Identification of a presymptomatic and early disease signature for amyotrophic lateral sclerosis (ALS): protocol of the premodiALS study
- PMID: 40830802
- PMCID: PMC12366133
- DOI: 10.1186/s42466-025-00417-9
Identification of a presymptomatic and early disease signature for amyotrophic lateral sclerosis (ALS): protocol of the premodiALS study
Abstract
Introduction: The median time to diagnosis of amyotrophic lateral sclerosis (ALS) is approximately 12 months after the onset of first symptoms. This diagnostic delay is primarily due to the nonspecific nature of early symptoms and the clinical challenges in differentiating ALS from its mimics. Therefore, the discovery of reliable biomarkers for the early and accurate diagnosis of ALS represents a critical medical need.
Methods: A total of 330 participants will be recruited across six international study sites. The cohort will include (1) pre-symptomatic gene mutation carriers, (2) symptomatic individuals up to 12 months after symptom onset with either ALS, ALS mimics, or a pure motor syndrome with yet unclear assignment, and (3) healthy controls. Participants will engage in a one-year longitudinal study, consisting of an initial evaluation at baseline visit and a follow-up visit 12 months later. Assessments will include an environmental and medical history questionnaire, neurological examinations, olfactory testing, cognitive/behavioral evaluations, and the collection of biological samples (serum, plasma, urine, tear fluid, and cerebrospinal fluid). Proteomic, metabolomic, and lipidomic analyses will be performed using mass spectrometry and targeted immunoassays, with all samples processed under standardized protocols. The resulting multimodal dataset will be systematically integrated in an effort to uncover a presymptomatic and early ALS signature. Perspective The premodiALS study aim to identify a clinico-molecular signature characteristic of presymptomatic and early ALS. These findings may have relevance to early diagnosis and future clinical practice for ALS disease.
Keywords: Biomarkers; Early diagnosis; Motoneuron disease; Multi-omic; Observational study; Pre-symptomatic.
© 2025. The Author(s).
Conflict of interest statement
Declarations. Ethics approval and consent to participate: This observational clinical study is conducted in accordance with the current ICH-GCP-guidelines and the Declaration of Helsinki. The studies involving humans are approved by the ethics committee at TU München [2022-520_2-S-SB] and are conducted following the local legislation and institutional requirements. We obtained ethics committee approval from all recruitment centers. All participants provided their written informed consent to participate in this study. Written informed consent from the patient must be obtained prior to inclusion into this study. Consent for publication: Not applicable. Competing Interests: The authors declare that they have no competing interests.
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Update of
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Identification of a presymptomatic and early disease signature for Amyotrophic Lateral Sclerosis (ALS): protocol of the premodiALS study.medRxiv [Preprint]. 2025 May 27:2025.05.27.25328387. doi: 10.1101/2025.05.27.25328387. medRxiv. 2025. Update in: Neurol Res Pract. 2025 Aug 19;7(1):56. doi: 10.1186/s42466-025-00417-9. PMID: 40492096 Free PMC article. Updated. Preprint.
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Grants and funding
- SyNergy - ID 390857198/Germany's Excellence Strategy within the framework of the Munich Cluster for Systems Neurology
- 01ED2204A/Bundesministerium für Bildung und Forschung
- No. 950293 - COMBAT-RES/European Union's Horizon 2020 Research and Innovation Programme
- 3-18370/Ministry of Health of Israel
- ANR-21-JPW2-0007-03/Agence Nationale de la Recherche
- 01ED2204B/Bundesministerium für Bildung und Forschung
- 01ED2204B/Karlsruhe School of Elementary Particle and Astroparticle Physics: Science and Technology, Karlsruhe Institute of Technology
- 32ND30_206536/Swiss National Science Foundation (SNSF)
- 2021/03/Y/NZ7/00111/Polish National Science Center (NCN)
- R01 NS105479/NS/NINDS NIH HHS/United States
- EXC 2145/Germany's Excellence Strategy within the framework of the Munich Cluster for Systems Neurology
- 112N004/Scientific and Technological Research Council of Turkey (TÜBİTAK)
- 05-CIG-Rogers 2022/FightMND
- R01NS105479/U.S. National Institutes of Health
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