Literature DB >> 20855570

General epistatic models of the risk of complex diseases.

Yun S Song1, Fulton Wang, Montgomery Slatkin.   

Abstract

The range of possible gene interactions in a multilocus model of a complex inherited disease is studied by exploring genotype-specific risks subject to the constraint that the allele frequencies and marginal risks are known. We quantify the effect of gene interactions by defining the interaction ratio, CR=KR/KRI, where KR is the recurrence risk to relatives with relationship R for the true model and KRI is the recurrence risk to relatives for a multiplicative model with the same marginal risks. We use a Markov chain Monte Carlo (MCMC) procedure to sample from the space of possible models. We find that the average of CR increases with the number of loci for both low frequency (p=0.03) and higher frequency (p=0.25) causative alleles. Furthermore, the probability that CR>1 is nearly 1. Similar results are obtained when more weight is given to risk models that are closer to the comparable multiplicative model. These results imply that, in general, gene interactions will result in greater heritability of a complex inherited disease than is expected on the basis of a multiplicative model of interactions and hence may provide a partial explanation for the problem of missing heritability of complex diseases.

Entities:  

Mesh:

Year:  2010        PMID: 20855570      PMCID: PMC2998324          DOI: 10.1534/genetics.110.119008

Source DB:  PubMed          Journal:  Genetics        ISSN: 0016-6731            Impact factor:   4.562


  16 in total

1.  A perspective on epistasis: limits of models displaying no main effect.

Authors:  Robert Culverhouse; Brian K Suarez; Jennifer Lin; Theodore Reich
Journal:  Am J Hum Genet       Date:  2002-01-08       Impact factor: 11.025

Review 2.  Epistasis: what it means, what it doesn't mean, and statistical methods to detect it in humans.

Authors:  Heather J Cordell
Journal:  Hum Mol Genet       Date:  2002-10-01       Impact factor: 6.150

3.  Genome-wide strategies for detecting multiple loci that influence complex diseases.

Authors:  Jonathan Marchini; Peter Donnelly; Lon R Cardon
Journal:  Nat Genet       Date:  2005-03-27       Impact factor: 38.330

4.  Genotypic probabilities for pairs of inbred relatives.

Authors:  Wenlei Liu; B S Weir
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2005-07-29       Impact factor: 6.237

5.  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

6.  Bayesian inference of epistatic interactions in case-control studies.

Authors:  Yu Zhang; Jun S Liu
Journal:  Nat Genet       Date:  2007-08-26       Impact factor: 38.330

Review 7.  Epistasis--the essential role of gene interactions in the structure and evolution of genetic systems.

Authors:  Patrick C Phillips
Journal:  Nat Rev Genet       Date:  2008-11       Impact factor: 53.242

Review 8.  Genetic mapping in human disease.

Authors:  David Altshuler; Mark J Daly; Eric S Lander
Journal:  Science       Date:  2008-11-07       Impact factor: 47.728

Review 9.  Epistasis: too often neglected in complex trait studies?

Authors:  Orjan Carlborg; Chris S Haley
Journal:  Nat Rev Genet       Date:  2004-08       Impact factor: 53.242

Review 10.  Data and theory point to mainly additive genetic variance for complex traits.

Authors:  William G Hill; Michael E Goddard; Peter M Visscher
Journal:  PLoS Genet       Date:  2008-02-29       Impact factor: 5.917

View more
  9 in total

1.  The mystery of missing heritability: Genetic interactions create phantom heritability.

Authors:  Or Zuk; Eliana Hechter; Shamil R Sunyaev; Eric S Lander
Journal:  Proc Natl Acad Sci U S A       Date:  2012-01-05       Impact factor: 11.205

2.  Misspecification in Mixed-Model-Based Association Analysis.

Authors:  Willem Kruijer
Journal:  Genetics       Date:  2015-11-19       Impact factor: 4.562

Review 3.  Missing heritability of complex diseases: Enlightenment by genetic variants from intermediate phenotypes.

Authors:  Adrián Blanco-Gómez; Sonia Castillo-Lluva; María Del Mar Sáez-Freire; Lourdes Hontecillas-Prieto; Jian Hua Mao; Andrés Castellanos-Martín; Jesus Pérez-Losada
Journal:  Bioessays       Date:  2016-05-31       Impact factor: 4.345

Review 4.  Challenges and opportunities in genome-wide environmental interaction (GWEI) studies.

Authors:  Hugues Aschard; Sharon Lutz; Bärbel Maus; Eric J Duell; Tasha E Fingerlin; Nilanjan Chatterjee; Peter Kraft; Kristel Van Steen
Journal:  Hum Genet       Date:  2012-07-04       Impact factor: 4.132

5.  Three legs of the missing heritability problem.

Authors:  Lucas J Matthews; Eric Turkheimer
Journal:  Stud Hist Philos Sci       Date:  2022-05-06       Impact factor: 1.379

6.  Identification of QTL for UV-protective eye area pigmentation in cattle by progeny phenotyping and genome-wide association analysis.

Authors:  Hubert Pausch; Xiaolong Wang; Simone Jung; Dieter Krogmeier; Christian Edel; Reiner Emmerling; Kay-Uwe Götz; Ruedi Fries
Journal:  PLoS One       Date:  2012-05-02       Impact factor: 3.240

7.  T2DM: Why Epigenetics?

Authors:  Delphine Fradin; Pierre Bougnères
Journal:  J Nutr Metab       Date:  2011-11-03

8.  Candidate gene sequencing of SLC11A2 and TMPRSS6 in a family with severe anaemia: common SNPs, rare haplotypes, no causative mutation.

Authors:  Anita Kloss-Brandstätter; Gertraud Erhart; Claudia Lamina; Bernhard Meister; Margot Haun; Stefan Coassin; Markus Seifert; Andreas Klein-Franke; Bernhard Paulweber; Lyudmyla Kedenko; Barbara Kollerits; Dorine W Swinkels; Sita H Vermeulen; Tessel E Galesloot; Florian Kronenberg; Günter Weiss
Journal:  PLoS One       Date:  2012-04-11       Impact factor: 3.240

9.  High order gene-gene interactions in eight single nucleotide polymorphisms of renin-angiotensin system genes for hypertension association study.

Authors:  Cheng-Hong Yang; Yu-Da Lin; Shyh-Jong Wu; Li-Yeh Chuang; Hsueh-Wei Chang
Journal:  Biomed Res Int       Date:  2015-04-19       Impact factor: 3.411

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.