Potential biomarker identification for Friedreich's ataxia using overlapping gene expression patterns in patient cells and mouse dorsal root ganglion

Abstract

Friedreich's ataxia (FA) is a neurodegenerative disease with no approved therapy that is the result of frataxin deficiency. The identification of human FA blood biomarkers related to disease severity and neuro-pathomechanism could support clinical trials of drug efficacy. To try to identify human biomarkers of neuro-pathomechanistic relevance, we compared the overlapping gene expression changes of primary blood and skin cells of FA patients with changes in the Dorsal Root Ganglion (DRG) of the KIKO FA mouse model. As DRG is the primary site of neurodegeneration in FA, our goal was to identify which changes in blood and skin of FA patients provide a 'window' into the FA neuropathomechanism inside the nervous system. In addition, gene expression in frataxin-deficient neuroglial cells and FA mouse hearts were compared for a total of 5 data sets. The overlap of these changes strongly supports mitochondrial changes, apoptosis and alterations of selenium metabolism. Consistent biomarkers were observed, including three genes of mitochondrial stress (MTIF2, ENO2), apoptosis (DDIT3/CHOP), oxidative stress (PREX1), and selenometabolism (SEPW1). These results prompted our investigation of the GPX1 activity as a marker of selenium and oxidative stress, in which we observed a significant change in FA patients. We believe these lead biomarkers that could be assayed in FA patient blood as indicators of disease severity and progression, and also support the involvement of mitochondria, apoptosis and selenium in the neurodegenerative process.

Fig 1. The overlap between human FA fibroblasts, human FA lymphocytes, KIKO mouse DRG, KIKO mouse heart and KIKO mouse glia cells (p < .05).

Genes overlapping in 4/5 analyses passed to the next level of analysis.

Fig 2. The 87 genes that were significantly changed in 4/5 experiments are shown as a heat map (Red = negative value, green = positive value, black = not significant).

Lymphocyctes, fibroblasts, glia, and heart samples are all expressed as FA/Control. Mouse DRGs are analyzed as a FXN correlation, (-1)x logFC of gene/FXN expression. Outlined genes in the gene column were significant in all 5 datasets.

Fig 3. STRING network analysis of the 87 genes showing 3 clusters.

Cluster 1 is primarily composed of the 10 genes significantly associated with regulation of apoptosis (FDR = .03). Cluster 2 is primarily composed of RNA transcription and mitochondrial translation related genes. Cluster 3 is primarily composed of selenium and glutathione metabolism genes.

Fig 4. Cluster 3 genes include SEPW1, GPX7, and TXNRD1 which are significantly altered in 4/5 experiments (p<0.05).

Fig 4a. In the mouse DRG SEPW1 expression is significantly correlated with FXN expression (r = 0.59) (FDR = 0.035). Fig 4b. GPX7 is not significantly correlated with FXN expression in mouse DRG (r = 0.28, FDR = 0.33). Fig 4c. TXNRD1 is significantly correlated with FXN expression in mouse DRG (r = -0.55, FDR = 0.04). Fig 4d. SELM is significantly correlated with FXN expression in mouse DRG (r = 0.6, FDR = 0.035). Fig 4e. ANPEP is significantly correlated with FXN expression (r = 0.69, FDR = 0.035).

Fig 5. Glutathione peroxidase activity in whole blood was significantly increased in FA patients compared to controls (p = .047).