PT  - JOURNAL ARTICLE
AU  - Marc Santolini
AU  - Milagros C. Romay
AU  - Clara L. Yukhtman
AU  - Christoph D. Rau
AU  - Shuxun Ren
AU  - Jeffrey J. Saucerman
AU  - Jessica J. Wang
AU  - James N. Weiss
AU  - Yibin Wang
AU  - Aldons J. Lusis
AU  - Alain Karma
TI  - A personalized, multi-omics approach identifies genes involved in cardiac hypertrophy and heart failure
AID  - 10.1101/120329
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 120329
4099  - http://biorxiv.org/content/early/2017/03/24/120329.short
4100  - http://biorxiv.org/content/early/2017/03/24/120329.full
AB  - Identifying genes underlying complex diseases remains a major challenge. Biomarkers are typically identified by comparing average levels of gene expression in populations of healthy and diseased individuals. However, genetic diversities may undermine the effort to uncover genes with significant but individual contribution to the spectrum of disease phenotypes within a population. Here we leverage the Hybrid Mouse Diversity Panel (HMDP), a model system of 100+ genetically diverse strains of mice exhibiting different complex disease traits, to develop a personalized differential gene expression analysis that is able to identify disease-associated genes missed by traditional population-wide methods. The population-level and personalized approaches are compared for isoproterenol(ISO)-induced cardiac hypertrophy and heart failure using pre- and post-ISO gene expression and phenotypic data. The personalized approach identifies 36 Fold-Change (FC) genes predictive of the severity of cardiac hypertrophy, and enriched in genes previously associated with cardiac diseases in human. Strikingly, these genes are either up- or down-regulated at the individual strain level, and are therefore missed when averaging at the population level. Using insights from the gene regulatory network and protein-protein interactome, we identify Hes1 as a strong candidate FC gene. We validate its role by showing that even a mild knockdown of 20-40% of Hes1 can induce a dramatic reduction of hypertrophy by 80-90% in rat neonatal cardiac cells. These findings emphasize the importance of a personalized approach to identify causal genes underlying complex diseases as well as to develop personalized therapies.Significance A traditional approach to investigate the genetic basis of complex diseases is to look for genes with a global change in expression between diseased and healthy individuals. Here, we investigate individual changes of gene expression by inducing heart failure in 100 strains of genetically distinct mice. We find that genes associated to the severity of the disease are either up- or down-regulated across individuals and are therefore missed by a traditional population level approach. However, they are enriched in human cardiac disease genes and form a coregulated module strongly interacting with a cardiac hypertrophic signaling network in the human interactome. Our analysis demonstrates that individualized approaches are crucial to reveal all genes involved in the development of complex diseases.