Multiple Sclerosis
Conditions
Brief summary
To determine if biomarker-based CSF testing is reliably detecting differences between patients with Multiple Sclerosis (MS), different MS-subtypes, and other central nervous system (CNS) diseases. This study will also look to identify biomarkers that could be used for the prediction, at the time of diagnosis, of the future disease clinical course and response to therapy. The SOMAscan assay will be used for CSF samples analysis.
Detailed description
Using machine learning, the investigators have developed from SOMAScan: 1. A molecular diagnostic test that differentiates MS from other inflammatory and non-inflammatory central nervous system (CNS) diseases (area under receiver-operator characteristic curve-AUROC of 0.98); 2. A molecular test that differentiates relapsing-remitting MS from progressive MS variants (AUROC of 0.91); and 3. A molecular test that predicts future rates of disability progression, concordance coefficient of 0.425 (p\<0.001). Because these results are derived from a single research center (NIAID/NDS), it is imperative to determine their performance in real clinical practice settings as a necessary step for their potential regulatory approval. Consequently, his application has 2 specific aims: AIM 1. To independently validate afore-mentioned CSF-biomarker-based tests for their clinical value within the multicenter Spinal fluid Consortium for MS (SPINCOMS). In Aim 1, each of the 3 defined tests will be validated in 100 new SPINCOMS patients. To validate the prognostic test, 100 MS patients with CSF collected at least 3 years ago will be evaluated at follow-up examination with standardized clinical outcomes. CSF will be analyzed blinded using pre-defined statistical models. AIM 2. To explore whether collected CSF-biomarkers point towards pathogenic heterogeneity that may predict patient-specific efficacy for different disease-modifying treatments (DMTs) or identify pathogenic mechanisms not targeted by current DMTs. In Aim 2, clustering analysis will assess pathogenic heterogeneity and explore potential predictors of response to therapy.
Interventions
None listed
Sponsors
National Institute of Allergy and Infectious Diseases (NIAID)
University of Colorado, Denver
University of Ottawa
Montana State University
Washington University School of Medicine
Study design
Observational model
OTHER
Time perspective
OTHER
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
MS Patients selection criteria * Lumbar puncture (LP) in the untreated stage with cryopreserved CSF (serum/blood optional) with consent to use it for future research * ≥ 3 and ≤ 10 years of follow-up from LP * At time of LP untreated and not treated with steroid or off steroids ≥ one month * Available/willing to come for in-person follow-up * Available/willing to sign the NIH 09-I-0032 Sample processing only consent form * Diagnosis of MS based on 2017 McDonald criteria at time of follow-up visit Non-MS Patients selection criteria Required: 25 Non-Inflammatory Neurological Disease (NIND), 25 Other Inflammatory Neurological Disease (OIND) * Lumbar puncture (LP) in the untreated stage with cryopreserved CSF (serum/blood optional) with consent to use it for future research * ≥ 3 and ≤ 10 years of follow-up from LP * At time of LP untreated and not treated with steroid or off steroids ≥ one month * Up to date contact information * Available/willing to sign the NIH 09-I-0032 Sample processing only consent form * Diagnosis: NIND: e.g., ischemic-gliotic changes, CADASIL and other leukodystrophies, migraines, ischemic spinal cord lesions etc OIND: e.g. CNS Sjogren's, SLE, vasculitis, CNS infections, MOG-associated disorders, NMO spectrum disorders (NMOSD)
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Biomarker Predicted Outcomes against NeurEx-based outcomes | 3 years | CSF-biomarker-predicted outcomes against measured NeurEx-based outcomes, considering a Bonferroni-adjusted significance level 0.05/3 = 0.017 (to adjust for 3 tests). |
| MS Severity Model Analyses | 3 years | As secondary analyses of MS severity model,assessment of correlations between CSF-biomarker-predicted outcomes and more traditional MS outcomes. Specifically, correlate CSF-biomarker-based scores of MS severity and MSSS, ARMSSS and by MS-DSS, calculated from the follow-up visit scores. Based on power calculations, 100 relevant patients/classifier will provide \> 90% power to externally validate all 3 Somascan CSF-biomarker-based models. |
Countries
United States
Outcome results
None listed