Using Cluster Analysis to Overcome the Limits of Traditional Phenotype-Genotype Correlations: The Example of RYR1-Related Myopathies

Abstract

Thanks to advances in gene sequencing, RYR1-related myopathy (RYR1-RM) is now known to manifest itself in vastly heterogeneous forms, whose clinical interpretation is, therefore, highly challenging. We set out to develop a novel unsupervised cluster analysis method in a large patient population. The objective was to analyze the main RYR1-related characteristics to identify distinctive features of RYR1-RM and, thus, offer more precise genotype-phenotype correlations in a group of potentially life-threatening disorders. We studied 600 patients presenting with a suspicion of inherited myopathy, who were investigated using next-generation sequencing. Among them, 73 index cases harbored variants in RYR1. In an attempt to group genetic variants and fully exploit information derived from genetic, morphological, and clinical datasets, we performed unsupervised cluster analysis in 64 probands carrying monoallelic variants. Most of the 73 patients with positive molecular diagnoses were clinically asymptomatic or pauci-symptomatic. Multimodal integration of clinical and histological data, performed using a non-metric multi-dimensional scaling analysis with k-means clustering, grouped the 64 patients into 4 clusters with distinctive patterns of clinical and morphological findings. In addressing the need for more specific genotype-phenotype correlations, we found clustering to overcome the limits of the "single-dimension" paradigm traditionally used to describe genotype-phenotype relationships.

Keywords: NGS; RYR1-related myopathies; genotype–phenotype correlation; unsupervised cluster analysis.

Figure 1

The most representative clinical features of symptomatic patients presented using HPO-based ID codes and nomenclature.

Figure 2

Dots-box plot (top) and representative Western Blot (bottom) show the levels of RYR1 protein in different clusters (expressed as % of controls) and protein detection, respectively. RYR1 protein levels of each cluster were compared to controls (whose levels were set equal to 100%). ** = p < 0.05; **** = p < 0.0001.

Figure 3

Different mutation types and their relative frequency among the pathogenic ones identified in this study.

Figure 4

Distribution of frequencies of the most relevant clinical characteristics (indicated as HPO-based codes), shown per cluster.

Figure 5

Distribution of frequencies of muscle biopsy (MB) findings, shown per cluster.

Figure 6

Myopathic changes in patients with RYR1 alteration. (A) Gomori trichrome staining showing some mild variation in fiber size and an increased number of fibers with internal nuclei in Pt 14. (B) Hematoxylin and eosin staining demonstrating the variation of fiber sizes, and multiple internal nuclei in some fibers in Pt 12. (C) NADH stain showing multiple minicores in some fibers. 40× magnification.