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Generation of human steroid-producing organoids: a new approach to treat adrenal insufficiency

Total Cost €


EC-Contrib. €






 GHSO project word cloud

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

stress    engineered    harbouring    efficient    reversible    suitably    specialized    insufficiency    homeostasis    lifelong    variables    generate    primary    platform    overexpression    drug    mediate    glucocorticoids    hyperplasia    advantages    mineralocorticoids    salt    hormonal    hescs    stem    disorders    exogenous    organoids    blood    mutations    producing    steroids    bench    requiring    source    temporally    utilize    offers    synthesis    diurnal    crispr    threatening    found    vivo    pattern    metabolism    transcription    transform    carbohydrate    healthy    individuals    site    replacement    models    adrenal    molecules    cellular    quality    ai    accelerate    cell    steroid    functions    patients    functional    volume    cortex    protein    tractable    genome    faster    cah    disease    cortisol    human    noted    tunable    suffering    paradigm    embryonic    mimics    cells    pluripotent    cas9    reprogramming    mammalian    life    small    congenital    translation    directed    therapies    lacking    therapy   

Project "GHSO" data sheet

The following table provides information about the project.


Organization address
postcode: 1069

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 Germany [DE]
 Total cost 246˙669 €
 EC max contribution 246˙669 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2018
 Funding Scheme MSCA-IF-GF
 Starting year 2019
 Duration (year-month-day) from 2019-06-01   to  2022-05-31


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 


 Project objective

The adrenal cortex is essential for life; it is the primary site of steroid synthesis, producing glucocorticoids, which affect carbohydrate metabolism and mediate the mammalian stress response and mineralocorticoids, which control blood volume and salt homeostasis. Adrenal insufficiency (AI), which can be life threatening, is cause by a number of adrenal disorders, and lifelong management of these patients with exogenous steroids can be challenging. No drug suitably mimics the diurnal pattern of cortisol noted in healthy individuals, and objective variables to measure hormonal replacement therapy quality are lacking. The ability to generate steroid-producing cells from pluripotent stem cells through cell reprogramming, a process where a specialized cell type is induced to transform into a different cell, offers a new paradigm for functional studies, modelling human disease and drug testing and eventually can be used as a cell source for cellular therapies for patients suffering from adrenal conditions. This proposal aims to develop methodologies to generate adrenal-like organoids from human embryonic stem cells (hESCs), which have not been generated so far, without requiring overexpression of exogenous transcription factors and test them in in vivo models of adrenal insufficiency. Because small molecules provide several distinct advantages in controlling protein functions (e.g., temporally controllable, reversible, tunable and tractable) I will utilize them for a faster, more efficient, and directed cellular reprogramming. CRISPR-Cas9 genome engineered steroid-producing organoids harbouring common mutations found in congenital adrenal hyperplasia (CAH), the most common type of AI, will be generated and used as a disease modelling platform to study CAH. This proposal aims to accelerate the translation of this promising bench research to patients affected by adrenal insufficiency over the next 10 years.

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The information about "GHSO" are provided by the European Opendata Portal: CORDIS opendata.

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