Modeling DNA Diversity in Reverse Cholesterol Transport

NCT ID: NCT00064493

Last Updated: 2021-10-01

Basic Information

• Recruitment Status: COMPLETED
• Total Enrollment: 4146 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2003-06-30
• Study Completion Date: 2008-05-31

Brief Summary

To identify genetic variation in reverse cholesterol transport (RCT) and its role in cardiovascular disease and atherosclerosis.

Detailed Description

BACKGROUND:

The collaborative research project will address a major problem in genetic epidemiology, namely the development of strategies to rationally identify and select sites or combinations of sites for genotype-phenotype studies that will be most relevant for predicting and understanding the role of genes in physiological phenotypes. Knowledge could be advanced in both specific and general terms. The project will focus on the genetic architecture of 62 genes either known or hypothesized to have a role in cholesterol transport. The data and conclusions generated by this project will enrich our understanding of both the extant genetic variation in these genes and the functional or causative relationships between such variation and phenotypes measured at a variety of organizational scales (pathway, systemic and clinical outcome). The additional focus on environmental interaction terms will enhance understanding of specific gene x environment interactions in the cholesterol transport system. The project involves three collaborating grants: R01HL72810 to Eric A. Boerwinkle at the University of Texas School of Public Health; R01HL72905 to Charles F. Sing at the University of Michigan at Ann Arbor; and R01HL72904 to Andrew Clark at Cornell University in Ithaca, New York.

DESIGN NARRATIVE:

This Collaborative Research Project will model DNA diversity in Reverse Cholesterol Transport (RCT) by exploring the genetic basis underlying this pathway and its contribution to atherosclerosis risk and cardiovascular disease (CVD). Given the progress of the Human Genome Project and the development of laboratory and analytic resources, the delineation of a gene's complete genetic architecture and contribution to individual differences within a population becomes (theoretically) feasible. This study will explore the variation in 8 of 62 candidate genes that will be screened using a battery of single nucleotide polymorphisms (SNPs). The eight genes (and the 6-10 SNPs within each) will be chosen based upon association with a surrogate quantitative trait (using a cholesterol efflux assay). The genes will be exhaustively characterized by analysis of DNA sequence variation, linkage disequilibrium (LD), and haplotypes in samples from the community-based CARDIA study. Genotype-phenotype relationships will be determined using analytic methods that take advantage of population/evolutionary history, underlying complexity, and other innovative approaches.

Component 1 of this Collaborative Research Project under Eric Boerwinkle will generate a large amount of new data on complex patterns of variation in a substantial number of genes. A major objective is to develop methods for analyzing these data to find etiologically relevant aspects of variation. For each of 62 candidate genes, the initial responsibility of Component 2 under Andrew Clark is to analyze the distribution of single DNA site and haplotype variation in terms of the population processes responsible for that variation. The investigators will develop systematic methods to identify subsets of sites that most fully capture the haplotypic structure of the data and thereby reduce the dimensionality of the variation. These methods will be applied to haplotype and genotype variation in a population-based sample of 2007 African-Americans and 2139 European-Americans from the CARDIA study. Single nucleotide polymorphisms frequency spectra, linkage disequilibrium and the block-wise structure of haplotypes will be quantified and related to expectations of population genetic theory. Novel approaches to genotype-phenotype associations will be pursued, in close collaboration with Component 3, by testing the fit of the neutral site frequency spectrum to data stratified by phenotypic measures.

Conditions

Cardiovascular Diseases; Heart Diseases; Atherosclerosis

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: RETROSPECTIVE

Eligibility Criteria

Inclusion Criteria

No eligibility criteria

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 30 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

National Heart, Lung, and Blood Institute (NHLBI)

NIH

Sponsor Role: collaborator

The University of Texas Health Science Center, Houston

OTHER

Sponsor Role: lead

Responsible Party

Eric Boerwinkle

Professor - School of Public Health

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

Eric Boerwinkle

Role: PRINCIPAL_INVESTIGATOR

University of Texas School of Public Health

Andrew Clark

Role: PRINCIPAL_INVESTIGATOR

Cornell University

Charles Sing

Role: PRINCIPAL_INVESTIGATOR

University of Michigan

References

Hamon SC, Stengard JH, Clark AG, Salomaa V, Boerwinkle E, Sing CF. Evidence for non-additive influence of single nucleotide polymorphisms within the apolipoprotein E gene. Ann Hum Genet. 2004 Nov;68(Pt 6):521-35. doi: 10.1046/j.1529-8817.2003.00112.x.

Reference Type: BACKGROUND

PMID: 15598211 (View on PubMed)

Klos KL, Hamon S, Clark AG, Boerwinkle E, Liu K, Sing CF. APOA5 polymorphisms influence plasma triglycerides in young, healthy African Americans and whites of the CARDIA Study. J Lipid Res. 2005 Mar;46(3):564-71. doi: 10.1194/jlr.M400437-JLR200. Epub 2004 Dec 16.

Reference Type: BACKGROUND

PMID: 15604515 (View on PubMed)

Other Identifiers

R01HL072810

Identifier Type: NIH

Identifier Source: secondary_id

View Link

1223

Identifier Type: -

Identifier Source: org_study_id