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Genomic Dissection of a QTL Affecting the Lipid Profile

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ClinicalTrials.gov Identifier: NCT00064688
Recruitment Status : Withdrawn (This protocol was created to support work as part of an NIH-funded study.)
First Posted : July 14, 2003
Last Update Posted : September 10, 2015
Sponsor:
Collaborator:
National Heart, Lung, and Blood Institute (NHLBI)
Information provided by (Responsible Party):
Medical College of Wisconsin

Brief Summary:
To search for the genetic cause of the metabolic syndrome, a lipid disorder that poses a major risk for coronary heart disease.

Condition or disease
Cardiovascular Diseases Heart Diseases Obesity Hyperlipidemia, Familial Combined

Detailed Description:

BACKGROUND:

The metabolic syndrome is a common disorder posing a significant major risk for coronary heart disease and early mortality in the Western hemisphere. Central to its cardiovascular complications is the association of the syndrome with the specific abnormalities in plasma lipid and lipoprotein profiles including increased plasma triglycerides, decreased HDL cholesterol, and predominance of dense lipoprotein particles. In search for the genetic etiology of this lipid disorder, the investigators identified a quantitative trait locus (QTL) on human chromosome 7q36 strongly linked to variation in plasma lipid levels. They hypothesize that this QTL contains genetic variants that contribute to alterations in biologic pathways underlying the genesis of the lipid disorder.

DESIGN NARRATIVE:

The study will search for the genetic cause of the metabolic syndrome, a lipid disorder that poses a major risk for coronary heart disease. The investigators have identified a quantitative trait locus (QTL) on human chromosome 7q36 strongly linked to variation in plasma lipid levels. The investigators hypothesize that this QTL contains genetic variants that contribute to alterations in biologic pathways underlying the genesis of the lipid disorder. To test for this hypothesis, they propose a comprehensive approach utilizing established resources and expertise to identify the functional sequence variants within this QTL. Specifically, they will 1.) identify single nucleotide polymorphisms (SNPs) and their haplotype and linkage disequilibrium structure across the entire QTL region; 2.) Analyze association of informative SNPs with plasma triglyceride levels, LDL levels, and lipoprotein density fractions using variance component linkage/disequilibrium analyses; and 3.) Identify potentially functional sequence variants in associated genes or genomic regions using Bayesian quantitative trait nucleotide analysis. This comprehensive application of newly available genomic technologies, novel statistical approaches, the DNA and phenotypic information available, and the consortium of expertise assembled behind this project will ensure the successful elucidation of the genetic etiology of this lipid disorder and consequently the development of effective means for prevention and/or treatment of cardiovascular complications of the metabolic syndrome.


Study Type : Observational
Actual Enrollment : 0 participants
Observational Model: Cohort
Time Perspective: Cross-Sectional
Official Title: Genomic Dissection of a QTL Affecting the Lipid Profile
Study Start Date : July 2003
Actual Primary Completion Date : June 2008
Actual Study Completion Date : June 2008



Biospecimen Retention:   Samples With DNA
DNA


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Ages Eligible for Study:   Child, Adult, Senior
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Criteria
No eligibility criteria

Responsible Party: Medical College of Wisconsin
ClinicalTrials.gov Identifier: NCT00064688     History of Changes
Other Study ID Numbers: 1230
R01HL074168 ( U.S. NIH Grant/Contract )
First Posted: July 14, 2003    Key Record Dates
Last Update Posted: September 10, 2015
Last Verified: September 2015

Additional relevant MeSH terms:
Cardiovascular Diseases
Heart Diseases
Hyperlipidemias
Hyperlipoproteinemias
Hyperlipidemia, Familial Combined
Dyslipidemias
Lipid Metabolism Disorders
Metabolic Diseases
Lipid Metabolism, Inborn Errors
Metabolism, Inborn Errors
Genetic Diseases, Inborn