Integrated gene expression profiling and functional enrichment analyses to discover biomarkers and pathways associated with Guillain-Barré syndrome and autism spectrum disorder to identify new therapeutic targets

Abstract

Guillain-Barré syndrome (GBS) is one of the most prominent and acute immune-mediated peripheral neuropathy, while autism spectrum disorders (ASD) are a group of heterogeneous neurodevelopmental disorders. The complete mechanism regarding the neuropathophysiology of these disorders is still ambiguous. Even after recent breakthroughs in molecular biology, the link between GBS and ASD remains a mystery. Therefore, we have implemented well-established bioinformatic techniques to identify potential biomarkers and drug candidates for GBS and ASD. 17 common differentially expressed genes (DEGs) were identified for these two disorders, which later guided the rest of the research. Common genes identified the protein-protein interaction (PPI) network and pathways associated with both disorders. Based on the PPI network, the constructed hub gene and module analysis network determined two common DEGs, namely CXCL9 and CXCL10, which are vital in predicting the top drug candidates. Furthermore, coregulatory networks of TF-gene and TF-miRNA were built to detect the regulatory biomolecules. Among drug candidates, imatinib had the highest docking and MM-GBSA score with the well-known chemokine receptor CXCR3 and remained stable during the 100 ns molecular dynamics simulation validated by the principal component analysis and the dynamic cross-correlation map. This study predicted the gene-based disease network for GBS and ASD and suggested prospective drug candidates. However, more in-depth research is required for clinical validation.

Communicated by Ramaswamy H. Sarma

KEY POINTS

• 17 common differentially expressed genes (DEGs) were identified from 693 DEGs of the GBS dataset (GSE72748) and 365 DEGs of the ASD dataset (GSE113834), which is the preliminary part of this investigation.

• From the PPI network analysis, a total of 10 hub genes were identified and two common DEGs named CXCL9 and CXCL10 were found in both the hub gene and essential module analysis.

• The identified leading pathways and GO pathways, TF-gene interaction, and TF-miRNAs network has made the process more relevant and appropriate for suggesting probable drug candidates.

• Among the drug candidates, imatinib was suggested as the main drug candidate due to its interaction with the hub gene CXCL9 and CXCL10 and lower p value than the other candidates. It showed the highest binding affinity score and remained stable with the CXCR3 chemokine receptor.

Keywords:

• Guillain-Barré syndrome
• autism spectrum disorder
• molecular docking
• molecular dynamics simulation
• principal component analysis
• dynamic cross-correlation map

Acknowledgments

We express our gratitude to all of our well-wishers for their everlasting encouragement and support.

Authors’ contributions

RAH and MCA designed the whole project. RAH, SA, SS, SZS, and ZA wrote the manuscript. RAH and MHR did the analysis and made the figures. MSSS performed the molecular dynamics simulation. MHR and MAHMJ reviewed and supervised the entire project.

Disclosure statement

The authors declare no conflict of interest.

Additional information

Funding

The author(s) reported that there is no funding associated with the work featured in this article.