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Published in: Journal of Neuroinflammation 1/2022

Open Access 01-12-2022 | Multiple Sclerosis | Research

Metabolomics detects clinically silent neuroinflammatory lesions earlier than neurofilament-light chain in a focal multiple sclerosis animal model

Authors: Tianrong Yeo, Halwan Bayuangga, Marcus Augusto-Oliveira, Megan Sealey, Timothy D. W. Claridge, Rachel Tanner, David Leppert, Jacqueline Palace, Jens Kuhle, Fay Probert, Daniel C. Anthony

Published in: Journal of Neuroinflammation | Issue 1/2022

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Abstract

Background

Despite widespread searches, there are currently no validated biofluid markers for the detection of subclinical neuroinflammation in multiple sclerosis (MS). The dynamic nature of human metabolism in response to changes in homeostasis, as measured by metabolomics, may allow early identification of clinically silent neuroinflammation. Using the delayed-type hypersensitivity (DTH) MS rat model, we investigated the serum and cerebrospinal fluid (CSF) metabolomics profiles and neurofilament-light chain (NfL) levels, as a putative marker of neuroaxonal damage, arising from focal, clinically silent neuroinflammatory brain lesions and their discriminatory abilities to distinguish DTH animals from controls.

Methods

1H nuclear magnetic resonance (NMR) spectroscopy metabolomics and NfL measurements were performed on serum and CSF at days 12, 28 and 60 after DTH lesion initiation. Supervised multivariate analyses were used to determine metabolomics differences between DTH animals and controls. Immunohistochemistry was used to assess the extent of neuroinflammation and tissue damage.

Results

Serum and CSF metabolomics perturbations were detectable in DTH animals (vs. controls) at all time points, with the greatest change occurring at the earliest time point (day 12) when the neuroinflammatory response was most intense (mean predictive accuracy [SD]—serum: 80.6 [10.7]%, p < 0.0001; CSF: 69.3 [13.5]%, p < 0.0001). The top discriminatory metabolites at day 12 (serum: allantoin, cytidine; CSF: glutamine, glucose) were all reduced in DTH animals compared to controls, and correlated with histological markers of neuroinflammation, particularly astrogliosis (Pearson coefficient, r—allantoin: r = − 0.562, p = 0.004; glutamine: r = − 0.528, p = 0.008). Serum and CSF NfL levels did not distinguish DTH animals from controls at day 12, rather, significant differences were observed at day 28 (mean [SEM]—serum: 38.5 [4.8] vs. 17.4 [2.6] pg/mL, p = 0.002; CSF: 1312.0 [379.1] vs. 475.8 [74.7] pg/mL, p = 0.027). Neither serum nor CSF NfL levels correlated with markers of neuroinflammation; serum NfL did, however, correlate strongly with axonal loss (r = 0.641, p = 0.001), but CSF NfL did not (p = 0.137).

Conclusions

While NfL levels were elevated later in the pathogenesis of the DTH lesion, serum and CSF metabolomics were able to detect early, clinically silent neuroinflammation and are likely to present sensitive biomarkers for the assessment of subclinical disease activity in patients.
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Metadata
Title
Metabolomics detects clinically silent neuroinflammatory lesions earlier than neurofilament-light chain in a focal multiple sclerosis animal model
Authors
Tianrong Yeo
Halwan Bayuangga
Marcus Augusto-Oliveira
Megan Sealey
Timothy D. W. Claridge
Rachel Tanner
David Leppert
Jacqueline Palace
Jens Kuhle
Fay Probert
Daniel C. Anthony
Publication date
01-12-2022
Publisher
BioMed Central
Published in
Journal of Neuroinflammation / Issue 1/2022
Electronic ISSN: 1742-2094
DOI
https://doi.org/10.1186/s12974-022-02614-8

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