Hypothesis-based analysis of gene-gene interactions and risk of myocardial infarction
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- dc.contributor.author Lucas, Gavin, 1977-ca
- dc.contributor.author Lluís Ganella, Carla, 1984-ca
- dc.contributor.author Subirana Cachinero, Isaacca
- dc.contributor.author Musameh, Muntaser D.ca
- dc.contributor.author González Ruiz, Juan Ramónca
- dc.contributor.author Nelson, Christopher P.ca
- dc.contributor.author Sentí Clapés, Marianoca
- dc.contributor.author Myocardial Infarction Geneticsca
- dc.contributor.author Wellcome Trust Case Control Constortiumca
- dc.contributor.author Schwartz, Stephen Mca
- dc.contributor.author Siscovick, Davidca
- dc.contributor.author O'Donnell, Christopher Jca
- dc.contributor.author Melander, Olleca
- dc.contributor.author Salomaa, Veikkoca
- dc.contributor.author Purcell, Shaunca
- dc.contributor.author Altshuler, Davidca
- dc.contributor.author Samani, Nilesh J.ca
- dc.contributor.author Kathiresan, Sekarca
- dc.contributor.author Elosua Llanos, Robertoca
- dc.date.accessioned 2015-05-12T09:46:58Z
- dc.date.available 2015-05-12T09:46:58Z
- dc.date.issued 2012ca
- dc.description.abstract The 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
- dc.format.mimetype application/pdfca
- dc.identifier.citation Lucas G, Lluis-Ganella C, Subirana I, Musameh MD, Gonzalez JR, Nelson CP et al. Hypothesis-based analysis of gene-gene interactions and risk of myocardial infarction. PLoS ONE. 2012;7(8):e41730. DOI: 10.1371/journal.pone.0041730ca
- dc.identifier.doi http://dx.doi.org/10.1371/journal.pone.0041730
- dc.identifier.issn 1932-6203ca
- dc.identifier.uri http://hdl.handle.net/10230/23555
- dc.language.iso engca
- dc.publisher Public Library of Science (PLoS)ca
- dc.relation.ispartof PLoS ONE. 2012;7(8):e41730
- dc.rights This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedicationen
- dc.rights.accessRights info:eu-repo/semantics/openAccessca
- dc.subject.other Infart de miocardi -- Epidemiologiaca
- dc.title Hypothesis-based analysis of gene-gene interactions and risk of myocardial infarctionen
- dc.type info:eu-repo/semantics/articleca
- dc.type.version info:eu-repo/semantics/publishedVersionca