Ayoglu B.,KTH Royal Institute of Technology |
Chaouch A.,Northumbria University |
Lochmuller H.,Northumbria University |
Politano L.,The Second University of Naples |
And 20 more authors.
EMBO Molecular Medicine | Year: 2014
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 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. © 2014 The Authors.
Agency: Department of Health and Human Services | Branch: | Program: SBIR | Phase: Phase I | Award Amount: 242.98K | Year: 2014
Ariadne Diagnostics, Llc | Entity website
Ariadne Diagnostics LLC (Ariadne-Dx) is a start-up diagnostic discovery and development company founded in December, 2011 and located in the 270 Technology Corridor with its main office in Rockville, MD. The Company licensed certain rights to discoveries and intellectual property with regard to biomarker panels for mCRC and neurodegenerative / neuromuscular diseases from Ariadne Genomics which over the last ten years has designed and developed bioinformatics software and algorithms for biomedical research ...
Ariadne Diagnostics, Llc | Entity website
Companion Diagnostics Tests In pharmaceutical discovery an emphasis on the personalized medicine became a reality, and many new drugs start coming to market supported by tests that will help to make the decisions of who gets what drug, whats the appropriate dose, and whos in the greatest danger of serious side effects. In recognition of the value of such tests, internal research and development at Ariadne-Dx is focused on the development of companion diagnostics (CDx) for cancer and neuromuscular/neurodegenerative disorders ...
Pyatnitskiy M.,Ariadne Diagnostics, Llc |
Mazo I.,Ariadne Diagnostics, Llc |
Shkrob M.,Elsevier |
Schwartz E.,Ariadne Diagnostics, Llc |
And 2 more authors.
PLoS ONE | Year: 2014
One of the main challenges in modern medicine is to stratify different patient groups in terms of underlying disease molecular mechanisms as to develop more personalized approach to therapy. Here we propose novel method for disease subtyping based on analysis of activated expression regulators on a sample-by-sample basis. Our approach relies on Sub-Network Enrichment Analysis algorithm (SNEA) which identifies gene subnetworks with significant concordant changes in expression between two conditions. Subnetwork consists of central regulator and downstream genes connected by relations extracted from global literature-extracted regulation database. Regulators found in each patient separately are clustered together and assigned activity scores which are used for final patients grouping. We show that our approach performs well compared to other related methods and at the same time provides researchers with complementary level of understanding of pathway-level biology behind a disease by identification of significant expression regulators. We have observed the reasonable grouping of neuromuscular disorders (triggered by structural damage vs triggered by unknown mechanisms), that was not revealed using standard expression profile clustering. For another experiment we were able to suggest the clusters of regulators, responsible for colorectal carcinoma vs adenoma discrimination and identify frequently genetically changed regulators that could be of specific importance for the individual characteristics of cancer development. Proposed approach can be regarded as biologically meaningful feature selection, reducing tens of thousands of genes down to dozens of clusters of regulators. Obtained clusters of regulators make possible to generate valuable biological hypotheses about molecular mechanisms related to a clinical outcome for individual patient. © 2014 Pyatnitskiy et al.