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Cluster analysis of sarcopenia in older adults: significant factors contributing to disease severity
L V Machekhina1, O N Tkacheva2, E N Dudinskaya2
1Federal State Autonomous Educational Institution of Higher Education "Russian National Research Medical University named after N.I. Pirogov" of the Ministry of Health of the Russian Federation, Separate structural unit "Russian Gerontology Research and Clinical Centre", 16 1st Leonova Street, Moscow, Russia, 129226. mlv66@list.ru.
Introduction:
The European Working Group on Sarcopenia in Older People (EWGSOP2) defines sarcopenia as a muscle disease (muscle failure) rooted in adverse muscle changes that accrue across a lifetime; sarcopenia is common among adults of older age. New findings on the hormonal and metabolic characteristics of patients with sarcopenia have aided in developing more targeted therapeutic strategies. However, treating older patients with sarcopenia still poses a number of challenges. Despite numerous studies on sarcopenia, no comprehensive phenotyping of older sarcopenic patients has yet to be offered. Cluster analysis has been successfully used to study various diseases. It may be extremely advantageous for collecting data on specific sarcopenia progressions based on a simultaneous assessment of a whole range of factors.
Aim:
To identify disease progression specific to older patients based on cluster analysis of blood biomarkers and lifestyle.
Methods:
This study included 1709 participants aged 90 and older. The median age was 92. Seventy-one percent of participants were female. Participants underwent a comprehensive geriatric assessment and had their metabolic, hormonal, and inflammatory blood biomarkers measured. The data were analyzed and clustered using the R programming language.
Results:
Seven sarcopenia clusters were identified. The most significant variables, in descending order, were malnutrition, physical activity, body mass index, handgrip strength, testosterone, albumin, sex, adiponectin, total protein, vitamin D, hemoglobin, estradiol, C-reactive protein, glucose, monocytes, and insulin. Handgrip strength measurements and free T3 levels increased linearly between the cluster with the lowest measurements and the cluster with the highest measurements.
Conclusion:
The findings of this study may greatly aid in understanding the relationship between blood biomarkers, lifestyle and sarcopenia progression in older adults, and may help in developing better prevention and diagnostic strategies as well as more personalized therapeutic interventions.
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