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. 2022 May 10:13:814303.
doi: 10.3389/fimmu.2022.814303. eCollection 2022.

Transcriptome-Wide Association Studies and Integration Analysis of mRNA Expression Profiles Identify Candidate Genes and Pathways Associated With Ankylosing Spondylitis

Ruoyang Feng  1 , Mengnan Lu  2 , Lin Liu  1 , Ke Xu  1 , Peng Xu  1
Affiliations

Transcriptome-Wide Association Studies and Integration Analysis of mRNA Expression Profiles Identify Candidate Genes and Pathways Associated With Ankylosing Spondylitis

Ruoyang Feng et al. Front Immunol. .

Abstract

This study aimed to identify susceptibility genes and pathways associated with ankylosing spondylitis (AS) by integrating whole transcriptome-wide association study (TWAS) analysis and mRNA expression profiling data. AS genome-wide association study (GWAS) summary data from the large GWAS database were used. This included data of 1265 AS patients and 452264 controls. A TWAS of AS was conducted using these data. The analysis software used was FUSION, and Epstein-Barr virus-transformed lymphocytes, transformed fibroblasts, peripheral blood, and whole blood were used as gene expression references. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed for the important genes identified via TWAS. Protein-protein interaction (PPI) network analysis based on the STRING database was also performed to detect genes shared by TWAS and mRNA expression profiles in AS. TWAS identified 920 genes (P <0.05) and analyzed mRNA expression profiles to obtain 1183 differential genes. Following comparison of the TWAS results and mRNA expression characteristics, we obtained 70 overlapping genes and performed GO and KEGG enrichment analyses of these genes to obtain 16 pathways. Via PPI network analysis, we obtained the protein interaction network and performed MCODE analysis to acquire the HUB genes. Similarly, we performed GO and KEGG analyses on the genes identified by TWAS, obtained 98 pathways after screening, and analyzed protein interactions via the PPI network. Through the integration of TWAS and mRNA expression analysis, genes related to AS and GO and KEGG terms were determined, providing new evidence and revealing the pathogenesis of AS. Our AS TWAS work identified novel genes associated with AS, as well as suggested potential tissues and pathways of action for these TWAS AS genes, providing a new direction for research into the pathogenesis of AS.

Keywords: ankylosing spondylitis; genome-wide association study (GWAS); mRNA expression profile; susceptibility genes; transcriptome-wide association study (TWAS).

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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
Venn diagram of genes obtained from TWAS identification in four: Gray, YBL; orange, NBL; blue, EL; pink, TF.
Figure 2
Figure 2
Manhattan plot of AS-associated genes identified by TWAS (colored dots). Each dot represents a gene, the x-axis is the physical location (chromosomal localization) and the y-axis is the -log10 (p-value) of the gene’s association with AS. Significant genes in different tissues/cells are highlighted in different colors (A, TF; B, EL; C, YBL; D, NBL).
Figure 3
Figure 3
Venn diagram of TWAS versus common genes identified by mRNA expression profiling. Gray, TWAS; Orange, DEGs.
Figure 4
Figure 4
Network diagram of GO term analysis for TWAS-identified genes, where each circular point in the network represents a term whose size is proportional to the number of input genes for that term. (A) KEGG; (B) BP; (C) CC; (D) MF.
Figure 5
Figure 5
GO term analysis network diagram for TWAS-identified genes, where each circular dot in the network represents a term whose size is proportional to the number of input genes for that term. (A) Common pathway; (B) Common genes enrichment pathways.
Figure 6
Figure 6
PPI network of the TWAS-identified genes and their functional exploration.
See this image and copyright information in PMC

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