Parameters in dynamic models of complex traits are containers of missing heritability

PLoS Comput Biol. 2012;8(4):e1002459. doi: 10.1371/journal.pcbi.1002459. Epub 2012 Apr 5.


Polymorphisms identified in genome-wide association studies of human traits rarely explain more than a small proportion of the heritable variation, and improving this situation within the current paradigm appears daunting. Given a well-validated dynamic model of a complex physiological trait, a substantial part of the underlying genetic variation must manifest as variation in model parameters. These parameters are themselves phenotypic traits. By linking whole-cell phenotypic variation to genetic variation in a computational model of a single heart cell, incorporating genotype-to-parameter maps, we show that genome-wide association studies on parameters reveal much more genetic variation than when using higher-level cellular phenotypes. The results suggest that letting such studies be guided by computational physiology may facilitate a causal understanding of the genotype-to-phenotype map of complex traits, with strong implications for the development of phenomics technology.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Action Potentials / genetics*
  • Animals
  • Calcium Signaling / physiology*
  • Cells, Cultured
  • Computer Simulation
  • Mice
  • Models, Genetic*
  • Myocytes, Cardiac / physiology*
  • Polymorphism, Single Nucleotide / genetics*
  • Quantitative Trait, Heritable*