Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disorder that currently lacks validated molecular biomarkers for early diagnosis and prognosis, severely delaying personalized care. Interleukin 18 (IL-18), a proinflammatory cytokine linked to NLRP-3 inflammasome activation, has emerged as a promising biomarker for ALS. However, traditional colorimetric Enzyme-Linked Immunosorbent Assays (ELISAs) lack the sensitivity to distinguish IL-18 levels between Fast- and Slow-progressing ALS patients. To overcome this, we developed a highly sensitive electrochemical ELISA (e-ELISA) test by systematically optimizing key parameters, including the capture antibody immobilization strategy, the electrochemical mediator, and reagent concentrations. We then applied the optimized e-ELISA protocol to quantify IL-18 in 3D innervated skin models constructed using 3D-printed methacrylated hyaluronic acid (MeHA) and electrospun polylactic acid (PLLA) fibers, and colonized with patient-derived fibroblasts and neuronal cells. Reaching a limit of detection of 1.77 pg✕mL-1, the e-ELISA not only differentiated ALS models from the healthy control but, most critically, distinguished between a Fast- and a Slow-progressing ALS models based on significantly different IL-18 concentrations. By discriminating IL-18 levels in biologically representative models, this work validates the developed high-performance e-ELISA for personalized clinical use, providing a foundation for the design of portable diagnostic devices.
Keywords: 3D skin model; Amyotrophic lateral sclerosis (ALS); Electrochemical Enzyme-Linked Immunosorbent Assays (e-ELISA); Interleukin 18 (IL-18).
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