Evidence map›Paper›PMID 38770718›Full record

ReviewBriefings in bioinformatics2024

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

Jana Schwarzerova, Martin Hurta, Vojtech Barton, Matej Lexa, Dirk Walther, Valentine Provaznik, Wolfram Weckwerth

Abstract readReview
In one paragraph

Review in Briefings in bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Jana SchwarzerovaDepartment of Biomedical Engineering, Faculty of Electrical Engineering and Communication, Brno University of Technology, Technicka 10, Brno 61600, Czechia.ORCID 0000-0003-2918-9313
Martin HurtaDepartment of Computer Systems, Faculty of Information Technology, Brno University of Technology, Brno 612 00, Czechia.ORCID 0000-0002-7915-8147
Vojtech BartonDepartment of Biomedical Engineering, Faculty of Electrical Engineering and Communication, Brno University of Technology, Technicka 10, Brno 61600, Czechia.ORCID 0000-0002-1918-2989
Matej LexaFaculty of Informatics, Masaryk University, Botanicka 68a, Brno 60200, Czech Republic.ORCID 0000-0002-4213-5259
Dirk WaltherMax-Planck-Institute of Molecular Plant Physiology, Potsdam 14476, Germany.ORCID 0000-0002-5755-9265
Valentine ProvaznikDepartment of Biomedical Engineering, Faculty of Electrical Engineering and Communication, Brno University of Technology, Technicka 10, Brno 61600, Czechia.ORCID 0000-0002-3422-7938
Wolfram WeckwerthMolecular Systems Biology (MOSYS), Department of Functional and Evolutionary Ecology, University of Vienna, Vienna 1010, Austria.ORCID 0000-0002-9719-6358

Funding

Brno University of Technology intra-university junior project FEKT/FIT-J-23-8274
6 · The paper itself

Abstract

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.

Indexed as

Genetic Predisposition to DiseaseMultifactorial InheritanceSoftwareComputational BiologyGenetic Risk ScoreGenome-Wide Association StudyHumansRisk AssessmentRisk Factorsgenetic variationsgenomic predictiongenotypeGWASphenotypepolygenic risk score

Identifiers

PMID38770718
PMCPMC11106636

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.