Evidence map›Paper›PMID 24586361›Full record

ArticlePloS one2014

Deficient phosphorylation of Stat1 in leukocytes identifies neutralizing antibodies in multiple sclerosis patients treated with interferon-beta.

Sonia Gavasso, Ellen Faergestad Mosleth, Tove Marøy, Katarina Jørgensen, Hanne-Linda Nakkestad, Bjørn-Tore Gjertsen, Kjell-Morten Myhr, Christian Vedeler

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.0field-weighted citation impact, top 24% 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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 11 citations in OpenAlex.

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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

8 authors at 3 institutions in 1 country.

Sonia GavassoDepartment of Neurology, Haukeland University Hospital, Bergen, Norway ; The Norwegian Multiple Sclerosis Competence Centre, Department of Neurology, Haukeland University Hospital, Bergen, Norway ; Department of Clinical Medicine, University of Bergen, Bergen, Norway.
Ellen Faergestad MoslethNofima, Ås, Norway.
Tove MarøyThe Norwegian Multiple Sclerosis Competence Centre, Department of Neurology, Haukeland University Hospital, Bergen, Norway.
Katarina JørgensenDepartment of Clinical Science, Hematology Section, University of Bergen, Bergen, Norway.
Hanne-Linda NakkestadDepartment of Clinical Medicine, University of Bergen, Bergen, Norway.
Bjørn-Tore GjertsenDepartment of Clinical Science, Hematology Section, University of Bergen, Bergen, Norway ; Department of Internal Medicine, Haukeland University Hospital, Bergen, Norway.
Kjell-Morten MyhrDepartment of Neurology, Haukeland University Hospital, Bergen, Norway ; The Norwegian Multiple Sclerosis Competence Centre, Department of Neurology, Haukeland University Hospital, Bergen, Norway ; Department of Clinical Medicine, University of Bergen, Bergen, Norway ; The KG Jebsen Centre for MS Research, University of Bergen, Bergen, Norway.
Christian VedelerDepartment of Neurology, Haukeland University Hospital, Bergen, Norway ; Department of Clinical Medicine, University of Bergen, Bergen, Norway ; The KG Jebsen Centre for MS Research, University of Bergen, Bergen, Norway.
University of Bergen · NOHaukeland University Hospital · NOFafo Foundation · NO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAnti interferon-beta (IFN-β) neutralizing antibodies (NAb) affect efficacy of treatment of multiple sclerosis patients, but exactly when the detrimental effects of NAbs offset therapeutic efficacy is debated. Quantification of intracellular pathway-specific phosphorylation by phospho-specific flow cytometry (phosphoflow) is a promising tool for evaluation of these effects in primary immune cells from treated patients at the single-cell level.

methodSamples for phosphoflow and gene expression changes were collected before administration of IFN-β and at four, six, and eight hours thereafter. Patients were NAb negative (n = 3) or were NAb positive with low/medium (n = 1) or high (n = 2) NAb titers. Levels of phosphorylation of six Stat transcription factors (pStat) in seven cell subtypes and expression levels of 71 pathway-specific genes in whole blood were measured. The data was subjected to principal component analysis (PCA), fifty-fifty MANOVA, ANOVA, and partial least square regression (PLSR).

resultsPCA of pStat levels clustered patients according to NAb class independently of time. PCA of gene expression data clustered patients according to NAb class but was affected by time and treatment. In the fifty-fifty MANOVA, NAb class was significant for both pStat levels and gene expression data. The ANOVA identified pStat1 protein in several cell subtypes as significantly affected by NAb class. The best fitting model for NAb prediction based on PLSR included pStat1 in monocytes, T cells, or lymphocytes and pStat3 in monocytes (r = 0.97). Gene expression data were slightly less predictive of NAb titers.

conclusionBased on this proof of concept study, we hypothesize that NAb effects can be monitored by evaluation of a single biomarker, pStat1, in either monocytes or T cells by phosphoflow directly after IFN-β administration. The method will significantly reduce cost relative to labor intensive in vitro methods and offers a patient-specific approach to NAb evaluation.

Indexed as

AdultAntibodies, NeutralizingFemaleGene Expression RegulationHumansInterferon-betaLeukocytesMaleMiddle AgedMultiple SclerosisPhosphoproteinsPhosphorylationSignal TransductionSingle-Cell AnalysisSTAT1 Transcription FactorTreatment FailureAntibodies, NeutralizingInterferon-betaPhosphoproteinsSTAT1 protein, humanSTAT1 Transcription Factor

Identifiers

PMID24586361
PMCPMC3929401
OpenAlexW1979969759

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.