A Data-Driven Methodology Reveals Novel Myofiber Clusters in Older Human Muscles

Skeletal muscles control posture, mobility and strength, affecting whole-body metabolism. The muscle is composed of different types of myofibers, which are defined by their contractile properties, and are marked by the expression of sarcomeric proteins. Three myosin heavy-chain (MyHC) isoforms, MyHC-1, MyHC-2A and MyHC-2X characterize myofiber properties in humans, yet characterization of myofibers is often performed considering only a single MyHC isoform expression. We aimed to study heterogeneity in muscle tissue composition, by detailed analysis of the expression of the three MyHC isoforms in consortium. We created a dataset with high-throughput MyHC immunofluorescence imaging in muscle tissues of 56 older adults. Our analyses revealed six distinct myofiber clusters, some of which could not be detected or are misclassified by the traditional visual myofiber assessment. Transcriptome analyses revealed that the abundance of these myofiber clusters was correlated with the expression of distinct modules of sarcomeric genes. Interestingly, one of the novel clusters, expressing all three MyHC isoforms, correlated to multiple histological measures of muscle health. Collectively, we present a data-driven procedure for a deeper characterization of muscle tissue composition, that opens new options to unravel the relations between alterations in muscle composition and changes in a variety of health conditions and aging.