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

Background and purposeThe 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.MethodsMagnetic resonance imaging scans from 80 RRMS patients were classified at baseline of interferon-beta (IFN & beta;) 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 IFN & beta; response, and times to second-line therapies, secondary-progressive MS (SPMS) conversion and Expanded Disability Status Scale (EDSS) 6.0.ResultsMean (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 IFN & beta; 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 IFN & beta; treatment (p = 0.004).ConclusionsMagnetic 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.