Current strategies to identify children at increased risk of premature atherosclerosis, based on family history and selective screening for hyperlipidemia, have limited sensitivity and specificity. The goals of this research are to identify new genotypic and phenotypic biomarkers for increased risk of premature atherosclerosis; to test hypotheses regarding associations between behavioral/environmental factors and biomarkers of increased risk; and to examine the stability over time of phenotypic biomarkers. We will enroll and follow yearly for three years a total of 400 children aged 4-15 and their parents, with 100 children in each of the following groups: (i) Children with positive family history and elevated serum LDL; (ii) children with negative family history and elevated LDL; (iii) children with positive family history and normal LDL; and (iv) children with negative family history and normal LDL. Thus, the specific aims will be tested in a design based on 4 groups of families so that the influence of candidate biomarkers on family risk can be estimated separately in hyperlipidemic and normolipidemic children. Estimates of statistical power and least detectable differences indicate that this sample size is sufficient. We propose to measure family history of ischemic heart disease using a validated questionnaire and clinical and arteriographic data and to assay the following genotype/haplotypes: fibrinogen, ACE, lipoprotein lipase, LDL receptor, apo B, and apo E isoforms; the following phenotypes: serum fibrinogen, LDL particle size, serum Lp(a), serum apo Al, post prandial and fasting lipids (total and HDL cholesterol and triglycerides), and blood pressure; and the following behavioral/environmental factors: body composition, aerobic fitness, diet, and exposure to environmental cigarette smoke. Separately for hyperlipidemic and normolipidemic children, we will test hypotheses concerning associations with family history of genotypic (Aim 1) and phenotypic (Aim 2) characteristics; between genotypes and phenotypes (Aim 3); and between behavioral!environmental factors and phenotypes (Aim 4); and estimate the stability of phenotypic biomarkers over time (Aim 5). The main statistical methods for testing associations will be linear and logistic regression with adjustment for covariates. Analyses will allow for careful delineation of the influence of each biomarker on family history as well as on the expression of other markers. When this research is complete, we hope to have identified new biomarkers for premature atherosclerosis and to have gained new knowledge that will improve targeting of prevention strategies for the population as a whole and improve identification and intervention strategies for children specifically.
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