Compositional epistasis: An epidemiologic perspective

Etsuji Suzuki, Tyler J. VanderWeele

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)


Under Bateson's original conception, the term "epistasis" is used to describe the situation in which the effect of a genetic factor at one locus is masked by a variant at another locus. Epistasis in the sense of masking has been termed "compositional epistasis." In general, statistical tests for interaction are of limited use in detecting compositional epistasis. Using recently developed epidemiological methods, however, it has been shown that there are relations between empirical data patterns and compositional epistasis. These relations can sometimes be exploited to empirically test for certain forms of compositional epistasis, by using alternative nonstandard tests for interaction. Using the counterfactual framework, we show conditions that can be empirically tested to determine whether there are individuals whose phenotype response patterns manifest epistasis in the sense of masking. Only under some very strong assumptions would tests for standard statistical interactions correspond to compositional epistasis. Even without such strong assumptions, however, one can still test whether there are individuals of phenotype response type representing compositional epistasis. The empirical conditions are quite strong, but the conclusions which tests of these conditions allow may be of interest in a wide range of studies. This chapter highlights that epidemiologic perspectives can be used to shed light on underlying mechanisms at the genetic, molecular, and cellular levels.

Original languageEnglish
Title of host publicationEpistasis
Subtitle of host publicationMethods and Protocols
PublisherSpringer New York
Number of pages20
ISBN (Electronic)9781493921553
ISBN (Print)9781493921546
Publication statusPublished - Nov 17 2014


  • Causality
  • Compositional epistasis
  • Counterfactual
  • Epidemiologic methods
  • Mechanistic interaction
  • Monotonicity assumptions
  • Potential outcomes
  • Statistical epistasis
  • Statistical models
  • Sufficient-cause framework

ASJC Scopus subject areas

  • Medicine(all)
  • Biochemistry, Genetics and Molecular Biology(all)


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