| Titre : | An integrated approach to the meta-analysis of genetic association studies using Mendelian randomization. (2004) |
| Auteurs : | Cosetta MINELLI ; Keith-R Abrams ; John-R THOMPSON ; Martin-D TOBIN ; University of Leicester. Leicester Medical School. Department of Health Sciences. Centre for Biostatistics and Genetic Epidemiology. Leicester. GBR |
| Type de document : | Article |
| Dans : | American journal of epidemiology (vol. 160, n° 5, 2004) |
| Pagination : | 445-452 |
| Langues: | Anglais |
| Mots-clés : | Génétique ; Association ; Randomisation ; Epidémiologie ; Méthode |
| Résumé : | [BDSP. Notice produite par INIST-CNRS 6R0xo7Yx. Diffusion soumise à autorisation]. A natural randomization process, sometimes called Mendelian randomization, occurs at conception to determine a person's genotype. By combining information from genotype-disease and genotype-phenotype studies, it is possible to use this Mendelian randomization to derive an estimate of the association between phenotype (risk factor) and disease that is free of the confounding and reverse causation typical of classical epidemiology. When one is synthesizing evidence, studies evaluating genotype-phenotype associations, studies evaluating genotype-disease associations, and studies evaluating both are encountered, and methods should be used that allow for this structure. Plotting the log odds ratio of genotype-disease against the mean genotype-phenotype difference may help investigators detect departures from the assumptions underlying Mendelian randomization. Testing for differences between studies reporting on only the genotype-phenotype or genotype-disease association and those reporting on both associations may help in detecting reporting bias. This integrated approach to the meta-analysis of genotype-phenotype and genotype-disease studies is illustrated here using the example of the methylenetetrahydrofolate reductase (MTHFR) gene, homocysteine level, and coronary heart disease. An integrated meta-analytical approach may increase the precision of this estimate and provide information on the assumptions underlying Mendelian randomization. Serious biases may arise if the assumptions behind the analysis based on Mendelian randomization are not met. |
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