Evidence map›Paper›PMID 29059494›Full record

ArticleAnnals of neurology2017

Molecular-based diagnosis of multiple sclerosis and its progressive stage.

Christopher Barbour, Peter Kosa, Mika Komori, Makoto Tanigawa, Ruturaj Masvekar, Tianxia Wu, Kory Johnson, Panagiotis Douvaras, Valentina Fossati, Ronald Herbst and 4 more

Registry-linked trialOpen access · greenAbstract read
In one paragraph

Article in Annals of neurology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04496830 (Cerebrospinal Fluid-biomarkers-based Diagnostic and Prognostic Models for Multiple Sclerosis), which is not on this map. Cited by 35 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 2 pooled it
3.5field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT04496830 completednot on this mapstarted 2020, after this paper: background citation

Cerebrospinal Fluid-biomarkers-based Diagnostic and Prognostic Models for Multiple Sclerosis

TypeobservationalSponsorWashington University School of MedicineRan2020 to 2023Enrolled161ConditionsMultiple Sclerosis
3 · Its place in the literature

Who cites it

35 citing papers in PubMed, 2 syntheses or guidelines pooled it, 54 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Trial
  5. Trial
  6. Trial
  7. Article
  8. Profiling the Cerebrospinal Fluid Proteome in Progressive Multiple Sclerosis: Treatment Effects and Associations with IgM Oligoclonal Bands.Journal of neuroimmune pharmacology : the official journal of the Society on NeuroImmune Pharmacology · 2025
    Article
  9. Article
  10. Review
  11. Review
  12. Article
  13. Article
  14. Review
  15. Review
  16. Article
  17. Review
  18. Review
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors at 6 institutions in 3 countries.

Christopher BarbourNeuroimmunological Diseases Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD.
Peter KosaNeuroimmunological Diseases Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD.
Mika KomoriNeuroimmunological Diseases Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD.
Makoto TanigawaNeuroimmunological Diseases Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD.
Ruturaj MasvekarNeuroimmunological Diseases Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD.
Tianxia WuClinical Trials Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD.
Kory JohnsonBioinformatics Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD.
Panagiotis DouvarasNew York Stem Cell Foundation Research Institute, New York, NY.
Valentina FossatiNew York Stem Cell Foundation Research Institute, New York, NY.
Ronald HerbstDepartment of Oncology Research, MedImmune, Gaithersburg, MD.
Yue WangDepartment of Oncology Research, MedImmune, Gaithersburg, MD.
Keith TanTranslational Medicine, Neuroscience, Innovative Medicines, and Early Development, AstraZeneca, Cambridge, United Kingdom.
Mark GreenwoodDepartment of Mathematical Sciences, Montana State University, Bozeman, MT.
Bibiana BielekovaNeuroimmunological Diseases Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD.
National Institute of Neurological Disorders and Stroke · USNational Institutes of Health · USAltimmune (United States) · USNew York Stem Cell Foundation · USAstraZeneca (United States) · USMontana State University · US

Funding

Comprehensive multimodal analysis of patients with neuroimmunological diseasesZIANS003055 · NINDS · NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE · PI BIELEKOVA, BIBIANA · 2009 to 2018
$9.0M
Intramural NIH HHS Z99 NS999999Intramural NIH HHS ZIA NS003055
6 · The paper itself

Abstract

objectiveBiomarkers aid diagnosis, allow inexpensive screening of therapies, and guide selection of patient-specific therapeutic regimens in most internal medicine disciplines. In contrast, neurology lacks validated measurements of the physiological status, or dysfunction(s) of cells of the central nervous system (CNS). Accordingly, patients with chronic neurological diseases are often treated with a single disease-modifying therapy without understanding patient-specific drivers of disability. Therefore, using multiple sclerosis (MS) as an example of a complex polygenic neurological disease, we sought to determine whether cerebrospinal fluid (CSF) biomarkers are intraindividually stable, cell type-, disease- and/or process-specific, and responsive to therapeutic intervention.

methodsWe used statistical learning in a modeling cohort (n = 225) to develop diagnostic classifiers from DNA-aptamer-based measurements of 1,128 CSF proteins. An independent validation cohort (n = 85) assessed the reliability of derived classifiers. The biological interpretation resulted from in vitro modeling of primary or stem cell-derived human CNS cells and cell lines.

resultsThe classifier that differentiates MS from CNS diseases that mimic MS clinically, pathophysiologically, and on imaging achieved a validated area under the receiver operating characteristic curve (AUROC) of 0.98, whereas the classifier that differentiates relapsing-remitting from progressive MS achieved a validated AUROC of 0.91. No classifiers could differentiate primary progressive from secondary progressive MS better than random guessing. Treatment-induced changes in biomarkers greatly exceeded intraindividual and technical variabilities of the assay.

interpretationCNS biological processes reflected by CSF biomarkers are robust, stable, disease specific, or even disease stage specific. This opens opportunities for broad utilization of CSF biomarkers in drug development and precision medicine for CNS disorders. Ann Neurol 2017;82:795-812.

Indexed as

AdolescentAdultAgedBiomarkersCase-Control StudiesCell LineCerebrospinal Fluid ProteinsDiagnosis, DifferentialFemaleHumansMaleMiddle AgedMultiple Sclerosis, Chronic ProgressiveMultiple Sclerosis, Relapsing-RemittingYoung AdultBiomarkersCerebrospinal Fluid Proteins

Identifiers

PMID29059494
PMCPMC5743213
OpenAlexW2767098446

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.