title: Serum lipids and neopterin in urine as new biomarkers of malnutrition and inflammation in the elderly.
abstract: OBJECTIVE
  Levels of serum lipids are influenced by malnutrition and inflammation. The study aimed to find the relation of the lipidogram to positive and negative markers of inflammation in geriatric patients. Attention was paid to neopterin in urine as a non-protein positive bioindicator of inflammation.
  
  
  METHODS
  It was a local, monocentric, prospective clinical study in hospitalized patients older than 80 y. The study included 101 patients (54 women, 47 men). The average age of the entire group was 85.37 +/- 4.88 y. The dependence of the values of total cholesterol, high-density lipoprotein (HDL), low-density lipoprotein (LDL), and triacylglycerols (TAGs) on C-reactive protein (CRP), neopterin in urine, and prealbumin was examined.
  
  
  RESULTS
  When we compared CRP and serum lipids, we found a statistically significant negative correlation between levels of CRP and total cholesterol (P < 0.05), HDL (P < 0.01), and LDL (P < 0.05). Also the level of neopterin in urine was negatively correlated with levels of total cholesterol (P < 0.05) and HDL (P < 0.01). A statistically highly significant interaction was demonstrated between levels of prealbumin and total cholesterol (P < 0.001), HDL (P < 0.001), LDL (P < 0.001), and TAG (P < 0.05).
  
  
  CONCLUSIONS
  A significant negative correlation between levels of inflammation markers (neopterin in urine, CRP) and total cholesterol and HDL was found. LDL was influenced to a lesser extent. A close relation between serum lipids and prealbumin was also demonstrated. Total cholesterol, HDL, and LDL can be considered novel biomarkers of malnutrition and inflammation in geriatric patients.
authors.affiliation: Department of Gerontology and Metabolic Care, Faculty Hospital, Hradec Kralove, Czech Republic. danahrnciarikova@seznam.cz
authors.forename: Dana
authors.initials: D
authors.lastname: Hrnciarikova
authors.forename: Radomir
authors.initials: R
authors.lastname: Hyspler
authors.forename: Pavel
authors.initials: P
authors.lastname: Vyroubal
authors.forename: Petr
authors.initials: P
authors.lastname: Klemera
authors.forename: Miloslav
authors.initials: M
authors.lastname: Hronek
authors.forename: Zdenek
authors.initials: Z
authors.lastname: Zadak
mesh_terms: D000369:Aged, 80 and over; D015415:Biomarkers / Q000097:blood / Q000652:urine; D002097:C-Reactive Protein / Q000032:analysis / Q000378:metabolism; D002784:Cholesterol / Q000097:blood; D008076:Cholesterol, HDL / Q000097:blood; D008078:Cholesterol, LDL / Q000097:blood; D005260:Female; D006760:Hospitalization; D006801:Humans; D007249:Inflammation / Q000097:blood / Q000175:diagnosis* / Q000652:urine; D008055:Lipids / Q000097:blood*; D008297:Male; D044342:Malnutrition / Q000097:blood / Q000175:diagnosis* / Q000652:urine; D019798:Neopterin / Q000652:urine*; D011228:Prealbumin / Q000032:analysis / Q000378:metabolism; D011446:Prospective Studies; D014280:Triglycerides / Q000097:blood
chemical_list: D015415:Biomarkers; D008076:Cholesterol, HDL; D008078:Cholesterol, LDL; D008055:Lipids; D011228:Prealbumin; D014280:Triglycerides; D019798:Neopterin; D002097:C-Reactive Protein; D002784:Cholesterol