Author Of 1 Presentation
P0515 - Application of Metabolomics to Identify Biofluid Biomarkers for Multiple Sclerosis Diagnosis (ID 297)
Abstract
Background
Early diagnosis of multiple sclerosis (MS), a lifelong chronic disease without a permanent cure, allows for the implementation of therapies that may delay the progression of the disease, reduce neurological damage, reduce relapse rates, and improve the quality of life for patients. A diagnosis of MS is limited to the exclusion of other diseases through a complex combination of expensive, invasive, and risky tests (magnetic resonance imaging, spinal tap, etc.) and a subjective interpretation of a patient’s history. The pathological heterogeneity, the different phenotypic variations, the similarity with other CNS diseases, and the complex diagnostic protocol presents a serious challenge to obtaining a rapid and accurate diagnosis for MS. As a consequence, MS patients routinely encounter extensive delays (7.5 years on average) in receiving a correct diagnosis and proper treatments.
Objectives
The objective of this study was to use our integrated NMR and mass spectrometry metabolomics methodology to identify a statistically valid set of urinary, serum and cerebrospinal fluid (CSF) metabolites correlated with MS that can be used to differentiate MS patients from healthy controls as biomarkers of disease diagnosis.
Methods
Nuclear magnetic resonance (NMR) imaging was done to identify the spectral differences found in the biofluids of MS patients and healthy controls. Biofluid samples analyzed in this study included CSF, serum and urine. Then principal component analysis (PCA), partial least squares (PLS) and orthogonal projection to latent structures- discriminant analysis (OPLS-DA) scores plot statistical analyses were done to analyze statistical differences.
Results
A statistical difference was seen in the CSF, serum and urine profiles between healthy controls and MS patients as well as between Primary Progressive MS patients and Relapsing MS patients.
Conclusions
Urinary metabolites can be used to differentiate between MS patients and healthy controls. This methodology could be used in conjunction with the McDonald criteria to help support a more rapid and accurate diagnosis of Multiple Sclerosis.