Abstract Details

Title Regional Body Composition in Myotonic Dystrophy Type 2: Associations of Lower Extremity Lean Mass Index and Clinical Endpoints

Topic Neuromuscular and Clinical Neurophysiology (EMG)

Presentation(s) P12 - Poster Session 12 (5:30 PM-6:30 PM)

Poster/Presentation
Number 11-002

Background Progressive proximal muscle weakness, myotonia, and multisystemic features are key characteristics of myotonic dystrophy type 2 (DM2), a late-onset autosomal dominant muscular dystrophy. Although MRI has become a preferred imaging method to evaluate muscle pathology and disease severity in muscular dystrophies, it requires dedicated facilities, expensive cost, and labor-intensive analyses. Dual-Energy X-ray Absorptiometry (DXA) regional body composition has been utilized in several studies to estimate lean mass and fat mass. However, this method has not been carefully evaluated in DM2.

Objective To evaluate lower extremity lean mass index (LMI) and fat mass index (FMI) and their relationships with clinical endpoints and MRI muscle volume.

Design/Methods DXA regional body compositions were obtained from ten genetically-proven DM2 subjects. Lower extremity LMI and FMI were calculated by dividing lean and fat masses in both legs by height²(kg/m²). Seven subjects underwent 3T MRI scans for quantitative measures of leg muscle volume (15-mm thickness segmentation from proximal, middle, and distal levels of the thighs and calves). LMI and FMI were correlated with quantitative muscle testing (QMT), functional outcomes, and MRI leg muscle volume using Spearman’s correlation (ρ).

Results Mean age was 62±11 years and disease duration was 18±14 years. Mean LMI and FMI of the lower extremity were 5.67±0.75 and 5.58±1.05 kg/m², respectively. LMI was strongly correlated with QMT of hip flexors (ρ=0.67, p-value=0.049) and knee extensors (ρ=0.77, p-value=0.02). LMI was also moderately associated with grip strength (ρ=0.43, p-value=0.24), pinch gauge (ρ=0.58, p-value=0.09), and disease duration (ρ=0.6, p-value=0.09). There was a strong correlation between LMI and MRI leg muscle volume (ρ=0.93, p-value=0.003). FMI displayed only weak correlation with clinical endpoints and MRI leg muscle volume.

Conclusions Lower extremity LMI offers a practical, cost-effective, and time-efficient method that can be used for evaluation of muscle weakness and atrophy for clinical trial readiness in DM2.

Authors/Disclosures
Carolyn Foster Aldendail, MD (University of Colorado Anschutz Medical Campus) PRESENTER	Dr. Foster Aldendail has nothing to disclose.
Diana A. Madrid, MS (Wake Forest School of Medicine)	Miss Madrid has received personal compensation in the range of $10,000-$49,999 for serving as a Grantee with Institute of Internation Education. Miss Madrid has received personal compensation in the range of $500-$4,999 for serving as a Early Investigator Travel Award with American Society for Bone and Mineral Research. Miss Madrid has received personal compensation in the range of $0-$499 for serving as a Travel Award with American Neurological Association.
	No disclosure on file
Delanie Lynch	Ms. Lynch has nothing to disclose.
	No disclosure on file
Paula R. Clemens, MD (Univ of Pittsburgh/ Dept of Neurology)	The institution of Dr. Clemens has received research support from NS Pharma. The institution of Dr. Clemens has received research support from ReveraGen. The institution of Dr. Clemens has received research support from Amicus. The institution of Dr. Clemens has received research support from Sanofi. The institution of Dr. Clemens has received research support from Spark. The institution of Dr. Clemens has received research support from NIH. The institution of Dr. Clemens has received research support from MDA. The institution of Dr. Clemens has received research support from FDA.
Araya Puwanant, MD (Wake Forest University School of Medicine)	The institution of Dr. Puwanant has received research support from Muscular Dystrophy Association. The institution of Dr. Puwanant has received research support from NIH/NINDS. The institution of Dr. Puwanant has received research support from NIH/NINDS.