Journal
BRAIN
Volume 144, Issue -, Pages 2625-2634Publisher
OXFORD UNIV PRESS
DOI: 10.1093/brain/awab147
Keywords
CNS autoimmunity; multiple sclerosis; differential diagnosis; CSF; immune profile
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By analyzing a large number of patients with autoimmune neuroinflammatory, degenerative, or vascular conditions, this study identified pan-disease parameters and inter-autoimmunity classifiers that can aid in the differential diagnosis of neurological diseases. Combining multiple parameters into composite scores was shown to assist in the classification of neurological patients, ultimately improving early treatment decisions.
Although CSF analysis routinely enables the diagnosis of neurological diseases, it is mainly used for the gross distinction between infectious, autoimmune inflammatory, and degenerative disorders of the CNS. To investigate, whether a multi-dimensional cellular blood and CSF characterization can support the diagnosis of clinically similar neurological diseases, we analysed 546 patients with autoimmune neuroinflammatory, degenerative, or vascular conditions in a cross-sectional retrospective study. By combining feature selection with dimensionality reduction and machine learning approaches we identified pan-disease parameters that were altered across all autoimmune neuroinflammatory CNS diseases and differentiated them from other neurological conditions and inter-autoimmunity classifiers that subdifferentiate variants of CNS-directed autoimmunity. Pan-disease as well as diseases-specific changes formed a continuum, reflecting clinical disease evolution. A validation cohort of 231 independent patients confirmed that combining multiple parameters into composite scores can assist the classification of neurological patients. Overall, we showed that the integrated analysis of blood and CSF parameters improves the differential diagnosis of neurological diseases, thereby facilitating early treatment decisions.
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