TY - JOUR
T1 - Integration of genetically regulated gene expression and pharmacological library provides therapeutic drug candidates
AU - Konuma, Takahiro
AU - Ogawa, Kotaro
AU - Okada, Yukinori
N1 - Publisher Copyright:
© 2021 The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: [email protected].
PY - 2021/2/1
Y1 - 2021/2/1
N2 - Approaches toward new therapeutics using disease genomics, such as genome-wide association study (GWAS), are anticipated. Here, we developed Trans-Phar [integration of transcriptome-wide association study (TWAS) and pharmacological database], achieving in silico screening of compounds from a large-scale pharmacological database (L1000 Connectivity Map), which have inverse expression profiles compared with tissue-specific genetically regulated gene expression. Firstly we confirmed the statistical robustness by the application of the null GWAS data and enrichment in the true-positive drug-disease relationships by the application of UK-Biobank GWAS summary statistics in broad disease categories, then we applied the GWAS summary statistics of large-scale European meta-analysis (17 traits; naverage = 201 849) and the hospitalized COVID-19 (n = 900 687), which has urgent need for drug development. We detected potential therapeutic compounds as well as anisomycin in schizophrenia (false discovery rate (FDR)-q = 0.056) and verapamil in hospitalized COVID-19 (FDR-q = 0.068) as top-associated compounds. This approach could be effective in disease genomics-driven drug development.
AB - Approaches toward new therapeutics using disease genomics, such as genome-wide association study (GWAS), are anticipated. Here, we developed Trans-Phar [integration of transcriptome-wide association study (TWAS) and pharmacological database], achieving in silico screening of compounds from a large-scale pharmacological database (L1000 Connectivity Map), which have inverse expression profiles compared with tissue-specific genetically regulated gene expression. Firstly we confirmed the statistical robustness by the application of the null GWAS data and enrichment in the true-positive drug-disease relationships by the application of UK-Biobank GWAS summary statistics in broad disease categories, then we applied the GWAS summary statistics of large-scale European meta-analysis (17 traits; naverage = 201 849) and the hospitalized COVID-19 (n = 900 687), which has urgent need for drug development. We detected potential therapeutic compounds as well as anisomycin in schizophrenia (false discovery rate (FDR)-q = 0.056) and verapamil in hospitalized COVID-19 (FDR-q = 0.068) as top-associated compounds. This approach could be effective in disease genomics-driven drug development.
UR - http://www.scopus.com/inward/record.url?scp=85106069940&partnerID=8YFLogxK
U2 - 10.1093/hmg/ddab049
DO - 10.1093/hmg/ddab049
M3 - Article
C2 - 33577681
AN - SCOPUS:85106069940
SN - 0964-6906
VL - 30
SP - 294
EP - 304
JO - Human Molecular Genetics
JF - Human Molecular Genetics
IS - 3-4
ER -