Opendata, web and dolomites


Emerging Simplex ORigins In ALS

Total Cost €


EC-Contrib. €






 EScORIAL project word cloud

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

machine    considerably    effect    3d    learning    data    thousands    therapeutic    phenomena    collection    assays    sclerosis    erc    lateral    small    contribution    interaction    of    profiles    clinical    reporter    identifies    expression    my    cellular    continuum    mutation    unbiased    blood    unexplained    understand    few    splitting    heterogeneity    screens    imaging    folding    diseases    brain    exact    uses    modifiers    nbsp    overlays    urgent    environmental    amyotrophic    mutations    genomics    als       diagnostic    drug    frequency    cas9    translated    created    lethal    crispr    dna    disease    dimensional    counselling    patients    trial    interact    play    unravel    integrates    lumping    reclassify    algorithms    patterns    gene    models    expressivity    variants    epigenetic    shown    morphology    time    pleiotropic    unmet    disproportionate    life    genetic    me    patient    penetrance    risk    successful    monogenetic    simply    c9orf72    genomic    mri    biological    scope    simplex    causal    nor    rare    clear   

Project "EScORIAL" data sheet

The following table provides information about the project.


Organization address
postcode: 3584 CX

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 Netherlands [NL]
 Total cost 1˙980˙434 €
 EC max contribution 1˙980˙434 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2017-COG
 Funding Scheme ERC-COG
 Starting year 2018
 Duration (year-month-day) from 2018-07-01   to  2023-06-30


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 


 Project objective

My aim is to understand the exact genetic contribution in every patient with Amyotrophic Lateral Sclerosis (ALS), a lethal disease with a life time risk of 0.3% and an urgent unmet therapeutic need. I have recently shown a disproportionate large contribution from low-frequency genetic variants in ALS. ALS is not simply a collection of unique rare diseases with a monogenetic cause nor is it a diagnostic continuum with a complex contribution of thousands of small effect factors. ALS is in-between, which I call “simplex”, where in each patient a few, considerably strong genetic factors with or without environmental factors are at play. ALS mutations are characterized by reduced penetrance, variable clinical expressivity, have specific pleiotropic clinical features and interact with environmental factors. These phenomena are unexplained, but provide me with important and new opportunities in order to unravel the clinical, genetic and biological heterogeneity in ALS. I have created new research fields to go an important step beyond the state of the art: Splitting by lumping uses novel machine learning algorithms to reclassify patients using clinical pleiotropic features, environmental factors and blood epigenetic profiles to identify novel ALS mutations. Imaging genomics overlays patterns in ALS-associated brain morphology on MRI with brain gene-expression patterns to find ALS mutations. ALS risk in 3D integrates data on three-dimensional folding of DNA with genetic data to identify causal mutations and mutation-to-mutation interaction. ALS genomic modifiers in 3D identifies modifiers of C9orf72 mutations through the development of cellular reporter assays and CRISPR-Cas9 based screens. Genomic findings are translated using cellular models which can be used for targeted and unbiased drug screens. If successful, my approaches can be applied beyond the scope of this ERC and will have a clear impact on clinical trial design and genetic counselling in ALS in particular.


year authors and title journal last update
List of publications.
2019 Egor Dolzhenko, Viraj Deshpande, Felix Schlesinger, Peter Krusche, Roman Petrovski, Sai Chen, Dorothea Emig-Agius, Andrew Gross, Giuseppe Narzisi, Brett Bowman, Konrad Scheffler, Joke J F A van Vugt, Courtney French, Alba Sanchis-Juan, Kristina Ibáñez, Arianna Tucci, Bryan R Lajoie, Jan H Veldink, F Lucy Raymond, Ryan J Taft, David R Bentley, Michael A Eberle
ExpansionHunter: a sequence-graph-based tool to analyze variation in short tandem repeat regions
published pages: 4754-4756, ISSN: 1367-4803, DOI: 10.1093/bioinformatics/btz431
Bioinformatics 35/22 2020-03-05
2019 Hannelore K. van der Burgh, Henk-Jan Westeneng, Jil M. Meier, Michael A. van Es, Jan H. Veldink, Jeroen Hendrikse, Martijn P. van den Heuvel, Leonard H. van den Berg
Cross-sectional and longitudinal assessment of the upper cervical spinal cord in motor neuron disease
published pages: 101984, ISSN: 2213-1582, DOI: 10.1016/j.nicl.2019.101984
NeuroImage: Clinical 24 2020-03-05
2019 Annelot M. Dekker, Frank P. Diekstra, Sara L. Pulit, Gijs H. P. Tazelaar, Rick A. van der Spek, Wouter van Rheenen, Kristel R. van Eijk, Andrea Calvo, Maura Brunetti, Philip Van Damme, Wim Robberecht, Orla Hardiman, Russell McLaughlin, Adriano Chiò, Michael Sendtner, Albert C. Ludolph, Jochen H. Weishaupt, Jesus S. Mora Pardina, Leonard H. van den Berg, Jan H. Veldink
Exome array analysis of rare and low frequency variants in amyotrophic lateral sclerosis
published pages: , ISSN: 2045-2322, DOI: 10.1038/s41598-019-42091-3
Scientific Reports 9/1 2020-03-05
2019 Rick A.A. van der Spek, Wouter van Rheenen, Sara L. Pulit, Kevin P. Kenna, Leonard H. van den Berg, Jan H. Veldink
The project MinE databrowser: bringing large-scale whole-genome sequencing in ALS to researchers and the public
published pages: 432-440, ISSN: 2167-8421, DOI: 10.1080/21678421.2019.1606244
Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration 20/5-6 2020-03-05

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

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