Summary
Neuromuscular Diseases (NMDs), affecting both children and adults with a prevalence of 1 in a 1000 people, form a large and heterogeneous group of genetic diseases causing progressive degeneration of skeletal muscles. Most NMDs result in chronic long-term disability imposing a significant burden on patients, families and public health care. In many cases, patients die prematurely from respiratory, and in some cases cardiac, muscle impairment. There are more than 200 NMDs, including over 30 types of Muscular Dystrophy (MD) which results from the mutation of genes controlling muscle functions and structures. The classification of MDs is not fixed but evolves with the constant discovery of new genes/mutations responsible for these diseases. Despite more than 40 genes involved in MDs have already been identified many genes are still to be discovered. In Europe, thousand patients with MD are currently without molecular diagnosis. Delayed or inaccurate diagnoses postpone the adequate care and may have irreversible consequences for the patients. MUMDUPSC aims combining descriptive clinical diagnosis, genomics and disease modelling from patients’ induced Pluripotent Stem Cells (hiPSC) to identify both molecular mechanisms and genetic mutations underlying undiagnosed muscular dystrophies (UMDs). Specifically, I propose to generate hiPSC from selected UMD patients and investigate their transcription profile during skeletal muscle differentiation compared to control cells (unaffected or affected with known MDs). By identifying, for the first time, DEGs specifically modulated in UMDs, MUMDUPSC will reveal the genes and pathways specifically contributing to the diseases. It will represent a proof of concept for the classification of unlabeled muscle pathologies and, in the long term, will provide innovative leads for the diagnosis and the treatment of these debilitating diseases.
Unfold all
/
Fold all
More information & hyperlinks
Web resources: | https://cordis.europa.eu/project/id/101025510 |
Start date: | 15-09-2021 |
End date: | 14-09-2023 |
Total budget - Public funding: | 196 707,84 Euro - 196 707,00 Euro |
Cordis data
Original description
Neuromuscular Diseases (NMDs), affecting both children and adults with a prevalence of 1 in a 1000 people, form a large and heterogeneous group of genetic diseases causing progressive degeneration of skeletal muscles. Most NMDs result in chronic long-term disability imposing a significant burden on patients, families and public health care. In many cases, patients die prematurely from respiratory, and in some cases cardiac, muscle impairment. There are more than 200 NMDs, including over 30 types of Muscular Dystrophy (MD) which results from the mutation of genes controlling muscle functions and structures. The classification of MDs is not fixed but evolves with the constant discovery of new genes/mutations responsible for these diseases. Despite more than 40 genes involved in MDs have already been identified many genes are still to be discovered. In Europe, thousand patients with MD are currently without molecular diagnosis. Delayed or inaccurate diagnoses postpone the adequate care and may have irreversible consequences for the patients. MUMDUPSC aims combining descriptive clinical diagnosis, genomics and disease modelling from patients’ induced Pluripotent Stem Cells (hiPSC) to identify both molecular mechanisms and genetic mutations underlying undiagnosed muscular dystrophies (UMDs). Specifically, I propose to generate hiPSC from selected UMD patients and investigate their transcription profile during skeletal muscle differentiation compared to control cells (unaffected or affected with known MDs). By identifying, for the first time, DEGs specifically modulated in UMDs, MUMDUPSC will reveal the genes and pathways specifically contributing to the diseases. It will represent a proof of concept for the classification of unlabeled muscle pathologies and, in the long term, will provide innovative leads for the diagnosis and the treatment of these debilitating diseases.Status
CLOSEDCall topic
MSCA-IF-2020Update Date
28-04-2024
Images
No images available.
Geographical location(s)
Structured mapping