune cells in bronchitis. The identified types of immune cells may increase the risk of bronchitis by promoting inflammatory responses and cell-mediated immune reactions, while other cell types may offer protection by promoting immune balance and effective defense.

Keywords: bronchitis, GWAS, immune cells, Mendelian randomization

1. Introduction

Bronchitis is a common respiratory disease characterized by inflammation of the inner layer of the bronchial wall, posing a significant public health challenge due to its impact on respiratory function. The disease is classified into 2 main types: acute and chronic, each with its unique pathophysiological characteristics.[1] Acute bronchitis is primarily triggered by viral infections, manifesting as temporary inflammation of the airways, leading to coughing and mucus production.[2] Chronic bronchitis is a more persistent condition, defined as the presence of cough and mucus production for at least 3 months in 2 consecutive years, typically attributed to long-term exposure to irritants, such as tobacco smoke and environmental pollution.[3] The progression of bronchitis involves a complex interplay of environmental, genetic, and infectious factors. Acute episodes are mainly viral, but bacterial infections can exacerbate or prolong the disease.[4] Chronic bronchitis is closely associated with exposure to smoking and air pollutants, although genetic predispositions also play a role.[5] Treatment approaches vary according to the type and severity of bronchitis, ranging from supportive care and symptom management in acute cases to comprehensive strategies for chronic cases, including smoking cessation, pharmacotherapy, and pulmonary rehabilitation.[6] These strategies aim not only to alleviate symptoms but also to improve quality of life and reduce the risk of complications. Current research in the field of bronchitis focuses on unveiling the disease’s molecular and immune mechanisms, identifying new therapeutic targets, and evaluating the effectiveness of emerging treatment methods.[7] Studies show that immune cells act through various mechanisms to combat pathogens and maintain lung health. The initial response of the immune system involves innate immune cells, such as macrophages and dendritic cells, which recognize specific molecular patterns of pathogens through pattern recognition receptors, thereby triggering the release of a series of inflammatory mediators.[8] These mediators, including cytokines and chemokines, not only promote the migration of neutrophils and monocytes to the infected area, enhancing phagocytosis, but also facilitate the intervention of the adaptive immune response.[9] In the adaptive immune response, the production of antibodies by B cells and the cytotoxic action of CD8+ T cells work together to clear pathogens. Additionally, CD4+ T cells coordinate the entire immune response by secreting cytokines.[10] After the infection is controlled, inflammation is reduced through regulatory T cells and other mechanisms, restoring tissue homeostasis, highlighting the complexity and precision of the immune system in maintaining respiratory health.

In modern epidemiological trend analysis, distinguishing between statistical associations and genuine causal relationships becomes complicated due to confounding variables, reverse causation, and various research biases. Although randomized controlled trials are considered the gold standard for assessing causal effects, they may be limited in practice due to costs, ethical considerations, and operational challenges.[11] Mendelian randomization (MR) offers a unique method by using genetic variations as instrumental variables to assess causal relationships in observational studies. This approach is based on the random distribution of genetic variants and their independence from environmental factors. When a genetic variant is associated with a risk factor, which in turn is associated with the development of a disease, this variant can serve as an instrumental variable to reveal the causal relationship between them. Mendelian randomization essentially simulates a “natural” randomized controlled trial, allowing researchers to evaluate the impact of specific exposure factors on health without direct intervention.[12]

Currently, the exact role of immune cells in the development of bronchitis remains unclear. Early research suggests that the immune response may play a key role in the pathogenesis of bronchitis, but due to the limitations of traditional epidemiological research methods in establishing causality, it is still uncertain whether changes in immune cells are a cause or a result of bronchitis. Given this, the search for potential immune therapeutic targets for bronchitis is particularly urgent. This study employs the MR approach to assess the causal link between immune cells and bronchitis. By identifying specific genetic variants directly related to the quantity or function of immune cells, this study can evaluate the potential impact of these immune properties on the risk of bronchitis. This method avoids the problems of reverse causation and confounding variables, providing new scientific evidence for our understanding of the role of immune cells in bronchitis. Therefore, this study aims to explore the role of immune cells in the development of bronchitis. Especially, considering the current lack of studies using the MR method to explore the connection between immune cells and bronchitis, the results of this study may offer new directions for immune-mediated treatment strategies.

2. Materials and methods

2.1. Data sources

In this study, we utilized data from the publicly available genome-wide association study (GWAS) database “Open GWAS.”[13] To ensure the comprehensiveness and accuracy of our research findings, we selected the most exhaustive GWAS dataset of peripheral blood immune phenotypes currently available. This dataset includes a multidimensional array of immune characteristics: 118 absolute cell counts, 389 median fluorescence intensities of cell surface antigen levels, 32 cell morphology parameters (such as forward scatter and side scatter indices), and 192 relative cell counts. The statistics for these 731 distinct immune features have been made public in the GWAS catalog, with access numbers GCST0001391 and GCST0002121.[14] Additionally, the GWAS summary data related to bronchitis that we analyzed also came from the Open GWAS database, with the dataset identifier ebi-a-GCST90018802. This dataset encompasses 479,301 individuals of European ancestry, including 4483 diagnosed cases of bronchitis and 474,818 healthy control participants. Since the data used in our study is entirely sourced from an open database, no additional ethical approval was required for our research. The open access approach to data strengthens the transparency of our research, ensures the credibility of data quality, and facilitates the widespread dissemination and discussion of our research findings in the international scientific community.

2.2. Selection of instrumental variables

In our study, we filtered single nucleotide polymorphisms (SNPs) that showed significant relevance to our research objective, specifically selecting those with genome-wide significance (P-value below 5 × 10‐8) as instrumental variables (IVs). To ensure the genetic independence of the selected SNPs, we performed linkage disequilibrium testing and excluded SNPs with a linkage disequilibrium index (r2) higher than 0.001 or a genomic distance of <10,000 base pairs. We also estimated the F-statistics for each potential IV to confirm its association strength with the exposure and excluded IVs with an F-statistic lower than 10 to enhance the validity and strength of the IVs in the analysis. Additionally, to avoid potential pleiotropy issues, we conducted exhaustive searches for each IV in the “PhenoScanner” database to exclude SNPs that may be associated with multiple traits. Through this rigorous selection process, we improved the precision and reliability of the MR analysis.

2.3. Statistical analysis

In this study, we employed a suite of MR analysis methods aimed at establishing the precise causal relationship between immune cells and bronchitis. Our analytical strategy encompassed inverse variance weighted method, weighted median method, MR-Egger approach, along with simple mode and weighted mode among other statistical techniques. These techniques operate under different assumptions, providing us with a multifaceted framework for causal inference. The inverse variance weighted method utilizes each selected SNP as an unbiased instrumental variable and combines it with its inverse variance as weights to synthesize the effect estimate. The MR-Egger method can detect and adjust for pleiotropic bias, offering a corrected causal estimate even in the presence of pleiotropy. The weighted median method is based on the assumption that at least half of the instrumental variables are valid, thus providing a robust estimate of the causal relationship.

To assess the consistency and heterogeneity of our results, we used Cochran Q statistic test and performed leave-one-out analysis to investigate any potential pleiotropic bias. This strategy involves sequentially excluding each SNP and reperforming the MR analysis to identify outlier instrumental variables that may affect the conclusions. Finally, multiple corrections of the P-values were made to ensure the robustness of our final results.[15] All MR analyses were conducted in the R software environment, using statistical packages such as “TwoSampleMR” and “MR-PRESSO” for computation. These packages include the necessary algorithms and statistical frameworks, making our analysis more precise and reliable. Through this comprehensive approach and validation steps, we greatly enhanced the credibility and scientific integrity of our research findings.

3. Results

3.1. Impact of immune cells on bronchitis

To assess the impact of immune cells on bronchitis, we identified 18,183 SNPs highly related to immune cells, listed in Supplementary File 1, Supplemental Digital Content, http://links.lww.com/MD/N965. To evaluate the potential causal relationship between types of immune cells and bronchitis, this study employed 5 independent MR analysis methods. Through this complex series of analyses, we found a significant causal link between 28 different types of immune cells and the incidence of bronchitis. Specifically, IgD+ CD24‐ _lymphocytes, CD25 on naive-mature B cells, CD28‐ CD25++ CD8br AC, CD127‐ CD8br _T cells, CD14‐ CD16+ monocytes _monocytes, CD33 on CD33br HLA DR+, CD25 on B cells, CD28‐ CD127‐ CD25++ CD8br AC, CD25 on IgD+, HLA DR on CD33dim HLA DR+ CD11b+, CX3CR1 on CD14+ CD16+ monocytes, and CD28+ CD45RA+ CD8br AC were identified as risk factors for bronchitis. Conversely, IgD‐ CD38dim AC, CD80 on monocytes, CD66b on granulocyte-like myeloid-derived suppressor cells, CD20 on IgD‐ CD24‐, FSC-A on CD14+ monocytes, IgD+ CD24‐ _B cells, CD33‐ HLA DR‐ AC, HLA DR+ CD8br _T cells, CCR2 on myeloid dendritic cells (DCs), IgD‐ CD27‐ _B cells, IgD+ CD38‐ _B cells, HLA DR+ T cell AC, CD8dim _T cells, CD123 on plasmacytoid DCs, CD123 on CD62L+ plasmacytoid DCs, and CD8dim AC were shown to have a protective effect against bronchitis (Figs. 1–4). To verify the robustness of these findings, this study also employed a leave-one-out analysis method, which involves recalculating the causal effect after excluding each SNP in turn from the MR analysis. The results showed no significant change in causal effects (Figures S1–S4, Supplemental Digital Content, http://links.lww.com/MD/N958, http://links.lww.com/MD/N959, http://links.lww.com/MD/N960, http://links.lww.com/MD/N961). Furthermore, to assess the consistency and robustness of the causal estimates, we also used the inverse variance weighted method and MR-Egger regression to detect heterogeneity in causal effect estimates. These analyses indicated no significant heterogeneity (Supplementary File 2, Supplemental Digital Content, http://links.lww.com/MD/N966). Additionally, the application of the MR-Egger method showed no pleiotropy issue among the SNPs of the 28 types of immune cells (Supplementary File 3, Supplemental Digital Content, http://links.lww.com/MD/N967). Finally, to visually present the quantified impact of these 28 types of immune cells on bronchitis, we created a forest plot (Fig. 5), summarizing the strength and effect of the causal relationship between the 28 immune cell types and bronchitis.

Figure 1.

Figure 1.

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Scatterplot of Mendelian randomization methods for immune cells. Scatterplot of CCR2 on myeloid DC (A), CD8dim _T cell (B), CD8dim AC (C), CD14‐ CD16+ monocyte_monocyte (D), CD20 on IgD‐ CD24‐ (E), CD25 on B cell (F), and CD25 on IgD+ (G).

Figure 4.

Figure 4.

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Scatterplot of Mendelian randomization methods for immune cells. Scatterplot of HLA DR+ CD8br_T cell (A), HLA DR+ T cell AC (B), IgD‐ CD27‐ _B cell (C), IgD‐ CD38dim AC (D), IgD+ CD24‐ _B cell (E), IgD+ CD24‐_lymphocyte (F), and IgD+ CD38‐ _B cell (G).

Figure 5.

Figure 5.

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Forest diagram of 28 immune cells.

Figure 2.

Figure 2.

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Scatterplot of Mendelian randomization methods for immune cells. Scatterplot of CD25 on naive-mature B cell (A), CD28‐ CD25++ CD8br AC (B), CD28‐ CD127‐ CD25++ CD8br AC (C), CD28+ CD45RA+ CD8br AC (D), CD33‐ HLA DR‐ AC (E), CD33 on CD33br HLA DR+ (F), and CD66b on Gr MDSC (G).

Figure 3.

Figure 3.

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Scatterplot of Mendelian randomization methods for immune cells. Scatterplot of CD80 on monocyte (A), CD123 on CD62L+ plasmacytoid DC (B), CD123 on plasmacytoid DC (C), CD127‐ CD8br _T cell (D), CX3CR1 on CD14+ CD16+ monocyte (E), FSC-A on CD14+ monocyte (F), and HLA DR on CD33dim HLA DR+ CD11b+ (G).

4. Discussion

Bronchitis is a common respiratory disease characterized by acute inflammation, edema, and necrosis of the small airways, leading to a significant pathological burden.[16] Studies have shown that the pathogenesis of bronchitis involves complex interactions among various immune cells, with each type of cell playing a unique role in the disease’s onset and progression through different mechanisms. Neutrophils, as the first responders to viral infections in the bronchioles, promote inflammation by releasing proteases and reactive oxygen species, which can damage airway epithelial cells.[17] CD8+ T cells play a key role in the antiviral immune response by recognizing and eliminating cells infected with the virus. However, their cytotoxic action also leads to epithelial damage and obstruction of the bronchioles.[18] Meanwhile, CD4+ T cells regulate the activity of other immune cells, including B cells that produce virus-specific antibodies, aiding in virus clearance but also potentially leading to immune complex deposition and further inflammation.[19] Macrophages and dendritic cells, as antigen-presenting cells, engulf viral particles and present antigens to T cells, thereby initiating the adaptive immune response. These cells also release cytokines and chemokines, recruiting more immune cells to the site of infection and thus exacerbating the inflammatory response.[20] Regulatory T cells attempt to mitigate excessive inflammation and prevent immune-mediated tissue damage, highlighting the balance between effective viral clearance and immunopathology in bronchitis.[21]

Our research findings indicated that the 28 immune cells primarily belonged to T cells, B cells, monocytes, and others. Recent studies had uncovered key insights into various aspects of the immune system, particularly in bronchitis. One study showed that IgD+ CD24‐ lymphocytes, a specific subset of B cells with roles in mucosal and autoimmune responses, were involved in abnormal mucosal immune reactions or autoimmunity in bronchitis, leading to chronic inflammation and airway damage.[22] The expression of CD25 (IL-2 receptor α chain) on mature B cells indicated a regulatory or activated state, suggesting that these B cells could help regulate the immune response to persistent infections by producing specific antibodies or modulating other immune cells.[19] CD28‐ CD25++ CD8+ activated cells and CD127‐ CD8+ T cells had defined highly activated cytotoxic T cells and regulatory T cells, respectively. In bronchitis, they might have been involved in directly killing infected cells and regulating inflammatory responses. The balance between cytotoxicity and regulatory functions could have influenced the severity and progression of the disease.[23] CD14‐ CD16+ nonclassical monocytes were known for their roles in tissue repair and inflammation, potentially contributing to the chronic inflammatory environment of bronchitis and participating in the repair of damaged airways.[24] The expression of CD33 and HLA DR on myeloid cells reflected their activation state and antigen-presenting capability, playing key roles in coordinating the immune response to persistent airway infections and leading to chronic inflammation.[25] CX3CR1 on CD14+ CD16+ monocytes, an important chemokine receptor for monocyte migration to inflammatory sites, was associated with promoting inflammation and potentially contributing to tissue remodeling, relevant to the pathogenesis of chronic inflammatory diseases, including bronchitis. CD28+ CD45RA+ CD8+ activated cytotoxic T cells represented naive or early-differentiated cytotoxic T cells with high proliferative potential. Their activation in bronchitis might have reflected an ongoing immune response to pathogens, causing tissue damage through cytotoxic actions. The expression of CD80 on monocytes indicated a co-stimulatory role in T cell activation, while CD66b expression on granulocyte-like myeloid-derived suppressor cells suggested an immunosuppressive function. In bronchitis, these markers had highlighted the complex regulation of the immune response, balancing pathogen clearance and limiting tissue damage.[26] Activated cells lacking CD33 and HLA DR, along with CCR2 expression on myeloid dendritic cells, indicated subgroups with unique functions in bronchitis, such as tissue repair or fibrosis. The expression of CCR2 emphasized their role in migrating to inflammatory sites, contributing to the immune response in the lungs of bronchitis.[27] CD123 expression on plasmacytoid DCs, key producers of type I interferons, was crucial for antiviral defense. In bronchitis, their role might have extended to regulating immune responses to viruses and potentially bacterial pathogens, influencing the course of the disease.[28] In summary, the diverse roles of these immune cells and markers in bronchitis underscored the complexity of the immune response under this condition. Understanding these complex dynamics had provided potential therapeutic targets to modulate the immune response, aiming to reduce chronic inflammation, enhance pathogen clearance, and minimize airway damage in bronchitis. These studies had highlighted the significance of understanding the role of immune cells in bronchitis for improving prevention strategies and therapeutic interventions.

This study, through MR analysis, successfully revealed significant causal relationships between 28 types of immune cells and bronchitis. These findings have strengthened our understanding of the immunopathology of bronchitis and laid the groundwork for the development of new therapeutic approaches. Nevertheless, this study still has several limitations. Firstly, the relatively small sample size may limit the generalizability of the results. Secondly, due to technological and resource limitations, the study population was European, and we were unable to comprehensively analyze all possible subgroups of immune cells and cytokines involved. Furthermore, future research should further explore the direct interactions between immune cells and bronchitis and assess the dynamic changes in immune cell phenotypes across different populations and stages of treatment.

5. Conclusion

In this study, we identified immune cells associated with an increased risk of bronchitis, including IgD+ CD24‐ lymphocytes, CD25 on naive-mature B cells, and CD25 on B cells, which may have promoted inflammation and cell-mediated immune responses. Conversely, CD80 on monocytes, CD123 on plasmacytoid dendritic cells, and CCR2 on myeloid DCs exhibited protective roles, potentially contributing to immune balance and effective defense. These findings revealed the dual role of immune cells in bronchitis and pointed to the regulation of specific immune cell subgroups as a potential strategy for improving treatment outcomes. Future research will need to further explore the specific impacts of these cell phenotype changes on treatment to optimize therapeutic approaches for bronchitis.

Author contributions

Conceptualization: Zhiyu Tian, Zhanliang Jiang, Li Shi.

Data curation: Zhiyu Tian, Zhanliang Jiang, Li Shi.

Formal analysis: Zhiyu Tian, Li Shi.

Investigation: Zhiyu Tian.

Methodology: Zhiyu Tian.

Resources: Zhanliang Jiang, Li Shi.

Software: Zhanliang Jiang, Li Shi.

Supervision: Li Shi.

Validation: Li Shi.

Visualization: Li Shi.

Writing – original draft: Zhiyu Tian, Li Shi.

Writing – review & editing: Zhiyu Tian, Li Shi.

Supplementary Material

medi-103-e40541-s006.xlsx (106.3KB, xlsx)
medi-103-e40541-s007.xlsx (68.4KB, xlsx)

Abbreviations:

DCs
dendritic cells
GWAS
genome-wide association study
IVs
instrumental variables
MR
Mendelian randomization
SNPs
single nucleotide polymorphisms

The authors have no funding and conflicts of interest to disclose.

The datasets generated during and/or analyzed during the current study are publicly available.

Supplemental Digital Content is available for this article.

How to cite this article: Tian Z, Jiang Z, Shi L. Mendelian randomization analysis of two samples to determine the impact of immune cells on bronchitis. Medicine 2024;103:48(e40541).

Contributor Information

Zhiyu Tian, Email: 506744447@qq.com.

Zhanliang Jiang, Email: m15754377529@163.com.

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Associated Data

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Supplementary Materials

medi-103-e40541-s001.xlsx (4.1MB, xlsx)
medi-103-e40541-s002.tiff (1MB, tiff)
medi-103-e40541-s003.tiff (1.1MB, tiff)
medi-103-e40541-s004.tiff (1MB, tiff)
medi-103-e40541-s005.tiff (1.1MB, tiff)
medi-103-e40541-s006.xlsx (106.3KB, xlsx)
medi-103-e40541-s007.xlsx (68.4KB, xlsx)

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