Open AccessDisease Type- and Status-Specific Alteration of CSF Metabolome Coordinated with Clinical Parameters in Inflammatory Demyelinating Diseases of CNS
Author(s) -
Soo Jin Park,
Ilgyu Jeong,
Byung Soo Kong,
Jung Eun Lee,
Kyoung Heon Kim,
Eun Jig Lee,
Ho Jin Kim
Publication year - 2016
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0166277
Subject(s) - multiple sclerosis , neuromyelitis optica , biomarker , medicine , biomarker discovery , metabolome , metabolite , demyelinating disorder , expanded disability status scale , multiplex , cerebrospinal fluid , demyelinating disease , disease , immunology , pathology , bioinformatics , biology , proteomics , biochemistry , gene
Central nervous system (CNS) inflammatory demyelinating diseases (IDDs) are a group of disorders with different aetiologies, characterized by inflammatory lesions. These disorders include multiple sclerosis (MS), neuromyelitis optica spectrum disorder (NMOSD), and idiopathic transverse myelitis (ITM). Differential diagnosis of the CNS IDDs still remains challenging due to frequent overlap of clinical and radiological manifestation, leading to increased demands for new biomarker discovery. Since cerebrospinal fluid (CSF) metabolites may reflect the status of CNS tissues and provide an interfacial linkage between blood and CNS tissues, we explored multi-component biomarker for different IDDs from CSF samples using gas chromatography mass spectrometry-based metabolite profiling coupled to multiplex bioinformatics approach. We successfully constructed the single model with multiple metabolite variables in coordinated regression with clinical characteristics, expanded disability status scale, oligoclonal bands, and protein levels. The multi-composite biomarker simultaneously discriminated four different immune statuses (a total of 145 samples; 54 MS, 49 NMOSD, 30 ITM, and 12 normal controls). Furthermore, systematic characterization of transitional metabolic modulation identified relapse-associated metabolites and proposed insights into the disease network underlying type-specific metabolic dysfunctionality. The comparative analysis revealed the lipids, 1-monopalmitin and 1-monostearin were common indicative for MS, NMOSD, and ITM whereas fatty acids were specific for the relapse identified in all types of IDDs.