Analyzing Gene Expression Profiles from Ataxia and Spasticity Phenotypes to Reveal Spastic Ataxia Related Pathways

Abstract

Spastic ataxia (SA) is a group of rare neurodegenerative diseases, characterized by mixed features of generalized ataxia and spasticity. The pathogenetic mechanisms that drive the development of the majority of these diseases remain unclear, although a number of studies have highlighted the involvement of mitochondrial and lipid metabolism, as well as calcium signaling. Our group has previously published the GBA2 c.1780G > C (p.Asp594His) missense variant as the cause of spastic ataxia in a Cypriot consanguineous family, and more recently the biochemical characterization of this variant in patients’ lymphoblastoid cell lines. GBA2 is a crucial enzyme of sphingolipid metabolism. However, it is unknown if GBA2 has additional functions and therefore additional pathways may be involved in the disease development. The current study introduces bioinformatics approaches to better understand the pathogenetic mechanisms of the disease. We analyzed publicly available human gene expression datasets of diseases presented with ‘ataxia’ or ‘spasticity’ in their clinical phenotype and we performed pathway analysis in order to: (a) search for candidate perturbed pathways of SA; and (b) evaluate the role of sphingolipid signaling pathway and sphingolipid metabolism in the disease development, through the identification of differentially expressed genes in patients compared to controls. Our results demonstrate consistent differential expression of genes that participate in the sphingolipid pathways and highlight alterations in the pathway level that might be associated with the disease phenotype. Through enrichment analysis, we discuss additional pathways that are connected to sphingolipid pathways, such as PI3K-Akt signaling, MAPK signaling, calcium signaling, and lipid and carbohydrate metabolism as the most enriched for ataxia and spasticity phenotypes.

Transcriptomic characterization of tissues from patients and subsequent pathway analyses reveal biological pathways that are implicated in spastic ataxia

“…We also highlight the most enriched pathways that result from the analyses performed. We finally report common candidate pathways to those that resulted from our previous work on the analysis of multiple gene expression datasets from ataxia and spasticity phenotypes [ 10 ], thus further supporting the implication of the hereby proposed pathways in SA.…”

“…The results of pathway enrichment analysis of the top 500 DEGs for each tissue were compared to the pathways identified through our previous work on gene expression data analysis derived from ataxia and spasticity phenotypes-related microarray datasets [ 10 ]. We compared the pathways from the two studies based on the tissue similarity (i.e.…”

Signaling pathways of genetic variants and miRNAs in the pathogenesis of myasthenia gravis

“…The key genes were defined as those with higher degrees of connectivity in PPIs, which were identified by a network topology analysis. The PathExNet tool was also used to isolate the genes that participate in each of the selected pathways based on KEGG 2019 along with the logFC and P value metrics, as provided by the differential expression analysis (13).…”

Effect of Expression of Human Glucosylceramidase 2 Isoforms on Lipid Profiles in COS-7 Cells

“…Although there is a database entry for a cDNA from substantia nigra mRNA for isoform X1, that does not really indicate the expression level of this isoform in that tissue. GBA2 has been noted to be under expressed in neurons in ataxia datasets, although alternative splicing was not considered [43]. In the future, it would be interesting to analyze the expression of specific isoforms in human tissues.…”