title: Traditional cardiovascular risk factors explain the minority of the variability in carotid plaque.
abstract: OBJECTIVE
  Subclinical atherosclerotic plaque is an important marker of increased vascular risk. Identifying factors underlying the variability in burden of atherosclerotic carotid plaque unexplained by traditional vascular risk factors may help target novel preventive strategies.
  
  
  METHODS
  As a part of the carotid substudy of the Northern Manhattan Study (NOMAS), 1790 stroke-free individuals (mean age, 69±9; 60% women; 61% Hispanic, 19% black, 18% white) were assessed for total plaque area (TPA) burden using 2-dimensional carotid ultrasound imaging. Multiple linear regression models were constructed. Model 1 used prespecified traditional risk factors: age, sex, low-density lipoprotein cholesterol, diabetes mellitus, pack-years of smoking, blood pressure, and treatment for blood pressure; and Model 2, an addition of socioeconomic and less traditional risk factors. The contributions of the components of the Framingham heart risk score and the NOMAS Global Vascular Risk Score to the TPA were explored.
  
  
  RESULTS
  Prevalence of carotid plaque was 58%. Mean TPA was 13±19 mm2. Model 1 explained 19.5% of the variance in TPA burden (R2=0.195). Model 2 explained 21.9% of TPA burden. Similarly, the Framingham heart risk score explained 18.8% and NOMAS global vascular risk score 21.5% of the TPA variance.
  
  
  CONCLUSIONS
  The variation in preclinical carotid plaque burden is largely unexplained by traditional and less traditional vascular risk factors, suggesting that other unaccounted environmental and genetic factors play an important role in the determination of atherosclerotic plaque. Identification of these factors may lead to new approaches to prevent stroke and cardiovascular disease.
authors.affiliation: Department of Neurology, Miller School of Medicine, University of Miami, Clinical Research Building, CRB 1348, 1120 NW 14th Street, Miami, FL 33136, USA. trundek@med.miami.edu
authors.forename: Frank
authors.initials: F
authors.lastname: Kuo
authors.forename: Hannah
authors.initials: H
authors.lastname: Gardener
authors.forename: Chuanhui
authors.initials: C
authors.lastname: Dong
authors.forename: Digna
authors.initials: D
authors.lastname: Cabral
authors.forename: David
authors.initials: D
authors.lastname: Della-Morte
authors.forename: Susan H
authors.initials: SH
authors.lastname: Blanton
authors.forename: Mitchell S V
authors.initials: MS
authors.lastname: Elkind
authors.forename: Ralph L
authors.initials: RL
authors.lastname: Sacco
authors.forename: Tatjana
authors.initials: T
authors.lastname: Rundek
mesh_terms: D000367:Age Factors; D000368:Aged; D016893:Carotid Stenosis / Q000000981:diagnostic imaging* / Q000208:ethnology*; D015331:Cohort Studies; D003920:Diabetes Mellitus / Q000000981:diagnostic imaging / Q000208:ethnology; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009519:New York City / Q000208:ethnology; D011159:Population Surveillance / Q000379:methods; D012307:Risk Factors; D012737:Sex Factors; D012907:Smoking / Q000009:adverse effects / Q000208:ethnology; D020521:Stroke; D014463:Ultrasonography