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Joint analysis of multiple blood pressure phenotypes in GAW19 data by using a multivariate rare-variant association test

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posted on 05.03.2015, 14:54 by Jianping Sun, Sahir Bhatnagar, Karim Oualkacha, Antonio Ciampi, Celia Greenwood

Introduction: Large-scale sequencing studies often measure many related phenotypes in addition to the genetic variants. Joint analysis of multiple phenotypes in genetic association studies may increase power to detect disease associated loci.

Methods: In this paper, we apply a recently developed multivariate rare-variant association test to the Genetic Analysis Workshop 19 data in order to test associations between genetic variants and multiple blood pressure phenotypes simultaneously. We also compare this multivariate test with a widely used univariate test that analyzes phenotypes separately.

Results: The multivariate test identified 2 genetic variants which have been previously reported as associated with hypertension or coronary artery disease. In addition, our region-based analyses also show that the multivariate test tends to give smaller p-values than the univariate test.

Conclusions: Hence, the multivariate test has potential to improve test power, especially when multiple phenotypes are correlated.