The long-term goal of this Multi-Institutional Research Project grant is to elucidate the genetic architecture of high density lipoprotein-cholesterol (HDL-C) in the general population and to evaluate the added value of this genetic information for predicting incident coronary heart disease (CHD) beyond the established risk factors. Special emphasis will be given to the contribution of low frequency variation, and variant-variant and variant-environment interactions to the genetic architecture of HDL-C.
In AIM 1 we will resequence 20 HDL-related genes in a sample of 400 individuals from the Coronary Artery Risk Development in Young Adults (CARDIA) cohort who consistently have high (top quartile;n=200) or low (bottom quartile;n=200) plasma HDL-C concentrations across multiple examinations. The genes to be studied have been selected and prioritized based on three criteria: i) findings about their association with HDL-C in the first cycle of research funding of this project, ii) as being under replicated linkage peaks and resulting in changes in HDL-C levels in genetically modified mice, and iii) as being replicated in genome-wide association studies of HDL-C. To detect evidence for the contribution of low frequency variations in these genes to HDL-C variation we will test whether the sequence variation in one extreme of the HDL-C distribution differs from the other extreme and whether the distributions in the extremes differ from neutral expectations. Neither genome-wide association studies or sequencing the extremes of the HDL-C distribution will reveal the contribution of variants to the genetic architecture in the population-at-large. Therefore, we will genotype the entire CARDIA cohort for the genetic variations characterized by the resequencing carried out in AIM 1, and use all of the genotype data (i.e. SNPs and insertion/deletions) to quantify the marginal genotypic (AIM 2) and interaction (AIM 3) effects of each gene variant on inter-individual variation in plasma concentrations of HDL-C in the population-at-large.
AIM 3 will consider interactions of the effects of variations in each gene with the effects of variations in the same gene and in other genes (i.e. variant-variant interactions);with indices of environmental variations such as gender, weight, smoking and alcohol consumption (i.e. variant-environment interaction) and with time (i.e. longitudinal analyses).
AIM 4 will evaluate the ability of the variations identified in AIMS 2 and 3 as contributing to the genetic architecture of HDL-C: i) to predict whether a person will have low HDL-C (<40 mg/dl) in the large Atherosclerosis Risk in Communities (ARIC) study (n=15,792), and ii) to predict incident CHD in the ARIC study beyond that afforded by the established risk factors. The proposed research is made possible by three linked R01s from Drs. Boerwinkle, Clark and Sing. Reduced high-density lipoprotein cholesterol (HDL-C) is a risk factor for coronary heart disease (CHD). The goal of this research program is to identify the genes influencing HDL-C in the population-at-large, and to ask if these genetic variations predict CHD beyond the traditional risk factors. This research not only considers the individual effects of variation in each gene, but their interactions with other genes and with the environment.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
5R01HL072904-07
Application #
7848941
Study Section
Cardiovascular and Sleep Epidemiology (CASE)
Program Officer
Sholinsky, Phyliss
Project Start
2003-06-01
Project End
2013-02-28
Budget Start
2010-03-01
Budget End
2011-02-28
Support Year
7
Fiscal Year
2010
Total Cost
$322,783
Indirect Cost
Name
Cornell University
Department
Biochemistry
Type
Schools of Arts and Sciences
DUNS #
872612445
City
Ithaca
State
NY
Country
United States
Zip Code
14850
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Ma, Li; Clark, Andrew G; Keinan, Alon (2013) Gene-based testing of interactions in association studies of quantitative traits. PLoS Genet 9:e1003321
Chakravarti, Aravinda; Clark, Andrew G; Mootha, Vamsi K (2013) Distilling pathophysiology from complex disease genetics. Cell 155:21-6
Ma, Li; Brautbar, Ariel; Boerwinkle, Eric et al. (2012) Knowledge-driven analysis identifies a gene-gene interaction affecting high-density lipoprotein cholesterol levels in multi-ethnic populations. PLoS Genet 8:e1002714
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Coventry, Alex; Bull-Otterson, Lara M; Liu, Xiaoming et al. (2010) Deep resequencing reveals excess rare recent variants consistent with explosive population growth. Nat Commun 1:131
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Nielsen, Rasmus; Hubisz, Melissa J; Hellmann, Ines et al. (2009) Darwinian and demographic forces affecting human protein coding genes. Genome Res 19:838-49

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