Cerebrospinal fluid metabolomic signatures in paediatric MOGAD and POMS.

INTRODUCTION

Myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease (MOGAD) and paediatric-onset multiple sclerosis (POMS) are acquired demyelinating syndromes (ADSs) that are increasingly recognised in paediatric care. They share clinical and magnetic resonance imaging (MRI) features, but they differ in prognosis and management, as POMS is a chronic inflammatory neurodegenerative disorder, whereas MOGAD is not. Early POMS diagnosis is essential to limit disability accumulation. Thus, early identification of these syndromes is key to their adequate management and family counselling and improving the outcome. Cerebrospinal fluid (CSF) biochemistry and cell count, oligoclonal band, IgG index, and serum MOG antibodies, together with brain and spine MRI, are the most valuable diagnostic biomarkers for differential diagnosis. However, it is not always possible to rely on these specific biomarkers to correctly identify these syndromes, especially at disease onset. In this perspective, metabolomic and lipidomic analyses have recently gained ground as a novel diagnostic approach.

METHODS

In the present study, high-sensitivity shotgun mass spectrometry was used to characterise the CSF metabolome and lipidome of children with MOGAD and POMS disorders compared with the CSF of children with non-demyelinating diseases used as controls.

RESULTS

The identification of 128 CSF hydrophilic metabolites and 210 lipids revealed characteristic changes in the relative metabolic concentrations in MOGAD compared with POMS, mainly related to the energy metabolism pathways. The lipidomic profile revealed the accumulation of the plasmalogens phosphatidylethanolamine (PE) and cholesterol esters as specific features of the lipid metabolic derangement. In this exploratory cohort, POMS showed higher very-long-chain PE and triglyceride (TG) signal intensities after false discovery rate (FDR) correction and effect size evaluation; however, these trends require confirmation in larger, independent cohorts.

CONCLUSION

By exploring the CSF metabolomic profile, we demonstrated the usefulness of broad-range omic analysis as a fast and reliable method of biomarker discovery in children with demyelinating neurological disorders at the onset of the disease, which may be a valuable diagnostic complement to the existing biomarkers.