title: Abnormal lipoprotein(a) levels predict coronary artery calcification in Southeast Asians but not in Caucasians: use of noninvasive imaging for evaluation of an emerging risk factor.
abstract: Subclinical atherosclerosis can be quantified by coronary artery calcium (CAC) scoring. Due to its high specificity for atherosclerosis, CAC is an excellent phenotypic tool for the evaluation of emerging risk markers. Lipoprotein(a) [Lp(a)] is atherogenic due to the presence of apoB and may be thrombogenic through its apo(a) component. Lp(a) has been linked to cardiovascular events in Caucasians; however, its link to atherosclerosis in various ethnicities remains unclear. We evaluated the ability of Lp(a) mass to predict subclinical atherosclerosis in Southeast Asians and Caucasians, as measured by CAC. Traditional lipid measurements, Lp(a) measurements, and CAC by 64-slice multidetector computed tomography was performed in 103 consecutive patients in the USA and in 104 consecutive patients in Jakarta, Indonesia. Proportion of positive CAC and median CAC in Southeast Asians and in Caucasians was 61.5% and 63.1%, and 23.5 (interquartile range, 0-270) and 13 (interquartile range, 0-388), respectively. Significantly higher proportion of Southeast Asians had elevated Lp(a) levels, compared to Caucasians (51.0% vs. 29.2%; p = 0.005). In Southeast Asians, Lp(a) remained an independent predictor of CAC with an odds ratio of 4.97 (95% confidence interval, 1.56-15.88; p < 0.0001), but not in Caucasians. Receiver operating characteristic analysis showed an improvement in area under the curve from 0.81 to 0.86 (p = 0.05) when including Lp(a) in the predictive model in Southeast Asians. This translated to 7% of Southeast Asians reclassified to correct CAC status. Lp(a) measurements may have a role in risk stratification of Southeast Asians. Ethnic variation should be taken into account when considering the use of Lp(a) measurements in risk assessment.
authors.affiliation: Piedmont Heart Institute, 95 Collier Road, 2nd Floor Suite 2085, Atlanta, GA 30309, USA. Abhinav.Sharma@piedmont.org
authors.forename: Abhinav
authors.initials: A
authors.lastname: Sharma
authors.forename: Manoefris
authors.initials: M
authors.lastname: Kasim
authors.forename: Parag H
authors.initials: PH
authors.lastname: Joshi
authors.forename: Zhen
authors.initials: Z
authors.lastname: Qian
authors.forename: Eric
authors.initials: E
authors.lastname: Krivitsky
authors.forename: Kamran
authors.initials: K
authors.lastname: Akram
authors.forename: Sarah
authors.initials: S
authors.lastname: Rinehart
authors.forename: Gustavo
authors.initials: G
authors.lastname: Vazquez
authors.forename: Joseph
authors.initials: J
authors.lastname: Miller
authors.forename: Mohammad Saifur
authors.initials: MS
authors.lastname: Rohman
authors.forename: Szilard
authors.initials: S
authors.lastname: Voros
mesh_terms: D000328:Adult; D000368:Aged; D044466:Asian People; D015415:Biomarkers / Q000097:blood; D002114:Calcinosis / Q000097:blood* / Q000000981:diagnostic imaging / Q000208:ethnology*; D003324:Coronary Artery Disease / Q000097:blood* / Q000000981:diagnostic imaging / Q000208:ethnology*; D005260:Female; D005845:Georgia / Q000453:epidemiology; D006801:Humans; D007214:Indonesia / Q000453:epidemiology; D017270:Lipoprotein(a) / Q000097:blood*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D016017:Odds Ratio; D011237:Predictive Value of Tests; D012189:Retrospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D014057:Tomography, X-Ray Computed; D015854:Up-Regulation; D044465:White People
chemical_list: D015415:Biomarkers; D017270:Lipoprotein(a)