Macrophages as determinants and regulators of systemic sclerosis-related interstitial lung disease

Abstract

Background: Interstitial lung disease (ILD) is the primary cause of mortality in systemic sclerosis (SSc), an autoimmune disease characterized by tissue fibrosis. SSc-related ILD (SSc-ILD) occurs more frequently in females aged 30-55 years, whereas idiopathic pulmonary fibrosis (IPF) is more prevalent in males aged 60-75 years. SSc-ILD occurs earlier than IPF and progresses rapidly. FCN1, FABP4, and SPP1 macrophages are involved in the pathogenesis of lung fibrosis; SPP1 macrophages demonstrate upregulated expression in both SSc-ILD and IPF. To identify the differences between SSc-ILD and IPF using single-cell analysis, clarify their distinct pathogeneses, and propose directions for prevention and treatment.

Methods: We performed single-cell RNA sequencing on NCBI Gene Expression Omnibus (GEO) databases GSE159354 and GSE212109, and analyzed lung tissue samples across healthy controls, IPF, and SSc-ILD. The primary measures were the filtered genes integrated with batch correction and annotated cell types for distinguishing patients with SSc-ILD from healthy controls. We proposed an SSc-ILD pathogenesis using cell-cell interaction inferences, and predicted transcription factors regulating target genes using SCENIC. Drug target prediction of the TF gene was performed using Drug Bank Online.

Results: A subset of macrophages activates the MAPK signaling pathway under oxidative stress. Owing to the lack of inhibitory feedback from ANNEXIN and the autoimmune characteristics, this leads to an earlier onset of lung fibrosis compared to IPF. During initial lung injury, fibroblasts begin to activate the IL6 pathway under the influence of SPP1 alveolar macrophages, but IL6 appears unrelated to other inflammatory and immune cells. This may explain why tocilizumab (an anti-IL6-receptor antibody) only preserves lung function in patients with early SSc-ILD. Finally, we identified BCLAF1 and NFE2L2 as influencers of MAPK activation in macrophages. Metformin downregulates NFE2L2 and could serve as a repurposed drug candidate.

Conclusions: SPP1 alveolar macrophages play a role in the profibrotic activity of IPF and SSc-ILD. However, SSc-ILD is influenced by autoimmunity and oxidative stress, leading to the continuous activation of MAPK in macrophages. This may result in an earlier onset of lung fibrosis than in IPF. Such differences could serve as potential research directions for early prevention and treatment.

Keywords: IL6; Lung fibrosis; MAPK; Macrophage; SSc-ILD; Systemic sclerosis.

Fig. 1

Single-cell RNA-sequencing analysis of lung samples from sysetmic sclerosis (SSc), idiopathic pulmonary fibrosis (IPF) and healthy controls (HCs). A Overview of study design and analysis. B–F Overview of the scRNAseq landscape of GSE159354. Markers were used to identify the clusters and differences among the SSc-ILD, IPF, and HC groups. B The analyzed cell counts of the SSc-ILD, IPF, and HC groups. UMAP of samples from the (C) SSc-ILD and HC group and (D) IPF and HC group. E Enriched ontology clusters of all samples. F Bar plots showing the KEGG pathways of macrophages in SSc-ILD and IPF. Illustrations in A were created using BioRender (http://biorender.com)

Fig. 2

Single-cell RNA-sequencing analysis of monocyte/macrophage from systemic sclerosis (SSc). A–C Overview of the scRNAseq landscape of GSE159354. A Differential expression of key gene heatmap across cluster 4-alveolar macrophage, cluster 2-monocyte, and cluster 7-macrophage of SSc-ILD. B Violin plots showing the differential expression of key genes across cluster 2-monocyte, cluster 4-alveolar macrophage, and cluster 7-macrophage of SSc-ILD. C Suggested trajectory from monocytes, macrophage, and alveolar macrophages of SSc-ILD on the 2D map. D, E Overview of the scRNAseq landscape of GSE212109. Markers were used to identify the clusters and differences between SSc-ILD and HC. D UMAP of samples from the SSc-ILD and HC group. E Violin plots showing the differential expression of key genes across clusters 1, 3, 12, and 26

Fig. 3

Functional differences between cell cluster interactions for candidate signaling pathways. A River plots of outgoing and incoming signal between cell clusters in SSc. B Heatmap highlighting the differential cell interaction strengths of outgoing and incoming signals. C–J Plots showing cell–cell interaction and strength for specific pathways, including (C) UGPR1, (D) COMPLEMENT, (E) SAA, (F) SPP1, (G) BAFF, (H) VEGF, (I) VISFATIN, and (J) IL6. K Heatmap illustrating cell–cell interaction and strength of ANNEXIN signaling pathway. L Graphical abstract of the lung single-cell interaction map of SSc-ILD. Illustrations were created using BioRender (http://biorender.com)

Fig. 4

Regulons (transcription factor and downstream target genes) identified using SCENIC. A Heatmap of upregulated regulons of macrophages in samples of SSc-ILD. The AUC and binary matrix. B The upregulated regulons of macrophages overlapping with the MAPK pathway. C Networks of transcription factors and downstream target genes