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. 2024 Sep 16:15:1424308.
doi: 10.3389/fimmu.2024.1424308. eCollection 2024.

Identification of common signature genes and pathways underlying the pathogenesis association between nonalcoholic fatty liver disease and heart failure

Gerui Li #  1   2   3 , Zhengjie Lu #  4 , Ze Chen  1   3
Affiliations

Identification of common signature genes and pathways underlying the pathogenesis association between nonalcoholic fatty liver disease and heart failure

Gerui Li et al. Front Immunol. .

Abstract

Background: Non-alcoholic fatty liver disease (NAFLD) and heart failure (HF) are related conditions with an increasing incidence. However, the mechanism underlying their association remains unclear. This study aimed to explore the shared pathogenic mechanisms and common biomarkers of NAFLD and HF through bioinformatics analyses and experimental validation.

Methods: NAFLD and HF-related transcriptome data were extracted from the Gene Expression Omnibus (GEO) database (GSE126848 and GSE26887). Differential analysis was performed to identify common differentially expressed genes (co-DEGs) between NAFLD and HF. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) were conducted to explore the functions and regulatory pathways of co-DEGs. Protein-protein interaction (PPI) network and support vector machine-recursive feature elimination (SVM-RFE) methods were used to screen common key DEGs. The diagnostic value of common key DEGs was assessed by receiver operating characteristic (ROC) curve and validated with external datasets (GSE89632 and GSE57345). Finally, the expression of biomarkers was validated in mouse models.

Results: A total of 161 co-DEGs were screened out in NAFLD and HF patients. GO, KEGG, and GSEA analyses indicated that these co-DEGs were mainly enriched in immune-related pathways. PPI network revealed 14 key DEGs, and SVM-RFE model eventually identified two genes (CD163 and CCR1) as common key DEGs for NAFLD and HF. Expression analysis revealed that the expression levels of CD163 and CCR1 were significantly down-regulated in HF and NAFLD patients. ROC curve analysis showed that CD163 and CCR1 had good diagnostic values for HF and NAFLD. Single-gene GSEA suggested that CD163 and CCR1 were mainly engaged in immune responses and inflammation. Experimental validation indicated unbalanced macrophage polarization in HF and NAFLD mouse models, and the expression of CD163 and CCR1 were significantly down-regulated.

Conclusion: This study identified M2 polarization impairment characterized by decreased expression of CD163 and CCR1 as a common pathogenic pathway in NAFLD and HF. The downregulation of CD163 and CCR1 may reflect key pathological changes in the development and progression of NAFLD and HF, suggesting their potential as diagnostic and therapeutic targets.

Keywords: bioinformatics; biomarker; heart failure; macrophage polarization; nonalcoholic fatty liver disease.

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Conflict of interest statement

The 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
Identification of co-differentially expressed genes (DEGs) between non-alcoholic fatty liver disease (NAFLD) and heart failure (HF). (A) Volcano plot showing DEGs between the NAFLD group and the healthy control group in GSE126848, with upregulated genes indicated in red and downregulated genes in blue. (B) Heatmap showing the result of clustering analysis based on the expression of NAFLD-DEGs in GSE126848. (C) Volcano plot showing DEGs between the HF group and the healthy control group in GSE26887, with upregulated genes indicated in red and downregulated genes in blue. (D) Heatmap showing the result of clustering analysis based on the expression of HF-DEGs in GSE26887. (E) Proportional Venn diagram depicting the co-DEGs by overlapping NAFLD-DEGs and HF-DEGs.
Figure 2
Figure 2
Gene ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) functional enrichment analysis of co-differentially expressed genes (DEGs). (A) The enriched GO-biological process (BP) terms. (B) The enriched GO-molecular function (MF) terms. (C) The enriched GO-cellular component (CC) terms. (D) The enriched KEGG pathways.
Figure 3
Figure 3
Gene Set Enrichment Analysis (GSEA) of co-differentially expressed genes (DEGs) in GSE126848 and GSE26887 datasets. (A, B) Biological processes found by GSEA in NAFLD (A) and normal (B) groups in GSE126848 dataset. (C, D) KEGG pathways enriched by GSEA in NAFLD (C) and normal (D) groups in GSE126848 dataset. (E, F) Biological processes found by GSEA in heart failure (E) and normal (F) groups in GSE26887 dataset. (G, H) KEGG pathways enriched by GSEA in heart failure (G) and normal (H) groups in GSE26887 dataset.
Figure 4
Figure 4
Identification of common key differentially expressed genes (DEGs). (A) Protein-protein interaction (PPI) network of co-DEGs. (B) The three significant modules in the PPI network found by MCODE plugin. (C) Top 20 genes based on the maximal clique centrality (MCC), maximum neighborhood component (MNC), Degree, and edge percolated component (EPC) algorithms, respectively. (D) Venn diagram showing the key DEGs obtained by taking the intersection set of the top 20 genes in the four algorithms. (E) Accuracy and error plots of SVM-RFE model in GSE126848 dataset. (F) Accuracy and error plots of SVM-RFE model in GSE26887 dataset. (G) Common key DEGs obtained by taking the intersection of the key DEGs in GSE126848 and GSE26887.
Figure 5
Figure 5
Validation and receiver operating characteristic (ROC) curve analyses of CCR1 and CD163 in heart failure (HF) and nonalcoholic fatty liver disease (NAFLD). (A–D) Expression of CCR1 and CD163 in GSE26887 (A), GSE57345 (B), GSE126848 (C), and GSE89632 (D), respectively. (E–H) ROC curve and area under the curve (AUC) of CCR1 and CD163 in GSE26887 (E), GSE57345 (F), GSE126848 (G), and GSE89632 (H), respectively. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001 vs. healthy controls.
Figure 6
Figure 6
Gene Set Enrichment Analysis (GSEA) of CCR1 and CD163 in GSE126848 and GSE26887 datasets. (A, B) Biological processes (A) and KEGG pathways (B) found by singe-gene GSEA of CCR1 in NAFLD dataset GSE126848. (C, D) Biological processes (C) and KEGG pathways (D) found by singe-gene GSEA of CD163 in NAFLD dataset GSE126848. (E, F) Biological processes (E) and KEGG pathways (F) found by singe-gene GSEA of CCR1 in HF dataset GSE26887. (G, H) Biological processes (G) and KEGG pathways (H) found by singe-gene GSEA of CD163 in HF dataset GSE26887.
Figure 7
Figure 7
Interaction of CCR1 and CD163 with inflammatory genes and chemical drugs. (A) Regulatory network of CCR1 and CD163 and their co-expression genes constructed by the GeneMANIA database. (B, C) The correlation between CCR1 and CD163 with inflammation-related genes in the GSE126848 (B) and GSE26887 (C) datasets. (D) The interactions between CCR1 and CD163 with chemicals and proteins constructed by the STITCH database.
Figure 8
Figure 8
Validation of CCR1 and CD163 in a non-alcoholic fatty liver disease mouse model. (A) Hematoxylin&eosin (H&E) staining of liver tissues in mice with normal chow (10% of calorie from fat, NC) or high-fat diet (60% of calorie from fat, HFD) for 14 weeks. The black arrow indicates infiltrated immune cells. Scale bar = 100 μm. (B) NAFLD activity score (NAS) based on the H&E staining of liver tissues. (C) Hepatic triglyceride (TG) concentrations. (D) Serum alanine aminotransferase (ALT) levels. (E) Relative mRNA expression level of inflammatory marker genes in liver tissues. (F–I) Relative mRNA expression level of Ccr1 (F), Cd163 (G), Cd80 (H), and Cd206 (I) in liver tissues. (J) Representative images under fluorescence microscopy showing CD163 staining (red) and nuclear staining (DIPA, blue) of liver tissues. Scale bar = 100 μm. (K) Representative images under fluorescence microscopy showing CD80 staining (red) and nuclear staining (DIPA, blue) of liver tissues. Scale bar = 100 μm. Mean ± S.E.M., n = 12. * P<0.05, ** P<0.01 vs. the NC group.
Figure 9
Figure 9
Validation of CCR1 and CD163 in a heart failure with reduced ejection fraction (HFpEF) mouse model. (A) Wheat germ agglutinin (WGA, green) staining of heart tissues in mice with saline (CON group) or uninephrectomy surgery followed by 0.15mg/h d-aldosterone (HFpEF group) treatment for 4 weeks. Scale bar = 100 μm. (B) Quantitative results of the left ventricular cross-sectional area based on the WGA staining of heart tissues. (C) Heart weight/body weight (HW/BW) ratio. (D–F) Relative mRNA expression level of left ventricular hypertrophy markers Anp (D), Bnp (E), and β-MHC (F) in heart tissues. (G) Relative mRNA expression level of inflammatory marker genes in heart tissues. (H–K) Relative mRNA expression level of Ccr1 (H), Cd163 (I), Cd80 (J), and Cd206 (K) in heart tissues. (L) Representative images under fluorescence microscopy showing CD163 staining (red) and nuclear staining (DIPA, blue) of heart tissues. Scale bar = 100 μm. (M) Representative images under fluorescence microscopy showing CD80 staining (red) and nuclear staining (DIPA, blue) of heart tissues. Scale bar = 100 μm. Mean ± S.E.M., n = 6. * P<0.05, ** P<0.01 vs. the control group.
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Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This study was supported by the National Natural Science Foundation of China (82200974 and 32400947) and Hubei Provincial Natural Science Foundation of China (2023AFB217).