Clinical and genetic factors associated with lipoprotein-associated phospholipase A2 in the Framingham Heart Study☆
Received 1 July 2008; received in revised form 15 October 2008; accepted 16 October 2008. published online 09 January 2009.
Abstract
Objective
To conduct an investigation of clinical and genetic correlates of lipoprotein-associated phospholipase (Lp-PLA2) activity and mass in a large community-based cohort. Higher circulating Lp-PLA2 predicts cardiovascular disease risk, but sources of inter-individual variability are incompletely understood.
Methods
We conducted stepwise regression of clinical correlates of Lp-PLA2 in four Framingham Heart Study cohorts (n=8185; mean age 50±14 years, 53.8% women, 9.8% ethnic/racial minority cohort). We also conducted heritability and linkage analyses in Offspring and Generation 3 cohorts (n=6945). In Offspring cohort participants we performed association analyses (n=1535 unrelated) with 1943 common tagging SNPs in 233 inflammatory candidate genes.
Results
Sixteen clinical variables explained 57% of the variability in Lp-PLA2 activity; covariates associated with Lp-PLA2 mass were similar but only explained 27% of the variability. Multivariable-adjusted heritability estimates for Lp-PLA2 activity and mass were 41% and 25%, respectively. A linkage peak was observed for Lp-PLA2 activity (chromosome 6, LOD score 2.4). None of the SNPs achieved experiment-wide statistical significance, though 12 had q values <0.50, and hence we expect at least 50% of these associations to be true positives. The strongest multivariable-association with Lp-PLA2 activity was found for MEF2A (rs2033547; nominal p=3.20×10−4); SNP rs1051931 in PLA2G7 was nominally associated (p=1.26×10−3). The most significant association to Lp-PLA2 mass was in VEGFC (rs10520358, p=9.14×10−4).
Conclusions
Cardiovascular risk factors and genetic variation contribute to variability in Lp-PLA2 activity and mass. Our genetic association analyses need replication, which will be facilitated by web posting of our genetic association results.
aEvans Memorial Department of Medicine, Boston University, School of Medicine, Boston, MA, United States
bWhitaker Cardiovascular Institute, Boston University, School of Medicine, Boston, MA, United States
cDepartment of Preventive Medicine, Boston University, School of Medicine, Boston, MA, United States
dDepartment of Biostatistics, Boston University, School of Public Health, Boston, MA, United States
eDepartment of Epidemiology, Boston University, School of Public Health, Boston, MA, United States
fBoston University’s Mathematics and Statistics Department, Boston, MA, United States
gThe NHLBI’s Framingham Heart Study, Framingham, MA, United States
hDepartment of Medicine, Division of Cardiology, Emory University, School of Medicine, Harlow, UK
iCardiovascular, Metabolic and Genetic Support, GlaxoSmithKline R&D, Harlow, UK
Corresponding author at: Boston University, The Framingham Heart Study, 73 Mount Wayte Avenue, Suite 2, Framingham, MA 01702-5827, United States. Tel.: +1 617 638 8968; fax: +1 508 626 1262.
☆ Supported by NIH/NHLBI contract N01-HC-25195 and NIH grants HL64753 and HL076784 AG028321 (E.J.B.), HL70139 (R.S.V). NIH Research career award HL04334 (R.S.V.), NIH grant HG000848 (J.D.); Deutsche Forschungsgemeinschaft (German Research Foundation) Research Fellowship SCHN 1149/1-1 (RS). Portion of these analyses were conducted using the Boston University Linux Cluster for Genetic Analysis (LinGA) funded by the NIH NCRR (National Center for Research Resources) Shared Instrumentation grant (1S10RR163736-01A1).
ABSTRACT