A ferroptosis–based panel of prognostic biomarkers for Amyotrophic Lateral Sclerosis View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-12

AUTHORS

David Devos, Caroline Moreau, Maeva Kyheng, Guillaume Garçon, Anne Sophie Rolland, Hélène Blasco, Patrick Gelé, T. Timothée Lenglet, C. Veyrat-Durebex, Philippe Corcia, Mary Dutheil, Peter Bede, Andreas Jeromin, Patrick Oeckl, Markus Otto, Vincent Meninger, Véronique Danel-Brunaud, Jean-christophe Devedjian, James A. Duce, Pierre François Pradat

ABSTRACT

Accurate patient stratification into prognostic categories and targeting Amyotrophic Lateral Sclerosis (ALS)-associated pathways may pave the way for promising trials. We evaluated blood-based prognostic indicators using an array of pathological markers. Plasma samples were collected as part of a large, phase III clinical trial (Mitotarget/TRO19622) at months 1, 6, 12 and 18. The ALSFRS-r score was used as a proxy of disease progression to assess the predictive value of candidate biological indicators. First, established clinical predictors were evaluated in all 512 patients. Subsequently, pathologic markers, such as proxies of neuronal integrity (Neurofilament light chain and phosphorylated heavy chain), DNA oxidation (8-oxo-2'-desoxyguanosine), lipid peroxidation (4-hydroxy-2-nonenal, isoprostane), inflammation (interleukin-6) and iron status (ferritin, hepcidin, transferrin) were assessed in a subset of 109 patients that represented the whole cohort. Markers of neuronal integrity, DNA and lipid oxidation, as well as iron status at baseline are accurate predictors of disability at 18-month follow-up. The composite scores of these markers in association with established clinical predictors enable the accurate forecasting of functional decline. The identified four biomarkers are all closely associated with 'ferroptosis', a recently discovered form of programmed cell death with promising therapeutic targets. The predictive potential of these pathophysiology-based indicators may offer superior patient stratification for future trials, individualised patient care and resource allocation. More... »

PAGES

2918

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41598-019-39739-5

DOI

http://dx.doi.org/10.1038/s41598-019-39739-5

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112394096

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30814647


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1038/s41598-019-39739-5'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/s41598-019-39739-5'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/s41598-019-39739-5'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/s41598-019-39739-5'


 

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