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Genetic Prediction of Risk of Common Diseases

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Genetics and Genomics".

Deadline for manuscript submissions: 20 September 2025 | Viewed by 1183

Special Issue Editor


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Guest Editor
Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Nedlands, Perth, WA 6009, Australia
Interests: type 1 diabetes; immune tolerance; monoclonal antibodies; asthma; obesity; demyelinating diseases; cardiovascular disease; malaria

Special Issue Information

Dear Colleagues,

Common diseases, such as cancer, heart disease, diabetes, and dementia, affect millions of people and impose billions of dollars in costs on national health care budgets. These diseases have a complex genetic basis, and now hundreds of genetic variants have been identified that interact with each other and environmental factors to mediate susceptibility. However, the individual impact of these variants on disease risk is too low to be clinically useful. Polygenic risk scores and similar approaches have been employed to combine variants with the aim of developing more useful predictive tests. This Special Issue publishes reports of the latest advances in complex genetic analyses to define genetic signatures that can identify individuals at a higher or lower risk of suffering these diseases.

Dr. Grant Morahan
Guest Editor

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Keywords

  • complex genetic diseases
  • cancer
  • heart disease
  • diabetes
  • dementia
  • polygenic risk score
  • genetic risk signatures

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Published Papers (1 paper)

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Research

14 pages, 904 KiB  
Article
A Genetic Test to Identify People at High Risk of Heart Failure
by Xintian Ge, Bek Brittain, Luke Dawson, Girish Dwivedi, David M. Kaye and Grant Morahan
Int. J. Mol. Sci. 2025, 26(4), 1782; https://doi.org/10.3390/ijms26041782 - 19 Feb 2025
Viewed by 920
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Genetic Prediction of Risk of Common Diseases)
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