title: LIPID PROFILE AND CYTOKINES INTERACTIONS DURING SUCCESSFUL AGING.
abstract: Aging is accompanied by a loss of homeostasis, which leads to increase of susceptibility and vulnerability to cancers, cardiovascular, neurodegenerative and autoimmune diseases. Numerous studies have been suggested that even in the absence of acute infection ageing associated with chronic low-grade inflammation and the underlying cause of this process may be an immunosenescence as well as shifts production of cytokines levels. However, the results on age-related alterations of these cytokine levels are inconsistent. The main aim of our study was to evaluate how the pro- and anti-inflammatory cytokines and lipoproteins fraction varies through aging as well as how these changes related each other in an apparently healthy population. For this purposes, 220 healthy volunteers were selected on the basis of clinical records and laboratory examinations. Individuals with various health problems were excluded. Fasting triglycerids (TG), low and high density lipoproteins (LDL and HDL) and cytokines (IL-6, IL4, 10, 17, IFN, TNF) levels were measured using commercial assay kits. The statistical analysis was performed using SPSS (Chicago, IL, USA). The results revealed that all studied cytokines levels did not fluctuate by gender. LDL means value differ significantly between men and women. Age are not main predictor for HDL, TG, IL4, IL6, IFN circulating levels, however, the production of LDL, IL17 and IL10 showed significant deviations through aging: especially, LDL and IL17 were augmented, while IL-10 were reduced. It is interestingly, that besides the age, LDL levels were correlated with TNF-alfa and IL10, while triglyceride were only associated with IL10 levels. It has to be note that the correlations did not changes after adjustment of age. The result of our study shown that lipoproteins (LDL, TG) and cytokines (TNF, IL10, IL17) levels are linked and can be used as a prognostic markers of cardiovascular diseases development.
authors.affiliation: Tbilisi State Medical University, Institute of Medical Biotechnology, Georgia.
authors.forename: I
authors.initials: I
authors.lastname: Pantsulaia
authors.affiliation: Tbilisi State Medical University, Institute of Medical Biotechnology, Georgia.
authors.forename: M
authors.initials: M
authors.lastname: Iobadze
authors.affiliation: Tbilisi State Medical University, Institute of Medical Biotechnology, Georgia.
authors.forename: N
authors.initials: N
authors.lastname: Kikodze
authors.affiliation: Tbilisi State Medical University, Institute of Medical Biotechnology, Georgia.
authors.forename: N
authors.initials: N
authors.lastname: Pantsulaia
authors.affiliation: Tbilisi State Medical University, Institute of Medical Biotechnology, Georgia.
authors.forename: T
authors.initials: T
authors.lastname: Chikovani
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000097:blood* / Q000502:physiology; D002784:Cholesterol / Q000097:blood; D050171:Dyslipidemias / Q000097:blood / Q000473:pathology; D005260:Female; D064368:Healthy Volunteers; D006801:Humans; D007249:Inflammation / Q000097:blood* / Q000473:pathology; D008055:Lipids / Q000097:blood*; D008074:Lipoproteins / Q000097:blood / Q000502:physiology; D008297:Male; D008875:Middle Aged; D014280:Triglycerides / Q000097:blood*
chemical_list: D008055:Lipids; D008074:Lipoproteins; D014280:Triglycerides; D002784:Cholesterol