Evidence map›Paper›PMID 42249273›Full record

ArticleClinical proteomics2026

Quantitative tandem mass tag-based serum proteomics for longitudinal biomarker monitoring in Duchenne muscular dystrophy.

Ahmed Naveed, Elissa Recinos, Dexter Chow, Chiara Degan, Roula Tsonaka, Michela Guglieri, Cristina Al-Khalili Szigyarto, Pietro Spitali, Yuri E M van der Burgt, Jordi Diaz-Manera and 3 more

Registry-linked trialAbstract read
In one paragraph

Article in Clinical proteomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01603407 (Duchenne Muscular Dystrophy), which is not on this map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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.

NCT01603407 phase3completednot on this map

Duchenne Muscular Dystrophy: Double-blind Randomized Trial to Find Optimum Steroid Regimen

TypeinterventionalSponsorUniversity of RochesterRan2013 to 2019Enrolled196ConditionsDuchenne Muscular DystrophyArmsPrednisone, Deflazacort
3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Ahmed NaveedSchool of Pharmacy and Pharmaceutical Sciences, Dept. of Pharmaceutical Sciences, Binghamton University, Binghamton, NY, USA.ORCID http://orcid.org/0009-0002-8884-9967
Elissa RecinosSchool of Pharmacy and Pharmaceutical Sciences, Dept. of Pharmaceutical Sciences, Binghamton University, Binghamton, NY, USA.
Dexter ChowSchool of Pharmacy and Pharmaceutical Sciences, Dept. of Pharmaceutical Sciences, Binghamton University, Binghamton, NY, USA.
Chiara DeganLeiden University Medical Center, Leiden, Netherlands.
Roula TsonakaLeiden University Medical Center, Leiden, Netherlands.
Michela GuglieriNewcastle University, Newcastle Upon Tyne, UK.
Cristina Al-Khalili SzigyartoDept. of Protein Science, KTH Royal Institute of Technology, Stockholm, Sweden.
Pietro SpitaliLeiden University Medical Center, Leiden, Netherlands.
Yuri E M van der BurgtLeiden University Medical Center, Leiden, Netherlands.
Jordi Diaz-ManeraNewcastle University, Newcastle Upon Tyne, UK.
Utkarsh J DangCarleton University, Ottawa, Canada.
FOR-DMD investigators of the Muscle Study Group
Yetrib HathoutSchool of Pharmacy and Pharmaceutical Sciences, Dept. of Pharmaceutical Sciences, Binghamton University, Binghamton, NY, USA. yhathout@binghamton.edu.

Funding

Biomarker Signatures for Duchenne Muscular DystrophyR61NS119639 · NINDS · STATE UNIVERSITY OF NY,BINGHAMTON · PI DANG, UTKARSH J, HATHOUT, YETRIB · 2022 to 2024
$1.6M
NINDS NIH HHS R61 NS119639NINDS NIH HHS R61NS119639
6 · The paper itself

Abstract

backgroundDuchenne muscular dystrophy (DMD) is an X-linked recessive disorder characterized by progressive and severe muscle degeneration. Motor function tests are commonly used to evaluate treatment efficacy in clinical trials. However, they are subject to interobserver variability and may lack sensitivity for detecting early changes in disease progression. These limitations highlight the need for blood-based biomarkers to monitor disease status and progression. In this study, we used tandem mass tag-based mass spectrometry to quantify proteins in longitudinal serum samples from patients with DMD and to identify proteins associated with motor function performance.

methodsSerum samples collected at three time points (baseline, 12, and 24 months) were obtained from participants in the FOR-DMD trial (NCT01603407) and processed for multiplexed analysis using TMT 6-plex isobaric tags and LC-MS/MS. Protein intensities were log2-transformed and analyzed using linear mixed-effects models to assess their associations with age and repeated functional outcome measurements, such as the North Star Ambulatory Assessment (NSAA) score, 6-minute walk test (6MWT), rise from supine velocity (RSV), and 10-meter run/walk velocity (10mRWV). P-values were adjusted for multiple comparisons, with FDR < 0.05 considered statistically significant.

resultsMixed-model analysis identified 22 proteins associated with age and 77 proteins associated with at least 1 functional outcome, including 26 associated with 2 clinical outcomes after FDR correction. Most associations were observed with NSAA (73 proteins), followed by the 6MWT (28 proteins) and RSV (3 proteins). These proteins spanned multiple disease-relevant categories, including muscle-associated proteins, extracellular matrix (ECM), complement and inflammatory pathways, coagulation/hemostasis, carrier proteins, proteolysis, and cell adhesion.

conclusionUsing longitudinal serum proteome profiles and clinical outcome data, we identified proteins that associate with age and functional outcomes, particularly NSAA and 6MWT, highlighting key molecular pathways in DMD disease progression.

trial registrationThe FOR-DMD clinical trial was registered on ClinicalTrials.gov (registration no. NCT01603407). First submission: 03/04/2012.

Indexed as

Duchenne muscular dystrophyLongitudinal analysisMass spectrometryMonitoring biomarkersQuantitative proteomicsTandem mass tag

Identifiers

PMID42249273
PMCPMC13459337

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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.