Association of magnetic resonance imaging phenotypes and serum biomarker levels with treatment response and long-term disease outcomes in multiple sclerosis patients

Abstract

Background and purpose: The aim was to evaluate whether magnetic resonance imaging (MRI) phenotypes defined by inflammation and neurodegeneration markers correlate with serum levels of neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) in relapsing-remitting multiple sclerosis (RRMS) patients; and to explore the role of radiological phenotypes and biomarker levels on treatment response and long-term prognostic outcomes.

Methods: Magnetic resonance imaging scans from 80 RRMS patients were classified at baseline of interferon-beta (IFNβ) treatment into radiological phenotypes defined by high and low inflammation and high and low neurodegeneration, based on the number of contrast-enhancing lesions, brain parenchymal fraction and the relative volume of non-enhancing black holes on T1-weighted images. Serum levels of NfL and GFAP were measured at baseline with single molecule array (Simoa) assays. MRI phenotypes and serum biomarker levels were investigated for their association with IFNβ response, and times to second-line therapies, secondary-progressive MS (SPMS) conversion and Expanded Disability Status Scale (EDSS) 6.0.

Results: Mean (SD) follow-up was 17 (2.9) years. Serum NfL levels and GFAP were higher in the high inflammation (p = 0.04) and high neurodegeneration phenotypes (p = 0.03), respectively. The high inflammation phenotype was associated with poor response to IFNβ treatment (p = 0.04) and with shorter time to second-line therapies (p = 0.04). In contrast, the high neurodegeneration phenotype was associated with shorter time to SPMS (p = 0.006) and a trend towards shorter time to EDSS 6.0 (p = 0.09). High serum NfL levels were associated with poor response to IFNβ treatment (p = 0.004).

Conclusions: Magnetic resonance imaging phenotypes defined by inflammation and neurodegeneration correlate with serum biomarker levels, and both have prognostic implications in treatment response and long-term disease outcomes.

Keywords: long-term prognosis; magnetic resonance imaging; multiple sclerosis; neurofilament light chain; treatment response.

FIGURE 1

Association between radiological phenotypes and serum biomarker levels. Box plots showing the distribution of serum NfL levels (a) and GFAP levels (b) in MS patients with high and low inflammation, and with high and low neurodegeneration.

FIGURE 2

Time to evidence of disease activity at year 5 of IFNβ treatment. Kaplan–Meier curves showing the survival of patients with RRMS for the event evidence of disease activity in the first 5 years on IFN treatment for high and low inflammation phenotypes (a) and high and low neurodegeneration phenotypes (b). The blue and red lines correspond to survival probability for the low and high inflammation phenotypes, respectively. Shaded areas correspond to the 95% confidence interval for each curve, and overlap between confidence intervals is represented in gray. Discontinued lines indicate median times to the event for each group.

FIGURE 3

Comparison of serum biomarker levels between two extreme groups of therapeutic outcome. Box plots showing the distribution of serum NfL levels (a) and GFAP levels (b) in MS patient responders to IFNβ versus non‐responders to a third disease‐modifying treatment (DMT).

FIGURE 4

Radiological phenotypes and time to second‐line therapies. Kaplan–Meier curves showing the survival of MS patients for the event initiation of a second‐line therapy for high and low inflammation phenotypes (a) and high and low neurodegeneration phenotypes (c). The blue and red lines correspond to survival probability for the low and high inflammation phenotypes, respectively. Shaded areas correspond to the 95% confidence interval for each curve, and overlap between confidence intervals is represented in gray. Discontinued lines indicate median times to the event for each group. Proportion of patients from high and low inflammation phenotypes (b) and high and low neurodegeneration phenotypes (d) on second‐line therapies at the last follow‐up visit. “No” and “Yes” indicate patients not receiving second‐line therapies and treated with second‐line therapies, respectively.

FIGURE 5

Radiological phenotypes and time to SPMS. Kaplan–Meier curves showing the survival of MS patients for the event development of SPMS for high and low inflammation phenotypes (a) and high and low neurodegeneration phenotypes (c). The blue and red lines correspond to survival probability for the low and high inflammation phenotypes, respectively. Shaded areas correspond to the 95% confidence interval for each curve, and overlap between confidence intervals is represented in gray. Proportion of patients from high and low inflammation phenotypes (b) and high and low neurodegeneration phenotypes (d) with SPMS at the end of the study. “No” and “Yes” indicate patients not developing SPMS and patients with SPMS, respectively.

FIGURE 6

Radiological phenotypes and time to EDSS 6.0. Kaplan–Meier curves showing the survival of MS patients for the event reaching EDSS 6.0 for high and low inflammation phenotypes (a) and high and low neurodegeneration phenotypes (c). The blue and red lines correspond to survival probability for the low and high inflammation phenotypes, respectively. Shaded areas correspond to the 95% confidence interval for each curve, and overlap between confidence intervals is represented in gray. Proportion of patients from high and low inflammation phenotypes (b) and high and low neurodegeneration phenotypes (d) with EDSS 6.0 at the end of the study. “No” and “Yes” indicate patients who do not reach a EDSS 6.0 and patients who do, respectively.