Metastable Epiallele: Role of Epigenetic Variability for the Development of Meta...
Metastable Epiallele: Role of Epigenetic Variability for the Development of Metabolic and Endocrine Diseases
The development of obesity in industrial and low-and middle-income countries is leading to a severe burden for patients and health care systems based on associated comorbidities as cardiovascular diseases and type 2 diabetes melli...
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Descripción del proyecto
The development of obesity in industrial and low-and middle-income countries is leading to a severe burden for patients and health care systems based on associated comorbidities as cardiovascular diseases and type 2 diabetes mellitus. Apart from the genetic background, epigenetic modifications like DNA methylation are supposed to play an important role for body weight regulation. So far, epigenome-wide association studies were not able to elucidate this relationship, as most methylation differences were related to a genetic variant. Therefore, the identification of the POMC (pro-opiomelanocortin) gene, a key factor for hypothalamic body weight regulation, as a metastable epiallele in humans, was of importance to understand how methylation variability affect the individual phenotype. Metastable epialleles are methylome-regions, which are non-genetically determined, stochastically regulated and set in early embryonic development. Furthermore, they are non-tissue specific, stable over time and modified by Carbon-1 metabolites in-utero. However, their role for human diseases remained unclear. Within this application, I want to elucidate and characterize how epigenetic modifications as metastable epialleles modulate human susceptibility and predisposition to metabolic and endocrine diseases and analyse the impact of environmental factors. To achieve this goal, I propose a unique approach using advanced technologies to analyse human postmortem samples and human embryonic stem cells to identify new metastable epialleles in humans and elucidate new mechanisms and relationships between phenotypic variation and methylation variability. The combination of the algorithm to identify methylation variability and the use of stem cell models to functionally characterize epigenetic variants will be a blueprint for the analysis of the epigenetic contribution for other endocrine, neurological or cardiovascular diseases and will generate a powerful resource for researchers worldwide.
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