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Chitinase dysregulation predicts disease aggressiveness in ALS: Insights from the D50 progression model
  1. Nayana Gaur1,2,
  2. Robert Steinbach2,
  3. Mario Plaas1,
  4. Otto W Witte2,3,
  5. Monika S Brill4,5,
  6. Julian Grosskreutz2,6
  1. 1 Laboratory Animal Center, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
  2. 2 Department of Neurology, Universitätsklinikuum Jena, Jena, Germany
  3. 3 Center for Healthy Ageing, Universitätsklinikuum Jena, Jena, Germany
  4. 4 Technische Universität München, Institute of Neuronal Cell Biology, Munich, Germany
  5. 5 Munich Cluster of Systems Neurology (SyNergy), Munich, Germany
  6. 6 Department of Neurology, Precision Medicine, Universität zu Lübeck, Lübeck, Germany
  1. Correspondence to Dr. Nayana Gaur, Laboratory Animal Center, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu 50411, Estonia; nayana.gaur{at}ut.ee

https://doi.org/10.1136/jnnp-2022-330318

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    Amyotrophic lateral sclerosis (ALS) is the most prevalent form of adult-onset motor neuron disease with a median survival of 2–3 years from symptom onset. No cure exists as therapeutic development has been severely constrained by the disease’s multifactorial aetiology and phenotypic heterogeneity. Biomarkers that reflect specific pathological processes can assist with patient stratification and provide readouts of treatment efficacy. In lieu of this, reports of chitinases as markers of neuroinflammation in several neurodegenerative disorders are particularly interesting. Mammalian chitinases are hydrolytic enzymes involved in chitin degradation and several cellular processes, including chemotactic signalling and inflammatory responses.1 Although CHIT1, CHI3L1 and CHI3L2 are elevated in ALS, the clinical implications remain unclear: existing studies have reported discrepant links with outcome metrics, including survival, total Amyotrophic Lateral Sclerosis Functional Rating Scale (ALSFRS-R) score and the calculated disease progression rate (PR).2–5 This may partially stem from limitations associated with the ALSFRS-R itself; it has limited interindividual comparability owing to its multidimensionality.6 Similarly, the derived PR presumes linear functional decline and depends on the sampling time point.7 Progression type stratification (for example, rapid versus slow) is also arbitrary as there are no universal cut-offs. The D50 model was developed to address these limitations; briefly, it uses iterative fitting of all ALSFRS-R scores available for an individual to generate a sigmoidal curve spanning the disease course from full health to functional loss. This yields two key metrics: (1) D50 (time taken in months for ALSFRS-R score to halve, ie, 50% functional loss) and (2) relative D50 (rD50), an open-ended reference scale describing individual disease covered (0=disease onset and 0.5=time point of halved functionality). Together, these provide unified descriptors that are independent of sampling time for overall disease aggressiveness (D50) and accumulated degeneration (rD50). Therefore, links between potential biomarkers and either of these …

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    Footnotes

    • Contributors Study conception and design: NG, RS and JG; Data acquisition and analysis: NG and RS. Manuscript original draft compilation, subsequent editing and figure preparation: NG, RS, MP, OWW, MSB and JG. All authors consented to the final version of this manuscript.

    • Funding JG was supported by the German Ministry for Education and Research (BMBF) through the JPND grants SOPHIA (01ED1202B) and ONWebDUALS (01ED15511A), the E-RARE grant PYRAMID (01GM1304), the Deutsche Forschungsgemeinschaft (DFG Grant GR 1578/6-1) and the Boris Canessa foundation. JG is also supported by the Cluster of Excellence Precision Medicine in Inflammation (DFG grant EXC 2167). MSB is the recipient of a Deutsche Forschungsgemeinschaft research grant (LE 4610/1-1; 450131873). JG and MSB are also supported by the Deutsche Gesellschaft für Muskelkranke (DGM). NG was supported by a doctoral scholarship (Landesgraduiertenstipendien) from the Graduate Academy of Friedrich Schiller University, Jena, Germany and the state of Thuringia and is currently supported by a postdoctoral fellowship from the Estonian Research Council (Grant SJD90). MP is funded by the Estonian Research Council (Grant PSG471). RS is supported by the Deutsche Forschungsgemeinschaft (DFG) with a clinician scientist programme grant (413668513).

    • Competing interests None declared.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.