Evidence map›Paper›PMID 19712003›Full record

ReviewMolecular diagnosis & therapy2009

Disease biomarkers in multiple sclerosis: potential for use in therapeutic decision making.

Violaine K Harris, Saud A Sadiq

Registry-linked trialAbstract readReview
PubMed Publisher
In one paragraph

Review in Molecular diagnosis & therapy, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01626248 (Analysis of Lymphocyte Cell Surface Adhesion Marker Expression in a Natalizumab Treated Population With Active Control Assessment), which is not on this map. Cited by 41 papers.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed
3.8field-weighted citation impact, top 6% 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.

NCT01626248 completednot on this mapstarted 2012, after this paper: background citation

Analysis of Lymphocyte Cell Surface Adhesion Marker Expression in a Natalizumab Treated Population With Active Control Assessment

TypeobservationalSponsorJohn F. Foley, MDRan2012 to 2013Enrolled164ConditionsMultiple Sclerosis
3 · Its place in the literature

Who cites it

41 citing papers in PubMed, 105 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Current and Future Biomarkers in Multiple Sclerosis.International journal of molecular sciences · 2022
    Review
  6. Review
  7. Review
  8. Potential Biomarkers Associated with Multiple Sclerosis Pathology.International journal of molecular sciences · 2021
    Review
  9. Article
  10. Review
  11. Article
  12. Article
  13. Review
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  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

2 authors at 1 institution in 1 country.

Violaine K HarrisMultiple Sclerosis Research Center of New York, New York, New York 10019, USA.
Saud A Sadiq
Multiple Sclerosis Center Of Northeastern New York · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multiple sclerosis (MS) is an autoimmune disorder of the brain and spinal cord that predominantly affects white matter. MS has a variable clinical presentation and has no 'diagnostic' laboratory test; this often results in delays to definite diagnosis. In confronting the disease, early diagnosis and appropriate, timely therapeutic intervention are critical factors in ensuring favorable long-term outcomes. The availability of reliable biomarkers could radically alter our management of MS at critical phases of the disease spectrum. Identification of markers that could predict the development of MS in high-risk populations would allow for intervention strategies that may prevent evolution to definite disease. Work with anti-myelin antibodies and the ongoing analysis of microarray gene expression have thus far not yielded biomarkers that predict future disease development. Similarly, extensive studies with serum and cerebrospinal fluid (CSF) have not yielded a disease-specific and sensitive diagnostic biomarker for MS. Establishment of disease diagnosis always leads to questions about long-term prognosis because in an individual patient the natural history of the disease is clinically unpredictable. Biomarkers that correlate with myelin loss, spinal cord disease, grey matter and subcortical demyelination need to be developed in order to accurately predict the disease course. The bulk of effort in biomarker development in MS has been concentrated in the area of monitoring disease activity. At present, a disease 'activation' panel of CSF biomarkers would include the following: interleukin-6 or its soluble receptor, nitric oxide and nitric oxide synthase, osteopontin, and fetuin-A. Although disease activity in MS is predominantly inflammatory, disease progression is likely to be the result of neurodegeneration. Therefore, the roles of proteins indicative of neuronal, axonal, and glial loss such as neurofilaments, tau, 14-3-3 proteins, and N-acetylaspartate are all under investigation, as are proteins affecting remyelination and regeneration, such as Nogo-A. With the increasing awareness of cognition dysfunction in MS, molecules such as apolipoprotein and proteins in the amyloid precursor protein pathway implicated in dementia are also being examined. Serum biomarkers that help monitor therapeutic efficacy such as the titer of antibody to beta-interferon, a first-line medication in MS, are established in clinical practice. Ongoing work with biomarkers that reflect drug bioavailability and factors that distinguish between medication responders and nonresponders are also under investigation. The discovery of new biomarkers relies on applying advances in proteomics along with microarray gene and antigen analysis and will hopefully result in the establishment of specific biomarkers for MS.

Indexed as

BiomarkersHumansMultiple SclerosisBiomarkers

Identifiers

PMID19712003
OpenAlexW42114648

What OpenQuestion holds

Textmetadata
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.