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Publication
The identification of gene expression profiles associated with progression of
human diabetic neuropathy.
Authors
Hur J, Sullivan KA, Pande M, Hong Y, Sima AA, Jagadish HV, Kretzler M, Feldman
EL
Submitted By
Eva Feldman on 8/1/2012
Status
Published
Journal
Brain : a journal of neurology
Year
2011
Date Published
11/1/2011
Volume : Pages
134 : 3222 - 3235
PubMed Reference
21926103
Abstract
Diabetic neuropathy is a common complication of diabetes. While multiple
pathways are implicated in the pathophysiology of diabetic neuropathy, there are
no specific treatments and no means to predict diabetic neuropathy onset or
progression. Here, we identify gene expression signatures related to diabetic
neuropathy and develop computational classification models of diabetic
neuropathy progression. Microarray experiments were performed on 50 samples of
human sural nerves collected during a 52-week clinical trial. A series of
bioinformatics analyses identified differentially expressed genes and their
networks and biological pathways potentially responsible for the progression of
diabetic neuropathy. We identified 532 differentially expressed genes between
patient samples with progressing or non-progressing diabetic neuropathy, and
found these were functionally enriched in pathways involving inflammatory
responses and lipid metabolism. A literature-derived co-citation network of the
differentially expressed genes revealed gene subnetworks centred on
apolipoprotein E, jun, leptin, serpin peptidase inhibitor E type 1 and
peroxisome proliferator-activated receptor gamma. The differentially expressed
genes were used to classify a test set of patients with regard to diabetic
neuropathy progression. Ridge regression models containing 14 differentially
expressed genes correctly classified the progression status of 92% of patients
(P < 0.001). To our knowledge, this is the first study to identify
transcriptional changes associated with diabetic neuropathy progression in human
sural nerve biopsies and describe their potential utility in classifying
diabetic neuropathy. Our results identifying the unique gene signature of
patients with progressive diabetic neuropathy will facilitate the development of
new mechanism-based diagnostics and therapies.
Investigators with authorship
Name
Institution
Eva Feldman
University of Michigan
Matthias Kretzler
University of Michigan
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Please acknowledge all posters, manuscripts or scientific materials that were generated in part or whole using funds from the Diabetic Complications Consortium(DiaComp) using the following text:
Financial support for this work provided by the NIDDK Diabetic Complications Consortium (RRID:SCR_001415, www.diacomp.org), grants DK076169 and DK115255
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