Age-Dependent z Scores and eGFR-Adjusted Reference Ranges for Neurofilament Light: A Practical Approach for Clinical Laboratories

BACKGROUND: Neurofilament light (NfL) has emerged as a sensitive biomarker of neuroaxonal damage across a wide spectrum of neurological conditions, including acute brain injury as well as chronic inflammatory and neurodegenerative diseases. However, its clinical utility is compromised by physiological confounders, particularly age and renal function. The aim of the study was to establish age-dependent z scores for plasma NfL and evaluate the impact of estimated glomerular filtration rate (eGFR) on NfL concentrations to enhance interpretative accuracy. METHODS: Plasma NfL was measured in 133 healthy adults (18-90 years) using the Siemens Atellica® platform; serum NfL in 20 adults (25-61 years) using Lumipulse® G. eGFR was estimated with Chronic Kidney Disease Epidemiology Collaboration (<70 years) and the Berlin Initiative Study 1 (≥70 years). Age-stratified z scores, multivariate regression, and artificial intelligence-assisted modeling assessed relationships between NfL, age, and eGFR. A novel composite index, the Age- and eGFR-Adjusted NfL Index (AGI), defined as Age2/eGFR0·5, was developed and validated. RESULTS: NfL concentrations demonstrated a significant positive polynomial correlation with age (r = 0.83, P < 0.001) and a negative exponential correlation with eGFR (r = -0.78, P < 0.001). The AGI Index exhibited a linear relationship with NfL concentrations (r = 0.87, P < 0.001), which strongly predicted NfL reference values. Age-stratified z scores showed high concordance with eGFR-adjusted reference intervals (Pearson r = 0.96, P < 0.001). A strong correlation (r = 0.94) was observed between the predicted and released laboratory-specific serum NfL reference ranges. CONCLUSIONS: This study provides the first age-dependent NfL z scores for the Siemens Atellica platform. The proposed AGI index enables individualized reference intervals, supporting broader clinical application while accounting for key physiological confounders.