Literature DB >> 1427023

Two-locus models of disease.

R J Neuman1, J P Rice.   

Abstract

Most complex diseases have not been amenable to genetic analysis under the assumption of single locus or multifactorial models. Consequently, interest has turned to the consideration of the properties of oligogenic models. i.e., genetic models involving a small number of genes. Nine two-locus models of disease, representing both epistatic and heterogeneous genetic models, are investigated: three models of heterogeneity and six models of epistatis. For each model we derive formulas for the recurrence risk to various classes of relatives in terms of penetrances and gene frequencies. We also develop formulas for the components of variance for the epistatic models in terms of the same genetic parameters. The range of penetrances and the associated gene frequencies that predict a predetermined value for the population prevalence and recurrence risk to the sibling of proband are calculated for various rates of the prevalence and risk to sibs. It is found that for many of these genetic models, there is a very limited range of penetrances that fit a particular set of assumed risks. Estimated population prevalence and risks to sibs and monozygotic twins for bipolar and schizophrenia illness are used to test for compatibility with expected values for recurrence risks under these models.

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Year:  1992        PMID: 1427023     DOI: 10.1002/gepi.1370090506

Source DB:  PubMed          Journal:  Genet Epidemiol        ISSN: 0741-0395            Impact factor:   2.135


  42 in total

1.  Multipoint linkage-disequilibrium-mapping approach based on the case-parent trio design.

Authors:  K Y Liang; F C Hsu; T H Beaty; K C Barnes
Journal:  Am J Hum Genet       Date:  2001-03-15       Impact factor: 11.025

2.  Parametric and nonparametric multipoint linkage analysis with imprinting and two-locus-trait models: application to mite sensitization.

Authors:  K Strauch; R Fimmers; T Kurz; K A Deichmann; T F Wienker; M P Baur
Journal:  Am J Hum Genet       Date:  2000-05-04       Impact factor: 11.025

3.  The relationship between the sibling recurrence-risk ratio and genotype relative risk.

Authors:  B A Rybicki; R C Elston
Journal:  Am J Hum Genet       Date:  2000-02       Impact factor: 11.025

4.  Generalized T2 test for genome association studies.

Authors:  Momiao Xiong; Jinying Zhao; Eric Boerwinkle
Journal:  Am J Hum Genet       Date:  2002-03-29       Impact factor: 11.025

5.  Detecting genome-wide epistases based on the clustering of relatively frequent items.

Authors:  Minzhu Xie; Jing Li; Tao Jiang
Journal:  Bioinformatics       Date:  2011-11-03       Impact factor: 6.937

6.  BOOST: A fast approach to detecting gene-gene interactions in genome-wide case-control studies.

Authors:  Xiang Wan; Can Yang; Qiang Yang; Hong Xue; Xiaodan Fan; Nelson L S Tang; Weichuan Yu
Journal:  Am J Hum Genet       Date:  2010-09-10       Impact factor: 11.025

7.  Test for interaction between two unlinked loci.

Authors:  Jinying Zhao; Li Jin; Momiao Xiong
Journal:  Am J Hum Genet       Date:  2006-09-21       Impact factor: 11.025

8.  Backward genotype-trait association (BGTA)-based dissection of complex traits in case-control designs.

Authors:  Tian Zheng; Hui Wang; Shaw-Hwa Lo
Journal:  Hum Hered       Date:  2006-11-15       Impact factor: 0.444

9.  Restricted parameter space models for testing gene-gene interaction.

Authors:  Minsun Song; Dan L Nicolae
Journal:  Genet Epidemiol       Date:  2009-07       Impact factor: 2.135

10.  Testing gene-gene interactions in genome wide association studies.

Authors:  Jie Kate Hu; Xianlong Wang; Pei Wang
Journal:  Genet Epidemiol       Date:  2014-01-15       Impact factor: 2.135

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