Related Experiment Video
Updated: Aug 6, 2026
Fractionation for Resolution of Soluble and Insoluble Huntingtin Species
Published on: February 27, 2018
Fat-free mass and its predictors in Huntington's disease
S D Süssmuth1, V M Müller, C Geitner
1Department of Neurology, Ulm University, Oberer Eselsberg 45/1, 89081, Ulm, Germany.
Insights
Huntington's disease (HD) patients have lower BMI but similar fat-free mass to controls. Leptin levels predict fat-free mass, suggesting it may help identify HD patients at risk for weight loss.
Area of Science:
- Neurology
- Metabolism
- Human Physiology
Background:
- Weight loss in Huntington's disease (HD) is a concern, but its causes are not fully understood.
- Identifying risk factors for loss of metabolically active tissues, such as fat-free mass, is crucial for managing HD patients.
- Previous studies suggest metabolic dysregulation contributes to weight loss in neurodegenerative conditions.
Purpose of the Study:
- To investigate the causes of weight loss in Huntington's disease (HD).
- To identify risk factors associated with the loss of fat-free mass in HD.
- To explore the role of metabolic regulators like leptin, insulin, and ghrelin in HD-related weight changes.
Main Methods:
- Recruited a cohort of non-diabetic HD participants (manifest and pre-symptomatic) and healthy controls.
- Assessed food intake, basic metabolic rate, glucose homeostasis, and fat-free mass using bioelectric impedance analysis.
- Measured serum levels of leptin, insulin, and ghrelin.
Main Results:
- HD participants had a lower body mass index (BMI) than controls, but fat-free mass and basic metabolic rate did not differ significantly.
- Fat-free mass was not associated with disease burden (CAG repeat length or stage).
- Leptin was identified as the most significant predictor of fat-free mass in both HD participants and controls.
Conclusions:
- Despite lower BMI, HD patients maintain similar fat-free mass compared to controls, with leptin being a key predictor.
- Leptin levels and bioelectric impedance analysis for fat-free mass may serve as valuable screening tools to identify HD patients at risk of weight loss.
- Further research is warranted to elucidate the complex metabolic alterations in HD and develop targeted interventions.
Abstract:
The causes of weight loss in Huntington's disease (HD) are not entirely clear. The aim was to identify risk factors that are associated with a loss of metabolically active tissues, i.e. fat-free mass. A consecutive cohort of non-diabetic HD participants (manifest HD, n = 43; CAG: mean 43.6.0 ± 3.6; preHD, n = 10; CAG: mean 41.4 ± 1.4) and 36 healthy controls was recruited. Twenty-five HD participants were early-stage HD (UHDRS Total Functional Capacity [TFC] stages I and II), 12 mid-stage HD (TFC stage III), and 6 participants were in late-stage HD (TFC stages IV and V). Food intake, basic metabolic rate and glucose homeostasis were assessed. In addition, fat-free mass was determined using bioelectric impedance analysis, and leptin, insulin and ghrelin as key metabolic regulators. Sex ratio and age were similar in HD participants (71 % women; age 50.6 ± 10.9) and controls (66 % women; age 46.4 ± 14.5). Body mass index (BMI) was lower in HD participants than controls (median 24.1 vs. 25.9, p = 0.04). However, fat-free mass and basic metabolic rate were not statistically different between groups and showed no association with disease burden. In controls and HD participants, leptin was the most important predictor of fat-free mass. While BMI was lower in HD participants, fat-free mass was similar to controls with leptin as its most important predictor. Leptin levels and fat-free mass measurements using bioelectric impedance analysis may be good screening tools to identify HD patients at risk for weight loss.
More Related Videos
09:06Whole-brain Segmentation and Change-point Analysis of Anatomical Brain MRI—Application in Premanifest Huntington's Disease
Published on: June 9, 2018
09:18Measurements of Motor Function and Other Clinical Outcome Parameters in Ambulant Children with Duchenne Muscular Dystrophy
Published on: January 12, 2019
