%0 Journal Article %J Bioessays %D 2016 %T Missing heritability of complex diseases: Enlightenment by genetic variants from intermediate phenotypes. %A Blanco-Gómez, Adrián %A Castillo-Lluva, Sonia %A Del Mar Sáez-Freire, María %A Hontecillas-Prieto, Lourdes %A Jiang-Hua Mao %A Castellanos-Martín, Andrés %A Perez-Losada, Jesus %X

Diseases of complex origin have a component of quantitative genetics that contributes to their susceptibility and phenotypic variability. However, after several studies, a major part of the genetic component of complex phenotypes has still not been found, a situation known as "missing heritability." Although there have been many hypotheses put forward to explain the reasons for the missing heritability, its definitive causes remain unknown. Complex diseases are caused by multiple intermediate phenotypes involved in their pathogenesis and, very often, each one of these intermediate phenotypes also has a component of quantitative inheritance. Here we propose that at least part of the missing heritability can be explained by the genetic component of intermediate phenotypes that is not detectable at the level of the main complex trait. At the same time, the identification of the genetic component of intermediate phenotypes provides an opportunity to identify part of the missing heritability of complex diseases.

%B Bioessays %V 38 %P 664-73 %8 2016 Jul %G eng %N 7 %1 http://www.ncbi.nlm.nih.gov/pubmed/27241833?dopt=Abstract %R 10.1002/bies.201600084 %0 Journal Article %J Genome Biol %D 2015 %T Unraveling heterogeneous susceptibility and the evolution of breast cancer using a systems biology approach. %A Castellanos-Martín, Andrés %A Castillo-Lluva, Sonia %A Sáez-Freire, María Del Mar %A Blanco-Gómez, Adrián %A Hontecillas-Prieto, Lourdes %A Patino-Alonso, Carmen %A Galindo-Villardon, Purificación %A Pérez Del Villar, Luis %A Martín-Seisdedos, Carmen %A Isidoro-Garcia, María %A Abad-Hernández, María Del Mar %A Cruz-Hernández, Juan Jesús %A Rodríguez-Sánchez, César Augusto %A González-Sarmiento, Rogelio %A Alonso-López, Diego %A De Las Rivas, Javier %A García-Cenador, Begoña %A García-Criado, Javier %A Lee, Do Yup %A Bowen, Benjamin %A Reindl, Wolfgang %A Northen, Trent %A Jiang-Hua Mao %A Perez-Losada, Jesus %K Animals %K Breast Neoplasms %K Disease Progression %K Female %K Gene Expression Regulation, Neoplastic %K Humans %K MAP Kinase Signaling System %K Mice %K Models, Genetic %K Neoplasm Metastasis %K Proto-Oncogene Proteins c-akt %K Receptor, ErbB-2 %K Systems Biology %X

BACKGROUND: An essential question in cancer is why individuals with the same disease have different clinical outcomes. Progress toward a more personalized medicine in cancer patients requires taking into account the underlying heterogeneity at different molecular levels.

RESULTS: Here, we present a model in which there are complex interactions at different cellular and systemic levels that account for the heterogeneity of susceptibility to and evolution of ERBB2-positive breast cancers. Our model is based on our analyses of a cohort of mice that are characterized by heterogeneous susceptibility to ERBB2-positive breast cancers. Our analysis reveals that there are similarities between ERBB2 tumors in humans and those of backcross mice at clinical, genomic, expression, and signaling levels. We also show that mice that have tumors with intrinsically high levels of active AKT and ERK are more resistant to tumor metastasis. Our findings suggest for the first time that a site-specific phosphorylation at the serine 473 residue of AKT1 modifies the capacity for tumors to disseminate. Finally, we present two predictive models that can explain the heterogeneous behavior of the disease in the mouse population when we consider simultaneously certain genetic markers, liver cell signaling and serum biomarkers that are identified before the onset of the disease.

CONCLUSIONS: Considering simultaneously tumor pathophenotypes and several molecular levels, we show the heterogeneous behavior of ERBB2-positive breast cancer in terms of disease progression. This and similar studies should help to better understand disease variability in patient populations.

%B Genome Biol %V 16 %P 40 %8 2015 %G eng %1 http://www.ncbi.nlm.nih.gov/pubmed/25853295?dopt=Abstract %R 10.1186/s13059-015-0599-z