A Powerful Method for Pleiotropic Analysis Under Composite Null Hypothesis Identifies Novel Shared Loci Between Type 2 Diabetes and Prostate Cancer

    Debashree Ray, Nilanjan Chatterjee
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    Studysummary This study introduced a statistical method, PLACO, which revealed novel genetic regions associated with both Type 2 Diabetes and Prostate Cancer from GWAS data.
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    Three years ago, a new statistical approach, PLACO, was proposed for detecting pleiotropic loci between two traits. This method was designed to test the composite null hypothesis that a genetic variant is associated with none or only one of the traits. The approach was based on the product of the Z-statistics of the SNPs across two studies and a null distribution of the test statistic was derived in the form of a mixture distribution. Simulation studies showed that this method could maintain type I error and achieve major power gain over alternative simpler methods typically used for testing pleiotropy. When applied to publicly available summary data from two large case-control GWAS of Type 2 Diabetes and Prostate Cancer, PLACO identified several novel shared genetic regions.
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