Frontiers in GeneticsGeneticsPeer-reviewed journal article
Shared regulatory pathways reveal novel genetic correlations between grip strength and neuromuscular disorders
Sreemol GokuladhasiD, William S. SchierdingiD, David Cameron‐SmithiD, Melissa A WakeiD, Emma L. ScotteriD, Justin Martin O'SullivaniD
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Abstract
BackgroundMuscle weakness and muscle wasting can be a consequence of aging (sarcopenia) and neuromuscular disorders (NMD). Genome-wide association (GWA) studies have identified genetic variants associated with grip strength (GS, an inverse measure of muscle weakness) and NMD (multiple sclerosis (MS), myasthenia gravis (MG) and amyotrophic lateral sclerosis (ALS)). However, how these variants contribute to the muscle weakness caused by aging or NMD remains obscure.\n\nMethodsWe have integrated GS and NMD associated SNPs in a multimorbid analysis that leverages high-throughput chromatin interaction (Hi-C) data and expression quantitative trait loci (eQTL) data to identify allele-specific gene regulation (i.e. eGenes). Pathways and shared drug targets that are enriched by colocalised eGenes were then identified using pathway and drug enrichment analysis.\n\nResultsWe identified gene regulatory mechanisms (eQTL-eGene effects) associated with GS, MG, MS and ALS. The eQTLs associated with GS regulate a subset of eGenes that are also regulated by the eQTLs of MS, MG and ALS. Yet, we did not find any eGenes commonly regulated by all four phenotypes associated eQTLs. By contrast, we identified three pathways (mTOR signaling, axon guidance, and alcoholism) that are commonly affected by the gene regulatory mechanisms associated with all four phenotypes. 13% of the eGenes we identified were known drug targets, and GS shares at least one druggable eGene and pathway with each of the NMD phenotypes.\n\nConclusionsCollectively, these findings identify significant biological overlaps between GS and NMD, demonstrating the potential for spatial genetic analysis to identify mechanisms underlying muscle weakness due to aging and NMD.
- organism: human
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- approach: statistical model
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