Assessment of Weighted Gene Co-Expression Network Analysis to Explore Key Pathways and Novel Biomarkers in Muscular Dystrophy

Abstract

Purpose This study aimed to explore the key molecular pathways involved in Duchenne muscular dystrophy (DMD) and Becker muscular dystrophy (BMD) and thereby identify hub genes to be potentially used as novel biomarkers using a bioinformatics approach. Methods Raw GSE109178 data were collected from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was conducted on the top 50% of altered genes. The key modules associated with the clinical features of DMD and BMD were identified. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed using the DAVID website. A protein-protein interaction (PPI) network was constructed using the STRING website. MCODE, together with the Cytohubba plug-ins of Cytoscape, screened out the potential hub genes, which were subsequently verified via receiver operating characteristic (ROC) curves in other datasets. Results Among the 11 modules obtained, the black module was predominantly associated with pathology and DMD, whereas the light-green module was primarily related to age and BMD. Functional enrichment assessments indicated that the genes in the black module were primarily clustered in “immune response” and “phagosome,” whereas the ones in the light-green module were chiefly enriched in “protein polyubiquitination”. Eleven essential genes were eventually identified, including VCAM1, TYROBP, CD44, ITGB2, CSF1R, LCP2, C3AR1, CCL2 , and ITGAM for DMD, along with UBA5 and UBR2 for BMD. Conclusion Overall, our findings may be useful for investigating the mechanisms underlying DMD and BMD. In addition, the hub genes discovered might serve as novel molecular markers correlated with dystrophinopathies.

Identification of Auxiliary Biomarkers and Description of the Immune Microenvironmental Characteristics in Duchenne Muscular Dystrophy by Bioinformatical Analysis and Experiment

“…Therefore, we speculate TYROBP may be involved in the progression of DMD by mediating key inflammatory pathways. Recent studies have also identified TYROBP as a key gene in DMD co-expression networks based on other DMD datasets; these findings are consistent with those reported herein (Wang et al, 2021;Xu et al, 2021). Thus, C3, SPP1, TMSB10, and TYROBP are likely to affect the progression of the inflammatory response in DMD and serve as auxiliary markers, although further clinical research is needed to validate the diagnostic significance of these candidates.…”

“…Advances in genome sequencing technologies and the microarray analysis of disease-related datasets have made it possible for us to quantify immune cell infiltration in a diverse set of different diseases. Over recent years, several studies have provided an overview of the immune response as a key molecular pathway in DMD and identified key genes by using Gene Expression Omnibus (GEO) datasets (Wang et al, 2021;Xu et al, 2021). However, the specific relationships between immune cells and the key genes which influence inflammatory responses have yet to be studied systematically; the differences in the expression of key genes between patients with DMD and normal individuals remain unclear.…”

Identification of key genes and pathways in atherosclerosis using integrated bioinformatics analysis

“…The GSEA results showed that these genes were enriched in ribosome, N-glycanbiosynthesis, and rig-I-like receptor signaling pathway, which were in line with the KEGG pathway analysis identified phagosome, Leishmaniasis, and osteoclast differentiation. Some hub genes, including TYROBP, TNF, SP11, LCP2 and CSF1R, played important roles in phagosome [ 31 , 32 ]. TNF and SP11 are related to leishmaniasis infection [ 33 , 34 ].…”

Proteome-wide systems genetics identifies UFMylation as a regulator of skeletal muscle function

“…In further support of a negative association of UFMylation and muscle function, mutations in UFSP2 have been identified which increase UFMylation and result in musculoskeletal dysplasia ( Watson et al, 2015 ; Zhang et al, 2020 ). Furthermore, the expression of UFC1 is also up-regulated in skeletal myocytes differentiated from induced pluripotent stem cells derived from familial ALS (C9ORF72 mutations) ( Lynch et al, 2021 ), and the expression of UBA5, the E1 ligase for UFMylation has recently been associated with Becker muscular dystrophy ( Xu et al, 2021 ). Interestingly, genetic ablation of UFMylation in cell culture reduces viral-mediated interferon production and correlates with our observed down-regulation of proteins involved in the innate immune response following UFC1 knockdown suggesting an overall reduction in inflammation ( Snider et al, 2022 ).…”