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dc.contributor.authorLucas, Gavin
dc.contributor.authorLluís-Ganella, Carla
dc.contributor.authorSubirana, Isaac
dc.contributor.authorMusameh, Muntaser D.
dc.contributor.authorGonzalez, Juan Ramon
dc.contributor.authorNelson, Christopher P.
dc.contributor.authorSentí, Mariano
dc.contributor.authorSchwartz, Stephen M.
dc.contributor.authorSiscovick, David
dc.contributor.authorO’Donnell, Christopher J.
dc.contributor.authorMelander, Olle
dc.contributor.authorSalomaa, Veikko
dc.contributor.authorSamani, Nilesh J.
dc.contributor.authorKathiresan, Sekar
dc.contributor.authorElosua, Roberto
dc.contributor.authorPurcell, Shaun
dc.contributor.authorAltshuler, David Matthew
dc.date.accessioned2013-03-26T19:56:41Z
dc.date.issued2012
dc.identifier.citationLucas, Gavin, Carla Lluís-Ganella, Isaac Subirana, Muntaser D. Musameh, Juan Ramon Gonzalez, Christopher P. Nelson, Mariano Sentí, et al. 2012. Hypothesis-based analysis of gene-gene interactions and risk of myocardial infarction. PLoS ONE 7(8): e41730.en_US
dc.identifier.issn1932-6203en_US
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:10465999
dc.description.abstractThe genetic loci that have been found by genome-wide association studies to modulate risk of coronary heart disease explain only a fraction of its total variance, and gene-gene interactions have been proposed as a potential source of the remaining heritability. Given the potentially large testing burden, we sought to enrich our search space with real interactions by analyzing variants that may be more likely to interact on the basis of two distinct hypotheses: a biological hypothesis, under which MI risk is modulated by interactions between variants that are known to be relevant for its risk factors; and a statistical hypothesis, under which interacting variants individually show weak marginal association with MI. In a discovery sample of 2,967 cases of early-onset myocardial infarction (MI) and 3,075 controls from the MIGen study, we performed pair-wise SNP interaction testing using a logistic regression framework. Despite having reasonable power to detect interaction effects of plausible magnitudes, we observed no statistically significant evidence of interaction under these hypotheses, and no clear consistency between the top results in our discovery sample and those in a large validation sample of 1,766 cases of coronary heart disease and 2,938 controls from the Wellcome Trust Case-Control Consortium. Our results do not support the existence of strong interaction effects as a common risk factor for MI. Within the scope of the hypotheses we have explored, this study places a modest upper limit on the magnitude that epistatic risk effects are likely to have at the population level (odds ratio for MI risk 1.3–2.0, depending on allele frequency and interaction model).en_US
dc.language.isoen_USen_US
dc.publisherPublic Library of Scienceen_US
dc.relation.isversionofdoi:10.1371/journal.pone.0041730en_US
dc.relation.hasversionhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC3410908/pdf/en_US
dash.licenseLAA
dc.subjectBiologyen_US
dc.subjectGeneticsen_US
dc.subjectHeredityen_US
dc.subjectComplex Traitsen_US
dc.subjectEpistasisen_US
dc.subjectGenotypesen_US
dc.subjectHuman Geneticsen_US
dc.subjectGenetic Association Studiesen_US
dc.subjectGenome-Wide Association Studiesen_US
dc.subjectPopulation Geneticsen_US
dc.subjectGenetic Polymorphismen_US
dc.subjectGenetics of Diseaseen_US
dc.subjectGenomicsen_US
dc.subjectGenome Analysis Toolsen_US
dc.subjectMedicineen_US
dc.subjectCardiovascularen_US
dc.subjectCoronary Artery Diseaseen_US
dc.subjectMyocardial Infarctionen_US
dc.subjectEpidemiologyen_US
dc.subjectGenetic Epidemiologyen_US
dc.titleHypothesis-Based Analysis of Gene-Gene Interactions and Risk of Myocardial Infarctionen_US
dc.typeJournal Articleen_US
dc.description.versionVersion of Recorden_US
dc.relation.journalPLoS ONEen_US
dash.depositing.authorAltshuler, David Matthew
dc.date.available2013-03-26T19:56:41Z
dc.identifier.doi10.1371/journal.pone.0041730*
dash.authorsorderedfalse
dash.contributor.affiliatedPurcell, Shaun M.
dash.contributor.affiliatedAltshuler, David


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