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Journal article
Entering the era of precision medicine to treat amyotrophic lateral sclerosis
Molecular neurodegeneration, Vol.20(1), 111
2025
PMID: 41131592
Abstract
With the disease modifying therapy Qalsody (tofersen) which targets the RNA product of the SOD1 gene, having been shown effective in amyotrophic lateral sclerosis (ALS), the present perspective seeks to explore progress towards the implementation of precision medicine principles in ALS drug development. We address the advances in our understanding of the complex genetic architecture of ALS, including the varying models of genetic contribution to disease, and the importance of understanding population genetics and genetic testing when considering patient selection for clinical studies. Additionally, we discuss the advances in long-read whole-genome sequencing technology and how this method can improve streamlined genetic testing and our understanding of the genetic heterogeneity in ALS. We highlight the recent advances in omics-data for understanding ALS patient sub-groups and how this knowledge should be applied to pre-clinical drug development in a proposed patient profiling workflow, particularly for gene targeted therapies. Finally, we summarise key ethical considerations that are pertinent to equitable care for patients, as we enter the era of precision medicine to treat ALS.
Key points
1. Precision medicine means giving the right drug to the right patient at the right time. With the emergence of antisense oligonucleotide technologies, additional gene targeted therapies will soon enter the market for ALS.
2. The improved understanding of the complex genetic architecture of ALS and pathophysiological mechanisms involved in disease has increased the number of validated drug targets for ALS.
3. Long-read sequencing will revolutionise our understanding of ALS genetics through the comprehensive mapping of genetic variation. Long read sequencing has enabled the complete sequence of a human genome and subsequently, the first human global and population-specific pan-genome references, adding hundreds of millions of bases that were not present in the previous human genome reference.
4. Leveraging omics data and machine learning methodologies will improve our understanding of both ALS phenotype and the underlying molecular heterogeneity between ALS patients, enhancing patient stratification through the detection of specific sub-groups of patients.
5. Comprehensive patient profiling through the collection of full omics data will be critical to define responder populations. A patient profiling workflow is proposed to conduct in vitro trials alongside early clinical studies as more antisense therapies begin entering the clinic.
6. Ethical strategies to consider for population targeted therapeutic development include tiered pricing models, public-private partnerships, and global distribution initiatives, all of which may be valuable for facilitating access to genetic therapies, thereby reducing inequalities in ALS care.
Details
- Title
- Entering the era of precision medicine to treat amyotrophic lateral sclerosis
- Authors/Creators
- Frances Theunissen - The University of Notre Dame AustraliaLoren Flynn - Murdoch UniversityAlfredo Iacoangeli - King's College LondonAhmad Al Khleifat - Perron Institute for Neurological and Translational ScienceAmmar Al-Chalabi - King's College LondonJames J Giordano - Georgetown UniversityMasha Strømme - Murdoch UniversityP Anthony Akkari - Murdoch University
- Publication Details
- Molecular neurodegeneration, Vol.20(1), 111
- Publisher
- BioMed Central Ltd unless otherwise stated. Part of Springer Nature.
- Number of pages
- 25
- Identifiers
- 991005824542507891
- Copyright
- © The Author(s) 2025
- Murdoch Affiliation
- Personalised Medicine Centre
- Language
- English
- Resource Type
- Journal article
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- Collaboration types
- Domestic collaboration
- International collaboration
- Citation topics
- 1 Clinical & Life Sciences
- 1.52 Neurodegenerative Diseases
- 1.52.765 ALS Mechanisms
- Web Of Science research areas
- Neurosciences
- ESI research areas
- Neuroscience & Behavior