Characteristics of systemic inflammation parameters in patients with chronic obstructive pulmonary disease depending on the body composition

As far as the incidence of chronic respiratory diseases is increasing significantly worldwide, assessing the mutual influence of body composition on chronic obstructive pulmonary disease (COPD) and conversely is an urgent issue. Objective. To identify and compare cytokine and adipokine profiles in patients with chronic obstructive pulmonary disease depending on the body composition. Materials and methods. This study is multicenter, comparative and case-control. Patients with COPD and conditionally healthy individuals for the control group are included. All participants of the study underwent survey, blood sampling was done to determine the levels of leptin, resistin, adiponectin, visfatin, tumor necrosis factor-alpha (TNF-α), IL-4, IL-6, IL-8, IL-10 interleukins, monocyte chemoattractant protein-1 (MCP-1). Complete blood count was performed for calculation of the inflammation indices: systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR); lymphocyte-to-monocyte ratio (LMR), platelet-neutrophil product (PPN). Anthropometry, bioimpedance analysis and spirometry were also carried out. Results. The highest levels of inflammation indices were determined for patients with COPD and normal body mass. When patients were divided by the body fat percentage, those with the lowest amount of fat had the highest levels of TNF-α and MCP-1 inflammatory cytokines and at the same time the highest values of anti-inflammatory IL-10 and adiponektin that is probably a protective mechanism at the higher level of inflammation. Patients with COPD and higher fat-free mass index (17 kg/m2 and above) had better spirometry and higher MCP-1 indicators. Conclusion. The body composition and mainly the adipose tissue have a relationship with adipocytokines and inflammation indices in patients with chronic obstructive pulmonary disease. Bioimpedance analysis can be a valuable diagnostic tool for developing personalized recommendations on correction of the nutritional status of patients with this pathology.