New DNA test predicts dangerous heart rhythms early
A powerful new genetic test reveals hidden heart rhythm dangers before they strike.
- Date:
- November 17, 2025
- Source:
- Northwestern University
- Summary:
- Scientists at Northwestern Medicine have developed a new genetic risk score that predicts who is most likely to experience irregular or dangerous heart rhythms. The test merges several types of genetic analysis into one powerful model, offering doctors a clearer way to spot risk early. Researchers believe this “genetic roadmap” could transform how conditions like AFib are detected and prevented. It may also help shape targeted therapies tailored to a person’s unique DNA.
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Key Points
- Researchers used whole genome sequencing to bring together monogenic and polygenic testing, two methods that are usually separated in both research and clinical practice.
- Experts say many more physicians should be using genetic testing, although a large portion of the medical workforce is not yet trained to interpret it.
- The results provide an early foundation for creating targeted treatments tailored to each person's unique genetic profile.
New Genetic Approach to Predicting Dangerous Heart Rhythms
In a new study from Northwestern Medicine, researchers have created a more refined genetic risk score that helps determine whether a person is likely to develop arrhythmia, a condition in which the heart beats irregularly. Arrhythmias can lead to serious medical problems, including atrial fibrillation (AFib) and sudden cardiac death.
The team reports that this improved method strengthens the accuracy of heart disease risk prediction while also offering a broad framework for genetic testing. According to the scientists, the same strategy could be adapted to assess other complex, genetically influenced conditions such as cancer, Parkinson's Disease and autism.
Building a More Complete Genetic Picture
"It's a very cool approach in which we are combining rare gene variants with common gene variants and then adding in non-coding genome information. To our knowledge, no one has used this comprehensive approach before, so it's really a roadmap of how to do that," said co-corresponding author Dr. Elizabeth McNally, director of the Center for Genetic Testing and a professor of medicine in the division of cardiology and of biochemistry and molecular genetics at Northwestern University Feinberg School of Medicine.
The researchers say their findings could support the development of targeted treatments shaped around an individual's full genetic profile. They also note that this type of analysis may allow clinicians to identify people at risk long before any symptoms arise.
The study, which analyzed data from 1,119 participants, was published on November 11 in Cell Reports Medicine.
Integrating Three Major Genetic Testing Methods
Current genetic testing typically falls into one of three separate categories:
- Monogenic testing: Identifies rare mutations in a single gene, similar to spotting a typo in a single word.
- Polygenic testing: Looks at many common gene variants to estimate overall risk, similar to examining the tone of a chapter.
- Genome sequencing: Reads the complete genetic code, much like reviewing an entire book.
"Genetic researchers, companies and geneticists often operate in silos," McNally said. "The companies that offer gene panel testing are not the same ones that provide polygenic risk scores."
In this study, the team combined information from all three genetic sources to produce a fuller view of disease risk. This integrated method uncovers rare mutations, evaluates cumulative genetic effects and reveals subtle patterns across the entire genome.
"When you sequence the whole genome, you can say, 'Let me look at this cardiomyopathy gene component, the gene panel and the polygenic component.' By combining the data together, you get a very high odds ratio of identifying who is at highest risk, and that's where we think this approach can really improve upon what is currently used," McNally said.
Why Physicians Need Greater Access to Genetic Testing
Cardiologists usually assess heart risk based on symptoms, family history and diagnostic tools such as EKGs, echocardiograms and MRIs. McNally said she also incorporates genetic testing into her patient evaluations.
"It helps me manage that patient better, know who's at greatest risk, and if we think the risk is really high, we'll recommend defibrillators for patients like that," McNally said. "Knowledge is power."
Despite the benefits, genetic testing remains underused. McNally said that only an estimated 1 to 5% of people who would benefit from genetic testing actually receive it. Even within cancer care, where genetic links are widely recognized, only 10 to 20% of eligible patients undergo testing.
"We need to improve uptake," McNally said. "The biggest challenge is a workforce that isn't trained in how to use genetic testing. As polygenic risk scores become more common, our approach will become even more valuable."
How Researchers Carried Out the Study
The research team enrolled 523 people diagnosed with arrhythmias, some of whom also had heart failure. They thoroughly reviewed each participant's records, including data directly from implanted devices, to confirm the diagnoses. Afterward, the scientists sequenced each person's genome and used both monogenic and polygenic testing to calculate a risk score.
They then compared these results to the genomes of 596 control participants drawn from the NUgene biobank. These control individuals were age 40 or older and had no known history of cardiac disease.
"It was painstaking going through 500-plus records and making sure that the people in the study really belonged in the study," McNally said.
The paper is titled "A combined genomic arrhythmia propensity score delineates cumulative risk." Additional Northwestern contributors include Tanner Monroe, Megan Puckelwartz, Lorenzo Pesce, Dr. Alfred George and Dr. Gregory Webster.
Story Source:
Materials provided by Northwestern University. Note: Content may be edited for style and length.
Journal Reference:
- Tanner O. Monroe, Megan J. Puckelwartz, Lorenzo L. Pesce, Samuel D. Kearns, Patrick Page, Nora Ibrahim, Zachary T. Weber, Emmanuel I. Ugwor, Marcelo A. Nóbrega, Prince Kannankeril, Laura J. Rasmussen-Torvik, Lisa M. Dellefave-Castillo, Alfred L. George, Gregory Webster, Elizabeth M. McNally. A combined genomic arrhythmia propensity score delineates cumulative risk. Cell Reports Medicine, 2025; 102455 DOI: 10.1016/j.xcrm.2025.102455
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