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EPIORGABOLISM SIGNED

Diabetic nephropathy modelling in hESC-derived 3D kidney organoids

Total Cost €

0

EC-Contrib. €

0

Partnership

0

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 EPIORGABOLISM project word cloud

Explore the words cloud of the EPIORGABOLISM project. It provides you a very rough idea of what is the project "EPIORGABOLISM" about.

disease    renal    stage    model    status    gained    enhancers    genetic    discovery    enzymes    structural    evidences    crispr    elucidate    drug    embryonic    fibrosis    pressure    vivo    metabolic    differentiation    diabetic    reprogramming    occurring    hesc    models    ing    stop    progression    human    therapeutic    validated    links    drugs    recapitulate    regulators    epithelial    preclinical    therapies    somatic    lack    esrd    impediments    kidney    acid    cell    molecular    mainly    architecture    tissue    chemistry    tool    date    stages    proximal    physiological    cells    nephropathy    therapy    good    patients    reprograming    background    epigenome    diabetes    treatment    fatty    methylation    kptcs    functional    engineered    metabolism    montserrat    dn    epigenetic    genes    organoids    regeneration    dna    dr    acting    serve    oxidation    cas9    tubular    aberrant    stem    pathology    blood    mimic    signature    promoted    alterations    glycaemic    promoters    encoding    hypothesize    vitro    expertise   

Project "EPIORGABOLISM" data sheet

The following table provides information about the project.

Coordinator
FUNDACIO INSTITUT DE BIOENGINYERIA DE CATALUNYA 

Organization address
address: CARRER BALDIRI REIXAC PLANTA 2A 10-12
city: BARCELONA
postcode: 8028
website: http://www.ibecbarcelona.eu

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Spain [ES]
 Total cost 158˙121 €
 EC max contribution 158˙121 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2017
 Funding Scheme MSCA-IF-EF-RI
 Starting year 2019
 Duration (year-month-day) from 2019-04-18   to  2021-08-14

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    FUNDACIO INSTITUT DE BIOENGINYERIA DE CATALUNYA ES (BARCELONA) coordinator 158˙121.00

Map

 Project objective

Diabetic Nephropathy is the leading cause of end-stage renal disease (ESRD). To date, treatment of DN is mainly based on drugs acting on glycaemic and blood pressure control, as there is no validated therapy able to stop the progression towards renal failure. One of the main impediments for developing new therapies for DN has been the lack of a good preclinical model which can recapitulate important functional, structural, and molecular features of advanced human diabetic kidney disease. Here, we aim to develop a DN modelling using human Embryonic Stem Cell (hESC) derived kidney organoids which can recapitulate the in vivo architecture, functionality, and genetic signature of DN. Due to the increasing evidences that links aberrant DNA methylation with kidney fibrosis and metabolic reprograming in DN, we hypothesize that early DN progression is promoted by the metabolic alterations occurring in diabetic patients, resulting in the epigenetic reprogramming of kidney proximal tubular epithelial cells (KPTCs). Based in my background in the fields of metabolism and diabetes, together with the expertise of Dr. Montserrat in the field of somatic reprograming, DN and tissue regeneration/differentiation, this proposal seeks to:1) Elucidate the methylation status of the promoters/enhancers of genes encoding enzymes and regulators of fibrosis and fatty acid oxidation in proximal tubular cells obtained from diabetic patients at different stages of DN progression 2) Establish two in vitro models using hESC-derived kidney organoids; an engineered DN in vitro model, using CRISPR Cas9 to mimic the epigenome signature of DN patients and a physiological DN in vitro model which mimic the diabetic physiological chemistry. The information gained from this DN modelling will offer improved insight into disease pathology and progression. Moreover, it may also serve as a tool for drug discovery to identify therapeutic targets for DN.

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