Comprehensive Analysis of scRNA-Seq and Bulk RNA-Seq Reveals Transcriptional Signatures of Macrophages in Intrahepatic Cholestasis of Pregnancy

Abstract

Purpose: Intrahepatic cholestasis of pregnancy (ICP) is a disorder that characterized by maternal pruritus, abnormal liver function, and an elevation in total bile acid concentrations during pregnancy. Immune factors have been recognized as playing a vital role in the mechanism of ICP. However, the underlying mechanisms regulating dysfunctional immune cells and immune genes remain to be fully elucidated.

Patients and methods: Single-cell RNA sequencing and bulk RNA sequencing data of the placenta were downloaded from the SRA database. The AUCell package, Monocle package and SCENIC package were utilized to explored immune cell activity, cell trajectory and transcription factor, respectively. GO, KEGG, and GSEA were employed to explore potential biological mechanisms. Cell-cell communications were further investigated using the CellChat package. RT-PCR, and Western blot were used to verify the gene expression in placenta.

Results: In placenta cells, macrophages were found to be significantly increased in ICP. Additionally, macrophages exhibited the highest immune gene score and were divided into four subclusters (MF1-4). Our analysis revealed significant elevations in MF2, associated with LPS response and antigen presentation, and MF4, associated with TNF and cytokine production. MF3 displayed an anti-inflammatory phenotype. MF1, closely related to ribosomes and proteins, exhibited a sharp decrease. Although ICP maintained an anti-inflammatory state, macrophage trajectories showed a gradual progression toward inflammation. Subsequently, we confirmed that cytokine- and chemokine-related signaling pathways were emphasized in macrophages. Within the CXCL signaling pathway, the increased expression of CXCL1 in macrophages can interact with CXCR2 in neutrophils, potentially inducing macrophage infiltration, stimulating neutrophil chemotaxis, and leading to an inflammatory response and cellular damage.

Conclusion: In conclusion, we firstly revealed the transcriptional signatures of macrophages in ICP and discovered a tendency toward an inflammatory state. This study also provides new evidence that the CXCL1-CXCR2 axis may play an important role in the pathogenesis of ICP.

Keywords: bulk RNA-Seq; immune gene; intrahepatic cholestasis of pregnancy; macrophage; scRNA-Seq.

Figure 1

Placenta cells in ICP. (A) UMAP analysis of scRNA-seq data. (B) Violin plot of marker genes in placenta cells. (C) FeaturePlot of marker genes in trophoblast cells. VCT (markers: KRT7, PEG10, EGFR, CYP19A1, CDH1), SVT (markers: KRT7, CSH2, CGA, CYP19A1, CSH1), EVT (markers: KRT7, HLA-G, CDH1, CSH1). (D) Clusters annotation and cell types identification via UMAP. (E) Cell distribution in control and ICP groups. (F) Score of 271 screened immunogene. The threshold was chosen as 0.28. (G) UMAP of Immunogene score in all clusters. As regulon is conceptually defined as a set of target genes regulated by a transcription factor, AUC values represent the activity of Regulons in cells. Macrophage and DC cells express more genes and exhibit higher AUC values. (H) Subcluster of macrophages via UMAP. (I) Distribution of Macrophages in each group. (J) Subcluster of macrophages in each group.

Figure 2

Enrichment analysis of macrophages in ICP. (A) Marker gene expression of each subcluster in macrophage. (B–E) The top 4 GO analysis and KEGG analysis of DEGs in MF1, MF2, MF3 and MF4 cluster. GO analysis includes three parts: Molecular Function (MF), Biological Process (BP) and CellComponent (CC). (F–I) GSVA analysis of MF1, MF2, MF3 and MF4 cluster.

Figure 3

Trajectory analysis and transcription factor regulatory network of macrophages. (A) Cell distribution in each cluster. (B) Cell trajectory analysis of macrophages. (C) Heatmap of the inferred transcription-factor gene-regulatory networks of macrophages. (D) Regulon Specificity Score (RSS) is calculated to evaluate macrophage specificity. The dot size represents the RSS, higher RSS indicates stronger association between transcription factors and Regulon, besides, z-score can compare the specificity of the same regulon between different cell types.

Figure 4

Placenta genes from SRP378990 dataset. (A) Volcano plot of DEGs in Bulk RNA-seq data. Up-regulated genes and down-regulated genes were colored in red. (B) The top 3 GO and KEGG of analysis of DEGs in SRP378990 dataset. (C) GSEA analysis of Cytokine-cytokine receptor interaction in SRP378990 dataset.

Figure 5

Cell-cell communication changes in cytokine related pathways. In cell-cell communication, the pathways revolved around cytokine includes IL10, IL6, TNF signaling pathways. (A) Chord diagram of IL10 signaling pathway network in placenta cell-cell communication. (B) Gene expression of IL10 signaling pathway in placenta cell-cell communication. (C) Expression of gene IL10RA in Bulk RNA-seq data. (D and E) Circle plot of IL6 and TNF signaling pathway network in placenta cell-cell communication. (F and G) Gene expression of IL6 and TNF signaling pathway in placenta cell-cell communication. (H and I) Expression of gene IL6, IL6ST, TNF, TNFRSF1A and TNFRSF1B in scRNA-seq data. (J) Enrichment degree of cellular pathways in macrophage subgroups. (K) Chord diagram of IL10 signaling pathway network in cell-cell communication of macrophage subgroups.

Figure 6

Cell-cell communication changes in chemokine related pathways. In cell-cell communication, the pathways revolved around chemokine includes CCL and CXCL signaling pathways. (A) Circle plot of CCL signaling pathway network in cell-cell communication. (B) Gene expression of CCL signaling pathway in cell-cell communication. (C) Circle plot of CXCL signaling pathway network in cell-cell communication. (D) Gene expression of CXCL signaling pathway in cell-cell communication. In ICP, the expression of CXCL1 is enhanced in macrophage. (E) Bubble plot of ligand receptor pairs of macrophages interacting with other cells. CXCL1-CXCR2, the ligand receptor of macrophages and neutrophils, is elevated in ICP.

Figure 7

Expression of gene CXCL1 and CXCR2 in ICP. (A) FeaturePlot of gene CXCL1 in macrophages. (B) The cell trajectory of CXCL1 in macrophages. (C) Expression of gene CXCL1 and CXCR2 in Bulk RNA-seq data.(D) The QRT-PCR data shows the gene expression levels of CXCL1 and CXCR2 in control and ICP placentas (n = 5 in the control group and ICP group). * P < 0.05,** P < 0.01. (E) Western blot data shows the gene expression levels of CXCL1 and CXCR2 in control and ICP placentas (n = 5 in the control group and ICP group).