Understanding the molecular basis of stochastic bi-stable obesity

Informazioni relative al progetto

EPOC

ID dell’accordo di sovvenzione: 707123

DOI

10.3030/707123

Progetto chiuso

Data della firma CE 21 Aprile 2016

Data di avvio 1 Dicembre 2016

Data di completamento 30 Novembre 2018

Finanziato da

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Costo totale

€ 159 460,80

Contributo UE

€ 159 460,80

Coordinato da

MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV
Germany

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

Periodo di rendicontazione: 2016-12-01 al 2018-11-30

Sintesi del contesto e degli obiettivi generali del progetto

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.

Lavoro eseguito dall’inizio del progetto fino alla fine del periodo coperto dalla relazione e principali risultati finora ottenuti

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).

Progressi oltre lo stato dell’arte e potenziale impatto previsto (incluso l’impatto socioeconomico e le implicazioni sociali più ampie del progetto fino ad ora)

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.