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Heritability and genetic associations of triglyceride and HDL-C levels using pedigree-based and empirical kinships

Overview of attention for article published in BMC Proceedings, September 2018
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Title
Heritability and genetic associations of triglyceride and HDL-C levels using pedigree-based and empirical kinships
Published in
BMC Proceedings, September 2018
DOI 10.1186/s12919-018-0133-x
Pubmed ID
Authors

Nicholas B. Blackburn, Arthur Porto, Juan M. Peralta, John Blangero

Abstract

The heritability of a phenotype is an estimation of the percent of variance in that phenotype that is attributable to additive genetic factors. Heritability is optimally estimated in family-based sample populations. Traditionally, this involves use of a pedigree-based kinship coefficient generated from the collected genealogical relationships between family members. An alternative, when dense genotype data are available, is to directly measure the empirical kinship between samples. This study compares the use of pedigree and empirical kinships in the GAW20 data set. Two phenotypes were assessed: triglyceride levels and high-density lipoprotein cholesterol (HDL-C) levels pre- and postintervention with the cholesterol-reducing drug fenofibrate. Using SOLAR (Sequential Oligogenic Linkage Analysis Routines), pedigree-based kinships and empirically calculated kinships (using IBDLD and LDAK) were used to calculate phenotype heritability. In addition, a genome-wide association study was conducted using each kinship model for each phenotype to identify genetic variants significantly associated with phenotypic variation. The variant rs247617 was significantly associated with HDL-C levels both pre- and post-fenofibrate intervention. Overall, the phenotype heritabilities calculated using pedigree based kinships or either of the empirical kinships generated using IBDLD or LDAK were comparable. Phenotype heritabilities estimated from empirical kinships generated using IBDLD were closest to the pedigree-based estimations. Given that there was not an appreciable amount of unknown relatedness between the pedigrees in this data set, a large increase in heritability in using empirical kinship was not expected, and our calculations support this. Importantly, these results demonstrate that when sufficient genotypic data are available, empirical kinship estimation is a practical alternative to using pedigree-based kinships.

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The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 30%
Student > Doctoral Student 2 20%
Researcher 2 20%
Professor 1 10%
Other 1 10%
Other 0 0%
Unknown 1 10%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 30%
Medicine and Dentistry 2 20%
Pharmacology, Toxicology and Pharmaceutical Science 1 10%
Philosophy 1 10%
Agricultural and Biological Sciences 1 10%
Other 1 10%
Unknown 1 10%
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 September 2018.
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#20,535,139
of 23,105,443 outputs
Outputs from BMC Proceedings
#322
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Outputs of similar age
#297,106
of 341,524 outputs
Outputs of similar age from BMC Proceedings
#11
of 15 outputs
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