title: Inflammation and hemostasis biomarkers and cardiovascular risk in the elderly: the Cardiovascular Health Study.
abstract: BACKGROUND
  There are few studies of inflammation and hemostasis biomarkers and cardiovascular disease risk (CVD) in older adults.
  
  
  OBJECTIVE
  To assess multiple biomarkers simultaneously and in combinations for CVD risk assessment in older individuals.
  
  
  METHODS
  Thirteen biomarkers, interleukin-6 (IL-6), C-reactive protein (CRP), D-dimer, fibrinogen, factor VII, factor VIII, leukocyte count (WBC), platelet count, lipoprotein(a), soluble intercellular adhesion molecule-1 (sICAM-1), albumin, homocysteine and uric acid, were correlated with incident CVD in 4510 individuals in the Cardiovascular Health Study. Baseline biomarkers were analyzed as gender-specific SD increments and quintiles in proportional hazards models adjusted for demographics, CVD risk factors and medications.
  
  
  RESULTS
  Over 9 years with 1700 CVD events, seven biomarkers were associated with CVD. Adjusted hazard ratios (HRs, 95% CI) per SD increment were 1.16 (1.09, 1.23) for IL-6, 1.16 (1.09, 1.23) for CRP, 1.13 (1.05, 1.21) for D-dimer, 1.17 (1.09, 1.25) for homocysteine, 1.06 (1.00, 1.12) for WBC, 1.06 (1.00, 1.12) for factor VIII, and 1.07 (1.00, 1.13) for lipoprotein(a). Fibrinogen was associated with CVD in men only (HR 1.12, 95% CI 1.04, 1.22) and sICAM-1 in women only (HR 1.16, 95% CI 1.05, 1.27). IL-6 and CRP remained associated with CVD when modeled with WBC. Participants were classified by all combinations of two biomarkers being high or low (IL-6, CRP, WBC, factor VIII, cholesterol/HDL). All were associated with CVD when cholesterol/HDL was low and none when CRP was low.
  
  
  CONCLUSIONS
  Seven biomarkers were associated with CVD in older adults, with CRP having some advantages compared with others. Even larger studies are needed to better characterize these associations.
authors: Department of Medicine, Brown University and Boston University, Providence, RI, USA.
authors: N A
authors: NA
authors: Zakai
authors: R
authors: R
authors: Katz
authors: N S
authors: NS
authors: Jenny
authors: B M
authors: BM
authors: Psaty
authors: A P
authors: AP
authors: Reiner
authors: S M
authors: SM
authors: Schwartz
authors: M
authors: M
authors: Cushman
mesh_terms: D000368:Aged; D000375:Aging / Q000097:blood*; D015415:Biomarkers / Q000097:blood; D002097:C-Reactive Protein / Q000378:metabolism; D002318:Cardiovascular Diseases / Q000097:blood / Q000145:classification / Q000209:etiology*; D002784:Cholesterol / Q000097:blood; D015331:Cohort Studies; D005169:Factor VIII / Q000378:metabolism; D005260:Female; D005340:Fibrinogen / Q000378:metabolism; D006487:Hemostasis / Q000502:physiology*; D006710:Homocysteine / Q000097:blood; D006801:Humans; D018836:Inflammation Mediators / Q000097:blood*; D015850:Interleukin-6 / Q000097:blood; D007958:Leukocyte Count; D017270:Lipoprotein(a) / Q000097:blood; D008297:Male; D011446:Prospective Studies; D012307:Risk Factors
chemical_list: D015415:Biomarkers; C508600:IL6 protein, human; D018836:Inflammation Mediators; D015850:Interleukin-6; D017270:Lipoprotein(a); D006710:Homocysteine; D005169:Factor VIII; D005340:Fibrinogen; D002097:C-Reactive Protein; D002784:Cholesterol