Utilization of Hydroxyl-Methyl Butyrate, Leucine, Glutamine and Arginine Supplementation in Nutritional Management of Sarcopenia-Implications and Clinical Considerations for Type 2 Diabetes Mellitus Risk Modulation.
Adeline MaykishAngelos K SikalidisPublished in: Journal of personalized medicine (2020)
While onset characteristics may vary, sarcopenia gradually develops over time as a result of the aging process, leading to muscle loss, disturbance of the muscle to fat ratio, and a variety of negative symptoms undermining the wellbeing, quality of life, and lifespan in the aging population globally. There is evidence that sarcopenia may be a cause and consequence of type 2 diabetes mellitus (T2DM) in the aging population. The importance of nutritional management in the prevention and/or deceleration of sarcopenia is critical, with the main focus placed on the amount and quality of protein intake. Significant efforts are being made towards the development of medical nutrition therapies involving certain amino acids and amino compounds, as well as their combinations, for the improvement in muscle strength, muscle function and protein synthesis. This may reduce hospitalization times and hasten the recovery of patients with sarcopenia. The administration of protocols with varying dose and frequencies, as well as their efficacy, is being investigated. In the work herein, we present and evaluate data derived from human trials regarding the utilization of hydroxyl-methyl butyrate (HMB), L-leucine (Leu), L-glutamine (Gln) and L-arginine (Arg) supplementation for optimal management of sarcopenia in geriatric patients, a topic of significant clinical nutrition interest which may have important implications in T2DM status.
Keyphrases
- skeletal muscle
- amino acid
- community dwelling
- insulin resistance
- nitric oxide
- physical activity
- healthcare
- endothelial cells
- ejection fraction
- newly diagnosed
- electronic health record
- glycemic control
- cardiovascular disease
- adipose tissue
- metabolic syndrome
- fatty acid
- small molecule
- machine learning
- big data
- patient reported outcomes
- cardiovascular risk factors
- patient reported