Gokuladhas Sreemol, Schierding William, Cameron-Smith David, Wake Melissa, Scotter Emma L, O'Sullivan Justin
Liggins Institute, The University of Auckland, Auckland, New Zealand.
Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research (A∗STAR), Singapore, Singapore.
Front Genet. 2020 Apr 24;11:393. doi: 10.3389/fgene.2020.00393. eCollection 2020.
Muscle weakness is a common consequence of both aging (sarcopenia) and neuromuscular disorders (NMD). Whilst genome-wide association (GWA) studies have identified genetic variants associated with grip strength (GS; measure of muscle strength/weakness) and NMDs, including multiple sclerosis (MS), myasthenia gravis (MG) and amyotrophic lateral sclerosis (ALS), it is not known whether there are common mechanisms between these phenotypes. To examine this, we have integrated GS and NMD associated genetic variants (single nucleotide polymorphisms; SNPs) in a multimorbid analysis that leverages high-throughput chromatin interaction (Hi-C) data and expression quantitative trait loci data to identify target genes (i.e., SNP-mediated gene regulation). Biological pathways enriched by these genes were then identified using next-generation pathway enrichment analysis. Lastly, druggable genes were identified using drug gene interaction (DGI) database. We identified gene regulatory mechanisms associated with GS, MG, MS, and ALS. The SNPs associated with GS regulate a subset of genes that are also regulated by the SNPs of MS, MG, and ALS. Yet, we did not find any genes commonly regulated by all four phenotype associated SNPs. By contrast, we identified significant enrichment in 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 genes we identified were known drug targets, and GS shares at least one druggable gene and pathway with each of the NMD phenotypes. We have identified significant biological overlaps between GS and NMD, demonstrating the potential for spatial genetic analysis to identify common mechanisms between potential multimorbid phenotypes. Collectively, our results form the foundation for a shift from a gene to a pathway-based approach to the rationale design of therapeutic interventions and treatments for NMD.
肌肉无力是衰老（肌肉减少症）和神经肌肉疾病（NMD）的常见后果。虽然全基因组关联（GWA）研究已经确定了与握力（GS；肌肉力量/无力的度量）和NMD相关的基因变异，包括多发性硬化症（MS）、重症肌无力（MG）和肌萎缩侧索硬化症（ALS），但尚不清楚这些表型之间是否存在共同机制。为了研究这一点，我们在一项多病分析中整合了与GS和NMD相关的基因变异（单核苷酸多态性；SNP），该分析利用高通量染色质相互作用（Hi-C）数据和表达数量性状位点数据来识别靶基因（即SNP介导的基因调控）。然后使用下一代通路富集分析来识别这些基因富集的生物通路。最后，使用药物基因相互作用（DGI）数据库识别可成药基因。我们确定了与GS、MG、MS和ALS相关的基因调控机制。与GS相关的SNP调控的一部分基因也受MS、MG和ALS的SNP调控。然而，我们没有发现所有四种表型相关SNP共同调控的任何基因。相比之下，我们在三个通路（mTOR信号传导、轴突导向和酒精中毒）中发现了显著富集，这些通路通常受与所有四种表型相关的基因调控机制影响。我们识别出的基因中有13%是已知的药物靶点，并且GS与每种NMD表型至少共享一个可成药基因和通路。我们已经确定了GS和NMD之间存在显著的生物学重叠，证明了空间遗传分析在识别潜在多病表型之间共同机制方面的潜力。总体而言，我们的研究结果为从基于基因的方法转向基于通路的方法来合理设计NMD的治疗干预和治疗奠定了基础。
