Label-free morphology-based phenotypic analysis of spinal and bulbar muscular atrophy muscle cell models

Background Spinal and bulbar muscular atrophy (SBMA) is a neuromuscular disorder caused by a CAG trinucleotide expansion in the androgen receptor ( AR ) gene. The pathogenesis of SBMA is not fully understood and there are less effective treatments for SBMA. To improve the quality of in vitro cell-based assays for the evaluation of potential drug candidates for SBMA, we aimed to develop a morphology-based phenotypic analysis for a muscle cell model of SBMA that involves multiparametric morphological profiling to quantitatively assess the therapeutic effects of drugs on muscle cell phenotypes. Methods We applied morphology-based phenotypic analysis to a muscle cell model of SBMA. The analysis was validated using dihydrotestosterone (DHT) and pioglitazone (PG), which have been shown to exacerbate and ameliorate the pathophysiology of SBMA, respectively. We then performed gene expression analysis to identify disease-associated pathways. We selected five compounds as potential candidates capable of modulating the disease state of SBMA and compared the morphological profiles using principal component analysis (PCA) and hierarchical clustering. Results The quantified morphological phenotypes of SBMA model cells treated with DHT or PG accurately reflected the exacerbation or amelioration of cell pathology. The results of gene expression analysis revealed that the JNK pathway was activated in the SBMA cells compared to the control cells. Phenotypic analysis revealed the effect of naratriptan (NRT), a JNK inhibitor, on the phenotypic changes of SBMA cells, and the results were confirmed by lactate dehydrogenase (LDH) assays. We then trained a predictive machine learning model to classify the drug responses, and it successfully discriminated between PG-type and NRT-type morphological profiles based on their morphological characteristics. Conclusions We developed a noninvasive and efficient in vitro drug screening technique using morphology-based phenotypic analysis and SBMA model C2C12 cells. Phenotypic analysis revealed that NRT rescued the morphological phenotype and exerted therapeutic effects via the JNK signaling pathway. Furthermore, the 'drug effect prediction model' was able to distinguish the different morphological changes caused by each drug. Our analysis will accelerate the development of the therapeutics for SBMA.