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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.

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

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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