AI Article Synopsis

  • A traditional method of studying complex diseases focuses on finding genes with overall expression differences between healthy and diseased individuals, but this can overlook individual gene contributions due to population diversity.
  • By analyzing gene expression changes in over 100 genetically distinct mouse strains, researchers identified genes linked to heart disease severity that may be missed in broader analyses.
  • These identified genes are not only relevant to cardiac diseases in mice but also interact significantly with human cardiac disease genes, highlighting the need for personalized approaches to discover and treat complex diseases effectively.

Article 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 of , 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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5825397PMC
http://dx.doi.org/10.1038/s41540-018-0046-3DOI Listing

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