Systems biology or pathway-based data analysis approaches allow the identification of networks of biological entities that may collectively define mechanisms and phenotypes, especially as they relate to disease. Herein, we applied an integrative systems biology workflow to hypothesize clinically relevant biomarkers and drugs targets for Alzheimer's disease.1 Our workflow included several in silico approaches that integrate the prioritization of disease gene signatures, the analysis of disease-gene pathways and networks, and the Ranking of putative drug targets based on their novelty scores (ie, evaluating complete novelty, condition novelty or evidence of early development). We foresee this workflow as a universal tool for the prioritization of drug targets and biomarkers in complex diseases including, cancer, diabetes and many neurodiseases.
In this session, we will be using MetaCore to compare and analyze the differentially expressed genes (DEGs) in 6 brain regions of Alzheimer's disease patients calculated from the gene expression profiles reported in Gene Expression Omnibus (GEO) dataset GSE5281. Next, we will apply Causal Reasoning in MetaCore Key Pathway Advisor (MetaCore KPA) to identify upstream regulatory hubs that could be prioritized drug targets and / or biomarkers. The gene and protein hits identified from the upstream key hub predictions and downstream enrichment analyzes will be integrated and analyzed using the network building tools available in MetaCore to understand the underlying mechanisms. Finally, the prioritized hypotheses will be evaluated and putative drug targets will be ranked based on their novelty scores, using the Drug Research Advisor-Target Druggability (DRA-TD) .2 At the end of this session we will be able to answer the following Key questions:
• What pathways and process networks are potentially disrupted in Alzheimer's disease?
• What are the key regulatory hubs that are potentially activated or inhibited in Alzheimer's disease?
• How to integrate results from upstream and downstream analyzes to generate higher confidence, clinically-relevant hypotheses about drug targets and biomarkers?
• How to evaluate the resulting hypotheses and score putative drug targets?
1) Hajjo, R & Willis, C. Systems biology approaches to omics data analysis in complex diseases. 253rd Am Chem Soc (ACS) Natl Meet (April 2-6, San Francisco) 2017, Abst BIOT 461.
2) Drug research Advisor, 2017.
Video credits to LS Education YouTube channel