Literature DB >> 3327665

Genetic architecture of inter-individual variability in apolipoprotein, lipoprotein and lipid phenotypes.

C F Sing1, E A Boerwinkle.   

Abstract

Phenotypes that predict coronary heart disease (CHD) are the consequence of interactions between many genetic and environmental factors. Quantitative measures of plasma apolipoproteins, lipoproteins and lipids are examples of phenotypes that link genetic and environmental factors to the CHD end-point. Population studies in Hawaii, Michigan and elsewhere have established that a significant fraction of variability in these phenotypes is attributable to genetic differences among individuals. Recent advances in molecular biology provide measures of the gene loci that code for the apolipoproteins, the cellular receptors for lipoprotein particles and the catalysts and cofactors in lipoprotein metabolism. By measuring polymorphic protein variability and restriction site variability in small regions of DNA known to contain genes that code for the proteins involved in these functions, it is possible to assign polygenetic effects to specific alleles or haplotypes. This 'measured genotype' approach may be used to study the genetic architecture (number of loci involved, the frequencies and effects of their alleles, and the type of loci, i.e., structural or regulatory) of quantitative variation in the plasma apolipoproteins, lipoproteins and lipids. This paper reviews statistical models, sampling designs and results of studies designed to estimate the genetic architecture of selected apolipoproteins, lipoproteins and lipids. The usefulness of these studies for answering questions about the prediction of CHD in the population, the family and the individual are discussed and the directions that human quantitative genetic studies will take in the future are considered.

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Year:  1987        PMID: 3327665     DOI: 10.1002/9780470513507.ch7

Source DB:  PubMed          Journal:  Ciba Found Symp        ISSN: 0300-5208


  5 in total

1.  Complex adaptive system models and the genetic analysis of plasma HDL-cholesterol concentration.

Authors:  Thomas J Rea; Christine M Brown; Charles F Sing
Journal:  Perspect Biol Med       Date:  2006       Impact factor: 1.416

2.  The contribution of individual and pairwise combinations of SNPs in the APOA1 and APOC3 genes to interindividual HDL-C variability.

Authors:  C M Brown; T J Rea; S C Hamon; J E Hixson; E Boerwinkle; A G Clark; C F Sing
Journal:  J Mol Med (Berl)       Date:  2006-05-17       Impact factor: 4.599

Review 3.  Creating animal models of genetic disease.

Authors:  R P Erickson
Journal:  Am J Hum Genet       Date:  1988-11       Impact factor: 11.025

4.  The ClinSeq Project: piloting large-scale genome sequencing for research in genomic medicine.

Authors:  Leslie G Biesecker; James C Mullikin; Flavia M Facio; Clesson Turner; Praveen F Cherukuri; Robert W Blakesley; Gerard G Bouffard; Peter S Chines; Pedro Cruz; Nancy F Hansen; Jamie K Teer; Baishali Maskeri; Alice C Young; Teri A Manolio; Alexander F Wilson; Toren Finkel; Paul Hwang; Andrew Arai; Alan T Remaley; Vandana Sachdev; Robert Shamburek; Richard O Cannon; Eric D Green
Journal:  Genome Res       Date:  2009-07-14       Impact factor: 9.043

5.  Strategies and issues in the detection of pathway enrichment in genome-wide association studies.

Authors:  Mun-Gwan Hong; Yudi Pawitan; Patrik K E Magnusson; Jonathan A Prince
Journal:  Hum Genet       Date:  2009-05-01       Impact factor: 4.132

  5 in total

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