Nutrients (Jul 2024)

Adipokines and Myokines as Markers of Malnutrition and Sarcopenia in Patients Receiving Kidney Replacement Therapy: An Observational, Cross-Sectional Study

  • Sylwia Czaja-Stolc,
  • Antoine Chatrenet,
  • Marta Potrykus,
  • Jakub Ruszkowski,
  • Massimo Torreggiani,
  • Monika Lichodziejewska-Niemierko,
  • Alicja Dębska-Ślizień,
  • Giorgina Barbara Piccoli,
  • Sylwia Małgorzewicz

DOI
https://doi.org/10.3390/nu16152480
Journal volume & issue
Vol. 16, no. 15
p. 2480

Abstract

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Chronic kidney disease (CKD) is linked to an elevated risk of malnutrition and sarcopenia, contributing to the intricate network of CKD-related metabolic disorders. Adipokines and myokines are markers and effectors of sarcopenia and nutritional status. The aim of this study was to assess whether the adipokine–myokine signature in patients on kidney replacement therapy could help identify malnutrition and sarcopenia. The study involved three groups: 84 hemodialysis (HD) patients, 44 peritoneal dialysis (PD) patients, and 52 kidney transplant recipients (KTR). Mean age was 56.1 ± 16.3 years. Malnutrition was defined using the 7-Point Subjective Global Assessment (SGA) and the Malnutrition-Inflammation Score (MIS). Sarcopenia was diagnosed based on reduced handgrip strength (HGS) and diminished muscle mass. Concentrations of adipokines and myokines were determined using the enzyme-linked immunosorbent assay (ELISA). 32.8% of all study participants were identified as malnourished and 20.6% had sarcopenia. For malnutrition, assessed using the 7-Point SGA, in ROC analysis albumin (area under the curve (AUC) 0.67 was the best single biomarker identified. In dialysis patients, myostatin (AUC 0.79) and IL-6 (AUC 0.67) had a high discrimination value for sarcopenia, and we were able to develop a prediction model for sarcopenia, including age, albumin, adiponectin, and myostatin levels, with an AUC of 0.806 (95% CI: 0.721–0.891). Adipokines and myokines appear to be useful laboratory markers for assessing malnutrition and sarcopenia. The formula we propose could contribute to a better understanding of sarcopenia and potentially lead to more effective interventions and management strategies for dialysis patients.

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