Association Between the Growth Hormone/Insulin-Like Growth Factor-1 Axis and Muscle Density in Children and Adolescents of Short Stature.

OBJECTIVE

To evaluate the association between the growth hormone (GH)/insulin-like growth factor-1 (IGF-1) axis and muscle density in children and adolescents of short stature.

METHODS

Participants were children and adolescents of short stature hospitalized in the Affiliated Hospital of Jining Medical University between January 2020 and June 2021. All participants had CT scan images available. We performed an analysis of the images to calculate the muscle density or skeletal muscle attenuation (SMA), skeletal muscle index (SMI), and fat mass index (FMI). Bioelectrical impedance analysis (BIA) was used to ensure that chest CT is a credible way of evaluating body composition.

RESULTS

A total of 297 subjects were included with the mean age of 10.00 ± 3.42 years, mean height standard deviation score (SDS) of -2.51 ± 0.53, and mean IGF-1 SDS of -0.60 ± 1.07. The areas of muscle and fat tissues at the fourth thoracic vertebra level in the CT images showed strong correlation with the total weights of the participants (  = 0.884 and 0.897, respectively). The peak of GH was negatively associated with FMI (r = - 0.323, P <.01) and IGF-1 SDS was positively associated with SMI (r = 0.303, P <.01). Both the peak GH and IGF-1 SDS were positively associated with SMA (r = 0.244, P <.01 and r = 0.165, P <.05, respectively). Multiple stepwise linear regression analysis demonstrated that the GH peak was the predictor of FMI (β = - 0.210, P < .01), the IGF-1 SDS was the predictor of SMI (β = 0.224, P < .01), and both the peak GH and IGF-1 SDS were predictors of SMA (β = 0.180, P < .01 and β = 0.222, P < .01).

CONCLUSIONS

A chest CT scan is a credible method of evaluating body composition in children and adolescents of short stature. In these patients, peak GH and IGF-1 SDS are independent predictors of muscle density and the GF/IGF-1 axis may regulate body composition through complex mechanisms.