Dysregulated mechanisms underlying Duchenne muscular dystrophy from co-expression network preservation analysis.

TitleDysregulated mechanisms underlying Duchenne muscular dystrophy from co-expression network preservation analysis.
Publication TypeJournal Article
Year of Publication2015
AuthorsMukund K, Subramaniam S
JournalBMC Res Notes
Volume8
Pagination182
Date Published2015
ISSN1756-0500
Abstract

BACKGROUND: Duchenne Muscular Dystrophy (DMD) is an X-linked recessive disorder with its primary insult on the skeletal muscle. Severe muscle wasting, chronic inflammation and fibrosis characterize dystrophic muscle. Here we identify dysregulated pathways in DMD utilizing a co-expression network approach as described in Weighted Gene Co-expression Network Analysis (WGCNA). Specifically, we utilize WGCNA's "preservation" statistics to identify gene modules that exhibit a weak conservation of network topology within healthy and dystrophic networks. Preservation statistics rank modules based on their topological metrics such as node density, connectivity and separability between networks.

METHODS: Raw data for DMD was downloaded from Gene Expression Omnibus (GSE6011) and suitably preprocessed. Co-expression networks for each condition (healthy and dystrophic) were generated using the WGCNA library in R. Preservation of healthy network edges was evaluated with respect to dystrophic muscle and vice versa using WGCNA. Highly exclusive gene pairs for each of the low preserved modules within both networks were also determined using a specificity measure.

RESULTS: A total of 11 and 10 co-expressed modules were identified in the networks generated from 13 healthy and 23 dystrophic samples respectively. 5 out of the 11, and 4 out of the 10 modules were identified as exhibiting none-to-weak preservation. Functional enrichment analysis identified that these weakly preserved modules were highly relevant to the condition under study. For instance, weakly preserved dystrophic module D2 exhibited the highest fraction of genes exclusive to DMD. The highly specific gene pairs identified within these modules were enriched for genes activated in response to wounding and affect the extracellular matrix including several markers such as SPP1, MMP9 and ITGB2.

CONCLUSION: The proposed approach allowed us to identify clusters of genes that are non-randomly associated with the disease. Furthermore, highly specific gene pairs pointed to interactions between known markers of disease and identification of putative markers likely associated with disease. The analysis also helped identify putative novel interactions associated with the progression of DMD.

DOI10.1186/s13104-015-1141-9
PubMed URLhttp://www.ncbi.nlm.nih.gov/pubmed/25935398?dopt=Abstract
Alternate JournalBMC Res Notes
PubMed ID25935398
PubMed Central IDPMC4424514
Grant ListHL106579 / HL / NHLBI NIH HHS / United States
HL108735 / HL / NHLBI NIH HHS / United States
R01 HL106579 / HL / NHLBI NIH HHS / United States
R01 HL108735 / HL / NHLBI NIH HHS / United States
Track(s): 
Bioinformatics and Systems Biology