| Titre : | Genetic effects versus bias for candidate polymorphisms in myocardial infarction : Case study and overview of large-scale evidence. (2007) |
| Auteurs : | Evangelia-E NTZANI ; IOANNIDIS (John-Pa) : GRC. Biomedical Research Institute. Foundation for Research and Technology-Hellas. Ioannina. ; RIZOS (Evangelos-C) : GRC. The Internal Medicine Clinic. University Hospital. Ioannina. ; University of Ioannina School of Medicine. Department of Hygiene and Epidemiology. Clinical and Molecular Epidemiology Unit. Ioannina. GRC |
| Type de document : | Article |
| Dans : | American journal of epidemiology (vol. 165, n° 9, 2007) |
| Pagination : | 973-984 |
| Langues: | Anglais |
| Mots-clés : | Génétique ; Etude comparée ; Biais ; Etude cas ; Epidémiologie ; Gène ; Homme ; Appareil circulatoire [pathologie] ; Myocarde [pathologie] ; Cardiopathie |
| Résumé : | [BDSP. Notice produite par INIST-CNRS X2MdR0xg. Diffusion soumise à autorisation]. Several genetic polymorphisms have been proposed to be associated with myocardial infarction (Ml). The authors examined the evidence and biases underlying such associations using a case-study meta-analysis and an overview of large-scale data. In a meta-analysis of 27 studies addressing the association of the angiotensin type 1 receptor (AT1R)+1166A/C polymorphism with Ml (10,180 cases, 17,129 controls), the *Callele conferred an increase in Ml risk (odds ratio=1.13 per allele, p=0.005). However, there was large between-study heterogeneity ; the largest study showed no effect, contradicting smaller studies ; and studies with blinded genotyping showed no effect. The authors conducted an overview of meta-analyses of genetic associations for Ml or coronary artery disease, including at least three studies and 3,000 subjects. In their latest meta-analysis, another 14 polymorphisms were found to have formally significant associations. If true, these associations would already explain 42% of the Ml risk for Caucasian populations. Significant between-study heterogeneity was common. Across the 32 largest studies, only two found formally significant results (nine would be expected if each meta-analysis showed a true association). Even with large-scale evidence from meta-analyses, significant associations for Ml may be subject to bias. Large-scale single studies and prospective consortia should be used for detecting and validating the genetic determinants of Ml. |
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