Relationships between Circulating Biomarkers and Body Composition Parameters in Patients with Metabolic Syndrome: A Community-Based Study

Nader Tarabeih, Alexander Kalinkovich, Shai Ashkenazi, Stacey S. Cherny, Adel Shalata, Gregory Livshits

Research output: Contribution to journalArticlepeer-review


Metabolic syndrome (MetS) is a complex disease involving multiple physiological, biochemical, and metabolic abnormalities. The search for reliable biomarkers may help to better elucidate its pathogenesis and develop new preventive and therapeutic strategies. In the present population-based study, we looked for biomarkers of MetS among obesity- and inflammation-related circulating factors and body composition parameters in 1079 individuals (with age range between 18 and 80) belonging to an ethnically homogeneous population. Plasma levels of soluble markers were measured by using ELISA. Body composition parameters were assessed using bioimpedance analysis (BIA). Statistical analysis, including mixed-effects regression, with MetS as a dependent variable, revealed that the most significant independent variables were mainly adipose tissue-related phenotypes, including fat mass/weight (FM/WT) [OR (95% CI)], 2.77 (2.01–3.81); leptin/adiponectin ratio (L/A ratio), 1.50 (1.23–1.83); growth and differentiation factor 15 (GDF-15) levels, 1.32 (1.08–1.62); inflammatory markers, specifically monocyte to high-density lipoprotein cholesterol ratio (MHR), 2.53 (2.00–3.15), and a few others. Additive Bayesian network modeling suggests that age, sex, MHR, and FM/WT are directly associated with MetS and probably affect its manifestation. Additionally, MetS may be causing the GDF-15 and L/A ratio. Our novel findings suggest the existence of complex, age-related, and possibly hierarchical relationships between MetS and factors associated with obesity.

Original languageEnglish
Article number881
Issue number2
StatePublished - 10 Jan 2024


  • adipokines
  • body composition
  • inflammation
  • metabolic syndrome (MetS)
  • monocytes

All Science Journal Classification (ASJC) codes

  • Molecular Biology
  • Spectroscopy
  • Catalysis
  • Inorganic Chemistry
  • Computer Science Applications
  • Physical and Theoretical Chemistry
  • Organic Chemistry


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