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. 2023 Oct 17:14:1275845.
doi: 10.3389/fimmu.2023.1275845. eCollection 2023.

Mucosal immune alterations at the early onset of tissue destruction in chronic obstructive pulmonary disease

Charlotte de Fays  1   2 , Vincent Geudens  2 , Iwein Gyselinck  2 , Pieterjan Kerckhof  2 , Astrid Vermaut  2 , Tinne Goos  2 , Marie Vermant  2 , Hanne Beeckmans  2 , Janne Kaes  2 , Jan Van Slambrouck  2 , Yousry Mohamady  2 , Lynn Willems  2 , Lucia Aversa  2 , Emanuela E Cortesi  2 , Charlotte Hooft  2 , Gitte Aerts  2 , Celine Aelbrecht  2 , Stephanie Everaerts  2 , John E McDonough  3 , Laurens J De Sadeleer  2 , Sophie Gohy  1   4 , Jerome Ambroise  5 , Wim Janssens  2 , Laurens J Ceulemans  2 , Dirk Van Raemdonck  2 , Robin Vos  2 , Tillie L Hackett  6 , James C Hogg  6 , Naftali Kaminski  3 , Ghislaine Gayan-Ramirez  2 , Charles Pilette  1   4 , Bart M Vanaudenaerde  2
Affiliations

Mucosal immune alterations at the early onset of tissue destruction in chronic obstructive pulmonary disease

Charlotte de Fays et al. Front Immunol. .

Abstract

Rationale: COPD is characterized by chronic airway inflammation, small airways changes, with disappearance and obstruction, and also distal/alveolar destruction (emphysema). The chronology by which these three features evolve with altered mucosal immunity remains elusive. This study assessed the mucosal immune defense in human control and end-stage COPD lungs, by detailed microCT and RNA transcriptomic analysis of diversely affected zones.

Methods: In 11 control (non-used donors) and 11 COPD (end-stage) explant frozen lungs, 4 cylinders/cores were processed per lung for microCT and tissue transcriptomics. MicroCT was used to quantify tissue percentage and alveolar surface density to classify the COPD cores in mild, moderate and severe alveolar destruction groups, as well as to quantify terminal bronchioles in each group. Transcriptomics of each core assessed fold changes in innate and adaptive cells and pathway enrichment score between control and COPD cores. Immunostainings of immune cells were performed for validation.

Results: In mildly affected zones, decreased defensins and increased mucus production were observed, along CD8+ T cell accumulation and activation of the IgA pathway. In more severely affected zones, CD68+ myeloid antigen-presenting cells, CD4+ T cells and B cells, as well as MHCII and IgA pathway genes were upregulated. In contrast, terminal bronchioles were decreased in all COPD cores.

Conclusion: Spatial investigation of end-stage COPD lungs show that mucosal defense dysregulation with decreased defensins and increased mucus and IgA responses, start concomitantly with CD8+ T-cell accumulation in mild emphysema zones, where terminal bronchioles are already decreased. In contrast, adaptive Th and B cell activation is observed in areas with more advanced tissue destruction. This study suggests that in COPD innate immune alterations occur early in the tissue destruction process, which affects both the alveoli and the terminal bronchioles, before the onset of an adaptive immune response.

Keywords: airway inflammation; chronic obstructive pulmonary disease; emphysema severity; lung mucosal immunity; lung tissue destruction.

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Conflict of interest statement

IG reports travel support from AstraZeneca, not related to the content of this work. MV reports travel support from Sanofi, not related to the content of this manuscript. SE reports consulting fees from GSK, lecture honoraria from GSK, Boehringer Ingelheim, Chiesi and AstraZeneca, travel support from GSK and Sanofi, not related to the content of this manuscript. WJ reports grants and lecture honoraria from AstraZeneca and Chiesi, consulting fees from AstraZeneca, Griffols, GSK and Chiesi and travel support from Chiesi and AstraZeneca; has a leadership or fiduciary role in Board of VRGT and Board of ArtiQ, and is a co-founder and shareholder of ArtiQ NV. NK served as consultant for Biogen Idec, Boehringer Ingelheim, Third Rock, Pliant, Samumed, NuMedii, Theravance, LifeMax, Three Lake Partners, Astra Zeneca, RohBar, Veracyte, Augmanity, CSL Behring, Thyron, BMS, Biotech, Gilead, Galapagos, Chiesi, Arrowhead, Sofinnova and GSK, reports equity in Pliant and Thyron, and has a patent in new therapies for IPF, new therapies for ARDS and new biomarkers for IPF, licensed to Biotech. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Schematic overview of the methodology. Unused donor and COPD explant lungs were inflated at total lung capacity and frozen. Four cores were sampled from each lung, and a high resolution microCT of each core was performed, for morphometric analysis. One piece of each core was used for RNA extraction. RNAseq data were used for differential gene expression analysis, pathway enrichment analysis and cellular deconvolution enrichment scores analysis. Another piece of each core was used for cell type immunostainings. Created with BioRender.com .
Figure 2
Figure 2
Classification of lung tissue cores according to emphysema severity. (A) Cores tissue percentage and surface density were determined based on microCT and used to define emphysema severity groups among COPD cores, separated by a dashed line (lower panel): mild COPD cores, moderate COPD cores and severe COPD cores, in addition to control cores (CT). A transversal section microCT of one representative core per group is presented (upper panel). Each point corresponds to individual core data. (B) Terminal bronchioles (TB) count in controls and COPD cores. Each point corresponds to individual core data, ***p<0.0005 vs controls (CT) by a linear mixed effects regression models including cores disease subgroups, age, and gender as fixed effect and patient as random effect (C) Volcano plots of differential gene expression data in mild COPD cores, moderate COPD cores and severe COPD cores as compared with controls. Top significant genes are labeled. Each point corresponds to individual core data. (D) PCA analysis with component 1 and 2 plotted. Each point corresponds to individual core data. (E) Venn diagram showing numbers of differentially expressed genes in each cores group comparison with controls.
Figure 3
Figure 3
Cores RNA-seq based transcriptome analysis. (A) Top differentially expressed genes in mild COPD cores, moderate COPD cores and severe COPD cores as compared to control cores (CT). *FDR<0.1, **FDR<0.01, ***FDR<0.001 vs controls by a multiple linear regression test including age and gender as variables. (B) Differential expression data of genes involved in antigen presentation and mucosal immunity. * FDR<0.1, **FDR<0.01, ***FDR<0.001 vs controls using a multiple linear regression test including age and gender as variables. (C) Significantly up- and downregulated pathways in mild COPD cores (left panel), moderate COPD cores (middle panel) and severe COPD cores (right panel) as compared with controls. * FDR<0.1, **FDR<0.01, ***FDR<0.001 versus controls by a multiple linear regression test including age and gender as variables. AMP, antimicrobial peptides; MHC, Major histocompatibility complex.
Figure 4
Figure 4
Immune cell types cores composition. (A) xCell enrichment scores of cell types involved in the adaptive immune response and fibroblasts in COPD, moderate and –severe cores as compared with controls cores (CT). Each point corresponds to individual core data, * FDR<0.1, **FDR<0.01, ***FDR<0.001 versus controls by a linear mixed effects regression models including cores disease subgroups, age, and gender as fixed effect and patient as random effect. (B, C) Adaptive immune cell types and fibroblasts immunostainings (log2-transformed staining index). Each point corresponds to individual core data, * p<0.05, **p<0.01, ***p<0.001 vs controls by a linear mixed effects regression models including cores disease subgroups, age, and gender as fixed effect and patient as random effect.
Figure 5
Figure 5
Mucosal immunity alterations and CD8+ T cells activation in mild COPD cores, followed by an adaptive IgA response in moderate and severe COPD cores. Gene expression data are in green, xCell deconvolution data are in blue, pathway enrichment data are in red. Created with BioRender.com .
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References

    1. Vos T, Lim SS, Abbafati C, Abbas KM, Abbasi M, Abbasifard M, et al. . Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet (2020) 396(10258):1204–22. doi: 10.1016/S0140-6736(20)30925-9 - DOI - PMC - PubMed
    1. Organization WH . The top 10 causes of death 2020. Available at: https://www.who.int/news-room/fact-sheets/detail/the-top-10-causes-of-death.
    1. Salvi SS, Barnes PJ. Chronic obstructive pulmonary disease in non-smokers. Lancet (London England). (2009) 374(9691):733–43. doi: 10.1016/S0140-6736(09)61303-9 - DOI - PubMed
    1. McDonough JE, Yuan R, Suzuki M, Seyednejad N, Elliott WM, Sanchez PG, et al. . Small-airway obstruction and emphysema in chronic obstructive pulmonary disease. New Engl J Med (2011) 365(17):1567–75. doi: 10.1056/NEJMoa1106955 - DOI - PMC - PubMed
    1. Viniol C, Vogelmeier CF. Exacerbations of COPD. Eur Respir Rev an Off J Eur Respir Soc (2018) 27(147):170103. doi: 10.1183/16000617.0103-2017 - DOI - PMC - PubMed

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The author(s) declare financial support was received for the research, authorship, and/or publication of this article. CdF was supported by Fondation Saint-Luc, Cliniques universitaires Saint-Luc, Brussels, Belgium. BV, WJ and GG-R are supported by the KU Leuven (C16/19/005). DV is supported by the Broere Charitable Foundation. RV is Senior Clinical Research Fellows of the Research Foundation Flanders (FWO; 12G8715N) and is supported by an UZ Leuven research grant (STG15/023). CP and SG are Researchers clinicians of the Fonds National de la Recherche Scientifique (FNRS; grants 1R016.20F and 1R01618, respectively). JK, IG, TG, MV and VG are junior research fellows of the Research Foundation Flanders, Belgium.