In this work we present a simple, yet powerful approach for performing multivariate meta-analysis of genetic association studies when multiple outcomes are assessed. The key element of our approach is the analytical calculation of the within-studies covariances. We propose a model based on summary data, uniformly defined for both discrete and continuous outcomes (using log odds-ratios or mean differences). The within-studies covariances can be calculated using the cross-classification of the genotypes in both outcomes, which are retrieved using a log-linear model using the iterative proportional fitting algorithm under the assumption of no three-way interaction. As an example, we examine the association of GNB3 C825T polymorphism with two non-exclusive dichotomous outcomes (Type 2 Diabetes Mellitus and Essential Hypertension). We also present an application using continuous outcomes (diastolic and systolic blood pressure). We show the applicability and the generality of the method performing the analysis assuming the genetic model beforehand or following a genetic model-free approach. The method is simple and fast, it can be extended for several outcomes and can be fitted in nearly all statistical packages. There is no need for individual patient data or the simultaneous evaluation of both outcomes in all studies. We conclude that the proposed method constitute a useful framework for performing meta-analysis for multiple outcomes within the context of genetic association studies. Connections to other similar models presented in the literature, are discussed, as well as potential extensions to future work.
Niki L. Dimou and Pantelis G. Bagos A Multivariate Method for Meta-Analysis of Multiple Outcomes in Genetic Association Studies. (under review).
Niki L. Dimou and Pantelis G. Bagos A Multivariate Method for Meta-Analysis of Multiple Outcomes in Genetic Association Studies, Abstracts from the 35th Annual Conference of the International Society for Clinical Biostatistics. Vienna, Austria. pp 26. Available through: http://www.abstractserver.com/iscb2014/eBook/index.html [PDF]