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


Journal

Briefings in bioinformatics
ISSN: 1477-4054
Titre abrégé: Brief Bioinform
Pays: England
ID NLM: 100912837

Informations de publication

Date de publication:
27 Mar 2024
Historique:
received: 03 10 2023
revised: 14 04 2024
accepted: 03 05 2024
medline: 21 5 2024
pubmed: 21 5 2024
entrez: 21 5 2024
Statut: ppublish

Résumé

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.

Identifiants

pubmed: 38770718
pii: 7676477
doi: 10.1093/bib/bbae240
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Brno University of Technology intra-university junior project
ID : FEKT/FIT-J-23-8274

Informations de copyright

© The Author(s) 2024. Published by Oxford University Press.

Auteurs

Jana Schwarzerova (J)

Department of Biomedical Engineering, Faculty of Electrical Engineering and Communication, Brno University of Technology, Technicka 10, Brno 61600, Czechia.
Molecular Systems Biology (MOSYS), Department of Functional and Evolutionary Ecology, University of Vienna, Vienna 1010, Austria.

Martin Hurta (M)

Department of Computer Systems, Faculty of Information Technology, Brno University of Technology, Brno 612 00, Czechia.

Vojtech Barton (V)

Department of Biomedical Engineering, Faculty of Electrical Engineering and Communication, Brno University of Technology, Technicka 10, Brno 61600, Czechia.
RECETOX, Faculty of Science, Masaryk University, Kotlarska 2, Brno 62500, Czech Republic.

Matej Lexa (M)

Faculty of Informatics, Masaryk University, Botanicka 68a, Brno 60200, Czech Republic.

Dirk Walther (D)

Max-Planck-Institute of Molecular Plant Physiology, Potsdam 14476, Germany.

Valentine Provaznik (V)

Department of Biomedical Engineering, Faculty of Electrical Engineering and Communication, Brno University of Technology, Technicka 10, Brno 61600, Czechia.
Department of Physiology, Faculty of Medicine, Masaryk University, Brno 62500, Czech Republic.

Wolfram Weckwerth (W)

Molecular Systems Biology (MOSYS), Department of Functional and Evolutionary Ecology, University of Vienna, Vienna 1010, Austria.
Vienna Metabolomics Center (VIME), University of Vienna, Vienna 1010, Austria.

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Classifications MeSH