Open AccessAffinity proteomics within rare diseases: a BIO ‐ NMD study for blood biomarkers of muscular dystrophies
Author(s) -
Ayoglu Burcu,
Chaouch Amina,
Lochmüller Hanns,
Politano Luisa,
Bertini Enrico,
Spitali Pietro,
Hiller Monika,
Niks Eric H,
Gualandi Francesca,
Pontén Fredrik,
Bushby Kate,
AartsmaRus Annemieke,
Schwartz Elena,
Le Priol Yannick,
Straub Volker,
Uhlén Mathias,
Cirak Sebahattin,
‘t Hoen Peter A C,
Muntoni Francesco,
Ferlini Alessandra,
Schwenk Jochen M,
Nilsson Peter,
AlKhalili Szigyarto Cristina
Publication year - 2014
Publication title -
embo molecular medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.923
H-Index - 107
eISSN - 1757-4684
pISSN - 1757-4676
DOI - 10.15252/emmm.201303724
Subject(s) - proteomics , muscular dystrophy , biology , dystrophin , antibody , computational biology , pathology , biochemistry , medicine , bioinformatics , microbiology and biotechnology , genetics , gene
Abstract 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 ( CA 3) and myosin light chain 3 ( MYL 3), both specifically expressed in slow‐twitch muscle fibers and mitochondrial malate dehydrogenase 2 ( MDH 2) and electron transfer flavoprotein 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.