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  • Title: Independent predictive roles of eotaxin Ala23Thr, paraoxonase 2 Ser311Cys and beta-adrenergic receptor Trp64Arg polymorphisms on cardiac disease in Type 2 Diabetes--an 8-year prospective cohort analysis of 1297 patients.
    Author: Wang Y, Luk AO, Ma RC, So WY, Tam CH, Ng MC, Yang X, Baum L, Lam V, Tong PC, Chan JC.
    Journal: Diabet Med; 2010 Apr; 27(4):376-83. PubMed ID: 20536507.
    Abstract:
    AIMS: To examine the independent and joint effects of multiple genetic variants on a cardiac end-point in an 8-year prospective study of a Chinese diabetic cohort. METHODS: Seventy-seven single nucleotide polymorphisms (SNPs) of 53 candidate genes for inflammation, thrombosis, vascular tone regulation and lipid metabolism were genotyped in 1297 Chinese patients with no prior history of coronary heart disease (CHD) or heart failure at baseline. Cardiac end-point was defined by the occurrence of CHD and/or heart failure. RESULTS: In Cox regression model, after adjustment for baseline confounding variables including age, sex, smoking status, duration of diabetes, glycaemic control, lipid levels, waist circumference, blood pressure, albuminuria and estimated glomerular filtration rate, genetic variants, including Ala/Ala of SCYA11 (eotaxin) Ala23Thr, Cys/Cys or Cys/Ser of PON2 (paraoxonase 2) Ser311Cys and Arg/Arg of ADRB3 (beta3-adrenergic receptor) Trp64Arg, were independently associated with incident cardiac end-point, with respective hazard ratios (95% confidence interval) of 1.70 (1.10-2.61, P=0.037), 1.42 (1.08-1.88, P=0.013) and 3.84 (1.18-12.50, P=0.025). Analysis of the joint effect of the risk alleles showed significant increased risk of the cardiac end-point with increasing number of risk alleles (P<0.001). The adjusted risk for the cardiac end-point was 4.11 (P=0.002) for patients carrying four risk alleles compared with those carrying one or no risk allele. CONCLUSIONS: The independent risk conferred by genetic variants encoding pathways such as inflammation and lipid metabolism, not adequately reflected by conventional biomarkers, may identify high-risk individuals for intensified control of modifiable risk factors.
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