Identifying significant genes and functionally enriched pathways in familial hypercholesterolemia using integrated gene co-expression network analysis

Abstract

Familial hypercholesterolemia (FH) is a monogenic lipid disorder which promotes atherosclerosis and cardiovascular diseases. Owing to the lack of sufficient published information, this study aims to identify the potential genetic biomarkers for FH by studying the global gene expression profile of blood cells. The microarray expression data of FH patients and controls was analyzed by different computational biology methods like differential expression analysis, protein network mapping, hub gene identification, functional enrichment of biological pathways, and immune cell restriction analysis. Our results showed the dysregulated expression of 115 genes connected to lipid homeostasis, immune responses, cell adhesion molecules, canonical Wnt signaling, mucin type O-glycan biosynthesis pathways in FH patients. The findings from expanded protein interaction network construction with known FH genes and subsequent Gene Ontology (GO) annotations have also supported the above findings, in addition to identifying the involvement of dysregulated thyroid hormone and ErbB signaling pathways in FH patients. The genes like CSNK1A1, JAK3, PLCG2, RALA, and ZEB2 were found to be enriched under all GO annotation categories. The subsequent phenotype ontology results have revealed JAK3I, PLCG2, and ZEB2 as key hub genes contributing to the inflammation underlying cardiovascular and immune response related phenotypes. Immune cell restriction findings show that above three genes are highly expressed by T-follicular helper CD4⁺ T cells, naïve B cells, and monocytes, respectively. These findings not only provide a theoretical basis to understand the role of immune dysregulations underlying the atherosclerosis among FH patients but may also pave the way to develop genomic medicine for cardiovascular diseases.

Keywords: DEGs; Familial hypercholesterolemia; Gene expression; Microarray; Network; PPI.

Fig. 1

A & B represents the volcano plots built based on their gene expression distribution across the different datasets. C&D shows the mean difference (MD) plots, which represents log2 fold change (FC) verses average log2 expression values. All the up and down regulated genes are shown in red and blue dots, respectively. E shows venny diagram representing the shared DEGs between the two expression datasets (GSE13985 and GSE6088).

Fig. 2

A. The PPI network showing interactions between FH genes through nodes and edges. B-E The scatterplots showing functional enrichment of DEGs against different GO-terms like biological processes (BP), molecular function (MF), and cellular components (CC) based their p-values. F. PPI network showing interactions between hub genes (red) interacting with known FH genes (in yellow).

Fig. 3

A. The Clustergram of Enrich tool shows the enrichment of FH genes under different GO terms like biological processes (BP), molecular function (MF), and cellular components (CC). The input genes are represented in columns and matrices represents the enriched terms of those genes. B. The volcano plots illustrating the significance of gene sets are represented by each dot against the odds ratios. x- and y- axes shows odds ratios and -log(p-value) of the each gene set, respectively. C. The network wiring shows interconnectivity between different pathways enriched by hub genes.

Fig. 4

A. Bar graph represents the significant pathways enriched by DEGs at a p-value of < 0.05. B. The thyroid hormone signaling pathway with red color boxes highlighting the hub genes.

Fig. 5

Open Target Platform based gene-disease phenotype analysis showing the association of JAK3, ZEB2 and PLCG2 genes with cardiac and immune related diseases. The disease names are mentioned in bubble, the shade and size of bubble color determine based on the gene-disease assocation score of > 0.1.

Fig. 6

DICE tool shows the expression restriction of (A) JAK3, (B) ZEB2 and (C) PLCG2 genes across 13 immune cells in the form of box plots and pairwise comaprsion graphs.