title: Elevated circulating adipocyte-fatty acid binding protein levels predict incident cardiovascular events in a community-based cohort: a 12-year prospective study.
abstract: BACKGROUND
  Obesity is closely associated with various cardiovascular diseases (CVDs). Adipose tissue inflammation and perturbation of adipokine secretion may contribute to the pathogenesis of CVD. This study aimed to evaluate whether the 2 most abundant adipokines, adipocyte-fatty acid binding protein (A-FABP) and adiponectin, are independent risk factors predisposing to CVD.
  
  
  RESULTS
  We investigated prospectively the 12-year development of CVD in relation to the baseline levels of A-FABP and adiponectin in a population-based community cohort comprising 1847 Chinese subjects recruited from the Hong Kong Cardiovascular Risk Factors Prevalence Study 2 (CRISPS 2) cohort without previous CVD. Baseline serum levels of A-FABP, adiponectin, and C-reactive protein (CRP), an established biomarker predictive of CVD, were measured. In all, 182 (9.9%) of the 1847 Chinese subjects developed CVD during a median follow-up of 9.4 years. The CVD group had more traditional risk factors, higher baseline levels of A-FABP and CRP (both P<0.001), but similar adiponectin levels (P=0.881) compared with the non-CVD group. In Cox regression analysis including both biomarkers, the adjusted HR for A-FABP and CRP for subjects above the optimal cutoff values were 1.57 (95% CI, 1.14 to 2.16; P=0.006) and 1.60 (95% CI, 1.12 to 2.27; P=0.01), respectively, after adjustment for traditional risk factors. The category-free net reclassification index, but not the c-statistic, showed improvement in predictive performance by the addition of A-FABP to the traditional risk factor model (P=0.017).
  
  
  CONCLUSIONS
  Circulating A-FABP level predicts the development of CVD after adjustment for traditional risk factors in a community-based cohort. Its clinical use for CVD prediction warrants further validation.
authors.affiliation: Department of Medicine, The University of Hong Kong, Hong Kong.
authors.forename: Wing Sun
authors.initials: WS
authors.lastname: Chow
authors.forename: Annette Wai Kwan
authors.initials: AW
authors.lastname: Tso
authors.forename: Aimin
authors.initials: A
authors.lastname: Xu
authors.forename: Michele Mae Ann
authors.initials: MM
authors.lastname: Yuen
authors.forename: Carol Ho Yi
authors.initials: CH
authors.lastname: Fong
authors.forename: Tai Hing
authors.initials: TH
authors.lastname: Lam
authors.forename: Su Vui
authors.initials: SV
authors.lastname: Lo
authors.forename: Hung Fat
authors.initials: HF
authors.lastname: Tse
authors.forename: Yu Cho
authors.initials: YC
authors.lastname: Woo
authors.forename: Chun Yip
authors.initials: CY
authors.lastname: Yeung
authors.forename: Bernard Man Yung
authors.initials: BM
authors.lastname: Cheung
authors.forename: Karen Siu Ling
authors.initials: KS
authors.lastname: Lam
mesh_terms: D052242:Adiponectin / Q000097:blood; D000328:Adult; D000368:Aged; D015415:Biomarkers / Q000097:blood; D002097:C-Reactive Protein / Q000032:analysis; D002318:Cardiovascular Diseases / Q000097:blood* / Q000453:epidemiology*; D016009:Chi-Square Distribution; D050556:Fatty Acid-Binding Proteins / Q000097:blood*; D005260:Female; D006723:Hong Kong / Q000453:epidemiology; D006801:Humans; D015994:Incidence; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D016017:Odds Ratio; D057216:Propensity Score; D016016:Proportional Hazards Models; D011446:Prospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D013997:Time Factors; D015854:Up-Regulation
chemical_list: C499918:ADIPOQ protein, human; D052242:Adiponectin; D015415:Biomarkers; C493410:FABP4 protein, human; D050556:Fatty Acid-Binding Proteins; D002097:C-Reactive Protein