While considerable effort has gone into reducing genotype measurement error and ensuring genotype accuracy and consistency of results [de Bakker et al., 2008], phenotype heterogeneity, in both outcomes and covariates across studies, represents a major challenge to successful GWAS analysis of common traits [Zeggini and Ioannidis, 2009; Seminara et al., 2007] or genome-wide assessment of G*E interactions in complex diseases. The recent discovery of markers that are specifically associated with estrogen-receptor negative breast cancer highlights the potential importance of specific, harmonized phenotypes: earlier GWAS of a general breast cancer phenotype did not identify these markers, due to lack of power [Kraft and Haiman, 2010]. In contrast, cross-study analysis groups, such as those established by the Psychiatric Genetics Consortium [Psychiatric GWAS Consortium Coordinating Committee et al., 2009], have begun to analyze GWAS results related to differing psychiatric diagnoses that are known to have shared genetic underpinnings (e.g. Schizophrenia and Bipolar Disorder, Bipolar and Major Depressive Disorder) [International Schizophrenia Consortium et al., 2009; Liu et al., 2011]. The existing literature suggests that phenotype harmonization may reveal novel loci for disease subtypes as
