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Multiplex Panel Detects Glial and Inflammatory Biomarker Signatures in Sporadic and C9orf72-ALS

Jul 2026 · Neurology(R) neuroimmunology & neuroinflammation · Vol 13 · 0 citations · 36 references
Medicine

Abstract

Background and Objectives CSF proteomics has emerged as a valuable strategy for identifying diagnostic and prognostic biomarkers in amyotrophic lateral sclerosis (ALS). However, the limited availability and volumes of CSF samples restrict the broader clinical application of CSF-based biomarker panels. To address this challenge, we investigated whether the novel nucleic acid-linked immuno-sandwich assay (NULISA) multiplex platform—capable of quantifying multiple neural, glial, and inflammatory markers from minimal biofluid volumes—could validate previously proposed biomarkers and identify additional candidates relevant to ALS. Methods Using this platform, we measured a targeted panel of 131 biomarkers in cohorts of patients with C9orf72-associated ALS, sporadic ALS (sALS), and matched healthy controls. Results The 6 markers neurofilament heavy chain (NEFH) and neurofilament light chain (NEFL), chitinases—particularly chitotriosidase-1 (CHIT1) and chitinase-3-like protein-1 (CHI3L1), and chemokines CCL2 and CCL3 were significantly elevated in both ALS groups compared with controls. These biomarkers correlated with disease progression and demonstrated strong diagnostic performance when combined into aggregate scores, as reflected by a high area under the receiver operating characteristic curve for ALS. Notably, C9orf72-ALS patients exhibited higher levels of the oxidative stress-related markers PRDX6 and ENO2, compared with sALS patients, suggesting a genotype-specific molecular signature. Discussion Overall, our findings support the use of a multiplexed panel of diverse, inflammatory, glial, and neurodegeneration-associated biomarkers as a complementary diagnostic and prognostic tool alongside established measurements of neurofilaments. This approach may enhance biomarker robustness while minimizing CSF volume requirements, thereby improving clinical feasibility in ALS research and care.

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