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Inhibition of immunoglobulin E attenuates pulmonary hypertension

Nature Cardiovascular Research volume 1, pages 665–678 (2022)Cite this article

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Abstract

Pulmonary hypertension (PH) is a severe cardiopulmonary disease characterized by pulmonary vascular remodeling. Immunoglobulin E (IgE) is known to participate in aortic vascular remodeling, but whether IgE mediates pulmonary vascular disease is unknown. In the present study, we found serum IgE elevation in pulmonary arterial hypertension (PAH) patients, hypoxia-induced PH mice and monocrotaline-induced PH rats. Neutralizing IgE with an anti-IgE antibody was effective in preventing PH development in mice and rat models. The IgE receptor FcεRIα was also upregulated in PH lung tissues and Fcer1a deficiency prevented the development of PH. Single-cell RNA-sequencing revealed that FcεRIα was mostly expressed in mast cells (MCs) and MC-specific Fcer1a knockout protected against PH in mice. IgE-activated MCs produced interleukin (IL)-6 and IL-13, which subsequently promoted vascular muscularization. Clinically approved IgE antibody omalizumab alleviated the progression of established PH in rats. Using genetic and pharmacological approaches, we have demonstrated that blocking IgE–FcεRIα signaling may hold potential for PAH treatment.

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Fig. 1: Serum IgE levels in PAH patients and PH animal models.
Fig. 2: Blocking serum IgE attenuated the development experimental PH in mice and rats.
Fig. 3: Fcer1a deficiency attenuated hypoxia-induced PH in mice.
Fig. 4: FcεRIα expression in mast cells contributed to the development of PH in a mouse model.
Fig. 5: IgE-stimulated MCs to produce IL-6 and IL-13 in experimental PH.
Fig. 6: Anti-IgE therapy using omalizumab might prevent established PH development in MCT rats.
Fig. 7: Graphic abstract.

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Data availability

Sequencing data generated in the present study have been deposited at the Genome Sequence Archive (https://ngdc.cncb.ac.cn/gsa) and are publicly available at the date of publication. The accession nos. of scRNA-seq and RNA-seq data are CRA007001 and CRA007019, respectively. Additional data supporting the findings in the present study are included in the main article and associated files. Source data are provided with this paper.

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Acknowledgements

This project was supported by grants from the National Natural Science Foundation of China (grant no. 82000063 to Y.L.), the Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences (grant no. 2021-I2M-1-049 to J.W.), the Non-pit Central Research Institute Fund of Chinese Academy of Medical Sciences (grant nos. 2018JB31001 and 2019JB310001 to C.W.) and State Key Laboratory Special Fund (grant no. 2060204). We thank C. Yan (Department of Medicine, University of Rochester) for advice.

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Author notes

  1. These authors contributed equally: Ting Shu, Ying Liu, Yitian Zhou, Zhou Zhou.

Authors and Affiliations

  1. State Key Laboratory of Medical Molecular Biology, Department of Pathophysiology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China

    Ting Shu, Yitian Zhou, Bolun Li, Junling Pang, Xiaomin Song, Xin Ning, Jing Wang & Chen Wang

  2. State Key Laboratory of Medical Molecular Biology, Department of Physiology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China

    Ying Liu, Yanjiang Xing, Peiran Yang, Jinqiu Li, Xianmei Qi & Chen Wang

  3. Peking Union Medical College, MD Program, Beijing, China

    Yitian Zhou

  4. State Key Laboratory of Cardiovascular Disease, Beijing Key Laboratory for Molecular Diagnostics of Cardiovascular Diseases, Center of Laboratory Medicine, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China

    Zhou Zhou, Hang Yang & Qianlong Chen

  5. Department of Cardiology, Pulmonary Vascular Disease Center, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China

    Changming Xiong

  6. Transplant Center, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Jiangsu, China

    Jingyu Chen

  7. Department of Pharmacology and Tianjin Key Laboratory of Inflammatory Biology, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China

    Ying Yu

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Contributions

T.S. carried out investigations, methodology and visualization, and wrote the original draft. Y.L. carried out investigations, methodology, visualization and formal analysis. Y.Z. carried out investigations, created software, and did a formal analysis, data curation and visualization. Z.Z. provided resources, did a formal analysis and administered the project. P.Y. supervised the writing, review and editing of the paper. J.L. carried out investigations, validation and visualization. Y.X. carried out investigations and writing (review and editing). X.S. carried out validation and visualization. B.L. and J.P. created software and curated data. X.N. and X.Q. carried out investigations and validation. C.X. provided resources and carried out a formal analysis. H.Y. and Q.C. provided resources. J.C. supervised the project and provided resources. Y.Y. supervised the project and wrote, reviewed and edited the paper. J.W. and C.W. conceived and supervised the project, wrote, reviewed and edited the paper, administered the project and acquired funding.

Corresponding author

Correspondence to Jing Wang.

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Nature Cardiovascular Research thanks Wolfgang Kuebler and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Characterization of the hypoxia-induced PH mouse model and sample collection for scRNA-seq.

a. Schematic diagram for the hypoxia-induced PH mouse model in C57BL/6 mice and sample collection for scRNA-seq. b. RVSP of C57BL/6 mice before (H0w) and after 4 weeks of hypoxia (H4w). c. RV/LV + S of these mice. d. PA AT/ET of these mice. e. Representative image of H&E and α-SMA staining, scale bar=25μm. f. Quantification of wall thickness. g. Proportion of non-muscularized (N), partially muscularized (P), or full muscularized (F) pulmonary arterioles. All above quantitative results are shown as mean ± SEM, and difference between groups was evaluated by unpaired two-tailed t-test.

Source data

Extended Data Fig. 2 Bar plots of enriched GO pathways between pairs of time points.

Differentially enriched genes (DEGs) were calculated between two adjacent time points by Seurat and used to perform GO enrichment analysis employed by clusterProfiler package, whereas over representation analysis (ORA) was used for statistic test. P values was calculated by hypergeometric distribution and adjusted by FDR with Benjamini–Hochberg procedure controlled. The color in bar plots was coded by log-transformed P values.

Source data

Extended Data Fig. 3 ScRNA-seq revealed Th2 response and T cell-B cell interaction in hypoxia-induced mice PH model.

a. Cell cluster identification by Cd45, Cd3d and Cd4 enrichment on t-SNE plot. b. GO pathway enrichment bar plot of DEGs in Cd4+ T cells during hypoxia exposure. c. Flow cytometry quantification of CD3+ CD4+ T cells. (n = 5 mice in 0-week hypoxia and n = 8 mice in 4-week hypoxia). d. Flow cytometry quantification of CD4+ IL4+ T cells. (n = 5 mice in 0-week hypoxia and n = 8 mice in 4-week hypoxia). e. Relative mRNA expression of Il4 and Gata3 in CD4+ T cells (n = 4). f. Dot plot of the interaction of gene pairs between B cells and Cd4+ T cells (Cd40lg_CD40, Cd28_Cd86) in four hypoxia groups. g. Dot plots of the expression of Cd86, Cd40 in B cell (left), and Cd28, Cd40lg in Cd4+ T cell (right) in four hypoxia groups. h. Relative mRNA expression of Cd28 in CD4+ T cells and relative mRNA expression of Cd40 and Cd86 in CD19+ B cells (n = 4). For b, p value was calculated by hypergeometric distribution and adjusted by FDR with Benjamini–Hochberg procedure controlled. For c-e and h, quantitative results are shown as mean ± SEM and compared by unpaired two-tailed t-test.

Source data

Extended Data Fig. 4 Proportion changes in B cells subtypes from control and hypoxic lung.

a. Flow cytometry gate strategy for germinal center B cells, memory B cells, plasma cells and plasma blasts in lung tissues. b. Relative Aicda mRNA expression in sorted germinal center B cells (GC B cells) from control and hypoxic lungs. c. The proportion of memory B cells from control and hypoxic lungs. d. The proportion of IgE+ cells in memory B cell population. e. The proportion of plasma cells from control and hypoxic lungs. f. The proportion of plasma blasts from control and hypoxic lungs. g. Immunochemistry staining of CD138 in bronchovascular space from control and hypoxic lung. h. The proportion of IgE+ cells in B cell population in spleen from control and hypoxic mice. i. The proportion of IgE+ cells in B cell population in lymph node from control and hypoxic mice. All values are presented as the mean ± SEM. Difference between groups were evaluated by unpaired two-tailed t-test. n = 5 for each group. PA, pulmonary artery; Br, bronchus.

Source data

Extended Data Fig. 5 The efficiency of anti-IgE-neutralizing antibody in mice and rats.

a. Serum IgE levels in isotype control antibody- and anti-IgE antibody-treated mice under control or hypoxia. n = 5 for control groups, n = 8 for hypoxia groups. b. The representative pressure tracing waveform of RVSP in isotype control or anti-IgE treated mice. c. Serum IgE levels in isotype control antibody- and anti-IgE antibody-treated rats after saline or MCT injection. n = 6 for saline groups, n = 6 for MCT rat treated with isotype control, n = 8 for MCT rats treated with anti-IgE. d. The representative pressure tracing waveform of PAP in isotype control or anti-IgE treated rats. All above quantitative results are shown as mean ± SEM. Difference between multiple groups was evaluated by two-way ANOVA with Bonferroni’s post hoc test.

Source data

Extended Data Fig. 6 Bar plot of FCER1A mRNA levels for individual patients’ data.

Data were analyzed from published genome-wide expression data (GSE117261) through GEO2R. Donor, n = 23; PAH, n = 54, logFc=0.338, adj. p value=0.00706 adjusted by Benjamini & Hochberg (False discovery rate).

Source data

Extended Data Fig. 7 Immunofluorescence staining of FcεRIα in human lung tissues.

a. Representative images showing staining of tryptase (green) and FcεRIα (red) in lung sections of control subjects (non-PAH) and PAH patients. Scale bar=50 μm. b. Representative images showing staining of α-SMA (green) and FcεRIα (red) in lung sections of control subjects and PAH patients. Scale bar=50 μm. c. Representative images showing staining of CC10 (green) and FcεRIα (red) in lung sections of control subjects and PAH patients. Scale bar=50 μm. The arrows indicate examples of positive-staining cells. PA, pulmonary artery; AE, airway epithelium. For a-c, the same results were observed in 4 individual samples each group.

Extended Data Fig. 8 Immune cell proportions in WT and MCKO mice at basal level.

a. The proportion of CD45+ cells from indicated lungs. b. The proportion of CD19+ cells from indicated lungs. c. The proportion of CD3+ cells from indicated lungs. d. The proportion of CD11b+ cells in CD45+ population from indicated lungs. e. The proportion of CD11c+ cells in CD45+ population from indicated lungs. f. Quantification of tryptase+ cell numbers in lung tissues from indicated mice. g. Serum histamine levels from indicated mice. h. Serum IgE levels in KO mice model. i. Serum IgE levels in MCKO mice model. All values are presented as the mean ± SEM. For a-e, n = 4 for each group. Differences between groups were evaluated by unpaired two-tailed t-test. For f and g, n = 4 for control group. n = 7 for hypoxia group, for h and i, n = 4 for control groups, n = 6 for hypoxia groups. Differences between groups were evaluated by two-way ANOVA with Bonferroni’s post hoc test.

Source data

Extended Data Fig. 9 mRNA expression of Il6 and Il13 in mouse lung tissues.

a. Relative Il6 mRNA expression from lung tissues in anti-IgE treated mouse model. b. Relative Il13 mRNA expression from lung tissues in anti-IgE treated mouse model. c. Relative Il6 mRNA expression from lung tissues in KO mouse model. d. Relative Il13 mRNA expression from lung tissues in KO mouse model. e. Relative Il6 mRNA expression from lung tissues in MCKO mouse model. f. Relative Il13 mRNA expression from lung tissues in MCKO mouse model. All values are presented as the mean ± SEM and compared by two-way ANOVA with Bonferroni’s post hoc test. n = 4 for control groups, n = 6 for hypoxia groups.

Source data

Extended Data Fig. 10 mRNA and protein levels of IL6 and IL13 in rat lung tissues.

a. Relative Il6 mRNA expression from lung tissues in anti-IgE treated rat model. b. Relative Il13 mRNA expression from lung tissues in anti-IgE treated rat model. c. IL6 protein levels from lung tissues in anti-IgE treated rat model. d. IL13 protein levels from lung tissues in anti-IgE treated rat model. n = 4 for control groups, n = 6 for MCT groups. All values are presented as the mean ± SEM and compared by two-way ANOVA with Bonferroni’s post hoc test.

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Shu, T., Liu, Y., Zhou, Y. et al. Inhibition of immunoglobulin E attenuates pulmonary hypertension. Nat Cardiovasc Res 1, 665–678 (2022). https://doi.org/10.1038/s44161-022-00095-9

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