Co-expression Network Approach Reveals Functional Similarities among Diseases Affecting Human Skeletal Muscle

Abstract

Diseases affecting skeletal muscle exhibit considerable heterogeneity in intensity, etiology, phenotypic manifestation and gene expression. Systems biology approaches using network theory, allows for a holistic understanding of functional similarities amongst diseases. Here we propose a co-expression based, network theoretic approach to extract functional similarities from 20 heterogeneous diseases comprising of dystrophinopathies, inflammatory myopathies, neuromuscular, and muscle metabolic diseases. Utilizing this framework we identified seven closely associated disease clusters with 20 disease pairs exhibiting significant correlation (p < 0.05). Mapping the diseases onto a human protein-protein interaction network enabled the inference of a common program of regulation underlying more than half the muscle diseases considered here and referred to as the “protein signature.” Enrichment analysis of 17 protein modules identified as part of this signature revealed a statistically non-random dysregulation of muscle bioenergetic pathways and calcium homeostasis. Further, analysis of mechanistic similarities of less explored significant disease associations [such as between amyotrophic lateral sclerosis (ALS) and cerebral palsy (CP)] using a proposed “functional module” framework revealed adaptation of the calcium signaling machinery. Integrating drug-gene information into the quantitative framework highlighted the presence of therapeutic opportunities through drug repurposing for diseases affecting the skeletal muscle.

Skeletal muscle: A review of molecular structure and function, in health and disease

“…Colors on the tree indicate the clusters/grouping of diseases, while the red line indicates the threshold used for clustering. (Reprinted with permission from Mukund and Subramaniam (). Copyright 2017 Frontiers Publication)…”

Personalized Medicine and Molecular Interaction Networks in Amyotrophic Lateral Sclerosis (ALS): Current Knowledge

“…Applications of gene coexpression network analysis have been successfully applied in ALS. Multiple gene coexpression studies have revealed several pathways believed to be implicated in ALS, including cell adhesion, calcium ion binding, inflammatory processes, and tumour necrosis factor (TNF) signalling [72,73,74,75,76,77]. Brohawn et al took gene expression data gathered from seven ALS spinal cord samples and eight control spinal cord samples [78].…”

Integrative transcriptomic analysis of tissue-specific metabolic crosstalk after myocardial infarction

“…Systems biology has also been employed in the identification of novel biomarkers, characterization of patients, and stratification of heterogenous cancer patients ( Benfeitas et al, 2019 ; Bidkhori et al, 2018 ; Lee et al, 2016 ). Specifically, integrated networks (INs) ( Lee et al, 2016 ) and co-expression networks (CNs) ( Lee et al, 2017 ) have been proven to be robust methods for revealing the key driver of metabolic abnormalities, discovering new therapy strategies, as well as gaining systematic understanding of diseases ( Bakhtiarizadeh et al, 2018 ; Mukund and Subramaniam, 2017 ).…”