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. 2020 Nov 9:11:578143.
doi: 10.3389/fgene.2020.578143. eCollection 2020.

Key Molecules and Pathways Underlying Sporadic Amyotrophic Lateral Sclerosis: Integrated Analysis on Gene Expression Profiles of Motor Neurons

Jianing Lin  1 , Pian Huang  1 , Weineng Chen  1 , Chenghui Ye  2 , Huanxing Su  3 , Xiaoli Yao  1
Affiliations

Key Molecules and Pathways Underlying Sporadic Amyotrophic Lateral Sclerosis: Integrated Analysis on Gene Expression Profiles of Motor Neurons

Jianing Lin et al. Front Genet. .

Abstract

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder characterized by progressive loss of motor neurons. The complex mechanisms underlying ALS are yet to be elucidated, while the lack of disease biomarkers and therapeutic options are associated with the poor prognosis of ALS patients. In this study, we performed bioinformatics analysis to clarify potential mechanisms in sporadic ALS (sALS). We compared three gene expression profiles (GSE18920, GSE56500, and GSE68605) of motor neurons obtained from sALS patients and healthy controls to discover differentially expressed genes (DEGs), and then performed integrated bioinformatics analyses to identify key molecules and pathways underlying sALS. We found that these DEGs were mainly enriched in the structure and functions of extracellular matrix (ECM), while functional enrichment in blood vessel morphogenesis was less correlated with motor neurons. The clustered subnetworks of the constructed protein-protein interaction network for DEGs and the group of selected hub genes were more significantly involved in the organization of collagen-containing ECM. The transcriptional factors database proposed RelA and NF-κB1 from NF-κB family as the key regulators of these hub genes. These results mainly demonstrated the alternations in ECM-related gene expression in motor neurons and suggested the role of NF-κB regulatory pathway in the pathogenesis of sALS.

Keywords: FN1 gene; bioinformatics analysis; gene expression profiles; motor neurons; sporadic amyotrophic lateral sclerosis.

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Figures

FIGURE 1
FIGURE 1
The analysis of differentially expressed genes (DEGs) of multiple gene expression profiles by GEO2R. (A–C) The volcano plots of the distribution of multiple gene expression series, with red dots and blue dots indicating upregulated and downregulated genes, respectively. (D) Online Venn diagram tool was applied to discover the overlapping DEGs of three datasets.
FIGURE 2
FIGURE 2
Gene Ontology (GO) function and pathway enrichment analysis of all differentially expressed genes by Metascape. The results were colored by different GO terms.
FIGURE 3
FIGURE 3
Network analysis of differentially expressed genes (DEGs). (A) The protein-protein interaction (PPI) network of overlapping DEGs, in which thicker line indicates stronger data support. (B) The clustered subnetwork 1 identified from the whole PPI network. (C) Enrichment analysis of the cluster 1 by Metascape. (D) The clustered subnetwork 2 identified from the whole PPI network. (E) Enrichment analysis of the cluster 2 by Metascape.
FIGURE 4
FIGURE 4
The integrated bioinformatics analysis on hub genes. (A) Twenty hub genes were identified by the maximum correlation criterion scoring in Cytoscape. (B) The heat map of expression levels of 20 hub genes in the original gene expression series. Red indicated higher expression level in motor neurons in sALS compared with healthy controls, while green indicated lower expression level. (C) Enrichment analysis of the identified hub genes by Metascape. (D) The visualization of the hub genes and the functional group network constructed by the ClueGO and CluePedia plugin of Cytoscape. (E) Interactions between the predicted regulatory transcriptional factors and target genes.
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