BioEssays · 2005 · 347 citations · 57 references
Life SciencesBiologyGeneticsHuman GeneticsMedical GeneticsStatistical GeneticsDisease MechanismsEpistasisGenotype-phenotype Association AnalysisGenotype-phenotype CorrelationEpistasis AnalysisEpistatic InteractionsEpistatic VarianceGenotype-phenotype AssociationsPhenotypic Trait VariationRegulatory Gene NetworksStatistical EpistasisSystems Biology Integration
Epistasis, crucial to common human disease genetics, is viewed either biologically—as physical interactions among biomolecules affecting phenotypes—or statistically—as deviations from additivity in multilocus genotype–phenotype models. The essay poses two reciprocal questions—whether statistical epistasis implies underlying biomolecular interactions and whether biomolecular interactions generate statistical epistasis—and proposes that systems biology and model organisms can answer them to improve disease diagnosis, prevention, and treatment. The essay reviews definitions and examples of biological and statistical epistasis and explores their relationship. BioEssays 27:637–646, 2005; © 2005 Wiley Periodicals, Inc.
Abstract Epistasis plays an important role in the genetic architecture of common human diseases and can be viewed from two perspectives, biological and statistical, each derived from and leading to different assumptions and research strategies. Biological epistasis is the result of physical interactions among biomolecules within gene regulatory networks and biochemical pathways in an individual such that the effect of a gene on a phenotype is dependent on one or more other genes. In contrast, statistical epistasis is defined as deviation from additivity in a mathematical model summarizing the relationship between multilocus genotypes and phenotypic variation in a population. The goal of this essay is to review definitions and examples of biological and statistical epistasis and to explore the relationship between the two. Specifically, we present and discuss the following two questions in the context of human health and disease. First, when does statistical evidence of epistasis in human populations imply underlying biomolecular interactions in the etiology of disease? Second, when do biomolecular interactions produce patterns of statistical epistasis in human populations?Answers to these two reciprocal questions will provide an important framework for using genetic information to improve our ability to diagnose, prevent and treat common human diseases. We propose that systems biology will provide the necessary information for addressing these questions and that model systems such as bacteria, yeast and digital organisms will be a useful place to start. BioEssays 27:637–646, 2005. © 2005 Wiley Periodicals, Inc.
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