Differential co-expression network analysis for identification of functional modules in HIV infection and tubercolosis-HIV co-infection

Submitted: April 21, 2016
Accepted: September 15, 2016
Published: December 20, 2016
Abstract Views: 1580
PDF: 746
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Authors

Co-infection with tuberculosis (TB) is the preeminent cause of demise in human immunodeficiency virus (HIV) infected individuals. However, diagnosis of TB, particularly in the presence of an HIV co-infection, can be limiting owing to the high inaccuracy associated with conventional diagnostic strategies. Here we determine dysregulated pathways in TB-HIV co-infection and HIV infection utilizing coexpression networks. Primarily, we utilized preservation statistics to identify gene modules that exhibit a weak conservation of network topology within HIV infected and TB-HIV co-infected networks. Raw data was downloaded from Gene Expression Omnibus (GSE50834) and duly pre-processed. Co-expression networks for each condition (HIV infected and TB-HIV co-infected) were constructed independently. Preservation of HIV infected network edges was evaluated with respect to TB-HIV co-infected and vice versa using weighted correlation network analysis. Two out of the 22 modules were identified as exhibiting weak preservation in both conditions. Functional enrichment analysis identified that weakly preserved modules were pertinent to the condition under study. For instance, weakly preserved TBHIV co-infected module T1 enriched for genes associated with mitochondrion exhibited the highest fraction of gene interaction pairs exclusive to TB-HIV co-infection. Concisely, we illustrated the application of using preservation statistics to detect modules functionally linked with dysregulated pathways in disease, as exemplified by the mitochondrion module T1. Our analyses discovered gene clusters that are non-randomly linked with the disease. Highly specific gene pairs pointed to interactions between known markers of disease and favoured identification of possible markers that are likely to be associated with the disease.

Dimensions

Altmetric

PlumX Metrics

Downloads

Download data is not yet available.

Citations

How to Cite

Jha, M., Gupta, A., Singh, S., & Pandey, K. M. (2016). Differential co-expression network analysis for identification of functional modules in HIV infection and tubercolosis-HIV co-infection. Journal of Biological Research - Bollettino Della Società Italiana Di Biologia Sperimentale, 89(2). https://doi.org/10.4081/jbr.2016.5950