A perspective on genetic and polygenic risk scores-advances and limitations and overview of associated tools

被引：3

作者：

Schwarzerova, Jana ^{[1
,2
]}

Hurta, Martin ^{[3
]}

Barton, Vojtech ^{[1
,4
]}

Lexa, Matej ^{[5
]}

Walther, Dirk ^{[6
]}

Provaznik, Valentine ^{[1
,7
]}

Weckwerth, Wolfram ^{[2
,8
]}

机构：

[1] Brno Univ Technol, Fac Elect Engn & Commun, Dept Biomed Engn, Tech 10, Brno 61600, Czech Republic

[2] Univ Vienna, Dept Funct & Evolutionary Ecol, Mol Syst Biol MOSYS, A-1010 Vienna, Austria

[3] Brno Univ Technol, Fac Informat Technol, Dept Comp Syst, Brno 61200, Czech Republic

[4] Masaryk Univ, RECETOX, Fac Sci, Kotlarska 2, Brno 62500, Czech Republic

[5] Masaryk Univ, Fac Informat, Botanicka 68a, Brno 60200, Czech Republic

[6] Max Planck Inst Mol Plant Physiol, D-14476 Potsdam, Germany

[7] Masaryk Univ, Fac Med, Dept Physiol, Brno 62500, Czech Republic

[8] Univ Vienna, Vienna Metabol Ctr VIME, A-1010 Vienna, Austria

来源：

BRIEFINGS IN BIOINFORMATICS | 2024年 / 25卷 / 03期

关键词：

polygenic risk score; genetic variations; GWAS; genomic prediction; genotype; phenotype; GENOME-WIDE ASSOCIATION; SUSCEPTIBILITY LOCI; SYSTEMS; ANCESTRY;

D O I：

10.1093/bib/bbae240

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Polygenetic Risk Scores are used to evaluate an individual's vulnerability to developing specific diseases or conditions based on their genetic composition, by taking into account numerous genetic variations. This article provides an overview of the concept of Polygenic Risk Scores (PRS). We elucidate the historical advancements of PRS, their advantages and shortcomings in comparison with other predictive methods, and discuss their conceptual limitations in light of the complexity of biological systems. Furthermore, we provide a survey of published tools for computing PRS and associated resources. The various tools and software packages are categorized based on their technical utility for users or prospective developers. Understanding the array of available tools and their limitations is crucial for accurately assessing and predicting disease risks, facilitating early interventions, and guiding personalized healthcare decisions. Additionally, we also identify potential new avenues for future bioinformatic analyzes and advancements related to PRS.

引用

页数：11

共 77 条

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