4.7 Article

Affinity proteomics within rare diseases: a BIO-NMD study for blood biomarkers of muscular dystrophies

期刊

EMBO MOLECULAR MEDICINE
卷 6, 期 7, 页码 918-936

出版社

WILEY
DOI: 10.15252/emmm.201303724

关键词

antibody-based proteomics; disease severity biomarkers; Duchenne muscular dystrophy; plasma profilling; protein profiling

资金

  1. European Community [241665]
  2. ProNova VINN Excellence Centre for Protein Technology (VINNOVA, Swedish Governmental Agency for Innovation Systems)
  3. Knut and Alice Wallenberg Foundation
  4. SciLifeLab Stockholm
  5. Great Ormond Street Children's Charity
  6. Medical Research Council (UK)
  7. TREAT-NMD (EU FP6) [036825]
  8. TREAT-NMD Alliance
  9. MRC [MR/K000608/1] Funding Source: UKRI
  10. Fondazione Telethon Funding Source: Custom
  11. Medical Research Council [MR/K000608/1] Funding Source: researchfish
  12. National Institute for Health Research [NF-SI-0512-10036] Funding Source: researchfish

向作者/读者索取更多资源

Despite the recent progress in the broad-scaled analysis of proteins in body fluids, there is still a lack in protein profiling approaches for biomarkers of rare diseases. Scarcity of samples is the main obstacle hindering attempts to apply discovery driven protein profiling in rare diseases. We addressed this challenge by combining samples collected within the BIO-NMD consortium from four geographically dispersed clinical sites to identify protein markers associated with muscular dystrophy using an antibody bead array platform with 384 antibodies. Based on concordance in statistical significance and confirmatory results obtained from analysis of both serum and plasma, we identified eleven proteins associated with muscular dystrophy, among which four proteins were elevated in blood from muscular dystrophy patients: carbonic anhydrase III (CA3) and myosin light chain 3 (MYL3), both specifically expressed in slow-twitch muscle fibers and mitochondrial malate dehydrogenase 2 (MDH2) and electron transfer flavo-protein A (ETFA). Using age-matched sub-cohorts, 9 protein profiles correlating with disease progression and severity were identified, which hold promise for the development of new clinical tools for management of dystrophinopathies.

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