AUTHOR=Tortosa-Carreres Jordi , Cubas-Núñez Laura , Castillo-Villalba Jéssica , Forés-Toribio Lorena , Gasque-Rubio Raquel , Quintanilla-Bordas Carlos , Alcalà-Vicente Carmen , Carratalà-Boscà Sara , Vaño-Bellver Ana , Laiz-Marro Begoña , Pérez-Miralles Francisco Carlos , Casanova Bonaventura 

TITLE=Cross-platform analytical assessment of serum GFAP quantification in multiple sclerosis: SIMOA versus two automated immunoassays

JOURNAL=Frontiers in Neurology

VOLUME=Volume 16 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2025.1682198

DOI=10.3389/fneur.2025.1682198

ISSN=1664-2295

ABSTRACT=IntroductionSerum glial fibrillary acidic protein (sGFAP) is a promising biomarker, but its quantification mainly relies on SIMOA, a technology not widely available in clinical practice.ObjectivesTo evaluate the analytical performance of two high-throughput automated platforms—Alinity® i (Abbott) and Lumipulse® G1200 (Fujirebio)—for sGFAP quantification.MethodsA retrospective longitudinal study included 107 serum samples from 23 MS patients. sGFAP was measured with SIMOA SR-X®, Lumipulse® G1200, and Alinity® i. Data were log-transformed. Agreement was assessed using Pearson correlations, Passing–Bablok regression, Bland–Altman analysis, and Δlog correlations between visits. Longitudinal differences across platforms were tested with a linear mixed-effects model (platform as fixed effect, SIMOA as reference). Moreover, ΔSIMOA was modeled against ΔLumipulse and ΔAlinity, adjusting for ΔEDSS, phenotype, relapses and new MRI lesions.ResultsPassing–Bablok regression yielded slopes of 0.85 (SIMOA–Lumipulse), 0.81 (SIMOA–Alinity), and 0.95 (Lumipulse–Alinity), with intercepts of −0.32, −0.35, and −0.05. Mean log-biases were −0.622, −0.733, and 0.109. Correlations between log-means and log-differences were r = 0.26 (p = 0.006), 0.44 (p < 0.0001), and 0.15 (p = 0.13). The mixed-effects model showed no significant Δlog differences relative to SIMOA (p > 0.1). When modeling ΔSIMOA, ΔLumipulse was a significant predictor (β = 0.51; p = 0.002), whereas ΔAlinity showed only a trend (β = 0.31; p = 0.051). No clinical covariates were significantly associated.ConclusionAutomated platforms, particularly Lumipulse, showed strong concordance with SIMOA supporting the role in analytical monitoring.