10.5061/DRYAD.QG6Q2
Boca, Simina M.
Georgetown University Medical Center
Nishida, Maki
Georgetown University Medical Center
Harris, Michael
Georgetown University Medical Center
Rao, Shruti
Georgetown University Medical Center
Cheema, Amrita K.
Georgetown University Medical Center
Gill, Kirandeep
Georgetown University Medical Center
Seol, Haeri
George Washington University
Morgenroth, Lauren P.
George Washington University
Henricson, Erik
University of California, Davis
McDonald, Craig
University of California, Davis
Mah, Jean K.
University of Calgary
Clemens, Paula R.
University of Pittsburgh
Hoffman, Eric P.
George Washington University
Hathout, Yetrib
George Washington University
Madhavan, Subha
Georgetown University Medical Center
Data from: Discovery of metabolic biomarkers for Duchenne Muscular
Dystrophy within a natural history study
Dryad
dataset
2016
Duchenne muscular dystrophy
Homo Sapiens
2016-04-20T05:02:13Z
2016-04-20T05:02:13Z
en
https://doi.org/10.1371/journal.pone.0153461
5318994325 bytes
1
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Serum metabolite profiling in Duchenne muscular dystrophy (DMD) may enable
discovery of valuable molecular markers for disease progression and
treatment response. Serum samples from 51 DMD patients from a natural
history study and 22 age-matched healthy volunteers were profiled using
liquid chromatography coupled to mass spectrometry (LC-MS) for discovery
of novel circulating serum metabolites associated with DMD. Fourteen
metabolites were found significantly altered (1% false discovery rate) in
their levels between DMD patients and healthy controls while adjusting for
age and study site and allowing for an interaction between disease status
and age. Increased metabolites included arginine, creatine and unknown
compounds at m/z of 357 and 312 while decreased metabolites included
creatinine, androgen derivatives and other unknown yet to be identified
compounds. Furthermore, the creatine to creatinine ratio is significantly
associated with disease progression in DMD patients. This ratio sharply
increased with age in DMD patients while it decreased with age in healthy
controls. Overall, this study yielded promising metabolic signatures that
could prove useful to monitor DMD disease progression and response to
therapies in the future.
Raw CDF files, sample information, code to process themThis is a zipped
directory. Once unzipped, it has the following directory structure: Neg
(directory), Pos (directory), DMD_Metabolomics_samples_files.csv,
process_data.R . The Neg and Pos directories each have a DMD directory and
a Normal directory, along with the files Annodiffre_neg.RData and
Annodiffre_pos.RData, respectively, which are generated by running the
code in process_data.R . The files in the DMD and Normal directories are
raw CDF files consisting of the samples from DMD patients and from healthy
(normal) controls, respectively. The Neg and Pos directories correspond to
the negative, respectively, positive modes. The sample information is
given in the DMD_Metabolomics_samples_files.csv file.data_for_PLOS_ONE.zip