Evidence mapPaperPMID 40186687Full record

ReviewDiabetologia2025

Clinical use of polygenic scores in type 2 diabetes: challenges and possibilities.

Rashmi B Prasad, Liisa Hakaste, Tiinamaija Tuomi

Abstract readReview
In one paragraph

Review in Diabetologia, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Trial
  2. Review
  3. Review
  4. Review
  5. Review
  6. Article
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.

Rashmi B PrasadLund University Diabetes Centre, Department of Clinical Sciences, Genetics and Diabetes, CRC, Lund University, Malmö, Sweden. rashmi.prasad@med.lu.se.ORCID http://orcid.org/0000-0002-4400-6741
Liisa HakasteInstitute for Molecular Medicine Finland (FIMM), Helsinki University, Helsinki, Finland.ORCID http://orcid.org/0000-0001-9212-3873
Tiinamaija TuomiLund University Diabetes Centre, Department of Clinical Sciences, Genetics and Diabetes, CRC, Lund University, Malmö, Sweden.ORCID http://orcid.org/0000-0002-8306-6202

Funding

Diabetesfonden DIA2023-847EFSD/Lilly European Diabetes Research Programme 2022 2022Folkhälsan Research Foundation, as well as The Academy of Finland and University of Helsinki 312072Folkhälsan Research Foundation, as well as The Academy of Finland and University of Helsinki 336822Folkhälsan Research Foundation, as well as The Academy of Finland and University of Helsinki 336826Hjelt Foundations 2023Vetenskapsrådet 2021-02623
6 · The paper itself

Abstract

Resulting from a combination of genetic and environmental factors, type 2 diabetes is highly heterogeneous in manifestation and disease progression, with the only common feature being chronic hyperglycaemia. In spite of vigorous efforts to elucidate the pathogenetic origins and natural course of the disease, there is still a lack of biomarkers and tools for prevention, disease stratification and treatment. Genome-wide association studies have reported over 1200 variants associated with type 2 diabetes, and the decreased cost of generating genetic data has facilitated the development of polygenic scores for estimating an individual's genetic disease risk based on combining effects from most-or all-genetic variants. In this review, we summarise the current knowledge on type 2 diabetes-related polygenic scores in different ancestries and outline their possible clinical role. We explore the potential applicability of type 2 diabetes polygenic scores to quantify genetic liability for prediction, screening and risk stratification. Given that most genetic risk loci are determined from populations of European origin while other ancestries are under-represented, we also discuss the challenges around their global applicability. To date, the potential for clinical utility of polygenic scores for type 2 diabetes is limited, with such scores outperformed by clinical measures. In the future, rather than predicting risk of type 2 diabetes, the value of polygenic scores may be in stratification of the severity of disease (risk for comorbidities) and treatment response, in addition to aiding in dissecting the pathophysiological mechanisms involved.

Indexed as

Diabetes Mellitus, Type 2Multifactorial InheritanceGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansAncestriesComorbiditiesGenetic riskMechanismsPolygenic scoresPredictionReviewScreeningSubtypesType 2 diabetes

Identifiers

PMID40186687
PMCPMC12177005

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.