Evidence map›Paper›PMID 40806220›Full record

ArticleInternational journal of molecular sciences2025

Identifying Therapeutic Targets for Amyotrophic Lateral Sclerosis Through Modeling of Multi-Omics Data.

François Xavier Blaudin de Thé, Cornelius J H M Klemann, Ward De Witte, Joanna Widomska, Philippe Delagrange, Clotilde Mannoury La Cour, Mélanie Fouesnard, Sahar Elouej, Keith Mayl, Nicolas Lévy and 4 more

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

François Xavier Blaudin de ThéServier Research & Development, 91190 Saclay, France.ORCID 0000-0002-9135-4116
Cornelius J H M KlemannDonders Institute for Brain, Cognition and Behaviour, Radboud University, 6525 EN Nijmegen, The Netherlands.
Ward De WitteDonders Institute for Brain, Cognition and Behaviour, Radboud University, 6525 EN Nijmegen, The Netherlands.
Joanna WidomskaDonders Institute for Brain, Cognition and Behaviour, Radboud University, 6525 EN Nijmegen, The Netherlands.
Philippe DelagrangeServier Research & Development, 91190 Saclay, France.
Clotilde Mannoury La CourServier Research & Development, 91190 Saclay, France.
Mélanie FouesnardServier Data Factory, 92284 Suresnes, France.ORCID 0000-0003-4514-5265
Sahar ElouejServier Research & Development, 91190 Saclay, France.
Keith MaylServier Research & Development, 91190 Saclay, France.
Nicolas LévyServier Research & Development, 91190 Saclay, France.
Johannes KruppServier Research & Development, 91190 Saclay, France.
Ross JeggoServier Research & Development, 91190 Saclay, France.
Philippe MoingeonServier Research & Development, 91190 Saclay, France.
Geert PoelmansDonders Institute for Brain, Cognition and Behaviour, Radboud University, 6525 EN Nijmegen, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease that primarily affects motor neurons, leading to loss of muscle control, and, ultimately, respiratory failure and death. Despite some advances in recent years, the underlying genetic and molecular mechanisms of ALS remain largely elusive. In this respect, a better understanding of these mechanisms is needed to identify new and biologically relevant therapeutic targets that could be developed into treatments that are truly disease-modifying, in that they address the underlying causes rather than the symptoms of ALS. In this study, we used two approaches to model multi-omics data in order to map and elucidate the genetic and molecular mechanisms involved in ALS, i.e., the molecular landscape building approach and the Patrimony platform. These two methods are complementary because they rely upon different omics data sets, analytic methods, and scoring systems to identify and rank therapeutic target candidates. The orthogonal combination of the two modeling approaches led to significant convergences, as well as some complementarity, both for validating existing therapeutic targets and identifying novel targets. As for validating existing targets, we found that, out of 217 different targets that have been or are being investigated for drug development, 10 have high scores in both the landscape and Patrimony models, suggesting that they are highly relevant for ALS. Moreover, through both models, we identified or corroborated novel putative drug targets for ALS. A notable example of such a target is MATR3, a protein that has strong genetic, molecular, and functional links with ALS pathology. In conclusion, by using two distinct and highly complementary disease modeling approaches, this study enhances our understanding of ALS pathogenesis and provides a framework for prioritizing new therapeutic targets. Moreover, our findings underscore the potential of leveraging multi-omics analyses to improve target discovery and accelerate the development of effective treatments for ALS, and potentially other related complex human diseases.

Indexed as

Amyotrophic Lateral SclerosisGenomicsComputational BiologyDrug DiscoveryHumansMolecular Targeted TherapyMultiomicsProteomicsamyotrophic lateral sclerosis (ALS)MATR3molecular landscapemulti-omics modelingpatrimonytherapeutic targets

Identifiers

PMID40806220
PMCPMC12346086

What Socratic holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.