CD138 as a Specific CSF Biomarker of Multiple Sclerosis.

BACKGROUND AND OBJECTIVES: The aim of this study was to identify novel biomarkers for multiple sclerosis (MS) diagnosis and prognosis, addressing the critical need for specific and prognostically valuable markers in the field. METHODS: We conducted an extensive proteomic investigation, combining analysis of (1) CSF proteome from symptomatic controls, fast and slow converters after clinically isolated syndromes, and patients with relapsing-remitting MS (n = 10 per group) using label-free quantitative proteomics and (2) oligodendrocyte secretome changes under proinflammatory or proapoptotic conditions using stable isotope labeling by amino acids in cell culture. Proteins exhibiting differential abundance in both proteomic analyses were combined with other putative MS biomarkers, yielding a comprehensive list of 87 proteins that underwent quantification through parallel reaction monitoring (PRM) in a novel cohort, comprising symptomatic controls, inflammatory neurologic disease controls, and patients with MS at various disease stages (n = 10 per group). The 11 proteins that passed this qualification step were subjected to a new PRM assay within an expanded cohort comprising 158 patients with either MS at different disease stages or other inflammatory or noninflammatory neurologic disease controls. RESULTS: This study unveiled a promising biomarker signature for MS, including previously established candidates, such as chitinase 3-like protein 1, chitinase 3-like protein 2, chitotriosidase, immunoglobulin kappa chain region C, neutrophil gelatinase-associated lipocalin, and CD27. In addition, we identified novel markers, namely cat eye syndrome critical region protein 1 (adenosine deaminase 2, a therapeutic target in multiple sclerosis) and syndecan-1, a proteoglycan, also known as plasma cell surface marker CD138 and acting as chitinase 3-like protein 1 receptor implicated in inflammation and cancer signaling. CD138 exhibited good diagnostic accuracy in distinguishing MS from inflammatory neurologic disorders (area under the curve [AUC] = 0.85, CI 0.75-0.95). CD138 immunostaining was also observed in the brains of patients with MS and cultured oligodendrocyte precursor cells but was absent in astrocytes. DISCUSSION: These findings identify CD138 as a specific CSF biomarker for MS and suggest the selective activation of the chitinase 3-like protein 1/CD138 pathway within the oligodendrocyte lineage in MS. They offer promising prospects for improving MS diagnosis and prognosis by providing much-needed specificity and clinical utility. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that CD138 distinguishes multiple sclerosis from other inflammatory neurologic disorders with an AUC of 0.85 (95% CI 0.75-0.95).

Kappa Free Light Chain Biomarkers Are Efficient for the Diagnosis of Multiple Sclerosis: A Large Multicenter Cohort Study.

BACKGROUND AND OBJECTIVES: Kappa free light chains (KFLC) seem to efficiently diagnose MS. However, extensive cohort studies are lacking to establish consensus cut-offs, notably to rule out non-MS autoimmune CNS disorders. Our objectives were to (1) determine diagnostic performances of CSF KFLC, KFLC index, and KFLC intrathecal fraction (IF) threshold values that allow us to separate MS from different CNS disorder control populations and compare them with oligoclonal bands' (OCB) performances and (2) to identify independent factors associated with KFLC quantification in MS. METHODS: We conducted a retrospective multicenter study involving 13 French MS centers. Patients were included if they had a noninfectious and nontumoral CNS disorder, eligible data concerning CSF and serum KFLC, albumin, and OCB. Patients were classified into 4 groups according to their diagnosis: MS, clinically isolated syndrome (CIS), other inflammatory CNS disorders (OIND), and noninflammatory CNS disorder controls (NINDC). RESULTS: One thousand six hundred twenty-one patients were analyzed (675 MS, 90 CIS, 297 OIND, and 559 NINDC). KFLC index and KFLC IF had similar performances in diagnosing MS from nonselected controls and OIND (p = 0.123 and p = 0.991 for area under the curve [AUC] comparisons) and performed better than CSF KFLC (p < 0.001 for all AUC comparisons). A KFLC index of 8.92 best separated MS/CIS from the entire nonselected control population, with better performances than OCB (p < 0.001 for AUC comparison). A KFLC index of 11.56 best separated MS from OIND, with similar performances than OCB (p = 0.065). In the multivariate analysis model, female gender (p = 0.003), young age (p = 0.013), and evidence of disease activity (p < 0.001) were independent factors associated with high KFLC index values in patients with MS, whereas MS phenotype, immune-modifying treatment use at sampling, and the FLC analyzer type did not influence KFLC index. DISCUSSION: KFLC biomarkers are efficient tools to separate patients with MS from controls, even when compared with other patients with CNS autoimmune disorder. Given these results, we suggest using KFLC index or KFLC IF as a criterion to diagnose MS. CLASSIFICATION OF EVIDENCE: This study provides Class III evidence that KFLC index or IF can be used to differentiate patients with MS from nonselected controls and from patients with other autoimmune CNS disorders.

Neurofilament Light Chain Levels Are Predictive of Clinical Conversion in Radiologically Isolated Syndrome.

BACKGROUND AND OBJECTIVES: To evaluate the predictive value of serum neurofilament light chain (sNfL) and CSF NfL (cNfL) in patients with radiologically isolated syndrome (RIS) for evidence of disease activity (EDA) and clinical conversion (CC). METHODS: sNfL and cNfL were measured at RIS diagnosis by single-molecule array (Simoa). The risk of EDA and CC according to sNfL and cNfL was evaluated using the Kaplan-Meier analysis and multivariate Cox regression models including age, spinal cord (SC) or infratentorial lesions, oligoclonal bands, CSF chitinase 3-like protein 1, and CSF white blood cells. RESULTS: Sixty-one patients with RIS were included. At diagnosis, sNfL and cNfL were correlated (Spearman r = 0.78, p < 0.001). During follow-up, 47 patients with RIS showed EDA and 36 patients showed CC (median time 12.6 months, 1-86). When compared with low levels, medium and high cNfL (>260 pg/mL) and sNfL (>5.0 pg/mL) levels were predictive of EDA (log rank, p < 0.01 and p = 0.02, respectively). Medium-high cNfL levels were predictive of CC (log rank, p < 0.01). In Cox regression models, cNfL and sNfL were independent factors of EDA, while SC lesions, cNfL, and sNfL were independent factors of CC. DISCUSSION: cNfL >260 pg/mL and sNfL >5.0 pg/mL at diagnosis are independent predictive factors of EDA and CC in RIS. Although cNfL predicts disease activity better, sNfL is more accessible than cNfL and can be considered when a lumbar puncture is not performed. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that in people with radiologic isolated syndrome (RIS), initial serum and CSF NfL levels are associated with subsequent evidence of disease activity or clinical conversion.

Full spectrum of vitamin D immunomodulation in multiple sclerosis: mechanisms and therapeutic implications.

Vitamin D deficiency has been associated with the risk of multiple sclerosis, disease activity and progression. Results from in vitro experiments, animal models and analysis of human samples from randomized controlled trials provide comprehensive data illustrating the pleiotropic actions of Vitamin D on the immune system. They globally result in immunomodulation by decreasing differentiation of effector T and B cells while promoting regulatory subsets. Vitamin D also modulates innate immune cells such as macrophages, monocytes and dendritic cells, and acts at the level of the blood-brain barrier reducing immune cell trafficking. Vitamin D exerts additional activity within the central nervous system reducing microglial and astrocytic activation. The immunomodulatory role of Vitamin D detected in animal models of multiple sclerosis has suggested its potential therapeutic use for treating multiple sclerosis. In this review, we focus on recent published data describing the biological effects of Vitamin D in animal models of multiple sclerosis on immune cells, blood-brain barrier function, activation of glial cells and its potential neuroprotective effects. Based on the current knowledge, we also discuss optimization of therapeutic interventions with Vitamin D in patients with multiple sclerosis, as well as new technologies allowing in-depth analysis of immune cell regulations by vitamin D.

Biological Markers in Early Multiple Sclerosis: the Paved Way for Radiologically Isolated Syndrome.

Radiologically Isolated Syndrome (RIS) is characterized by MRI-typical brain lesions fulfilling the 2009 Okuda criteria, detected in patients without clinical conditions suggestive of MS. Half of all RIS patients convert to MS within 10 years. The individual course of the disease, however, is highly variable with 12% of RIS converting directly to progressive MS. Demographic and imaging markers have been associated with the risk of clinical MS in RIS: male sex, younger age, infra-tentorial, and spinal cord lesions on the index scan and gadolinium-enhancing lesions on index or follow-up scans. Although not considered as a distinct MS phenotype, RIS certainly shares common pathological features with early active and progressive MS. In this review, we specifically focus on biological markers that may help refine the risk stratification of clinical MS and disability for early treatment. Intrathecal B-cell activation with cerebrospinal fluid (CSF) oligoclonal bands, elevated kappa free light chains, and cytokine production is specific to MS, whereas neurofilament light chain (NfL) levels reflect disease activity associated with neuroaxonal injury. Specific microRNA profiles have been identified in RIS converters in both CSF and blood. CSF levels of chitinases and glial acidic fibrillary protein (GFAP) reflecting astrogliosis might help predict the evolution of RIS to progressive MS. Innovative genomic, proteomic, and metabolomic approaches have provided several new candidate biomarkers to be explored in RIS. Leveraging data from randomized controlled trials and large prospective RIS cohorts with extended follow-up to identify, as early as possible, biomarkers for predicting greater disease severity would be invaluable for counseling patients, managing treatment, and monitoring.