BACKGROUND

Alzheimer's disease (AD) is a neurodegenerative disease characterized by brain atrophy and closely correlated with sarcopenia. Mounting studies indicate that parameters related to sarcopenia are associated with AD, but some results show inconsistent. Furthermore, the association between the parameters related to sarcopenia and gray matter volume (GMV) has rarely been explored.

AIM

To investigate the correlation between parameters related to sarcopenia and cerebral GMV in AD.

METHODS

Demographics, neuropsychological tests, parameters related to sarcopenia, and magnetic resonance imaging (MRI) scans were collected from 42 patients with AD and 40 normal controls (NC). Parameters related to sarcopenia include appendicular skeletal muscle mass index (ASMI), grip strength, 5-times sit-to-stand (5-STS) time and 6-m gait speed. The GMV of each cerebral region of interest (ROI) and the intracranial volume were calculated by computing the numbers of the voxels in the specific region based on MRI data. Partial correlation and multivariate stepwise linear regression analysis explored the correlation between different inter-group GMV ratios in ROIs and parameters related to sarcopenia, adjusting for covariates.

RESULTS

The 82 participants included 40 NC aged 70.13 ± 5.94 years, 24 mild AD patients aged 73.54 ± 8.27 years and 18 moderate AD patients aged 71.67 ± 9.39 years. Multivariate stepwise linear regression showed that 5-STS time and gait speed were correlated with bilateral hippocampus volume ratios in total AD. Grip strength was associated with the GMV ratio of the left middle frontal gyrus in mild AD and the GMV ratios of the right superior temporal gyrus and right hippocampus in moderate AD. However, ASMI did not have a relationship to any cerebral GMV ratio.

CONCLUSIONS

Among parameters related to sarcopenia, 5-STS time and gait speed were associated with bilateral hippocampus volume ratios at different clinical stages of patients with AD. Five-STS time provide an objective basis for early screening and can help diagnose patients with AD.