A personalized, multiomics approach identifies genes involved in cardiac hypertrophy and heart failure. (December 2018)

• Record Type: Journal Article
• Authors: Santolini, Marc; Romay, Milagros; Yukhtman, Clara; Rau, Christoph; Ren, Shuxun; Saucerman, Jeffrey; Wang, Jessica; Weiss, James; Wang, Yibin; Lusis, Aldons; Karma, Alain
• Is Part Of: Npj systems biology and applications. Volume 4(2018)
• Page Start: 1
• Page End: 13
• Publication Date: 2018-12
• Subjects: Systems biology -- Periodicals; 570.113
• DOI: 10.1038/s41540-018-0046-3
• Languages: English
• ISSNs: 2056-7189

Abstract

Abstract A traditional approach to investigate the genetic basis of complex diseases is to identify genes with a global change in expression between diseased and healthy individuals. However, population heterogeneity may undermine the effort to uncover genes with significant but individual contribution to the spectrum of disease phenotypes within a population. Here we investigate individual changes of gene expression when inducing hypertrophy and heart failure in 100 + strains of genetically distinct mice from the Hybrid Mouse Diversity Panel (HMDP). We find that genes whose expression fold-change correlates in a statistically significant way with the severity of the disease are either up or down-regulated across strains, and therefore missed by a traditional population-wide analysis of differential gene expression. Furthermore, those "fold-change" genes are enriched in human cardiac disease genes and form a dense co-regulated module strongly interacting with the cardiac hypertrophic signaling network in the human interactome. We validate our approach by showing that the knockdown ofHes1, predicted as a strong candidate, induces a dramatic reduction of hypertrophy by 80–90% in neonatal rat ventricular myocytes. Our results demonstrate that individualized approaches are crucial to identify genes underlying complex diseases as well as to develop personalized therapies. Personalized medicine: uncovering missed disease genes A multitude of genes associated with complex diseases are revealed by a novel personalized, as opposed to population-level, analysis of differential gene expression. While traditional investigations of the genetic basis of complex diseases assume homogeneity across individuals and identify genes differentially expressed between a diseased and a healthy population, Northeastern University and University of California Los Angeles researchers have identified a different class of disease genes that exhibit heterogeneous up and down-regulation across 100 genetically distinct mouse strains subject to a stressor inducing heart failure, but show no significant change of expression at the population level. The results, validated by in vitro knockdown, demonstrate that individualized approaches are crucial to unmask all genes involved in complex diseases, opening new avenues for the development of personalized therapies.