The Bogalusa Heart Study – Early Natural History of Arteriosclerosis

Investigators
Gerald S. Berenson, MD, Principal Investigator
Sathanur R. Srinivasan, PhD, Co-Investigator
Wei Chen, MD, PhD, Co-Investigator
Eric Boerwinkle, PhD, Co-Investigator
Leann Myers, PhD, Co-Investigator

Funding Agent
National Heart, Lung, and Blood Institute, NIHParticipating Institutes
Human Genetics Center, University of Texas Houston Health Science Center

Description
The Bogalusa Heart Study is a longitudinal biracial (black-white) community study committed to understand the early natural history of arteriosclerosis from childhood to adulthood in a cohort now reaching early middle age. The role of genetics in the etiology and pathophysiology of atherosclerosis is proving to be important. However, the genetic loci linking susceptibility to early, underlying subclinical changes in cardiac and vascular structure and function is almost unknown. The specific aims of the proposed research are: 1) to locate loci indicating susceptibility for subclinical measures of structure-function characteristics of the cardiovascular (C-V) system, independent of C-V risk factor phenotypes, such as dyslipidemia, adiposity, hypertension and insulin resistance; and 2) to examine the influence of candidate genes on subclinical measures and to test for the dependence of any identified association or linkage on the long-term burden of C-V risk factor phenotypes. The sib-pair cohort (1374 sib-pairs, 36% black) followed since childhood consists of 1591 siblings. The proposed major subclinical C-V outcome variables include carotid artery intima-media thickness and elasticity, left ventricular structure and function, brachial artery compliance, and arterial pulse wave velocity. These measures are available on 35% of the sib-pair cohort, while genome-wide scan microsatellite markers (n=368, an average spacing of 9.0 cM) are available on entire cohort. Thirteen candidate genes with 30 polymorphsims related to multiple phenotypic manifestations of the metabolic syndrome X and to the various C-V structure-functions have been selected. The C-V risk factor phenotypes to be measured concurrently with C-V outcome variables include obesity measures, blood pressure, lipoprotein variables, insulin, glucose, interleukin-6, C-reactive protein, and E-selectin. Data analysis will focus on genome scan linkage analysis and candidate gene (single polymorphism, haplotypes, and gene-gene interaction) association/linkage analysis to address the specific aims. In addition, a combined association and linkage model will be performed using candidate genes and genome scan markers to examine the putative genetic loci in more detail. The availability of a longitudinal, biracial database since childhood with serial measurements of major C-V risk factor phenotypes related to metabolic syndrome provides an unique and innovative approach to gain insights into the contribution of genes to the evolution of underlying C-V disease.