Original Contributions |
From the Department of Human Genetics, University of Michigan, Ann Arbor, Mich (S.L.R.K., M.B.H., C.F.S.) and the Department of Human Genetics, University of Pittsburgh, Pittsburgh, Penn (R.E.F.).
Correspondence to Dr. Sharon L. R. Kardia, Department of Human Genetics, 4708 Medical Science Building II, University of Michigan Medical School, Ann Arbor, MI 48109-0618. E-mail skardia{at}umich.edu
AbstractAn important research
question in the study of the genetics of coronary artery
disease (CAD) is whether information about genetic variation will
improve our ability to predict CAD beyond established risk factors.
This question is especially relevant to the goal of identifying young,
asymptomatic adults with coronary
atherosclerosis who would benefit most from
interventions to reduce risk. Coronary artery calcification
(CAC) detected by electron-beam computed tomography is a relatively new
method for detecting coronary atherosclerosis
in asymptomatic individuals that has been shown to be a
more accurate indicator of coronary
atherosclerosis in asymptomatic individuals
than other noninvasive techniques. In a study of
asymptomatic women (n=169) and men (n=160) between the ages
of 20 and 59 representative of the Rochester, Minnesota
population, we used logistic regression to ask whether the most common
Apolipoprotein (Apo) E genotypes
(
3/2,
3/3, and
4/3) predict the presence of CAC. The addition of
information about ApoE genotypes to logistic
models containing each separate risk factor did not improve prediction
of CAC (P>0.10 in both women and men). However, there
was significant evidence (P<0.10) that associations
between variation in the probability of having CAC and variation in
body mass index, plasma total cholesterol, and
plasma ApoB in men and body mass index, plasma
triglycerides, plasma ApoA1, and plasma ApoE in women were
dependent on ApoE genotype. Thus, variation in
the gene coding for ApoE may play a role in determining the
contribution of established risk factors to risk of CAC.
Key Words: atherosclerosis risk factors genetics calcium computed tomography
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