Navigating personalized medicine dependent on modular flexibility

Detection of an anti-angina therapeutic module in the effective population treated by a multi-target drug Danhong injection: a randomized trial

It’s a challenge for detecting the therapeutic targets of a polypharmacological drug from variations in the responsed networks in the differentiated populations with complex diseases, as stable coronary heart disease. Here, in an adaptive, 31-center, randomized, double-blind trial involving 920 patients with moderate symptomatic stable angina treated by 14-day Danhong injection(DHI), a kind of polypharmacological drug with high quality control, or placebo (0.9% saline), with 76-day following-up, we firstly confirmed that DHI could increase the proportion of patients with clinically significant changes on angina-frequency assessed by Seattle Angina Questionnaire (ΔSAQ-AF ≥ 20) (12.78% at Day 30, 95% confidence interval [CI] 5.86–19.71%, P = 0.0003, 13.82% at Day 60, 95% CI 6.82–20.82%, P = 0.0001 and 8.95% at Day 90, 95% CI 2.06–15.85%, P = 0.01). We also found that there were no significant differences in new-onset major vascular events (P = 0.8502) and serious adverse events (P = 0.9105) between DHI and placebo. After performing the RNA sequencing in 62 selected patients, we developed a systemic modular approach to identify differentially expressed modules (DEMs) of DHI with the Z_summary value less than 0 compared with the control group, calculated by weighted gene co-expression network analysis (WGCNA), and sketched out the basic framework on a modular map with 25 functional modules targeted by DHI. Furthermore, the effective therapeutic module (ETM), defined as the highest correlation value with the phenotype alteration (ΔSAQ-AF, the change in SAQ-AF at Day 30 from baseline) calculated by WGCNA, was identified in the population with the best effect (ΔSAQ-AF ≥ 40), which is related to anticoagulation and regulation of cholesterol metabolism. We assessed the modular flexibility of this ETM using the global topological D value based on Euclidean distance, which is correlated with phenotype alteration (r²: 0.8204, P = 0.019) by linear regression. Our study identified the anti-angina therapeutic module in the effective population treated by the multi-target drug. Modular methods facilitate the discovery of network pharmacological mechanisms and the advancement of precision medicine. (ClinicalTrials.gov identifier: NCT01681316).

IMCC: A Novel Quantitative Approach Revealing Variation of Global Modular Map and Local Inter-Module Coordination Among Differential Drug's Targeted Cerebral Ischemic Networks

Stroke is a common disease characterized by multiple genetic dysfunctions. In this complex disease, detecting the strength of inter-module coordination (genetic community interaction) and subsequent modular rewiring is essential to characterize the reactive biosystematic variation (biosystematic perturbation) brought by multiple-target drugs, whose effects are achieved by hitting on a series of targets (target profile) jointly. Here, a quantitative approach for inter-module coordination and its transition, named as IMCC, was developed. Applying IMCC to mouse cerebral ischemia–related gene microarray, we investigated a holistic view of modular map and its rewiring from ischemic stroke to drugs (baicalin, BA; ursodeoxycholic acid, UA; and jasminoidin, JA) perturbation states and locally identified the cooperative pathological module pair and its dissection. Our result suggested the global modular map in cerebral ischemia exhibited a characteristic “core–periphery” architecture, and this architecture was rewired by the effective drugs heterogeneously: BA and UA converged modules into an intensively connected integrity, whereas JA diverged partial modules and widened the remaining inter-module paths. Locally, the PMP dissociation brought by drugs contributed to the reversion of the pathological condition: the focus of the cellular function shift from survival after nervous system injury into development and repair, including neurotrophin regulation, hormone releasing, and chemokine signaling activation. The core targets and mechanisms were validated by in vivo experiments. Overall, our result highlights the holistic inter-module coordination rearrangement rather than a target or a single module that brings phenotype alteration. This strategy may lead to systematically explore detailed variation of inter-module pharmacological action mode of multiple-target drugs, which is the principal problem of module pharmacology for network-based drug discovery.

Confirming an integrated pathology of diabetes and its complications by molecular biomarker-target network analysis

Despite ongoing research into diabetes and its complications, the underlying molecular associations remain to be elucidated. The systematic identification of molecular interactions in associated diseases may be approached using a network analysis strategy. The biomarker-target interrelated molecules associated with diabetes and its complications were identified via the Comparative Toxicogenomics Database (CTD); the Search Tool for Recurring Instances of Neighboring Genes was utilized for network construction. Functional enrichment analysis was performed with Database for Annotation, Visualization and Integrated Discovery software to investigate connections between diabetes and its complications. A total of 142 (including 122 biomarkers, 10 therapeutic targets and 10 overlapping molecules) biomarker-target interrelated molecules associated with diabetes and its complications were identified via the CTD database, and analysis of the network yielded 1,087 biological processes and fifteen Kyoto Encyclopedia of Genes and Genomes pathways with significant P‑values. Various critical aspects of the networks were examined in the present study: a) Intermolecular horizontal and vertical combinations in biomarkers and therapeutic targets associated with diabetes and its complicationb) network topology properties associated with molecular pathological responsec) contribution of key molecules to integrated regulation; and d) crosstalk between multiple pathways. Based on a multi-dimensional analysis, it was concluded that the integrated molecular pathological development of diabetes and its complications does not proceed randomly, which suggests a requirement for integrated, multi-target intervention.

Multi-hierarchical profiling: an emerging and quantitative approach to characterizing diverse biological networks

Multi-hierarchical profiling may offer valuable insights into the structural stability and functional direction of biological networks in cellular development, pathological process and disease variation. Owing to the emergence of several new techniques, such as bioinformatics for omics data, structural biology and structural bioinformatics, the pace of network hierarchical research has accelerated a lot in recent years. Here, we discuss and compare the techniques available for quantifying multilevel hierarchies, with a focus on their features, capabilities and drawbacks when used for different applications. Then, we classify these methods into three types: topological spatial-scales, multilevel hierarchical control and feature ordering. We observe that challenges and limitations do exist in functional hierarchical identification. And, we also provide useful suggestions on how to analyze the dynamic data of complex network studies.

System-wide assembly of pathways and modules hierarchically reveal metabolic mechanism of cerebral ischemia

The relationship between cerebral ischemia and metabolic disorders is poorly understood, which is partly due to the lack of comparative fusing data for larger complete systems and to the complexity of metabolic cascade reactions. Based on the fusing maps of comprehensive serum metabolome, fatty acid and amino acid profiling, we identified 35 potential metabolic biomarkers for ischemic stroke. Our analyses revealed 8 significantly altered pathways by MetPA (Metabolomics Pathway Analysis, impact score >0.10) and 15 significantly rewired modules in a complex ischemic network using the Markov clustering (MCL) method; all of these pathways became more homologous as the number of overlapping nodes was increased. We then detected 24 extensive pathways based on the total modular nodes from the network analysis, 12 of which were new discovery pathways. We provided a new perspective from the viewpoint of abnormal metabolites for the overall study of ischemic stroke as well as a new method to simplify the network analysis by selecting the more closely connected edges and nodes to build a module map of stroke.

Phenotype-dependent alteration of pathways and networks reveals a pure synergistic mechanism for compounds treating mouse cerebral ischemia

AIM

Our previous studies have showed that ursodeoxycholic acid (UA) and jasminoidin (JA) effectively reduce cerebral infarct volume in mice. In this study we explored the pure synergistic mechanism of these compounds in treatment of mouse cerebral ischemia, which was defined as synergistic actions specific for phenotype variations after excluding interference from ineffective compounds.

METHODS

Mice with focal cerebral ischemia were treated with UA, JA or a combination JA and UA (JU). Concha margaritifera (CM) was taken as ineffective compound. Cerebral infarct volume of the mice was determined, and the hippocampi were taken for microarray analysis. Particular signaling pathways and biological functions were enriched based on differentially expressed genes, and corresponding networks were constructed through Ingenuity Pathway Analysis.

RESULTS

In phenotype analysis, UA, JA, and JU significantly reduced the ischemic infarct volume with JU being superior to UA or JA alone, while CM was ineffective. As a result, 4 pathways enriched in CM were excluded. Core pathways in the phenotype-positive groups (UA or JA) were involved in neuronal homeostasis and neuropathology. JU-contributing pathways included all UA-contributing and the majority (71.7%) of JA-contributing pathways, and 10 new core pathways whose effects included inflammatory immunity, apoptosis and nervous system development. The functions of JU group included all functions of JA group, the majority (93.1%) of UA-contributing functions, and 3 new core functions, which focused on physiological system development and function.

CONCLUSION

The pure synergism between UA and JA underlies 10 new core pathways and 3 new core functions, which are involved in inflammation, immune responses, apoptosis and nervous system development.