Plasma NfL and GFAP as Candidate Biomarkers of Disease Activity in NMOSD and MOGAD

Background and Objectives: Neuromyelitis optica spectrum disorder (NMOSD) and MOG antibody-associated disease (MOGAD) are distinct autoimmune demyelinating disorders of the central nervous system, characterized by different pathological and clinical features. Reliable biomarkers are essential for accurate diagnosis and monitoring of disease activity. Glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) are promising candidates, reflecting astrocytic and axonal damage, respectively. Materials and Methods: To investigate the relationship between astroglial (GFAP) and neuronal (NfL) protein levels in the peripheral blood, 89 plasma samples were analyzed using Simoa immunoassays. The concentrations of pNfL and pGFAP were measured in three groups: AQP4-IgG-positive NMOSD patients (n = 18), MOGAD patients (n = 12), and healthy controls (HCs, n = 19). Statistical analyses assessed group differences, correlations, and the predictive value of biomarkers for disease activity. Results: Both NMOSD and MOGAD patients exhibited elevated pNfL compared with controls, indicating neuroaxonal injury. No significant differences in pNfL, pGFAP, or pGFAP/pNfL ratios were observed between patient groups. The pGFAP levels and the pGFAP/pNfL ratio were significantly higher in NMOSD patients, particularly during attacks, indicating prominent astrocyte damage. Correlations revealed associations between biomarker levels, disability, and disease duration. pNfL demonstrated high accuracy in predicting recent relapses (AUC = 0.906), whereas pGFAP showed moderate predictive capacity (AUC = 0.638). Elevated pNfL and pGFAP levels were associated with an increased likelihood of relapse within six months. Conclusions: Plasma NfL and GFAP are promising biomarkers for assessing tissue injury and disease activity in NMOSD and MOGAD. NfL predicts relapses, while GFAP primarily reflects astrocytic damage in NMOSD. Longitudinal studies are warranted to validate these biomarkers and establish clinical thresholds for disease management.