Evidence map›Paper›PMID 38755654›Full record

ArticleBMC medical genomics2024

Generalizability of polygenic prediction models: how is the R

Christian Staerk, Hannah Klinkhammer, Tobias Wistuba, Carlo Maj, Andreas Mayr

Abstract read
In one paragraph

Article in BMC medical genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. An introduction to polygenic scores - methodological basics and recent advances.Medizinische Genetik : Mitteilungsblatt des Berufsverbandes Medizinische Genetik e.V · 2026
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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

5 authors.

Christian StaerkDepartment of Medical Biometry, Informatics and Epidemiology, Medical Faculty, University of Bonn, Bonn, Germany. christian.staerk@uni-bonn.de.
Hannah KlinkhammerDepartment of Medical Biometry, Informatics and Epidemiology, Medical Faculty, University of Bonn, Bonn, Germany.
Tobias WistubaDepartment of Medical Biometry, Informatics and Epidemiology, Medical Faculty, University of Bonn, Bonn, Germany.
Carlo MajCenter for Human Genetics, University of Marburg, Marburg, Germany.
Andreas MayrDepartment of Medical Biometry, Informatics and Epidemiology, Medical Faculty, University of Bonn, Bonn, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPolygenic risk scores (PRS) quantify an individual's genetic predisposition for different traits and are expected to play an increasingly important role in personalized medicine. A crucial challenge in clinical practice is the generalizability and transferability of PRS models to populations with different ancestries. When assessing the generalizability of PRS models for continuous traits, the

methodsBased on large-scale genotype data from the UK Biobank, we compare three definitions of the

resultsOur analysis shows that the choice of the

conclusionsAwareness of the different definitions of the

Indexed as

Models, GeneticMultifactorial InheritanceGenetic Predisposition to DiseaseHumansPhenotypeCalibrationCoefficient of determinationPolygenic risk scoresPredictionR squared

Identifiers

PMID38755654
PMCPMC11100126

What Socratic holds

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LicenceCC BY
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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 Socratic graph.