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Hypothesis-Based Analysis of Gene-Gene Interactions and Risk of Myocardial Infarction
by
Samani, Nilesh J.
, Lucas, Gavin
, Gonzalez, Juan Ramon
, Purcell, Shaun
, Subirana, Isaac
, Siscovick, David
, Elosua, Roberto
, Lluís-Ganella, Carla
, Nelson, Christopher P.
, Musameh, Muntaser D.
, Kathiresan, Sekar
, Schwartz, Stephen M.
, O’Donnell, Christopher J.
, Sentí, Mariano
, Salomaa, Veikko
, Melander, Olle
, Altshuler, David
in
Age
/ Biology
/ Biomedical research
/ Cardiovascular disease
/ Cardiovascular diseases
/ Consortia
/ Coronary artery disease
/ Disease control
/ Epidemiology
/ Epistasis
/ Epistasis, Genetic
/ Gene frequency
/ Genes
/ Genetic Predisposition to Disease
/ Genetics
/ Genome-wide association studies
/ Genome-Wide Association Study
/ Genomes
/ Genomics
/ Genotype
/ Health care networks
/ Health risk assessment
/ Health risks
/ Heart attack
/ Heart attacks
/ Heart diseases
/ Heritability
/ Hospitals
/ Humans
/ Hypotheses
/ Interaction models
/ Medical research
/ Medical schools
/ Medicine
/ Myocardial infarction
/ Myocardial Infarction - epidemiology
/ Myocardial Infarction - genetics
/ Polymorphism, Single Nucleotide
/ Population (statistical)
/ Population genetics
/ Public health
/ Regression analysis
/ Reproducibility of Results
/ Risk
/ Risk analysis
/ Risk Factors
/ Single-nucleotide polymorphism
/ Statistical analysis
/ Strong interactions (field theory)
/ Studies
/ Trusts (Law)
/ Type 2 diabetes
2012
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Hypothesis-Based Analysis of Gene-Gene Interactions and Risk of Myocardial Infarction
by
Samani, Nilesh J.
, Lucas, Gavin
, Gonzalez, Juan Ramon
, Purcell, Shaun
, Subirana, Isaac
, Siscovick, David
, Elosua, Roberto
, Lluís-Ganella, Carla
, Nelson, Christopher P.
, Musameh, Muntaser D.
, Kathiresan, Sekar
, Schwartz, Stephen M.
, O’Donnell, Christopher J.
, Sentí, Mariano
, Salomaa, Veikko
, Melander, Olle
, Altshuler, David
in
Age
/ Biology
/ Biomedical research
/ Cardiovascular disease
/ Cardiovascular diseases
/ Consortia
/ Coronary artery disease
/ Disease control
/ Epidemiology
/ Epistasis
/ Epistasis, Genetic
/ Gene frequency
/ Genes
/ Genetic Predisposition to Disease
/ Genetics
/ Genome-wide association studies
/ Genome-Wide Association Study
/ Genomes
/ Genomics
/ Genotype
/ Health care networks
/ Health risk assessment
/ Health risks
/ Heart attack
/ Heart attacks
/ Heart diseases
/ Heritability
/ Hospitals
/ Humans
/ Hypotheses
/ Interaction models
/ Medical research
/ Medical schools
/ Medicine
/ Myocardial infarction
/ Myocardial Infarction - epidemiology
/ Myocardial Infarction - genetics
/ Polymorphism, Single Nucleotide
/ Population (statistical)
/ Population genetics
/ Public health
/ Regression analysis
/ Reproducibility of Results
/ Risk
/ Risk analysis
/ Risk Factors
/ Single-nucleotide polymorphism
/ Statistical analysis
/ Strong interactions (field theory)
/ Studies
/ Trusts (Law)
/ Type 2 diabetes
2012
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Hypothesis-Based Analysis of Gene-Gene Interactions and Risk of Myocardial Infarction
by
Samani, Nilesh J.
, Lucas, Gavin
, Gonzalez, Juan Ramon
, Purcell, Shaun
, Subirana, Isaac
, Siscovick, David
, Elosua, Roberto
, Lluís-Ganella, Carla
, Nelson, Christopher P.
, Musameh, Muntaser D.
, Kathiresan, Sekar
, Schwartz, Stephen M.
, O’Donnell, Christopher J.
, Sentí, Mariano
, Salomaa, Veikko
, Melander, Olle
, Altshuler, David
in
Age
/ Biology
/ Biomedical research
/ Cardiovascular disease
/ Cardiovascular diseases
/ Consortia
/ Coronary artery disease
/ Disease control
/ Epidemiology
/ Epistasis
/ Epistasis, Genetic
/ Gene frequency
/ Genes
/ Genetic Predisposition to Disease
/ Genetics
/ Genome-wide association studies
/ Genome-Wide Association Study
/ Genomes
/ Genomics
/ Genotype
/ Health care networks
/ Health risk assessment
/ Health risks
/ Heart attack
/ Heart attacks
/ Heart diseases
/ Heritability
/ Hospitals
/ Humans
/ Hypotheses
/ Interaction models
/ Medical research
/ Medical schools
/ Medicine
/ Myocardial infarction
/ Myocardial Infarction - epidemiology
/ Myocardial Infarction - genetics
/ Polymorphism, Single Nucleotide
/ Population (statistical)
/ Population genetics
/ Public health
/ Regression analysis
/ Reproducibility of Results
/ Risk
/ Risk analysis
/ Risk Factors
/ Single-nucleotide polymorphism
/ Statistical analysis
/ Strong interactions (field theory)
/ Studies
/ Trusts (Law)
/ Type 2 diabetes
2012
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Hypothesis-Based Analysis of Gene-Gene Interactions and Risk of Myocardial Infarction
Journal Article
Hypothesis-Based Analysis of Gene-Gene Interactions and Risk of Myocardial Infarction
2012
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Overview
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).
Publisher
Public Library of Science,Public Library of Science (PLoS)
Subject
/ Biology
/ Genes
/ Genetic Predisposition to Disease
/ Genetics
/ Genome-wide association studies
/ Genome-Wide Association Study
/ Genomes
/ Genomics
/ Genotype
/ Humans
/ Medicine
/ Myocardial Infarction - epidemiology
/ Myocardial Infarction - genetics
/ Polymorphism, Single Nucleotide
/ Risk
/ Single-nucleotide polymorphism
/ Strong interactions (field theory)
/ Studies
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