Aug 2026· Diagnostics· Vol 16· 0 citations· 32 references
Medicine
TL;DR
SERPINA3 is therefore an exploratory adjunctive serum biomarker candidate rather than a stand-alone diagnostic test; prospective external validation in clinically representative cohorts is required.
Abstract
Background: Diagnostic evaluation of suspected neuromyelitis optica spectrum disorder (NMOSD) integrates AQP4-IgG testing, clinical assessment, neuroimaging, and exclusion of alternative inflammatory demyelinating disorders; nevertheless, some patients remain diagnostically unresolved or may be misclassified as multiple sclerosis (MS) or other disorders. Methods: This single-center retrospective exploratory study analyzed quantitative serum proteomics from 20 patients with MS and 20 with NMOSD. Proteins meeting nominal p < 0.05 together with prespecified fold-change criteria were considered exploratory candidates. VWF, PPBP, and SERPINA3 were subsequently assessed by ELISA in a separate, non-overlapping cohort from the same center, together with routine hematological variables. Results: Among 261 protein entries, 34 met the exploratory nominal threshold and fold-change criteria, but none remained significant after Benjamini–Hochberg correction (lowest q = 0.0734). VWF and PPBP showed no significant differences across the four validation groups. SERPINA3 differed across groups (Kruskal–Wallis H = 44.982, p = 9.34 × 10−10) and was higher in NMOSD than in MS, TBI, and HCs after Holm adjustment (adjusted p = 0.036, 1.49 × 10−9, and 1.13 × 10−5, respectively). In the full ELISA cohort, the AUC was 0.928 for NMOSD versus HC and 0.800 for NMOSD versus MS. In a post hoc sensitivity analysis excluding participants with preceding infection, the NMOSD–MS separation was attenuated. In smaller complete-case analyses, adding an additional laboratory variable to SERPINA3 did not significantly improve apparent discrimination. Conclusions: SERPINA3 is therefore an exploratory adjunctive serum biomarker candidate rather than a stand-alone diagnostic test; prospective external validation in clinically representative cohorts is required.
Systemic autoimmune overlap was present in approximately one in five patients and the overlap group showed more frequent systemic autoantibody positivity and a predominance of optic neuritis at onset, but disability measures, treatment patterns, and most clinical outcomes were similar between groups.
Yazmin Martinez-Lopez, Alexis García-Sarreón, E. Tetlalmatzi-Azuara et al.· Multiple Sclerosis and Relat...· 1 citation
The roles of several CSF metabolites in NMOSD are elucidated, with specific glycerophosphocholine species showing risk associations in AQP4-IgG positive and AQP4-IgG negative subtypes, while ascorbate and N-acetylhexosamines demonstrate protective effects across both subtypes, thereby providing valuable insights.
Li Deng, Shiguang Ling, Lin-Ze Li et al.· Medicine· 0 citations
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.
Karthik Baskar, Christina Steffke, S. Bernsen et al.· Neurology(R) neuroimmunology...· 0 citations
Investigating risk factors for disease severity in acute aquaporin-4 -IgG-seropositive neuromyelitis optica spectrum disorders patients revealed significant differences in white blood cell count, neutrophil count, neutrophil-to-lymphocyte ratio, and serum complement levels among patients in the acute phase, those in the remission phase, and HCs.
Yibo Zhan, Min Zhao, Jiahui Zhang et al.· Frontiers in Immunology· 0 citations
DN-NMOSD is a heterogenous, severe and highly relapsing disease, where attacks lead to irreversible dysfunction, and the administration of maintenance immunotherapy reduces the relapse risk and should be considered early to prevent further disability.
A. Malvaso, F. Bovis, Giacomo Greco et al.· Neurology(R) neuroimmunology...· 0 citations
Abstract Objectives Serum neurofilament light chain (sNfL) reflects neuroaxonal injury in relapsing-remitting multiple sclerosis (RRMS), but its clinical utility is limited by high interindividual variability and confounders such as renal function. Population-based thresholds may therefore be suboptimal for longitudinal monitoring. The reference change value (RCV), an intraindividual approach based on biological variation, remains insufficiently validated in real-world settings. Methods In this retrospective cohort study, 967 sNfL determinations from 295 RRMS patients were analyzed (LUMIPULSE G600II). Measurements were matched to clinical relapse and MRI activity within ±90 days. Associations with log-sNfL were assessed using linear mixed-effects models. RCV and population-based threshold (PBT) were compared as factors associated with inflammatory activity using cluster-robust logistic regression and ROC analysis. Correlation with new MRI lesion count was also evaluated. Results The intraclass correlation coefficient was 0.536. RCV elevation showed a highly significant association with active MRI (OR 4.93, 95 % CI 2.49–9.77) and clinical relapse (OR 6.48, 95 % CI 2.75–15.25), whereas PBT elevation did not reach statistical significance for either outcome (active MRI: OR 1.52, p=0.290; clinical relapse: OR 2.38, p=0.073). Clinical relapse and MRI activity were independently associated with mean sNfL increases of +72.1 % (95 % CI +53.7 %, +92.7 %) and +24.5 % (95 % CI +13.7 %, +36.3 %), respectively. Renal impairment was a major confounder, with sNfL elevations of +16.0 % in eGFR G2 and +67.8 % in G3–G5. Negative predictive values exceeded 91 % across all markers and outcomes. sNfL correlated with new MRI lesion count (Spearman ρ=0.498, p<0.0001), with a Youden-optimal threshold of ≥4 lesions. Conclusions sNfL measured on the LUMIPULSE platform is a valid real-world biomarker of inflammatory activity in RRMS. Its high interindividual variability makes RCV-based intraindividual interpretation substantially more informative than population-based thresholding for longitudinal monitoring. The consistently high negative predictive value supports its use as a rule-out tool for active neuroinflammation and provides a rational basis for risk-adapted MRI surveillance in clinically stable patients.
Silvia de las Heras Flórez, Gema García de la Rosa, V. Martín García et al.· Clinical Chemistry and Labor...· 0 citations
Related blog posts
MIT News · Artificial Intelligence· news.mit.eduAug 27, 2026
A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.
