A practical guideline of genomics-driven drug discovery in the era of global biobank meta-analysis

Shinichi Namba; Takahiro Konuma; Kuan-Han Wu; Wei Zhou; Global Biobank Meta-analysis Initiative; Yukinori Okada

doi:10.1016/j.xgen.2022.100190

A practical guideline of genomics-driven drug discovery in the era of global biobank meta-analysis

Cell Genom. 2022 Oct 12;2(10):100190. doi: 10.1016/j.xgen.2022.100190.

Authors

Shinichi Namba¹, Takahiro Konuma^{1

2}, Kuan-Han Wu³, Wei Zhou^{4

5}; Global Biobank Meta-analysis Initiative; Yukinori Okada^{1

6

7

8

9

10}

Affiliations

¹ Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita 565-0871, Japan.
² Central Pharmaceutical Research Institute, Japan Tobacco Inc., Takatsuki 569-1125, Japan.
³ Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
⁴ Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
⁵ Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
⁶ Department of Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8654, Japan.
⁷ Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan.
⁸ Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita 565-0871, Japan.
⁹ Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita 565-0871, Japan.
¹⁰ Center for Infectious Disease Education and Research (CiDER), Osaka University, Suita 565-0871, Japan.

Abstract

Genomics-driven drug discovery is indispensable for accelerating the development of novel therapeutic targets. However, the drug discovery framework based on evidence from genome-wide association studies (GWASs) has not been established, especially for cross-population GWAS meta-analysis. Here, we introduce a practical guideline for genomics-driven drug discovery for cross-population meta-analysis, as lessons from the Global Biobank Meta-analysis Initiative (GBMI). Our drug discovery framework encompassed three methodologies and was applied to the 13 common diseases targeted by GBMI (N _mean = 1,329,242). Individual methodologies complementarily prioritized drugs and drug targets, which were systematically validated by referring previously known drug-disease relationships. Integration of the three methodologies provided a comprehensive catalog of candidate drugs for repositioning, nominating promising drug candidates targeting the genes involved in the coagulation process for venous thromboembolism and the interleukin-4 and interleukin-13 signaling pathway for gout. Our study highlighted key factors for successful genomics-driven drug discovery using cross-population meta-analyses.

Keywords: Mendelian randomization; cross-population meta-analysis; gene prioritization; genetically regulated gene expression; genome-wide association study; genomics-driven drug discovery.