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  • Review Article
  • Published:

Biomarkers in amyotrophic lateral sclerosis: current status and future prospects

Nature Reviews Neurology volume 19, pages 754–768 (2023)Cite this article

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Abstract

Disease heterogeneity in amyotrophic lateral sclerosis poses a substantial challenge in drug development. Categorization based on clinical features alone can help us predict the disease course and survival, but quantitative measures are also needed that can enhance the sensitivity of the clinical categorization. In this Review, we describe the emerging landscape of diagnostic, categorical and pharmacodynamic biomarkers in amyotrophic lateral sclerosis and their place in the rapidly evolving landscape of new therapeutics. Fluid-based markers from cerebrospinal fluid, blood and urine are emerging as useful diagnostic, pharmacodynamic and predictive biomarkers. Combinations of imaging measures have the potential to provide important diagnostic and prognostic information, and neurophysiological methods, including various electromyography-based measures and quantitative EEG–magnetoencephalography-evoked responses and corticomuscular coherence, are generating useful diagnostic, categorical and prognostic markers. Although none of these biomarker technologies has been fully incorporated into clinical practice or clinical trials as a primary outcome measure, strong evidence is accumulating to support their clinical utility.

Key points

  • The heterogeneity in both the clinical presentation and underlying pathobiology of amyotrophic lateral sclerosis in humans has limited the translation from preclinical models to successful clinical trials.

  • Disease categorization might be improved using ancillary and companion measures. Such biomarkers can serve diagnostic, categorical and prognostic functions.

  • Biomarkers that are closest to use in the clinical domain include neurofilaments, which can be measured in serum and cerebrospinal fluid.

  • Promising emerging biomarkers include those derived from neurophysiological assessment such as quantitative EEG and transcranial magnetic stimulation.

  • No single biomarker modality will adequately cover all of the diagnostic, categorical prognostic and pharmacodynamic requirements to support the successful development of novel therapeutics.

  • The future landscape is likely to both integrate different biomarker modalities and use deep learning and artificial intelligence to fully address the complexity of amyotrophic lateral sclerosis.

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Fig. 1: Biomarkers for ALS.
Fig. 2: Fluid biomarkers for amyotrophic lateral sclerosis.
Fig. 3: Protein modifications that can inform amyotrophic lateral sclerosis biomarker discovery.
Fig. 4: Neurophysiological biomarkers.
Fig. 5: Multimodal integration of biomarkers for amyotrophic lateral sclerosis.

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Acknowledgements

The authors wish to thank Juliette Foucher, PhD student in the Department of Clinical Neuroscience, Karolinska Institute, for her contribution to the figures in this Review. This work was funded in part by Science Foundation Ireland grants SP20/SP/8953, 16/RC/3948 and 13/RC/2106_P2. R. McMackin is supported by the Motor Neurone Disease Association UK (McMackin/Oct20/972–799). P.B. is supported by the Health Research Board (HRB EIA-2017–019 & JPND-Cofund-2–2019–1), the Irish Institute of Clinical Neuroscience (IICN) and the EU Joint Programme – Neurodegenerative Disease Research (JPND).

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Authors and Affiliations

  1. Discipline of Physiology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, The University of Dublin, Dublin, Ireland

    Roisin McMackin

  2. Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, The University of Dublin, Dublin, Ireland

    Roisin McMackin, Peter Bede & Orla Hardiman

  3. Computational Neuroimaging Group, School of Medicine, Trinity College Dublin, The University of Dublin, Dublin, Ireland

    Peter Bede

  4. Department of Neurology, St James’s Hospital, Dublin, Ireland

    Peter Bede

  5. Department of Neuroscience, Karolinska Institute, Stockholm, Sweden

    Caroline Ingre

  6. Department of Neurology, Karolinska University Hospital, Stockholm, Sweden

    Caroline Ingre

  7. Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, University College London, London, UK

    Andrea Malaspina

  8. Department of Neurology, Beaumont Hospital, Dublin, Ireland

    Orla Hardiman

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The authors contributed equally to all aspects of the article.

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Correspondence to Orla Hardiman.

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Competing interests

C.I. has consulted for Cytokinetics and Pfizer and is a data monitoring committee member for Appelis Pharmaceutical. A.M. has acted as an adviser for Roche and Accure Therapeutics and has given a Lecture to Pfizer. He has been part of biomarker data licencing to Biogen. R.M. has provided consultancy to The Science Behind. O.H. has consulted for the following companies: Biogen, Novartis, Denali and Cytokinetics. She is Chair of a Data Safety Monitoring Board for Accelsiors. She is Lead PrincipaI Investigator on an academic–industry collaboration funded by Science Foundation Ireland, in partnership with Biogen, Takeda, Novartis, IQVIA and Accenture. She is Editor-in-Chief of the journal Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration. P.B. declares no competing interests.

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McMackin, R., Bede, P., Ingre, C. et al. Biomarkers in amyotrophic lateral sclerosis: current status and future prospects. Nat Rev Neurol 19, 754–768 (2023). https://doi.org/10.1038/s41582-023-00891-2

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