Development and Implementation of Polygenic Risk Score in Vietnamese Population

  • Nguyễn Trần Thế Hùng Department of Computational Biomedicine, Vingroup Big Data Institute, Hanoi
  • Lê Đức Hậu Department of Computational Biomedicine, Vingroup Big Data Institute, Hanoi
DOI: https://doi.org/10.32913/mic-ict-research.v2019.n2.893
Keywords: Genetic, clinical, single nucleotide polymoyphism (SNP), polygenic risk score (PRS)

Abstract

Recent technological advancements and availability of genetic databases have facilitated the integration of genetic factors into risk prediction models. A Polygenic Risk Score (PRS) combines the effect of many Single Nucleotide Polymorphisms (SNP) into a single score. This score has lately been shown to have a clinically predictive value in various common diseases. Some clinical interpretations of PRS are summarized in this review for coronary artery disease, breast cancer, prostate cancer, diabetes mellitus, and Alzheimer’s disease. While these findings gave support to the implementation of PRS in clinical settings, the populations of interest were derived mainly from European ancestry. Therefore, applying these findings to non-European ancestry (Vietnamese in this context) requires many efforts and cautions. This review aims to articulate the evidence supporting the clinical use of PRS, the concepts behind the validity of PRS, approach to implement PRS in Vietnamese population, and cautions in selecting methods and thresholds to develop an appropriate PRS.

Author Biographies

Nguyễn Trần Thế Hùng, Department of Computational Biomedicine, Vingroup Big Data Institute, Hanoi

Nguyen Tran The Hung received his doctor of medicine degree from Universities of Medicine and Pharmacy of Ho Chi Minh city (Viet Nam) in 2016. He then got a master degree in biomedical science from China Medical Universities (Taichung, Taiwan) in 2019. His research field is human genetic and diabetes mellitus. He worked briefly as a pediatrician before pursuing his career in academia as a research scientist at Vingroup Big Data Institute from 2019 until now. His thesis on type 2 diabetic nephropathy and the application of polygenic risk score made him believe in the potential impact that genetic research can make in healthcare.

Lê Đức Hậu, Department of Computational Biomedicine, Vingroup Big Data Institute, Hanoi

Le Duc Hau obtained his PhD degree in Bioinformatics from University of Ulsan, Republic of Korea in 2012. He is now leading the Department of Computational Biomedicine, Vingroup Big Data Institute, Vietnam. He has been focusing on proposing computational methods for disease- and drug-related problems in personalized medicine, especially on identification of diseaseassociated biomarkers, prediction of drug targets and response. In parallel, he has been developed bioinformatics tools. So far, he has been published more than fifty papers in well-recognized journals and conferences, nearly a half of those are in ISI-indexed journals. In addition, he has been a member of program committees and reviewer of several international conferences/journals. Moreover, he is a principal investigator and a key member of some national/ministry-level projects. Specially, he is the principal investigator of the biggest genome project in Vietnam (i.e., building databases of genomic variants for Vietnamese population). Finally, he has been collaborating with some well-recognized international research institutes.

Published
2019-12-31
Issue
Vol 2019 No 2
Section
Selected Articles