Subject:
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DCN 1: Perception and Action DCN 2: Functional Neurogenomics DCN 3: Neuroinformatics EBP 2: Effective Hospital Care EBP 4: Quality of Care NCEBP 10: Human Movement & Fatigue NCEBP 11: Alzheimer Centre NCEBP 6:Quality of nursing and allied health care UMCN 3.2 Cognitive Neurosciences UMCN 3.2: Cognitive neurosciences UMCN 5.1: Genetic defects of metabolism NCEBP 10: Human Movement & Fatigue |
Abstract:
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BACKGROUND: Differentiating idiopathic late-onset cerebellar ataxia (ILOCA) from ataxia due to the cerebellar subtype of multiple-system atrophy (MSA-C) can be difficult in the early stages of the disease METHODS: The authors analyzed the levels of various CSF biomarkers in 27 patients with MSA-C and 18 patients with ILOCA and obtained cut-off points for each potential biomarker to differentiate MSA-C from ILOCA. RESULTS: Increased levels of neurofilament light chain (NFL) and neurofilament heavy chain (NFHp35) and decreased levels of the neurotransmitter metabolites homovanillic acid (HVA), 5-hydroxyindoleaceticacid (5-HIAA), and 3-methoxy-4-hydroxyphenylethyleneglycol (MHPG) were observed in MSA-C compared with ILOCA patients. Receiver operating characteristic analysis showed high sensitivity and specificity levels for NFL, NFHp35, and MHPG analysis. At a cut-off of 24.4 ng/L for the NFL analysis, a sensitivity of 79% and a specificity of 94% were obtained for differentiating MSA-C from ILOCA. At a cut-off point for NFHp35 of 129.5 ng/L, sensitivity was 87% and specificity 83%. Analysis of MHPG levels (cut-off 42.5 nM) resulted in a sensitivity of 86% with a specificity of 75%. A multivariate logistic regression model selected NFL, MHPG, and tau as independent predictive biomarkers that separated the MSA-C and ILOCA groups. CONCLUSIONS: Increased levels of neurofilament light chain and tau and decreased levels of 3-methoxy-4-hydroxyphenylethyleneglycol were associated with high accuracy levels in differentiating the cerebellar subtype of multiple-system atrophy from idiopathic late-onset cerebellar ataxia (LOCA). CSF analysis may thus serve as a useful tool in early diagnostic differentiation of LOCA.
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