Real-world applicability of glial fibrillary acidic protein and neurofilament light chain in Alzheimer’s disease - Parvizi, Tandis; König, Theresa; Wurm, Raphael; Silvaieh, Sara; Altmann, Patrick; Klotz, Sigrid; Rommer, Paulus Stefan; Furtner, Julia; Regelsberger, Günther; Lehrner, Johann; Traub-Weidinger, Tatjana; Gelpi, Ellen; et al. (Frontiers in Aging Neuroscience, 2022)
Background: Blood-based biomarkers may add a great benefit in detecting the earliest neuropathological changes in patients with Alzheimer’s disease (AD). We examined the utility of neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) regarding clinical diagnosis and differentiation between amyloid positive and negative patients. To evaluate the practical application of these biomarkers in a routine clinical setting, we conducted this study in a heterogeneous memory-clinic population. Methods: We included 167 patients in this retrospective cross-sectional study, 123 patients with an objective cognitive decline [mild cognitive impairment (MCI) due to AD, n = 63, and AD-dementia, n = 60] and 44 age-matched healthy controls (HC). Cerebrospinal fluid (CSF) and plasma concentrations of NfL and GFAP were measured with single molecule array (SIMOA®) technology using the Neurology 2-Plex B kit from Quanterix. To assess the discriminatory potential of different biomarkers, age- and sex-adjusted receiver operating characteristic (ROC) curves were calculated and the area under the curve (AUC) of each model was compared. Results: We constructed a panel combining plasma NfL and GFAP with known AD risk factors (Combination panel: age+sex+APOE4+GFAP+NfL). With an AUC of 91.6% (95%CI = 0.85–0.98) for HC vs. AD and 81.7% (95%CI = 0.73–0.90) for HC vs. MCI as well as an AUC of 87.5% (95%CI = 0.73–0.96) in terms of predicting amyloid positivity, this panel showed a promising discriminatory power to differentiate these populations. Conclusion: The combination of plasma GFAP and NfL with well-established risk factors discerns amyloid positive from negative patients and could potentially be applied to identify patients who would benefit from a more invasive assessment of amyloid pathology. In the future, improved prediction of amyloid positivity with a noninvasive test may decrease the number and costs of a more invasive or expensive diagnostic approach.