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Article details
Title
Fine mapping of a linkage peak with integration of lipid traits identifies novel coronary artery disease genes on chromosome 5
Published in
BMC Genetics, February 2012
DOI 10.1186/1471-2156-13-12
Pubmed ID
Authors
Abstract

Coronary artery disease (CAD), and one of its intermediate risk factors, dyslipidemia, possess a demonstrable genetic component, although the genetic architecture is incompletely defined. We previously reported a linkage peak on chromosome 5q31-33 for early-onset CAD where the strength of evidence for linkage was increased in families with higher mean low density lipoprotein-cholesterol (LDL-C). Therefore, we sought to fine-map the peak using association mapping of LDL-C as an intermediate disease-related trait to further define the etiology of this linkage peak. The study populations consisted of 1908 individuals from the CATHGEN biorepository of patients undergoing cardiac catheterization; 254 families (N = 827 individuals) from the GENECARD familial study of early-onset CAD; and 162 aorta samples harvested from deceased donors. Linkage disequilibrium-tagged SNPs were selected with an average of one SNP per 20 kb for 126.6-160.2 MB (region of highest linkage) and less dense spacing (one SNP per 50 kb) for the flanking regions (117.7-126.6 and 160.2-167.5 MB) and genotyped on all samples using a custom Illumina array. Association analysis of each SNP with LDL-C was performed using multivariable linear regression (CATHGEN) and the quantitative trait transmission disequilibrium test (QTDT; GENECARD). SNPs associated with the intermediate quantitative trait, LDL-C, were then assessed for association with CAD (i.e., a qualitative phenotype) using linkage and association in the presence of linkage (APL; GENECARD) and logistic regression (CATHGEN and aortas).

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Professor 6 21%
Other 3 11%
Student > Ph. D. Student 3 11%
Researcher 3 11%
Professor > Associate Professor 3 11%
Other 6 21%
Unknown 4 14%
Readers by discipline
Readers by discipline Count As %
Medicine and Dentistry 8 29%
Biochemistry, Genetics and Molecular Biology 6 21%
Agricultural and Biological Sciences 3 11%
Nursing and Health Professions 1 4%
Immunology and Microbiology 1 4%
Other 2 7%
Unknown 7 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 February 2012.
All research outputs
#27,665,137
of 33,493,714 outputs
Outputs from BMC Genetics
#879
of 1,144 outputs
Outputs of similar age
#164,105
of 198,997 outputs
Outputs of similar age from BMC Genetics
#18
of 24 outputs
Altmetric has tracked 33,493,714 research outputs across all sources so far. This one is in the 9th percentile – i.e., 9% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,144 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one is in the 12th percentile – i.e., 12% of its peers scored the same or lower than it.
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We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.