Autism spectrum disorder (ASD) is one of the most common neurodevelopment disorders, characterized by a multifactorial etiology based on the interaction of genetic and environmental factors. Recent evidence supports the neurobiological hypothesis based on neuroinflammation theory. To date, there are no sufficiently validated diagnostic and prognostic biomarkers for ASD. Therefore, we decided to investigate the potential diagnostic role for ASD of two biomarkers well known for other neurological inflammatory conditions: the glial fibrillary acidic protein (GFAP) and the neurofilament (Nfl). Nfl and GFAP serum levels were analyzed using SiMoA technology in a group of ASD patients and in a healthy control group (CTRS), age- and gender-matched. Then we investigated the distribution, frequency, and correlation between serum Nfl and GFAP levels and clinical data among the ASD group. The comparison of Nfl and GFAP serum levels between ASD children and the control group showed a mean value of these two markers significantly higher in the ASD group (sNfL mean value ASD pt 6.86 pg/mL median value ASD pt 5.7 pg/mL; mean value CTRS 3.55 pg/mL; median value CTRS 3.1 pg; GFAP mean value ASD pt 205.7 pg/mL median value ASD pt 155.4 pg/mL; mean value CTRS 77.12 pg/mL; median value CTRS 63.94 pg/mL). Interestingly, we also found a statistically significant positive correlation between GFAP levels and hyperactivity symptoms (p-value <0.001). Further investigations using larger groups are necessary to confirm our data and to verify in more depth the potential correlation between these biomarkers and ASD clinical features, such as the severity of the core symptoms, the presence of associated symptoms, and/or the evaluation of a therapeutic intervention. However, these data not only might shed a light on the neurobiology of ASD, supporting the neuroinflammation and neurodegeneration hypothesis, but they also might support the use of these biomarkers in the early diagnosis of ASD, to longitudinally monitor the disease activity, and even more as future prognostic biomarkers.

Although cladribine induces sustained reductions in peripheral T and B lymphocytes, little is known about its effect on axonal damage reduction in multiple sclerosis (MS), which could be demonstrated by assessing the serum neurofilament light chain (sNfL) levels. We investigated the reduction/reconstitution of different lymphocyte subsets (LS) by verifying the correlation with no evidence of disease activity (NEDA) and the variation in sNfL levels during cladribine treatment. We analysed 33 highly active relapsing MS patients and followed them up for 12 ± 3.3 months; blood samples were collected at treatment start (W0) and after 8, 24 and 48 weeks. Seventeen patients (60.7%) showed NEDA during the first treatment. At week 8, we observed a significant decrease in B memory cells, B regulatory 1 CD19+/CD38+ and B regulatory 2 CD19+/CD25+, a significant increase in T regulatory CD4+/CD25+, a slight increase in T cytotoxic CD3+/CD8+ and a non-significant decrease in T helper CD3+/CD4+. Starting from week 24, the B subsets recovered; however, at week 48, CD19+/CD38+ and CD19+/CD25+ reached values near the baseline, while the Bmem were significantly lower. The T cell subsets remained unchanged except for CD4+/CD25+, which increased compared to W0. The LS changes were not predictive of NEDA achievement. The sNfL levels were significantly lower at week 24 (p = 0.046) vs. baseline. These results could demonstrate how cladribine, by inflammatory activity depletion, can also reduce axonal damage, according to the sNfL levels.

Background: Cladribine (2-CdA) can cross the blood–brain barrier, resulting in inhibition of DNA synthesis and repair and disruption of cellular proliferation in actively dividing lymphocytes. No data on effect on neurons are available. Aim: To study “in vitro” 2-CdA apoptotic effects on neurons in healthy donor and multiple sclerosis patient lymphocytes. Methods: Neuroblastoma cells were co-cultured with lymphocytes, with and without 2-CdA. Results: Apoptosis increased in lymphocytes with 2-CdA; increase was also observed when lymphocytes were cultured with neuronal cells. However, neurons were not affected by 2-CdA for apoptosis. Conclusions: 2-CdA causes peripheral and central lymphocyte death preserving neurons, with a reasonable impact on inflammation and neuroprotection.

Myelin oligodendrocyte glycoprotein antibody–associated disease (MOGAD) is an inflammatory demyelinating disorder of the central nervous system characterised by heterogeneous clinical and radiological presentations. Accurate interpretation of serum anti–myelin oligodendrocyte glycoprotein (anti-MOG) antibody titres is critical to improve diagnostic precision and prognostic assessment. This single-centre retrospective study evaluated 19 patients diagnosed with MOGAD in 2023, all of whom were seropositive for anti-MOG IgG, as confirmed by live cell-based assays (CBAs) using full-length human MOG and IgG1-specific secondary antibodies. Antibody quantification combined a ratiometric semi-quantitative fluorescence index with classical endpoint dilution titres, enabling classification into low, medium, and high titre groups. Stratification revealed titre-dependent phenotypic heterogeneity: high-titre patients were older at onset and predominantly presented with optic neuritis, often bilateral, and encephalic involvement, whereas low-titre patients more frequently exhibited spinal cord syndromes, cerebellar or brainstem symptoms, and a higher prevalence of cerebrospinal fluid-restricted oligoclonal bands. Semi-quantitative fluorescence ratios correlated consistently with endpoint titres, and exponential decay analysis demonstrated slower signal loss in high-titre sera, confirming assay reliability. No significant association emerged between titre level and monophasic versus relapsing disease course. Anti-MOG antibody titres could serve not only as a diagnostic biomarker but also to capture clinically relevant immunopathological diversity, supporting a titre-stratified approach to diagnosis and early prognostication. Incorporating semi-quantitative metrics alongside clinical and imaging features may refine the diagnostic algorithm and prevent misclassification of atypical presentations.