A personalized pharmaco-epistatic network model of precision medicine

Li Feng; Wuyue Yang; Mengdong Ding; Luke Hou; Claudia Gragnoli; Christopher Griffin; Rongling Wu

doi:10.1016/j.drudis.2023.103608

A personalized pharmaco-epistatic network model of precision medicine

Drug Discov Today. 2023 Jul;28(7):103608. doi: 10.1016/j.drudis.2023.103608. Epub 2023 May 4.

Authors

Li Feng¹, Wuyue Yang², Mengdong Ding¹, Luke Hou³, Claudia Gragnoli⁴, Christopher Griffin⁵, Rongling Wu⁶

Affiliations

¹ Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China.
² Beijing Yanqi Lake Institute of Mathematical Sciences and Applications, Beijing 101408, China.
³ Ward Melville High School, East Setauket, NY 11733, USA.
⁴ Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA 17033, USA; Division of Endocrinology, Department of Medicine, Creighton University School of Medicine, Omaha, NE 68124, USA; Molecular Biology Laboratory, Bios Biotech Multi-Diagnostic Health Center, Rome 00197, Italy.
⁵ Applied Research Laboratory, The Pennsylvania State University, University Park, PA 16802, USA.
⁶ Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China; Beijing Yanqi Lake Institute of Mathematical Sciences and Applications, Beijing 101408, China; Yau Mathematical Sciences Center, Tsinghua University, Beijing 100084, China. Electronic address: ronglingwu@bimsa.cn.

PMID: 37149282
DOI: 10.1016/j.drudis.2023.103608

Abstract

Precision medicine, the utilization of targeted treatments to address an individual's disease, relies on knowledge about the genetic cause of that individual's drug response. Here, we present a functional graph (FunGraph) theory to chart comprehensive pharmacogenetic architecture for each and every patient. FunGraph is the combination of functional mapping - a dynamic model for genetic mapping and evolutionary game theory guiding interactive strategies. It coalesces all pharmacogenetic factors into multilayer and multiplex networks that fully capture bidirectional, signed and weighted epistasis. It can visualize and interrogate how epistasis moves in the cell and how this movement leads to patient- and context-specific genetic architecture in response to organismic physiology. We discuss the future implementation of FunGraph to achieve precision medicine.

Keywords: Epistasis; association studies; functional graph theory; functional mapping; genetic network; personalized medicine.

Publication types

Review

MeSH terms

Chromosome Mapping
Epistasis, Genetic*
Humans
Precision Medicine*