Differential gene expression patterns in Niemann-Pick Type C and Tay-Sachs diseases: Implications for neurodegenerative mechanisms

Abstract

Lysosomal storage disorders (LSDs) are a group of rare genetic conditions characterized by the impaired function of enzymes responsible for lipid digestion. Among these LSDs, Tay-Sachs disease (TSD) and Niemann-Pick type C (NPC) may share a common gene expression profile. In this study, we conducted a bioinformatics analysis to explore the gene expression profile overlap between TSD and NPC. Analyses were performed on RNA-seq datasets for both TSD and NPC from the Gene Expression Omnibus (GEO) database. Datasets were subjected to differential gene expression analysis utilizing the DESeq2 package in the R programming language. A total of 147 differentially expressed genes (DEG) were found to be shared between the TSD and NPC datasets. Enrichment analysis was then performed on the DEGs. We found that the common DEGs are predominantly associated with processes such as cell adhesion mediated by integrin, cell-substrate adhesion, and urogenital system development. Furthermore, construction of protein-protein interaction (PPI) networks using the Cytoscape software led to the identification of four hub genes: APOE, CD44, SNCA, and ITGB5. Those hub genes not only can unravel the pathogenesis of related neurologic diseases with common impaired pathways, but also may pave the way towards targeted gene therapy of LSDs.In addition, they serve as the potential biomarkers for related neurodegenerative diseases warranting further investigations.

Fig 1. An overview of all the performed analyses.

Fig 2. Quality control boxplot for TSD RNA-seq raw versus normalized counts using the DESeq2 package.

Fig 3. Quality control boxplot for NPC RNA-seq raw versus normalized counts using the DESeq2 package.

Fig 4. Volcano plots for TSD and NPC datasets.

The volcano plot shows the spread of differentially expressed genes based on their LFC and padj values.

Fig. 5. (a, b) MD plots for NPC and TSD, and (c, d) dispersion plots for NPC and TSD. In the MD plots, the vertical axis (y-axis) represents the log fold-change, where positive values indicate upregulated genes and negative values indicate downregulated genes in one condition. The horizontal axis (x-axis) represents the average gene expression across the two conditions, normalized and log10-transformed. In the dispersion plots, the x-axis shows the mean of normalized reads, and the y-axis represents the dispersion estimates. A well-fitted trend line is observed in both conditions.

Fig 6. Venn diagram showing the overlap between TSD and NPC.

A total of 147 DEGs were found to be shared. The diagram was generated using ggplot2.

Fig 7. Enriched GO terms for the identified DEGs for TSD and NPC.

a) Biological Process b) Cellular Component c) Molecular Function d) KEGG Pathways.

Fig 8. Significant clusters within the DEG network using the MCODE plugin in Cytoscape.

Three cluster were identified with the MCODE 3. The third cluster (c) was found to be the most significant cluster.

Fig 9. Enriched KEGG pathways for the highest scoring MCODE cluster within the constructed DEG network.

Most of the top pathways are related to the metabolism of amino acids. a) GO-BP b) KEGG pathways.

Fig 10. GO and KEGG pathway analyses for the combined MCODE clusters.

a) GO-MF b) KEGG c) GO-CC d) GO-BP.

Fig 11. Identification of hub genes with six different algorithms using the CytoHubba plugin in Cytoscape.

Fig 12. Enriched GO terms for the 4 identified hub genes.

a) Biological Process b) Cellular Component c) Molecular Function d) KEGG Pathways.

Fig 13. Gene-gene interaction network generated based on the four identified hub genes using the GeneMANIA platform

http://genemania.org/. Nodes represent genes, with node size reflecting interaction degree, and edges represent functional associations (e.g., physical interactions, co-expression, pathway involvement). Edge colors indicate different types of interactions, as detailed in the legend. Central hub genes, including APOE, CD44, SNCA, and ITGB5, show high connectivity.