Serum neurofilament light chain reflects inflammation-driven neurodegeneration and predicts delayed brain volume loss in early stage of multiple sclerosis

Srpová, Barbora; Uher, Tomáš; Hrnčiarová, Tereza; Barro, Christian; Andělová, Michaela; Michalak, Zuzanna; Vaněčková, Manuela; Krásenský, Jan; Nosková, Libuše; Havrdová, Eva; Kuhle, Jens; Horáková, Dana

doi:10.1177/1352458519901272

Cited by 44 publications

(40 citation statements)

References 34 publications

(73 reference statements)

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“…Similar findings have been reported in a few studies. 2,21 This may be also reflected by the two AUC values: NEDA-3-AUC (0.902) was higher than NEDA-BVL-AUC (0.757). This probably reflects the smaller number of patients with NEDA-BVL status compared with the NEDA-3.…”

Section: Discussionmentioning

confidence: 93%

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Plasma neurofilament light chain levels are predictors of disease activity in multiple sclerosis as measured by four-domain NEDA status, including brain volume loss

et al. 2021

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Background: The research is focused on sensitive biomarkers in multiple sclerosis (MS). Objective: The aim of the study was to assess the relationship between plasma neurofilament light chain (pNfL) and disease activity as defined by the concept NEDA (no evident disease activity), including brain volumetry, in a cohort of MS patients treated with disease-modifying treatment (DMT). Methods: Levels of pNfL (Single Molecule Array (SIMOA) technology) were examined in 95 RRMS (relapsing-remitting multiple sclerosis) patients and analyzed in relationship to NEDA-3 status and NEDA-BVL (brain volume loss; NEDA-3 extended by brain volumetry) during the last 12 months. The statistical model was developed using logistic regression analysis, including the independent variables: demographic, clinical, and magnetic resonance imaging (MRI) data. Dependent variables were NEDA-3 and NEDA-BVL status. Results: The mean age of the study participants ( n = 95, 62% females) was 37.85 years (standard deviation (SD) = 9.62) and the median disability score was 3.5 (2.5–4.1). Receiver operating characteristics (ROC) analysis showed that pNfL predicts NEDA-3 (the sensitivity and specificity of the model were 92% and 78%, respectively, p < 0.001) and NEDA-BVL status (the sensitivity and specificity were 80% and 65%, respectively, p < 0.001). Conclusion: The results show that pNfL levels are a useful biomarker of disease activity determined by NEDA-BVL status, including brain MRI-volumetry in patients with RRMS.

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Section: Discussionmentioning

confidence: 93%

“…4,25 Studies have shown that BVL in MS correlates with brain inflammatory activity and predicts long-term disability status. 21 Slowing brain atrophy is currently one of the important markers of effective MS therapy. The study of Sormani et al 9 pointed out the relationship between NfL and NEDA-3 as well as the NEDA-BVL concept.…”

Section: Discussionmentioning

confidence: 99%

Plasma neurofilament light chain levels are predictors of disease activity in multiple sclerosis as measured by four-domain NEDA status, including brain volume loss

et al. 2021

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“…SET was an investigator-initiated, prospective observational cohort study involving eight centers in the Czech Republic. 13,23 Enrolment started in October/2005 and was completed in July 2009.…”

Section: Methodsmentioning

confidence: 99%

Measurement of neurofilaments improves stratification of future disease activity in early multiple sclerosis

et al. 2021

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Background: The added value of neurofilament light chain levels in serum (sNfL) to the concept of no evidence of disease activity-3 (NEDA-3) has not yet been investigated in detail. Objective: To assess whether combination of sNfL with NEDA-3 status improves identification of patients at higher risk of disease activity during the following year. Methods: We analyzed 369 blood samples from 155 early relapsing-remitting MS patients on interferon beta-1a. We compared disease activity, including the rate of brain volume loss in subgroups defined by NEDA-3 status and high or low sNfL (> 90th or < 90th percentile). Results: In patients with disease activity (EDA-3), those with higher sNFL had higher odds of EDA-3 in the following year than those with low sNFL (86.5% vs 57.9%; OR = 4.25, 95% CI: [2.02, 8.95]; p = 0.0001) and greater whole brain volume loss during the following year (β = −0.36%; 95% CI = [−0.60, −0.13]; p = 0.002). Accordingly, NEDA-3 patients with high sNfL showed numerically higher disease activity (EDA-3) in the following year compared with those with low sNfL (57.1% vs 31.1%). Conclusion: sNfL improves the ability to identify patients at higher risk of future disease activity, beyond their NEDA-3 status. Measurement of sNfL may assist clinicians in decision-making by providing more sensitive prognostic information.

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“…MI reflects astrocytic density, while NfL reflects neuro-axonal injury from any mechanism. 57–59 This association perhaps reflects astrocytic involvement in neuroinflammation or in compensating for neurodegeneration. 60–63 However, this finding was not replicated in the follow-up cohort and will require further study to better elucidate the relationship between the two measures.…”

Section: Discussionmentioning

confidence: 99%

Longitudinal Evaluation of Magnetic Resonance Spectroscopy Metabolites as Biomarkers in Huntington’s Disease

Lowe

Rodrigues

Arridge

et al. 2021

Preprint

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Magnetic resonance spectroscopy (MRS) is a non-invasive method of exploring cerebral metabolism. In Huntingtons disease, altered MRS-determined concentrations of several metabolites have been described; however, findings are often discrepant and longitudinal studies of metabolite trajectory are lacking. MRS metabolites may represent a valuable source of biomarkers, thus their relationship with established biofluid and structural imaging markers of disease progression require further exploration to assess prognostic value and elucidate biochemical pathways associated with neurodegeneration. In a prospective single-site controlled cohort study with standardised collection of CSF, blood, phenotypic and imaging data, we used MRS to evaluate metabolic profiles in the putamen of 56 participants at baseline (15 healthy controls, 15 premanifest and 26 manifest gene expansion carriers) and at 2-year follow-up. Intergroup differences and associations with established measures were assessed cross-sectionally using generalized linear models and partial correlation, controlling for age and CAG repeat length. We report no significant groupwise differences in metabolite concentration but found several metabolites to be associated with measures of disease progression; however, only two relationships were replicated across both time points, with total Creatine (creatine + phosphocreatine) and myo-inositol displaying significant associations with reduced caudate volume. Although relationships were observed between MRS metabolites and biofluid measures, these were not consistent across time points. To further assess prognostic value of the metabolites, we examined whether baseline MRS values, or rate of change, predicted subsequent change in established measures of disease progression. Several associations were found but were inconsistent across known indicators of disease progression. Finally, longitudinal mixed effects models, controlling for age, revealed no significant change in metabolite concentration over time in gene expansion carriers. Altogether, our findings show some interesting cross-sectional associations between select metabolites, namely total creatine and myo-inositol, and markers of disease progression, potentially highlighting the proposed roles of neuroinflammation and metabolic dysfunction in disease pathogenesis. However, the absence of group differences, inconsistency between baseline and follow-up, and lack of clear longitudinal change over two years suggests that MRS metabolites have limited potential as biomarkers in Huntingtons disease.

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Serum neurofilament light chain reflects inflammation-driven neurodegeneration and predicts delayed brain volume loss in early stage of multiple sclerosis

Cited by 44 publications

References 34 publications

Plasma neurofilament light chain levels are predictors of disease activity in multiple sclerosis as measured by four-domain NEDA status, including brain volume loss

Plasma neurofilament light chain levels are predictors of disease activity in multiple sclerosis as measured by four-domain NEDA status, including brain volume loss

Measurement of neurofilaments improves stratification of future disease activity in early multiple sclerosis

Longitudinal Evaluation of Magnetic Resonance Spectroscopy Metabolites as Biomarkers in Huntington’s Disease

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