Journal article
Short structural variants as informative genetic markers for ALS disease risk and progression
BMC Medicine, Vol.20(1), Art. 11
2022
Abstract
There is considerable variability in disease progression for patients with amyotrophic lateral sclerosis (ALS) including the age of disease onset, site of disease onset, and survival time. There is growing evidence that short structural variations (SSVs) residing in frequently overlooked genomic regions can contribute to complex disease mechanisms and can explain, in part, the phenotypic variability in ALS patients. Here, we discuss SSVs recently characterized by our laboratory and how these discoveries integrate into the current literature on ALS, particularly in the context of application to future clinical trials. These markers may help to identify and differentiate patients for clinical trials that have a similar ALS disease mechanism(s), thereby reducing the impact of participant heterogeneity. As evidence accumulates for the genetic markers discovered in SQSTM1, SCAF4, and STMN2, we hope to improve the outcomes of future ALS clinical trials.
Details
- Title
- Short structural variants as informative genetic markers for ALS disease risk and progression
- Authors/Creators
- F. Theunissen (Author/Creator) - Perron Institute for Neurological and Translational ScienceL.L. Flynn (Author/Creator) - Murdoch UniversityR.S. Anderton (Author/Creator) - The University of Western AustraliaP.A. Akkari (Author/Creator) - Murdoch University
- Publication Details
- BMC Medicine, Vol.20(1), Art. 11
- Publisher
- BioMed Central
- Identifiers
- 991005542678207891
- Copyright
- © 2022 Theunissen et al.
- Murdoch Affiliation
- Centre for Molecular Medicine and Innovative Therapeutics
- 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
- Genetics & Heredity
- ESI research areas
- Clinical Medicine