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Troponin T and Neurofilament Light Chain Levels as Complementary Biomarkers of Disease Accumulation and Aggressiveness in Amyotrophic Lateral Sclerosis

Jul 2026 · Annals of Clinical and Translational Neurology · 0 citations · 30 references
Medicine

Abstract

ABSTRACT Objective Amyotrophic lateral sclerosis (ALS) is a clinically heterogeneous neurodegenerative disease requiring reliable biomarkers to improve patient stratification and trial design. While serum neurofilament light chain (sNfL) reflects neuroaxonal stress and disease aggressiveness, troponin T (TnT) may capture complementary aspects of neuromuscular involvement. We assessed the associations of TnT and sNfL with D50‐derived measures of disease aggressiveness (D50) and disease accumulation (rD50) in ALS. Methods In this retrospective observation, TnT and sNfL levels from ALS patients in two independent German cohorts were analyzed using the D50 disease progression model; discovery cohort (Essen, n = 433) and an independent replication cohort (Bonn, n = 185). Results TnT levels were strongly associated with rD50‐defined disease phases in the discovery cohort (p < 0.001). While not all subgroup‐specific associations were replicated, the overall relationship between TnT and disease accumulation was supported in the independent replication cohort. In contrast, sNfL showed no consistent relationship with rD50‐derived disease phases. sNfL concentrations demonstrated a significant inverse association with D50, supporting a relationship with disease aggressiveness across both cohorts (p < 0.001). Associations between TnT levels and D50‐defined disease aggressiveness were generally weaker and less consistent. Interpretation TnT was associated with measures of disease accumulation (rD50), whereas sNfL was more closely associated with disease aggressiveness (D50). Our results suggest that TnT and sNfL capture different dimensions of disease status within the D50 framework. Further longitudinal studies are needed to determine whether combining these biomarkers improves disease stratification or prognostic assessment in clinical practice and therapeutic trials.

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