@article{10.1371/journal.pcbi.1002459, doi = {10.1371/journal.pcbi.1002459}, author = {Wang, Yunpeng AND Gjuvsland, Arne B. AND Vik, Jon Olav AND Smith, Nicolas P. AND Hunter, Peter J. AND Omholt, Stig W.}, journal = {PLOS Computational Biology}, publisher = {Public Library of Science}, title = {Parameters in Dynamic Models of Complex Traits are Containers of Missing Heritability}, year = {2012}, month = {04}, volume = {8}, url = {https://doi.org/10.1371/journal.pcbi.1002459}, pages = {1-9}, abstract = {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.}, number = {4}, }