MyoScore: a Genetically Anchored Transcriptomic Scoring System for Quantifying Human Skeletal Muscle Health

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Abstract

Muscle health varies continuously from optimal function to severe pathology, yet no unified genetic framework quantifies this spectrum objectively. Here we develop MyoScore, a transcriptomic scoring system derived from transcriptome-wide association studies of 27 muscle-related phenotypes in over one million participants. TWAS selects genes whose genetically regulated expression in skeletal muscle associates with muscle-related traits, providing the genetic anchoring of the scoring system, while MyoScore itself is computed from measured bulk RNA-seq expression in new samples. From 1,116 transcriptome-wide association study (TWAS)-significant genes, 417 are expressed in skeletal muscle and form the basis of the scoring system. These genes are organized into five dimensions of muscle biology (Strength, Mass, LeanMuscle, Youth and Resilience), each scored from 0 to 100. Across 1,722 human skeletal muscle transcriptomes from four independent cohorts, MyoScore defines a continuous four-stage muscle health spectrum, discriminates healthy from diseased muscle (area under the curve 0.751–0.873), and correlates with histopathological severity, quantitative MRI and clinical outcomes. Functional validation through iPSC-to-myotube differentiation supports predicted expression changes for novel MyoScore genes. UK Biobank analysis of blood biomarker proxies in 467,123 participants demonstrates concordant associations with muscle phenotypes, and two-sample Mendelian randomization using skeletal muscle cis-eQTL supports causal directionality for 78% of gene-outcome pairs tested. Single-cell validation across 475,584 cells from two independent muscle ageing atlases shows that pseudobulk MyoScore declines with age, with type II myofibre nuclei most affected. Together, MyoScore establishes the first genetically anchored, dimension-resolved quantification of human muscle health, enabling objective assessment, patient stratification and biomarker discovery across the full spectrum from optimal function to severe disease.

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