Literature DB >> 20357478

Feasible and successful: genome-wide interaction analysis involving all 1.9 x 10(11) pair-wise interaction tests.

Michael Steffens1, Tim Becker, Thomas Sander, Rolf Fimmers, Christine Herold, Daniela A Holler, Costin Leu, Stefan Herms, Sven Cichon, Bastian Bohn, Thomas Gerstner, Michael Griebel, Markus M Nöthen, Thomas F Wienker, Max P Baur.   

Abstract

The Genome-Wide Association Study (GWAS) is the study design of choice for detecting common genetic risk factors for multifactorial diseases. The performance of full Genome-Wide Interaction Analyses (GWIA) has always been considered computationally challenging. Two-stage strategies to reduce the amount of numerical analysis require the detection of single marker effects or prior pathophysiological hypotheses before the analysis of interaction. This prevents the detection of pure epistatic effects. Our case-control study in idiopathic generalized epilepsy demonstrates that a full GWIA is feasible through use of data compression, specific data representation, interleaved data organization, and parallelization of the analysis on a multi-processor system. Following extensive quality control of the genotypes, our final list of top interaction hits contains only pairs of interacting SNPs with negligible marginal effects. The TOP HIT interaction was between a SNP-pair intragenic to gene DNER (chr 2) and gene CTNNA3 (chr 10). Both of these genes are functionally involved in neuronal migration, synaptogenesis, and the formation of neuronal circuits. Our results therefore indicate a possible interaction between these two genes in epileptogenesis. Results from GWAS are beginning to reveal a 'missing heritability' in complex traits and diseases. Systematic, hypothesis-free analysis of epistatic interaction (GWIA) may help to close this increasingly recognized gap in heritability. Copyright 2010 S. Karger AG, Basel.

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Year:  2010        PMID: 20357478     DOI: 10.1159/000295896

Source DB:  PubMed          Journal:  Hum Hered        ISSN: 0001-5652            Impact factor:   0.444


  10 in total

1.  A systematic eQTL study of cis-trans epistasis in 210 HapMap individuals.

Authors:  Jessica Becker; Jens R Wendland; Britta Haenisch; Markus M Nöthen; Johannes Schumacher
Journal:  Eur J Hum Genet       Date:  2011-08-17       Impact factor: 4.246

2.  Genome-wide association scan allowing for epistasis in type 2 diabetes.

Authors:  Jordana T Bell; Nicholas J Timpson; N William Rayner; Eleftheria Zeggini; Timothy M Frayling; Andrew T Hattersley; Andrew P Morris; Mark I McCarthy
Journal:  Ann Hum Genet       Date:  2010-12-06       Impact factor: 1.670

Review 3.  Using biological knowledge to uncover the mystery in the search for epistasis in genome-wide association studies.

Authors:  Marylyn D Ritchie
Journal:  Ann Hum Genet       Date:  2011-01       Impact factor: 1.670

4.  An examination of single nucleotide polymorphism selection prioritization strategies for tests of gene-gene interaction.

Authors:  Valentina Moskvina; Nick Craddock; Bertram Müller-Myhsok; Tony Kam-Thong; Elaine Green; Peter Holmans; Michael J Owen; Michael C O'Donovan
Journal:  Biol Psychiatry       Date:  2011-04-09       Impact factor: 13.382

5.  Hypothesis-based analysis of gene-gene interactions and risk of myocardial infarction.

Authors:  Gavin Lucas; Carla Lluís-Ganella; Isaac Subirana; Muntaser D Musameh; Juan Ramon Gonzalez; Christopher P Nelson; Mariano Sentí; Stephen M Schwartz; David Siscovick; Christopher J O'Donnell; Olle Melander; Veikko Salomaa; Shaun Purcell; David Altshuler; Nilesh J Samani; Sekar Kathiresan; Roberto Elosua
Journal:  PLoS One       Date:  2012-08-02       Impact factor: 3.240

6.  SNP-SNP interactions dominate the genetic architecture of candidate genes associated with left ventricular mass in African-Americans of the GENOA study.

Authors:  Kristin J Meyers; Jian Chu; Thomas H Mosley; Sharon L R Kardia
Journal:  BMC Med Genet       Date:  2010-11-10       Impact factor: 2.103

7.  Alzheimer's disease genes are associated with measures of cognitive ageing in the lothian birth cohorts of 1921 and 1936.

Authors:  Gillian Hamilton; Sarah E Harris; Gail Davies; David C Liewald; Albert Tenesa; John M Starr; David Porteous; Ian J Deary
Journal:  Int J Alzheimers Dis       Date:  2011-06-12

8.  Multifactor dimensionality reduction as a filter-based approach for genome wide association studies.

Authors:  Noffisat O Oki; Alison A Motsinger-Reif
Journal:  Front Genet       Date:  2011-11-21       Impact factor: 4.599

9.  Statistical epistasis and functional brain imaging support a role of voltage-gated potassium channels in human memory.

Authors:  Angela Heck; Christian Vogler; Leo Gschwind; Sandra Ackermann; Bianca Auschra; Klara Spalek; Björn Rasch; Dominique de Quervain; Andreas Papassotiropoulos
Journal:  PLoS One       Date:  2011-12-21       Impact factor: 3.240

10.  A comparison of methods for interpreting random forest models of genetic association in the presence of non-additive interactions.

Authors:  Alena Orlenko; Jason H Moore
Journal:  BioData Min       Date:  2021-01-29       Impact factor: 2.522

  10 in total

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