Abstract
Background : Multiple system atrophy (MSA), an atypical parkinsonian syndrome, is a rapidly progressive neurodegenerative disease with currently no established fluid biomarkers available. MSA is characterized by an oligodendroglial α-synucleinopathy, progressive neuronal cell loss and concomitant astrocytosis. Here, we investigate glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) as fluid biomarkers for differential diagnosis, assessment of clinical disease severity and prediction of disease progression in MSA. Methods : GFAP and NfL levels were analyzed in plasma and CSF samples of 47 MSA patients as well as 24 Parkinson’s disease (PD) and 25 healthy controls (HC) as reference cohorts. In MSA, biomarker levels were correlated to baseline and longitudinal clinical disease severity (UMSARS scores). Results : In MSA, GFAP levels in CSF and plasma predicted baseline clinical disease severity as indicated by UMSARS scores, while NfL levels predicted clinical disease progression as indicated by longitudinal changes in UMSARS scores. Cross-sectionally, NfL levels in CSF and plasma were significantly elevated in MSA compared to both PD and HC. Receiver operating curves (ROC) indicated high diagnostic accuracy of NfL for distinguishing MSA from PD (CSF: AUC = 0.97, 95% CI 0.90–1.00; plasma: AUC = 0.90, 95% CI 0.81–1.00). Discussion : In MSA, GFAP shows promise as novel biomarker for assessing current clinical disease severity, while NfL might serve as biomarker for prediction of disease progression and differential diagnosis of MSA against PD.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Medizin
Medizin > Munich Cluster for Systems Neurology (SyNergy) Medizin > Institut für Schlaganfall- und Demenzforschung (ISD) Medizin > Klinikum der LMU München > Neurologische Klinik und Poliklinik mit Friedrich-Baur-Institut |
Themengebiete: | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit |
URN: | urn:nbn:de:bvb:19-epub-123158-6 |
ISSN: | 0340-5354 |
Sprache: | Englisch |
Dokumenten ID: | 123158 |
Datum der Veröffentlichung auf Open Access LMU: | 19. Dez. 2024 07:29 |
Letzte Änderungen: | 19. Dez. 2024 07:29 |
DFG: | Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - 390857198 |