RNAmetasome network for macromolecule biogenesis in human cells

Identification of hub genes based on integrated analysis of single-cell and microarray transcriptome in patients with pulmonary arterial hypertension

BACKGROUND

Pulmonary arterial hypertension (PAH) is a devastating chronic cardiopulmonary disease without an effective therapeutic approach. The underlying molecular mechanism of PAH remains largely unexplored at single-cell resolution.

METHODS

Single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database (GSE210248) was included and analyzed comprehensively. Additionally, microarray transcriptome data including 15 lung tissue from PAH patients and 11 normal samples (GSE113439) was also obtained. Seurat R package was applied to process scRNA-seq data. Uniform manifold approximation and projection (UMAP) was utilized for dimensionality reduction and cluster identification, and the SingleR package was performed for cell annotation. FindAllMarkers analysis and ClusterProfiler package were applied to identify differentially expressed genes (DEGs) for each cluster in GSE210248 and GSE113439, respectively. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) were used for functional enrichment analysis of DEGs. Microenvironment Cell Populations counter (MCP counter) was applied to evaluate the immune cell infiltration. STRING was used to construct a protein-protein interaction (PPI) network of DEGs, followed by hub genes selection through Cytoscape software and Veen Diagram.

RESULTS

Nineteen thousand five hundred seventy-six cells from 3 donors and 21,896 cells from 3 PAH patients remained for subsequent analysis after filtration. A total of 42 cell clusters were identified through UMAP and annotated by the SingleR package. 10 cell clusters with the top 10 cell amounts were selected for consequent analysis. Compared with the control group, the proportion of adipocytes and fibroblasts was significantly reduced, while CD8+ T cells and macrophages were notably increased in the PAH group. MCP counter revealed decreased distribution of CD8+ T cells, cytotoxic lymphocytes, and NK cells, as well as increased infiltration of monocytic lineage in PAH lung samples. Among 997 DEGs in GSE113439, module 1 with 68 critical genes was screened out through the MCODE plug-in in Cytoscape software. The top 20 DEGs in each cluster of GSE210248 were filtered out by the Cytohubba plug-in using the MCC method. Eventually, WDR43 and GNL2 were found significantly increased in PAH and identified as the hub genes after overlapping these DEGs from GSE210248 and GSE113439.

CONCLUSION

WDR43 and GNL2 might provide novel insight into revealing the new molecular mechanisms and potential therapeutic targets for PAH.

Genome-wide association study of SNP- and gene-based approaches to identify susceptibility candidates for lupus nephritis in the Han Chinese population

Background

Lupus nephritis (LN) is one of the most common and serious complications of systemic lupus erythaematosus (SLE). Genetic factors play important roles in the pathogenesis of LN and could be used to predict who might develop LN. The purpose of this study was to screen for susceptible candidates of LN across the whole genome in the Han Chinese population.

Methods

592 LN patients and 453 SLE patients without renal damage were genotyped at 492,970 single nucleotide polymorphisms (SNPs) in the genome-wide association study (GWAS). Fifty-six SNPs were selected for replication in an independent cohort of 188 LN and 171 SLE without LN patients. Further quantitative real-time (qRT) PCR was carried out in 6 LN patients and 6 healthy controls. Gene-based analysis was conducted using the versatile gene-based test for GWAS. Subsequently, enrichment and pathway analyses were performed in the DAVID database.

Results

The GWAS analysis and the following replication research identified 9 SNPs showing suggestive correlation with LN (P<10-4). The most significant SNP was rs12606116 (18p11.32), at P=8.72×10−6. The qRT-PCR results verified the mRNA levels of LINC00470 and ADCYAP1, the closest genes to rs12606116, were significantly lower in LN patients. From the gene-based analysis, 690 genes had suggestive evidence of association (P<0.05), including LINC00470. The enrichment analysis identified the involvement of transforming growth factor beta (TGF-β) signalings in the development of LN. Lower plasma level of TGF-β1 (P<0.05) in LN patients and lower expression of transforming growth factor beta receptor 2 in lupus mice kidney (P<0.05) futher indicate the involvement of TGF-β in LN.

Conclusions

Our analyses identified several promising susceptibility candidates involved in LN, and further verification of these candidates was necessary.