Integrative Transcriptomic and Network-Based Analysis of Neuromuscular Diseases

TL;DR

This paper uses advanced network analysis to uncover shared molecular patterns and potential new targets in rare neuromuscular diseases like DMD and ALS.

Contribution

The novel integrative approach combines transcriptomics, PPI networks, and network embeddings to reveal systemic and shared disease mechanisms in NMDs.

Findings

Differential expression analysis identified unexpected pathways like renal development in NMDs.

Shared pathways such as glycosaminoglycan binding were found in DMD and FUS-related ALS.

Dysregulated non-coding RNAs like PAX8-AS1 and candidate genes like HS3ST3A1 were identified as potential regulators.

Abstract

Neuromuscular diseases (NMDs) like Duchenne muscular dystrophy (DMD), limb–girdle muscular dystrophy (LGMD), and amyotrophic lateral sclerosis (ALS) are rare, progressive disorders with complex molecular mechanisms. Traditional transcriptomic analyses often struggle to capture systems-level dysregulation, especially given the small sample sizes typical of rare disease studies. Our differential expression analysis of eight public RNA-seq datasets from various cell types in DMD, LGMD, and ALS revealed not only disease-relevant pathways but also unexpected enrichments, such as renal development, suggesting systemic impacts beyond muscle tissue. To address limitations in capturing broader molecular mechanisms, we applied an integrative systems biology approach combining differential expression data, protein–protein interaction (PPI) networks, and network embedding techniques. Comparative functional enrichment revealed shared pathways, including glycosaminoglycan binding in both DMD and FUS-related ALS, implicating extracellular matrix–protein interactions in FUS mutation effects. Mapping DEGs onto the human PPI network and assessing their proximity to causal genes uncovered dysregulated non-coding RNAs, such as PAX8-AS1, SBF2-AS1, and NEAT1, potentially indicating common regulatory roles. We also found candidate genes within disease-proximal clusters, like HS3ST3A1, which may contribute to pathogenesis. Overall, this integrative approach reveals shared transcriptional programs and novel targets, advancing our understanding and potential treatment strategies for NMDs.

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