Analysis of crucial molecules involved in herniated discs and degenerative disc disease

Network Pharmacological Dissection of the Mechanisms of Eucommiae Cortex-Achyranthis Radix Combination for Intervertebral Disc Herniation Treatment

Eucommiae cortex (EC) and Achyranthis radix (AR) are herbal medicines widely used in combination for the treatment of intervertebral disc herniation (IDH). The mechanisms of action of the herbal combination have not been understood from integrative and comprehensive points of view. By adopting network pharmacological methodology, we aimed to investigate the pharmacological properties of the EC-AR combination as a therapeutic agent for IDH at a systematic molecular level. Using the pharmacokinetic information for the chemical ingredients of the EC-AR combination obtained from the comprehensive herbal drug-associated databases, we determined its 31 bioactive ingredients and 68 IDH-related therapeutic targets. By analyzing their enrichment for biological functions, we observed that the targets of the EC-AR combination were associated with the regulation of angiogenesis; cytokine and chemokine activity; oxidative and inflammatory stress responses; extracellular matrix organization; immune response; and cellular processes such as proliferation, apoptosis, autophagy, differentiation, migration, and activation. Pathway enrichment investigation revealed that the EC-AR combination may target IDH-pathology-associated signaling pathways, such as those of cellular senescence and chemokine, neurotrophin, TNF, MAPK, toll-like receptor, and VEGF signaling, to exhibit its therapeutic effects. Collectively, these data provide mechanistic insights into the pharmacological activity of herbal medicines for the treatment of musculoskeletal diseases such as IDH.

DCGL v2.0: an R package for unveiling differential regulation from differential co-expression

Motivation

Differential co-expression analysis (DCEA) has emerged in recent years as a novel, systematic investigation into gene expression data. While most DCEA studies or tools focus on the co-expression relationships among genes, some are developing a potentially more promising research domain, differential regulation analysis (DRA). In our previously proposed R package DCGL v1.0, we provided functions to facilitate basic differential co-expression analyses; however, the output from DCGL v1.0 could not be translated into differential regulation mechanisms in a straightforward manner.

Results

To advance from DCEA to DRA, we upgraded the DCGL package from v1.0 to v2.0. A new module named “Differential Regulation Analysis” (DRA) was designed, which consists of three major functions: DRsort, DRplot, and DRrank. DRsort selects differentially regulated genes (DRGs) and differentially regulated links (DRLs) according to the transcription factor (TF)-to-target information. DRrank prioritizes the TFs in terms of their potential relevance to the phenotype of interest. DRplot graphically visualizes differentially co-expressed links (DCLs) and/or TF-to-target links in a network context. In addition to these new modules, we streamlined the codes from v1.0. The evaluation results proved that our differential regulation analysis is able to capture the regulators relevant to the biological subject.

Conclusions

With ample functions to facilitate differential regulation analysis, DCGL v2.0 was upgraded from a DCEA tool to a DRA tool, which may unveil the underlying differential regulation from the observed differential co-expression. DCGL v2.0 can be applied to a wide range of gene expression data in order to systematically identify novel regulators that have not yet been documented as critical.

Availability

DCGL v2.0 package is available at http://cran.r-project.org/web/packages/DCGL/index.html or at our project home page http://lifecenter.sgst.cn/main/en/dcgl.jsp.