Literature DB >> 25027324

Discovery of serum protein biomarkers in the mdx mouse model and cross-species comparison to Duchenne muscular dystrophy patients.

Yetrib Hathout1, Ramya L Marathi2, Sree Rayavarapu2, Aiping Zhang2, Kristy J Brown2, Haeri Seol2, Heather Gordish-Dressman2, Sebahattin Cirak2, Luca Bello2, Kanneboyina Nagaraju2, Terry Partridge2, Eric P Hoffman2, Shin'ichi Takeda3, Jean K Mah4, Erik Henricson5, Craig McDonald5.   

Abstract

It is expected that serum protein biomarkers in Duchenne muscular dystrophy (DMD) will reflect disease pathogenesis, progression and aid future therapy developments. Here, we describe use of quantitative in vivo stable isotope labeling in mammals to accurately compare serum proteomes of wild-type and dystrophin-deficient mdx mice. Biomarkers identified in serum from two independent dystrophin-deficient mouse models (mdx-Δ52 and mdx-23) were concordant with those identified in sera samples of DMD patients. Of the 355 mouse sera proteins, 23 were significantly elevated and 4 significantly lower in mdx relative to wild-type mice (P-value < 0.001). Elevated proteins were mostly of muscle origin: including myofibrillar proteins (titin, myosin light chain 1/3, myomesin 3 and filamin-C), glycolytic enzymes (aldolase, phosphoglycerate mutase 2, beta enolase and glycogen phosphorylase), transport proteins (fatty acid-binding protein, myoglobin and somatic cytochrome-C) and others (creatine kinase M, malate dehydrogenase cytosolic, fibrinogen and parvalbumin). Decreased proteins, mostly of extracellular origin, included adiponectin, lumican, plasminogen and leukemia inhibitory factor receptor. Analysis of sera from 1 week to 7 months old mdx mice revealed age-dependent changes in the level of these biomarkers with most biomarkers acutely elevated at 3 weeks of age. Serum analysis of DMD patients, with ages ranging from 4 to 15 years old, confirmed elevation of 20 of the murine biomarkers in DMD, with similar age-related changes. This study provides a panel of biomarkers that reflect muscle activity and pathogenesis and should prove valuable tool to complement natural history studies and to monitor treatment efficacy in future clinical trials.
© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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Year:  2014        PMID: 25027324      PMCID: PMC4240201          DOI: 10.1093/hmg/ddu366

Source DB:  PubMed          Journal:  Hum Mol Genet        ISSN: 0964-6906            Impact factor:   6.150


  65 in total

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  52 in total

1.  Contemporary cardiac issues in Duchenne muscular dystrophy. Working Group of the National Heart, Lung, and Blood Institute in collaboration with Parent Project Muscular Dystrophy.

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2.  Role of adiponectin in the metabolism of skeletal muscles in collagen VI-related myopathies.

Authors:  Tania Gamberi; Francesca Magherini; Michele Mannelli; Martina Chrisam; Matilde Cescon; Silvia Castagnaro; Alessandra Modesti; Paola Braghetta; Tania Fiaschi
Journal:  J Mol Med (Berl)       Date:  2019-03-29       Impact factor: 4.599

3.  Longitudinal metabolomic analysis of plasma enables modeling disease progression in Duchenne muscular dystrophy mouse models.

Authors:  Roula Tsonaka; Mirko Signorelli; Ekrem Sabir; Alexandre Seyer; Kristina Hettne; Annemieke Aartsma-Rus; Pietro Spitali
Journal:  Hum Mol Genet       Date:  2020-03-27       Impact factor: 6.150

4.  N-terminal α Dystroglycan (αDG-N): A Potential Serum Biomarker for Duchenne Muscular Dystrophy.

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5.  Ionizing radiation exposure: hazards, prevention, and biomarker screening.

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6.  A tissue communication network coordinating innate immune response during muscle stress.

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Journal:  J Cell Sci       Date:  2018-12-18       Impact factor: 5.285

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Review 9.  Non-Glycanated Biglycan and LTBP4: Leveraging the extracellular matrix for Duchenne Muscular Dystrophy therapeutics.

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Journal:  Matrix Biol       Date:  2018-02-23       Impact factor: 11.583

10.  Degenerative and regenerative pathways underlying Duchenne muscular dystrophy revealed by single-nucleus RNA sequencing.

Authors:  Francesco Chemello; Zhaoning Wang; Hui Li; John R McAnally; Ning Liu; Rhonda Bassel-Duby; Eric N Olson
Journal:  Proc Natl Acad Sci U S A       Date:  2020-11-04       Impact factor: 11.205

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