Your browser doesn't support javascript.
loading
Metabolomics detects clinically silent neuroinflammatory lesions earlier than neurofilament-light chain in a focal multiple sclerosis animal model.
Yeo, Tianrong; Bayuangga, Halwan; Augusto-Oliveira, Marcus; Sealey, Megan; Claridge, Timothy D W; Tanner, Rachel; Leppert, David; Palace, Jacqueline; Kuhle, Jens; Probert, Fay; Anthony, Daniel C.
  • Yeo T; Department of Pharmacology, University of Oxford, Mansfield Road, Oxford, OX1 3QT, UK.
  • Bayuangga H; Department of Neurology, National Neuroscience Institute, Singapore, Singapore.
  • Augusto-Oliveira M; Duke-NUS Medical School, Singapore, Singapore.
  • Sealey M; Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.
  • Claridge TDW; Department of Pharmacology, University of Oxford, Mansfield Road, Oxford, OX1 3QT, UK.
  • Tanner R; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
  • Leppert D; Department of Neurology, Faculty of Medicine, Public Health, and Nursing, Gadjah Mada University, Yogyakarta, Indonesia.
  • Palace J; Department of Pharmacology, University of Oxford, Mansfield Road, Oxford, OX1 3QT, UK.
  • Kuhle J; Laboratório de Farmacologia Molecular, Instituto de Ciências Biológicas, Universidade Federal Do Pará, Belém, Brazil.
  • Probert F; Programa de Pós-Graduação em Farmacologia e Bioquímica, Instituto de Ciências Biológicas, Universidade Federal do Pará, Belém, Brazil.
  • Anthony DC; Department of Pharmacology, University of Oxford, Mansfield Road, Oxford, OX1 3QT, UK.
J Neuroinflammation ; 19(1): 252, 2022 Oct 09.
Article en En | MEDLINE | ID: mdl-36210459
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.
Asunto(s)
Palabras clave

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Esclerosis Múltiple Tipo de estudio: Prognostic_studies Límite: Animals / Humans Idioma: En Año: 2022 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Esclerosis Múltiple Tipo de estudio: Prognostic_studies Límite: Animals / Humans Idioma: En Año: 2022 Tipo del documento: Article