Genetic Testing Trifecta Predicts Risk of Arrhythmia

In a new Northwestern Medicine study published in Cell Reports Medicine, scientists have developed a more precise genetic risk score to determine whether a person is likely to develop arrhythmia, an irregular heartbeat that can lead to serious conditions such as atrial fibrillation (AFib) or sudden cardiac death.

Their approach not only improves the accuracy of heart disease risk prediction but also offers a comprehensive framework for genetic testing that, according to the scientists, could be applied to anything, including other complex, genetically influenced diseases like cancer, Parkinson’s disease and autism.

“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 Elizabeth McNally, MD, PhD, the Elizabeth J. Ward Professor of Genetic Medicine, director of the Center for Genetic Medicine, and a professor of Medicine in the Division of Cardiology and of Biochemistry and Molecular Genetics.

The study, which involved 1,119 participants, also lays the groundwork for developing targeted therapies tailored to a person’s full genetic profile, the authors said, and physicians will be able to spot a person’s risk before symptoms even appear. 

Combining all three types of genetic testing

Currently, genetic testing is divided into three distinct approaches:

• Monogenic testing: Detects rare mutations in a single gene, akin to spotting a typo in one word
• Polygenic testing: Assesses multiple common gene variants to understand overall risk, like analyzing the tone of a book chapter
• Genome sequencing: Reads the entire genetic code, similar to reading a book cover to cover

“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, scientists integrated data from all three genomic compartments to create a 360-degree view of disease risk. Their approach identifies rare mutations, evaluates cumulative genetic influences and uncovers hidden patterns in the full 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 more physicians should order genetic testing

Traditionally, cardiologists assess heart risk by evaluating symptoms, family history and diagnostic tests like EKGs, echocardiograms and MRIs. McNally also incorporates genetic testing into her practice, she said.

“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 its potential, genetic testing remains underutilized, McNally said, adding that it’s estimated that only 1 percent to 5 percent of people who should receive genetic testing actually do. Even in cancer care, where genetic links are well established, only 10 percent to 20 percent of 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 the study was conducted:

The scientists recruited 523 participants who had arrhythmias, and some of these people also had heart failure. The team meticulously went through every case, examining every record to ensure the participants really had had arrhythmias, including looking at data directly from patients’ devices. Finally, they sequenced the patients’ genomes, using monogenetic and polygenetic testing, to determine a risk score and compared the results to the genomes of 596 control participants from the NUgene biobank aged 40 and up with no known cardiac disease history.

“It was painstaking going through 500-plus records and making sure that the people in the study really belonged in the study,” McNally said.

Reference: Monroe TO, Puckelwartz MJ, Pesce LL, et al. A combined genomic arrhythmia propensity score delineates cumulative risk. Cell Rep Med. Published online November 2025:102455. doi: 10.1016/j.xcrm.2025.102455

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