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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.

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

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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