Evidence map›Paper›PMID 37308827›Full record

ArticleClinical proteomics2023

Orthogonal proteomics methods warrant the development of Duchenne muscular dystrophy biomarkers.

Camilla Johansson, Helian Hunt, Mirko Signorelli, Fredrik Edfors, Andreas Hober, Anne-Sophie Svensson, Hanna Tegel, Björn Forstström, Annemieke Aartsma-Rus, Erik Niks and 3 more

Open access · goldAbstract read
In one paragraph

Article in Clinical proteomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.9field-weighted citation impact, top 16% 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

8 citing papers in PubMed, 9 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Serum protein biomarker signature of Duchenne muscular dystrophy.European journal of translational myology · 2025
    Article
  6. Review
  7. Article
  8. Review
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

13 authors at 4 institutions in 2 countries.

Camilla JohanssonDepartment of Protein Science, School of Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden.
Helian HuntScience for Life Laboratory, KTH - Royal Institute of Technology, Solna, Sweden.
Mirko SignorelliMathematical Institute, Leiden University, Leiden, The Netherlands.
Fredrik EdforsScience for Life Laboratory, KTH - Royal Institute of Technology, Solna, Sweden.
Andreas HoberScience for Life Laboratory, KTH - Royal Institute of Technology, Solna, Sweden.
Anne-Sophie SvenssonDepartment of Protein Science, School of Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden.
Hanna TegelDepartment of Protein Science, School of Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden.
Björn ForstströmScience for Life Laboratory, KTH - Royal Institute of Technology, Solna, Sweden.
Annemieke Aartsma-RusDepartment of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands.
Erik NiksDepartment of Neurology, Leiden University Medical Center, Leiden, The Netherlands.
Pietro SpitaliDepartment of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands.
Mathias UhlénScience for Life Laboratory, KTH - Royal Institute of Technology, Solna, Sweden.
Cristina Al-Khalili SzigyartoDepartment of Protein Science, School of Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden. caks@kth.se.
KTH Royal Institute of Technology · SELeiden University Medical Center · NLScience for Life Laboratory · SELeiden University · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMolecular components in blood, such as proteins, are used as biomarkers to detect or predict disease states, guide clinical interventions and aid in the development of therapies. While multiplexing proteomics methods promote discovery of such biomarkers, their translation to clinical use is difficult due to the lack of substantial evidence regarding their reliability as quantifiable indicators of disease state or outcome. To overcome this challenge, a novel orthogonal strategy was developed and used to assess the reliability of biomarkers and analytically corroborate already identified serum biomarkers for Duchenne muscular dystrophy (DMD). DMD is a monogenic incurable disease characterized by progressive muscle damage that currently lacks reliable and specific disease monitoring tools.

methodsTwo technological platforms are used to detect and quantify the biomarkers in 72 longitudinally collected serum samples from DMD patients at 3 to 5 timepoints. Quantification of the biomarkers is achieved by detection of the same biomarker fragment either through interaction with validated antibodies in immuno-assays or through quantification of peptides by Parallel Reaction Monitoring Mass Spectrometry assay (PRM-MS).

resultsFive, out of ten biomarkers previously identified by affinity-based proteomics methods, were confirmed to be associated with DMD using the mass spectrometry-based method. Two biomarkers, carbonic anhydrase III and lactate dehydrogenase B, were quantified with two independent methods, sandwich immunoassays and PRM-MS, with Pearson correlations of 0.92 and 0.946 respectively. The median concentrations of CA3 and LDHB in DMD patients was elevated in comparison to those in healthy individuals by 35- and 3-fold, respectively. Levels of CA3 vary between 10.26 and 0.36 ng/ml in DMD patients whereas those of LDHB vary between 15.1 and 0.8 ng/ml.

conclusionsThese results demonstrate that orthogonal assays can be used to assess the analytical reliability of biomarker quantification assays, providing a means to facilitate the translation of biomarkers to clinical practice. This strategy also warrants the development of the most relevant biomarkers, markers that can be reliably quantified with different proteomics methods.

Indexed as

Biomarker quantificationDuchenne muscular dystrophyMass spectrometryParallel reaction monitoring.Sandwich immunoassaySerum biomarkers

Identifiers

PMID37308827
PMCPMC10258980
OpenAlexW4380244148

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.