Evidence mapPaperPMID 42416883Full record

ArticleMedizinische Genetik : Mitteilungsblatt des Berufsverbandes Medizinische Genetik e.V2026

An introduction to polygenic scores - methodological basics and recent advances.

Hannah Klinkhammer, Andreas Mayr, Carlo Maj

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In one paragraph

Article in Medizinische Genetik : Mitteilungsblatt des Berufsverbandes Medizinische Genetik e.V, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Hannah KlinkhammerMarburg University Institute for Medical Biometry and Statistics Hans-Meerwein-Str. 6 35032 Marburg Germany.ORCID https://orcid.org/0000-0003-3752-1275
Andreas MayrMarburg University Institute for Medical Biometry and Statistics Hans-Meerwein-Str. 6 35032 Marburg Germany.ORCID https://orcid.org/0000-0001-7106-9732
Carlo MajMarburg University Center for Human Genetics Baldingerstr. 35043 Marburg Germany.ORCID https://orcid.org/0000-0002-9559-1725

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Polygenic scores (PGS) allow the estimation of genetic predisposition to complex diseases and traits. Based on results from genome-wide association studies (GWAS) and data from large deeply phenotyped population biobanks, numerous PGS have been developed in recent years. These scores summarize the combined effects of many genetic variants and can support risk stratification for multifactorial diseases based on an individual's genetic susceptibility. In this review, we introduce the basic principles and methods of PGS and explain how they are generated and applied. We outline their potential translational role, particularly in the context of precision medicine and personalized risk stratification for preventive measures, in combination with established clinical risk factors. At the same time, we discuss important limitations, including limited generalizability across populations and the issue of missing heritability. Finally, we highlight current methodological developments and future perspectives for the integration of PGS into clinical practice.

Identifiers

PMID42416883
PMCPMC13340550

What Socratic holds

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Registered trials

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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.