Neurofilament Light Chain as a Discriminator of Disease Activity Status in MOG Antibody-Associated Disease.

Abstract

Background and objectives: In patients with myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease (MOGAD), acute disease activity is generally identified through medical history, neurologic examination, and imaging. However, these may be insufficient for detecting disease activity in specific conditions. This study aimed to investigate the dynamics of serum neurofilament light chain (sNfL) and serum glial fibrillary acidic protein (sGFAP) after clinical attacks and to assess their utility in discriminating attacks from remission in patients with MOGAD.

Methods: We conducted a multicenter, retrospective, longitudinal study including 239 sera from 62 MOGAD patients assessed from 1995 to 2023 in a discovery and validation setup. Sera were measured for sNfL and sGFAP with a single-molecule array assay and for MOG-IgG with a live cell-based assay. sNfL and sGFAP Z scores and percentiles adjusted for age, body mass index, and sex (sGFAP) were calculated from a healthy control normative database. Mixed-effects regression models were used to characterize biomarkers' dynamics and to investigate associations between serum biomarkers, clinical variables, and disease activity status.

Results: Among the 62 study participants, 29 (46.8%) were female, with a median age at baseline of 40.0 years (interquartile range [IQR] 29.5-49.8) and a median duration of follow-up of 20.0 months (IQR 3.0-62.8). sNfL and sGFAP Z scores were nonlinearly associated with time from attack onset (p < 0.001 and = 0.002, respectively). During attacks, both biomarkers presented higher median values (sNfL Z score 2.9 [IQR 1.4-3.5], 99.8th; sGFAP Z score 0.4 [IQR -0.5 to 1.5], 65.5th) compared with remission (sNfL Z score 0.9 [IQR -0.1 to 1.6], 81.6th, p < 0.001; sGFAP Z score -0.2 [IQR -0.8 to 0.5], 42.1th; p < 0.001) across all clinical phenotypes. sNfL values consistently discriminated disease activity status in the discovery and validation cohorts, showing a 3.5-fold increase in the odds of attacks per Z score unit (odds ratio 3.5, 95% confidence interval 2.3-5.1; p < 0.001). Logistic models incorporating sNfL Z scores demonstrated favorable performance in discriminating disease activity status across both cohorts.

Discussion: sNfL Z scores may serve as a biomarker for monitoring disease activity in MOGAD.