TY - JOUR
T1 - Systems pharmacology-based approach of connecting disease genes in genome-wide association studies with traditional Chinese medicine
AU - Kim, Jihye
AU - Yoo, Minjae
AU - Shin, Jimin
AU - Kim, Hyunmin
AU - Kang, Jaewoo
AU - Tan, Aik Choon
N1 - Funding Information:
The authors thank the Tan Lab members for their useful comments on this manuscript. This work is partly supported by the David F. and Margaret T. Grohne Family Foundation.
Publisher Copyright:
Copyright © 2018 Jihye Kim et al.
PY - 2018
Y1 - 2018
N2 - Traditional Chinese medicine (TCM) originated in ancient China has been practiced over thousands of years for treating various symptoms and diseases. However, the molecular mechanisms of TCM in treating these diseases remain unknown. In this study, we employ a systems pharmacology-based approach for connecting GWAS diseases with TCM for potential drug repurposing and repositioning. We studied 102 TCM components and their target genes by analyzing microarray gene expression experiments. We constructed disease-gene networks from 2558 GWAS studies. We applied a systems pharmacology approach to prioritize disease-target genes. Using this bioinformatics approach, we analyzed 14,713 GWAS disease-TCM-target gene pairs and identified 115 disease-gene pairs with q value < 0.2. We validated several of these GWAS disease-TCM-target gene pairs with literature evidence, demonstrating that this computational approach could reveal novel indications for TCM. We also develop TCM-Disease web application to facilitate the traditional Chinese medicine drug repurposing efforts. Systems pharmacology is a promising approach for connecting GWAS diseases with TCM for potential drug repurposing and repositioning. The computational approaches described in this study could be easily expandable to other disease-gene network analysis.
AB - Traditional Chinese medicine (TCM) originated in ancient China has been practiced over thousands of years for treating various symptoms and diseases. However, the molecular mechanisms of TCM in treating these diseases remain unknown. In this study, we employ a systems pharmacology-based approach for connecting GWAS diseases with TCM for potential drug repurposing and repositioning. We studied 102 TCM components and their target genes by analyzing microarray gene expression experiments. We constructed disease-gene networks from 2558 GWAS studies. We applied a systems pharmacology approach to prioritize disease-target genes. Using this bioinformatics approach, we analyzed 14,713 GWAS disease-TCM-target gene pairs and identified 115 disease-gene pairs with q value < 0.2. We validated several of these GWAS disease-TCM-target gene pairs with literature evidence, demonstrating that this computational approach could reveal novel indications for TCM. We also develop TCM-Disease web application to facilitate the traditional Chinese medicine drug repurposing efforts. Systems pharmacology is a promising approach for connecting GWAS diseases with TCM for potential drug repurposing and repositioning. The computational approaches described in this study could be easily expandable to other disease-gene network analysis.
UR - http://www.scopus.com/inward/record.url?scp=85056139132&partnerID=8YFLogxK
U2 - 10.1155/2018/7697356
DO - 10.1155/2018/7697356
M3 - Article
AN - SCOPUS:85056139132
VL - 2018
JO - International Journal of Genomics
JF - International Journal of Genomics
SN - 2314-436X
M1 - 7697356
ER -