Statistical validation of endophenotypes using a surrogate endpoint analytic analogue

Guan-Hua Huang*, Chin Chiang Hsieh, Chen Hsin Chen, Wei J. Chen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


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.

Original languageEnglish
Pages (from-to)549-558
Number of pages10
JournalGenetic Epidemiology
Issue number6
StatePublished - 14 Sep 2009


  • Continuous Performance Test
  • Heritability
  • Liability threshold model
  • Schizophrenia-related personalitydisorder
  • Variance component analysis


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