Statistical validation of endophenotypes using a surrogate endpoint analytic analogue.

Endophenotypes, which involve the same biological pathways as diseases but presumably are closer to the relevant gene actions than diagnostic phenotypes, have emerged as an important concept in the genetic studies of complex diseases. In this report, we develop a formal statistical methodology for validating endophenotypes. The proposed method was motivated by the conditioning strategy used for surrogate endpoints commonly seen in clinical research. We define an endophenotype to be "a trait for which a test of null hypothesis of no genetic heritability implies the corresponding null hypothesis based on the phenotype of interest". An index, the proportion of heritability explained, is used as an operational criterion of validation. Statistical inferences on this index are also developed. Usefulness of the proposed method is demonstrated through computer simulations and a study of assessing the Continuous Performance Test as an endophenotype of the schizophrenia spectrum.