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Validation ​

Study Cohorts ​

MyoScore was validated across 1,722 human skeletal muscle RNA-seq transcriptomes from four independent cohorts:

CohortnSourceComposition
GTEx v8803Genotype-Tissue Expression ProjectAutopsy skeletal muscle; four-stage wasting spectrum
GEO668NCBI GEO (15 studies)Multiple myopathy studies (FSHD, DM1, CDM, DMD, cancer cachexia)
Helsinki Myofin154University of HelsinkiTitinopathy, IBM, control
HuashanMuscle97Huashan Hospital, Fudan UniversityDM1, LGMD, control

Disease Discrimination ​

ROC analysis demonstrated consistent discrimination across all four cohorts:

CohortAUC95% CI
GTEx0.8250.793–0.855
GEO0.7860.749–0.822
Helsinki Myofin0.7510.588–0.886
HuashanMuscle0.8730.786–0.948

Continuous Muscle Health Spectrum ​

UMAP dimensionality reduction of all 1,722 samples revealed a continuous gradient from healthy to severely diseased muscle. Diffusion component 1 correlated strongly with MyoScore (r = 0.417, P = 1.37 × 10⁻⁷³), confirming that the scoring system captures the primary biological axis of muscle health variation.

StageDescriptionMyoScore (mean, 95% CI)n
IHealthy (accidental/unexpected death)51.4 (50.9–51.8)234
IIMild Disease (intermediate death, overweight, sleep restriction)49.3 (48.7–49.8)173
IIIModerate Wasting (ventilator/slow death, cancer cachexia)46.8 (46.5–47.2)595
IVSevere Muscle Disease (sIBM, TMD, FSHD, LGMD, DM1, CDM, DMD)44.6267

Clinical Correlations ​

DM1 (n = 27) ​

  • CTG repeat length: r = −0.41, P = 0.034
  • 10-metre walk time: r = −0.42, P = 0.029
  • Grip strength: r = 0.37, P = 0.058

CDM (n = 29) ​

  • CTG repeats: r = −0.35, P = 0.060

FSHD (n = 32) ​

  • Histological inflammation score: r = −0.45, P = 0.024

LGMD R12 (n = 41) ​

  • Mercuri MRI score: r = −0.57, P < 0.001
  • Selective muscle involvement: semimembranosus most affected (P = 0.009), vastus lateralis intermediate (P = 0.037), rectus femoris preserved (P = 0.567)

Histopathological Validation ​

Automated quantification of H&E-stained whole slide images (same biopsy specimen as RNA-seq) using MyoPath:

GTEx cohort (n = 399 slides) ​

  • LeanMuscle vs fat infiltration: r = −0.12, P = 0.019
  • LeanMuscle vs fibrosis: r = −0.20, P < 0.001
  • LeanMuscle vs fiber variability: r = −0.24, P < 0.001

HuashanMuscle disease cohort (n = 74 slides) ​

  • LeanMuscle vs fat infiltration: r = −0.50, P < 0.001
  • LeanMuscle vs fibrosis: r = −0.44, P < 0.001
  • LeanMuscle vs fiber variability: r = −0.57, P < 0.001
  • Resilience vs nuclear centralization: r = −0.25, P = 0.032

MRI Validation ​

Within-individual comparison of transcriptomic MyoScore with quantitative thigh MRI:

HuashanMuscle (n = 46) ​

  • LeanMuscle vs fat fraction: r = −0.35, P = 0.018
  • Mass vs muscle volume: r = 0.31, P = 0.037

Helsinki Myofin (n = 13) ​

  • LeanMuscle vs fat fraction: r = −0.62, P = 0.023
  • Mass vs muscle volume: r = 0.49, P = 0.087

Novel Gene Validation ​

iPSC-to-Myotube Differentiation ​

Five novel MyoScore genes tracked across 4 healthy donors, 6 time points:

GeneDirectionFold Change (D20/D0)P valueConcordant
TMEM52Positive1.733.6 × 10⁻⁴Yes
CEP250Negative0.202.3 × 10⁻⁷Yes
YWHABNegative0.517.8 × 10⁻⁷Yes
SNRPCNegative0.337.4 × 10⁻⁷Yes
RSRC2Negative0.800.60Yes (trend)

Mendelian Randomization ​

28/36 gene–outcome pairs (78%) showed MR effect directions concordant with MyoScore predictions. Tissue-matched skeletal muscle cis-eQTL were essential — blood eQTL gave discordant results for ACSS2 and GGT7.

Single-Cell Validation ​

Across 475,584 cells from two independent muscle ageing atlases (HLMA, 292,423 cells; Sanger, 183,161 cells):

  • Combined pseudobulk correlation with age: ρ = −0.39, P = 0.014 (n = 40 donors)
  • Type II myofiber nuclei showed the largest age-related decline (Cohen's d = 0.19)
  • Youth dimension declined in all 13 cell types examined

Stability ​

MyoScore showed no significant change after a 16-week lifestyle intervention in overweight individuals (n = 54, P = 0.567), consistent with its design as a measure of genetically regulated expression driven by germline variants rather than acute environmental stimuli.

Limitations ​

  • GWAS data derive predominantly from European ancestry populations
  • Primarily cross-sectional validation; longitudinal studies needed
  • Captures 417 of 1,116 identified genes due to bulk RNA-seq detection limits
  • Blood biomarker proxies may not directly reflect tissue-specific gene expression
  • iPSC validation used a limited sample (n = 4 donors)
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