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Published on: January 16, 2019
A Genetic Test to Identify People at High Risk of Heart Failure
Xintian Ge1,2, Bek Brittain1, Luke Dawson3
1Centre for Diabetes Research, Harry Perkins Institute of Medical Research, Nedlands, WA 6009, Australia.
Insights
A new genetic test can identify individuals at high risk for heart failure (HF) before clinical signs appear. This breakthrough offers potential for earlier intervention and improved patient outcomes in cardiovascular disease management.
Area of Science:
- Cardiovascular Genetics
- Genomic Prediction
- Biomarker Discovery
Background:
- Heart failure (HF) is a significant global health burden.
- Current methods lack the ability to predict HF risk accurately before clinical manifestation.
- Early intervention strategies are crucial for managing and potentially preventing HF progression.
Purpose of the Study:
- To develop and validate a novel genetic test for predicting heart failure (HF) risk.
- To identify genetic variants associated with HF development.
- To assess the clinical utility of a comprehensive genetic risk prediction tool.
Main Methods:
- Genome-wide interaction and association analyses were performed on the Baker Biobank cohort.
- A two-phase genetic test was developed, identifying 41 and 29 genetic variants respectively.
- The aggregate test was validated across three independent cohorts: Baker Biobank, Busselton Health Study, and Atherosclerosis Risk in Communities.
Main Results:
- The aggregate genetic test demonstrated high predictive accuracy with an Area Under the Curve (AUC) of 0.93 and balanced accuracy of 0.89 in the development cohort.
- High genetic risk individuals in the Baker Biobank cohort showed a significantly elevated odds ratio (533.2) for HF.
- Validation in independent cohorts yielded AUCs of 0.83 and 0.72, with corresponding odds ratios of 12.3 and 4.6, confirming test robustness.
Conclusions:
- Genetic factors play a critical role in the pathogenesis of heart failure.
- The developed genetic test is a robust and accurate tool for predicting HF risk.
- This test holds significant potential for early clinical risk stratification and personalized HF prevention strategies.
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.
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