Associations between skeletal muscle parameters and metabolic markers in metabolic syndrome: an exploratory cross-sectional study using photon-counting computed tomography

Background: Metabolic syndrome (MetS) is associated with altered body composition, but the relationship between skeletal muscle parameters and metabolic markers remains incompletely understood. This exploratory cross-sectional study aimed to investigate associations between skeletal muscle quantity and quality, measured by photon-counting computed tomography (PCCT), and circulating metabolic markers in individuals with and without MetS.

Methods: A total of 117 participants [38 with MetS and 79 healthy controls (HCs)] underwent abdominal non-contrast PCCT. Skeletal muscle area (SMA), skeletal muscle density (SMD), and skeletal muscle index (SMI) were measured at the third lumbar vertebral level. Fasting plasma glucose (FPG), glycated hemoglobin (HbA1c), and lipid profiles were collected. Spearman correlation, multivariable regression, and interaction analyses were performed. False discovery rate (FDR) adjustment was applied to exploratory subgroup correlations.

Results: The MetS group had significantly higher SMI (median, 42.73 vs. 39.16 cm²/m²; P<0.001) and a trend toward lower SMD [30.54 vs. 35.22 Hounsfield units (HU); P=0.074]. SMA was not associated with FPG in controls (ρ≈0.001) but showed a positive correlation in the MetS group (ρ=0.411, FDR-adjusted P=0.035). Fisher’s r-to-z test suggested a between-group difference (P=0.033). However, this association was no longer statistically significant after adjustment for age, sex, and body mass index (BMI) (P=0.451). A positive correlation between SMI and triglycerides was observed only in controls (ρ=0.289, FDR-adjusted P=0.024).

Conclusions: MetS was associated with higher SMI and a trend toward lower SMD. Exploratory differences in association patterns between skeletal muscle quantity and glycemic markers were observed but were not independent of BMI. These hypothesis-generating findings require confirmation in larger, well-powered prospective studies.