Epigenetic control and probabilistic disease programming

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PROJECT SUMMARY Dogma teaches that an individual’s phenotype (and disease) results from genetics, the environment, and their interactions. Yet numerous studies of monozygotic human twins and isogenic animal models indicate that significant portions of disease variability cannot be explained by genetic and environmental inputs. For example, genetics accounts for ~50% and environment accounts for <1% of metabolic disease in monozygotic twins, leaving a striking unexplained variance (discordance) of ~50%. Similar results are reported for many other human diseases and complex traits. The long-term goal of this project is to understand the origins and regulatory mechanisms underlying this unexplained phenotypic and disease variation. The operating hypotheses are that phenotypic variation itself is a quantitative trait, and there are probabilistic, intracellular processes regulated by epigenetic mechanisms that are responsible for significant portions of unexplained phenotypic variation. The hypothesis is based on prior work with haploinsufficient Trim28+/D9 mice, where genetically and environmentally identical littermates emerge as either lean or obese, with few intermediates (i.e., an epigenetically driven obesity polyphenism). TRIM28 mRNA expression levels also predict obesity in human children. This body of work suggests that epigenetic silencers are master regulators of probabilistic processes in humans, and may also be responsible for regulating phenotypic variation. However, the epigenetic mechanisms and genomic loci responsible for this remarkable, probabilistic, and bi-stable disease potential are unknown. Before the field can even begin deciphering the (epi)genetic architecture that regulates probabilistic process and variability, we need to first determine which type of epigenetic silencers are involved in the bistable switch from one development trajectory to the other, and which genetic loci respond to the switch. We will meet this objective by performing a focused gene-gene and gene-environment epistasis experiment with Trim28+/D9 mice, and score the offspring for stability, severity, and frequency (i.e. the variability) of bistable metabolic disease. For crosses showing additive effects on disease variability, we will perform total RNAseq and RELACS in precursor and mature adipocytes to identify genomic loci associated with metabolic disease switches and variation. With this knowledge, we will be able to generate specific hypotheses about the genes, pathways, and physiological mechanisms that not only regulate metabolic disease, but control phenotypic variation as a quantitative trait.