Polymorphisms in 33 inflammatory genes and risk of myocardial infarction—a system genetics approach View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2007-11

AUTHORS

Sandrine Barbaux, David-Alexandre Tregouet, Viviane Nicaud, Odette Poirier, Claire Perret, Tiphaine Godefroy, Carole Francomme, Christophe Combadiere, Dominique Arveiler, Gerald Luc, Jean-Bernard Ruidavets, Alun E. Evans, Frank Kee, Caroline Morrison, Laurence Tiret, Stefan Martin Brand-Herrmann, François Cambien

ABSTRACT

The hypothesis of a causal link between inflammation and atherosclerosis would be strengthened if variants of inflammatory genes were associated with disease. Polymorphisms of 33 genes encoding inflammatory molecules were tested for association with myocardial infarction (MI). Patients with MI and a parental history of MI (n = 312) and controls from the UK (n = 317) were genotyped for 162 polymorphisms. Thirteen polymorphisms were associated with MI (P values ranging from 0.003 to 0.041). For three genes, ITGB1, SELP, and TNFRSF1B haplotype frequencies differed between patients and controls (P values < 0.01). We further assessed the simultaneous contribution of all polymorphisms and relevant covariates to MI using a two-step strategy of data mining relying on Random Forest and DICE algorithms. In a replication study involving two independent samples from the UK (n = 649) and France (n = 706), one interaction between the ITGA4/R898Q polymorphism and current smoking status was replicated. This study illustrates a strategy for assessing the joint effect of a large number of polymorphisms on a phenotype that may provide information that single locus or single gene analysis may fail to uncover. Overall, there was weak evidence for an implication of inflammatory polymorphisms on susceptibility to MI. More... »

PAGES

1271-1280

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00109-007-0234-x

DOI

http://dx.doi.org/10.1007/s00109-007-0234-x

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1016661563

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/17634906


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