Significant Interplay Between Lipids, Cytokines, Chemokines, Growth Factors, and Blood Cells in an Outpatient Cohort.

Cardiovascular disease (CVD) remains the leading global cause of morbidity and mortality, largely driven by atherosclerosis, a chronic inflammatory process involving lipids and immune cells. Although traditional lipid biomarkers such as low-density lipoprotein (LDL) and high-density lipoprotein (HDL) are well-established in CVD risk stratification, the interplay between cytokines, chemokines, growth factors (CCGFs), lipid metabolism, and hematological parameters in non-cardiac populations remains underexplored. We investigated associations between plasma cytokines and lipid-related biomarkers and their relationships with circulating blood cell counts in a cohort of 164 essentially healthy adults aged 18-44 years. CCGF profiling was performed using a proximity extension assay (PEA), and statistical correlations were adjusted for multiple testing using false discovery rate (FDR) correction. The CCGFs that were associated with HDL and apolipoprotein A1 all displayed negative associations. Several pro-inflammatory cytokines, including CCL3, IL-6, and TNFSF10, showed strong positive associations with triglycerides, remnants, non-HDL, and body mass index (BMI). Furthermore, triglycerides and remnants were consistently correlated with elevated leukocyte, neutrophil, and platelet counts. HGF and FGF-21, mainly considered as anti-inflammatory, were positively associated with BMI and negatively associated with HDL, which is compliant with a multitude of actions, depending on the local milieu and the cellular interplay. Our results support the existence of a complex immunometabolic network involving lipids, CCGFs, and blood cells, even in non-diseased individuals. The observed patterns underscore the importance of understanding the intricate cytokine-lipid-cell interactions that may occur in early pathophysiological processes and highlight their potential utility in refining cardiovascular risk assessment beyond traditional lipid metrics.