Evidence map›Paper›PMID 29682908›Full record

ArticleJournal of cachexia, sarcopenia and muscle2018

Tracking disease progression non-invasively in Duchenne and Becker muscular dystrophies.

Pietro Spitali, Kristina Hettne, Roula Tsonaka, Mohammed Charrout, Janneke van den Bergen, Zaïda Koeks, Hermien E Kan, Melissa T Hooijmans, Andreas Roos, Volker Straub and 7 more

Open access · goldAbstract read
In one paragraph

Article in Journal of cachexia, sarcopenia and muscle, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed
2.9field-weighted citation impact, top 8% 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

51 citing papers in PubMed, 67 citations in OpenAlex.

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  10. Serum protein biomarker signature of Duchenne muscular dystrophy.European journal of translational myology · 2025
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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

17 authors at 5 institutions in 3 countries.

Pietro SpitaliDepartment of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands.ORCID 0000-0003-2783-688X
Kristina HettneDepartment of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands.
Roula TsonakaDepartment of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands.
Mohammed CharroutDepartment of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands.
Janneke van den BergenDepartment of Neurology, Leiden University Medical Center, Leiden, The Netherlands.
Zaïda KoeksDepartment of Neurology, Leiden University Medical Center, Leiden, The Netherlands.
Hermien E KanC.J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
Melissa T HooijmansC.J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
Andreas RoosJohn Walton Muscular Dystrophy Research Centre, MRC Centre for Neuromuscular Diseases, Institute of Genetic Medicine, University of Newcastle, Newcastle upon Tyne, UK.
Volker StraubJohn Walton Muscular Dystrophy Research Centre, MRC Centre for Neuromuscular Diseases, Institute of Genetic Medicine, University of Newcastle, Newcastle upon Tyne, UK.
Francesco MuntoniDubowitz Neuromuscular Centre, University College London Great Ormond Street Institute of Child Health, London, UK.
Cristina Al-Khalili-SzigyartoDivision of Proteomics, School of Biotechnology, KTH-Royal Institute of Technology, Stockholm, Sweden.
Marleen J A Koel-SimmelinkNeurochemistry Lab and Biobank, Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center Amsterdam, The Netherlands.
Charlotte E TeunissenNeurochemistry Lab and Biobank, Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center Amsterdam, The Netherlands.
Hanns LochmüllerJohn Walton Muscular Dystrophy Research Centre, MRC Centre for Neuromuscular Diseases, Institute of Genetic Medicine, University of Newcastle, Newcastle upon Tyne, UK.
Erik H NiksDepartment of Neurology, Leiden University Medical Center, Leiden, The Netherlands.
Annemieke Aartsma-RusDepartment of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands.
Leiden University Medical Center · NLCentre for Life · GBAmsterdam Neuroscience · NLGreat Ormond Street Hospital · GBKTH Royal Institute of Technology · SE

Funding

Department of Health
6 · The paper itself

Abstract

backgroundAnalysis of muscle biopsies allowed to characterize the pathophysiological changes of Duchenne and Becker muscular dystrophies (D/BMD) leading to the clinical phenotype. Muscle tissue is often investigated during interventional dose finding studies to show in situ proof of concept and pharmacodynamics effect of the tested drug. Less invasive readouts are needed to objectively monitor patients' health status, muscle quality, and response to treatment. The identification of serum biomarkers correlating with clinical function and able to anticipate functional scales is particularly needed for personalized patient management and to support drug development programs.

methodsA large-scale proteomic approach was used to identify serum biomarkers describing pathophysiological changes (e.g. loss of muscle mass), association with clinical function, prediction of disease milestones, association with in vivo

resultsCross-sectional comparison enabled to identify 10 proteins discriminating between healthy controls, DMD and BMD patients. Several proteins (285) were able to separate DMD from healthy, while 121 proteins differentiated between BMD and DMD; only 13 proteins separated BMD and healthy individuals. The concentration of specific proteins in serum was significantly associated with patients' performance (e.g. BMP6 serum levels and elbow flexion) or dystrophin levels (e.g. TIMP2) in BMD patients. Analysis of longitudinal trajectories allowed to identify 427 proteins affected over time indicating loss of muscle mass, replacement of muscle by adipose tissue, and cardiac involvement. Over-representation analysis of longitudinal data allowed to highlight proteins that could be used as pharmacodynamic biomarkers for drugs currently in clinical development.

conclusionsSerum proteomic analysis allowed to not only discriminate among DMD, BMD, and healthy subjects, but it enabled to detect significant associations with clinical function, dystrophin levels, and disease progression.

Indexed as

AdultAgedBiomarkersComputational BiologyCross-Sectional StudiesDisease ProgressionFollow-Up StudiesHumansMiddle AgedMuscle, SkeletalMuscular Dystrophy, DuchenneProteomeProteomicsYoung AdultBiomarkersProteomeBecker muscular dystrophyBiomarkerDuchenne muscular dystrophyLongitudinal analysisProteomicsSarcopenia

Identifiers

PMID29682908
PMCPMC6104105
OpenAlexW2802855982

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

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.