Evidence map›Paper›PMID 40004245›Full record

ArticleInternational journal of molecular sciences2025

A Genetic Test to Identify People at High Risk of Heart Failure.

Xintian Ge, Bek Brittain, Luke Dawson, Girish Dwivedi, David M Kaye, Grant Morahan

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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

6 authors.

Xintian GeCentre for Diabetes Research, Harry Perkins Institute of Medical Research, Nedlands, WA 6009, Australia.
Bek BrittainCentre for Diabetes Research, Harry Perkins Institute of Medical Research, Nedlands, WA 6009, Australia.
Luke DawsonHeart Failure Research Group, Baker Heart and Diabetes Institute, Melbourne, VIC 3004, Australia.
Girish DwivediCentre for Diabetes Research, Harry Perkins Institute of Medical Research, Nedlands, WA 6009, Australia.ORCID 0000-0003-0717-740X
David M KayeHeart Failure Research Group, Baker Heart and Diabetes Institute, Melbourne, VIC 3004, Australia.
Grant MorahanCentre for Diabetes Research, Harry Perkins Institute of Medical Research, Nedlands, WA 6009, Australia.

Funding

Medical Research Future Fund BMTH2_029
6 · The paper itself

Abstract

Earlier intervention may delay or prevent heart failure (HF), a widespread health problem. However, it is not currently possible to identify those who are most at risk, especially before the appearance of any clinical signs. This study presents the development and subsequent validation of a novel genetic test for predicting the risk of HF, utilizing data from three independent cohorts of Australian and US subjects. We developed a first-phase test using the Baker Biobank case-control cohort, identifying 41 genetic variants indicative of HF risk through genome-wide interaction and association analyses. Subsequently, a second-phase test was designed. This identified 29 additional single-nucleotide polymorphisms. The combination of these two tests resulted in an aggregate test with a high predictive accuracy, achieving an Area Under the Curve of 0.93 and a balanced accuracy of 0.89. High genetic risk subjects in the Baker Biobank cohort had an odds ratio of 533.2. The test's robustness was validated by applying it to data from the Busselton Health Study and the Atherosclerosis Risk in Communities cohorts, yielding, respectively, Areas Under the Curve of 0.83 and 0.72, a balanced accuracy of 0.76 and 0.67, and Odds Ratios of 12.3 and 4.6. These results highlight the critical role of genetic factors in the development of heart failure and demonstrate this test's potential as a significant tool for clinical HF risk prediction.

Indexed as

Genetic Predisposition to DiseaseGenetic TestingHeart FailureAgedAustraliaCase-Control StudiesFemaleGenome-Wide Association StudyHumansMaleMiddle AgedPolymorphism, Single NucleotideRisk Factorscomplex genetic diseasesgenetic riskheart failurepersonalized risk scoreprecision medicine

Identifiers

PMID40004245
PMCPMC11855781

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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 OpenQuestion graph.