Understanding the molecular basis of stochastic bi-stable obesity

Project Information

EPOC

Grant agreement ID: 707123

DOI

10.3030/707123

Project closed

EC signature date 21 April 2016

Start date 1 December 2016

End date 30 November 2018

Funded under

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Total cost

€ 159 460,80

EU contribution

€ 159 460,80

Coordinated by

MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV
Germany

Periodic Reporting for period 1 - EPOC (Understanding the molecular basis of stochastic bi-stable obesity)

Reporting period: 2016-12-01 to 2018-11-30

Summary of the context and overall objectives of the project

Recent estimates place obesity incidence at more than 600 millions of people worldwide. The long-term implications of this disease include exacerbation of global heart disease, diabetes, and cancer, making obesity one of the world's chief socio-economic challenges of the next decade.
People are not all equal when it comes to emergence of obesity. Indeed, some populations seem protected, others seem prone to its development. Population level phenotypic variation, which describes the variability of a phenotype in a given population, is thought to serve as a mechanistic platform for adaptation and evolution. Phenotypic variation can be of genetic and/or epigenetic origin.
Whereas, the last decade has seen much progress in obesity genetics, our understanding of epigenetic regulation of the disease is poor.
Our lab recently published data about specific mutant mice developing an unprecedented bi-stable stochastic obesity phenotype. Approximately 20% of the genetically identical, littermate-controlled heterozygous mutant mice develop obesity while the remaining ~80% remain as lean as wild-type littermates, resulting in a bi-modal body weight distribution in the population. Here, we proposed to map the molecular basis of a chromatin state dependent epigenetic switch that to the best of our knowledge buffers metabolic programming, establishes phenotypic bi-stability and thereby generate a deeper understanding of the mechanisms underlying bi-stable obesity.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

During the period covered by the report, we established a high-dimensional phenome matrix based on the body weight and Fat/lean mass. This matrix served as a critical genetic reference point for understanding variation and stochasticity at the physiological and molecular levels. By using two mice models [Trim28D9/ and Nnat+/-p], we performed metabolic and neurologic phenotyping, and we also processed to RNA-sequencing and ChIP-sequencing on epididymal biopsy from phenotypic extremes.

In the same time, we began to set up a sufficient matrix for determination of high-confidence core molecular patterns specific to each model and to stochastic obesity in general. This matrix is based on in vivo analysis (indirect calorimetry during fed state) and ex vivo analysis (blood profile and adipocytes profile).

This study clearly demonstrated a new example of phenotypic co-variation with specific molecular mechanisms underlying this bi-stable obesity. We have still datas to analyze and experiments to perform before the publication step, but the results were presented in differents scientific meetings (TRIRHENA Chromatin club meeting, MPI-IE Institute Seminar, MPI-IE Epigenetics meeting).

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

We believe that switch-like developmental processes may underpin as much as 50% of pre-pubescent obesity with strong potential for life-long added risk for some of the most widespread modern diseases (diabetes, cardiovascular and neurological disease, and cancer). As indicated, the project has, in a preliminary sense, identified a second-ever polyphenism in the mouse and therefore demonstrates a novel dimension to the possible outcomes of mammalian epigenetic reprogramming. The greatest impact of this project therefore is a significantly deeper understanding of the epigenetic (re)programming in metabolic diseases. Based on this knowledge, our goal is to begin work towards identification of early epigenetic biomarkers to prediction the non-mendelian components of metabolic disease. Novel therapeutic and preventative strategies will naturally go hand in hand with such developments.