Cardiac troponin T as a serum biomarker of respiratory impairment in amyotrophic lateral sclerosis.


Journal

Annals of clinical and translational neurology
ISSN: 2328-9503
Titre abrégé: Ann Clin Transl Neurol
Pays: United States
ID NLM: 101623278

Informations de publication

Date de publication:
25 Jun 2024
Historique:
revised: 26 05 2024
received: 09 05 2024
accepted: 03 06 2024
medline: 26 6 2024
pubmed: 26 6 2024
entrez: 26 6 2024
Statut: aheadofprint

Résumé

Informative biomarkers are an urgent need in the management of amyotrophic lateral sclerosis. Serum cardiac troponin T is elevated in the majority of amyotrophic lateral sclerosis patients and increases with disease progression. We sought to establish the informative value of cardiac troponin T with regard to respiratory function, a major prognostic factor in amyotrophic lateral sclerosis. In this retrospective observation, we analyzed two independent hospital-based cohorts (d = discovery cohort; v = validation cohort) regarding serum cardiac troponin T (n Serum cardiac troponin T, in contrast to serum neurofilament levels, was associated with the respiratory domain of the revised amyotrophic lateral sclerosis functional rating scale and with pulmonary function parameters, namely forced vital capacity % (r = -0.45, p = 0.001) and slow vital capacity % (r = -0.50, p = 0.001). Serum cardiac troponin T reliably discriminated benchmarks of slow vital capacity <80% (AUC 0.73, 95% CI 0.62-0.84) and <50% (AUC 0.80, 95% CI 0.68-0.93), forced vital capacity <80% (AUC 0.72, 95% CI 0.61-0.83) and <50% (AUC 0.79, 95% CI 0.67-0.91). Our findings position cardiac Troponin T as a valuable serum biomarker in amyotrophic lateral sclerosis, complementing neurofilaments and expanding the understanding of underlying physiological mechanisms. In clinical practice, serum cardiac troponin T can flag benchmarks of compromised respiratory function.

Identifiants

pubmed: 38923228
doi: 10.1002/acn3.52126
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Boris Canessa Foundation
Organisme : Alzheimer Forschung Initiative e.V
ID : 21060
Organisme : Hertie Network of Excellence in Clinical Neuroscience
ID : 2021-1A-12
Organisme : BONFOR-Forschungskommission der Medizinischen Fakultät Bonn
Organisme : Neuro-aCSis Bonn Neuroscience Clinician Scientist Program
Organisme : Deutsche Forschungsgemeinschaft
ID : EXC2151-390873048

Informations de copyright

© 2024 The Author(s). Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.

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Auteurs

Teresa Koch (T)

Department of Neuromuscular Diseases, Center for Neurology, University Hospital Bonn, Bonn, 53127, Germany.

Rachel Fabian (R)

Department of Neuromuscular Diseases, Center for Neurology, University Hospital Bonn, Bonn, 53127, Germany.

Leonie Weinhold (L)

Department for Medical Biometry, Informatics and Epidemiology, University Hospital Bonn, Bonn, 53127, Germany.

Franz-W Koch (FW)

Department of Pulmology, Neukölln Hospital, Berlin, Germany.

Saman Barakat (S)

Department of Neuromuscular Diseases, Center for Neurology, University Hospital Bonn, Bonn, 53127, Germany.

Sergio Castro-Gomez (S)

Department of Parkinson, Sleep and Movement Disorders, Center for Neurology, University Hospital Bonn, Bonn, 53127, Germany.
Institute of Physiology II, University Hospital Bonn, Bonn, 53115, Germany.

Torsten Grehl (T)

Department of Neurology, Alfried - Krupp-Hospital, Essen, Germany.

Sarah Bernsen (S)

Department of Neuromuscular Diseases, Center for Neurology, University Hospital Bonn, Bonn, 53127, Germany.
German Center for Neurodegenerative Diseases (DZNE), Bonn, 53127, Germany.

Patrick Weydt (P)

Department of Neuromuscular Diseases, Center for Neurology, University Hospital Bonn, Bonn, 53127, Germany.
Department of Parkinson, Sleep and Movement Disorders, Center for Neurology, University Hospital Bonn, Bonn, 53127, Germany.
German Center for Neurodegenerative Diseases (DZNE), Bonn, 53127, Germany.

Classifications MeSH